Sustainability, Volume 15, Issue 14 (July-2 2023) – 731 articles

Digital finance (DF) has provided important financial support for the transformation and upgrading of China’s manufacturing industry. Innovation is the engine of industrial upgrading. To solve the dilemma of developing the manufacturing industry, it is necessary to enhance independent innovation capabilities. On this basis, this article studies the impact of DF on manufacturing technology innovation (MTI). It uses the data of listed manufacturing firms in the Shenzhen and Shanghai A-share markets from 2011 to 2020 to establish a fixed-effects model and a panel-threshold model for empirical analysis. The results revealed that, first, DF significantly accelerates technological innovation in manufacturing enterprises and has a significant positive impact on technological innovation. Secondly, DF drives manufacturing enterprises’ technological innovation by alleviating financial constraints (FCs). Thirdly, there is a dual-threshold effect based on market competition between DF and MTI based on market competition, and the promotion effect of DF on technology innovation decreases with the increasing degree of market competition. Finally, DF better enhances the technological innovation of non-state-owned manufacturing firms in the respective regions compared to state-owned firms. In terms of factor-intensive types, DF is more able to advance the innovative technologies of labor-intensive and capital-intensive enterprises, while it has no significant positive effect on technology-intensive enterprises. Policy implications are suggested to boost manufacturing technology innovation and aid future studies. Full article

Utilizing Chinese provincial panel data from 2006–2019, this paper applies the super-efficient epsilon-based measure (EBM) model including non-desired output to measure carbon emission efficiency (CE) and analyze spatio-temporal characteristics of CE, in which social fixed asset investment, energy consumption and urban employment per unit are used as input indicators and regional GDP and CO2 emissions are used as output indicators. Additionally, we use the spatial Durbin model to explore the impact of urban-rural income disparity (URID) on carbon emission efficiency and its spatial spillover effect and explore indirect mechanisms of consumption level and consumption structure on CE using mediating effect test. The results showed that: (1) The national CE level generally declined between 2006–2012 and fluctuated upward from 2013–2019. The trend of regional CE showed “high in the east and low in the west”. (2) The “inverted U” model accurately reflects the relationship between national CE and URID, with a “U” shaped association in the central, western, and northeastern regions, and a positive correlation with consumption level and consumption structure. (3) There is a significant mediating effect of consumption level and structure in the mechanism of URID in regulating CE. Local governments should adopt local policies, take measures to narrow URID and CLD, advocate low-carbon and environmentally friendly living for residents, and promote the upgrading of consumption structure to boost carbon emission efficiency. Full article

An increasing trend of anthropogenic activities such as urbanization and industrialization has resulted in induction and accumulation of various kinds of heavy metals in the environment, which ultimately has disturbed the biogeochemical balance. Therefore, the present study was conducted to probe the efficiency of conocarpus (Conocarpus erectus L.) waste-derived biochar and its modified derivatives for the removal of lead (Pb), cadmium (Cd), copper (Cu), and zinc (Zn) from aqueous solutions. Biochar was produced at 600 °C and modified with humic acid (1:10 w/v ratio) and rock phosphate (0.5:1 w/w ratio). Additionally, produced biochar, as well as humic acid and rock phosphate-modified biochars, were subjected to ball milling separately. Equilibrium and kinetics batch experiments were conducted to investigate heavy metals adsorption on synthesized adsorbents. Adsorption isotherms and kinetics models were employed to explore the adsorption efficiency of produced materials for metals adsorption. Among all the applied adsorbents, ball-milled biochars showed comparatively higher adsorption compared to un-milled biochars. Humic acid and rock phosphate-modified milled biochar showed the highest adsorption capacity for Pb (18.85 mg g⁻¹), while rock phosphate-modified milled biochar showed the highest adsorption capacity for Cu and Zn (24.02 mg g⁻¹ and 187.14 mg g⁻¹), and humic acid modified biochar adsorbed maximum Cd (30.89 mg g⁻¹). Adsorption isotherm study confirmed Freundlich as the best-suited model (R² = 0.99), while kinetics adsorption was well described by the pseudo-second-order (R² = 0.99). Hence, it was concluded that ball-milled biochar modified with humic acid and rock phosphate could potentially remove heavy metals from contaminated water. Full article

The present study focuses on finding potential sites for ecotourism development using GIS and remote-sensing-based weightage sum overlay techniques in Western Rajasthan, India. Ecotourism is one of the fastest growing and revenue-making sectors incorporating a sustainable future. Western Rajasthan has a broad scope to develop tourism-based activity in various ways, mainly through cultural heritage, historical and archaeological wonders, and rare wildlife. Weightage sum overlay analysis is a useful and simple tool to compare each thematic layer. These values are based on various factors and understanding taken during the study. For this purpose, different data types have been taken from the USGS website. Arc GIS 10.8 and ERDAS Imagine software 2015 have been utilized to process the data. This research incorporates seven thematic layers, i.e., elevation, proximity to streams, land use/cover, population density, road connectivity, proximity to protected areas, and heritage hotspots. Based on the physical and cultural characteristics of Western Rajasthan, the weightage of each thematic layer has been decided, which is finally overlaid using Arc GIS software. After processing all the thematic layers, we finally get an outcome in the form of a suitability map. The final suitability map represents five suitability classes that divide the total area into the following categories, very high (37.31%), high (26.85%), moderate (7.89%), low (0.83%), and very low (27.12%), which represents the potential of ecotourism in Western Rajasthan. Full article

In Bangladesh’s hill regions, where there is less cultivable land, increasing crop output requires efficient land use. Thus, in this challenging farming setting, two crop-based patterns evolved into three or four crop-based patterns. To increase cropping intensity and farmer income by incorporating mustard and mungbean in a rice-based cropping pattern, a field experiment was carried out at Sadar and Panchari Upazila, Khagrachhari during 2017–2018 and 2018–2019. Two years’ mean data (using a block farming approach) showed that the modified pattern had produced a much higher yield through improved management practices. In the improved cropping pattern (Transplant aman (T. aman)–mustard–mungbean–aus rice), a higher rice equivalent yield (16.25 t ha⁻¹) was found due to the inclusion of mustard and mungbean in the existing rice-based cropping patterns T. aman–fallow–boro (9.87 t ha⁻¹) and T. aman–fallow–tomato (9.09 t ha⁻¹). The gross margin from the improved cropping pattern was 448,715 BDT, which was 44.26% higher than the mean gross margin (311,050 BDT) of the two existing cropping patterns. Farmers are interested in growing mustard and mungbean since both can easily cultivated in hilly areas and can yield great economic returns quickly. For the large-scale production of oil and pulse, the T. aman–mustard–mungbean–aus rice cropping pattern might be introduced in the Khagrachhari district of Bangladesh. Full article

Local observations of climate change can be a critical resource for understanding the impacts of climate change, particularly in data-scarce areas. This study examines local observations of climate change in two montane areas of Kenya- Mt. Kenya and Mt. Elgon. Household questionnaires, focus group discussions, and interviews were used to explore local perceptions of ecosystem services and changes to those services. Results showed that communities had a strong appreciation for ecosystem services and had witnessed major changes in those services. Water provision was seen as the most important service and the one that had changed the most. Other observations of changes included shifts in species ranges, weather patterns, temperature, and soil properties. These changes are consistent with predictions from climate models, but they provide context-specific nuance that the models cannot provide. Spatial variables, such as distance to road and the alpine zone, played as large or larger role in affecting perceptions as demographics, which further points to the importance of context in understanding climate changes. Those that interacted with the mountains the most—the mountain guides—had particularly revealing observations of changes; these types of observations can be critical to understand and prepare for changes in the alpine areas of Kenya. Full article

The pursuit of sustainability in the construction and demolition (C&D) sector calls for effective decision-making strategies, both in terms of technical and environmental sustainability, capable of mitigating its huge demand for resources and emissions to the environment. The recycling of C&D waste is one of the potential solutions that could reduce the extraction of virgin materials as well as waste generation and landfilling. This study evaluates and compares, by means of the Life Cycle Assessment (LCA) approach, the production of concrete via five different mixtures made up of coarse natural aggregates (NA, primary, virgin materials), and coarse recycled concrete aggregates (RCA, recovered from previous uses). The present study assesses the environmental load of concrete production, by means of mixtures containing only coarse NA and mixtures with coarse RCA produced in fixed and mobile treatment plants, to be replaced with 30% and 100% of coarse NA by weight. The results point out that the use of coarse RCA in concrete mixtures provide greater energy savings and environmental advantages compared to the concrete with only coarse NA; the improvement increases up to a 100% replacement rate by weight of coarse NA with coarse RCA in the mixtures. In this case, the reduction of the impacts is significant for some impact categories such as freshwater ecotoxicity (−63.4%), marine ecotoxicity (−76.8%), human carcinogenic toxicity (−27.1%), human non-carcinogenic toxicity (−77.9%), land use (11.6%), and water consumption (−17.3%), while the total CED impacts decreases by about 10% and that of GWP by 0.4%. Results are discussed in light of the urgent need for advancing circular economy concepts and practices in the C&D sector and decrease the large use of primary resources (in particular sand and gravel). The replacement of NA with RA by weight could contribute to reducing the impacts of the C&DW management and disposal. For this to happen, further improvement of the quality of recycled aggregates is essential for their market development as well as dedicated policies and legislations. Full article

This research paper introduces a sensor that utilizes a machine-learning model to predict water salinity. The sensor’s concept and design are established through a simulation software which enables accurate modeling and analysis. Operating on the principle of light transmission physics, the sensor employs data collected from the simulation software as input parameters to predict the salinity parameter, serving as the output. The results of the prediction model exhibit excellent performance, showcasing high accuracy with a coefficient of determination value of 0.999 and a mean absolute error of 0.074. These outcomes demonstrate the model’s ability, particularly the multi-layer perceptron model, to effectively predict salinity values for previously unseen input data. This performance underscores the model’s accuracy and its proficiency in handling unfamiliar input data, emphasizing its significance in practical applications. Full article

Understanding how international trade, FDI and human capital (FDI-HC and ET-HC) in the ICT industry affect Taiwan’s stable economic growth between 2001 and 2020 is the main objective of this study. The empirical analysis method used in this study is mainly divided into two steps: First, it uses variables with reliability and authenticity as keywords for primary, data mining, and semantic network analysis (SNA). Second, it investigates the long- and short-term interactions between the variables using the vector error correction model (VECM). The results of data mining and SNA using FDI and ET as keywords reveal that terms connected to HC have high levels of centrality, clustering, and frequency. This finding implies that the variables FDI-HC and ET-HC are reliable and can be utilized as interaction variables. Moreover, FDI–HC and ET–HC exert positive short- and long-term influences on GDP, and ET–HC exerts strong mid- to long-term impacts on GDP, FDI–HC, and ET. Full article

The present study aimed to delve into the local ecological knowledge of fisheries in the Meghna River Basin (MRB) of Bangladesh by exploring the insights and perspectives of local communities. A survey was administered among six fishing communities from five districts along the MRB between August 2015 and January 2016 to accumulate data for this study. The study sites were selected meticulously based on three crucial criteria: upstream river, coastal area, and fish sanctuaries, which covered three major rivers, namely the Meghna, Andharmanik, and Payra. The study employed participatory rural appraisal (PRA) tools, including 120 individual interviews using purposive sampling, 25 focus group discussions, and 36 key informant interviews. The study identified the ten most frequently caught fish species along with their temporal and spatial variation as reported by the respondents. Nine of these species fell into the least concern category, which indicate their stable population status. Meanwhile, six out of ten species cited as highly caught in the previous one to two decades belong to the threatened or near-threatened category. Findings also reveal that fishers are able to recognize important microhabitats of the study area and their significance for fish species. In addition, fishers identified the negative drivers of ecosystem degradation as well as suggested several management measures to address these challenges. The results of this study underscore the critical role of engaging with local communities and integrating their ecological knowledge into initiatives for the sustainable exploitation and conservation of aquatic resources in the MRB. Full article

Climate stress poses a threat to the agricultural sector, which is vital for both the economy and livelihoods in general. Quantifying its risk to food security, livelihoods, and sustainability is crucial. This study proposes a framework to estimate the impact climate stress on agriculture in terms of three objectives: assessing the regional vulnerability (exposure, sensitivity, and adaptive capacity), analysing the climate variability, and measuring agricultural performance under climatic stress. The vulnerability of twenty-two sub-regions in Jammu, Kashmir, and Ladakh is assessed using indicators to determine the collective susceptibility of the agricultural framework to climate change. An index-based approach with min–max normalization is employed, ranking the districts based on their relative performances across vulnerability indicators. This work assesses the impact of socio-economic and climatic indicators on the performance of agricultural growth using the benchmark Ricardian approach. The parameters of the agricultural growth function are estimated using a linear combination of socio-economic and exposure variables. Lastly, the forecasted trends of climatic variables are examined using a long short-term memory (LSTM)-based recurrent neural network, providing an annual estimate of climate variability. The results indicate a negative impact of annual minimum temperature and decreasing land holdings on agricultural GDP, while cropping intensity, rural literacy, and credit facilities have positive effects. Budgam, Ganderbal, and Bandipora districts exhibit higher vulnerability due to factors such as low literacy rates, high population density, and extensive rice cultivation. Conversely, Kargil, Rajouri, and Poonch districts show lower vulnerability due to the low population density and lower level of institutional development. We observe an increasing trend of minimum temperature across the region. The proposed LSTM synthesizes a predictive estimate across five essential climate variables with an average overall root mean squared error (RMSE) of 0.91, outperforming the benchmark ARIMA and exponential-smoothing models by 32–48%. These findings can guide policymakers and stakeholders in developing strategies to mitigate climate stress on agriculture and enhance resilience. Full article

Traffic congestion is a typical phenomenon when motorways meet urban road networks. At this special location, the weaving area is a recurrent traffic bottleneck. Numerous research activities have been conducted to improve traffic efficiency and sustainability at bottleneck areas. Variable speed limit control (VSL) is one of the effective control strategies. The primary objective of this paper is twofold. On the one hand, turbulent traffic flow is to be smoothed on the special weaving area of motorways and urban roads using VSL control. On the other hand, another control method is provided to tackle the carbon dioxide emission problem over the network. For both control methods, a multi-agent reinforcement learning algorithm is used (MAPPO: multi-agent proximal policy optimization). The VSL control framework utilizes the real-time traffic state and the speed limit value in the last control step as the input of the optimization algorithm. Two reward functions are constructed to guide the algorithm to output the value of the dynamic speed limit enforced within the VSL control area. The effectiveness of the proposed control framework is verified via microscopic traffic simulation using simulation of urban mobility (SUMO). The results show that the proposed control method could shape a more homogeneous traffic flow, and reduces the total waiting time over the network by 15.8%. In the case of the carbon dioxide minimization strategy, the carbon dioxide emission can be reduced by 10.79% in the recurrent bottleneck area caused by the transition from motorways to urban roads. Full article

Taking all-day, all-weather airport security protection as the application demand, and aiming at the lack of complex meteorological conditions processing capability of current remote sensing image aircraft target detection algorithms, this paper takes the YOLOX algorithm as the basis, reduces model parameters by using depth separable convolution, improves feature extraction speed and detection efficiency, and at the same time, introduces different cavity convolution in its backbone network to increase the perceptual field and improve the model’s detection accuracy. Compared with the mainstream target detection algorithms, the proposed YOLOX-DD algorithm has the highest detection accuracy under complex meteorological conditions such as nighttime and dust, and can efficiently and reliably detect the aircraft in other complex meteorological conditions including fog, rain, and snow, with good anti-interference performance. Full article

In recent years, there has been growing interest in promoting sustainable agriculture and reducing the environmental impact of the food system. One approach to achieving these goals is through farm-to-Fork (FTF) sourcing, which involves direct procurement of food products from local farms to restaurants table. This approach has been touted as a way to support sustainable agriculture and decrease the carbon footprint of the food supply chain. This study aims to explore the relationship between farm-to-fork sourcing, perceived economic benefit, and environmental sustainability. Specifically, the research examines the moderating effect of the perceived economic benefit as well as the mediating role of environmental sustainability in the relationship between farm-to-fork (FTF) sourcing and sustainable agriculture practices. To investigate these relationships, a web-based questionnaire was designed and collected from 298 farmers. The collected data were analyzed via PLS-SEM. The results of the study suggest that farm-to-fork sourcing has a positive impact on sustainable agriculture practices and both perceived economic benefit and environmental sustainability have a moderating and mediating role in these relationships. This finding is consistent with the idea that direct procurement of food from local farms can lead to economic benefits for both farmers and restaurants, while also reducing the carbon footprint of the food supply chain. Full article

Taking the listed firms of heavy pollution industries in China for 2010–2021 as a sample, this study explored the impact and heterogeneity of corporate environmental disclosure behavior on analyst forecasts’ accuracy. We discovered that corporates measure or disclose environmental information and, the more environmental information is measured or disclosed, the more accurate analysts’ forecasts are; moreover, there is a strong and significant correlation between the environmental information given in the special reports and analysts’ forecast accuracy. This positive correlation is even more significant in cases of “matching words to deeds” and “brownwashing” by corporates. A mechanism analysis revealed that the analysts’ coverage and site visits both have a full or partial mediating effect. Specifically, analysts’ coverage is more likely to be elicited when corporates measure or disclose environmental information; the higher the degree of measurement or disclosure, disclose in the special reports, “matching words to deeds” and “brownwashing”. Analysts conducted site visits when corporates measured or disclosed environmental information, the higher the degree of measurement or disclosure, disclose in the special reports and “brownwashing”. The information above demonstrates that, on the one hand, specialized reports are published to supplement financial disclosures and, on the other hand, that analysts place importance on corporates’ incremental and explicit environmental information; however, “information screening” is insufficient and some “information mining” was carried out when corporate environmental information disclosure was insufficient. This study shed light on analysts’ roles in the improvement of the information environment of China’s capital market as well as the objective appraisal of the impact of corporate environmental information disclosure. Full article

While innovation is essential for sustainable development, micro, small, and medium-sized enterprises (MSMEs), which account for more than 90% of firms in Latin America, face the challenge of benefiting systematically from innovation due to capability and negotiation asymmetries when compared with large organizations. In this context, open innovation holds promise to enable shared-value creation in terms of developing MSME capabilities, operations, and the organization of activities, especially when mediated and supported by public sector actors. It may also hold promise for the development of MSMEs when there is a lack of well-developed ecosystems with multiple central actors, as is the case in many less-developed Latin American countries, such as Nicaragua. Open innovation ecosystems support platforms that form the delivery vehicles for the offerings of firms, providing a framework of processes, rules, and policies for the purpose of co-creating value. These platforms also offer a development gateway for the participating MSMEs, impacting the achievement of the Sustainable Development Goals (SDGs) created by The United Nations. Despite the potential for open innovation and its application in entrepreneurship ecosystems, few cases document the essential elements for designing these supporting platforms. In this case study, we aim to provide a framework for mediated, shared-value open innovation platforms by applying design science and case study approaches. Our work contributes to the field of knowledge-based ecosystems and open innovation platforms and considers best practices that can be applied in similar contexts. Full article

Non-renewable materials like plastics are widely applied on toothbrush handles and bristles. Polypropylene (PP) or polyethylene (PE) is often used to fabricate the toothbrush handle, while nylon (PA) is used to form the bristle. These plastics are sourced from non-renewable fossil fuels. The primary greenhouse gases—nitrous oxide (N₂O) and carbon dioxide (CO₂)—in the Earth’s atmosphere are released during the production of these plastics. Bamboo can generate 30% more oxygen than most plants and trees, which absorbs twice as much carbon dioxide as trees. A comparison of the cradle-to-grave material requirements between bamboo and plastic toothbrushes reveals that bamboo toothbrushes entail hidden environmental costs. Nevertheless, bamboo toothbrushes can be completely decomposed in the environment, which makes them eco-friendly and sustainable green products. This research aims to develop a bamboo toothbrush handle machine with a human–machine interactive interface and production management for optimizing process conditions. The machine is designed as a double-group to stably mass-produce high-quality bamboo toothbrush handles under optimal process conditions. Although bamboo is a sustainable green material, the shaping process is difficult due to an extremely anisotropic property in the bamboo structures. An improper process condition will induce a rough or scorched surface, which may further cause a tearing crack. The bamboo toothbrush handle milling machine is usually designed by a profiler, which uses various molds to change the shapes and sizes of bamboo toothbrush handles. This machine cannot probe the accurate cutting force for optimizing the cutting operations, paths, and parameters. The proposed equipment with a double-group design includes two storage racks of raw materials, two feeding devices, two exchange clamping devices, and a dual-spindle milling system required to form the shaping process of bamboo toothbrush handles. The whole system is propelled by a computer numerical control (CNC) SYNTEC controller, which can fabricate the bamboo toothbrush handle with various shapes and dimensions. This controller is integrated with a LabVIEW human–machine interactive interface via a Modbus RTU communication protocol. The optimal milling paths, manufacturing methods, and feeding rates are verified by a surveillance system to detect the instant currents of both spindles via the trial-and-error method and mass production. The maximum output of the equipment can reach four bamboo toothbrush handles per minute and 1600 bamboo toothbrush handles per day. Full article

In the contemporary world, the swift advancement of urbanization, the pressing need for environmental conservation, and humanity’s unyielding quest for a better quality of life have jointly underscored the escalating importance of research on landscape aesthetics and perceptual experiences. Researchers have often evaluated the overall scene’s beauty based on photos taken from a single viewpoint. However, it has been observed that different viewpoints of the same scene can lead to varying degrees of beauty perception. Some positive viewpoints highlight landscape features that contribute to beauty preferences, while negative viewpoints emphasize aspects that may evoke discomfort and decrease perceived beauty. Therefore, a crucial question arises: which viewpoint, positive or negative, holds more influence over the overall beauty of the scene? This paper aimed to address this question by utilizing panoramic map technology to establish a landscape perception evaluation model. The model was based on empirical evidence from various spatial scenes along the Yaozijian Ancient Road in Anhua County, encompassing towns and villages. The study analyzed the functional relationship between landscape factors, positive and negative viewpoints, and the degree of scenic beauty. It was found that (1) it is difficult to reflect the overall scenic beauty of a scene (OSBS) of a single viewpoint photo, and both positive and negative viewpoints of scenic beauty have significant effects on the OSBS. In the empirical case study, it was found that the overall effect of a positive viewpoint of scenic beauty (PVSB) on OSBS was greater; (2) PVSB had a major effect on OSBS with a high visual hierarchy and cloud ratio and a low type of vegetation and proportion of man-made objects; (3) a negative viewpoint of scenic beauty (NVSB) had a major effect on OSBS with a low visual hierarchy of the landscape. The results of the study reveal the relationship between landscape factors of different viewpoints and the OSBS, which can be applied to landscape beauty evaluation and landscape planning and design processes. Full article

The use of U-shaped girders has become increasingly popular in advanced projects such as metro rail systems due to their ability to provide greater vertical clearance beneath bridges. These girders, characterized by two webs and a bottom flange, contribute essential longitudinal stiffness and strength to the overall structure while effectively countering torsional forces in curved bridges. However, the design and construction of U-shaped girders present challenges, including their relatively higher self-weight compared to other girder types. Consequently, cost optimization has become a crucial focus in structural design studies. This research aims to develop an optimization model for prestressed U-shaped girders using the AASHTO LRFD bridge design specifications. The model is based on the Box complex method, with necessary modifications and improvements to achieve an optimal design. The objective is to minimize the total cost of materials, including concrete, steel reinforcement, and prestressing strands, while satisfying explicit and implicit design constraints. To facilitate the analysis, design, and optimization processes, a program is developed using Visual Studio 2010 and implemented in Visual Basic (VB.NET). The program incorporates separate subroutines for analysis, design, and optimization of the prestressed U-shaped girder, which are integrated to produce the desired results. When running the program, the optimization process required 229 iterations to converge to the optimal cost function value. The results demonstrate that the developed algorithm efficiently explores economically and structurally effective solutions, resulting in cost savings compared to the initial design. The convergence rate of the moment capacity constraint is identified as a key factor in achieving the optimal design. This research makes a significant contribution to the field of civil engineering by applying the classical Box complex method to the optimization of girders, an area where its utilization has been limited. Furthermore, this study specifically addresses the optimization of prestressed U-shaped girders in metro rail projects, where they serve as both the deck and support structure for train loading. By employing the Box complex method, this research aims to fill the research gap and provide valuable insights into the optimization of U-shaped girders. This approach offers a fresh perspective on designing these girders, considering their unique role in supporting metro rail loads. By leveraging the benefits of the Box complex method, researchers can explore new possibilities and uncover optimal design solutions for U-shaped girders in metro rail applications. Full article

Single-side natural ventilation is a commonly used means of ventilation to effectively regulate the thermal environment in building interiors without any fossil energy consumption. To achieve most of the potential for the efficiency of single-side natural ventilation, research needs to be undertaken into the forces that drive single-side natural ventilation. This paper examines the single-side natural ventilation of a single vertical single opening (SSO) and a vertical double opening (SDO) in a freestanding building under wind and thermal pressure. The change in the trajectory of vortex shedding when the building is leeward as well as the frequency of vortex shedding in square buildings was investigated by large eddy simulation (LES), and computational fluid dynamics was used to analyze the difference in the air exchange rate of single-side natural ventilation of SSO and SDO in the windward and leeward conditions of the building. Both of these methods were used in conjunction with one another. According to the findings, the creation of vortices at SSO and SDO in the presence of low wind speeds reduces the ventilation effect of thermal pressure under windward circumstances. Consequently, the influence of thermal stress and wind stress ultimately cancel each other out, and this phenomenon finally disappears as the wind blowing from the outside of the structure increases. The shedding of vortices in the leeward state accomplishes a form of air supply pumping with a particular periodicity of airflow fluctuations in the lateral direction. The Strouhal number computed using the LES simulation acts in a manner consistent with the experimental findings. Full article

An innovative and integrated scheme that encompasses two well-established waste treatment technologies, the aerobic biological degradation of organic matter bioprocess via membranes and anaerobic digestion, was demonstrated as a zero-waste approach that may effectively treat wastewater and biowaste in an integrated and symbiotic manner. Aiming to create a tool for the design, monitoring, and control of the scheme, prediction models were developed, validated, and implemented for the process simulation of the integrated scheme. The minimization of selected objective functions led to the estimation of the models’ parameters. The activated sludge model no. 1 (ASM1) was adopted for the simulation of the aerobic membrane bioreactor. The kinetic parameters were calibrated using volatile suspended solids and total nitrogen as the objective functions permitting the model to simulate the bioprocess satisfactorily (Nash–Sutcliffe efficiency > 0.86) and to calculate the concentration of the active biomass. The predominance of heterotrophic bacteria (4300 to 9770 mg COD/L) over autotrophic biomass (508 to 1422 mg COD/L) was showcased. For the anaerobic process unit, a simplified anaerobic digestion model 1 ADM1-R4 was used, and the first-order hydrolysis constants (k_ch 0.41 d⁻¹, k_pr 0.25 d⁻¹, k_li 0.09 d⁻¹) and microbial decay rate (k_dec 0.02 d⁻¹) were evaluated, enabling an accurate prediction of biogas production rates. A full-scale implementation of the integrated scheme was conducted for a decentralized waste treatment plant in a small community. Preliminary design calculations were performed in order to estimate the values related to certain process and technical parameters. The performance of this full-scale plant was simulated by the developed model, presenting clear benefits for practical applications in waste treatment plants. Full article

In the present scenario, air quality prediction (AQP) is a complex task due to high variability, volatility, and dynamic nature in space and time of particulates and pollutants. Recently, several nations have had poor air quality due to the high emission of particulate matter (PM_2.5) that affects human health conditions, especially in urban areas. In this research, a new optimization-based regression model was implemented for effective forecasting of air pollution. Firstly, the input data were acquired from a real-time Beijing PM_2.5 dataset recorded from 1 January 2010 to 31 December 2014. Additionally, the newer real-time dataset was recorded from 2016 to 2022 for four Indian cities: Cochin, Hyderabad, Chennai, and Bangalore. Then, data normalization was accomplished using the Min-Max normalization technique, along with correlation analysis for selecting highly correlated variables (wind direction, temperature, dew point, wind speed, and historical PM_2.5). Next, the important features from the highly correlated variables were selected by implementing an optimization algorithm named reinforced swarm optimization (RSO). Further, the selected optimal features were given to the bi-directional gated recurrent unit (Bi-GRU) model for effective AQP. The extensive numerical analysis shows that the proposed model obtained a mean absolute error ($MAE$) of 9.11 and 0.19 and a mean square error ($MSE$) of 2.82 and 0.26 on the Beijing PM_2.5 dataset and a real-time dataset. On both datasets, the error rate of the proposed model was minimal compared to other regression models. Full article

Issues of energy efficiency and sustainability in buildings are gaining increasing attention in the context of the “3060” dual-carbon initiative. In recent years, nearly zero-energy buildings (nZEBs) have emerged as a potentially viable solution to the challenges of the energy crisis in the building sector, and it is important to study the factors influencing their energy consumption and carbon emissions. However, existing research lacks analyses of multifactor interactions, and the problem of high energy consumption has not been sufficiently addressed. Taking a typical residential building in the Yangtze River basin as the study subject, this study, jointly funded by the University of Nottingham and Hubei University of Technology, proposes a hybrid approach that combines building energy simulation and orthogonal experiments to investigate factors pertaining to buildings, people, and the environment to identify key influencing factors and explore the energy consumption and carbon emission characteristics of residential buildings in hot summer and cold winter (HSCW) zones. Our findings reveal the following: (1) The use of renewable energy sources, such as solar photovoltaic power generation and solar hot water, and renewable energy systems such as ground-source heat pumps, in the operation phase of a baseline building can result in a 61.76% energy-saving and a 71% renewable energy utilization rate. (2) To more easily meet the requirements of nZEB standards, it is recommended to keep K_E within the range of 0.20–0.30 W/(m²·K), K_R within the range of 0.15–0.20 W/(m²·K), and VT within the range of 0.6–0.7 h⁻¹. This study will help to identify the critical factors affecting energy consumption and provide a valuable reference for building energy efficiency in HSCW zones. Full article

This article describes China’s entry into the World Trade Organization (WTO) as a quasi-natural experiment based on samples from the World Bank database, China Customs database, and China Industrial Enterprise Database from 2000 to 2007 and uses the difference-in-difference (DID) method to investigate the effect of trade policy uncertainty (TPU) on China’s agricultural exports. The study found that, first, a decline in TPU significantly increases the export volume of Chinese agricultural firms. Second, the decline in TPU significantly boosts companies engaged in general trade. Regarding export destination countries, the decline in TPU significantly promotes the agricultural firms whose export destination countries are developing countries. Regarding firms’ ownership, the promotion of agricultural exports by non-state-owned enterprises (non-SOEs) and Hong Kong-, Macao- and Taiwan-funded enterprises is even more pronounced. Third, the decline in TPU promotes the export of Chinese agricultural firms by alleviating their financing constraints. The study provides new explanations for changes in China’s agricultural exports and enriches research on the evaluation of TPU effects. Full article

This research aimed to develop a comprehensive model for the sustainable development of creative industries in Iran through digital transformation and interpretive structural modeling. Semi-structured interviews were conducted with 19 experts to extract the dimensions and components of sustainable development. The validated components were presented using a structural equation modeling questionnaire to obtain a comprehensive model. These components were identified and confirmed: sustainable competitive development, consolidation and freeze, sustainable development drivers, digital technology cultural taste, structural social capital, environmental and industrial intelligence, digital work environment, creativity and innovation, financial supply chain management, and digital entrepreneurial ecosystem. The experts validated these components through the research process. It is essential to focus on developing digital infrastructure to achieve sustainable development in creative industries based on digital transformation. It includes digital communications, necessary technologies, and information security, which serve as the foundation to promote creative industries in the digital sphere. Full article

Because of the social importance of hospitals, characterized by energy-intensive users, large-scale refurbishment projects for these types of buildings are required. With the aim of helping researchers and designers, this paper proposes a multistage methodological approach for the optimization of retrofit designs based on energy, environmental, and economic indicators. Some guidelines are also highlighted thanks to the results obtained from a case study of a private hospital in Naples (Southern Italy, Mediterranean climate) located in a constrained landscape area. The first step consists of the calibration of a simulation energy model defined via in situ investigations, direct surveys and monitoring of energy loads and indoor quality. Then, the model is used to verify the effectiveness of several efficiency measures regarding the building envelope, the active energy systems, and the energy conversion from renewables in order to minimize the energy demand with acceptable economic profitability. This case study demonstrates that electricity demand can be reduced by up to 48% with an investment of around EUR 720,030.00; the payback time without national incentives is 10 years, but it can be halved with appropriate financial support. Full article

With societal development and population increase, the amount of waste and energy consumption is also increasing. The use of waste for energy production is gradually establishing in the international and national legal norms and political programs of most developed countries around the world. Many experts are beginning to be inclined to hold the opinion that it will be necessary to include energy-recoverable waste as a renewable energy source. Slovakia is a country that understands the importance of producing energy from waste without harming the environment. The current paper focuses on the potential of Slovakia compared to other countries in the area of energy recovery from waste. With the use of regression analysis, the growth trend of municipal waste in Slovakia was defined. The results show that the Slovakian trend goes against the EU goals. On the one hand, this represents a very serious problem for the environment, but it also indicates the significant potential of secondary raw materials and energy in the case of energy recovery from waste. Full article

Jiangsu Province, situated in the Yangtze River basin, has rich traditional village resources and a prominent position in economic development and cultural integration. This study focuses on the analysis of the variation distribution pattern of traditional villages in Jiangsu Province using six batches of traditional village directories with data until 2023 as research samples. By employing ANN, Voronoi graph analysis, and Moran’s I index, the researchers determined the spatial distribution characteristics of rural settlements. Additionally, kernel density and spatial autocorrelation techniques were used to further examine the spatial distribution patterns, and geographic detector detection was introduced. The results showed the following: (1) The spatial distribution of traditional village settlements in Jiangsu Province showed a significant clustering distribution that is mainly concentrated in central Jiangsu Province. (2) The driving factors reflected a strong symbiotic relationship of “air–water–soil–man”. The spatial distribution of traditional villages was mainly driven by the annual mean temperature and soil type. The interaction between factors was dominated by the enhancement relationship between the two factors. (3) According to the detection results of risk areas in the region, the average annual temperature was 17~17.6 °C, the annual precipitation was 133.0~145.7 billion m³, the average annual wind speed was 0.549~0.565 m/s, the GDP was 85,100~204,000 CNY/km⁻², and the population density was 2.32~3.91 thousand/km⁻². Arable land was the main type of area and was conducive to the gathering of traditional villages. The preservation of rural settlements should take into account the complex and diverse factors that affect their distribution. Additionally, it is crucial to tailor protection strategies to specific local conditions and conduct flexible research. Full article

Life-LCA studies, which assess the environmental impacts of human beings, focused so far on the span from conception to 50 years. This case study extends the analysis to an “old adulthood stage”, including a retirement (65–75 years) and end-of-life phase (75–80 years), thus complementing the assessment gap in the life cycle of a human being. The Life-LCA method is applied to a fictional study object representing an average German adult using mainly secondary data. Over both life phases, impacts result in 1.2 × 10² t CO₂-eq for climate change, 9 × 10⁻⁵ CTUh for human toxicity cancer, 2 × 10⁻³ CTUh for human toxicity non-cancer, 1.35 × 10⁰ kg Sb-eq for abiotic depletion for elements, and 1.55 × 10⁰ TJ for fossil fuels. Across all impact categories, “transport” is a hotspot, contributing 41% to GWP, followed by “Energy and water” (39%) and “food” (20%). For abiotic depletion for elements, “Electronics” shows a share of 50%. The “retirement phase” causes a higher environmental impact than the “EoL phase” across all impact categories due to restricted mobility with higher age. A study with primary data collection is suggested to check the plausibility of the results. Full article