"Environment, Development and Sustainability"

Guo, Feng; Song, Yinghui

doi: 10.1007/s10668-025-06008-7pmid: N/A

Unregulated disposal of Construction and Demolition Waste (C&DW) has become a significant concern in urban areas. Although many developed nations have implemented classification and recycling measures, China alone produces over two billion tons of C&DW annually, with a recycling rate under five per cent. This study aims to enhance C&DW management by establishing a differential game model for the C&DW recycling and reproduction supply chain, introducing three types of subsidies: non-government subsidies (NGS), government subsidies for post-production costs (CGS), and after-sales unit government subsidies (UGS). The research evaluates how factors like the pricing of recycled products, their environmental impact, and quality influence consumer preferences. Additionally, it explores the decision-making processes of C&DW producers and recyclers under different subsidy mechanisms. Key findings include: (1) When subsidies are limited, CGS effectively enhances recycled products' quality and green degree, while UGS better supports market circulation. (2) Under certain conditions, UGS is the most efficient way to boost the green attributes of recycled products. (3) The revenue of C&DW producers may be lower under UGS compared to NGS. This research offers a diversified subsidy policy strategy for local government departments and provides practical guidance for C&DW producers and recyclers, contributing to improved C&DW management and promoting sustainable urban development.

Soundararajan, S.; Shirley, C. P.; Mallala, Balasubbareddy; Padmanaban, K.

doi: 10.1007/s10668-025-06021-wpmid: N/A

Smart agriculture, coupled with the implementation of modern technologies and artificial intelligence, is one crucial way of responding to the challenge caused by agricultural pests, through which the world loses crop products as pointed out by the Food and Agriculture Organization (FAO). In this manuscript, there is a new smartphone application designed to use cloud computing that implements a cycle-consistent generative adversarial network (CCGAN) used to identify pests in agriculture. The proposed system uses the IP102 public dataset to gather input images that represent different pests. The images are pre-processed using the Gaussian-Adaptive Bilateral Filter (GABF) method, which improves the quality of the images by removing noise. Feature extraction is done using the term frequency-inverse document frequency (TF-IDF) method, which helps in identifying key characteristics of the pests. A CCGAN model is then used for pest classification, targeting five pest categories: Aphids, Cicadellidae, Flax Budworms, Flea Beetles, and Red Spiders. The integration of cloud computing, facilitated through Python, enhances the system’s ability to augment and classify images efficiently. The effectiveness of the proposed model is evaluated using several performance metrics, including accuracy, precision, recall, sensitivity, F1-score, mean squared error (MSE), and computational time. The results show that the proposed method surpasses existing techniques by gaining 10.47%, 12.85%, 9.36%, 14.45%, 11.72%, 7.56%, and 5.56% accuracy compared to IYOLOv7-tiny, CNN-TL, DSS-DL, DCNN-Mnet, YOLOv5x, ResNet50, and EfficientNetB0, respectively. Furthermore, the proposed approach gains 20.59%, 25.47%, 18.64%, 32.5%, 27.03%, 22.75%, and 19.32% less computational time compared to the existing methods. This clearly shows the efficiency and better performance of the proposed method in terms of accuracy and computational efficiency.

Chen, Yanbi; Chen, Xingpeng; Xue, Bing

doi: 10.1007/s10668-024-05948-wpmid: N/A

The growing demand for rice and international trade has amplified the environmental and health risks associated with pesticide use in rice production, creating a complex network of risk transfer through global trade chains. Understanding how these pesticide-related risks are spatially distributed and transferred is critical for their effective mitigation and for advancing global Sustainable Development Goals. This study utilized the PEST-CHEMGRIDS database to estimate the pesticide footprint of rice production across 199 regions globally for the year 2020. Environmental Impact Quotient (EIQ) and Hazard Quotient (HQ) indices were employed to evaluate the environmental and health risks associated with pesticides in each region. Finally, by integrating international rice trade data, a framework based on complex network theory was adopted to analyze the transference characteristics of environmental and health burdens associated with pesticide use in global rice trade. The findings highlight the roles, positions, and characteristics of various countries and groups within this pesticide transfer network. The findings reveal that in 2020, global rice consumption was associated with 9.6 × 104 t of pesticide use, with associated EIQ of 4.1 × 109 and HQ of 8.2 × 1012. The high intensity of pesticide use in rice-importing countries indicates that the international rice trade helps reduce global pesticide risks. Additionally, most pesticide risks associated with rice production are concentrated in a few countries; the top ten regions with the highest pesticide use account over 70% of the pesticide risks in the global rice production. By identifying the spatial distribution of the pesticide footprints and dynamics of risk transfer, this study highlights the critical role of trade in shaping global pesticide risks and underscores the need for coordinated international efforts to promote sustainable pesticide management. The study provides actionable insights for policymakers, trade stakeholders, and researchers to mitigate pesticide-related risks and advance global sustainability objectives.

Watson, Ancy S.; Bai, R. Sudha

doi: 10.1007/s10668-025-06016-7pmid: N/A

Vegetation plays a significant role in the regulation of homeostasis in an ecosystem. This study assessed the ecosystem services and disservices of street trees in thirteen heavily polluted corridors of Thiruvananthapuram, Kerala, using the i-Tree Eco Model. The results indicated that the avenue trees stored approximately 1016.15 metric tons of carbon, with an annual carbon sequestration of 25.69 tons. Peltophorum pterocarpum emerged as the dominant species in these areas. Eucalyptus sp. and Albizia saman were deemed more suitable for less disturbed areas, such as green belts and wastelands, due to their higher disservice profile. In contrast, Ailanthus sp., Tamarindus indica, and Swietenia mahagoni provided significant ecosystem benefits with minimal Volatile Organic Compound (VOC) emissions. Statistical analysis revealed significant positive correlations (p < 0.05) among variables like, tree density, carbon storage, carbon sequestration, avoided runoff and VOC release. Carbon storage and avoided runoff had the highest correlation (r = 0.97), indicating the influence of allometric canopy cover on surface runoff reduction. The lowest correlation (r = 0.66) was between tree density and carbon storage which depicted the impact of tree diameter over tree population in the enhancement of biomass. Spatial analysis further emphasized the benefits of species diversity over monocultures in mitigating abiotic stressors, like air pollutants.

Nanor, Michael Ayertey

doi: 10.1007/s10668-025-06046-1pmid: N/A

Household relocation choices are critical in shaping urban socio-economic landscapes, especially within the framework of the Sustainable Development Goals (SDGs). This study investigates the complex factors influencing household relocation decisions in Kumasi, Ghana, an urban center undergoing rapid growth. The aim is to understand how socio-economic conditions, environmental challenges, and urban policy dynamics interact to shape relocation intentions. Using a qualitative approach, this research use qualitative interviews and natural language processing (NLP) technique to capture the diverse push and pull factors motivating relocation. Findings indicate that push factors, such as inadequate housing, urban congestion, and environmental degradation, diminish quality of life and drive relocation. Conversely, pull factors, including employment opportunities, access to education and healthcare, and enhanced urban amenities, attract households to particular areas within Kumasi. This study situates these relocation dynamics within the SDG framework, highlighting the need for sustainable urban development strategies that address residents' aspirations and challenges. The results emphasize that aligning urban planning with principles of inclusivity, equity, and environmental sustainability can enhance urban resilience and community well-being. The study’s insights are valuable for policymakers, urban planners, and stakeholders seeking to foster urban environments conducive to sustainable development, equitable growth, and social inclusion, ultimately advancing progress toward achieving the SDGs.

Elatroush, Ibrahim

doi: 10.1007/s10668-024-05873-ypmid: N/A

This study aims to explore the link between financial development (FD) and economic growth on environmental quality in 60 developing and emerging countries over the period 1980–2021. Before assessing the employed model, the CDS, slope heterogeneity, and CIPS tests are performed for the study variables. Afterwards, the Pooled Mean Group and panel quantile regression techniques are carried out. The countries were clustered to assess the impact of FD and the study variables on environmental quality, as measured by CO2 emissions. Additionally, the Dumitrescu-Hurlin panel causality test was performed. The findings revealed a positive relationship between variables and CO2 in some clusters, which contributed to greater environmental degradation. In contrast, in other clusters, there was a significant negative relationship existed between study variables and CO2 emissions, which helped to mitigate of environmental damage. The discrepancy in results between groups can be related to differences in income levels, development patterns, production technologies, FD scores, and other socioeconomic characteristics between countries. The study underlines the crucial role of policymakers, authorities, and financial institutions in achieving the 2030 sustainable development goals (SDGs) 7, 11, 12, and 13 to improve the environmental quality in developing and emerging countries. It recommends that policies and strategies be undertaken to promote environmentally friendly products, eliminate polluting activities, embrace eco-friendly manufacturing technologies, and increase the use of bioenergy and renewable energy while reducing nonrenewable energy use. Policymakers, authorities, civic society, and financial institutions must all take responsibility for ensuring the proposals' successful implementation.

Feng, Zhongwei; Zhao, Wanting; Yi, Wentao; Yang, Yuzhong

doi: 10.1007/s10668-025-06039-0pmid: N/A

Given the transition problem for the after-sales service channel of Tesla and the emerging electric vehicle manufacturers (EVMs) in China, consider an electric vehicle (EV) supply chain consisting of an EVM and a reseller, we investigated the issue of after-sales service channel design by distinguishing a direct channel and four decentralized channels. In the direct channel, the EVM engages in production and sale of EVs and hires a third-party (3P) to undertake the after-sales service (i.e., EV-D-3P channel). In the decentralized channels, the after-sales service of EVs can be provided by the EVM (EV-M channel), reseller (EV-R channel), or the 3P hired by the EVM or reseller (EV-M-3P or EV-R-3P channel). We construct Stackelberg game models and examine the equilibrium solutions. It is shown that the after-sales service or the vehicle price may become the factor that significantly affects the demand of EVs under some conditions. It is also shown that the EVM and reseller have a conflict in the choice of after-sales service channels, and they prefer to undertake the service or hire the 3P by themselves, although EV-M channel generates the highest after-sales service level and the largest demand. Furthermore, the market demand of EVs is more sensitive to after-sale service level and the marginal after-sale service cost to increase after-sale service level is lower, the EVM prefers the reseller or a 3P (who possesses a lower after-sale service cost of EVs) to undertake the after-sales service.

Wang, Lu; Jie, Feilong; He, Bing

doi: 10.1007/s10668-025-06050-5pmid: N/A

sWater resources in arid zones suffer from spatial distribution imbalance, inefficiency, and high consumption. However, the regional and temporal evolution, as well as the spatial differentiation features of agricultural water and soil resource matching in arid zones, remain unclear, and they mostly focus on water quantity while ignoring agricultural pollution (water quality). In this paper, we take the Tarim River Basin (TRB) as the research object, and use crop water footprint, agricultural water and soil resource matching model, and agricultural available water resource abundance index to analyze the spatial and temporal evolution of blue, green, and grey water footprints, as well as the match of agricultural water and soil resources, to reveal the relationship between crop water demand and irrigation water quantity, and to adjust the crop planting layout. The results show that from 2000 to 2020: (1) The TRB water footprint is increasing from southeast to northwest. The blue-green water and grey water footprints of different crops were different. (2) The matching degree of agricultural water and soil resources in TRB decreased year after year, with a geographical pattern of “high in the north and low in the south, high in the west and low in the east, and low in the edge and high in the hinterland”. (3) The agricultural available water resources index per unit area decreased overall but increased spatially from west to east and south to north. Therefore, cultivated land expansion in the eastern TRB in land-rich and water-poor areas should be limited, high-water-demand crops (cotton) should be decreased, and cash crops such as maize and winter wheat should be raised. The study is significant in successfully easing the contradiction between supply and demand for soil and water resources in arid zones, hence boosting resource utilization efficiency and assuring the long-term use of agricultural soil and water resources.

Amaral, António L.; Martins, Rita; Dias, Luís C.

doi: 10.1007/s10668-025-06022-9pmid: N/A

Identifying service providers with the best performance regarding their main operational indicators is relevant to improve the sustainability of the water sector. It is also critical to determine the corresponding drivers, and understand the interdependences, to enlighten the relevant stakeholders about the best course of action. The energy consumption of the service provider is a major issue, regarding sustainability, both for financial (being one of the largest operating expenses) and environmental (emission of greenhouse gases) reasons. In that regard, a Data Envelopment Analysis—Slacks Based Measure is employed to identify the service providers within the efficiency frontier. Only the efficient providers were considered to determine the main drivers and to model the energy consumption by multilinear regression. The current study identifies the effectively served population and the number of served households as paramount for the estimation of energy consumption at the efficiency frontier in wastewater and drinking water treatment, respectively. Other explanatory factors were also found to be significant, especially regarding normalized (per water intake) energy consumption, including energy certification, wastewater treatment plants typology, mains and sewers grid rehabilitation, wastewater satisfactory treatment, number of septic tanks and drinking water treatment plants and collected water volumes. The proposed methodology can be applied to data from any country to identify the role model SP and the corresponding energy consumption drivers, allowing policy recommendations to be tailored to each specific context.

Muñoz-Martínez, J.; Cañete-Massé, C.; Cussó-Parcerisas, I.; Carrillo-Álvarez, E.

doi: 10.1007/s10668-024-05954-ypmid: N/A

A transition towards sustainable and healthy diet(SHD) is crucial for both population and planetary health. However, changing consumer’s behaviour is challenging due to the many factors influencing food choices. Tools that comprehensively assess these factors are paramount, yet none are available in Spain. Hence, we created and validated the SALSA questionnaire to capture self-perceived barriers and facilitators for SHD. The process involved three phases: First, item development combining insights from a scoping review and content validity with experts(n = 9) and the target population(n = 38); Second, scale development by pre-testing the questionnaire(n = 4), administering it through an online survey to two samples(Dimensionality-Sample, n = 516; Reliability-Sample, n = 61), and applying exploratory factor analysis for factors extraction and item reduction; Third, scale evaluation by testing its dimensionality through confirmatory factor analysis, its reliability through Cronbach’s alpha and McDonald’s omega, and intra-class correlation coefficient, and construct validity through discriminant validity, convergent validity, and correlation analysis. Results yielded a questionnaire with 27 items grouped into four dimensions: personal factors, sociocultural factors, external factors, and meat and plant-based meat alternatives. The psychometric analysis revealed that the SALSA questionnaire is a reliable instrument to identify behavioural determinants.