GAW Report No. 205 - IGAC Project

© World Meteorological Organization, 2012The right of publication in print, electronic and any other form and in any language is reserved by WMO. Shortextracts from WMO publications may be reproduced without authorization, provided that the complete sourceis clearly indicated. Editorial correspondence and requests to publish, reproduce or translate this publication inpart or in whole should be addressed to:Chair, Publications BoardWorld Meteorological Organization (WMO)7 bis, avenue de la Paix Tel.: +41 (0) 22 730 84 03P.O. Box 2300 Fax: +41 (0) 22 730 80 40CH-1211 Geneva 2, SwitzerlandE-mail: publications@wmo.intISBN 978-0-9882867-0-2NOTEThe designations employed in WMO publications and the presentation of material in this publication do not imply the expression of any opinionwhatsoever on the part of the Secretariat of WMO concerning the legal status of any country, territory, city or area, or of its authorities, orconcerning the delimitation of its frontiers or boundaries.Opinions expressed in WMO publications are those of the authors and do not necessarily reflect those of WMO. The mention of specificcompanies or products does not imply that they are endorsed or recommended by WMO in preference to others of a similar nature which arenot mentioned or advertised.This document (or report) is not an official publication of WMO and has not been subjected to its standard editorial procedures. The viewsexpressed herein do not necessarily have the endorsement of the Organization.

PrefaceWith increasing global population and extensive, ongoing urbanization, over half the world’spopulation resides now in urban areas and this number is projected to nearly double by 2050, from3.5 billion to 6.3 by 2050. The number of megacities (cities with population over 10 million)currently is 23 and is expected to reach 37 in 2025.Megacities are areas with the most intensive human activities, including economic andsocial activities, together with tremendous energy consumption. These activities lead toconcentrated emissions of air pollutants, greenhouse gases, and waste heat, which impactterrestrial and aquatic ecosystems as well as air quality and climate.The negative impact of megacities on local air quality has long been recognized. In recentyears, the impact of anthropogenic emissions from megacities on regional and global climate hasalso received increasing attention. Both of these impacts are linked through energy consumptionderived from fossil fuel combustion with emissions that change the atmospheric concentrations ofshort-lived species that impact both human health and climate, such as aerosols and ozone.Because of these linkages, it has been argued that megacities are the best places to realize theco-benefits of simultaneously controlling air pollution and reducing climate change.With the growing trend towards urbanization, understanding the role of megacities in localto global atmospheric chemistry is critical to effectively realize the co-benefits of controlling airpollution and reducing climate change. The scientific and engineering knowledge that has beenaccumulated when developed megacities dealt with their air quality problems in earlier years is asignificant resource for current and future megacities. Experiences of developed countries showthat the pronounced air quality degradation that accompanied past development can be avoided.In recent years, there have been a growing number of internationally coordinated integratedstudies and collaborative projects examining the impacts of megacities on air pollution and climatechange. An assessment of these research results and general information about megacities areimportant for both scientific communities and policy makers dealing with urbanization, air qualitymanagement, and climate change.At the IGAC (International Global Atmospheric Chemistry) Scientific Steering Committee(SSC) meeting in September 2007inSeattle, USA, a possible initiative focused on an IntegratedMegacities Assessment was discussed. In May 2008, the plan for an IGAC Assessment onImpacts of Megacities on Air Quality and Climate was formally proposed and approved by theIGAC SSC in Cape Town, South Africa. By June 30, 2008, an outline was sent out for feedbackand to identify potential contributors. On September 8, 2008, at the IGAC SSC meeting in AnnecyFrance, we discussed the outline, identified the lead authors and contributing authors, formed anIGAC Megacity Report Working Group, and decided on the lead authors meeting schedule.The first lead authors meeting was held at Peking University in Beijing on May 22-24, 2009,with the presence of Sarah Doherty, Michael Gauss, Laura Gallardo Klenner, AbdourahamaneKonare, Mark G. Lawrence, David Parrish, Min Shao, Min Hu, and Tong Zhu, supported by theIGAC Project Office and CAREBeijing project. The outline and lead authors of each chapter weredecided at the meeting.At the 24 th IGAC SSC meeting in October 2009 held in Kyoto, Japan, it was decided thatthe World Meteorological Organization (WMO) and IGAC would publish the report jointly. WMO isplacing a growing interest and focus on megacities, especially through its Commission onAtmospheric Sciences (CAS) and GAW Urban Research Meteorology and Environment (GURME).Urban areas as environments pose unique challenges to atmospheric modelling and monitoringand create a multi-disciplinary spectrum of potential threats, including air pollution, which needs tobe addressed in an integrated way.i

The second lead authors meeting was held on November 16-18, 2009 to compile and workon detail contents of the report, at Peking University in Beijing. The attendees included SarahDoherty, Michael Gauss, Maria Kanakidou, Laura Gallardo Klenner, David Parrish, and Tong Zhu,supported by the IGAC International Project Office and the State Key Joint Laboratory forEnvironmental Simulation and Pollution Control, Peking University. The lead authors met again inJuly 2010 during the 11 th IGAC Science Conference in Halifax, Canada, to discuss the integratedand outlook topics of the report.The IGAC Megacity Report Working Group includes Sarah Doherty, Laura Gallardo,Michael Gauss, Maria Kanakidou, Abdourahamane Konare, Mark Lawrence, Cathy Liousse,Megan Melamed, David Parrish, and Tong Zhu (Group Leader). In early 2011, Megan L. Melamedreplaced Sarah Doherty as the IGAC Executive Officer; she also took over Sarah Doherty’s role asa lead author of Chapter 1, and contributed greatly to editing and finalizing the report.Given the current state of available information about many megacities around the world, atruly comprehensive, integrated assessment of the impact of megacities on air pollution is notpossible at this time. However, an initial assessment of what information is available on airpollution in megacities across Africa, Asia, South America, North America, and Europe wasdeemed to be valuable and worth pursuing. Therefore, a large portion of the report is devoted tosummarizing the current situations of megacities on different continents. Exceptions are Chapter1, which gives the introduction of this report and Chapters 7 and 8 that provide an overview ofinternational collaborative research activities and key issues and outlook. Due to decades of airpollution measurements and studies in North America, Chapter 5does provide an integratedanalysis about megacities in North America.Many issues and scientific questions remain to be addressed and discussed, such astropical/sub-tropical cities versus mid-latitude cities, direct and indirect radiative forcing of aerosolsin megacities and the surrounding regions. We plan to address these issues and scientificquestions, along with more integrated analysis, in a future updated version of this report.Tong ZhuOn behalf ofIGAC Megacity Report Working GroupLiisa JalkanenWorld Meteorological Organizationii

AcknowledgementsThe lead authors meetings of the report were financially supported by the IGACInternational Project Office, the U.S. National Oceanic and Atmospheric Administration (NOAA),CAREBeijing project and the State Key Joint Laboratory for Environmental Simulation andPollution Control, Peking University.We would like to acknowledge the great efforts of all the contributing authors of this report.Special appreciation is extended to Beth Tully at University of Washington, Edit-Design Center, forher graphic design work on all the figures throughout the report, June Landenburger and StevenBrey, University of Washington undergraduate students, for their work on the references, figures,and editing of the report, and Pauline Mooney of World Meteorological Organization for making thefinal editing of this report.iii

CHAPTER 1 - INTRODUCTIONatmospheric composition, increasing the importance of understanding the impacts of urbanizationon atmospheric chemistry.Figure 1 - Urban Agglomeration in 2009 (urban proportion of the world population: 50.1%)Source: [UN Department of Economic and Social Affairs, 2010]Figure 2 - Urban Population by major geographical area (in percent of total population)[UN Department of Economic and Social Affairs, 2010]This report focuses on the atmospheric chemistry of megacities, typically defined as urbanagglomerates with ≥10 million inhabitants. The definition of a megacity is an imperfect and inexactmetric, however, as it does not account for other important factors such as population density(Figure 3) or criteria for defining its boundaries (e.g. administrative boundaries vs. countyboundaries vs. the “true” urban area, all of which can change with time [Montgomery, 2008], nor2

CHAPTER 1 - INTRODUCTIONdoes it account for highly urbanized regions where multiple smaller cities essentially constitute onelarge urban area. In the context of atmospheric chemistry, one of the most importantcharacteristics of a “megacity” is an area of highly concentrated anthropogenic emissions.Figure 3 - Map of the world population density (persons per km 2 ), based on 0.25 o gridded data for 2000 from the Center forInternational Earth Science Information Network (CIESIN) at Columbia University[http://sedac.ciesin.columbia.edu/gpw/]Therefore, this report also addresses “major population centers (MPCs)” and “majorindustrial centers (MICs) [Lawrence et al., 2007]. MPCs are areas where several cities aresituated such that they effectively constitute an important regional source of anthropogenicemissions. The northeast US urban corridor of New York City, Newark, Washington D.C. andBoston, the Po Valley in Europe, or the Pearl River Delta in Asia are all considered to be MPCs.MICs are areas with concentrated industrial emissions in proximity to urban areas, such as theHighveld near Johannesburg, South Africa or the Houston, Texas industrial area in the US MPCsand MICs are not only complex in terms of their atmospheric chemistry, but they pose a specialdifficulty in the context of emissions regulation since they generally encompass more than oneregulatory area.The geographic scale and intensity of megacities’ impact on air pollution and climate isdetermined not only by the extent of their emissions but also by their regional geography andmeteorology. These factors affect the degree to which the emissions are trapped, such as byvalley or basin walls or by persistent atmospheric inversions, and the degree to which theemissions are transported to the regional to global scale, such as via uplift in deep convectivesystems. These factors also combine to determine how megacity emissions interact withemissions from surrounding areas. Notably, most of the world’s megacities are situated in coastalzones. In these areas, the mixture of urban and marine air masses result in a unique set ofchemistry. For instance, meso-scale circulations export sulphur and nitrogen compounds out tosea, which can trigger emissions of halogens that are subsequently transported back into urbanareas by the sea breeze giving rise to ozone production [Von Glasow, 2008; Lawler et al., 2009].Continental emissions, e.g., biomass burning, can also interact with urban emissions, altering howthe urban emissions affect air quality and climate. Clearly, each urban area’s unique set ofcharacteristics must be considered in the study of the impacts of urbanization on atmosphericchemistry.3

CHAPTER 1 - INTRODUCTIONThe impact of megacities on air pollution and climate must also be considered in thecontext of the world’s total population. Emissions associated with the economic activity required tofeed, house, clothe and otherwise provide for the needs of the 9.1 billion people expected in 2050will inevitably impact the atmosphere. When addressing the fraction of emissions that originatefrom megacities, it is important to consider how the magnitude and the impact of these emissionswould be different if the population and associated economic activity of the megacities weredispersed in a less concentrated population distribution. Given the concentration of wealth andintellectual resources in megacities, it may well be that the overall impact on the atmosphere isless if the world’s population is indeed concentrated in urban areas as current forecasts predict.This assessment seeks to summarize the geography, meteorology, emissions, atmosphericchemistry, and climate of megacities in North America, South America, Europe, Asia, and Africaand to provide a summary of the research done and still needed regarding megacities andatmospheric chemistry.1.2 ATMOSPHERIC CHEMISTRY OF AIR POLLUTIONThe negative impacts of air pollution in urban areas have a long history dating back to the13 th century when coal began to replace wood as a heating source. For many centuries, “dilutionis the solution”, i.e. putting taller and taller smoke stacks on emission sources, was used to curbthe human health impacts in urban areas. Then, after a series of “minor” air pollution episodes,over 4000 people died in the London Killer Smog Episode of 1952 when a dense fog containingsulphuric acid particles persisted for days. That same year a landmark paper was published byA.J. Haagen-Smit on the “Chemistry and Physiology of Los Angeles Smog”, a city that alsocontinually experienced air pollution episodes. Haagen-Smit showed that the cause of air pollutionin Los Angeles was the release of large quantities of hydrocarbons and nitrogen oxides to theatmosphere that through a complex series of photochemical reactions create ozone and otherharmful secondary pollutants. Although different emission sources and atmospheric chemistrycaused the London Killer Smog episode and Los Angeles smog, both of these historical eventsmotivated the scientific and policy communities to begin unravelling the atmospheric chemistryinvolved in air pollution and implementing regulations to improve air quality.Today, air pollution typically refers to a set of criteria pollutants typically referred to as lead(Pb), carbon monoxide (CO), sulphur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), ozone (O 3 ), andparticulate matter (PM). These criteria pollutants were historically designated as such due to theirimpacts on human health and later to their impacts on ecosystems. The proceeding sectionssummarize the environmental impacts and basic atmospheric chemistry of four criteria pollutants:SO 2 , NO 2 , O 3 , and PM. These four criteria pollutants all have an impact on air pollution andclimate and are key active species in atmospheric chemistry.1.2.1 Acid rain formationBoth SO 2 and NO 2 were named criteria pollutants for their role in the formation of acid rain,a general term for wet and dry deposition of sulphuric and nitric acids (H 2 SO 4 and HNO 3 ,respectively) and for their direct and indirect human health impacts (see following sections ontropospheric ozone and particulate matter). Acidic deposition lowers the pH of lakes, rivers, andstream causing harm to entire watersheds and ecosystems and also erosion of building andautomotive parts. The formation of acid rain occurs through a series of chemical reactions that arecentral to the relationship between the precursors and the sulphuric and nitric acid deposition[Seinfeld and Pandis, 1998]. In industrialized regions, anthropogenicsources, i.e. energyproduction, industry and transportation, typically dominate emissions of SO 2 and NO 2 and theirprecursors.Sulphur dioxide is converted to sulphuric acid via both aqueous phase (eq. 1.1) and gasphaseoxidation (eq. 1.2). The aqueous phase pathway is believed to be responsible for morethan 50% of the ambient sulphate concentration [Seinfeld and Pandis, 1998]. The lifetime of SO 2in the aqueous phase pathway is very short whereas the lifetime of SO 2 in the gas-phase oxidation4

CHAPTER 1 - INTRODUCTIONpathway is on the order of 1-2 weeks, which explains why high concentrations of sulphate ( )can be found both near and far downwind from SO 2 sources.(eq. 1.1)(eq. 1.2)Nitrogen oxides are converted to nitric acid primarily by gas-phase oxidation during thedaytime (eq. 1.3) and by a nitrate radical (NO 3 ) heterogeneous pathway during nighttime whenNO 3 cannot be photolyzed (eq. 1.4).(eq. 1.3)(eq. 1.4)Although the gas-phase oxidation rate of NO X to nitric acid is approximately 10 times fasterthan the gas-phase oxidation rate of SO 2 to sulphuric acid, high concentrations of nitric acid in theaqueous form are not generally found in most source regions. This is because sulphuric acidformed in the gas-phase immediately associates with water molecules to form sulphuric acidaerosol, which excludes nitric acid. Nitric acid will remain in the gas phase until deposited tosurfaces or absorbed by a cloud or rain droplet with lower concentrations of sulphuric acid, whichcan occur downwind from the emission sources. It is also important to note that both sulphuric andnitric acid formation is dependent on OH formation or in more general terms, the oxidation capacityof the atmosphere [Jacob, 1999].1.2.2 Tropospheric ozoneOzone near the surface in the troposphere is harmful to human health and ecosystems dueto its ability to oxidize biological tissue. A common human health impact of tropospheric ozone isrespiratory illnesses such as asthma in children. Tropospheric ozone is formed when volatileorganic compounds (VOC) are oxidized in the atmosphere in the presence of nitrogen oxides (NO+ NO 2 = NO X ) and sunlight. VOC comprise a very large (many 100s of individual species) family oforganic compounds, including both non-methane hydrocarbons (NMHC) and oxidized organicspecies. In addition to chemical formation, ozone is transported from the stratosphere to thetroposphere through stratospheric/tropospheric exchange. Figure 4 provides a simplifiedschematic of the physical and chemical processes involved in the tropospheric ozone budget.The major emission source of NO X in urban areas is fossil fuel combustion, typically utilizedfor transportation, electrical power generation and industrial processes. However, the major urbanemission sources of VOCs are both anthropogenic and natural. Anthropogenic VOC emissionsources are combustion, fuel evaporation, solvent use, and chemical manufacturing. The primarynatural VOC source is emissions from terrestrial vegetation, such as from forests [Jacob, 1999].Therefore, the natural emissions of VOCs have an impact on the effectiveness of either NO X orVOC controls to reduce O 3 concentrations.Tropospheric ozone production occurs when the hydroxyl radical oxidizes VOCs, carbonmonoxide (CO), and methane (CH 4 ) in the presence of nitrogen oxides (NO X ) [Penkett et al.,1999]. Due to the large number of different VOC species, their complex oxidation pathways andtheir numerous emission sources, the formation of tropospheric O 3 is extremely complex.5

CHAPTER 1 - INTRODUCTIONEquations 1.5 show the simplest pathway, the formation of O 3 during the oxidation of CO. Inaddition, ozone and its precursors from large urban areas can be transported on hemisphericscales in the free troposphere and increase background levels of surface ozone such that thehemispheric transport may offset local mitigation strategies to reduce ozone levels [Jacob andWinner, 2009]. To fully understand the tropospheric O 3 budget, a quantitative understanding of theidentity and sources of its precursors, the numerous chemical reactions that constitute theatmospheric VOC oxidation processes, and transport processes that control background ozoneand its precursor levels as well as stratospheric/tropospheric exchange must be incorporated intoatmospheric models. Finally, tropospheric ozone is also a radiatively active trace gas, and thusimpacts climate at regional and global scales.(eq. 1.5)Figure 4 - Physical and chemical processes affecting tropospheric ozone[http://www.globalchange.umich.edu/gctext/Inquiries/Inquiries_by_Unit/Unit_9.htm]6

CHAPTER 1 - INTRODUCTION1.2.3 Particulate matterAn aerosol is technically defined as a suspension of particulate matter (fine solid or liquidparticles) in gas. Aerosols and particulate matter (PM), which are often used synonymously, arereferred to in a variety of different terminologies as shown in Table 1. Aerosols and PM have avariety of impacts including causing respiratory illnesses, decreasing visibility, and impactingclimate through both direct (the particles themselves absorbing or scattering radiation) and indirect(the particles serving as a cloud condensation nuclei) effects.Table 1 - Terminology Related to Atmospheric ParticlesSource: Seinfeld and Pandis, 1998 (pg. 97)Aerosols, aerocolloids,Aerodisperse systemsDustFogFumeHazeMistParticleSmogSmokeSootTiny particles dispersed in gasesSuspension of solid particles produced by mechanical disintegration of material such as crunching,grinding, and blasting.A loose term applied to visible aerosols in which the dispersed phase is liquid. Usually a dispersionof water or ice close to the ground.The solid particles generated by condensation from the vapour state, generally after volatilizationfrom melted substances, and often accompanied by a chemical reaction such as oxidation.An aerosol that impedes vision and may consist of a combination of water droplets, pollutants, anddust.Liquid, usually water in the form of particles suspended in the atmosphere at or near the surface ofthe Earth; small water droplets floating or falling, approaching the form of rain, and sometimesdistinguished from fog as being more transparent or as having particles perceptibility movingdownward.An aerosol particle may consist of a single continuous unit of solid or liquid containing manymolecules held together by intermolecular forces. A particle may also be considered to consist of twoor more such unit structures held together by interparticle adhesive forces such that it behaves as asingle unit in suspension or upon deposit.A term derived from smoke and fog, applied to extensive contamination by aerosols. Now sometimesused loosely for any contamination of the air.Small gas-borne particles resulting from incomplete combustion, consisting predominately of carbonand other combustible material, and present in sufficient quantity to be observable independently ofthe presence of other solids.Agglomerations of particles of carbon impregnated with “tar”, formed in the incomplete combustion ofcarbonaceous material.Figure 5 summarizes the main sources and sinks of atmospheric aerosols. Particles maybe directly emitted from a source (primary aerosol) or formed in the atmosphere through a gas-toparticleconversion process (secondary aerosol). Aerosols have both natural and anthropogenicsources. Natural sources include dust, sea spray, forest fires, volcanoes and vegetation.Anthropogenic sources include transportation, industry, fires, mechanical sources, and humaninduced changes in vegetation. Particles change their size and composition in the time betweenemission and their removal from the atmosphere by dry or wet deposition. The chemical andphysical mechanisms of particle formation and transformation are not completely understood andremain a topic of continual research.The composition of aerosols varies greatly across urban areas due to different emissionsources and meteorological conditions. Figure 6 shows aerosol mass spectroscopy (AMS)measurements of aerosol taken at a variety of locations in the Northern Hemisphere [Jimenez etal., 2009]. Organic aerosols (OA) are of particular importance since they make up between 20 to90% of the submicron particle mass. Organic aerosols exist in the atmosphere as both primaryand secondary aerosol. Primary organic aerosol (POA) is directly emitted from emission sourcessuch as fossil fuel combustion and biomass burning. However, the evolution of POA in theatmosphere is not well understood. Secondary organic aerosols (SOA) result from the oxidation ofgas-phase species. It is believed that SOA accounts for a large portion of total OA and henceaerosol in general. The evolution of the gas-phase species to SOA is also still poorly understood.7

CHAPTER 1 - INTRODUCTIONThere is a need for further research on OA in order to reduce uncertainty of the role of aerosol inhuman health and climate.Figure 5 - Sources of atmospheric aerosol [http://www.ems.psu.edu/~lno/Meteo437/Figures437.html]Figure 6 - Average aerosol mass concentration and chemical of composition measured with an AMSat multiple locations in the Northern Hemisphere. [Zhang et al., 2007]8

CHAPTER 1 - INTRODUCTION1.2.4 Climate changeAir pollution and climate change have largely been kept separate in both the scientific andpolicy communities. This was primarily due to the temporal and spatial differences between airpollution and climate with air pollutants being short-lived reactive species that have impacts on thelocal and regional scale and climate forcing agents being longer-lived radiatively active speciesthat have impacts on the global scale. However, more recently and into the future, it is clear thatair pollution and climate change are inexorably linked (Figure 7). Air pollutants that typically wereresearched and regulated for their air quality impacts are now being recognized as importantdrivers of climate change. In addition, the scientific community has begun to provide informationon the regional impacts of climate change and how these changes may impact air pollution. It isclear that air pollution and climate change are issues that now have overlapping temporal andspatial scales and should be addressed in an integrated manner.Figure 7 - Air pollution and climate are inexorably linked[http://www.ocw.cn/OcwWeb/Chemical-Engineering/10-571JSpring-2006/CourseHome/index.htm]Figure 8 shows the global average estimates and ranges for human-caused radiativeforcing in 2005 through the principal climate forcing agents [IPCC, 2007]. Species that typicallywere considered solely air pollutants in the past include tropospheric ozone, black carbon, andother aerosols. The positive radiative forcing due to tropospheric ozone and black carbon has ledto much interest in mitigating both of these air pollutants in order to both improve air quality andreduce radiative forcing, a win:win strategy. The linkage between air pollution and climate foraerosols is more complicated. Mitigation of aerosols from an air quality standpoint is clearly a winstrategy for human health and wellbeing. However, from a climate standpoint, mitigating aerosolswould eliminate a cooling effect, thus increasing the overall net global radiative forcing, a net lossfor climate [Ramanathan and Feng, 2008]. Figure 9 depicts a diagram showing that trade-off thatpolicy makers must consider when improving air quality or mitigating climate change.9

CHAPTER 1 - INTRODUCTIONFigure 8 - Global average radiative forcing estimates and ranges in 2005 [IPCC, 2007]Figure 9 - Schematic of the trade-offs between the implications for regional air quality and climate change of new policiesfor management of the atmosphere [adapted from Williams, 2012]10

CHAPTER 1 - INTRODUCTIONIn addition to air pollution having an impact on radiative forcing, climate change has animpact on air pollution meteorology and chemical process. Projected changes in surfacetemperature and precipitation (Figure 10) due to radiative forcing caused by both long and shortlivedclimate forcers will impact regional air pollution. A strong warming occurs over the northernmid-latitude continents and no area shows cooling [Jacob and Winner, 2009]. The increase intemperature leads to an increased frequency of heat waves, which are strongly associated withhigh pollution episodes, e.g., the 2003 heat wave in Europe. Precipitation is expected to increasedue to increased evaporation from the oceans. However, the frequency and intensity of theincreased precipitation varies considerably at a regional scale. Less frequent but heavierprecipitation events could lead to more pollution episodes by reducing wet deposition of aerosoland other pollutants. Models also indicate a warming climate could impact large-scaleatmospheric dynamic patterns. For example, Leibensperger et al. [2008] show a significant longtermdecline in the number of summertime mid-latitude cyclones across the northeastern UnitedStates, which in turn strongly correlates with the number of high ozone episodes due to decreasedpollutant ventilation. It is now widely recognized that air pollution and climate change can nolonger be considered as separate issues in the scientific and policy communities [Tai et al.,2010].Figure 10 - Differences in annual mean surface temperatures and precipitation in Europe, Asia, and North America for 2080-2099 vs. 1980-1999 averaged over an ensemble of about 20 GCMs contributing to the IPCC 4 th Assessment[Jacob and Winner, 2009]1.3 HEALTH IMPACTS OF AIR POLLUTIONThere is great evidence linking air pollution with mortality and morbidity in the generalpopulation [Brunekreef and Forsberg, 2005; Zanobetti and Schwartz, 2005; Pope and Dockery,1996; Nawrot et al., 2006; Dominici et al., 2006; Barnett et al., 2006; Guaderman et al., 2007].Several physiopatological mechanisms of injury are described [Osornio-Vargas et al., 2003; Inoueet al., 2006;Yeatts et al.,2007; Sakamoto et al., 2007; Barlowet al., 2007]. Public health damage isconsistently found with adverse effects concentrated in urban areas both in developed anddeveloping countries [WHO, 2005]. The range of adverse health effects is broad, affecting both therespiratory and the cardiovascular system. Children, women, and older adults are the mostsusceptible to these adverse health effects in the general population [WHO, 2005; Peel et al.,2007; Miller et al.,2007; Tecer et al., 2008]. The risk increases with intensity of exposure. Littleinformation supports the presence of a threshold level for these effects. In fact, effects were foundat very low levels of particulate matter, e.g. 3 to 5 µg/m3. The adverse health effects of air pollutionare observed both in short-term exposures and for long-term exposures [WHO, 2005]. Theseproblems are exacerbated by indoor air pollution typically caused by the burning of solid fuels.11

CHAPTER 1 - INTRODUCTIONLow-income population in general, and women and young children in particular are subject to ahigher exposure since they spend the most time near the domestic hearth [WHO, 2009]. One ofthe main sources of pollution and health damage is traffic [Kim et al., 2008].The World Health Organization conducted a study of the burden of disease caused byenvironmental problems attributed to air pollution effects on respiratory diseases, perinatalconditions and birth defects, cancer, cardiovascular diseases, bronchial obstructive disease, andasthma. The study estimated that in developing countries 42% of all respiratory diseases areattributable to air pollution [Prúss-Utsunand Corvalán, 2006]. Exposure to complex mixtures of airpollutants, mainly particulate matter and ozone, causes structural lung changes that are inducedby sustained inflammation, leading to vascular reconstruction of the lung airways and impairing therepair process. Children are particularly vulnerable to respiratory problems because of theirphysical characteristics and behaviour. In children under 5 years of age it has been estimatedglobally that acute lower respiratory infections (pneumonia, bronchiolitis and bronchitis) areresponsible for about 20% of the 10.6 million deaths annually worldwide. About 90% of thesedeaths are due to pneumonia [Rudan et al., 2004].Over the last decade research shows an increased risk of cardiovascular disease due toboth particulate matter and ozone exposure [Tsai et al., 2003; Kan and Chen, 2003; Hong et al.,2002; Tamagawa and Van Eaden, 2006; Maheswaran et al., 2005; Higgs, 2011]. Manycardiovascular indexes show cardiovascular injury induced by increased levels of ambient particles(changes in the heart rate, or heart rate variability, blood pressure, vascular tone, and bloodcoagulability). In addition, chronic exposure to increased concentrations of particulate airpollutants accelerates the progression of atherosclerosis [Simkhovich et al., 2008]. The evidencesuggests that stroke mortality and hospital admissions are higher in areas with elevated levels ofoutdoor air pollution because of the combined acute and chronic effects of air pollution on strokerisk [Maheswaran et al., 2005]. The impacts of air pollution on human health are the main drivertoward implementing air quality regulations.Vector-borne diseases, impacts on maternal and newborn health, nutrition of general publicand heat related stress are among the health problems that have been linked with climate change[Aklesso et al., 2011; Rylander et al., 2011; Myers and Bernstein, 2011; Toutan et al., 2011].1.4 AIR QUALITY REGULATIONFollowing the major pollution episodes in Los Angeles USA and London UK in the 1950s,governments began to implement legislation to first fund research on air pollution and then tocontrol air pollution. This effort culminated in the US with enaction of the 1970 Clean Air Act, whichauthorized the development of comprehensive federal and state regulations to limit emissions fromboth stationary and mobile sources and initiated the National Ambient Air Quality Standards(NAAQS) amongst other regulatory programmes. The Clean Air Act was amended in 1977 andagain in 1990, with the latter implementing the Acid Rain Programme and significantly increasingthe authority and responsibility of the federal government to protect human health and theenvironment from the impacts of air pollution (http://www.epa.gov/air/caa/caa_history.html). Table2 shows the current NAAQS for the USTable 2 - US National Ambient Air Quality StandardsPollutant Concentration Averaging PeriodParticulate Matter (PM2.5)15 µg/m335 µg/m31 year24 hourParticulate Matter (PM10) 150 µg/m3 24 hourOzone 0.075 ppm 8 hourNitrogen Dioxide100 ppb53 ppb1 hour1 yearSulphur Dioxide75 ppb0.5 ppm1 hour3 hour12

CHAPTER 1 - INTRODUCTIONIn Europe, air quality management began with the signing of the United Nations EconomicCommission for Europe (UNECE) 1979 Geneva Convention on Long-Range Transboundary AirPollution (LRTAP), which has been extended by eight protocols, the 1999 Gothenburg Protocolbeing the last one. LRTAP aims to limit and gradually reduce and prevent air pollution bydeveloping policies and strategies across its 51 parties. In parallel to LRTAP, in 2001 theEuropean Commission established National Emissions Ceilings (NEC), which set nationalemissions limits for four pollutants that are responsible for acidification, eutrophication, andground-level ozone pollution. The NECs are largely based on the Gothenburg Protocol. In 2005,the European Commission also launched the Thematic Strategy on Air Pollution (TSAP), the firstof its seven Thematic Strategies in the European Union’s Sixth Environment Action Programme(EAP). TSAP established interim objectives for air pollution in the EU and proposes appropriatemeasures for achieving them, e.g. setting air quality standards and rules for monitoring. Air qualitymanagement in the European Union is thus an interplay between the Air Quality Directives definedunder TSAP, the NEC directives, and LRTAP. Table 3 shows the current European CommissionAir Quality Standards.Table 3 - European Commission Air Quality StandardsPollutant Concentration Averaging PeriodParticulate Matter (PM2.5) 25 µg/m3 1 yearParticulate Matter (PM10) 50 µg/m3 24 hoursOzone 120 µg/m3 8-hrNitrogen Dioxide40 µg/m31 yearSulphur Dioxide200 µg/m3125 µg/m3350 µg/m324 hour24 hours1 hourIn 1987, the World Health Organization (WHO) published Air Quality Guidelines for Europe.The aim of the guidelines was to provide a basis for protecting public health from adverse effectsof air pollutants, to eliminate or reduce exposure to those pollutants, and to guide national andlocal authorities in risk management decisions. In 2005, following important new research fromlow- and middle-income countries, the WHO released new Air Quality Guidelines for four commonpollutants (PM, O 3 , NO 2 , and SO 2 ) that are intended to inform policy-makers from different parts ofthe world on appropriate targets for policy related to air quality management. Table 4 shows the2005 WHO air quality guidelines.Table 4 - World Health Organization Air Quality GuidelinesPollutant Concentration Averaging PeriodParticulate Matter (PM2.5) 10 µg/m 325 µg/m 31 year24 hourParticulate Matter (PM10) 20 µg/m 350 µg/m 31 year24 hourOzone 100 µg/m 3 8 hourNitrogen Dioxide 40 µg/m 3200 µg/m 31 year1 hourSulphur Dioxide 20 µg/m 3500 µg/m 324 hour10 minuteIt must be pointed out that air quality improvements throughout the world do not merelyfollow from the dictation of air quality standards similar to those designed by US EPA, theEuropean Commission, or the WHO. Each country’s national air quality standards should and willlikely vary according to the approach adopted for balancing health risks, technological feasibility,economic considerations, and various other political and social factors. Determining national airquality standards and enforcing them depends greatly on the level of development and nationalcapability in air quality management.13

CHAPTER 1 - INTRODUCTION1.5 SCIENTIFIC TOOLS FOR STUDYING AIR POLLUTION IN MEGACITIESOne of the main challenges in addressing the impacts of megacities on the environmentand human health is the interaction of different spatial scales. Traditional problems of urbanizationinclude local to regional air quality and health issues. Scientific tools have been developed to coverlocal to regional scales at appropriate spatial and temporal resolutions. However, given their largeand increasing emission strength, megacities can also have effects on the global scale, which canonly be assessed by tools with global coverage. Global coverage, however, usually implies a lossof detail. The study of megacity impacts, both in terms of air quality and climate, thus necessitatesthe development and use of scale-bridging observations, emission inventories, and modelling.1.5.1 Ground-based, ship, and aircraft observationsGround-based observation networks are crucial for studying atmospheric chemistry inmegacities. In particular, continuous ground-based meteorological networks are essential in orderto characterize meteorological processes that control air pollution transport and stagnation events.In addition, year-round ground-based observation networks of atmospheric pollutants can detectexceedances of air quality standards, identify trends, detect or quantify emission sources, anddetermine the effects of air pollution control measures. Several examples of long-term groundbasedobservation databases of different spatial coverage are the AIRBASE database throughEIONET (http://air-climate.eionet.europa.eu/databases/airbase), the EBAS database hosted byNILU Norway (http://ebas.nilu.no/), and the AirParifdatabase for Paris (http://www.airparif.asso.fr/).In addition, many regulatory agencies in developed and developing countries have air pollutionmonitoring networks that provide hourly concentrations of important air pollutants such as O 3 , SO 2 ,NO X , PM 10 , etc. The number of air pollution monitors within a city and the air pollutants measuredvary greatly. A more globally consistent air pollution monitoring network would provide a robustdataset to study atmospheric chemistry in megacities and the environmental and human healthimpacts of air pollutants.More recently, surface “super-sites” have been incorporated into megacity field campaignsto complement and extend observations from aircraft and satellites. Super-sites providesimultaneous measurements of a variety of chemical and meteorological parameters and tend tohave more specific scientific purposes than long-term ground-based observation networks. Forexample, a series of super-sites may be used to study the chemical composition of air parcels or ofparticles as a function of time and location. Some examples of data from super-sites are therecent MEGAPOLI [http://megapoli.dmi.dk/] and MILAGRO[http://www.eol.ucar.edu/projects/milagro/] campaigns that focused on Paris, France and MexicoCity, Mexico respectively.In addition to surface super-sites, field campaigns in megacities often include aircraft andships that provide highly sophisticated platforms for studying atmospheric chemistry. Suchplatforms include in-situ and/or remote sensing instrumentation that provides observations ofprimary pollutants, secondary species, meteorological conditions, vertical profiles, and a widerange of other parameters. An airborne research platform provides a unique way to study thesource region, vertical and horizontal dispersion, and chemical and physical transformation ofatmospheric pollutants. Meanwhile, ship platforms provide the means to study meteorological andchemical processes at the surface ocean-atmosphere interface and in the marine boundary layer,which are regions difficult to measure using ground-based and aircraft observations, see Chapter 7for further details.The type of platform and instrumentation used to study atmospheric chemistry is dependenton the unique characteristics of the megacity of interest. Ground based, aircraft, and shipobservations often provide a very detailed local to regional view of air pollution. Therefore, there isa need to integrate observations from field campaigns and monitoring networks in order to bridgescales from a local to regional to global level. Such integration would enhance the globalperspective of the impacts of air pollution from megacities while still maintaining the critical detailedlocal and regional information.14

CHAPTER 1 - INTRODUCTION1.5.2 Satellite observationsGround, ship, and aircraft observations provide a detailed snapshot of atmosphericcomposition. Satellite-based observations provide a complementary global, continuousperspective, overcoming some of the temporal and spatial limitations of surface and aircraftmeasurements. Historically, satellites were most readily used to determine stratosphericatmospheric composition, largely because the presence of clouds and the overhead stratospheremake tropospheric measurement challenging. However, in recent decades, new instrumentstargeting tropospheric composition have been developed and deployed on satellites, rapidlyenhancing our ability to track global tropospheric composition. These observations can providecritical information for monitoring and forecasting of air quality, studying long-range transport ofpollution, and monitoring emissions of air pollutants and climate forcers. The majority oftropospheric measurements from space have employed nadir (downward looking) geometry.Occultation measurements offer much better sensitivity to trace species in the atmosphere;however detection is limited to the upper troposphere, which is generally less informative for airquality applications [Burrows et al., 2011].Solar backscatter measurements observe reflected and backscattered solar radiation in theultraviolet (UV), visible (VIS), and near infrared (NIR) spectral region and are typically sensitivedown to the lowest layers of the atmosphere, except in the case of significant cloud cover. Thisnear surface sensitivity and the narrow field of view obtained with nadir observations are importantpre-requisites for obtaining information about air pollutants. A number of key atmospheric tracegases absorb in the UV-visible range: O 3 , NO 2 , HCHO, SO 2 , BrO, and Glyoxal (CHOCHO).Retrievals of trace gas concentrations are a two-step process. First the slant column densities(SCD) are estimated along the radiation path using absorption spectroscopy and second thisquantity must be converted to the vertical column density (VCD) via the application of an air massfactor (AMF) (Figure 11). An AMF is the enhancement of the optical path length from the VCD dueto the viewing geometry of the satellite, the scattering properties of the atmosphere and surface,and the vertical distribution of the absorber. AMFs are commonly determined by combining tracegas profiles estimated from a chemical transport model with a radiative transfer model. Accountingfor clouds, aerosols and stratospheric contributions are non-trivial challenges associated withthese retrievals. Figure 12 illustrates recent satellite instruments that apply solar backscattertechniques to measure global tropospheric composition.Figure 11 - Simplified schematic of solar backscattering measurements15

CHAPTER 1 - INTRODUCTIONFigure 12 - Atmospheric composition measurements from UV-VIS-NIR backscatter instrumentsA disadvantage of solar backscatter sounders such as GOME and SCIAMACHY is that themeasurements require solar light, i.e., they can only be performed on the Earth’s sunlit side. Incontrast, satellite observations using thermal emission permit measurements during night as wellas day. Thermal emission measurements use the thermal infrared (TIR) spectral region tomeasure tropospheric trace gases (Figure 13), including tropospheric O 3 , CO, CH 4 , H 2 O, HDO andvolcanic SO 2 . Several experimental retrievals for species with weaker emission features, such asNH 3 and CH 3 OH, have been recently demonstrated with the TES and IASI instruments [Beer et al.,2008; Clarisse et al., 2009]. Retrieval of these species and others may become routine in thefuture with higher spectral resolution instruments. Measurement sensitivity in the TIR dependsprimarily on the thermal contrast between the Earth’s surface and the lowest layer of theatmosphere, which is typically highest in the mid to upper troposphere [Deeter et al., 2007]. Thus,these instruments provide a characterization of the total column concentration, but with lesssensitivity to boundary layer concentrations. Developing techniques to enhance sensitivity to theboundary layer, for example by integrating UV/visible and IR measurements is a major researchchallenge. Figure 14 shows the history of thermal emission instruments used to measureatmospheric composition.16

CHAPTER 1 - INTRODUCTIONFigure 13 - Schematic of thermal emission measurementsFigure 14 - Atmospheric composition measurements from thermal emission instrumentsTropospheric aerosols are challenging to characterize due to the variety and variability ofaerosol sources as well as the short residence time of aerosols in the atmosphere. From space,the total radiative extinction resulting from aerosols can be measured. When summed vertically,this is the aerosol optical depth (AOD). Further details on the composition, size and properties of17

CHAPTER 1 - INTRODUCTIONthese aerosols are difficult to extract. AOD is typically measured at visible wavelengths and is thusmost sensitive to fine-mode aerosol. The information is therefore optimum for air qualityapplications focused on PM 2.5 . Efforts to convert AOD observations to surface PM 2.5 concentrationsrequire additional information on the vertical distributions and speciation of total aerosol, oftenobtained from chemical transport models [Liuet al., 2004]. AOD in the mid-visible is also verysensitive to the surface reflectivity. Historically, the first AOD retrievals were performed solely overoceans, where dark surfaces were more easily characterized. More recently, both multi-spectral(e.g. MODIS) and multi-angle (e.g. MISR) approaches have been applied to account for the impactof surface reflectivity and measure AOD over land as well as ocean [Levy et al., 2010]. Thepresence of clouds is an additional challenge for passive remote sensing observations of aerosols.Active sensors, such as lidars, can profile aerosol and cloud extinction at high vertical resolution. Inrecent years, CALIOP observations have provided detailed observations of aerosol plumes, andoverlaying vertical layers. The drawback of these observations for air quality applications is theirlimited coverage and long repeat times. However, detailed snap shots may provide importantinsight into aerosol distributions and export mechanisms over urban centres (Figure 15).Figure 15 - Aerosol measurements from spaceAll current satellites relevant for air pollution research are in polar low Earth orbit (LEO).This limits the number of passes over a given area to twice per day, but observations can belimited further by cloud cover and by the swath width of satellites dictating a longer time betweenrepeat visits. For air quality monitoring, more frequent observations would be highly desirable. Thiscan be achieved with several LEO satellites or, for the tropics and mid-latitudes, with ageostationary satellite such as the proposed GeoTROPE mission [Burrows et al., 2004]. At presentsuch an instrument is not in orbit, but in a few years the launch of the geostationary Sentinel 418

CHAPTER 1 - INTRODUCTIONUVN instrument is planned, which will deliver information on air pollutants at much higher temporalresolution than currently available. Similar instruments are planned for Asia and North America.1.5.3 Emission inventoriesA critical step in improving our understanding of the impact of megacitieson air quality,atmospheric composition, and climate is the development of high-quality emission inventories ofrelevant gases, aerosols, and their precursors. An emissions inventory is a current, comprehensivelisting, by source, of air pollutant emissions associated with a specific geographical area for aspecific time interval [http://epa.gov/air/oaqps/eog/course419a/index.html]. Therefore, emissionsinventories are developed for local, regional, and global applications as well as scientific and policyapplications (chemical transport models, global climate models, trend analysis, regional and localscale air quality modelling, regulatory impact assessments, and human exposure modelling).Global emission inventories typically have resolutions of about half a degree or very recently onetenth of a degree (EDGAR V4). Regional inventories often have scales from 5 to 100 km whereaslocal inventories have resolutions of 1 to 10 km.Two fundamental tools for developing emission estimates of air pollutants are emissionfactors and emission estimation models. Emission factors relate the quantity of a pollutantreleased to the atmosphere as a function of activity level for a given source by(eq. 1.6)where E is the emissions, A is the activity rate, EF is the emissions factor, and ER is the overallemission reduction efficiency using capture or control techniques (given in %). Emission factoruncertainty is dependent on the kind of emissions released, the number of tests used to determinethe emissions factor, using the appropriate percentile within the distribution range, and the numberof similar emissions units within a specific area [http://www.epa.gov/ttn/chief/efpac/abefpac.html].Determining emission factors for every source and every pollutant under a variety of operatingconditions throughout the world is a daunting task. Therefore, most emission factors aredeveloped from only a limited sampling of the emissions source population for any given category,i.e. source population average. The limited number of samples likely results in emission factors notstatistically representative of the actual emissions of a source category [Seinfeld and Pandis,1998].Emission estimation models use empirically developed process equations to estimateemissions from a given source. In general, an emission estimation model is used rather than anemission factor when a large number of equations, interactions, and parameters impact theemissions estimate. In many cases, emission estimation models are used to develop inventoriesfor mobile and non-road source categories since it is difficult to directly measure activity fornumerous individual sources operating under a wide variety of conditions.Emission estimates derived using emission factors or emission estimation models are thendeveloped into an emission inventory. There are two approaches to emission inventorydevelopment: down-scaled and bottom-up. The down-scaled approach develops emissioninventories based on global, national, or regional data by downscaling the larger scale data usingsome measure of activity data or proxy (e.g. population density) related to the emissions in thearea of study. The bottom-up approach estimates emissions for individual sources and thenaggregates all sources in the area of study to derive regional, national, or global emissionestimates. The down-scaled approach is typically used when local emissions are unknown, costprohibitive to obtain, or not publically available. Figure 16 shows how a bottom-up emissionsinventory can be merged into a regional down-scaled emissions inventory. In addition, aircraft andsatellite observations can be used to derive top-down emission estimates using a-priori informationfrom a bottom-up emissions inventory. The result is an optimized a posteriori estimate ofemissions [Martin et al., 2003].19

CHAPTER 1 - INTRODUCTIONFigure 16: Merging a local bottom-up emisison inventory for Paris [Airparif, 2010] into a regional down-scaledEuropan emisison inventory [Denier van der Gon et al., 2009; 2011].However, discrepancies often exist between emission inventories developed by downscaledversus bottom-up approaches as illustrated in four European megacities or urbanagglomerations; London, Paris, Rhine-Ruhr area (Germany) and the Po Valley (Italy). The localinventories use local statistics and activity data to estimate the emissions within their domain usinga bottom-up approach. The European emission inventory is a down-scaled inventory based onnational totals by source sector and then distributed over a grid by using source sector specificspatial distribution proxies [Denier van der Gon et al., 2009]. A ratio comparison of down-scaledversus bottom-up emission inventories for these four cities is shown in Figure 17. A value of 1 inFigure 17 indicates that the local megacity inventory and the regional scale down-scaled inventoryhave the same estimate for the pollutants from the megacity domain. The differences can be quitedramatic. For example, the PM 10 emission allocated to London and Paris by the regional scaleinventory is a factor of 3-4 higher than the local inventories for London and Paris. The discrepancyfor NO X is limited but for other pollutants like PM, NMVOC, and CO the discrepancies aresignificant. SO 2 stands out in Figure 17 but this is not very relevant because European cities aresmall sources of SO 2 , hence even a small mis-allocation of emissions using the down-scalingapproach results in several factors overestimation. In general the smaller the domain, the largerthe discrepancy between down-scaled and bottom-up emission inventories.Figure 17 - Ratio of megacity emissions derived from the Regional European scale inventory compared to the localmegacity emission inventory [Denier van der Gon et al., 2011]20

CHAPTER 1 - INTRODUCTIONEmission inventories are critical in order to understand atmospheric chemistry in general,but especially for megacities. It is clear that discrepancies exist between down-scaled versusbottom-up methodologies as well as between national and regional emission inventorydevelopment. In order to understand atmospheric chemistry in megacities, an integratedemissions approach that transcends methodologies and political boundaries is needed. Such anapproach would allow for scale-bridging of emission inventories that would provide consistentlocal, regional, and global emissions inventories.1.5.4 ModellingAlong with laboratory studies and field measurements, modelling represents one of themain pillars of atmospheric chemistry research. Atmospheric models can be thought of asmathematical representations of the chemical and physical behaviour of the atmosphere. Mostcommonly, models are used to simulate the state of the atmosphere on computers. For thispurpose the atmosphere is divided into a large number of small compartments, so-called gridboxes, for each of which the chemical and physical parameters are calculated based on initialconditions, internal tendencies, and external forcings. For instance, the concentration of a chemicalcomponent after some short amount of time, usually referred to as time step, can be calculatedfrom its initial value and the rate of change during the time step. The rate of change will be a resultof chemical reactions, emissions, transport through winds, wet removal by precipitation, and manyother physico-chemical processes. The new calculated concentration will then serve as initial valuefor the calculation of the next time step, and so forth.In such calculations, atmospheric models have to rely on various kinds of input, for instancevalues for chemical reaction rates, the radiation from the sun, and spatially and temporallyresolved emission data. By using all available input information as well as our basic understandingof the processes occurring in the atmosphere, a model calculates the chemical state for each of itsgrid boxes and for each time step, thus yielding the distribution and evolution of chemicalcomponents in space and time.An atmospheric model can be used in two fundamental ways, either as a diagnostic tool, oras a prognostic tool. In the former case the model aims to answer the question why things are theway they are. For example, what are the physical and chemical processes that contribute toobserved air pollution? In contrast to the real atmosphere, processes can be switched on and off ina model in order to assess their importance. The impact of different types of emissions, e.g.anthropogenic vs. natural sources, can thus be investigated. Concentrations of species that cannoteasily be measured can be calculated even for remote or inaccessible regions of the atmosphere,thus allowing gap-free distributions for all chemical components included in the model. Asprognostic tools, models are used to calculate future distributions of chemical components. In thisway, the future evolution of atmospheric composition responding to natural and anthropogenicinfluences can be predicted. Different emission scenarios can be simulated, and the effectivenessof different emission reduction scenarios can be assessed.However, in order to gain confidence in a model it is important to carefully evaluate itagainst measurements. Only when it is established that the model succeeds in simulating past andpresent states of the atmosphere with reasonable accuracy, can it be used to predict futurebehaviour.Figure 18 shows the basic components of atmospheric models, summarizing the basicinput and output components of atmospheric models. There are various types of atmosphericmodels: Chemical transport models take meteorological parameters (temperature, wind,precipitation, etc.) as input and calculate the chemical composition of the atmosphere. Othermodels, e.g. numerical weather prediction models and climate models, calculate meteorologicalparameters themselves and take chemical distributions (e.g. ozone and aerosols) as input. A moreadvanced group of models calculates both meteorology and chemistry in a coupled way, allowingfor interactions between chemistry and climate, but are computationally expensive so thatsimplifications have to be made, or the model resolution has to be coarse.21

CHAPTER 1 - INTRODUCTIONFigure 18 - Concept of atmospheric modelling. Yellow boxes: A priori knowledge that is not calculated by the model itself.Green boxes: Forcings that may or may not be calculated by the model itself but are needed for accurate model output.Blue ovals: Main purpose (or output) of the model. Numerical Weather Prediction models (NWP) andGeneral Circulation models (GCMs) use prescribed fields of chemical species (e.g. aerosols) and calculate meteorology,while chemical transport models (CTMs) take meteorology as input and calculate the chemical composition of theatmosphere. Coupled climate-chemistry models (CCMs) calculate both meteorology and chemical composition and allowfor couplings between the two. This figure is not exhaustive but is meant to illustrate the most basic components onlyResolution is one of the most fundamental features of a model. As a model usuallycalculates only one value per parameter for each grid box, assuming that the value is constant allover the grid box, many patterns that vary on finer spatial scales than the grid box dimensioncannot be resolved. For example, some air pollutants have very short lifetimes compared toatmospheric transport timescales, and thus have rather uneven distributions, which reflect pointsources of emissions. Also, topography and land use vary, in general, on smaller scales than canbe resolved in a regional, let alone, global model. In order to resolve fine scale patterns in a modelit is necessary to run the model on a higher resolution (i.e. to use a smaller grid box size). When alarge domain has to be investigated this necessarily leads to a large number of grid boxes in themodel, and often exceeds the limitations with respect to computer power.Megacities affect their environment on very local scales, down to street level, but as strongemission sources they also have global environmental impacts. Conversely, global change willinfluence megacities related to both climate change and long-range transport of air pollution. Giventhe multi-scale character of the effects of and upon megacities, trade-offs have to be made inmodelling. Models having a sufficiently fine resolution for local air pollution studies cannot be runglobally, but only for a confined region of the atmosphere (so-called regional or local models). Theprovision of boundary conditions for these models is not trivial, and effects from the model domainon the areas beyond cannot be taken into account. On the other hand, global models that addresschanges in large-scale meteorological parameters and changes in the background concentrationsof long-lived air pollutants have too coarse a resolution to be applied to local studies. Althoughcomputer power is increasing, this problem cannot be easily solved because the ongoing (anddesirable) inclusion of ever more complex physical and chemical processes largely compensatesfor the increase in available computing power.Baklanov and Nuterman [2009] therefore note the importance of building a chain of modelsof different spatial scales with nesting of high-resolution/small-domain models into lowerresolution/larger-domainmodels. Their example describes the bridging from regional to localscales, using coupled systems of obstacle-resolved urban models and coarser-scale local models.It is shown how features from outside the obstacle-resolved model influence its results, thusjustifying a proper inclusion of information from the coarser scale. In general, scale interactions canplay an important role in both directions, i.e. not only from the larger scale to the smaller scale, but22

CHAPTER 1 - INTRODUCTIONalso from the urban/microscale to larger scale processes (e.g. transport of atmospheric pollutants,initially released and dispersed in a street canyon, urban climate and wind climatology, etc.).Several scale-bridging methods can be distinguished. The following main strategies havebeen considered:a) Online coupling of two versions of the same model (course resolution/large domain and fineresolution/small domain).b) Zoomed grid realizing high resolution in a region of special interest, with a continuoustransition towards coarser resolutions outside that region.c) Offline coupling of two models of different scales, e.g. a global model delivers 3-hourlyboundary conditions to a regional model, or the (fine resolution) output from a regionalmodel is used to improve (coarse resolution) results of the larger scale model.d) Online coupling of two different models of different scales, e.g. one regional model and oneglobal model exchange information at each model time step, within one combined modelsystem.The techniques can also be grouped in terms of information flow only: 1) one-way nesting,where effects of the local/micro-scale on the larger scale are not considered, and 2) two-waynesting, where the scale effects in both directions are considered. In the last case both domainsare run simultaneously to enable feedbacks (corresponding to item (d) in the list above), and theterrain in the overlapping areas must be comparative to avoid mass imbalances and numericalnoise.Observations of the atmosphere are typically unevenly distributed in space and time andwith differing precision and accuracy. Models, on the other hand, provide a self-consistentframework but are subject to multiple errors due to uncertain estimates of parameters, inadequaterepresentation of processes, and lacking of process understanding. However, the combination ofmeasurements and models provides complementary information that leads to a better descriptionof the system and its evolution. To achieve this, the combination must be made in an optimumsense, which either minimizes the distance between model and observations (variationalapproach) or minimizes the error variance of the system’s predictor (statistical approach). Bothvariational (e.g., 4-D Var) and statistical (e.g., Kalman filter) methods have been widely used bythe meteorological community over the last decades for dealing with weather forecasting as a wayto avoid the uncontrolled propagation of errors due to the uncertain and incomplete description ofinitial conditions [Kalnay, 2003]. In atmospheric chemistry these methods are nowadays beingincreasingly used as both in-situ and remote observations become more readily available. Thesemethods provide a way to improve emissions at different scales [Pétron et al., 2002; Chai et al.,2009; Saide et al., 2011], to limit the propagation of model errors [Elbern et al., 2007; Carmichaelet al., 2008], and to evaluate and optimize monitoring networks [Hoelzemann et al., 2009; Abida etal., 2008].1.6 SUMMARYThis chapter summarizes the world trend in urbanization, the atmospheric chemistry of airpollution and scientific tools to investigate air pollution, the impacts of air pollution on humanhealth, and air quality regulations. The following chapters describe the current scientificknowledge of atmospheric chemistry in megacities in Africa, Asia, South America, North America,and Europe. A summary of megacity field campaigns is presented in Chapter 7 and the finalchapter presents key issues that still need to be addressed in the study of atmospheric chemistryof megacities.23

CHAPTER 1 - INTRODUCTIONReferencesAbida, R., Bocquet, M., Vercauteren, N., & Isnard, O. (2008). Design of a monitoring network overFrance in case of a radiological accidental release. Atmospheric Environment, 42(21),5205-5219.doi: 10.1016/j.atmosenv.2008.02.065Airparif. (April 2010). Bilan des émissions de polluantsatmosphériqueset de gaz à effet de serre enIle-de-France, Paris.Baklanov, A. A., & Nuterman, R. B. (2009). Multi-scale atmospheric environment modeling forurban areas. Advanced Science Research, 3, 53-57.doi: 10.5194/asr-3-53-2009Barlow, P. G., Brown, D. M., Donaldson, K., MacCallum, J., & Stone, V. (2007). Reduced alveolarmacrophage migration induced by acute ambient particle (PM 10 ) exposure. Cell Biology andToxicology, 24(3), 243-252. doi: 10.1007/s10565-007-9033-yBarnett, A. G., Williams, G. M., Schwartz, J., Best, T. L., Neller, A. H., Petroeschevsky, A. L., &Simpson, R. W. (2006). The effects of air pollution on hospitalizations for cardiovasculardisease in elderly people in Australian and New Zealand cities. Environ. Health Perspect.,114(7), 1018-1023. doi: 10.1289/ehp.8674Beer, R., Shephard, M. W., Kulawik, S. S., Clough, S. A., Eldering, A., Bowman, K. W., S. P.Sander, B. M. Fisher, V. H. Payne, M. Luo, G. B. Osterman and Worden, J. R. (2008). Firstsatellite observations of lower tropospheric ammonia & methanol. Geophysical ResearchLetters, 35(L09801), 5.doi: 10.1029/2008GL033642Brunekreef, B., & Forsberg, B. (2005). Epidemiological evidence of effects of coarse airborneparticles on health. Euro. Respir. J., 26(2), 309-318. doi: 10.1183/09031936.05.00001805Burrows, J. P., Bovensmann, H., Bergametti, G., Flaud, J. M., Orphal, J., Noel, S., S., Monks, P.S., Corlett, G. K., Goede, A. P., von Clarmann, T., Steck, T., Fischer, H., and Friedl-Vallon,F. (2004). The geostationary tropospheric pollution explorer (GeoTROPE) mission:objectives, requirements and mission concept. Advances in Space Research, 34, 682-687.doi: 10.1016/j.asr.2003.08.067Burrows, J. P., Platt, U., &Borrell, P. (2011). The Remote Sensing of Tropospheric Compositionfrom Space (1st ed.).Carmichael, G. R., Sandu, A., Chai, T., Daescu, D., Constantinescu, E., & Tang, Y. (2008).Predicting air quality: improvements through advanced methods to integrate models andmeasurements. J. Comput. Phys., 227(7), 3540-3571.doi: 10.1016/j.jcp.2007.02.024Chai, T., Carmichael, G. R., Tang, Y., Sandu, A., Heckel, A., Richter, A., & Burrows, J. P. (2009).Regional NOx emission inversion through a four-dimensional variational approach usingSCIAMACHY tropospheric NO 2 column observations. Atmospheric Environment, 43(32),5046-5055.doi: 10.1016/j.atmosenv.2009.06.052Clarisse, L., Clerbaux, C., Dentener, F., Hurtmans, D., & Coheur, P.-F. (2009). Global ammoniadistribution derived from infrared satellite observations. Nature Geoscience, 2, 479-483.doi:10.1038/ngeo551Deeter, M. N., Edwards, D. P., Gille, J. C., & Drummond, J. R. (2007). Sensitivity of MOPITTobservations to carbon monoxide in the lower troposphere. J. Geophys. Res.,112(D24306), 9.doi: 10.1029/2007JD008929Denier van der Gon, H., Beevers, S., D'Allura, A., Finardi, S., Honoré, C., Kuenen, J., O. Perrussel,P. Radice, J. Theloke, M. Uzbasich, and Visschedijk, A. (2011). Discrepancies BetweenTop-Down and Bottom-Up Emission Inventories of Megacities: The Causes and Relevancefor Modeling Concentrations and Exposure. In D. G. Steyn& S. T. Castelli (Eds.), AirPollution Modeling and its Application XXI, NATO Science for Peace and Security Series C:Environmental Security (Vol. 4, pp. 194-204).Denier van der Gon, H., Visschedijk, A. J. H., Brugh, H. v. d., Dröge, R., & Kuenen, J. (2009). Abase year (2005) MEGAPOLI European gridded emission inventory (1st version)MEGAPOLI Scientific Report 09-02 (pp. 17).24

CHAPTER 1 - INTRODUCTIONDominici, F., Peng, R. D., Bell, M. L., Pham, L., McDermott, A., Zeger, S. L., & Samet, J. M.(2006). Fine particulate air pollution and hospital admission for cardiovascular andrespiratory diseases. J. American Med. Assoc., 295(10), 1127-1134. doi:10.1001/jama.295.10.1127Egbendewe-Mondzozo, A., Musumba, M., McCarl, B. A., & Wu, X. (2011). Climate change andvector-borne diseases : an economic impact analysis of Malaria in Africa. Int. J. Environ.Res. Public Health, 8(3), 913-930.doi: 10.3390/ijerph8030913Elbern, H., Strunk, A., Schmidt, H., & Talagrand, O. (2007). Emission rate and chemical stateestimation by 4-dimensional variational inversion. Atmos. Chem. Phys., 7(14), 3749-3769.doi: 10.5194/acp-7-3749-2007Haagen-Smit, A. J. (1952). Chemistry and Physiology of Los Angeles Smog. Industrial &Engineering Chemistry, 44(6), 1342-1246.doi: 10.1021/ie50510a045Higgs, R. (2011). Public health: Ozone pollution—a link with cardiac and cerebral ischemic events?Nature Reviews Cardiology, 8(66).doi: 10.1038/nrcardio.2010.220Hoelzemann, J. J., Longo, K. M., Fonseca, R. M., Rosário, N. M. E. d., Elbern, H., Freitas, S. R., &Pires, C. (2009). Regional representativity of AERONET observation sites during thebiomass burning season in South America determined by correlation studies with MODISAerosol Optical Depth. J. Geophys. Res., 114(D13301), 20.doi: 10.1029/2008JD010369Hong, Y. C., Lee, J. T., Kim, H., & Kwon, H. J. (2002). Air pollution: a new risk factor in ischemicstroke mortality. Stroke 33(9), 2165-2169.doi: 10.1161/01.STR.0000026865.52610.5Inoue, K.-i., Takono, H., Sakurai, M., Oda, T., Tamura, H., Yanagisawa, R., Shimada, A.,Yoshikawa, T. (2006). Pulmonary exposure to diesel exhaust particles enhancescoagulatory disturbance with endothelial damage and systemic inflammation related to lunginflammation. Exp. Biol. Med., 231(10), 1626-1632.IPCC. (2007). Summary for Policymakers. In S. Solomon, D. Qin, M. Manning, Z. Chen, M.Marquis, K. B. Averyt, M. Tignor & H. L. Miller (Eds.), Climate Change 2007: The PhysicalScience Basis. Contribution of Working Group I to the Fourth Assessment Report of theIntergovernmental Panel on Climate Change. Cambridge.Jacob, D. J. (1999). Introduction to Atmospheric Chemistry. Princeton, NY: Princeton UniversityPress.Jacob, D. J., & Winner, D. A. (2009). Effect of climate change on air quality. AtmosphericEnvironment, 43(1), 51-63.doi: 10.1016/j.atmosenv.2008.09.05Jimenez, J. L., Canagaratna, M. R., Donahue, N. M., Prevot, A. S. H., Zhang, Q., Kroll, J. H., P. F.DeCarlo, J. D. Allan, H. Coe, N. L. Ng, A. C. Aiken, K. S. Docherty, I. M. Ulbrich, A. P.Grieshop, A. L. Robinson, J. Duplissy, J. D. Smith, K. R. Wilson, V. A. Lanz, C. Hueglin, Y.L. Sun, J. Tian, A. Laaksonen, T. Raatikainen, J. Rautiainen, P. Vaattovaara, M. Ehn, M.Kulmala, J. M. Tomlinson, D. R. Collins, M. J. Cubison, E. J. Dunlea, J. A. Huffman, T. B.Onasch, M. R. Alfarra, P. I. Williams, K. Bower, Y. Kondo, J. Schneider, F. Drewnick, S.Borrmann, S. Weimer, K. Demerjian, D. Salcedo, L. Cottrell, R. Griffin, A. Takami, T.Miyoshi, S. Hatakeyama, A. Shimono, J. Y Sun, Y. M. Zhang, K. Dzepina, J. R. Kimmel,D. Sueper, J. T. Jayne, S. C. Herndon, A. M. Trimborn, L. R. Williams, E. C. Wood, A. M.Middlebrook, C. E. Kolb, U. Baltensperger, and Worsnop, D. R. (2009). Evolution ofOrganic Aerosols in the Atmosphere. Science, 326(5959), 1525-1529.doi:10.1126/science.1180353Kalnay, E. (2003). Atmospheric Modeling, Data Assimilation and Predictability. Cambridge:Cambridge University Press.Kan, H., & Chen, B. (2003). A case-crossover analysis of air pollution and daily mortality inShanghai. J. Occup. Health, 45(2), 119-124.doi: 10.1539/joh.45.119Kim, J. J., Huen, K., Adams, S., Smorodinsky, S., Hoats, A., Malig, B., Lipsett, M., and Ostro, B.(2008). Residential traffic and children's respiratory health. Environ. Health Perspect.,116(9), 1274-1279. doi: 10.1289/ehp.10735Lawrence, M. G., Butler, T. M., Steinkamp, J., Gurjar, B. R., & Lelieveld, J. (2007). Regionalpollution potentials of megacities and other major population centers. Atmos. Chem. Phys.,7(14), 3969-3987. doi: 10.5194/acp-7-3969-200725

CHAPTER 1 - INTRODUCTIONLeibensperger, E. M., Mickley, L. J., & Jacob, D. J. (2008). Sensitivity of US air quality to midlatitudecyclone frequency and implications of 1980-2006 climate change.Atmos. Chem.Phys., 8(23), 7075-7086. doi: 10.5194/acp-8-7075-2008Levy, R. C., Remer, L. A., Kleidman, R. G., Mattoo, S., Ichoku, C., Kahn, R., & Eck, T. F. (2010).Global evaluation of the Collection 5 MODIS dark-target aerosol products over land. Atmos.Chem. Phys. Discuss., 10(6), 14815-14873. doi: 10.5194/acpd-10-14815-2010Liu, Y., Park, R. J., Jacob, D. J., Li, Q., Kilaru, V., &Sarnat, J. A. (2004). Mapping annual meanground-level PM 2.5 concentrations using Multiangle Imaging Spectroradiometer aerosoloptical thickness over the contiguous United States. J. Geophys. Res., 109(D22206),10.doi: 10.1029/2004JD005025Maheswaran, R., Haining, R. P., Brindley, P., Law, J., Pearson, T., Fryers, P. R., Wise, S., andCampbell, M. J. (2005).Outdoor air pollution and stroke in Sheffield, United Kingdom: smallarealevel geographical study. Stroke, 36(2), 239-243.doi: 10.1161/01.STR.0000151363.71221.12Martin, R. V., Jacob, D. J., Chance, K., Kurosu, T. P., Palmer, P. I., & Evans, M. J. (2003). GlobalInventory of nitrogen dioxide emissions constrained by space-based observations of NO 2columns. J. Geophys. Res., 108(4537), 12.doi: 10.1029/2003JD003453Miller, K. A., Siscovick, D. S., Sheppard, L., Shepherd, K., Sullivan, J. H., Anderson, G. L., &Kaufman, J. D. (2007). Long term exposure to air pollution and incidence of cardiovascularevents in women. N. Engl. J. Med., 356(5), 447-458. doi: 10.1056/NEJMoa054409Montgomery, M. R. (2008). The Urban Transformation of the Developing World.Science,319(5864), 761-764.doi: 10.1126/science.1153012Myers, S. S., & Bernstein, A. (2011). The coming health crisis: indirect health effects of globalclimate change Biology Reports (Vol. 3, pp. 1-5).Nawrot, T., Nemmar, A., &Nemery, B. (2006). Update in Environmental and Occupational Medicine2005. American Journal of Respiratory and Critical Care Medicine, 173, 948-952.doi:10.1164/rccm.2601010Osornio-Vargas, A. R., Bonner, J. C., Alfaro-Moreno, E., Martínez, L., García-Cuellar, C., Rosales,S. P.-d.-L., Miranda, J., and Rosas, I. (2003). Proinflammatory and cytotoxic effects ofMexico city air pollution particulate matter in vitro are dependent on particle size andcomposition. Environ. Health Perspect., 111(10), 1289-1293. doi: 10.1289/ehp.5913Parrish, D. D., & Zhu, T. (2009). Clean Air for Megacities. Science, 326(5953), 674-675.doi:10.1126/science.1176064Peel, J. L., Metzger, K. B., Klein, M., Flanders, W. D., Mulholland, J. A., & Tolbert, P. E. (2007).Ambient air pollution and cardiovascular emergency department visits in potentiallysensitive groups. Am. J. Epidemiol., 165(6), 625-633. doi: 10.1093/aje/kwk051Penkett, S. A., Clemitshaw, K. C., Savage, N. H., Burgess, R. A., Cardenas, L. M., Carpenter, L.J., McFadyen, G.G., and Cape, J. N. (1999). Studies of oxidant production at theWeybourne Atmospheric Observatory in summer and winter conditions. J. Atmos. Chem.,33(2), 111-128. doi: 10.1023/A:1005969204215Pétron, G., Granier, C., Khattatov, B., Lamarque, J. F., Yudin, V., Müller, J. F., &Gille, J. (2002).Inverse modeling of carbon monoxide surface emissions using Climate Monitoring andDiagnostics Laboratory network observations. J. Geophys. Res. Atmos., 107(4761), 23.doi: 10.1029/2001JD001305Pope, A., & Dockery, D. (1996). Epidemiology of Chronic Health Effects: Cross-Sectional Studies.In R. Wilson & J. D. Spengler (Eds.), Particles in our air Concentrations and Health Effects(pp. 265): Harvard School of Public Health.Prúss-Utsun, A., & Corvalán, C. (2006). Preventing Disease Through Healthy Environments:Towards an estimate of the environmental burden of disease. Geneva: WHO.Ramanathan, V., & Feng, Y. (2008). On avoiding dangerous anthropogenic interference with theclimate system: Formidable challenges ahead. Proceedings of the National Academy ofSciences, 105(38), 14245-14250.doi: 10.1073/pnas.080383810526

CHAPTER 1 - INTRODUCTIONRudan, I., Tomaskovic, L., Boschi-Pinto, C., & Campbell, H. (2004). Global estimate of theincidence of clinical pneumonia among children under five years of age. Bulletin of theWorld Health Organization, 82(12), 891-970Rylander, C., Sandanger, T. M., Petrenya, N., Konoplev, A., Bojko, E., & Odland, J. O. (2011).Indications of decreasing human PTS concentrations in North West Russia.Global HealthAction, 4(8452), 1-11.doi: 10.3402/gha.v4i0.8427Sakamoto, N., Hayashi, S., Gosselink, J., Ishii, H., Ishimatsu, Y., Mukae, H, Hogg, J.C., andEeden, S. F. v. (2007). Calcium dependent and independent cytokine synthesis by airpollution particle exposed human bronchial epithelial cells. Toxicology and AppliedPharmacology, 225(2), 134-141.doi: 10.1016/j.taap.2007.07.006Seinfeld, J. H., & Pandis, S. N. (1998). Atmospheric Chemistry and Physics: Air Pollution toClimate Change. New York City, NY: John Wiley & Sons, Inc.Simkhovich, B., Kleinman, M., & Kloner, R. (2008). Air pollution and cardiovascular injury. J. Am.Coll. Cardiol., 52, 719-726. doi: 10.1016/j.jacc.2008.05.029Tai, A. P. K., Mickley, L. J., & Jacob, D. J. (2010). Correlation between fine particle matter (PM 2.5 )and meteorological variables in the United States: Implications for the sensitivity of PM 2.5 toclimate change. Atmospheric Environment, 44(32), 3976-3984.doi:10.1016/j.atmosenv.2010.06.060Tamagawa, E., & Van Eeden, S. F. (2006). Impaired lung function and risk for stroke: role of thesystemic inflammation response? Chest, 130(6), 1631-1633.doi: 10.1378/chest.130.6.1631Tecer, L. H., Alagha, O., Karaca, F., Tuncel, G., & Eldes, N. (2008). Particulate Matter (PM 2.5 ,PM 10 - 2.5 , PM 10 ) and children’s hospital admissions for asthma and respiratory diseases: abidirectional case-crossover study. J. Toxicol. Environ. Health, 71(8), 512-520. doi:10.1080/15287390801907459Tsai, S. S., Goggins, W. B., Chiu, H. F., & Yang, C. Y. (2003). Evidence for an associationbetween air pollution and daily stroke admissions in Kaohsiung, Taiwan. Stroke, 34, 2612-2616.doi: 10.1161/01.STR.0000095564.33543.64United Nations, Department of Economic and Social Affairs (2010), Population Division: WorldUrbanization Prospects, the 2009 Revision: Highlights. New York.Von Glasow, R. (2008). Atmospheric Chemistry: Pollution meets sea salt. Nature Geoscience, 1,292-293.doi: 10.1038/ngeo192Williams, M.L. (2012, in Press). Tackling Climate Change: What is the impact on air pollution?,Carbon Management.World Health Organization (WHO) Air quality guidelines for Europe, World Health Organization,Geneva, 2000.World Health Organization (WHO) Air quality guidelines global update, Reporting on a workinggroup meeting, World Health Organization, Bonn, Germany 2005.World Health Organization (WHO) Global Health Risks: Mortality and burden of diseaseattributable to selected major risks, World Health Organization, Geneva 2009.Yeatts, K., Svendsen, E., Creason, J., Alexis, N., Herbst, M., James, S., Luawrence, K., Williams,R., Neas, L., Cascio, W., Devlin, R.B, and Peden, D.B. (2007). Coarse particulate matter(PM 2.5 - 10 ) affects heart rate variability, blood lipids, and circulating eosinophils in adults withasthma. Environ. Health Perspect., 115(5), 709-714. doi: 10.1289/ehp.9499Zanobetti, A., & Schwartz, J. (2005). The effect of particulate air pollution on emergencyadmissions for myocardial infarction: a multicity case-crossover analysis. Environ. HealthPerspect., 113(8), 978-982. doi: 10.1289/ehp.7550Zhang, Y., Huang, J.-P., Henze, D. K., & Seinfeld, J. H. (2007). Role of isoprene in secondaryorganic aerosol formation on a regional scale. J. Geophys. Res., 112(D20207), 13.doi:10.1029/2007JD008675_______27

CHAPTER 2 - AFRICACoordinating author: Cathy Liousse (1) and Abdourahamane Konaré (2)Contributing authors: Maria Kanakidou (3) and Kobus Pienaar (4)(1)Laboratoire d’Aérologie, CNRS-UPS, Toulouse, France(2)University of Cocody, Laboratoire de Physique Atmospherique, Abidjan, Ivory Coast(3)University of Crete, Department of Chemistry, Crete, Greece(4)North-West University, Potchefstroom, South Africa2.1 INTRODUCTIONMegacities are generally defined as cities with at least 10 millions inhabitants. In Africa,Johannesburg in South Africa, Cairo in Northern Africa and Lagos (Nigeria) are such megacities.Figure 1 shows the population density of Africa.Figure 1 - Map of the population density in Africa (persons per km 2 ), based on 0.25 o gridded data for 2000 from the Centerfor International Earth Science Information Network (CIESIN) at Columbia University(http://sedac.ciesin.columbia.edu/gpw/)As clearly seen from emissions in Figure 2, in these cities, population is exposed to highpollution levels. Nevertheless, in Lagos, Nigeria, Abidjan, Accra and other capitals, there is anexplosive growth of population, partly due to high levels of rural migration towards coastal cities.Consequently, by 2020 population is expected to reach above 10 millions inhabitants in Abidjanand between 5-10 millions in Dakar, Bamako, Accra, Lomé and Cotonou. With such projections, anumber of megacities will emerge in West Africa. This population pressure greatly increasespollution levels from traffic, burning of household wastes and charcoal and wood as domestic28

CHAPTER 2 - AFRICAenergy sources. In addition, refineries and other industries, thermal and cement plants, powerplants, roads and building construction are strong sources of pollutants, which also significantlyimpact air quality in African urban areas.Figure 2 – (a) CO emissions for the year 2000 based on the EDGARv3.2 FT2000 database. (b) NOX emissions for the year2000 based on the EDGARv3.2 FT2000 database. (c) SO2 emissions for the year 2000 basedon the EDGARv3.2 FT2000 database29

CHAPTER 2 - AFRICAFigure 3 displays black carbon anthropogenic emissions from a regional emission inventoryin different sectors (traffic, biofuel, power plant, industries) and different African regions.Anthropogenic Black carbon (BC) emissions in Africa are of the order of 0.68 TgC (about 13% ofglobal emissions), whereas African anthropogenic organic carbon (OC) emissions are above 40%.The same pattern occurs in West, Central and South Africa, with predominance of domestic fireemissions and a moderate traffic contribution. It is also important to note the contribution ofindustrial activities and power plant emissions in South Africa. In Northern Africa, traffic is thepredominant emission source with a smaller contribution of domestic fires and industrial activities.Total budgets for every region are of the same order, with enhanced emissions in West Africa ascompared to other areas. With such differences in mind between African areas, this chapter willcomprise three parts, respectively relating to megacities in (1) West Africa, (2) South Africa and (3)Northern Africa. In each part, specific features of some cities will be presented, followed bydescriptions of on emission sources, atmospheric pollution and the impacts on health.Figure 3 - Black carbon emission (in tons of carbon) in different sectors (traffic (C), biofuel (D), power plant (PPLT),industries (I)) and different African regions [Liousse et al., 2012; Assamoi, PhD 2011]2.2 WEST AFRICA2.2.1 Specific features of some West African citiesIn West Africa, climatic domains range from wet Tropics with heavy rainfall to arid deserts.Climate is wetter and humid in the South, getting drier and arid when moving north. So, there aretwo categories of cities: “wetter” ones along the Gulf of Guinea and others, in drier sahelian areas.After the independencies in the 1960’s, large cities have been very attractive forneighbouring and rural population, leading to a net demographic densification, especially in coastalcities. Such unplanned, spontaneous city sprawl has led to socio-economical difficulties (lack ofjobs, violence, etc.) with accompanying extreme poverty and the formation of shantytowns at theperiphery of many cities. Consequently, there is a lack of basic amenities such as drinkable water,sewage systems, waste treatment, electricity, roads, urban transportation and even schools.This also causes an intense degradation of suburban environments. One of the mainreasons for the degradation, noticeable in Figure 2 and 3 and stressed in Table 1 for CO andvolatile organic compound (VOC) emissions in Ouagadougou, is the increase in biofuel use, themain source of energy for cooking and heating. Gas energy is still a luxury in the absence ofgeneralized wind or solar energy use. Initiatives already exist to test cleaner fuels (such as gasfuels) in new cook stoves in Ghana [Bawakyillenuo, 2012]. Another pollution source is related to30

CHAPTER 2 - AFRICAvehicles, such as second hand engines from Europe (France-Aurevoir vehicles) and fromgeneralized 2-wheels individual transportation. The relative importance of traffic sources on NO 2 ,CO and VOC emissions is highlighted in Table 1 for Ouagadougou.Table 1 - Gas pollutants and their origin in Ouagadougou (in tons/year)PollutantsNO2 CO VOCEmission typeWood combustion 98 17.127 1.346Charcoal combustion 40 5.64 443Automobile 846 3.766 479Motorbikes 12 1.980 1.188Total 996 28.517 3.456Moreover, urban environment is degraded by external factors. For example, dust transportfrom northern deserts causes visibility reductions during Harmattan periods in late fall and winter(late November to mid-March). This pollution, reaching the surface in winter, is found aloft (900-1800 m) in summer. A second example as shown in Dakar [Doumbia et al., 2012], is generalizedbiomass burning that occurs during winter (dry season) [Liousse et al., 2010]. Finally, climaticfactors also play an important role: high temperatures and humidity in coastal cities, drought,winds, etc., cause conditions for intense photochemistry, which results in strong pollution formationenhancement.As a result, these cities and megacities are increasingly facing very acute public healthproblems due to air pollution at the origin of inhalation, ingestion and dermal contacts with pollutantgases and particles of all sizes (from nanometers to micrometers) and compositions.Seven representative capitals are selected in West Africa, Abidjan (Ivory Coast), Cotonou(Benin), Bamako (Mali), Dakar (Senegal), Ouagadougou (Burkina Faso), Lagos (Nigeria) andAccra (Ghana). For each of them, environmental features will be highlighted in terms ofgeographical location, population and other pertinent economical parameters. This will allow amore detailed examination of the impact of those parameters upon air quality in West African subregions.Ouagadougou in Burkina Faso (12° 22' 20" N, 1° 31' 15" W, 300 m a.s.l.) is the country's largestcity, with a population of 1.5 million inhabitants (2006). Ouagadougou, has a flat topography, withvery poor peripheral environment, and is regularly swept by harmattan winds. Based on theKöppen climate classification, this city features a typical tropical savanna climate. The city is in theSoudano-Sahelian area, with rainfall of about 900 mm per year. The rainy season stretches fromMay to October, with 30°C average temperature. The dry season runs from December to May witha minimum temperature (19°) in December-January and maximum temperature (45°) from Marchto May. Primary industries are food processing and textiles.Abidjan (5° 19' N, 4° 02'W) is the economical capital of Ivory Coast. It is the largest city of thecountry and the third-largest French-speaking city in the world, after Paris and Kinshasa. With apopulation of 8.9 million in 2006, Abidjan will soon become a megacity. The city has a tropicalmonsoon climate with a long rainy season from May to July, a short rainy season (September–November) and two dry seasons, though rain is observed even during these dry seasons. Abidjanis generally humid throughout the year, at levels generally higher than 80 percent. Total rainfall is31

CHAPTER 2 - AFRICAabout 2,000 mm per year. Temperature is almost constant (about 27°C). The observatory of airquality envisaged in the Code of the Environment for air quality control is not yet set up.Dakar, the capital of Senegal (14° 41' 34" N, 17° 26' 48" W), located on the Cap-Vert Peninsula atthe Atlantic coast and the westernmost city of Africa mainland is a major regional harbour. Dakarand its metropolitan area have a population of 3.5 million. Dakar has a hot semi-arid climate with ashort rainy season (July to October) and a long dry season (November-June). Total rainfall is540 mm per year. Temperatures are not as hot as other African cities. Diesel fuel is predominantlyused in traffic activities.Bamako is the capital of Mali (12° 39' N, 8° 0' W) with a population of 1.8 million. Bamako isranked as the fastest growing city in Africa, the sixth one in the world. Bamako, in a basin sitesurrounded by sandstone plateaus indented with small valleys favouring air channelling, isregularly swept by harmattan winds. Based on the Köppen climate classification, Bamako hasalternately a tropical wet and dry climate. Annual temperatures are over 30°C with highertemperatures from March to May (46°C) and lower ones from November to February (16 to 19°C).The rainy season is from July to September (total annual rainfall about 990mm). Localmanufacturing includes textiles, meat processing, and metal goods. There is commercial fishing onthe Niger River. Bamako has a large fleet of 2-stroke vehicles.Accra (5° 33' 00" N, 0° 12' 00" W), capital of Ghana, has a population of 5.7 million. The averageannual rainfall is about 730 mm during two rainy seasons (April - mid-July) and in October. Thereare only small temperature variations throughout the year with minimum temperature (24.7°C) inAugust and maximum in March (28°C). Relative humidity is generally high, varying between 65%in mid-afternoon and 95% at night. Predominant wind directions are from the WSW to NNE sectorswith speeds ranging between 8 and 16 km/h. Economical activities in Accra are in the financial andagricultural sectors, Atlantic fishing and manufacturing of processed food, lumber, plywood,textiles, clothing and chemicals.Cotonou (6° 22' N, 2° 26' E) is Benin’s economical capital with a population estimated between761,137 to 1.2 million, the population in 1960 was only 70,000. The urban area continues toexpand, notably towards the west. Based on Köppen's climate classification, Cotonou displaysalternately a tropical wet and dry climate with two rainy seasons (April–July and September–October with 800 to 1,200 mm of rain per year) and two dry seasons. In December and January,the city is affected by harmattan winds. Temperatures are relatively constant throughout the year,with higher temperatures at 30°C, and lower temperatures at 25°C. A familiar feature of the city isthe motorcycle–taxis (Zémidjans).Lagos (6° 27'N; 3° 21' E) was the federal capital of Nigeria until 1991 with a population growingvery rapidly from 346,137 in 1950 to 1.1 million in the 1963 census. With an estimated annualgrowth rate of 6% per annum, the estimated population of Lagos is now expected to reach 25million by 2015. Despite the high poverty index for Nigeria, Lagos State has a relatively HighHuman Development Index (HDI) with a 25% contribution to National GDP, hosting most of theindustrial and commercial Nigerian activities. Based on Köppen's climate classification, Lagos hasa tropical savanna climate with two rainy seasons (April-July and October-November) and two dryseasons (December-March and August-September). Total annual rainfall amounts to about1800mm, with temperatures in the range 24°-30° throughout the year.2.2.2 Emissions of air pollutants in West African megacitiesRecently, an urgent need has emerged to develop regional emission estimates includingAfrican specificities within global inventories. Indeed, diesel consumption from the United Nationdatabase has been shown to highly differ from regional database such as Africaclean. Significantdifferences were also noticed between traffic emission factors measured in Europe and WestAfrica [Assamoi and Liousse, 2010]. For all these reasons, a regional African emission inventoryhas been developed for carbonaceous aerosols, including African specificities for 2005 and 2030projections [Assamoi and Liousse, 2010; Liousse et al., 2012]. Estimates given by this newinventory are different from ACCMIP and RCP global inventories, especially for organic carbon32

CHAPTER 2 - AFRICAparticles [Lamarque et al., 2010]. In 2005 and 2030, mean OC estimates are higher by at least afactor 2 in the regional inventory versus ACCMIP/RCP inventories. Such investigations still needfurther development. Indeed, a study on traffic intensity in Burkina Faso for the period 2001 to2020 has shown that vehicle inventories (cars and motorbikes) are evolving very rapidly from 2001to 2005 (Figure 4). In Lagos (Nigeria) also, more information is now available for roadtransportation with details on gasoline and diesel consumption by types of vehicles (motorcycles,light duty trucks, cars and heavy duty trucks). Such examples underline the urgent need to fullycollect regional fuel data in every West-African country.Figure 4 - Evolution of the number and composition of the pool motor vehicles in Burkina FasoThis work has also shown that all sources present in West Africa are not well characterized.That is the case for air transport and the small industries sector in Nigeria and, more importantlyand generally, in West Africa, emissions from unpaved roads, waste management and burning(such as electronic wastes) and processing of used lead batteries.2.2.3 Atmospheric pollutionUnexpected high pollutionUnexpected high pollution levels have been recently measured at traffic sites in WestAfrican megacities in the frame of IGAC DEBITS in Africa (IDAF) and Pollution des CapitalesAfricaines (POLCA) programmes. NO 2 and PM 2.5 concentrations have been found to be particularlyhigh in many cities (Figure 5 and 6), much higher than WHO norms [Liousse and Galy-Lacaux,2010; Doumbia et al., 2012]. This has been confirmed with more details in Dakar and Bamako. Forexample, Figure 7 shows the annual NO 2 , HNO 3 and SO 2 concentrations in Dakar and Bamako,which are much higher than at the rural site of Katibougou (Mali) [Yoboué et al., 2012]. Anotherexample given in Table 2 shows that black carbon pollution measured in West Africa is of thesame order of the rest of the world. Note that the high PM 2.5 concentrations reported in Doumbia etal. [2012] were also obtained in Guerreiro et al., [2005] and Dieme et al. [2012] in Dakar. Finally,studies in Ouagadougou in December 2007 and April 2010 and in Abidjan in January 2008 byLinden et al. [2012] and Kouassi et al. [2010] show urban centers, urban residential, suburbanresidential and industrial sites have exceptionally high concentrations of gases and particles. PM 10mass concentrations found in Ouagadougou, for example, also largely exceed WHO 2006 airquality guideline.33

CHAPTER 2 - AFRICAFigure 5 - NO2 measurements in African capitals [Liousse and Galy-Lacaux, 2010].(Also shown in Chapter 7 as Figure 15)Figure 6 - Monthly PM2.5 concentrations in Dakar (from June 2008 to May 2009) [Doumbia et al., 2012](Also shown in Chapter 7 as Figure 16)34

CHAPTER 2 - AFRICAFigure 7 - Mean annual concentrations of NO2, HNO3 and SO2 at Dakar and Bamako traffic sites. Values for Katibougou(IDAF rural site) are added for comparison (Mali, 2008-2010), (Yoboué et al., 2013, in prep.)Table 2 - Black carbon concentrations at urban sites (adapted from Table 1 in Doumbia et al., 2012)Location Period BC (µg m -3 ) ReferencesDakar. Senegal June 08-July 09 5.7-15.4 Doumbia et al., 2012Bamako. Mali April 2008 19.2 ± 8.9 Doumbia et al., 2012Cotonou. Benin May 2005 4.9 ± 3.9 Doumbia et al., 2012Yaounde. Cameroon June-July 2004 2.4 ± 0.8Ouafo, Personal Com.August 2010 5.7 ± 2.3Paris. France Aug.-Oct. 97 10-20 Ruellan et Cachier, 2001Singapore. Asie Jan.-Dec. 00 3-14 Balasubranmanian et al., 2003Kanpur. India December 04 12.3 Tripathi et al., 2005Karachi. Pakistan Apr. 06-Apr. 07 2-15 Vincent et al., 2009Beijing. Chine Jan. 03- Aug. 04 1.2-16.3 Guinot et al., 2007Xi’an. Chine Sept 03-April 04 16.5 ± 9.8 Li et al., 2004Marylebone. Londres Oct-Dec 06 12.2 Green, 2007Spatial and temporal variability of gases and particulate concentrations in West AfricancitiesIn West-African cities, concentrations are spatially highly variable : this was observed forexample in Cotonou (Benin) and Bamako (Mali) during AMMA and POLCA programmesrespectively, from real time measurements of BC and CO in a taxi [Doumbia et al., 2012]. It wasalso noticed in Dakar (Sénégal) and in Bamako (Mali) with passive samplers for NO 2 and SO 2gases in the frame of POLCA [Yoboué et al., 2012]. Doumbia et al. [2012] show that differences bya factor of 5 may be found between different BC measurements downtown in Bamako, withmaximum and minimum levels respectively located near the markets and the Niger river. InBurkina Faso, Linden et al. [2012], Boman et al. [2009], Eliasson et al. [2009] and Arku et al.[2008] have observed high variability in PM concentrations at street level, in downtownOuagadougou, with maximum values near unpaved roads and vegetated areas. Also in this study,it is underlined that PM 1 and combustion pollutant concentrations are much higher at traffic sitesthan in suburban areas, whereas PM 10 concentrations are much higher in suburban zones, due tothe important relative impact of household fuel use in such areas.35

CHAPTER 2 - AFRICAIn West-African cities, concentrations display high temporal variability. In most of them, wecan underline morning and evening peaks associated with combustion pollution. In Ouagadougou,background concentrations are highly affected by diurnal meteorological stability and dynamics :the highest CO concentrations are found in conditions of extreme stability during evening rushhours with a CO peak much larger than in the morning (at 7am) [Linden et al., 2012]. Eveningpeaks are also observed in BC concentrations at Bamako traffic sites (Figure 8). However, suchpeaks are lower in Dakar and Cotonou than in Bamako [Doumbia et al., 2012]. This can beexplained by meteorological effects as previously shown in Ouagadougou, but also by importantuse of biofuel at this time of the day at Bamako. Note that this late and large peak never exists forNO 2 concentrations, since its considered only as a traffic tracer. Weekly variations display higherconcentrations from Monday to Friday than for Sundays, independent of the type of pollutant(gaseous or particulates).Figure 8 - Weekly variations of BC concentrations in Bamako [Doumbia et al., 2012]As already mentioned, gaseous and particulate concentrations are affected both by localpollution and/or long range transport. This is reflected in monthly variations (not shown here) of BCand NO 2 concentrations, displaying higher values during the biomass burning season. This is alsoseen during dust tranport events, particularly in Bamako and Ouagadougou. Finally, note thatduring the wet season, wet deposition also contributes to lower particulate concentrations than inthe dry season in all capitals.Link between pollution chemical characterization and main combustion sourcesAs discussed above, main prevailing combustion sources in West-African cities are traffic,domestic fuel combustion, dust resuspension from unpaved roads, waste burning and industries.In Ouagadougou, toluene/benzene, NO X /benzene and PM1/PM10 ratios are used to discriminatebetween traffic and domestic fuel combustion sources [Linden et al., 2012].In Abidjan, where rural/urban/industrial sites have air pollution monitors, the influence ofboth natural and anthropogenic emissions are observed [Kouassi et al., 2010]. Higher benzeneconcentrations are found in urban and industrial sites than in the rural one, whereas other organicgaseous compound concentrations are higher at the rural site. Transition metals are retrieved atevery sampling site (Table 3). Due to coastal influences linked to the location of the industrial site,chlorides are more important at this site than at other sites. Iron (Fe) is more important in urbanthan in industrial sites, whereas aluminium (Al) is maximum at the rural site. The same compoundshave been studied in Dakar at traffic and rural sites by the same team [Dieme et al., 2012]. Theyhave drawn similar conclusions for Fe, i.e. more abundant at urban than at rural sites due toanthropogenic influence, but lower concentrations of Al are retrieved at the rural site near Dakar36

CHAPTER 2 - AFRICAthan near Abidjan. In contrast to Abidjan, lower concentrations of lead are measured in Dakar : thisis due to unleaded gasoline effectively used in Dakar, which has not yet been implemented inAbidjan. Same conclusions appear for SO 4 concentrations in both studies, higher at urban than atrural sites due to unregulated combustion of fossil fuels in the traffic and industrial sectors. Bothstudies also suggest possible coating by VOC, inorganics and PAH onto PM particles, with higherspecific surface areas at urban than at rural sites.Table 3 - Inorganic and ionic compositions of collected PM. Inorganic compounds were detected in particle matter (PM) byinductively coupled plasma–atomic emission spectrometry. Ionic compounds were quantified with ionic chromatography[Kouassi et al., 2010]Ions;(µg;mg − 1;PM) Rural Urban IndustrialCl− 6.17 3.35 31.37NH4+ 6.16 2.65 4.30NO3 12.23 19.62 20.04SO4 19.62 13.36 17.24Metals;(µg;mg − 1;PM)Al 78.79 60.59 56.01Ca 31.57 35.54 36.31Cr 0.11 1.44 0.86Cu 0.14 0.24 0.11Fe 46.32 54.25 34.30K 16.20 9.69 17.45Mg 11.55 7.19 10.75Mn 2.79 0.68 0.57Na 9.59 10.06 24.64Ni 0.07 0.05 0.07Pb 0.06 0.49 0.40Sb

CHAPTER 2 - AFRICAratios in Bamako suggest higher organic carbon content, in agreement with more incompletecombustions in Bamako. This feature is confirmed with PAH concentrations being much higher inDakar (diesel sources) than in Bamako. Finally, water-soluble organic carbon (WSOC)concentrations are found much higher in Bamako than in Dakar.2.2.4 Atmospheric Pollution and HealthExposure/Epidemiological studiesIn West Africa, air pollution exposure is expected to be responsible for most respiratorydiseases [WHO, 2006], with lung affections and respiratory irritations respectively due to CO, NO X ,PM 1 , benzene and toluene. However, potential exposures vary with populations, depending ontheir daily activities. As shown by Linden et al. [2012] for Ouagadougou, careful consideration ofboth location and time resolution of measurements is required for accurate exposure assessments.There is an urgent need for exposure scenarios, through displaying for example individual datamonitoring measurements. Heavy exposures are expected for workers near traffic sources and forfemales and young children near domestic fuel combustion. In Nigeria, occupational exposureintensive measurements are available, linking air pollution at workplaces to adverse implications forthe health of workers [Baumbach et al., 1995; Adejumo et al., 1994; Ogunsola et al., 1994; Oyedele etal., 1995].During the POLCA programme, groups of people have been identified for health studieslinked to pollution. In Bamako for example, O. Koita [personal communication] has shown that theselected group is mainly affected by traffic and domestic fuel sources prevailing at the site (only15% of this group is exposed to waste burning, 18% to cigarette smoke, 7% to industries). InDakar, the concept of bio-indicators for air quality was examined: several cytokines such asInterleukin 1 β (IL-1β), interleukin 5 (IL-5) interleukin 8 (IL-8) and proteins (Clara Cells, CC16) havebeen evaluated for subjects exposed to air pollutants prevailing at the POLCA traffic site [Gueye,PhD Thesis 2008]. About 67 subjects are enrolled, including 33 merchants (traders) with collectionof their blood for pro-inflammatory cytokine study. This study has shown a glutathione statusalteration implying a defense system alteration due to atmospheric pollution [Gueye, PhD Thesis2008 ; Gning, PhD 2011].Finally, only few results are presently available for epidemiological studies linked to air pollutionin West Africa using long-term observations. An example is given in Table 4 with a follow up realizedin Kossodo (Burkina Faso) and carried out by the Laboratoire de Physique et de Chimie del'Environnmement of the University of Ouagadougou over 3 years (1999, 2001 and 2002), detectedan increase of upper and lower respiratory track infections (Table 5). Such results are encouragingand need to be largely extended to other cities in West Africa and linked to atmospheric pollution.Indeed, up to now, all estimates for asthma, morbidity or mortality in West Africa are based on doseresponsefunctions only established for northern developed countries. As shown earlier, and due toAfrican pollution specificities, such functions urgently need to be specifically determined for WestAfrica, using in parallel both long-term pollution measurements and health registrations: this is quite aimportant point to be stressed.Table 5 - Prevalence of respiratory infections in the Health District of Kossodo (Ouagadougou). Source: LPCE/UO. Thenumber of cases of respiratory infections was 3 times greater in 2002 than observed in 1999 (35 405 cases versus 11 466)Kossodo Health District/Year 1999 2001 2002Upper respiratory track infections 4 819 9 428 15 072Lower respiratory track infections 6 647 11 847 20 331Total 11 466 21 275 35 40338

CHAPTER 2 - AFRICASeveral studies in Nigeria have dealt with the consequences, such as mental developmentin children, of high blood lead concentrations [Ogunsola et al., 1994]. However, recent leadmeasurements in Lagos and Abuja show that atmospheric lead concentration are now between 1 and2 orders of magnitude lower than previous measurements, following the gasoline lead phase out in2006 [Ezeh et al., 2010].Aerosol biological reactivities of human bronchial epithelial cells from in vitro studiesThe fine and ultrafine aerosol fractions are now recognized to induce biological effects dueto their capacity to reach the distal lung, together with specific compositions including transitionmetals and organic compounds [Happo et al., 2008; Seagrave et al., 2006; Huang et al., 2003].Particle toxicity results from their ability to trigger intracellular production of reactive oxygenspecies in epithelial cells and macrophages, the first cells encountered by particles in therespiratory tract. This oxidative stress activates signalling pathways, leading to the release of proinflammatorybiomarkers (IL-8; IL-6, GM-CSF….) [Mitschik et al., 2008]. Such comprehensiveprocesses of particle health effects have been extensively studied in developed countries, leadingto specific regulations [Ramgolam et al., 2009]. Only a few studies have been conducted indeveloping countries, especially in West Africa [Val et al., 2012; Kouassi et al., 2010; Dieme et al.,2012].An example of such results was part of POLCA, with the aim of characterizing atmosphericparticulate pollution and to determine induced toxicity potential of particles in epithelium cells(16HBE) according to their sizes (coarse, fine and ultrafine particles). Three main situations werescrutinized: Bamako during (BK1) and after (BK2) a typical dust event and Dakar (DK) (aerosolchemical specificities given in Figure 9 and in Table 4). PM biological reactivities werecharacterized from measurements of the expression of a panel of biomarkers.Figure 9 - Size speciated chemical aerosol composition in Dakar and in Bamako during (BK1)and after (BK2) a dust event [Val et al., 2013](Also shown in Chapter 7 as Figure 17)39

CHAPTER 2 - AFRICAAs shown in Figure 10, ultra fine and fine PM induce higher biological effects (GM-CSFcytokines) as compared to coarse particles, whatever the sites. Bamako aerosol can bedistinguished by an impressive biological reactivity associated to local sources, since less reactivewhen diluted by external input such as dusts. This reactivity is stronger in Bamako than in Dakar.Considering aerosol chemical speciation in the two cities, aerosol biological responses seem to beclosely related to organic compound contents [Val et al., 2013].Figure 10 - GM-CSF cytokine concentrations as a function of aerosol size classes for the reference sample (Ctr), andBamako (BK1 and BK2) and Dakar samples. Different doses (1-5 et 10 g/cm 2 ) have been tested [Val et al., 2012]Other in-vitro studies dealing with air pollution effects possibly involved in lung toxicity inepithelium cells have been recently conducted in Abidjan for urban, industrial and rural sites onA549 cells and in Dakar for traffic and rural sites on BEAS-2B cells [Kouassi et al., 2010; Dieme etal., 2012]. Both studies have confirmed that both anthropogenic transition metals (Fe, Al, Al, Pb,Mn, Zn) and organic compounds (PAH) are involved in a time and dose dependent secretion ofinflammatory mediators and ensuing oxidative damages. Note that high levels of reactive oxygenspecies have been measured at Abidjan sites, not in Dakar.Finally, in the frame of POLCA (O. Koita, pers. com.), atmospheric bacterial population hasbeen studied in Bamako for a six-month period (57% Bacillus against 34% Cocci). The presence ofthese bacteria is an important factor for the prevalence and incidence of respiratory andcardiovascular diseases in Bamako. Note that dust-carrying bacteria are generally associated withmeningitis epidemics in the Sahelian belt. Indeed, meningitis outbreaks typically occur a few daysafter dust events: mechanistically, combination of lung system damage due to atmosphericpollution, dust vectors and bacteria could jointly act in developing epidemics. Many studies are stillon going to decipher such occurrences.2.2.5 ConclusionAs mentioned in the present chapter, air pollution and health is a real joint problem in WestAfrican capitals. The main sources of emissions are linked to traffic, domestic fuel combustion andwaste burning. The importance of industrial activities has been pointed out in South Africa only.The main emissions sources are controlled with only a few regulations (e.g. fuel desulfurization inSenegal, lead decrease in Nigeria). The situation is expected to rapidly deteriorate in the absenceof any further actions. Moreover, political conditions in West Africa will result again and again inpopulation migration and urbanization. It is now urgent for research studies to focus on integratedprojects combining emissions, air quality, health studies (epidemiological monitoring, toxicology,hospitalizations), acid deposition and impacts on soil and water resources together with local andregional climate change studies to provide possible emission mitigation options resulting in positiveimpacts.40

CHAPTER 2 - AFRICA2.3 SOUTH AFRICA2.3.1 Johannesburg conurbation and the Vaal triangle area: characteristics, geography,population, meteorologySouth Africa is experiencing large-scale social and economic changes, coping with bothdeveloped and developing world problems that affect its regional environment. For example,Greater Johannesburg is faced with great differentiation in terms of service deliveries betweendifferent areas.Significant impacts are due to population growth, population migration, industrialdevelopment, water shortages and change in agriculture practices. Increasing demand fordomestic food sources and exports in southern Africa lead to growing needs for agricultural land aswell as intensification of industrialization. South Africa is under severe anthropogenic pressure withincreasing emissions due to rapid growth in energy needs, particularly in the Vaal Triangle close toJohannesburg (Figure 11).Figure 11 - South Africa map with a focus on Johannesburg conurbation and the Vaal triangle areaThe Johannesburg conurbation and the Vaal triangle area is a large industrial area with 18million inhabitants, 13 million of which live in Johannesburg conurbation. Four “industrialized” citiesare included in the conurbation, including huge industries such as Sasol, Natref, Dow, ArcelorMittal, Samancor, Emsa (electro chemical) and many coal mines such as Sigma, Coalbrooke,Eskom mines and Wonderwater. In this 3600km 2 area, there are six big townships with strongemissions also linked to domestic combustion of firewood, coal and other biofuels.Johannesburg is, by population, the largest city in South Africa, ranking amongst the 50largest metropolitan areas in the world. According to the 2007 Community Survey, the population41

CHAPTER 2 - AFRICAof the city of Johannesburg was 3.9 million and the population of the Greater JohannesburgMetropolitan Area was 7.2 million. A broader definition of the Johannesburg metropolitan area,including Ekurhuleni, the West Rand, Soweto and Lenasia, has a population of 10.3 million.Johannesburg is the provincial capital of Gauteng, with the largest economy of any metropolitanareas in Sub Saharan Africa. Johannesburg owes its location to the presence of gold, comprising40% of Gauteng’s GDP. Though Johannesburg is not one of South Africa’s three capital cities, it isthe location of the Constitutional Court.Johannesburg is located in the eastern plateau area of South Africa (Highveld) at anelevation of 1753m. Johannesburg features a subtropical highland climate. Temperatures inJohannesburg are usually fairly mild, with average maximum daytime temperatures in January of25.6 °C, dropping to an average maximum of 16°C in June. Regular cold fronts pass over in winterbringing very cold southerly winds but usually clear skies. The annual average rainfall is 713mm,mostly concentrated in the summer months.In Johannesburg, 80% of households have access to running water, and 80% useelectricity as the main source of energy. Thirty percent of Johannesburg residents live in informaldwellings with less than adequate accommodations. Some 15% of households are still burningfossil fuels for their cooking and heating requirements. With an inadequate public transport system,traffic volumes are rapidly growing with a 25% increase between 1996 and 2000 for example.The Vaal triangle area (also called dirty triangle) is notorious for its poor air quality, withindustrial and mining emissions combining with large-scale domestic coal burning emissions ininformal settlements and townships to produce a formidable air quality problem in the region.Moreover this outdoor pollution is often related to problems of indoor air quality. This region, theindustrial heartland of South Africa, is located roughly 40km south-southwest of Johannesburg.Major towns within the region are Vereeniging, Vanderbijlpark, Sasolburg and Meyerton. However,the majority of the population lives in the townships of Boipatong, Bophelong, Evaton, OrangeFarm, Sebokeng, Sharpville and Zamdela. The annual average rainfall in the Vaal triangle area isbetween 500 and 700mm, with cold winters.Note that the Vaal triangle area has been recognized by the Air Quality Act from NationalEnvironment Management in 2010 as one “priority area”, where hot spot of pollution needs to bemanaged. The other one is the Highveld area, not detailed here.Finally, another important combustion source of pollution in South Africa to note that is wellestablished in publications is biomass burning during the dry season (from August to November).The different pollutants from a variety of emission sources (e.g. fossil fuel, biomass burning andnatural sources) are mixed together and transported, sometimes as far as Amsterdam Island in theIndian Ocean or over the Atlantic Ocean [Piketh et al., 1996; Tyson et al., 2002].2.3.2 Emission sources of air pollutantsAs depicted in Figure 2, South African emissions are mainly linked to domestic, industrialand power plant activity sectors.The South African power generation sector is heavily dependent on coal (Scorgie et al.,2004). Based on 2001 Eskom data, coal is responsible for about 90% of Eskom's powergeneration, other sources including nuclear (5.7%) and hydro (1.1%). These power stations aredesigned to use low-grade coal associated with higher emissions than high-grade coal availablefor export. South African coal has a relatively lower sulphur content than coal elsewhere. Due tohigh ash content in combusted coal, particulate emissions and ash production are higher thanwould be the case with low-ash coals. As a consequence, Eskom's pollution control policy hasbeen concerned primarily with the control of particulate emissions using electro-static precipitators(ESPs) to remove bulk particulate emissions from flue gases [Scorgie et al., 2004].The industrial sector (non-power generation) includes coal, anthracite, coke, heavy fuel oil,gas, diesel and paraffin. This sector has a large variety of industrial and waste disposal processes42

CHAPTER 2 - AFRICAranging from waste incineration (including medical, toxic, animal and other waste types), petroleumrefining, inorganic and organic chemical processing (e.g. carbon black processes), mineral productindustries (e.g. brickworks), cement manufacturing, coal conversion (e.g. Sasol oil from coal plantsat Sasolburg and Secunda), glass manufacture and metallurgical industries. Note that the Sasolprocess of coal gasification in the production of synthetic liquid fuels from gas is a relatively uniqueprocess, whose emissions are expected to be very high.Fuel other than electricity, used for household for cooking, lighting and/or space heatingpurposes primarily include: coal, wood, LPG, paraffin and candles. Waste material, including oldshoes and tires, is also burned by households unable to afford other fuel carriers. In rural areas,some households burn animal dung to meet their energy, heating and cooking needs. Continueduse of coal and wood by a large section of the population in South Africa is a cause of concernwith regard to air pollution and health risk potentials. These fuels continue to be used for primarilytwo reasons: (i) rapid urbanization and growth of informal settlements (ii) Coal is readily availableand inexpensively in Gauteng and Mpumalanga. Given the availability of coal and relatively lowtemperatures experienced during winter months, coal consumption is high in these regions. Woodis burned in place of coal in coastal regions including Cape Town and Ethekwini. Household fuelburning tends to peak during early morning and evening at which times the atmosphere ischaracterised by limited mixing depths and stable conditions favourable to stagnation of pollution[Engelbrecht et al., 2000]. Due to emissions in a confined space (indoor pollution) and due towinter maximum uses being associated with minimum atmospheric dispersion, domestic fuelburning emissions have a greater potential impact on air quality as compared to equivalentemissions from, for example, industrial sources.Focus on coal use in the different sectors shows that 2% is for industry, 2% for thedomestic sector (producing 25% of the emissions), 43% for electricity, 30% for export and 21% forcoal liquefaction (synthetic fuel production).Diesel and petrol (including leaded and unleaded petrol) represent the main fuels used byvehicles. Note that reductions in ambient lead concentrations (consequently in blood lead levels ofchildren) have been observed. This could be due to the introduction of unleaded fuels, with leadedfuel phased out in January 2006. Other mobile source uses a variety of fuels, e.g. aircraft mainlyuse jet fuel, ship engines typically use marine diesel oil and non-electrified trains use primarilydiesel and coal.Local inventoriesSince 1990, a national effort has taken place to develop local emission inventories. Certainmetropolitan areas have emission inventories for common pollutants such as SO 2 , NO X , CO, CO 2 ,hydrocarbons and particulates (TSP or PM 10 ).In Johannesburg, combustion-related emission sources have been identified and effortshave been made to quantify some of these sources, but no exhaustive emission inventory currentlyexists. For example, in the National emission inventory database (1994), emission inventories forcoal power plants in the area are available. Domestic coal combustion emission inventories havebeen developed from different assessments and measurements [Scorgie et al., 2003a], giving amean total of 3878 tons/yr for PM 10 . Emissions data for the transport sector only included dieselfuel with 1625 tons/yr of PM 10 . Data is also available for spatial emission based on road density,industry and power plant location maps.In 1995 an emissions inventory for municipal areas in the Vaal Triangle was established[Van Nierop, 1995]. The emissions inventory includes industrial, domestic, vehicular and powerplant sectors. In parallel, a few experiments took place on domestic fuel emissions forcharacterization. During the winter of 1997, Engelbrecht et al. [1998; 2002] and Terblanche[1995b; 1998] found 62% of PM25 came from domestic burning, 14% from biomass burning, 11%from dust and only a minor contribution from power plants and vehicles. More interestingly, twotypes of coal were studied: D grade coal (low quality usually used) and low smoke coal (as analternative source of energy). The results showed a 25% reduction of particulate emissions when43

CHAPTER 2 - AFRICAlow smoke coal was used instead of D grade coal.To conclude, it is important to note that the existing inventories were not followed up on.Also, these emission inventories are sometimes incomplete and need to be extended to otherpollutants and to include other sources (particularly industrial and institutional fuel burning,industrial processes, household fuel combustion and vehicle emissions).Note that much work is going on to compensate for the current lack of information. Forexample, a PhD study was just completed on emission inventories linked to domestic burning inSouth African townships [Naidoo, 2012]. Other measurements on emission characterization arebeing carried out and results are expected soon (power plant, coal liquefaction).Regional emissionsAs mentioned in the introduction, a regional emission inventory has recently beendeveloped for Africa, including some African specificities [Assamoi, PhD 2011; Liousse et al.,2012]. For example, a particular effort has been made on spatial emission characterization ofpower plant and industrial activities. Figure 12 displays industrial and power plant OC emissions in2005, either spatially distributed with CIESIN (2005) population density (left) or with emissionlocations after Flemming data (right). Other important work has been conducted on emissionprojections for 2030. Indeed, in the socio-economical POLE model used to obtain fuel consumptionin 2030 for different scenarios, South Africa was considered as a developing country. A newscenario (2030ccc*) has been constructed by applying projection factors typical for semidevelopedcountries and by applying improved emission factors for domestic fuels, both actionsthus reducing OC emissions by 62%, as compared to the previous “best” scenario.Figure 12 - Organic carbon emissions (in tons C) in South Africa in 2005 with the new regional African inventory [Liousse etal., 2012]: left with CIESIN spatialization (0.25° x 0.25°), right with the data of Flemming et al. (Fourié, pers. com)Finally, Figure 13 presents OC emissions obtained with the regional inventory for 2005and for the three 2030 scenarios. Data given by global ACCMIP/RCP inventories are added forcomparison [Lamarque et al., 2010]. OC is higher in the regional inventory than in ACCMIPinventory for 2005 (BC, not shown here, is quite comparable). OC projections differ, especially forthe BAU scenario. Differences are smaller for the “best” scenarios. Such a study underlines theneed to construct local and regional inventories for the past, the present and the future.44

CHAPTER 2 - AFRICAFigure 13 - OC anthropogenic emission annualbudget for 2005 and different 2030 scenarios. Inblack, Liousse et al. [2012], in grey; ACCMIP/RCPinventories[Lamarque et al., 2010]2.3.3 Air PollutantsAs displayed by satellite retrievals (e.g. Sciamachy), there are NO 2 pollution hot spots inSouth Africa Highveld. Indeed, tropospheric NO 2 column densities of this area are comparable tothose observed in central and northern Europe, eastern North-America and south-east Asia. Inaddition, existing ground measurements in South Africa confirm such a picture, showing the hugeimpacts of domestic coal burning, industrial and power plant sources and traffic on air quality. Arecent example, including a box model with detailed gas-phase chemistry developed along withnew measurements of trace gases at several locations in and around Johannesburg conurbationinvestigated the impact of industrial activities on tropospheric photochemistry and showed that NO 2concentrations in the megacity have diurnal peaks during early morning and late afternoon, whichcoincide with peak traffic hours and domestic combustion [Josipovic et al., 2010; Lourens et al.,2012]. During these periods, NO 2 concentrations in the megacity were even higher than in theHighveld hotspot. These diurnal NO 2 peaks in the megacity have generally been overlooked bysatellite observations, since satellites have fixed local overpass times that do not coincide withsuch peak periods. This implies that the importance of NO 2 in the megacity has beenunderestimated (Figure 14).Figure 14 - Median diurnal NO2 mixing ratios at all ground-based stations for the period March to May 2009 together withaverage values over the regions. M denotes a Megacity station and H a Highveld hotspot station [Lourens et al., 2012]Such results highlight numerous previous studies conducted since the 1990s in SouthAfrican that measured elevated concentrations of particulate matter, sulphur dioxide (SO 2 ),nitrogen oxides (NO X ), carbon monoxide (CO), carbon dioxide (CO 2 ), ozone (O 3 ), volatile organiccompounds (VOCs) and semi-volatile organic compounds (SVOCs), methane (CH 4 ), hydrogensulphide (H 2 S) and various trace elements at urban, industrial and coal burning site. These airquality studies are fragmented and unsystematic: though a number of studies have been45

CHAPTER 2 - AFRICAcompleted, their results have not been yet integrated and made easily accessible (South Africacountry report, 2005). Despite this limitation in information, South’s Africa air quality is consideredas being relatively good on the whole, though with a number of air pollution “hot spots” wheresevere problems are encountered. As already mentioned, such a concern is tackled by theNational Environmental Management agency with the AQA program providing measures for airquality improvement (ambient air quality standard, control of emissions ...). A few examples ofstudies focused on Johannesburg conurbation and on the Vaal triangle priority area follows.JohannesburgScorgie et al. [2003a], gather ambient air quality monitoring data in Johannesburg from fieldcampaigns at occasional sites and at continuously operating monitoring stations. Note that manymonitoring sites exist in the Johannesburg conurbation (Mintek, New town, Lapa, Kemton Park,City Deep, City Hall, Soweto), some of them since the 1980s (Piketh 2007). High heterogeneity inenvironmental air quality in this conurbation is noticed with poorest situations in the northern part ofthe metropolitan area, Alexandra, the mining and industrial belt and the Klip River area, Roodeportvicinity and the area around Soweto, Orange Farm and Poortjie(http://ceroi.net/reports/johannesburg/csoe/navpoll.htm).Ambient air quality monitoring data at the Soweto site taken as part of the Soweto AirMonitoring Project (Project SAM, Department of Environmental Affairs and Tourism (DEAT),Soweto Health Department, Soweto Branch of the National Association of Clean Air (NACA))examined ambient particulate concentration and their health risks from domestic coal burning inSoweto residential areas between 1991 and 1999. Seasonal trends show increasing particulateconcentrations during winter months, associated with an increase in coal burning for space heatingand unfavourable atmospheric dispersion potentials. Winter time concentrations are in exceedanceof the US-EPA standard by a factor as high as 4.8. This is confirmed by PM2.5 sourceapportionment also conducted in Soweto in 1996-1997, with 57% to ~75% of PM2.5concentrations due to domestic coal burning emissions [Annegarn and Grant, 1999]. A downwardtrend in airborne particulate concentrations was observed during the studied period (1992-1999),confirming results in Annegarn and Sithole [1998]. The downward trend is mainly explained by adecrease in coal use in favour of less polluting fuels, such as electricity, in the immediate vicinity ofthe monitoring site. Morning and evening peaks in airborne particulate concentrations have beenassociated with cooking and heating activities and peak hour commuter traffic. Distinct increases insulphur dioxide, oxides of nitrogen and volatile organic carbon concentrations are also apparentduring winter months, with temporal trends also indicative of domestic fuel burning periods. NO 2levels measured during this period exceeded WHO guidelines, whereas O 3 concentrationsexceeded both the South African and WHO guidelines [WHO, 2000].A regional study conducted by IVL Swedish Environmental Research Institute and CSIRand appointed by the City of Johannesburg, allowed SO 2 and NO 2 air pollution level mappingacross Johannesburg, from a passive diffusive sampling campaign at almost 300 sites in July1999. Elevated sulphur dioxide levels are evident across the industrial areas with significantcontribution of domestic coal burning in townships and informal settlements during winter months.The zones of NO 2 maxima closely coincide with the areas of high vehicle activity.Vaal triangleThe Vaal Triangle Air Pollution Health Study (VAPS) was initiated in 1990 to study thepotential impacts of air pollution on human health. Several other sampling campaigns have alsooccurred in this region [Burger, 1994; van Nierop, 1995; Engelbrecht et al., 1998; Terblanche,1998]. Main findings of VAPS and related studies are as follows:• Particulate matter appears as the pollutant of greatest concern in the region with annualaverage levels exceeding international health standards by at least a factor of 2.5.• High ambient particulate concentrations are found to coincide with low ambienttemperatures and low rainfall. As shown earlier for Soweto, the highest concentrationswere predicted to occur in or near coal burning residential areas (townships and informalsettlements), with maximum values during winter months (2 to 4-fold increase) and a46

CHAPTER 2 - AFRICAdistinct diurnal trend. Within coal burning townships, levels of TSP were 4-6 times worsethan regional averages.• Sulphur dioxide levels were found to exceed air quality guidelines less than 5% of the timein the Sasolburg industrial area, with SO 2 levels in residential areas being below air qualityguidelines. Concentration peaks observed during the early morning are associated withemissions from tall stacks in the region.• No exceedances of ambient air quality guidelines for NO X were observed to occur duringVAPS. An increase in annual averages occurred during the 1990 to 1993 period, withincreasing NO X concentrations at the Sasolburg Industrial site.A similar pattern was observed 10 years later.More recent data are now available in the Vaal Triangle area, in connection with Sasoland Eskom monitoring sites. Also new measurements are being developed in the frame of theGRDI ARSAIO programme, a collaboration between North-West University (South Africa) andLaboratoire d’Aérologie (France). Efforts will focus on aerosol chemical speciation and biologicalimpacts on human health in the Vaal triangle. An example of expected results is shown in Figure15. Aerosol chemical speciation was obtained during the 2006 winter months for PM2.5 and PM10particles at the Amersfoot rural site, which has an industrial influence (IDAF/DEBITS network,http://idaf.sedoo.fr). The data show high relative contribution of organic carbon particles followedby sulphate and black carbon. Corresponding results obtained from a modelling study are addedfor comparison.Figure 15 - Modelled/Measured size speciated aerosol chemistry at the Amersfoort site for the 2005-2007 period[K. Martin, PhD 2008; Guillaume et al., 2007]Finally, as previously indicated, this review shows that air quality is a national concern andair quality national legislation is becoming more and more stringent. The National EnvironmentalManagement (Air Quality Act, Act No. 39, 2004, 2010) is now replacing the Atmospheric PollutionPrevention Act (APPA), Act 45 of 1965. In 2010, national ambient air quality standards have beendefined for SO 2 , NO 2 , PM10, 0 3 , benzene, lead, CO (http://www.naca.org.za) with addition ofPM2.5 in September 2012. Note that a recent workshop in 2011 “Changing Chemistry in aChanging Climate: Human and Natural Impacts over southern Africa – C4-SAR” organized byBurrows, Piketh and Thompson also gathered many studies here mentioned.2.3.4 HealthMany epidemiological studies related to indoor and outdoor air pollution have beenconducted in South Africa since 20 years, using different indicators (mortality rate, risk assessmentstudies, health index…). A few of them (this is not an exhaustive list), is now presented tounderline the evidence of air pollution impacts.General studies in South AfricaThe mortality rate of acute respiratory infections (ARI) in South Africa is reported to be 270times greater than for children in Western Europe [Terblanche et al., 1993]. Recent47

CHAPTER 2 - AFRICAepidemiological data have indicated that ARIs are one of the leading causes of death for blackSouth African children. More recently, Barnes et al. (2009) reviewed evidence of the associationbetween household energy, indoor pollution and child ALRI (Acute Lower Respiratory Infections) inSouth Africa, showing high relative mortality risks from different studies in South Africa.In Scorgie et al. [2003, 2004] the focus is on epidemiological studies in many SouthAfrican cities (Cape Point, Johannesburg, Vaal triangle, Highveld). Using northern developedcountry dose-response functions (no values exist for Africa) of 1.20 x 10 -5 for PM10 daily exposureand respiratory hospital admissions and 2.01 x 10 -6 for SO 2 (values for PM10 are more harmfulthan for SO2) the studies showed:Table 6 - Numbers of health endpoint in Johannesburg and in the Vaal triangle [Scorgie et al., 2004]HEALTH ENDPOINTRespiratory hospital admissions (due to PM10, SO 2 and NO 2exposures)CITY OF JOBURG & VAALEKURHULENI TRIANGLE34,021.1 9,440.0Cardiovascular hospital admissions (due to PM10 exposures) 262.2 71.0Premature mortality (due to PM10 and SO 2 exposures) 71.5 19.9Chronic bronchitis (due to PM10 exposures) 38,550.4 9,457.5Restricted activity days (RAD, due to PM10 exposures) 238,326.3 62,546.5Minor restricted activity days (MRAD, due to SO 2 exposures) 12,396,320.4 6,128,743.4Leukemia cases (due to 1.3 butadiene and benzene exposures) 67.4 9.1Nasal carcinoma cases (due to formaldehyde exposures) 1.5 0.2Number of children exposed to Pb> 2!g/m 3 & hence to potentialfor IQ point reductions5,285.8 0• Combustion sources are responsible for 0.64% of hospital.• Domestic sources account for 70% of all respiratory related hospital admissions (RPHA)and 75% of all premature mortalities• Traffic is responsible of 12% of all RPHA and 6% of all premature mortalities.• Electricity generation accounts for 6% of all RPHA and 5% of all premature mortalitiesDue to paramount importance of coal burning sources in townships and informalsettlements, health indices (HI) were calculated by Terblanche [1996] to demonstrate themagnitude of household exposures and associated risks. The health index (HI) represents theratio of the sum of pollutant doses over acceptable doses, summed for all pollutants with the samehealth effects. Generally, HI

CHAPTER 2 - AFRICATerblanche [1996] concluded that, based on calculated HIs, a reduction in particulateconcentrations near 100% would be required to meet with WHO health standards. More recently,Norman et al. (2007a and b) have estimated the burden of diseases attributable to urban areas(including Johannesburg and Vaal triangle area) and to indoor air pollution from solid fuel burningrespectively by using the Comparative risk assessment methodology developed by WHO. PM2.5and PM10 were used as exposure metrics. They showed that outdoor air pollution was estimatedto cause 3.7% of national mortality in 2000 from cardiopulmonary diseases, 5.1% from respiratorytrack cancers in adults aged 30 and older and 1.1% of mortality from ARI in children under 5 yearsold. Regarding indoor pollution, it is estimated 20% of South African households are exposed tosolid fuel burning with marked variations between population groups. Such exposure wasestimated to have caused 0.5% of all deaths in South Africa in 2000.Vaal triangleExposure studies have been conducted in Sebokeng (Vaal triangle) in 1991 by CSIR andthe Medical Research Centre. Forty-five children were monitored between the ages of 8 to 12years old. The study revealed extremely high levels of exposure to total suspended particulates, inexceedance of the US-EPA air quality standard [Terblanche et al., 1992]. Exposures to indoor COconcentrations were found to be up to 180% higher in coal-burning households as compared towood-burning ones within the Vaal Triangle [Terblanche et al., 1995a].More recently, the VAP programme (1990-1993) using six monitoring sites studied thehealth status of adults who had spent their developing years in a polluted area in the Vaal triangleand for whom their respiratory health status was known [Oosthuizen, 2004 Master; Oosthuizen etal., 2008]. Approximate 14,000 children (10 years old) were involved in this programme. Bothoutdoor and indoor measurements with personal monitoring on 30 children (teenagers = 15male/15 female) were performed. The results indicate that the upper prevalence of respiratoryhealth effects is 65% for 10 year olds children compared to 72% for young adults (i.e. 20 yearsold). The risk was the same whether or not the young adults has stayed or left from the Vaaltriangle region. Consequently, exposure to pollution only cannot explain such an increase. Thiscould be due to external risk factors such as pollution perception, allergies, smoking, family history,weight, etc.Johannesburg conurbationAn epidemiological study took place in Soweto lead by the Medical Research Council.The programme, Birth to Ten, focused on neonates to ten years old children (3275 children total).This program now called Birth to twenty is focused on growth and pubertal development in relationto the many risk factors facing young people. Questionnaires on a monthly basis were distributedover a period of one year. Information was obtained on housing factors, fuel usage and healthstatus of children involved. It was reported that 54% of the children in the sub study experienced ahigh frequency of colds and chest illness since birth.To conclude, epidemiological studies show interesting results on domestic coal burningand urban areas source impacts. Such work still needs to be linked to target aerosol species (suchas organic particles, PAH, etc.). Also parallel long-term atmospheric and epidemiological surveyshould be organized to produce dose response functions typical to South Africa. Finally, integratedstudies from processes (biological impacts) to epidemiological studies can provide a betterunderstanding of links between pollution and health.2.4 NORTHERN AFRICA2.4.1 The Greater Cairo Area; City characteristics, geography, population, meteorologyEgypt is located in Northern Africa, bordering the Mediterranean Sea, between Libya andthe Gaza Strip, and the Red Sea north of Sudan, and includes the Asian Sinai Peninsula. It has apopulation of 73.5 million with approximately 43% of the population living in urban areas [WMO,2008]. In 2009 it was estimated that Egypt’s population increased at a rate of 1.64 % per year andurban population increased at an annual rate of 1.8% (http://world.bymap.org/49

CHAPTER 2 - AFRICAPopulationGrowthRates.html). According to WHO [2006], the life expectance at birth in 2004 was68 yr (66 yr for men and 70 yr for women). The percentage of population older than 60 years oldincreased from 6.4% in 1994 to 7.1% in 2004 [WHO, 2006]. Thus, in 2009 the life expectance was72.12 yr for the whole population (69.56 yr for males and 74.81 yr for females) [CIA, 2009].Cairo (Al-Qāhirah), the capital of Egypt, is the largest city in Egypt, followed by Alexandria. TheGreater Cairo Area (GCA) consists of 16 agglomeration with a population of combined populationof 15.2 million (including the close-by Cairo cities of Giza (Al-Jizah), Helwan (Hulwan) and Shubraal-Khaymah over a total surface of 8815 km 2 [Brinkhoff, 2009]. Cairo is a rapidly expanding city,which has led to many environmental problems. The Greater Cairo Area is situated south of thedelta in the Nile basin. The main populated area is ~200 km 2 , an area 4 km wide and stretching 50km along the banks of the Nile River (Figure 16). Climatologically, GCA is in the subtropical region.Dust and sand storms frequently occur in spring and autumn and hot desert cyclones known as the“Khamasin” depressions pass over the desert during spring [Zakey and Omran, 1997]. Thesecyclones are always associated with strong hot and dry winds often carrying dust and sand thatincrease PM levels. During winter the general climate is cold, humid and rainy; while during thesummer season the predominant weather is hot and dry [Zakey et al., 2008].Figure 16 - Map of the Greater Cairo area with significant land features- grey from light to dark: urban, industrial andcommercial areas respectively. Cairo Air Improvement Project (CAIP) monitoring site locations are also shown[Abu-Allaban et al., 2002]2.4.2 Emission sources of air pollutantsIn Egypt the main industrial sectors consist of cement industry, metal smelters, brickfactories, fertilisers, aluminium, petrochemical, chemical, sugar factories, and textiles(http://www.eeaa.gov.eg/eimp/typicalsourcesof%20pollution. html). About 52% of the industriesand about 40% of the electricity production in Egypt are located in the GCA [Nasralla, 2001]. Cairo50

CHAPTER 2 - AFRICAalso has many unregistered lead and copper smelters that heavily pollute the city. There are over 2million cars on the streets of Cairo, 60% of which are over 10 years old and therefore lack modernemission cutting features like catalytic converters. Cairo has a very poor dispersion factor becauseof the lack of rain and its layout of tall buildings and narrow streets. This resulted in a permanenthaze over the city with particulate matter in the air reaching over three times WHO levels. Openfire burnings is a common practice in Egypt and a major contributor to air pollution in the area.Their signal is seen in the AOD seasonality derived from satellite data (Figure 17).The information regarding the amounts of pollutants released in the atmosphere of Cairois very limited [El Mowafi and Atalla, 2005]. The only available emissions inventories in the areaare those of EMEP in 50km resolution as well as emission inventories developed for globalmodelling such as, for example, EDGAR, GEIA, and ACCMIP [Vestreng et al., 2006; Olivier et al.,2001; Graedel et al., 1993; Lamarque et al. 2010]. These inventories are found to be inadequate tosupport contemporary air quality applications in a large urban agglomeration such as Cairo due totheir coarse resolution. Thus a more updated and detailed emission inventory such as the regionalinventory developed for Africa in Liousse et al., [2012] and Assamoi [PhD 2011] will greatlyimprove our understanding of air pollution levels in the area.Figure 17 - Intra-annual variation of visible aerosol optical thickness (AOT) over Greater Cairo Area (29°N-31°N, 30°E-31°E),based on data taken from MODIS-Terra (2000-2005, solid lines), MODIS-"qua (2002-2005, dashed lines) and TOMS (1980-2001, dotted lines). The AOT values are provided at λ = 500 nm and λ = 550 nm for TOMS and MODIS, respectively(Figure adopted from Hatzianastassiou et al., 2009)Some information on the sources responsible for air pollution levels is derived from sourceapportionment analysis based on simultaneous observations of several non-methanehydrocarbons (NMHC), including Benzene, toluene, ethylbenzene and xylene (BTEX), or ofaerosol components, including metals [Abu-Allaban et al., 2002; 2007; 2009]. They point to mobileemissions and industrial emissions (lead smelting and liquefied petroleum gas- LPG, consideringthat industrial processes may be fuelled by LPG) as the major source of NMHC during bothsummer and winter. Mobile evaporative emission contributions were higher during warmer periods.Mobile sources and open burning are major contributors to particulate matter levels (PM). Thelarge particles, PM10, have also important geological contribution, instead of the secondaryspecies that are contained in the smaller particles (PM2.5).2.4.3 Air pollutantsOzone and its precursorsAs a consequence of the high pollutant emissions and the meteorological conditions thataffect GCA, volatile aromatic hydrocarbon levels are higher than many other similar cities [Khoder,2007]. Air quality measurements in Cairo have also been recording dangerous levels of lead (Pb),sulphur dioxide (SO 2 ) and suspended particulate matter concentrations due to decades ofunregulated vehicle emissions, urban industrial operations, and chaff and trash burning [Khoder,2002]. Ozone in the southwestern Cairo area has been observed to exhibit a seasonal and diurnal51

CHAPTER 2 - AFRICAcycle with levels reaching 140 µg.m -3 in summer 2001 (Egyptian Environmental Affairs Agency,Environmental Information monitoring programme; http://www.eeaa.gov.eg/ eimp/news8.html).Khoder [2009] reported a year (Dec 2004-Nov 2005) of observations of ground level O 3 , nitrogendioxide (NO 2 ) and nitric oxide (NO) concentrations at Giza in the GCA. The mean values of O 3were about 44, 65, 91 and 58 ppb in daytime during the winter, spring, summer and autumnseasons, respectively. The diurnal cycles of O 3 concentrations during the four seasons revealed auni-modal peak in the mid-day time, with highest O 3 levels in summer due to the localphotochemical production. The diurnal variations in NO and NO 2 concentrations during the winterand summer showed two daily peaks linked to traffic density. The highest levels of NO X were foundin winter. Year-around, the observed mean daytime O 3 concentrations exceeded by about 35%(winter) to 100% (summer) of the days the Egyptian and European Union air quality standards of60 ppb for daytime (8-h) O 3 concentrations.Vrekoussis et al. [2009], based on SCIAMACHY satellite-sensor observations gridded into0.125x0.125 o girds over the GCA, deduced mean tropospheric NO 2 columns over the period 2003-2007 higher than 6 x 10 15 molecules cm -2 . They also derived an increasing trend that correspondsto 0.2-1.0 ppbv y -1 for this 4 years period.Abu-Allaban et al. [2009] also reported very high NMHC, including BTEX, in the GCAvarying from 365 ± 102 to 1849 ±298 ppb C in later winter and 462±315 to 2037±1369 ppb C inlate fall 1999. In summer 2004, observations of NMHC by Khoder [2007] at three locations, twourban areas in GCA and background one in the rural area in Menofiya province point to road trafficas the major source of aromatic NMHC. The mean concentrations of n-hexane, n-heptane,benzene, toluene, ethylbenzene, (m, p)-xylene, o-xylene, 1,3,5-trimethylbenzene and 1,2,4-trimethylbenzene were about 124, 71, 87, 214, 43, 141, 74, 31 and 65 µg m -3 , respectively in citycentre of Cairo where the total average concentration of NMHC was about 2 times higher thanthose found in other urban sites, and 22 times than those found in background sites. These levelswere among the highest reported for megacity regions [Khoder, 2007].Particulate matterAbu-Allaban et al. [2002; 2007] reported pollutant observations at 6 sites in the greaterCairo area from 1999 to 2002, showing average PM 10 (PM 2.5 ) mass ranged from 265 µg m -3 (216µg m -3 ) at an industrial site to 88 µg m -3 (30 µg m -3 ) at a residential location. High levels of tracemetals were also observed, with an average PM2.5 Pb level of 26.8 µg m -3 . Based on weeklyobservations from Jan 2003 to May 2006, Favez et al. [2008a] reported bulk aerosol seasonalmean levels of 115, 165, 215 and 190 µg m -3 during summer, autumn, winter and springrespectively at two urban sites in Cairo.Khoder [2002] measured sulphate (SO 4 = ) and nitrate (NO 3 - ) aerosol components and theirprecursor gases SO 2 , NΟ 2 , nitric acid (HNΟ 3 ) and O 3 during winter 1999-2000 and summer 2000.The average concentrations were 6.2 and 9.8 µg.m -3 for particulate nitrate, 1.1 and 6.7 µg.m -3 forgaseous nitric acid and 15.3 µg.m -3 and 25.1 µg.m -3 for particulate sulphate, during the winter andthe summer seasons, respectively. The highest average concentration ratio of gaseous nitric acidto total nitrate was found during the summer season. Particulate sulphate and nitrate and gaseousnitric acid concentrations were relatively higher in the daytime than in the nighttime.Favez et al. [2008a,b] reported more than 2 years of weekly observations of bulk aerosolsand their chemical characterization with respect to selected ionic species and carbonaceousaerosols (sum of elemental carbon (EC) and organic carbon (OC)) at two Cairo urban sites. Dustaerosols have been derived from calcium (Ca 2+ ) measurements and displayed high backgroundconcentration levels (50 µg m -3 ) all year long and maximum concentrations during the dust stormperiods [Favez et al., 2008a]. About 40% of Ca 2+ on these dust aerosols was found to beassociated with ions of anthropogenic origin like SO = 4 , NO - 3 and/or Cl - , pointing out human drivenprocesses that alter the chemical characteristics of dust and thus its climatic impact on a regionalscale. High concentration levels of non-sea-salt chloride (up to 15 µg m -3 on a monthly basis), likelyof industrial origin, were observed in autumn and winter.52

CHAPTER 2 - AFRICADuring autumn, biomass burning aerosols originating from rice straw burning in the NileDelta, known as the ‘‘Black Cloud’’ event, have shown to account for 12%, 35% and 50% of CairoEC, water insoluble organic carbon (WIOC) and water soluble organic carbon (WSOC) massconcentrations, respectively. Overall, non-dust aerosols were equally distributed betweencarbonaceous aerosols and ions, and their concentrations were of the order of 100 µg m -3 inautumn and winter, and of 60 µg m -3 in spring and summer. Remarkably, relatively low WSOC/OCratios (about 1/3) were obtained all the year-long [Favez et al., 2008a]. Favez et al. [2008b] furtherinvestigated the carbonaceous content in the sub micron fraction of aerosols by at an urban site inCairo in spring 2005. They found well-marked diurnal patterns for the WSOC/EC and WIOC/ECratios, with minima during the traffic-influenced morning period and maxima during the intensephotochemical period, suggesting significant formation of both water-soluble and water insolublesecondary organic aerosols during the afternoon. Applying the EC-tracer method, freshly formedsecondary organic carbon was found to possibly account for more than 50% of OC concentrationsmeasured during the early afternoon period, and this fresh SOC was calculated to be mainly(~60%) composed of water-insoluble species. The latter (unexpected) result has been suggestedto be due to low ambient relative humidity as well as to the importance of anthropogenic volatileorganic compounds in Cairo [Favez et al., 2008b].RegulationsIn 1995, the first environmental acts were introduced and the situation has seen someimprovement with 36 air monitoring stations and emissions tests on cars. Twenty thousand buseshave also been commissioned to the city to improve congestion levels, which are very high. In2003, Egypt initiated an enforced vehicle emission-testing programme in Greater Cairo. The limitsof CO, hydrocarbons and opacity for the vehicles before and after 1995 have the values of (7, 4.5percent) (1000, 900 ppm) and (65, 50 percent), respectively. The publicized information indicatedan overall failure rate of about 10 percent [El Mowafi and Atalla, 2005].2.4.4 HealthLead smelters have been found to be major sources of lead in Cairo’s ambient atmosphere[Abu-Allaban et al., 2007]. Melting down of old circuit boards and other electronic components fortheir metal content has been shown to expose communities to extremely high levels of dioxins andmetals such as lead, cadmium and mercury [Carroll and Essik, 2008]. About 40% of the totalpopulation in Egypt is below 25 years old while only 3% exceeds the age of 65. In 2006 the birthrate was significantly higher than the death rate with 25.3 ‰ births compared to 6.2‰ deaths.As reported by El Mowafi and Atalla [2005] health risks studies due to air pollution in Cairoconducted by Smith [1999] indicated that approximately 3% of the population is chronicallyexposed to PM 10 levels above 100µg/m 3 , compared to 48 % exposed to 50-100 µg/m 3 and 49 %exposed to 5-50 µg/m 3 PM 10 . Thus, it was suggested that Cairo air pollution causes about 3,400premature deaths, 28 million restricted activity days and other additional cases of air pollutionrelateddiseases, e.g. asthma attacks and chronic bronchitis. Based on ambient atmosphericconcentrations of criteria pollutants, notably total suspended particles (TSP; 593 µg.m -3 ), SO 2 (37µg.m -3 ), and nitrogen dioxide (NO 2 ; 59 µg.m -3 ), Gurjar et al. [2008] have classified Cairo asextremely poor air quality megacity where measures for air pollution reduction need to be takenurgently. It is estimated that 10,000 to 25,000 people a year in Cairo die due to air pollution-relateddiseases. The World Bank [2002] evaluated that environmental degradation in Egypt at 0.7-2.3 ofGDP per year, accounting that air pollution causes about 20,000 premature deaths every year, inthe two metropolitan areas and 450,000 disability adjusted life year with about 92 % of them beingin the Greater Cairo because of the higher air pollution and larger population. These findingsindicate the significant benefits that could be achieved by implementing the proper abatementmeasures to improve air quality in Cairo.2.5 GENERAL CONCLUSIONSThis chapter strongly stresses the need to seriously considering air pollution andassociated health risks in African megacities as a subject of its own. Air pollution levels are53

CHAPTER 2 - AFRICAcomparable to those encountered in the most polluted cities of the world. Due to anthropogenicpressure and lack of present regulations, pollution and associated risks are expected to increasemore and more in the absence of any mitigation plan. These are not only national problems, butinternational problems due first to pollutant transport but also to technological trades (e.g. China toAfrica for two wheel vehicles, Africa to China for coal liquefaction process).The actions to be taken are complex and multiple because Africa has a wide representationof development levels. Africa has to fight against problems of both developed, semi-developed anddeveloping countries, e.g. food and energy development, political instability, high pollutingtechnologies related to industries and domestic fuel burning conversion, growing traffic reduction,health diseases, etc. Indeed, in most places, importance of health diseases due to air pollution isnow competitive to ones due to infectious diseases. This is very critical due to expectedinteractions between both diseases and public health deterioration.Moreover, air pollution and health problems have a significant cost on national economicslinked to hospital costs but also to absenteeism, job losses, and deaths. All of the proposed planswill need to be tested from an economical point of view as well as from the consequence ofmorbidity/mortality effects.These actions can also have an important impact on climate change due toreduction/increase of greenhouse gases and aerosol emissions, not only due to pollutantconcentrations but also due to quality with relative composition of atmospheric pollution mixtures.In conclusion, it is time to act, and the actions for research studies have to focus onintegrated projects combining emissions, air quality, health studies (epidemiological monitoring,toxicology, hospitalizations), acid deposition and impacts on soil, crop and water resources, localand regional climate change and cost-benefit studies to provide possible emission mitigationsoption that include air quality and climate change feedback impacts. A required condition forsuccessful action could be found if a strong link between these research programmes isconstructed regionally with educational systems and policy makers.ReferencesAir Quality Guidelines. (2000). Geneva: World Health Organization.Arab Republic of Egypt-cost assessment of environmental degradation. (2002): World Bank.Atlas of Health in Europe (2008). World Health Organization, Geneva.Abu-Allaban, M., Gertler, A. W., & Lowenthal, D. H. (2002). A preliminary apportionment of thesources of ambient PM10, PM2.5, and VOCs in Cairo. Atmospheric Environment, 36(35),5549-5557. doi: 10.1016/S1352-2310(02)00662-3Abu-Allaban, M., Lowenthal, D. H., Gertler, A. W., & Labib, M. (2007). Sources of PM10 and PM2.5in Cairo’s ambient air. Environ. Monit. Assess., 133(1-3), 417-425. doi: 10.1007/s10661-006-9596-8Abu-Allaban, M., Lowenthal, D. H., Gertler, A. W., & Labib, M. (2009). Sources of volatile organiccompounds in Cairo’s ambient air Environ. Monit. Assess., 157(1-4), 179-189. doi:10.1007/s10661-008-0526-9Adejumo, J. A., Obioh, J. B., Ogunsola, O. J., Akeredolu, F. A., Olaniyi, H. B., Asubiojo, O. I.,Oluwole, A.F., Akanle, O.A., and Spyrou, N. M. (1994). The atmospheric deposition of major,minor and trace elements within and around three cement factories. Journal ofRadioanalytical and Nuclear Chemistry, 179(2), 195-204. doi: 10.1007/BF02040153Annegarn, H. J., & Grant, M. R. (1999). Direct Source Apportionment of Particulate Pollution withina Township. Pretoria: Department of Minerals and Energy, Low Smoke Coal Programme.Annegarn, H. J., & Sithole, J. S. (1998). Soweto Air Monitoring – SAM Trend Analysis ofParticulate Pollution 1992 – 1997 and Recommendations for Future Air Quality Monitoring.54

CHAPTER 2 - AFRICAArku, R. E., Vallarino, J., Dioniso, K. L., Willis, R., Choi, H., Wilson, J. G., Hemphill, C., Agyei-Mensah, S., Spengler, J.D., and Ezzati, M. (2008). Characterizing air pollution in two lowincome neighborhoods in Accra, Ghana. Sci Total Environ., 402(2-3), 217-231. doi:10.1016/j.scitotenv.2008.04.042Assamoi, E., & Liousse, C. (2010). A new inventory for two-wheel vehicle emissions in West Africafor 2002. Atmospheric Environment, 44(32), 3985-3996. doi:10.1016/j.atmosenv.2010.06.048Barnes B., A. Mathee, E. Thomas and N. Bruce, Household energy, indoor air pollution and childrespiratory health in South Africa, Journal of Energy in South Africa, 20, 4-13, 2009.Baumbach, G., Vogt, U., Hein, K. R. G., Oluwole, A. F., Ogunsola, O. J., Olaniyi, H. B., &Akeredolu, F. A. (1995). Air-pollution in a large tropical city with a high traffic density- resultsof measurements in Lagos, Nigeria. Sci Total Environ., 169(1-3), 25-31. doi: 10.1016/0048-9697(95)04629-FBawakyillenuo, S. (2012). Lpg supply at the cross-roads in Ghana: a missed opportunity for healthand environmental improvements. Paper presented at the Planet Under Pressure, London.Boman, J., Linden, J., Thorsson, S., Holmer, B., & Ellasson, I. (2009). A tentative study of urbanand suburban fine particles (PM2.5) collected in Ouagadougou, Burkina Faso. X-RaySpectrometry, 38(4), 354-362. doi: 10.1002/xrs.1173Brinkhoff, T. (2009). The Principal Agglomerations of the World, from http://www.citypopulation.deBurger, L. W. (1994). Analysis of Meteorological and Airborne Pollutant Data Collected in the VaalTriangle for the Period 1990 to 1993 (D. o. N. H. a. P. Development, Trans.).Carroll, C., & Essik, P. (2008). High-tech trash. National Geographic, 213, 64-81Dieme, D., Cabral-Ndior, M., Garçon, G., Verdin, A., Billet, S., Cazier, F., Courcot, D., Diouf, A.,and Shirali, P. (2012). Relationship between physicochemical characterization and toxicity offine particulate matter (PM2.5) collected in Dakar city (Senegal). Environ. Research, 113, 1-13. doi: 10.1016/j.envres.2011.11.009Doumbia, E. H. T., Liousse, C., Galy-Lacaux, C., Ndiaye, S. A., Diop, B., Ouafo, M., Yoboue, V.Gardrat, E., and Sigha, L. (2012). Real time Black Carbon measurements in West andCentral Africa urban sites. Atmospheric Environment. doi: 10.1016/j.atmosenv.2012.02.005Eliasson, I., Jonsson, P., & Holmer, B. (2009). Diurnal and intra-urban particle concentrations inrelation to windspeed and stability during the dry season in three African cities. Environ.Monit. Assess., 154(1-4), 309-324. doi: 10.1007/s10661-008-0399-yEngelbrecht, J. P. (1998). Aerosol Monitoring and Source Apportionment in Qalabotjha, Free State,South Africa (D. o. M. a. Energy, Trans.) (Vol. 1-2).Engelbrecht, J. P., Reddy, V., Swanepoel, L., & Mostert, J. (1998). Aerosol Monitoring and SourceApportionment in the Vaal Triangle (pp. 116).Engelbrecht, J. P., Swanepoel, L., Chow, J. C., Watson, J. G., & Egami, R. T. (2002). Thecomparison of source contributions from residential coal and low-smoke fuels, using CMBmodelling, in South Africa. Environment Science & Policy, 5(2), 157-167. doi:10.1016/S1462-9011(02)00029-1Engelbrecht, J. P., Swanepoel, L., Zunckel, M., Chow, J. C., Watson, J. G., & Egami, R. T. (2000).Modelling PM10 aerosol data from the Qalabotjha low-smoke fuels macro-scale experimentin South Africa. Ecological Modelling, 127(2-3), 235-244. doi: 10.1016/S0304-3800(99)00212-4Ezeh, A. C., Izugbara, C. O., Kabiru, C. W., Fohn, S., Kahn, K., Manderson, L., Undieh, A.S.,Omigbodun A., and Thorogood, M. (2010). Building capacity for public and population healthresearch in Africa: the consortium for advanced research training in Africa (CARTA) model.Global Health Action, 3(5), 5693. doi: 10.3402/gha.v3i0.5693Favez, O., Cachier, H., Sciare, J., Alfaro, S., El-Araby, T. M., Harhash, M. A., & Abdelwahab, M. M.(2008a). Seasonality of major aerosol species and their transformations in Cairo megacity.Atmospheric Environment, 42(7), 1503-1516. doi: 10.1016/j.atmosenv.2007.10.08155

CHAPTER 2 - AFRICAFavez, O., Sciare, J., Cachier, H., Alfaro, S. C., & Abdelwahab, M. M. (2008b). Significantformation of water-insoluble secondary organic aerosols in semi-arid urban environment.Geophys. Res. Lett., 35(L15801), 5. doi: 10.1029/2008GL034446Graedel, T. F., Bates, T. S., Bouwman, A. F., Cunnold, D., Dignon, J., Fung, I., Jacob, D.J., Lamb,B.K., Logan, J.A., Marland, G., Middleton, P., Pacyna, J.M., Placet, M., and Veldt, C. (1993).A compilation of inventories of emissions to the atmosphere. Global Biogeochemical Cycles,7(1), 1-26. doi: 10.1029/92GB02793Guerreiro, C., Laupsa, H., & Sivertsen, B. (2006). Ambient Air Pollution Screening Study Dakar2005.Guillaume, B., Liousse, C., Rosset, R., Cachier, H., Velthoven, P. V., Bessagnet, B., & Poisson, N.(2007). ORISAM-TM4 : a new global sectional multi-component aerosol model includingSOA formation - Focus on carbonaceous BC and OC aerosols. Tellus B, 59(2), 283-302. doi:10.1111/j.1600-0889.2006.00246.xGurjar, B. R., Butler, T. M., Lawrence, M. G., & Lelieveld, J. (2008). Evaluation of emissions and airquality in megacities. Atmospheric Environment, 42(7), 1593-1606. doi:10.1016/j.atmosenv.2007.10.048Happo, M. S., Hirvonen, M. R., Hälinen, A. I., Jalava, P. I., Pennanen, A. S., Sillanpää, M., Hillamo,R., and Salonen, R. O. (2008). Chemical compositions responsible for inflammation andtissue damage in the mouse lung by coarse and fine particulate samples from contrasting airpollution in Europe. Inhalation Toxicology, 20(14), 1215-1231. doi:10.1080/08958370802147282Hatzianastassiou, N., Gkikas, A., Mihalopoulos, N., Torres, O., & Katsoulis, B. D. (2009). Naturalversus anthropogenic aerosols in the eastern Mediterranean basin derived from multiyearTOMS and MODIS satellite data. J. Geophys. Res., 114(D24202), 14. doi:10.1029/2009JD011982Huang, S. L., Hsu, M. K., & Chan, C. C. (2003). Effects of submicrometer particle compositions oncytokine production and lipid peroxidation of human bronchial epithelial cells. Environ. HealthPerspect., 111(4), 478-482. doi: 10.1289/ehp.5519Josipovic, M., Annegarn, H. J., Kneen, M. A., Pienaar, J. J., & Piketh, S. J. (2010). Concentrations,distributions and critical level exceedance assessment of SO2, NO2 and O3 in South Africa.Environ. Monit. Assess., 171(1-4), 181-196. doi: 10.1007/s10661-009-1270-5Khoder, M. I. (2002). Atmospheric conversion of sulfur dioxide to particulate sulfate and nitrogendioxide to particulate nitrate and gaseous nitric acid in an urban area. Chemosphere, 49(6),675-684. doi: 10.1016/S0045-6535(02)00391-0Khoder, M. I. (2007). Ambient levels of volatile organic compounds in the atmosphere of GreaterCairo. Atmospheric Environment, 41(3), 554-566. doi: 10.1016/j.atmosenv.2006.08.051Khoder, M. I. (2009). Diurnal, seasonal and weekdays-weekends variations of ground level ozoneconcentrations in an urban area in greater Cairo. Environ. Monit. Assess., 149(1-4), 349-362.doi: 10.1007/s10661-008-0208-7Kouassi, K. S., Billet, S., Garçon, G., Verdin, A., Diouf, A., Cazier, F., Djaman, J., Coutcot, D., andShirali, P. (2010). Oxidative damage induced in A549 cells by physically and chemicallycharacterized air particulate matter (PM2.5) collected in Abidjan, Côte d'Ivoire. J. Appl.Toxicol., 30(4), 310-320. doi: 10.1002/jat.1496Lamarque, J.-F., Bond, T.C., Eyring, V., Granier, C., Heil, A., Klimont, z., Lee, D., Liousse, C.,Mieville, A., Owen, B., Schultz, M.G., Shindell, D., Smith, S.J, Stehfest, E., Van Aardenne,J., Cooper, O.R., Kainuma, M., Mahowald, N., McConnell, J.R., Naik, V., Riahi, K., and vanVuuren, D.P. (2010). Historical (1850–2000) gridded anthropogenic and biomass burningemissions of reactive gases and aerosols: methodology and application. Atmos. Chem.Phys., 10(15), 7017-7039. doi: 10.5194/acp-10-7017-2010Linden, J., Boman, J., Holmer, B., Thorsson, S., & Eliasson, I. (2012). Intra-urban air pollution in arapidly growing Sahelian city. Environ. Int., 40, 51-62. doi: 10.1016/j.envint.2011.11.005Liousse, C., Assamoi, E., Criqui, P., Guillaume, B., & Rosset, R. (2012). African anthropogenicemissions: an unexpected relative importance in 2030. Journal Article.56

CHAPTER 2 - AFRICALiousse, C., & Galy-Lacaux, C. (2010). Urban pollution in West Africa: IGBP Newsletter.Liousse C., B. Guillaume, J.M. Grégoire, M. Mallet, C. Galy, V. Pont, A. Akpo, M. Bedou, P.Castéra, L. Dungall, E. Gardrat, C. Granier, A. Konaré, F. Malavelle, A. Mariscal, A. Mieville,R. Rosset, D. Serça, F. Solmon, F. Tummon, E. Assamoi, V. Yoboué, and P. Van Velthoven,(2010). Updated African biomass burning emission inventories in the framework of theAMMA-IDAF programme, with an evaluation of combustion aerosols. Atmos. Chem. Phys.,10(19), 9631-9646. doi: 10.5194/acp-10-9631-2010Lourens A.S.M., T.M. Butler, J.P. Beukes, P.G. van Zyl, S. Beirle, T. Wagner, K-P. Heue, J.J.Pienaar, G.D. Fourie, M.G. Lawrence. (2012). Re-evaluating the NO2 hotspot over the SouthAfrican Highveld. South African Journal of Science.Mitschik, S., Schierl, R., Nowak, D., & Jörres, R. A. (2008). Effects of particulate matter on cytokineproduction in vitro: a comparative analysis of published studies. Inhalation Toxicology, 20(4),399-414. doi: 10.1080/08958370801903784Mowafi, S. A. E., & Atalla, A. G. (2005). Strategies for controlling mobile emissions in Cairo.Management of Environmental Quality: An International Journal, 16(5), 548-559. doi:10.1108/14777830510614385Norman R., B. Barnes, A. Mathee, D. Bradshaw and the South African Comparative RiskAssessment Collaborating Group, Estimating the burden of disease attributable to indoor airpollution from household use of solid fuels in South Africa in 2000, SAMJ, 97, 764-771,2007a.Norman R., E. Cairncross, J. Witi, D. Bradshaw and the South African Comparative RiskAssessment Collaborating Group, Estimating the burden of disease attributable to urbanoutdoor air pollution in South Africa in 2000, SAMJ, 97, 782-790, 2007b.Nasralla, M. M. (2001). Greater Cairo Air Quality Profile. Cairo: Egyptian Environmental AffairAgency.Nieron, P. G. V. (1995). A Source Inventory of Particulate Air Pollution in the Vaal Triangle.University of the Wiwatersrand, Johannesburg.Ogunsola, O. J., Oluwole, A. F., Asubiojo, O. I., Durosinmi, M. A., Fatusi, A. O., & Ruck, W. (1994).Environmental impact of vehicular traffic in Nigeria: health aspects. Sci Total Environ., 146-147, 111-116. doi: 10.1016/0048-9697(94)90226-7Olivier, J. G. J., Berdowski, J. J. M., Peters, J. A. H. W., Bakker, J., Visschedijk, A. J. H., & Bloos,J.-P. J. (2001). Applications of EDGAR. Including a description of EDGAR 3.0: referencedatabase with trend data for 1970-1995 (pp. 142).Oosthuizen, M. A., Jinabhai, C. C., Terblanche, A. P., & Becker, P. J. (2008). A transition in healthstatus from childhood to adulthood and associated lifestyle risk factors: a 13-year follow-upstudy in South Africa. Int. J. Environ. Health Res., 18(1), 65-72.Oyedele, D. J., Obioh, I. B., Adejumo, J. A., Oluwole, A. F., Aina, P. O., & Asubiojo, O. I. (1995).Lead contamination of soils and vegetation in the vicinity of a lead smelter in Nigeria. SciTotal Environ., 172(2), 189-195. doi: 10.1016/0048-9697(95)04810-3Piketh, S. J., Annegarn, H. J., & Kneen, M. A. (1996). Regional scale impacts of biomass burningemissions over southern Africa. In J. S. Levine (Ed.), Biomass Burning and Global Change(pp. 320-326). Cambridge: MIT Press.Ramgolam, K., Favez, O., Cachier, H., Gaudichet, A., Marano, F., Martinon, L., & Baeza-Squiban,A. (2009). Size-partitioning of an urban aerosol to identify particle determinants involved inthe proinflammatory response induced in airway epithelial cells. Part Fibre Toxicol., 6(10),12. doi: 10.1186/1743-8977-6-10Scorgie, Y., Annegarn, H., & Burger, L. (2004). Definition of Air Pollutants associated withCombustion Processes. In FRIDGE (Ed.).Scorgie, Y., Annegarn, H. J., & Randell, L. (2003a). Air Quality Situation Assessment for the City ofJohannesburg, Final Report.Scorgie, Y., Kneen, M. A., Annegarn, H. J., & Burger, L. W. (2003b). Air pollution in the Vaaltriangle - quantifying source contributions and identified cost-effective solutions. Clean AirJournal, 13(2), 5-18.57

CHAPTER 2 - AFRICASeagrave, J., McDonald, J. D., Bedrick, E., Edgerton, E. S., Gigliotti, A. P., Jansen, J. J., Ke, L.,Naeher, L.P, Seilkp, S.K., Zheng, M., and Mauderly, J. L. (2006). Lung toxicity of ambientparticulate matter from southeastern US sites with different contributing sources:relationships between composition and effects. Environ. Health Perspect., 114(9), 1387-1393. doi: 10.1289/ehp.9234Smith, M. A. K., Abdel-Rehiem, A. G., & Lotayef, D. (1999). Economic analysis and incentives inenvironmental policy and decision-making with respect to chronic ambient air pollution inCairo. Paper presented at the Second International Conference and Trade Fair forEnvironmental Management and Technology, Cairo.Terblanche, P. (1996). Impacts of Removing Air Pollution: Health Aspects: Department of Mineralsand Energy.Terblanche, P. (1998). Vaal Triangle Air Pollution Health Study: Summary of Key Findings,Recommendations and Bibliography (pp. 20).Terblanche, P., Danford, I. R., & Pols, A. S. (1995b). Comparative evaluation of human exposuresto air pollution from low-smoke and conventional household coal usage. Journal of Energy inSouthern Africa, 131-136.Terblanche, P., Nel, C. M. E., & Tosen, G. R. (1995a). Respiratory health impacts of threeelectrification scenarios in South Africa. Journal of Energy in Southern Africa, 6(2), 93-96.Terblanche, P., Nel, M. E., Opperman, L., & Nyikos, H. (1993). Exposure to air pollution fromtransitional household fuels in a south African population. J. Expo. Anal. Environ. Epidemiol.,3(Suppl 1), 15-22.Terblanche, P., Nel, R., Reinach, G., & Opperman, L. (1992). Personal exposures to totalsuspended particulates from domestic coal burning in south Africa. NACA Clean Air Journal,8(6), 15-17.The World Factbook. (2009). from https://www.cia.gov/library/publications/the-worldfactbook/fields/2102.html?countryName=&countryCode=&regionCode=rThe World Health Report 2006. (2006). World Health Organization.Tyson, P., Odada, E., Schulze, R., & Vogel, C. (2002). Regional-global change linkages : southernAfrica. In P. Tyson (Ed.), Global-Regional Linkages in the Earth System (pp. 3-73). NewYork: Springer.Val, S., Liousse, C., Doumbia, T., Baeza-Squiban, A., Galy-Lacaux, C., Cachier, H., & Marchand,N. (2012). Inflammatory and adaptative responses of human bronchial epithelial cells due toaerosol urban pollution in Bamako and Dakar in Africa. Journal Article. Environ. HealthPerspect.Vestreng, V., Rigler, E., Adams, M., Kindbom, K., Pacyna, J. M., Gon, H. D. r. v. d., . . . Travnikov,O. (2006). Inventory Review 2006; Emission Data reported to LRTAP Convention and NECDirective, Initial review of HMs and POPs Convention on Long-range Transboundary AirPollution: EMEP.Vrekoussis M., E. Gerasopoulos, N. Mihalopoulos, U. Im, A. Richer, A. Hilboll, M. Petrakis, M.Kanakidou, S. Myriokefalitakis, O. Yenigun, T. Kindap, A. Ladstätter-Weißenmayer, A.F.A.Youssef , E.A Morsy, J.P Burrows, C. Zerefos (2009, 24-27 March). Spatial and temporalvariability of NO2 mixing ratios inferred from satellite and ground-based observations aboveSE Europe: Role of Megacities. Paper presented at the 7th International Conference on AirQuality - Science and Application, Istanbul.Yoboué, V., Galy-Lacaux, C., Liousse, C., Marcellin, A., Gardrat, E., & Castera, P. (2012).Measurement of NO2, NH3, SO2, HNO3 and O3 concentrations in West African urban sites.Journal Article. Atmos. Environ.Zakey, A. S., Abdel-Wahab, M. M., Pettersson, J. B. C., Gatari, M. J., & Hallquist, M. (2008).Seasonal and spatial variation of atmospheric particulate matter in a developing megacity,the Greater Cairo, Egypt. Atmósfera, 21(2), 171-189.Zakey, A. S., & Omran, M. A. (1997). 1st LAS/WMO International Symposium on Sand and DustStorms WMO Programme on Weather Prediction Research: World MeteorologicalOrganization (WMO).58

CHAPTER 3 - ASIACoordinating Author: Tong Zhu (1)Contributing Authors: Mylene G. Cayetano (2) , Changhong Chen (3) , Sarath Guttikunda (4) , Min Hu (1) , Young J. Kim (2) ,Yataka Kondo (5) , Peter K.K. Louie (1) , Luisa Molina (6) , Yu Morino (7) , Nguyen Thi Kim Oanh (8) , Eduardo P. Olaguer (9) ,Didin Agustian Permadi (8) , Prapat Pongkiatkul (8) , Abdus Salam (10) , Min Shao (1) , Xuesong Sun (1) ,Shinji Wakamatsu (11) , Hongli Wang (3) and Peyman Zawar-Reza (12)(1)College of Environmental Sciences and Engineering, Peking University, Beijing, China(2)School of Environmental Science and Engineering, Gwangju Institute of Science and Technology, Gwangju,Korea(3)Shanghai Academy of Environmental Sciences, Shanghai, China(4)Division of Atmospheric Sciences, Desert Research Institute, Reno, NV, USA(5)Department of Earth and Planetary Science, The University of Tokyo, Tokyo, Japan(6)Molina Center for Energy and the Environment, California and Massachusetts Institute of Technology,Massachusetts. USA(7)National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan(8)Environmental Engineering and Management, School of Environment, Resources and Development, AsianInstitute of Technology, Thailand(9)Houston Advanced Research Center, Texas, USA(10)Department of Chemistry, University of Dhaka, Dhaka - 1000, Bangladesh(11)Ehime University, Matsuyama City, Ehime Prefecture, Japan(12)Department of Geography, University of Canterbury, Christchurch, New Zealand3.1 ASIAN MEGACITIES: GENERAL CHARACTERISTICSPopulation and geographyWith more than 50% of the world population, Asia is the most intensely populated continenton the earth. Based on the World Urbanization Prospects of the United Nations (2009 Revision), in2010, 10 of the 21 world megacities and 15 of the worlds 30 largest cities are in Asia (Table 1).Table 1 - The 15 of the 30 world largest cities in Asia in 2010.Source: the World Urbanization Prospects of the United Nations (2009 Revision)RankorderCountry Megacity Population (Million)1 Japan Tokyo 36.672 India Delhi 22.164 India Mumbai (Bombay) 20.047 China Shanghai 16.588 India Kolkata (Calcutta) 15.559 Bangladesh Dhaka 14.6510 Pakistan Karachi 13.1213 China Beijing 12.3915 Philippines Manila 11.6316 Japan Osaka-Kobe 11.3422 Republic of Korea Seoul 9.7723 China Chongqing 9.4024 Indonesia Jakarta 9.2126 China Shenzhen 9.0128 China Guangzhou, Guangdong 8.8859

CHAPTER 3 - ASIAThe bottom-up and top-down methods for estimating population in Asia may have largedifferences. For example, Beijing Municipal Bureau of Statistics reports that Beijing has 15.38million long-term residents and 3.57 million temporary migrants in 2005(http://www.bjstats.gov.cn/sjfb/pcsj/rkpc/200607/t20060704_45124.htm), while the WorldUrbanization Prospects of the United Nations (the 2009 Revision) reports that Beijing has apopulation of 11.45 million in 2005 an 12.39 million in 2010 (Table 1).One of the major reasons for this large difference is that urbanization in Asia is occurring ata fast speed due to the dynamic social and economical development. Projections based on thecensus data years ago might not be able to reflect the real situation in many cities in Asia.The continent of Asia is characterized by high diversity and inhomogeneity in geography,this leads to large spatial variation in the population density in Asia. Figure 1 shows that, besidesthe hot spots of large cities with high population density, Asia also has large regions with highpopulation density, such as Bangladesh, Indo-Gange plain, and North China plain. Bangladesh isone of the most densely populated regions in the world.Figure 1 - Map of the population density in Asia (persons per km2), based on 0.25 o gridded data for 2000 from theCenter for International Earth Science Information Network (CIESIN) at Columbia University[http://sedac.ciesin.columbia.edu/gpw/]Asian megacitiesThis chapter covers 12 Asian megacities and major population centers (MPC) (Table 2)that reflect the high diversity of geography and socio-economical development of megacities in Asia.Tables 1 and 2 clearly show that there is a large difference in the population of each of these cities.Due to the inconsistence of the population data from different sources, the selection of the citiescovered in this report is not only based on population, but also based on country and geographicalrepresentation, and equally important, the availability of authors and data to report on thesemegacities.60

CHAPTER 3 - ASIATable 2 also lists the area, latitude, and longitude of each city. One has to keep in mind thatthe definition of the area of each city may vary greatly as some estimation are based onadministrative borders and others are based on the urban area.Table 2 - Twelve Asian megacities reported in this chapter. The source of information can be found in the sectionof each megacity in this chapterMegacity CountryPopulation Area (km 2 )[Million] (year) (urban area)Latitude LongitudeBangkok Thailand [10.1] (2007) 7762 13°45’ 100°35’Beijing China [16.3] (2008) 16808(735) 39°54’ 116°24’Delhi India [16] (2007) 900 28°36’ 77°13’Dhaka Bangladesh [13] 23º76´ 90º38´Hong Kong China [6.98] 1104 22º15‘ 114º10‘Jakarta Indonesia [8.7] (2005) 661 6 o 12’ S 106 o 48’Manila Philippines [11.56] (2007) 636 14 o 34’ 120 o 58’Osaka-Kansai Japan [22.7] (2008) 34.67° 135.53°Pearl River Delta China [47.9] (2009) 4170 21 ° 17´–23 ° 56´111 ° 59´–115 ° 25´Seoul Korea [23.9] (2008) 37° 33’ 126° 58’Shanghai China [19.2] (2009) 6341 30 o 40’ 31 o 53’Tokyo Japan [12.9] 35.69° 159.69°EmissionFigure 2 shows the emissions of CO, NO X , and SO 2 in Asia for the year 2000 based on theEDGARv3.2 FT2000 database, reflecting fossil fuel based energy consumption. The bottom-up andtop-down methods may also have large differences in emission data, especially in Asia where theemission inventories are constantly changing due to dynamic economic development. However, thelarge spatial variations of CO, NO X , and SO 2 emissions are clearly associated with the high diversityand inhomogeneity of the population density.Asia is also highly diversified and inhomogeneous in its economical development stages.Tokyo and Osaka-Kobe are well-developed megacities, while the rest of megacities in Asian are stillin the developing stage. This is an important factor when determining how pollution is generatedand controlled in the megacities.In the well-developed megacities, such as Tokyo, the sources of air pollutants andgreenhouse gases (GHGs) are dominated by the vehicle emissions, whereas in the developingmegacities, biomasses burning from agriculture waste and forest fires are also important sources tolocal air pollution.One unique source of air pollution to the East Asian megacities is dust and sand storm (DSS)that originate in the Mongolia desert and Gobi area every spring. The air quality in megacities likeBeijing, Seoul, and Tokyo is frequently deteriorated due to DSS.61

CHAPTER 3 - ASIAFigure 2 - (a) CO emissions for the year 2000 based on the EDGARv3.2 FT2000 database. (b) NOX emissions for theyear 2000 based on the EDGARv3.2 FT2000 database. (c) SO2 emissions for the year 2000based on the EDGARv3.2 FT2000 database62

CHAPTER 3 - ASIAAir pollution levelsAir pollution is a serious environmental problem in Asian megacities. Concentrations of airpollutants, especially particulate matter, are frequently higher than those of the WHO guidelines andthe ambient air quality standards of their own countries.Megacities in Asia have taken various measures to control air pollution; some measuresimplemented in developing megacities are equally strict as those in the developed ones. Forexample, in 2008, Beijing implemented vehicular emission standards on new cars equivalent toEURO-IV. Introducing lead-free gasoline in many developing megacities proved to be effective inreducing lead concentrations in particulate matter. Clean energy and advanced publictransportation systems have also played important roles in improving the air quality in Asianmegacities.Monitoring network data show that air pollution in Asian megacities remains a serious risk tohuman health and ecosystems. This indicates that all the air pollution mitigation efforts put forwardby megacities to date still have not gone far enough. With the fast social and economicaldevelopment and urbanization in Asia, new emission sources are being added to the old emissionsources that are currently not well controlled. How to realize the co-benefits of controlling airpollution and reducing climate change in Asian megacities requires systematic research efforts.3.2 BANGKOK, THAILANDIntroduction and specific features of the cityBangkok, the capital city of Thailand, is recognized as a megacity in South East Asia and isfacing serious air pollution problems. Bangkok and five bordering provinces including SamutPrakarn, Nonthaburi, Pathumthani, Nakorn Pathom, and Samut Sakorn are known collectively asthe Bangkok Metropolitan Region (BMR), which is an economic centre of Thailand. BMR has anarea of 7,762 km 2 and is situated in the central part of Thailand in the Chao Phraya River Basin.Bangkok city is located around 13°45’ Northern latitude and 100° 35’ longitudes in an immediateproximity to the Gulf of Thailand. BMR has a total population of about 10.1 million (as of 2007),which comprises around 16% of the total population in Thailand (63.0 million, as of 2007). In 2007,the population density in Bangkok was 3,644 persons per km 2 while the average population densityin BMR is 1,297 persons per km 2 [NSO, 2009]. Bangkok land use comprises 23.4% for residentialarea, 23.6% for agricultural area, 8.2% for road transportation, 3.9% for commercial area, 24.2%un-use land, and the rest are for other purposes [Department of City Planning, 2008].The Gross Domestic Product (GDP) of Thailand is continuously increasing. In 2008,Thailand GDP was 9,075 Billion Baht, a growth of around 6.4% from 2007, and the national incomewas 6,687 Billion Baht [BOT, 2010] (the exchange rate is around 35 Bath for 1 USD in 2007).Accordingly, the demand for electricity has increased. In 2008, a total of 148,200.93 Million kWhwas required across the country, 0.87% increase from 2007 [EGAT, 2008]. Electricity consumptionin BMR is also increasing, similar to the trends of electrical consumption in Thailand, especially inthe inner Bangkok area.BMR experiences the tropical monsoon climate with two distinct seasons. The wet seasonextends from mid-May to mid-October, when the southwest monsoon dominates and brings inwarm, moist air from the Gulf of Thailand and the Andaman Sea. The southwest monsoon and theInter Tropical Convergence Zone (ITCZ) cause heavy rainfall during the wet season. The dryseason can be further classified into two periods. The first period (mid-October to mid-February),known as the local winter, is characterized by mild weather under the influence of the northeastmonsoon that brings in cold, dry air associated with a high-pressure ridge extending from theanticyclone in China. The second period of the dry season (mid-February to mid-May) is known asthe local summer when weather is the hottest of the year, with the highest temperature occurring inApril [TMD, 2009]. Bangkok is also under the influence of a sea land breeze. The southerly seabreeze counteracts the northeasterly monsoon during the winter, which results in low windconditions over the city. This, in turn, reduces the mixing and enhances pollution build-up [Zhang63

CHAPTER 3 - ASIAand Kim Oanh, 2002]. Meteorological conditions, averaged over 1981-2007 period, show theannual average temperature of Bangkok ranges between 26.7-28.0 o C and average annual rainfallbetween 1,320-1,950 mm. Low wind, average of 1.3 m/s and mostly below 3 m/s, is observedthroughout the year [TMD, 2009]. Monthly windroses of a 10-year period, 1991 – 2000, show highpercentages of calm conditions, ranging from 30% in March to 61% in October [Zhuang, 2001].Monthly meteorological variables in Bangkok, averaged for 1971 to 2000, are presented in Figure 3.Figure 3 - Monthly observed average meteorological conditions in Bangkok, Thailand (1971-2000)[Zhang, 2001]Emission sources of air pollutantsMajor sources of air pollution in BMR include traffic, power plants, industries andincinerators. In addition, agroresidue field open burning also contributes significantly to urban airpollution but has not yet been properly quantified. Point sources (industry, power plants) are themajor source of SO 2 , whereas mobile source contributes significantly to NO X , CO, VOC/HC, andPM emission. Area sources also contribute a remarkable amount to CO emission.The average growth rate of vehicles in Bangkok, over an 18-year period starting from 1989,is around 7% per year. There were approximately six million vehicles registered in Bangkok as ofMay 2009 [Department of Land Transport, 2007]. A high growth rate of vehicles and inadequateroad infrastructures are major causes of traffic congestion in Bangkok that lead to high air pollutionemissions. In recent years, in order to improve air quality, the European standards have beenimposed for new vehicles progressively. For example, in 1998 new heavy-duty diesel vehiclesregistered in Thailand had to meet EURO1 standards. The EURO2 standard was implemented in2003 and since 2007, new heavy-duty diesel vehicles have to meet the EURO-3 standard [PCD,2009]. For over a decade, development of fuel specification has been continuously implemented inThailand. Leaded gasoline was phased out as of January 1996. Sulphur content in diesel fuel isbeing reduced, e.g. 500 ppm sulphur was enacted on July 1998; 350 ppm sulphur was enacted onJanuary 2004; and 50 ppm sulphur is currently proposed for 2010 [ESMAP, 2008]. Thailand has apolicy of encouraging use of compressed natural gas (CNG) and ethanol in transport [ESMAP,2008]. Nowadays, the CNG use is widely spread, especially in taxis and trucks.For point sources, there are two thermal power plants under EGAT operated in BMR.Fortunately one is oil-based and the other is natural gas (NG) based, which are cleaner thancoal-based power plants. Around 38,593 industries of different types and sizes are registered inBMR [DIW, 2007]. Half of them (19,082 industries) are located in Bangkok city. Most of theseindustries are of small scales and potentially more polluting. A few waste incinerators are also inoperation in BMR to treat the hygiene and hospital wastes [IPEP, 2006] and also emit air pollutants.64

CHAPTER 3 - ASIAData available on air pollutantsMonitoring of ambient air quality in Thailand was established in 1983 under the PollutionControl Department (PCD) of Thailand. The ambient air quality monitoring network consists of over50 permanent automated ambient air quality monitoring stations located throughout the country[PCD, 2006]. Ambient air pollutants measured include CO, NO X , SO 2 , O 3 , TSP, PM 10 , Pb, and HC.Most of them also have 10 or 30 meter meteorological masts. Data are generated on hourlybasis (except for TSP) and are transmitted daily to the central data processing system at the PCDthrough a dial-up telemetric communication system [Supat, 1999].Bangkok has 17 permanent automatic monitoring stations (as of 2006), whereas eachsurrounding province has only one station located at the most densely populated area. In addition, anumber of temporary monitoring stations have also been set up in the Bangkok area [PCD, 2006].The monitoring stations in Bangkok are categorized into two types, namely, general and roadsidestations. General ambient air quality monitoring stations are located within 50-100 m from mainroads, whereas roadside street-level stations are situated within 2-5 m from main road [Supat,1999a].The status and trend of the pollutionResults of ambient air quality monitoring for more than 10 years indicate that the airpollutants of greatest concern in Bangkok are suspended particulate matter, especially PM 10 , andground level ozone. Both of them usually exceed the air quality standard of Thailand: PM 10 atroadside (annual average standard: 50 µg/m 3 ) and ozone at ambient sites (one hour maximumstandard: 100 ppb). Other pollutants, such as CO, SO 2 , NO X , and lead (Pb), are generally lowerthan the standards. Table 3 summarizes the quality of the ambient air in Bangkok as of 2008.Trends of the ambient air pollution levels over the period 1995-2008 for PM 10 and other pollutantsare shown in Figure 4 and Figure 5, respectively.PM 2.5 data, available from monitoring of the AIRPET research network, show high levels ofPM 2.5 especially during the dry season with the average of 50 µg/m 3 , which is significantly higherthan the wet season level of 18 µg/m 3 [Kim Oanh et al., 2006].Table 3 - Ambient air quality in Bangkok as of 2008. (Source: PCD, 2008)Pollutant Unit Range 95-percentilesGeneral areas24-hr avg TSP24-hr avg PM101-hr avg CO8-hr avg CO1-hr avg O31-hr avg SO224-hr avg SO21-hr avg NO2Roadside areas24-hr avg TSP24-hr avg PM101-hr avg CO8-hr avg CO1-hr avg O31-hr avg SO224-hr avg SO21-hr avg NO2mg/m 3µg/m 3ppmppmppbppbppbppbmg/m 3µg/m 3ppmppmppbppbppbppb0.01-0.3312.1-180.9.0.0-6.80.0-4.40-1530-530-160-1520.03-0.868.1-205.40.0-16.40.0-10.00-1160-450-180-1770.1786.91.71.556.010.08.752.00.28113.63.53.437.012.09.370.0Standard0.331203091003001201700.33120309100300120170Times exceedingstandard /measurementtimes (%)0/541 (0)30/2,540 (1.2)0/80,728 (0)0/83,758 (0)194/77,541 (0.3)0/80,981 (0)0/3,337 (0)0/81,534 (0)25/695 (3.6)82/2,000 (4.1)0/64,716 (0)7/65,491 (0.01)10/25,988 (0.04)0/25,566 (0)0/1,089 (0)1/26,169 (0.004)Annualaverage0.0847.90.70.71744230.1461.81.41.4115534Annualstandard0.150---4040-0.150---4040-65

CHAPTER 3 - ASIAFigure 4 - Annual average PM10 concentration in Bangkok from 1995-2008 [PCD, 2008]Figure 5 - Annual average air pollutant concentrations in the general area of Bangkok from 2003-2008Relationships of the trends to regulationsThe air quality management programme in BMR follows the policy and prospective plan ofThailand. This programme covers enhancement and conservation of natural environmental quality,which is a cross-sectoral operation involving the environment, transport, and urban dimensions. Theair quality management policy of Thailand for 1997-2016 focuses on the following key issues: (1) airquality in pollution control zones and urban areas, particularly on dust, (2) other pollutants inambient air, particularly on carbon monoxide, and (3) air pollutants in industrial zones and generalcommunities, particularly on sulphur dioxide and nitrogen oxides, to be within designated AmbientAir Quality Standards [Supat, 1999].Successful stories include the phasing out of leaded gasoline, establishment of oxygenatedgasoline, reducing sulphur content in diesel, and development of the standard for low-smoke 2Tlubricating oil. Phasing out of lead in gasoline, starting in January 1996, has substantially reducedPb in ambient air (Figure 6). At present, lead concentration in ambient air is much lower than thestandard. Recently, due to the concern of toxic effects of volatile organic compounds (VOCs),VOC ambient air quality standards have been established [PCD, 2006].66

CHAPTER 3 - ASIAFigure 6 - Annual average curbside lead concentration in Bangkok from 1985-1998 [Supat, 1999]Climatic change issuesThe Intergovernmental Panel on Climate Change (IPCC) estimated that, as of 2004,Thailand contributes around 265 million tons of CO 2 per year, ranked 25 th in the world. The datashows that 56.1% of greenhouse gases (GHG) in Thailand are from energy uses (as of 2003),whereas the remaining GHG emissions are from agriculture (24.1%), wastes (7.8%), land usechange (6.65%), and industrial sector (5.4%) [TGO, 2009].Thailand signed the United Nations Framework Convention on Climate Change (UNFCCC)in June 1992 and ratified the Convention in March 1995, as a Non-Annex I country. In addition,Thailand signed the Kyoto Protocol in February 1999, and ratified it on 28 August 2002. Accordingto the agreement, a promotion of Clean Development Mechanisms (CDM) under the guideline fromthe Kyoto Protocol has been implemented in order to encourage clean and environmental friendlytechnologies for GHG reduction in the country, as well as to promote the country's capability bydeveloping sustainable business practices [TGO, 2009].In 2007, the Thailand Greenhouse Gas Management Organization (Public Organization)(TGO) under the Ministry of Natural Resources and Environment (MNRE) was established. Theorganization is responsible for implementation of GHG emission reductions, promoting low carbonactivities, investment and marketing on GHG emission reductions, establishing GHG informationcentre, reviewing CDM (Clean Development Mechanism) projects for approval, and providingcapacity development and outreach for CDM stakeholders. The organization in particular performsthe role as the Designated National Authority for CDM (DNA-CDM) office in Thailand. As of 2007,there were five CDM projects approved by the Cabinet. They are expected to reduce CO 2 emissionin Thailand by around 578,700 tons per year [TGO, 2009].Research projects on air quality in BMRSeveral governmental air quality projects have been implemented. A project onmeasurement of agro-residual open burning in Thailand has been established in order to assess thestatus of agro-residual open burning and to provide a database for implementation of abatementprogrammes. PCD also conducted a project on the comparison of PM emissions from internalcombustion diesel engine using commercial diesel and bio-diesel fuel. An inspection and67

CHAPTER 3 - ASIAmaintenance programme is being promoted in BMR among private bus companies in order toreduce vehicle emission. Development of strategies for reduction of diesel emissions anddemonstration project on emission control devices for diesel vehicles has been conducted since themiddle of 2006 [PCD, 2006].There are also a number of international projects funded by donors and carried out inThailand through research networks. These include the DIESEL project [DIESEL, 2008], whichaims at development of integrated emissions strategies for existing land-transport. JapanInternational Cooperation Agency (JICA) has also provided funding and technical supports throughmany projects in Thailand e.g. development of environmental and emission standard of VOCs,emission inventory and modelling for acid deposition assessment. BMR is also a target city of theresearch network for “Improving Air quality in Asian Developing Countries” or AIRPET(http://www.serd.ait.ac.th/airpet), funded by Sida. ARRPET conducts monitoring of toxic pollutants,modelling of air quality, and develops integrated management strategies for agro-residues openburning.Problems remainingPresently, high PM 10 and ozone remain the most serious air quality issue in Bangkok. Trafficis the major sources of air pollution in the city. Air toxics, in particular the volatile organiccompounds (VOCs/HC), are also of concern in BMR and need continuous monitoring and standardenforcement. Open burning of agro-residues contributes significantly to air pollution in BMR andappropriate regulations have to be established and enforced in conjunction with the educativemeasures.3.3 BEIJING, CHINAIntroduction and specific features of the cityBeijing, China (Figure 7) is a megacity that is experiencing fast air quality improvements.The city is located between 39 0 28’ N to 41 0 05’N latitude, and between 115 0 25’ and 117 0 30’longitude. Beijing is surrounded by mountains on three sides: the Taihang Mountain lies to the west,while the Yanshan Mountain lies to the north and the northeast; the Great North China Plain linksthe south of Beijing all the way to Bohai Bay. The average height of the surrounding mountains isabout 1000 m.a.s.l with a descending trend from northwest to southeast. The administration areaof Beijing is 16,808 km 2 , of which 61% is mountainous area. The special topography results in amountain-plain breeze: north wind at night and south wind during the day. This effect leads to anisolated local circulation that is unfavourable for the dispersion of air pollutants within the city.Figure 7 – Map of Beijing city in China68

CHAPTER 3 - ASIABeijing has a population of 16.3 million as of 2008. As the capital of China, the city has hadfast economic growth in the last two decades: the GDP per capita has been increasing at a rate ofmore than 13% within the last 5 years, and reached 9075 USD in 2008. In the same period, theenergy consumption increased at a rate of 6% ~7% per year. The number of vehicles in Beijing,which increased at an annual growth rate of 13.3 % from 1999 to 2008 and reached to 3.5 million in2008, is also an important driving force influencing air quality trends.Emission sources of air pollutantsThe trend of annual emissions of SO 2 and dust as well as the increase in the number ofvehicles are shown in Figure 8. According to a study by Hao et al. [2005], the major SO 2 emissionsources are power plants, domestic heating, and industrial sources; accounting for 49%, 26% and24% of the total emissions, respectively, in 1999. Due to stringent air pollution controls, SO 2emissions show a decreasing trend from 2.24×10 5 tons in 2000 to 1.52×10 5 tons in 2007. In 2008,the SO 2 emissions dropped by 12.9 % of the 2007 level. The emission of NO X in Beijing appears tobe stabilized and a constant, NO 2 concentration in Beijing from 1998 to 2005 suggests that there isno significant increase in NO X emissions in Beijing [Chan & Yao, 2008]. National Ambient AirQuality Standards for NO X were relaxed in 2000; this is one of reason that the NO X emission controlin China is not as stringent as SO 2 . However, the NO X emission reduction policy is one of the toppriorities for the coming the 12 th five-year-plan of China.Figure 8 - The variation of emissions of SO2 and particulate matter and the increase of vehicle numbers in Beijing[Beijing Municipal Environmental Protection Bureau, The communiqué on the Environmental Status ofBeijing City, 1999 ~ 2007]The information for volatile organic compounds (VOC) emission inventories, e.g. emissionfactors of sources and correspondent activity data is very limited in China. Vehicular emissionshave been extensively studied for measuring the emission factors [Fu et al., 2005]. A more recentwork was to map the anthropogenic VOCs emissions in China from 1980 to 2005 based on updatedactivity data and available emission factors [Bo et al., 2008]. This study revealed a very fastincrease of VOCs emissions in China, from 3.91 Tg in 1980 to 16.49 Tg in 2005 with the annualgrowth rate at 10.6%. Beijing, Yangtze River Delta, and Pearl River Delta region were the mostintensive VOCs emissions areas. Beijing city alone contributed 0.32 Tg VOC. On the other hand,the VOCs source apportionments using receptor models were performed for Beijing city, the resultsshow that mobile sources contributed more than 50 % of VOCs (in mass concentrations) to ambientair, other important sources are gasoline evaporation, painting, and solvent use [Lu et al., 2007;Song et al, 2008]. More importantly, alkenes and aldehydes were found to be the most reactivespecies for ozone formation and vehicle exhaust was the largest contributor to reactive alkenes,69

CHAPTER 3 - ASIAnearly half of the C1–C3 aldehydes were attributed to secondary sources, while regionalbackground accounted for 21-23% of the mixing ratios of aldehydes. Primary anthropogenicemissions contribution to aldehydes was comparable to biogenic emissions contributions (10–16%)[Liu et al, 2009].Data available on air pollutantsThe air quality in Beijing is routinely measured by Beijing Municipal EnvironmentalProtection Monitoring center. The center runs 27 automatic monitoring stations with 13 stations inthe urban center and 14 stations in sub-urban regions. The air pollutants measured at thesestations are ambient concentrations of SO 2 , NO 2 , and PM 10 . The monitoring data are available viaBeijing Municipal EPB.From 2006, the air chemistry in Beijing city and surrounding areas were studied in theCareBeijing field campaigns. More species including O 3 , PM 2.5 , CO, volatile organic compounds(including carbonyls), HONO, and size distributions and chemical compositions of particles weremeasured. A database for CareBeijing-2006, 2007, and 2008 was established and assessablebased on the data protocol of the project.The status and trend of the pollutionThe trends of the concentrations of SO 2 , NO 2 , CO, and PM 10 were evaluated based on theannual communiqué released by Beijing Municipal Environmental Protection Bureau from 1999 to2007 (Figure 9). The SO 2 levels have been decreasing and went below the national ambient airquality standard (NAAQS) for SO 2 at grade II in 2005. The annual average NO 2 concentration hasstayed at a level of about 70 µg/m 3 and almost remained constant. PM 10 is reported to be the majorair pollutant on about 90% of the days in the last nine years in Beijing and its annual averageconcentrations were all above the NAAQS for PM 10 from 1999 to 2007. On 30% of the days eachyear, the daily average PM 10 concentration exceeded the Grade-II standard of 150 µg/m 3 .Figure 9 - The change of annual average concentrations of SO2, NO2, CO, and PM10 in Beijing between 1999 and 2007[Beijing Municipal Environmental Protection Bureau, The communiqué on the Environmental Status ofBeijing City, 1999 ~ 2007]The air quality is assessed by an Air Pollution Index (API) that reflects the concentrations ofthree pollutants; SO 2 , NO 2 , and PM 10 . However, the secondary air pollutants cause more significantadverse effects on public health and eco-systems. From a recent evaluation of air quality in Beijing[Tang et al., 2009], NO X concentrations decreased linearly at a rate of 3.9±0.5 ppbv/yr after 2002,70

CHAPTER 3 - ASIAwhile ozone concentrations increased at a rate of 1.1±0.5 ppbv/yr in a two-year cycle during2001-2006, and O X (O X = NO 2 +O 3 ) concentrations remained nearly constant (Figure 10). Thereduction of NO X emissions and elevated non-methane hydrocarbon (NMHCs) emissions may havecontributed to the increased O 3 concentrations in Beijing.The concurrence of high levels of ozone and fine particles suggest that air pollution inBeijing is very severe and complex [Shao et al., 2006]. Beijing is a typical city suffering fromcomplex air pollution with recent ambient PM 2.5 concentrations ranging between 96.5 µg/m -3 and154.3 µg/m -3 , six to ten times as high as the limit recommended by the US EPA (15 µg/m -3 annualaverage) [Chan and Yao, 2008]. In Beijing, the non-attainment days for ground-level ozone (numberof days with hourly ozone concentration >100 ppbv) accounted for more than 10% of days from1999–2007 [Beijing Municipal Environmental Protection Bureau, 1999-2007]. At one site in Beijing,about 20 km northwest of Beijing downtown area, an evident increase in ozone concentrations wasfound from long-term diurnal variations in ozone between 1987 and 2003 as shown in Figure 10[Shao et al., 2006]. Wang et al., [2006] measured ambient ozone concentrations in a northernmountainous site in Beijing in summer 2005 where ozone levels exceeded 120 ppbv on 13 out of 39days and maximum hourly average concentration reached 286 ppbv, the highest reported ozoneconcentration in China. The concurrent high concentrations of fine particles and ground-level ozone,especially the interaction between atmospheric oxidation processes and the formation of fineparticles is of great concern for air quality improvement in Beijing.Figure 10 - Concentration trends for (a) NO, NO2, NOX, (b) O3, OX, 2001–2006. The concentration of each species representsan average of measurements from all six representative stations in Beijing [Tang et al., 2009]71

CHAPTER 3 - ASIARelationships of the trends to regulationsFrom 1998 to 2009, Beijing municipal government implemented 15 stages of air pollutioncontrol countermeasures (http://govfile.beijing.gov.cn). These measures covered a wide range of airpollution controls including the use of low sulphur coal and promotion of cleaner fuels, a ban on highemitter vehicles in the urban fleet and implementation of a vehicle inspection/maintenance system,the prevention of fugitive dust from road and construction sites, and inspection of the operation ofemission control devices, amongst others. More stringent control measures including the control inTianjin city and surrounding provinces were enacted in 2008 for the Olympic and ParalympicsGames. The 15 th stage measures began in 2009 and includes the use of renewable energy, controlof several VOCs emission sources, and emergent actions under extreme weather conditions wererequired.The decrease of SO 2 emissions shown in Figure 9 was mainly due to mandatory phase-outof high emission, low efficiency enterprises and facilities, especially in sectors such as electricity,metallurgy, building materials, and chemical industries, as well as due to the use of coal withsulphur content lower than 0.5% and the increase use of liquefied petroleum gas and compressednatural gases in the city.Beijing is the first city in China to adopt the Euro-IV vehicular emission standards as ofMarch 2008, making Beijing the leader in China in upgrading vehicular emission standards. Beijinghas also very stringent controls for already in-use vehicles. Vehicles in the urban fleet with lowerthan the Euro I emission standard have been banned from circulation since October 2009 and thecity buses will be upgraded to electricity/natural gas powered and hybrid buses. Beijing is also thefirst city in China to implement the gasoline vapour recovery for gasoline stations and gasolinetanks across the entire city.Climatic change issuesFrom a study by the National Climate Center and Beijing Municipal Meteorological Bureau,the air temperature in Beijing showed an evident increasing in the last 40 years: the growth rate inurban areas was observed to be 0.43 0 C/10a, while in rural areas the rate was 0.21 0 C/10a,indicating a clear heat island effect [Song et al., 2003]. However, the study on ambient levels andthe emissions of greenhouse gases are very limited for Beijing. A 10 years study (1993-2002) donein Beijing by Liu et al., [2005] indicates that the ambient CO 2 increased at an annual rate of 0.57%,higher than the annual growth rate obtained at a global background site in China, 0.46% (Waliguan).The ambient N 2 O was more or less constant for the first 5 years and then increased very quickly atannual rate of 2.4%. The ambient CH 4 concentration increased from 1993-1998, but changed todecreasing from 1998 to 2002, dropping at 1.33% per year. Black carbon is an important radiativeactive species and recent work estimated that the black carbon emission in Beijing was 7.77 Gg in2000 and would be 2.97 Gg in 2008 due to the energy restructuring [Liu &Shao, 2007]. Noliterature was found regarding CO 2 emission inventory in Beijing.Research projects on air quality of Beijing cityStarting in late 1990s, Beijing city organized a series of air quality research programmes.The first one was launched in 1998, known as the Blue Sky Project, aimed at exploring therelationship between atmospheric visibility and fine particles. The Blue Sky Project was followed bya project from 2000-2003 addressing mainly emission sources, including both primary pollutantssuch as SO 2 , NO 2 , CO, and PM 10 and also the sources for high levels of ozone in Beijing. From2004-2006 a third project was funded to study secondary air pollution, i.e. the formation ofground-level ozone and fine particles. The research goal was to formulate a strategy for Beijing tobe in compliance with the NAAQS of China. From 2006-2008, the project CareBeijing wasimplemented to investigate the air quality problems with a regional perspective. The mostimportant objective of the CareBeijing project was to propose control measures for 2008 BeijingOlympic Games for both Beijing, Tianjin, and surrounding provinces (Hebei, Shanxi, InnerMongolia). In May 2009, the Beijing Municipal Government initiated a 3 year project to supportlong-term control strategies of air quality improvement.72

CHAPTER 3 - ASIAProblems remainingThe success of air quality improvements for Beijing Olympic Games proved that thereduction of precursors of ozone and fine particles were correct in the short-term, but will be toughin long term. Xu et al., [2008] used a 3D air quality model to show that the Beijing urban area was ina VOC-limited regime, while the downwind area changed gradually to a NO X -controlled process.Furthermore, 35–60% of the ozone during pollution episodes at the Beijing Olympic Stadium wasfound to come from sources of ozone precursors outside Beijing, e.g. from Hebei Province andTianjin [Streets et al., 2007]. Fine particles have significant origins of both primary emissions andsecondary production and therefore are not very well understood yet for Beijing. Furthermore, thegrey haze and fine particles issue is known to be a regional problem. Therefore, a regionalperspective is required to provide efficient control measures to overcome ozone and fine particleproblems. A better understanding of the interaction between the formation of ozone and fineparticles, shown in Figure 11, is essential in order to implement effective measures to abate bothfine particle and the ground-level ozone pollution in the next 20 years.Figure 11 - The change of peak concentrations of ambient ozone levels at Zhongguancun site in Beijingduring ozone episodes [Shao et al., 2006]3.4 DELHI, INDIADelhi, the capital city of India, hosted the Commonwealth Games in October 2010 (CWG2010). With the Games, the debate on air quality in Delhi and athletes health during the Games tookcenter stage, similar to the debates on air quality in Beijing before and during the Olympics Gamesin 2008 [UNEP, 2009].The National Capital Region (NCR) of Delhi has grown rapidly in the past two decades. Itnow covers an estimated area of 900 km 2 , which includes new townships and satellite centers suchas Noida, Gurgaon, Ghaziabad, and Faridabad, all of which are a combination of informationtechnology firms and industrial clusters (a graphical representation of the NCR is presented inFigure 12). In 2007, the population of NCR was estimated at 16 million. It is expected to reach 22.5million in 2025 [UNHABITAT, 2008].73

CHAPTER 3 - ASIAFigure 12 - Graphical representation o the National Capital Region and the travel demand from the satellite citiesAir pollution in DelhiDelhi is a rapidly expanding city; transportation, energy generation, construction, domesticburning, and industrial activity are contributing to increasing air pollution and its resulting health andrespiratory impacts. Figure 13 presents the summary of measured daily averages for the period of2004-07 for PM 10 and NO X concentrations from the four monitoring stations in Delhi. The collectionefficiency at each of the stations is ~25 percent [CPCB, 2010].A summary of the PM and ozone pollution observed at one of the continuous air monitoringstations in Delhi (located at the Income Tax Office - ITO) is presented in Figure 14. Data is collectedfrom the period of 2006-09 for the ITO station covering a range of pollutants and meteorology[CPCB, 2010]. On an average, the PM pollution exceeded 2-3 times the daily ambient standard of100 µg/m 3 for PM 10 and 60 µg/m 3 for PM 2.5 and ozone remained lower than the daily standard of 80µg/m 3 but exceeds the 8-hr standard (plotted as thick blue line).Over the past decade, the government has introduced some green initiatives to address theair pollution problem in the city. In 1998, the Supreme Court ruled that the city of Delhi should takeconcrete steps to address air pollution in the transport and industrial sectors. The timeline ofimplementation (in the transport and industrial sector) and the experience for instituting change hasbecome a model for other Indian cities and is described in detail in Narain et al. [2005].For the transport sector, this ruling led to the largest recorded compressed natural gas (CNG)switch in the world for public vehicles. This resulted in a dramatic decrease in the reduction of theair pollution. Since 2000, Delhi has enforced Euro II emission standards (five years ahead ofschedule), Euro III standards in 2005 for all passenger vehicles, and Euro IV fuel standards in April,2010 (in Delhi and 11 other cities).74

CHAPTER 3 - ASIAFigure 13 - PM10 and NOX measured at four manual stations in Delhi, India. The error bars indicate one standard deviationfor the daily averages over each month; thick line indicates the annual ambient standardFigure 14 - Daily average measured at a continuous air monitoring station located near ITO in Delhi, India75

CHAPTER 3 - ASIAAnother significant fallout of the Supreme Court ruling was in the industrial sector.Approximately 500 heavy industries were shut down and relocated to areas outside the Delhiadministrative boundaries. This not only led to a significant drop in air pollution, but also energyefficiency as several relocated industries took the opportunity of the relocation to upgrade theirsystems.Yet, there still remains a tremendous amount of potential to reduce air pollution and itsimpacts as the demand rises for infrastructure and services.Pollution sourcesNo single sector is responsible for all of Delhi's air pollution. Rather, it is a combination offactors including industries, power plants, domestic combustion of coal and biomass, and transport(direct vehicle exhaust and indirect road dust) that contribute to air pollution [Garg et al., 2006;Gurjar et al., 2004; Reddy et al., 2002; Shah et al., 2000]. Seasonal changes in demand for fuel andnatural pollution result in differing sources during the summer and the winter months. These need tobe taken into account to maximize the effectiveness of anti-pollution initiatives. Figure 15 presentsthe results of particulate matter source apportionment of the urban air pollution in Delhi, conductedby the Georgia Tech University (USA) in 2005.Figure 15 - PM2.5 Source apportionment results for Delhi76

CHAPTER 3 - ASIAIn summer, in addition to the road dust already present on the Delhi roads, dust storms fromthe desert to the southwest [Earth Observatory, 2008] contribute to increased fugitive dust, which isenhanced by growing vehicular movement. This is exacerbated by the low moisture content in theair, leading to higher resuspension of road dust (40 percent of particulate pollution in summer,compared to 4 percent in winter). In the winter months, the mix of pollution sources changesdramatically. The use of biomass, primarily for heating contributes to as much as 30 percent ofparticulate pollution in winter. Most of this burning takes place at night, when the “mixing layerheight” is low due to inversion. In summer, biomass accounts for only 9 percent of particulatepollution.Another external factor to air pollution in Delhi is agricultural clearing [Earth Observatory,2008]. After harvesting crops, the land is cleared, a common practice in surrounding (largelyagricultural) states. The smoke from clearing crops reaches Delhi and contributes to the smogformation and ozone pollution.Apart from biomass burning and ambient dust, transportation and industries are majorcontributors. With a growing city, transportation needs are increasing, creating a rise in privatevehicles (2 and 4 wheelers), taxis and auto-rickshaws. Idling time and pollution are correspondingfactors that have increased due to increased use of vehicles. The largest gain in the air qualitywas observed at the peak of the CNG conversions for the public transport buses, taxis, and3-wheelers in 2001-2002. Air quality levels since have declined gradually over the years in theresidential areas and along the major corridors, which is directly linked to the growing passengerfleet, especially diesel based, increasing commuter times leading to idling, and more vehiclekilometres travelled.The efforts to address this by building flyovers that connect and bypass major junctions inthe city have not yielded results as expected. For one, this solution addresses only the supply sideof the equation and does not influence demand management. In fact, as it becomes easier to take aprivate vehicle, the number of vehicles has increased (about 1000 new registrations per day in 2006)thus negating many of the planned improvements. In addition, the increase in the on-street parkingand encroachments by hawkers has exacerbated the situation.Industry, the other major source – accounts for about a fifth of the air pollution in Dehli andincludes five power plants at Indraprastha, Faridabad, Badarpur, Pragati, and Rajghat (using a mixof coal and natural gas for electricity generation) and ~3,000 industries ranging from pharmaceuticalto metal processing that use coal, fuel oil, and biomass [CPCB, 1997].The growing industrial conglomerations and information technology (IT) parks, under theSpecial Economic Zone (SEZ) schemes have also led the way in increasing the travel demand..This leads to a significant change in the geographical settings, the travel behaviour and the mode oftransport (transformed to motorized transport), and not only increased vehicle kilometres travelledper day, but also exerting pressure on the limited infrastructure that results in congestion, idling, andpollution (Figure 11). On a daily basis, in and out travel between Delhi and the satellite citiesaccounts for nearly 30-40 percent of the passenger trips [CRRI, 2008].These satellite cities are also prone to regular power cuts, leading to increasing use ofgenerators for in-situ needs. This includes cinemas, hotels, hospitals, farmhouses, apartmentbuildings, and institutions. The rapid growth in generator use has consequently led to increased fuelcombustion, poor traffic management, and lack of sufficient public transport. This results indeteriorating air quality, increased trip costs, extended commuter times, thus means longerexposure to increasing air pollution and health impacts [Guttikunda, 2009a].Seasonality in pollutionThe seasonal variation of the mixing layer height is very prominent in Delhi. During thewinter months, the mixing layer height is low which leads to increased air pollutant concentrations.The recurring impacts include heavy persistent smog during the months of November to February,higher pollution levels for all criteria pollutants, frequent delay or cancellation of flights (domestic77

CHAPTER 3 - ASIAand international), and reduced visibility causing minor and major accidents along the roads. Thiswintertime phenomenon is of utmost importance because it starts forming in the month of October,the start of the CWG 2010 [Guttikunda, 2010a].Correlations for air pollutants like CO, NO, SO 2 , and PM 2.5 measured at the ITO station arepresented in Figure 16. Note that the figure indicates measured concentrations and not emissionsand most likely indicate the sources in the vicinity of the monitor rather than as a city average. Thegraphs also provide a distinction between the summer (dark dots) and non-summer months that arelinked to the seasonal differences in the mixing layer heights [Guttikunda, 2009c].The correlation between PM 2.5 and CO concentrations is an indication of direct emissions,most likely transport and fresh plumes from the industrial areas to the East. The CO concentrationsare also sourced to the chemical conversion of VOCs via photochemistry and the fraction of the PMalso originates from the chemical conversion of SO 2 and NO X emissions. The fractional analysis ofthe secondary contributions is not presented.For the NO X emissions in the transport sector, the nitric oxide (NO) is close to 90 percent ofthe emissions and readily oxides to nitrogen dioxide (NO 2 ) in the presence of sunlight. Figure 16(top right) indicates a direct emission source with a strong correlation between NO and SO 2 , whichin this case is linked to diesel combustion from the transportation sector and possibly generators inthe vicinity. Lower concentrations of NO in the summer months coincide with the faster oxidation toNO 2 in sunlight. The ozone pollution is higher in the summer months and linked to the presence ofVOCs (CO as a proxy in Figure 16, bottom left) and the oxidizing capacity of NO X , details of whichare described in the following section.Figure 16 - Correlations between criteria pollutants of measured daily averages (2006-09) at the ITO station in Delhi, India78

CHAPTER 3 - ASIATracer model simulations over Delhi, IndiaA snapshot of the variation in monthly tracer concentrations compared to the annualaverage over Delhi area for 2008 is presented in Figure 17(a). This is the result of a dispersionmodel simulation conducted over the Delhi area with constant emissions from all the grid cells andvarying only the meteorological conditions based on NCEP Reanalysis data [Guttikunda, 2010a].A clear conclusion is that irrespective of the constant emissions over each month, theobserved concentrations are invariably 40% to 80% higher in the winter months (November,December, and January) and 10% to 60% lower in the summer months (May, June, and July) whencompared to the annual average tracer concentrations for the emissions domain. The pattern isconsistent over the years and the shift is primarily due to the variability in the mixing layer heightsand wind speeds between the seasons (and years). During the day, similar patterns are alsoevident, when the mixing layer height is routinely lower during the nighttime compared to the day,irrespective of the seasons.Mathematically, this is better illustrated in Figure 17(b) as a box model. By definition, theambient concentration is defined as mass over volume. Assuming that the emissions are equallymixed in an urban environment under the mixing layer, for the same emissions, a lower mixingheight means higher ambient concentrations.Similar to the mixing layer height, the wind speed is also very relevant. Figure 17(c) presents asummary of the surface layer wind speeds in 2008 from ECMWF for Delhi. The higher wind speedsobserved in the summer months are responsible for driving part of the pollution out of the city limits,as evident in the months of June, July, and August (Figure 13) when the predominantly southerlywinds move the pollution more north, thus reducing the average contribution of the local emissions.The mixing layer height, presented in Figure 17(d), shows the highs in the spring and summermonths for the period of 2007-2008.It is important to note that while the modelling is conducted using the meteorology pertinentto the city area, the emissions are not. The simulations provide a better understanding of thedispersion of the air pollution within the city. However, the pollution patterns would be best studiedusing a local emissions inventory, including the contributions of emissions originating outside thecity (transboundary pollution). For example, in case of Delhi, a constant traffic between Delhi and itssatellite cities in the south (Gurgaon and NOIDA) is a growing emission source along with all theindustrial estates in the northeast and northwest sectors.Back-trajectory analysis of meteorological fields reaching DelhiThe analysis presented in the previous section focused primarily on understanding whathappens to the emissions originating in Delhi city limits, but the question of how much is thecontribution of emissions outside Delhi to the pollution experienced in Delhi is explored via aback-trajectory analysis.The back-trajectory analysis was conducted for the year 2008 using the HYSPLIT (HybridSingle Particle Lagrangian Integrated Trajectory) model, a web-based portal for trajectory analysis,utilizing the NCEP Reanalysis data [Draxler et al., 2003; Guttikunda, 2010a]. The trajectories aregenerated once per day and advected backwards for 24 hours to indicate the meteorological originof the air parcel. The source point, Delhi, India is assigned at 28.6 o N latitude and 77.2 o E longitudeat 100m above ground level. Each line in Figure 18 indicates a trajectory for one day.The winter and summer months see a strong influence of northern and northeasterly winds,passing cold temperatures over the city and the resultant low mixing layer heights. The summer andlate fall months experience a mix of southern winds, increasing the possibility of pollutionentrainment from the southern satellite cities.79

CHAPTER 3 - ASIAFigure 17 - (a) Variation of monthly averaged tracer concentrations compared to the annual average concentration for theDelhi emission domain; (b) Box model illustration of the impact of the mixing layer height; (c) Figure 6: Wind Speed forDelhi domain, estimated from ECMWF; (d) Mixing layer height in Delhi, estimated from NCEP Reanalysis data80

CHAPTER 3 - ASIAFigure 18 - Back trajectories for Delhi, India for four months in 2008Diurnal cycles in pollutionIn the morning and evening traffic hours, the transport sector is the predominant source ofpollution at the ITO monitoring site. Figure 19 shows typical variation of PM 2.5 , Ozone, CO, SO 2 ,NO X , and NO 2 , over a 24-hour period in 2008. The graphs indicate an average of the measuredconcentrations for each hour over all days in 2008.Truck pollution at nightAn important observation in Figure 19 is the diurnal variation of the PM 2.5 pollution. Besidesthe rush hours bumps (8-10 in the morning and 6-9 in the evening) the steady increase in thepollution levels is attributed to two reasons – a direct source from trucks, which are allowed to passthrough the city after 9 PM and a change in the mixing layer height. The influence of the truckemissions is more evident in the direct correlation of the PM 2.5 and SO 2 cycles, possibly originatingfrom the diesel combustion in trucks.While the passenger travel in the city has grown over the last decade [Guttikunda, 2009b],the importance of the freight transport (via trucks) during the night should not be neglected, sincethe high concentrations observed during the night tend to linger during the rush hours (mixed withthe passenger travel) and beyond (through ~11 AM) and hence increasing the exposure times andrelated health concerns along the major corridor.Figure 19 - Diurnal variation of pollution at the ITO station in Delhi, India averaged over all days in 200881

CHAPTER 3 - ASIAEmissions inventory for Delhi, IndiaFor the area covering the NCR of Delhi an emissions inventory that reflects the trends andsources observed in 2010 is under development, including all key species – PM, SO 2 , NO X , BC, CO,and VOCs, and covering the primary sources – transport (especially passenger travel), industrialclusters, power plants, residential fuel use for cooking and heating (including biomass), generatorsets (in households, industries, cinemas, institutions, hospitals, hotels, apartment buildings, andfarm houses) and garbage burning (especially for the areas where the waste collection efficienciesare small) [Guttikunda, 2010b].The urban inventory is further segregated spatially (Figure 20) to allow for diurnal andgeographical variations among all the sectors. For this inventory, data was collected from manysources – including surveys conducted by local agencies, such as Center for Road ResearchInstitute on traffic density on main corridors, CPCB on the industrial clusters in NCR, and fuel usagefor cooking and heating in the residential sector by the project team. The inventory presented inFigure 20 is updated to reflect the consumption patterns in 2010.A summary of the emissions inventory is presented in Table 4, segregated into majorsectors. The largest sectors are transport and power plants. However, due to the release of airpollutants at higher altitudes, the pollution from the power plants is felt less than the low lyingemissions from vehicle exhaust, waste burning in the residential areas, low stack emissions fromindustries, and fuel (fossil and biomass) for residential cooking.The emissions inventory is maintained in a geo-referenced system to further analyze thevulnerable areas, residential vs. industrial, hot spots for the monitoring air pollution, transportcorridors, venue locations and the Games Village (specific product for the 2010 CWG). Themodel-ready emission inventory also includes diurnal cycles for the transport sector emissions todistinguish between rush and non-rush hours for all modes, operational hours for the industrialsector, and cooking and heating hours for the domestic sector.This emission inventories are now in use for dispersion modelling, as part of air qualityforecasting for Delhi, including scenario analysis for future projections. The “Clean Air for Delhi2010 and beyond” project is funded by the Government of France under their FASEP bilateral funds;implemented by Aria Technologies SA and Leosphere SA (Paris, France), in technical collaborationwith the Central Pollution Control Board (CPCB), Delhi, India. The analysis results will be presentedin 2011.Figure 20 - Distribution mechanisms utilized for urban scale emissions. (IND = industries; PP = power plants; DOM =domestic; TR = transport; RD = road dust; WB = waste burning; CON = construction activities;BK = brick kilns; GS = generator sets)82

CHAPTER 3 - ASIATable 4 - A summary of the emissions inventory (Tons/yr) for 2010 for NCR of Delhi, IndiaAir Quality Index for DelhiApplied methodologyThe methodology to calculate the air quality index (AQI) is presented below, along with thesupporting data for various ranges (Table 5).WhereCONC = concentration of the pollutantAQI = air quality index for the pollutantBP hi = the breakpoint that is greater than or equal to CONCBP lo = the breakpoint that is less than or equal to CONCAQI hi = the AQI value corresponding to BP hiAQI lo = the AQI value corresponding to BP loThe break point concentrations (high and low) are adjusted to the national ambientstandards of India for each of the pollutants [NAAQS, 2010]. The AQI ranges are adjusted with 150as the threshold, corresponding to the ambient standard for that pollutant. This is not an official AQImethodology for India, but an attempt to consolidate the available information and put together areasonable methodology based on applications from across the world.Applications of the methodology in various in cities across the world and how the informationis utilized for public awareness is presented in Guttikunda [2010c].Table 5 - The applicable ranges for AQI methodology for Delhi, India83

CHAPTER 3 - ASIAAir Quality Index resultsUsing the methodology above, AQI was calculated for the period of August 2006 to June2010 utilizing the data for two stations across Delhi; (1) Income Tax Office (ITO) and (2) DelhiCollege of Engineering (DCE), where the PM monitoring data is available. For this analysis, AQI’sare calculated in 6 bins, explained in Table 6. The first three bins, at par with the national ambientair quality standards are considered “safe mode” or “clean air” days and the others “polluted” days[Guttikunda, 2010d].Table 6 - The AQI colour codes and their definitions"HEALTHY" – this range poses little or no risk tothe general public. No cautionary actions areprescribed."UNHEALTHY" - is borderline unhealthy,particularly for members of sensitive groups."VERY UNHEALTHY" - can trigger a health alert,meaning everyone may experience more serioushealth effects."MODERATE" - is acceptable for general public.However, unusually sensitive people should becautious."UNHEALTHY" - is considered unhealthy for mostof the public where everyone may begin toexperience some discomfort."HAZARDOUS" – this range triggers healthwarnings under emergency conditions, affecting allage groups.Of the six criteria pollutants – PM (coarse and fine), SO 2 , NO X , CO, and Ozone - the PMpollution is routinely above the daily average standards (Daily average national ambient air qualitystandards for PM 10 and PM 2.5 are 100 µg/m 3 and 60 µg/m 3 , respectively) and the conditionalpollutant for calculating the AQI for health impacts assessments – presenting the worst AQI. Figure21 presents estimated AQI due to PM 2.5 pollution at ITO and estimated AQI due to PM 10 pollution atDCE.Observations on AQI• At the monitoring sites, AQI is often morethan the healthy levels of 150. The ITO islocated at a traffic junction. On 19% of thedays the AQI is less than 100 and on 33% ofthe days less than 150. The DCE is abackground station in the north and tends tomeasure lower than the city averages and yetstruggled to stay in the green with only 24%of the days with an AQI less than 150.• In Figure 21(a) and 21(b), the winter months,which are highlighted with a blue box for eachyear, show the worst pollution each yearstarting in October and leading up toFebruary the following year.• A large portion of the AQI’s greater than 300(summary presented in Figure 21(c)) areassociated with the winter season.Figure 21 - (a) AQI based on PM2.5 measurements at ITO monitoringstation; (b) AQI based on PM10 measurements at DCE monitoringstation; (c) Frequency of AQI between July 2006 and August 201084

CHAPTER 3 - ASIAAir quality management in DelhiThe air quality in Delhi improved in the early 2000's due to a number of interventions,including the large-scale conversion of the bus fleet and the three wheel fleet from the conventionalgasoline and diesel to CNG (The benefits of CNG conversion in Delhi on global climate and localpollution are summarized in Reynolds et al. [2008]). However, the large increase in the demand forpersonal transport and construction activities reversed these trends in the last 3 years.A major intervention that Delhi is banking on is the extension of the metro rail system inorder to shift the motorized transport trends to the metro rail system. The expected level of the shiftis uncertain and depends on a number of factors. A “what-if” analysis revealed a potential reductionof 20-45 percent in the criteria pollutant emissions due to completion of the metro rail system in2010. This is also very consistent with other cities like Mumbai, Shanghai, Beijing, Bangkok, andHong Kong, which experienced significant changes in the air quality after the expansion of thepublic transport systems with a metro system. Certainly, the challenge will be public awareness,promotions, and incentive schemes for the public to use metro rail system more frequently thantheir personal mode of transport.In the transport sector, the emphasis is on the public transport. The JNNURM funds forbuses and urban transport strategy of India are promoting the need for infrastructure for new buses(via two of the largest manufacturing firms - Tata and Ashok Leyland). A good public transportsystem, including substantial support for non-motorized transport (NMT), is expected to help reducethe congestion levels, energy demand, and thus emissions from the transport sector. However, theinitial phase via the introduction of the Rapid Bus Transport for ~5km and promoting NMT along thepath has had a difficult time gaining traction in Delhi.In the short termIn order to improve air quality during the 2010 Commonwealth Games, Delhi implementedlessons learned from when Beijing hosted the Olympics in 2008. The lesson focused on the localair quality in order to bring the pollution to a manageable level, fast and efficiently. Some of thelessons learned from Beijing that were suggested to Delhi include:• Improve the number of air quality monitors operating in the city. There are more monitoringstations than those that can actually deliver monitoring data. Even if we consider the mostimportant pollutants, such as PM, and not worry about the other pollutants (in order to keepthe costs low), the stations that measure this are limited.• More than operations, the data should be made public as frequently and consistently aspossible so the general public is aware of the consequences of their actions.• Better understanding of emission source contributions of both within and outside the city.Currently, a lot of emphasis is put on the transport sector. However, the contributions fromthe industrial, power, and residential sources are very significant and in October (and in thewinter months), with low inversions, these low lying residential sources (via biomass burning)will hinder the “clean air” goal.• The hot spots of industrial and residential areas (many of them outside the Delhi area, butincluded in the National Capital Region) should be monitored to manage the emissions inreal time.• In the case of Beijing, stringent regulations and policy measures were implemented monthsin advance to ensure clean air days before and during the 2008 Olympic Games. However,this remains a challenge for the Delhi authorities.During the Commonwealth Games, the Delhi Government was unable to shutdownindustries nor stop half of the vehicle fleet, making it more difficult to improve the air quality.Therefore, some innovative interventions were needed in order to implement fast and effective airquality management. Some of the innovative interventions were:• Shut down part of the industries, depending on the meteorological and air quality forecasts(either daily or weekly).85

CHAPTER 3 - ASIA• Strict restrictions on garbage burning during the winter months, especially the open burningfor heating purposes in the residential areas.• One-way transport along the major corridors for better flow of the traffic. Some corridors bededicated for the movement of the athletes, but similar provisions should be made forpassenger travel.• Aggressive procurement of buses and incentives to promote the use of bus and metro railsystems.• Promote telecommuting where possible, especially along the satellite cities like NOIDA andGurgaon, which experiences the largest rush hour traffic during the week days• Promote wet sweeping of the all the major roads, at least once every two days to reduce theamount of dust loading and thus reduce the resuspension due to increasing vehicularmovement.In the long run Delhi should implement some of the following air pollution managementstrategies:• The air quality monitoring network needs serious improvement in all respects – the numberof operational monitors, placement of the monitors across the city, dissemination of themonitoring data to the public and the media, access to the archives of monitoring data, andprovisions for further analysis.• In general, there is greater understanding of the pollution sources in the city now than everbefore. There is also a greater awareness among the public on the harmful impacts ofgrowing air pollution. Systematic programmes should be introduced in all sectors, startingwith tackling low lying sources, such as road dust and residential open waste burning toreduce the daily pollution levels.• For power plants, coal was slowly being replaced with natural gas, at least in the smallerpower plants, in order to reduce pollution during the 2010 Commonwealth Games. Thisintervention should be part of the long-term strategy.• In the transport sector, the public transport (via buses) and the NMT should be promotedequally, along with better traffic management for the passenger cars.3.5 DHAKA, BANGLADESHIntroduction and specific features of Dhaka, BangladeshBangladesh is situated in the eastern part of South Asia. The country is surrounded by India tothe west, the north, and the northeast, Myanmar to the southeast, and the Bay of Bengal on thesouth (Figure 22). Bangladesh is one of the most densely populated regions of the world.Meteorologically, the year can be divided into four seasons [Salam et al., 2003; Azad and Kitada,1996] pre-monsoon (March - May), monsoon (June - September), post monsoon (October -November), and winter (December - February). The average temperatures vary between 7 o C and25 o C in winter and high values between 25 o C and 38 o C in summer. Dhaka (23º76Ń, 90º38´ E, and8 m above sea level) is the capital of Bangladesh (Figure 22). Dhaka is a rapidly growing megacitywith a population of approximately 13 million. Dhaka is the center for commercial, political, andcultural activities in Bangladesh. With the modernization of its transport, communication, publicworks sectors as well as industries, the capital city Dhaka is facing severe air pollution challenges.Emission sources of air pollutantsThere are many emission sources for air pollutants in Dhaka, e.g. large number of motorvehicles, construction activities (road and building), industry, brick fields, etc. Natural gas burningfor cooking and long-range transport also contributed to the air pollution in Dhaka. Begum et al.[2004] sampled fine and coarse fractions of ambient particulate matter (PM) in Dhaka between June2001 and June 2002. Six and seven different factors of elemental compositions for coarse and finePM fractions were identified with positive matrix factorization (PMF) technique. The sources are soildust, road dust, cement, sea salt, motor vehicles, and biomass burning. A large fraction, more than50%, of the PM 2.5–10 mass came from soil dust and road dust. Motor vehicles, including two strokes,contributed about 48% of the PM 2.5 mass in Dhaka.86

CHAPTER 3 - ASIAParticulate matter (PM) is the main pollutant of concern in Dhaka, Bangladesh, especiallyduring the winter months. There have been several studies to characterize atmospheric pollution inDhaka. Data are available for particulate matter, heavy metals, and trace gases [Salam et al., 2008and 2003; Mahmud, 2008; Bilkis et al., 2008 and 2004; Nasiruddin, 2006 - DoE, Government ofRepublic of Bangladesh].Salam et al. [2008] studied aerosol particulate matter (SPM, PM 10 and PM 2.5 ) and tracegases (SO 2 , NO 2 , CO and O 3 ) in Dhaka between January and April 2006. The total averageconcentrations of SPM, PM 10 and PM 2.5 were 263, 75.5, and 66.2 µgm –3 , respectively. The mass ofPM 2.5 is approximately 88% of the PM 10 mass, indicating fossil fuels as the main source ofparticulate matter in Dhaka. The total average concentrations of SO 2 , NO 2 , CO, and O 3 were 48.3,21.0, 166.0 and 28 µgm –3 , respectively. The total average concentrations of As, Cd, Cu, Fe, Pb, andZn in PM 2.5 were 6.3, 13, 94, 433, 204, and 381 ngm –3 , respectively. The measuredconcentrations for trace gases and metals were much lower than the ambient standard values forBangladesh.Begum et al. [2008] measured particulate matter (PM) in Dhaka (Farmgate), which is a hotspot (HSD) with very high pollutant concentrations due to its proximity to major roadways. Fineparticulate matter concentrations at HSD have decreased over this period (from January 2000 toMarch 2006) to less than half of the initial value, even with an increasing number of vehicles. Thisdecrease is likely the result of governmental policy interventions such as the requirement of vehiclemaintenance, training of repair workers, and phase-wise removal of two-stroke three wheelers fromthe roads in Dhaka. Other policy interventions include the banning of old buses and trucks fromoperating in Dhaka, promotion of the compressed natural gas, introduction of pollution controldevices on vehicles, control of emissions from industries, etc.Salam et al. [2003] studied aerosol chemical composition of atmospheric aerosol particles inDhaka under pre-monsoon conditions (March–April 2001). The elemental carbon (EC), organiccarbon (OC), organic acids, major inorganic ions, and trace elements were measured in TSP. Thereconstructed average particulate mass (TSP) was 516 µgm –3 . On average about 76% of theaerosol is from soil-type materials, around 18% from carbonaceous material, and around 6% aresoluble ions, and trace elements (without iron) are about 0.3%. Coal fly ash is likely a main sourcefor Cd, Pb, and Zn in Dhaka aerosol, while as appears to be of geogenic origin. High concentrationof elemental carbon and organic carbon concentrations were observed in Dhaka, e.g. about 22µgm –3 of EC and 45 µgm –3 of OC. The correlation between EC and OC was quite high (0.81)indicating a potential joint source of emission for carbonaceous aerosols. The EC/total carbon (TC)and K/EC ratios indicated that biomass combustion was not a main contributor to EC in Dhaka,which implicates that the fossil fuel combustion is the major contributor to EC levels in Dhakaaerosol.Nasiruddin [2006] reported the variation of the particulate matter (TSP, PM 10 , PM 2.5 ), andtrace gases (SO 2 and NO 2 ) from a continuous monitoring station on the premises of the nationalParliament Building, Dhaka. Annual average PM concentrations (PM 10 and PM 2.5 ) in the city ofDhaka showed a slight increasing tendency from April 2002 to July 2006 (2002 data is average ofconcentrations from April to December and 2006 data is average of concentrations from January toJuly 2006). Both PM 10 and PM 2.5 concentrations exhibit more than twice the national standards ofannual PM 10 (50 µg m -3 ) and PM 2.5 (15 µg m -3 ). Annual average concentration of SO 2 in 2003 (6.67ppb) is within the national ambient air quality standard of 30 ppbv. The annual averageconcentration of NO 2 in 2003 was 27.6 ppb, which is also bellow the annual ambient standardsvalue of Bangladesh of 53ppb. Khaliquzzaman [1998] reported the SO 2 concentrations were from64 to 143 µg m –3 at Dhaka (Tezgaon), where as NO 2 concentrations were between 25 and 32 µgm –3 at Dhaka (Farmgate) in 1996.The status and trend of the pollutionThe overall air quality situation in Dhaka, Bangladesh is improving day by day due to theawareness among the city dwellers and also due to control measures implemented by thegovernment of Bangladesh. The major achievements in improving air quality in Dhaka, Bangladesh87

CHAPTER 3 - ASIAis due the ban of leaded gasoline, introduction of lubricant standards, switching to CNG fuel, andbanning of baby taxis, old trucks, and buses. For example, the lead concentration in the Dhaka cityair (493ngm –3 ) was the highest in the world during the dry season in 1996, which falls down duringthe periods of medium and heavy rainfall. However, the lead concentration in Dhaka air isdecreasing [Salam et al. 2008] due to the ban of leaded fuel. Core [1998] also reported themeasurement of the Department of Environment, Bangladesh for suspended particulate matter(SPM) concentrations at several locations for eight hours along busy roads of Dhaka city between1996 and 1997. Results showed that the SPM concentrations of 665-2456 µg m –3 at a hot spot inDhaka (Farmagte). The SPM trends are highest during the dry season (December-March) due to anincrease in roadway dust, dust from dust-carrying vehicles, and also increased open burning.Salam et al. [2003] measurements show that the SPM concentrations were also decreasingremarkably.Relationships of the trends to regulationsThe Ministry of Environment and Forestry is the key institution for air quality monitoring andmanagement in Dhaka, Bangladesh. The primary legislation instituted to mitigate air pollutionproblems is from the Department of Environment (DoE), Government of Bangladesh. They haveadapted the 1995 Bangladesh Environmental Conservation Act and the 1997 EnvironmentalConservation Rules (ECR) to control air pollution (DOE 1997, DOE 2002).Climatic change issuesThere have been several socioeconomic studies done for climate change issues. TheGovernment of Bangladesh as well as the Department of Environment, educational institutes, andresearch organizations are aware of the climate change issue. No literature values could be foundregarding CO 2 and other trace gas emissions in Dhaka.Research projects on air quality of Dhaka cityAcademic institutions like the Department of Chemistry, Dhaka University, BangladeshUniversity of Engineering and Technology, and Jahangirnagar University are researching variousissues in order to understand air pollution in Dhaka. The AQMP Project (BoE, the GovernmentRepublic of Bangladesh) has long-term measurements for PM and trace gases in Dhaka.Organizations such as the Forum of Environmental Journalists, Bangladesh Paribesh Andolon,Bangladesh Environmental Lawyers’ Association, and the Society for Urban EnvironmentProtection help raise awareness among the public on environmental issues including air pollutionthrough conferences, reports, and ad campaigns. There is certainly a need for long-term problemresearch of air pollution in Dhaka, Bangladesh.Problems remainingDhaka still needs to assess the status of the air quality more completely, as well as monitorthe impact of reduction measures in emissions. The lack of information on the positive impacts ofmeasures implemented by the government may undermine the efforts to improve air quality in thecountry further. However, there is a need to conduct further studies to understand the impacts ofair pollution on climate and health as well as to guide policy.3.6 HONG KONG, CHINAIntroduction and specific features of the cityThe Hong Kong Special Administrative Region (HKSAR; 22º15‘N 114º10‘E) is located at theeastern bank of the Pearl River Delta facing the South China Sea [GovHK, 2009]. Covering a landarea of 1104 km 2 , the territory is composed of New Territories that adjoin Mainland China, KowloonPeninsula, Hong Kong Island, Lantau Island, and 262 outlying islands (Figure 23). Due to themountainous terrains, less than 25% of the land area is developed, whist ~40% of the remaininglandmass is designated as country parks and nature reserves. HKSAR experiences a subtropical,monsoonal climate, with a hot (mean air temperature: ~26ºC), wet (80% of the 3066 mm annualrainfall) summer influenced by the southwest monsoon, when typhoons are most common, and a88

CHAPTER 3 - ASIAcool (mean air temperature: ~15ºC), dry winter when the northeast monsoon prevails(http://www.hko.gov.hk/wxinfo/climat/climahk.htm).HKSAR has a population of ~6.98 million. Being an international trade and financial centre,HKSAR experiences a fast growing economy. The GDP has increased by >170% since 1990,reaching HK$1620 billion in 2007. During 1990 - 2007, the energy consumption rate has increased~20% (i.e. 290000 TJ in 2007) and the vehicle-kilometres travelled (VKT) increased by ~50%(Figure 24).Figure 23 - Locations of EPD’s Air Quality Monitoring StationsFigure 24 - Trends of gross domestic product (GDP), energy and electricity consumption, vehicle kilometres travelled(VKT), and atmospheric emissions of sulphur dioxide (SO2), nitrogen oxides (NOX), volatile organic compound (VOC),respirable suspended particulates (PM10), carbon dioxide (CO2) and carbon dioxide equivalent (CO2-e) in HKSAR in1990 – 2007 (1990 = 100). Note: Energy consumption stands for energy consumed via town gas, liquefied petroleum gas,oil and coal products, and electricity. CO2-e is a measure used to compare the emissions from various greenhouse gases(e.g. carbon dioxide, methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs)and sulphur hexafluoride (SF6)) based upon their global warming potential89

CHAPTER 3 - ASIAAvailability of air pollutant dataOwing to the potential negative human health impacts, air quality is one of the most pressingenvironmental topics in HKSAR [Leverett et al., 2007; Civic Exchange, 2008]. To better understandthe patterns, sources, and origins of air pollutants in HKSAR, as well as to report Air Pollutant Index(API) to the public, the Environmental Protection Department (EPD) has developed a fixed networkof ambient air quality monitoring stations (AQMS) to measure the concentrations of nitrogen oxides(NO X ), respirable suspended particulates (PM 10 ), carbon monoxide (CO), sulphur dioxide (SO 2 ),and ozone (O 3 ) (Figure 23). This 14-station network involves 11 general and three roadside stations.Two toxic air pollutant (TAP) monitoring stations are co-located with Tsuen Wan andCentral/Western AQMS to measure total polychlorinated biphenyls, polychlorinateddibenzo-p-dioxins/dibenzofurans, polycyclic aromatic hydrocarbons, volatile organic compounds(VOC), carbonyls and hexavalent chromium [Lau et al., 2007]. In addition, three stations (TsuenWan, Tung Chung, and Tap Mun) are incorporated with another 13 regional stations to form the16-station Pearl River Delta (PRD) regional air quality monitoring network, which reports the PRDregional air quality index (RAQI) to the public [Zhong et al., 2007]. Hourly, daily, and annual dataare posted to relevant websites for data sharing with the public and academic communities (e.g.http://www.epd.gov.hk/epd/english/environmentinhk/air/data/air_data.html andhttp://www.epd.gov.hk/epd/english/ environmentinhk/air/air_quality/air_quality.html).Emission sources of air pollutants and emission inventoryHKSAR is currently facing serious particulate and photochemical smog problems(http://www.epd.gov.hk/epd/english/environmentinhk/air/air_maincontent.html). One of the majoremerging particulate problems is fine suspended particulates (PM 2.5 ), which comprises ~70% ofPM 10 concentration, and, are emitted from a number of sources, including vehicle exhaust,electricity generation, navigation, other fuel combustion, road dust, etc. See Louie et al. [2005a andb]; Huang et al. [2009]; Yuan et al. [2006b and c] for PM 10 source apportionment information.Photochemical smog is produced from a photochemical reaction between nitrogen oxides (NO X )and volatile organic compounds (VOCs). In HKSAR, NO X are mainly produced by electricitygeneration, vehicle exhaust and shipping(http://www.epd.gov.hk/epd/english/environmentinhk/air/data/emission_inve.html), while VOCs aremainly emitted from consumer products, paint application and printing process [Guo et al., 2004aand b, 2007].The current status and air pollution trendsThe particulate and photochemical smog problems in HKSAR have severely impaired localvisibility since the early 1990s [Wang, 2003] Intensification of the particulate problem is likely fromambient concentration of SO 2 and NO X , but the regional influence should not be neglected. (Figure25) Whilst SO 2 is predominantly originates from regional industrial sources [Wang, 2003; Louie etal., 2005b] and shows similar patterns amongst the fixed network monitoring stations, NO X andcarbonaceous matters which explain ~50% of PM 2.5 mass are emitted mainly from local vehicleexhaust and is more concentrate in urban than in rural sites [Yu et al., 2004; Louie et al., 2005a; Leeet al., 2006]. So et al. [2007] compared PM 2.5 levels in HKSAR between 2000/2001 to 2004/2005 intwo differente PM 2.5 speciation campaigns that suggest over 36% growth of ambient sulphateconcentrations most likely resulted from an increase in regional sulphate pollution.Intensification of the regional photochemical smog problem, on the other hand, has resultedin the increase in O 3 concentration in HKSAR (Figure 26). Similar results were obtained by Wang etal. [2009b], in which the ozone concentration increased by an averaged rate of 0.55 ppbv/yr in 1994– 2007. Wang et al. [2009b] suggested that this rising O 3 trend is predominantly due to the increasein nitrogen dioxide (NO 2 ) and probably VOC emitted from regional sources. Under the rapidurbanization and industrialization of the PRD region in recent decades, this trend will probablypersist for the foreseeable future [Louie et al., 2008]. The box-plots of ozone trends as observed indifferent sites in Hong Kong as depicted in Figure 27, show the regional nature of the photochemicalozone problem. Amongst the four fixed network monitoring stations, O 3 concentrations were higherin rural than in urban sites (Figures 26 & 27). Nitrogen monoxide (NO) from vehicle exhaust wouldremove some ambient O 3 (http://www.info.gov.hk/gia/general/200411/24/1124240.htm), while90

CHAPTER 3 - ASIAbiogenic emission (~10% in Tap Mun, Yuan et al. 2006a) would enhance O 3 formation. These twoprocesses explain the higher O 3 concentration in rural sites.Visibility impairment is usually more severe during the winter than in the summer [Wang,2003]. During winter, the northeast monsoon facilitates long-range transport of regional pollutants toHKSAR [Louie et al., 2005b; Guo et al., 2009]. Land-sea breeze circulation would further trap andaccumulate air pollutants in the PRD region [Lo et al., 2006; 2007], resulting in higher air pollutantconcentrations. Winter accounts for ~80% of high PM days [Huang et al., 2009] but O 3concentration is highest in autumn when more sunlight is available for photochemical formation ofthis pollutant. The southwest monsoon in summer, in contrast, brings in fresh air to HKSAR and thehigh rainfall help washing away air pollutants in the atmosphere [Wang, 2003; Louie et al., 2005b].Particulate and photochemical smog problems in summer usually occur with typhoon episodeswhen the outskirt subsidence of airflow restricts the dilution and dispersion of air pollutants in thePRD region [Huang et al., 2009].Figure 25 - Concentration of sulphur dioxide, nitrogen oxides, ozone, respirable suspended particulates, and finesuspended particulates at Central/Western, Tsuen Wan, Tung Chung andTap Mun Air Quality Monitoring Stations from 1998 to 200891

CHAPTER 3 - ASIAFigure 26 - Box plots of ozone concentrations at Central/Western, Tsuen Wan, Tung Chung, and Tap Mun Air QualityMonitoring Stations from 1998 to 2008. The boundaries of the box represent the 25 th and 75 th percentiles, the line within thebox represents the median, the error bars illustrate the 10 th and 90 th percentiles, and the dots indicate outlying points.Note: An outlier is a point which falls >1.5 times the interquartile range above the third quartile or below the first quartileFigure 27 - Vehicle kilometres travelled (VKT) and sulphur dioxide (SO2), nitrogen oxides (NOX) respirable suspendedparticulates (PM10), volatile organic compound (VOC), carbon dioxide (CO2), and carbon dioxide equivalent (CO2-e) emittedin HKSAR from 1990 to 200792

CHAPTER 3 - ASIARelationships of the trends to regulationsThe Air Pollution Control Ordinance empowers the HKSAR Government to establish AirQuality Objectives (AQO) and to control air pollution from industry, commercial operations, andconstruction work [Trumbull, 2007]. To improve local air quality, the HKSAR Government hasintroduced a wide range of control measures (e.g. increase fuel efficiency, reduce consumption ofpollutant-emitting products, restricted emissions, etc.) since 1990 in order to reduce emissions frommotor vehicles (PM 10 and NO X ), power plants, industrial, commercial (SO 2 ) and VOC sources (seeGuo et al., 2004a andb;http://www.epd.gov.hk/epd/english/environmentinhk/air/prob_solutions/vocs_smog.html fordetails). These control measures have effectively reduced local emission of these pollutants (~50%reduction in SO 2 , NO X , and PM 10 and ~34% reduction in VOCs) despite the increase in VKT (~50%)and energy (~20%) and electricity consumption (~70%) over the years (Figures 24 & 27). In additionto local emission measures, the HKSAR Government and Guangdong Provincial Governmentreached a consensus in April 2002 to prevent air quality from further deterioration and, in thelong-term, to achieve good air quality for the Pearl River Delta region. Specifically, this consensusaims to reduce the regional emission of SO 2 , NO X , PM 10 , and VOCs by 40%, 20%, 55%, and 55%,respectively by 2010, using 1997 as the base year [Trumbull, 2007].Climatic change issuesLike other parts of the globe, HKSAR is undergoing climatic change in recent decades (ruraland urban temperature increased by 0.2ºC/decade and 0.6ºC/decade, respectively) [Lam et al.,2006]. This climatic change is likely a result of the ~20% increase in greenhouse gases (carbondioxide (CO 2 = ~80% contribution; ERM 2000), methane (CH 4 ), nitrous oxide (N 2 O),hydrofluorocarbons (HFCs), perfluorocarbons (PFCs) and sulphur hexafluoride (SF 6 )) content in theatmosphere due to increased energy use in recent decades (increase in VKT, energy and electricityconsumption = ~50%, ~20% and ~70%, respectively, for HKSAR; Figure 27). Lam et al. [2006]discovered that the ozone concentration in Tung Chung was positively correlated with temperature,wind speed, and solar radiation. The increase in greenhouse gases is believed to trap solarradiation in the atmosphere which, in turn, raise air temperature and intensify photochemicalformation of smog, resulting in further deterioration of visibility at a rate of 1.9%/decade [Lam et al.,2006]. Wang et al. [2009a] further suggested that aerosols reflect and absorb solar radiations atEarth‘s surface, as well as modify cloud cover and other cloud properties, resulting in considerableuncertainty in the estimation of aerosol impacts on radiation.The United Nations Framework Convention on Climate Change (UNFCCC) and KyotoProtocol were extended by the Central Peoples' Government (CPG) of China to Hong Kong as of 5May 2003. As with other developing countries that have ratified the Kyoto Protocol, China (includingthe HKSAR) is not required to achieve any greenhouse gas (GHG) emission limits. Instead, it isrequired to submit national communications in accordance with the specific requirements of theProtocol.(http://www.legco.gov.hk/yr08-09/english/panels/ea/ea_iaq/papers/ ea_iaq0113cb1-531-4-e.pdf).A host of measures have begun to reduce the level of GHG emissions in Hong Kong.Measures include Buildings Energy Efficiency Funding Scheme and the Mandatory EnergyEfficiency Labelling Scheme, banning the construction of coal-fired power generating units, andproviding economic incentives to encourage development of renewable energy sources. At thesame time, policy measures to reduce energy intensity are being pursued to address GHGemissions from other major emission sources including the transportation sector and landfills.These include continuously extending the coverage of the public transport system (in particular therailway network), promoting the use of electric vehicles, and enhancing the utilization of landfill gasas an alternative fuel (http://www.info.gov.hk/gia/general/200911/04/P200911040130_print.htm).Notwithstanding the concerted efforts mentioned above, if more specific GHG mitigation measuresare put in place, more tangible rewards could be resulted.93

CHAPTER 3 - ASIAResearch projects on air quality in HKSARTo date, over 600 scientific articles and technical reports related to air quality in HKSAR/thePRD region, focusing on the techniques, source characterization and transport, ambientconcentrations, and effects on health and visibility, have been published (see Lee et al., 2009 forreview). In addition to routine air quality monitoring, the EPD has commissioned various researchprojects on air quality in HKSAR and the PRD regions(http://www.epd.gov.hk/epd/english/environmentinhk/air/studyrpts/air_studyrpts.html). Periodiccampaigns in PM 2.5 speciation (2000/2001 and 2004/2005) study, for example, were carried out tobetter understand the source apportionment of PM 2.5 in HKSAR [So et al., 2007; Guo et al. 2009].The EPD has been monitoring VOC speciation at Tung Chung AQMS, in which the data can beapplied to projects related to VOC source apportionment, temporal variation, etc.With an aim to enhance the air quality in the PRD region, the EPD commissioned two airquality feasibility studies in the 3rd quarter of 2007: (i) major industrial pollution sources study(http://www.epd.gov.hk/epd/english/news_events/press/press_071018c.html) and (ii) VOC andphotochemical ozone pollution study (http://www.epd.gov.hk/epd/english/news_events/press/press_070927a.html). In order to improve the overall air quality in the PRD region, the EPD hasworked closely with local and international scientists and academics to estimate the feasibility todevelop a cross-boundary air quality monitoring network [Lee et al., 2009].Apart from research projects, the EPD has developed various computer models, includingthe PATH (Pollutants in the Atmosphere and their Transport over Hong Kong) model to investigatethe transport patterns of aerosol pollutants and photochemical ozone problems [Louie et al., 2008]and, with the aid of Wang [2003], HK-WinHaze to calculate and visualize the extent of visibilityimpairment. These research projects and models highlighted the importance of collaboration amongHKSAR, mainland China, local, and international scientists and academics [Lee et al., 2009].Guangdong and Hong Kong Regional Cooperation EffortsThe HKSAR Government makes controlling both street-level air pollution and smog as highpriority. In particular, it has been working closely with Guangdong Provincial Authorities toimplement a joint plan to tackle the regional smog problem.(http://www.epd.gov.hk/epd/english/environmentinhk/air/air_maincontent.html). In December 2003,the two governments jointly created the PRD Regional Air Quality Management Plan (the"Management Plan") with the goal of meeting the emission reduction targets set in 2010. The PRDRegional Air Quality Monitoring Network, established under the Management Plan between 2003and 2005, is now in full operation and provides comprehensive and accurate air quality data, whichare made available to the public.(http://www.epd.gov.hk/epd/english/resources_pub/publications/m_report.html). The Network alsoevaluates the effectiveness of the air pollution control measures through long-term monitoring.Problems remainingNotwithstanding the considerable studies on air pollutions and the effectiveness of localemission control measures, HKSAR still suffers from elevated levels of air pollution [Leverett et al.,2007]. This implies the air quality of HKSAR is not only influenced by local emission sources, butalso strongly affected by regional contribution, especially during winter and typhoon episodes [Louieet al., 2005b; Huang et al., 2009]. Under the influences of global climate change, as mentionedabove, the extent of air quality deterioration and related health and environmental impacts inHKSAR and the PRD region will need to be studied further. In order to minimize air pollutionproblems in HKSAR and to improve the overall air quality in the PRD region, there is, as aconsequence, an emerging need to (i) conduct more scientific studies between academia andgovernment to fill knowledge gaps from previous studies (ii) integrate multi-pollutant emissionreduction policy framework based on sound science, including: establishment of mitigationmeasures in greenhouse gases, as well as reviewing (see ERM 2000 for details) and updating AQOperiodically(http://www.epd.gov.hk/epd/english/environmentinhk/air/air_quality_objectives/air_quality_objectives.html), and (iii) intensify cross-boundary collaboration with mainland China and foreign countries94

CHAPTER 3 - ASIAand fully implement all possible control measures [National Academy of Engineering and NationalResearch Council, 2008, Lee et al., 2009].3.7 JAKARTA, INDONESIAIntroduction and geographical information of the cityJakarta, the capital city of Indonesia is located in a low land area with an average height ofaround 7 m.s.a.l and centred at 6 o 12’ South latitude and 106 o 48’ East longitude with 661 km 2 of landarea (see Figure 28). Jakarta is bounded by a mountain range extending along the south coast ofthe western Java Island with the average height of 1500 m and the highest mountain named SalakMountain is 3019 m. The climate of the city is characterized by monsoons that bring about 2 majorseasons, the dry (centred in September-November) and wet (centred in January – March). In thedry season the southeasterly (SE) monsoon dominates while in the wet season the northwesterly(NW) wind dominates [Sofyan et al., 2007]. As commonly found in coastal areas, sea-land breeze isalso prevalent in Jakarta. The Salak mountain range, with an almost V- shape directed alongNortheast on one side and Northwest on the other, tends to modify wind direction surrounding thecity [Permadi and Kim Oanh, 2008].Jakarta is inhabitated by approximately 8.7 million people as of 2005 with the averagegrowth rate of 0.16 % from 1990 to 2005 [JBS, 2006]. Jakarta’s annual Gross Domestic Product(GDP) increased at a stable annual growth rate of approximately 9% from 1990 to 2005. Over thesame period, fuel consumption increased at an annual average of around 2.6%. Major fuels used byhouseholds are kerosene and LPG while for transportation gasoline and diesel oil are used. In theindustrial sector, diesel oil, coal, and natural gas are used. Number of motor vehicles population,which is a main source of air pollution in the city, has been increasing rapidly with an averageannual rate of around 15 %. Almost 50 % of motorized vehicles registered in Jakarta aremotorcycles that still consist of numerous polluting two-stroke motorcycles. Road capacity isinsufficient compared to the massive increase of vehicles, which leads to high traffic congestion andhence further urban air quality deterioration.Emission sources of air pollutantsInvestigation of pollution sources is one of the most important tasks in air qualitymanagement. Soedomo et al. [1992a] reported the first emission inventory of Jakarta, which wasreported for the base year of 1990 (Table 7). The emissions inventory includes five pollutants,carbon monoxide (CO), total hydrocarbon (THC), nitrogen oxides (NO X ), particulate matter (PM),and sulphur oxides (SO X ) from four sectors (industry, residential, solid waste burning, andtransportation). The transportation sector was the major contributor for all pollutants except for SO 2 ,for which industry was the major source. The residential sector was found to also contributesignificantly to PM emission.Japan International Cooperation Agency (JICA) and National Environmental ProtectionAgency (BAPEDAL) jointly conducted emission inventory for Jakarta and its surrounding cities forthe base year of 1995 [JICA, 1997]. The similar 5 target pollutants were addressed but not for allsectors. Note that, the mobile sources in JICA study include road transport, ships, and aircraft. Ahigher total emission was recorded in JICA’s study, which may reflect the increase in the emissionsduring the five-year period. Transportation remained the main source of air pollution. However, therelative contribution by industry was higher for PM and SO 2 as compared to the previous estimateby Soedomo et al. [1992a].Air Quality Monitoring Network (data availability)The air quality monitoring network of Jakarta is operated by Jakarta EnvironmentalProtection Agency (JEPA) and includes both manual and automatic monitoring stations. Theintermittent manual monitoring was initiated in 1986 at twelve monitoring sites that are operated ona rotational basis. Each station measures selected air pollutants for 24-hrs every eight days [ADB,2002]. In early 2002, continuous air quality monitors for ambient air quality at 5 (five) JEPAautomatic monitoring stations (JAF1, JAF2, JAF3, JAF4, and JAF5) began. All of these automated95

CHAPTER 3 - ASIAmonitoring stations are equipped to monitor CO, NO, NO 2 , SO 2 , PM 10 , and O 3 as well asmeteorology (wind speed and direction, temperature, relative humidity, and global radiation)producing 30-minute average data online. Methane (CH 4 ) and non-methane hydrocarbons (NMHC)are not monitored at any station. The operation and maintenance of the stations are handled by theRegional Center (RC) in JEPA, which calibrates the equipment once per year. Data is also sent toJEPA center in order to be converted to daily air pollution index (API). Daily API data is then sent to4 data displays automatically that are located at several public spaces.All of the automated stations are classified as general ambient stations that are not locatedat the curbside of main roads. Accordingly, JAF1 is located in a dense residential area while JAF2is located near a commercial area and between office buildings. JAF3 is located in an open spaceof mixed land use including commercial facilities and residential areas. Both JAF4 and JAF5 arelocated near the city center with dense population and road traffic. JAF5 is in the city park insidethe Senayan Sport Complex Stadium and JAF4 is in a municipality building complex [Permadi andKim Oanh, 2008]. Detail information of each monitoring station is given in Table 7.Table 7 - Information on air quality monitoring stations Source: Permadi and Kim Oanh, [2008]No Stations a Area Type LatitudeCoordinateLongitudeCoordinateHeightm ASL b1 JAF 1Municipality building 6° 12’53.28’’ 106°56’41.72’’ 6(East Jakarta)2 JAF 2Commercial and open 6° 09’ 12.54’’ 106° 51’ 22.56’’ 2(Kemayoran) c space3 JAF 3Open space (City Park) 6° 15’ 40.94’’ 106° 47’ 00.73’’ 23(Pondok Indah) c4 JAF 4Municipality building 6° 11’ 07.17’’ 106° 44’ 12.36’’ 7(West Jakarta)5 JAF 5(Senayan Sport)Sport complex 6° 12’ 53.28’’ 106° 48’ 18.43’’ 12a All five stations are of the general ambient typeMonitored parameters include CO, NO, NO2, SO2, O3, WS – Wind speed, WD – Wind direction, Temperature, Relative Humidityand Global radiation.b ASL : Above Sea LevelHeight of air intake: 3mc much missing dataAir pollution trend and status of JakartaJakarta experienced serious air pollution problems due to intensive industrialization,urbanization, and economic development. WB. [1997] reported the initial assessment of air qualityin Jakarta, Indonesia addressing concentrations of NO 2 , CO, O 3 and TSP during the period of 1981– 1993. Annual average NO X was reported around 20-160 µg/m 3 while its maximum 24-hrconcentrations were observed around 200-500 µg/m 3 . The annual values are well above thecorresponding National Air Quality Standard (NAAQS) of 100 µg m -3 and the 24-hr NAAQS of 150µg m -3 , respectively. Average 8-hour CO levels were reported around 3.5 mg m -3 in residential areaand 27 mg m -3 in a central commercial area, well above the WHO Air Quality Guideline of 10 mgm -3 . 24-hr average values of TSP were observed of 300-450 µg m -3 , which were well above thecorresponding NAAQS of 230 µg m -3 while the annual TSP averages in the most polluted areas (citycenter) were reported to be 5-6 times the national air quality standard of 90 µg m -3 . Ozoneconcentrations ranged from 2-15 µg m -3 for the annual mean and 86-200 µg m -3 for the highest 1-hrconcentration, which were within the NAAQS (annual: 50 µg m -3 and hourly: 235 µg m -3 ). Thus,photochemical smog pollution was not serious a problem at that time.More recent trends, for the period of 2001 to 2007, of annual average concentrations arereported in the Jakarta State of Environment Document [JEPA, 2008]. As seen in Figure 29, CO,NO 2 , PM 10 , and O 3 seem to follow similar variation patterns, i.e. decreases in recent years. This96

CHAPTER 3 - ASIAmay be indicating the improvement in transportation emissions that are related to the operation ofTrans-Jakarta busway, a rapid transit system started in January 2004 that links most of the mainroads in the city. Nevertheless, PM 10 levels are observed to be consistently above the WHOannual average guideline of 20 µgm -3 . The highest annual average of SO 2 was observed in 2004(110 µg m -3 ) exceeding the standard of 60 µg m -3 . Annual average O 3 in this period was consistentlyabove the standard of 50 µg m -3 , which indicates photochemical air pollution in the city.Figure 29 - Trends of air pollution in Jakarta. [modified from JEPA,2008]. Annual NAAQS: CO: na; PM10: 20 µg m -3[WHO, 2006]; SO2: 60 µg m -3 ; NO2: 100 µg m -3 ; O3: 50 µg m -3Suhadi et al. [2005] and Permadi & Kim Oanh (2008) provided a detailed study ofphotochemical smog pollution in Jakarta in relation to its precursors and meteorology. During theperiod of 1996 to 1998, the annual ozone averages in ambient stations located off the city centerhave exceeded the annual NAAQS and showed an increasing trend [Suhadi et al., 2005]. Frequentexceedances of the hourly NAAQS were also observed from 2002 to 2003 with over 450 hourlymeasurements or 0.7 % out of 66,000 hourly ozone measurements at the 5 stations [Permadi andKim Oanh, 2008]. Both studies suggested that the highest monthly average ozone occur during thedry season (September-November) and the lowest during the wet season (December-March). Thediurnal cycle of ozone in Jakarta and its precursors is clearly shown and is typical for polluted urbanareas [Permadi and Oanh, 2008].Air quality managementThis section highlights the attempts of the local government in implementing regulations andactions under the scheme of urban air quality management. During past decades, initiated by JEPA,many attempts have been initiated in order to improve air quality in Jakarta. Urban air qualitymonitoring stations have significantly improved by updating the monitoring method from rotationalmanual basis to the automated continuous monitoring systems with QA/QC. Air pollution Index (API)is used to display the results in public spaces to enhance public participation and awareness. Localgovernment is also working to reduce traffic congestion by improving the urban transportationsystem. Busway corridor VII – X has been built covering the entire city. This has been recognizedas the largest busway system in Asia and won a BAQ award in 2006. A rail-based Mass RapidTransit (Monorail) is still under construction. Intensive development of urban green space hasoccurred in recent years. Car free day programme has been campaigned intensively calling forpublic participation in more sustainable ways. Unleaded gasoline has been promoted in the citysince June 2000 with support from the government and industry [JEPA, 2008]. As of January 2008,the government is said to be enforcing the Euro 2 standard [MOE, 2003].Climate change issueAccording to IDRC – EEPSEA [2009], Jakarta is one of the most vulnerable cities to climatechange in Southeast Asia. Therefore, climate change issue has attracted more attention from thelocal government and scientists. However, the studies on ambient levels and the emissions ofgreenhouse gases or other climate forcing agents such as black carbon in the city are still in the97

CHAPTER 3 - ASIApreliminary stage. Kosasih [2004] presented the total CO 2 emitted from the transportation sector inJakarta, which is around 12 million tons/year while the residential sector contributes around 10million tons/year. So far, there has been no other reported climate forcing agent inventories forJakarta. Several potential Clean Development Mechanism (CDM) projects have been proposedsuch as CDM for Trans-Jakarta bus way (Bus Rapid Transport) project, clean buses, reducingmethane emission from municipal solid waste disposal site, and fuel shifting in residential sector[Pelangi Foundation, 2007].Recorded research on air pollution in the cityThere have been several research projects on air pollution in Jakarta since early 1990’s.MOE initiated the “blue sky” project focusing on implementation of emission controls of stationaryand mobile sources. In 1993, the Urban Air Quality Management in Jakarta (URBAIR) project wasimplemented to collect benchmark information on air quality in Jakarta [WB, 1997]. The studyincluded monitoring, modelling, and cost benefit and health assessment. It provided the firstrecorded emission inventory of air pollutants for Jakarta and applied a simple dispersion model. Thestudy on the Integrated Air Quality Management for Jakarta Metropolitan Area was carried out in1997 by Japan International Cooperation Agency [JICA, 1997] providing more detailed informationon emission inventories and dispersion modelling of Jakarta and the surrounding area. AsianDevelopment Bank sponsored the RETA Project on the “Study on Air Quality in Jakarta: FutureTrends, Health Impacts, Economic Value, and Policy Options” with a focus on projected healthassessment of air pollution in Jakarta region [ADB, 2002]. A more recent study was conductedunder the project of Asian Regional Research Programme in Energy, Environment, and Climate,Phase III (ARRPEEC III) coordinated by the Asian Institute of Technology and implemented by theInstitut Teknologi Bandung that aimed to develop scenarios of emission reductions of air pollutionand GHG from the transportation sector. A number of different research projects conducted byuniversities and research institutions are also available (see publications cited above).Recent air quality problemsPhotochemical smog has become more serious in Jakarta in recent years [Permadi andOanh, 2008] with frequent exceedances of NAAQS. Higher emission strength of ozone precursors(NO X , VOC) and favourable meteorological conditions are the driving forces to the increased O 3concentrations. Ozone concentrations are expected to remain the same or even get worse sincethere is no reported systematical attempt to formulate mitigation strategies. This may endanger thehuman health and agricultural crops of Jakarta since ozone is toxic and phytotoxic.Particulate matter pollution remains a major air quality issue in Jakarta as well. Effortsshould be put forward to monitor fine particles as well as their composition.The transportation sector is still considered the main contributor of emissions in Jakarta. Thenumber of two-stroke motorcycles in Jakarta is reduced every year but high levels of pollutants arestill observed. The difficulties may be due to high growth rate of vehicle population in Jakarta, whichwas almost 100% from 1995 to 2000. The government has also promoted the Trans-Jakartabusway, unleaded gasoline, and bio-fuel that may improve air quality. New sources such as openbiomass burning in areas surrounding the city have not been addressed adequately. Therefore,more comprehensive air pollution research needs to be carried out in order to provide relevantinformation for decision makers.3.8 MANILA, PHILIPPINESManila demography, topography and climateThe Manila Metropolitan Area, or Metro Manila, is the administrative region encompassingthe city of Manila, the national capital of the Republic of the Philippines. Metro Manila is a megacitymade up of 17 cities and municipalities of the National Capital Region (NCR). A 2007 governmentcensus estimated its population at approximately 12 million over an area of only 636 km 2 . The 2009UN population estimate for the same region was over 20 million and projected to increase to 29.5million by 2025. Manila proper (i.e., excluding surrounding cities and municipalities) has one of the98

CHAPTER 3 - ASIAhighest population densities of any major city in the world, currently estimated to be 46,000people/km 2 [Columbus, 2003].Metro Manila is the political, economic, social, and cultural center of the Philippines and isone of the more modern metropolises in Southeast Asia. Metro Manila’s topography ranges fromflat fluvial and deltaic lands in the west to the rugged Marikina Valley and Sierra Madre mountains inthe east. It is bordered by the larger and more fertile plains of Central Luzon to the north. MetroManila is bisected by the Pasig River and sandwiched by two bodies of water: Manila Bay to thewest and the Laguna de Bay to the southeast (see Figure 30). Lying as it does within the Philippinearchipelago very close to the equator at 14˚N, 121˚E, Metro Manila’s climate is hot and humid, witha temperature range of about 20-38 ˚C. It has a distinct, short dry season from January throughApril, and a longer wet season from May through December.Figure 30 - Metro Manila RegionAir quality in Metro ManilaIn 1999, the Philippine government established the Clean Air Act (CAA), which set legallimits for ambient levels of major air pollutants to protect public health and the environment. Table 8presents the air quality standards set by this legislation.99

CHAPTER 3 - ASIATable 8 - National Ambient Air Quality Guideline Values (NAAQGV) for Criteria PollutantsAir Pollutant Averaging Time Standard in µg/m 3Total Suspended Particulates(TSP)DailyAnnual23090Particulate Matter Less than 10 µ(PM10)DailyAnnual15060Sulphur Dioxide(SO2)DailyAnnual18080Nitrogen Dioxide(NO2)DailyAnnual150150Ozone(O3)1 Hour8 Hours14060Carbon Monoxide(CO)1 Hour8 Hours35,00010,000Lead(Pb)3 MonthsAnnual1.51.0The Department of Environment and Natural Resources (DENR) operates a network of 44air quality monitoring stations in 15 regions located throughout the country. A network of tenautomated continuous monitoring stations was implemented by DENR within Metro Manila tomeasure criteria pollutants (PM 10 , SO 2 , NO 2 , CO and O 3 ) and meteorological data [EMB, 2006], ofwhich two stations could also measure PM 2.5 , methane, non-methane hydrocarbons, benzene,toluene, and xylene [ADB and CAI-Asia, 2006]. The stations were operational from 2004-2005;however, operations were halted due to a contractual dispute. In addition to the monitoring activitiesof the DENR, the Philippine Nuclear Research Institute (PNRI) of the Department of Science andTechnology (DOST) monitors PM 10 and PM 2.5 at three sites in Metro Manila.Of the different types of air pollution prevalent in Metro Manila, PM has received the greatestattention. Figure 31 presents annual average TSP concentrations in Metro Manila for the period1987-2008 as measured by the Environmental Management Bureau (EMB) of the PhilippineDepartment of Environment and Natural Resources (DENR). The data show that substantialprogress has been made in reducing TSP concentrations since 1995, despite the fact that annualmean concentrations still exceeded the national standard of 90 µg m -3 .Figure 31 - Average annual TSP concentrations in Metro Manila for the period 1987-2008. Red line indicates NAAQGV valueof 90 µg m -3 . Sources: ADB, 2002 (data from 1987-2001); CAI-Asia, 2009 (data from 2002-2008)Figures 32 and 33 show the average annual PM 10 and PM 2.5 concentrations at the PNRIsampling sites in Metro Manila from 2001 to 2008. Although PM 10 is consistently below thenational standard of 60 µg m -3 , it exceeds the WMO Air Quality Guidelines (AQG) of 20 µg m -3 . ThePhilippines currently does not have a PM 2.5 standard. However, PM 2.5 annual meanconcentrations exceed the WHO AQG of 10 µg m -3 .100

CHAPTER 3 - ASIAFigure 32 - Annual mean concentrations of PM10 inMetro Manila for the period 2001-2008.Red line: NAAQGV value of 60 µg m -3 ;Green line: WHO AQG of 20µg m -3 [CAI-Asia, 2009]Figure 33 - Annual mean concentrations of PM2.5for the period 2001-2008.Red line indicates WHO AQG of 10 µg m -3[CAI-Asia, 2009]The Manila Observatory (MO) participated in the Asian Regional Air Pollution ResearchNetwork (ARPET), coordinated by the Asian Institute of Technology [Oanh et al., 2006]. DuringPhase 1 of ARPET (2001-2004), MO collected over a thousand PM 2.5 and PM 10 samples at fivesites in Metro Manila using both MiniVol and dichotomous samplers. Table 9 presents the results ofARPET Phase 1 for Metro Manila for both the dry and wet seasons.Table 9 - ARPET Phase 1 Results for Metro Manila averaged over all samples. [Oanh et al., 2006]RangePMSizeSeason Number of Samples Mass in µg m -3PM2.5 Dry 407 44PM10 Dry 122 54PM2.5 Wet 376 43PM10 Wet 136 55From the data in Table 9, it is clear that seasonal average PM 2.5 concentrations in MetroManila already exceed the current WHO 24-hour AQG of 25 µg m -3 in both dry and wet seasons,while seasonal average PM 10 concentrations are almost within the WHO 24-hour AQG of 50 µgm -3 in both dry and wet seasons.Limited monitoring of other criteria pollutants (SO 2 , NO 2 , and O 3 ) has been conducted inMetro Manila. The concentrations of SO 2 and NO 2 are below the NAAQGV at the monitoringstations, while O 3 concentrations exceed the one-hour guideline on most days at one stationbetween 2001-2002 [World Bank, 2002], but are relatively low elsewhere.Sources of air pollutants and emission inventoriesThe DENR conducted a national emissions inventory of air pollution sources in 1990 andsubsequently updated the inventory in 2001, 2004, and 2006 as mandated by the Philippine CleanAir Act. The emissions inventory includes criteria pollutants such as PM, SO 2 , NO X , CO, and VOCs.According to the latest (2006) inventory, the transportation sector is the major source of air pollutioncontributing about 65% of the pollutants, while 21% is from stationary [point] sources and 14% fromarea sources, with total national emissions of seven million tons per year from all sources [DENR,2009]. The same emissions inventory shows that CO has the biggest pollution load contribution of50%, followed by NO X at 15%, VOCs at 15%, PM at 11%, and SO X at 9%. CO emissions arecaused by the increasing population of gasoline-powered vehicles, which include cars (13.6%) andmotorcycles/tricycles (47.9%) [DENR, 2009].101

CHAPTER 3 - ASIAControl strategiesAmong the environmental success stories in the Philippines is the phase-out of lead ingasoline that was implemented after 1993, as summarized in Table 10. Control strategies for othercriteria pollutants have also been implemented in the Philippines with very limited success, assummarized in Tables 11-12. (Source: World Bank: Philippines Environment Monitor, 2002).Table 10 - Lead phase-out in the Philippines. Source: World Bank: Philippines Environment Monitor, 2002DateApril 1993February 1994January 1995April 2000December 31, 2000ActionLead content in gasoline was reduced from 0.6 g/l to 0.15 g/lIntroduction of unleaded gasoline (ULG)Oil Deregulation Law lowered tax on ULG, and priced it cheaper than leadedgasoline; ULG sales roseLeaded gasoline phased out in Metro ManilaLeaded gasoline completely phased out in the Philippines.Table 11 - PM control options and their use in the Philippines(Source: World Bank: Philippines Environment Monitor, 2002)102

CHAPTER 3 - ASIATable 12 - NOX Control options and their use in the Philippines(Source: World Bank: Philippines Environment Monitor, 2002)Table 13 - SO6 Control options and their use in the Philippines(Source: World Bank: Philippines Environment Monitor, 2002)The EMB through its regional offices is in charge of monitoring industrial firms and issuingnotices of violations (NOVs) and permits-to-operate (POs). According to DENR [2009], from2005-2007 a total of 18,697 firms were monitored. Within that three-year period, a total of 1,676NOVs and 24,391 POs were issued DENR [2009].The Land Transportation Office (LTO) enforces compliance with emission standards formotor vehicles. EURO 2 standards for new motor vehicles took effect in 2008. A Motor VehicleInspection System (MVIS) project is currently being implemented so that all private motor vehicleswill only be allowed renewal of annual registration upon inspection by the LTO or other authorizedprivate motor vehicle inspection center. In addition, vehicles observed to be emitting excessivesmoke while operating in any public highway may be subjected to an emission test byproperly-equipped law enforcers and other deputized agents. Total annual apprehensions ofsmoke-belching vehicles exceeded 15,000 in both 2005 and 2006, but declined to under 12,000 in2007 [DENR, 2009].Another major control strategy is the Alternative Fuels Programme, which was intended tofacilitate the country’s attainment of 60% energy self-sufficiency by 2010, as well as to curb airpollution. The Programme has four major subprogrammes: Biodiesel, Bioethanol, Natural GasVehicle Programme for Public Transport (NGVPPT), and the Autogas Programme. Othertechnologies advocated under the Programme are hybrid, fuel cell, hydrogen, and electric vehicles.In addition, the Bio-fuels Act of 2006 has enabled a bio-diesel blend of 1% by volume to be availableat all gas/pump stations nationwide since 2007. Likewise, a gasoline fuel consisting of 10%bio-ethanol blend (E10) by volume is distributed and sold by all oil companies and dealers in thecountry [DENR, 2009].103

CHAPTER 3 - ASIAMetro Manila Air Quality Improvement Sector Development PlanBeginning in 1999, the Asian Development Bank agreed to loan the Philippine governmentapproximately $296 million to address air pollution in Metro Manila. This programme, known as theMetro Manila Air Quality Improvement Sector Development Plan, was intended to help thegovernment implement its 1998 Air Quality Action Plan (AQAP). While the programme helped toeliminate lead from gasoline in Metro Manila, it did not fully achieve other intended outcomes, whichincluded: (i) mitigating air pollution from mobile sources; (ii) mitigating air pollution from stationarysources; (iii) improving fuel quality; (iv) reducing emissions from vehicular use; (v) reducing trafficcongestion and improving traffic flow; (vi) strengthening ambient air quality monitoring, evaluation,and reporting; (vii) intensifying public awareness; (viii) monitoring coordination and implementationof the AQAP; and (ix) strengthening the capacity of relevant institutions.The programme’s complexity demonstrated design inadequacies during its implementation,a problem compounded by the lack of permanent staff positions at the DENR to sustain theprogramme efficiently and to maintain the air quality monitoring network.Climate change policiesThe Philippines is a signatory to the UN Framework Convention on Climate Change andratified the Kyoto Protocol in 1998. The National Action Plan was formulated in 1997, whichprovides guidance on prioritizing mitigation measures. In 2006, the DENR launched the PhilippineGreenhouse Gas Accounting and Reporting Programme (PhilGARP) to encourage the privatesector to undertake voluntary actions on the inventory of greenhouse gas (GHGs) and identificationof mitigating measures. The President of the Philippines signed the Climate Change Act of 20 in2009, which will establish a commission to develop a Framework Strategy on Climate Change andto formulate and implement a National Climate Change Action Plan (see DENR website).Future challengesThe contribution of the transport sector to the worsening air pollution requires immediateaction and poses an increasing threat to the health of the city dwellers. Unsustainable urbanizationhad led to growing traffic congestions necessitating transport planning and management [DENR,2009].Among the challenges facing the Philippines in improving air quality in Metro Manila are: 1)the lack of trained technical personnel, particularly in regulatory agencies; and 2) the difficulty offostering a culture that can address the complex social, organizational, scientific, and engineeringissues involved in improving air quality amid a scarcity of financial resources. The implementation ofexisting regulations is thus rendered extremely difficult without adequate monitoring andgovernment oversight and enforcement. Complex and overambitious programmes are not likely towork under these circumstances. Rather, a step-wise approach with realistic goals is more likely tosucceed, especially if it is aimed at increasing capacity within the research, educational, industrial,policy, and regulatory sectors in the Philippines.3.9 OSAKA, JAPANIntroductionOsaka is located in south-central Japan (Osaka Prefectural Government: 34.67°N,135.53°E). The population of Osaka Prefecture was about 8.8 million, and the population of theKansai area (Osaka Prefecture and the five surrounding prefectures) was about 22.7 million in 2008(Figure 34).Because the Osaka Plain is narrower than the Kanto Plain and is surrounded by mountains,the geographically complex distribution of urban areas, mountains, and sea plays an important rolein local atmospheric circulation [Ohashi and Kida, 2001]. In summer, sea breezes blow from OsakaBay to the Kyoto basin (southern part of Kyoto Prefecture) and the Nara basin (northern part ofNara Prefecture) until late afternoon.104

CHAPTER 3 - ASIAFigure 34 - NOX emission rates over the East Asia (left) and Kansai area (right). Numbers indicate six prefectures in theKansai area (1, Osaka; 2, Hyogo; 3, Kyoto; 4, Shiga; 5, Nara; 6, Wakayama).Red points in the right panel show the locations of monitoring stations in the AEROS networkEmissions sources and regulationsIn the entire Kansai area, motor vehicles accounted for 75%, 50%, 42%, 15%, and 5% ofemissions of CO, PM 2.5 , NO X , VOCs, and SO 2 , respectively, in 2000 [Table 14, Kannari et al., 2007].Large point sources were the largest contributors to SO 2 emissions (~46%) and other transportsector sources (mostly ships) were the second largest contributors (37%). Stationary evaporativesources were the largest contributors to VOCs emissions (~48%) and biogenic sources were thesecond largest (35%).Table 14 - Source contributions to NOX, SO2, PM2.5, VOC, and CO emissions (Gg/year) over the Kansai area in 2000estimated in the EAGrid inventory (Kannari et al., 2007)NOX SO2 PM2.5 VOC COLarge point sources 85 24% 42 46% 4.0 21% 2.9 1% 148 19%Other point sources 16 5% 11 11% 1.2 6% 1.6 0% 19 2%Motor vehicles 149 42% 4.2 5% 9.7 50% 79 15% 598 75%Off-road vehicles 24 7% 0.5 0% 0.8 4% 3.0 1% 26 3%Other transport 78 22% 34 37% 3.8 20% 3.7 1% 8.9 1%Stationary evaporativesources248 48%Biogenic 179 35%Total 352 92 20 517 800Trends of ozone and its precursorsWakamatsu et al. [1996] reported that maximum hourly oxidant concentrations in the OsakaBay area showed a decreasing trend during 1978–1990 (Figure 35). By contrast, increasing trendswere observed in the inland Kyoto and Nara areas. The locations where daily maximum oxidantconcentrations were observed tended to move further away from the emission area of the OsakaBay area to the Kansai area. Concentrations of non-methane hydrocarbons (NMHCs) greatlydecreased during the 1970s and 1980s, whereas NO X concentrations did not show any significanttrend. As a result, ratios of the NMHCs concentration to the NO X concentration decreased. Thedecrease of NMHCs indicates a decrease in photochemical reactivity, which leads to a decrease inthe photochemical reaction rate. By contrast, the increase in the NO X /NMHCs ratio caused anincrease in the O 3 formation potential. Higher concentrations of O 3 are usually observed near theshore in the morning, and as the sea-breeze penetrates inland, the high O 3 concentration area also105

CHAPTER 3 - ASIAmoves inland and O 3 concentration increases with time. Under these meteorological conditions, thedecrease in the NMHCs/NO X ratio caused the location where maximum O 3 is typically observed tomove inland in the Kansai area.Figure 35 - Trends in maximum hourly oxidant concentrations during 1978–1990 in the Osaka Bay area (filled circles) andthe Kyoto and Nara areas (line). Reproduced by permission of Elsevier from Wakamatsu, S., T. Ohara, and I. Uno (1996),Recent trends in precursor concentrations and oxidant distributions in the Tokyo and Osaka areas[Wakamatsu et al., 1996]Sadanaga et al. [2008] analyzed weekday–weekend differences in O 3 , NO X , and NMHCsconcentrations in Tokyo and Osaka from 2001 to 2004. In Osaka, weekend O 3 concentrations werefound to be greater than weekday concentrations during most periods, although the precursorconcentrations were higher on weekdays. Weekday O 3 concentrations in Osaka decrease owingto the reaction of O 3 with NO, which results in higher O 3 but lower O X (the sum of O 3 and NO 2 )concentrations on weekdays than on weekends.Research projectIn spring, the Osaka area is generally located closer to the center of an anticyclone thanTokyo. Thus, the temperature is higher and photochemical air pollution occurs more often in Osakathan in Tokyo. Also, because the Osaka area is closer to the Asian continent than Tokyo, it is morestrongly affected by the outflow of Asian pollutants. To investigate the structure and mechanism ofspringtime photochemical air pollution in the Osaka area, intensive measurements of O 3 fromaircraft were carried out by the National Institute of Environmental Studies and the Osaka CityGovernment in March of 2001 and 2003 [Itano et al., 2006]. The concentrations of particles in theultrafine to supermicron size range were also measured in March 2003 [Hasegawa et al., 2007].These studies showed that transboundary air pollution contributes significantly to the springtime O 3[Itano et al., 2006] and aerosol [Hasegawa et al., 2007] concentrations in the Osaka MetropolitanArea in spring. By combining filter sampling of particulate matters in the boundary layer at300–1300 m over Osaka Prefecture with a numerical simulation, Hasegawa et al. [2007] concludedthat soil dust particles as well as black carbon (BC) particles are transported from the Asiancontinent to Japan (flight ME0307 in Figure 36).106

CHAPTER 3 - ASIAFigure 36 - Mass concentrations of carbonaceous and ionic species of total suspended particles during level flights madeat 300, 600, and 1300 m on 19 March 2003. ME0307, ME0308, and ME0309 correspond to flights (~2 h) that took off at 08:30,12:30, and 16:30 local time, respectively. Reproduced by permission of Elsevier from Hasegawa, S., S. Wakamatsu,T. Ohara, Y. Itano, K. Saitoh, M. Hayasaki, and S. Kobayashi (2007), Vertical profiles of ultrafine to supermicron particlesmeasured by aircraft over Osaka metropolitan area in Japan [Hasegawa et al., 2007]Traffic-related air pollutants have been monitored near major roads at 10 sites in the Kanto,Chubu, and Kansai areas by the Ministry of the Environment of Japan (MOE) since 2005 [e.g.,Naser et al., 2009]. Nitrogen oxides (NO X ), suspended particulate matter (SPM, 100% cut-offaerodynamic diameter at 10 mm), PM 2.5 , and BC were instantaneously and continuously monitoredat four stations at various distances (about 5, 35, 70, and 150 m) from each of the target roads.Naser et al. [2009] used these measurement data and a Gaussian plume model to derive theemission factor of BC to SPM at roadside sites. They obtained good agreement between theobserved and estimated ratios with a proportionality constant (BC/SPM) of 0.4, indicating that thesame BC/SPM emission ratio.MOE also measured VOCs (63 compounds) at four urban sites in the Kansai areathroughout 2004 [Sasaki and Sakamoto, 2007]. Five samples were collected at each site in everyseason. The analysis, made by using a Chemical Mass Balance model, suggested that gasolinevapour and gasoline vehicle exhaust were significant sources of atmospheric VOCs.Remaining problemsThe effects of regulations of NO X , VOCs, and PM emissions on O 3 and PM concentrationsshould be assessed by using the monitoring data from MOE and various research groups. Also,source contributions of O 3 and PM should be evaluated by analyzing these measurement data incombination with model simulation. Because the Osaka area is closer to the Asian continent thanTokyo, it is more strongly affected by the outflow of Asian pollutants. More systematic assessmentof the effect of transboundary pollution on pollutants in the Kansai area is needed.3.10 PEARL RIVER DELTAIntroduction and specific features of the cityThe Pearl River Delta (PRD) situated at 21 ° 17´–23 ° 56Ń and 111 ° 59´–115 ° 25É is connectedto the South China Sea. The PRD region covers 4.17 × 10 4 km 2 with a population of over 38 million.Most of the PRD region includes Guangdong Province and two Special Administrative Regions of107

CHAPTER 3 - ASIAHong Kong and Macau. The PRD region mainly consists of floodplains between the Nan LingMountains to the North and the South China Sea to the south, except in Hong Kong, where morethan 50% of the land is mountainous area. The region has a subtropical marine monsoon climatewith an annual average temperature of 22.8°C and average relative humidity of 68%. A largenumber of rainfalls occur annually due to its subtropical location and weather conditions and theannual rainfall at the urban area is over 1,600 mm. The annual variation of rainfall can greatly affectair quality in the whole PRD region because rainfall is a major pathway to remove air pollutants [Waiand Tanner, 2005; Chan and Yao, 2008].The PRD region has been a leader in economic reform, economic development andurbanization in Guangdong and China under the "opening up" policy since 1978. The GDP in thePRD excluding Hong Kong and Macau increased at a rate of about 19.6% annually and reachedmore than 3.11 × 10 6 million yuan in 2007 (Figure 37) (Guangdong Statistical Yearbook). Thevehicular population in Guangzhou and Shenzhen increases by 10% per year over the last decade.The expansion of the economy in this region causes higher demands for energy, mobility, andcommunications. As a consequence, both coal combustion and traffic exhaust cause seriousphotochemical smog and particulate pollution from the urban to regional scale.Figure 37 - GDP of Guangdong Province. (Guangdong Statistical Yearbook)Emission sources of air pollutantsAccording to the report by Chan and Yao [2008], the annual SO 2 emission in Guangzhouexhibits a decreasing trend from 2000 to 2005, and was 14.9 × 10 4 tons in 2005. In Hong Kong, SO 2emissions slightly increased from 5.65 × 10 4 in 1999 to 6.76 × 10 4 tons in 2002 and increased byabout 40% in 2004 due to the increased emissions from public utilities. Wang et al. [2005] estimatedthat 32.9% of SO 2 concentrations were due to the power plant emissions and the transportationsource was the main contributor to NO X , CO, and O 3 concentrations accounting for 34.2%, 33.1%,and 17.8% of their total concentrations, respectively. NO X concentrations were rather uniformlydistributed in the different sites of Guangdong Province [Zhang et al., 2008a]. The annual NO Xemissions varied from 8.65 to 10.2 × 10 4 tons from 1999 to 2005 in Hong Kong. The publicelectricity generation accounted for about 50% of the total NO X emissions in 2003 [Chan and Yao,2008].Limited data of both ambient VOCs concentrations and VOC emission inventories in thePRD region is available. Receptor models were used to apportion the source of ambient VOCs inthe PRD region. The results showed that VOC emission sources include vehicle exhaust, liquidpetroleum gas leakage, paint vapours, biomass and coal combustion. Vehicle exhaust was thelargest source of VOCs, contributing to more than 50% of ambient VOCs at urban sites, and liquidpetroleum gas leakage also played an important role [Liu et al., 2008].108

CHAPTER 3 - ASIAData available on air pollutantsComprehensive and accurate information on air quality in the PRD is available from the PRDRegional Air Quality Monitoring Network, which has 16 automated air quality monitoring stationsjointly established by the Guangdong Provincial Environmental Monitoring Centre and theEnvironmental Protection Department of the Hong Kong Special Administrative Region. Thirteenstations are operated in Guangdong while three stations are located in Hong Kong. Theconcentrations of air pollutants like SO 2 , NO X , NO 2 , O 3 , RSP (Respirable Suspended Particulate,PM 10 ), and CO are regularly and continuously monitored. On November 30, 2005, the PRDRegional Air Quality Monitoring Network allowed for daily publication of the Regional Air QualityIndex on the Internet (http://www-app.gdepb.gov.cn/raqi3/RAQI_en.htm)The Programme of Regional Integrated Experiments of Air Quality over Pearl River Delta(PRIDE-PRD) provides a comprehensive understanding of the air pollutants. More speciesincluding NO, NO 2 , NO Y , VOCs, SO 2 , CO, CO 2 , O 3 , HONO, and PM 2.5 as well as the sizedistribution, chemical composition, and optical property of particles were measured. These data canhelp to appraise the air quality situation and pollution problems in the PRD region. The results arepublished in a special issue of Atmospheric Environment (42(25), 2008) for PRIDE-PRD 2004 aswell as on Atmos. Chem. Phys. for PRIDE-PRD 2006.The status and trend of the pollutionPrevious studies showed that PRD is suffering from a serious air quality degradationproblem, which is characterized by the coexistence of the high levels of O 3 , PM 2.5 , NO X , and SO 2(Zhang et al., 2008a). High aerosol concentration events are observed in the MODIS aerosol opticaldepth data (Figure 38) [Wu et al., 2005]. The high concentration of aerosol particles is a majorreason for the low visibility and haze day occurrence remain very high, e.g. around 150 days year –1between 1980 and 2006 (Figure 39) [Wu et al., 2005; Deng et al., 2008].Figure 38 - MODIS measurements of aerosol optical depth form on 2 November (upper panel) and 3rd November(lower panel) 2003 at 8am local time. The white circle indicates the location of Guangzhou [Wu et al., 2005]109

CHAPTER 3 - ASIAFigure 39 - A 52-year observation of haze day occurrences in Guangzhou [Deng et al., 2008]As seen from Figure 40, the annual average SO 2 concentration in Guangzhou and in HongKong increased from 1999 to 2005. At the same time, decreases in CO concentrations wereobserved at Guangzhou and Tsuen Wan, but not at other sites in Hong Kong. There was noincrease in the annual averages of O 3 and (NO 2 +O 3 ) concentrations at the three sites in Hong Kong(Figure 41) [Chan and Yao, 2008]. The average O 3 exhibited maximum concentrations during thefall in Hong Kong and O 3 levels increased during the days with intense solar radiation, light winds,and the presence of unique wind convergence circulation [Wang et al, 2001]. The experimentsrevealed O 3 precursor emissions from vehicle exhaust are likely one of the reasons for high O 3concentrations in the PRD and a regional air quality model indicated the ozone formation wascontrolled by ambient VOCs [Zhang et al., 2008a and b].Figure 40 - (a) SO2, (b) NO2, and (c) CO concentrations in the PRD region from 1995 to 2005 [Chen and Yao, 2008]110

CHAPTER 3 - ASIAFigure 41 - O3 and (NO2 +O3) concentrations in the PRD region from 1999 to 2005 [Chen and Yao, 2008]Relationships or the trends to regulationsThe Hong Kong and Pearl River Delta Pilot Air Monitoring Project was initiated in May 2002.The Project aimed to study the cause of ground-level O 3 pollution in Hong Kong and to study thecharacteristics of fine particles (PM 2.5 ) in the Pearl River Delta. The project aims to reduce regionalemissions of SO 2 , NO X , RSP, and VOCs by 40%, 20%, 55% and 55%, respectively, by 2010 in PRDregion, using 1997 as a baseline year. Enhanced control measures of the HKSAR is implemented,including encouragement to replace light diesel buses with ones using clean fuel, reduce VOCemissions from the printing process and consumer products, reduce emissions from power stations,and enhance energy efficiency of buildings. In 2007, the Environmental Protection Bureau (EPD) ofHong Kong and Guangdong announced the implementation framework for the Emissions tradingPlot Scheme for Thermal Power Plants in the PRD region.The results for 2008 from the regional Air Quality Monitoring Network indicated that the airquality in PRD region showed improvement in 2008. The overall average annual concentration ofSO 2 and RSP decreased by 19% and 11%, respectively, as compared to the 2007 levels. Theannual averages of NO 2 and O 3 remained the same.(http://sc.info.gov.hk/gb/www.epd.gov.hk/epd/textonly/english/news_events/press/press_090422a.html). The SO 2 levels in Guangzhou decreased from 0.077 mg m –3 in 2004 to 0.046 mg m –3 in 2008and were lower than the national ambient air quality standard for SO 2 at grade II (annual average 60µg m -3 ) except in 2004. The annual average NO 2 concentration had a slightly decrease during2000–2008 (Figure 42).Figure 42 - The change of the annual average concentration of SO2 and NO2 in Guangzhou from 1999 to 2007 [GuangzhouEnvironmental Buttetion, 1999–2008 Guangzhou Environmental Protection Bureau, Guangzhou, www.gzepb.gov.cn]. Thered dashed up and bottom lines indicate the grad II (60 mg/m 3 ) and grad I (20 mg/m 3 ) Chinese National Ambient AirStandards for SO2, respectively. The blue dashed line is the grad I/II (40 mg/m 3 )Chinese National Ambient Air Standard for NO2111

CHAPTER 3 - ASIAClimatic change issuesThe regional climate in the PRD is sensitive to changes from urban expansion (Lin et al.,2007). Climate data of south China indicates the rapid urbanization contribute a warming trend inwinter temperature by approximately 0.32°C/10y from 1960 to 1996 (Liang and Wu, 1999). Figure43 shows that that the annual mean temperature had an increasing trend from 1990 to 2000 (Chenet al., 2006). The urban heat island (UHI) effect is very important to global change. The UHI effecthas become more prominent in areas of rapid urbanization (e.g., Shenzhen) in the PRD region. It’sreported that the total annual contribution of land use/cover changes in Shenzhen (0.042 °C) toincreases in temperature is greater than that in the PRD (0.027 °C) (Chen et al., 2006). CO 2 ofcoal-fired power units remained quite constant at about 84–88% of the total GHG emissions from1990 to 2005 (Leung et al., 2009).Figure 43 - Fluctuations of yearly and monthly mean temperature form 1989 to 2000 in the PRD region [Chen et al., 2006]Research projects on air quality of PRDFrom 2005 to 2007, a project on the effect of atmospheric haze on the deterioration ofvisibility over the PRD was implemented to study the formation mechanism and forecast method ofhaze. The Programme of Regional Integrated Experiment of Air Quality over Pearl River Delta(PRIDE-PRD) was developed by Peking University. The objective of PRIDE-PRD is to investigatemajor air pollutants and provide a comprehensive understanding of the air pollution in the PRD.Gaseous pollutants (SO 2 , O 3, and NO X ) and particulate matter (PM 10 and PM 2.5 ) were measured in2004. The study measured high levels of O 3 that exceed China’s National Standard at grade II(hourly maximum 160 µg/m 3 ), throughout the PRD region. The research of PRIDE-PRD 2006indicated that hydroperoxides play an important role in the formation of secondary sulphate in theaerosol phase. A major project “Synthesized prevention techniques for air pollution complex andintegrated demonstration in key city-cluster region” (3C-STAR, 2006–2010) was funded to build upthe capacity of regional air pollution control and to establish regional coordination mechanism.Problems remainingReduced pollutant concentrations show that both the Guangzhou governments and HongKong are committed emission reduction efforts for further improving the regional air quality. But fineparticle is still a serious pollution problem as well as O 3 . Aircraft measurements showed a highlevel of O 3 pollution in the PRD region (Wang et al., 2008). The previous study from PRDcampaigns (PRD2004 and PRD2006) indicated concurrent high concentrations of O 3 and PM 2.5throughout the PRD region. Such high concentrations of both primary and secondary pollutantscause an “air pollution complex” problem. Furthermore the high concentration of aerosol particles isa major cause for the low visibility and the grey haze that has been a regional problem of concern.Both the Guangzhou governments and Hong Kong are committed to continuing to enhanceemission reduction efforts to further improve regional air quality.112

CHAPTER 3 - ASIA3.11 SEOUL, KOREAIntroduction and Specific Features of the CitySeoul is a megacity located at the heart of the Korean Peninsula. It stretches from 37° 41’ Nto 37° 25’ latitude and from 126° 47’ E to 127° 11’ longitude at the level of the temperate zone. Thecity is also located in the middle of several major Northeast Asian Metropolises, such as Tokyo,Beijing, and Shanghai. It is at the eastern end of the Asian land mass and therefore experiencescoastal climate as well. Several mountain peaks of historical significance surround the city of up to500 meters or more above sea level. The major river that bisects Seoul into a North and Southregion is the Hangang River, the location of post-Korean War economic development.Surrounding Seoul are Incheon Metropolitan City and Gyeonggi province, which areemerging megacities as well (Figure 44). Combined, this region comprises 12 % of the area ofKorea, yet holds 47% of Korea’s population, ranking as the second most populated megacity in theworld (next to Tokyo, Japan), with a combined population of approximately 24 million as of 2008.The population explosion in Seoul was due to the city’s rapid urbanization and can be traced backto before Seoul hosted the 1988 Summer Olympics. South Korean Industry was already in the gripof a technological revolution before it hosted the Olympics. GDP expanded by around 10% per yearfrom the mid 1980’s to the early 1990s due to the creation of one of the largest steel plants in theworld (POSCO), drastic demand in foreign and local car sales (Hyundai, Kia, DaeWoo),revolutionizing the electronics industry (Samsung, LG), and establishment of numerous localmanufacturing companies. Opportunities for modern livelihood, employment, and a better life leadto migration of people into the region.As skyscrapers, condominium, and industrial plants established, Seoul developed into aheat island like other urban centres around the world. Also, like other urban cities, Seoul hasexperienced its fair share of pollution as it has developed. With this, the City has enacted severalpolicies to counter pollution and is one of the earliest respondents to clean air initiatives among themajor cities in Northeast Asia.Figure 44 - Map of South Korea and its Megacity Study sites (Seoul, Incheon, and Gwangju)113

CHAPTER 3 - ASIAEmission sources of air pollutantsDuring the post-Korean War economic development period, South Korea’s urban air qualitystructure was characterized by high-energy intensity associated with primarily fossil fuel energyconsumption. As a consequence, urban air pollution caused by the rapid proliferation of cars,growth in heavy and chemical industries, the increasing severity of traffic congestion, and otherurban issues stressed the cities during South Korea’s high-growth eras. The Clean Air ConservationAct of 1990 was in its initial stage during the post-Korean War economic development. Until 1994,The United Nations Environment Programme (UNEP) reported Seoul to have serious problems withhigh sulphur dioxide and lesser, though increasing, problems with nitrogen oxides (1). Poor airquality is evident from high PM 10 , SO 2 , and CO concentration since 1991. Greenhouse gasemissions have also been a concern, both regionally and globally. Korea has made various effortsto improve the air quality through, among others, supplying clean energy (natural gas, low-sulphurfuel, etc.) and strengthening emission standards for industries and motor vehicles. These effortsmarkedly reduced air pollutant emission for SO 2 and CO in major cities. However, the air pollution inSeoul is higher than any other metropolis in the nation, requiring special management. To date, theconcentration of vehicles already exceeds the environmental capacity. In 2002, road transportaccounted for 77% of all PM 10 (and PM 2.5 ) emissions in Seoul (2, 3). Moreover, periodical Asiandusts storms and haze events add to the existing air quality problem by aggravating PM 10 levels,making the atmosphere more deleterious to health. Increasing growth of air pollution relatedsickness and death has become a major issue. As of 2003, the number of premature deaths due toPM 10 in the Seoul Metropolitan area reached 10,000 per year (4) and research data (5) hasestimated the social costs to be 8 billion USD.Data available on air pollutantsSince the implementation of the Clean Air Conservation Act, the Ministry of Environment(MOE) has established city air quality monitoring sites all throughout Korea. Annual Mean CriteriaPollutant data starting from 1991 are available for public use. In 1991, there were 20 city air qualitymonitoring stations in Korea that measure PM 10 , SO 2 , O 3 , NO 2 , and CO. As of 2007, the citymonitoring stations have increased to 226. The Ministry on Environment has established andoperated Air Pollution Observation Networks that can be classified into six types: suburbanatmosphere monitoring, density monitoring of various substances, hazardous air pollutantmonitoring, photochemical air pollutants monitoring, acidic deposition monitoring, and earthatmosphere observation, while municipal and provincial governments operate air pollutionobservations that are classified into four types: urban atmosphere monitoring, roadside atmospheremonitoring, monitoring of heavy metal in the atmosphere, and visibility observation. Cityatmosphere observation networks represent 55% of the total observation networks. The datacollected by the nationwide air pollution observation network is processed by the NationalAtmosphere Pollution Information Management System (NAMIS, collaboratively operated byMinistry of Environment and the Environment Management Corporation) and is utilized as aresource for regulation of the atmosphere in order to understand air quality, analyze theeffectiveness of environmental regulations, and preserve the health of citizens. Moreover, amongthe data collected by National Atmosphere Pollution Information Management System, the changein concentration of five standard air pollutant (SO 2 , CO, NO 2 , PM 10 and O 3 ) is disclosed to the publicin real time on the air pollution homepage (www.airkorea.or.kr ).Data status and the trend of pollutionThe concentration trends for SO 2 , NO 2 , CO, PM 10 and Pb were evaluated based on thepublished data by the Ministry of Environment, Republic of Korea (6), the latest being in 2008, with2007 as the most recent data. The annual average SO 2 levels has dramatically decreased by 20ppbv from 1991 to 1993, and has been decreasing by 2.5 ppbv per year from 1993 to 2000 (Figure45). It has maintained an annual average value of 5 ppbv from 2001 to 2006, though it hasincreased by 1 ppbv in 2007. The annual CO levels has also decreased by 0.11 ppmv per year from1991 to 2002 (Figure 46).114

CHAPTER 3 - ASIAFigure 45 - Annual Mean concentrations of SO2 in Seoul (1991-2007)Figure 46 - Annual mean concentrations of CO in Seoul (1991-2007)It was maintained at 0.6 ppmv from 2003 to 2006 and has increased by 0.1 ppmv in 2007.From 1991 to 2007, the decrease in annual mean NO 2 levels is strongly followed by an increase inannual mean O 3 levels, except in 2006-2007 (Figure 47). In particular, the annual mean increase of1.21 ppbv/yr by NO 2 was followed by the linear decreasing trend of 0.57 ppbv/yr by O 3 since 1998 to2004. But on the following years, both NO 2 and O 3 trends has been increasing, which may beattributed to the increasing complexity of the urban atmosphere.Figure 47 - Annual mean concentrations ofNO2 and O3 in Seoul (1991-2007)115

CHAPTER 3 - ASIAIn the case of PM 10 , a series of stringency has been implemented since the annual meanstandard was implemented in 1993. The annual mean dropped from 80 µg m -3 in 1993, to 70 µg m -3in 2001 and lastly, to 50 µg m -3 in 2007 (Figure 49). The annual mean standard for PM 10 wasexceeded in 2001-2002 and in 2007.Particularly in 2002, the annual mean PM 10 concentration has almost levelled off with the1995 PM 10 , mainly due to the extraordinarily severe Asian dust event that happened on that year.For Pb, the annual mean levels have always been met, and the trend linearly decreased from 1993to 2004 at 0.01 µg m -3 yr -1 (Figure 50). This is expected trend due to the worldwide shift to unleadedgasoline.Figure 48 - Frequency of Ozone exceedances per year in SeoulFigure 49 - Annual mean concentrations of PM10 in Seoul (1995-2007)116

CHAPTER 3 - ASIAFigure 50 - Annual mean concentrations of Pb in Seoul (1991-2007)Figure 51 - Increasing trend in Number of Vehicles (1991-2007), in relation to the trend inPM10 concentrationRelationship of the trends to regulationsSince the enactment of the Clean Air Conservation Act in 1990, most of the criteriapollutants have decreased dramatically in order to comply with local standards. The SO 2 annualaverage in Seoul has experienced improvement from 43 ppbv in 1991 to nearly 6 ppbv in 2007(Figure 45). As seen in Figure 45, the annual WHO air quality standard for SO 2 of 19 ppbv was notmet in Seoul until 1995. Since then, SO 2 levels have gradually decreased until it levelled off at 5ppbv. The same is true with CO levels, but although the two pollutants have experienced aremarkable decrease through the years, PM concentrations experienced a steady increase from1998 to 2002. Although PM concentrations were declining following the implementation of the CleanAir Conservation Act until 1998, when rising vehicle emissions and dust and sandstorms (DSS)originating from Asian continent increase PM concentrations. In line with this, the Seoulmetropolitan area Air Quality Management Plan (SAMQP), which is now in its second phases, wasenacted in 1999 to reduce emission levels of major pollutants such as PM 10 and NO X to half theircurrent levels by 2014, to improve the metropolitan air quality to the level of advanced countries,and mandates a total local discharge amount management system, a transferable discharge permitsystem, and the mandatory purchase of low emission vehicles as its major components. Althoughthe general trend on the number of vehicles has been increasing, the annual PM 10 level hasdeclined as of 2003 (Figure 51), which is believed to be a result of SAMQP’s comprehensive policyfor air quality improvement. In general, PM 10 concentrations increase temporarily during the spring117

CHAPTER 3 - ASIAdue to yellow sand and low relative humidity. In the case of O 3 and NO 2 (Figure 47), the annualmean has started to increase due to the increase in the number of automobiles in Seoul during thelast five years. However, the frequency of ozone exceedances (Figure 48) events is more importantrather than changes in annual average of ozone concentrations because exposure to high ozoneconcentrations during the short term poses a threat to humans. The status of ozone exceedanceevents during the short term (0.1 ppm/h), which is not shown here, shows that exceedance eventshave been increasing, from 343 exceedances at 49 stations nationwide in 1996 to 1,090 at 220stations in 2006 (9).Climatic change issuesThe Korean peninsula has experienced its fare share of climate change trends along withthe rest of the world. It has experienced a 0.23°C rise in annual mean temperature per decade, anincreasing diurnal range, and more frequent heavy rain events in the recent years (10, 11). Theincrease in average temperature and precipitation over the Korean peninsula has widened theregional and seasonal weather differences, making the weather more like a subtropical climate.In terms of emission inventories, the National Institute of Environmental Research conductsregular inventories of several air pollutants by emission sources (point, area, and mobile sources)for Seoul. Emission deductions of major air pollutants (NO X , SO X , PM 10 and VOCs) are betterachieved when mobile sources are more augmented (9). Moreover, to evaluate the air qualityimpacts of these emission reductions, the EPA’s Models-3/Community Multi-scale Air Quality(CMAQ) modelling system is used. The impact of changes in air quality on human health is thenestimated using EPA’s Environmental Benefits Mapping and Analysis Programme (BenMAP). Onthe average, health benefits could be more substantial if pollutants other than PM 10 are givenattention. Furthermore, aside from CO 2 , other greenhouse gases such as NO X and CH 4 should alsobe analyzed for emission closure because they also have a high potential for global warming.Research Projects on Air quality of Seoul Metropolitan City and emerging megacitiesThe MOE aimed to lower ozone concentrations by reducing two major sources, volatileorganic compounds (VOCs) and nitrogen oxides (NO X ) using a stepwise improvement of urban airquality. The need for further air quality improvement led the MOE to conducted an initialperformance assessment of measures for improving air quality of Seoul, including the attachment ofexhaust emission reduction devices, upgrading the quality of paint supplied in the city, reducing nonpoint pollution sources of VOCs, and attaching additional devises for VOC retrieval. Themetropolitan atmospheric environment management plan aimed to reduce the air pollutionemissions in the metropolitan area to half of 2001 levels by 2004, while reducing PM 10 density to 40µg m -3 , and NO 2 to 22 ppb. The provision of eco-friendly fuels was expanded through improvingindustrial heavy oil, increasing provisions of low-sulphur gasoline, and promoting the use ofbiodiesel for automobiles running on diesel. Lastly, the MOE developed "city climate maps" whichshow at a glance green areas, hot spots of air pollution, as well as wind flow through urban streetcanyons to alleviate the urban heat island phenomenon.The MOE has also addressed the emerging air quality problems associated with long-rangetransboundary air pollution, revising the Clean Air Conservation Act, which became a legal basis forformulating a "Dust and Sandstorms (DSS) countermeasure commission" and a "comprehensivemeasure for preventing damage by DSS”. Stations were built to conduct research on the riskassessment of particulate matter and other harmful substances in dust and sandstorms.Furthermore, Korea, China, and Japan have been cooperating since 1996 through the jointResearch on Long Range Transboundary Air Pollutants in the Northeast Asia to carry out a jointstudy to measure the amount of long-range transboundary air pollutants (especially sulphur andnitrogen) into Northeast Asia.The budget allotment for air quality improvement by the MOE increased from 10.1% in 2003to 10.8% in 2007 (6). The budget in 2007 for air quality was increased by 5.8% compared to the2006 budget allotment. This budget is mainly allocated for the project on the improvement ofmetropolitan air quality, countermeasures for climate change, and measures for the prevention andcontrol of DSS.118

CHAPTER 3 - ASIAAside from Seoul, intensive research studies on chemical components of urban air wereconducted in adjacent urban cities (i.e., Incheon) during August to October 2004 to supplement theair quality information in the Seoul Metropolitan City. Using a high time resolution measurementmethod for organic carbon and elemental carbon, it was identified that elevated concentrationevents were brought about by transported aerosols in the direction originating from high traffichighways (12). Lim, 2005 retrieved the NO 2 using Imaging Differential Absorption Sprectroscopy(I-DOAS) Technique to understand the rate of plume emission coming from two stacks of a thermalpower plant near the Seoul Metropolitan City area (13). In 2005, Kim et al studied the fineparticulate matter characteristics and its impact on visibility in Seoul and Incheon (14).In emerging megacities such as Gwangju, South Korea, Asian DSS and haze events arealso compromising air quality. Several studies have been conducted to study the aerosolcharacteristics and surface radiative forcing components during a dust outbreak in Gwangju (15) aswell as some aerosol optical properties and satellite parameters (16, 17, 18). For instance, during asevere haze and smoke episodes in Gwangju, aerosol optical properties and microphysicalparameters were determined from the ground using a multi wavelength Raman Lidar. Two differentaerosol types were identified based on the variability of optical characteristics for different air massconditions and indicated that there is a distinct light absorbing characteristics (based on Singlescattering albedo , SSA) for different haze aerosols from China (haze) and from Siberia (forest-firesmoke). The features of two air mass characteristics (haze and smoke) are now understood interms of their optical properties and microphysical parameters (16).Problems remainingMuch effort has to be made to improve air quality in metropolitan areas (Seoul City,Gyeonggi province, and other metropolitan cities) in order to meet the more stringent air qualitystandards that were applied in 2007 to Particulate Matters (PM 10 : from 70 µg m -3 to 50 µg m -3 ) andNitrogen dioxide (NO 2 : from 50 ppb to 30 ppb). Although the MOE has launched an emission capsystem, the effectiveness will not be seen for a few more years. Still, there is much to focus on,especially the inventory of VOCs in the Seoul urban area, which is notorious for serious air pollutionissues. Although the Clean Air Conservation Act was enacted in 1990, certain revisions were donein order to tailor-fit it to the provincial and municipal jurisdictions for better implementation and toKorean atmospheric conditions. Lastly, the severity of the effect DSS and other long-rangetransported pollutants needs to be further studied in order to create more efficient countermeasuresduring the events.5.12 SHANGHAI, CHINAIntroductionShanghai is a coastal megacity in the southeast of China and is located between 30 o 40’ Nto 31 o 53’ N latitude and between 120 o 51’ and 122 o 12’ longitude. The administration area ofShanghai is 6340.5 km 2 , with a width of 100 km in the east-west direction and a length of 120 km inthe south-north direction. Shanghai is in the front of the alluvial plain of the Yangtze River Delta.The city is embraced by a river basin: the East Sea lies to the east, the Yangtze River lies to thenorth, the Hangzhou Bay to the south and Jiangsu and Zhejiang provinces border Shanghai to thewest. Shanghai experiences a subtropical monsoon climate with plenty of rainfall. Shanghai’sgeographic location and climate condition favour the dispersion of air pollutants.As one of the first regions in China to initiate a market economy, Shanghai has beenexperiencing very rapid economic growth since the 1980s. The GDP of Shanghai has beenincreasing at a rate of more than 10%/yr within the last 15 years and the GDP per capita exceeded10,000 USD for the first time in 2008 [Shanghai Statistical Yearbook, 2009]. The energyconsumption increased at an average rate of 6% per year correspondingly, reaching 10% per yearthe past three years. The increase in energy consumption resulted from rapid economic growth,which is followed by the dramatic increase of air pollutant emissions, and deteriorated air quality inShanghai. Additionally, the increase of vehicles has also played a significant role in decreasing theair quality in Shanghai.119

CHAPTER 3 - ASIAEmission inventories of major air pollutantsThe emission of SO 2 and particulate matter, the vehicle number, and GDP of Shanghai overthe past years are shown as Figure 52. The emission of SO 2 seemed to be stable in the past withsmall fluctuations, even though GDP was growing. However, emission of SO 2 has increased sincethe beginning of the 21st century. From 2003 to 2007 emission of SO 2 increased by 14.3% to 497.8kt. The emission of particles decreased gradually in past years. From 2003 to 2007, emission ofparticles decreased by 50.8% to 106 kt. In addition, the vehicle number increased dramatically withthe large growth of GDP in the last decades, especially since this century, which resulted in theincrease in emissions of NO X and volatile organic compounds (VOCs). According to the study byChen et al. [2009], the NO X emission had increased to 599.7 kt in 2007, and the vehicular emissionaccounted for 14%. More importantly, the contribution of vehicular emission to NO X in urban areaswas much larger than that of the whole city, accounting for 40.8%. Obviously, vehicular emission isthe largest source of NO X in urban area of Shanghai. The VOCs emission was 597.4 kt in 2007 andvehicle emissions accounted for 14.5%, whereas in the case of urban area, the vehicular emissionaccounted for 18.8%.Figure 52 - Variation of emissions of SO2 and particles, the vehicle number, andGDP in Shanghai from 1991 to 2007 [Municipal Environmental Protection Bureau,The communiqué on the Environmental Status of Shanghai City, 1991~2008]Based on the study by Chen et al. [2009], the major SO 2 emission sources are power plants,dispersed combustion processes of industry, and industry furnaces, accounting for 46%, 27%, and10%, respectively. Similar to SO 2 , power plants are also the most important source of NO X (34%).Dispersed combustion processes of industry and vehicle emissions contribute 18% and 17% to thetotal NO X emissions, respectively. In the case of PM 10 , the largest source is dust resuspension frommotorways, accounting for 44%, followed by uncovered yard, dispersed combustion processes ofindustry, and power plants. Additionally, solvents and other product contributes the largest portionof the VOC emissions, accounting for 28%, followed by industrial processes, 23%, and vehicleemissions, 15%.In summary, power plants, industry, and vehicular emissions are the major sources of airpollutants in Shanghai and the contribution of vehicular emissions to NO X and VOCs emissions ismuch larger in urban area than in rural area. Beside these pollution sources, dust is one of the mostimportant sources of PM 10 .The ambient air qualityThe profile of annual average concentrations of SO 2 , NO 2 , CO, and PM 10 in Shanghai from2002 to 2007 is shown in Figure 53. The SO 2 annual average concentration was lower than thenational ambient air quality standard (NAAQS) for SO 2 at grade II (60 µg m -3 ) during these six years.120

CHAPTER 3 - ASIAHowever, the SO 2 annual average concentration kept on increasing gradually from 2002 and theconcentration in 2007 increased by 83.3% of the 2002. The trend of SO 2 pollution should beimproved by 2010, with the completion of the desulphurization policy of the 11 th -5-years-plan ofChina. The NO 2 annual average concentration seems to be stable between 2002 and 2007, and islower than the NAAQS for NO 2 at grade II (80 µg m -3 ). The CO annual average concentrationdecreased during this period except in 2005 when the concentration reached 1.81 mg m -3 , muchhigher than that in other years. The CO annual average concentration in 2007 had decreased15.9% compared to 2002 levels. The PM 10 annual average concentration seems almost to bedecreasing, except that there was a slight increase from 2006 to 2007, which could have been dueto the sharp increase of construction for the 2010 EXPO. The PM 10 annual average concentration islower than the NAAQS for PM 10 at grade II (100 µg m -3 ). Obviously, particle control policy has beeneffective.Figure 53 - Profile of the annual average concentrations of primary pollutants in Shanghai from 2002 to 2007 [MunicipalEnvironmental Protection Bureau, The communiqué on the Environmental Status of Shanghai City, 2002~2008]The Shanghai air pollution index (API) at grade II (100) demonstrates the improvement in airquality. The days with good and excellent rate of API was more than 85% of the year, continuouslyfor the past six years and the API did not exceed 100 for 324 days in 2008. However, the API isdetermined by the concentration of SO 2 , NO 2 , and PM 10 , which does not reflect the secondarypollutant, which are even more important than the primary pollutants in megacities with rapideconomic development and sharp increases in number of vehicles. The high level of ozone duringthe summer, poor visibility, and the high frequency of acid rain, almost all result from the secondarypollutants [Chen et al., 2009].The 2007 monthly average ozoneconcentration in Shanghai at 14:00 areshown in Figure 54. Ozone pollution is veryhigh during the summer, with the highesthourly average concentration of ozonereaching 380 µg m -3 , which is much higherthan the NAAQS at grade II of 200 µg m -3 .Based on the hourly data in July 2007, theconcentration of ozone exceeded 200 µgm -3 for 22 days [Chen et al., 2009].Furthermore, the high levels of ozone arealways accompanied with highconcentration of fine particles. The highlevel of ozone therefore cannot be the onlycause of adverse effects on public healthand ecosystems. The strong oxidativeFigure 54 - The 2007 monthly average ozone concentration at14:00 in Shanghai121

CHAPTER 3 - ASIAatmosphere, which is favourable for the formation of fine particles, results in the decrease ofvisibility and the transformation of S(IV) to S(VI) causing the occurrence of acid rain [Tang et al.,2006]. Consequently, high ozone levels during the summer have been one of the complex problemsfor the further improvement of the air quality in Shanghai.Air pollution control countermeasuresShanghai municipal government (SMG) has carried out many air pollution control measuresthrough three 3-year action plans to improve the air pollution of the city since 2000. Theimplementation of the first 3-year action plan included several measures that were carried outsuccessively, such as promoting cleaner fuels, shutting down the Yangshupu coal/gas factory,extending the scope of applying natural gas, the use of low sulphur coal, conducting an integratedenvironmental pollution control policies for industrial parks, closing or suspending the factories withlarge influence to the air quality.After the implementation of the second 3-year action plan, according to the nationalenvironmental protection requirements and the necessity of the city environmental protection work,Shanghai municipal government implemented the desulfurization project for all coal fired powerplants and closed or stopped small coal fired units with a total capability of 695 MW from 2006 to2008. All these measures largely decreased the emissions of SO 2 and PM 10 . In addition, during thisperiod, the prevention and control of industrial pollution and the comprehensive improvement of themajor industrial parks was announced and carried out and the pollutants emission from Jinshanpetroleum industry and Gaoqiao petroleum industry were checked.Measures were also implemented to deal with vehicle emissions. Shanghai adopted thevehicular emission standards equivalent to Euro-II and Euro-III in 2003 and 2006, and the oneequivalent to Euro-IV on November 1, 2009 [Huang et al., 2008]. Additionally, in order to reduce theemission from in-use vehicles, “Limits for exhaust pollutants from in-use vehicle equipped ignitionengine in short transient loaded mode (DB31/357-2006)” and “Limits for exhaust smoke from in-usevehicle equipped with compression ignition engine under lug-down test (DG31/379-2007)” wereimplemented. Those vehicles that could not meet the emission standards equivalent to Euro I wereforbidden to drive in the city center during the daytime, and this area was expanded in August of2009. These control measures for vehicles are favourable for the improvement of the air quality inthe Shanghai urban area.Besides the control measures mentioned above, Shanghai municipal government launcheda project for environment comprehensive improvement and landscaping of the city for the EXPO2010, which led to a large drop in the level of particles. Shanghai environmental protection agencyorganized a project “The control measures for the air pollution during the period of EXPO 2010”.This project focused on local air pollution controls. Meanwhile the large pollution sources of theYangtze River Delta were also asked to reduce their emissions selectively [Chen et al., 2007a],aimed at improving the air quality during the period of EXPO 2010.Climatic change issuesThe increase in temperature in China was similar to the global average of 0.74˚C over thepast 100 years (China's National Assessment Report on Climate Change, 2007; IPCC 2007).According to the study by Li et al. [2008], the CO 2 emission from energy transformation accountedfor 43%, and was followed by industry at 29% and transportation at 18% [Chen et al., 2004, 2007b;Dolf and Chen, 2001; Wang et al., 2001]. Suggestions on the bio-energy research, such asincreasing biomass resources, improving biomass processing techniques, and energy transferefficiency, are recommended, in order to reduce the CO 2 emissions in Shanghai.SummaryThe air quality in Shanghai is gradually improving. The annual average concentrations ofprimary pollutants are near the NAAQS at grade II over the past years. The good and excellent rateof the API was larger than 85% continuously for the past six years. However, the secondarypollution caused by the photochemical transformation of the primary pollutants is increasing and notconsidered in the API. The high level of ozone in the summer time, the decrease of the visibility, and122

CHAPTER 3 - ASIAthe high frequency of the occurrence of acid rain, suggests there is still much research andemission control strategies needed to further improve the air quality in Shanghai.3.13 TOKYO, JAPANIntroductionTokyo is located in the southeastern part of central Japan (Tokyo Metropolitan Government:35.69°N, 159.69°E). The population of the Tokyo Metropolis was about 12.7 million, and thepopulation of the Kanto area (Tokyo Metropolis and the six surrounding prefectures) was about 41.9million in 2008. The Greater Kanto Area is one of the world’s largest megacities in terms ofpopulation [Gurjar et al., 2008].The southeastern part of the Kanto area, called the Kanto Plain (150 × 150 km 2 ), faces thePacific Ocean and to the west and north is surrounded by mountains exceeding 1000 m in height.Local meteorologyFrom late spring to mid-summer, a sea-land breeze circulation pattern driven by the heatingand cooling of the Kanto Plain during daytime and nighttime, respectively, often prevails [Kondo etal., 2006]. On clear, calm days, southerly winds typically dominate during the daytime, and air isbrought from over the ocean to the Tokyo Metropolis and further northward. From midnight to earlymorning, weak northerly winds dominate and air is transported from the northern Kanto Plain to theTokyo Metropolis.In winter, northwesterly winds associated with a strong Siberian high-pressure systemgenerally dominate over the Japanese islands. As a result, air is transported primarily from thenorthwest, over the northern part of the Kanto Plain and then to the Tokyo Metropolis. When thenorthwesterly winds dominate, sea-land breeze circulation pattern does not develop.Emissions sources and regulationsKannari et al. [2007] developed an emission inventory, called EAGrid, which estimatedhourly emissions over all of Japan with a horizontal resolution of approximately 1 km for each monthin 2000. Over the Kanto area, motor vehicles were estimated to account for 80%, 52%, 43%, 17%,and 5% of emissions of carbon monoxide (CO), particulate matter with a diameter of less than 2.5µm (PM 2.5 ), nitrogen oxides (NO X ), volatile organic compounds (VOCs), and sulphur dioxide (SO 2 ),respectively, in 2000 (Table 15). Large point sources made the largest contributions to SO 2emissions (~62%) and stationary evaporative sources were the largest contributors to VOCemissions (~63%).Table 15 - Source contributions to NOX, SO2, PM2.5, VOC, and CO emissions (Gg/year) over the Kanto areain 2000 estimated in the EAGrid inventory [Kannari et al., 2007]NOX SO2 PM2.5 VOC COLarge point sources 164 28% 95 62% 6.7 22% 5.5 1% 230 17%Other point sources 30 5% 22 14% 2.3 7% 5.8 1% 29 2%Motor vehicles 256 43% 7.2 5% 15.9 52% 144 17% 1059 80%Off-road vehicles 80 14% 1.8 1% 2.3 8% 10 1% 0 0%Other transport 60 10% 27. 18% 3.5 11% 4.2 0% 11 1%Stationaryevaporative sources535 63%Biogenic 148 17%Total 589 153 30 854 1330123

CHAPTER 3 - ASIAEmissions of NO X from motor vehicles have been regulated by the Automobile NO X Lawsince 1992 and PM emissions have been regulated by the Automobile NO X –PM Law since 2001.Regulations implemented in 2005 (“new long-term regulation”) are stricter than the European UnionEuro V emission standards for NO X and PM and regulations implemented in 2010 (“post newlong-term regulation“) are stricter than the Euro VI standards. The Ministry of the Environment ofJapan (MOE) (2005) estimated that from 2000 to 2005 (2010) NO X emission rates decreased by16% (41%), and PM 2.5 emission rates by 42% (77%) over Japan. In addition, MOE estimated thatNO X and PM emission rates will be reduced by 68% and 93%, respectively, from 2010 to 2020[MOE, 2008a]. Emissions of primary pollutants should be greatly reduced within the next 10 years,a prediction that should be validated by the monitoring data.Emissions of VOCs from stationary evaporative sources have been regulated by the AirPollution Control Law since 2004. MOE [2008b] estimated that VOC emission rates from stationaryevaporative sources decreased by 20% from 2000 to 2005 over Japan.Monitoring networksMOE has operated an atmospheric pollutants measurement system (AtmosphericEnvironmental Regional Observation System, AEROS) over Japan since the 1970s. Hourlyconcentrations of NO, NO 2 , SO 2 , O 3 , CO, non-methane hydrocarbons (NMHCs), and suspendedparticulate matter (SPM) are observed by this system at about 300 sites in the Greater Kanto Area(Figure 55).Figure 55 - NOX emission rates over East Asia (left) and the Tokyo Metropolitan Area (right). Numbers indicate the TokyoMetropolis and the six prefectures in the Kanto area (1, Tokyo Metropolis; 2, Kanagawa; 3, Chiba; 4, Saitama; 5, Gunma; 6,Tochigi; 7, Ibaraki). Red points in the right panel show the locations of monitoring stations in the AEROS networkTrends and air quality standardsFrom 1991 to 2004, both NO X and NMHCs showed continuous decreases [TokyoMetropolitan Government, 2005] (Figure 56) as a result of the regulations to reduce emissions ofthese species. Their concentrations were considerably lower in the Kanto area than wereconcentrations in megacities in the developing countries of Asia in the late 1990s to early 2000s[Molina and Molina, 2004]. Despite decreases in these O 3 precursors, the average O 3 concentrationin the Kanto area during the summer (June–August) increased during 1991–2004. According toJapanese air quality standards (AQSs), hourly O 3 mixing ratios should be lower than 60 ppbv. Thefrequency with which the concentration exceeds the Japanese AQS for O 3 has increased,124

CHAPTER 3 - ASIAespecially since 2000. For example, the fraction of days when the hourly O 3 mixing ratio exceeded120 ppb (i.e., 2 × AQS) has increased (Figure 57) [Kondo et al., 2010].Figure 56 - Annually averaged hourly mixing ratios of NOX (black, left axis) and total NMHCs (gray, right axis) measured atabout 30 sites in Tokyo from 1991 to 2004. The original data used in this figure were provided by theNational Institute for Environmental StudiesFigure 57 - Three-month summertime (June–August) percentages of days with hourly O3 mixing ratios exceeding 120 ppbat 41 sites in Tokyo (filled circles) and 57 sites in Saitama (open circles). The original data used in this figure were providedby the National Institute for Environmental StudiesMOE has measured PM 2.5 concentrations at 12 (8), 14 (8), and 5 (0) monitoring stations atroadsides and in urban and suburban areas, respectively, in Japan (Kanto) since 2001 [MOE,2008c; 2009]. From 2001 to 2008, PM 2.5 concentrations decreased by ~35% and ~25% at roadsideand urban stations (Figure 58). Minoura et al. [2006] also measured the concentrations of PM 2.5species at an urban station in central Tokyo from 1994 to 2004 and found that mass concentrationsof fine-mode particles in Tokyo have decreased since 1996 (2.4 µg m –3 yr –1 for PM 2.1 ) (Figure 59).Most of this decrease was due to decreases in elemental and organic carbon [Minoura et al., 2006],suggesting that the decrease in the PM 2.5 concentration was achieved by decreasing vehicleemissions. MOE set the AQS for PM 2.5 in Japan in September 2009 (daily average, 35 µg m –3 ;annual average, 15 µg m –3 ). From 2001 to 2008, annually averaged PM 2.5 concentrations in urbanareas were higher than this AQS (Figure 58).125

CHAPTER 3 - ASIAFigure 58 - Annually averaged PM2.5 concentrations observed by the Taper Elemental Oscillation Method at roadside, urban,and suburban stations [Ministry of the Environment of Japan, 2009]. The numbers of each type of measurement site inJapan and the Kanto area are given in the textFigure 59 - Fine and coarse aerosol concentrations observed at an urban background site in Tokyo. Reproduced bypermission of Elsevier from Minoura, H., K. Takahashi, J. C. Chow, and J. G. Watson (2006), Multi-year trend in fine andcoarse particle mass, carbon, and ions in downtown Tokyo, Japan [Minoura et al., 2006]Research projectIntegrated Measurement Programme for Aerosol and oxidant Chemistry in Tokyo (IMPACT)campaigns were conducted within the framework of the International Global Atmospheric ChemistryProject (IGAC), Mega-Cities: Asia. The background, objectives, methodology, and importantfindings of the IMPACT campaigns are presented in Chapter 7.Remaining problemsAccording to the Tokyo Metropolitan Government (2005), the observed increase in thefrequency of high-O 3 days over Tokyo cannot be explained by year-to-year variations inmeteorological parameters, such as solar radiation and temperature. Thus, improved understandingof the factors controlling O 3 concentrations is needed to assess effective ways to lower the levels ofphotochemical pollution over Tokyo, which requires more detailed studies of the relationships of O 3concentrations with its precursors’ emissions in various areas.126

CHAPTER 3 - ASIATo establish an effective control strategy for achieving the AQS for PM 2.5 , comprehensivesource apportionment of PM 2.5 is necessary. Organic aerosols account for a large fraction of thetotal fine-mode aerosol mass concentration in the Kanto area. However, the observed levels oforganic aerosols are not well reproduced by 3-D chemical transport models [e.g., Matsui et al.,2009]. Further studies on the formation of organic aerosols are clearly needed.3.14 TEHRAN, IRANIntroduction and geographical settingTehran, the capital of the Islamic Republic of Iran, has a population of approximately 10million people. Located at (35° 42’N, 51° 25’E) with an area of 2300 km 2 , the city is situated in asemi-enclosed basin just south of the Alborz Mountain chain (with average height of 2000 mASL;Figure 60). Tehran has suffered from poor air quality since the oil boom decade of the 1970s andover the last fifteen years rapid population growth has made matters even worse. On some days,the pollution loading of the atmosphere is so high that the impressive Alborz Ranges becomeinvisible from most vantage points. Tehran’s Clean Air Committee stated recently that 10,000people die every year due to air pollution related cardio-pulmonary disease.Figure 60 - Map of TehranTehran’s location is unusual; unlike most major cities it is not near a river or even close tothe sea. Due to high elevation (approximately 1140 m), aridity, and latitude, Tehran experiencesfour seasons. Climate can be extremely hot in the summer (with midday temperatures rangingbetween 30 to 40°C) and cold in winter, when night temperatures can fall well below the freezingpoint (Figure 61). Local precipitation is absent for 6 months of the year in low lying areas.Originating in the Mediterranean, synoptic scale low pressure systems propagate over the region inspring and autumn, while in winter the southward extension of the Siberian high pressure systemcan advect cold air over the Iranian Plateau. The average annual rainfall is approximately 230 mm,with most precipitation falling in autumn and winter months. The large scale easterly flow thatdominates the area in the summer is thought to be associated with a circulation pattern named ‘thewinds of 120 days’ caused by a thermal low over Pakistan [Zawar-Reza, 2008]. Outside of the basinwhere Tehran is situated westerly winds prevail except in summer when the flow tends to beeasterly. The airflow over most of Tehran is influenced by the sloping topography as discussedbelow.127

CHAPTER 3 - ASIAThe predominance of a diurnally reversing local wind system is of special importance to airquality, with a major influence on vertical stability and surface-layer meteorology. During the day, asouth south-westerly direction prevails, while at night and early morning, the direction of flow ismostly from a north north-east quadrant (Figure 61). Daytime up-slope winds are most frequent inthe summer and autumn seasons. The nocturnal northerly drainage winds are also most prevalentduring summer and autumn. The combined effect of less isolation to drive thermally generated flowsand the regular passage of the eastward propagating depressions that pass over Tehran make thebi-modal behaviour of wind more diffuse in spring and winter [Zawar-Reza et al., 2010]. During thetransition in the diurnal wind direction, the wind speed tends to drop, hence reducing the ventilationcapacity of the atmosphere at a time when peak emission of pollutants from rush hour traffic isoccurring (Figure 61). In general, the median wind speed does not go above 3 m/s at any hour, sothe ventilation capacity of the urban atmosphere is poor.Figure 61 - Meteorological variables at the Foothills Station for 2005 for (a) Wind Direction in degrees; (b) Wind Speed inm/s. Each hour is represented by a coloured pixel, where each day is shown as a vertical strip. The morning transitionphase is highlighted by the ellipse; (c) temperature ( o C)To illustrate just how dire the air quality is in Tehran, Figure 62 provides information on dailyand hourly averages of particulate matter with aerodynamic radius of 10 µm or less (PM 10 ). The redline indicates the World Health Organization’s (WHO) guideline of 50 µg m -3 ; it is apparent that mostdays the air quality is at dangerous levels.Figure 62 - a) Daily averages of PM10, and b) hourly values for PM10 in µg/m 3 averaged over 2001 – 2005 at a monitoringstation on the foothills of the Alborz Mountain (northern Tehran)128

CHAPTER 3 - ASIAThe scale of this air quality problem is huge, with the economic impact of air quality onIranian economy and population health estimated at US $7 billion; equivalent to 8.4% of GrossDomestic Productivity [GDP; Shafie-Pour and Ardestani, 2007]. Though there are numerouspublications on this issue in Farsi, only a few internationally published scholarly papers focus on airpollution and its environmental impacts in Tehran.Emission sources of air pollutantsEmissions in Tehran are from mobile sources (transport), stationary sources such asindustries (mostly in the outskirts), and residences. By far the worst offender, mobile sources areestimated to contribute a massive 89% of the total emission by some studies; other studies suggestthat this contribution might be smaller, at approximately 71%. As this would indicate, Carbonmonoxide (CO) and PM 10 are the main concern for air quality in Tehran.Emission(ton/annum)Table 16 - (Data from Air Quality Control Company, AQCC)Mobile Sources PercentagecontributionStationary SourcesCO 1,354,652 99 18,222 1SO2 6,142 10 57,173 90NOX 109,917 70 46,253 30THC 155,609 71 64,761 29PM 18,777 69 8,444 31PercentagecontributionTable 16 summarizes the relative and absolute contribution for each emission source in2005. Mobile emission inventory surveys for Tehran cover emissions from light duty vehicles,private cars, motorcycles, public transport buses, and trucks. According to an Air Quality ControlCompany (AQCC) study performed in 2005, the contribution of light duty vehicles to air pollutioncaused from mobile sources has been estimated to be close to 50%. Factors that determine such ahigh contribution by the transport sector are complex, including government subsidized inexpensivefuel, which can be of poor quality (unleaded gasoline became available after 2001), and largenumbers of older, domestically produced cars.Data available on air pollutantsThere are approximately 13 permanent ambient air monitoring stations dispersed throughoutTehran, which are operated by AQCC and the Tehran Municipality. Daily and hourly averaged dataare available for CO, NO X , SO 2 , HC, TSP, O 3 and lead.The status and trend of the pollutionAs mentioned above, international scholarly work on analysis of in situ data is rare forTehran. Yet some good examples can be found; Halek et al. [2004] examined the monthly averagesof PM 10 for 2003 and discovered that autumn tends to have the highest concentrations and springthe lowest. Maximum values were observed in September at just over 370 µg m -3 ; the minimum wasreached in April at 65 µg m -3 . Hassanzadeh et al. [2009] show that SO 2 has a seasonal patternsimilar to that of PM 10 . Monitoring SO 2 levels at 5 monitoring stations for the period of 2000-2005,they concluded that at most sites SO 2 concentration fluctuations were similar.A link between hospital admissions due to angina pectoris and several pollutants wasestablished by Hosseinpoor et al. [2004]. This study established that exposure to CO provided theclearest link to negative health outcomes for the population in Tehran, although the confoundingrole of other pollutants was acknowledged.Shirazi and Harding (2001) provide information on trends for some common pollutants suchas CO and particulate matter (PM) for the period between 1988 and 1993. Indicating a rapid upwardtrend for most pollutants except NO 2 , they point out that all pollutants except TSM routinely andsubstantially exceeded WHO guidelines. These findings suggest that as the population continues togrow, and drives increasing numbers of motor vehicles, there will be a corresponding increase in129

CHAPTER 3 - ASIAthe negative health effects resulting from exposure to the rise in pollutants. The role of the transportsector on ambient levels of particulates is considered by Halek et al. [2004] where the agedistribution and polluting potential of the car fleet is examined in conjunction with seasonal variationin PM levels.SO 2 trends between 1995 and 2002 were the focus of a study by Aspari et al. [2002].Measurements were taken from seven main monitoring stations at different locations in the city. Thetrend in annual concentrations was downward until 1998, but since then there has been anincreasing trend. The seasonality of concentrations is similar to the previous studies.Information on spatial and temporal concentrations of volatile organic compounds (VOC) ishard to find. Jafari and Ebrahimi [2007] provide information on measured concentrations forBenzene. Finding that that benzene concentrations in Tehran average around 0.1 mg/m 3 , they notethat this is significantly higher than the U.S. Environmental Protection Agency (EPA)recommendation.Relationships of the trends to regulationsIn 1995, Tehran Municipality initiated a two-year project entitled ‘Tehran TransportEmissions Reduction Project’ to identify strategies for reducing motor vehicle emissions, and also toconsider greenhouse gas emissions. The Global Environmental Facility (GEF) and the localmunicipality supported this research. Key recommendations from this programme included phasingout older more polluting vehicles, cleaner fuel, mandatory inspection and maintenance, publiceducation and better traffic management. However, lack of coordination between local authoritieshas meant that the key recommendations have not been successfully implemented(Asadollah-Fardi) despite the Clean Air Act passed by the Iranian Parliament in 1995 to address thisimportant issue. This act prohibits the use of polluting (smoking) vehicles in urban areas, amongstother decrees.A cursory examination of annual averages from a monitoring station in the commercialheartland of Tehran (Bazaar) shows a decreasing trend for all pollutants (Asadollah-Fardi,Unpublished Report), but a more robust assessment is needed. Future studies should considerstatistically removing the influence of inter-annual variation in meteorology.Climatic change issuesA clear link between global climate change and air quality has not been established forTehran, however a summary of findings up to now follows next. Significant, increasing trends havebeen found in the annual statistics for temperature (Figure 63). Several climactic metrics, includingmaximum of daily maximum and minimum temperature, the annual minimum of daily maximum andminimum temperature, the number of summer nights, and the number of days where dailytemperature has exceeded its 90th percentile were examined by Zhang el al. [2005]. Analysis ofdaily airport data from 1956 to 2003 has shown significant negative trend in frost days and asignificant positive trend for summer days when maximum temperature exceeds 25 °C. Significantnegative trends have been found in the number of days when daily temperature is below its 10thpercentile. Positive trend in extreme precipitation events for Tehran was also found by Asgari et al.[2008].Figure 63 - Trends in mean annual temperature and population for Tehran130

CHAPTER 3 - ASIAResearch has shown that temperature trend is not only significantly affected by globalclimate change, but also by local factors such as the Urban Heat Island (UHI). Recent work bySoltanzadeh et al. [2009] on the interaction between nocturnal down-slope winds and the urbanboundary layer is still at an early stage, but shows promise in shedding light on the role of thisinteraction in air pollution dispersion, especially at night time.Research projects on air quality of TehranExtensive systematic air pollution study campaigns of significance have not yet beenconducted in Tehran, although an international framework for an ‘Integrated Plan for air pollutionreduction’ is in place. This plan covers topics such as the role that public transport, fuel quality,traffic management, and public awareness play in air quality. Small scale research projects thathave looked at constructing emission inventory databases, characterizing air pollutants and limiteddispersion modelling with mesoscale models have been performed by various researchers fromuniversities and governmental agencies such as the Islamic Republic of Iran MeteorologicalOrganization (IRIMO). But a co-operative multi-agency research programme that simultaneouslymeasures variables such as emission factors, low level meteorology, and boundary layer height isdesperately needed to answer the many key scientific questions that remain.Various Departments at the University of Tehran are active in air quality research. Work iscurrently in progress to understand boundary-layer processes over the urban fabric of Tehran, forexample, in the Department of Geophysics. A long-term SODAR dataset is the main observationaltool here, and extensive postgraduate work is underway to validate mesoscale outputs with thisdata. Previously, theoretical work in this department concentrated on the climatology of mixed-layerevolution. The Department of Geography is mainly concerned with long-term spatial variation ofpollutants, and linkages with synoptic scale flow.Problems remainingIt is obvious that there is plenty of scope for air pollution research in Tehran. There are manyunanswered questions regarding mesoscale meteorology and its role in local and regionaladvection of pollutants. Basins exhibit peculiar vertical stability characteristics that directly controlvertical mixing of pollution, but this aspect has not been examined over Tehran. The twice dailyradiosonde from Mehrabad International Airport ascends too rapidly through the first few hundredmeters above the ground to provide comprehensive information about stability. So there is very littleinformation on the formation and destruction of the nocturnal inversion layer or its seasonalvariation, or on the mixed-layer height evolution throughout the day.Peer-reviewed published work is badly needed examining long-term pollutant trends afterstatistically removing the meteorological signal. Given the influence of the surrounding topographyon Tehran’s meteorology, however, this might not be as vital as it is for cities on less complexterrain. Certainly the AQCC dataset makes a comprehensive overview of trends possible.In view of the significant amount of air and pollution that can be injected into the uppertroposphere via the daytime up-slope flows and transported away by the free atmosphere, it is alsovital to research and understand the role this process plays in Tehran’s air quality.ReferencesADB (2002). RETA Project on “ Study on Air Quality in Jakarta: Future Trends, Health Impacts,Economic Value, and Policy Options”. Asian Development Bank.Asadollah-Fardi G., Air quality management in Tehran. Unpublished Report.Asgari, A., Rahimzadeh, F., Mohammadian, N. and Fattahi, E. (2008). Trend Analysis of ExtremePrecipitation Indices Over Iran. Iran-Water Resources Research. 3, 42-55Asian Development Bank, Philippines: Metro Manila Air Quality Improvement Sector DevelopmentPlan, ADB Completion Report, Project No. 30480, 2008131

CHAPTER 3 - ASIAAsrari, E., Ghole, V. and Sen, P. (2005). Study on the Status of SO2 in the Tehran- Iran. Journal ofApplied Sciences & Environmental Management,10, 75-82Azad A. K. and T. Kitada. (1998). Characteristics of the air pollution in the city of Dhaka,Bangladesh in winter. Atmospheric Environment 32:1991-2005Bank of Thailand. (2010). Statistic. Available at URL:,accessed August 2010.Begum B. A, E. Kim, S. K. Biswas, P. K. Hopke. (2004). Investigation of sources of atmosphericaerosol at urban and semi-urban areas in Bangladesh. Atmospheric Environment38:3025–3038Begum B. A, S. K. Biswas, P. K. Hopke. (2006). Temporal variations and spatial distribution ofambient PM2.2 and PM10 concentrations in Dhaka, Bangladesh. Science of the TotalEnvironment 358:36–45Begum B. A, S. K. Biswas, P. K. Hopke. (2008). Assessment of trends and present ambientconcentrations of PM2.2 and PM10 in Dhaka, Bangladesh. Air Quality, Atmosphere andHealth, Springer, 1, 125-133. DOI 10.1007/s11869-008-0018-7Beijing Municipal Environmental Protection Bureau, The communiqué on the Environmental Statusof Beijing City, 1999 ~ 2007Biswas S. K, S. A. Tarafdar, A. Islam, M. Khaliquzzaman, H. Tervahattu, K. Kupiainen (2003).Impact of unleaded gasoline introduction on the concentration of lead in the air of Dhaka,Bangladesh. J Air Waste Manage Assoc 53:1355–1362Bo Y., Cai H., Xie S. D. (2008). Spatial and temporal variation of historical anthropogenic NMVOCsemission inventories in China, Atmospheric Chemistry and Physics, 8, 7297–7316CAI-Asia, Country Synthesis Report on Urban air quality management, Philippines. 2006.http://www.cleanairnet.org/caiasia/1412/channel.html (Accessed, February 2010).CAI-Asia, Philippines Country Profile: Focus on Smaller Cities, Philippines, October, 2009.Census: 2007 Census of the Populationhttp://www.census.gov.ph/data/census2007/index.html (Accessed February 2010).Chae, Y. et al. (2007). Cost- Benefit Analysis of Integrated Environmental Strategies for Air QualityImprovement and Greenhouse gas emission Reductions. Integrated EnvironmentalStrategies. Korea Environment Institute and National Research Environment Laboratories.Chan C.K., Yao X.H. (2008). Air pollution in megacities in China. Atmospheric Environment, 42:1-42Chen C.H., Cai F.H., Huang C., Li L., Huang H.Y. (2007a). Study on the transportation of the airpollution in the Yangtze River Delta, Shanghai Academy of Environmental Science. (inChinese).Chen C.H., Chen B.H., Wang B.Y., Huang C., Zhao J., Dai Y., and Kan H.D. (2007b). Low-carbonenergy policy and ambient air pollution in Shanghai, China: A health-based economicassessment, Science of the Total Environment, 373: 13-21Chen C.H., Li L., Huang C., Chen Z., Wang H.L., Huang H.Y., et al., (2009). Study on the airpollution control countermeasures for 2010 EXPO, Shanghai Academy of EnvironmentalScience, 2009 (in Chinese).Chen C.H., Wang B.Y., Fu Q.Y., Green C., and Streets D.G. (2006). Reductions in emissions oflocal air pollutants and co-benefits of Chinese energy policy: a Shanghai case study, EnergyPolicy, 34, 754-762Chen, X.L., Zhao, H.M., Li, P.X., Yin, Z.Y. (2006). Remote sensing image-based analysis of therelationship between urban heat island and land use/cover changes. Remote Sensing ofEnvironment, 104, 133–146China's National Assessment Report on Climate Change, Science Press, Beijing. (2007) (inChinese).Chom Chon Thai Foundation. (2003). Thailand Country report. GAIA global meeting 2003 atCopthorne Orchid Hotel, Penang, Malaysia, March 17-21, 2003132

CHAPTER 3 - ASIACivic Exchange. (2008). A price too high: the health impacts of air pollution in southern China.http://www.civic-exchange.org/eng/upload/files/200806_pricetoohigh.pdf.Columbus, F. (2003). Asian Economic and political Issues, Vol. 9, Nova Science Publishers, Inc.,Hauppauge, New York.Core J. (1998). Sources of air pollution and control options. Paper presented in the ConsultativeMeeting of World Bank and Department of Environment, Government of Bangladesh duringApril 26-27, Dhaka.Cruz, R.V., H. Harasawa, M. Lal, S. Wu, Y. Anokhin, B. Punsalmaa, Y. Honda, M. Jafari, C. Li andN. Huu Ninh (2007). Asia. ClimateChange 2007: Impacts, Adaptation and Vulnerability.Contribution of Working Group II to the Fourth Assessment Report of theIntergovernmentalPanel on Climate Change, M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden andC.E. Hanson, Eds.,Cambridge University Press, Cambridge, UK, 469-50Deng, X.J., Tie, X.X., Wu,D., Zhou, X.J. Bi, X.Y., Tan, H.B., Li, F., Jiang, C.L. (2008). Long-ten trendof visibility and its characterizations in the Pearl River Delta (PRD) region, China.Atmospheric Environment 42, 1424–1435DENR (Department of Environment and Natural Resources): http://denr.gov.ph (Accessed Feb2010).DENR (Department of Environment and Natural Resources): National air quality status report,2005-2007, Environmental Management Bureau, Quezon City, Philippines, 2009.Department of City Planning. (2008). Planning database 2008, Policy and Planning division,Department of City Planning.Department of Industrial Works. (2007). List of factories in Bangkok. Available at URL:: last updated 11-Jan-2008.Department of Land Transport. (2009). Number of Vehicle Registered in Thailand as of 31 May2009. Available at URL: : last updated 31-May-2009.DIESEL. (2008). Developing Integrated Emissions Strategies for Existing Land-Transport(DIESEL), UNDP/World Bank Energy Management Assistance Programme, Bangkok,Thailand.Dolf G., and Chen C.H. (2001). The CO2 emission reduction benefits of Chinese energy policiesand environmental policies: A case study for Shanghai, period 1995–2020, EcologicalEconomics, 39: 257-270ECOREA. (2008). Environmental review by the Ministry of Environment, Republic of Korea.Electricity Generating Authority of Thailand (2008). Annual report 2008.ERM. (2000). Greenhouse gas emission control study: revised executive summary. Reportprepared for Environmental Protection Department of the HKSARG under Agreement No.CE 58-98ESMAP. (2008). Developing Integrated Emissions Strategies for Existing Land-transport (DIESEL).Joint UNDP/World Bank Energy Sector Management Assistance Programme (ESMAP)Estimating the total costs of Air Pollutions and developing Emission Control Strategies forKyonggi-do. Gyeonggi Research Institute, 2003.Fu, L. L., Shao, M., Liu, Y., Liu, Y., Lu, S. H., and Tang, D. G. (2005). Tunnel experimental study onthe emission factors of volatile organic compounds (VOCs) from vehicles, Acta ScientiaeCircumstantiae, 25(7), 879–885 (in Chinese).Fung C. “The challenge of modeling air quality in Hong Kong” http://www.science.gov.hk/paper/EPD_CFung.pdf (last visited on 10 July 2009).GovHK. (2009). Hong Kong – the Facts. ttp://www.gov.hk/en/about/abouthk/facts.htm.Guangdong Statistical Yearbook principal aggregate indicators on national economic and socialdevelopment and their related indices and growth rates/main indicators on industry, 2005.Guangzhou Environmental Buttetion, 1999–2008. Guangzhou Environmental Protection Bureau,Guangzhou, www.gzepb.gov.cn.133

CHAPTER 3 - ASIAGuo H, Fine AJ, So KL, Ayoko G, Li YS, Hung WT. (2009). Receptor modeling of sourceapportionment of Hong Kong aerosol and the implication of urban and regional contribution.Atmospheric Environment 43, 1159-1169Guo H, Lee SC, Louie PKK, Ho KF. (2004b). Characterization of hydrocarbons, halocarbons andcarbonyls in the atmosphere of Hong Kong. Chemosphere 57:1363-1372Guo H, So KL, Simpson IJ, Barletta B, Meinardi S, Blake DR. (2007). C1-C8 volatile organiccompounds in the atmosphere of Hong Kong: overview of atmosphere processing andsource apportionment. Atmospheric Environment 41, 1456-1472Guo H, Wang T, Louie PKK. (2004a). Source apportionment of ambient non-methane hydrocarbonsin Hong Kong: application of a principal component analysis/absolute principal componentscores (PCA/APCS) receptor model. Environmental Pollution 129:489-498Gurjar, B. R., T. M. Butler, M. G. Lawrence, and J. Lelieveld. (2008). Evaluation of emissions and airquality in megacities, Atmos Environ, 42(7), 1593-1606Halek, F., Kavouci A. and Montehaie H. (2004). Role of motor-vehicles and trend of air borneparticulate in the Great Tehran area, Iran. International Journal of Environmental HealthResearch. 14: 307-313Hao, J., Wang, L., Li, L., Hu, J.N., Yu, X.C. (2005). Air pollutants contribution and control strategiesof energy-use related sources in Beijing. Science in China (Series D), 48(Suppl. II), 138–146Hasegawa, S., S. Wakamatsu, T. Ohara, Y. Itano, K. Saitoh, M. Hayasaki, and S. Kobayashi.(2007). Vertical profiles of ultrafine to supermicron particles measured by aircraft overOsaka metropolitan area in Japan, Atmos Environ, 41(4), 717-729Hassanzadeh, S., Hosseinibalam, F. and Alizadeh, R. (2009). Statistical models and time seriesforecasting of sulfurdioxide: a case study Tehran. Environmental Monitoring andAssessment. 155, 149–155Hosseinpoor, A-R, Forouzanfar, M-H, Yunesian, M., Asghari, F., Holakouie-Naienia, K., Farhood, D.(2005). Air pollution and hospitalization due to angina pectoris in Tehran, Iran: A time-seriesstudy. Environmental Research, 99, 126–131.http://www.epd.gov.hk/epd/english/climate_change/files/ghg_study_es.pdfHuang C., Chen C.H., Li L., Chen M.H., Fu Q.Y., Huang H.Y., Chen Z. (2008). Study on adopt ion ofthe Euro-IV vehicular emission standards in advance in Shanghai, Shanghai Academy ofEnvironmental Science. (in Chinese).Huang X-F, Yu JZ, Yuan Z, Lau AKH, and Louie PKK (2009) Source analysis of high particulatematter days in Hong Kong. Atmospheric Environment 43, 1196-1203IDRC–EEPSEA. (2009). Climate matters: vulnerability map of Southeast Asia, InternationalDevelopment Research Centre’s Economy and Environment Programme for Southeast Asia.Retrieved on 29 June 2009 fromhttp://www.idrc.ca/eepsea/ev-135299-201-1-DO_TOPIC.html.Itano, Y., S. Wakamatsu, S. Hasegawa, T. Ohara, S. Sugata, M. Hayasaki, T. Moriya, and S.Kobayashi. (2006). Local and regional contributions to springtime ozone in the Osakametropolitan area, estimated from aircraft observations, Atmos Environ, 40(12), 2117-2127.Jafari, H. R. and Ebrahimi, S. (2007). A Study on Risk Assessment of Benzene as one of the VOCsAir Pollution. International Journal of Environmental Research. 1, 214-217JBS. (2006). Jakarta in statistics 2006, Jakarta Bureau of Statistic, Indonesia. Retrieved on 28 June2009 from http://www.bps.go.id/~jakarta/.JEPA. (2008). Status of Environment Report 2008, Jakarta Environmental Protection Agency.Retrieved on 30 June 2009 from http://bplhd.jakarta.go.id/lapsld2008.php.JICA. (1997). Project of “The Study on the Integrated Air Quality Management for JakartaMetropolitan Area”, conducted by Japan International Cooperation Agency (JICA).Jo, WK. (2005). Analysis of Roadside Inhalable Particulate Matter (PM10) in Major Korean Cities.Environment Management, 36(6), 826-841Jo. WK. (2000). Analysis of air pollution in two major Korean cities: trends, seasonal variations,daily one hour maximum versus hour based concentration, and standard exceedances.Environmental Pollution, 110, 11-18134

CHAPTER 3 - ASIAJoh, Seunghun, Studies on Health Benefit Estimation of Air Pollution in Korea, presented forWorkshop On Assessing The Ancillary Benefits And Costs Of Greenhouse Gas MitigationStrategies, 27-29 March 2000, Washington, DC, United States.Jung, H.S., Y. Choi, J.-H. Oh and G.H. Lim (2002). Recent trends in temperature and precipitationover South Korea. Int. J. Climatol, 22, 1327-1337Kannari, A., Y. Tonooka, T. Baba, and K. Murano. (2007). Development of multiple-species 1 km x1 km resolution hourly basis emissions inventory for Japan, Atmos Environ, 41(16),3428-3439Khaliquzzaman M, S. K. Biswas, S. A. Tarafdar, A. Islam, A. H. Khan. (1997). Trace ElementComposition of Size Fractionated Airborne Particulate Matter in Urban and Rural Areas inBangladesh. Report AECD/AFD-CH/6-4Khaliquzzaman M. (1998). Objectives, structures and expected follow-up. Paper presented at theConsultative Meeting on Integrated approach to vehicular air pollution control in Dhaka heldbetween April 26-27, World Bank and Department of Environment, Government ofBangladesh.Kim Oanh N. T., Upadhyay N., Zhuang Y-H., Hao Z-P., Murthy D.V.S., Lestari P., Villarin J.T.,Chengchua K., H. X. Co., Dung N. T., Lindgren E. S. (2006). Particulate air pollution in sixAsian cities: spatial and temporal distributions, and associated sources. AtmosphericEnvironment, 40, 3367-3380Kim YJ., K. W. Kim . , S. D. Kim, Bo K. Lee, Jin S. H. (2005). Fine particulate matter characteristicsand its impact on visibility impairment at two urban sites in Korea: Seoul and Incheon.Atmospheric Environment, 40, S593-S605Kim, J. E., S. Y. Ryu, and Y. J. Kim. (2008). Determination of Radiation Amplification Factor ofAtmospheric Aerosol from the Surface UV Irradiance Measurement at Gwangju, Korea,Theoretical and Applied Climatology, 91, 217-228Kondo, Y., et al. (2006). Temporal variations of elemental carbon in Tokyo, J Geophys Res-Atmos,111(D12).Kondo, Y., N. Takegawa, T. Miyakawa, M. Koike, Y. Miyazaki, Y. Kanaya, M. Mochida, M. Kuwata,Y. Morino, and M. Shiraiwa. (2010). Formation and transport of aerosols in Tokyo in relationto their physical and chemical properties: a review, J. Meteorol. Soc. Jpn., 88 (4), 597-624Kosasih, W. (2002). Jakarta Air Quality Management: Trend and Policies. Regional Workshop onBetter Air Quality (BAQ), Hongkong.Lam KS, Hung WT, Fung WY. (2006). Characterization of climate change impact in Hong Kong.Report prepared for Environmental Protection Department of the HKSARG under TenderAM02-316http://www.epd.gov.hk/epd/english/climate_change/climate_change_report.html.Lau AKH, Wong TW, Yu JZ, Yu ITK, Louie PKK. (2007). Toxic air pollutant monitoring in HongKong: environmental and health implications. In: Livingston JV (ed) Air Pollution: NewResearch. Nova Science Publishers, Inc., p1-87Lee SC, Cheng Y, Ho KF, Cao JJ, Louie PKK, Chow JC. (2006). PM 1.0 and PM 2.5 characteristics inthe roadside environment of Hong Kong. Aerosol Science and Technology 36:157-165Lee SC, Waston JG, Chow JC, Ho KF, Cheng Y, Wang T, Lau A, Guo H, Liu S. (2009). Feasibility ofestablishing air monitoring supersites in Hong Kong. Report prepared for EnvironmentalProtection Department of the HKSARG under Tender AS 07-386Lee, H., Y. J. Kim, and C. Lee (2008). Estimation of the rate of increase in nitrogen dioxideconcentrations from power plant stacks using an Imaging-DOAS, Environmental Monitoringand Assessment, DOI 10.1007/s10661-008-0296-4.Leung, D.Y.C., Yung, D., Ng, A., Leung, N.K.H., Chan, A. (2009). An overview of emissions tradingand its prospects in Hong Kong. Environmental Science & Policy, 12, 92–101Leverett B, Hopkinson L, Loh C, Trumbull K. (2007). Idling engine: Hong Kong‘s environmentalpolicy in a ten year stall 1997-2008. Civic Exchange, Hong Kong. 194pp.135

CHAPTER 3 - ASIALi L., Chen C.H., Huang C., Chen Z., Wang H.L., Huang H.Y. (2008). Preliminary measurement ofthe carbon dioxide emission in Shanghai, Shanghai Academy of Environmental Science (inChinese).Liang, J.Y., Wu,s.S. (1999). Climatological diagnosis of winter temperature variation in Gangdong.Tropical Meteor, 15, 221–229Lin, W.S., Sui, C.H., Wang, l.M., Wang, X.M., Deng, R.R., Fan, S.J., Wu, C.S., Wang, A.Y., Fong,S.K., Lin, H. (2007). A numerical study of the influence of urban cepansion on monthlyclimate in dry autumn over the Pearl River Delta, China. Theor. Appl. Climatol, 89, 63–72Liu Q., Wang Y.S., Wang M.X., Li J., Liu G.R. (2005). Trends of greenhouse gases in recent 10years in Beijing, Chinese Journal of Atmospheric Sciences, 29(2): 267-271, (in Chinese).Liu Y., Shao* M., Kuster W. C., Goldan P. D., Li X.h., Lu S.H., de Gouw J. A. (2009). Sourceidentification of reactive hydrocarbons and oxygenated VOCs in the summertime in Beijing,Environmental Science and Technology, 43 (1), 75-81, DOI: 10.1021/es801716nLiu Yuan, Shao Min. (2007). Estimation and prediction of black carbon emissions in Beijing city,Chinese Science Bulletin, 52(9):1274-1281Liu, Y., Shao, M., Lu, S.H., Chang, C.C., Wang, J.L., Fu, L.L. (2008). Source apportionment ofambient volatile organic compounds in the Pearl River Delta, China: Part Ⅱ. AtmosphericEnvironment, 42, 6261–6274Lo JCF, Lau AKH, Chen F, Fung JCH, Leung KKM. (2007). Urban modification in a mesoscalemodel and the effects on the local circulation in the Pearl River Delta region. Journal ofApplied Meteorological and Climatology 46, 457-476Lo JCF, Lau AKH, Fung JCH, Chen F. (2006). Investigation of enhanced cross-city transport andtrapping of air pollutants by coastal and urban land-sea breeze circulations. Journal ofGeophysical Research – Atmosphere, 111(D14104).Louie PKK, Chow JC, Chen L-WA, Watson JG, Leung G, Sin DWM. (2005a). PM 2.5 chemicalcomposition in Hong Kong: urban and regional variations. Science of the Total Environment338, 267-281Louie PKK, Watson JG, Chow JC, Chen A, Sin DWM, Lau AKH. (2005b). Seasonal characteristicsand regional transport of PM 2.5 in Hong Kong. Atmospheric Environment 39, 1695-1710Louie PKK, Zheng J-Y, Cheung BKH, Leung KMM, Fung C. (2008). Application of measured VOCsspeciation data in support of PATH model development in Hong Kong. China EnvironmentalScience 28, 304-308Lu S.H., Liu Y., Shao M., Huang S. (2007). Chemical speciation and anthropogenic sources ofambient volatile organic compounds (VOCs) during summer in Beijing, 2004. Frontiers ofEnvironmental Sciences and Engineering in China, 1(2):147-152Mahmud T. A, M. N. A Siddique, A. Salam, and A. M. S. Alam. (2008). Temporal Variation ofAtmospheric Aerosol Particulate Matters and Heavy Metal Concentrations in Dhaka,Bangladesh. Pakistan Journal of Analytical and Environmental Chemistry.Matsui, H., M. Koike, N. Takegawa, Y. Kondo, R. J. Griffin, Y. Miyazaki, Y. Yokouchi, and T. Ohara.(2009). Secondary organic aerosol formation in urban air: Temporal variations and possiblecontributions from unidentified hydrocarbons, J Geophys Res-Atmos, 114.Ministry of the Environment of Japan (2005). Investigation on intensity and total amount of emissionfrom motor-vehicle exhaust (in Japanese), Research report (200745), Tokyo.Ministry of the Environment of Japan (2008a). Investigation on intensity and total amount ofemission from motor-vehicle exhaust (in Japanese), Research report (207939), Tokyo.Ministry of the Environment of Japan (2008b). Report of investigation on formation of suspendedparticulate matters and photochemical oxidants from volatile organic compounds (inJapanese), Tokyo.Ministry of the Environment of Japan (2008c). Report of investigative commission of the healtheffect of fine particulate matters (in Japanese), Tokyo.Ministry of the Environment of Japan (2009). Report of expert committee of air quality standards forfine particulate matters (in Japanese), Tokyo.136

CHAPTER 3 - ASIAMinoura, H., K. Takahashi, J. C. Chow, and J. G. Watson (2006). Multi-year trend in fine and coarseparticle mass, carbon, and ions in downtown Tokyo, Japan, Atmos Environ, 40(14),2478-2487MOE (2003). Ministry of Environment (MOE) decree no. 141/2003, Jakarta, Indonesia.Molina, M. J., and L. T. Molina (2004). Megacities and atmospheric pollution, J Air Waste Manage,54(6), 644-680Naser, T. M., I. Kanda, T. Ohara, K. Sakamoto, S. Kobayashi, H. Nitta, and T. Nataami. (2009).Analysis of traffic-related NO X and EC concentrations at various distances from major roadsin Japan, Atmos Environ, 43(15), 2379-2390Nasiruddin M. (2006). Setting Ambient Air Quality and Vehicular Emission Standards: Dhaka’sExperience. Presented during the Pakistan Development Partners Meeting on Clean Air. 14September. Karachi.Nasrallah, H.A., Balling, R.C. (1993). Spatial and temporal analysis of middle eastern temperaturechanges. Clim. Chang, 25, 153–161National Academy of Engineering and National Research Council. (2008). Energy Futures andUrban Air Pollution: Challenges for China and the United States. The National AcademesPress, 365 pp.National Statistical Office, (2009). Statistic Available at URL:, 28-Jun-09.Noh, Y. M., Detlef Muller, D. H. Shin, J. S. Jung, K. H. Lee, Z. Li, and Y. J. Kim. (2009). Optical andMicrophysical Properties of Severe Haze Aerosol Measured by Integrated Remote SensingTechniques in Gwangju, Korea, Atmospheric Environment, 43(4), 879-888Noh, Y. M.. Y. J. Kim, and D. Muller. (2008). Seasonal characteristics of lidar ratio measured with aRaman Liar at Gwangju, Korea in spring and autumn, Atmospheric Environment, 42(9),2208-2224Oanh, N.T. Kim, N. Upadhyay., Y.-H. Zhuang., Z.-P. Hao . , D.V.S. Murthy., P. Lestari., J.T. Villarin.,K. Chengchua., H.X. Co., N.T. Dung. (2006). E.S. Lindgren . Particulate air pollution in sixAsian cities: Spatial and temporal distributions, and associated sources, Atmos. Environ., 40,3367-3380, 2006.Ogunjobi, K. O. and Y. J. Kim (2008). Aerosol characteristics and surface radiative forcingcomponents during a dust outbreak in Gwangju, Republic of Korea, EnvironmentalMonitoring and Assessment, 137(1-3), 111-126Ohashi, Y., and H. Kida. (2001). Observational results of the sea breeze with a weak wind regionover the northern Osaka urban area, J Meteorol Soc Jpn, 79(4), 949-955.Park, S. S., K. H. Lee, Y. J. Kim, T. Y. Kim, S. Y. Cho, and S. J. Kim (2008). High time-resolutionmeasurements of carbonaceous species in PM2.5 at an urban site of Korea, AtmosphericResearch, 89(1-2), 48-61Park, S.-U., and H.-J. In (2003). Parameterization of dust emission for the simulation of the yellowsand (Asian dust) event observed in March 2002 in Korea, J. Geophys. Res., 108(D19),4618, doi:10.1029/2003JD003484Park, S., Kim, YJ. (2005). Source contributions to fine particulate matter in an urban atmosphere.Chemosphere, 59, 217-226Pelangi Foundation. (2007). Paper to celebrate 15 years of yayasan pelangi Indonesia. Retrievedon 3 July 2009 from http://www.pelangi.or.id/publikasi/2007/15 years of pelangi.pdf.Permadi, D.A. and Kim Oanh, N.T. (2008). Episodic ozone air quality in Jakarta in relation tometeorological conditions. Atmospheric Environment. 42, 6806-6815.Pollution Control Department, 2003. Annual report 2003.Pollution Control Department, 2004. Annual report 2004.Pollution Control Department, 2005. Annual report 2005.Pollution Control Department, 2006. Annual report 2006.Pollution Control Department, 2007. Annual report 2007.Pollution Control Department, 2008. Annual report 2008.137

CHAPTER 3 - ASIAPollution Control Department, 2009. Emission standard for mobile sources. Available at URL: , 28-Jun-09.Sadanaga, Y., S. Shibata, M. Hamana, N. Takenaka, and H. Bandow. (2008). Weekday/weekenddifference of ozone and its precursors in urban areas of Japan, focusing on nitrogen oxidesand hydrocarbons, Atmos Environ, 42(19), 4708-4723Salam A, H. Bauer, K. Kassin, S M Ullah, and H Puxbaum (2003). Aerosol chemical characteristicsof a mega-city in Southeast Asia (Dhaka, Bangladesh). Atmospheric Environment 37:2517-28Salam A, T. Hossain, M. N. A. Siddique, A. M. S. Alam. (2008). Characteristics of AtmosphericTrace Gases, Particulate Matters, and Heavy Metal pollutions in Dhaka, Bangladesh. AirQuality, Atmosphere and Health, Springer, 2(1).Sasaki, K., and K. Sakamoto. (2007). Seasonal Characteristics of VOC Compositions and SourceApportionment in the Kansai Area, Japan, J. Jpn. Soc. Atmos. Environ., 42(4), 219-233Shafie-Pour, M. and Ardestani, M. (2007). Environmental damage costs in Iran by the energy sector.Energy Policy, 35, 4413-4423Shanghai Municipal Environmental Protection Bureau, The communiqué on the EnvironmentalStatus of Shanghai City, 1991 ~ 2008 (in Chinese).Shanghai Municipal Statistics Bureau, Shanghai statistical yearbook, China Statistics Press. (2009).(in Chinese).Shao, M., Tang, X.Y., Zhang, Y.H., Li, W.J. (2006). Air and surface water pollution of city clusters inChina: current situation and challenges. Frontiers in Ecology and the Environment,7(4)353-361Shirazi, M.A. and Harding, A.K. (2001). Ambient air quality levels in Tehran, Iran, from 1988 to 1993.International Journal of Environment and Pollution, 15(5), 517-527So KL, Guo H, Li YS. (2007). Long-term variation of PM 2.5 levels and composition at rural, urban,and roadside sites in Hong Kong: increasing impact of regional air pollution. AtmosphericEnvironment 41, 9427-9434Soedomo, M., Irsyad M. (1992a). Ambient air quality monitoring in Jakarta and Bandung, LPMITB-BAPEDAL.Sofyan A., Toshihiro K., Gakuji K. (2007). Difference of sea breeze in Jakarta between dry and wetseasons: implication in NO 2 and SO 2 distributions in Jakarta. Journal of Global EnvironmentEngineering, Vol. 12.Soltanzadeh, I., Zawar-Reza, P. and Bidokhti, A. (2009). Idealized numerical analysis ofatmospheric conditions over Tehran using Weather Research and Forecasting model(WRF). Proceedings of the Numerical Modelling Conference. Tehran, Iran.Song Y., Shao M., Liu Y., Lu S.H., Kuster W., Goldan P.D., Xie S.D. (2007). Source apportionmentof ambient volatile organic compounds in Beijing. Environmental Science and Technology,41:4348–4353Song Y.L., Dong W.J., Zhang S.Y., Zhang D.K., Wang S.R., Hu B.K. (2003). Study oncharacteristics of climate elements in Beijing, Arid Meteorology, 21(3): 63-68. (in Chinese).Streets D.G., Fu J.S., Jang C.J., Hao J.M., He K.B, Tang X.Y, Zhang Y.H., Wang Z., Li Z.P., ZhangQ., Wang L.T, Wang B.Y., Yu C. (2007). Air quality during the 2008 Beijing Olympic Games.Atmospheric Environment, 41: 480-492Su F., Shao M., Cai X.H., Zeng L.M., Zhu T. (2002). Estimation of methane emissions in Beijingarea using backward trajectory model, Acta Scientiae Circumatantiae, 22(5): 586-591Suhadi, D.R. M. Awang, M.N. Hassan, R.A. and Azizi Hj. Muda. (2005). Review of PhotochemicalSmog Pollution in Jakarta Metropolitan, Indonesia. American Journal of EnvironmentalSciences. 2, 110 – 118Summary for Policymakers of Climate Change 2007: The Physical Science Basis. Contribution ofWorking Group I to the Fourth Assessment Report of the Intergovernmental Panel onClimate Change [M]. Cambridge University Press, IPCC. Cambridge.138

CHAPTER 3 - ASIASupat, W. (1999a). Ambient air quality monitoring network in Thailand. Paper presented at NationalWorkshop on Phasing Out Leaded Gasoline in Vietnam, Hanoi, Nov.28-Dec.1.Tang G., Li X., Wang Y., Xin J., Ren X. (2009). Surface ozone trend details and interpretations inBeijing, 2001–2006, Atmospheric Chemistry and Physics Discussion, 9, 8159–8185Tang X.Y., Zhang Y.H., and Shao M. (2006). Atmospheric Environmental Chemistry, HigherEducation Press, Beijing (in Chinese). Thai Greenhouse Gas Management Organization.(2009). About TGO, Available at URL: , 28-Jun-09.Thai Meteorological Department. (2009). Meteorological in Thailand. Available atURL:, 28-Jun-09.The United Nations Environment Programme and the World Health Organization. (1994). “AirPollution in the World’s Megacities,” Environment, 36, 4-37Tokyo Metropolitan Government, (2005). Final report of committee on photochemical oxidantcontrol, pp. 1-78, Tokyo (in Japanese).Trumbull K. (2007). Still holding our breath a review of air quality policy in Hong Kong 1997-2007.Civic Exchange, Hong Kong, 149pp.Wai, K.M., Tanner, P.A. (2005). Extreme particulate levels at a Western Pacific Coastal City: theinfluence of meteorological factors and the contribution of long-range transport. Journal ofAtmospheric Chemistry, 50, 103–120Wakamatsu, S., T. Ohara, and I. Uno. (1996). Recent trends in precursor concentrations andoxidant distributions in the Tokyo and Osaka areas, Atmos Environ, 30(5), 715-721.Wang B.Y., Chen C.H., Huang C., Zhao J., and Dai Y. (2004). Local air pollutant and CO 2 emissionsscenarios under low carbon developmentShanghai case study, Energy Research andInformation, 20 (3): 137-145 (in Chinese).Wang K, Dickinson RE, Liang S. (2009a). Clear sky visibility has decreased over land globally from1973 to 2007. Science 323, 1468-1470Wang T, Wei XL, Ding AJ, Poon CN, Lam KS, Li YS, Chan LY, Anson M. (2009b). Increasingsurface ozone concentrations in the background atmosphere of southern China, 1994 –2007. Atmospheric Chemistry and Physics Discussions 9:10429-10455Wang T. (2003). Study of visibility reduction and its causes in Hong Kong. Report prepared forEnvironmental Protection Department under Tender AS 01-286http://www.epd.gov.hk/epd/english/environmentinhk/air/studyrpts/files/study_of_visibility_reduction_and_its_causes_in_hk.pdfWang T., Ding A.J., Gao J., Wu W.S. (2006). Strong ozone production in urban plumes from Beijing,China. Geophysical Research Letters, 33, dio: 10.1029/2006GL027689Wang, T., Wu, Y.Y., Cheung, T.F., Lam, K.S. (2001). A study of surface ozone and the relation tocomplex wind flow in Hong Kong. Atmospheric Environment, 35, 3203–3215Wang, W., Ren, L., Zhang, Y., Li, H., Chen, J., Liu, H., Wang, Z., Bao, L., Tang, D. (2008). Aircraftmeasurements of gaseous pollutants and particulate matters over Pearl River Delta in China.Atmospheric Environment, 42, 6187–6202Wang, X.M., Carmichael, G., Chen, D.L., Tang, Y.H., Wang, T.J. (2005). Impacts of differentemission sources on air quality during March 2001 in the Pearl River Delta (PRD) region.Atmospheric Environment, 39, 5227–5341WB. (1997). Urban air quality management strategy in Asia; Jakarta report, edited by Jitendra J.Shah and Tanvi Nagpal. World Bank Technical Paper no. 379.WHO. (2005). WHO Air quality guideline for particulate matter, ozone, nitrogen dioxide and sulphurdioxide Global update 2005. retrieved on 15 July 2009 fromhttp://www.who.int/phe/health_topics/outdoorair_aqg/en/.World Bank, Philippines Environmental Monitor 2002, Pasig City, Philippines, 2002.Wu D., Tie X, Li C, Ying Z, Lau A K H, Huang J, Deng X, Bi X. (2005). An extremely low visibilityevent over Guangzhou region: a case study. Atmospheric Environment, 39, 6568-6577Xu J., Zhang Y.H., Fu J.S., Zheng S.Q., Wang W. (2008). Process analysis of typical summertimeozone episodes over the Beijing area. Science of the Total Environment, 399:147-157139

CHAPTER 3 - ASIAYu JZ, Tung JWT, Wu AWM, Lau AKH, Louie PKK, Fung JCH. (2004). Abundance and seasonalcharacteristics of elemental and organic carbon in Hong Kong PM 10 . AtmosphericEnvironment 38, 1511-1521Yuan ZB, Lau AKH, Zhang HY, Yu JZ, Louie PKK, Fung JCH. (2006c). Identification andspatiotemporal variations of dominant PM 10 sources over Hong Kong. AtmosphericEnvironment 40, 1803-1815Yuan ZB, Lau KH, Yu JZ, Fung J. (2006a). Evaluation of local ozone production through sourceapportionment of volatile organic compounds in Hong Kong. Geophysical ResearchAbstracts 8:04978Yuan ZB, Yu JZ, Lau AKH, Louie PKK, Fung JCH (2006b). Application of positive matrixfactorization in estimating aerosol secondary organic carbon in Hong Kong and itsrelationship with secondary sulphate. Atmospheric Chemistry and Physics 6, 25-34Zawar-Reza, P. (2008). Numerical analysis of the ‘120 day wind’ over the Sistan Region,South-West Asia with TAPM. Clean Air and Environmental Quality, 42, 21-24Zawar-Reza, P., Appelhans, T., Gharaylou, M., Shamsipour, A. (2010). Mesoscale controls onparticulate matter pollution for a mega-city in a semi-arid mountainous environment: Tehran,Iran. International Journal of Environment and Pollution. In Press.Zhang B-N. and Kim Oanh N. T. (2002). Photochemical smog pollution in the Bangkok MetropolitanArea in relation to O 3 precursor concentrations and meteorological conditions. AtmosphericEnvironment, 36:4211-4222Zhang, X., and 24 co-authors. (2005). Trends in Middle East climate extreme indices from 1950 to2003, J. Geophys. Res., 110, D22104, doi:10.1029/2005JD006181Zhang, Y.H., Hu, M., Zhong, L.J., Wiedensohler, A., Liu, S.C., Andreae, M.O., Wang, W., Fan, S.J.(2008a). Regional integrated experiments on air quality over Pearl River Delta 2004(PRIDE-PRD 2004): overview. Atmospheric Environment, 42, 6157–6173Zhang, Y.H., Su, H., Zhong, L.J., Cheng, Y.F., Zeng, L.M., Wang, X.S., Xiang, Y.R., Wang, J.L.,Hao, D.F., Shao, M., Fan, S.J., Liu, S.C. (2008b). Region ozone pollution andobservation-based approach for analyzing ozone-precursor relationship during thePRIDE-PRD2004 campaign. Atmospheric Environment, 42, 6203–6218Zhong LJ, Zheng JY, Louie PKK, Chen J. (2007). Quantitative uncertainty analysis in air pollutantemission inventories: methodology and case study. Research of Environmental Sciences20, 15-20_______140

CHAPTER 4 - SOUTH AMERICACoordinating Author: Laura Gallardo (1)Contributing Authors: Marcelo Alonso (2) , María de F. Andrade (3) , Vanessa Silveira Barreto Carvalho (3) , EduardoBehrentz (4) , Pérola de Castro Vasconcellos (5) , Ariela D’Angiola (6) , Laura Dawidowski (7) , Saulo Freitas (2) , Darío Gómez (7) ,Karla M. Longo (2) , Leila Doprichinski Martins (8) , Marcelo Mena (9) , Patricia Matus (10) , Axel Osses (11) , Mauricio Osses (12) ,Néstor Rojas (13) , Pablo Saide (14) , Odón Sánchez-Ccoyllo (15) , María V. Toro (16)(1)Departamento de Geofísica & Centro de Modelamiento Matemático, Universidad de Chile. Blanco Encalada2002, piso 4, Santiago, Chile(2)Centro de Previsão de Tempo e Estudos Climáticos, Instituto Nacional de Pesquisas Espaciais, Rod.Presidente Dutra, km 40, 12630-000, Cachoeira Paulista, Brazil(3)Department of Atmospheric Sciences, Institute of Astronomy, Geophysics and Atmospheric Sciences,University of São Paulo, Rua do Matão, 1226, 05508-090 São Paulo, Brazil(4)Grupo de Estudios en Sostenibilidad Urbana y Regional, Universidad de los Andes Carrera 1 Este # 19 A - 40,Bogotá, Colombia.(5)Instituto de Química, Universidade de São Paulo, Av. Lineu Prestes, 748 São Paulo, Brazil(6)Laboratoire Atmosphère, Milieux, Observations Spatiales, Université Pierre et Marie Curie (Paris VI), 4 PlaceJussieu, 75252, Paris Cedex 05, France(7)Comisión Nacional de Energía Atómica, Gerencia Química, Av. Gral. Paz 1499 (B1650KNA), San Martín, Pcia.de Buenos Aires, Argentina(8)Universidade Tecnológica Federal do Paraná, UTFPR, Marcílio Dias 635, l, 86812-460 Apucarana, PR, Brazil(9)Facultad de Ecología y Recursos Naturales, Universidad Andrés Bello, Santiago, Chile(10)Salud Pública Facultad de Medicina Clínica Alemana- Universidad del Desarrollo, Santiago, Chile(11)Departamento de Ingeniería Matemática & Centro de Modelamiento Matemático, Universidad de Chile. BlancoEncalada 2002, piso 4, Santiago, Chile(12)Sistemas Sustentables, Santa Magdalena 75, Of 311, Santiago, Chile & International Sustainable SystemsResearch Center, ISSRC, 605 South Palm Street, Suite C, La Habra, CA 90631, USA(13)Department of Chemical and Environmental Engineering. Universidad Nacional de Colombia. Carrera 45 26-85Ed 412 Of 206. 111321 Bogotá, Colombia(14)Center for Global and Regional Environmental Research, University of Iowa, Iowa City, Iowa, USA(15)Servicio Nacional de Meteorología e Hidrología del Perú, Jr. Cahuide 785 Jesús María, Lima11 – Perú(16)Grupo de Investigaciones Ambientales, Universidad Pontificia Bolivariana Bloque 11 Circular 1 No.70-01,Medellín, Colombia4.1 OVERVIEWAir pollution is a reoccurring phenomenon in many South American cities. Like in manycities around the world, population growth and urbanization result in a convergence of a variety ofair pollutant emission drivers such at industry, transportation, and energy production andconsumption amongst others. This convergence, however, is rather extreme in South Americawhere about 84% of the population today lives in mid- to large size cities (larger than 750 kinhabitants) [UNPOP, 2009]. The emptiness of the South American continent is also striking, ascities, and population densities, are mainly located close to coastal areas or a few hundreds ofkilometres in land (Figure 1). Although the rate of growth in larger cities of more than 5 millioninhabitants has decreased over the last decades (from an average of 3%/yr between 1975 and1990 to 2% between 1995 and 2010), the growth rate is still enough to ensure the proclivity ofthese agglomerations to concentrate pollution drivers and hence face environmental problems.Moreover, mid-size cities (2% growth per yearbetween 2005 and 2010).Oftentimes, South America is referred to as a homogeneous entity, possibly due to ourcommon historic background in connection to the European “conquest” of the territories. However,if one wants to assert global change drivers in the region, one must deal with the actualheterogeneity of South America’s physical and human geography. Our economies and politicalsystems vary giving rise to diversity in our policies. Table 1 shows relevant population, economic,141

CHAPTER 4 – SOUTH AMERICAand human development indexes for South American cities. From Table 1 it is apparent that theeconomic growth has also increased the life expectancy, educational attainment and incomemeasured by the Human Development Index in the region. However, South America is still subjectto severe inequity as expressed by the Gini index, which is a measure of income distribution.These inequities act as amplifiers of environmental problems and, in particular, they usuallyincrease the overall air pollution problem as well as domestic air pollution and other concomitantvulnerabilities [Smith et al., 2000; Adonis and Gil, 2001; Emmelin and Wall, 2007].Figure 1 - Map of the population density in South America (persons per km 2 ), based on 0.25 o gridded data for 2000 from theCenter for International Earth Science Information Network (CIESIN) at Columbia University[http://sedac.ciesin.columbia.edu/gpw/]Table 1 - Location, population (http://esa.un.org/unpd/wup/index.htm), gross domestic product (GDP) per city (Haworths etal. 2009), human development index (HDI) per country (http://hdr.undp.org/en/statistics/) and Gini Index in urban areas(http://www.eclac.org/estadisticas/) for selected South American citiesUrbanAgglomerationGeographicalCoordinatesPopulation(in k inhabitants)GDP inUS$ atPPPHDIGini IndexLat Lon Alt 1975 2010 2025 2008 2025 1975 2000 2007 Ca. Ca. Ca.(S) (W) (m.a.s.l.)1990 2000 2007São Paulo 23,6 46,8 720 9.614 20.262 21.651 388 782 0,644 0,771 0,813 0,606 0,628 0,586Buenos Aires 34,5 58,5 20 8.745 13.074 13.708 362 651 0,784 0,854 0,866 0,501 0,590 0,510Rio de Janeiro 22,9 43,2 30 7.557 11.950 12.650 201 407 0,644 0,771 0,813 0,606 0,628 0,586Lima 12,0 77,0 110 3.696 8.941 10.530 109 213 0,642 - 0,806 - 0,477 0,421Bogotá -4,6 74,1 2600 3.040 8.500 10.537 100 192 0,661 0,771 0,807 - 0,484 0,587Santiago 33,5 70,5 500 3.138 5.952 6.503 120 207 0,703 0,835 0,878 0,543 0,558 0,517Medellín -6,2 73,6 1500 1.536 3.594 4.494 50 97 0,661 0,771 0,807 - 0,484 0,587142

Typically, air pollution research and management initiatives have been triggered by severeproblems. Therefore, emphasis has been put on short-term and local-scale analyses designed todeal with acute problems, i.e., extreme pollution events, whereas little attention has been paid tolong-term, large-scale effects. This is slowly starting to change in places where environmentalgoals have become more ambitious (e.g., Santiago, São Paulo). It is encouraging to see that themajority of the environmental authorities in the region (Brazil, Chile, Colombia, Peru, etc.) haveadopted in principle the Internet as a tool for publishing data, assessments, and procedures. Inpractice, however, one often finds inconsistencies and information gaps.A summary of the situation in different urban agglomerations in South America is givenhere. The following section addresses crosscutting issues related to modelling, emissions,monitoring, and regulation. In addition, we look at the continent as a whole looking at the impact ofnon-urban sources on megacities and the footprints of megacities. We then describe the situationin Bogotá and Medellín in Colombia, Buenos Aires in Argentina, Lima in Peru, Santiago in Chile,and Rio de Janeiro and São Paulo in Brazil. In all of these cities, except in Buenos Aires, there isconcern about air quality, systematic air quality monitoring, and attainment plans have alreadybeen implemented. This review is to be considered illustrative, not comprehensive, of the presentsituation in South American megapolis by showing specific characteristics and features as well asthe differences across cities and countries. The review considers relatively smaller cities that areexpected to grow and that already show significant pollution levels (e.g., Medellín), medium-sizecapitals with heavy air pollution (e.g., Bogotá, Santiago, Lima), and cities that already surpassed10 million inhabitants (Buenos Aires, São Paulo and Rio de Janeiro).4.1.1 ModellingDispersion modelling, and its operational implementation “chemical weather forecasting”, isa key-tool for dealing with air quality problems. There is an increasing number of groups in SouthAmerica developing and applying air quality models [Andrade et al., 2004; Freitas et al., 2005a;Freitas et al., 2005b; Martins and Andrade, 2008a; e.g., Gallardo et al., 2002; Olivares et al., 2002;Schmitz, 2005; Saide et al., 2009a; Jorquera and Castro, 2009; Freitas et al., 2009; Longo et al.,2010; Saide et al., 2011a, etc.]. Several institutions, including research centres, environmentalauthorities, and weather services (See Table 2) have implemented operational chemical weatherforecasting systems. Inverse modelling is also being used [Hoelzemann et al., 2009; Saide et al.,2009a; Jorquera and Castro, 2010; Saide et al., 2011b]. Further, fast Internet connections arealready available (http://www.redclara.net/) making it possible to develop grid-computingapplications, particularly within the framework of atmospheric physical and chemical weatherforecasting [D’Almeida et al, 2008].Table 2 - Examples of operational Chemical Weather Forecasting Systems at the urban and continental scalein South AmericaInstitution responsible Coverage SpeciesforecastedBrazilian Center for Continental Criteria pollutantsWeather Forecast andand AOD fromClimate (INPE/CPTEC)biomass burningAtmospheric SciencesDepartment, University ofSão PauloDirección Meteorológicade Chile (DMC, ChileanWeather Office)Dirección del ÁreaMetropolitana del Valle deAburráSão Paulo andsurroundingareasCriteria pollutantsInternethttp://www.cptec.inpe.br/meio_ambiente/http://www.master.iag.usp.brSantiago Ozone http://www.meteochile.cl/modeloPOLYPHEMUSozono.htmlMedellín Criteria pollutants http://www.metropol.gov.co/aire/143

CHAPTER 4 – SOUTH AMERICA4.1.2 EmissionsIt is well known that developing emission inventories is an extremely complex process,which requires detailed statistics, process-level understanding, and continuous evaluation andupdating. South America lacks a sustained and coordinated activity and record for building reliableemission inventories for urban centres. There are a few inventories available for cities for whichattainment plans have been implemented (Table 3). Unfortunately, transparency, completeness,consistency, comparability, and accuracy requirements are not always met. For instance, many ofthese inventories are based on emission factors determined elsewhere that are not representativefor the very specific and diverse conditions of South American cities. This is changing due to theimplementation of comparable methods and the determination of local emission factors that arenow starting to be introduced in new inventories [Behrentz et al., 2009; Martins et al., 2006;Vivanco and Andrade, 2006; Sánchez-Ccoyllo et al., 2009; Martins and Andrade, 2008a; 2008b;D’Angiola et al., 2010]. These inventories are restricted to a few activity sectors such as urban andindustrial energy use and transportation, leaving aside rural and natural emissions. Efforts tointegrate and reconcile local and global emission inventories for South America have also beeninitiated [Alonso et al., 2010]. Figure 2 shows emissions of CO, NO X , and SO 2 for South Americabased on the EDGAR v3.2 FT2000 database.Table 3 - Emission inventories developed for South American cities. Fluxes are given in kton/yr of species,except for VOCs that are in ktonC/yr and NOX given in kton of 90% NO and 10% NO2City Base Year Source TypeSpeciesReferencePM10 PM2.5 CO NOX VOCs SO2Bogotá 2001 Mobile 1.6 - 306 13.7 47.6 2.32001 Stationary 2.9 - 8 1.4 4.4 5.1Total 4.5 - 314 15.1 52.0 7.4 Zárate et al., 2007Buenos Aires 2006 Mobile 5.2 - 569 81.0 70 6.6 D'Angiola et al., 20102006 Stationary 2.5 - 9.9 29.8 1.6 15.9 Oreggioni, 2009Total 7.7 - 579 130.8 71.6 22.5Lima 2000 Mobile 4.6 - 198.5 63.4 32.6 28.7 MTC, 20102004 Stationary 8.8 - 11 7.8 8.4 40.3 DIGESA, 2005Total - - 341 78 81 51.5Medellín 2008 Mobile 2.2 - 204 18.2 29 0.22008 Stationary 2.8 - 12.8 5.1 5 31.4Total 5.0 - 217 23.3 34 31.6 AMVA, 2008Rio de Janeiro 2003 Stationary 10.6 - 6.3 30.3 26 55.82003 Mobile 7.8 - 315 60.2 53 7.5Total 18.4 - 321 90.5 79.0 63.3 FEEMA, 2004Santiago 2005 Mobile 1.8 1.4 211 37.9 20 0.22005 Stationary 3.0 2.4 24 13.8 83 13.2Total 4.8 3.8 235 51.7 103 13.4 DICTUC, 2007São Paulo 2009 Mobile 31* - 1533 362 370 82009 Stationary 32* - 39 14 12 17 CETESB, 2010*For São Paulo it is calculated as total particulate matter including PM10.4.1.3 ObservationsConsiderable resources have been invested by local authorities in various urban areas inSouth America in air quality monitoring, focusing on exposure to so-called criteria pollutants (Cf.Table 4). However, aerosol measurements in the region, except for some areas of Brazil andVenezuela, are still sparse and are usually limited to concentration levels of PM 10 and PM 2.5 .Overall, there is an appalling lack of accurate observations of air quality in South America in bothurban, rural, and background environments. In addition, oftentimes, the quality and accessibility ofthe data is not reliable.144

CHAPTER 4 – SOUTH AMERICAFigure 2 - CO, NOX and SO2 emissions for the year 2000 based on the EDGARv3.2 FT2000 database145

CHAPTER 4 – SOUTH AMERICATable 4 - Available air quality monitoring available in South American citiesCity CurrentnumberofstationsPollutants measuredBogotá 15 NO, NO2, SO2, TSP, PM10, PM2.5, O3, CO, CH4, HCHO, NMHC,benzene, tolueneBogotá 15 NO, NO2, SO2, TSP, PM10,PM2.5, O3, CO, CH4, HCHO,NMHC, benzene, tolueneBuenosAiresBeginning ofmeasurements4 CO,NO,NO2,PM10 Dust Fall 19852009Lima 5 TSPDust fallPM10, PM2.5CO, SO2, NO2, O3Medellín 17 NO, NO2, SO2, TSP, PM10,PM2.5, O3, CO, HCSantiago 11 NO, NOX, SO2, PM10, PM2.5, O3,SãoPauloRio deJaneiroCO, CH4, NMHC30 NO, NO2, NOX, SO2, PM10,PM2.5, O3, CO36 TSPNO, NOX, SO2, PM10, O3, CO,CH4, NMHCNote1997 Not all stations measure all pollutantshttp://www.secretariadeambiente.gov.co1997 Not all stations measure all pollutants1987199020002001http://www.dama.gov.cohttp://www.agenciaambiental.gob.ar/At one station the record goes back to 1985Two out of the four stations have been added in2009.http://www.digesa.minsa.gob.pe/Only data summaries are available on theinternet1993 http://www.metropol.gov.co/1997 http://www.asrm.cl/At 4 stations the record goes back to 19881981 automated http://www.cetesb.sp.gov.brstations1973 manualstations for SO2and smoke1967 http://www.inea.rj.gov.br1998 32 are manual stations and 4 automated4.1.4 RegulationsThe World Health Organization (WHO) air quality guidelines represent the current bestscientific understanding of the impacts of air pollution on human health. While designing nationalregulations, local factors such as race related health risks, available technologies, social factors,degree of development, capability to implement regulations, and control compliance should ideallybe considered [WHO, 2005]. A comparative assessment of environmental regulations in SouthAmerica shows that most countries first reproduce the standards developed by United StatesEnvironmental Protection Agency (USEPA), regardless of their specific national and regionalcircumstances. However, South American governments do not update these standards at thefrequency of the USEPA [Rincón et al., 2007]. Aerosols are regulated in the majority of countriesby means of establishing concentrations for PTS, PM 10 and/or PM 2.5 . All the current levels in SouthAmerican countries with published air quality information, are several times over WHO standardsfor PM 10 , PM 2.5 and SO 2 [Romero-Lankao et al, 2010]. In the case of NO 2 , Peru and Colombiaestablished the same standard proposed by WHO. Colombia has established an annual ozonestandard more stringent than that of the WHO standard. Chile is the only South American countrythat follows WHO air quality guidelines for lead. Only Chile and Peru have recently introducedstandards for PM 2.5 .4.1.5 Non-urban sources and megacitiesSouth American cities are not only subject to air pollution that originates in the citiesthemselves but they are often affected by large industrial sources [Gallardo et al., 2002], volcaniceruptions, and most notably large-scale biomass burning. Despite of the international claims andthe Brazilian government commitment to limit deforestation in the Amazonia, the effectiveness ofcurrent actions is still open to discussion and their efficacy within the next decades is questionable.146

CHAPTER 4 – SOUTH AMERICAIn this context, the perspective of rapid progression of urbanization in South America and anyassessment of its impact on atmospheric chemistry must take into account the regional scaleemissions associated with biomass burning. The typical atmospheric circulation in South Americaimpose a long range transport of biomass burning smoke from its source areas in the Amazonia tothe southern and southeastern part of the South American continent, thus impacting large areas inthe subtropics [Freitas et al., 2005 a; Longo et al., 2009]. Most of the smoke produced by fires inthe Amazonia and central region of South America is transported towards the South AtlanticOcean throughout the southeastern part of the continent driven by the typical pole-ward warm andmoist air flow in the lower troposphere on the east side of the Andes called the South AmericanLow Level Jet [Vera et al., 2006]. This lower troposphere smoke transport very often affects citiesin the Southern part of the South American continent. Landulfo et al. [2009] investigated the impactof the regional smoke from vegetation fires on larger cities. Figure 3 shows a model simulation ofthe biomass burning aerosol optical thickness (AOT) at 550 nm on 30 August 2005. The smokeriver over South America emerging from the biomass burning areas and flowing towards the SouthAtlantic Ocean is evident and consistent with in-situ observations.Figure 3 - Left, CATT-BRAMS model simulation of AOT at 550 nm for 30 August 2005 over South America (the star symboldefines the location of São Paulo megacity). Right, AOT observation from CIMEL sunphotometer at 550 nm and PM2.5column integrated model simulated concentration (PMINT) during a period of ten days starting on 22 August 2005[Landulfo et al., 2009]An assessment of the relative contribution of urban and biomass burning emissions on thenear surface ozone on the regional scale was conducted using the regional chemical transportmodel CCATT-BRAMS [Longo et al., 2009]. The transport of O 3 and its precursors by the typicalsynoptic systems in the planetary boundary layer affects mainly areas on the central part of SouthAmerica; however long range transport at upper levels affects the atmospheric chemistry far awayfrom the source areas and has the potential to connect the regional smoke plume with local urbanemissions.4.1.6 Air Pollution Footprint of South American MegacitiesAn estimate of the footprints of South American megacities is shown in Figure 4. Thecontribution from southeastern megacities in South America to surface ozone levels duringOctober 2007 was in excess of 30%, affecting large areas downwind of these cities. Santiago’sfootprint is relatively concentrated due to the enclosed basin in which it is located. However, itsurban emissions affect larger areas on the West coast of South America, well beyond the cityborders. Figure 5 shows the monthly mean O 3 mixing ratio over São Paulo, Santiago, BuenosAires, and Bogotá with and without urban emissions included in the simulation. São Paulo urban147

CHAPTER 4 – SOUTH AMERICAemissions increase O 3 about two times near the surface and affect the lower troposphere from thesurface up to 3 km. A small perturbation is also noted in the middle and upper troposphere (3 to 9km), which might be explained by convective transport. Santiago imposes a much shallowervertical extension of the disturbance (less than 2 km) and increases O 3 by a factor of 20% onaverage, which can be explained by the low occurrence of moist convection. Buenos Aires showsa similar pattern to São Paulo except that the disturbance is confined to below 4 km. Noticeable isthe deep vertical disturbance on tropospheric ozone imposed by Bogotá. Its urban emissionsstrongly affect the troposphere from surface up to 10 km. The most plausible explanation for thisfeature is the intense convective regime in this area. These findings point to a high potential impacton regional and global scales by increasing emissions on urban areas located in the Northwesternpart of South America.Figure 4 - Percentage O3 contribution from urban sources elucidating the South American megacities footprintand average wind fields within the first 1 km height above local surface.Average for October 2007148

CHAPTER 4 – SOUTH AMERICAFigure 5 - Monthly average vertical profile of O3 concentration over (A) São Paulo, (B) Santiago, (C) Buenos Airesand (D) Bogotá cities considering simulation with and without urban emissions4.2 BOGOTÁBogotá, Colombia, located at 4˚36’N and 74˚4’W at an altitude of 2625 m.a.s.l., covers anurban area of ~520 km 2 with a population of approximately 8.5 million(http://www.citymayors.com/statistics/largest-cities-density-125.html) as of 2010, making itspopulation density around 13,500/km 2 , among the ten highest in the world. Bogotá’s growth,however, has been rather chaotic, with around a quarter of a million people arriving in the citybetween 1995 and 2005 [Urdinola, 2001]. Annual population growth was as high as 3% during the1980s and 1990s, and it is currently around 1.5%.Bogotá is located on the eastern branch of the Colombian Andes. The city and itsMetropolitan area are built on a fertile plateau known as Bogotá’s Savanna, bordered to the east,southeast by a mountain range reaching 4200 m.a.s.l. To the west, Bogotá is bordered by anothermountain range reaching 3600 m.a.s.l. that goes down to the Magdalena Valley (500 m.a.s.l.). A149

CHAPTER 4 – SOUTH AMERICAthird mountain range partially borders Bogotá to the North, limiting the influence of winds and thetransport of moisture and pollutants.Bogota’s climate is influenced by rainy and dry seasons. The passage of the IntertropicalConvergence Zone (ITCZ) and its trade winds produces two rainy seasons in March, April, May,and another in September, October, and November. The rest of the year is dry. The annualaverage temperature is 14°C, with daily oscillations between 5°C and 23°C in the dry season andbetween 9 and 17°C in the rainy season. These large daily oscillations promote the formation ofthermal inversions during the night, which are clearly visible as a brown haze over the city in theearly morning hours. The inversions are normally break around 8 AM. Bogotá’s climate is alsounder influence of the El Niño/ La Niña phenomenon.Since the 1990’s, transportation plans were developed in Bogotá to reduce air pollution.The transportation plans resulted in the construction of a highly efficient Bus Rapid Transit (BRT)system under the name of Transmilenio and an extensive bicycle path network of 340 km knownas Ciclo Ruta, with the idea of promoting the use of high-quality, sustainable public transportationand reducing the dependence on private cars. The BRT system serves 25% of public bus trips; theremaining 75% are still being served by a disorganized system with undetermined bus stops,aggressive driving, and high-emitting buses. The third phase of the BRT system is now underconstruction and will represent an additional 15% of total public bus trips by 2012(http://www.transmilenio.gov.co).Despite the relatively low share of trips made in private cars, traffic jams are frequent. Thisis due to several causes including the inconvenient distribution of main avenues, the poormaintenance of many secondary roads, and the inadequate behaviour of public buses, taxis,private cars and motorcycle drivers, among others. Several restrictions on private cars have beenimplemented to initially reduce the traffic load during rush hours, but have been extended to thewhole day (6 AM. to 8 PM.). Restrictions to public buses depend on the environmentalperformance of the buses, which is controlled according to the opacity level of their exhaustemissions, and are known as the Programa de autorregulación which works together with the Picoy placa ambiental, a one-day-a-week restriction based on the final plate number of the vehicles.According to the national inspection and maintenance programme, vehicles must undergo anemissions test every year if they are private or every half-a-year if they are public, The inspectionis carried out at privately owned centres called Centros de Diagnóstico Automotor (CDA).As the main centre of Colombia’s economic activity, Bogotá and its metropolitan area haveattracted a number of important industrial facilities across a diverse range of activities. Theindustrial facilities range from food and drink production to textiles, chemicals, plastics, and rubberto metallurgy and metal products to non-metallic mineral extraction and production and paper,cardboard and derivatives production. Many of these facilities are west of the main urban centre,while others are located in industrial sites in neighbouring towns to the north and west.During the last decade, several initiatives were undertaken to build an emission inventory.At first, it was based on emission activity indices and foreign emission factors [Zárate et al., 2007].Recently, a new inventory considering local emission factors has become available [Behrentz et al.,2009]. Traffic related emissions are identified as the main source of particulate matter.Since 1997, 13 automatic air quality stations (12 stationary and 1 mobile) measure criteriaair pollutants. Datasets are available to the public on the website of the city’s Secretary of theEnvironment (http://www.secretariadeambiente.gov.co).Various studies have concluded that concentrations of NO X , SO X and CO are not asignificant threat to public health, since they are normally below the Colombian air qualitystandards of 80 ppb (24-hour), 96 ppb (24-hour) and 8.8 ppm (8-hour), respectively [Behrentz et al.,2009]. However, PM 10 concentrations show a high number of exceedance-days of the annual airquality standard of 60 µg/m 3 and the 24-hour air quality standard of 150 µg/m 3 , particularly in theWestern bound part of the city. The USEPA 24-hour limit of 20 µg/m 3 for PM 2.5 is exceeded most of150

CHAPTER 4 – SOUTH AMERICAthe year, whereas the annual standard of 65 µg/m 3 is not exceeded. Ozone is also a regulated airpollutant and its concentrations often surpass the Colombian standard (1-hour averages > 81 ppb).In spite of significant changes in traffic management, an increasing transition from coal to naturalgas for industries, and decreases in fuel sulphur content (from over 1000 ppm in 2007 to 50 ppm in2010), over the last ten years, no significant pollution trends are observed in Bogotá, except for CO.These features are illustrated in Figure 6. The health impacts of air pollution in Bogotá have alsobeen studied [e.g., Hernández, 2009].Figure 6 - Evolution of annual average of hourly concentrations of sulfur dioxide, nitrogen dioxide, carbon monoxide,ozone, PM10 and PM2,5 in Bogotá for the period 1998-2008. Data from all monitoring stations included[Secretaría Distrital de Ambiente, 2008]Although the number and quality of studies in the last decade have resulted in an increasedknowledge of air pollution in Bogotá, the sources and impacts of air pollution in Bogotá haveincreased significantly and further research is needed to reduce uncertainties. Therefore, moreeffective air pollution research and policy strategies should be applied in the future. Air qualitymodelling would definitely help in solving these uncertainties and it has been perhaps the leastdeveloped air quality management tool in the city. Zárate et al. [2007] developed an air qualitymodel for Bogotá. Unfortunately the Secretary of the Environment has not used the model on acontinuous basis due to a lack of a capacity building strategy to use the model regularly, but therehave been recent developments towards improving and distributing emission inventories withmodelling purposes. Another contributing factor to the lack in decreasing pollution trends is theweakness in enforcing regulations.151

4.3 BUENOS AIRES, ARGENTINACHAPTER 4 – SOUTH AMERICAThe Metropolitan Area of Buenos Aires (MABA), Argentina is located at 34˚35”S and58˚40”W at an altitude of 20 m.a.s.l, with a population of ~13 million as of 2009(http://esa.un.org/unpd/wup/unup/). The MABA is situated by the estuary of the La Plata River,resulting in good ventilation and a low frequency (~ 4%) of calm situations. Summer months arecharacterized by high temperature (24 °C daily average) and humidity values (60-70%), which isassociated with the development of thunderstorms during the afternoon hours. Summerprecipitation is between 150-250 mm/month. Occasionally, these conditions are disrupted by coldfront passages originating in the South. Winter months are characterized by lower temperatures(11 °C daily average) and higher humidity (ca. 80%). Overall, the prevailing atmospheric conditionsand MABA’s topography prevent the accumulation of pollutants. At the same time, these conditionsfavour long-range transport.During the last twenty years, research institutions have performed air quality measurementactivities in the MABA region in an uncoordinated manner producing fragmented and scarceinformation for MABA. In the City Area since 1985 and for the following 20 years, air qualitymonitoring was conducted at only one monitoring site (Palermo). Previous to 1985 there is ahistorical record for Buenos Aires air quality between 1964 and 1983 [Arrechea, 1998]. The currentauthorities in the city of Buenos Aires are installing a new monitoring network composed of fourstations that meet international quality standards to measure criteria pollutants(http://www.agenciaambiental.gob.ar). In the literature, one can only find sporadic measurementsin connection with a few campaigns [e.g., Bogo et al., 2003; Reich et al., 2006; Dos Santos et al.,2009].In 2009 the annual average of 1-hour CO concentrations measured at the Palermomonitoring station was 25 % lower than that of 2002 (Figure 7). The key driver for the fall inconcentration levels is the decreasing level of emissions associated with the incorporation of newgasoline vehicles with lower emission rates in spite of the increasing number of vehicles. Timeseries of 1-hour and 8-hour CO concentrations measured by the government of the City of BuenosAires are, in general, below air quality standards. The levels increase from open to congestedareas and reach maximum levels during winter months and minimum levels during summermonths. The reported exceedances of City of Buenos Aires standard are normally registeredduring rush-hour of working days and close to vehicle exhaust emissions generally confined withinurban street canyons.In the period, 2002-2009, annual average of 1-hour NO X concentrations measured in thePalermo monitoring station exhibit fluctuations (Figure 7) largely associated with NO levels, whileNO 2 presents a flatter pattern. Similar to CO concentrations NO levels are higher in winter than insummer. NO 2 concentrations measured by the government of the City of Buenos Aires show a fewexceedances of City’s standard in the reported period.Figure 7 - Annual mean concentrations of CO (ppm) and NOX (µg m-3) from 2002 to 2009 in the reference monitoring site[Palermo, http://www.agenciaambiental.gob.ar]152

CHAPTER 4 – SOUTH AMERICAMaximum SO 2 concentrations measured in the 1970s were 90% lower than the air qualitystandards. Therefore, SO 2 was considered a pollutant of non-concern in the region and within aminimal budget for air quality monitoring the environmental authorities decided againstsystematically measuring this pollutant. This decision has remained until present. The availableSO 2 concentration data come from different measurement campaigns undertaken mostly in the late90s [e.g., Bogo et al., 2001]. However the increasing use of liquid fuels in both mobile sources,including ships, and power plants have the potential to revert the present low levels towardsincreasing values. Therefore, it may be advisable to include SO 2 in future air quality monitoringstrategies.The few measurements of O 3 concentrations in the MABA region have been undertaken byacademia. The results show that 1-hour concentrations do not exceed the standards of the City ofBuenos Aires. In accordance with ground level ozone chemistry, O 3 and NO concentrations areinversely correlated, with O 3 concentrations being lower in areas with high vehicular traffic.Because of the small size of the sample, the O 3 situation in the region cannot be assessed.In line with worldwide trends, monitoring of particles in the MABA evolved from measuringtotal suspended particulate matter (TSP) to PM 10 and more recently PM 2.5 . Measurements of TSPwere carried out mostly by governmental agencies while those of PM 10 and PM 2.5 were carried outby research groups that have been interested in a number of issues such as assessing the impactof specific sources, characterizing multi-elemental aerosol composition, and source identificationthrough receptor models. PM 10 levels are relatively high, although 24-hour concentrations do nottypically exceed the air quality standard. The monthly average PM 10 levels are in some casesclose to or slightly higher than 50 µg/m 3 . PM 2.5 levels are typically high with 24-hour concentrationsclose to or relatively higher than the air quality standard of the City of Buenos Aires whilst monthlyaverages are twice the strict limit established by the US air quality standards. Mass concentrationsof PM 10 levels increase from the inner part of the city towards the La Plata river shore while PM 2.5 isthe size fraction more homogeneously distributed. The influence of the adjacent ocean is apparentin terms of sea salt and halogens [Dos Santos et al., 2009].Lead concentrations in particulate matter were reported in three different studies [Caridi etal., 1989; Ozafrán et al., 1999; Smichowski et al., 2004]. The two latter studies show thedecreasing levels of this metal with respect to those measured in the first study, reflecting thephase out of the use of lead alkyl additives to gasoline enforced in Argentina since 1995.Until recently, no consistent emission inventory was available for Buenos Aires. The firstsystematic attempt is described in D'Angiola et al. [2010]. This inventory refers to on-road mobilesources of MABA and reports emissions for the period 2000-2006 of greenhouse gases (CO 2 , CH 4and N 2 O) and criteria pollutants (CO, NOx , NMVOCS, PM and SO 2 ) disaggregated by district andalso presented in a grid of 1x1 km 2 using a distribution algorithm described by Saide et al. [2009b].The same research group is now developing the inventory for stationary sources [Oreggioni, 2009].According to these data, on-road vehicles are the main contributors for almost all of the pollutantsin MABA with the only exception of SO 2 and CO 2 , for which stationary sources are dominant.Compared to other cities in South America, the existent relatively high emission rates fromMABA are generally not perceived as an environmental threat due to the atmospheric conditionthat rapidly vent the MABA. Nevertheless, the large population density of Buenos Aires constitutesa risk as more population is exposed to pollution, increasing the probability of health impacts. Inaddition, the strong ventilation and vertical mixing of the MABA, the tenth largest megapolis of theworld, is subject to impact long-range transport of pollution from Buenos Aires.4.4 LIMA, PERULima, Peru is located at 12˚3’S and 77°3’˚W at an altitude of 110 m.a.s.l with a populationof ~9 million inhabitants. The quasi-permanent subtropical Pacific high and the Chilean-Peruvianoceanic current determine largely the climate of Lima, which is arid with an annual precipitation of153

CHAPTER 4 – SOUTH AMERICAless than 10 mm/year. Winter temperatures range between 15°C and 19°C and summertemperatures between 21°C and 29°C with high relative humidity (ca. 80%) year around. Thepermanent high humidity is associated with the presence of a stratocumulus deck capped by thesubsidence inversion. In summer, when the subtropical high is weaker, the cloud deck breaks bymid-morning whereas in winter cloudy skies prevail all day. To the east of Lima there is a mountainrange reaching altitudes of about 1000 m.a.s.l. that creates, together with the thermal contrastbetween land and ocean, up-slope winds in the afternoon and down-slope winds in the night andmorning hours [SENAMHI, 1988].In the last few years, and in connection with the establishment of an attainment plan for theLima region, an emission inventory for stationary sources of criteria pollutants has been compiled[DIGESA, 2005]. Preliminary estimates are also available for mobile sources [MTC, 2010]. Theseestimates are not spatially distributed. Only recently, these inventories are being verified andupdated under the leadership of the National Hydrological and Meteorological Service of Peru(SENAMHI) within the framework of chemical weather forecasting applications.The Peruvian Ministry of Health (Dirección General de Salud Ambiental, DIGESA) in 2000started systematic air quality measurements at five stations. These stations provide informationabout SO 2 , NO 2 , PM 2.5 , and PM 10 . Only part of this information is available on the Internet(http://www.digesa.minsa.gob.pe/DEPA/pral2/lima.asp). Lately, SENAMHI has also compiled airquality data for O 3 , NO, NO 2 , SO 2 , and PM 10 with automated stations at five sites. These data thathave hourly resolution are available on the Internet (http://www.senamhi.gob.pe/?p=0412).Peruvian air quality standards for NO 2 (hourly 200 µg/m 3 ), SO 2 (80µg/m 3 , 24 hours) andPM 2.5 (50 µg/m3, 24 hours) are often exceeded. NO X follows traffic activity with maximumconcentrations coinciding with the morning and evening rush-hours. PM 10 concentrations arehighest in summer by mid-morning, which suggests the contribution of multiple sources.Concurrently, Arellano [2010] analyzed the mixing height over Lima and showed that the mixinglayer height reaches 500 m in the summer and 700 m in the winter. High concentrations ofparticulate matter and sulphur oxides are associated with a very old fleet (>25 years old), very highsulphur content in diesel (5000 ppm), and poor traffic control. The situation is slowly starting toimprove as a BRT system is being implemented and sulphur content is expected to decrease to 50ppm by 2015.In addition to the obvious health impacts to be expected in a city like Lima, it is alsoimportant to address the potential impacts of Lima’s pollution on cloud properties. Such impactshave been suggested earlier [e.g., Kuang and Yung, 2000] and they might be enhanced by thepresence of La Oroya copper smelter some 150 km northeast from Lima that is responsible for anannual emission of sulphur dioxide around 0.16 TgS/year [Carn et al., 2007].4.5 MEDELLÍN, COLOMBIAThe city of Medellín, Colombia is located at 6˚17’N and 75˚32’W at an altitude of 1500m.a.s.l. with a population of ~3.5 million. Medellín is situated in the Aburrá Valley between thebasins of the Cauca and Magdalena rivers. As in the case of Bogotá, the climate of the area isdetermined by the passage of the ITCZ with rainy seasons between March and May and betweenSeptember and November and relatively dry conditions during the rest of the year. The AburráValley is bordered by high mountains (ca. 2500 m.a.s.l.) that strongly influence the wind flow in theregion.A sustained effort regarding emission inventories has taken place since 2000 in the AburráValley (http://www.metropol.gov.co/aire or http://modemed.upb.edu.co). This is a joint venturebetween environmental authorities and academia. Today’s inventory for criteria pollutants and theirprecursors is a dynamical and automatized database that allows the construction of emissionscenarios including changes in emission factors, activity data, etc. Overall, this inventory goes154

CHAPTER 4 – SOUTH AMERICAbeyond mere numbers and it provides a more mechanistic approach in which the methodology istransparent to the (authorized) users.The air quality monitoring network of Aburrá Valley retrieves continuously data collected byautomated instruments. Elevated particulate matter concentrations are of concern, often exceedingthe new Colombian annual standard of 50 mg/m 3 . For instance, in 2008, annually averaged PM 10concentrations were above 50 mg/m 3 at 8 out of 10 stations. In addition, annually averaged PM 2.5concentrations, measured at four sites, were about 30 mg/m 3 . The ozone hourly standard of61ppbv and 8-hour standard of 41 ppbv standards are also frequently surpassed. Available airquality data shows the close relationship between fuel consumption and vehicle emissions of PM 10and PM 2.5 , since the maximum hourly concentrations are occur during rush-hour traffic.The national air quality network (SISAIRE, http://www.siac.gov.co) is a potentially usefultool for air quality management but it must be fed with reliable data collected in a standardizedmanner and subject to strict validation and analysis procedures. Such procedures and standardsrequire further work from the community in Colombia.A notorious decline in sulphur content in diesel fuel took place in 2008 when it was loweredfrom 3200 ppm to 2127 ppm. In 2010, diesel sulphur content was reduced again to 500 ppmthroughout all of Colombia and it is expected to be lowered to 50 ppm by 2013. Given thesignificant contribution of diesel use to mobile emissions, these measures should result in alowering of particulate matter levels in the Aburrá Valley, and elsewhere in Colombia.Observed high concentrations of PM 2.5 are linked to transportation, mainly diesel vehicleswith very old technologies. Ozone precursors are also associated to mobile sources. Hence, abetter characterization of mobile emissions is required. This will in turn require locallyrepresentative emission factors and better measurement capabilities.4.6 SANTIAGO, CHILESantiago, Chile is located at 33˚27’S and 70˚40’W at an altitude of 500 m.a.s.l with apopulation of ~6 million inhabitants. The city of Santiago is located in a semi-arid basin (annualrainfall

CHAPTER 4 – SOUTH AMERICApart of Santiago where the highest ozone mixing ratios (>100 ppbv) are usually measured.Pudahuel is in a low-income area in the western side of the city. Pudahuel is the station thatusually triggers pollution events by inhalable particle matter during the nighttime. Only CO, SO 2and PM 10 show at both stations statistically significant decreases since 1997. At Las Condes amarginal decrease in ozone is observed, coinciding with roughly unchanged or slowly increasingNO X levels since 2000. Carbon monoxide median values decrease moderately and ratherhomogenously at all stations, with a slightly steeper slope before 2000. For PM 2.5 , there is nostatistically significant trend since 2000. PM 10 shows up to 35 mg/m 3 and a 40 mg/m 3 decline inmedian and mean daily averages, respectively, over 12 years. Still, except for Las Condes, annualmean daily averages exceeded 75 mg/m 3 in 2008.Figure 8 - Air quality data collected at station Las Condes since mid 1997 up to 2008. These are box plots of daily averages.Lower quartile, median, and upper quartile values are shown by the boxes. The whiskers indicate the extent of the rest ofthe data. Outliers are illustrated with red crosses. The linear annual trends (slopes of linear regressions), and thecorresponding 95% confidence levels, of median and mean values are also indicated.Arithmetic means are indicated by green dots156

CHAPTER 4 – SOUTH AMERICAFigure 9 - Air quality data collected at station Pudahuel since mid 1997 up to 2008. These are box plots of daily averages.Lower quartile, median, and upper quartile values are shown by the boxes. The whiskers indicate the extent of the rest ofthe data. Outliers are illustrated with red crosses. The linear annual trends (slopes of linear regressions), and thecorresponding 95% confidence levels, of median and mean values are also indicated.Arithmetic means are indicated by green dots157

CHAPTER 4 – SOUTH AMERICAThe National Commission for the Environment (CONAMA, now Ministry for theEnvironment) has over the years driven various campaigns to assess the composition of particles[e.g., Artaxo et al., 1999; Didyk et al., 2000; Kavouras et al., 1999; Gramsch et al., 2009] and toaddress speciation of volatile organic compounds and photochemical products [e.g., Rappenglücket al., 2000; Rubio et al., 2004; Rappenglück et al., 2005]. Other studies have been developedwithin a pure academic framework addressing, again, particles and photochemistry [e.g., Sienra etal., 2005; Sienra and Rosazza, 2006; Rubio et al., 2006; Richter et al., 2007; Morata et al., 2008;Elshorbany et al., 2009a; 2009b; Seguel et al., 2009].In addition to air quality stations, a meteorological network was put in place in 1997. Itconsisted of 22 stations and it was designed to capture mesoscale meteorological featuresinduced by complex topography in the area. Today, only 10 stations are operational. Verticalsoundings have been sporadic, and only since 2007, a ceilometer located in downtown Santiago isproviding a record of daytime mixed layer for cloud free days [Muñoz and Undurraga, 2010]. In2010, a backscatter LIDAR was installed by the Chilean Weather Office that is expected to provideunprecedented information about atmospheric stability and aerosol properties.Regarding impacts of air pollution, health issues have received the greatest attention,particularly the association between particulate matter and morbidity and mortality statistics [e.g.,Adonis and Gil, 1993; Ostro et al., 1996; Ostro et al., 1999; Ilabaca et al., 1999; Cifuentes et al.,2001a; 2001b]. A few studies have approached health issues within the framework of climatechange scenarios and mitigation measures [e.g., Cifuentes et al., 2001a; 2001b]. Less attentionhas been paid to effects on vegetation [e.g., García-Huidobro et al., 2001]. Only recently, thepotential impacts of air pollution on the stratus deck downwind from Santiago are beginning to bestudied [e.g., Mena et al., 2009; Spak et al., 2010; Saide et al., 2012; Heinrichs et al., 2012].Since the implementation of the attainment plan for Santiago, CONAMA has supportedformulation of emission inventories for base years 1997, 2000, and 2005, and a projection for 2010[CENMA, 1997; CENMA, 2000; DICTUC, 2007]. Unfortunately, over time this endeavour has beencontracted under consultancies of different organizations giving room for differences betweenmethodologies and even lack of transparency in some results.Mobile emissions were estimated in the CENMA inventories (1997, 2000) according to abottom-up methodology [Corvalán et al., 2002] considering official traffic modelling results,comprehensive traffic counts, analysis of databases for vehicle technology distribution andemission factors from COPERT III model [Ntziachristos and Samaras, 2000] and localmeasurements. Later, subsequent contractors have modified this methodology but it is unclearwhat the modifications are. Industrial and biogenic emissions are estimated following USEPAmethodologies.In the first version of the attainment plan (1997), curbing measures considered theintroduction of natural gas in the industrial sector, a reduction in sulphur content in diesel (from5000 ppm in 1989 to 1000 ppm in 1997, and 300 ppm in 2001), introducing emission controls forvehicles and phasing out 3000 old buses, etc. These measures explain the relatively fast reductionin PM 10 and SO 2 between 1997 and 2000. A second revision of the attainment plan in 2004emphasized emission control for vehicles, including a reduction in diesel sulphur content to 50 ppm,and the introduction of an ambitious public transportation system called Transantiago(http://www.transantiagoinforma.cl/). Transantiago intended to completely overhaul the existingtransportation system with new EURO III diesel buses, and reducing the total amount of busesfrom more than 8000 to ~4000. Soon after its implementation in early 2006, the collapse of thesystem due to increased demand required that 2500 old buses (which had been removed fromcirculation) to be reintroduced, bringing the current total to 6500 units. The contracts required thatthese old buses would use retrofitted particulate filters, as their emissions are roughly 10 timeshigher than the new Euro III buses. To date these buses continue to circulate without particulatefilters, making the success of Transantiago’s emission reductions less apparent.158

CHAPTER 4 – SOUTH AMERICABetween 2000 and 2006, a toll based urban highway was built, which allowed sprawlingsuburbs to connect with the city in substantially less time. The combination of a slow publictransportation system with an efficient highway system may have led previous users of the publictransportation system to buy cars and motorcycles. From 2000 to 2008, the number of cars inSantiago grew by 42% to 1.2 million. This growth in private transportation probably accounts forthe lack of substantial reductions in pollutant levels despite the improvements in fuel and vehicletechnology over the same period. In addition, after 2004, imports of natural gas from Argentinawere restricted forcing industry to reconvert to other liquid fuels, such as petroleum products ordiesel. This caused increased SO 2 and NO X emissions, ultimately leading to increased PM 2.5 yearlymeans for 2007 and 2008. It is hoped that the recent installation of a Liquefied Natural Gasterminal will allow natural gas use to be re-established in Chile. The latest revision of the air qualitypollution prevention programme (2009) includes retrofitting particulate filters in new and old busesand trucks, a scrapping programme for older gasoline and diesel vehicles, introducing a morestringent emission standard for wood burning heaters, banning agricultural burns, and a cap andtrade system for SO 2 and NO X emissions from industry.According to Fuenzalida et al. [2006] who provided the first set of regional present andfuture climate scenarios using dynamical downscaling, the central part of Chile, where Santiago islocated, will see a 40% decline in precipitation, an increase in surface temperatures, and asouthward expansion of the subtropical high. These changes may in turn affect stability andventilation but these aspects were not addressed in this study. One can only speculate that theprobable southward expansion of the arid regime could intensify the radiatively driven circulation inthe Santiago basin, generating more summer like conditions, which are very favourable forphotochemical pollution. If the degree of centralization persists, the expected demographicscombined with a warmer climate may result in increased vulnerability [e.g., Bell et al., 2008].Santiago’s air quality has been subject to multiple studies since, at least, the early 1980’s.Over the years, the amount and the complexity of such studies have increased notoriously. Like inmany other cities in the world, research and management initiatives in Santiago were triggered byacute air pollution problems, in this case very high concentrations of inhalable particles (800 mg/m 3hourly averages in the late 1980’s) and associated respiratory problems that followed fromuncontrolled traffic and urban growth in the mid 70’s [e.g., Romero et al., 1999]. Therefore, theaccent of these initiatives has focused first on reducing extreme pollution events that areresponsible for acute effects and short-term air quality standards. Measures have focused on largeemitters: industries, non-catalytic cars, buses and trucks [e.g., Emmelin et al., 2007; Morales et al.,2006]. Such curbing measures could be identified based on relatively imprecise emissioninventories for criteria pollutants and simple receptor modelling approaches. However, as theattainment objectives become more ambitious (e.g., long-term air quality standards for dealing withaccumulative effects), the need of determining more subtle cost-effective measures and moreprecise tools increases. This, in turn, requires coordinated efforts to provide more of a systemicapproach [e.g., Molina and Molina, 2004].The number of active, highly qualified (PhD) researchers that can contribute to address airquality and climate issues is increasing but it is still insufficient. For instance, according to theChilean Academy of Science, in 2005 there were around 50 active scientists in the area ofanalytical and environmental chemistry, twice as many as in 1997 [Allende et al., 2005]. InAtmospheric Science, there are less than 20 active researchers at PhD level, and this number hasprobably tripled over the last decade. Up to now, the connection between policy making andresearch has been made based on short-term consultancies, which by construction hampers theestablishment of necessary synergies and the study of more complex issues. Hence, it appearsnecessary to create a research consortium able to convey scientists from different disciplines,combining natural and social science, which, in addition to scientific knowledge, is able to provideindependent opinions to environmental authorities. Such consortium could provide a platform forinternational collaboration and capacity building.159

CHAPTER 4 – SOUTH AMERICA4.7 SÃO PAULO, BRAZILThe Metropolitan Area of São Paulo, Brazil (MASP) is located at 23˚31’S and 46˚37’W at analtitude of 720 m.a.s.l. with a population of ~20 million inhabitants. The MASP is situated 60 kmnorthwest of the South Atlantic coast and in a valley bounded by mountain ranges on thenorthwest side and to the south and southeast by the “Serra do Mar” scarp (ca. 1000 m.a.s.l.).MASP is one of the largest urban regions in the world. It covers a total area over 8000 km 2 and19 % of this area is highly urbanized. Additionally, MASP is the most industrialized area in SouthAmerica and is different from other cities in South America due to its unconventional mix of vehicletypes. The vehicle fleet consists of approximately 9.7 million vehicles that burn on a variety ofgasoline blends, including oxygenated gasoline, as well as ethanol and bio-diesel. The high levelsof pollution in the MASP constitute a critical health problem in the region [Lin et al., 1999; Braga etal., 2001; Martins et al., 2002; CETESB, 2010].The climate of São Paulo is characterized by a dry winter during June-August and a wetsummer during December-March. The minimum values of daily monthly-averaged temperatureand relative humidity occur in July and August (16 °C and 74%, respectively), and the minimummonthly-accumulated precipitation occurs in August (35 mm). Combined effects of the geographiclocation and relative intensity of the semi-stationary South-Atlantic Anticyclone and continental lowpressuresystems control the seasonal variation of surface winds in São Paulo. They inducesurface winds from NE-E during the winter and N-NE during the summer. In addition, cold frontsfrequently affect this pattern in winter, as well as sea-breeze fronts [Oliveira et al., 2003].MASP has since 1981 a systematic air quality monitoring programme run by the StateEnvironmental Agency (CETESB, http://www.cetesb.sp.gov.br). Nowadays 21 automatic stationsare in operation in MASP in addition to 40 automatic and 47 manual station operating throughoutthe state of São Paulo. In addition, measurement campaigns of other tracers have been performedin MASP. Results of these measurements can be found in the literature [e.g., Castanho and Artaxo,2001; Miranda et al., 2002; Andrade et al., 2004; Ynoue and Andrade, 2004; Miranda and Andrade,2007; Martins et al., 2006; Sánchez-Ccyollo et al., 2009].The concentration of pollutants in São Paulo in the last thirteen years shows, in spite of thevehicular fleet increase, a sharp drop in the concentrations of CO, NO X , PM 10 and SO 2 over theMASP (Figure 10). The decline in concentrations of these pollutants is mostly due to the BrazilianVehicular Emission Control Programme (PROCONVE), described elsewhere [Szwarcfiter et al.,2005; Sánchez-Ccoyllo et al., 2007]. In 1979, the Brazilian government started the AlcoholNational Programme (PROALCOOL), which led to new and important changes in the fuelcomposition of light-duty vehicles (LDV). In 2005, Petrobras (Brazilian Oil Company) introducedthe S500 diesel with sulphur limit of 500 ppm replacing the 2000 ppm diesel at metropolitan areas.There was also a programme to control industrial emissions starting in the late 80’s, when manyfuel boilers were switched to electrical power or natural gas. Only in the case of O 3 concentrations,a declining trend is not observed. The maximum hourly Brazilian national air quality standard for O 3is frequently violated in MASP [Freitas et al., 2005b; Martins and Andrade, 2008a; Sánchez-Ccoyllo et al, 2009].MASP has an official emission inventory, which is annually updated [e.g., CETESB, 2010].However, this inventory is not geographically distributed. A great effort has been made to improvethe emission inventory for MASP [Ynoue and Andrade, 2004; Vivanco and Andrade, 2006; Martinset al., 2006; Sánchez-Ccyollo et al., 2007; Sánchez-Ccyollo et al., 2009]. Like in other urban areas,vehicles in MASP contribute greatly to emissions. According to the official emission inventorymobile sources are responsible for 97% of carbon monoxide (CO) emissions, 97% ofhydrocarbons emissions (HC), 96% of nitrogen oxides (NO X ), 32% of sulphur oxides (SO X ), and40% of particulate matter [CETESB, 2010].To improve the mobile emission inventory for São Paulo, measurements inside roadtunnels were performed [Vasconcellos et al., 2005; Martins et al., 2006; Sánchez-Ccoyllo et al.,2009]. The mean contributions of heavy-duty vehicles (HDV) to emissions of BC, PM 10 , PM 2.5–10 ,160

CHAPTER 4 – SOUTH AMERICAand PM 2.5 were 29, 4, 6, and 6 times higher than were those of LDVs. The main constituent ofdiesel exhaust particles was found to be black carbon (BC). The calculated emission factors wereused in air quality models to estimate the impact the vehicle fleet has on air quality [Martins andAndrade, 2008a; 2008b; Sánchez-Ccoyllo et al., 2007].Figure 10 - Annual mean concentrations of CO (ppm), NO2 (µg m -3 ), PM10 (µg m -3 ) and SO2 (µg m -3 ) from 1996 to 2006Air pollution exposure has shown to cause increased respiratory mortality and morbidity[Gouveia and Fletcher, 2000; Martins et al., 2002; Vermylen et al., 2005; Bourotte et al., 2007].Also, some studies in São Paulo have shown the impacts of air pollutants in mice [Silva et al.,2008] and the mutagenic activity of air organic matter extracts [e.g., Umbuzeiro et al., 2008]. Inaddition, Martins et al. [2010] investigated the relationships among air quality, aerosol sizedistribution, and meteorological conditions using data from aerosol number size distribution (9.82-414 nm) and numerical modelling for São Paulo. They suggested that the period characterized asclean, based on PM 10 measurements, could not be considered a period presenting low healthimpacts, when using ultrafine particles concentrations as criteria.Winter atmospheric measurements of gaseous carbonyl and carboxylic acids were carriedout in urban sites in the city of São Paulo [e.g., Montero et al., 2001]. High values of formic toacetic ratios were found suggesting that photochemical production was the predominant source ofthese acids during the afternoon. Higher average mixing ratios of acetaldehyde and formaldehydewere found in the morning and gradually decreased from midday to evening. In the morning,vehicle direct emission seemed to be the primary source of formaldehyde and acetaldehyde,whereas at midday and evening, these compounds appeared to be mainly formed byphotochemistry [Montero et al., 2001]. In recent work, mutagenic and carcinogenic organiccompounds were investigated [Vasconcellos et al., 2008]. Most nitro-PAH (polycyclic aromatic161

CHAPTER 4 – SOUTH AMERICAhydrocarbons) were related to diesel powered vehicle emission. The exceptions are 2-nitrofluoranthene and 2-nitropyrene, photochemical compounds that appear as the most abundantin airborne particles, which seems to be associated with sugarcane emissions, suggesting thatagricultural activities released the precursors of ambient nitro-PAH identified at all sites.A tentative identification of some of the mechanisms that influence the concentrations oftrace metals and water-soluble ions in different sites in São Paulo State was done [Vasconcellos etal., 2007]. Sugarcane burning and industrial activities are most strongly implicated. In addition, theburning of solid waste and biomass is responsible for the high chloride ion concentrations. In allsites the abundance of nitrate and sulphate suggested vehicle emissions. Remote sources alsocontribute to the concentrations of aerosol produced by fossil fuel combustion, soil resuspension,and biomass burning.The characterization of particles in the atmosphere of São Paulo started in the late 70s[Orsini and Boueres, 1977]. The first large experiment in Brazil was performed to characterize thecomposition of particles at important Brazilian cities; the results are presented in Orsini et al. [1986].In the 80´s, receptor models to identify the sources of the particles came into use. PrincipalComponent analysis and Absolute Principal Component Analysis were applied with theidentification of mobile emissions as the principal source of fine particles and soil resuspension forthe coarse mode for São Paulo Metropolitan Area [Andrade et al., 1994]. Castanho & Artaxo[2001] showed that a significant fraction of fine particulate matter is constituted by organic carbon(OC) representing approximately 40% of the mass concentration. The BC mean concentrationrepresented 21% of PM 2.5 . In total, 60% of the fine particles mass concentration is explained bycarbon compounds, mainly due to vehicular emissions, being the heavy-duty diesel the mainsource of fine particles [Sanchez-Ccoyllo et al., 2009]. Recent studies regarding the sizedistribution and composition of the São Paulo aerosol using Scanning Mobility Particle Size(SMPS-TSI) have been performed. Studies considering trace metals, and chemical speciation foraddressing secondary aerosol formation have also been recently undertaken.There is concern in the scientific community and government that air quality standardsshould be reviewed mainly for particulate matter. In Brazil, there is no air quality standard for PM 2.5 ,although there are many studies showing its importance. There is also the concept that it would beimportant to measure VOCs, mainly those originated from the emission of alcohol fuelled vehicularmotors. In addition, also continuous measurements of greenhouse gases, at least CO 2 , CH 4 andN 2 O should be done for São Paulo. Brazil has nowadays only one station to measure these gasesand has to create a greenhouse gases inventory for its enlarged urban areas.4.8 RIO DE JANEIRO, BRAZILThe Metropolitan Region of Rio de Janeiro (MARJ) is located at 22˚54’S and 43˚13’W at analtitude of 30 m.a.s.l. with a population of ~12 million. The MARJ is situated on the Atlantic Coastof Brazil and occupies an area of 4825 km2 [CIDE, 2008; Godoy et al., 2009]. The uncontrolledgrowth of the region becomes clear from the assessment of population density that exceeds 1900inhabitants per km 2 and is the highest in Brazil [Corrêa and Arbilla, 2007; Godoy et al., 2009;Gioda et al., 2011].The climate of the region is characterized by a well-defined dry season during the SouthernHemisphere winter and a rainy season in summer, associated with the occurrence of convectiverainfall. Synoptic scale phenomena such as the Convergence Zone of the South Atlantic, coldfronts, the position of Anticyclone Subtropical South Atlantic, and the upper air cyclonic vortex areimportant to the rainfall in the region. Corrêa et al. [2003] also points out that rainfall rates areinfluenced by factors related to geographical features of the region.Air quality monitoring in the MARJ began in the late 60's with intermittent measurements oftotal suspended particles (TSP). This manual sampling network is still in operation and nowadaysperforms measurements of TSP and inhalable particulate matter (PM 10 ) every six days. Since the162

CHAPTER 4 – SOUTH AMERICAlate 90's, automatic air quality monitoring stations were acquired and the manual sampling networkwas expanded throughout the region. Nevertheless, the existent monitoring network does notcover most of the Metropolitan area.According to air quality annual reports [e.g., FEEMA, 2008], the highest pollutantconcentration levels measured in the region are particulate matter and ozone. High particulatematter levels have been persistently observed in the MARJ since the beginning of air qualitymonitoring [Trindade et al., 1980; Kretzschmar, 1994; Campos et al., 1999; Quiterio et al., 2004;Quiterio et al, 2008]. Although values are still higher than the Brazilian standards, Kretzschmar[1994] identified a decreased trend in average and extreme levels of TSP concentrationsregistered in Rio. However, annual mean values still are higher than the national air qualitystandards established in 1990 (80µg.m-3 and 50µg.m-3 for TSP and PM 10 , respectively).A few epidemiological studies discuss the health effects of these high particulate matterlevels in the MARJ [Penna and Duchiade, 1991; Daumas et al., 2004; Gouveia et al., 2003].Quiterio et al. [2008] showed that Zn, Cu, Cd and Pb present in particulate matter samples fromthe area are higher in comparison with other urban and industrial areas. Ozone concentrationslevels that exceed the Brazilian standard of 160 µg.m-3 (1 hour) have been registered since 2004.These high values are mostly measured in sites located in near the area of a petrochemicalcomplex [FEEMA, 2008]. It is important to emphasize that the extension of the ozone problem inthe MARJ is not yet fully known since the existent network does not cover most parts of the region.MARJ has the second largest number of emission sources in Brazil, mainly distributed betweenseven industrial districts and in several traffic routes where more than 2.8 million vehicles circulate[CIDE, 2008].In 2004, the first inventory of atmospheric pollutant emissions from stationary and mobilesources in the region was completed [FEEMA, 2004]. The vehicular fleet in MARJ runs off ofgasohol (64.7%), ethanol (11.7%), compressed natural gas - CNG (12.3%), and diesel (8.8%)[Machado et al., 2009]. Major industrial emissions in the area are due to petrochemical and energygeneration industries [FEEMA, 2004]. Industrial sources are the largest contributor to sulphurdioxide emissions (SO 2 ) at 88% and to particulate matter (PM 10 ) at 58%. Vehicular emission ofcarbon monoxide (CO) is significantly higher as expected and represents 98% of the total. Of thetotal, approximately 67% of emissions of nitrogen oxides (NO X ) and hydrocarbons are also due tovehicular emissions [FEEMA, 2004]. Lately, sophisticated photochemical measurements havebeen undertaken in Rio de Janeiro (Correa et al, 2010).4.9 SUMMARY AND OUTLOOKAir quality is an issue of general concern in many South American capitals (e.g., Bogotá,Lima, Santiago, and Sao Paulo). In addition, it is a growing problem in medium-size cities (e.g.,Medellín.). Attainment plans have been developed for these urban agglomerations generallyreducing the most acute problems over the last decades. Curbing measures have been identifiedbased on relatively simple approaches involving more or less accurate emission estimates andemission-receptor models, and of course adopting experiences from the developed world.Typically, such measures considered the replacement of fossil fuel by natural gas, ethanol, biodiesel,etc., and a reduction in fuel sulphur content. However, when objectives become moreambitious and cost-effective measures less obvious, there is an increased need of local knowledgeand articulated long-term planning. Unfortunately, except in Brazil, material and human resourcesfor atmospheric research in South America on a country-by-country basis are far too small to allowa significant contribution to international programmes and to produce sustained impacts on localdevelopment. Thus, international linkage among our countries is critical. Further, it is essential thata significant fraction of our resources be dedicated to capacity building at various levels.Coordinated activities should focus on key steps such as reconciling global inventories with,when available, regional, country and city-specific data, and putting in to place validation tools,including inverse modelling, which in turn requires better monitoring. It is very important to note163

CHAPTER 4 – SOUTH AMERICAthat such activities in the region require establishing a network involving not only members ofacademia but also technical staff from governmental agencies who are in charge of emissioninventories to assure the interests of both groups are met while harmonizing the differentapproaches. All this is needed in order to be able to accurately evaluate the efficiency of policiesand to improve our diagnostic and prognostic abilities, not only in the short-term (days to fewyears) but also in the long-term (years to decades).There is a growing need of an integrated monitoring network that, in addition to solelyaddress the attainment of health related standards, is able to address the many processesresponsible for those impacts as well as the impacts on vegetation and climate. This will require, inaddition to stronger coordination and planning efforts, the integrated use of modelling tools. Also,as there is an increasing need for and cost in instrument calibration and maintenance, moreintensive use and sharing of local laboratory and analytical facilities is badly needed.Often, air quality studies in South American cities remain largely isolated from one another,short-term, and lack a scientific synthesis. Moreover, scientific research has not sufficientlypermeated into environmental policies. The establishment of scientific consortia and networks isone possibility, as it may be more cost-effective manner to promote the exchange and sharing ofexpertise, laboratory and computational resources, and human resources. Such a community,which is already emerging, would be able to deal with the particular “flavours” of our cities (e.g.,sugarcane, ethanol fuel, biomass burning, smelting, power plants), in their particular human andnatural geography.ReferencesAdonis, M., & Gil, L. (1993). Mutagenicity of Organic Extracts From Santiago (Chile) AirborneParticulate Matter. Mutation Research/Environmental Mutagenesis and Related Subjects,292(1), 51-61. doi: 10.1016/0165-1161(93)90007-MAdonis, M., & Gil, L. (2001). Indoor Air Pollution in a Zone of Extreme Poverty of MetropolitanSantiago, Chile. Indoor and Built Environment 10(3-3), 138-146. doi:10.1177/1420326X0101000304Allende, J., Babul, J., Martinez, S., & Ureta, T. (2005). Análisis y proyecciones de la cienciachilena 2005. Academia Chilena de Ciencias.Alonso, M., Longo, K., Freitas, S., Fonseca, R., Marcecal, V., Pirre, M., & Gallardo, L. (2010). Anurban emissions inventory for South America and its application in numerical modelling ofatmospheric chemical composition at local and regional scales. Atmospheric Environment.Andrade, F., Orsini, E., & Meanhaut, W. (1994). Relation between aerosol sources andmeteorological parameters for inhalable atmospheric particles in São Paulo city, Brazil.Atmospheric Environment, 28(14), 2307-2315Andrade, M. F., Ynoue, R. Y., Harley, R., & Miguel, A. H. (2004). Air quality model simulatingphotochemical formation of pollutants: the São Paulo Metropolitan Area, Brazil. InternationalJournal Environmental Pollution, 22, 460-475Arellano, C. (2010). Estudio de la variación estacional y diurna del comportamiento de la Capa deInversión Térmica sobre la Lima Metropolitana. Universidad Nacional de San Marcos,Facultad de Ciencias Físicas.Arrechea, G. (1998). Datos de calidad de aire en la Ciudad de Buenos Aires. Programa de AireLimpio Buenos Aires, Gobierno de la Ciudad de Buenos Aires, Subsecretaría de MedioAmbiente, in Frese(Fogliatti y J.R. Walsh (Eds)), 209-230Artaxo, P., Oyola, P., & Martinez, R. (1999). Aerosol composition and source apportionment inSantiago de Chile. Nuclear Instruments and Methods in Physics Research Section B- BeamInteractions with Material and Atoms, 150(151-154),409-416Behrentz, Eduardo, Sanchez, N., Fandino, M., & Rodriguez, P. (2009). Inventario de emisionesprovenientes de fuentes fijas y móviles. Proyecto contratado por la Secretaría Distrital deAmbiente de Bogotá y Desarrollado por el Grupo de Estudios en Sostenibilidad Urbana yRegional de la Universidad de los Andes164

CHAPTER 4 – SOUTH AMERICABell, M. L., O'Neill, M. S., Ranjit, N., Borja-Aburto, V. H., Cofuentes, L. A., & Gouveia, N. C. (2008).Vulnerability to heat-related mortality in Latin America: a case-crossover study in Sao Paulo,Brazil, Santiago, Chile and Mexico City, Mexico. International Journal of Epidemiology, 37(4),796-804Bogo, H., Gomez, D., Reich, S., Negri, R., Roman, E. S., & (2001). Traffic pollution in a downtownsite of Buenos Aires City. Atmospheric Environment, 35, 1717-1721Bogo, H., Marcelo, O., Castro, P., Ozafran, M. J., Kreiner, A., Ernesto, C. J., & Negri, R. M. (2003).Study of atmospheric particulate matter in Buenos Aires city. Atmospheric Environment,37(8), 1135-1147. doi: 10.1016/S1352-2310(02)00977-9Bourotte, C., Curi-Amarante, A.-P., Forti, M.-C., Pereira, L. A. A., Braga, A. L., & Lotufo, P. A.(2007). Association between ionic composition of fine and coarse aerosol soluble fractionand peak expiratory flow of asthmatic patients in Sao Paulo city (Brazil). AtmosphericEnvironment, 41(10), 2036-2048. doi: 10.1016/j.atmosenv.2006.11.004Braga, A. L., Saldiva, P. H., Pereira, L. A., Menezes, J. J., Conceicao, G. M., Lin, C. A., Zanobetti,A., Schwartz, J., and Dockery, D. W. (2001). Health effects of air pollution exposure onchildren and adolescents in São Paulo, Brazil. Pediatr Pulmonol, 31, 106-113Campos, I. C. B., Pimentel, A. S., Correa, S. M., & Arbilla, G. (1999). Simulation of Air Pollutionfrom Mobile Source Emissions in the City of Rio de Janeiro. Journal of the BrazilianChemical Society, 10(3), 203-208Caridi, A., Kreiner, A. J., Davidson, J., Davidson, M., Debray, H., Hojman, D., & Stantos, D. (1989).Determination of Atmospheric Lead Pollution of Automitve Origin. Atmospheric Environment,23, 2855-2856Carn, S. A., Krueger, A. J., Krotkov, N. A., Yang, K., & Levelt, P. F. (2007). Sulfer DioxideEmissions from Peruvian Copper Smelters Detected by the Ozone Monitoring InstrumentGeophys. Res. Lett, 34(L09801). doi: 10.1029/2006GL029020Castanho, A. D. A., & Artaxo, P. (2001). Wintertime and summertime São Paulo Aerosol sourceapportionment study. Atmospheric Environment, 29, 4489-4902CENMA. (1997). Mejoramiento del inventario de emisiones de la RM. Informe Final ComisiónNacional del Medio Ambiente. Available from: Oficina de Informaciones -OIRS- de laDirección Ejecutiva de Conama Nacional. Teatinos Nº254, Santiago.CENMA. (2000). Inventario de emisiones atmosféricas de la RM para 1997 y proyecciones al2005. Informe Final Comisión Nacional del Medio Ambiente. Available from: Oficina deInformaciones -OIRS- de la Dirección Ejecutiva de Conama Nacional. Teatinos Nº254,Santiago, Chile.CETESB. (2010). Relatório de qualidade do ar no Estado de São Paulo 2009. São Paulo.CIDE. (2008). Centro de informação e dados do Rio de Janeiro.Cifuentes, L., Borja-Aburto, V. H., Gouveia, N., Thurston, G., & Davis, D. L. (2001a). Assessing thehealth benefits of urban air pollution reductions associated with climate change mitigation(2000-2020): Santiago, Sao Paulo, México City, and New York. Environmental HealthPerspectives, 109(3), 419-425Cifuentes, L., Borja-Aburto, V. H., Gouveia, N., Thurston, G., & Davis, D. L. (2001b). Climatechange. Hidden health benefits of greenhouse gas mitigation. Science, 293(5533), 1257-1259. doi: 10.1126/science.1063357Corrêa, S. M., & Arbilla, G. (2007). A two-year monitoring program of aromatic hydrocarbons in Riode Janeiro downtown area. Journal of the Brazilian Chemical Society, 18, 539-543. doi:10.1590/S0103-50532007000300007Corrêa, S. M., Arbilla, G., & Martins, E. M. (2003). Formaldehyde and acetaldehyde in a high trafficstreet of Rio de Janeiro, Brazil. Atmospheric Environment, 37(1), 23-29. doi: 10.1016/S1352-2310(02)00805-1Correa, S. M., Arbilla, G., Martins, E. M., Quiterio, S. L., Guimaraes, C. d. S., & Gatti, L. V. (2010).Five years of formaldehyde and acetaldehyde monitoring in the Rio de Janeiro downtownarea - Brazil, Atmospheric Environment. Atmospheric Environment, 44(19), 2302-2308. doi:10.1016/j.atmosenv.2010.03.043165

CHAPTER 4 – SOUTH AMERICACorvalán, R., Osses, M., & Urrutia, C. (2002). Hot emission model for mobile sources: applicationto the Metropolitan Region of the city of Santiago, Chile. Journal of the Air and WasteManagement Association, 52(2), 167-174D’Almeida, E., Delgado, R., Rodrigues, L., Baeza, C., Silva, L. d., Gallardo, L., Longo, K., andFreitas, S. (2008). SAEMC_GRID: SOUTH AMERICA MEGACITIES EMISSIONS ANDCLIMATE GRID. LAGRID 08. Campo Grande. Retrieved from http://lagrid08.lncc.br/).D’Angiola, Ariela, Dawidowski, L. E., Gómez, D. R., & Osses, M. (2010). On-road traffic emissionsin the metropolitan area of Buenos Aires, Argentina Atmospheric Environment, 44(4), 483-493.Daumas, R.P, Mendonça, GA, & León, A. P. (2004). Air pollution and mortality in the elderly in Riode Janeiro: a time-series analysis. Caderno de Saúde Pública – Rio de Janeiro, 20(1), 311-319DICTUC. (2007). Actualización del inventario de emisiones de contaminantes atmosféricos en laRM 2005. Informe Final Comisión Nacional del Medio Ambiente. Retrieved July 2010http://www.conama.cl/rm/568/articles-41184_Dictuc0ActuaizaIforFinal.pdf.Didyk, B. M., Simoneit, B., Pezoa, A., Riveros, L., & Flores, A. (2000). Urban aerosol particles ofSantiago, Chile: organic content and molecular characterization. Atmospheric Environment,34(8), 1167–1179. doi: 10.1016/S1352-2310(99)00403-3DIGESA. (2005). Resultados del Inventario de emisiones de fuentes fijas- Cuenca Atmosférica dela ciudad de Lima – Callao.Dos Santos, M., Gomez, D., Dawidowski, L., Gautier, E., & Smichowski, P. (2009). Determinationof water-soluble and insoluble compounds in size classified airborne particulate matter.Microchemical Journal, 91(1), 133-139. doi: 10.1016/j.microc.2008.09.001Elshorbany, Y. F., Kleffmann, J., Kurtenbach, R., Lissi, E., Rubio, M., Lissi, R., Villena, G.,Gramsch, E., Rickard, A.R, Pilling, M.J., and Wiesen, P. (2009b). Seasonal dependence ofthe oxidation capacity of the city of Santiago de Chile. Atmospheric Environment, 44(40),5383-5394. doi: 10.1016/j.atmosenv.2009.08.036Elshorbany, Y. F., Kleffmann, J., Kurtenbach, R., Lissi, E., Rubio, M., Lissi, R., Villena, G.,Gramsch, E., Rickard, A.R, Pilling, M.J., and Wiesen, P (2009a). Summertime photochemicalozone formation in Santiago, Chile. Atmospheric Environment, 43(40), 6398-6407. doi:10.1016/j.atmosenv.2009.08.047Emmelin, A., & Wall, S. (2007). Indoor air pollution: a poverty-related cause of mortality among thechildren of the world. Chest, 132(5), 1615-1623FEEMA. (2004). Inventário de Fontes Emissoras de Poluentes Atmosféricos da RegiãoMetropolitana do Rio de Janeiro. Retrieved August 2004 http://www.feema.rj.gov.br/FEEMA. (2008). Relatório anual da qualidade do ar. Retrieved June 2008http://www.feema.rj.gov.brFreitas, E. D., Martins, L. D., Silva Dias, P. L., & Andrade, M. F. (2005b ). A simple photochemicalmodule implemented in RAMS for tropospheric ozone concentration forecast in theMetropolitan Area of São Paulo - Brazil: coupling and validation. Atmospheric Environment,39(34), 6352-6361. doi: 10.1016/j.atmosenv.2005.07.017Freitas, S., Longo, K. M., Dias, S., Dias, P. S., Chatfield, R., Prins, E., Artaxo, P., Grell, G., andRecuero, F. (2005a). Monitoring the transport of biomass burning emissions in SouthAmerica. Environmental Fluid Mechanics, 5(1-2), 135 - 167Freitas, S. R., Longo, K. M., Silva Dias, M. A. F., Chatfield, R., Silva Dias, P., Artaxo, P., Andrea,M.O., Grell, G., Rodrigues, L.F., Fazenda, A., and Panetta, J. (2009). The Coupled Aerosoland Tracer Transport model to the Brazilian developments on the Regional AtmosphericModeling System (CATT-BRAMS) - Part 1: Model description and evaluation. AtmosphericChemistry and Physics, 9, 2843-2861Fuenzalida, H., Falvey, M., Rojas, M., Aceituno, P., & Garreaud, R. (2006). Estudio de lavariabilidad climática en Chile para el siglo XXI. Informe final CONAMA. Universidad deChile.166

CHAPTER 4 – SOUTH AMERICAGallardo, L., Olivares, G., Langner, J., & Aarhus, B. (2002). Coastal lows and sulfur air pollution inCentral Chile. Atmospheric Environment, 36(23), 3829-3841García-Huidobro, T., Marshall, F., & Bell, J. (2001). A risk assessment of potential crop losses dueto ambient SO 2 in the central regions of Chile. Atmospheric Environment, 35(29), 4903-4915.doi: 10.1016/S1352-2310(01)00344-2Garreaud, R., Rutllant, J., & Fuenzalida, H. (2002). Coastal lows in north-central Chile: Meanstructure and evolution. Mon. Wea. Rev. , 130, 75-88Gioda, A., Silva Amaral, B., Luizi Gonçalves Monteiro, I., and Dillenburg Saint’Pierre, T. (2011).Journal of Environmental Monitoring (13), 2134–2142Godoy, M. L. D. P., Godoy, J. M., Roldão, L. A., Soluri, D., & R.A, D. (2009). Coarse and fineaerosol source apportionment in Rio de Janeiro, Brazil. Atmospheric Environment, 43(14),2366-2374. doi: 10.1016/j.atmosenv.2008.12.046Gouveia, & Fletcher. (2000). Time series analysis of air pollution and mortality: effects by cause,age and socioeconomic status. J Epidemiol Community Health, 54(10), 750-755. doi:10.1136/jech.54.10.750Gouveia, N., Mendonça, G. A. S., León, A. P., Correia, J. E. M., Junger, W. L., Freitas, C. U.,Caumas, R.P., Martins, L.C., Giussepe, L., Conceicao, G.M., Manerich, A., and Cunha-Cruz,J. (2003). Air pollution and health effects in two Brazilian metropolis. Epidemiologia eServiços de Saúde, 12(1), 29-40. doi: 10.5123/S1679-49742003000100004Gramsch, E., Gidhagen, L., Wahlin, P., Oyola, P., & Moreno, F. (2009). Predominance of sootmodeultrafine particles in Santiago de Chile. Atmospheric Environment, 43(14), 2260–2267.doi: 10.1016/j.atmosenv.2009.01.047Heinrichs, D., K. Krellenberg, B. Martinez (Eds). (2012). Risk Habitat Megacity. Springer.Hernández, L. J. (2009). Asociación entre la contaminación del aire y la morbilidad porenfermedad respiratoria aguda en menores de 5 años en tres localidades de Bogotá.Universidad Nacional de Colombia. Programa de doctorado en Salud Pública. Tesisdoctoral.Hoelzemann, J. J., Longo, K. M., Fonseca, R. M., Rosário, N. M. E. d., Elbern, H., Freitas, S. R., &Pires, C. (2009). Regional representativity of AERONET observation sites during thebiomass burning season in South America determined by correlation studies with MODISAerosol Optical Depth. J. Geophys. Res, 114(D13). doi: 10.1029/2008JD010369Ilabaca, M., Olaeta, I., Campos, E., Villaire, J., Tellez, M. M., & Romieu, I. (1999). Associationbetween levels of fine particulate and emergency visits for pneumonia and other respiratoryillnesses among children in Santiago, Chile. Air Waste Manage. Assoc 49, 154-163Jorquera, H., & Castro, J. (2010). Analysis of urban pollution episodes by inverse modeling. Atmos.Env, 44(1), 42-54. doi: 10.1016/j.atmosenv.2009.09.040Kavouras, I., Lawrence, J., Koutrakis, P., Stephanou, E., & Oyola, P. (1999). A Measurement ofParticulate Aliphatic and Polynuclear Aromatic Hydrocarbons in Santiago de Chile.Atmospheric Environment, 33(30), 4977-4986. doi: 10.1016/S1352-2310(99)00281-2Kretzschmar, J. G. (1994). Particulate matter levels and trends in Mexico City, São Paulo, BuenosAires and Rio de Janeiro. Atmospheric Environment, 28(19), 3181-3191. doi: 10.1016/1352-2310(94)00149-FKuang, & Yung. (2000). Reflectivity variations off the Peru Coast: Evidence for indirect effect ofanthropogenic sulfate aerosols on clouds. Geophysical Research Letters, 27(16), 2501-2504.doi: 10.1029/2000GL011376Landulfo, E., Freitas, S. R., Longo, Karla, M., Uehara, S., & Sawamura, P. (2009). A comparisonstudy of regional atmospheric simulations with an elastic backscattering Lidar andSunphotometry in an urban area. Atmospheric Chemistry and Physics, 9, 6767-6774. doi:10.5194/acpd-9-9151-2009Lin, C.A., Martins, M.A., Farhat, S.C.L., Pope III, C.A., Conceição, G.M.S., Anastácio, V.M.,Hatanaka, M., Andrade, W.C., Hamaue, W.R., Bohm, G.M., and Saldiva, P. H. N. (1999). Airpollution and respiratory illness of children in São Paulo, Brazil. Paediatr. Perinat. Epidemiol,13, 475-488167

CHAPTER 4 – SOUTH AMERICALongo, K. M., Freitas, S. R., Alonso, M., Rodrigues, L., Mello, R., Stockler, R., & Moreira, D.(2010). New air quality product at CPTEC/INPE: forecasting troposphere ozone and itsprecursors from biomass burning and urban emissions. Boletim da Sociedade Brasileira deMeteorologia (in press)Longo, K. M., Freitas, S. R., Andreae, M. O., Yokelson, R., & Artaxo, P. (2009). Biomass burning,long range transport of products, and regional and remote impacts. In: LBA synthesis book"Amazonia and Global Change", ed. by Michel Keller; Mercedes Bustamante; John Gash;Pedro Dias. American Geophysical Union.Machado, M. C. S., Loyola, J., Quiterio, S. L., Rocha, G. O. d., Andrade, J. B. d., & Arbilla, G.(2009). Particle-Associated Polycyclic Aromatic Hydrocarbons and their Dry DepositionFluxes from a Bus-Station in the Rio de Janeiro Metropolitan Area, Brazil. J. Braz. Chem.Soc., 20(9), 1565-1573. doi: 10.1590/S0103-50532009000900002Martins, L., Martins, J. A., Freitas, E. D., Mazzoli, C. R., Gonçalves, F. L. T., Ynoue, R. Y., Hallak,R., Albuquergue, TT.A., and Andrade, M. d. F. (2010). Potential Health Impact of UltrafineParticles Under Clean and Polluted Urban Atmospheric Conditions: A Model-Based Study.Air Quality, Atmosphere & Health, 3(1), 29-39. doi: 10.1007/s11869-009-0048-9Martins, L. C., Latorre Mdo, R., Saldiva, P. H., & Braga, A. L. (2002). Air pollution and emergencyroom visits due to chronic lower respiratory diseases in the elderly: an ecological time-seriesstudy in São Paulo, Brazil. J Occup. Enrin. Med., 44(7), 622–627Martins, L. D., & Andrade, M. F. (2008 a ). Ozone Formation Potentials of Volatile OrganicCompounds and Ozone Sensitivity to Their Emission in the Megacity of São Paulo, Brazil.Water Air Soil Pollut, 195:201–213. doi: 10.1007/s11270-008-9740-Martins, L. D., & Andrade, M. F. (2008 b ). Emission Scenario Assessment of GasoholReformulation Proposals and Ethanol Use in the Metropolitan Area of São Paulo, The OpenAtmospheric Journal (2), 166-175. doi: 10.2174/1874282300802010166Martins, L. D., Andrade, M. F., Freitas, E. D., Pretto, A., Gatti, L. V., Albuquerque, E. L., Tomaz, E.,Guardiani, M.L., Martins, M.H.R.B, and Junior, O. M. A. (2006). Emission Factors for Gas-Powered Vehicles Traveling through Road Tunnels in São Paulo City, Brazil. EnvironmentalScience and Technology, 40(21), 6722-6729. doi: 10.1021/es052441uMena, M., Carmichael, G. R., Molina, L. T., Sp k, S. N., Campos, T. McNaughton, C., Clarke, A.,and Gallardo, L. (2009). Evaluating the regional influence of Santiago de Chile on air qualityand meteorology during VOCSALS-REx, Geophysical Research Abstracts. GeophysicalResearch Abstracts, 11.Miranda, R. M., & Andrade, M. F. (2007). Physicochemical characteristics of atmospheric aerosolduring winter in the São Paulo Metropolitan Area in Brazil. Atmospheric Environment, 39(33),6188-6193. doi: 10.1016/j.atmosenv.2005.06.055Miranda, R. M., Andrade, M. F., Worobiec, A., & Grieken, R. (2002). Characterization of aerosolparticles in the São Paulo metropolitan area. Atmospheric Environment, 36(2), 345–352. doi:10.1016/S1352-2310(01)00363-6Molina, M. J., & Molina, L. T. (2004). Megacities and atmospheric pollution. Journal of the Air andWaste Management Association, 54(6), 644–680Montero, L., Vasconcellos, P. C., Souza, S. R., Pires, M. A. F., Andrade, M. F., & Carvaljo, L. R. F.(2001). Measurements of Atmospheric Carboxylic Acids and Carbonyl Compounds in SãoPaulo City, Brazil. Environmental Science & Technology, 35, 3071-3081Morals, R. G. E. (2006). Atmospheric Urban Pollution. Critical episodes of the Environmentalpollution in the City of Santiago of Chile.Morata, D., Polvé, M., Valdés, A., Belmar, M., Dinator, M. I., Silva, M., Leiva, M., Aigouy, T. andMorales, J. R. (2008). Characterisation of aerosol from Santiago, Chile: an integrated PIXE-SEM-EDX study. Environmental Geology 56, 81-95. doi: 10.1007/s00254-007-1141-8MTC. (2010). Ministerio de Transportes y Comunicaciones del PerúMinisterio de Transportes yComunicaciones del Perú. Programa IM-04-PROCLIM.MTC. Inventario de emisiones.168

CHAPTER 4 – SOUTH AMERICAMuñoz, R., & Undurraga, A. (2010). Daytime Mixed Layer over the Santiago Basin: Description ofTwo Years of Observations with a Lidar Ceilometer. Journal of Applied Meteorology andClimatology, 49.Ntziachristos, L., & Samaras, Z. (2000). COPERT III Computer Programme to Calculate Emissionsfrom Road Transport. European Environment Agency, Copenhagen, Denmark, TechnicalReport 49.Olivares, G., Gallardo, L., Langner, J., & Aarhus, B. (2002). Regional dispersion of oxidized sulfurin Central Chile. Atmospheric Environment, 36(23), 3819-3828Oliveira, A. P., Bornstein, R. D., & Soares, J. (2003). Annual and Diurnal Wind Patterns in the Cityof São Paulo. Water, Air, and Soil Pollution, 3, 3-15. doi: 10.1023/A:1026090103764Oreggioni. (2009). Evolución de las emisiones provenientes de la combustión fósil en el áreametropolitana de Buenos Aires (1970-2006). Undergaduate, Universidad de Buenos Aires,Buenos Aires.Orsini, C., & Bouéres, L. (1977). A PIXE system for air pollution studies in South America. NuclearInstruments and Methods, 142(1-2), 27-32. doi: 10.1016/0029-554X(77)90802-3Orsini, C., Tabacniks, M., Artaxo, P., Andrade, F., & Kerr, A. (1986). Characteristics of fine andcoarse particles of natural and urban aerosols of Brazil. Atmospheric Environment, 20(11),2259-2269. doi: 10.1016/0004-6981(86)90316-1Ostro, B., Sanchez, J. M., Aranda, C., & Eskeland, G. S. (1996). Air pollution and mortality: resultsfrom a study of Santiago, Chile. J Expo Anal Environ Epidemiol 6, 97-114Ostro, B. D., Eskeland, G. S., Sanchez, J. M., & Feyzioglu, T. (1999). Air pollution and healtheffects: a study of medical visits among children in Santiago, Chile. Environ Health Perspect,107(1), 69-73Ozafrán, M. J., Vázquez, M. E., Burlón, A., Buhler, M., Cardona, M. A., Debray, M. E., Hojman, D.,Kesque, J.M., Kreiner, A.J., Levinton, G., Menendez, J.J., Naab, F., Stoliar, P., Davidson, M.,and Davidson, J. (1999). PIXE analysis of atmospheric aerosols in the city of Buenos Aires.Int PIXE 9(1-2), 21-28Penna, M. L., & Duchiade, M. P. (1991). Air pollution and infant mortality from pneumonia in theRio de Janeiro Metropolitan Area. Relation Bulletin of the Pan American Health Organization,25(1), 47-56Quiterio, S. L., Arbilla, G., Escaleira, V., Silva, C. R. S., & Maia, L. F. P. G. (2004). Metals inairborne particulate matter in downtown Rio de Janeiro (Brazil). Bulletin of EnvironmentalContamination and Toxicology 72, 916-922Quiterio, S. L., Sousa, C. R., Arbilla, G., & Escaleira, V. (2008). Evaluation of levels, sources anddistribution of airborne trace metals in seven districts of the Baixada Fluminense, Rio deJaneiro, Brazil. Atmospheric Environment, 39(19), 3503-3512. doi:10.1016/j.atmosenv.2005.02.030Rappenglück, B., Oyola, P., Olaeta, I., & Fabian, P. (2000). The evolution of photochemical smogin the Metropolitan Area of Santiago de Chile. Appl. Meteor, 39(3), 275-290Rappenglück, B., Schmitz, R., Bauerfeinda, M., Cereceda-Balic, F., von Baer, D., Jorquera, H,Silva, Y., and Oyola, P. (2005). An urban photochemistry study in Santiago de Chile.Atmospheric Environment, 39(16), 2913-2931. doi: 10.1016/j.atmosenv.2004.12.049Reich, S., Magallanes, J., Dawidowski, L., Gómez, D., Groselj, N., & Zupan , J. (2006). An Analysisof Secondary Pollutants in Buenos Aires City. Environmental Monitoring and Assessment,119, 441-443. doi: 10.1007/s10661-005-9035-2Richter, P., Griño, P., Ahumada, I., & Giordano, A. (2007). Total element concentration andchemical fractionation in airborne particulate matter from Santiago, Chile. AtmosphericEnvironment, 41(32), 6729–6738. doi: 10.1016/j.atmosenv.2007.04.053Rincón, G., Cremades, L., Ehrman, U., & Peña, A. (2007). Comparative study of environmentalregulations in Latin America. Biomedicine and Health, 11, 259-268. doi: 10.2495/EHR070271Romero, H., Ihl, M., Rivera, A., Zalazar, P., & Azócar., P. (1999). Rapid urban growth, land-usechanges and air pollution in Santiago, Chile. Atmospheric Environment, 33(24-25), 4039-4047. doi: 10.1016/S1352-2310(99)00145-4169

CHAPTER 4 – SOUTH AMERICARomero Lankao, P., Wilhelmi, O., Borbor, M. C., Parra, D., Behrenz, E., & Dawidowski, L. (2009).Health impacts of weather and air pollution - what current challenges hold for the future inLatin American cities. The Changing Environment for Human Security: New Agendas forResearch, Policy, and Action, edited by Karen O’Brien, Linda Sygna and Johanna Wolf,GECHS, Oslo NorwayRubio, M., Oyola, P., Gramsch, E., Lissi, E., Pizarro, J., & Villena, G. (2004). Ozone andperoxyacetylnitrate in downtown Santiago, Chile. Atmospheric Environment, 38(29), 4931–4939. doi: 10.1016/j.atmosenv.2004.05.051Rubio, M. A., Zamorano, N., Lissi, E., Rojas, A., Gutiérrez, L., & von Baer, D. (2006). Volatilecarbonylic compounds in downtown Santiago, Chile. Chemosphere, 62(6), 1011–1020. doi:10.1016/j.chemosphere.2005.06.022Saide, P.E, Spak, S.N., Carmichael, G.R., Mena-Carrasco, M.A., Yang, Q., Howell, S., Leon, D.C.,Snider, J.R., Bandy, A.R., Collett, J.L., Benedict, K.B., de Szoeke, S.P., Hawkins, L.N., Allen,G., Crawford, I., Crosier, J., and Springston, S.R. (2012) Evaluating WRF-Chem aerosolindirect effects in Southeast Pacific marine stratocumulus during VOCALS-REx, Atmos.Chem. Phys., 12, 3045-3064.Saide, P., Carmichael, G., Spak, S., Gallardo, L., Osses, A., Mena, M., and Pagowski, M.,Forecasting urban PM 10 and PM 2.5 pollution episodes in very stable nocturnal conditions andcomplex terrain using WRF-Chem CO tracer model (2011 a). Atmospheric Environment 45,2769-2780.Saide, P., Bocquet, M., Osses, A., & Gallardo, L. (2011 b). Constraining surface emissions of airpollutants using inverse modeling: method intercomparison and a new two-step multiscaleapproach. Tellus, 63B, 360–370. doi: 10.1111/j.1600-0889.2011.00529.xSaide, P., Osses, A., Gallardo, L., & Osses, M. (2009 a). Adjoint inverse modeling of a COemission inventory at the city scale: Santiago de Chile's case. Atmospheric Chemistry andPhysics Discussions, 9(2), 6325-6361Saide, P., Zah, R., Osses, M., & Eicker, M. O. d. (2009 b). Spatial disaggregation of trafficemission inventories in large cities using simplified top-down methods. AtmosphericEnvironment, 43(32), 4914-4923. doi: 10.1016/j.atmosenv.2009.07.013Sánchez-Ccyllo, O. R., Martins, L. D., Ynoue, R. Y., Astolfo, R., Miranda, R. M., Freitas, E. DBorges, A. S., Fornaro, A., Moreira, A., and Andrade, M. F. (2009). Vehicular particulateMatter Emission in Road Tunnels in São Paulo, Brazil. Environmental Monitoring andAssessment, 149, 241-249Sánchez-Ccyollo, O. R., Martins, L. D., Ynoue, R. Y., & Andrade, M. F. (2007). The impact ontropospheric ozone formation on the implementation of a program for mobile emissionscontrol: a case study in São Paulo, Brazil. Environmental Fluid Mechanics (Dordrecht), 7, 95-119. doi: 10.1007/s10652-007-9018-7Schmitz, R. (2005). Modeling of air pollution dispersion in Santiago de Chile. AtmosphericEnvironment, 39(11), 2035–2047. doi: 10.1016/j.atmosenv.2004.12.033Seguel, R., Morales, R., & Leiva, M. (2009). Estimations of primary and secondary organic carbonformation in PM 2.5 aerosols of Santiago City, Chile. Atmospheric Environment, 43, 2125–2131SENAMHI. (1988). Mapa de Clasificación Climática del Perú y su memoria descriptiva. EdiciónSENAMHI-Lima Perú. Jr. Cahuide (11), 785.Sienra, M. R., & Rosazza, N. G. y. (2006). Occurrence of nitro-polycyclic aromatic hydrocarbons inurban particulate matter PM 10 . Atmospheric Research 81(4), 265–276. doi:10.1016/j.atmosres.2006.01.003Sienra, M. R., Rosazza, N. G. y., & Préndez, M. M. (2005). Polycyclic aromatic hydrocarbons andtheir molecular diagnostic ratios in urban atmospheric respirable particulate matter.Atmospheric Research 75(4), 267-281. doi: 10.1016/j.atmosres.2005.01.003Silva, I. R. R. e., Lichtenfels, A. J. F. C., Pereira, L. A. A., & Saldiva, P. H. N. (2008). Effects ofambient levels of air pollution generated by traffic on birth and placental weights in mice.Fertility and Sterility, 90(5), 1921-1924. doi: 10.1016/j.fertnstert.2007.10.001170

CHAPTER 4 – SOUTH AMERICASmichowski, P., Gómez, D. R., Dawidowski, L. E., Giné, M. F., y, A. C. S. B., & Reich, S. L. (2004).Monitoring trace metals in urban aerosols from Buenos Aires city. Determination by plasmabasedtechniques. Environmental Monitoring, 6, 286-294.Smith, K., Samet, J., Romieu, I., & Bruce, N. (2000). Indoor air pollution in developing countriesand acute lower respiratory infections in children. Thorax, 55(6), 518-532. doi:10.1136/thorax.55.6.518Spak, S., Mena, M., & Carmichael, G. (2010). Atmospheric transport of oxidized sulfur over theSoutheast Pacific during VOCALS Rex. Clivar Exchanges, 15(2).Szwarcfiter, L., Mendes, F. E., & Rovere, E. L. L. (2005). Enhancing the effects of the Brazilianprogram to reduce atmospheric pollutant emissions from vehicles. Transportation ResearchPart D. Transport and Environment, 10(2), 153-160Trindade, H. A., Oliveira, A. E., Pfeiffer, W. C., Londres, H., & Ribeiro, C. C. (1980). Meteorologicalparameters and concentration of total suspended particulates in the urban area of Rio deJaneiro. Atmospheric Environment, 14(8), 973-978. doi: 10.1016/0004-6981(80)90012-8Umbuzeiro, G. d. A., Franco, A., Magalhães, D., de Castro, F. J., Kummrow, F., Rech, C. M.,Rothschild, F.d.C.L., and Vasconcellos, P. d. C. (2008). A preliminary characterization of themutagenicity of atmospheric particulate matter collected during sugar cane harvesting usingthe Salmonella/microsome microsuspension assay. Environmental and MolecularMutagenesis, 49(4). doi: 10.1002/em.20378UNPOP. (2009). United Nations, Department of Economic and Social Affairs, Population Division(2010). World Urbanization Prospects: The 2009 Revision. Retrieved August 2010http://esa.un.org/unpd/wup/index.htmUrdinola, P. (2001). La población desplazada interna: el caso colombiano”, Amérique LatineHistoire et Mémoire. (February 2010). http://alhim.revues.org/index525.htmlVasconcellos, P. C., Balasubramanian, R., Bruns, R. E., Sanchez-Ccoyllo, O., Andrade, M. F., &Flues, M. (2007). Water-soluble ions and trace metals in Airborne Particles over Urban Areasof the State of São Paulo, Brazil: Influences of Local Sources and Long Range Transport.Water, Air and Soil Pollution 186, 63-73. doi: 10.1007/s11270-007-9465-2Vasconcellos, P. C., Carvalho, L. R. F., & Pool, C. S. (2005). Volatile Organic Compounds InsideUrban Tunnels of São Paulo City, Brazil. Brazilian Chemistry Society 16(6), 1210-1216.Vasconcellos, P. C., Sanchez-Ccoyllo, O., Balducci, C., Mabilia, R., & Cecinato, A. (2008).Occurrence and concentration levels of nitro-PAH in the air of three Brazilian citiesexperiencing different emission impacts. Water, Air and Soil Pollution 190(1-4), 87-94. doi:10.1007/s11270-007-9582-yVera, C., Higgins, W., Amador, Ambrizzi, T., Garreaud, R., Gochis, D., Gutzler, D., Lettenmaier,D., Marengo, J., Mechoso, C.R., Nogues-Paegle, J., Silva Dias, P.L., and Zhang, C. (2006).A Unified View of the American Monsoon Systems. Journal Of Climate, 19(20), 4977–5000.Vermylen, J., Nemmar, A., & Hoylerts, M. F. (2005). Ambient air pollution and acute myocardialinfaction. Journal of Thrombosis and Haemostasis 3, 1955-1961. doi: 10.1111/j.1538-7836.2005.01471.xVivanco, M. G., & Andrade, M. F. (2006). Validation of the emission inventory in the São PauloMetropolitan Area of Brazil, based on ambient concentrations ratios of CO, NMOG and NO Xand on a photochemical model. Atmospheric Environment, 40(40), 40, 1189-1198. doi:10.1016/j.atmosenv.2005.10.041WHO. (2005). Guidelines for Air Quality for particulate matter, ozone, nitrogen dioxide, carbonmonoxide, 2005. Retrieved July 2010http://www.who.int/phe/health_topics/outdoorair_aqg/en/index.htmlYnoue, R. Y., & Andrade, M. F. (2004). Size-resolved mass balance of aerosol particles over theSão Paulo Metropolitan Area of Brazil. Aerosol Science and Technology, 38(2), 52-62.Zárate, E., Belalcazar, L. C., Clappier, A., Manzi, V., & Bergh, H. V. d. (2007). Air quality modellingover Bogota, Colombia: Combined techniques to estimate and evaluate emission inventories.Atmospheric Environment, 41(29), 6302-6318. doi: 10.1016/j.atmosenv.2007.03.011171

CHAPTER 5 - NORTH AMERICACoordinating Authors: David Parrish (1)Contributing Authors: Hanwant Singh (2) , Luisa Molina (3)(4) , Sasha Madronich (5)(1)NOAA, ESRL, Chemical Sciences Division, Boulder, CO, USA(2)NASA, Ames Research Center, Field, CA, USA(3)Molina Center for Strategic Studies in Energy and the Environment (MCE2, La Jolla, CA, USA(4)Department of Earth, Atmospheric and Planetary Sciences, MIT, Cambridge, MA USA(5)National Center for Atmospheric Research, Atmospheric Chemistry Division and Chemical Processingand Regional Modelling Group, Boulder, CO, USANorth American megacities include Mexico City, perhaps the second largest metropolitanarea in the world, and Los Angeles and New York City in the United States, two of the ten largestmetropolitan areas. Figure 1 shows the population density of North America. The megacities ofLos Angeles, New York, and Mexico City are visible, as well as several other high-density urbanareas such as Houston, Texas. Summertime photochemical smog was first recognized as asevere environmental problem in Los Angeles, and has been the subject of extensive studies theresince the 1940’s [e.g., Haagen-Smit, 1952]. Differences in topography, meteorological conditions,and anthropogenic emissions lead to marked differences in the air quality considerations in theseNorth American megacities as well as their impacts on the larger troposphere. Figure 2 showsemissions of CO, NO X , and SO 2 for the year 2000 throughout North America. Probably thegreatest difference in emissions between the megacities in North America is their SO 2 emissions,which depend greatly on the type of coal (low- versus high-sulphur) used in energy production.This chapter discusses these differences, as well as the similarities. The greater Houston, Texasurban area in the United States is discussed as an additional contrast; with a populationapproaching 6 million, this area is not generally considered a megacity, but it is a large urbancentre of particular interest since it is home to a large fraction of the petrochemical industrialfacilities of the US, which leads to a unique mix of anthropogenic emissions.Figure 1 - Map of the population density in North America (persons per km 2 ), based on 0.25 o gridded data for 2000from the Center for International Earth Science Information Network (CIESIN) at Columbia University[http://sedac.ciesin.columbia.edu/gpw/]172

CHAPTER 5 – NORTH AMERICAFigure 2 - (a) Emissions of CO; (b) NOX; (c) SO2 for North America in kg/m -2 s -1 . The figures were generated fromthe EDGAR emission inventory[EC-JRC/PBL. EDGAR version 4.1. http://edgar.jrc.ec.europa.eu/, 2010]5.1 LOS ANGELES: AN ENVIRONMENTAL SUCCESS STORYThe Los Angeles Megacity (LAMC), here defined as the South Coast Air Basin (SoCAB)shown in Figure 3, is located at 34˚3’N and 118˚14’W with a population approaching 17 millioninhabitants. LAMC is an excellent example for the evolution of emission control strategies in agrowing megacity. By several measures LAMC is one of the greatest environmental success173

CHAPTER 5 – NORTH AMERICAstories found anywhere in the world. Between 1970 and the present, SoCAB VOC and NO Xemissions have declined markedly despite a substantial increase in commerce and vehicle traffic[Cox et al., 2009]. Peak O 3 levels that exceeded 600 ppbv in the 1960’s have not reached 200ppbv since 1998.Figure 3 - The Los Angeles Megacity defined as the South Coast Air Basin (outline). The colours indicate the topographyof the basin (blues for low elevation, brown for high elevation).The Pacific Ocean lies to the south and westThis improvement in air quality has been accomplished despite several unfavourablecircumstances that make SoCAB particularly susceptible to high air pollution concentrations. Thelarge population lives in a basin bounded by the Pacific Ocean on the west and by mountains onthe other three sides, which prevent efficient horizontal ventilation of the area. Low inversionheights associated with a persistent high pressure system and the adjacent Pacific marineenvironment limits the vertical mixing within the basin, and the land-sea breeze system recirculatespolluted air within the basin. These topographic and meteorological features allowemissions to accumulate over several days during episodes of relatively stagnant airflow. Duringthe summer ozone season, May through October, clear skies and high temperatures dominate,which speed photochemical production of O 3 and other photochemical products. Privateautomobiles on extensive freeway systems provide the primary transportation in the area. Thistransportation system accounts for a large fraction of the emissions in the urban area.Over the past three decades ambient concentrations of key pollutants in the SoCAB regionhave decreased substantially despite a doubling of the population and tripling of vehicle use.Figure 4 compares the temporal trends of four pollutant concentrations. These data are presentedin units that correspond to US EPA National Ambient Air Quality Standards (NAAQS)(http://www.epa.gov/air/criteria.html), which are presently: O 3 - 75 ppbv (8-hr); CO - 9 ppmv (8-hr);NO 2 - 53 ppbv (1-yr); PM 2.5 - 35 µg/m 3 (24-hr). The numbers in parentheses give the averagingperiod. The O 3 data are 3-yr averages of the 4 th highest annual maxima, the CO data are annualmaxima, and the PM 2.5 are annual 98 th percentiles. Ozone concentrations apparently peaked inthe late 1960s. It is evident that there has been an impressive decline in ozone concentrations aswell as other air pollutants since then. Although it still violates the NAAQS for O 3 and PM 2.5 , theLos Angeles basin is in compliance with the NAAQS for nitrogen dioxide and carbon monoxide, aswell as sulphur dioxide and lead. It is fair to say that this megacity has gone from being one of themost polluted in the world 50 years ago to presently one of the “least polluted” cities of its size.Estimates are that many thousands of lives have been saved in LAMC from improvements in airquality [Hall et al., 2008].174

CHAPTER 5 – NORTH AMERICAThe relative temporal trends of the primary pollutants, NO 2 and CO, reflect the history of theair quality control strategy adopted in the United States. Initially, the control focus was upon VOCsand CO, notably including the introduction of catalytic convertors on automobiles in the mid-1970s.The focus later shifted to include NO X emission controls. Figure 4 shows that this controlemphasis has led to a significantly larger decrease in ambient CO concentrations (factor of 5.2)than that for the ambient NO 2 concentrations (factor of 2.3) from 1980 to 2008. SO 2 emissionshave also decreased substantially over the last three decades, primarily due to reduced sulphurcontent of fuels utilized in mobile (as of 1 June 2006 15 ppm for on-road diesel) and point sources,and to scrubbing of sulphur from flue gases emitted by point sources.Figure 4 - Air quality trends over the South Coast Air Basin of California. National Air Quality Data derived from monitoringstations in the SoCAB region[Alexis et al., 1999; Cox et al., 2009; http://www.arb.ca.gov/adam/cgi-bin/db2www/polltrendsb.d2w/Branch].The O3 trends have some caveats: since the earliest years there have been changes in the measurement methods, thequality control procedures initially were limited and the monitoring network was smaller,and many site locations have changedIt is important to recognize that there are still significant problems remaining. The regionstill violates the ozone standard and indeed despite continued emission reductions littleimprovement in O 3 air quality has been observed since 2000. During 2005-2008 the 8-h O 3exceeded the NAAQS on 110-120 days each year. The current peak O 3 levels are roughly doublethe accepted levels set to protect the most vulnerable populations. Several difficulties exist inachieving air quality goals in LAMC. Due to extremely non-linear nature of VOC-NO X -O 3 chemicalsystem, it is possible that VOC/NO X ratios over time have shifted to a regime where further VOCreductions are only minimally effective. Controlling emissions from heavy-duty diesel trucks hasbeen far more difficult than passenger cars as the turnover time for this fleet (25-30 years) greatlyexceeds that for the passenger fleet (7-10 years). A relatively small fraction of the total motorvehicle fleet, currently 10 million vehicles in the Los Angeles basin, accounts for a very largefraction of the total mobile source emissions. A related problem is the emergence of the Ports ofLos Angeles and Long Beach as dominant point sources of diesel-related pollution in the LosAngeles Basin due to a tripling of goods movement from Asia through these ports over the past 15years. Future progress is anticipated from a greater use of plug-in hybrids, electric cars, alternatefuels and better control technology. Current targets call for on-road emission reductions of VOC,NO X , SO X , and PM 2.5 by respectively 70%, 70%, 50% and 12% between 2007 and 2020Megacities contribute significantly to the burden of GHGs in the atmosphere. In the past,air quality control strategies have been based largely on health implications with little considerationfor the associated climate change consequences. An added complication for future controlstrategy development is the need to mitigate climate change impacts while improving air quality[Bell et al., 2007]. These interactions are often nonlinear and require a better understanding of thefeedback processes between air pollution and climate change [Ramanathan and Feng, 2009;Jacob and Winner, 2009 and references there in]. California is presently embarking on strategies175

CHAPTER 5 – NORTH AMERICAthat improve air quality as well as mitigate the impacts of local and global climate change. Recentstudies [Diffenbaugh et al., 2008] indicate that LA basin has extremely high sensitivity to futureclimate change (Figure 5). A warmer climate, with increasingly hotter days, is also likely to bedeleterious to air quality [Steiner et al., 2006; Murazaki and Hess, 2006]. In California, the firsttask in controlling CO 2 and other GHG emissions (CH 4 , N 2 O, CFCs) has begun with inventoryingtheir baseline emissions and atmospheric abundances so future progress can be measuredagainst a reference point expected to be 2010.Figure 5 - Future climate change hot spots over North America. The colour scale gives aggregate climate change scores,which take into account long-term mean and variability of warm- and cold-season temperature and precipitation[Diffenbaugh et al., 2008]Over the last several decades, there have been great advances in measurementtechnology and it is now possible to measure a large number of precursors and intermediatespecies (carbonyls, free radicals, aerosol composition etc.) to test and validate models thatsimulate air quality and climate change interactions. Complementing the models have beenseveral intensive field campaigns that use aircraft platforms to acquire data in three dimensionsand provide boundary conditions necessary for model development and forecasts of air quality andclimate change. Some of the recent intensive campaigns that have provided unique observationaldata from SoCAB have been the 1997 South Coast Ozone Study [Croes and Fujita, 2003], the2002 Intercontinental Transport and Chemical Transformation study [Parrish et al., 2004], and the2008 ARCTAS-CARB study (http://www.espo.nasa.gov/arctas/; unpublished). These campaignsused aircraft platforms to assess emission sources, atmospheric composition, and boundaryconditions applicable to this region. Figure 6 shows that emission signatures of different sourcescan be identified in such measurements. In the upper panel the anthropogenic sources insouthern California have relatively small CO to CO 2 emission ratios compared to biomass burning(BB) plumes encountered in Canadian boreal fires as well as wildfires in southern California. Inthe lower panel, the CH 4 to CO emission ratios are seen to be quite high over agricultural regionsof California, lower in urban emissions and much lower in BB plumes. In this lower panel, elevatedbenzene concentrations (colour scale) are found in the urban emissions and BB plumes, whileacetonitrile (CH 3 CN) is strongly elevated only in the BB plumes (inset).More recently, satellites have been able to provide a new dimension to the repertoire ofsurface based atmospheric observations [Martin, 2008]. Although less precise than in-situtechniques, satellite observations extend over several years and provide data on scales muchlarger than aircraft campaigns. Also, satellites generally provide columns and relating these tosurface observations still remains a challenge. Figure 7 shows tropospheric NO 2 columns overurban areas in the western US. The highest concentrations are seen over the Los Angeles basin.Generally all urban areas show strong weekday-weekend differences in emissions. Such satellitemeasurements provide tests of NO 2 emission inventories [Boersma et al., 2008; Kim et al., 2009].Similar data are available for aerosols and attempts are being made to relate these to PM 2.5measured by ground networks [Engel-Cox et al., 2006]. In the future column measurements ofGHGs (e.g. methane) are likely to provide new information on their sources and sinks.176

CHAPTER 5 – NORTH AMERICAFigure 6 - Relationships between selectedtrace constituents over Southern Californiameasured from June 17-26, 2008. The upperpanel compares the California data with latermeasurements in forest fire plumes inCanada. The lower panel comparesmeasurements over different Californiaregions: agricultural areas, urban (traffic) andin forest fire plumes (BB). Data werecollected aboard the NASA DC-8 by multipleinvestigators of the ARCTAS campaign[Jacob et al., 2009]Figure 7 - SCIAMACHY satellite derivedtropospheric NO2 columns overurban areas in the western US for 2003 –2007 May - September averages[after Kim et al., 2009]177

CHAPTER 5 – NORTH AMERICA5.2 THE US NORTHEAST URBAN CORRIDOR AND HOUSTON, TEXAS: CONTRASTINGUS URBAN AREASLocated at 40˚42’N and 74˚W near sea level, by its widest definition, the New York Cityregion includes 22 million people in parts of three states: New York, New Jersey and Connecticut.It is embedded in the US Northeast urban corridor (Figure 8), which extends from Boston toWashington D.C. and has a population of about 55 million people. In many respects New YorkCity has a more favourable situation from an air quality perspective than does Los Angeles. TheNortheast urban corridor in general and New York City in particular has lower per capita emissionsof ozone and aerosol precursors and greenhouse gases than western US cities like Los Angelesand Houston. The greater population density that allows much greater use of public transportationaccounts for this difference. With no significant topographic barriers to air flow there is generallymuch better ventilation of the northeast urban areas allowing winds to sweep pollutants away fromthe point of emission. With the prevailing winds from the continent, the daytime convectiveboundary layer is generally deeper allowing also greater vertical mixing of emissions. On theeastern coast of the US the summertime period is not so dominated by clear skies. Consequentlythe New York City area has not experienced the very high O 3 concentrations observed in LosAngeles.Figure 8 - The US Northeast urban corridor including New York City coloured according to greater population density[Rankin, 2009] (http://en.wikipedia.org/wiki/File:Boswash.png)178

CHAPTER 5 – NORTH AMERICAThe Houston, Texas urban area located at 29˚45’N and 95˚21’W along the Gulf of Mexicocoast has a much smaller population approaching ~6 million. However, Houston has much greaterindustrial emissions than either the Los Angeles or New York City area. Figure 9 shows thelocation of these facilities relative to the urban area. Unfortunately, a large fraction of the facilitiesare located within the urban area along the Houston Ship Channel, which extends from GalvestonBay nearly to the centre of the city. These emissions have a profound effect on photochemical O 3production [Ryerson et al., 2003], which causes the ambient O 3 concentrations in Houston to becomparable to those found in the two larger US megacities. In fact, in most summers from 1999-2004 the nation’s highest 1-hr average O 3 concentrations were found in Houston. In addition to theexceptional industrial emissions, Houston suffers some of the same disadvantages as LosAngeles. It is a coastal city, so is subject to the shallow boundary layers and recirculationassociated with the land-sea breeze circulation. It also experiences very hot, sunny and stagnantsummertime meteorological conditions.Figure 9 - Location of point emission sources of VOC and NOX within the greater Houston, Texas region. The Gulf ofMexico is in the lower right corner, and Galveston Bay lies east of the metropolitan area [after Ryerson et al., 2003]Recent temporal trends of ambient concentrations of O 3 and PM 2.5 in New York City andHouston approximately parallel those in Los Angeles (Figure 10). In general, Los Angelesexperiences the highest concentrations of both O 3 and PM 2.5 , while New York and Houston exhibitsimilar concentrations, with New York City slightly lower in O 3 , but higher in PM 2.5 . Only slowimprovement is evident for either pollutant in any of the three urban areas for the time periodplotted.Sulphur dioxide (SO 2 ) emissions differ markedly between the western and eastern US, andthis difference is clearly reflected in differences in aerosol composition (Figure 11) and acidity ofprecipitation (Figure 12). Sulphur emissions are much higher in the eastern US due to both moreconcentrated emission sources from the greater density of electrical power generation facilities andthe greater utilization of high sulphur coal. Figure 11 shows that sulphate makes smaller fractionalaerosol contribution in Los Angeles compared to the northeast US. The lower sulphate179

CHAPTER 5 – NORTH AMERICAcontribution allows accommodation of a larger contribution from nitrate. In both regions, organicsalso account for a major aerosol fraction. The high density of primarily SO 2 and secondarily NO Xemissions in the eastern US has led to greatly increased acidity of precipitation in that region.However, due to the implementation of the US EPA Acid Rain programme in 1990, the averageambient sulphate and nitrate concentrations in the Northeastern US have decreased by 49% and44%, respectively, from 1989-1991 to 2007-2009[http://www.epa.gov/airmarkt/progress/ARP09_3.html]. This decrease has led to a decrease inprecipitation acidity (i.e. higher pH) of 43% in the Eastern United States that is clearly illustrated inFigure 12.Figure 10 - Comparison of air quality trends for three mega-cities for O3 (lighter bars, in ppbv) and PM2.5 (darker bars, inµg/m 3 ). The data are averaged and derived, as in Figure 4 [http://www.epa.gov/air/airtrends/values.html]Figure 11 - Comparison of fine aerosol composition (units: µg/m 3 ) in (a) Los Angeles (b) Northeast [after DeBell et al., 2003]as a function of month of the year. The two minor component bars are soil (brown) and light absorbing carbon (black).Data are from US EPA’s Speciated Trend Network180

CHAPTER 5 – NORTH AMERICAFigure 12 - The spatial distribution of annual precipitation-weighted average concentration of hydrogen ion (pH units) forthree years [after http://nadp.sws.uiuc.edu/lib/data/97as.pdf].Data are from US National Atmospheric Deposition Programme5.3 MEXICO CITY: NORTH AMERICA’S MOST POPULOUS AND RAPIDLY DEVELOPINGMEGACITYThe Mexico City Metropolitan Area (MCMA) 19°25’N latitude and 99°10’W longitude lies inan elevated basin at an altitude of 2240 m. The nearly flat basin floor covers about 5000 km 2 ofthe Mexican Plateau, and is confined on three sides (east, south and west) by mountain ridges butwith a broad opening to the north and a narrower gap to the south-southeast (Figure 13). Twomajor volcanoes, Popocatépetl and Ixtaccíhuatl are on the mountain ridge southeast of the basin.The metropolitan area covers about 1500 km 2 on the southwest side of the basin. During thetwentieth century Mexico City increased rapidly in urbanized area and population, from fewer than3 million people in 1950 to about 20 million presently. MCMA has a very high population densityas well as a high concentration of industrial and commercial activities [Molina and Molina, 2002].Figure 13 - Topographical map of the Mexico City Metropolitan Area showing urban expansion[Molina and Molina, 2002]The topography and meteorology of the MCMA markedly affect air quality. A cool dryseason from November to February is followed by a warm dry season until May and a rainy181

CHAPTER 5 – NORTH AMERICAseason from June to October. Synoptic forcing is generally weak and air transport is stronglyinfluenced by the mountain-valley winds in the basin. Weak winds and strong temperatureinversions at night lead to high primary pollutant concentrations that persist into the morning,followed by very rapid boundary layer growth to maximum heights of 2 to 4 km in the earlyafternoon. There is relatively little recirculation and day-to-day carry-over of pollutants within thebasin [de Foy et al., 2006; 2008]. The cool season has stronger surface inversions and highermorning concentrations of primary pollutants. The warm dry season has more intense solarradiation with faster photochemical oxidant formation, as well as increased aerosol loading due todust and biomass burning. The rainy season has lower PM and CO but continues to have highozone due to intense photochemistry occurring before the afternoon showers. Air pollution istherefore a year round concern.Despite the rapid growth and development in the MCMA, air quality has markedly improvedduring the past two decades (Figure 14) and the rate of increase of greenhouse gas emissions hasbeen reduced. Comprehensive air quality management programmes have been implemented[Molina and Molina, 2002]. In the late 1980s, the newly established automatic air qualitymonitoring network (RAMA, Red Automática de Monitoreo Atmosférico) revealed highconcentrations of all criteria pollutants: lead, carbon monoxide, nitrogen oxides, sulphur dioxide,ozone, and particulate matter (PM). Ozone exceeded the air quality standards of 110ppbv (1-hr)more than 90% of the days, and peaked above 300 ppbv 40-50 days a year, among the worst inthe world [Molina and Molina, 2002]. Specific actions included removal of lead from gasoline,installation of catalytic converters in automobiles, reduction of sulphur content in diesel fuel;substitution of natural gas for fuel oil in industry and power plants, reformulation of liquefiedpetroleum gas for heating and cooking, strengthening the vehicle inspection and maintenanceprogramme, and modernizing the driving restriction programme (Hoy no circula). Theconcentrations of criteria pollutants have decreased substantially over the past decade despite thecontinuing increase in population and economic activity. Figure 14 indicates that in the early1990s the ozone concentrations in MCMA may have been larger than those in Los Angeles.Ozone has decreased significantly in both cities, but even more rapidly in MCMA, and in recentyears the MCMA concentrations have been lower than in Los Angeles. The MCMA representsaround 20% of Mexico's population, but only 9% of its greenhouse gas emissions. Policiesfocused on greenhouse gas emissions include biogas capture and waste management projects,improved public transportation, fleet renewal projects for taxis and medium-capacity buses, andsustainable housing development projects [Molina et al., 2009].Figure 14 - Comparison of air quality trends for O3 in Mexico City and Los Angeles. The data are 3-yr averages of the 4 thhighest annual maxima. The data are derived from Fig. 4 for Los Angeles and from Sistema de Monitoreo Atmosférico dela Ciudad de México (SIMAT) [http://www.sma.df.gob.mx/simat/] for MCMA182

CHAPTER 5 – NORTH AMERICAEmission inventories have been developed in the MCMA since 1986. There were largeuncertainties in the early inventories, especially for VOC emissions [Molina and Molina, 2002].Figure 15 presents the 2006 MCMA emissions inventory for PM 10 , PM 2.5 , VOC and NO X [SMA-GDF, 2008]. Mobile emission sources represent a significant fraction of the total anthropogenicemissions of NO X and PM 2.5 (76% and 62%, respectively) but only a relatively small fraction (34%)of VOC. However, ambient VOC measurements suggest that emissions associated with gasolineemissions dominate in MCMA as well as some other mega-cities [Parrish et al., 2009a]. As in allcurrent emission inventories throughout the world, a great deal more effort is required for emissioninventory testing and improvement.Figure 15 - Emissions inventory for the Year 2006 [SMA-GDF, 2008]The combination of population, topography, meteorology, and multi-pollutant emissiondensity of the MCMA has attracted a number of field studies. The Mexico City Air QualityResearch Initiative (MARI) project gathered surface and vertical profile observations ofmeteorology and pollutants during 1990-1994 [Streit and Guzman, 1996]. The IMADA-AVER(Investigación sobre Materia Particulada y Deterioro Atmosférico, Aerosol and Visibility EvaluationResearch) campaign in February - March 1997 yielded comprehensive meteorologicalmeasurements in the basin, and provided insights into particulate composition [Doran et al., 1998;Edgerton et al., 1999]. The MCMA-2002/2003 campaigns in February 2002 and April 2003provided detailed measurements of many oxidant precursors and photochemical intermediatesincluding radicals, as well as meteorology and emissions [Molina et al., 2007]. The largest study todate, MILAGRO (Megacity Initiative: Local and Global Research Observations), took place inMarch 2006 and included a wide range of instruments at ground sites, on aircraft, and satellitesthat provided detailed measurements of gas and aerosol chemistry, aerosol microphysics andoptics, radiation and meteorology [Molina et al., 2010; Singh et al., 2009; and references therein].The intensive field campaigns have provided a wealth of information on the emission,dispersion and transformation of species emitted to the MCMA atmosphere and their urban,regional and hemispheric impacts. Motor vehicles produce abundant amounts of VOC and NO X(ozone and aerosol precursors), primary PM, elemental carbon, particle-bound polycyclic aromatichydrocarbons, CO and a wide range of air toxics, including formaldehyde, acetaldehyde, benzene,183

CHAPTER 5 – NORTH AMERICAtoluene, and xylenes [Molina et al., 2007]. VOC/CO emission ratios are notably higher than in theUS (Figure 16) and aldehydes emissions are significant [Garcia et al., 2006; Lei et al., 2009]. VOCflux measurements have been made with fast-response sensors coupled with eddy covariancetechniques, from both tower and aircraft platforms, to provide independent evaluation of emissionsinventories [Velasco et al. 2005; 2007; 2009; Karl et al., 2009]. A mobile laboratory measured onroadvehicle fleet emission indices for various vehicle classes and driving speeds [Zavala et al.,2006; 2009]. Figure 17 compares the total annual emissions from light-duty gasoline vehiclesestimated from fuel-based emission factors from on-road and remote sensing measurementscombined with 2006 fuel sales records against the corresponding mobile emissions estimates inthe official emissions inventory [SMA-GDF, 2008]. The comparison indicates agreement to betterthan 30% for CO and NO, but an inventory under estimate by a factor of 1.4 to 1.7 for VOCs and aprobable severe under estimate by a factor > 4 for primary PM 2.5 emissions [Zavala et al., 2009].Figure 16 - Correlations between hydrocarbons (a) Acetylene; (b) Propane; (c) C8-aromatics; (d) 1-Butene, and carbonmonoxide measured in Mexico City (blue points) compared to fits obtained in US cities (red lines) [deGouw et al., 2009].Here ER represents emission ratio, which is equal to the best-fit slopesFigure 17 - Evaluation of the Mobile Emissions inventory for light-duty gasoline vehicles [Zavala et al., 2009]184

CHAPTER 5 – NORTH AMERICAThe response of urban O 3 to VOC and NO X precursor emissions remains a topic of interest,and may have shifted toward more VOC-sensitive conditions in recent years. Recent modellingstudies [Lei et al., 2006; 2008; Tie et al., 2007] suggest that O 3 production is VOC-limited. This issupported by studies of radical budgets showing significant chain termination by NO X chemistry[Volkamer et al., 2010; Sheehy et al., 2010 Dusanter et al., 2009], and by the weekend effectshowing large reductions in NO X and CO but not O 3 on Saturdays and Sundays relative toweekdays [Stephens et al., 2008]. However, definitive policy recommendations must be basedupon more extensive modelling studies with emission inventories tested and improved asdiscussed above.High aerosol concentrations were observed both at ground sites and from all aircraft duringMILAGRO. These aerosol particles included a large fraction of organics, but black carbon, crustalmatter, sulphate and nitrate were also significant contributors. Figure 18 shows the averagesubmicron PM composition within the MCMA basin during two different studies. Secondaryorganic aerosols (SOA) dominate the organic fraction in the city and their origin is still under study[Volkamer et al. 2006; Dzepina et al., 2009]. Biomass burning (agricultural, forest, wood cookingand trash burning) also contributes to the urban and regional pollution in the Mexico Basin[Salcedo et al., 2006; Johnson et al., 2006; Yokelson et al., 2007; 2009; Moffet et al., 2008; Stoneet al., 2008; Querol et al., 2008; Crounse et al., 2009; Aiken et al., 2009; Christian et al., 2009].Figure 18 - Submicron PM composition (mass and percent) measured during (a) March 2006; (b) April 2003 field campaignsat surface sites in the Mexico City basin.[From Aiken et al., 2009]5.4 POLLUTION TRANSPORT IN NORTH AMERICABy the 1980s it had become apparent that local air quality was not simply due to localemissions, but had significant contributions due to pollutant transport from upwind sources. TheOzone Transport Assessment Group (OTAG) studied this transport contribution in the eastern US;Figure 19 summarizes the important transport regimes found during high ozone events. Within theboundary layer, but above about 800 m, flow is controlled by synoptic meteorological systems, andis generally from the west to northwest during pollution episodes. Channelled flows below theridge heights of 200 to 800 m follow important terrain features, and often transport air from thesouthwest along the northeast US urban corridor. These channelled flows include low-levelnocturnal jets that are apparently particularly important for transporting pollutants precedingepisodes. Finally, near surface flows (below 200m) during episodes are typically light during nightand morning allowing accumulation of emissions. Fresh emissions as well as aged urban plumesmove downwind and react during daytime, while O 3 aloft and aged precursors are entrained as themixing layer deepens. This low-level transport is typically to the north through east along theurban corridor for 50-250 km by evening. In summary, meteorological processes interact at large185

CHAPTER 5 – NORTH AMERICAand small scales to determine local O 3 concentrations. The relative contribution from each scale,from local to inter-regional, can vary widely between episodes. This understanding has led tocoordinated multi-state abatement strategies within the US.Figure 19 - Conceptual diagram illustrating the multiple, concurrent scales of transport winds typically observed duringhigh ozone events in the Northeast US [after Blumenthal et al., 1997]The proximate location of urban areas in the northeast urban corridor has made theimportance of transport processes particularly obvious in that region, but even in the relativelysparsely populated western US, regional transport makes significant contributions to the urbanozone concentrations. For example, recent studies in Texas demonstrate that the transport ofozone from upwind regions can predominate over in situ production within the Houston urban area,even during O 3 exceedance conditions [see Parrish et al., 2009b, and references cited therein].Indeed, the transported ozone in eastern Texas, which represents the minimum ozoneconcentration that is likely achievable through only local controls, can approach or exceed thecurrent NAAQS.Pollutant transport also is important on intercontinental scales. A large fraction of NorthAmerican emissions, as well as the resulting ozone and aerosol produced over the continent, istransported beyond the national borders, primarily to the Gulf of Mexico and North Atlantic regionsand potentially on to Europe. Significant recent research efforts have been directed towardquantifying the importance of this pollutant export from the Northeastern US [see Fehsenfeld et al.,2006 and references cited therein.] The pollution plume from Mexico City also can be observedseveral hundreds of kilometres downwind. Figure 20 compares the increase in O 3 relative to CO inpollution plumes exported from these two regions. Air masses close to urban areas exhibit shallowslopes that steepen during downwind transport. Interestingly, quite similar slopes are seen in theaged plumes transported from Mexico City (0.35) and New York City (0.38). Aircraft-basedmeasurements show ongoing production of SOA [Kleinman et al., 2008; DeCarlo et al., 2008] aswell as ozone for several days downwind, with active photochemistry sustained by aldehydes [Tieet al., 2009] and nitrogen oxides from the thermal decomposition of peroxyacyl nitrates andphotolysis and OH oxidation of nitric acid [Neuman et al., 2006].Intercontinental transport into North America gives an added complexity to Los Angeles airquality issues. There is strong evidence that the background O 3 concentration transported intoCalifornia is increasing [Parrish et al., 2009c], possibly in response to increasing Asian emissionsof O 3 precursors. This background O 3 increase may be occurring throughout the northern midlatitudetroposphere [e.g. Parrish et al., 2009c], and this increase may be negating many of thebenefits from local pollution control measures in California [Jacob et al., 1999; Lin et al., 2008].The impact of transport of background ozone on surface air quality is a matter of considerable186

CHAPTER 5 – NORTH AMERICAdebate [Lefohn et al., 2008; Oltmans et al., 2008]. Presently no strategies exist to mitigate theimpact of increasing background O 3 upon local or regional air quality. It is likely that all northernmid-latitude emissions contribute to this background.Figure 20 - Odd oxygen (OX = O3 + NO2) and CO measured in the vicinity of Mexico City on 18 March 2006 (light red), in thesame airmass a day later and about 500 km downwind (dark red), near Boston on 21 July 2004 (light green), and on thesame day about 500 km downwind from New York City (dark green). The steeper slopes defined by the latter, darkcoloured data result from regional OX production during transport.[Mexico City data derived from NCAR C-130 and DOE G1 flights reported by Zaveri et al., 2007; northeast US data derivedfrom NOAA WP-3D flights reported by Neuman et al., 2006]5.5 CONCLUSIONSThe experiences in North American megacities demonstrate that urban and industrialdevelopment can proceed simultaneously with air quality improvement. Results from past andfuture field studies will continue to contribute to a fuller understanding of air pollution and itsimpacts on human health, ecosystem viability, and climate change. The integration of air qualityinformation from old and new studies of megacities in different settings will improve significantlythe scientific basis that decision makers in megacities around the world will need to craft effectiveenvironmental policies.ReferencesAiken, A. C., Foy, B. d., Wiedinmyer, C., DeCarlo, P. F., Ulbrich, I. M., Wehrli, M. N., Szidat, S.,Prevot, A.S.H., Noda, J., Wacker, L., Volkamer, R., Fortner, E., Wang, J., Laskin, A.,Shutthanandan, V., Zheng, J., Zhang, R., Paredes-Miranda, G., Arnott, W.P., Molina, L.T.,Sosa, G., Querol, X., and Jimenez, J. L. (2009). Mexico City aerosol during MILAGROusing high resolution aerosol mass spectrometry at the urban supersite (T0) - Part 1: Fineparticle composition and organic source appportionment. Atmos. Chem. Phys., 9(12),6633-6653. doi: 10.5194/acp-10-5315-2010Alexis, A., Gaffney, P., Garcia, C., Nystrom, M., & Rood, R. (1999). The 1999 California Almanacof emissions and air quality. California Air Resources Board.Bell, M. L., Goldberg, R., Hogrefe, C., Kinney, P. L., Knowlton, K., Lynn, B., Rosenthal, J.,Rosenzweig, C., and Patz, J. A. (2007). Climate change, ambient ozone, and health in 50US cities. Climate Change(82), 61-76187

CHAPTER 5 – NORTH AMERICABlumenthal, D. L., Lurmann, F. W., Kumar, N., Dye, T. S., Ray, S. E., Korc, M. E., Londergan, R.,and Moore, G. (1997). Transport and mixing phenomena related to ozone exceedances inthe Northeast US (Analysis of NARSTO-Northeast Data). Santa Rosa, CA.Boersma, K. F., Jacob, D. J., Buscela, E. J., Perring, A. E., Dirksen, R., van der, A., Yanrosca, R.,Park, R., Wenin, M., Bertram, T.H, and Cohen, R. C. (2008). Validations of OMItropospheric NO2 observations during INTEX-B and application to constrain NO X emissionsover the eastern US and Mexico. Atmos. Environ., 42, 4480-4497Christian, T. J., Yokelson, R. J., Cardenas, B., Molina, L. T., Engling, G., & Hsu, S. C. (2009).Trace gas and particle emissions from domestic and industrial biofuel use and garbageburning in central Mexico. Atmos. Chem. Phys., 9(2), 10101-10152. doi: 10.5194/acp-10-565-2010Cox, P., Delao, A., Komorniczak, A., & Weller, R. (2009). The California Almanac of emissions andair quality-2009 edition. California Air Resources Board.Croes, B. E., & Fujita, E. M. (2003). Overview of the 1997 Southern California OzoneStudy(SCOS97-NARSTO). Atmos. Environ., 37(Supplement No. 2), 3-26Crounse, J. D., DeCarlo, P. F., Blake, D. R., Emmons, L. K., Campos, T. L., Apel, E. C., Clarke,A.J., Weinheimer, A.J., McCabe, D.C., Yokelson, R.J., Jimenez, J.L., and Wennberg, P. O.(2009). Biomass burning and urban air pollution over the Central Mexican Plateau. Atmos.Chem. Phys., 9(1), 4929-4944. doi: 10.5194/acpd-9-2699-2009DeBell, L. J., Gebhart, K. A., Hand, J. L., Malm, W. C., Pitchford, M. L., Schichtel, B. A., & White,W. H. (2006). Spatial and seasonal patterns and temporal variability of haze and itsconstituents in the United States: Report IV. IMPROVE.DeCarlo, P. F., Dunlea, E. J., Kimmel, J. R., Aiken, A. C., Sueper, D., Crounse, J., .Wennberg,P.O., Emmons, L., Shinozuka, Y., Clarke, A., Zhou, J., Tomlinson, J., Collins, D.R., Knap,D., Weinheimer, A.J., Montzka, D.D., Campos, T., and Jimenez, J. L. (2008). Fast airborneaerosol size and chemistry measurments above Mexico City and Central Mexico during theMILAGRO campaign. Atmos. Chem. Phys., 8(14), 4027-4048. doi: 10.5194/acp-8-4027-2008.Diffenbaugh, N. S., Giorgi, F., & Pal, J. S. (2008). Climate change hotspots in the United States.Geophys. Res. Letts., 35(L16709). doi: 10.1029/2008GL035075Doran, & al, e. (1998). The IMADA-AVER boundary layer experiment in the Mexico City area. Bull.Am. Met. Soc., 79(11), 2497-2508. doi: 10.1175/1520-0477(1998)0792.0.CO;2Dusanter, S., Vimal, D., Stevens, P. S., Volkamer, R., & Molina, L. T. (2009). Measurements of OHand HO2 concentrations during the MCMA-2006 field campaign- Part 1: Deployment of theIndiana University laser-induced fluorescence instrument. Atmos. Chem. Phys., 9(5), 1665-1685. doi: 10.5194/acp-9-1665-2009Dzepina, K., Volkamer, R. M., Madronich, S., Tulet, P., Ulbrich, I. M., Zhang, Q., Cappa, C.D.,Ziemann, J., and Jimenez, J. L. (2009). Evaluation of recently-proposed secondary organicaerosol models for a case study in Mexico City. Atmos. Chem. Phys., 9(15), 5681-5709.doi: 10.5194/acp-9-5681-2009Edgerton, S. A., Bian, X., Doran, J. C., Fast, J. D., Hubbe, J. M., Malone, E. L., .Shaw, W.J.,Whiteman, C.D., Zhing, S., Arriaga, J.L., Ortiz, E., Ruiz, M., Sosa, G., Vega, E., Limon, T.,Guzman, F., Archuleta, J., Bossert, J.E., Elliott, S., Lee, J.T., McNair, L.A., Chow, J.C.,Watson, J.G., Coulter, R.L., Doskey, P.V., Gaffney, J.S., Marley, N.A., Neff, W., and Petty,R. (1999). Particulate air pollution in Mexico City: A collaborative research project. J. AirWaste Manag. Assoc., 49, 1221-1229Engel-Cox, J. A., Hoff, R. M., Rogers, R., Dimmick, F., Rush, A. C., Szykman, J. J., Al-Saadi, J.,Chu, D.A., and Zell, E. R. (2006). Integrating lidar and satellite optical depth with ambientmonitoring for 3-dimensional particulate characterization. Atmos. Environ., 40(40), 8056-8067. doi: 10.1016/j.atmosenv.2006.02.039188

CHAPTER 5 – NORTH AMERICAFehsenfeld, F. C., Ancellet, G., Bates, T. S., Goldstein, A. H., Hardesty, R. M., Honrath, R., Law,K.S., Lewis, A.C., Lealtch, R., McKeen, S., Meagher, J., Parrish, D.D., Pszenny, A.A.P.,Russell, P.B., Schlager, H., Seinfeld, J., Talbot, R., and Zbinden, R. (2006). InternationalConsortium for Atmospheric Research on Transport and Transformation (ICARTT): NorthAmerica to Europe-Overview of the 2004 summer field study. J. Geophys. Res.,111(D23S01). doi: 10.1029/2006JD007829Foy, B. d., Fast, J. D., Paech, S. J., Phillips, D., Walters, J. T., Coulter, R. L., Martin, T.J., Pekour,M.S., Shaw, W.J., Kastendeuch, P.P., Marley, N.A., Retama, A., and Molina, L. T. (2008).Basin-scale wind transport during the MILAGRO field campaign and comparison toclimatology using cluster analysis. Atmos. Chem. Phys., 8(5), 1209-1224. doi: 10.5194/acp-8-1209-2008Foy, B. d., Varela, J. R., Molina, L. T., & Molina, M. J. (2006). Rapid ventilation of the Mexico CityBasin and regional fate of the urban plumes. Atmos. Chem. Phys., 6(8), 2321-2335. doi:10.5194/acp-6-2321-2006Garcia, A. R., Volkamer, R., Molina, L. T., Molina, M. J., Samuelson, J., Mellqvist, J., Galle, B.,Herdon, C., and Kolb, C. E. (2006). Separation of emitted and photochemical formaldehydein Mexico City using a statistical analysis and a new pair of gas-phase tracers. Atmos.Chem. Phys., 6(12), 4545-4557. doi: 10.5194/acp-6-4545-2006Haagen-Smit, A. J. (1952). Chemistry and physiology of Los Angeles smog. Indust. Eng. Chem.,44(1342).Hall, J. V., Brajer, V., & Lurmann, F. W. (2008). The benefits of meeting federal clean air standardsin the South Coast and San Joaquin Valley air basins (pp. 98): William and Flora HewlettFoundation.Jacob, D. J., Crawford, J. H., Maring, H., Dibb, J. E., Clarke, A. D., Ferrare, R. A., Hostetler, C.A.,Russell, P.B., Singh, H.B., Thompson, A.M., Shaw, G.E., McCauley, E., Pederson, J.R.,and Fisher, J. A. (2009). The ARCTAS aircraft mission: design and execution. Atmos.Chem. Phys. Disc., 9(4), 17073-17123. doi: 10.5194/acpd-9-17073-2009Jacob, D. J., Logan, J. A., & Murti, P. P. (1999). Effect of rising Asian emissions on surface ozonein the United States. Geophys. Res. Letts., 26(14), 2175-2178Jacob, D. J., & Winner, A. (2009). Effect of climate change on air quality. Atmos. Environ., 43(1),51-63. doi: 10.1016/j.atmosenv.2008.09.051Johnson, K. S., Foy, B. d., Zuberi, B., Molina, L. T., Molina, M. J., Xie, Y.,Laskin, A., andShutthanandan, V. (2006). Aerosol composition and source apportionment in the MexicoCity Metropolitan Area with PIXE/PESA/STIM and multivariate analysis. Atmos. Chem.Phys., 6(12), 4591-4600. doi: 10.5194/acp-6-4591-2006Karl, T., Apel, E., Hodzic, A., Riemer, D. D., Blake, D. R., & Wiedinmyer, C. (2009). Emissions ofvolatile organic compounds inferred from airborne flux measurements over a megacity.Atmos. Chem. Phys., 9(1), 271-285. doi: 10.5194/acp-9-271-2009Kim, S. W., Heckel, A., Frost, G. J., Richter, A., Gleason, J., Burrows, J. P., McKeen, S., Hsie, E.-Y., Granier, C., and Trainer, M. (2009). NO2 columns in the western United Statesobserved from space and simulated by a regional chemistry model and their implicationsfor NO X emissions. J. Geophys. Res., 114(D11301). doi: 10.1029/2008JD011343Kleinman, L. I., Springston, S. R., Daum, P. H., Lee, Y.-N., Nunnermacker, L. J., Senum, G. I.,Wang, J., Weinstein-Lloyd, J., Alexander, M.L., Hubbe, J., Ortega, J., Canagaratna, M.R.,and Jayne, J. (2008). The time evolution of aerosol composition over the Mexico Cityplateau. Atmos. Chem. Phys., 8(5), 1559-1579. doi: 10.5194/acpd-7-14461-2007Lefohn, A. S., Shadwick, D., & Oltmans, S. J. (2008). Characterizing long-term changes in surfaceozone levels in the United States (1980-2005). Atmos. Environ., 42(35), 8252-8262. doi:10.1016/j.atmosenv.2008.07.060Lei, W., Foy, B. d., Zavala, M., Volkamer, R., & Molina, L. T. (2006). Characterizing ozoneproduction in the Mexico City Metropolitan Area: a case study using chemical transportmodel. Atmos. Chem. Phys., 6(4), 1347-1366. doi:10.5194/acpd-6-7959-2006189

CHAPTER 5 – NORTH AMERICALei, W., Zavala, M., Foy, B. d., Volkamer, R., & Molina, L. T. (2009). Impact of primaryformaldehyde on air pollution in the Mexico City Metropolitan Area. Atmos. Chem. Phys.,9(7), 2607-2618. doi: 10.5194/acp-9-2607-2009Lei, W., Zavala, M., Foy, B. d., Volkamer, R., Molina, M. J., & Molina, L. T. (2008). Characteriingozone production and response under different meterological conditions in Mexico City.Atmos. Chem. Phys., 8(3), 7571-7581. doi: 10.5194/acpd-8-12053-2008Lin, J. T., Wuebbles, D. J., & Liang, X. G. (2008). Effects of intercontinental transport on surfaceozone over the United States: Present and future assessment with a global model.Geophys. Res. Letts., 35(2). doi: 10.1029/2007GL031415Martin, R. V. (2008). Satellite remote sensing of surface air quality. Atmos. Environ., 42(34), 7823-7843. doi: 10.1016/j.atmosenv.2008.07.018Moffet, R. C., Foy, B. d., Molina, L. T., Molina, M. J., & Prather, K. A. (2008). Measurement ofambient aerosols in northern Mexico City by single particle mass spectrometry. Atmos.Chem. Phys., 8(16), 4499-4516. doi: 10.5194/acp-8-4499-2008Molina, L. T., Foy, B. d., Vazquez-Martinez, O., & Paramo-Figueroa, V. H. (2009). Air quality,weather and climate in Mexico city. WMO Bulletin, 58(1), 48-53Molina, L. T., Kolb, C. E., Foy, B. d., Lamb, B. K., Brune, W. H., Jimenez, J. L., Ramos-Villegas,R., Sarmiento, J., Paramo-Figueroa, V.H., Cardenas, B., Gutierres-Avedoy, V., and Molina,M. J. (2007). Air quality in North America's most populous city- overview of the MCMA-2003 campaign. Atmos. Chem. Phys., 7(10), 2447-2473. doi: 10.5194/acp-7-2447-2007Molina, L. T., Madronich, S., Gaffney, J. S., Apel, E., Foy, B. d., Fast, J., Ferrare, R., Herndon, S.,Jiminez, J.L., Lamb, B., Osornio-Vargas, A.R., Russell, P., Schauer, J.J., Stevens, P.S.,Volkamer. R., and Zavala, M. (2010). An overview of the MILAGRO 2006 campaign:Mexico City emissions and their transport and transformation. Atmos. Chem. Phys., 10,8697-8760. doi: 10.5194/acp-10-8697-2010Molina, L. T., & Molina, M. J. (Eds.). (2002). Air quality in the Mexico megacity: An integratedAssessment (Vol. 2): Kluwer Academic Publishers.Murazaki, K., & Hess, P. (2006). How does climate change contribute to surface ozone changeover the United States? J. Geophys. Res., 111(D05301). doi: 10.1029/2005JD005873Neuman, J. A., Parrish, D. D., Trainer, M., Ryerson, T. B., Holloway, J. S., Nowak, J. B., Swanson,A., Flocke, F., Roberts, J.M., Brown, S.S., Stark, H., Sommariva, R., Stohl, A., Weber, R.,Wollney, A.G., Suerper, D.T., Hubler, G., and Fehsenfeld, F. C. (2006). Reactive nitrogentransport and photochemistry in urban plumes over the North Atlantic Ocean. J. Geophys.Res., 111(D23S54), 11. doi: 10.1029/2005JD007010Oltmans, S. J., Lefohn, A. S., Harris, J. M., & Shadwick, D. S. (2008). Background ozone levels ofair entering the west coast of the US and assessment of longer-term changes. Atmos.Environ., 42(24), 6020-6038. doi: 10.1016/j.atmosenv.2008.03.034Parrish, D. D., Allen, D. T., Bates, T. S., Fehsenfeld, F. C., Feingold, G., Ferrare, R., Hardesty,R.M., Meagher, J.F., Nielsen-Gammon, J.W., Pierce, R.B., Ryerson, T.B., Seinfeld, J.H.,and Williams, E. J. (2009b). Overview of the Second Texas Air Quality Study (TexAQSII)and the Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS). J.Geophys. Res., 114(D00F13). doi: 10.1029/2009JD011842Parrish, D. D., Kondo, Y., Cooper, O. R., Brock, C. A., Jaffe, D. A., Trainer, M., Ogawa, T., Hubler,G., and Fehsenfeld, F. C. (2004). Intercontinental Transport and Chemical Transformation2002 (ITCT 2K2) and Pacific Exploration of Asian Continental Emission (PEACE)experiments: An overview of the 2002 winter and spring intensives. J. Geophys. Res.,109(D23S01). doi: 10.1029/2004JD004980Parrish, D. D., Kuster, W. C., Shao, M., Yokouchi, Y., Kondo, Y., Goldan, P. D., de Goue, J.A.,Koike, M., and Shirai, T. (2009a). Comparison of air pollutant emissions among megacities.Atmospheric Environment. doi: 10.1016/j.atmosenv.2009.06.024Parrish, D. D., Millet, D. B., & Goldstein, A. H. (2009c). Increasing ozone in marine boundary layerair inflow at the west coast of North America and Europe. Atmos. Chem. Phys., 9(4), 1303-1323. doi: 10.5194/acpd-8-13847-2008190

CHAPTER 5 – NORTH AMERICAQuerol, X., Prey, J., Minguillon, M. C., Perez, N., Alasteuy, A., Viana, M., Moreneo, T., Bernabe,R.M., Blanco, S., Cardenas, B., Vega, E., Sosa, G., Escalona, S., Ruiz, H., and Artinano, B.(2008). PM speciation and sources in Mexico during the MILAGRO-2006 Campaign.Atmos. Chem. Phys., 8(1), 111-128. doi: 10.5194/acp-8-111-2008Ramanathan, V., & Feng, Y. (2009). Air pollution, greenhous gases and climate change: Globaland regional perspectives. Atmos. Environ., 43(1), 37-50. doi:10.1016/j.atmosenv.2008.09.063Rankin, B. (2009). Population-density map of the Northeast megalopolis. In Boswash.png (Ed.).Ryerson, T. B., Trainer, M., Angevine, W. M., Brock, C. A., Dissly, R. W., Fehsenfeld, F. C., . . .Senff, C. J. (2003). Effect of petrochemical industrial emissions of reactive alkenes andNO X on tropospheric ozone formation in Houston, Texas. J. Geophys. Res., 108(D8), 4249.doi: 10.1029/2002JD003070Salcedo, D., Onasch, T. B., Dzepina, K., Canagaratna, M. R., Zhang, Q., Huffman, J. A., DeCarlo,P.F., Jayne, J.T., Mortimer, P., Worsnop, D.R., Kolb, C.E., Johnson, K.S., Zuberi, B., Marr,L.C., Volkamer, R., Molina, L.T., Molina, M.J., Cardenas, B., Bernabe, R.M., Marquez, C.,Gaffney, J.S., Marley, N.A., Laskin, A., Shuttanandan, V., Xie, Y., Brune, W., Lesher, R.,Shirley, T., and Jimenez, J. L. (2006). Characterization of ambient aerosols in Mexico Cityduring the MCMA-2003 campaign with Aerosol Mass Spectrometry. Atmos. Chem. Phys.,6(4), 925-946. doi: 10.5194/acp-6-925-2006Sheehy, P. M., Volkamer, R., Molina, L. T., & Molina, M. J. (2010). Oxidative capacity of theMexico City atmosphere- Part 2: A ROx radical cycling perspective. Atmos. Chem. Phys.,10(14), 6993-7008. doi: 10.5194/acp-10-6993-2010Singh, H. B., Brune, W. H., Crawford, J. H., Flocke, F., & Jacob, D. J. (2009). Chemistry andtransport of pollution over the Gulf of Mexico and the Pacific: Spring 2006 INTEX-BCampaign overview and first results. Atmos. Chem. Phys., 9(7), 2301-2318. doi:10.5194/acp-9-2301-2009SMA-GDF. (2008). Inventario de emisiones de la atmosfera. Zona Metropolitana del Valle deMexico 2006, 2008Steiner, A. L., Tonse, S., Cohen, R. C., Goldstein, A. H., & Harley, R. A. (2006). Influence of futureclimate and emissions on regional air quality in California. J. Geophys. Res., 111(D18303).doi: 10.1029/2005JD006935Stephens, S., Madronich, S., Wu, F., Olson, J. B., Ramos, R., Retama, A., & Munoz, R. (2008).Weekly patterns of Mexico City's surface concentrations of CO, NO X , PM 10 and O 3 during1986-2007. Atmos. Chem. Phys., 8(17), 5313-5325. doi: 10.5194/acp-8-5313-2008Stone, E. A., Snyder, D. C., Sheesly, R. J., Sullivan, A. P., Weber, R. J., & Schauer, J. J. (2008).Source apportionment of fine organic aerosol in Mexico City during the MILAGROexperiement. Atmos. Chem. Phys., 8(5), 1249-1259. doi: doi:10.5194/acp-8-1249-2008Streit, G. E., & Guzman, F. (1996). Mexico City Air Quality: Progress of an internationalcollaborative project to define air quality management options. Atmos. Environ., 30(5), 723-733. doi: 10.1016/1352-2310(95)00275-8Tie, X., Madronich, S., Li, G., Ying, Z., Weinheimer, A., Apel, E., & Campos, T. (2009). Simulationof Mexico City plumes during the MIRAGE-MEx field campaign using the WRF-Chemmodel. Atmos. Chem. Phys., 9(2), 4621-4638. doi: 10.5194/acpd-9-9221-2009Tie, X., Madronich, S., Li, G., Ying, Z., Zhang, R., Garcia, A., Leet-Tayloe, J., and Liu, Y. (2007).Characterization of chemical oxidants in Mexico city: A regional chemical dynamical model(WRF-Chem) study. Atmos. Environ., 41(9), 1989-2008. doi:10.1016/j.atmosenv.2006.10.053Velasco, E., Lamb, B., Pressley, S., Allwine, E., Westberg, H., Jobson, T., Alexander, M.,Prazeller, P., Molina, L. and Molina, M. (2005). Flux measurements of volatile organiccompounds from an urban landscape. Geophys. Res. Letts., 32(L20802). doi:10.1029/2005Gl023356191

CHAPTER 5 – NORTH AMERICAVelasco, E., Lamb, B., Westberg, H., Allwine, E., Sosa, G., Arriaga-Colina, J. L., Jobson, B. T.,Alexander, M. L., Prazeller, P., Knighton, W. B., Rogers, T. M., Grutter, M., Herndon, S. C.,Kolb, C. E., Zavala, M., de Foy, B., Volkamer, R., Molina, L. T., and Molina, M. J. (2007).Distribution, magnitudes, reactivities, ratios and diurnal patterns of volatile organiccompounds in the valley of Mexico during the MCMA 2002 and 2003 field campaigns.Atmos. Chem. Phys., 7(2), 329-353. doi: 10.5194/acp-7-329-2007Velasco, E., Pressley, S., Grivicke, R., Allwine, E., Coons, T., Foster, W., Jobson, T., Westberg,H., Ramos, R., Hernandez, F., Molina, L.T., and Lamb, B. (2009). Eddy covariance fluxmeasurements of pollutant gases in urban Mexico City. Atmos. Chem. Phys., 9(2), 7325-7342. doi: 10.5194/acpd-9-7991-2009Volkamer, R., Jimenez, J. L., Martini, F. S., Dzepina, K., Zhang, Q., Salcedo, D., Molina, L.,T.,Worsnop, D.R., and Molina, M. J. (2006). Secondary organic aerosol formation fromanthropogenic air pollution: Rapid and higher than expected. Geophys. Res. Letts.,33(L17811). doi: 10.1029/2006GL026899Volkamer, R., Sheehy, P. M., Molina, L. T., & Molina, M. J. (2010). Oxidative capacity of theMexico City atmosphere- Part 1: A radical source perspective. Atmos. Chem. Phys., 7(14),5365-5412. doi: 10.5194/acp-10-6969-2010Yokelson, R. J., Crounse, J. D., DeCarlo, P. F., Karl, T., Urbanski, S., Atlas, E., Campos, T.,Shinozuka, Y., Kapustin, V., Clarke, A.D., Weinheimer, A., Knapp, D.J., Montzka, D.D.,Halloway, J., Weibring, P., Flocke, F., Zheng, W., Toohey, D., Wennherg, P.O.,Wiedinmyer, C., Mauldin, L., Fried, A., Richter, D., Walega, J., Jiminez, J.L., Adachi, K.,Buseck, P.R., Hall, S.R., and Shetter, R. (2009). Emissions from biomass burning in theYucatan. Atmos. Chem. Phys., 9(15), 5785-5812. doi: 10.5194/acp-9-5785-2009Yokelson, R. J., Urbanski, S. P., Atlas, E. L., Toohey, D. W., Alvarado, E. C., Crounse, J. D.,Wennberg, M. E. Fisher, C. E. Wold, T. L. Campos, K. Adachi, P. R. Buseck, and Hao, W.M. (2007). Emissions from forest fires near Mexico City. Atmos. Chem. Phys., 7(3), 5569-5584. doi: 10.5194/acpd-7-6687-2007Zavala, M., Herndon, S. C., Wood, E. C., Onasch, T. B., Knighton, W. B., Kolb, C. E., & Molina, L.T. (2006). Characterization of on-road vehicle emissions in the Mexico City MetropolitanAreas using a mobile laboratory in chase and fleet average measurement modes during theMCMA-2003 field campaign. Atmos. Chem. Phys., 6(12), 5129-5142. doi: 10.5194/acp-6-5129-2006Zavala, M., Herndon, S. C., Wood, E. C., Onasch, T. B., Knighton, W. B., Kolb, C. E., & Molina, L.T. (2009). Evaluation of mobile emissions contributions to Mexico City's emissionsinventory using on-road and cross-road emission measurements and ambient data. Atmos.Chem. Phys., 9(17), 6363-6395. doi: 10.5194/acp-9-6305-2009Zaveri, R. A., Chapman, E. G., Easter, R. C., Fast, J. D., Flocke, F., Kleinman, L. I., Madronich, S.,Pringston, S.R., Voss, P.B., and Weinheimer, A. (2007). Modeling gas-aerosol processesduring MILAGRO 2006. Eos Trans. AGU, Fall Meeting 2007, 88(52)._______192

CHAPTER 6 - EUROPECoordinating Authors: Michael Gauss (1) , Mark Lawrence (2)Contributing Authors: Erika von Schneidemesser (3) , Paul S. Monks (3) , Matthias Beekmann (4) , Alexander Baklanov (5) ,Alexander Ginzburg (6) , Michael Memmesheimer (7) , Jochen Theloke (8) , Balendra Thiruchittampalam (8) , Rainer Friedrich (8) ,Melinda Uzbasich (8) , Hermann Jakobs (9) , Sabine Wurzler (10) , Sandro Finardi (11) , Paola Radice (12) , Maria Kanakidou (13) ,Konstantinos Markakis (14) , Ulas Im (13) , Nikos Mihalopoulos (13) , Dimitris Melas (14) , Mihalis Vrekoussis (15,16)(1)Norwegian Meteorological Institute (met.no), Oslo, Norway(2)Institute for Advanced Sustainability Studies, Potsdam, Germany(3)Department of Chemistry, University of Leicester, Leicester, UK(4)Laboratoire Inter-Universitaire de Systèmes Atmosphériques (LISA), CNRS UMR 7583, Universités Paris-EstCréteil and Paris Diderot, Créteil, France(5)Danish Meteorological Institute (DMI), Copenhagen, Denmark(6)Institute of Atmospheric Physics, Russian Academy of Sciences, Moscow, Russia(7)Rhenish Institute for Environmental Research, University of Cologne, Cologne, Germany(8)Institute of Energy Economics and the Rational Use of Energy (IER), University of Stuttgart, Stuttgart, Germany(9)Rhenish Institute for Environmental Research, University of Cologne, Cologne, Germany(10)North-Rhine Westphalia State Agency for Nature, Environment, and Consumer Protection (LANUV-NRW),Essen, Germany(11)ARIANET Consulting, Milan, Italy(12)Paola Radice: ARIANET Consulting, Milan, Italy(13)Environmental Chemical Processes Laboratory (ECPL), Department of Chemistry, University of Crete,Heraklion, Greece(14)Laboratory of Atmospheric Physics, Physics Department, Aristotle University of Thessaloniki, Thessaloniki,Greece(15)Research Centre for Atmospheric Physics and Climatology, Academy of Athens, Athens, Greece(16)Institute of Environmental Physics, University of Bremen, Bremen, Germany6.1 EUROPEAN MEGACITIES: GENERAL AND COMPARATIVE CHARACTERISTICS6.1.1 Population and GeographyThis chapter gives an overview of the megacities and major population centres (MPCs) ofEurope, namely London, Paris, Moscow, the Benelux/Rhine-Ruhr region, the Po Valley, and theEastern Mediterranean including Istanbul.A summary of the populations and location of the European MPCs is given in Table 1. Incontrast to MPCs in several other parts of the world, e.g., Asia and Africa, the populations of theEuropean MPCs, with the exception of Istanbul, have been relatively stable over the past severaldecades, and are predicted to remain so for at least the next couple decades.Table 1 - Populations and Characteristics of European Megacities and Major Population CentresMegacity / MPC Population 1 (Million) Latitude LongitudeParis, France 10.4 49.4 1.9London, England 8.6 51.3 0.0Po Valley, Italy ca.20 ~45-46 ~11-12Ruhrgebiet, Germany and Benelux Region 28 (BeNeLux) + 5.7 3 ~49-54 ~2-8(Belgium, Netherlands, Luxemburg)(Ruhrgebiet)Moscow, Russia 10.5 55.0 37.5Istanbul, Turkey 10.4 40.1 28.11 Population Source (unless otherwise noted): Population Division of the Department of Economic and Social Affairs of the UnitedNations Secretariat World Urbanization Prospects: The 2009 Revision, Web: http://esa.un.org/unpd/wup/index.htm193

CHAPTER 6 - EUROPEFigure 1 shows a map of the population density of Europe. For Europe, the bottom-upstatistical and census-based population data plotted here are generally very consistent withtop-down estimates based on analyses of stable night lights; alternate representations of thepopulation are available on the internet, e.g., a mapping by district complied by the IIASA EuropeanRural Development (ERD) Project (http://www.iiasa.ac.at/Research/ERD/DB/mapdb/map_9.htm).The map shows that each of the six European MPCs listed in Table 1 is characterized by a largecentral region with a population density exceeding 1000 persons/km 2 . There are also a handful ofother cities within Europe with population densities as high as this, e.g., Berlin and Madrid, but thetotal populations of these cities are not large enough to generally be classified as Megacities orMPCs for the sake of this overview. Beyond the commonality of a dense core region, however,there are substantial differences in the geographical locations and urban and suburban structure ofthe European MPCs. One interesting feature is that while a large fraction of the MPCs worldwideare either coastal or close to large bodies of water, only one of the European MPCs, Istanbul, isreally a coastal city. London is also relatively close to the coast, while Paris, the Po Valley and theBenelux/Rhine-Ruhr region are all several hundred km away from the nearest coast, and Moscow isthe most land-locked of all megacities worldwide. Further differences in the demographical andgeographical characteristics are elucidated in the discussions of the individual cities, below.Figure 1 - Map of the population density in Europe and western Asia (persons per km 2 ), based on 0.25 o gridded data for2000 from the Centre for International Earth Science Information Network (CIESIN) at Columbia University[http://sedac.ciesin.columbia.edu/gpw/]6.1.2 EmissionsExemplary emissions of key pollutant gases in Europe are depicted in Figure 2. Research onemissions from megacities worldwide has included several studies of city-specific emissions. ForEurope in particular, a significant recent effort has gone into developing a collection of inventoriesfor European cities within the City Delta project [Cuvelier et al., 2007]. Four of the European MPCswere also included in the study of Butler et al. [2008)], which contrasted the emissionscorresponding to 32 MPCs in three widely-used global emissions datasets (EDGAR, RETRO andIIASA) with each other and with city-specific emissions, where available. The comparison showsfrequently large differences (often a factor of two or more) between the emissions for individualcities within the global datasets, and normally large underestimates compared to the city-specificdatasets. This applies especially to Paris, for which the CO emissions in the global datasets rangeover nearly a factor of two, from 263 Gg(CO)/yr (EDGAR) to 490 Gg(CO)/yr (RETRO), and are afactor of 4-7 less than the 1907 Gg(CO)/yr estimated in the City Delta project. The discrepancydetermined for London is smaller, but still exceeding a factor of 2, with a range of 800-1043Gg(CO)/yr from the global inventories versus 1993 Gg(CO)/yr from the City Delta inventory.Interestingly, a much better agreement is found for Moscow, with a range of 979-1249 Gg(CO)/yr194

CHAPTER 6 - EUROPEfrom the global inventories versus 1324 Gg(CO)/yr from the study of Gurjar et al. [2008]. A muchsmaller but still highly uncertain CO source is estimated for Istanbul (244-602 Gg(CO)/yr from theglobal inventories, with no city-specific inventory available). The discrepancies between thedatasets for NO X and NMHCs tend to be even larger. This large uncertainty – even for EuropeanMegacities, which should be among the best characterized around the world – points towards thelarge difficulty which will be inherent in assessing the role of megacities in regional and globalatmospheric pollution and climate change, and ascertaining effective mitigation strategies. On theother hand, despite the large differences in the totals, there is a notable similarity in thecharacteristics of the relative importance of various sectors for different gases. In particular, similarto most OECD nations, the emissions of CO are generally dominated by road transport, and of NO Xand NMHC by a combination of road transport and industrial processes, contrasted with the largerole of residential biofuel use for emissions from non-OECD countries.Figure 2 - (a) CO emissions for theyear 2000 based on the EDGARv3.2FT2000 database. (b) NOX emissionsfor the year 2000 based on theEDGARv3.2 FT2000 database. (c) SO2emissions for the year 2000 basedon the EDGARv3.2 FT2000 database195

CHAPTER 6 - EUROPE6.1.3 Pollution levelsThe air pollution in the European MPCs which results from the emissions discussed in theprevious section, as part of the broader topic of general urban air quality, has a very long history ofslowly increasing recognition and research. In particular, London has a very important historical rolein this respect, with the “London Smog” events dating back at least to the 17 th century, culminatingin the weeklong tragedy in December, 1952, which caused about 12,000 deaths. Many other largecities have been renowned for their poor air quality, as well as for the substantial clean-up effortsover more recent years, e.g., the reduction of acid rain throughout Europe in the latter part of the20 th century.6.1.4 Outflow characteristics and effects on regional ozone-related atmospheric chemistryTo our knowledge, only one published study thus far [Butler and Lawrence, 2009] hasexamined the impact of megacities worldwide on regional and global ozone-related atmosphericchemistry, and none have done so yet for aerosol and climate impacts. A few further studies haveexamined this for specific regions [e.g., for Asia in Guttikunda et al., 2005], but none to ourknowledge specifically for the European MPCs. Some studies on the impacts of individual cities willbe discussed in the following sections.Butler and Lawrence [2009] used a zeroth-order approach, the so-called “annihilationscenario”, to examine the megacity effects by removing their emissions from the correspondinggridcells in a global emissions inventory (at 1 o horizontal resolution) before interpolating to theglobal model grid, and comparing these results with a simulation including the normal totalemissions. The results show that the overall impact of megacities on the major ozone precursorgases NO X and CO are of the order of 5-10%, corresponding to the relative contribution ofmegacities to the global total emissions of the precursor gases, while the impact on global O 3 ismuch smaller, around 1%. The change in July mean surface ozone is shown for four scenarios inFigure 3. The exact dependence of the regional chemistry on the emissions varies as a function ofgeographical location, and corresponds particularly strongly with the latitudes of the MPCs. In theindividual grid cells containing megacities, the response for European megacities is similar to mostother extratropical megacities, with a reduction in ozone year-round, and often an increase in ozonein the downwind grid cells, particularly in summertime; in tropical megacity grid cells, on the otherhand, ozone generally increases year-round. The influence is found to change for various futurescenarios. Under a future scenario with a maximum feasible reduction of emissions, the influence ofmegacities is generally reduced, while under a high-emission future scenario, although the localinfluence of megacities is increased, the geographical extent of the influence becomes smaller. Onenote worth making about these results is that the tendency for global emissions datasets tounderestimate the emissions compared to city-specific datasets, as discussed above, also meansthat the impacts of megacities are probably somewhat underestimated in these simulations.Finally, a special characteristic of the European MPCs has been pointed out and quantifiedby Lawrence et al. [2007], who examined results of simulations with generic, gas-phase tracers withthree different representative lifetimes (1, 10 and 100 days) emitted from 36 MPCs distributedglobally. Using metrics to rank different outflow characteristics (“regional pollution potentials”) of theMPCs, it was found that the MPCs in this region tend to be ranked highest amongst all globalregions in terms of the tendency for pollutants to both accumulate locally in the surface layer of theregion immediately surrounding each MPC, as well as to be transported extensive distances (e.g.larger than 1000 km) downwind, while still remaining in the boundary layer. Conversely, theemissions from European MPCs are least effectively transported into the upper tropospherecompared to other world regions. Two major open issues for follow-up studies are currently beinginvestigated: the same kind of simulations with aerosol tracers (including sedimentation,scavenging and deposition) are being performed for comparison to the gas-phase tracer results [D.Kunkel et al., 2011], and comparable regional model simulations are being set up for the Europeanregion to determine the impact of using a considerably higher resolution in a non-hydrostatic modelon the pollutant dispersion characteristics [I. Coll et al., LISA, pers. comm.].196

CHAPTER 6 - EUROPEFigure 3 - The percentage change in the global surface July O3 mixing ratio due to megacity emissionsunder four scenarios [Butler and Lawrence, 2009]6.2 LONDON6.2.1 City introductionLondon is located in the southeast of England, UK. Greater London, which includes the Cityof London as well as 32 London boroughs in the surrounding area has a population ofapproximately 7.5 million (as of mid-2005). The entire London metropolitan area is just under 14million people. Greater London covers an area of 1,570 sq km and sits on either side of theThames River, approximately 40 km west of the coast of the North Sea. The minimum andmaximum temperatures range from 2.4 to 13.7°C and 7.2 to 22.3°C in January and July,respectively.6.2.2 Emissions sources, trends and dataThe large majority of nitrogen oxides (NO X ), carbon monoxide (CO), particulate matter withan aerodynamic diameter less than or equal to 10 µm (PM 10 ) and certain volatile organic compound(VOC) emissions in London are from mobile sources [Mattai and Hutchinson, 2008]. In an estimatefrom 1997, road emissions of NO X , CO, and PM 10 were found to contribute 76%, 97%, and 77% tototal emissions for all of London, respectively [Crabbe et al., 2000]. Correspondingly, a significantnumber of studies monitoring roadside pollution throughout London have been conducted. Thetrends in NO 2 and NO X from 1997 to 2003 from 36 sites in London have been documented by[Carslaw, 2005] as shown in Figure 4. While NO X concentrations decreased, the NO 2concentrations have remained basically the same from 1997 to 2003. These may have been due tochanges in the vehicle fleet composition, changes in traffic management in London and/or controltechnologies applied to diesel vehicles [Carslaw, 2005]. Changes in the concentration of PM inLondon have also been linked to traffic. Annual mean PM 10 from 1994 to 2004 at different types oflocations throughout London were documented by [Fuller and Green, 2006], and are shown inFigure 5. [Fuller and Green, 2006] found that secondary and natural sources of PM 10 declinedfrom 1997 to 2003, whereas primary sources increased from 1998 to 2003; the largest increases inprimary PM were observed at roadside sites. It should also be noted that long-term transport of airmasses, primarily from mainland Europe, can contribute significantly to PM concentrations in theLondon metropolitan area, especially episodes of elevated concentrations [Charron et al., 2007].197

CHAPTER 6 - EUROPEFigure 4 - [Carslaw, 2005] Trends in monthly mean concentrations of NOX and NO2 averaged across 36 air pollutionmonitoring sites in London (1997-2003). A 12-month moving average trend has been fitted to both data setsFigure 5 - Running annual mean PM10 in London from 1994 to 2004 showing outer London background concentrations(mean of 3 sites), inner London background concentrations (mean of 3 sites), and central London roadside concentrations(1 site). Measurements made during 2004 are provisional [Fuller and Green, 2006]Although there are no extensive ambient VOC monitoring sites across Europe, there havebeen a number of studies done in the UK, with monitoring sites in London [Dollard et al., 2007; Fieldet al., 1994]. Data from Field et al., [1994] showed that generally, VOC concentrations declined from1986 to 1992, especially those associated with motor vehicle exhaust. Later monitoring by Dollardet al. [2007] throughout the UK from 1993 to 2004 also found decreasing VOC concentrations. Theconcentrations were observed to be highest at curbside monitoring stations and lowest in rurallocations; decreases were attributed to the implementation of exhaust gas catalyst and evaporativecanister control technologies on gasoline motor vehicles [Dollard et al., 2007]. Annual meanconcentrations in 2000 ranged from 1.3 to 28.8 µg m -3 for toluene, 0.6 to 14.6 µg m -3 for ethylene,and 0.4 to 7.2 µg m -3 for propylene at rural and curbside locations, respectively [Dollard et al., 2007].Over the past decade, reductions of carbon monoxide and sulphur dioxide concentrations inLondon have been successful. For both, significant decreases in concentration have been observedsince the late 1990s. Carbon monoxide was decreased by 56% from 1997 to 2007, and has been inattainment of the EU limit of 10 mg m -3 (max daily 8h mean) since 2000 [Fuller et al., 2007]. Thehighest concentrations of CO are found near roadways, reflecting the fact that motor vehicles arethe main source. Sulphur dioxide concentrations in London decreased by 78% from 1997 to 2007198

CHAPTER 6 - EUROPEand have been within the UK air quality guidelines of 125 µg m -3 daily mean (350 µg m -3 hourlymean; 266 µg m -3 15min mean) since 1998 [Fuller et al., 2007]. Unfortunately, episodes of elevatedSO 2 still occur in London. A plot of the annual mean index value has been reproduced here asFigure 6 from the London Air Quality Report to show the trends from 1997 to 2008.Figure 6 - London Air Quality Network annual mean index values for CO, PM10, and SO2. Measurements following thedashed line were provisional [LAQN www.londonair.org.uk]6.2.3 Air quality regulationsThe set of air quality guidelines most recently published in the UK are from July 2007. Thestandards are set to protect human health and the environment, based on the most current science,and all those discussed here can be found at www.airquality.co.uk. The air pollutants regulatedinclude benzene, 1,3-butadiene, carbon monoxide, lead, nitrogen dioxide, particulate matter (bothPM 2.5 and PM 10 ), sulphur dioxide, polycyclic aromatic hydrocarbons (PAHs), and ozone. CurrentlyPM 10 is regulated at an annual mean of 40 µg m -3 ; PM 2.5 regulations are not in effect yet, but havean annual mean target of 25 µg m -3 to be reached by 2020. The annual mean standard is also notyet in effect for benzene (5.00 µg m -3 ) or PAHs (0.25 ng m -3 ), which were to be reached by the end2010. All other compounds have annual mean values as follows, 1,3-butadiene (2.25 µg m -3 ), lead(0.25 µg m -3 ), nitrogen dioxide (40 µg m -3 ), and PM 10 (40 µg m -3 ). Carbon monoxide and ozone areboth regulated by 8 hour running means, with standards of 10.0 mg m -3 and 100 µg m -3 , respectively.The 24 hour mean for sulphur dioxide is 125 µg m -3 . Many of these compounds in addition have alimited number of exceedences allowed per year, as well as standards for shorter time periods. Formore detail, please see the website listed above. In addition to the UK air quality standards, thereare some issued by the European Commission (EC) for ozone, nitrogen dioxide, and sulphurdioxide. The time frames for the EC standards do not correspond to those from the UK. Overall, theUK standards are similar to or lower than those issued by the EC.An additional measure taken in Greater London in an attempt to combat the air pollution,specifically that from motor vehicles (the main cause of air pollution for London), was the creation ofa Low Emissions Zone on certain roads and motorways throughout Greater London. In addition, aCongestion Charging Zone (CCZ) was set up in central London in an attempt to reduce trafficcongestion (and emissions) and encourage other methods of transport in the centre of the city. TheCCZ was initially started in February 2003 and was expanded into West London on 19 February2007, and is applicable only on weekdays. The low emission zone (LEZ) regulations went into effecton February 4, 2008, and are being updated with more stringent emissions standards in 2012.Currently, the LEZ does not apply to cars or motorcycles, but does apply to diesel-engined lorries,buses, coaches, motor caravans, motorized horsebox, large vans, minibuses, and other specialistvehicles [tfl.gov.uk]. In order not to be charged for driving in the LEZ, vehicles must meet the Euro IIIstandards for particulate matter. Figure 7 shows the Greater London area with the LEZ and CCZdemarcated.199

CHAPTER 6 - EUROPEFigure 7 - Greater London Map with the Low Emission Zone and the Congestion Charging Zone marked[tfl.gov.uk/lezlondon]6.2.4 Monitoring networkThe London Air Quality Network (LAQN) was set up in 1993 by the Environmental ResearchGroup (ERG) at King’s College in London in cooperation with the London Boroughs and RegionalHealth Authorities. There are over 160 continuous monitoring sites throughout Greater London, andup to date information about air pollution levels is available on their website www.londonair.org.uk.6.3 PARIS6.3.1 Population and geographyAmong the 22 regions of French mainland, the Ile de France region has the highestpopulation, with about 11.7 millions inhabitants, and the highest population density (nearly 1000inhabitants per km 2 ), over an area of about 12000 km 2 . It hosts about 19% of the French population,but generates 28.6 % of the gross domestic product of France (excluding overseas departments)[source: INSEE, Institut National de la Statistique et des Etudes Economiques].Most of the Ile de France population is living in an urbanised area of about 30 – 40 kmdiameter, around Paris city. In these areas, population density is between 3000 and more than30000 inhabitants per km 2 . The agglomeration is also surrounded by rural areas, mainly agriculturalland and forest areas (Figure 8). The Ile de France region is mainly flat, altitudes varying from 11 to221 meters above sea level.200

CHAPTER 6 - EUROPEFigure 8 - Land use in the Ile de France region. Red: urban areas; green: forested areas; yellow: agricultural areas.The administrative borders of different departments are also indicated.[http://www.iau-idf.fr/fileadmin/user_upload/SIG/cartes_telecharge/thema/Densipop_1999.pdf]6.3.2 Pollutant emissionsPollutant emissions from the Ile de France region represent approximately 10 % of thenational French emissions for NO X , SO 2 and CO 2 , and approximately 5% for CO, NMVOC, andPM 10 [AIRPARIF, http://www.airparif.asso.fr/pages/emissions/emisidf]. For NO X and CO, traffic isthe dominant source (Figure 9). For NMVOC and PM 10 , both traffic and industry are dominantsources followed by the residential / tertiary sector. For SO 2 , industry is the dominant source.Over the Ile de France area, emissions are mainly intense over the city of Paris (red colourin Figure 10), the agglomeration, over a larger urbanised area of about 40 km diameter, and alongmajor highways. This is shown in Figure 10 for the example of NO X emissions.201

CHAPTER 6 - EUROPEFigure 9 - Partitioning of major pollutant emissions in the Ile de France region among major activities, for the year 2005 (inpercent); from left to right: nitrogen oxides, non-methane volatile organic compounds, particulate matter PM10, fineparticulate matter PM2.5, sulphur dioxide, climate active gases (CO2, CH4, N2O in CO2 equivalents, from top to bottom:nature (dark green), agriculture (light green), waste treatment (dark magenta), energy production (light magenta), industry(medium magenta), residential and tertiary (yellow), rail and ship traffic (light blue),airports (medium blue), road traffic (dark blue)Source: [AIRPARIF http://www.airparif.asso.fr/pages/emissions/emisidf]Figure 10 - Density of annual NOX emissions over the Ile de France area, in [tonnes/km 2 /yr], for year 2005;Source: [AIRPARIF http://www.airparif.asso.fr/pages/emissions/emisidf]6.3.3 MeteorologyMost of the time Paris benefits from relatively sustained winds from south-west to west,advecting relatively clean oceanic air masses to the region, and allowing for good dispersion of localpollution sources. Under anticyclonic conditions, sunny weather and weaker northerly to easterlywinds allow for local pollution build-up, its photochemical processing, and for advection ofcontinental air masses to the area (see example in Figure 11).202

CHAPTER 6 - EUROPEFigure 11 - Wind direction at the SIRTA/IPSL site at Ecole Polytechnique, 20 km southwest of downtown Paris. Red bars:July 2005 – 2009, black bars: particular situation during the MEGAPOLI campaign in July 2009[Courtesy of M. Haeffelin, SIRTA / IPSL]6.3.4 General air pollution situationIn the Ile de France region, the Air Quality survey network AirParif(http://www.airparif.asso.fr/) has a dense routine measurement network with nearly 50 automatedsites located within the Paris agglomeration and neighbouring rural areas, giving hourlyconcentrations of target pollutants. Nearly 15 years of gathered data allow for a climatologicalanalysis of the evolution of urban and peri-urban pollution.Figure 12 illustrates that yearly averages of primary pollutants such as benzene and NO, orSO 2 (of dominant industrial origin) show a negative trend at urban background sites over the last tenyears. Ozone shows an upward trend, probably due to decreasing titration with fresh NO emissions.NO 2 and PM 10 do not show a significant trend. Both are due to primary emissions and secondarychemical transformation.Figure 12 - Trends of major atmospheric pollutants: SO2, (top left), of major industrial origin, NOX (top right), of major trafficorigin for urban background sites from the AirParif network; ozone monthly averages for year 2005(bottom, left) for anurban background site (dark purple) and an rural site (light purple), PM10 annual distribution for year 2009 showing largervalues in Paris downtown (inner circle)[AIRPARIF http://www.airparif.asso.fr/pages/polluants/evolution]203

CHAPTER 6 - EUROPEFrom a regulatory point of view, enhanced urban NO 2 levels present the biggest problem.During the last few years, the annual average limit value of 40 µg/m 3 as of 2010 was violated over alarge part of the Paris agglomeration. For ozone, the national air quality standard for protection ofhuman health in 2010 limits exceedances of the daily maximum 8 h average of 120 µg/m 3 at 25times per year, averaged over three years. According to measurements in recent years, the newozone standard is achievable, except for a year with exceptionally hot and anticyclonic conditionslike during the summer of 2003. The information threshold of 180 µg/m 3 (hourly mean) for ozone isexceeded several times a year. For PM 10 , the objective of an annual average below 30 µg/m 3 isviolated in the central region of the agglomeration during some years (e.g. 2003 and 2007).6.3.5 Specific scientific campaignsIn addition to the operational air quality monitoring, a large number of field campaigns andscientific studies have been performed in the last ten years to study the processes of air pollutionbuild-up in the Paris agglomeration. A comprehensive gas phase chemistry experiment wasperformed as part of the ESQUIF campaign during the summers 1998 and 1999. Particulate matterformation in the region has been recently addressed during the very comprehensive MEGAPOLIexperiment campaigns in July 2009 and January-February 2010.A) Photo-oxidant pollution ESQUIF campaign and later studiesThe ESQUIF campaign (IPSL and LISA, Research Centre Jülich, Météo-France, AirParif,Laboratoire d’Aérologie) has allowed a detailed documentation of major gaseous pollutants (O 3 ,NO X , NOy, VOC) and a first characterisation of particulate matter (chemical, size distribution) withinthe Paris agglomeration and its plume during 13 multiday IOP’s (Intensive Observation Periods)between 1998 and 2000 [Menut et al., 2000; Vautard et al., 2003a]. An integrated observationnetwork including ground based in-situ and remote sensing instruments as well as airbornemeasurements were set up. Major outcomes from this campaign are presented in the followingparagraphs.Emission uncertaintyAirborne NOy, CO, and VOC measurements from the ESQUIF campaign were used incombination with the air quality photochemical model CHIMERE in order to diagnose uncertaintiesin the current emission inventory from AirParif for the year 2000 [Vautard et al., 2003b]. There isreasonable consistency between simulated and measured concentrations. NO y simulations agreewith measured concentrations to within 35%. There are significant underestimations andoverestimations in some individual primary hydrocarbons. However, the total mass and reactivity ofthe measured hydrocarbon mixture, which accounts for only about half of the total emitted mass,agree with modelled values to within an estimated uncertainty of 40%. These values give directconstraints for the emission uncertainty, given that uncertainty in model parameters (for exampleboundary layer height) is lower than that of the uncertainty for emissions.This work was later extended by inverse modelling work assessing the uncertainty inregional emission inventories [Pison et al., 2006; Deguillaume et al., 2007]. The latter authorsapplied a Bayesian Monte Carlo analysis using urban and surrounding air quality observations tocorrect average Paris agglomeration with respect to the initial inventory and to derive theiruncertainty: for VOC emissions the result was 0 ± 20 % (1 sigma), and for VOC emissions +16 ± 30%.Ozone plume characteristicsAverage photochemical ozone build-up in the Paris agglomeration plume during summers1998 and 1999 was about 15 ppb [Deguillaume et al., 2008]. During the ESQUIF IOP days, thisvalue was often several tenths of ppb (Figure 13). During summers 1998 and 1999, plumes weremost often encountered in the north-eastern sector, consistent with the climatology of the region ofpredominantly south-westerly winds. However, the plumes with the highest pollution levels wereencountered in the south-western sector, corresponding to anticyclonic situations with stagnantnorth-easterly winds.204

CHAPTER 6 - EUROPEFigure 13 - Number of ozone plumes during summers 1998 and 1999. An ozone plume is defined for days with aphotochemical OX (=O3+NO2) production of more than 10 ppb [Derognat, 2002]Major factors of photooxidant pollution and chemical regimesFrom an observational based approach, using ozone, NOy, and VOC measurements in theplume in conjunction with simulations, Sillman et al. [2003] derived either a VOC or NO X sensitivechemical regime ozone build-up depending on the meteorological conditions for particular days.Using Monte Carlo analysis with an observational constraint, Beekmann and Derognat [2003]showed that using the ESQUIF data set could reduce the uncertainty by a factor of 1.5 to 3 fordifferent days. Extending this type of analysis to summers 1998 and 1999, Deguillaume et al. [2008]showed that the photochemical ozone build-up in the plume was in general VOC sensitive, and thatthe result of an average VOC sensitive regime was robust with respect to model uncertainty.Derognat et al. [2003] showed that biogenic VOC emissions (mainly isoprene) significantlycontribute to photochemical ozone build-up in the region, 9 ppb on the median for ESQUIF IOPdays (a selection of more polluted days), and up to 40 ppb for an exceptionally hot and polluted day.Using the CHIMERE adjoint for sensitivity analysis, Menut et al. [2003] tested the sensitivity ofozone build-up due to a large variety of parameters and found them mainly driven by traffic andsolvent surface emissions and meteorological parameters such as temperature. On average, onlyabout a quarter of the ozone present in the Paris agglomeration plume is formed from localemissions, with the majority of the ozone advected from outside. During high pollution episodes (O 3> 90 ppb), the local fraction is more than 40% [Derognat, 2003]. In extension of results of theESQUIF campaign, the LISAIR campaign (LSCE /IPSL, AirParif) has gathered a large amount ofurban VOC measurements (C2 – C12) during May 2005 in conjunction with aerosol lidarmeasurements (boundary layer height evolution) in order to address the spatial and diurnal VOCvariability for different urban sites [Gros et al., 2007].205

CHAPTER 6 - EUROPEB) Particulate matter pollutionBesides from air quality network measurements, climatological information about aerosolloads over the Paris region is available from optical measurements. Aerosol optical density (AOD) ismeasured by a sunphotometer part of the AERONET network 20 km SW of Paris town centre.During clear sky days, AOD is mostly comprised between 0.1 and 0.4, with a median value of 0.17[Chazette et al., 2005]. The average single scattering ratio (at 532 nm) of 0.9 is typical for urbanaerosol [Raut and Chazette, 2007]. From comparisons of aerosol backscatter lidar measurementsat the same site and model simulations, it has been inferred that secondary organic aerosol wasprobably underestimated in the CHIMERE model simulations [Hodzic et al., 2004].Regional / continental origin of aerosols in the Paris regionHourly concentrations of inorganic salts (ions) and carbonaceous material in fine aerosols(aerodynamic diameter, A.D. < 2.5µm) have been determined from fast measurements performedfor a 3-week period during the spring of 2007 at an urban site within the city of Paris [Sciare et al.,2010, submitted]. The sum of these two chemical components (ions and carbonaceous aerosols)has shown to account for most of the fine aerosol mass (PM 2.5 ) in this area. This time-resolveddataset allowed investigation of the factors controlling the levels of PM 2.5 and showed that pollutedperiods with PM 2.5 >40µg/m 3 (during periods I and III in Figure 14) were characterized by air massesof continental (European) origin and a chemical composition made up of 75% of ions. By contrast,clean marine air masses show the lowest PM 2.5 concentrations (typically of about 10µg/m 3 , period IIin Figure 14) with carbonaceous aerosols contributing most of the mass (typically 75%). The ratherstable levels of carbonaceous aerosols observed during this study suggest that the region of Parisis a major contributor to this fraction.Figure 14 - Time resolved PM measurements in downtown Paris in May/June 2007. The periods I and III correspond to apredominance of inorganic ions of mainly continental origin in Paris downtown PM2.5, the period II corresponds to apredominance of carbonaceous aerosol of mainly local origin[Sciare et al., 2010]By contrast, long-range transport from Europe is proposed as the main contributor for ionsmeasured in Paris during the springtime. Further studies need to address if these results are validon a longer climatological time scale.206

CHAPTER 6 - EUROPEC) The MEGAPOLI campaignThe campaign, performed in the framework of the EC FP7 project MEGAPOLI, aimed at abetter quantification of primary and secondary organic aerosol sources and their relation to gaseousprecursors, at the example of a big European Megacity, the Paris region. Indeed, these aerosolfractions make up an important contribution to urban fine particle matter and their sources areamong the most uncertain. The campaign design included three primary and four secondary fixedground measurement sites, an aircraft, and five mobile platforms (Figure 15). Fixed sites weredistributed over urban and peri-urban areas. Mobile platforms allowed sampling the pollution plumeand background conditions. For many sites, complete instrumentation was set-up comprisingaerosol chemistry and physical properties as well as components of gas phase chemistry. Thesummer part of the campaign took place in July 2009 while the winter part took place from January15 to February 15, 2010. More than 25 laboratories participated (funded by EC, from Frenchnational funding, or from own means).Figure 15 - MEGAPOLI campaign set-up3 primary sites => full in situ measurements (LHVP, SIRTA, Livry_Gargan / + meteo at SIRTA3 secondary sites => lidar and spectrospcopic measurements / or in some situ3 mobile labs => in situ measurements, aerosol characterisation1 mobile lab => lidar measurements1 mobile lab => MAXDOAS1 aircraft ATR-42 => full in situ measurements (SAFIRE, CNRS, MPI)Additional lidar network in winter (red stars)The campaign was clearly a success, with measurement coverage above 90%. At themoment, measurements are being analyzed and quality checked by partners. Measurementquick-looks have already been submitted to the campaign database at LISA(http://megapoli.lisa.univ-paris12.fr/). First interesting results include:• From airborne primary pollutant measurements, the pollution plume was still well defined atmore than one hundred kilometres downwind from the agglomeration.• Very preliminary attribution of organic aerosol (OA) from AMS mass spectrometer urban andperi-urban measurements during the summer campaign shows a large fraction of oxidisedorganic aerosol (OOA) of secondary origin and a smaller fraction of unoxidised organicaerosol (HOA) of primary origin. At the urban site, about half of OA is water soluble,corresponding probably to classical secondary organic aerosol, another half is waterinsoluble, corresponding probably to primary and chemically processed primary OA.• Significant new particle formation events were observed in the area during the whole monthof the summer campaign. These events were assisted by the relatively low particulatematter concentration levels and resulting low surface area during most of July 2009.207

CHAPTER 6 - EUROPE• During the winter campaign, wood burning was a significant source of organic aerosol. Bothlocal emissions and continental advection were responsible for aerosol pollution build-up.6.3.6 Conclusion and outlookIn conclusion the Paris agglomeration is a major population hotspot with high pollutantemissions from traffic, the residential/tertiary sector, and industry. Good dispersive conditions limitthe impact on air quality of these emissions. With respect to valid air quality regulation (or valid innear future), NO 2 (annual mean) is the most critical pollutant, followed by fine particles and ozone.Several intense studies have allowed to draw a rather coherent picture of photo-oxidantpollution in the agglomeration and its plume, as well as a quantification of precursor emissions (NO X ,CO and VOC) and their respective impact on photo-oxidant levels. For particulate matter, theobservations, simulations, and source apportionment of carbonaceous aerosol is still uncertain tohighly uncertain. The recent MEGAPOLI campaign intends to close this knowledge gap. Detaileddata sets on aerosols and their radiative and hygroscopic properties from this campaign should alsohelp to better quantify the aerosol impact on regional climate in the region.6.4 MOSCOW6.4.1 Population, demographics, geography, and urban structureMoscow is the capital and the largest city of Russia. It is also the largest metropolitan area inEurope, and is the seventh largest megacity in the world. According to the 2002 census the Moscowpopulation was estimated at 10,382,754. However, this figure only takes into account legalresidents. Substantial numbers of internal migrants mean that Moscow's population is stillincreasing, whereas the population of many other Russian cities is in decline. The cityencompasses an area of 1035 km 2 . The Moscow River flows through the centre of the city and theKremlin lies in the direct centre. In Figure 16 the blue-gray pixels in this false-colour image areurban areas of Moscow. The light green areas surrounding the city are farms and the brown regionsare more sparsely vegetated areas. This image of Moscow was acquired by the EnhancedThematic Mapper plus (ETM+), flying aboard the Landsat 7 satellite on July 23, 2002. Averageelevation of the city is 156 m. The highest point is Teplostanskaya highland at 255 m. The lowestpoint, 110 m, is the Moscow river bank in the South-eastern part of the city. Green areas make up30% of the territory, which is a fairly high value for a megacity.Figure 16 - Left: Satellite image of Moscow acquired by the Enhanced Thematic Mapper plus (ETM+), flying aboard theLandsat 7 satellite. July 23, 2002 (NASA, http://visibleearth.nasa.gov/view_rec.php?id=3434)Right: Map of the Mosecomonitoring air pollution monitoring stations in Moscow and suburbs208

CHAPTER 6 - EUROPEMoscow has a humid continental climate with warm, somewhat humid summers and long,cold winters. Typical high temperatures in the warm months of June-August are around 23 °C, butduring heat waves daytime temperature highs often top 30 °C. In the winter, temperatures normallydrop to approximately −10 °C, though there can be periods of warmth with temperatures risingabove 0 °C. Snow cover is formed at the end of November and melts in mid-March, but in recentyears snow cover has melted earlier than usual. For example, in the winter of 2006-2007 there wasalmost no snow cover up to February and during the winter of 2007-2008 the snow cover melted atthe end of February. The winter of 2009-2010 was very unusual for the last decade – a ‘real’Russian winter with lots of snow, minus temperatures, and winter sunshine. Monthly rainfall totalsvary minimally throughout the year (575 mm a year), although the precipitation levels tend to behigher during summer vs. winter. On average Moscow has 1731 hours of sunshine per year.Urban features influence meteorological conditions and microclimate of the megacity. Theestimated anthropogenic heat flux for Moscow gives 55.9 W/m 2 and surface air temperature in thecity is on 2-5 degrees higher than outside Moscow.Overall data show a complex environmental situation in Moscow. The average populationdensity is 8,900 people/km 2 , and the city is growing rapidly, with extensive emissions: 46 kg ofpollutants per year are emitted per capita in Moscow [Report of the Moscow Environment, 2002].While hundreds of thousands of sources emit pollutants into the air, only 60% of the enterpriseshave implemented pollution control measures. Cars provide a significant amount of the pollutionand the majority of them do not meet typically European air pollution standards. In addition toextensive atmospheric gaseous and particulate pollutants, motor vehicles also contribute to highlytoxic heavy metals: vehicular exhaust is the largest contributor of lead, while zinc comes from tirewear and diesel engines release cadmium into the environment. Industrial enterprises producelarge amounts of dust, nitrogen oxides, iron, calcium, magnesium, and silicon. These compoundscontribute to the haze over the city, increasing fog and precipitation and reducing solar radiationthat reaches the surface.The Moscow environment is closely associated with the background pollution, the regionalnatural conditions, and the climate of Eastern Europe. The dominance of westerlies is of keyimportance for air pollution: the western and northwestern districts of the city tend to receive morefresh air, due to the forests west of the Moscow region. Polluted air from the western parts of thecity is transported to the eastern parts. During periods of easterly and southeasterly winds Moscowgets less fresh air, since the south-east area is only 25-30% forested, the land is largely plowed foragriculture, and more industries are located in this area.6.4.2 Overview of emissions estimatesAccording to the Report of the Moscow Environment [2002; 2009] the main emissionsources in Moscow are the following: 31,000 industrial and construction sites (including 2,500vehicles companies), 14 central thermo-electrical factories and branches, 71 district thermalstations, 110 small heating plants, as well as about 3.5 million vehicles.Every year about one million tons of pollutants are emitted from Moscow into theatmosphere (Figure 17). The main source of pollution is motor vehicles (from 83% to 92% of thetotal emission based on different estimates) followed by emissions from industrial stationarysources (up to 8%), and thermal power generation facilities (up to 4%). Thus, vehicular exhausthas a decisive role in shaping the level of air pollution in the surface layer of the urban Moscowatmosphere. Average vehicle emissions for the Moscow transport sector are shown in Figure 18.Specific urban pollution episodes can also be caused by emissions from outside the city: e.g. fromforest fires, industrial emissions, dust from soil, etc.209

CHAPTER 6 - EUROPEFigure 17 - Total emissions from different sources in Moscow during 1990 – 2008[Report, 2002; 2009; Kasimov et al., 2004]Figure 18 - Average vehicle fleet emissions for the Moscow transport sector in g/km and % of the total emissions[Atlas, 2000]6.4.3 Overview of pollution levelsUrban and in the surrounding suburb regionsAir pollution in Moscow is very inhomogeneous (Figure 19). Hotspots are the roads and theirsurrounding areas. In residential areas, the pollutant concentrations are about 15-30% less than inthe centre of Moscow and 30-50% less than in the vicinity of highways (Table 2). There is also somevariability over time, though the overall integrated level of pollution is relatively stable, as can beseen in the integrated air pollution index (API), which calculated based on the concentrations of 5major pollutants (CO, NO 2 , NO, O 3 , and formaldehyde) relative to the national guidelineconcentrations for each pollutant, and a scaling factor which indicates the relative toxicity of eachpollutant, so that a dimensionless comparable quantity indicating the overall pollution level isdetermined. The API was 6.2 in 2008, 6.3 in 2007, 6.4 in 2006, 6.1 in 2005, and 6.2 in 2004.210

CHAPTER 6 - EUROPEFigure 19 - Moscow NO2 air pollution in threshold limit values, TLV (0.04 mg/m 3 ): Left: from Moscow transport, (> 2.0 - deepblue, 1.0-2.0 - blue, 0.5-1.0 – light blue); Right: from industrial and energy production sources (> 2.5 - deep red, < 0.5 - blue)[Atlas, 2000]Table 2 - Annual average concentrations of the main pollutants (mg/m 3 ) in years 2006 – 2008 for different areas of theMoscow megacity and national threshold limit values (TLV) [based on Report, 2009]Average for city Close to highways City centre Residence areasTLV * 2006 2007 2008 2006 2007 2008 2006 2007 2008 2006 2007 2008CO 3.0 0.8 0.7 0.57 1 1 0.71 0.9 0.8 0.59 0.7 0.6 0.51NO2 0.04 0.046 0.042 0.036 0.05 0.051 0.044 0.05 0.044 0.035 0.043 0.039 0.031NO 0.06 0.048 0.046 0.038 0.067 0.057 0.053 0.055 0.054 0.035 0.039 0.041 0.026SO2 0.05 0.006 0.006 0.003 0.007 0.007 0.004 0.006 0.006 0.004 0.006 0.007 0.002PM10 (0.15) 0.033 0.035 0.037 0.045 0.048 0.046 0.035 0.035 0.039 0.031 0.032 0.038O3 0.03 0.028 0.032 0.032 0.031 0.039 0.037 0.025 0.031 0.03 0.026 0.028 0.032API ** - 6.4 6.3 6.2 7.3 7.1 7 6.3 6.5 6.3 6.1 6.1 6* national threshold limit values for daily average concentrations (TLV)** integrated air pollution index (API) calculated on 5 major pollutants: CO, NO2, NO, O3, and formaldehydeHigh levels of air pollution are observed near large highways and industrial zones, especiallyin eastern and south-eastern parts of the city. The highest air pollution levels are observed in areasof Kapotnya, Lyublino, and Maryino due to the location of an oil refinery. The minimum level ofpollution is observed in the city districts of Krylatsky and Silver Bor.The annual O 3 concentration in 2008 of 0.032 mg/m 3 exceeded the national threshold limitvalues (TLV, see Table 2). In the city, average O 3 concentrations varied from 0.023-0.027 mg/m 3(0.8-0.9 TLV) in the central part of the city, while close to highways the O 3 concentration is up to0.036-0.038 mg/m 3 (1.2-1.3 TLV). The highest O 3 concentrations are observed in May (1.5 TLV),June, and July (1.3-1.4 TLV). The lowest O 3 concentrations are observed during winter (0.5-0.6TLV). Daily mean concentrations were above the TLV 30 to 70% of the time.Contamination of the surface air layer, to a large extent, depends on meteorologicalconditions. On average, the air pollution potential is low directly in the Moscow region, due to agood dispersion potential. This leads in turn to a large regional pollution potential, which affects the211

CHAPTER 6 - EUROPEair quality in the surrounding areas; Moscow is computed to be the most effective megacityworldwide in exporting pollutants to the boundary layer of regions more than 1000 km downwind[Lawrence et al., 2007]. In certain periods, when meteorological conditions trigger accumulation ofharmful substances in the surface layer, the pollution concentrations may be drastically increased,leading to high pollution episodes. Both summer and winter episodes with high concentrationsoccur frequently in Moscow. One of highest summer pollution episodes in Moscow occurred inSeptember 2002 and was caused by peat fires in the Moscow region [Chubarova et al., 2009].The highest winter pollution episode occurred during February 2006 [Report of the MoscowEnvironment, 2007] when from 3 to 9 February 2006 a combination of weak winds and a cappinginversion layer increased pollutant concentration levels to the highest yet seen. Elevated levels ofair pollution led to the continuous growth of allergic and asthmatic diseases for children and highmortality among elderly population during the summer smog events.Historical trends, connection to political regulations, future prognosisMosEkoMonitoring has established a multiyear database of pollutant concentrations inMoscow that gives the possibility to analyze trends, develop forecasts, and to inform the decisionmaking process. Analysis of air quality monitoring data shows (Figure 20) that in recent years airquality has generally remained at an approximately constant mean level. During the last 10 yearsthe level of air pollution was highest during 2002 (an anomalous year with long-term adverseweather conditions when Moscow was polluted from forest and wood smoke-peat fires in thesurrounding areas). There are modest negative trends in the air concentrations of SO 2 and NO X ,while the CO concentrations have been decreasing continuously and significantly since 2002.Figure 20 - Temporal annual mean concentrations of the main pollutants in Moscow during the years 2002-2008; inthreshold limit values (TLV) for CO, NO2, SO2, O3 and in mg/m 3 for PM10 [Report, 2009]The concentration of total hydrocarbons has remained approximately unchanged since 2004at 1.6-1.7 mg/m 3 for residential areas outside the direct impact of road transport and industrialenterprises and 1.7-1.9 mg/m 3 for areas exposed to vehicle emissions. SO 2 , as an indicator of theuse of reserve fuel types by thermal power plants, in recent years has remained stably low in allareas of the city (average concentrations amounted 0,006 - 0,007 mg/m 3 ). Average concentrationsof PM 10 remained almost unchanged, except for a notable interannual variability. Since 2004 PM 10212

CHAPTER 6 - EUROPEconcentrations have remained stable at 0.037-0.036 mg/m 3 in areas away from highways, wherethe major sources of pollution are due to long-range atmospheric transport and soil dust fromneighbourhoods. Close to major highways a slight (within 6%) but steady annual increase in themaximum observed annual average concentrations of PM 10 (0.045 mg/m 3 in 2004, 0.046 mg/m 3 in2005, and 0.049 mg/m 3 in 2006) is observed. Since 2006 a trend of slow but steady decrease inNO 2 pollution has been observed, but the average concentration is still very high (1.1 national TLVfor the central part and 0.8 TLV – for peripheral residential areas). The average concentration ofground-level O 3 , which is linked strongly to meteorological conditions, varies substantially over theyears, from a minimum of 0.6 mg/m 3 (2004) up to a maximum of 1.5 mg/m 3 (2002).The CO 2 concentration in Moscow is measured at 3 stations situated within residentialareas as well as on the TV tower Ostankino. The mean annual CO 2 mixing ratio in the surface airvaries from 423 to 451 ppm and does not exceed the EC norms. Vertical profiles CO 2 measured atthe TV tower give the following average values: at 130 m – 390 ppm; at 250 m – 400 ppm; and at350 m – 370 ppm. The main cause of maximum at 250 m could be hot air (with CO 2 ) emissionsfrom smokestacks of the city’s power plants.6.4.4 Field campaigns in MoscowThe Moscow air quality monitoring system started in 1996 by the decision of theGovernment of Moscow. Over the years the system is continually evolving and improving. At thepresent time it includes a network of 28 automatic stations and 2 mobile laboratories that measure18 priority pollutants. Near real time monitoring data is transferred to a joint information-analyticalcentre of «Mosekomonitoring».In March of 1998, the Moscow government, the Fund Programme Management Branch ofUNEP, the UN Centre for Human Settlements (Habitat), and the Centre for International Projects(CIP) signed an agreement to carry out the Moscow sustainable cities project in the framework ofthe world Sustainable Cities Programme (SCP). The Moscow sustainable cities project was aimedat conducting municipal, national, and international activities in the framework of the SCP andpreparing and publishing the local options of the Habitat agenda for Moscow [Ginzburg, 2000].The Moscow government initiated in 2000 a WMO GURME Pilot Project on “MeteorologicalServicing for Sustainable Development of the Moscow Megalopolis” [Vasiliev and Liakhov, 2000].The project focused on atmospheric pollution and urban meteorology and in particular the urbanheat island (UHI) effect measured by microwave remote sensing data [Kuznetsova et al., 2004].Continuous temperature observations in the PBL provided unique data to investigate spatial andtemporal features of temperature fields over the Moscow megalopolis. The results showed that overthe Moscow megalopolis, meteorological conditions are more favourable for self-cleaning of air thenin suburban areas. Temperature inversions block vertical exchange of air in the Moscowmegalopolis less often then in suburban areas and they are less powerful. There are twoseasonally-varying types of UHI over the megalopolis: (i) the high dome (up to 600 m) and (ii) lowdome (up to 200-300 m).One of the most interesting field campaigns was on the long-term transport of megacityplumes and observations of the atmospheric composition over Russia. This field campaign beganin 1995 and is called “TROICA” (TRans-Siberian Observations Into the Chemistry of theAtmosphere). Long-range transport is monitored using the TROICA mobile observatory, which isimplemented in a wagon in the trans-siberian railway train [Elansky, 2006]. Scientists from acrossthe world joined forces in a number of TROICA measurement field campaigns to gather thenecessary information for better understanding the chemistry of the atmosphere [Crutzen et al.,1998]. The TROICA campaigns have been carried out over different regions of Russia, includingsampling urban atmospheric pollution in Moscow and in other large Russian cities. In addition toprimary pollutants, greenhouse gases, and volatile organic compounds, the chemical compositionand characteristics of different aerosols in size bins ranging from 0.4 to 1000 nm were alsomeasured. The results will help understand the scale of possible urban pollution effects fromRussian megacities like Moscow, Novosibirsk, and Omsk. Several further research organizationsare also doing field research and studies of Moscow air pollution, including IFA RAS, Geographical213

CHAPTER 6 - EUROPEfaculty of MSU, IGCE RAS, AeroCosmos, HydroMetCenter, etc. More information on these andother programmes is given at the end of the next section.As examples of the other kinds of international cooperation air pollution projects, twobilateral Russian-British projects during the last decade were:1. Project “Creation and distribution of collected volumes for air contamination in Moscow”[Moscow city government, British Council and DEFRA, 2004; 2005]. The project indentifies targetgroups among organizations and the public interested in environmental information and creatingmechanisms of gathering, analysis, presenting, and disseminating environmental informationtargeted to these groups using UK experience.2. Project “Air quality management in Moscow and London” (2006-2007)The aims of this project were to compare air quality in both cities, share knowledge ofmodelling air pollution using the ADMS-Urban dispersion model, share experience in relation topolicies to reduce pollution, and establish a long-term biological monitoring network using lichen. Areview of the pollutants measured, physicochemical equipment used, and characteristics of thesites monitored has been carried out for each city and the results have been compared. Theinformation is related to objectives defined by the EU Air Quality Directive for the protection ofhuman health and sensitive vegetation and ecosystems and the Russian health objectives. Airquality policies in each city have been reviewed with particular interest in schemes such as trafficmanagement and alternative transport modes. This part of the project is led by Prof. Frank Kelly ofKing's College London, UK.6.4.5 Current and planned major activities focusing on the city's air pollutionIn Moscow, which was a very polluted city a few decades ago, there has been somereduction in urban pollution due, in many cases, to the economical crisis and industry degradation in1990s after the USSR collapse. However, nowadays Moscow pays much more attention to airquality management programmes and emissions reduction strategies, so that the air quality isapproaching the standards of West European cities.The current Master Plan for the City of Moscow up to 2025 (approved by the Government ofMoscow in 2005) defines the main priorities of urban development trends and practices to ensureenvironmental safety as well as a combination of economic, environmental, and urban developmentpriorities. The main measures in air pollution mitigations include: (i) reducing the negative impactsof road transport system by tightening the requirements for environmental performance of transport(the transition to Euro-IV and Euro-V); (ii) reduction of total stationary source emissions by 25% dueto the use of advanced environmental technologies and abatement equipment.An important factor in improving the ecosystems of the city is the preservation anddevelopment of gardens, parks, and trees in yards, which have suffered in recent years due to afocus on building. The forest-park protective belt surrounding Moscow has decreased by 7% since1997 due to the expansion of Moscow and the remaining suburban forests are rapidly losing theirecological protective functions [Report, 2002]. According to the ecological requirements theforest-park belt area around a megacity shall exceed the city area by not less than 5 times, and inMoscow it is just 1.5 times (in comparison with about 10 times for London, Paris, and Washington).Several research organizations are doing research and studies of Moscow air pollution,including:1. Institute of Atmospheric Physics of the Russian Academy of Sciences (IFA RAS),http://www.ifaran.ru.2. Moscow State University (MSU), especially the Faculty of Geography, Department ofMeteorology and Climatology, http://www.geogr.msu.ru/cafedra/meteo/.3. Scientific Center of Aerospace Monitoring «Aerokosmos», http://www.aerocosmos.info.4. Institute of Global Climate and Ecology, http://www.igce.ru/.5. Mosekomonitoring, http://www.mosecom.ru/, which is responsible for organization and214

CHAPTER 6 - EUROPEimplementation of the state environmental monitoring system for the city of Moscow.6. Institute of Applied Geophysics of Roshydromet, SPA "Typhoon", and Institute ofExperimental Meteorology (Obninsk, Kaluga reg.), http://www.typhoon.obninsk.ru/.7. State Institution «Moscow Center for Hydrometeorology and Environmental Monitoring withregional functions» (PG Moscow ITF-R), as specifically authorized by the territorial authorityRoshydromet, monitor pollution in the territory of Moscow and Moscow region.8. Department of natural resources and environmental protection in Moscow (MoscowGovernment), http://www.moseco.ru/moscow-ecology/monitoring/air/. It monitors gascomponent of pollution (mainly CO, NO, NO 2 , O 3 , CH 4 , CH) using the gas and aerosol (PM 10 )in the network of automatic inspection of quality of atmospheric air (approximately 30positions) and the Ostankino TV tower.9. Research and design and survey institute of ecology city (Department of AtmosphericEnvironment), http://www.ecocity.ru/catalog/eco_mod/s_lowzagr.According to a joint agreement between the EC DG Research and the Russian Ministry ofHigh Education and Science, a new research call for a collaborative project with the EC FP7 projectMEGAPOLI was opened in the year 2008 by the Russian Agency of Science and Innovations. Thispartnership project, complementary to MEGAPOLI and within the scope of the Federal FrameworkProgramme of the Federal Science and Innovations Agency / Ministry of Education and Science ofthe Russian Federation, is focusing on development of integrated technologies of aerospace andground-based monitoring of the urban-conglomerate and megacity (first of all Moscow)environments. The “AEROCOSMOS” Scientific Centre for Aerospace Monitoring, Moscow iscoordinating the project with a Russian research consortium including MSU, IFA RAS andRoshydromet centre.6.5 BENELUX/RHINE-RUHR6.5.1 Population, demographics, geography, urban structure of major population centresThe Benelux/Rhine-Ruhr area is a strongly industrialized region located in Central Europewith high population density and about 40 million inhabitants. The BeNeLux area consists ofBelgium (10.7 million inhabitants, area: 30.528 km 2 ), the Netherlands (16.5 million inhabitants, area:41.526 km 2 ) and Luxembourg (0.5 Million inhabitants, area: 2.586 km 2 ). Overall within Benelux 27.7million inhabitants are living on an area of 74.640 km 2 . Additionally, the Rhine-Ruhr area (12 millioninhabitants, area: about 7.000 km 2 ) within the German state of North-Rhine-Westphalia (NRW) ispart of this emission hot spot. High emissions due to traffic and industrial activities makeBenelux/Rhine-Ruhr a hot spot area with respect to air pollution in Europe.Three major European metropolitan areas are located within Benelux/Rhine-Ruhr. Thelargest one is the urban agglomeration of Rhine-Ruhr itself with 12 million inhabitants living in anarea of about 7.000 km 2 , which has a megacity character with respect to population density, traffic,industry, and environmental issues. The main centre of European steel production and the biggestinland port in the world is located in Duisburg, one of the major cities in the Rhine-Ruhr area (majorcities are: Cologne, Düsseldorf, Duisburg, Essen, Dortmund, Bochum). The Randstad is aconurbation in the Netherlands consisting of the four largest Dutch cities (Amsterdam, Rotterdam,The Hague, and Utrecht) with 6.7 million inhabitants in total, about 40% of the Netherlands, withRotterdam as one of the most important sea harbours of the world. Within Belgium theBrussels-Antwerp region with 4 million inhabitants (about 40% of Belgium) again forms aconurbation with metropolitan character and an important sea harbour (Antwerp).Ship traffic along the coast and toward the harbours, including ships going along the riverRhine, is an important source of air pollution to this area (see Dalørsen et al., 2009 for a generalglobal picture of ship emissions). Population density weighted fine particle concentrations (PM 2.5 ) ingeneral are the highest in Europe, in particular the contribution of ships has been found to be high inthe Benelux/Rhine-Ruhr area according to recent modelling studies [Andersson et al., 2009]. CO,SO 2 and benzene are no longer a big issue in air quality within the Benelux/Rhine-Ruhr area due tothe strong efforts for improvement of air quality in Europe during the last decades [Vestreng et al.,215

CHAPTER 6 - EUROPE2007; Andersson et al., 2007]. Harmonized regulations within the European Community are aimingat further improvement of air quality in Europe (e.g. air quality directive 2008/50/EC and theemission ceiling directives). Major problems within urban agglomerations remain with respect toozone, which can still exceed 300 µg/m 3 during summer conditions (e.g. in 2003 and 2006), to PM 10 ,which still exceeds the 24h average limit value of 50 µg/m 3 more than 35 times in a calendar year,and to NO 2 which still has a tendency to increase and exceeds the annual limit value of 40 µg/m 3considerably, especially in street canyons.Nearby metropolitan areas are London, Paris, and Frankfurt. Due to atmospheric transportprocesses, the air quality in the Benelux/Rhine-Ruhr area might be influenced from the transport ofpollutants from Paris, London, and/or Frankfurt depending on atmospheric conditions. In particular,compounds formed during transport or with a long lifetime might contribute from outside to the airquality within Benelux/Rhine-Ruhr. On the other hand compounds emitted withinBenelux/Rhine-Ruhr might contribute considerably to air pollution outside this hot spot due tolong-lived primary constituents as well as secondary formed air pollutants such as aerosols orozone. Therefore it is interesting to investigate the import/export budgets for air pollutants underdifferent meteorological conditions relevant for the area considered.Meteorological features in Central Europe are characterized by predominant westerly flow,and, therefore, quite often, clean air is transported with moderate or high wind speeds from theAtlantic towards the Benelux/Rhine-Ruhr area. Meteorological patterns leading to air qualityproblems often are related to high pressure systems over Central Europe. Anticyclone conditions,due to low wind speeds, favour the accumulation of primary emitted gases or particulate matter, inparticular during winter or fall with limited vertical exchange (temperature inversions). Temperaturesmay reach 40 ◦ C during summer, as for example during the summer heat wave in August 2003 or inJuly 2006 summer smog conditions [Vautard et al., 2006]. Episodes with high particleconcentrations during winter or fall are quite often correlated with easterly winds over CentralEurope leading to transport of polluted air masses towards areas located west ofBenelux/Rhine-Ruhr. This can cause additional impact from Benelux/Rhine-Ruhr to France and/orthe UK. The quite high ship emissions in interaction with specific meteorological (or other)conditions in coastal areas (e.g. land-sea breeze, boundary layer height, deposition, sea spray)may lead to particular events with respect to air quality. Other large-scale factors, which mightinfluence the air quality in Central Europe, include transport of dust from the Sahara desert[Bruckmann et al., 2008] and from the Ukraine by resuspended soil from dried-out farmlands [Birmiliet al., 2008].6.5.2 Overview of emission estimatesThe Benelux/area is heavily burdened with air pollutants like ozone, NO 2, and PM 10 . Inaddition, large amounts of ammonia, an important gaseous precursor for secondary particlesformation, are emitted in areas of the Benelux/NRW regions that are characterized by agriculturaluse. Table 3a shows the emissions for the Benelux/NRW area for 2004 as a reference year.Emission density in the area is about twice as high as the German average, similar to the populationdensity. Table 3b shows the emission trends based on EMEP data from 1980 till 2020. Figure 21shows as an example the nitrogen oxide emissions for the region [Thiruchittampalam et al., 2008].The metropolitan areas Randstadt (Amsterdam, Rotterdam), Brussels-Antwerp and Rhine-Ruhr areclearly visible as well as the strongly burdened cities of London and Paris. The relations between1980 and 2004, upper part of Table 3b, show the considerable success of the efforts to decreaseemissions in the Benelux area (and Europe) during the last decades. In particular sulphur emissionshave been diminished considerably. Future emission abatement strategies are assumed to besuccessful with respect to NO X , SO X , CO, PM 10 and NMVOC but not for NH 3 , 95% of which is due toagricultural activities.216

CHAPTER 6 - EUROPEFigure 21 - NOX emissions in Central Europe, including the Benelux-Rhine-Ruhr area. Ship emissions are not included onthis scale, but they contribute considerably to emissions in the domain shown here [Thiruchittampalam et al., 2008]Table 3a - Area, population and annual emissions for the Benelux/NRW/Rhine-Ruhr area. Emission data for the Benelux andGermany are for the year 2004 and based on EMEP (www.emep.int), expert emissions as used in EMEP models (Vestreng,2006a; W-06emis04-V7 (2006-08-29), emission data for NRW are taken from the LANUV web site (www.lanuv.nrw.de)Year: 2004Area(km2)Population(Mill.)NOX(kt as NO2)SO2(kt as SO2)CO(kt)NMVOC(kt)Netherlands 41.526 16,50 360,00 66,00 623,00 216,00 134,00 41,00Belgium 30.528 10,70 298,00 154,00 972,00 167,00 74,00 62,00Luxembourg 2.586 0,50 29,00 4,00 48,00 10,00 7,00 4,00Benelux 74.640 27,70 687,00 224,00 1.643,00 393,00 215,00 107,00NH3(kt)PM10(kt)NRW 34.084 18,00 418,00 167,00 1.506,00 273,00 73,00 32,00Benelux/NRW 108.724 45,70 1.105,00 391,00 3.149,00 666,00 288,00 139,00E/P-density (to/km2) 420,33 10,16 3,60 28,96 6,13 2,65 1,28Germany 357.104 82,00 1.554,00 559,00 4.095,00 1.268,00 641,00 173,00E/P-density (to/km2) 229,62 4,35 1,57 11,47 3,55 1,79 0,48Benelux+NRW/GER 1,83 2,34 2,30 2,53 1,73 1,48 2,64217

CHAPTER 6 - EUROPETable 3b - Past and future emissions in the Benelux area for the years 1980 and 2020. Data are taken from EMEP(www.emep.int) for 1980 for all pollutants. The CO emissions for 2020 based on expert estimates as used in EMEP models(Vestreng, 2004: ‘W-04emis20-BL-V3’ (2004-07-15)). The projected emissions for all other pollutants based on the‘NEC_6_Current legislation’ scenario from the GAINS model(http://www.iiasa.ac.at/rains/gains-online.html?sb=9 based on Amann et al., 2008)Year: 1980NOX(kt as NO2)SOX(kt as SO2)CO(kt)NMVOC(kt)NH3(kt)Netherlands 583,00 490,00 1.530,00 579,00 234,00Belgium 442,00 828,00 1.285,00 274,00 89,00Luxembourg 23,00 24,00 193,00 15,00 7,00Benelux 1.048,00 1.342,00 3.008,00 868,00 330,001980/2004 1,53 5,99 1,83 2,21 1,53Year: 2020NOX(kt as NO2)SOX(kt as SO2)CO(kt)NMVOC(kt)Netherlands 196,00 50,00 678,00 161,00 130,00 39,00Belgium 158,00 88,00 286,00 127,00 77,00 48,00Luxembourg 14,00 1,00 37,00 7,00 6,00 3,00Benelux 368,00 139,00 1.001,00 295,00 213,00 90,002020/2004 0,54 0,62 0,61 0,75 0,99 0,841980/2020 2,85 9,66 3,00 2,94 1,55NH3(kt)PM10(kt)PM10(kt)6.5.3 Overview of pollution levelsAir pollutants, in particular SO 2 , NO X , CO, ozone, and total suspended matter (TSP) havebeen measured by the local environmental agencies or responsible institutions for several decades.Due to the success of local and European abatement strategies sulphur and carbon monoxide nolonger constitute a major problem in air pollution, in particular in western and Central Europe.Therefore the number of measurement sites has diminished considerably during the last years. Onthe other hand, measurement networks for PM 10 and PM 2.5 have been established during the past 5– 10 years.During the last two decades the emissions of air pollutants decreased due to measuresundertaken to reduce anthropogenic emissions. This in general leads to a decrease of pollutantsconcentrations in the region. For example the annual average of SO 2 in NRW decreasedconsiderably from about 60 µg/m 3 in the beginning of the 1980s to about 10 µg/m 3 today; the annualaverage of NO 2 decreased from 50 µg/m 3 in the beginning of the 1980s to 30 µg/m 3 today for urbanbackground stations, for measurement sites near streets, however, it remains between 40 and 50µg/m 3 since 1989 with small variations only (see:www.lanuv.nrw.de/luft/immissionen/ber_trend/konti_trend_2008.pdf). Minor variations might beattributed to interannual variations due to meteorology. The decrease of SO 2 is directly related tothe strong decrease of SO 2 emissions, whereas the decrease of NO 2 -emissions is less pronounced.In particular the primary NO 2 emissions due to traffic have a tendency to increase even if the totalNO X emissions are decreasing. It is expected that the tendency of an increased relative amount ofNO 2 in the total NO X emissions in traffic emissions in the European Union will continue in thecoming years from 12.4% in 2004 to 19.6% in 2010 and 32% in 2020 [Grice et al., 2009]. Thereforeit is expected that the annual limit values for NO 2 (40 µg/m 3 ) according to the air quality directive2008/50/EC will not be fulfilled within the next years.Fewer problems might occur with respect to the annual averages of PM 10 (limit value of 40µg/m 3 , implmented in 2010), and PM 2.5 (limit value of 25 µg/m 3 , to be fulfilled in 2015). However,with respect to PM 10 , problems may arise in the number of exceedances of the daily average of 50µg/m 3 . The daily limit values should not be exceeded more than 35 times a calendar year accordingto the air quality directive 2008/50/EC. Measurement sites in the Benelux/Rhine-Ruhr area show, asfor other sites in Europe, that the requirements of the air quality directive cannot be expected to be218

CHAPTER 6 - EUROPEfulfilled for the daily limit values set in 2010. According to model calculations the situation might beimproved by 2015 (see Figure 22).Figure 22 - (a) PM10, number of days with daily average above 50 µg/m 3 for the base case, reference year 2006 (b) Thescenario 2015 with an emission projection for 2015 (CLE). Based on calculations with the EURAD-model [Memmesheimer etal., 2009]. (c) NO2, number of days with daily average above 50 µg/m 3 for the base case, reference year 2006 (d) Thescenario 2015 with an NO2 emission projection for 2015 (CLE). Based on calculations with the EURAD-model[Memmesheimer et al., 2009]Annual averages of near surface ozone over Europe show an increasing trend on a decadalbasis since the 1990s [Vautard et al., 2006] whereas the number of episodes with high ozonevalues, e.g. with hourly values above the information or alert level (180 µg/m 3 , 240 µg/m 3 ), show atendency to decrease. The decrease of ozone precursors over Europe during the 1990s led to anozone increase both during urban minima and urban maxima due to less titration (see also Figure23). Especially during winter, with less photochemistry, one might expect less ozone in the urbanareas for the ‘1990’ simulation due to titration effects. However, in addition to the impact of regionalprecursor emissions, there are several processes which influence the average and high ozoneconcentrations as e.g. stratospheric intrusion events, stratospheric depletion of ozone, long-rangetransport, and global increase of ozone precursor emissions.Health effects of air pollution have been discussed for the European scale within the CAFEprogramme [Amann et al., 2005]. It was estimated that the losses in statistical life expectancyattributable to the exposure to anthropogenic PM 2.5 for the EU-25 is 8.1 months. It turned out thatthis value is considerably higher for Belgium (13.2 months) and the Netherlands (11.8 months),which show the highest value within the EU-25, in contrast to Finland with 2.6 months, which is thelowest value. All numbers are for the reference year 2000. It can be expected that the loss in life219

CHAPTER 6 - EUROPEexpectancy in NRW, in particular the Rhine-Ruhr area according to the methodology used by theIIASA (Amann et al., 2005) is on the same order as for Belgium and the Netherlands. Thesefindings emphasize the importance of the Benelux/Rhine-Ruhr area as one “hot spot” within Europefor air pollution and related problems, e.g. health. Furthermore it should be mentioned that thecalculations performed by IIASA have been undertaken with a horizontal resolution of 50 km. Thequite large horizontal gradients for particle mass concentrations from the urban agglomeration tothe nearby mountain areas as the Eifel cannot be displayed with appropriate accuracy. Urbanagglomeration show annual averages for PM 10 of 35 – 40 µg/m 3 and the mountain areas showannual averages of about 15 – 20 µg/m 3 . The concentration of air pollutants in inhabited areasmight even be higher than calculated for a 50 km grid in most cases, which is due toneighbourhoods that have quite high primary emissions in inhabited areas, in particular during weakwind conditions. A coarser resolution might thus underestimate concentrations in inhabited areasand health effects. Local impacts, in particular due to streets, on the prevalence of coronary heartdisease have been investigated within the framework of the Heinz Nixdorf RECALL study in theRuhr area [Hoffmann et al., 2007].6.5.4 Projections, modelling studiesAir quality modelling on regional and local scales is an important tool to investigate theimpact of past and future changes in emissions as well as the effect of future climate changes on airquality. Regional modelling efforts have been undertaken during the last decade [Forkel andKnoche, 2007; Cuvelier et al., 2007; Vautard et al., 2005; 2006; 2007; Stern et al., 2008;Memmesheimer et al., 2004; 2006; 2009] that focus on regional air quality in Europe and on thelocal urban scale within the Citydelta Initiative [Cuvelier et al., 2007; Vautard et al., 2007] in majorEuropean Cities. Two examples for modelling of PM 10 , NO 2 and ozone are given in Figures 22 and23. Figure 22a shows the number of exceedances of the daily limit value of 50 µg/m 3 (as defined inthe air quality directive 2008/50/EC) for a reference calculation in the year 2006 and a scenariocalculation performed with an emission projection for 2015 [Memmesheimer et al., 2009]. Theemission projection is based on data from IIASA that is available on the EMEP web site(www.emep.int). It can clearly be seen that a significant decrease of the number of exceedancescan be expected by 2015 according to the model calculations. Exceedances of the daily limit valueoccur predominantly within episodes governed by high-pressure systems during winter and fall.Therefore the number of exceedances may vary from year to year depending on the frequency ofmeteorological situations that favour their occurrence (high pressure systems during winter and fall,weak winds, temperature inversions). Annual averages of NO 2 are displayed for the same cases,values in Central Europe stay below the yearly limit value of the air quality directive of 40 µg/m 3 .However, it should be pointed out that measurements of sites in streets with high traffic densityshow annual average concentrations of NO 2 of 60 µg/m 3 or even more. And there is currently notrend for decreasing NO 2 concentrations in Europe because the NO 2 /NO X ratio for the emissions isexpected to increase considerably [Grice et al., 2009].To illustrate the impact of emission reduction on average and high ozone values a scenariocalculation for the August 2003 heat wave has been calculated using the same meteorological fields(for July and August 2003) as generated by the MM5 model but applying the emissions for 1990instead of the actual emissions for 2003. In central Europe, anthropogenic NO X and VOC emissionsfor 2003 are about 60% of those in 1990. Figure 23a shows average concentrations for ozone ascalculated for the episode from July 10 - August 15, 2003. The average ozone concentrations withinthe Rhine-Ruhr urban agglomeration area show only minor changes between the base case (2003with 2003 emissions) and the scenario calculation (2003 with 1990 emissions). Outside the urbanareas the average ozone concentrations for the scenario case are about 10 µg/m 3 higher as in thebase case. For the hourly maxima that are shown in Figure 23b the highest changes occur near theRuhr area. The hourly maxima increase by about 60 µg/m 3 for the scenario case with emissionsfrom 1990. Vautard et al. [2005] found, for the European scale, a significant decrease applying anemission projection for 2010 to the August 2003 heat wave for the information threshold (180 µg/m 3 )as well as for the AOT60 index, which is considered to be a relevant health impact index (integral ofpositive departures from 60 ppbv during 6 – 18 local time, i.e. daytime).220

CHAPTER 6 - EUROPEFigure 23 - (a) Ozone (µg/m 3 ) in 2003 (left) vs. (b) 1990 (right); averaged over the episode from July 10 – August 15, 2003.Based on model calculations for North-Rhine-Westphalia. (c) Ozone, 2003 (left) vs. (d) 1990 (right), hourly maximum (µg/m 3 ),based on model calculations for North-Rhine-Westphalia6.5.5 Effects of climate change on air pollutionAir quality depends on meteorological parameters and land use characteristics. Therefore itis clearly influenced by climatic changes and shows strong interannual variations [Forkel et al., 2007;Andersson et al., 2007]. On the other hand, changes in air quality by reduction of anthropogenicemissions can lead to changes in radiation, fog and in regional temperature trends as has beenshown recently by Vautard et al. [2009].Forkel et al. [2007] performed calculations with a nested regional climate-chemistry model(MCCM) with a horizontal resolution of 20 km for central Europe. Two time slices of about 10 yearsrepresenting present-day (1990s) and future climate conditions (2030s) were run. Anthropogenicemissions and outer domain boundary conditions were not changed. The model results show highertemperatures and decreased cloud cover and, in particular, increased emissions of isoprene lead toenhanced ozone formation in the troposphere. Daily maxima increase in the range of 2 – 10 ppbdepending on the region. Particulate matter has not been considered in this study.Regional climate-chemistry calculations with nested models, for several decades and with agrid resolution of 1 – 5 km, have not been undertaken until now for the Benelux/Rhine-Ruhr region.The development, application, and validation of these models are still a challenge for modellingactivities as discussed, for example, in the recent findings by Vautard et al. [2009]. Interactions ofair pollution and radiation, or even fog and clouds, have not been considered on this scale for the221

CHAPTER 6 - EUROPEtime range of several decades. On an episodic basis the impact of particulate matter on radiationand temperatures have been estimated for local scale applications in southern Germany (state ofBaden-Württemberg) by Riemer et al. [2003] and Bäumer et al. [2008].Vautard et al. [2009] have analysed multidecadal data of horizontal visibility, and found thatthe frequency of low-visibility conditions, such as fog and mist, has declined in Europe over the past30 years. They found that this decline is spatially and temporally correlated with trends in sulphurdioxide emissions and suggest a significant contribution of air-quality improvements. Further, usingstatistical methods to link local visibility changes with temperature variations they estimated acontribution of 10-20% of Europe’s recent daytime warming due to low-visibility conditions, andabout 50% in Eastern Europe. Vautard et al. [2009] discussed that their approach was of statisticalnature, and they assumed a causal relationship through radiation processes. However, theyemphasized that for a quantitative understanding of the processes a regional modelling approach isrequired. It is stated that this might be difficult to achieve with the current state-of-the-art regionalmodels and therefore further development will be a challenge for models.Long-range transport effects might influence the Central Europe region and might alsochange due to climate change connected at the global scale. There have been two interestingepisodes in the recent years leading to high concentrations of atmospheric particles in CentralEurope, including the Benelux/Rhine-Ruhr area. Birmili et al. [2008] discuss in detail one event,during which high concentrations of PM 10 between 200 and 1400 µg/m 3 were measured overCentral Europe during (24 March, 2007). Based on analysis of measured data, southern Ukrainecould be identified as the source region of the plume. Due to the meteorological situation soil dustcould be activated by high wind speeds and transported to Central Europe. Birmili et al. [2008] pointout that such an event might be an infrequent phenomenon that probably does not occur more oftenthan once in ten years. However, they emphasized that such events might become more frequent inthe future due to ongoing anthropogenic desertification processes. Again the quantitativeinvestigation of the atmospheric processes involved in such an event is a challenge for furtherdevelopment and application atmospheric models.A further episode with high PM 10 concentrations occurred end of May 2008 [Bruckmann etal., 2008]. Analyses of observational data and meteorological circulation patterns show clearly thatthe origin of the PM 10 -event can be attributed to the Sahara Desert (Sahara dust event). The dailyaverage of PM 10 -concentrations on 29 May and 30 May exceeded the European PM 10 daily limitvalue of 50 µg/m 3 . As an interesting feature it could be observed that the PM 2.5 /PM 10 ratio changedfrom quite small values of 0.3 – 0.4 in the Alpine region to 0.7 – 0.8 in the Benelux/Rhine-Ruhr area.Measurements of the chemical composition show an increase of secondary formed ammoniumnitrate and ammonium sulphate in the Benelux/Rhine-Ruhr area compared to the Alpine region andsouthern Germany. Secondary particulates therefore seem to be generated from anthropogenicprecursor emissions as NO X , NH 3 and SO 2 during the transport from the Alps towards theBenelux/Rhine-Ruhr area. Part of the mineral dust material seems to be replaced by the secondaryformed compounds.6.5.6 Major past studies or field campaigns examining the city’s air pollutionCoordinated studies for the whole Benelux/Rhine-Ruhr area are hampered by politicalboundaries. Some specific measurements for the Rhine-Ruhr area concerning atmosphericparticulate matter have been documented in Kuhlbusch et al. [2004]. The EU project CityZencollected measurement data used for evaluation models on different scales from 2008-2011.222

CHAPTER 6 - EUROPE6.6 PO VALLEY6.6.1 Introduction and specific features of the cityThe Po valley is neither a city nor an administrative unit. In can be identified by a geographicand pedological point of view as the floodplain enclosed between the Alps on the Western andNorthern side, the Apennines chain on the Southern and the Adriatic Sea on the Eastern side. It isroughly located around 45° N latitude and between 7°’30’ and 12° 30’ E longitude.The Po River Basin includes six administrative regions, its plains account for 2957 municipalunits for a total population of about 20 million people and an average population density of 414inhabitants/km 2 (Figure 24). The Basin accounts for nearly 50% of Italy’s GDP. It is home to 37% ofthe country’s industry, about 55% of livestock, and 35% of the country’s agricultural production. ThePo valley is therefore exposed to substantial emission loads. The population distribution and itsdensity (persons/km 2 ) are illustrated in Figure 25 on the basis of municipal land units. The majorurban conglomeration of Milan its clearly identified in central-northern part of the plain, while Turinurban area can be recognized towards its western edge and the largely urbanized zones of theVeneto plains and southern Emilia can be noticed near its eastern and southern limits. Thepopulation density is clearly correlated with the urbanisation represented in Figure 26 by urban landcover percentage on a 1 km 2 grid resolution. The core of Milan urban area, roughly coincident withits province, accounts for 3.7 millions inhabitants [see e.g. http://www.citypopulation.de/], while thecity commuting area has been evaluated to include around 7 million people [OECD, 2006]. Turinmetropolitan area accounts for more than 1.5 million people, while many cities counting more than100,000 inhabitants are scattered throughout the plains. During the last decades, the urbanisationof the region surrounding the major cities has increased by the re-settlement of part of thepopulation from the city core to nearby areas.Figure 24 - Po valley municipal units identified through pedological featuresUrban agglomerations located within the Po Valley basin suffer air quality conditions worsethan those experienced by other European cities like Paris and London. This is mainly due to theconcentration of urban and industrial emissions and to the adverse meteorological conditions thatoften affect the region due to its peculiar topographic and geographic features.The atmospheric circulation of the Po valley is characterised by the strong modification ofsynoptic flow due to the high mountains (Alps and Apennines chains) that surround the valley onthree sides. The local atmospheric circulation features, dominated by calms and weak winds, favourthe development of critical pollution episodes. Meteorological conditions causing winter air pollutionepisodes are analyzed in Kukkonen et al. [2005].223

CHAPTER 6 - EUROPEFigure 25 - Inhabitants (left) and population density (right) of the Po valley region. Elaboration on data published by theItalian Institute for Statistics [www.istat.it]Figure 26 - Po valley region topography and urban density(percentage of urban land cover elaborated from CORINE LandCover 2000)6.6.2 Emission sources of air pollutantsFrom an emission point of view, Lombardy Region represents the most important area in thePo Valley basin. About 20% of Italian industry is located here. In particular, the Milan MetropolitanArea is located in the Lomdardy region and accounts for about 8% of the national total of industrialemissions, especially due to the presence of specialized industry districts (textile, wood sector,metal, etc.) (http://sitis.istat.it/sitis/html/index.htm). The other large source of air pollution in thisregion is road transport due to the large number of vehicles (an average of 59 cars for every 100inhabitants; estimated by Osservatorio Autopromotec) and the presence of major roads that giverise to important traffic volumes.Table 4 shows emission from different source sectors in the Lombardy Region. The energyproduction sector is the dominant source for SO 2 emissions, while residential rombustion producesabout 1/3 of CO and PM 10 emissions. The industrial sector (industry combustion and productionprocesses) is a significant contributor to SO 2 emissions (due to gas oil and residual oil use inindustrial boilers) and is the second source, after road transport, of NO X emissions. The extraction224

CHAPTER 6 - EUROPEof fossil fuels and waste treatment sectors are important quite exclusively for CH 4 emissions,accounting for approximately1/4 of total emissions. The solvent use sector (in particular painting,chemical products’ synthesis and manufacturing, printing industry, and domestic use of solvents)produce only volatile organic compounds. About half of CO and NO X emissions are due to the roadtransport sector, which also produce 1/3 of regional PM 10 emissions, with different contribution givenby urban and non-urban traffic according depending on the pollutant.Table 4 - Annual emissions (t/year) of Lombardy RegionIf the attention is only focused on the Milan Metropolitan Area (here defined as a group of188 municipalities that form one of the administrative sub divisions of a region called “province”) it ispossible to stress some differences in the contribution of different sectors. Table 5 shows annualemissions of Lombardy Region and of the Milan Metropolitan Area. The Milan contribution to SO 2 ,PM 10 , N 2 O, and CH 4 emissions is between 15 and 20%, whereas for NO X , VOC, and CO it isbetween 25 and 30%. However, the Milan Metropolitan area accounts for a small amount of NH 3emissions (7%) due to the low presence of agricultural activities in the area surrounding Milan.Table 5 - Annual emissions (t/year) of Lombardy RegionFigure 27 compares sectorial contributions to total emissions in Lombardy Region and MilanMetropolitan Area. Milan has a lower percentage of emissions from energy production due to thefact that large power plants are located elsewhere in the Lombardy Region. As already observed,the contribution from agricultural activities is higher in the whole Region than in Milan area. On thecontrary, the very high fraction of urbanized area and the presence of very busy roads make thetraffic contribution higher in Milan than in the Lombardy Region.6.6.3 Data available on air pollutantsThe air quality monitoring network in the Lombardy Region is managed by RegionalEnvironmental Protection Agencies (ARPA), which provides information, data, and air qualityreports to the public with different methods and approaches. The air pollutants routinely measuredinclude SO 2 , NO 2 , CO, PM10, PM2.5, O 3 , and C 6 H 6 . Other chemical species as well as chemicalcomposition and size distribution of particulate matter is available for time limited field campaigns.Monitoring network description, recent data, archives, and air quality reports for the whole regionand main urban areas can be accessed on the ARPAs or municipalities web sites (all in Italianlanguage):225

CHAPTER 6 - EUROPEPiemonte (Turin): http://www.sistemapiemonte.it/ambiente/srqa/Lombardia (Milan): http://www.arpalombardia.it/qariaVeneto (Venice): http://www.arpa.veneto.it/aria_new/htm/qualita_aria.aspEmilia-Romagna (Bologna): http://www.arpa.emr.it/liberiamo/Friuli Venezia-Giulia (Udine): http://www.arpa.fvg.it/index.php?id=112Air quality data can also be downloaded from the National Environmental Protection Agency(ISPRA) central database BRACE (http://www.brace.sinanet.apat.it), where data are usually loadedwith a 1-2 years delay.Figure 27 - Comparison between sectors’ contribution to total emissions in Lombardy Region and Milan Metropolitan Area6.6.4 The status and trend of air pollutionThe main cities within the Po valley experience similar air quality problems with frequentexceedances of EC directives’ limit values for PM 10 during the winter and for ozone during thesummer. Non-attainment conditions are recorded for yearly averaged values of PM 10 and NO 2 .Examples of the air quality conditions experienced during the past decade are shown in Figures28-31. The yearly averages of NO 2 have values equal to or larger than 50 µg/m 3 with a very weakdeclining trend (Figure 28) at some stations. PM 10 concentrations are characterized by yearlyaverage concentrations above the limit threshold of 40 µg/m 3 (Figure 29) and a number ofexceedances of the daily average limit, often getting above 100 µg/m 3 (Figure 30). Stations locatedwithin urban parks (Parco Lambro) and around the urbanized area (Motta Visconti e Lacchiarella)show a large number of exceedances of the limit values for the ozone daily maximum of the 8 hoursrunning mean (Figure 31). Only stations located within the urban area (Juvara/Pascal) respect themaximum number of exceedances foreseen by EC directives during favourable years (2004-2006).The year 2003 summer heat wave caused much higher O 3 concentrations than all the followingyears.226

CHAPTER 6 - EUROPEFigure 28 - Yearly average NO2 concentrations in selected stations of Milan urban area.Solid line indicates the limit value stated by the European LegislationFigure 29 - Yearly average PM10 concentrations in selected stations of Milan urban area. Solid line indicates the limit valuestated by the European LegislationFigure 30 - Number of exceedances of PM10 daily average concentration limit in selected stations of Milan urban area.Solid line indicates the limit value stated by the European Legislation227

CHAPTER 6 - EUROPEFigure 31 - Number of exceedances of O3 daily maximum limit for 8 hours running average concentration in selectedstations of Milan urban area. Solid line indicates the limit value stated by the European LegislationLong-term trends of the major pollutants are described in Figure 32-33 for the station having thelongest air quality record in Milan (Juvara/Pascal). It has to be mentioned that this station wasrelocated during 2007 to a nearby site with similar environmental features. The dramatic decreaseof the yearly average SO 2 concentrations is the most evident concentration trend, declining fromabout 100 µ g/m 3 to values stably below 10 µg/m 3 over 20 years (Figure 32). The extent of theobserved reduction clearly dominates over the inter-annual variability and can be ascribed to thechange of fuel for house heating and transport as well as to the closure and/or relocation of largefactories that were located in Milan suburbs. The NO 2 trend shows an increase during the eightiesreaching values over 100 µg/m 3 followed by a decrease of yearly average concentrations untilvalues reached around 60 µg/m 3 in 2005. Positive effects on air quality due to changes in fuels, theimprovement of industrial technologies, and changes in domestic heating have been less effectivefor NO 2 than for SO 2 . In addition, much of the improvement is likely counterbalanced by the growthin traffic volume. The decrease of NO 2 from 1994-95 on is mostly likely due to the introduction ofcatalytic converters. Ozone yearly average concentrations increased until the end of the 20 thcentury, showing a slight decrease after the 2003 peak and a further increase during recent years.This behaviour can be tentatively explained, within urban areas, by the decrease of NO Xconcentrations and the variation of the NO X /VOC ratio, superposed to the natural variation of themeteorological forcing.Figure 32 - Yearly average concentrations of SO2,NO2 and O3 measured at the urban backgroundstation of Milano Juvara/Pascal228

CHAPTER 6 - EUROPEFigure 33 - Yearly average concentrations of TSP and PM10 measured at the stations of Milano Juvara, Liguria and PascalTotal Suspended Particulate (TSP) concentrations increased from 1983 to 1987 followed bya strong reduction from the late eighties to mid-nineties, and have more or less remained stablesince (Figure 33). The trend in PM concentration is likely due to previously discussed air pollutionreduction measures since PM is emitted by the main pollution sources, but is also produced bychemical transformation of other pollutants (e.g. SO 2 and NO 2 ) and by car traffic as a non-exhaustproduct.The air quality data presented here are from measurements from the Lombardia Region airquality network and were made available by the Lombardia Region Environmental ProtectionAgency (http://www.arpalombardia.it), see e.g. Angius et al. [2009].6.6.5 Relationships between trends regulations and practicesThe administrative regions of the Po Valley are negotiating with the EC about their nonattainment conditions in regard to PM 10 limits imposed by the European Directive 2008/50/EC.Similar difficulties are expected to be faced for NO 2 yearly average limits that are generallyexceeded within the major urban conglomerations.Different mitigation actions have been attempted during the last decade. These mitigationefforts include amongst other: traffic bans during the weekends in case of air pollution episodes (allthe main cities), partial traffic ban based on odd-even car plate number (Turin urban area), wintercirculation ban for obsolete (EURO 0) vehicles (Lombardy critical areas), and the ECOPASS (apollution charge experiment in Milan depending on the European vehicle classification). Themitigation efforts, generally managed and applied locally, thus far are not able to produce a clearlydetectable reduction in air pollution trends.During recent years, awareness is growing that air pollution within the Po valley is a basinproblem that cannot be fixed by local measures alone that are decided and managed independently.This consciousness carried the Po valley Italian Regions (Emilia-Romagna, Lombardia, Piemonte,Veneto, Trento and Bolzano autonomous Provinces) and the Swiss Canton Ticino to sign inFebruary 2007 an agreement to coordinated action to reduce air pollution over the whole Po Valley.Future common measures are expected to include: public transportation support, progressiveintroduction of limitation (in 2010) to the circulation of obsolete polluting vehicles, obligatoryparticulate matter filter for diesel cars, financial support for car park renewal, ban on dense oil forhouse heating, and enforcement of stricter limits for wood, biomass fired plants, and house heatingdevices. Negative contributions to PM air pollution increased due to the increase in the number ofdiesel vehicles that characterize the Italian car market from the late nineties and by the growingtrend to move from gas to wood fired stoves for house heating due to the rise of oil and gas prices.229

CHAPTER 6 - EUROPEAs for the development and implementation of technical instruments, Regions Piemonte,Emilia Romagna, Friuli Venezia Giulia, Veneto, Puglia, Trento and Bolzano autonomous Provincesare collaborating with Regione Lombardia to develop high-resolution emission inventories with thesame methodology originally developed by Caserini et al. [2004]. Many of the Po Valley ARPAsimplemented air quality modelling systems built around chemical transport models (CTM) toperform yearly air quality assessment, air quality forecast, and near real time air quality analyses[see e.g. Finardi et al., 2008; Silibello et al., 2008; Stortini et al., 2007).6.6.6 Climatic change issuesMilan city [Tebaldi et al., 2007] and the Po Valley [Brunetti et al., 2006a; 2006b] data show aclimatic trend in general agreement with mid latitude European trends. From 1970 a clear increasein temperatures has been observed, with milder winters, warmer springs, hotter and more humidsummers, and with a wider seasonal variability. The precipitation regime shows differences amongthe areas located around the Alps. During the last years, in Milan, it shows stationary behaviourduring the winter, a reduction of spring and autumn rains, and a growth of summer precipitationintensity.Mild winters may have contributed to fewer occurrences of temperature inversion episodesthat cause severe air pollution episodes [Finardi and Pellegrini, 2004; Kukkonen et al., 2005] and toa reduction in the number of NO 2 exceedances of the hourly average limit of 200 µg/m 3 , asobserved during the last years. The climatic tendency does not show reducing effects on winter PMconcentrations. Summer heat waves cause prolonged ozone episodes, as confirmed by bothaverage and peak ozone values recorded during summer 2003.6.6.7 Major past studies or field campaigns examining the city's air pollutionThe Po Valley is probably one of the areas of Europe where more research activities havebeen focused during the last decades. Several of these research activities are the PIPAPOcampaign [Baltensperger et al., 2002] for the characterization of ozone episodes, the PARFILproject and campaigns (http://www.disat.unimib.it/chimamb/parfil.htm) to investigate formation anddistribution of PM within critical areas of Lombardy Region, and the City Delta project[http://aqm.jrc.ec.europa.eu/citydelta/, Vautard et al., 2007] for inter-comparison of modelresponses to urban-scale emission-reduction scenarios.6.6.8 Cutting edge researchOngoing relevant projects include POMI Po-Valley Modelling Intercomparison Exercise(http://aqm.jrc.ec.europa.eu/POMI/) and the EC 7 th Framework Programme projects MEGAPOLI(http://megapoli.info/) and CITYZEN (https://wiki.met.no/cityzen/start), both of which are consideringthe Po Valley as a target area to analyse the effects on air quality and climate at regional and globalscales due to pollutants emission from megacities and pollution hot spots areas.6.6.9 Problems remainingDespite the large number of scientific investigations that targeted the Po Valley region, theprocesses driving formation and accumulation of PM within the basin are still far from beingcompletely understood. The region remains one of the EU pollution hotspots recording a largenumber of exceedances of EC directives air quality limits causing severe concerns on the impactson human health. Despite emission inventories estimates that cite a measurable reduction of PMemissions, PM 10 ambient concentrations did not show a decreasing trend during the last decade(1998-2008). The importance of secondary aerosol formation and the uncertain relationshipbetween local PM emission and background atmospheric concentrations make mitigation actionsdifficult to determine and to evaluate. Moreover, many modelling studies employing different CTMsover the Po Valley basin showed difficulties in reproducing winter PM 10 peak concentrations andaccumulation phenomena.230

CHAPTER 6 - EUROPE6.7 EASTERN MEDITERRANEAN AND ISTANBUL MEGACITY6.7.1 Introduction – location, meteorological patterns and air pollution levels6.7.1.1 Meteorological patternsThe Mediterranean region consists of a landmass surrounding a body of saline water, theMediterranean sea, which does not exchange very rapidly with the rest of the oceans. The typicalMediterranean climate is characterized by hot, dry summers and mild, rainy winters. Evaporationgreatly exceeds precipitation and river runoff in this region, a fact that is central to the watercirculation within the basin.The Mediterranean, and particularly its East basin, is at a crossroad of air masses comingfrom Europe, Asia, and Africa. At this crossroad, anthropogenic emissions, mainly from Europe,Balkans, and the Black sea, meet with natural emissions from the Saharan desert, vegetation, andthe Mediterranean Sea as well as from biomass burning, which presents a strong seasonal pattern.The transport of anthropogenic pollutants from North America also exerts a significant influence inthe free troposphere [Lelieveld et al., 2002]. As a consequence of its unique location and emissions,the Mediterranean region is a climatically sensitive region, often exposed to multiple stresses, suchas a simultaneous water shortage and air pollution exposure [IPCC, 2007]. Pollution in this regionhas been extremely high in the last couple of years. Pollution episodes are favoured due to theMediterranean climate and the likely growth in the future emissions due to rapid urbanization of theregion. The meteorology and chemistry of the Mediterranean lead to two “distinct” but interlinkedregions, the western and the eastern basins.Recirculation and regional patterns are more important in the western Mediterranean, whichreceives more precipitation, is drier, and has more oligotrophic seawater than the eastern basin.Evaporation is especially high in its eastern half, causing the sea water level to decrease andsalinity to increase eastward. In contrast to Central and Northern Europe, in the SouthernEurope/Mediterranean region, photochemical episodes can also occur since at these latitudes solarradiation is still important for photochemical reactions that favour air pollution.The Eastern basin of the Mediterranean and the surrounding regions include severalmegacities such as the Istanbul (>12 million inhabitants, Turkey) and Cairo (~16 million, Egypt) andseveral large urban centres such as Athens (>4 million) and Thessaloniki (>1 million) in Greece,Izmir (4 million) and Adana (>4 million) in Turkey, Amman (>2 million, Jordan), Beirut (~2 million,Lebanon), Damascus (6 million, Syria), and to the south Alexandria (4 million, Egypt). The regionalcoverage includes rural (inland Greek and Anatolian peninsulas), maritime (Crete island), anddesert (Anatolian plateau, north Africa, Middle East) conditions. Section 6.7.2 is dedicated to themegacity of Istanbul in the East Mediterranean region whereas in Section 6.7.3 we present somecharacteristics of the Athens extended area as another example of rapidly expanding urbanagglomeration. Relevant information for Cairo megacity situated at the South edge of the basin isprovided in the Chapter on African megacities.During the last decades the Mediterranean, following the general trend, has experienced arapid growth in urbanization, vehicle use, and industrialization, which is reflected in pollutantemissions to the atmosphere. Air pollution is one of the challenging environmental problems inIstanbul and Cairo megacities but also for the whole East Mediterranean region. Ozone and aerosolair quality limits are often exceeded over the entire Mediterranean in particular during the summermonths. High ozone and aerosol concentrations are harmful to human health and ecosystems, andthey also cause agricultural crop loss and contribute to climate change. The contribution of naturalemissions to these exceedances seems significant and remains to be determined.6.7.1.2 Air pollution in the East MediterraneanOzone and its precursors - The Mediterranean, located at the boundary between the tropical andmid-latitudes, is subject to large (about 50%) changes in the total O 3 column[Ladstaetter-Weissenmayer et al., 2007] that have been attributed to changes in the location of the231

CHAPTER 6 - EUROPEsub-tropical front [Hudson et al., 2003]. In summer, the total observed variability in tropospheric O 3is about 5-10% of the total O 3 column, that is 25 DU [Ladstaetter-Weissenmayer et al., 2007].Because Mediterranean background O 3 levels are high, particularly in the spring and summer, it isdifficult to control ozone in urban and industrial areas. This is especially true because thebackground ozone levels are controlled by meteorological conditions, large-scale atmosphericdynamics, long-range transport, and photochemical formation. Experimental studies over theeastern Mediterranean [Kourtidis et al., 2002; Kouvarakis et al., 2000] have demonstrated thattransport from the European continent is the main mechanism controlling ozone levels in theeastern Mediterranean, especially in summer (or spring depending on the prevailing air transportpatterns) when ozone presents a maximum of about 60±10 ppbv [Gerasopoulos et al., 2005].Kalabokas et al. [2007] found that during the summer, high tropospheric ozone values in theeastern basin were confined in the low troposphere whereas in the middle troposphere O 3 was only5–10% higher than over Central Europe. Enhanced levels of NO 2 pollution over the last decade canbe detected by satellites (NO 2 , Figure 34, O 3 ) over East Mediterranean (Istanbul, Athens and Izmir)and over the Middle East, in particular around the main ports of the Persian Gulf, around the RedSea port of Jedda near Mecca, and around the cities of Riyadh, Cairo, and Tehran [Van Noije et al.,2006, Lelieveled et al., 2008; Vrekoussis et al., 2009].Figure 34 - (left) SCIAMACHY Vertical Column Densities (VCDs) of NO2 over the eastern Mediterranean basin gridded to0.125x0.125 o . (right) Annual mean changes in the vertical tropospheric column density (VCD) of NO2 over the EastMediterranean from 2003 to 2007 in molecules NO2 . cm -2. y -1 as derived from SCIAMACHY observations[Vrekoussis et al., 2009; © IUP, University of Bremen]Airborne particulate matter - The Mediterranean is one of the areas with the highest aerosoloptical depth (AOD) in the world, which can be seen by satellites [Hatziannastassiou et al., 2009].Observations over the area show high concentrations of aerosols, both PM 10 and PM 2.5 [Querol etal., 2009]. Chemistry-transport models successfully simulate the occurrence of high loadings ofaerosols over remote locations in the Mediterranean [Gangoiti et al., 2006; Kallos et al., 2007;Kanakidou et al., 2007]. In the Mediterranean, PM 10 has a similar seasonal behaviour than PM 2.5 ,which is marked by dust emission and transport, particularly in spring and fall in the eastern basinand in February-March and late spring-summer in the western basin (especially at regionalbackground sites), whereas PM 1 behaves differently [Gerasopoulos et al., 2007; Koçak et al., 2007;232

CHAPTER 6 - EUROPESaliba et al., 2007]. Mineral dust transport events that occur episodically over the area are a majorcontributor (more than 40%) to the PM 10 exceedances of the EU limit of 50 µg m -3 [Koçak et al.,2007; Gerasopoulos et al., 2006b; Mitsakou et al., 2008]. This is also observed by lidar [Papayanniset al., 2008], sun photometer [Fotiadis et al., 2007] networks, and satellite observations[Papayannis et al., 2005; Kalivitis et al., 2007]. Re-suspension of dust is likewise a significantcomponent of aerosols in the cities [Rodriguez et al., 2004]. In industrial and urban areas, mostexceedances (around 70-80%) are due almost exclusively to local anthropogenic sources [Querolet al., 2009].In the eastern basin the fine aerosol fraction (

CHAPTER 6 - EUROPEpollutants around or even below the air quality standards set by national and internationalinstitutions. Air pollution effects on health, partly determined by specific mixtures of air pollutants,may be altered by other environmental, behavioural, and social patterns. Mediterranean countrieshave some common characteristics in terms of climate, geography, and population activities thatdiffer from those in the colder Central and Northern Europe. Katsouyanni [1995] summarizes theknowledge on the impact of air pollution on health in two major Mediterranean cities, mainly withregard to exposures to sulphur dioxide and black smoke. She points out that the health effects ofthe interactions between these pollutants and photochemical oxidants can be enhanced in theMediterranean. The area is also appropriate for the study of synergies between air pollutants, hightemperatures and humidity patterns. She stresses that even if the health effects of air pollution onlyslightly increase the risk to an individual, they are likely to be important for public health because ofthe ubiquitous exposure of the population. Zanobetti et al. [2002] studying 10 European citiesamong which 4 were in the Mediterranean area, found that the overall effect of PM 10 per 10 µg . m -3 isa 1.61% increase in daily deaths, whereas the mean of PM 10 on the same day and the previous dayis associated with only a 0.70% increase in deaths. Their study confirms that the effects observed indaily time-series studies are not due primarily to short-term mortality displacement and that theimpact of airborne particles more than doubles when longer-term effects are taken into account.6.7.2 The Greater Istanbul Area6.7.2.1 City characteristics, geography, population, meteorologyThe city of Istanbul located at 41.01 o N, 28.58 o E, is one of the largest cities (21 st in 2009)[Thomas Brinkhoff: The Principal Agglomerations of the World, http://www.citypopulation.de/] in theworld with 12.5 million inhabitants according to the last population census of 2007 and an annualgrowth rate to be about 4.5%. The city extends on two continents with the European part of the citybeing the oldest part, separated from the Asian part by the south part of the Bosporus strait. TheBosporus strait of 30-km length, connects the Marmara Sea at the south with the Black Sea at thenorth. In the past, the city expanded along the Marmara shore but in recent years a northerlyexpansion has also occurred (Figure 35, Ezber et al., 2007) to move away from the North AnatoliaFault which passes along the south of Istanbul in the Marmara sea and produced the large EarthQuake in Istanbul on August 17, 1999 [Stein et al., 1997; Armijo et al., 1999; Hubert-Ferrari et al.,2002]. The metropolitan region covers 6220 km 2 .Figure 35 - Istanbul is located on both European and Asian continents, separating the Black Sea from Bosporus[Ezber et al., 2007]234

CHAPTER 6 - EUROPEAlmost 17% of the population of Turkey occupies the Greater Area of Istanbul (GIA). In theGIA, almost the entire population inhabits the urbanized areas while a very small portion occupiesthe surrounding rural areas. The city’s population nearly doubled in the 20 years between 1980 and2000, the fastest growth period for the population. For the period between 1990 and 2000, thepopulation growth rate of Istanbul was 29.6% for urban parts and 81% for rural parts of the city.Total population growth rate was 33.1% for the same period. To compare, these figures are 26.8,4.2 and 18.3%, respectively, for the whole of Turkey (Figure 36; Ezber et al., 2007; CIA WorldFactbook, 2009]. GIA’s population growth rate is slightly over 4% [OECD, 2008]. The 2005Istanbul’s population is expected to grow from its present level of 12 million to 16 million in 2017,and to 23 million in 2023. This will result in intensified pressure on industrial and residential uses inthe northern part of the metropolitan region, where the natural protection areas and the watershedsare located [OECD, 2008].Figure 36 - Population growth in Istanbul from 1935 to 2000 [Ezber et al., 2007]WHO [2006] statistics for the year 2004 report for Turkey a mean life expectance at birth of71 yr that is lower for males (69 yr) and higher for females (73 yr). Similar numbers are given for2009 (71.96 yr, 70.12 and 73.89 yr respectively) by the 2009 CIA World Factbook. An increase isreported since 1990 when these numbers were 64 yr for males and 67 yr for females. According toTurkish Statistical Institute [TÜİK, 2007], the life expectance at birth was 66 yr in 1990 and 71.7 yr in2007 (70.1 yr for men and 73.9 yr for women) and is expected to increase to 74.4 yr in 2050.During the last decades the Mediterranean, following the general trend, has experienced arapid growth in urbanization that intensify vehicle circulation and industrialization, which arereflected by the increase in pollutant emissions to the atmosphere. Such development affected thecity of Istanbul within the last 40 years.The orography of Istanbul is dominated by seven hills that affect the air circulation in theregion. The prevailing wind in Istanbul is northeasterly. The southern part of the GIA, the mosturbanized, has Mediterranean type climate. During summer, it experiences sea and land breezecirculation patterns with wind blowing from Marmara sea to Istanbul during day and from the city tothe sea during night. Such circulation is influencing pollutants transport [Im et al., 2006]. Thenorthern part of GIA is affected by the colder northern air masses and the cooler Black Sea and hasslightly cooler temperatures and higher precipitation than the southern part of the GIA. Averageseasonal air temperatures in Istanbul are about 28 o C in summer and 8 o C in winter, and the windspeed is highest in winter and lowest in summer with annual average of about 17 km/h. Thehumidity is high during all seasons. Average annual total precipitation is around 800mm [Ezber etal., 2007]. The heating effect due to urbanization was found to produce two-cell structures duringthe summer, one on the European and one on the Asian side of the city. The cells extend to about600–800 m height in the atmosphere over the city and combine aloft [Ezber et al., 2007]. In235

CHAPTER 6 - EUROPEaddition to local pollution, Istanbul is vulnerable to trans-boundary transport of air pollutants fromEurope, because its location is on the eastern end of the Continent, where westerly winds prevail[Kidnap, 2008].6.7.2.2 Emissions sources of pollutants and their precursors in the areaBetween 1980 and 1990 the consumption ratio of coal to fuel-oil increased from 0.68 (in1980) to 3.09 in 1990 [Tayanc et al., 2000]. Liquefied petroleum gas (LPG) has been widely used intraffic starting from the beginning of 1998. Through the emissions from the transport sector, a bigportion of ozone precursors and aerosols are emitted to the atmosphere. There has been a shiftfrom coal to natural gas for domestic heating purposes starting from the early 1990s, leading to adecrease in the concentrations of primary pollutants such as sulphur oxides (SO x ) but an increasein secondary pollutants such as aerosols and ozone. The region experiences very dense industrialactivities, almost the highest in the country. Almost half of Turkish industry is located around theMarmara Sea [OECD, 2008]. Based on Istanbul Chamber of Industry reports, 37% of the industrialactivities comprise textile industry, 30% metal industry, 21%chemical industry, 5% food industry,and 7% other industries [Im et al., 2006]. Low quality solid and liquid fuels with high sulphur content,natural gas, and LPG are the most commonly used fuel types in the industrial activities. In addition,over 2 million cars circulate in Istanbul, most of them are older cars. Under these the density andvariety of industrial activities, the region experiences very complex air quality conditions.Markakis et al. [2009] have developed an emission process kernel aimed at compiling a highspatial and temporal resolution emission inventory for anthropogenic sources for the GIA at a 2 kmgrid. They considered nitrogen oxides (NO X = NO + NO2), carbon monoxide (CO), SO X , ammonia(NH3), non-methane volatile organic compounds (NMVOCs), PM 10 , and PM 2.5 . They estimated totalannual emissions in the GIA of 437 kt for CO, 305 kt for NO X , 91 kt for SO X , 77 kt for NMVOCs, 7 ktfor NH 3 , 61 kt for PM 10 , and 37 kt for PM 2.5 . Their results indicate that the road transport sector is themain contributor to the emissions in the area, whereas residential and industrial combustion as wellas cargo shipping are also important source categories. Industrial combustion (49% of PM 10 and24% of PM 2.5 ) and road transport (17% of PM 10 and 29% of PM 2.5 ) emissions also play the majorrole in PM emissions. Particularly, 76 % of the organic portion of PM comes from traffic. Energy andindustrial combustion are found to be the main SO X emitters (36 and 23%, respectively). NMVOCsmainly originate from road transport (45%), solvent use (30%), and waste (20%). The spatialdistribution of emissions follows the residential distribution and the seasonal variation shows higheremissions during the winter. Weekend emissions are lower than weekday emissions and diurnalcalculations show that the profile fits with the rush hours due to the highest contribution of trafficemissions [Makrakis et al., 2009].6.7.2.3 Air pollutantsOzone and its precursors - Im et al. [2008] reported O 3 observations from two different locationsin Istanbul close to the Marmara sea from 2001 to 2005. One location, Saraçhane, is on theEuropean side of the city and the other one location, Kadıköy, is the Asian side of the city. Thehighest ozone concentrations were observed during hot, sunny summer when maximumtemperatures were above 25 °C. These episodes were mainly characterized by southwesterlysurface winds during the day and northeasterly surface winds during the night. High VOC-to-NO Xratios at both stations indicated that NO X -sensitive chemistry was dominant in the region. However,higher correlations of VOCs in Kadıköy, as compared with those in Saraçhane, indicated that VOCsalso have an important contribution to ozone formation. High O 3 days demonstrated a typical diurnalprofile with maximum concentrations appearing during afternoon hours and minimumconcentrations appearing during rush hours due to NO X titration from traffic emissions. According tomeasurements, daily average O 3 concentrations were around 100 µg . m −3 whereas individualepisodic periods had hourly concentrations reaching 180 µg . m −3 in Saraçhane and 140 µg . m −3 inKadıköy [Im et al., 2008]. Lower-daily maximum values at the Kadıköy Station resulted from betterventilation due to its location near the sea and from larger titration values of NO X resulting fromclose proximity to dense traffic.236

CHAPTER 6 - EUROPEExceptionally high ozone concentrations up to 310µg . m −3 have been observed in Istanbul inthe early morning hours [Im et al., 2006]. The high ozone concentrations can be explained bydecreasing inversion heights during the early hours of the day that led to suppression of pollutantsclose to surface and thus an increase in ozone concentrations [Im et al., 2006]. During thisexceptionally high ozone event, high levels of NO 2 from traffic and CO, locally exceeding 100 µg . m -3and 1.5 mg . m -3 , were also reported.High correlations between NO and NO X were calculated for both stations suggesting thatNO X emissions originated locally. Vrekoussis et al. [2009] have also computed the annual levels ofthe vertical column densities of NO 2 (VCD NO2 ) based on SCIAMACHY observations during theperiod 2003-2007 and over a region of 0.5 o x0.5 ο (4 grids) around the city centre. The calculatedannual mean NO 2 VCDs over Istanbul are ~1 . 10 16 molecules . cm -2 . Satellite observations[Vrekoussis et al., 2009] indicate an increase in the tropospheric columns of NO 2 over recent years(Figure 34).Airborne particulate matter - Some regions of Istanbul are continuously exposed to high pollutionlevels during the heating season (November–March) [Gülsoy et al., 1999]. Since 1966, severalstations run by the Istanbul Municipality monitor PM 10 concentrations. At the end of the 1980s andthe beginning of the 1990s, sulphur dioxide (SO 2 ) and PM concentrations exceeded the short-termair quality standards 1 on many days [Tayanç, 2000]. The levels of SO 2 over Istanbul increased from1985 to 1991 reflecting the use of low quality fossil fuels during that period. In 1995-1996, there wasa considerable decrease in air pollution for 3 reasons: 1) increasing ventilation of the City, 2)switching to natural gas for heating and 3) treatment of coal before its entrance into the city.Karaca et al. [2005] found that the annual (July 2002-July 2003) arithmetic mean of PM 10was 47.1 µg m −3 , higher than the European Union air quality annual PM 10 standard of 40 µg . m −3 .The annual mean concentration of PM 2.5 (20.8 µg m −3 ) was also higher than United States EPAannual PM 2.5 standard of 15 µg m −3 . Ozdemir et al. [2009] reported average PM 10 levels of about 66µg . m -3 observed at 10 Istanbul municipality stations during the last 10 years with values rangingfrom 47 µg . m -3 to 115 µg . m -3 . Karaca and Camci [2010] have analyzed the episodes of high PM 10levels in Istanbul and attributed 52% of them to distant source contributions, massive anthropogenicactivity over all of Europe, and southwestern airflow most likely carrying PM 10 originating from theSahara Desert and other global dust generation regions located in the northern part of Africa.Recently, the first complete chemical characterization measurements of aerosol in GIAbecame available from the Bogaziçi University sampling station. The station is located at an urbanbackground site in Bosporus straight coast in Istanbul, and 9 different water-soluble ions, watersoluble organic carbon (WSOC), organic and elemental carbon (OC, EC) and several trace metalswere measured between November 2007 and June 2009. Theodosi et al. [2010] found that traceelements related to human activities (as Pb, V, Cd and Ni) reached peak values during winter due todomestic heating, whereas natural origin elements like Al, Fe and Mn peaked during the springperiod due to dust transport from Northern Africa. Organic carbon was found to be mostly primaryand elemental carbon was strongly linked to fuel oil combustion and traffic. Both OC and ECconcentrations increased during winter due to domestic heating, while the higher WSOC to OC ratioduring summer can be mostly attributed to the presence of secondary, oxidised and more solubleorganics. Source apportionment analysis of these observations using PMF indicates thatapproximately 80 % of the PM 10 in Istanbul is anthropogenic in origin [secondary, refuse incineration,fuel oil and solid fuel combustion and traffic, Koçak et al., 2010].Guelsoy et al. [1999] analyzed precipitation samples in Istanbul from January to October1996. They observed high sulphate and nitrate concentrations in the precipitation of up to 150 mg . l -1and 70 mg . l -1 , respectively, during the heating period, associated with high pH values due toneutralization of the acidity by calcium and ammonium observed at sufficient levels in these1 The current Turkish legislation sets SO2 and PM10 limits as follows (Ministry of Environment and Forest, Turkey, 2008): SO2 hourlylimit: 360 ug/m 3 ; SO2 24-hour limit: 125 ug/m 2 ; annual SO2 limit: 20 ug/m 3 . PM10 24-hour limit: 50 ug/m 3 ; annual PM10 limit: 40 ug/m 3 .237

CHAPTER 6 - EUROPEprecipitation samples. In general the Istanbul rainwater pH was about 6-7, only 18.6% of the eventsshowed acidic pH below 5.6.There have also been a limited number of modelling studies that investigate the elevatedPM 10 levels in the area. The results showed that local anthropogenic emissions under unfavourablemeteorological conditions can be responsible for up to 90 per cent of PM 10 levels [Im et al., 2010].Long range transport from Europe can contribute up to 50 per cent to these high concentrations[Kindap et al., 2006].6.7.2.4 Climate effects including Heat islandKaraca et al. [1995] and Ezber et al. [1997] have studied the climatic effects of urbanizationin Istanbul. Karaca et al. [1995] statistically analyzed long-term temperature data (1912- 1992) fromstations within and around the Istanbul and reported a warming trend in urban temperatures insouthern Istanbul, which was the most densely populated part of the city, whereas in northern GIA acooling trend was observed. Ezber et al. [2007] have focused the analysis for the period from 1951to 2004 by using both statistical and numerical mesoscale modelling tools. They have shown thatthe urbanization effect on climate was most pronounced during the summer. Changes in the trendsoccurred in the 1970s and 1980s when the population growth rate in Istanbul increased dramatically.A significant expansion of the urban heat island in Istanbul has been computed for the period from1951 to 2004, fairly consistent with the expansion of the city during this period. The maximumreference-level temperature difference between the past and present simulations was found to bearound 1 o C. The modelling experiment by Ezber et al. [2007] also indicated that the velocity of theprevailing northeasterly wind and the water vapour mixing ratio were both reduced over the city.6.7.3 The Greater Athens Area6.7.3.1 City characteristics, geography, population, meteorologyGreece has one of the most aged populations in Europe with almost one fifth over 65 yearsold. In 2004 the annual deaths of 104 000 inhabitants were slightly higher than the 101 000 births. In2004, the life expectancy of the total population at birth was 79 years. The male population, whichconstitutes 50% of the national total population, has a lower life expectancy (77 years) than females(82 years), one of the highest in Europe [WHO, 2006]. The Greater Athens Area (GAA) currentlyhas a population exceeding 4 million inhabitants, which is about 40% of the total population ofGreece, and has experienced a population growth rate of 0.6% per year over the last decade.The climate of Athens is typically Mediterranean with hot dry summers and wet mild winters.The mean daily summer and winter temperatures are 25.8 o C and 10.1 o C, respectively. The meanannual total precipitation is about 400 mm, 85% of which occurs from October to March [Kalabokaset al., 1999a]. The mean wind pattern in the atmospheric boundary layer in Athens during thewarmer part of the year is a persistent northeasterly flow. The Athens basin is exposed to thesummer monsoon circulation of the Eastern Mediterranean. The city of Athens is located in a basinon the west coast of the Attica peninsula (Figure 37). It is surrounded by moderately high mountainsforming a channel with only one major opening toward the sea to the southwest. The mountains actas physical barriers with only small gaps between them. The most important gap is the channelbetween Hymmetus and Pendeli leading to the northeast coast of the Attica peninsula that gives theAthens basin access to the Etesians, a system of semi persistent northerly winds. During theappearance of the Etesians, good ventilation of the basin is favoured and thus pollution episodes donot appear. The weakening of the synoptic wind allows the development of local circulation systems,such as sea/land breezes along the axis of the basin (NE to SW) and anabatic/catabatic flows fromthe surrounding mountains. During such cases, the ventilation of the basin is poor, the boundarylayer is shallow, and the air pollution potential increases [Melas et al., 1995 and references therein].Air pollution episodes may occur in Athens during all seasons of the year but most of theseepisodes are associated with the development of sea-breeze [Kallos et al., 1993].238

CHAPTER 6 - EUROPEFigure 37 - Map of Greater Athens Area with altitude contours at 200 m intervals[Melas et al., 1995]6.7.3.2 Emissions of pollutants and their precursors in the areaThe massive number of registered vehicles in circulation (over 2.5 million, growing at a rateof 7% yearly) is allegedly the major cause of air pollution related problems in the area, taking intoaccount that a large proportion of these vehicles are non-catalytic (0.8 million) or are powered byold technology diesel engines (0.2 million). Although the use of natural gas for domestic heatingpurposes has increased lately, combustion of fuel oil is still primarily used for central heating.An anthropogenic emissions inventory was compiled for Greece and the Greater AthensArea (GAA) for the reference year 2003 [Markakis et al., 2010a; Markakis et al., 2010b] with a 10km spatial grid over Greece and a 2 km grid over GAA. The emission inventory has monthly, weekly,and hourly temporal analysis. Total annual emissions for the GAA were estimated to be 473 kt forCO, 78 kt for NO X , 31 kt for SO 2 , 93 kt for NMVOCs, and 20 kt for PM 10 . Approximately 75% of CO,70% of NMVOCs, and almost half of NO X emissions originate from the road transport sector whilethe most important SO 2 emitter is the industrial sector. The majority of PM emissions stem from theindustrial sector. The large industrial complexes are located several kilometres outside the Athensbasin where the majority of the population resides. Inside the basin the road transport is again themost important emission source for PM. Almost 20% of PM emissions originate from non-exhaustsources like tire and break wear as well as road abrasion. The annual variation of emissions showsthat although the central heating operations do not account for more than a few percent in theannual totals (with an exception of SO 2 – 15% contribution), in the winter months they make asignificant contribution. According to Greek national totals Athens is responsible for almost half ofthe road transport sector CO emissions and 70% of the NO X emissions. Taking into account thatalmost half of the county’s population inhabits the GAA as well as the fact that Athens experiencesvery severe congestion with the average speed not to exceed 12 km/h during rush hours, the resultsare not surprising.6.7.3.3 Air pollution levels and abatement measuresThe GAA has been subject of intensive field campaigns like MECAPHOT-TRACE in summer1994 [Ziomas, 1998 and references therein] and PAUR I and II [in summer 1996; Zerefos et al.,2000 references therein]. For the GAA, the air quality reports have showed that there has been agreat improvement in the latest years regarding the pollution levels. This is mostly due the fact thatthe large industries were reallocated from inside the Athens basin to the greater area while more239

CHAPTER 6 - EUROPEstrict legislation were enforced with a number of large units to be equipped with filters. In addition,pollution abatement measures taken by the state authorities during the period 1990-1994,consisting in the replacement of the old technology gasoline-powered private cars and the reductionof the sulphur content in diesel oil, seem to be the primary cause of the improvement in air quality inAthens during the recent years.Kalabokas et al. [1999a; 1999b] analyzed 11 years of observations from the automated localair pollution network operating by the Ministry of Environment. Since 1987, a significant downwardtrend for almost all primary pollutants in all stations was observed. Comparison between the 3-yearperiods 1988-1990 and 1995-1997 gives the highest reduction in the centre of GAA of 52%, 34%,26% and 20% decreases for sulphur dioxide, carbon monoxide, nitrogen oxides and black smoke,respectively, whereas the concentrations of secondary gaseous pollutants (especially Ox = sum ofozone and nitrogen dioxide) appear to have remained essentially at the same levels since 1990.Observations of O 3 prior to 2000 [Kalabokas and Repapis, 2004] at three stations in the GAA andthe surroundings were found to exhibit characteristic seasonal variation of rural ozoneconcentrations with lowest concentrations occurring during winter afternoons with values at about50µg.m -3 in December–January and average summer afternoon values at about 120µg.m -3 inJuly–August, indicating that high summer values were observed all over the area.The latest air quality report of the Ministry of Environment concludes that, except for PMconcentrations, the gaseous pollutants are generally below the EU limits. In the GAA, PM stillshows large exceedences, in contrast to gaseous pollutants. At 3 urban stations, the daily limitvalue for PM was exceeded almost half of the year with the average annual value ranging from 48µg m -3 to 57 µg m -3 . Based on one year (2005-2006) of PM 10 observations at two locations in Athens,Koulouri et al. [2008b] reported that the 24-h limit value of 50 µg m -3 are exceeded 44% of the timeat both sites, far exceeding the compliance with the air quality standard that demands a maximumproportion of exceedences at 9.6 % per year. Furthermore, PM 2.5 concentrations at both stationsexceed the long-existing US-EPA limit value of 15 µg m -3 .6.7.4 Open questions for the areaOpen questions being addressed by current projects such as the EC FP6 projects CIRCEand SESAME and the FP7 project CityZen are: how air pollution sources affect air quality,human/ecosystem health, climate, and visibility, the effects on water resources and evaporation,and how large are the anthropogenic and natural contributions to deposition to ecosystems(acidification, eutrophication, ocean biological productivity). CityZen also investigates futuredevelopment and mitigation options applying state-of-the-art atmospheric models.Under the EU FP7 project CityZen, a number of key observations were performed in theEast Mediterranean with a focus on GIA and Athens as pollution sources and Finokalia (Crete) as apollution receptor location in the area. The new observations in Greater Istanbul Area (GIA) consistof aerosol chemical composition measurements at two sites within GIA and at two sites downwindto identify the main aerosol sources of this Megacity and quantify its role as source of air pollutantsin the area. In parallel, air quality data over Istanbul and other hot-spots in the East Mediterraneanregion for ground based stations and satellite observations are being compiled and analyzed inconjunction with back trajectory analysis and numerical chemistry/transport and climate modellingin order to identify possible trends, the factors that are causing them, and the environmentalconsequences of human impacts in the area. Cutting edge research in the area is investigating therole of Eastern Mediterranean Megacities and hot-spot areas compared to the transport of pollutionon aerosol load and their climatic relevant properties in the Eastern Mediterranean atmosphere.240

ReferencesCHAPTER 6 - EUROPEAmann, M. (2005). A final set of scenarios for the Clean Air For Europe (CAFE) programme. CAFEScenario Analysis Report Nr. 6.In IIASA (Ed.). Laxenburg: Austria.Amann, M., Bertok I., Cofala J., Heyes C., Klimont Z., Rafaj P., Schöpp W., Wagner F. (2008). NECScenario Analysis Report Nr. 6 National Emission Ceilings for 2020 based on the 2008Climate & Energy Package: International Institute for Applied Systems Analysis (IIASA).Andersson, C., Langner J. and R. Bergström. (2007). Interannual variation and trends in airpollution over Europe due to climate variability during 1958-2001 simulated with a regionalCTM coupled to the ERA40 reanalysis. Tellus B, 59, 77-98. doi:10.1111/j.1600-0889.2006.00196.xAndersson, C., Bergström R., Johannson C. (2009). Population exposure and mortality due toregional background PM in Europe – Long-term simulations of source region and shippingcontributions. Atmospheric Environment, 43, 3614-3630Angius S., C. C., Gianelle L.V., Lazzarini M., Tebaldi G., Chiesa M., Cigolini G., Cosenza R., FerrariR., Fregoni A., Gentile N., Ghezzi M., Ledda F., Raddrizzani F. (2009). Rapporto sullaqualita’ dell’aria di Milano e provincia anno 2008. ARPA Lombardia, www.arpalombardia.it.Armijo, R., Meyer, B., Hubert, A., and Barka, A. (1999). Propagation of the North Anatolian fault intothe north Aegean: Timing and kinematics: Geology, 27(267-270)Atlas. (2000). Moscow Ecological Atlas. Moscow Government.Baltensperger, U., Streit, N., Weingartner, E., Nyeki, S., Prévôt, A. S. H., Van Dingenen, R.,Virkkula, A., Putaud, J.-P., Even, A., ten Brink, H., Blatter, A., Neftel, A., and Gäggeler, H.W. (2002). Urban and rural aerosol characterization of summer smog events during thePIPAPO field campaign in Milan, Italy. Journal of Geophysical Research, 107(D22).Bardouki, H., Liakakou, H., Economou, C., Smolik, J., Zdimal, V., Eleftheriadis, K., Lazaridis, M.,Mihalopoulos, N. (2003). Chemical composition of size resolved atmospheric aerosols in theEastern Mediterranean during summer and winter. Atmospheric Environment, 37, 195-208Bäumer, D., & Vogel, B. (2007). An unexpected pattern of distinct weekly periodicities inclimatological variables in Germany. Journal of Geophysical Research, 34(L03819).doi:10.1029/2006GL028559Beekmann, M., & Derognat, C. (2003). Monte Carlo Uncertainty analysis of a regional sale transportchemistry model constrained by measurements from the ESQUIF campaign. Journal ofGeophysical Research, 108, 8559Birmili, W., Schepanski, K., Ansmann, A., Spindler, G., Tegen, I., Wehner, B., Nowak, A., Reimer,E., Mattis, I., Muller, K., Bruggemann, E., Gnauk, T., Herrmann, H., Wiedensohler, A.,Althausen, D., Schladitz, A., Tuch, T., and Löschau, G. (2008). A case of extreme particulatematter concentrations over Central Europe caused by dust emitted over the southernUkraine. Atmospheric Chemistry and Physics, 8, 997-1016. doi: 10.5194/acp-8-997-2008Bruckmann, P., W. Birmili, W. Straub, M. Pitz, D. Gladtke, U. Pfeffer, H. Hebbinghaus, S. Wurzler,A. Olschewski. (2008). An outbreak of Saharan dust causing high PM 10 levels north of theAlps. Gefahrstoffe – Reinhaltung der Luft, 68(Nr. 11/12), 490-498Brunetti, M., Maugeri, M., Monti, F., & Nanni, T. (2006a). Temperature and precipitation variability inItaly in the last two centuries from homogenized instrumental time series. InternationalJournal of Climatology, 26(345-381).Brunetti, M., Maugeri, M., Nanni, T., Auer, I., Bohm, R., & Schoner, W. (2006b). Precipitationvariability and changes in the greater Alpine region over the 1800–2003 period. Journal ofGeophysical Research, 111(D11107). doi: 10.1029/2005JD006674Butler, T. M., Lawrence, M. G., Gurjar, B., Aardenne, J. v., Schultz, M., & Lelieveld, J. (2008). Therepresentation of emissions from megacities in global emissions inventories. AtmosphericEnvironment, 42, 703-719. doi: 10.1016/j.atmosenv.2007.09.060Carslaw, D. C. (2005). Evidence of an increasing NO2/NO X emissions ratio from road trafficemissions. Atmospheric Environment, 39, 4793-4802241

CHAPTER 6 - EUROPECaserini, S., Fraccaroli, A., Monguzzi, A.M., Moretti, M., Giudici, A., Angelino, E., Fossati, G.,Gurrieri, G. (2004, 7-10 June 2004). A Detailed Emission Inventory for Air Quality Planning atthe Local Scale: the Lombardy (Italy). Paper presented at the 13th International EmissionInventory Conference "Working for Clean Air in Clearwater", Clearwater Florida, USA.Charron, A., Harrison, R. M., & Quincey, P. (2007). What are the sources and conditionsresponsible for exceedences of the 24 h PM 10 limit value (50 µg m -3 ) at a heavily traffickedLondon site. Atmospheric Environment, 41(9), 1960. doi: 10.1016/j.atmosenv.2006.10.041Chazette, P., Randriamiarisoa, H., Sanak, J., Couvert, P., and Flamant, C. (2005). Opticalproperties of urban aerosol from airborne and ground based in situ measurements performedduring the ESQUIF program. Journal of Geophysical Research, 110(D02206). doi:10.1029/2004JD004810Chubarova, N. Y., Prilepsky, N. G., Rublev, A. N., & Riebau, A. R. (2009). A Mega-Fire Event inCentral Russia: Fire Weather, Radiative, and Optical Properties of the Atmosphere, andConsequences for Subboreal Forest Plants. Developments in Environmental Science, 8,247-264CIA. (2009). from The World Factbookhttps://www.cia.gov/library/publications/the-world-factbook/fields/2102.html?countryName=&countryCode=&regionCode=rCrabbe, H., Beaumont, R., & Norton, D. (2000). Assessment of Air Quality, Emissions andManagement in a Local Urban Environment. Environmental Monitoring and Assessment, 65,435-442Crutzen, P. J., Elansky N.F., Hahn M., Golitsyn G.S., Brenninkmeijer C.A M., Scharffe D., BelikovI.B., Maiss M., Bergamaschi P., Röckmann T., Grisenko A.M. and Sevostyanov V.M. (1998).Trace gas measurements between Moscow and Vladivostok using the Trans-SiberianRailroad. Atmospheric Chemistry and Physics, 29(2), 179-194Cuvelier, C., Thunis, P., Vautard, R., Amann, M., Bessagnet, B., Bedogni, M., Berkowicz, R.,Brandt, J., Brocheton, F., Builtjes, P., Carnavale, C., Coppalle, A., Denby, B., Douros, J.,Graf, A., Hellmuth, O., Hodzic, A., Honore, C., Jonson, J., Kerschbaumer, A., de Leeuw, F.,Minguzzi, E., Moussiopoulos, N., Pertot, C., Peuch, V. H., Pirovano, G., Rouil, L., Sauter, F.,Schaap, M., Stern, R., Tarrason, L., Vignati, E., Volta, M., White, L., Wind, P., Zuber, A.(2007). CityDelta: A model intercomparison study to explore the impact of emissionreductions in European cities in 2010. Atmospheric Environment, 41(1), 189-207Deguillaume, L., Beekmann, M., & Derognat, C. (2008). Uncertainty evaluation of ozone productionand its sensitivity to emission changes over the Ile-de-France region during summer periods.Journal of Geophysical Research, 113(D02304). doi: 10.1029/2007JD009081Deguillaume, L., Beekmann, M., & Menut, L. (2007). Bayesian Monte Carlo analysis applied toregional scale inverse emission modelling for reactive trace gases. Journal of GeophysicalResearch, 112(D02307). doi: 10.1029/2006JD007518Derognat, C. (2002). Pollution photooxydante à l’échelle urbaine et interaction avec l’échellerégionale. Doctorate University Pierre et Marie Curie.Derognat, C., Beekmann, M., Bäumle, M., Martin, D., & Schmidt, H. (2003). Effect of biogenic VOCemissions on the tropospheric chemistry during elevated ozone periods in Ile de France.Journal of Geophysical Research, 108, 8560Dollard, G. J., Dumitrean, P., Telling, S., Dixon, J., & Derwent, R. G. (2007). Observed trends inambient concentrations of C2-C8 hydrocarbons in the United Kingdom over the period from1993 to 2004. Atmospheric Environment, 41, 2559-2569Elansky, N. F. (Editor), (2006). Mobile observatory TROICA and observations of the atmosphericcomposition over Russia. Moscow: SATURN, Institute of Atmospheric Physics of the RussianAcademy of Sciences. 46 p. (in Russian).European Commission. (2004). Commission Decision of 19 March 2004 concerning guidance forimplementation of Directive 2002/3/EC of the European Parliament and of the Council relatingto ozone in ambient air. Journal of the European Union, L87(50).Ezber, Y., Sen, O. L., Kindap, T., & Karaca, M. (2007). Climatic effects of urbanization in Istanbul: astatistical and modeling analysis. international Journal of Climatology, 27(667-679)242

CHAPTER 6 - EUROPEFalkovich, A. H., Schkolnik, G., Ganor, E., & Rudich, Y. (2004). Adsorption of organic compoundspertinent to urban environments onto mineral dust particles. Journal of GeophysicalResearch, 109(D02208). doi: 10.1029/2003JD003919Finardi, S., De Maria, R., D’Allura, A., Cascone, C., Calori, G., and Lollobrigida, F. (2008). ADeterministic Air Quality Forecasting System For Torino Urban Area, Italy. EnvironmentalModelling and Software, 23(344-355).Finardi, S., & Pellegrini, U. (2004). Systematic Analysis of Meteorological Conditions CausingSevere Urban Air Pollution Episodes In The Central Po Valley. Paper presented at the 9thInternational Conference on Harmonisation within Atmospheric Dispersion Modelling forRegulatory Purposes, Garmisch-Partenkirchen, Germany.Forkel, R., & Knoche, R. (2007). Nested regional climate–chemistry simulations for central EuropeSimulations imbriquées climat régional–chimie pour l’Europe centrale. Comptes RendusGeosciences, 339(11-12), 734-746. doi: 10.1016/j.crte.2007.09.018Fotiadi, A., Hatzianastassiou, N., Drakakis, E., Matsoukas, C., Pavlakis, K. G., Hatzidimitriou, D.,Gerasopoulos, E., Mihalopoulos, N., , & Vardavas, I. (2006). Aerosol physical and opticalproperties in the Eastern Mediterranean Basin, Crete, from Aerosol Robotic Network data.Atmospheric Chemistry and Physics, 6(5399-5413).Franze, T., Weller, M. G., Niessner, R., and Pöschl, U. (2005). Protein Nitration by Polluted Air.Environmental Science and Technology 39, 1673-1678. doi: 10.1021/es0488737Fuller et al, G. (2007). Air Quality in London, King's College London, London.Fuller, G. W., & Green, D. (2006). Evidence for increasing concentrations of primary PM 10 inLondon. Atmospheric Environment, 40, 6134-6145Gangoiti, G., Alonso, L., Navazo, M., Garcia, J.A., Millan, M. (2006). North African soil dust andEuropean pollution transport to America during the warm Seaton: Hidden links shown by apassive tracer simulation. Journal of Geophysical Research, 111(D10109). doi:10.1029/2005JD005941Gerasopoulos, E., Kouvarakis, G., Vrekoussis, M., Kanakidou, M., Mihalopoulos, N. (2005). Ozonevariability in the marine boundary layer of the Eastern Mediterranean based on 7-yearobservations. Journal of Geophysical Research, 110. doi: 10.1029/2005JD005991Gerasopoulos, E., Kouvarakis G., Babasakalis P., Vrekoussis M., Putaud J.-P., Mihalopoulos N.(2006). Origin and variability of particulate matter (PM 10 ) mass concentrations over theEastern Mediterranean. Atmospheric Environment, 40(25), 4679-4690Gerasopoulos, E., Koulouri, E., Kalivitis, N., Kouvarakis, S., Makela, T., Hillamo, R., Mihalopoulos,N. (2007). Size-segregated mass distributions of aerosols over Eastern Mediterranean:seasonal variability and comparison with AERONET columnar size-distributions. AtmosphericChemistry and Physics, 7, 2551-2561Ginzburg, A. (2000). Moscow City Environmental Profile. LEAD CIS Program, Moscow (in Russian).Grice, S., Stedman, J., Kent, A., Hobson, M., Norris, J., Abbott, J., & Cookea, S. (2009). Recenttrends and projections of primary NO2 emissions in Europe. Atmospheric Environment, 43,2154-2167. doi: 10.016/j.atmosenv.2009.01.019Gros, V., Sciare, J., and Yu, T. (2007). Air Quality Air-quality measurements in megacities: Focuson gaseous organic and particulate pollutants and comparison between two contrasted cities,Paris and Beijing. C. R. Geoscience. doi: 10.1016/j.crte.2007.08.007Gülsoy, G., Tayanç, M. and Ertürk, F. (1999). Chemical analysis of the major ions in theprecipitation of Istanbul, Turkey. Environmental Pollution, 105, 273-280Gurjar, B. R., Butler T.M., Lawrence M.J., Lelieveld J. (2008). Evaluation of emissions and airquality in megacities. Atmospheric Environment, 42, 1693-1606. doi:10.1016/j.atmosenv.2007.10.048Guttikunda, S. K., Tang, Y., Carmichael, G.R., Kurata, G., Pan, L., Streets, D.G., Woo, J.H.,Thongboonchoo, N., Fried, A. (2005). Impacts of Asian megacity emissions on regional airquality during spring 2001. Journal of Geophysical Research, 110. doi:10.1029/2004JD004921243

CHAPTER 6 - EUROPEHodzic A., C. H., Chazette P., Beekmann M., Bessagnet B., Drobinski P., Goloub P., Haeffelin M.,Morille Y., Vautard R. (2004). Comparison of aerosol chemistry-transport model simulationswith lidar and sun-photometer observations at a site near Paris. Journal of GeophysicalResearch, 109(D23201). doi: 10.1029/2004JD004735Hoffmann, B., Moebus A., Möhlenkamp S., Stang A., Lehmann N., Dragano N., Schmermund A., M.Memmesheimer, Mann K., Erbel R., Jöckel K.-H. (2007). Residential exposure to traffic isassociated with coronary atherosclerosis. Circulation, 116, 489-496. doi:10.1161/CIRCULATIONAHA.107.693622Hubert-Ferrari, A., Armijo R., King G., Meyer B. and Barka A. (2002). Morphology, displacement,and slip rates along the North Anatolian Fault, Turkey. Journal of Geophysical Research,107(B10). doi: 10.1029/2001JB000393Hudson, R. D., Frolov, A.D., Andrade, M.F., Follette, M.B. (2003). The total ozone field separatedinto meteorological regimes. Part I: defining the regimes. Journal of Atmospheric Sciences,60(14), 1669-1677Im, U., Tayanç, M., Yenigün, O. (2006). Analysis of major photochemical pollutants withmeteorological factors for high ozone days in Istanbul, Turkey. Water, Air, and Soil Pollution,175, 335-359Im, U., Markakis, K., Unal, A., Kindap, T., Poupkou, A., Incecik, S., Yenigun, O., Melas, D.,Theodosi, C., Mihalopoulos, N. (2010). Study of a winter PM episode in Istanbul using highresolution WRF/CMAQ modeling system. Atmospheric Environment, 44, 3085-3094Im, U., Tayanç M. & Yenigün, O. (2008). Interaction patterns of major photochemical pollutants inIstanbul, Turkey. Atmospheric Research. doi: 10.1016/j.atmosres.2008. 03.015Kalabokas, P.D., Viras L.G., Repapis C.C (1999a). Analysis of 11-year record (1987-1997) of airpollution measurements in Athens, Greece, Part I: primary air pollutants Global Nest: theInternational Journal, 1(3), 157-167Kalabokas, P., D., Viras, L.G., Repapis C.C., Bartzis, J.G. . (1999b). Analysis of 11-year record(1987-1997) of air pollution measurements in Athens, Greece, Part II: Photochemical airpollutants. Global Nest: the International Journal 1(3), 169-176Kalabokas, P. D., Volz-Thomas, A., Brioude, J., Thouret, V., Cammas, J.-P., and Repapis, C. C. .(2007). Vertical ozone measurements in the troposphere over the Eastern Mediterranean andcomparison with Central Europe. Atmospheric Chemistry and Physics, 7, 3783-3790Kalabokas, P. D., & Repapis, C. C. (2004). A climatological study of rural surface ozone in centralGreece. Atmospheric Chemistry and Physics, 4, 1139–1147Kalivitis, N., Gerasopoulos, E., Vrekoussis, M., Kouvarakis, G., Kubilay, N., Hatzianastassiou, N.,Vardavas, I., Mihalopoulos, N. . (2007). Dust transport over the Eastern Mediterranean fromTOMS, AERONET and surface measurements. Journal of Geophysical Research,112(D03202). doi: 10.1029/2006JD007510Kallos, G., Astitha, M., Katsafados, P., & Spyrou, C. (2007). Long-range transport ofanthropogenically and naturally produced particulate matter in the Mediterranean and NorthAtlantic: Current state of knowledge. Journal of Applied Meteorology and Climatology, 46,1230-1251Kanakidou, M., Mihalopoulos, N, Kalivitis, N, Tsigaridis, K, Kouvarakis, G, Koulouri, E,Gerasopoulos, E, Vrekoussis, M, Myriokefalitakis, S. (2007). Natural contributions toparticulate matter levels over Europe – the experience from Greece. In CEST2007:A-585-592, http://www.srcosmos.gr/ srcosmos/showpub.aspx?aa=9717Karaca, F., Alagha, O and Erturk, F. (2005). Statistical characterization of atmospheric PM 10 andPM 2.5 concentrations at a non-impacted suburban site of Istanbul, Turkey. Chemosphere,59(8)Karaca, F., & Camci, F. (2010). Distant source contributions to PM 10 profile evaluated by SOMbased cluster analysis of air mass trajectory sets. Atmospheric Environment, 44(7), 892-899doi: 10.1016/j.atmosenv. 2009.12.006244

CHAPTER 6 - EUROPEKaraca, M., Tayanç, M., & Toros, H. (1995). The effects of urbanization on climate of Istanbul andAnkara: a first study. Atmospheric Environment Part B-Urban Atmosphere, 29(23),3411–3421Kasimov, N. S., & Kurbatova, A. S., V.N. Bashkin, M.S. Myagkov, D.S. Sasvin. (2004). Ecologicalsolutions in Moscow megapolis. Smolensk: Madjzenta.Katsouyanni, K. (1995). Health Effects of Air Pollution in Southern Europe: Are There InteractingFactors? Environmental Health Perspectives, 103(S2), 23-2Kidnap, T. (2008). Identifying the Trans-Boundary Transport of Air Pollutants to the City of IstanbulUnder Specific Weather Conditions. Water Air Soil Pollution 189, 279–289. doi:10.1007/s11270-008-9618-yKindap, T., Unal, A., Chen, S., Hu, Y., Odman, M., & Karaca, M. (2006). Long-range aerosoltransport from Europe to Istanbul, Turkey. Atmospheric Environment, 40, 3536–3547Koçak, M., N., M., & Kubilay, N. (2007). Contributions of natural sources to high PM 10 and PM 2.5events in the eastern Mediterranean. Atmospheric Environment, 41(18), 3806- 3818Koçak, M., N., Theodosi Ch., C. T., P. Zarmpas, U. Im, A. Bougiatioti, O. Yenigun, & Mihalopoulos,N. (2010). Particulate matter (PM 10 ) in Istanbul: Origin, source areas and potential impact onsurrounding regions. Atmospheric Environment, In Press. doi:10.1016/j.atmosenv.2010.10.007Koulouri, E., Grivas, G., Gerasopoulos, E., Chaloulakou, A., Mihalopoulos, N., & Spyrellis, N.(2008b). Study of size-segregated particle (PM 1 , PM 2.5 , PM 10 ) concentrations over Greece.Global NEST Journal 10, 10(2), 132-139Koulouri, E., Saarikoski, S., Theodosi, C., Markaki, Z., Gerasopoulos, E., Kouvarakis, G., Makela,T., Hillamos, R., and Mihalopoulosa, N. (2008a). Chemical Composition and sources of fineand coarse aerosol particles in the Eastern Mediterranean. Atmospheric Environment, 42,6542–6550. doi: 10.1016/j.atmosenv.2008.04.010Kourtidis, K. (2002). Regional levels of ozone in the troposphere over eastern Mediterranean.Journal of Geophysical Research, 107(D18). doi: 10.1029/ 2000JD000140Kouvarakis, G., Mihalopoulos N., Tselepides T., Stavrakakis S. (2000). Temporal variations ofsurface regional background ozone over Crete Island in the southeast Mediterranean. Journalof Geophysical Research, 105(D4), 4399–4407Kouvarakis, G., & Mihalopoulos, N. (2002). Seasonal variation of dimethylsulfide in the gas phaseand of methanesulfonate and non-sea–salt sulfate in the aerosols phase in the EasternMediterranean atmosphere. Atmospheric Environment, 36(6), 929–938Kouvarakis, G., Mihalopoulos, N., Tselepides, T., & Stavrakakis, S. (2001). On the importance ofatmospheric nitrogen inputs on the productivity of Eastern Mediterranean Sea. GlobalBiogeochem Cycles, 15, 805-818Kukkonen, J. M., Pohjola, R. S., Sokhi, L., Luhana, N., Kitwiroon, M., Rantamäki, E., Berge, V.,Odegaard, L. H., Slørdal, B., Denby, & Finardi, S. (2005). Analysis and evaluation oflocal-scale PM 10 air pollution episodes in four European cities, Oslo, Helsinki, London andMilan. Atmospheric Environment, 39(2759-2773).Kunkel, D., Lawrence M.G., Tost H., Kerkweg A., Jöckel P. and Borrmann S. (2011). Urbanemission hot-spots as sources for remote aerosol deposition, submitted to Geophys. Res.Lett.LAQN. (2006). Air quality in London. Report 14, 2006-7, www.londonair.org.uk.Lawrence, M. G., Butler T.M., Steinkamp J., Gurjar B.R. and Lelieveld J. (2007). Regional pollutionpotentials of megacities and other major population centers. Atmospheric Chemistry andPhysics, 7, 3969-3987Lelieveld, J., Berresheim, H., Borrmann, S., Crutzen, P. J., Dentener, F. J., Fischer, H., Feichter, J.,Flatau, P.J., Heland, J., Holzinger, R., Korrmann, R., Lawrence, M.G., Levin, Z., Markowicz,K.M., Mihalopoulos, N., Minikin, A., Ramanathan, V., de Reus, M., Roelofs, G.J., Scheeren,H.A., Sciare, J., Schlager, H., Schultz, M., Siegmund, P., Steil, B., Stephanou, E.G., Stier, P.,Traub, M., Warneke, C., Williams, J., and Ziereis, H. (2002). Global air pollution crossroadsover the Mediterranean. Science, 298, 794–799. doi: 10.1126/science.1075457245

CHAPTER 6 - EUROPELondon, T. f. Cleaner air for Greater London: “The Low Emission Zone is now in operation”.www.tfl.gov.uk/lezlondon.Markakis, K., Poupkou, A., and Melas, D., Tzoumaka., P and Petrakakis, M. (2010a). Acomputational approach based on GIS technology for the development of an anthropogenicemission inventory for air quality applications in Greece. Water, Air & Soil Pollution, 207,157–180. doi: 10.1007/s11270-009-0126-5Markakis, K., Poupkou, A., and Melas, D. and Zerefos, C. (2010b). A GIS based methodology forthe compilation of an anthropogenic PM 10 emission inventory in Greece. EnvironmentalPollution Research, 1(2), 71-81Markakis, K., Im, U., Unal, A., Melas, D., Yenigun, O., & Incecik, S. (2009, March 2009). Acomputational approach for the compilation of a high spatially and temporally resolvedemission inventory for the Istanbul Greater Area. Paper presented at the 7th InternationalConference on Air Quality Science and Application, Istanbul.Mattai, J., & Hutchinson, D. (2008). London Atmospheric Emissions Inventory 2004 Report, GreaterLondon Authority, London.Melas, D., Ziomas I.C., Zerefos Ch S. (1995). Boundary layer dynamics in an urban coastalenvironment under sea breeze conditions. Atmospheric Environment, 29(24), 3605-3617Memmesheimer, M., Friese, E., Ebel, A., Jakobs, H.J., Feldmann, H., Kessler, C., Piekorz, G.(2004). Long-term simulations of particulate matter in Europe on different scales usingsequential nesting of a regional model. International Journal for Environment and Pollution,22, 108-132Memmesheimer, M., Wurzler, S., Friese, E., Jakobs, H.J., Feldmann, H., Ebel, A., Kessler, C.,Geiger, J., Hartmann, U., Brandt, A., Pfeffer, U., Dorn, H. P. (2007). Long-term simulations ofphoto-oxidants and particulate matter over Europe with emphasis on North-Rhine-Westphalia.Developments in Environmental Sciences, 6, 158-167. doi: 10,1016/S1474-8177(07)06028-7Memmesheimer, M. (2009). Air pollution in the Benelux/Rhine-Ruhr area: Scenarios andinterannual variations based on model calculations. Paper presented at the AQM, Istanbul.Menut, L. (2003). Adjoint modelling for atmospheric pollution processes sensitivity at regional scaleduring the ESQUIF IOP2. Journal of Geophysical Research, 108(D17). doi:10.1029/2002JD002549Menut L., V. R., Flamant C., Abonnel C., Beekmann M., Chazette P., Flamant P.H., Gombert D.,Guedalia D., Kley D., Lefebre M.P., Lodsec. B., Martin D., Mégie G., Perros P., Sicard M.,Toupance G. (2000). Measurements and modelling of atmospheric pollution over the Parisarea: an overview of the ESQUIF Project. Annales Geophysicae 18, 1467-1481Mihalopoulos, N., Stephanou E., Kanakidou M., Pilitsidis S. and Bousquet P. (1997). Troposphericaerosol ionic composition above the eastern Mediterranean area. Tellus B, 49, 314– 326.Mitsakou, C., Kallos, G., Papantoniou, N., Spyrou, C., Solomos, S., Astitha, M., and Housiadas, C.(2008). Saharan dust levels in Greece and received inhalation doses. AtmosphericChemistry and Physics, 8, 7181-7192OECD. (2006). OECD Territorial Reviews: Milan, Italy.OECD. (2008). OECD Territorial Reviews Vol.http://browse.oecdbookshop.org/oecd/pdfs/browseit/0408051E.PDFOzdemir, H., Im, U., Kostandinos, M., Agacayak, T., Unal, A., Kindap, T., & Kha, M. (2009, 19-21October 2009). Impacts of Istanbul emissions on regional air quality: Quantification usingmodel-3 framework and trajectory analysis. Paper presented at the 8th Annual CMASConference, Chapel Hill, NC.Papayannis, A., Amiridis, V., Mona, L., Tsaknakis, G., Balis, D., Bosenberg, J., Chalkovski, A., DeTomasi, F., Grigorov, I., Mattis, I., Mitev, V., Muller, D., Nickovic, S., Perez, C., Pietruczuk, A.,Ravetta, F., Rizi, V., Sicard, M., Tricki, T., Wiegner, M., Gerding, M., Mamouri, R.E., D’Amico,G.D., and Pappalardo, G. (2008). Systematic lidar observations of Saharan dust over Europein the frame of EARLINET (2000–2002). Journal of Geophysical Research, 113(D10204). doi:10.1029/2007JD009028246

CHAPTER 6 - EUROPEPapayannis, A., Balis, D., Amiridis, V., Chourdakis, G., Tsaknakis, G., Zerefos, C., Castanho,A.D.A., Nickovic, S., Kazadzis, S, and Grabowski, J. (2005). Measurements of Saharan dustaerosols over the Eastern Mediterranean using elastic backscatter-Raman lidar,spectrophotometric and satellite observations in the frame of the EARLINET project.Atmospheric Chemistry and Physics, 5, 2065-2079Pison, I., Menut, L., & Blond, N. (2006). Inverse modeling of emissions for local photo-oxidantpollution: Testing a new methodology with kriging constraints. Annales Geophysicae, 24,1523-1535Querol, X., Alastuey, A., Pey, J., Cusack, M., Pérez, N., Mihalopoulos, N., Theodosi, C.,Gerasopoulos, E., Kubilay, N., and Koçak, M. (2009). Variability in regional backgroundaerosols within the Mediterranean. Atmospheric Chemistry Physics 9, 4575-4591Raut, J.-C., & Chazette, P. (2008). Vertical profiles of urban aerosol complex refractive index in theframe of ESQUIF airborne measurements. Atmospheric Chemistry and Physics, 8, 901-919Report. (2002). Report on the state of the environment of Moscow in 2000-2001 L.A. Bochina.Moscow: Moscow Government: Department of Nature Management and EnvironmentProtection.Report. (2008). Report on the state of the environment of Moscow in 2007 MosEkoMonitoring.Moscow: Moscow Government: Department of Nature Management and EnvironmentProtection.Report. (2009). Report on the state of the environment of Moscow in 2008. Moscow: MoscowGovernment: Department of Nature Management and Environment Protection.Riemer, N., Vogel, H., Vogel, B., & Fiedler, F. (2003). Modeling aerosols on the mesoscale-γ:Treatment of soot aerosol and its radiative effects. Journal of Geophysical Research,108(D19). doi: 10.1029/2003JD003448Rodriguez, S., Querol, X., Alastuey, A., Viana, M., Alarcon, M., Mantilla, E., & Ruiz, C. (2004).Comparative PM 10 -PM 2.5 source contribution study at rural, urban and industrial sites duringPM episodes in Eastern Spain. Science of the Total Environment, 328, 95-113Rosenfeld, D. (2000). Suppression of rain and snow by urban and industrial pollution. Science, 287,1793-1796Sciare, J., d’Argouges O., Zhang Q., Sarda-Estève R., Gaimoz C., Gros V., Beekmann M. andSanchez O. (2010). Comparison between simulated and observed chemical composition offine aerosols in Paris (France) during springtime: contribution of regional versus continentalemissions. Atmospheric Chemistry and Physics, 10, 16861–16900. doi:10.5194/acpd-10-16861-2010Silibello, C., Calori G., Brusasca G., Giudici A., Angelino E., Fossati G., Peroni E., Buganza E.(2008). Modelling of PM 10 Concentrations Over Milano Urban Area Using Two AerosolModules. Environmental Modelling and Software, 23(333-343).Sillman, S., Vautard, R., L. Menut, & Kley, D. (2003). O3-NO X -VOC sensitivity and NO X -VOCindicators in Paris: Results from models and Atmospheric Pollution Over the Paris Area(ESQUIF) measurements. Journal of Geophysical Research, 108(D17). doi:10.1029/2002JD001561Stein, R. S., Barka, A., & Dieterich, J. H. (1997). Progressive failure on the North Anatolian Faultsince 1989 by earthquake stress triggering. Geophysical Journal International, 128, 594-604Stern, R., Builtjes, P., Schaap, M., Timmermans, R., Vautard, R., Hodzic, A., Memmesheimer, M.,Feldmann, H., Renner, E., Wolke, E., and Kerschbaumer, A. (2008). A modelinter-comparison study focussing on episodes with elevated PM 10 concentrations.Atmospheric Environment, 42(19), 4567-4588. doi: 10.1016/j.atmosenv.2008.01.068Stortini, M., Deserti, M., Bonafe, G., & Minguzzi, E. (2007). Long-term simulation and validation ofozone and aerosol in the Po Valley. Developments in Environmental Sciences, 6(2007),768-770Tayanç, M. (2000). An assessment of spatial and temporal variation of sulfur dioxide levels overIstanbul, Turkey. Environmental Pollution Research, 107, 61–69247

CHAPTER 6 - EUROPETebaldi, G., Angius, S., Lazzarini, M., Gianelle, L. V., Fusari, G., Fregoni, A., Nicola, G. (2007).Rapporto sulla qualita’ dell’aria di Milano e provincia. Anno 2006, http://www.arpalombardia.it.Theodosi, C., Im, U., Bougiatioti, A., Zarmpas, P., Yenigun, O., & Mihalopoulos, N. (2010). Aerosolchemical composition over Istanbul. Science of the Total Environment, 408(12), 2482-2491Thiruchittampalam, B., Köble, R., Theloke, J., Kummer, U., Geftler, T., Wagner, S., Friedrich, R.(2008, November 2008). High spatial and temporal resolution of emissions in Europe. Paperpresented at the TFEIP Workshop, Milan.Tragou, E., & Lascaratos, A. (2003). Role of aerosols on the Mediterranean solar radiation. Journalof Geophysical Research, 108. doi: 10.1029/2001JC001258TUIK. from http://www.tbb.org.tr/Dosyalar/Arastirma_ve_Raporlar/kureseel_demografik.pdfU.N. (2006). World Urbanization Prospects: The2005 Revision. Work Paper No ESA/P/WP/200,United Nations, Department of Economics and Social Affairs, Population Division.http://www.un.org/esa/population/publications/WUP2005/2005 wup.htm.UN-HABITAT. (2006). State of the World's Cities 2006/7: The Millennium Development Goals andUrban Sustainability: 30 Years of Shaping the Habitat Agenda.UNEP-WHO. (1992). Urban Air Pollution in Megacities of the World. From Blackwell, Oxford, UK.UNFPA. (2007). State of World Population 2007: Unleashing the Potential of Urban Growth.Vasiliev, A. A., & Liakhov, A. A. (2000). Moscow – status and development prospects for ahydrometeorological information system for the megapolis. WMO Bulletin, 49(4), 332-336Vautard, R., Menut L., Beekmann M., Chazette P., Flamant P.H., Gombert D., Guedalia D., Kley D.,Lefevre m.p., Martin D., Megie G., Perros P., Toupance G. (2003a). A synthesis of theESQUIF field campaign. Journal of Geophysical Research, 108.Vautard, R., Szopa S., Beekmann M., Menut L., Hauglustaine D.A., Rouil L., Roemer M. (2006). Aredecadal anthropogenic emission reductions in Europe consistent with surface ozoneobservations. Journal of Geophysical Research, 33(L13810). doi: 10.1029/2006GL026080Vautard, R., Yiou P., van Oldenborgh G.J. (2009). Decline of fog, mist and haze in EuropeNatureGeoscience 2, 115-119. doi: 10.1038/ngeo414Vautard, R., Builtjes, P. H. J., Thunis, P., Cuvelier, C., Bedognie, M., Bessagnet, B., Honore, C.,Moussiopoulos, N., Pirovano, G., Schaap, M., Stern, R., Tattason, L., and Wind, P. (2007).Evaluation and intercomparison of Ozone and PM 10 simulations by several chemistrytransport models over four European cities within the CityDelta project. AtmosphericEnvironment, 41, 173-188. doi: 10.1016/j.atmosenv.2006.07.039Vautard, R., & Martin D., M. B., Drobinsky P., Friedrich R., Jaubertie A., Kley D., Lauttati M., MoralP., Neininger B., and Thelocke J. (2003b). Paris emission inventory diagnostics from theESQUIF airborne measurements and a chemical transport model. Journal of GeophysicalResearch, 108.Vautard, R., Honore´ C., Beekmann M., & Rouil, L. (2005). Simulation of ozone during the August2003 heat wave and emission control scenarios. Atmospheric Environment, 39, 2957– 2967.Vestreng, V. (2004). Emission data reported to CLRTAP and the NEC Directive, EMEP/EEA JointReview Report. In I. R. 2004 (Ed.), EMEP/MSC-W Note 1.Vestreng, V. (2006a). Emission data reported to the LRTAP Convention and NEC directive. In I. R.2006 (Ed.), Evaluation of inventories of HMs and POPs.Vestreng, V., Myhre G., Fagerli H., Reis S., Tarrason L. (2007). Twenty-five years of continuoussulphur dioxide emission reduction in Europe. Atmospheric Chemistry and Physics, 7, 3663– 3681Vestreng, V., Rigler, E., Adams, M., Kindbom, K., Pacyna, J. M., van der Gon, H. D. r, Travnikov, O.(2006b). Inventory Review 2006, Emission Data reported to LRTAP Convention and NECDirective, Initial review of HMs and POPs Technical report MSC-W 1/2006.Vrekoussis, M., Gerasopoulos, E., Mihalopoulos, N., & Im, U. (2009, 24-27 March 2009). Spatialand temporal variability NO2 mixing ratios inferred from satellite and ground-basedobservations above SE Europe: Role of Megacities. Paper presented at the 7th InternationalConference on Air Quality –Science and Application, Istanbul.248

CHAPTER 6 - EUROPEVrekoussis, M., Liakakou, E., Kocak, M., Kubilay, N., Oikonomou, K., Sciare, J., & Mihalopoulos, N.(2005). Seasonal variability of optical properties of aerosols in the Eastern Mediterranean.Atmospheric Environment, 39, 7083–7094.Vrekoussis, M., Liakakou, N., Mihalopoulos, M., Kanakidou, P. J., Crutzen, J., & Lelieveld. (2006).Formation of HNO3 and NO3- in the anthropogenically-influenced eastern Mediterraneanmarine boundary layer. Geophysical Research Letters, 33(L05811). doi: 10.1029/2005GL025069World Health Organization (WHO), (2006). The World Health Report 2006http://www.who.int/whr/2006/annex/06_annex1_en.pdfWorld Health Organization (WHO), (2008). Atlas of Health in Europe. 2nd editions.Zanobetti, A., Schwartz, J., Samoli, E., Gryparis, A., Touloumi, G., Atkinson, R., Le Tertre, A.,Bobros, J., Celko, M., Goren, A., Forsberg, B., Michelozzi, P., Rabczenko, D., Aranguez Ruiz,E., and Katsouyanni, K. (2002). The Temporal Pattern of Mortality Responses to Air Pollution:A Multicity Assessment of Mortality Displacement. Epidemiology, 13(1), 87-93Zerefos, C., Ganev, K., Kourtidis, K., Tzortziou, M., A. Vasaras, & Syrakov, E. (2000). On the originof SO2 above northern Greece. Geophysical Research Letters, 27, 365– 368Zerefos, C.S., Kourtidis K.A., Balis D., Bais A. and Calpini B. (2001). Photochemical Activity Overthe Eastern Mediterranean Under Variable Environmental Conditions Phys. Chem. Earth (C).26, 7, 549-554Ziomas, I. C. (1998). The Mediterranean campaign of photochemical tracers-transport and chemicalevolution (MEDCAPHOT-TRACE): an outline. Atmospheric Environment, 32(12), 2045-2053_______249

CHAPTER 7 - OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESCoordinating Author: Tong Zhu (1)Contributing Authors: Mark Lawrence (2) , Michael Gauss (3) , David Parrish (4) , Luisa Molina (5,6) , Laura Gallardo (7) , PatriciaRomero-Lankao (8) , Yutaka Kondo (9) , Nobuyuki Takegawa (9) , Yuanhang Zhang (1) , Cathy Liousse (10) , Liisa Jalkanen (11)and Greg Carmichael (12)(1)College of Environmental Sciences and Engineering, Peking University, Beijing, China(2)Institute for Advanced Sustainability Studies, Potsdam, Germany(3)Norwegian Meteorological Institute, Oslo, Norway(4)NOAA ESRL Chemical Sciences Division, Boulder, CO, USA(5)Molina Center for Strategic Studies in Energy and the Environment (MCE2), La Jolla, CA(6)Department of Earth, Atmospheric and Planetary Sciences, MIT, Cambridge, MA(7)Departamento de Geofísica & Centro de Modelamiento Matemático, Universidad de Chile, Santiago, Chile(8)NCAR, Research Applications Laboratory, Boulder, CO, USA(9)Department of Earth and Planetary Science, Graduate School of Science, University of Tokyo(10)Laboratoire d’Aérologie, CNRS-UPS, Toulouse, France(11)World Meteorological Organization, Geneva, Switzerland(12)University of Iowa, USAIn this chapter we briefly describe a number of projects, usually international, intended toimprove our understanding of air pollution and its impacts, including policy relevant aspects. Thisreview is not exhaustive but reflects current efforts. Figure 1 shows the locations of these researchactivities.Figure 1 - The locations of the international collaborative research activities described in this chapter.ADAPTE: Adaptation to health impacts of air pollution and climate extremes in Latin American cities; CalNex 2010: AirQuality and Climate Change Field Study in California in 2010; CAREBeijing: Campaigns of Air Quality Research in Beijingand Surrounding Regions; CityZen: megaCITY–Zoom for the Environment; ICARTT: The International Consortium forAtmospheric Research on Transport and Transformation; IMPACT: Integrated Measurement Programme for Aerosol andoxidant Chemistry in Tokyo; MILAGRO: Megacity Initiative: Local and Global Research Observations, Mexico City;MEGAPOLI: Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integratedtools for assessment and mitigation; PRIDE-PRD: Programme of Regional Integrated Experiments of Air Quality over PearRiver Delta; SAEMC: the South American Emissions Megacities and Climate250

7.1 MEGAPOLICHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESMEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution andclimate effects, and Integrated tools for assessment and mitigation), funded by the European Unionthrough Framework Programme 7, brings together leading European research groups,state-of-the-art scientific tools and key players from other countries to investigate the interactionsamong megacities, air quality and climate. The project was coordinated by Alexander Baklanov(DMI, Denmark), with co-coordinators Spyros Pandis (FORTH, Greece) and Mark Lawrence (MPIC,Germany). A total of 23 groups from 11 countries in Europe were funded by the project. In addition,the MEGAPOLI framework has led to support from individual institutions and/or national fundingagencies for further scientific contributions to the project, such as a field campaign in Paris.The MEGAPOLI project bridges the spatial and temporal scales that connect local emissions, airquality and weather with global atmospheric chemistry and climate. The main objectives were:1. To assess impacts of megacities and large air-pollution hot-spots on local, regional andglobal air quality,2. To quantify feedbacks among megacity air quality, local and regional climate, and globalclimate change,3. To develop improved integrated tools for prediction of air pollution in megacities.In order to achieve these objectives, the partners of the project have undertaken various activities:• Develop and evaluate integrated methods to improve megacity emission data• Investigate physical and chemical processes starting from the megacity street level,continuing to the city, regional and global scales• Assess regional and global air quality impacts of megacity plumes• Determine the main mechanisms of regional meteorology/climate forcing due to megacityplumes• Assess global megacity pollutant forcing on climate• Examine feedback mechanisms including effects of climate change on megacity air quality• Develop integrated tools for prediction of megacity air quality• Evaluate these integrated tools and use them in case studies• Develop a methodology to estimate the impacts of different scenarios of megacitydevelopment on human health and climate change• Propose and assess mitigation options to reduce the impacts of megacity emissionsThese tasks were organized into nine WorkPackages, which are depicted in Figure 2, alongwith their interrelationships. Within MEGAPOLI, a pyramid strategy (see Figure 3) followed byundertaking detailed measurements in one European megacity, Paris, performing detailed analysisfor a subset of MPCs selected from 12 potential candidates with existing air quality datasets, andinvestigating the effects of all megacities on global atmospheric chemistry and climate. The resultswere disseminated to authorities, the policy community, researchers and the other stakeholders inthe corresponding megacities.The funding for MEGAPOLI ended in September 2011; the analysis of the project results,including model simulations and the Paris field campaign data, is on-going and being published in afinal report for the project, and in various journal papers, including two special issues inAtmospheric Chemistry and Physics, one for the "Megapoli-Paris 2009/2010 campaign"[http://www.atmos-chem-phys.net/special_issue248.html], and another titled “Megacities: air qualityand climate impacts from local to globalscales"[http://www.atmos-chem-phys.net/special_issue229.html], growing out of studies presentedin the annual megacity sessions of the EGU general assembly (including results from MEGAPOLI,CITYZEN and MILAGRO, among others discussed below).251

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESFigure 2 - Depiction of the Work Packages and their organization within MEGAPOLIFigure 3 - The pyramid of megacities examined within MEGAPOLI; the project addressed practically all major megacitiesaround the globe at three different levels of detail252

7.2 CITYZENCHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESThe CityZen project (megaCITY - Zoom for the ENvironment), funded by the EuropeanUnion through Framework Programme 7, investigated air pollution distribution and change in andaround selected megacities and emission hotspots for the last decade and the 3-year period of theproject (2008-2011). Long-term satellite observations, in-situ measurements, and a series ofdifferent scale models (local-regional-global) were employed in order to analyze the impacts of airpollution hot spots on regional and global air quality. Potential future changes were studied basedon various mitigation and climate change scenarios. CityZen chose four focus areas: 1) TheEastern Mediterranean including Istanbul, Athens and Cairo, 2) the Po Valley including Milan,Genova, and Torino, 3) the Ruhr region in West-Germany together with the BeNeLux area, and 4)the Pearl River Delta with the major cities being Guangzhou, Shenzhen, and Hong Kong. In addition,the hot and polluted European summers of 2003 and 2007 were chosen for intensive case studies.The project included a total of 16 partners from 11 countries in Europe, Africa, and Asia andwas coordinated by the Norwegian Meteorological Institute. Similar to MEGAPOLI, the CityZenproject aimed at bridging the spatial and temporal scales that connect local emissions, air qualityand weather with global atmospheric chemistry and climate. The main objectives for CityZen wereto:• Quantify and understand current air pollution distribution and development in and aroundselected megacities/hot spot regions, including the interaction across the different spatialscales• Estimate the future impact from emission changes with a focus on the effect of rapid growthin the population of megacities/hot spots and the increasing background of pollutants• Estimate how megacities/hot spots influence climate change• Estimate how megacities are responding to climate forcing which can influence transportpatterns, chemical oxidation and biogenic emissions• Study mitigation options, e.g. by introducing biofuels, to keep the air pollution load in andaround megacities/hot spots within sustainable limits in terms of human health effects andclimate impact• Develop tools to estimate interactions between different spatial scales (megacities to global)• Use the scientific results and methods developed and applied during the course of theproject for technical underpinning of policy workIn order to address these objectives several scientific questions have been addressed in theproject:1. Have megacities and hot spots changed the regional and global distribution of ozone,particulate matter, and their precursors including carbon monoxide CO and other pollutantssignificantly compared to what would be the case with more evenly distributed emissions?2. Have megacities affected the radiative budget and aerosol microphysics such thatprecipitation and the number of sunlit hours and thus temperature and photochemistry havechanged significantly both locally and over larger regions? Will this become more significantin the future as megacities and their emissions grow?3. Will climate change alter weather patterns (winds, temperature, stability, precipitation) andsurface properties, which affect air quality in megacities and regional hot spots? If morefrequent high pressure situations occur, will episodes with reduced air quality become morefrequent?4. Will climate change induce episodic and permanent changes in the natural andanthropogenic cycles of atmospheric trace chemicals?5. Will changes in frequency and intensity of forest fires and other biomass burning contributesignificantly to air pollution in megacities and hot spots?6. Can measures be defined that reduce the adverse effects of megacity/hot spot emissions?The adverse effects relate both to air quality (human health) and climate change/weathermodification.253

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESThe work was organized in four work packages, as illustrated in Figure 4. WP1 focused onanalyzing past trends and present distributions, using both models and observations. WP2 dealtwith climate-chemistry interactions, while WP3 looked at mitigation options. Both WP2 and WP3included subtasks for providing emissions inventories. In WP4 we integrated the work of the firstthree work packages, ensured dissemination and contact with policy workers and otherpolicy-oriented frameworks.Figure 4 - The organisation of the work in CityZen in work packagesThe CityZen consortium combines expertise in the fields of observations, modelling and theprovision of emission scenarios. The flow of information is intended to proceed from the datasources (observations, emissions, meteorology, chemical transformation and sink mechanisms)towards the "Core research activities" where all available information and model calculations areblended together into 4-dimensional datasets of a spatial and temporal resolution that aredetermined by the problem under study. On the basis of these "Core research activities" research isundertaken in work packages 1-3 by a goal-oriented and specialized analysis of the data fields(observed, calculated, assimilated). Figure 5 illustrates the coordinated action of different scientifictools.Figure 5 - Model systems bridge processes occurring on different spatial scales spanning from the urban to the global. Airpollution flows between megacities/hotspots, the surrounding regions and globally. The analysis and forecasting of airpollution in hotspots require observations and modelling efforts that take into account the interactions of transportprocesses and air pollution loads on this range of spatial scales and cover the range of temporal scales determined by theatmospheric life times of the essential pollutants involved254

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESA webpage was established for CityZen, with useful information about the project(http://www.cityzen-project.eu). Results and publication are uploaded to the web site as theybecome available. The project established collaboration with its sister project MEGAPOLI.Collaboration with partners outside the CityZen and MEGAPOLI consortia was encouraged.7.3 ICARTTICARTT (The International Consortium for Atmospheric Research on Transport andTransformation) coordinated several field studies, each focused on some aspect of climate changeand air quality issues over North America, the Atlantic and Europe [Fehsenfeld et al., 2006]. Thesestudies were independently planned for the summer of 2004, and early in the planning process itbecame evident that coordination between these studies would provide a more effective approachto addressing the common issues. This approach yielded a series of coordinated studies of theemissions of aerosol and ozone precursors, their chemical transformations and removal duringtransport to and over the North Atlantic, and their impact downwind on the European continent. Theprimary source of the emissions studied was the US Northeast urban corridor, a major megacity inNorth America (see Chapter. 5), so in an important sense, ICARTT was focused on the climate andair quality effects of a megacity.The independently planned research programmes (primary location and sponsor) wereNEAQS-ITCT (US - NOAA), INTEX-NA (US - NASA), COBRA (US - NASA), AIRMAP Network (US- NOAA) and CHAiOS (US - NSF, NOAA), PICO-NARE (Azores, Portugal, NOAA, NSF), ITOP(European - NERC, DLR), ITCT-Lagrangian-2K4 Experiment (IGAC), ICARTT Cloud-Aerosol Study(US - NSF, Environment Canada) ICARTT Radiation-Aerosol Study (US - NOAA, NASA). Thecoordinated programmes conducted extensive measurements from nine aircrafts, a research vessel,balloon-borne sondes launched from several sites, multiple ground stations located in thenortheastern United States, Nova Scotia, the Azores, and Western Europe, and several satelliteplatforms. Figure 6 schematically illustrates the platform deployment.Figure 6 - Schematic depiction of the locations of platform deployment during ICARTT255

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESThe combined research conducted in the programmes that constituted ICARTT focused onthree main areas: regional air quality, intercontinental transport, and radiation balance in theatmosphere. Fehsenfeld et al. [2006] present an overview of the ICARTT study, and the results arereported in four special sections of Journal of Geophysical Research-Atmosphere. Some specific,especially important foci of ICARTT include:• Role of nitrate radicals and N 2 O 5 in the nighttime chemistry of the troposphere• Effect of reductions in NO X Emissions from US power plants• Evaluation of forecasts from air quality models for ozone and particulate matter• Evolution of the organic component of aerosols in air masses leaving North America• Relation of CCN activity of aerosols to their composition• Direct and indirect radiative effects of aerosols• Transformation of gas and aerosol phase species during transport from North America, overthe Atlantic, and to Europe• Impact of transported pollutants on air quality in Europe7.4 CalNex 2010CalNex 2010 is a field study that addressed both climate change and air quality issues inCalifornia. The particular focus of the study is the nexus between climate change and air qualityissues – hence the name CalNex. Figure 7 illustrates the species involved in this nexus. Thoughwe often treat them as separate issues with separate solutions,climate change and air quality are interrelated in many ways.The major air pollutants - aerosols (including soot) and ozone inthe lower atmosphere - are also significant climate changeforcing agents. These agents often have the same sources(transportation, industry, agriculture, forests), and they areshort-lived in the atmosphere (days or months, rather thandecades and longer for other climate gases). The overall goal ofCalNex was to provide needed information to develop integratedpolicies that address these highly interrelated environmentalissues together. There are obvious economic and societalbenefits to an integrated approach, and managing the short-livedair quality agents can bring early co-benefits for climate (yearsinstead of decades). Importantly, some air quality strategies canbe detrimental to climate change mitigation (e.g. control ofaerosols removes their climate cooling effect) and some climatestrategies can be detrimental to air quality (e.g. introduction ofbiofuels to reduce carbon dioxide emissions may increase someair pollutant emissions). The goal is to develop policies thatsimultaneously improve both issues.Many of the measurements were concentrated in the LosAngeles urban area, a major megacity in North America (seeChapter 5), so in an important sense, CalNex also focused onthe climate and air quality effects of a megacity. The fieldmeasurement phase was conducted in late spring-early summerof 2010, and analyses of the results are ongoing. The study is acollaborative, multiagency effort led by NOAA and the CaliforniaAir Resources Board (CARB) that conducted measurementsfrom four aircraft, a research vessel, balloon-borne sondes launched from six sites spanning thelength of California, two instrumented tall towers, and multiple ground stations located in Californiaand Mexico, the latter under the NSF funded Cal-Mex programme focused in the California-Mexicoborder region. More information is available from the study websites:http://esrl.noaa.gov/csd/calnex/http://www.arb.ca.gov/research/fieldstudy2010/fieldstudy2010.htm256Figure 7 - Depiction of the focus ofCalNex 2010 – the nexus of airquality and climate change issues

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESCalNex was planned to address many specific and general science needs that are requiredto improve policy responses to air quality and climate change issues. These needs can be roughlycategorized as emission characterization and quantification (both greenhouse gases and ozoneand aerosol precursors), improved understanding of important atmospheric transformation andclimate processes, and transport and meteorology. Instrumentation and platforms were deployed tocollect the data sets necessary to address these issues. More detailed information is available fromthe CalNex White Paper (http://esrl.noaa.gov/csd/calnex/whitepaper.pdf) and the NOAA CalNexScience and Implementation Plan (http://esrl.noaa.gov/csd/calnex/scienceplan.pdf).7.5 MILAGROMILAGRO (Megacity Initiative: Local And Global Research Observations) is an internationalcollaborative project to examine the behaviour and export of atmospheric emissions from amegacity. The Mexico City Metropolitan Area (MCMA) – one of the world’s largest megacities andNorth America’s most populous city – was selected as the case study to characterize the sources,concentrations, transport, and transformation processes of the gases and fine particles emitted tothe MCMA atmosphere and to evaluate the regional and global impacts of these emissions. Thefindings of this study are relevant to the evolution and impacts of air pollution from many othermegacities.Specific goals of the MILAGRO Campaign included:i) Quantifying the spatial and temporal extent of the urban plumeii) Analyzing pollutant chemical and physical transformation in the plumeiii) Quantifying the regional impacts of the plume; andiv) Examining the interaction of the urban plume with surrounding sourcesThe MILAGRO campaign was organized under four coordinated components that took placesimultaneously during March 2006 and included the participation of over 450 scientists from 150institutions in 30 countries.1) The MCMA-2006 (Mexico City Metropolitan Area – 2006 Experiment) examined emissionsand surface concentrations within the Mexico City Basin, their transport and transformation in theatmosphere, and the effects on human health. MCMA-2006 was led by the Molina Center forEnergy and the Environment (MCE2) with projects sponsored by US-NSF, US-DOE, and severalMexican research agencies, including the Ministry of the Environment and Natural Resources andthe Metropolitan Environmental Commission of the Valley of Mexico, as well as European agencies.The overall purpose of MCMA-2006 was to strengthen the scientific base for the design andevaluation of policies to improve the air quality in the MCMA by gathering scientific information thathelps to better understand the generation and processing of pollutants in the MCMA. TheMCMA-2006 also provided many of the urban measurements needed for understanding the largerscale pollutant evolution which was the focus of its sister campaigns. Two health studies werecarried out during the Campaign.2) MAX-Mex (Megacity Aerosol Experiment: Mexico City) focused on examining how theMexico megacity aerosol evolves during transport and how the chemical and physical nature of theaerosol affected scattering and absorption of atmospheric radiation. MAX-Mex was conducted bythe Atmospheric Science Programme of the US-DOE Climate Change Research Division incollaboration with scientists supported by US-NSF, US-NASA, and Mexican agencies.Measurements were conducted using an airborne lidar, the DOE Gulfstream-1 (G-1) airborneplatform that obtained gas and aerosol measurements, and also at the three supersites to examinethe aerosol plume evolution.3) MIRAGE-Mex (Megacity Impacts on Regional and Global Environments - Mexico)examined the chemical/physical transformations of gaseous and particulate pollutants exportedfrom Mexico City, providing a case study of a megacity’s effect on regional and global atmospheric257

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIEScomposition and climate. MIRAGE-Mex was led by the US National Center for AtmosphericResearch (NCAR) in collaboration with academic researchers under US-NSF sponsorship. The USNCAR/NSF C-130 aircraft sampled air above and at different distances from Mexico City tomeasure how gases and particles age during transport, specifically tracking the chemical, physical,and optical properties that have the potential to affect air quality, weather, and climate on largegeographic scales. The Twin Otter conducted studies of fire emissions and their effect on the localand regional composition of the atmosphere.4) INTEX-B (Intercontinental Chemical Transport Experiment-B) was an integrated fieldcampaign designed to understand the transport and transformation of gases and aerosols ontranscontinental/intercontinental scales and to assess their impact on air quality and climate.Central to achieving this goal was the need to relate space-based observations with those fromairborne and surface platforms. The NASA DC-8 was operated from Houston, Texas with researchflights over Mexico and the Gulf of MexicoThe measurement phase consisted of using wide-ranging meteorological, gas and aerosolsinstruments at ground sites and on aircraft and satellites. All of these platforms together can beused to trace the evolution of the urban plume as it merges with the regional backgroundatmosphere (Figure 8). Three supersites, spaced ~ 30 km apart, were set up to examine theevolution of the primary emitted gases and fine particles. The designations “T0” (initial time), “T1”(first time step), and “T2” (second time step) in Figure 9 refer to the timing of transport of the urbanplume to different points in space and time. Additional platforms in or near Mexico City includedmobile vans containing scientific laboratories and mobile and stationary lidars. Seven researchaircraft provided information about the atmosphere over a large region and at various altitudes.Satellite-based instruments provided even larger geographical coverage. The overall campaign wascomplemented by meteorological forecasting and numerical simulations, as well as an ambient airquality monitoring network operated by the Mexico City government and meteorologicalmeasurements were provided by the Mexican National Weather Service. Together, theseobservations provided a very comprehensive characterization of the MCMA’s urban and regionalatmospheric composition and chemistry that will require extensive analyses and use in modelimprovement to yield maximum benefits.Figure 8 - MILAGRO Campaign Geographic Coverage. Measurements were performed in the MCMA (see Figure 9). Thesize of the circle (MAX-Mex, MIRAGE-Mex and INTEX-B) indicates the geographic coverage of the aircraft deployed258

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESFigure 9 - MILAGRO Campaign: Ground-based Measurement SitesMajor findings are being published in two special issues on MCMA-2003(http://www.atmos-chem-phys.net/special_issue21.html) and MILAGRO/INTEX-B(http://www.atmos-chem-phys.net/special_issue83.html) in Atmospheric Chemistry and Physics aswell as in other peer-reviewed journals. An overview article has been published [Molina et al., 2010],which reviews over 120 papers resulting from MILAGRO/INTEX-B Campaign that have beenpublished or submitted, as well as additional relevant papers from earlier MCMA-2003 Campaign[Molina et al., 2007], with the aim of providing a road map for the scientific community interested inunderstanding air quality in a megacity such as the MCMA and its local and regional impacts. Acomplete list of articles is available at: http://mce2.org/publications.html. All data sets are availableto the scientific community interested in evaluating the impact of urban emissions on human health,ecosystem viability, and climate change.The following summarizes some of the key findings:Meteorology and Dynamics: In order to support the goals of the MILAGRO field campaign, a largerange of meteorological measurements were carried out including: surface operational networks,surface supersites, fixed mobile units, radar wind profilers, lidars, rawinsondes, aircraft platformsand pilot, tethered and Controlled Meteorological (CMET) balloons. These were used tocharacterize the meteorological episodes in terms of emission transport. Numerical modellingduring MILAGRO showed that mesoscale models such as WRF and FLEXPART do a sufficientlygood job of simulating pollution transport that they can be further used for interpreting atmosphericchemistry measurements. Observations and modelling studies show that under most conditions,pollutant export from the basin is relatively rapid and that pollutant carryover from day to day is not amajor factor in the valley’s photochemistry. The overall synoptic conditions and boundary layercirculations were similar to those reported by MCMA previous studies and consistent with priorclimatology. Meteorological measurements at the surface and aloft coupled with measurements oftrace gases and aerosols indicate that the synoptic-scale transport of the Mexico City pollutantplume was predominantly towards the northeast, although regional-scale circulations transportedpollutants to the surrounding valleys and basins on some days. Drainage flows at night have astrong impact on air pollution transport and accumulation in the basin leading to high pollutantconcentrations. The MCMA has been found to be more similar to Houston, Texas than to LosAngeles, California in that poor air quality days can result early in the day from emissions on a dayof weak venting. Fast response actions should therefore be considered with a focus on nighttimeand morning emissions.259

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESEmission Measurements: Emissions studies confirmed that motor vehicles play a major role insupplying the NO X and VOC precursors that fuel MCMA’s extremely active photochemistry. Keyfindings include a vastly improved speciated emissions inventory from on-road vehicles, showingthat the MCMA motor vehicles produce abundant amounts of primary PM, elemental carbon,particle-bound polycyclic aromatic hydrocarbons, carbon monoxide and a wide range of air toxics,including formaldehyde, acetaldehyde, benzene, toluene, and xylenes. Measurement andmodelling studies suggest that PM emissions may be severely underestimated in the currentemissions inventory estimates. Several innovative techniques were developed in 2003 and usedagain in 2006 to evaluate the official emission inventories used in air quality models. On-roadvehicle fleet emission indices in fleet-average mode for various vehicle classes and driving speedswere obtained using a mobile laboratory. The feasibility of using eddy covariance techniques tomeasure fluxes of volatile organic compounds and aerosols in an urban core was demonstrated,proving a valuable tool for evaluating local emissions inventory. Together, these techniques haveallowed the re-evaluation of the emissions inventory used in air quality models with observations ofthe concentration of many species and fluxes for a few.Volatile Organic Compounds (VOCs): The studies have provided a much better understanding ofthe sources and atmospheric loadings of VOCs, including the first spectroscopic detection ofglyoxal in the atmosphere and a unique analysis of the high fraction of ambient formaldehyde fromprimary emission sources. Liquified petroleum gas (LPG) use continues to be an important sourceof low molecular weight alkanes. Evaporative fuel and industrial emissions are important sourcesfor aromatic VOCs and methanol in the basin. There are also large non-biogenic sources ofmethanol in the MCMA basin. The two most important measured VOC species in terms of OHreactivity were formaldehyde and acetaldehyde. Aldehydes are major components of the outflowreactivity. They are produced by atmospheric VOC oxidation and some are also emitted directly. Inspite of their importance, these compounds are not measured routinely.Photochemistry: The studies have significantly improved the characterization of ozone formationand its sensitivity to emission changes in VOCs and nitrogen oxides. The results of MILAGROdemonstrate that urban photochemical smog formation in the MCMA is VOC-limited, which isconsistent with the results of MCMA-2003; however the degree of sensibility to VOCs is higherduring MCMA-2006 due to the lower VOC/NO X emission ratio and VOC reactivity. Ozone formationin the surrounding mountain/rural area is mostly NO X -limited, but can be VOC-limited and the rangeof the NO X -limited or VOC-limited areas depends on meteorology. Although the formation of theurban photochemical smog is VOC-limited, the reductions of emissions of NO X can reduce theformation of regional oxidants. Ozone production continues in the outflow for several days, due tothe formation of peroxyacetyl nitrates (PANs) that effectively increase the NO X lifetime.Ambient Particulate Matter: The studies also provide a much more extensive knowledge of thecomposition, size distribution and atmospheric mass loadings of both primary and secondary finePM; and an improved understanding of the evolution and the radiative properties of aerosols. PM 10and PM 2.5 concentrations in the urban area were about double the concentrations in the rural areassurrounding Mexico City. Mineral matter and secondary inorganic ions each made up approximately25% of the PM 2.5 in the urban areas, with the remaining PM 2.5 mass being comprised of largelycarbonaceous aerosol. The dominant sources of carbonaceous aerosol were secondary organicaerosol, biomass burning, and vehicle exhaust emissions (soot). The impact of biomass burning onthe aerosol outflow from the region was much larger than on the surface concentrations inside thecity. During MCMA-2003 and again in 2006, SOA production was observed to grow very rapidlyduring sunlight hours – far faster than current atmospheric models or laboratory simulationexperiments with the expected precursor gases can explain. Results from MILAGRO 2006 indicatethat SOA formation from primary semivolatile and intermediate volatility precursors has the potentialto close the gap in predicted vs. measured SOA. However these predictions are poorly constrainedby the data and more specific measurements are needed in future campaigns.Aerosol Evolution and Radiative Effects: Results from both ground-based and airbornemeasurements confirm that the MCMA plumes are significant sources of both primary and260

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESsecondary aerosols at the regional scale and black carbon and SOA are contributing to singlescattering albedos in the MCMA and downwind that are substantially smaller than in other areas(such as the eastern United States). Studies from MILAGRO have reported significant enhancedUV-Visible absorption from biomass burning, SOA, and aged carbonaceous aerosol components.At the T0 and T1 surface sites single scattering albedos (SSA) were frequently in the 0.7-0.8 rangewith some early morning values having even lower SSA. This is consistent with high absorbingaerosol concentrations from both fossil and biomass burning sources during MILAGRO. Aerosolcontributions from biomass burning sources contained both black carbon and oxidized organics thatyielded enhanced UV absorption. This observation indicated biomass burning activities can haveimportant impacts on the absorption or heating by carbonaceous aerosols in megacity (urban) aswell as regional scales. Oxidized organics from primary fires and from secondary aerosol formationwere also found to have strong absorption in the 300-400 nm region that leads to enhanced opticalabsorption by these aerosols over that anticipated from black carbon alone.The results from LIDAR and aircraft operation as well as aerosol mass spectrometers allindicate that there is significant transport of aerosols and that most of this aerosol is in the lowerlayer of the atmosphere, but can be exported aloft into the free troposphere during venting events.Satellite retrievals of aerosols are being improved by comparisons with measurements of radiationand aerosol properties at the surface and from aircraft. Measurements of surface albedo andreflectance in the MCMA showed that many urban surfaces are more reflective than assumed incommon satellite retrieval algorithms, and that use of larger visible surface reflectance in algorithmscan produce more accurate retrieved aerosol optical depth (AOD).As described above, a very large number of instruments were used in the MCMA duringMILAGRO for both ground-based and aircraft measurements; and some innovative instruments andmeasurement techniques were deployed for the first time. The MILAGRO campaign has shown thesynergy of using multiple measuring platforms, instrumentation, and data analysis techniques forobtaining an improved understanding of the physical and chemical characteristics of emissions in amegacity. Furthermore, the deployment of a significant number of advanced instruments, manyoperating with sensitive, fast (~1 s) response times, along with a large number of established airquality monitoring instruments deployed on aircraft and at surface sites, as well as onboard severalmobile laboratories, have provided significant opportunities to intercompare and evaluate a numberof instruments in a highly polluted environment.Despite the use of many advanced PM techniques during MILAGRO, some questionsremain unanswered or strongly debated and should be the focus of further research. For example,the fraction of dust due to road resuspension vs. natural sources is unclear. The impact ofgas-particle reactions is important, for example for nitrate uptake into the coarse dust mode, butneeds to be further investigated to reach a quantitative understanding, including through 3Dmodelling. The identities of industrial sources of metals and organic aerosols and of the urbanchloride sources remain unclear. High time-resolution quantitative analyses of dust and metals mayyield very useful information for source identification.The 2006 MCMA emissions inventory underestimates primary PM 2.5 and needs to beupdated with the information arising from MILAGRO and other studies. Forest fire PM 2.5 appears tobe underestimated by an order of magnitude in the official MCMA inventory, but perhapsoverestimated about two-fold on a custom satellite-based inventory used in 3D modelling. Theimpact of some primary organic aerosol sources such as food cooking, biofuel use, and open trashburning may be important, but remains poorly characterized. Some differences in the apportionmentof biomass burning PM between different approaches were observed and need further research, asthese techniques together represent the state of the art for source apportionment. The differencesin the relative oxidation of organic aerosols in urban vs. background samples between differenttechniques need to be further investigated.The influence of “hot” sources of radiocarbon in aerosols needs to be further investigated asit could bias assessments of fossil vs. modern carbon. SOA from traditional precursors such asaromatics is much smaller than the observed SOA in the Mexico City urban area, but the dominant261

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESsources of anthropogenic SOA are still poorly characterized. SOA from biomass burning sources,although not dominant in the city, remains poorly characterized and appears to be under predictedby traditional models.Measurements of aerosol optical absorption in Mexico City and downwind also benefittedfrom the variety of techniques applied during MILAGRO. However, not all results are in perfectagreement. Future campaigns need increased focus on spatiotemporal coincidence betweendifferent techniques, to help resolve these questions. There are also persistent differences amongdifferent satellite retrievals of aerosols, as well as between results from satellite and suborbitaltechniques; this is an area that requires continued effort.In summary, the MILAGRO Campaign was designed to investigate the extremely vigorousatmospheric photochemistry of Mexico Megacity. Review of the published results has alreadyimproved significantly our understanding of the meteorological and photochemical processescontributing to the formation of ozone, secondary aerosols and other pollutants and their transportand transformation. Key findings have been presented at international conferences as well ascommunicated to Mexican government officials. We anticipate new results from MILAGRO willcontinue to contribute to our understanding of megacity emissions and their potential impacts onhuman health, ecosystem viability, and climate change on urban, regional, and even hemisphericscales. This information will provide the scientific knowledge for decision makers in Mexico todesign effective policies as well as provide insights to air pollution problems in other megacitiesaround the world.7.6 SAEMC/ADAPTEMore than 80% of South Americans live today in urban centres. These centres accumulatewealth but also environmental problems, which poses for South Americans a distinct vulnerability ina changing climate. Until recently though, these efforts have been largely decoupled frominternational efforts. With support from the Inter American Institute for Global Change (IAI,http://www.iai.int), the South American Emissions Megacities and Climate (SAEMC,http://saemc.cmm.uchile.cl) and Adaptation to health impacts of air pollution and climate extremesin Latin American cities (ADAPTE) studies are now underway. Working teams were developedaround five research axes: 1) emissions, 2) chemical weather forecasting, 3) modelling tools,including grid and high performance computing, 4) aerosols and 5) health impacts.Background and rationaleExcept in Brazil, Earth System Science capabilities in South America are sparse andoftentimes isolated. This also applies to more specific air pollution science and expertise. Typically,research teams consist of a few scientists and students, who deal with probably too broad a rangeof subjects and with funding related to short-term consultancies and small scientific grants (

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESAgain, except in Brazil, material and human resources for global change research in SouthAmerica on a country-by-country basis are far too small to allow a significant contribution tointernational programmes and to produce sustained impacts on local development. Nevertheless,global change science cannot be approached solely from a global perspective. On the contrary,turning points are to be found and faced locally. To illustrate this, let’s consider the apparentlysimple issue of conciliating local and global emission inventories. Today’s global chemistry-climatemodels that provide climate change scenarios are based on emission estimates for year 2000 andprojections, which are far from reflecting the actual development of large cities that were notrelevant for the year 2000. Local inventories are available for most cities in South America but haveyet to be included in the emission inventories used in global models. Is it a matter of not sharinginformation? Yes, to some extent due to too small an overlap of communities, something that isfortunately improving year by year, but also because it is non-trivial combining different scales in anon-linear system [Alonso et al., 2010].All in all, it is clear that there is a mutual benefit for scientists and policy makers in combiningefforts and exchanging perspectives, beyond short-term consultancies and perhaps creatingconsortia that provide a common but independent framework for sound science and policy making.It is also obvious that the understanding of global change requires global but more importantly localknowledge that is not feasible to obtain without the participation and leadership of local scientists.This in turn requires integration of local scientist into global programmes and investment in localcapabilities, both human and material. Following is a description of SAEMC/ADAPTE, whichdemonstrates what can be achieved in four years with less than 1 million dollars.Project description and highlightsMeasurement campaigns in Santiago, Bogotá, São Paulo, Lima and Buenos Aires wereperformed, which resulted in locally representative emission factors for vehicles, making it possibleto create the first consistent inventory for vehicular emissions for Buenos Aires [D’Angiola et al.,2010]. Also, tools were developed to obtain disaggregated emissions [Saide et al., 2009]. Past andfuture emission scenarios were completed for Argentina and have been initiated for other cities.Evaluation tools based on data assimilation techniques were developed and applied at the local andthe regional scales [Hoelzemann et al., 2009; Saide et al., 2011]. Reconciliation between global andlocal inventories was also achieved [Alonso et al., 2010]. All of these data have been reviewed andare becoming available for the whole community and are increasingly being integrated into globaldatabases.At the beginning of the project, there was a well-established regional transport modelespecially developed for addressing dispersion and impacts of biomass burning in tropical SouthAmerica [Freitas et al., 2005]. Regional weather services had some experience in numericalprediction for physical weather but none in chemical weather forecasting. Today, there is a fullycoupled model that provides operational chemical weather forecasting for South America [Freitas etal., 2009; Longo et al., 2009] and produces regionally relevant information for local applications.Also, both at the Chilean and Peruvian Weather Services, there are chemical weather forecastingtools available and operational as well as dedicated teams to run the models. Furthermore, thebasis for a community model is now feasible via the use of an already installed but veryunder-exploited high-speed Internet connection among South American countries and the rest ofthe world [D’Almeida et al., 2008].Existing air quality monitoring networks generally provide mass concentration for thedifferent cities. However, to address health and climate impacts, and even identifying emitters orany process understanding, one needs morphological and speciation information. This in turnrequires sophisticated instrumentation and analytical capabilities that are very expensive. For amarginal cost the project compiled and evaluated information on the chemical and physicalcharacterization of aerosols from Buenos Aires, São Paulo and Bogotá [Vasconcellos et al., 2011].This was made possible thanks to coordinated sampling and sharing of analytical resourcesincluding trace metals (Buenos Aires), organics (São Paulo) and ions (Bogotá). Local and specificstudies were also performed [Dos Santos et al., 2009].263

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESCities and climate are coevolving in a manner that could place more populations at risk fromexposure to extreme temperature and air pollution. Urban areas of Latin America are projected tobe increasingly affected by heat waves; yet, we do not know how vulnerable the urban population isto the health impacts that may result from this increase. ADAPTE gathered, validated, andanalyzed data on temperature, air pollution and vulnerability allowing measuring changes in theRelative Risk of health outcomes such as mortality due to changes in temperature and air pollutionand maps of differential patterns of vulnerability within the urban centres [Romero-Lankao et al.,2011]. Also, in São Paulo, advances were made to combine air quality models and health statistics[Martins et al., 2010].The project was very successful in connecting South American scientists and students andalso at establishing a two-way connection between scientists in South America and “First World”centres. Very importantly, we used the majority of our IAI resources in fellowships for students,some of which are now themselves starting to be leading scientists who can more easilyinterconnect between countries and between science and policy making. For all cities, we weresuccessful in producing relevant information and implementing tools for scientific understandingand policy making, Bogotá being an outstanding case [Behrentz et al., 2009]. We have shown thatsharing and using available resources is feasible and that the integrated sum of those is larger thanthe sum of the individual resources.Outlook and perspectives for SAEMC/ADAPTEContinued and future Developments:• The establishment of community model including shared computing and storage capabilities,which of course does not preclude the use of other tools but puts an emphasis on theestablishment and use of local know-how. For instance, which is the adequateaerosol/photochemical model for South American cities where bio-fuel is so prevalent? Howdo we handle extremely stable boundary layers along the Andes?• A permanent initiative on emission inventories as a dynamical tool that evolves according tosystematic, transparent, and recurrent evaluations.• Coordination for providing recurrent aerosol and gas phase chemistry characterization forunderstanding processes and impact assessments. This is especially needed in order toaddress aerosol-cloud-climate interactions as well as impacts on human health andecosystems.• Air quality monitoring is probably among the most resource intensive activities that isneeded. Therefore, it is crucial to have tools to facilitate decision making and to actuallyoptimize the design of monitoring networks. Variational and statistical methods have beenexplored to design and evaluate monitoring networks.• From the climate change aspects, South American countries need a feasible forecasting toolcustomized to the complex issues that face South America and relevant associatedprocesses to provide the forecasts to governmental and civil societies. Important questionsto be addressed, among others, are: how is global warming and land use/land coverchanges affecting the air quality of the densely urbanized areas? What is the impact ofaerosols and the urban heat effect on the hydrological cycles on local and regional scales?What is South America’s contribution to global changes?Other projects in South AmericaThere are at least two initiatives that deal with South American cities. One is a pilot projectfocusing on Santiago but that is expected to be replicated elsewhere in South America((http://www.risk-habitat-megacity.ufz.de/). Another one is the “Clean Air Initiative in Latin AmericanCities” (CAI-LAC) driven by the World Bank (http://www.cleanairnet.org). Risk Habitat Megacity(RHM) is a six year (2007-2013) joint initiative between Chilean and German researchers. It is an'Initiative and Networking Fund' of the Helmholtz-Association. RHM approaches several megacityissues, such as Land use management, Socio-spatial differentiation, Energy, Transportation, Airquality and health, Water resources and services, and Waste management. The programmecomprises ten topics: three “cross-cutting concepts” – Sustainable Development, Risk, and264

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESGovernance – and seven “fields of application” (Suppan and Schmitz, pers. comm.). CAI-LACstarted in 1998, and it was re-organized in 2006. The original purpose was to establish acomprehensive approach to addressing air quality challenges in Latin America. The initial phasesupported the development and enhancement of clean air action plans in large urban areasthroughout Latin America, enhanced scientific knowledge and understanding of urban air qualityand its associated impacts on human health, and provided decision makers with tools for assessingpolicy options. According to their web page, the restructuring of the original phase of the initiativewas envisioned to revitalize efforts by, among other things, creating a forum for strategy and projectdevelopment, as well as for channelling training, technical assistance, and information exchange ata regional level. Focal points of this initiative reside in environmental agencies and are largelydisconnected from academia.7.7 CAREBEIJINGCAREBEIJING (Campaigns of Air Quality Research in Beijing and Surrounding Regions)was an international collaborative research project to study the regional transport andtransformation processes of air pollution that impact air quality in Beijing and to formulate airpollution control strategies for 2008 Beijing Olympics and the long-term strategies for the region.CAREBEIJING was funded by Beijing Council of Science and Technology and coordinated by TongZhu of Peking University, it has conducted three campaigns in 2006, 2007, and 2008, with activeparticipation of more than 200 scientists and graduate students from 21 research institutes in Asia(mainland China, Hong Kong, Taiwan, Japan, Korea), Europe (Germany, Italy), and USA.Beijing is a megacity with a population close to 20 million and air pollution is a seriousconcern. With 14 stages of air pollution control in the last decade, the air quality in Beijing has beensignificantly improving. Yet this improvement is undermined by rapid increases in the number ofvehicles and energy consumption in Beijing, as well as the regional transport of air pollutants fromhighly industrialized area surrounding Beijing. The objectives of CAREBEIJING included:1. To learn about the current environmental conditions of the region, including social andeconomical factors, air quality, and emission sources.2. To identify the transport and transformation processes that lead to air pollutants surroundingregions to impact air quality in Beijing.3. To calculate the impact of the surrounding regions on air quality in Beijing.4. To formulate policy suggestion for air quality attainment during the 2008 Beijing Olympicgame.5. To propose objectives and strategy of air quality attainment in 2010 in Beijing.6. To design a regional air quality management framework and propose policy suggestions forregional air quality control.7. To evaluate the effectiveness of air quality control policies.8. To evaluate the health impacts of air pollution before and during the 2008 Olympics.To achieve these objectives, CAREBEIJING conducted intensive field campaigns based onground, aircraft, and satellite observations. The data was used to validate emission inventories andregional air quality models (Figure 10).The campaigns in 2006, 2007, and 2008 all served a different purpose:CAREBEIJING-2006:CAREBEIJING-2007:CAREBEIJING-2008:To understand the transport and transformation process of regional airpollutionTo evaluate air quality control policies proposed for the 2008 Olympicsbased on the findings of CAREBEIJING 2006To evaluate the effectiveness of the air quality control policies and theirimpacts on health265

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESFigure 10 - Research components of CAREBEIJINGMajor findings are being published in two special issues in Journal of GeophysicalResearch-Atmospheres(http://www.agu.org/journals/jd/special_sections.shtml?collectionCode=CARBS1&journalCode=JD) and in Atmospheric Chemistry and Physics(http://www.atmos-chem-phys.net/special_issue198.html) as well as in other peer-reviewedjournals. Based on the findings from CAREBEIJING and other related research projects, air qualitycontrol policies were formulated and the final implementation plan was approved by the Chinesecentral government. A series of aggressive measures to reduce pollutant emissions in Beijing and insurrounding areas were taken before and during the 2008 Beijing Olympics and Paralympics (July25 – September 17, 2008) in order to ensure the substantially improved ambient air quality. Inaddition to local efforts in Beijing, five cities and provinces surrounding Beijing also implementedstrict air quality control measures on area and point sources. Many heavy-polluting factories wereordered to reduce their operating capacities or completely shut down during the Olympics.Construction activities were all paused. Power plants near Beijing were required to reduce theiremissions.As an important component of CAREBEIJING was a health study with two panels assessingcardiovascular and respiratory responses of susceptible populations (CAREBEIJING-H) to airquality improvements were conduced. Using environmental exposure rates, time series, panelstudies, and toxicological experiments, it was shown that due to the improvements in air qualityduring the Beijing Olympics the number of emergency room visits due to cardiovascular disease aswell as the biomarkers of respiratory inflammation were reduced.During the Olympics, significant reductions of NO X , SO 2 , CO, BC, PM 2.5 , and O 3 wereobserved. The level of reduction ranged from 10% to 60% depending on the pollutant and whatbaseline concentration was used. The Beijing Olympics has been widely recognized as one of themost successful and exciting games in Olympic history. Improving air quality of Beijing certainlycontributed to the overall success. The experience from the large-scale regional efforts ofCAREBEIJING provides a valuable lesson for other megacities facing similar air pollution problemsas Beijing.More information can be found at the web site of CAREBEIJING:http://ceh.pku.edu.cn/carebjindex.html266

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIES7.8 IMPACT1. O 3 and aerosol studies in the Tokyo Metropolitan Area (TMA)Large amounts of reactive gases and aerosol are emitted from urban areas. Megacities,including the Tokyo Metropolitan Area (TMA), are very large, concentrated sources of thesespecies, which affect O 3 and aerosol levels on local, regional, and global scales [Molina and Molina,2004; Ramanathan et al., 2007]. The uncertainties in emission estimates of these air pollutants aregenerally large for Asia [Streets et al., 2006; Ohara et al., 2007] or do not assess the TMA [Kannariet al., 2007].The increased levels of pollutants have a large impact on regional air quality, nutrientdeposition patterns, and climate. In order to assess the impacts of anthropogenic species emittedfrom these megacities on surrounding areas, we need to understand quantitatively the keyprocesses involved in the oxidation of primary species and the fate of the oxidized species near thesource regions (Figure 11). In addition, clusters of megacities lead to accumulation of O 3 andaerosol through large-scale mixing. Reactive species with elevated concentrations in urbanoutflows can also interact with species emitted from natural sources surrounding the megacities. Itshould be noted here that O 3 and aerosol are coupled due to similar sources, photochemicalinteractions (e.g., UV changes by aerosol), and transport.Figure 11 - Schematic diagram of key processes of O3, aerosols, and their precursor gases near megacity regions2. Integrated Measurement Programme for Aerosol and oxidant Chemistry in Tokyo(IMPACT)Studies on characterizing primary emission and secondary formation of aerosols in theTokyo Metropolitan Area (TMA) have to date been very limited. Further observational studies ofaerosols, especially organic aerosol, near source areas are needed in order to improve theunderstanding of the amounts and chemical composition of aerosols emitted from these largesource areas. As a result, the Integrated Measurement Programme for Aerosol and oxidantChemistry in Tokyo (IMPACT) campaign was conducted. The specific goal of IMPACT was toimprove the understanding of atmospheric chemistry in the TMA [Kondo et al., 2010]. IMPACT wasconducted within the framework of the International Global Atmospheric Chemistry Project (IGAC),Mega-Cities: Asia. The major objectives of IMPACT were to:• Characterize the temporal and spatial changes of aerosols, oxidants, and their precursors,primarily through surface measurements near and downwind of urban centres• Characterize the composition, mixing state, and physical properties of aerosols in urban air• Evaluate emission inventories of trace gases (e.g., NO X , SO 2 , NH 3 , and VOCs) throughcomparisons of ratios of concentrations of trace species observed in urban air267

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESThe instruments used during IMPACT are described in detail elsewhere [Kondo et al., 2006;Takegawa et al., 2006a]. The observation sites were located at the Research Center for AdvancedScience and Technology (RCAST), Komaba, Tokyo (35°39’N, 139°40’E), and the Center forEnvironmental Science in Saitama (CESS), Kisai, Saitama prefecture (36°05’N, 139°33’E), which islocated about 50 km north of Tokyo (Figure 12). The locations of the observation sites allowedchemical processes of HO X radicals and O 3 formation [Kanaya et al., 2007; 2008] and emissionsand transformation of primary aerosol, especially BC [Kondo et al., 2006; Shiraiwa et al., 2007],secondary aerosol, cloud condensation nuclei (CCN) activity, and the hygroscopicity of aerosol[Kuwata et al., 2009; Kuwata and Kondo, 2009; Mochida et al., 2006; 2008] to be studied. Importantfindings made by IMPACT are summarized in Table 1.Figure 12 - Transport of pollutants from the urban centre (Tokyo) to suburban areas by the sea breeze3. Perspectives and future studiesThe methodology used for IMPACT is schematically shown in Figure 13 and proved to bevery successful for several reasons. First, a combination of a limited number of fully instrumentedobservational sites (super sites) and monitoring stations of fundamental species proved to becost-effective for a megacity study. During the IMPACT experiments, two super sites were set up(Figure 12); one was located near the urban centre of Tokyo (RCAST) and the other was about 50km downwind (CESS). Because of the typical transport time of 3-7 hours, time-resolvedmeasurements provided quite useful information on the chemical evolution of polluted air. Second,instrumentation for vertical sounding, including lidar, were also useful because they providedchanges in the boundary layer height that could be related to corresponding changes in theconcentrations of various species measured at the surface. Third, regional-scale model calculationswere evaluated by the data obtained by the measurement system mentioned above. Modelcalculations are useful in improving our understanding of chemistry and transport processes overthe entire TMA.The framework of IMPACT and its subsequent scientific findings can be very useful to helpunderstand atmospheric chemistry and transport in other megacities in Asia, especially consideringthat many of them are also located in coastal areas, i.e., Beijing, Shanghai, Hong Kong,Guangzhou, and Seoul.268

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESTable 1 - Summary of findings by IMPACTTopic Major findings ReferencesInstrumentation A HNO3-CIMS with a new calibration/zero systemwas developed.Performance of an Aerodyne AMS was evaluatedbased on intercomparison with a PILS-IC andSunset OC.A new method to quantify BC coating wasdeveloped using an SP2.OH/HO2/O3Measured OH was reproduced by a box model inwinter and summer.Measured HO2 was underestimated by the model inthe high-NOX regime.VOCs Seasonal variation of C2-C7 non-methanehydrocarbons was quantified.BCDiesel emissions were identified as a major sourceof BC in Tokyo.NitrateNitrate-HNO3 partitioning in summer was influencedby vertical mixing.SulphateOnly a small fraction (3% in winter and 18% insummer) of SO2 emitted was converted to sulphate.Organic aerosol Seasonal and diurnal variation of POA and SOAwas quantified.Most SOA (OOA) was found to be water soluble.Hygroscopicity and CCNOutflow from TokyoHygroscopicity and CCN activity were perturbed byorganics.BC can act as CCN with a small amount of coatingmaterial.Significant formation of organics and alteration ofBC mixing state took place within ~0.5 days insummer[Kita et al., 2006; Takegawa etal., 2005; Moteki and Kondo,2007; 2008][Kanaya et al., 2007; 2008][Shirai et al., 2007][Kondo et al., 2006;Shiraiwa et al., 2007][Morino et al., 2006][Miyakawa et al., 2007][Takegawa et al., 2006a;2006b; Miyazaki et al., 2006;Kondo et al., 2007; 2008;Matsui et al., 2009][Mochida et al., 2006; 2008Kuwata et al., 2009; Kuwataand Kondo, 2009][Takegawa et al., 2006b;Shiraiwa et al., 2007; Miyakawaet al., 2008]Figure 13 - System for megacity air quality studies: Observations at 1-2 main stations (st.) and routine monitoring stations,modelling, and science-policy feedback269

7.9 PRIDE-PRDCHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESPearl River Delta (PRD) is one of the three city-clusters in China that has experiencedextremely fast urbanization and industrialization. The breathtaking speed of economic growth forover three decades in PRD, however, has been accompanied by an increase in air pollution,namely elevated concentrations of ozone O 3 and fine particulates PM 2.5 . The concurrent highconcentrations of O 3 and PM 2.5 together with primary pollutants has led to rather unique pollutioncharacteristics due to interactions between primary emissions and photochemical processes,between gaseous compounds and aerosol phase species, and between local and regional scaleprocesses.PRIDE-PRD (The Programme of Regional Integrated Experiments on Air Quality over PearlRiver Delta of China), sponsored by the Ministry of Science and Technology of China (MOST)during 2003-2008, was developed to investigate in depth the air pollution problem and to improvethe understanding of the chemical and radiative processes in PRD. The main objectives were to:• Characterize the temporal and spatial distribution of the concentrations of aerosol, oxidants,and their precursors by ground based (routine monitoring network and super-sites), airborneand satellite measurements• Understand chemical composition, size distribution, hygroscopic properties, and opticalproperties of aerosols• Quantify the contribution of precursors to the formation of oxidants and secondary aerosolsby measurements and modelling• Study the interactions between aerosols and gases through measurements of precursors ofaerosols and oxidants as well as by modelling• Determine source-receptor relationship across cities within the PRD as well regionalcontribution to PRD air pollution• Define the regional mitigation strategies and technical options to keep the air pollution loadin PRD within sustainable limits in terms of ecological and human health effectsPRIDE-PRD consisted of two campaigns: PRIDE-PRD2004 during October 1 andNovember 4, 2004 and PRIDE-PRD2006 during July 4 and July 31, 2006. An international scienceteam from China (mainland, Taipei, and Hong Kong), Germany, Japan, and Korea was involved inboth campaigns. Yuanhang Zhang from Peking University and Liuju Zhong from GuangdongProvincial Environmental Monitoring Center coordinated PRIDE-PRD. The campaigns ofPRIDE-PRD were truly a team effort, bringing together more than 100 scientists, staff and studentsfrom 20 institutes, to operate two well-equipped super-sites, aircraft measurements, meteorologicalsoundings, as well as 16 routine sites of the PRD regional air quality monitoring network (Figure14).Figure 14 - Overview of PRIDE-PRDcampaign in 2004 and 2006270

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESThe successful accomplishment of the PRIDE-PRD campaigns deepened theunderstanding of regional air pollution and its environmental effects in the PRD. The results werepublished in a special issue of Atmospheric Environment for PRIDE-PRD2004 and in AtmosphericChemistry and Physics for PRIDE-PRD2006 as well as in other peer reviewed journals, i.e.,Science, JGR, and GRL. The important findings made by PRIDE-PRD are summarized in Table 2.PRIDE-PRD plays a very important role in the decision making process of the PRD localgovernment to implement regional management on basis of multi-pollutants and multi-objectives ofair quality. As one of consequences, Guangdong provincial government recently launched China’sfirst clean air initiative programme in PRD with focus on regional photochemical smog and regionalhaze. Meanwhile, MOST and Guangdong provincial government set up a major project called“Synthesized Prevention Techniques for Air Pollution Complex and Integrated Demonstration inKey City-Cluster Region (3C-STAR)” to help the PRD authority to build up the capacity of regionalair pollution control strategies, regional coordination mechanisms, and related joint actions. A 3-Dregional measurement network and real-time ensemble air quality forecasting system will be in useby the end of 2010, providing the basis for regional air quality management and further fundamentresearch on the complex air pollution in this region.OverviewTable 2 - Summary of findings by PRIDE-PRDTopic Major findings ReferencesInstrumentationBoundarymeteorologyOH/HO2/O3Introduction to PRIDE-PRD and major finding in [Zhang et al., 2008a]PRIDE-PRD2004 campaignAn instrument for measurement of atmospheric peroxy [Li et al., 2009]radical by chemical amplificationThree inversion layers were identified [Fan et al., 2008]HOX measurements and unknown recyclingRegional high O3 mainly comes from chemical production271[Hofzumahaus, et al., 2009; Lou et al.,2010; Lu et al., 2010; Wang et al., 2010;Zhang et al., 2008b]O3 production and its sensitivity to VOCs and NOXVOCs VOC speciation and source apportionment. [Liu Y. et al., 2008; 2008b; 2008c; WangJ.L. et al., 2008]H2O2 and PAN High concentrations were found in secondary pollutants [Hua et al., 2008;Wang et al., 2010]HONOVertical profiles ofair pollutionAerosol chemicaland opticalpropertiesAerosoldistributionECsizeAerosol watersoluble ionsSulfateSOAHigh concentration was found during the daytime andemissions from unknown sources with a photo-enhancedmechanism were estimatedHigh loadings of air pollution were found and theboundary layer height was determined by LIDARSulfate and OC/EC were major components of fineaerosol and major contributors to visibility degradation.Relative humidity dependence of aerosol opticalproperties was identified.New particle formation phenomenon was found andgrowth rate was estimatedHygroscopicity of aerosol was measured and numericallysimulatedEC mixing state was identified by numerical closuremodellingTemporal variation of EC was studiedNitrate-HNO3 partitioning in equilibrium was identified.water-soluble organic carbon aerosols were measuredSulfate production in submicron mode can be explainedby OH and SO2 reactionSOA was estimated by PMF and EC tracermethod[Qin et al., 2009; Su et al., 2008a;2008b][Ansmann et al., 2005; Mueller et al.,2006; Wang W. et al., 2008; Wendischet al., 2008; Sugimoto et al., 2009;Tesche et al., 2008; Tomoaki et al.,2010][Andreae et al., 2008; Cheng, 2008a;2008b; Gnauk et al., 2008; Garland etal., 2008; Jung et al., 2009; Liu S et al.,2008b; Liu X. et al., 2008][Liu S et al., 2008a; Gong et al., 2008;2010; Eichler et al., 2008; Rose et al.,2008][Cheng et al., 2006; Verma et al., 2009][Hu et al., 2008; Miyazaki et al., 2009][Xiao et al., 2009; 2011]

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIES7.10 INTEGRATED FOCUS ON WEST AFRICAN CITIESC. Liousse (1) , C. Galy-Lacaux (1) , E. Assamoi (1) , A. Ndiaye (2) , B. Diop (3) , H. Cachier (4) , T. Doumbia (1, 2) ,P. Gueye (2) , N. Marchand (5) , A. Ehgere (5) , A. Baeza (6) , S. Val (6) , I. George (6) , V. Yoboué (7) , L. Sigha (8) ,J.P. Lacaux (1) , B. Guinot (1) , J.F. Léon (1) , R. Rosset (1) , P. Castéra (1) , E. Gardrat (1) , C. Zouiten (9) , C. Jambert (1) ,A. Diouf (2) , O. Koita (3) , I. Annesi-Maesano (10) , A. Didier (11) , S. Audry (9) , A. Konaré (7)(1) Laboratoire d'Aérologie, UMR 5560 CNRS/UPS, Toulouse, France(2) Université C. A. Diop, Dakar, Sénégal(3) Université de Bamako, Mali(4) LSCE, Gif sur Yvette, France(5) LCP, Université d’Aix Marseille, Marseille, France(6) LCTC Université Paris Diderot-Paris 7, France(7) LAPA, Université d’Abidjan, Ivory Coast(8) CRH, Yaoundé, Cameroon(9) LMTG, Toulouse, France(10) Faculté de Médecine Saint-Antoine, Paris, France(11) Hôpital Larrey, Toulouse, FranceIntegrated Focus on West African cities (Cotonou, Bamako, Dakar, Ouagadougou, Abidjan,Niamey): Emissions, Air Quality, and Health Impacts of gases and aerosols in the frame ofAMMA and POLCA international programmes.West African cities are largely devoid of dedicated air quality monitoring stations, togetherwith no significant application of regulations. However fossil fuel and biofuel emissions of gases andparticles are highly emitted from traffic, transportation, domestic fires, wastes, tailings and industrialactivities. These emissions result in very poor still degrading air quality, exacerbated by the weatherand climate conditions, as can be readily realized on site. Clearly, this picture is still darkening dueto rapid sprawling urban growth into African megacities. Ensuing air quality degradation thus raisessevere public health problems such as respiratory and cardiovascular ailments.The POLlution in the African Capitals (POLCA) programme under the IDAF (IGAC DEBITSAfrica) framework jointly with the Laboratoire d'Aérologie (LA) as well as several Africanlaboratories took place in eight African capitals (Abidjan, Dakar, Bamako, Niamey, Ouagadougou,Bangui, Brazzaville, Yaounde). The preliminary results have highlighted the pressing urbanpollution problem in West Africa. As shown in Figure 15, measurements showed highconcentrations of NO 2 , SO 2 , etc. that regularly exceed the WHO air quality limits [Liousse andGaly-Lacaux, 2010].Within the African Monsoon Multidisciplinary Analysis (AMMA) and MOUSSON programmes(2005 - 2009), field studies were organized for the short term (May 2005) in Cotonou, Benin and forthe long term (2007-2009) in Ouagadougou (Burkina Faso) focusing on gas and aerosolconcentration measurements. These programmes have also revealed quite high particulate matterlevels. In addition, combustion emission inventories have been developed for African fossil andbiofuel emission sources [Assamoi and Liousse, 2010] for 2005 and 2030 (Figure 18).This context has proven to offer a unique opportunity to develop the POLCA programme intoa trans-disciplinary study between emissions, air quality and health impacts in West African cities.POLCA is now supported by the CORUS programmes(http://www.ird.fr/fr/science/dsf/corus/english_termes_reference.pdf) under the auspices of theFrench Ministry of Foreign Affairs (MFA), in partnership with African organizations.Within this framework, we have constructed a new integrated methodology that includes: (1)combustion emission characterizations; (2) joint experimental determination of gas concentrations(such as NO 2 , SO 2 , NH 3 , HNO 3 , O 3 , COV), size differentiated aerosol chemistry (total mass) (Figure16) [Doumbia et al., 2011], organic fraction (PAH), carbonaceous particles, inorganic particles(sulphates, nitrates…) and elements traces (iron, lead…) from ultrafine to coarse size fractions(Figure 17) [Val et al., 2011], as well as in vitro toxicological measurements (oxidative stress272

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESestimations through citokynes measurements). Some representative individuals (cohort) who live inpolluted areas and have experienced long-term exposure at the measurement sites have beenselected and will be tested for blood and spirometry analyses. Long-term follow up of diseases arealso obtained from local hospitals for epidemiological studies (3) integrated environmental-healthmodelling. Exposures obtained from modelling associated with satellite investigations are related toa new dedicated aerosol/gas module developed for intake, deposition and clearance of gases andparticles in the respiratory tract. Dakar and Bamako were first selected to initiate this study, whichwill soon be extended to Yaoundé (Cameroon) and Cotonou (Benin). Through extension of thelong-term IDAF network to correlated human health problems and air pollution, this integrativeprogramme aims at developing for Africa a new emerging multidisciplinary approach linkingenvironmental changes and health.Figure 16 - Monthly PM2.5 concentrations in Dakar (from June 2008 to May 2009) [Doumbia et al., 2011]Figure 17 - Size speciated chemical aerosol composition in Dakar and in Bamako during (BK1) and after (BK2) a dust event[Val et al., 2011]273

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESFigure 18 - Picture from Cotonou (Benin)Keywords: Health-environment-climate; Aerosol and chemistry; traffic; biofuel; health impacts.E-mail address: lioc@aero.obs-mip.frOMP: Observatoire Midi-Pyrénées, IDAF: IGAC/DEBITS/AFrique International Global AtmosphericChemistry, Deposition of Biogeochemical Trace Species/AFrique, POLCA: POllution of AfricanCapitals (http://www.redgems.org/spip.php?rubrique55), AMMA: African Monsoon andMultidisciplinary Analyses MOUSSON : http://mousson.csregistry.org/tiki-index.php.274

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIES7.11 GAW URBAN RESEARCH METEOROLOGY AND ENVIRONMENT (GURME) PROJECTThe main focus of the World Meteorological Organization’s GURME project, initiated in 1998,is the important cross-cutting area of urban air quality. GURME addresses the end-to-end aspectsof air quality, linking the observational capabilities of GAW with the needs of chemical weatherprediction, with the goal of providing decision makers and the general public with enhanced airquality services of appropriate quality. Priority activities include the improvement of observingsystems and their integration with urban-scale models and capacity building/training initiatives.Through a training team materials for a basic air quality modelling and forecasting course weredeveloped. These have been modified as per the requirements of each specific training event.GURME provides an international platform for cross-cutting urban air pollution activities,collaborating with other WMO Programmes, international organizations, National Meteorologicaland Hydrological Services (NMHSs), research institutes, academia and environmental agencies.Participation in MEGAPOLI and several European COST actions has been mutually beneficial.GURME pilot projects have been established for several megacities, below are short descriptions.GURME activities are shown in Figure 19, with the so-called “GURME Figure” in the middle.GURME activities are guided by the WMO/GAW Scientific Advisory Group (SAG) forGURME, chaired by Prof. Gregory Carmichael.Observational NeedsChemicalMeteorologicalAssimilationModelling NeedsWeather predictionChemical weather and airquality predictionDemonstrationCoordinationCapacity BuildingWorkshopsTrainingEducationAir Quality & RelatedProductsImproved ForecastsGuidelinesPilot ProjectsUSERSHealthAgricultureEnvironmentalPublicEmergency ResponseDisseminationFigure 19 - Main elements and goals of GURME for the strategic planning period 2008-2015Latin American Cities projectThe Latin American Cities project was originally focused on Mexico City, Santiago and SaoPaulo concentrating on capacity development. The project grew out of the GURME Experts Meetingheld in Cuernavaca, Mexico in October 2002, which was attended by 25 invited participants from 11countries. The first Workshop on Air Quality Forecasting in Latin American Cities was held in275

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESSantiago, Chile in October 2003; this was followed by a WRF-Chem and Remote SensingWorkshop in Sao Paolo, Brazil in 2005. The first GURME basic training course on air qualityforecasting was delivered in July 2006 in Lima, Peru and included participants from the SouthAmerican countries, generally from the NMHSs and Environmental Agencies. A comprehensiveTraining Course on Air Quality Modelling for Latin American Cities Project was held in Mexico City,Mexico in August 2009. Training was held for Central American countries in October 2011. Moreexpert workshops and training courses will be convened in the future as needed. A discussionforum with a network of scientists and groups active in Latin American cities and internationalexperts will be established to facilitate the exchange of information on air quality modelling andforecasting. The main contributors to this project are Luisa Molina, Maria de Fatima Andrade, PauloArtaxo, Pedro Oyola, Rainer Schmitz and Laura Gallardo.Beijing projectThe Study of Mechanism on Atmospheric Environmental Pollution in Capital Beijing projectwas established in 1998. Key scientific problems were:• Environmental and geochemical cycling processes and behaviour of atmospheric pollutants• The accumulative effect and tolerance of atmospheric pollutants in regional environments• The prediction theory of the atmospheric environment• The principles of pollution control on regional scales.The main topics were:• The mechanism of the formation of PBL pollution and its effects on the environment in Beijing• The physical, chemical and ecological function of pollutant between atmosphere and planetaryboundary layer• Formation mechanism of sand-dust and its impact on urban environment in Beijing• Theory and method of city atmosphere environment pollution monitoring and forecasting• Atmospheric environment pollution regulation and tackling technique in a comprehensive way.Shanghai projectShanghai faces multiple hazards, it is frequently affected by natural hazards such astyphoons, storm surges, heavy fog, heat-waves, and also by atmospheric pollution. Shanghai Expo– successfully launched new air quality and related services as a component of the Expo MultiHazard Early Warning System (MHEWS) Demonstration Project. The project under the leadershipof Xu Tang, Director General, Shanghai Regional Meteorological Center, CMA, is designed toexplore the full potentials of urban life in the 21st century. Key elements of the project are todisclose the physical and chemical mechanisms during the formation, transportation andtransformation processes of the main air pollutants in the Shanghai area, to establish an airpollution prediction system for the Shanghai area, and to improve the assessment techniques ofenvironmental quality. The observation capacity was increased considerably. Based on variousmeasurements (meteorological and environmental observations, diseases diagnostics) new andcomprehensive forecast products to support public health services were developed anddemonstrated during Expo. The services include those for air quality, pollen, food poisoning andheat stroke, among others. Through these services effective actions to protect the health ofindividuals, especially those in sensitive groups, will be designed. The project continues with furtherdevelopment of the public health services focus.Commonwealth Games New DelhiThe Indian Institute of Tropical Meteorology (IITM), Pune, a constituent under the Ministry ofEarth Sciences, Government of India, with Gufran Beig as the co-ordinator, led the country's firstmajor initiative on air quality forecasting, named as "System of Air Quality forecasting and Research(SAFAR)". It has been successfully tested during the commonwealth Games 2010 for NationalCapital Region Delhi. Currently SAFAR is being spread to other major cities in India.276

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESSAFAR provides location specific information on Air Quality in near real time and it isforecast 24 hours in advance. It is complemented by the weather forecasting system designed byIMD, New Delhi. The ultimate objective is to increase the awareness among the general publicregarding the air quality in their city, well in advance, so that appropriate mitigation action andsystematic measures can be taken up for the betterment of air quality and related health issues.More information is available on the GURME webpage at: http://mce2.org/wmogurme/ReferencesAlonso, M. F., Longo, K. M., Freitas, S. R., Fonseca, R. M. d., Marécal, V., Pirre, M., & Klenner, L. G.(2010). An urban emissions inventory for South America and its application in numericalmodeling of atmospheric chemical composition at local and regional scales. AtmosphericEnvironment, 44(39), 5072-5083. doi: 10.1016/j.atmosenv.2010.09.013Andreae, M. O., Schmid, O., Yang, H., Chand, D., Yu, J. Z., Zeng, L.-M., & Zhang, Y.-H. (2008).Optical properties and chemical composition of the atmospheric aerosol in urbanGuangzhou, China. Atmospheric Environment, 42(25), 6335-6350. doi:10.1016/j.atmosenv.2008.01.030Ansmann, A., Engelmann, R., Althausen, D., Wandinger, U., Hu, M., Zhang, Y., & He, Q. (2005).High aerosol load over the Pearl River Delta, China, observed with Raman lidar and Sunphotometer. Geophys. Res. Lett., 32(L13815). doi: 10.1029/2005GL023094.Assamoi, E.-M., & Liousse, C. (2010). A new inventory for two-wheel vehicle emissions in WestAfrica for 2002. Atmos. Environ., 44(32), 3985-3996. doi:doi:10.1016/j.atmosenv.2010.06.048Behrentz, E., Sánchez, B., Fandiño, M., & Rodriguez, P. (2009). Inventario de emisionesprovenientes de fuentes fijas y móviles.Cheng, Y. F., Eichler, H., Wiedensohler, A., Heintzenberg, J., Zhang, Y. H., Hu, M., Herrmann, H.,Zeng, L.M., Liu, S., Gnauk, T., Bruggemann, E., and He, L. Y. (2006). Mixing state ofelemental carbon and non-light-absorbing aerosol component derived from in situ particleoptical properties at Xinken in Pearl River Delta of China. J. Geophys. Res.-Atmos.,111(D20204), 18. doi: 10.1029/2005JD006929Cheng, Y. F., Wiedensohler, A., Eichler, H., Heintzenberg, J., Tesche, M., Ansmann, A., Wendisch,M., Su, H., Althanusen, D., Herrmann, H., Gnauk, T., Bruggemann, E., Hu, M., and Zhang, Y.H. (2008b). Relative humidity dependence of aerosol optical properties and direct radiativeforcing in the surface boundary layer of at Xinken in Pearl River Delta of China: anobservation based numerical study. Atmospheric Environment, 42(25), 6373-6397. doi:10.1016/j.atmosenv.2008.04.009Cheng, Y. F., Wiedensohler, A., Eichler, H., Su, H., Gnauk, T., Brüggemann, E., Hermann, H.,Heintzenberg, J., Slanina, J., Tuch, T., Hu, M., and Zhang, Y. H. (2008a). Aerosol opticalproperties and related chemical apportionment at Xinken in Pearl River Delta of China.Atmospheric Environment, 42(25), 6351-6372. doi: 10.1016/j.atmosenv.2008.02.034D'Almeida, E., Delgado, R., Rodrigues, L., Baeza, C., Silva, L. d., Gallardo, L., Longo, K., andFreitas, S. (2008). SAEMC_GRID: South America Megacities Emissions and Climate Grid.Campo Grande, Brazil: Latin American Grid (LAGrid) workshop.D'Angiola, A., Dawidowski, L. E., Gómez, D. R., & Osses, M. (2010). On-road traffic emissions in amegacity. Atmospheric Environment, 44(4), 483-493. doi: 10.1016/j.atmosenv.2009.11.004Doumbia, T., Liousse, C., Galy-Lacaux, C., Ndiaye, A.N., Diop, B., Oufa, M., Assamoi, E.M.,Gardrat, E., Castera, P., Rosset, R., Akpo, A., and Sigha, L. (2011). Real time black carbonmeasurements in West Africa urban sites. Atmos. Environ., 54, 529-532, doi:10.1016/j.atmosenv.2012.02.005277

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESEichler, H., Cheng, Y. F., Birmili, W., Nowak, A., Wiedensohler, A., Brüggemann, E., Gnauk, T.,Hermann, H., Althausen, D., Ansmann, A., Engelmann, R., Tesche, M., Wendisch, M.,Zhang, Y.H., Hu, M., Liu, S. and Zeng, L. M. (2008). Hygroscopic properties and extinctionof aerosol particles at ambient relative humidity in South-Eastern China. AtmosphericEnvironment, 42(25), 6321-6334. doi: 10.1016/j.atmosenv.2008.05.007Fan, S., Wang, B., Tesche, M., Engelmann, R., Althausen, A., Liu, J., Zhu, W., Fan, Q., Li, M., Ta,N., Song, L., and Leong, K. (2008). Meteorological conditions and structures of atmosphericboundary layer in October 2004 over Pearl River Delta area. Atmospheric Environment,42(25), 6174-6186. doi: 10.1016/j.atmosenv.2008.01.067Fehsenfeld, F. C., Ancellet, G., Bates, T. S., Goldstein, A. H., Hardesty, R. M., Honrath, R., Law,K.S., Lewis, A.C., Lealtch, R., McKeen, S., Meagher, J., Parrish, D.D., Pszenny, A.A.P.,Russell, P.B., Schlager, H., Seinfeld, J., Talbot, R., and Zbinden, R. (2006). InternationalConsortium for Atmospheric Research on Transport and Transformation (ICARTT): NorthAmerica to Europe-Overview of the 2004 summer field study. J. Geophys. Res.,111(D23S01). doi: 10.1029/2006JD007829Freitas, S., Longo, K., Dias, M. S., Dias, P. S., Chatfield, R., Prins, E., Artaxo, P., and Recuero, F.(2005). Monitoring the transport of biomass burning emissions in South America.Environmental Fluid Mechanics, 5(1-2), 135-167. doi: 10.1007/s10652-005-0243-7Freitas, S. R., Longo, K. M., Dias, M. A. F. S., Chatfield, R., Dias, P. S., Artaxo, P., Andreae, M.O.,Grell, G., Rodrigues, L.F., Fazenda, A., and Panetta, J. (2009). The Coupled Aerosol andTracer Transport model to the Brazilian developments on the Regional AtmosphericModeling System (CATT-BRAMS) - Part 1: Model description and evaluation. Atmos. Chem.Phys., 9(8), 2843-2861. doi: 10.5194/acp-9-2843-2009Garland, R. M., Yang, H., Schmid, O., Rose, D., Nowak, A., Achtert, P., Wiedensohler, A.,Takegawa, N., Kita, K., Kondo, Y., Hu, M., Shao, M., Zeng, L.M., Zhang, Y.H., Andreae,M.O., and Pöschl, U. (2008). Aerosol optical properties in a rural environment near themega-city Guangzhou, China: implications for regional air pollution, radiative forcing andremote sensing Guangzhou, China: implications for regional air pollution, radiative forcingand remote sensing. Atmos. Chem. Phys., 8(17), 5161-5186. doi: 10.5194/acp-8-5161-2008Gnauk, T., Müller, K., Pinxteren, D. v., He, L.-Y., Niu, Y., Hu, M., & Herrmann, H. (2008).Size-segregated particulate chemical composition in Xinken, Pearl River Delta, China:OC/EC and organic compounds. Atmospheric Environment, 42(25), 6296-6309. doi:10.1016/j.atmosenv.2008.05.001Gong, Y., Su, H., Cheng, Y., Liu, F., Wu, Z., Hu, M., Zeng, L., and Zhang, Y. (2008). Analysis onConcentration and Source Rate of Precursor Vapors Participating in Particle Formation andGrowth at Xinken in Pearl River Delta of China. Advances in Atmospheric Sciences, 25(3),427-436.Hoelzemann, J. J., Longo, K. M., Fonseca, R. M., Rosário, N. M. E. d., Elbern, H., Freitas, S. R., &Pires, C. (2009). Regional representativity of AERONET observation sites during thebiomass burning season in South America determined by correlation studies with MODISAerosol Optical Depth. J. Geophys. Res., 114(D13301). doi: 10.1029/2008JD010369Hofzumahaus, A., Rohrer, F., Lu, K., Bohn, B., Brauers, T., Chang, C.-C., Fuchs, H., Holland, F.,Kita, K., Kondo, Y., Li, X., Lou, S., Shao, M., Zeng, L., Wahner, A., and Zhang, Y. (2009).Amplified Trace Gas Removal in the Troposphere. Science, 324, 1702-1704.Hu, M., Wu, Z., Slanina, J., Lin, P., Liu, S., & Zeng, L. (2008). Acidic gases, ammonia andwater-soluble ions in PM2.5 at a coastal site in the Pearl River Delta, China. AtmosphericEnvironment, 42(25), 6310-6320. doi: 10.1016/j.atmosenv.2008.02.015Hua, W., Chen, Z. M., Jie, C. Y., Kondo, Y., Hofzumahaus, A., Takegawa, N., Chang, C.C., Lu, K.D.,Miyazaki, Y., Kita, K., Wang, H.L., Zhang, Y.H., and Hu, M. (2008). Atmospheric hydrogenperoxide and organic hydroperoxides during PRIDE-PRD'06, China: their concentration,formation mechanism and contribution to secondary aerosols. Atmos. Chem. Phys., 8(22),6755-6773. doi: 10.5194/acp-8-6755-2008278

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESJung, J., Lee, H., Kim, Y. J., Liu, X., Zhang, Y., Gu, J., & Fan, S. (2009). Aerosol chemistry and theeffect of aerosol water content on visibility impairment and radiative forcing in Guangzhouduring the 2006 Pearl River Delta campaign. J. Environ. Manage., 90(11), 3231-3244. doi:10.1016/j.jenvman.2009.04.021Kanaya, Y., Cao, R., Akimoto, H., Fukuda, M., Komazaki, Y., Yokouchi, Y., Koike, M., Tanimoto, H.,Takegawa, N. and Kondo, Y. (2007). Urban photochemistry in central Tokyo: 1. Observedand modeled OH and HO 2 radical concentrations during the winter and summer of 2004. J.Geophys. Res.-Atmos., 112(D21312), 20. doi: 10.1029/2007JD008670Kanaya, Y., Fukuda, M., Akimoto, H., Takegawa, N., Komazaki, Y., Yokouchi, Y., Koike, M., andKondo, Y. (2008). Urban photochemistry in central Tokyo: 2. Rates and regimes of oxidant(O 3 + NO 2 ) production. J. Geophys. Res.-Atmos., 113(D06301). doi:10.1029/2007JD008671Kannari, A., Tonooka, Y., Baba, T., & Murano, K. (2007). Development of multiple-species1km×1km resolution hourly basis emissions inventory for Japan. Atmospheric Environment,41(16), 3428-3439. doi: 10.1016/j.atmosenv.2006.12.015Kita, K., Morino, Y., Kondo, Y., Komazaki, Y., Takegawa, N., Miyazaki, Y., .Hirokawa, J., Tanaka, S.,Thompson, T.L., Gao, R-.,S., and Fahey, D. W. (2006). A chemical ionization massspectrometer for ground-based measurement of nitric acid. J. Atmos. Oceanic Technol., 23,1104-1113. doi: 10.1175/JTECH1900.1Kondo, Y., Komazaki, Y., Miyazaki, Y., Moteki, N., Takegawa, N., Kodama, D., Deguchi, S., Nogami,M., Fukuda, M., Miyakawa, T., Morino, Y., Koike, M., Sakural, H., and Ehara, K. (2006).Temporal variations of elemental carbon in Tokyo. J. Geophys. Res.-Atmos., 111(D12205),17. doi: 10.1029/2005JD006257Kondo, Y., Miyazaki, Y., Takegawa, N., Miyakawa, T., Weber, R. J., Jimenez, J. L., Zhang, Q., andWorsnop, D. R. (2007). Oxygenated and water-soluble organic aerosols in Tokyo. J.Geophys. Res.-Atmos., 112(D01203), 11. doi: 10.1029/2006JD007056Kondo, Y., Morino, Y., Fukada, M., Kanaya, Y., Miyazaki, Y., Takegawa, N., Tanimoto, H.,McKenzie, R., Johnston, P., Blake, D.R., Murayama, T., and Koike, M. (2008). Formationand transport oxidized reactive nitrogen, ozone, and secondary organic aerosol in Tokyo. J.Geophys. Res.-Atmos., 113(D21310), 23. doi: 10.1029/2008JD010134Kondo, Y., Takegawa, N., Matsui, H., Miyakawa, T., Koike, M., Miyazaki, Y., .Kanaya, Y., Mochida,M., Kuwata, M., Morino, Y., and Shiraiwa, M. (2010). Formation and transport of aerosols inTokyo in relation to their physical and chemical properties: a review. J. Meteorol. Soc. Japan,88(4), 597-624.Kuwata, M., & Kondo, Y. (2009). Measurements of particle masses of inorganic salt particles forcalibration of cloud condensation nuclei counters. Atmos. Chem. Phys., 9(1), 4653-4689. doi:10.5194/acpd-9-4653-2009Kuwata, M., Kondo, Y., & Takegawa, N. (2009). Critical condensed mass for activation of blackcarbon as cloud condensation nuclei in Tokyo. J. Geophys. Res.-Atmos., 114(D20202), 9.doi: 10.1029/2009JD012086Li, X., Qi, B., Zeng, L., & Tang, X. (2009). Development and deployment of an instrument formeasurement of atmospheric peroxy radical by chemical amplification. Science in ChinaSeries D: Earth Sciences, 52(3), 333-340. doi: 10.1007/s11430-009-0032-0Liousse, C., & Galy-Lacaux, C. (2010). Pollution urbaine en Afrique de l'Ouest.Liu, S., Hu, M., Slanina, S., He, L.-Y., Niu, Y.-W., Bruegemann, E., Gnauk, T., and Herrmann, H.(2008b). Size distribution and source analysis of ionic compositions of aerosols in pollutedperiods at Xinken in Pearl River Delta (PRD) of China. Atmospheric Environment, 42(25),6284-6295. doi: 10.1016/j.atmosenv.2007.12.035Liu, S., Hu, M., Wu, Z., Wehner, B., Wiedensohler, A., & Cheng, Y. (2008a). Aerosol number sizedistribution and new particle formation at a rural/coastal site in Pearl River Delta (PRD) ofChina. Atmospheric Environment, 42(25), 6275-6283. doi: 10.1016/j.atmosenv.2008.01.063279

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESLiu, X., Cheng, Y., Zhang, Y., Jung, J., Sugimoto, N., Chang, S.-Y., Kim, Y.J., Fan, S., and Zeng, L.(2008). Influences of relative humidity and particle chemical composition on aerosolscattering properties during the 2006 PRD campaign. Atmospheric Environment, 42(7),1525-1536. doi: 10.1016/j.atmosenv.2007.10.077Liu, Y., Shao, M., Fu, L., Lu, S., Zeng, L., & Tang, D. (2008b). Source profiles of volatile organiccompounds (VOCs) measured in China: Part I, Atmospheric Environment. AtmosphericEnvironment, 42(25), 6247-6260. doi: 10.1016/j.atmosenv.2008.01.070Liu, Y., Shao, M., Lu, S., Chang, C.-C., Wang, J.-L., & Fu, L. (2008a). Source apportionment ofambient volatile organic compounds in the Pearl River Delta, China: Part II. AtmosphericEnvironment, 42(25), 6261-6274. doi: 10.1016/j.atmosenv.2008.02.027Longo, K. M., Freitas, S. R., Andreae, M. O., Yokelson, R., & Artaxo, P. (2009). Biomass burning,long range transport of products and regional and remote impacts. In M. Keller, M.Bustamante, J. Gash & P. Dias (Eds.), Amazonia and Global Change: AmericanGeophysical Union.Lou, S., Holland, F., Rohrer, F., Bohn, B., Brauers, T., Chang, C. C., Fuchs, H., Haseler, R., Kita, K.,Kondo, Y., Li, X., Shao, M., Zeng, L., Wahner, A., Zhang, Y., Wang, W., and Hofzumahaus,A. (2010). Atmospheric OH reactivities in the Pearl River Delta -China in summer 2006:measurement and model results. Atmos. Chem. Phys., 10(22), 11243-11260. doi:10.5194/acp-10-11243-2010Lu, K., Zhang, Y., Su, H., Brauers, T., Chou, C. C., Hofzumahaus, A., Liu, S.C., Kita, K., Kondo, Y.,Shao, M., Wahner, A., Wang, J., Wang, X., and Zhu, T. (2010). Oxidant (O 3 +NO 2 )production processes and formation regimes in Beijing. J. Geophys. Res.-Atmos.,115(D07303). doi: 10.1029/2009JD012714Lu, K., Zhang, Y., Su, H., Shao, M., Zeng, L., Zhong, L. J., Xiang, Y.R., Chang, C.C. Chous, C.K.C.,and Wahner, A. (2010). Regional ozone pollution and key controlling factors ofphotochemical ozone production in Pearl River Delta during summer time. Science ChinaChemistry, 53(3), 651-663. doi: 10.1007/s11426-010-0055-6Martins, L., Martins, J. A., Freitas, E. D., Mazzoli, C. R., Gonçalves, F. L. T., Ynoue, R. Y., .Hallak,R., Alburquerque, T.T.A., and Andrade, M. d. F. (2010). Potential Health Impact of UltrafineParticles Under Clean and Polluted Urban Atmospheric Conditions: A Model-Based Study.Air Qual. Atmos. Health, 3(1), 29-39. doi: 10.1007/s11869-009-0048-9Matsui, H., Koike, M., Kondo, Y., Takegawa, N., Fast, J. D., Pöschl, U., Garland, R.M., Andreae,M.O., Wiedensohler, A., Sugimoto, N., and Zhu, T. (2010). Spatial and temporal variations ofaerosols around Beijing in summer 2006: 2. Local and column aerosol optical properties. J.Geophys. Res.-Atmos, 115(D22207), 20. doi: 10.1029/2010JD013895Matsui, H., Koike, M., Kondo, Y., Takegawa, N., Kita, K., Miyazaki, Y., Hu, M., Change, S.-Y., Blake,D.R., Fast, J.D., Zaveri, R.A., Streets, D.G., Zhang, Q., and Zhu, T. (2009). Spatial andtemporal variations of aerosols around Beijing in the summer 2006: Model evaluation andsource apportionment. J. Geophys. Res.-Atmos., 114(D00G13), 22. doi:10.1029/2008JD010906Matsui, H., Koike, M., Takegawa, N., Kondo, Y., Griffin, R. J., Miyazaki, Y., Yokouchi, Y., and Ohara,T. (2009). Secondary organic aerosol formation in urban air: Temporal variations andpossible contributions from unidentified hydrocarbons. J. Geophys. Res.-Atmos.,114(D04201), 22. doi: 10.1029/2008JD010164Miyakawa, T. (2008). Submicron aerosols in the Tokyo megacity region: Photochemical evolutionand transport. PhD, University of Tokyo.Miyakawa, T., Takegawa, N., & Kondo, Y. (2007). Removal of sulfur dioxide and formation of sulfateaerosol in Tokyo. J. Geophys. Res.-Atmos., 112(D13209), 13. doi: 10.1029/2006JD007896Miyakawa, T., Takegawa, N., & Kondo, Y. (2008). Photochemical evolution of submicron aerosolchemical composition in the Tokyo megacity region in summer. J. Geophys. Res.-Atmos.,113(D14304), 18. doi: 10.1029/2007JD009493280

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESMiyazaki, Y., Kondo, Y., Shiraiwa, M., Takegawa, N., Miyakawa, T., Han, S., Kita, K., Hu, M., Deng,Z.Q., Zhao, Y., Sugimoto, N., Blake, D.R., and Weber, R. J. (2009). Chemicalcharacterization of water-soluble organic carbon aerosols at a rural site in the Pearl RiverDelta, China, in the summer of 2006. J. Geophys. Res., 114(D14208), 13. doi:10.1029/2009JD011736Miyazaki, Y., Kondo, Y., Takegawa, N., Komazaki, Y., Fukuda, M., Kawamura, K., Mochida, M.,Okuzawa, K., and Weber, R. J. (2006). Time-resolved measurements of water-solubleorganic carbon in Tokyo. J. Geophys. Res.-Atmos., 111(D23206), 12. doi:10.1029/2006JD007125Mochida, M., & Kawamura, K. (2004). Hygroscopic properties of levoglucosan and related organiccompounds characteristic to biomass burning aerosol particles. J. Geophys. Res.-Atmos.,109(D21202), 8. doi: 10.1029/2004JD004962Mochida, M., Kuwata, M., Miyakawa, T., Takegawa, N., Kawamura, K., & Kondo, Y. (2006).Relationship between hygroscopicity and cloud condensation nuclei activity for urbanaerosols in Tokyo. J. Geophys. Res.-Atmos., 111(D23204), 20. doi: 10.1029/2005JD006980Mochida, M., Miyakawa, T., Takegawa, N., Morino, Y., Kawamura, K., & Kondo, Y. (2008).Significant alteration in the hygroscopic properties of urban aerosol particles by thesecondary formation of organics. Geophys. Res. Lett., 35(L02804), 6. doi:10.1029/2007GL031310Molina, L. T., Kolb, C. E., Foy, B. d., Lamb, B. K., Bruce, W. H., Jimenez, J. L., Ramos-Villegas, R.,Sarmiento, J., Paramo-Figueroa, V.H., Cardenas, B., Gutierrez-Avedoy, V., and Molina, M. J.(2007). Air quality in North America's most populous city-overview of MCMA-2003 campaign.Atmos. Chem. Phys., 7(10), 2447-2473. doi: 10.5194/acp-7-2447-2007Molina, L. T., Madronich, S., Gaffney, J. S., Apel, E., Foy, B. d., Fast, J., Ferrare, R., Herdon, S.,Jimenez, J.L., Lamb, B., Osornio-Vargas, A.R., Russell, P., Schauer, J.J., Stevens, P.S.,Volkamer, R., and Zavala, M. (2010). An overview of the MILAGRO 2006 campaign: MexicoCity emissions and their transport and transformation. Atmos. Chem. Phys., 10(18),8697-8760. doi: 10.5194/acp-10-8697-2010Molina, M. J., & Molina, L. T. (2004). Megacities and Atmospheric Pollution. J. Air & Waste Mange.Assoc., 54, 644-680.Morino, Y., Kondo, Y., Takegawa, N., Miyazaki, Y., Kita, K., Komazaki, Y., Fukuda, M., Miyakawa,T., Moteki, N., and Worsnop, D. R. (2006). Partitioning of HNO 3 and particulate nitrate overTokyo: Effect of vertical mixing. J. Geophys. Res.-Atmos., 111(D15215). doi:10.1029/2005JD006887Moteki, N., & Kondo, Y. (2007). Effects of mixing state on black carbon measurements byLaser-Induced Incandescence. Aerosol Sci. and Tech., 41(4), 398-417. doi:10.1080/02786820701199728Moteki, N., & Kondo, Y. (2008). Method to measure time-dependent scattering cross sections ofparticles evaporating in a laser beam. J. Aerosol Sci., 39(4), 348-364. doi:10.1016/j.jaerosci.2007.12.002Müller, D., Tesche, M., Eichler, H., Engelmann, R., Althausen, D., Ansmann, A., Cheng, Y.F., Zhang,Y.H., and Hu, M. (2006). Strong particle light absorption over the Pearl River Delta (southChina) and Beijing (north China) determined from combined Raman lidar and Sunphotometer observations. Geophys. Res. Lett., 33(L20811), 4. doi: 10.1029/2006GL027196Nishizawa, T., Sugimoto, N., Matsui, I., Shimizu, A., Liu, X., Zhang, Y., Li, R., and Liu, J. (2010).Vertical distribution of water-soluble, seasalt, and dust aerosols in the planetary boundarylayer estimated from two-wavelength backscatter and one-wavelength polarization lidarmeasurements in Guangzhou and Beijing, China. Atmospheric Research, 96(4), 602-611.doi: 10.1016/j.atmosres.2010.02.002Ohara, T., Akimoto, H., Kurokawa, J., Horii, N., Yamaji, K., Yan, X., & Hayasaka, T. (2007). AnAsian emission inventory of anthropogenic emission sources for the period of 1980-2020.Atmos. Chem. Phys., 7(16), 4419-4444. doi: 10.5194/acp-7-4419-2007281

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESQin, M., Xie, P., Su, H., Gu, J., Peng, F., Li, S., Zeng, L., Liu, J., Liu, W., and Zhang, Y. (2009). Anobservational study of the HONO-NO 2 coupling at an urban site in Guangzhou City, SouthChina. Atmospheric Environment, 43(36), 5731-5742. doi: 10.1016/j.atmosenv.2009.08.017Ramanathan, V., Li, F., Ramana, M. V., Praveen, P. S., Kim, D., Corrigan, C. E., Nguyen, H., Sonte,E.A., Schauer, J.J., Carmichael, G.R., Adhikary, B., and Yoon, S. C. (2007). Atmosphericbrown clouds: Hemispherical and regional variations in long-range transport, absorption,and radiative forcing. J. Geophys. Res.-Atmos., 112(D22S21), 26. doi:10.1029/2006JD008124Romero-Lankao, P., Wilhelmi, O., Borbor, M. C., Parra, D., Behrentz, E., & Dawidowski, L. (2011).The Changing Environment for Human Security: New Agendas for Research, Policy, andAction. In K. O'Brien, L. Sygna & J. Wolf (Eds.). Oslo Norway.Romero-Lankao, P., Wilhelmi, O., Borbor, M. C., Parra, D., Behrenz, E., & Dawidowski, L. (2011).Health impacts of weather and air pollution - what current challenges hold for the future inLatin American cities. In K. O'Brien, L. Sygna & J. Wolf (Eds.), The Changing Environmentfor Human Security: New Agendas for Research, Policy ,and Action. Oslo, Norway: GECHS.Rose, D., Nowak, A., Achtert, P., Wiedensohler, A., Hu, M., Shao, M., Zhang, Y., Andreae, M.O.,and Pöschl, U. (2010). Cloud condensation nuclei in polluted air and biomass burningsmoke near the mega-city Guangzhou, China; Part 1: Size-resolved measurements andimplications for the modeling of aerosol particle hygroscopicity and CCN activity. Atmos.Chem. Phys., 10, 3365-3383. doi: 10.5194/acpd-10-3365-2010Saide, P., Bocquet, M., Osses, A., & Gallardo, L. (2011). Constraining surface emissions of airpollutants using inverse modeling: method intercomparison and a new two-step multiscaleapproach. Tellus, 63(3), 360-370. doi: 10.1111/j.1600-0889.2011.00529.xSaide, P., Zah, R., Osses, M., & Eicker, M. O. d. (2009). Spatial disaggregation of traffic emissioninventories in large cities using simplified top-down methods. Atmospheric Environment,43(32), 4914-4923. doi: 10.1016/j.atmosenv.2009.07.013Santos, M. D., Gómez, D., Dawidowski, L., Gautier, E., & Smichowski, P. (2009). Determination ofwater-soluble and insoluble compounds in size classified airborne particulate matter.Microchemical Journal, 91(1), 133-139. doi: 10.1016/j.microc.2008.09.001Shirai, T., Yokouchi, Y., Blake, D. R., Kita, K., Izumi, K., Koike, M., Komazaki, Y., Miyazaki, Y.,Fukuda, M., and Kondo, Y. (2007). Seasonal variations of atmospheric C2–C7 nonmethanehydrocarbons in Tokyo. J. Geophys. Res.-Atmos., 112(D24305). doi:10.1029/2006JD008163Shiraiwa, M., Kondo, Y., Moteki, N., Takegawa, N., Miyazaki, Y., & Blake, D. R. (2007). Evolution ofmixing state of black carbon in polluted air from Tokyo. J. Geophys. Res.-Atmos.,34(L16803), 5. doi: 10.1029/2007GL029819Streets, D. G., Zhang, Q., Wang, L., He, K., Hao, J., Wu, Y., Tang, Y., and Carmichael, G. R. (2006).Revisiting China’s CO emissions after the Transport and Chemical Evolution over the Pacific(TRACE-P) mission: Synthesis of inventories, atmospheric modeling, and observations. J.Geophys. Res.-Atmos., 111(D14306), 16. doi: 10.1029/2006JD007118Su, H., Cheng, Y. F., Cheng, P., Zhang, Y. H., Dong, S., Zeng, L. M., Wang, X., Alanina, J., Shao,M., and Wiedensohler, A. (2008b). Observation of nighttime nitrous acid (HONO) formationat a rural site during PRIDE-PRD2004 in China. Atmospheric Environment, 42(25),6219-6232. doi: 10.1016/j.atmosenv.2008.04.006Su, H., Cheng, Y. F., Shao, M., Gao, D. F., Yu, Z. Y., Zeng, L. M., .Slanina, J., Zhang, Y.H., andWiedensohler, A. (2008a). Nitrous Acid (HONO) and its daytime sources at a rural siteduring the 2004 PRIDE-PRD experiment in China. J. Geophys. Res., 113(D14312), 9. doi:10.1029/2007JD009060Sugimoto, N., Nishizawa, T., Liu, X., Matsui, I., Shimizu, A., Zhang, Y., Kim, Y.J, Li, R., and Liu, J.(2009). Continuous Observations of Aerosol Profiles with a Two-Wavelength Mie-ScatteringLidar in Guangzhou in PRD2006. Journal of Applied Meteorology and Climatology, 48(9),1822-1830. doi: 10.1175/2009JAMC2089.1282

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESTakegawa, N., Miyakawa, T., Kondo, Y., Blake, D. R., Kanaya, Y., Koike, M., Fukuda, M., Komaki,Y., Miyazaki, Y, Shimono, A., and Takeuchi, T. (2006b). Evolution of submicron organicaerosol in polluted air exported from Tokyo. J. Geophys. Res.-Atmos., 33(L15814), 5. doi:10.1029/2006GL025815Takegawa, N., Miyakawa, T., Kondo, Y., Jimenez, J. L., Zhang, Q., Worsnop, D. R., & Fukuda, M.(2006a). Seasonal and diurnal variations of submicron organic aerosol in Tokyo observedusing the Aerodyne aerosol mass spectrometer. J. Geophys. Res.-Atmos., 111(D11206), 17.doi: 10.1029/2005JD006515Takegawa, N., Miyakawa, T., Kuwata, M., Kondo, Y., Zhao, Y., Han, S., Kita, K., Miyazaki, Y., Deng,Z., Xiao, R., Hu, M., van Pinxteren, D., Herrmann, H., Hofzumahaus, A., Holland, F., Wahner,A., Blake, D.R., Sugimoto, N., and Zhu, T. (2009). Variability of submicron aerosol observedat a rural site in Beijing in the summer of 2006. J. Geophys. Res.-Atmos., 114(D00G05), 21.doi: 10.1029/2008JD010857Takegawa, N., Miyakawa, T., Watanabe, M., Kondo, Y., Miyazaki, Y., Han, S., Zhao, Y., vanPinxteren, D., Bruggemann, E., Gnauk, T., Herrmann, H., Xiao, R., Deng, Z., Hu, M., Zhu, T.,and Zhang, Y. (2009). Performance of an Aerodyne Aerosol Mass Spectrometer (AMS)during Intensive Campaigns in China in the Summer of 2006. Aerosol Sci. and Tech., 43(3),189-204. doi: 10.1080/0278682080258225Takegawa, N., Miyazaki, Y., Kondo, Y., Komazaki, Y., Miyakawa, T., Jimenez, J. L., Jayne, J.T.,Worsnop, D.R., Allan, J.D., and Weber, R. J. (2005). Characterization of an AerodyneAerosol Mass Spectrometer (AMS): Intercomparison with other aerosol instruments. AerosolSci. and Tech., 39(8), 760-770. doi: 10.1080/0278682050024340Tang, X., Wang, Z., Zhu, J., Gbaguidi, A. E., Wu, Q., Li, J., & Zhu, T. (2010). Sensitivity of ozone toprecursor emissions in urban Beijing with a Monte Carlo scheme. Atmospheric Environment,44(31), 3833-3842. doi: 10.1016/j.atmosenv.2010.06.026Tesche, M., Müller, D., Ansmann, A., Hu, M., & Zhang, Y. (2008). Retrieval of microphysicalproperties of aerosol particles from one-wavelength Raman lidar and multiwavelength Sunphotometer observations. Atmospheric Environment, 42(25), 6398-6404. doi:10.1016/j.atmosenv.2008.02.014Val, S. (2011). Inflammatory responses of human bronchial epithelial cells due to aerosol pollutionin West Africa in the frame of POLCA/AMMA2 programs. Journal Article. EnvironmentalHealth Perspectives.Vasconcellos, P. C., Souza, D. Z., Simone, G. Á., Araújo, M. P., Naoto, E., Nascimento, K. H.,Cavalcante, F.S., Dos Santos, M., Smichowski, P., and Behrentz, E. (2011). Comparativestudy of the atmospheric chemical composition of three South American cities. AtmosphericEnvironment, 45(32), 5770-5777. doi: 10.1016/j.atmosenv.2011.07.018Verma, R. L., Sahu, L. K., Kondo, Y., Takegawa, N., Han, S., Jung, J. S., Kim, Y.J., Fan, S.,Sugimoto, N., Shammaa, M.H., Zhang, Y.H., and Zhao, Y. (2009). Temporal variation ofblack carbon in Guangzhou, China, in summer 2010. Atmos. Chem. Phys., 10, 6471-6485,doi: 10.5194/acpd-9-24629-2009Wang, B., Shao, M., Roberts, J. M., Yang, G., Yang, F., Hu, M., Zeng, L., Zhang, Y., and Zhang, J.(2010). Ground-based on-line measurements of peroxyacetyl nitrate (PAN) andperoxypropionyl nitrate (PPN) in the Pearl River Delta, China. International Journal ofEnvironmental Analytical Chemistry, 90(7), 548-559. doi: 10.1080/03067310903194972Wang, J.-L., Wang, C.-H., Lai, C.-H., Chang, C.-C., Liu, Y., Zhang, Y., Liu, S, and Shao, M. (2008).Characterization of ozone precursors in the Pearl River Delta by time series observation ofnon-methane hydrocarbons. Atmospheric Environment, 42(25), 6233-6246. doi:10.1016/j.atmosenv.2008.01.050Wang, M., Zhu, T., Zheng, J., Zhang, R. Y., Zhang, S. Q., Xie, X. X., Han, Y.Q., and Li, Y. (2009).Use of a mobile laboratory to evaluate changes in on-road air pollutants during the Beijing2008 Summer Olympics. Atmos. Chem. Phys., 9(21), 8247-8263. doi:10.5194/acp-9-8247-2009283

CHAPTER 7 – OVERVIEW OF INTERNATIONAL COLLABORATIVE RESEARCH ACTIVITIESWang, W., Ren, L., Zhang, Y., Chen, J., Liu, H., Bao, L., Fan, S., and Tang, D. (2008). AircraftMeasurements of Gaseous Pollutants and Particulate matters Over Pearl River Delta inChina. Atmospheric Environment, 42(25), 6187-6202. doi: 10.1016/j.atmosenv.2008.06.001Wang, X., Zhang, Y., Hu, Y., Zhou, W., Lu, K., Zhong, L., Zeng, L., Shao, M., Hu, M., and Russell, A.G. (2010). Process analysis and sensitivity study of regional ozone formation over the PearlRiver Delta of China during the PRIDE-PRD2004 Campaign using the CMAQ model. Atmos.Chem. Phys., 10(9), 4423-4437. doi: 10.5194/acp-10-4423-2010Wehner, B., Berghof, M., Cheng, Y. F., Achtert, P., Birmili, W., Nowak, A., Wiedensohler, A.,Garland, R.M., Poschl, U., Hu, M., and Zhu, T. (2009). Mixing state of non-volatile aerosolparticle fractions and comparison with light absorption in the polluted Beijing region. J.Geophys. Res.-Atmos., 114(D00G17), 16. doi: 10.1029/2008JD010923Wendisch, M., Hellmuth, O., Ansmann, A., Heintzenberg, J., Engelmann, R., Althausen, D., Eichlet,Muller, D., Hu, M., Zhang, Y., and Mao, J. (2008). Radiative and dynamic effects ofabsorbing aerosol particles over the Pearl River Delta, China. Atmospheric Environment,42(25), 6405-6416. doi: 10.1016/j.atmosenv.2008.02.033Wiedensohler, A., Cheng, Y. F., Nowak, A., Wehner, B., Achtert, P., Berghof, M., Birmill, W., Wu,Z.J., Hu, M., Zhu, T., Takegawa, N., Kita, K., Kondo, Y., Lou, S.R., Hofzumahaus, A.,Holland, F., Gunthe, S.S., Rose, D., Su, H., and Pöschl, U. (2009). Rapid aerosol particlegrowth and increase of cloud condensation nucleus activity by secondary aerosol formationand condensation: A case study for regional air pollution in northeastern China. J. Geophys.Res.-Atmos., 114(D00G08), 13. doi: 10.1029/2008JD010884Xiao, R., Takegawa, N., Kondo, Y., Miyazaki, Y., Miyakawa, T., Hu, M., Shao, M., Zeng, L.M.,Hofzumahaus, A., Holland, F., Lu, K., Sugimoto, N., Zhao, Y., and Zhang, Y. H. (2009).Formation of submicron sulfate and organic aerosols in the outflow from the urban region ofthe Pearl River Delta in China. Atmospheric Environment, 43(24), 3754-3763. doi:10.1016/j.atmosenv.2009.04.028Xiao, R., Takegawa, N., Zheng, M., Kondo, Y., Miyazaki, Y., Miyakawa, T., Hu, M., Shao, M., Zeng,L., Gong, Y., Lu, K., Deng, Z., Zhao, Y., and Zhang, Y. H. (2011). Characterization andsource apportionment of submicron aerosol with aerosol mass spectrometer during thePRIDE-PRD 2006 campaign. Atmos. Chem. Phys., 11, 6911-6929, doi:10.5194/acp-11-6911-2011Yuan, Z., Lau, A. K. H., Shao, M., Louie, P. K. K., Liu, S. C., & Zhu, T. (2009). Source analysis ofvolatile organic compounds by positive matrix factorization in urban and rural environmentsin Beijing. J. Geophys. Res.-Atmos., 114(D00G15). doi: 10.1029/2008JD011190Yue, D. L., Hu, M., Zhang, R. Y., Wang, Z. B., Zheng, J., Wu, Z. J., Wiedensohler, A., He, L.Y.,Huang, X.F., and Zhu, T. (2010). The Roles of Sulfuric Acid in New Particle Formation andGrowth in the Mega-city of Beijing. Atmos. Chem. Phys., 10(10), 4953-4960. doi:10.5194/acp-10-4953-2010Zhang, Y. H., Hu, M., Zhong, L. J., Wiedensohler, A., Liu, S. C., Andreae, M. O., Wang, W., and Fan,S. J. (2008). Regional Integrated Experiments on Air Quality over Pearl River Delta 2004(PRIDE-PRD2004): Overview. Atmospheric Environment, 42(25), 6157-6173. doi:10.1016/j.atmosenv.2008.03.025Zhang, Y. H., Su, H., Zhong, L. J., Cheng, Y. F., Zeng, L. M., Wang, X. S., Xiang, Y.R., Wang, J.L.,Gao, D.F., Shao, M., Fan, S.J., and Liu, S. C. (2008). Regional Ozone Pollution andObservation-Based Approach for Analyzing Ozone-Precursor Relationship during thePRIDE-PRD2004 Campaign. Atmospheric Environment, 42(25), 6203-6218. doi:10.1016/j.atmosenv.2008.05.002_______284

CHAPTER 8 - KEY ISSUES AND OUTLOOKLead Author: David Parrish (1)Contributing Authors: Laura Gallardo (2) , Tong Zhu (3) , Megan L. Melamed (4) and Mark Lawrence (5)(1)NOAA ESRL Chemical Sciences Division, Tropospheric Chemistry Programme Lead. 325 Broadway R/CSD7,Boulder, CO 80305 USA(2)Departamento de Geofísica & Centro de Modelamiento Matemático, Universidad de Chile. Blanco Encalada2002, piso 4, Santiago, Chile(3)College of Environmental Sciences and Engineering, Peking University, Beijing, China(4)IGAC International Project Office, University of Washington/JISAO, Seattle, WA USA(5)Institute for Advanced Sustainability Studies, Potsdam, GermanyThe population growth, economic and industrial development, and rising standard of livingin the world’s megacities will bring not only new problems but also new opportunities. There aremanifold challenges that accompany megacity growth: providing food, shelter, transportation andother goods and services for an ever-increasing population. Surmounting these challenges bringsobvious problems that affect the health and welfare of the urban population as well as societal andecological environment in areas well beyond the urban centre. At the same time, megacities areoften looked upon as the economic engines of the world. As such, they also represent aconcentration of resources that provide opportunities to address these challenges more efficientlythan possible if the same population were dispersed in smaller cities and rural environments. Aspecial section entitled Cities in the 8 February 2008 issue of Science explored these issues[http://www.sciencemag.org/content/319/5864.toc]. The goal of this chapter is to highlight some ofthe key questions and issues that have been identified regarding the challenges and opportunitiesthat accompany the emergence and evolution of megacities. This chapter is not intended to becomprehensive or detailed. Each of the issues will require significant future analysis that will bepublished elsewhere.8.1 THE SCALING LAW OF AIR POLLUTION AND HEALTH EFFECTS OF URBANPOPULATIONIt is generally recognized that ambient concentrations of air pollutants are higher in largeurban areas than in smaller cities. However, given the difficulty of comparing measurements fromdifferent cities due to differences in instrument siting, meteorological conditions, and many others,there is little quantitative information regarding how urban pollutant concentrations depend onpopulation. Satellite measurements can now provide such information. Figure 1 shows thevertical column abundance of NO 2 measured by the SCIAMACHY satellite over ten western UScities [Kim et al., 2009]. Since the predominant source of NO 2 is emissions from anthropogenicactivities, which are predominately located at the Earth’s surface, NO 2 is largely confined to thenear surface layer of the atmosphere, and the vertical column abundance is proportional to theurban ambient concentrations. In addition to the apparent day-of-week cycle in the figure, it isclear that larger cities (Los Angeles, San Francisco) generally have higher NO 2 columns than lesspopulated cities. Figure 2 is a log-log plot of the relationship between the average weekday NO 2column as a function of the population of the urban area (population taken for 2005 from a UScensus bureau web site: http://www.census.gov/popest/metro/CBSA-est2009-annual.html).The linear relationship shown in Figure 2 suggests that the relationship between urban NO 2column and population can be approximately captured as a scaling law in the form of a power lawfunction of population, as has been found for many urban relationships [Bettencourt et al., 2007]:column NO 2= N " eq 8.1i.e., many diverse urban properties increase as the population size (N) raised to an exponent b,which is between 0 and 1. The line in Figure 2 indicates the linear least-squares fit to the points!285

CHAPTER 8 – KEY ISSUES AND OUTLOOKand the slope of that line gives the numerical value of b, which in this case is 0.35. The correlationcoefficient for the fit is 0.77 and the y-intercept on that plot allows the calculation of 3.2 x 10 15 cm -2for the estimated column NO 2 for an average western US city with a population of 1 million. Similaranalyses have been done (L. Lamsal, R. Martin, Dalhousie University, private communication) forhundreds of cities in the US, Europe, China, and India. Each of these four regions gives similarresults with values of b between 0.34 and 0.61, correlation coefficients between 0.58 and 0.72, andintercepts indicating average satellite-derived surface NO 2 concentration for a city of 1 millioninhabitants increasing from India (0.35 ppbv) through China (1.0 ppbv) and Europe (1.2 ppbv) tothe US (1.4 ppbv). There is a great deal of scatter about these relationships from a variety ofcauses, e.g. differences in population density, energy use, topography, meteorology, etc. betweencities as well as differences in satellite retrievals over different environments. In addition it is likelythat different pollutants may have significantly different scaling exponents, i.e. values of b.Nevertheless, this scaling relationship provides a context in which to consider the populationdependence of ambient air pollutant concentrations in different societal environments.The scaling law in Equation 8.1 allows consideration of the dependence of the total healthimpact integrated over the population of an urban centre. Since a pollutant concentrationincreases with population with an exponent b, the total integrated exposure increases faster thanproportionally to population. Combining this dependence with the dose/response relationshipallows a first order estimate of the integrated health effects. The consideration of thedose/response relationship has not been done here, but these considerations suggest thatincreasing population exposed to increasing pollutant levels yields health impacts that increaserapidly with population, significantly more rapidly than directly proportional to the population.Figure 1: SCIAMACHY satellite derived troposphericNO2 columns over urban areas in the western US for2003 - 2007 May - September averages[Kim et al., 2009](Also shown in Chapter 5 as Figure 7)Figure 2 - Log-log plot of the estimated averageweekday (Mon – Fri) NO2 column from the dataincluded in Figure 2 as a function of urban areapopulation286

CHAPTER 8 – KEY ISSUES AND OUTLOOK8.2 COMPARISON OF AIR POLLUTANT CONCENTRATIONS, THEIR TEMPORALEVOLUTION, AND THEIR SOURCES ACROSS DIFFERENT MEGACITIESComparing air pollutant concentrations across different megacities, and comparing how theconcentrations have evolved with time, provides useful information regarding the sources of thepollutants and the likely effectiveness of control strategies. Figure 3 compares annual meanconcentrations of PM 10 recorded in 26 representative urban areas. Large differences are obvious,with concentrations varying by more than a factor of 10. However, even the most developed citiesapproach or exceed WHO air quality guidelines. Since PM is the air pollutant with the mostsignificant health effects, understanding the differences between concentrations observed indifferent cities is critical. Gurjar et al. [2008] have proposed a multi-pollutant index that evaluatesand ranks megacities in terms of their ambient air quality. This index considers the combinedconcentrations of PM 10 , SO 2 , and NO 2 , and can be used to monitor air quality changes over time,and relate these changes to the—often rapidly—changing state of a megacity. Local meteorology,local sources, and long-range transport all play roles in observed ambient air pollutant levels. Thedevelopment of a locally tailored control programme that adequately considers all relevant factorsis an expensive and lengthy process. Insightful comparisons between cities can certainly provideinitial and ultimately cost-effective guides to implementing effective PM control measures beforesuch a programme is ultimately put in place.Figure 3 - Comparison of annual mean concentrations of PM10 across 26 urban areas. These data were collected from avariety of papers and websites, some of which are cited in other chapters of this book [L. G. Klenner, privatecommunication]. It should be recognized that these data were derived from monitoring systems that differ widely in theircharacter, and thus cannot provide definitive comparisons among urban areasA comparison of chemical composition of PM 1 across different cities provides a rich sourceof information regarding the sources responsible for the ambient PM loading. As shown in Figure4, throughout the Northern Hemisphere, sulphate contributes a major portion to the ambientaerosol, but organics generally make an even larger contribution. Nitrate makes a generallysmaller, but quite variable contribution, and ammonium is nearly always present in significantamounts. Such data sets are quite informative, but must be interpreted with caution. The results287

CHAPTER 8 – KEY ISSUES AND OUTLOOKin Figure 4 were collected through deployments of aerosol mass spectrometers, which measureonly non-refractive particles with a diameter less than 1 µm. Consequently, they are insensitive toblack carbon, dust, and sea salt and thus overestimate the contributions for the chemicalcomponents they do measure. Figure 5 (also shown below) presents a more complete speciationof PM in Mexico City, which can be compared to the Mexico City result in Figure 4 (note thedifferent colour coding in the two figures.)Figure 4 - Comparison of composition of non-refractive PM1 at many sites in the Northern Hemisphere [Zhang et al., 2007].Pie charts show the average mass concentration and chemical composition: organics (green), sulphate (red), nitrate (blue),ammonium (orange), and chloride (purple). Colours for the study labels indicate the type of sampling location: urban areas(blue), 100 miles downwind (pink).(Also shown in Chapter 1 as Figure 6)Figure 5 - Submicron PM composition (mass and percent) measured during (a) March 2006; (b) April 2003 field campaignsat surface sites in the Mexico City basin. [From Aiken et al., 2009](Also show in Chapter 5 as Figure 18)288

CHAPTER 8 – KEY ISSUES AND OUTLOOKThe sources of organic aerosol (OA) are currently the subject of vigorous debate in thescientific community. The consensus is that most OA in rural areas is not directly emitted, butrather formed in the atmosphere from condensation of oxidized VOCs (secondary organic aerosolor SOA) [Zhang et al., 2007]. Radiocarbon dating of OA typically shows a very high fraction ofmodern carbon, suggesting that most SOA is formed from biogenic VOCs [Bench et al., 2007]. Onthe other hand, SOA typically correlates very well with the oxidation products of anthropogenicVOCs, suggesting that urban emissions play an important role in its formation [de Gouw et al.,2005]. Several studies indicated that there is much more SOA in urban air than models canaccount for [de Gouw et al., 2005; Volkamer et al., 2006]. Figure 6 summarizes some of the recentresearch aimed at explaining the observed levels of SOA using detailed chemical models. Thegraph shows that models underestimate SOA by 1-2 orders of magnitude over a wide range of thedegree of photochemical processing of an air mass. Given the relatively poor understanding of thesources of OA, it is very difficult to predict how a reduction in the emissions of precursors will affectthe levels of OA in the atmosphere. Since OA accounts for such an important contribution to totalPM levels, understanding OA sources is a high priority for establishing effective PM controlstrategies.Figure 6 - The ratio between measured and modelled secondary organic aerosol (SOA) as a function of photochemical age,i.e. the degree of photochemical processing, of a polluted air mass [Volkamer et al., 2006]It is important to note that currently developing megacities can benefit from the experiencesof megacities that developed earlier. An excellent example is provided by comparison of theevolution of maximum ozone and PM concentrations in three similarly sized megacities (Figure 7).Ozone concentrations peaked in Los Angeles about 1970 and have decreased over the followingfour decades. PM concentration measurements started later, but seem to have followed a similartrajectory. In Mexico City, a later developing megacity, the ozone concentrations apparently neverreached the peak concentrations observed in Los Angeles and dropped more rapidly, approachingLos Angeles concentrations. PM concentrations in Mexico City have approximately paralleled theozone concentrations. Evidently Mexico City avoided some to the most severe air pollutionproblems experienced in Los Angeles through implementation of emission controls beforeproblems became so severe. In contrast, pollutant concentrations in Beijing may be following adifferent trajectory; PM concentrations are decreasing, but ozone concentrations, which have beenlow, are evidently rising. Increased attention is being paid to air quality concerns in Beijing, and itwill be very enlightening to see how ozone concentrations evolve there in the future.Correlations between ambient concentrations of air pollutants can yield importantinformation regarding source emissions. For example, Parrish et al. [2009a] report ambientmeasurements of hydrocarbons, carbon monoxide, and nitrogen oxides from three megacities(Beijing, Mexico City, and Tokyo) and compare them with similar measurements from US cities inthe mid-1980s and the early 2000s (Figure 8). The common hydrocarbon pattern seen in all datasets indicates that emissions associated with gasoline-fuelled vehicles dominate in all of thesecities. This commonality suggests that vehicular emission controls are important to begin as soon289

CHAPTER 8 – KEY ISSUES AND OUTLOOKas possible in the growth of vehicle fleets in emerging megacities. Over the three decadescovered by the US data sets, the hydrocarbon emissions decreased by a significant factor(approximately an order of magnitude), while the ratios of the individual hydrocarbons remainednearly constant (Figure 8a). Differences in the hydrocarbon patterns between cities provideinformation regarding secondary sources. The ambient CO to NO X concentration ratio reported forthe three non-US megacities are higher than present US ratios (Figure 8b), but lower than thoseobserved in the 1980s in the US (not shown). The one exception to the preceding statement is thevery high concentrations of CO observed in Beijing, which apparently have a large regionalcontribution.Figure 7 - Comparison of evolution of ambient ozone (solid and dotted heavy lines) and PM10 (light lines shaded to zero)concentrations in three megacities of similar populations. Through the time period shown each of the three cities had apopulation within ± 40% of the 3-city average (dashed black line). The solid lines are polynomial fits to tabulated air qualitydata. The ozone for each city is the statistic that is used for the US NAAQS (3-year running mean of 4 th highest dailymaximum 8-hr average.) the dotted line is a fit to the maximum 8-hr average ozone observed in the limited research datasets that are available for Beijing. For Los Angeles PM10 is the annual average for the station measuring the highestconcentrations; for the other two cities the annual average over all stations in the city’s network is givenFigure 8 - Comparison of relationships between ambient concentrations of primary pollutants in three megacities.[Parrish et al., 2009a]290

CHAPTER 8 – KEY ISSUES AND OUTLOOKDuring the morning traffic peak, emissions from the on-road vehicle fleet generallydominate ambient concentrations of NO X , CO, and VOCs in urban areas. Measurements of theambient concentrations of these species thus provide quantitative information regarding the vehicleemissions. This information can provide “top-down” tests of emission inventories, and usefulcomparisons of vehicle emissions in different urban areas. For example, Figure 9 compares theCO to NO X ratio measured in the US (urban average and a specific city in Texas) with results fromthree urban areas in South America, Paris, Mexico City, and Tokyo.Figure 9 - Evolution of CO to NOX ratio in several cities. The black points are average US urban data reported to the USEnvironmental Protection Agency (USEPA), while the other points represent seven example cities throughout the world.The solid lines are linear, least-squares fits to the log-transformed data. USEPA data are from Parrish [2006]. Dallas, Texasdata are from the Texas Commission on Environmental Quality website (http://www.tceq.state.tx.us/nav/data/aq-data.html).Santiago and Buenos Aires data are from Gallardo et al. [2011], and São Paulo data from Vivanco and Andrade [2006].Tokyo and Mexico City data are from Parrish et al. [2009a].Paris data are from the Paris Air Quality Network (AIRPARIF), and were provided by A. BorbonDecadal scale changes in the CO to NO X vehicle emission ratio can be followed throughthe evolution of the measured ambient ratio (linear fits in Figure 9). Interestingly, the ambientratios in the US data sets, and in Santiago, Chile have decreased at similar rates, i.e. exponentialdecreases of 6 ± 1% / year, while the decrease in Paris, France has been considerably more rapid(10% / yr). The declining ratio in the US is attributed to the implementation of improved controlmeasures and the replacement of older, higher-emitting vehicles in the fleet [Parrish, 2006]. Thesecontrol measures, especially catalytic converters, are more effective at removing CO than NO X , soas vehicle fleets are modernized, the CO to NO X ratio decreases. Likely, a similar evolution of thevehicle fleet has occurred in Paris and Santiago. Importantly, US emission inventories do notcapture the observed rapid decrease in the CO:NO X ratio, so generally modelled emissions are toorich in CO compare to NO X in urban areas, which are often dominated by these on-road vehicleemissions.Inter-city differences in the US are attributed to differing average ages of the on-roadvehicles. For example the vehicle fleet in El Paso, Texas is significantly older than in Dallas Texasand the US average. The CO/NO X ratio in El Paso (not shown) follows the same rate of decrease,but the absolute trend is approximately 6 years behind the US average. However, other factorsmay be important in other cities. The CO to NO X emission ratio certainly depends on a variety offactors in addition to average vehicle fleet age, including relative fractions of diesel and gasolinefuelled vehicles, extent of ethanol usage (which is particularly high in São Paulo, Brazil), andemission control strategy and schedule of implementation. Importantly, Chilean emissioninventories generally underestimate the observed ratios; a preliminary analysis of the data, andresults from inverse modelling techniques for CO, suggest that NO X emissions in Santiago areprobably overestimated by a factor 2 to 3 [Gallardo et al., 2011], which accounts for the ambientinventoryratio differences.291

CHAPTER 8 – KEY ISSUES AND OUTLOOKThe VOC to NO X ratio in on-road vehicle emissions is of more critical importance tomodelling of photochemical production of ozone and SOA in urban areas than is the CO to NO Xratio. Parrish [2006] showed that VOC emissions from on-road vehicles have decreased at asimilar rate to CO emissions. This correspondence is expected because catalytic converters arethe principal control measure for both species. Although emission inventories accurately capturedthe VOC to NO X ratio in 2000, the subsequent decrease in the ratio was not accurately captured.Consequently, NO X to VOC emission ratios in US urban areas are likely underestimated by currentinventories, which will compromise air quality modelling.The results presented in Figure 9 represent a limited example of the world’s vehicle fleets.It is potentially useful to examine the CO to NO X emission ratio and its time evolution from vehiclefleets in a variety of megacities. Such an examination promises a wealth of information regardingthe emissions from vehicle fleets in those cities, and systematic differences may well provideguidance for developing air quality control strategies in the absence of detailed urban emissioninventories.8.3 IMPORTANCE OF REGIONAL TRANSPORT TO URBAN POLLUTION LEVELSPresently, many megacities, particularly in Asia, are developing in areas that are denselypopulated over large regions (e.g. the East China plains and the Indo-Gangetic Plain), and oftenthese megacities are in relatively close proximity to each other. Such cities have a critical newdimension to their air quality concerns – a significant, even dominant, fraction of some pollutantsmay be transported into the city from the surrounding region, rather than emitted or producedlocally. As one example, CO in Beijing behaves very differently compared to other cities. In atypical urban area, CO has a pronounced peak coincident with the morning vehicle trafficmaximum, while in Beijing such peaks are much less obvious, and CO concentrations can remainhigh for days, presumably due to regional accumulation and transport of CO on regional scales.This is reflected in Figure 8b that shows Beijing CO concentrations much higher than observed inother cities at comparable NO X concentrations. (Regional accumulation and transport are notnearly as important for NO X , due to its much shorter lifetime.)Model calculations [Zhao et al., 2009] indicate that under high-pressure systems, whichsuppress ventilation of pollutants from the boundary layer, elevated ozone concentrations canextend over a major fraction of East China (Figure 10). These results indicate that the highpollutant emissions over the vast stretch of the plains of East China makes the region susceptibleto regional accumulation of high ozone concentrations. During the episode illustrated in Figure 10,high ozone extended over an area >1 million km 2 , with a population of >800 million people.Figure 10 - Modelled ground-level ozone concentrations over East Asia on June 13, 2004 [from Zhao et al., 2009]292

CHAPTER 8 – KEY ISSUES AND OUTLOOKIt is clear that a single megacity in a large, densely populated region cannot effectivelyaddress its air quality issues in isolation; a region wide control strategy is required. The US facedthis issue in the 1980s when the Ozone Transport Assessment Group (OTAG) studied this issue.In that country regional transport is significant, but is dwarfed by its significance in Asia. China willhave to grapple with its daunting regional transport problem, which will become increasinglyimportant as that country continues to develop, but it may be much more difficult in the Indo-Gangetic Plain, which encompasses much of northern and eastern India, the most populous partsof Pakistan, parts of Nepal, and most of Bangladesh. Mobilizing the required internationalcoordination to develop effective air quality control policies will be difficult in a politicallychallenging region of the globe.8.4 AIR QUALITY CONTROL STRATEGIES: URBAN VERSUS DOWNWIND AREASVOC and NO X emitted to the atmosphere are oxidized through photochemical processesthat produce both ozone and SOA. The oxidation of anthropogenic emissions of these species isresponsible for the presence of elevated concentrations of ozone and SOA in urban areas. Overthe past decades, there has been a great deal of debate in the US regarding whether it is cheaperand more effective to control VOC or NO X emissions. This debate has been largely focused oncontrol of ozone rather than SOA [NRC, 1991]. A variety of analyses have argued that VOCcontrols are more effective and that NO X control may in fact be counter-productive. Thesearguments rely upon observationally based analysis, such as weekday-weekend differences[Blanchard et al., 2008 and references cited therein], EKMA type analysis [NRC, 1991] or evensimpler models [Stedman, 2004]. Unfortunately, photochemical ozone formation is a complexproblem involving emissions from urban cores, transport, distributed anthropogenic as well asbiogenic emissions of both VOC and NO X , etc. It is very likely that the relative effectiveness ofVOC and NO X controls is characteristic of each location, and varies with meteorology.It is also important to note that the debate described above has generally had a verylocalized focus – the air quality in the urban area for which emission controls are being considered– and impacts on downwind areas are not considered. If VOC emissions are controlled and NO Xemissions are not, ozone concentrations may well drop in the emission region, but the emitted NO Xmay be more efficiently transported to downwind regions, eventually forming a greater amount ofozone than in the absence of the VOC controls. This is an especially important consideration indensely populated regions such as Asia discussed in the preceding section.To reliably determine the most effective ozone or PM control strategy for a particular urbanarea or region requires air quality modelling incorporating accurate input from emission inventories,boundary condition characterization and meteorological fields as well as incorporating realisticdescriptions of chemical and physical processes [Song et al., 2010]. Arguably, such modelling tothe required accuracy is not yet possible for any urban area. Nevertheless, the detrimental healtheffects of air pollutants in the world’s megacities require that air quality improvement efforts mustbe implemented in lieu of such reliable information. Indeed, such efforts have been implementedand have resulted in great improvement in many cities (Figure 7). Fortunately, reduction ofemissions of any important pollutant brings beneficial effects from many perspectives, even if thereductions are not optimized for highest efficiency.8.5 CONTRIBUTION OF MEGACITIES TO REGIONAL AND GLOBAL CONCENTRATIONSStudying the impacts of megacities is challenging as they occur on different spatial scales,from the local to the global. Local and regional-scale measurements are crucial to understandingthe basic relationships between emissions, current ambient concentrations, and past trends overtime. There have been numerous observational studies of air pollution due to megacities on thelocal to global scale [Garland et al., 2008; Gurjar et al., 2008; Zhang et al., 2008]. MILAGRO was aparticularly large field programme that coordinated measurements to investigate the impact ofemissions from Mexico City on the air quality of the city and its surroundings [Molina et al., 2010,293

CHAPTER 8 – KEY ISSUES AND OUTLOOKsee Section 7.1]. In addition to the in-situ observations, satellite remote sensing also contributes tomegacity research, as is particularly being brought out by the EU CityZen and MEGAPOLIprojects. For instance, Hatzianastassiou et al. [2009] used MODIS and TOMS satellite data todiscriminate between anthropogenic and natural signals in the East Mediterranean, a regioninfluenced by the megacities Istanbul and Cairo (as well as by somewhat smaller cities like Athens,Izmir, and Ankara). Further details of various local-scale in situ observations and satelliteretrievals are given in Section 1.5 and Chapters 2-6 of this report.In order to go beyond our present understanding of the impacts of air pollutants onmegacities and to be able to develop future scenarios and information on mitigation strategies,atmospheric models are required. Megacities are a challenging scale problem for models. Due tolimited computer power, models that resolve urban air pollution cannot yet be run globally and theprovision of consistent boundary conditions for these regional models is not trivial. Global models,on the other hand, can be useful for examining effects such as large-scale transport and the role oflarge-scale changes in meteorological parameters, but they usually possess too coarse aresolution to be applied in local studies. Although computer power is increasing, the inclusion ofever-increasing complexity in contemporary models largely compensates for the increase incomputing power, so that resolution improves only slowly over time.Numerous modelling studies have examined the local urban-scale effects of megacities;several examples are discussed in the previous chapters. On the other hand, only a few studieshave examined the large-scale (regional to global) effects of megacity emissions. The firstexamination of the effects of megacities on global atmospheric chemistry using a global threedimensionalchemical transport model [Butler and Lawrence, 2009] found that the effects on airquality, radiative forcing, and atmospheric oxidation capacity of megacities are disproportionatelysmaller than the proportion of anthropogenic emissions due to megacities. In contrast,disproportionately large effects of megacities were modelled for reactive nitrogen compounds, inparticular PAN (peroxy acetyl nitrate). As an example, Figure 11 shows the effects fromFigure 11 - The percentage change in the global surface NOX mixing ratio due to megacity emissions, computedby the MATCH-MPIC model [Butler and Lawrence, 2009]. Four scenarios were considered, based on theemissions from the simulations for the IPCC-AR4 intercomparison [Dentener et al., 2005]: S1 - year 2000emissions; S2 - projected 2030 emissions based on current emissions control legislation and nationalexpectations of economic growth; S3 - maximum feasible reduction scenario(all currently available emission control technologies); S4 - pessimistic ‘worst case’ scenario294

CHAPTER 8 – KEY ISSUES AND OUTLOOKmegacities on global tropospheric NO X concentrations. Under the low-emission future scenarioS2, the influence of megacities is generally reduced, and under the high-emission future scenarioS4, although the local influence of megacities is increased, the geographical extent of the influencebecomes smaller. In terms of ozone response, the individual model grid cells that containmegacities respond to the megacity emissions differently depending on their latitude. Tropicalmegacity grid cells generally show increased ozone year-round, while northern extratropicalmegacities generally show reduced ozone year-round. Lawrence et al. [2007] offer anotherperspective, examining the “regional pollution potential” of emissions from megacities. That studyfound that the long-range transport characteristics of generic tracers are strongly affected by themegacity location and can be grouped into various regions. Eurasian megacities tend to bothretain the most pollution in the region immediately surrounding the city, and also to export the mostpollution to the boundary layer more than 1000 km away from the city, while tropical cities,especially from Southeast Asia, tend to primarily export the most pollution to the uppertroposphere. Vertical transport, especially by deep cumulus convection, is particularly importantfor determining the differences between the regions.8.6 URBAN HEAT ISLAND IN MEGACITIESUrban structures change the surface of land and sky view factor, and therefore the surfacebalance of energy, such as the short and long wave radiation, and the sensible and latent heatfluxes. This change together with the anthropogenic heat sources are the main causes of highertemperatures in urban centres than in suburban and rural areas, and hence the formation of urbanheat island (UHI).Urban heat island effect can be described with urban heat island intensity (UHII). UHII isdefined as the spatially-averaged temperature difference between an urban area and itssurrounding rural area [Kim and Baik, 2005]. UHII can be quantified by calculating air or surfacetemperature differences between an urban area and nearby rural area simultaneously with similargeographic features; satellite imagery has also been used to obtain surface-temperature basedUHII over a study area under clear skies. [Memon et al., 2009].High UHII have been reported in studies of megacities, such as 10 °C in Beijing [Hung et al.,2005], 8 °C in Tokyo [Saitoh et al., 1995] and Paris [Lemonsu and Masson, 2002], and 5 °C in NewYork [Gedzelman et al. 2003]. There is also a trend of temperature increase in large cities. Forexample, in Osaka the UHII increased from approximately 2.4 °C in 1901 to almost 3 °C after 1981,while the UHIIs of Seoul, Tokyo, and Taipei, have increased by 1 °C to 2 °C [Kataoka et al., 2009].The higher temperature in urban centres of megacities is associated with higher health risk.It is found that the anthropogenic heat plays an important role for UHII and the boundary layerdevelopment, and also has a significant impact on local circulation, such as land sea circulation[Lin et al., 2008]. The formation of an UHI has been shown to have a diurnal variation. For example,over Paris the UHII is stronger at night than during the day thus impacting the structure of theatmospheric boundary layer, which has an important impact on primary and secondary regional airpollutants such as ozone and nitrogen oxide [Sarrata, et al., 2006].With elevated temperatures, UHI has significant impacts on outdoor air quality, especiallyon the concentration of photochemical oxidants. Narumi et al., [2009] used an atmosphericdispersion model to reproduce the observed air pollution conditions for the typical summer day.The results showed that a 1°C increase in temperature leads to an increase of 11% in themaximum photochemical oxidant concentration. A temperature increase of up to 3°C will increasethe concentration of photochemical oxidants by 19 ppb. The concentration of photochemicaloxidants was 30 ppb higher in the afternoon due to the effect of biogenic VOCs, indicating theirstrong impact on photochemical oxidant concentrations under UHI condition.Few studies have discussed the association between UHI and air quality under synopticpatterns. Lai and Cheng [2009] analyzed this association in the Taichung metropolis region. The295

CHAPTER 8 – KEY ISSUES AND OUTLOOKresults show that certain synoptic patterns worsen the air quality and induce the UHI. Under thesepatterns, the concentrations of air pollutants increase significantly with the UHI intensity. Theconvergence usually associated with nocturnal UHI causes the accumulation of O 3 precursors, aswell as other air pollutants, thereby worsening the air quality that day and also during the followingdaytime period.The importance of UHI for the impacts of megacities on climate and air quality andtherefore mitigation measures has been well recognized. However, the roles of UHI in the airpollution formation processes and local to regional climate change are not well understood. Morestudies in this area are needed to formulate policies that have co-benefits of air quality and climatechange in megacities.8.7 CONCLUDING COMMENTSThe preceding chapters have described air quality research results from megacities on fiveof the world's continents. Notably, there is wide variability of available information - from LosAngeles, certainly the world's most extensively studied city where research has been ongoing forover six decades, to major megacities where very limited ambient measurements or modellinghave been conducted. This disparity emphasizes the critical need for both intensive fieldcampaigns and routine monitoring throughout the world.Nevertheless, experience in earlier developing megacities (e.g. Los Angeles, Mexico City)provides useful guidance for implementing emission control efforts in any megacity, even beforeextensive measurements and modelling allow formulation of a comprehensive air pollution controlprogramme. Such efforts can yield both immediate and long-term health benefits for the city'spopulation. Initial efforts could include inefficient combustion processes, e.g., open trash burningand cooking or home heating with biofuel and coal. Large industrial facilities and electricalgeneration plants are important emission sources, and a great deal of general knowledge isavailable regarding effective control of their emissions and these facilities can also be early targetsfor air quality improvement. On road motor vehicles are major sources of emissions in all cities,regardless of continent or society, and there is a great deal of similarity between the emissionsfrom vehicle fleets throughout the world. An early introduction of emission controls on newvehicles will sooner begin reducing vehicle emissions through the relatively long process of vehiclefleet turnover.Effective emission control strategies to improve air quality should also take into account theimpact the emission control strategies have on climate. The development of emission controlstrategies should seek "win-win" solutions for air quality problems that simultaneously benefitclimate. Such efforts to optimize the co-benefits of air quality policies for climate will pay dividendsat the local, regional and global scales.ReferencesBench, G., Fallon, S., Schichtel, B., Malm, W., & McDade, C. (2007). Relative contributions offossil and contemporary carbon sources to PM 2.5 aerosols at nine Interagency Monitoringfor Protection of Visual Environments (IMPROVE) network sites. J. Gepophys. Res. -Atmos., 112(D10205), 10. doi: 10.1029/2006JD007708Bettencourt, L. M. A., Lobo, J., Helbing, D., Kühnert, C., & West, G. B. (2007). Growth, innovation,scaling, and the pace of life in cities. Proc. Natl. Acad. Sci. USA., 104(17), 7301-7306. doi:10.1073/pnas.0610172104Blanchard, C. L., Tanenbaum, S., & Lawson, D. R. (2008). Differences between Weekday andWeekend Air Pollutant Levels in Atlanta; Baltimore; Chicago; Dallas–Fort Worth; Denver;Houston; New York; Phoenix; Washington, DC; and Surrounding Areas. J. Air & WasteMange. Assoc., 58(12), 1598-1615. doi: 10.3155/1047-3289.58.12.1598Butler, T. M., & Lawrence, M. G. (2009). The influence of megacities on global atmosphericchemistry: a modelling study. Environ. Chem., 6(3), 219-225. doi: 10.1071/EN08110296

CHAPTER 8 – KEY ISSUES AND OUTLOOKDentener, F., Stevenson, D., Cofala, J., Mechler, R., Amann, M., Bergamaschi, P., Raes, F., andDerwent, R. (2005). The impact of air pollutant and methane emission controls ontropospheric ozone and radiative forcing: CTM calculations for the period 1990–2030.Atmos. Chem. Phys., 5(7), 1731-1755. doi: 10.5194/acp-5-1731-2005de Gouw, J. A., Middlebrook, A. M., Warneke, C., Goldan, P. D., Kuster, W. C., Roberts, J. M.,Fehsenfeld, F.C., Worsnop, D.R., Canagaranta, M.R., Pszenny, A.A.P., Keene, W.C.,Marchewka, M., Bertram, S.B., and Bates, T. S. (2005). Budget of organic carbon in apolluted atmosphere: Results from the New England Air Quality Study in 2002. J.Gepophys. Res. - Atmos., 110(D16305), 22. doi: 10.1029/2004JD005623Gallardo, L., Escribano, J., Dawidowski, L., Rojas, N. J., Andrade, M. F, and Osses, M., (2011).Evaluation of vehicle emission inventories for carbon monoxide and nitrogen oxides forBogotá, Buenos Aires, Santiago, and São Paulo. Atmospheric Environment, 47, 12-19.Garland, R. M., Yang, H., Schmid, O., Rose, D., Nowak, A., Achtert, P., Wiedensohler, A.,Takegawa, N., Kita, K., Kondo, Y., Hu, M., Shao, M., Zeng, L.M., Zhang, Y.H., Andreae,M.O., and Pöschl, U. (2008). Aerosol optical properties in a rural environment near themega-city Guangzhou, China: implications for regional air pollution, radiative forcing andremote sensing Guangzhou, China: implications for regional air pollution, radiative forcingand remote sensing. Atmos. Chem. Phys., 8(17), 5161-5186. doi: 10.5194/acp-8-5161-2008Gedzelman, S. D., Ausin, S., Cermak, R., Stefano, N., Partridge, S., Quesenberry, S., & Robinson,D. A. (2003). Mesoscale aspects of the urban heat island around New York City.Theoretical and Applied Cimatology, 75(1/2), 29-42. doi: 10.1007/s00704-002-0724-2Gurjar, B. R., Butler, T. M., Lawrence, M. G., & Lelieveld, J. (2008). Evaluation of emissions andair quality in megacities. Atmospheric Environment, 42(7), 1593-1606. doi:10.1016/j.atmosenv.2007.10.048Hatzianastassiou, N., Gkikas, A., Mihalopoulos, N., Torres, O., & Katsoulis, B. D. (2009). Naturalversus anthropogenic aerosols in the eastern Mediterranean basin derived from multi-yearTOMS and MODIS satellite data. J. Gepophys. Res., 114(D24202), 14. doi:10.1029/2009JD011982Hung, T., Uchihama, D., Ochi, S., & Yasuoka, Y. (2005). Assessment with satellite data of theurban heat island effects in asian mega cities. International Journal of Applied EarthObservation and Geoinformation, 8(1), 34-48. doi: 10.1016/j.jag.2005.05.003Kataoka, K., Matsumoto, F., Ichinose, T., & Taniguchi, M. (2009). Urban warming trends in severallarge Asian cities over the last 100 years. Science of the Total Environment 407(9), 3112-3119. doi: 10.1016/j.scitotenv.2008.09.015Kim, S.-W., Heckel, A., Frost, G. J., Richter, A., Gleason, J., Burrows, J. P., McKeen, S., Hsie, E.-Y., Granier, C., and Trainer, M. (2009). NO2 columns in the western United Statesobserved from space and simulated by a regional chemistry model and their implicationsfor NO X emissions. J. Gepophys. Res., 114(D11301), 29. doi: 10.1029/2008JD011343Kim, Y. H., & Baik, J.-J. (2005). Spatial and temporal structure of the urban heat island in Seoul.American Meteorological Society, 44(5), 591-605. doi: 10.1175/JAM2226.1Lai, L. W., & Cheng, W. L. (2009). Air quality influenced by urban heat island coupled with synopticweather patterns. Science of the Total Environment, 407(8), 2724-2733. doi:10.1016/j.scitotenv.2008.12.002Lawrence, M. G., T. M. Butler, J. Steinkamp, B. R. Gurjar, and J. Lelieveld (2007), Regionalpollution potentials of megacities and other major population centers, Atmos. Chem.Phys., 7, 3969-3987Lemonsu, A., & Masson, V. (2002). Simulation of a summer urban breeze over Paris. BoundaryLayer Meteorology, 104(3), 463-490. doi: 10.1023/A:1016509614936Lin, C. Y., Chen, F., Huang, J. C., Chen, W. C., Liou, Y. A., Chen, W. N., & Liu, S. C. (2008).Urban heat island effect and its impact on boundary layer development and land– seacirculation over northern Taiwan. Atmospheric Environment, 42(22), 5635-5649. doi:10.1016/j.atmosenv.2008.03.015297

CHAPTER 8 – KEY ISSUES AND OUTLOOKMemon, R. A., Leung, D. Y. C., & Liu, C. H. (2009). An investigation of urban heat island intensity(UHII) as an indicator of urban heating. Atmospheric Research, 94(3), 491-500. doi:10.1016/j.atmosres.2009.07.006Molina, L. T., Madronich, S., Gaffney, J. S., Apel, E., Foy, B. d., Fast, J., Ferrare, R., Herdon, S.,Jimenez, J.L., Lamb, B., Osornio-Vargas, A.R., Russell, P., Schauer, J.J., Stevens, P.S.,Volkamer, R., and Zavala, M. (2010). An overview of the MILAGRO 2006 campaign:Mexico City emissions and their transport and transformation. Atmos. Chem. Phys., 10(18),8697-8760. doi: 10.5194/acp-10-8697-2010Narumi, D., Kondo, A., & Shimoda, Y. (2009). The effect of the increase in urban temperature onthe concentration of photochemical oxidants. Atmospheric Environment, 43(14), 2348-2359. doi: 10.1016/j.atmosenv.2009.01.028NRC. (1991). Rethinking the Ozone Problem in Urban and Regional Air Pollution. NationalResearch Council Committee on Tropospheric Ozone Formation and Measurement.Washington, D.C.: National Academy Press.Parrish, D. D. (2006). Critical evaluation of US on-road vehicle emission inventories. AtmosphericEnvironment, 40(13), 2288-2300. doi: 10.1016/j.atmosenv.2005.11.033Parrish, D. D., Allen, D. T., Bates, T. S., Fehsenfeld, F. C., Feingold, G., Ferrare, R., Hardesty,R.M., Meagher, J.F., Nielsen-Gammon, J.W., Pierce, R.B., Ryerson, T.B., Seinfeld, J.H.,and Williams, E. J. (2009b). Overview of the Second Texas Air Quality Study (TexAQSII)and the Gulf of Mexico Atmospheric Composition and Climate Study (GoMACCS). J.Geophys. Res., 114(D00F13). doi: 10.1029/2009JD011842Parrish, D. D., Kuster, W. C., Shao, M., Yokouchi, Y., Kondo, Y., Goldan, P. D., de Goue, J.A.,Koike, M., and Shirai, T. (2009a). Comparison of air pollutant emissions among megacities.Atmospheric Environment. doi: 10.1016/j.atmosenv.2009.06.024Saitoh, T. S., Shimada, T., & Hoshi, H. (1995). Modeling and simulation of the Tokyo urban heatisland. Atmospheric Environment, 30(20), 3431-3442. doi: 10.1016/1352-2310(95)00489-0Sarrata, C., Lemonsub, A., Massona, V., & Guedaliac, D. (2006). Impact of urban heat island onregional atmospheric pollution. Atmospheric Environment, 40(10), 1743-1758. doi:10.1016/j.atmosenv.2005.11.037Song, J., Lei, W., Bei, N., Zavala, M., Foy, B. d., Volkamer, R., Cardenas, B., Zheng, J., Zhang, R.,and Molina, L. T. (2010). Ozone response to emission changes: a modeling study duringthe MCMA-2006/MILAGRO Campaign. Atmos. Chem. Phys., 10(8), 3827-3846. doi:10.5194/acp-10-3827-2010Stedman, D. H. (2004). Photochemical ozone formation, simplified. Environ. Chem., 1, 65-66. doi:10.1071/EN04032Vivanco, M. G., & Andrade, M. d. F. (2006). Validation of the emission inventory in the Sao PauloMetropolitan Area of Brazil, based on ambient concentrations ratios of CO, NMOG and NO Xand on a photochemical model. Atmospheric Environment, 40(7), 1189-1198. doi:10.1016/j.atmosenv.2005.10.041Volkamer, R., Jimenez, J. L., Martini, F. S., Dzepina, K., Zhang, Q., Salcedo, D., Molina, L.T.Worsnop, D.R., and Molina, M. J. (2006). Secondary organic aerosol formation fromanthropogenic air pollution: Rapid and higher than expected. Geophys. Res. Lett.,33(L17811), 4. doi: 10.1029/2006GL026899Zhang, Q., Jimenez, J. L., Canagaratna, M. R., Allan, J. D., Coe, H., Ulbrich, I., Alfarra, M.R.,Takami, A., Middlebrook, A.M., Sun, Y.L., Dzepina, K., Dunlea, E., Docherty, K., DeCarlo,P.F., Salcedo, D., Onasch, T., Jayne, J.T., Miyoshi, T., Shimono, A., Hatakeyama, S.,Takegawa, N., Kondo, Y., Schneider, J., Drewick, F., Borrmann, S., Weimer, S., Demerjian,K., Williams, P., Bower, K., Bahreini, R., Cottrell, L., Griffin, R.J., Rautianen, J. Sun J.Y.,Zhange, Y.M., and Worsnop, D. R. (2007). Ubiquity and dominance of oxygenated speciesin organic aerosols in anthropogenically-influenced Northern Hemisphere midlatitudes.Geophys. Res. Lett., 34(L13801), 6. doi: 10.1029/2007GL029979298

CHAPTER 8 – KEY ISSUES AND OUTLOOKZhang, Y. H., Hu, M., Zhong, L. J., Wiedensohler, A., Liu, S. C., Andreae, M. O., Wang, W., andFan, S. J. (2008). Regional Integrated Experiments on Air Quality over Pearl River Delta2004 (PRIDE-PRD2004): Overview. Atmospheric Environment, 42(25), 6157-6173. doi:10.1016/j.atmosenv.2008.03.025Zhao, C., Wang, Y., & Zeng, T. (2009). East China Plains: A “basin” of ozone pollution. Environ.Sci. Technol., 43(6), 1911-1915. doi: 10.1021/es8027764_______299

LIST OF RECENT GLOBAL ATMOSPHERE WATCH REPORTS*100. Report of the Workshop on UV-B for the Americas, Buenos Aires, Argentina, 22-26 August 1994.101. Report of the WMO Workshop on the Measurement of Atmospheric Optical Depth and Turbidity, Silver Spring, USA, 6-10December 1993, (edited by Bruce Hicks) (WMO TD No. 659).102. Report of the Workshop on Precipitation Chemistry Laboratory Techniques, Hradec Kralove, Czech Republic, 17-21 October1994 (WMO TD No. 658).103. Report of the Meeting of Experts on the WMO World Data Centres, Toronto, Canada, 17 - 18 February 1995, (prepared byEdward Hare) (WMO TD No. 679).104. Report of the Fourth WMO Meeting of Experts on the Quality Assurance/Science Activity Centres (QA/SACs) of the GlobalAtmosphere Watch, jointly held with the First Meeting of the Coordinating Committees of IGAC-GLONET and IGAC-ACE,Garmisch-Partenkirchen, Germany, 13 to 17 March 1995 (WMO TD No. 689).105. Report of the Fourth Session of the EC Panel of Experts/CAS Working Group on Environmental Pollution and AtmosphericChemistry (Garmisch, Germany, 6-11 March 1995) (WMO TD No. 718).106. Report of the Global Acid Deposition Assessment (edited by D.M. Whelpdale and M-S. Kaiser) (WMO TD No. 777).107. Extended Abstracts of Papers Presented at the WMO-IGAC Conference on the Measurement and Assessment ofAtmospheric Composition Change (Beijing, China, 9-14 October 1995) (WMO TD No. 710).108. Report of the Tenth WMO International Comparison of Dobson Spectrophotometers (Arosa, Switzerland, 24 July - 4 August1995).109. Report of an Expert Consultation on 85Kr and 222Rn: Measurements, Effects and Applications (Freiburg, Germany, 28-31March 1995) (WMO TD No. 733).110. Report of the WMO-NOAA Expert Meeting on GAW Data Acquisition and Archiving (Asheville, NC, USA, 4-8 November 1995)(WMO TD No. 755).111. Report of the WMO-BMBF Workshop on VOC Establishment of a “World Calibration/Instrument Intercomparison Facility forVOC” to Serve the WMO Global Atmosphere Watch (GAW) Programme (Garmisch-Partenkirchen, Germany,17-21 December 1995) (WMO TD No. 756).112. Report of the WMO/STUK Intercomparison of Erythemally-Weighted Solar UV Radiometers, Spring/Summer 1995, Helsinki,Finland (WMO TD No. 781).112A. Report of the WMO/STUK ’95 Intercomparison of broadband UV radiometers: a small-scale follow-up study in 1999, Helsinki,2001, Addendum to GAW Report No. 112.113. The Strategic Plan of the Global Atmosphere Watch (GAW) (WMO TD No. 802).114. Report of the Fifth WMO Meeting of Experts on the Quality Assurance/Science Activity Centres (QA/SACs) of the GlobalAtmosphere Watch, jointly held with the Second Meeting of the Coordinating Committees of IGAC-GLONET and IGAC-ACE Ed , Garmisch-Partenkirchen, Germany, 15-19 July 1996 (WMO TD No. 787).115. Report of the Meeting of Experts on Atmospheric Urban Pollution and the Role of NMSs (Geneva, 7-11 October 1996) (WMOTD No. 801).116. Expert Meeting on Chemistry of Aerosols, Clouds and Atmospheric Precipitation in the Former USSR (Saint Petersburg,Russian Federation, 13-15 November 1995).117. Report and Proceedings of the Workshop on the Assessment of EMEP Activities Concerning Heavy Metals and PersistentOrganic Pollutants and their Further Development (Moscow, Russian Federation, 24-26 September 1996) (Volumes I and II)(WMO TD No. 806).________________* (A full list is available at http://www.wmo.int/pages/prog/arep/gaw/gaw-reports.html)

118. Report of the International Workshops on Ozone Observation in Asia and the Pacific Region (IWOAP, IWOAP-II), (IWOAP,27 February-26 March 1996 and IWOAP-II, 20 August-18 September 1996) (WMO TD No. 827).119. Report on BoM/NOAA/WMO International Comparison of the Dobson Spectrophotometers (Perth Airport, Perth, Australia, 3-14 February 1997), (prepared by Robert Evans and James Easson) (WMO TD No. 828).120. WMO-UMAP Workshop on Broad-Band UV Radiometers (Garmisch-Partenkirchen, Germany, 22 to 23 April 1996) (WMO TDNo. 894).121. Report of the Eighth WMO Meeting of Experts on Carbon Dioxide Concentration and Isotopic Measurement Techniques(prepared by Thomas Conway) (Boulder, CO, 6-11 July 1995) (WMO TD No. 821).122. Report of Passive Samplers for Atmospheric Chemistry Measurements and their Role in GAW (prepared by Greg Carmichael)(WMO TD No. 829).123. Report of WMO Meeting of Experts on GAW Regional Network in RA VI, Budapest, Hungary, 5 to 9 May 1997.124. Fifth Session of the EC Panel of Experts/CAS Working Group on Environmental Pollution and Atmospheric Chemistry,(Geneva, Switzerland, 7-10 April 1997) (WMO TD No. 898).125. Instruments to Measure Solar Ultraviolet Radiation, Part 1: Spectral Instruments (lead author G. Seckmeyer) (WMO TD No.1066), 2001.126. Guidelines for Site Quality Control of UV Monitoring (lead author A.R. Webb) (WMO TD No. 884), 1998.127. Report of the WMO-WHO Meeting of Experts on Standardization of UV Indices and their Dissemination to the Public (LesDiablerets, Switzerland, 21-25 July 1997) (WMO TD No. 921).128. The Fourth Biennial WMO Consultation on Brewer Ozone and UV Spectrophotometer Operation, Calibration and DataReporting, (Rome, Italy, 22-25 September 1996) (WMO TD No. 918).129. Guidelines for Atmospheric Trace Gas Data Management (Ken Masarie and Pieter Tans), 1998 (WMO TD No. 907).130. Jülich Ozone Sonde Intercomparison Experiment (JOSIE, 5 February to 8 March 1996), (H.G.J. Smit and D. Kley) (WMO TDNo. 926).131. WMO Workshop on Regional Transboundary Smoke and Haze in Southeast Asia (Singapore, 2 to 5 June 1998) (Gregory R.Carmichael). Two volumes.132. Report of the Ninth WMO Meeting of Experts on Carbon Dioxide Concentration and Related Tracer Measurement Techniques(Edited by Roger Francey), (Aspendale, Vic., Australia).133. Workshop on Advanced Statistical Methods and their Application to Air Quality Data Sets (Helsinki, 14-18 September 1998)(WMO TD No. 956).134. Guide on Sampling and Analysis Techniques for Chemical Constituents and Physical Properties in Air and Precipitation asApplied at Stations of the Global Atmosphere Watch. Carbon Dioxide (WMO TD No. 980).135. Sixth Session of the EC Panel of Experts/CAS Working Group on Environmental Pollution and Atmospheric Chemistry (Zurich,Switzerland, 8-11 March 1999) (WMO TD No.1002).136. WMO/EMEP/UNEP Workshop on Modelling of Atmospheric Transport and Deposition of Persistent Organic Pollutants andHeavy Metals (Geneva, Switzerland, 16-19 November 1999) (Volumes I and II) (WMO TD No. 1008).137. Report and Proceedings of the WMO RA II/RA V GAW Workshop on Urban Environment (Beijing, China, 1-4 November 1999)(WMO-TD. 1014) (Prepared by Greg Carmichael).138. Reports on WMO International Comparisons of Dobson Spectrophotometers, Parts I – Arosa, Switzerland, 19-31 July 1999,Part II – Buenos Aires, Argentina (29 Nov. – 12 Dec. 1999 and Part III – Pretoria, South Africa (18 March – 10 April 2000)(WMO TD No. 1016).139. The Fifth Biennial WMO Consultation on Brewer Ozone and UV Spectrophotometer Operation, Calibration and DataReporting (Halkidiki, Greece, September 1998)(WMO TD No. 1019).140. WMO/CEOS Report on a Strategy for Integrating Satellite and Ground-based Observations of Ozone (WMO TD No. 1046).

141. Report of the LAP/COST/WMO Intercomparison of Erythemal Radiometers Thessaloniki, Greece, 13-23 September 1999)(WMO TD No. 1051).142. Strategy for the Implementation of the Global Atmosphere Watch Programme (2001-2007), A Contribution to theImplementation of the Long-Term Plan (WMO TD No.1077).143. Global Atmosphere Watch Measurements Guide (WMO TD No. 1073).144. Report of the Seventh Session of the EC Panel of Experts/CAS Working Group on Environmental Pollution and AtmosphericChemistry and the GAW 2001 Workshop (Geneva, Switzerland, 2 to 5 April 2001) (WMO TD No. 1104).145. WMO GAW International Comparisons of Dobson Spectrophotometers at the Meteorological Observatory Hohenpeissenberg,Germany (21 May – 10 June 2000, MOHp2000-1), 23 July – 5 August 2000, MOHp2000-2), (10 – 23 June 2001, MOHp2001-1) and (8 to 21 July 2001, MOHp2001-2). Prepared by Ulf Köhler (WMO TD No. 1114).146. Quality Assurance in monitoring solar ultraviolet radiation: the state of the art. (WMO TD No. 1180), 2003.147. Workshop on GAW in RA VI (Europe), Riga, Latvia, 27-30 May 2002. (WMO TD No. 1206).148. Report of the Eleventh WMO/IAEA Meeting of Experts on Carbon Dioxide Concentration and Related Tracer MeasurementTechniques (Tokyo, Japan, 25-28 September 2001) (WMO TD No 1138).149. Comparison of Total Ozone Measurements of Dobson and Brewer Spectrophotometers and Recommended TransferFunctions (prepared by J. Staehelin, J. Kerr, R. Evans and K. Vanicek) (WMO TD No. 1147).150. Updated Guidelines for Atmospheric Trace Gas Data Management (Prepared by Ken Maserie and Pieter Tans (WMO TD No.1149).151. Report of the First CAS Working Group on Environmental Pollution and Atmospheric Chemistry (Geneva, Switzerland, 18-19March 2003) (WMO TD No. 1181).152. Current Activities of the Global Atmosphere Watch Programme (as presented at the 14 th World Meteorological Congress, May2003). (WMO TD No. 1168).153. WMO/GAW Aerosol Measurement Procedures: Guidelines and Recommendations. (WMO TD No. 1178).154. WMO/IMEP-15 Trace Elements in Water Laboratory Intercomparison. (WMO TD No. 1195).155. 1 st International Expert Meeting on Sources and Measurements of Natural Radionuclides Applied to Climate and Air QualityStudies (Gif sur Yvette, France, 3-5 June 2003) (WMO TD No. 1201).156. Addendum for the Period 2005-2007 to the Strategy for the Implementation of the Global Atmosphere Watch Programme(2001-2007), GAW Report No. 142 (WMO TD No. 1209).157. JOSIE-1998 Performance of EEC Ozone Sondes of SPC-6A and ENSCI-Z Type (Prepared by Herman G.J. Smit andWolfgang Straeter) (WMO TD No. 1218).158. JOSIE-2000 Jülich Ozone Sonde Intercomparison Experiment 2000. The 2000 WMO international intercomparison ofoperating procedures for ECC-ozone sondes at the environmental simulation facility at Jülich (Prepared by Herman G.J. Smitand Wolfgang Straeter) (WMO TD No. 1225).159. IGOS-IGACO Report - September 2004 (WMO TD No. 1235), 68 pp, September 2004.160. Manual for the GAW Precipitation Chemistry Programme (Guidelines, Data Quality Objectives and Standard OperatingProcedures) (WMO TD No. 1251), 186 pp, November 2004.161 12 th WMO/IAEA Meeting of Experts on Carbon Dioxide Concentration and Related Tracers Measurement Techniques(Toronto, Canada, 15-18 September 2003), 274 pp, May 2005.162. WMO/GAW Experts Workshop on a Global Surface-Based Network for Long Term Observations of Column Aerosol OpticalProperties, Davos, Switzerland, 8-10 March 2004 (edited by U. Baltensperger, L. Barrie and C. Wehrli) (WMO TD No. 1287),153 pp, November 2005.

163. World Meteorological Organization Activities in Support of the Vienna Convention on Protection of the Ozone Layer (WMONo. 974), 4 pp, September 2005.164. Instruments to Measure Solar Ultraviolet Radiation: Part 2: Broadband Instruments Measuring Erythemally Weighted SolarIrradiance (WMO TD No. 1289), 55 pp, July 2008, electronic version 2006.165. Report of the CAS Working Group on Environmental Pollution and Atmospheric Chemistry and the GAW 2005 Workshop,14-18 March 2005, Geneva, Switzerland (WMO TD No. 1302), 189 pp, March 2005.166. Joint WMO-GAW/ACCENT Workshop on The Global Tropospheric Carbon Monoxide Observations System, QualityAssurance and Applications (EMPA, Dübendorf, Switzerland, 24 – 26 October 2005) (edited by J. Klausen) (WMO TD No.1335), 36 pp, September 2006.167. The German Contribution to the WMO Global Atmosphere Watch Programme upon the 225 th Anniversary of GAWHohenpeissenberg Observatory (edited by L.A. Barrie, W. Fricke and R. Schleyer (WMO TD No. 1336), 124 pp, December2006.168. 13 th WMO/IAEA Meeting of Experts on Carbon Dioxide Concentration and Related Tracers Measurement Techniques(Boulder, Colorado, USA, 19-22 September 2005) (edited by J.B. Miller) (WMO TD No. 1359), 40 pp, December 2006.169. Chemical Data Assimilation for the Observation of the Earth’s Atmosphere – ACCENT/WMO Expert Workshop in support ofIGACO (edited by L.A. Barrie, J.P. Burrows, P. Monks and P. Borrell) (WMO TD No. 1360), 196 pp, December 2006.170. WMO/GAW Expert Workshop on the Quality and Applications of European GAW Measurements (Tutzing, Germany, 2-5November 2004) (WMO TD No. 1367).171. A WMO/GAW Expert Workshop on Global Long-Term Measurements of Volatile Organic Compounds (VOCs) (Geneva,Switzerland, 30 January – 1 February 2006) (WMO TD No. 1373), 36 pp, February 2007.172. WMO Global Atmosphere Watch (GAW) Strategic Plan: 2008 – 2015 (WMO TD No. 1384), 108 pp, August 2008.173. Report of the CAS Joint Scientific Steering Committee on Environmental Pollution and Atmospheric Chemistry (Geneva,Switzerland, 11-12 April 2007) (WMO TD No.1410), 33 pp, June 2008.174. World Data Centre for Greenhouse Gases Data Submission and Dissemination Guide (WMO TD No. 1416), 50 pp, January2008.175. The Ninth Biennial WMO Consultation on Brewer Ozone and UV Spectrophotometer Operation, Calibration and DataReporting (Delft, Netherlands, 31-May – 3 June 2005) (WMO TD No. 1419), 69 pp, March 2008.176. The Tenth Biennial WMO Consultation on Brewer Ozone and UV Spectrophotometer Operation, Calibration and DataReporting (Northwich, United Kingdom, 4-8 June 2007) (WMO TD No. 1420), 61 pp, March 2008.177. Joint Report of COST Action 728 and GURME – Overview of Existing Integrated (off-line and on-line) MesoscaleMeteorological and Chemical Transport Modelling in Europe (ISBN 978-1-905313-56-3) (WMO TD No. 1427), 106 pp, May2008.178. Plan for the implementation of the GAW Aerosol Lidar Observation Network GALION, (Hamburg, Germany, 27 - 29 March2007) (WMO TD No. 1443), 52 pp, November 2008.179. Intercomparison of Global UV Index from Multiband Radiometers: Harmonization of Global UVI and Spectral Irradiance(WMO TD No. 1454), 61 pp, March 2009.180. Towards a Better Knowledge of Umkehr Measurements: A Detailed Study of Data from Thirteen Dobson Intercomparisons(WMO TD No. 1456), 50 pp, December 2008.181. Joint Report of COST Action 728 and GURME – Overview of Tools and Methods for Meteorological and Air PollutionMesoscale Model Evaluation and User Training (WMO TD No. 1457), 121 pp, November 2008.182. IGACO-Ozone and UV Radiation Implementation Plan (WMO TD No. 1465), 49 pp, April 2009.183. Operations Handbook – Ozone Observations with a Dobson Spectrophotometer (WMO TD No. 1469), 91 pp, March 2009.184. Technical Report of Global Analysis Method for Major Greenhouse Gases by the World Data Center for Greenhouse Gases(WMO TD No. 1473), 29 pp, June 2009.

185. Guidelines for the Measurement of Methane and Nitrous Oxide and their Quality Assurance (WMO TD No. 1478), 49 pp,September 2009.186. 14 th WMO/IAEA Meeting of Experts on Carbon Dioxide, Other Greenhouse Gases and Related Tracers MeasurementTechniques (Helsinki, Finland, 10-13 September 2007) (WMO TD No. 1487), 31 pp, April 2009.187. Joint Report of COST Action 728 and GURME – Review of the Capabilities of Meteorological and Chemistry-TransportModels for Describing and Predicting Air Pollution Episodes (ISBN 978-1-905313-77-8) (WMO TD No. 1502), 69 pp,December 2009, electronic version -July 2009.188. Revision of the World Data Centre for Greenhouse Gases Data Submission and Dissemination Guide (WMO TD No.1507),55 pp, November 2009.189. Report of the MACC/GAW Session on the Near-Real-Time Delivery of the GAW Observations of Reactive Gases, Garmisch-Partenkirchen, Germany, 6-8 October 2009, (WMO TD No. 1527), 31 pp. August 2010.190. Instruments to Measure Solar Ultraviolet Radiation Part 3: Multi-channel filter instruments (lead author: G. Seckmeyer) (WMOTD No. 1537), 55 pp. November 2010.191. Instruments to Measure Solar Ultraviolet Radiation Part 4: Array Spectroradiometers (lead author: G. Seckmeyer) (WMO TDNo. 1538), 43 pp. November 2010.192. Guidelines for the Measurement of Atmospheric Carbon Monoxide (WMO TD No. 1551), 49 pp, July 2010.193. Guidelines for Reporting Total Ozone Data in Near Real Time (WMO TD No. 1552), 19 pp, April 2011 (electronic versiononly).194. 15 th WMO/IAEA Meeting of Experts on Carbon Dioxide, Other Greenhouse Gases and Related Tracers MeasurementTechniques (Jena, Germany, 7-10 September 2009) (WMO TD No. 1553). 330 pp, April 2011.195. WMO/GAW Expert Workshop on Global Long-term Measurements of Nitrogen Oxides and Recommendations for GAWNitrogen Oxides Network (Hohenpeissenberg, Germany, 8-9 October 2009) (WMO TD No. 1570), 45 pp, February 2011.196. Report of the First Session of the CAS JSC OPAG-EPAC and GAW 2009 Workshop (Geneva, Switzerland, 5-8 May 2009)(WMO TD No. 1577)197. Addendum for the Period 2012 – 2015 to the WMO Global Atmosphere Watch (GAW) Strategic Plan 2008 – 2015, 57 pp,May 2011.198. Data Quality Objectives (DQO) for Solar Ultraviolet Radiation Measurements (Part I). Addendum to WMO/GAW Report No.146 - Quality Assurance in Monitoring Solar Ultraviolet Radiation: State of the Art199. Second Tropospheric Ozone Workshop. Tropospheric Ozone Changes: observations, state of understanding and modelperformances (Météo France, Toulouse, France, 11-14 April 2011), 226 pp, September 2011200. WMO/GAW Standard Operating Procedures for In-Situ Measurements of Aerosol Mass Concentration, Light Scattering andLight Absorption (Edited by John A. Ogren), 134 pp, October 2011201. Quality Assurance and Quality Control for Ozonesonde Measurements in GAW (Prepared by Herman Smit and ASOPOSPanel).202. Workshop on Modelling and Observing the Impacts of Dust Transport/Deposition on Marine Productivity (Sliema, Malta, 7-9March 2011), 50 pp, November 2011.203. The Atmospheric Input of Chemicals to the Ocean. Rep. Stud. GESAMP No. 84/GAW Report No. 203. 69 pp.204. Standard Operating Procedures (SOPs) for Air Sampling in Stainless Steel Canisters for Non-Methane HydrocarbonsAnalysis (Prepared by Rainer Steinbrecher and Elisabeth Weiß)

GAW Report No. 205 - IGAC Project

Create successful ePaper yourself

Delete template?

Save as template?