Environmental Impact Assessment Review最新文献

{"title":"Linking production-living-ecological space transformations with sustainable development goals Progress in China's urban agglomerations","authors":"Mengting Wang ,&nbsp;Tianhui Zhou ,&nbsp;Yinshuai Li ,&nbsp;Nan Jia ,&nbsp;Ruishan Chen","doi":"10.1016/j.eiar.2026.108394","DOIUrl":"10.1016/j.eiar.2026.108394","url":null,"abstract":"<div><div>With accelerating urban expansion and increasing land-use pressures, achieving Sustainable Development Goals (SDGs) requires integrated approaches to production, living, and ecological spaces (PLES), yet current research remains without a systematic understanding of their synergies and trade-offs. To address this issue, this study examined five major urban agglomerations in China to quantify how PLES transformations relate to SDGs performance. Three indicators—land utilization structural information entropy (LUS), intensity (LUI), and dynamic degree (LUD)—were used to capture spatial reconfiguration, human activity, and land-use dynamism. Spearman correlation and network analysis were employed to identify the structural configuration of these synergy and trade-off relationships, while grey relational analysis explored the relative association strength. The results indicate that living and industrial spaces expanded continuously, while agricultural and ecological spaces contracted during the study period. Although overall sustainability improved, progress on SDG15 (Life on land) and SDG17 (Partnerships for the goals) remained slower, with significant though narrowing regional differences. More than 75% of SDGs pairs exhibited synergistic relationships, and PLES–SDGs linkages were largely positive, though persistent trade-offs remained with PLES indicators and SDG15. Network analysis based on statistical correlations identified SDG8 (Decent work) and SDG9 (Industry, innovation, and infrastructure) as topologically central nodes, with SDG15 served as a key intermediary linking ecological and socioeconomic goals, while grey relational analysis further revealed that transformations in living space exhibited the most pronounced co-evolutionary patterns with SDGs over time. By revealing where synergies strengthen and trade-offs persist, this study provides a spatially explicit diagnostic approach that links land use with SDGs, offering a transferable basis for integrating these relationships into evidence-based and sustainability-oriented planning.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108394"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial intelligence applications in urban extreme heat management: A systematic review of forecasting, monitoring, mitigation and decision support","authors":"Jin Rui ,&nbsp;Zahratu Shabrina ,&nbsp;Wenjing Gong","doi":"10.1016/j.eiar.2026.108363","DOIUrl":"10.1016/j.eiar.2026.108363","url":null,"abstract":"<div><div>Against the backdrop of global warming and rapid urbanization, urban extreme heat is becoming increasingly severe, with profound impacts on public health, infrastructure, and social equity. Advances in artificial intelligence (AI) offer new opportunities to address this challenge. This systematic review examines 102 publications on AI applications in urban extreme heat governance. The findings reveal a “Northern bias,” with most studies in the United States, China, and Europe, while gaps exist in sub-Saharan Africa and Latin America. Supervised learning dominates current approaches. AI demonstrates effectiveness across four dimensions of governance. In prediction and early warning, random forests and XGBoost are suitable for short-term forecasting, CNNs and LSTMs excel at spatiotemporal patterns, and hybrid models improve accuracy. In monitoring and assessment, AI overcomes spatiotemporal limits of remote sensing, shifting from static heat mapping to dynamic heat–population risk identification, with social media capturing residents' perceptions. In mitigation and adaptation, AI identifies thresholds of green–blue infrastructure, supports urban form regulation, and expands climate-adaptive design through generative AI. In scenario simulation and decision support, AI-powered digital twins and interactive platforms integrate planning and operations, fostering expert–public collaboration. Yet applications remain constrained by trade-offs between accuracy and efficiency, limited data integration, and insufficient causal inference, particularly in modeling the heat risk chain as a multi-stage system. Future work should build data frameworks integrating physical and social information and advance paradigm shifts toward causal inference and multi-objective optimization. A systematic AI framework can enable closed-loop governance from risk identification to intelligent response.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108363"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on multi-dimensional decision-making method of plastic waste management","authors":"Shujie Zhao ,&nbsp;Lile Cai ,&nbsp;Quanyin Tan ,&nbsp;Jinhui Li ,&nbsp;Yufei Qin","doi":"10.1016/j.eiar.2026.108360","DOIUrl":"10.1016/j.eiar.2026.108360","url":null,"abstract":"<div><div>In recent years, plastic waste has continued to increase, causing long-term damage to the environment. To reduce direct environmental contamination by plastics disposal processes, it is crucial to quantitatively evaluate plastic waste management methods from environmental, economic, and risk perspectives for optimal process selection. However, standard life cycle assessments (LCA) are unable to address these aspects from both producer and market viewpoints. This study examines four waste management methods of plastic waste—pyrolysis, mechanical recycling, landfilling, and incineration—employing a multi-objective evaluation framework integrating LCA, economic analysis, and risk assessment. Mechanical recycling emerged as the best option, having minimal environmental impact (human health: -16.02E-11, ecosystems: -13.18E−10, and resource scarcity: -31.80E-12), suitable profitability (24.55%), low pollution risk (1.50), and overall optimal benefits. Simultaneously, sensitivity analysis showed that electricity (−12.98 to 11.19%) had the greatest impact on the global warming potential of mechanical recycling technologies. This study evaluation of the environmental impacts, economics, and risk levels of different plastic waste management methods as a whole provides theoretical support for practical waste management systems. The results serve as a reference value for the selection and optimization of different plastic waste management methods.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108360"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating hybrid life cycle assessment to quantify carbon footprint in mariculture: Overcoming truncation errors and unveiling macroeconomic drivers","authors":"Ting Jiang ,&nbsp;Kangni Wu ,&nbsp;Yuanchao Hu ,&nbsp;Guobao Song ,&nbsp;Weiwei Sun ,&nbsp;Gengyuan Liu ,&nbsp;Zhaoyuan Yu ,&nbsp;Ling Cao ,&nbsp;Shaobin Li","doi":"10.1016/j.eiar.2026.108359","DOIUrl":"10.1016/j.eiar.2026.108359","url":null,"abstract":"<div><div>Marine aquaculture (mariculture) holds significant potential for reducing the carbon footprint (CF) compared to land-based meat production systems. However, conventional process-based life cycle assessment (P-LCA) methods tend to underestimate emissions due to truncation errors stemming from overlooked macroeconomic activities. Although integrated hybrid life cycle assessment (IH-LCA) has been introduced to mitigate truncation errors, its application in mariculture industry remains limited, largely because of the coarse granularity of the fishery sector in existing input-output models. In addition, CF of mariculture products are typically evaluated at the species level, without considering the differences between management practices. Here, an IH-LCA method with finer granularity was first developed by disaggregating products of mariculture into four categories (e.g., fish, shrimp, shellfish, and macroalgae) from the fishery sector in an input-output model. Then the CF of mariculture products was quantified by integrating process-based inventory data from 19 distinct management practices in China. Compared to P-LCA, IH-LCA method enhances estimation coverage of CF by 9.3%, 5.8%, 28.8%, and 24.7% on average for fish, shrimp, shellfish, and macroalgae, respectively. Further analysis reveals that macroeconomic sectors account for 5.7–46.5% of total CF, with major contributors from handling and warehousing services (33.84%), agricultural technical services (26.39%), and construction-related services (11.01%). For advancing economy-wide low-carbon transitions within the mariculture industry, stakeholders are suggested to look beyond process-based emissions and incorporate impacts from relevant macroeconomic sectors.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108359"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075173","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trade-off dynamics underpin distance thresholds in ecosystem service multifunctionality along alpine transportation corridors","authors":"Siqi Yang ,&nbsp;Qili Li ,&nbsp;Yujian Gao ,&nbsp;Jie Liu ,&nbsp;Xiaowen Yang","doi":"10.1016/j.eiar.2026.108382","DOIUrl":"10.1016/j.eiar.2026.108382","url":null,"abstract":"<div><div>Transportation infrastructure profoundly alters ecosystem structure and function in ecologically vulnerable regions, potentially triggering trade-offs among individual ecosystem services. More importantly, the impacts of these trade-offs on ecosystem service multifunctionality (ESM) remain poorly understood. This study developed a novel quantitative framework that incorporates trade-off dynamics into integrated multifunctionality assessment. Applying this framework to the Qinghai-Tibet highway and railway corridors from 2000 to 2020, we examined the spatiotemporal dynamics and spatial heterogeneity of ecosystem service trade-offs and ESM, focusing on carbon sequestration (CS), habitat quality (HQ), and soil retention (SR). The key findings included: 1) CS-SR synergies strengthened over time, whereas CS-HQ synergies weakened after railway construction. 2) ESM exhibited unimodal patterns with distance, reaching maximum values at approximately 4000 m for railway and 6000 m for highway, indicating a more localized impact from railway. As a regulatory factor in ESM calculation, trade-off intensity was higher within approximately 4000 m of railway but shifted to highway beyond this distance. 3) The dominant drivers varied across permafrost zones and transportation corridors, with vegetation and climate factors playing key roles; transportation distance had a stronger positive effect on highway ESM (17.09%) than on the railway in island permafrost areas; the effects of precipitation and temperature shifted in direction with increasing permafrost severity; and in continuous permafrost, significant drivers declined and vegetation index became the primary control (&gt;85%). These findings highlight the role of trade-off based multifunctionality assessment in guiding adaptive management of alpine transportation systems.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108382"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146170891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancing cumulative impact assessment frameworks: The role of indicators and their weighting in shaping environmental decision-making","authors":"Nefeli Maria Bompoti","doi":"10.1016/j.eiar.2026.108385","DOIUrl":"10.1016/j.eiar.2026.108385","url":null,"abstract":"<div><div>The study investigates multiple frameworks for evaluating cumulative impacts, focusing on the selection of indicators and their respective weighting in air quality-related decision-making processes while integrating climate change considerations. The main innovation of this study is the comparative analysis of cumulative impact assessment frameworks including context- and place-specific variables using quantitative metrics. The study assesses how methodological choices can influence the prioritization of communities within environmental justice policies and regulatory decision-making. Multiple frameworks were assessed, each tailored to the specific objectives of the decision-making process and the geographical context, and compared to a baseline model with minimal parameters. The context-specific model yielded results similar to the baseline but emphasized air quality parameters more heavily and increased average scores. In contrast, place-specific and hybrid models showed greater variance, influenced by factors such as proximity to coastal areas, flood risk, and health sensitivity. Statistical analysis revealed significant differences between the models with frameworks incorporating more indicators exhibiting greater variability and wider score distributions. The models also prioritized different communities at the 80th and 90th percentiles, highlighting that methodological choices within each framework can substantially influence which communities are being prioritized. The analysis also revealed high intercorrelation among certain parameters, reflecting the need for further exploration of how parameter selection influences their interrelationships. Sensitivity analysis on environmental weighting demonstrated that even when environmental burdens were weighed equally, they could not fully account for the cumulative impact of other variables, except in certain areas. Health sensitivity and socioeconomic factors had a more substantial effect when their weight was varied. The study concludes that while all frameworks capture the areas with the highest cumulative impacts, their choice has significant implications. Integration of lived experiences and community insights, alongside further research, is crucial for accurately capturing cumulative impacts and enhancing decision-making.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108385"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146170893","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The spillovers of ESG performance on peers' debt financing costs: evidence from China","authors":"Yao Wang ,&nbsp;Ziyao Zhang ,&nbsp;Zhili Du","doi":"10.1016/j.eiar.2026.108390","DOIUrl":"10.1016/j.eiar.2026.108390","url":null,"abstract":"<div><div>Amidst the uncertainties of global economy and relentless march of climate change, companies with strong ESG profiles are increasingly drawing the eye of investors. This shift has elevated ESG to a crucial factor in how capital is distributed. Simultaneously, the impact of ESG is no longer confined to individual firms; it is likely to extend to other enterprises within the same industry, giving rise to the spillover effect discussed in this paper. Employing China's A-share listed companies from 2010 to 2023, this paper explores the spillover effect that high ESG performance exerts on the debt financing costs of peer firms in the same industry. The study obtains interesting findings with practical significance. Firstly, the debt financing costs of peer firms have decreased by 10.58%, which is impacted by the high ratings of the first batch of enterprises to receive ESG ratings from institutions. This spillover effect mainly works through the credit attractiveness of the industry and learning mechanism in peer firms. Secondly, some spillover effects are limited by the constrained impact of a firm's ESG performance on its financing, while others face obstacles in the transmission pathways to peer firms. This paper identifies these differentiated constrains. Finally, the diversity of ESG ratings by third-party agencies can enhance the peer spillovers by enhancing information and inhibiting rent seeking. This study expands the research perspectives incorporating ESG and offers empirical evidence to improve enterprises financing efficiency and industry synergy.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108390"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146170827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Does agricultural industry agglomeration mitigate the trade shocks on food system resilience? Empirical evidence from China","authors":"Ruimin Yin ,&nbsp;Zhanqi Wang ,&nbsp;Yue Dou ,&nbsp;Xinyuan Liang ,&nbsp;Yunxiao Gao ,&nbsp;Dengying Huang","doi":"10.1016/j.eiar.2026.108377","DOIUrl":"10.1016/j.eiar.2026.108377","url":null,"abstract":"<div><div>The increasing interconnectedness among countries and regions presents significant risks from external disruptions to China's food security. In this study, we aimed to propose valuable insights amidst the transformation of China's food system by revealing relationships between trade shocks, agricultural industry agglomeration, and food system resilience. With panel data, we investigated the impact and transmission mechanisms of trade policy uncertainty (TPU) on food system resilience (FSR) and examined how agricultural industry agglomeration (AIA) regulated this relationship from the perspective of geographic clustering and specialization. Our findings indicated that heightened TPU considerably undermined FSR, while AIA mitigated the negative effects. Regional analyses revealed that TPU significantly affected FSR in major producing areas and major selling areas, whereas its impact differed comparatively in producing and selling balanced areas. Additionally, the geographic clustering substantially alleviated shocks in major producing and selling areas, with varying effects observed regarding specialization. A comparison of resilience dimensions indicated that geographic clustering significantly regulated different resilience dimensions. Notably, specialization diminished the impact of resistance and failed to contribute effectively to adaptation and transformation. These findings underscore the critical role of AIA in regulating external shocks to the food system, offering insights for enhancing and adjusting the resilience structure, as well as for formulating agricultural policies that account for regional functional disparities.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108377"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146170857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comparative evaluation of spatial cross-correlation approaches for diagnosing water-related compound risk: A case study in the Greater Bay Area, China","authors":"Peijun Lu ,&nbsp;Yimin Sun ,&nbsp;Yicheng Wang","doi":"10.1016/j.eiar.2026.108400","DOIUrl":"10.1016/j.eiar.2026.108400","url":null,"abstract":"<div><div>Compound disasters arising from interacting hazards increasingly challenge urban resilience, yet spatially explicit tools for diagnosing where hazards co-vary remain limited. To address this gap, this study develops a spatial explicit inferential diagnostic framework that applies moving-window cross-correlation to harmonized raster risk layers, providing a map-based assessment of local inter-hazard dependence. The framework implements three complementary statistics within a moving-window design—Dutilleul's modified <em>t</em>-test (spatial-autocorrelation-adjusted inference), mutual information (nonlinear dependence detection), and Kendall's τ (rank-based robustness)—and benchmarks their performance in terms of diagnostic consistency, computational efficiency, reliability, and scale sensitivity across multiple spatial scales. The Guangdong–Hong Kong–Macao Greater Bay Area, China, serves as the case study, focusing on water-related compound risk. Results show that high-to-very-high dependence zones concentrate in coastal–estuarine corridors and major urban drainage basins, highlighting interaction patterns not recoverable from single-hazard overlays alone. Under an uncertainty-aware validation framework, Dutilleul's modified <em>t</em>-test achieved the strongest fine-scale hotspot delineation, with 88.0% of river flood–urban inundation event and 65.7% of urban inundation–storm surge events intersecting mapped high-dependence zones. Kendall's τ provides balanced robustness and stable performance across scales, supporting regional screening and cross-validation of spatial patterns. Mutual information generates smoother dependence fields with low scale sensitivity, indicating value for reconnaissance-style mapping but reduced fidelity for localized hotspot targeting. Runtime comparisons further demonstrate that methodological performance is scale-conditional, with Dutilleul's test fastest at fine resolutions but increasingly computationally intensive at larger window sizes. Rather than replacing indicator-based risk assessment, the proposed framework functions as a complementary diagnostic tool that quantifies where hazards reinforce one another under spatial autocorrelation. By explicitly mapping localized dependence regimes, the study advances multi-hazard interpretation and provides a transferable workflow for compound-risk screening in data-rich urban regions. Future research should expand compound-event validation datasets, improve computational scalability, and extend the hazard-agnostic workflow to additional hazard combinations and scenario-based planning contexts.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108400"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Consumption-driven health burdens within borders: China's interprovincial transfers","authors":"Haoxuan Yu ,&nbsp;Izni Zahidi ,&nbsp;Chow Ming Fai ,&nbsp;Dongfang Liang","doi":"10.1016/j.eiar.2026.108367","DOIUrl":"10.1016/j.eiar.2026.108367","url":null,"abstract":"<div><div>China's clean-air strategies have led to remarkable improvements in air quality and public health, representing a critical environmental achievement. Building on this progress, understanding the spatial distribution of health benefits provides important insights for future policy optimization. Historically, the country's interprovincial economic networks have shaped the geographic distribution of pollution and health burdens, with emissions often occurring in industrial production regions while consumption benefits accrue in economic centers. This study provides a quantitative assessment of how historical economic linkages have influenced environmental health distribution patterns, integrating multi-regional input–output (MRIO) data, emission inventories, population exposure maps, and mortality estimates across 31 provinces over the 2012–2017 period. Using a consumption-based responsibility framework, the analysis quantifies the transfer of PM₂.₅-attributable premature deaths between producing and consuming provinces and examines how these spatial patterns evolved during this transformative period. Results show that approximately 40.0% of PM₂.₅-related premature deaths in 2015 were associated with production serving consumption in other provinces. Coastal economic hubs such as Beijing and Shanghai sourced over 80% of their consumption from other provinces, while inland industrial regions including Hebei, Shandong, and Shanxi experienced mortality rates up to three times higher than implied by their own consumption. Despite a one-third national reduction in PM₂.₅ concentrations, these historical development patterns persisted along east-to-inland economic corridors. By examining historical patterns of economic development and environmental health outcomes, this study offers evidence-based insights for future policy design. Learning from these spatial dynamics and embedding spatial equity considerations into fiscal and business strategies, strengthening interregional coordination mechanisms, and promoting comprehensive supply-chain accountability are essential steps toward aligning clean-air progress with sustainable and just development goals in China's next phase of ecological civilization construction.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108367"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146170831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}