Pub Date : 2026-01-22DOI: 10.1016/j.eiar.2026.108350
Ying Tian , Jun Pang
The mismatch between CO2 emission and economic benefit transfer embodied in China's interprovincial trade led to carbon inequity. While existing literature has investigated the phenomenon, its sectoral drivers and underlying mechanisms remained underexplored. To address this gap, this study developed a carbon inequity index, assessed provincial carbon inequity from 2012 to 2017, and classified provinces into four types: main beneficiary, inferior beneficiary, inferior victim, and main victim. The findings identified the electric and heat power, other manufacture, and service sectors as the primary drivers of carbon inequity. The root cause was their production-based carbon intensity difference. Decomposition analysis revealed that this difference was primarily driven by potential energy intensity gaps. Nationally, carbon inequity worsened, as carbon Gini coefficient increased from 0.255 to 0.321. In bilateral trade, beneficiary provinces gained economic advantages by principally exporting service and other manufacture products, while transferring electric and heat power related CO2 emission to victim provinces. These findings provided critical insights into the mechanisms of carbon inequity, guided the design of precise policies in China, and offered a valuable reference for other developing countries.
{"title":"Alleviating carbon inequity: Examining the primary mechanisms in China's interprovincial trade","authors":"Ying Tian , Jun Pang","doi":"10.1016/j.eiar.2026.108350","DOIUrl":"10.1016/j.eiar.2026.108350","url":null,"abstract":"<div><div>The mismatch between CO<sub>2</sub> emission and economic benefit transfer embodied in China's interprovincial trade led to carbon inequity. While existing literature has investigated the phenomenon, its sectoral drivers and underlying mechanisms remained underexplored. To address this gap, this study developed a carbon inequity index, assessed provincial carbon inequity from 2012 to 2017, and classified provinces into four types: main beneficiary, inferior beneficiary, inferior victim, and main victim. The findings identified the electric and heat power, other manufacture, and service sectors as the primary drivers of carbon inequity. The root cause was their production-based carbon intensity difference. Decomposition analysis revealed that this difference was primarily driven by potential energy intensity gaps. Nationally, carbon inequity worsened, as carbon Gini coefficient increased from 0.255 to 0.321. In bilateral trade, beneficiary provinces gained economic advantages by principally exporting service and other manufacture products, while transferring electric and heat power related CO<sub>2</sub> emission to victim provinces. These findings provided critical insights into the mechanisms of carbon inequity, guided the design of precise policies in China, and offered a valuable reference for other developing countries.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108350"},"PeriodicalIF":11.2,"publicationDate":"2026-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025606","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}
Pub Date : 2026-01-21DOI: 10.1016/j.eiar.2026.108346
Zhixiu Li , Yifei Sun , Jiajing Song , Yihan Wang , Yangyang Wei
With the increasing prominence of mental health issues among humans, the restorative benefits of natural environments have garnered widespread attention. As a typical high-restorative living environment, the forest village plays a significant role in generating positive restorative effects. Previous studies have mainly explored the simple correlations between environmental characteristics and psychological or physiological indicators, while the differences in restorative benefits between virtual and real environments have not yet been systematically quantified within a unified experimental framework. This study employs electroencephalography (EEG) technology through a dual-modal experiment of virtual reality (VR) observation and real-world experience to quantify the neurophysiological impacts of forest village environments on psychological restoration. Based on structural equation modeling analysis, it reveals the causal relationships between environmental characteristics and brainwave activity. Using national forest villages as case examples, EEG data were collected from participants with the eego™ mylab device. Combining restorative evaluation and environmental preference scales, the study comprehensively analyzes the “psychological–physiological” response mechanisms underlying the restorative benefits of typical sample environments. The results show that the forest village environment significantly enhances α wave power (real-world group: 0.351; VR group: 0.314; p < 0.05) and suppresses excessive β wave activity (real-world group: −0.242; VR group: −0.213; p < 0.05), confirming its neural mechanisms in stress alleviation and relaxation promotion. Environmental preference indirectly regulates brainwave activity through restorative evaluation, with “mystery” showing the highest explanatory power (real-world group standardized factor loading λ = 0.847, explanatory power λ2 = 71.7%; VR group λ = 0.821, λ2 = 67.4%). This study proposes an interdisciplinary framework and dynamic feedback pathway of “environmental preference–psychological evaluation–neural response.” It not only provides neuroscientific evidence for the restorative benefits of forest village environments and promotes a data-driven transformation in environmental psychology, but also offers new insights into the design of ecological wellness scenarios and the development of remote environmental healing systems.
{"title":"Neurophysiological assessment of restorative benefits in forest-rural landscapes: EEG responses to real-world and virtual environments","authors":"Zhixiu Li , Yifei Sun , Jiajing Song , Yihan Wang , Yangyang Wei","doi":"10.1016/j.eiar.2026.108346","DOIUrl":"10.1016/j.eiar.2026.108346","url":null,"abstract":"<div><div>With the increasing prominence of mental health issues among humans, the restorative benefits of natural environments have garnered widespread attention. As a typical high-restorative living environment, the forest village plays a significant role in generating positive restorative effects. Previous studies have mainly explored the simple correlations between environmental characteristics and psychological or physiological indicators, while the differences in restorative benefits between virtual and real environments have not yet been systematically quantified within a unified experimental framework. This study employs electroencephalography (EEG) technology through a dual-modal experiment of virtual reality (VR) observation and real-world experience to quantify the neurophysiological impacts of forest village environments on psychological restoration. Based on structural equation modeling analysis, it reveals the causal relationships between environmental characteristics and brainwave activity. Using national forest villages as case examples, EEG data were collected from participants with the eego™ mylab device. Combining restorative evaluation and environmental preference scales, the study comprehensively analyzes the “psychological–physiological” response mechanisms underlying the restorative benefits of typical sample environments. The results show that the forest village environment significantly enhances α wave power (real-world group: 0.351; VR group: 0.314; <em>p</em> < 0.05) and suppresses excessive β wave activity (real-world group: −0.242; VR group: −0.213; p < 0.05), confirming its neural mechanisms in stress alleviation and relaxation promotion. Environmental preference indirectly regulates brainwave activity through restorative evaluation, with “mystery” showing the highest explanatory power (real-world group standardized factor loading λ = 0.847, explanatory power λ<sup>2</sup> = 71.7%; VR group λ = 0.821, λ<sup>2</sup> = 67.4%). This study proposes an interdisciplinary framework and dynamic feedback pathway of “environmental preference–psychological evaluation–neural response.” It not only provides neuroscientific evidence for the restorative benefits of forest village environments and promotes a data-driven transformation in environmental psychology, but also offers new insights into the design of ecological wellness scenarios and the development of remote environmental healing systems.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108346"},"PeriodicalIF":11.2,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025615","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}
Pub Date : 2026-01-21DOI: 10.1016/j.eiar.2026.108341
Yuntong Zhao , Zhe Liu , Tony R. Walker , Michelle Adams , Weili Liu
The recycling and utilization of reclaimed water (RURW) is a crucial strategy for addressing the increasing imbalance between water supply and demand in water-scarce regions worldwide. Assessing the impact of the RURW policy and investigating its relationship with water resource utilization level (WRUL) are essential for improving the RURW model. Utilizing the Synthetic Control Method (SCM), this study focuses on Tianjin, a pilot city for the RURW policy and constructs a synthetic counterfactual Tianjin using non-policy provincial capitals and municipalities as the control group. This approach enables an empirical examination of how RURW allocation optimization enhances WRUL in China's first batch of pilot cities. The findings reveal that since the RURW policy implementation in 2022, this policy has gradually improved WRUL in Tianjin, with the efficiency gap between real Tianjin and synthetic Tianjin to expand over time. The mechanism analysis demonstrates that increased reclaimed water utilization directly contributes to higher WRUL in Tianjin. The findings demonstrate the essential role of RURW policy in supplementing water resource for urban development in water-scarce regions, while also contributing to the theoretical framework for evaluating such policies. Furthermore, it offers valuable insights for enhancing regional water resource management and promoting sustainable global water recycling practices.
{"title":"Does the recycling and utilization of reclaimed water policy effectively address regional water scarcity? Evidence from a pilot city in China","authors":"Yuntong Zhao , Zhe Liu , Tony R. Walker , Michelle Adams , Weili Liu","doi":"10.1016/j.eiar.2026.108341","DOIUrl":"10.1016/j.eiar.2026.108341","url":null,"abstract":"<div><div>The recycling and utilization of reclaimed water (RURW) is a crucial strategy for addressing the increasing imbalance between water supply and demand in water-scarce regions worldwide. Assessing the impact of the RURW policy and investigating its relationship with water resource utilization level (WRUL) are essential for improving the RURW model. Utilizing the Synthetic Control Method (SCM), this study focuses on Tianjin, a pilot city for the RURW policy and constructs a synthetic counterfactual Tianjin using non-policy provincial capitals and municipalities as the control group. This approach enables an empirical examination of how RURW allocation optimization enhances WRUL in China's first batch of pilot cities. The findings reveal that since the RURW policy implementation in 2022, this policy has gradually improved WRUL in Tianjin, with the efficiency gap between real Tianjin and synthetic Tianjin to expand over time. The mechanism analysis demonstrates that increased reclaimed water utilization directly contributes to higher WRUL in Tianjin. The findings demonstrate the essential role of RURW policy in supplementing water resource for urban development in water-scarce regions, while also contributing to the theoretical framework for evaluating such policies. Furthermore, it offers valuable insights for enhancing regional water resource management and promoting sustainable global water recycling practices.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108341"},"PeriodicalIF":11.2,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025564","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}
Pub Date : 2026-01-21DOI: 10.1016/j.eiar.2026.108354
Hyungsu Kang , Hyunmin Daniel Zoh , Sumin Jeon
While emission trading schemes (ETSs) have contributed to greenhouse gas (GHG) emission abatement achievement in some countries, current free allocation systems still contain baseline problems caused by measuring differences between baseline settings and actual emissions. Notably, existing grandparenting and benchmarking methodologies for the baseline setting would induce market participants to inflate their project baselines to overestimate emission reduction allowances. To mitigate overreporting risks above, this study introduces a GHG allocation model (GMD) applying the Macaulay duration (MD) financial concept. It addresses to incentivize honest GHG disclosure and promote carbon neutrality approaches, by avoiding limitations of traditional baseline setting. Suggested GMD model focuses on the GHG emission lifecycle similar to issuance and redemption of bonds. Mathematical derivation of the model is designed gradual emission reductions throughout project lifecycles. And honest disclosure of actual emissions represents the optimal strategy for agents. This model has two key novelties compared with other mechanisms: preventing baseline overestimation and ensuring continuous progress toward carbon neutrality. And additional simulation using initial realistic emission data shows how GMD model induces accurate emission reporting while naturally decreasing allowances over time. The simulation suggest that GMD model is more effective to avoid misreporting while maintaining flexibility by each project characteristic. Furthermore, policymakers can adjust project GHG emissions by setting simple GMD values according to operational periods. This presents a pathway enabling economic subjects to establish emission plans autonomously while achieving long-term abatement. GMD framework and modeling provides lifecycle-integrated GHG management for accurate report and net zero action.
{"title":"A lifecycle-integrated GHG management framework: Long-term allocation mechanism to prevent abatement misreporting","authors":"Hyungsu Kang , Hyunmin Daniel Zoh , Sumin Jeon","doi":"10.1016/j.eiar.2026.108354","DOIUrl":"10.1016/j.eiar.2026.108354","url":null,"abstract":"<div><div>While emission trading schemes (ETSs) have contributed to greenhouse gas (GHG) emission abatement achievement in some countries, current free allocation systems still contain baseline problems caused by measuring differences between baseline settings and actual emissions. Notably, existing grandparenting and benchmarking methodologies for the baseline setting would induce market participants to inflate their project baselines to overestimate emission reduction allowances. To mitigate overreporting risks above, this study introduces a GHG allocation model (GMD) applying the Macaulay duration (MD) financial concept. It addresses to incentivize honest GHG disclosure and promote carbon neutrality approaches, by avoiding limitations of traditional baseline setting. Suggested GMD model focuses on the GHG emission lifecycle similar to issuance and redemption of bonds. Mathematical derivation of the model is designed gradual emission reductions throughout project lifecycles. And honest disclosure of actual emissions represents the optimal strategy for agents. This model has two key novelties compared with other mechanisms: preventing baseline overestimation and ensuring continuous progress toward carbon neutrality. And additional simulation using initial realistic emission data shows how GMD model induces accurate emission reporting while naturally decreasing allowances over time. The simulation suggest that GMD model is more effective to avoid misreporting while maintaining flexibility by each project characteristic. Furthermore, policymakers can adjust project GHG emissions by setting simple GMD values according to operational periods. This presents a pathway enabling economic subjects to establish emission plans autonomously while achieving long-term abatement. GMD framework and modeling provides lifecycle-integrated GHG management for accurate report and net zero action.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108354"},"PeriodicalIF":11.2,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025616","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}
Pub Date : 2026-01-21DOI: 10.1016/j.eiar.2026.108358
Chang You , Wenshu Liu , Lanhui Zhou , Chen-Chieh Feng , Luo Guo
Against the backdrop of increasing global environmental pressures, clarifying the feature contribution factors influencing the ecosystem service scarcity value (ESSV) under human activities is essential for promoting ecological conservation and sustainable economic development. This study revolutionizes ESSV assessment by embedding supply-demand sensitivity and population elasticity into a reconstructed scarcity framework, combined with the interpretability of Transformer and SHAP to decode nonlinear, spatiotemporal human-ecosystem interactions in China (1990–2020). It is the first to integrate a nationwide multi-ethnic perception survey, revealing long-overlooked sociocultural drivers in ecosystem service research and expanding the analytical frontier beyond the biophysical and economic realms. The main findings include: (1) Over the past 30 years, the supply and demand side values have increased significantly, mainly influenced by demand-side factors such as population growth and consumption upgrades. Meanwhile, environmental quality indicators such as NDVI and PM2.5, along with demand-side measures of human activity intensity such as the human footprint and transportation accessibility, also play pivotal roles in shaping ESSV. These factors essentially reflect the ecological pressures stemming from growing demand and their subsequent feedback effects; the spatial pattern highlights the fluctuations and increased pressure on the economically active eastern coastal city clusters; (2) Among ecological indicators, NDVI becomes a positive core driving factor, while PM2.5 levels and human footprint index continue to inhibit ecosystem functions, and transportation accessibility shows a complex two-way impact; (3) Traditional agricultural cultural dependence, ecological knowledge dissemination, pressure perception, and conservation intentions enhance public recognition of ESSV and encourage pro-ecological behaviors (e.g., environmental protection, rational resource use), thereby indirectly shaping the supply-demand balance of ecosystem services. The obvious differences in perception among different ethnic groups highlight the key role of sociocultural dimensions in ecological management. The high-precision and interpretable deep learning spatiotemporal analysis framework proposed in this paper not only enriches the theoretical understanding of ESSV but also provides important insights for formulating spatially differentiated conservation policies and effectively catalyzing public ecological participation, thereby supporting the sustainable management and development of ecosystem services.
{"title":"Integrating spatial patterns of ecosystem service scarcity into territorial spatial governance with multiethnic perception perspective","authors":"Chang You , Wenshu Liu , Lanhui Zhou , Chen-Chieh Feng , Luo Guo","doi":"10.1016/j.eiar.2026.108358","DOIUrl":"10.1016/j.eiar.2026.108358","url":null,"abstract":"<div><div>Against the backdrop of increasing global environmental pressures, clarifying the feature contribution factors influencing the ecosystem service scarcity value (ESSV) under human activities is essential for promoting ecological conservation and sustainable economic development. This study revolutionizes ESSV assessment by embedding supply-demand sensitivity and population elasticity into a reconstructed scarcity framework, combined with the interpretability of Transformer and SHAP to decode nonlinear, spatiotemporal human-ecosystem interactions in China (1990–2020). It is the first to integrate a nationwide multi-ethnic perception survey, revealing long-overlooked sociocultural drivers in ecosystem service research and expanding the analytical frontier beyond the biophysical and economic realms. The main findings include: (1) Over the past 30 years, the supply and demand side values have increased significantly, mainly influenced by demand-side factors such as population growth and consumption upgrades. Meanwhile, environmental quality indicators such as NDVI and PM<sub>2.5</sub>, along with demand-side measures of human activity intensity such as the human footprint and transportation accessibility, also play pivotal roles in shaping ESSV. These factors essentially reflect the ecological pressures stemming from growing demand and their subsequent feedback effects; the spatial pattern highlights the fluctuations and increased pressure on the economically active eastern coastal city clusters; (2) Among ecological indicators, NDVI becomes a positive core driving factor, while PM2.5 levels and human footprint index continue to inhibit ecosystem functions, and transportation accessibility shows a complex two-way impact; (3) Traditional agricultural cultural dependence, ecological knowledge dissemination, pressure perception, and conservation intentions enhance public recognition of ESSV and encourage pro-ecological behaviors (e.g., environmental protection, rational resource use), thereby indirectly shaping the supply-demand balance of ecosystem services. The obvious differences in perception among different ethnic groups highlight the key role of sociocultural dimensions in ecological management. The high-precision and interpretable deep learning spatiotemporal analysis framework proposed in this paper not only enriches the theoretical understanding of ESSV but also provides important insights for formulating spatially differentiated conservation policies and effectively catalyzing public ecological participation, thereby supporting the sustainable management and development of ecosystem services.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108358"},"PeriodicalIF":11.2,"publicationDate":"2026-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025617","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}
Pub Date : 2026-01-20DOI: 10.1016/j.eiar.2026.108344
Xiangying Kong , Shengquan Lu , Baoqing Hu , Yurou Liang , Jiaxin Li
Topography critically shapes the distribution of Rural Settlements (RS). However, previous studies have often neglected the systematic role of topographic gradients, typically focusing on macro scales, which obscures the nuanced patterns and underlying mechanisms at the village level. To address this, we developed a two-dimensional elevation-slope framework to reconstruct the 40-year evolution of China's RS at the administrative village scale. We then quantified its morphological changes at the village level and employed a Geographically Weighted Machine Learning (GWML) framework, which integrates geographically weighted principles with machine learning capabilities to capture the spatial heterogeneity and non-linear effects of the driving factors. Our findings reveal a highly uneven RS distribution. By 2020, 78.49% of the settlement area was concentrated in Low elevation-Low slope (L-L) regions, comprising just 21.74% of China's landmass. Over the past four decades, expansion has trended towards higher elevations and steeper slopes, though patterns and land sources varied significantly by terrain. Plains expansion was dominated by edge-expansion onto Cultivated Land, whereas in topographically complex regions, it was more dispersed with diverse sources. Furthermore, settlement density in L-L villages was over a hundredfold greater than in High elevation-High slope (HH) villages. The optimal Geographically Weighted Random Forest (GWRF) model shows that expansion in plains is driven by land use intensity and village scale, while in complex terrains, it is governed by ecological constraints or economic density. This study systematically dissects the dynamic patterns and morphological differentiation of rural settlements under topographic constraints, offering scientific insights for rural revitalisation and regional planning.
{"title":"Understanding the village-scale expansion of rural settlements in China from a topographic perspective","authors":"Xiangying Kong , Shengquan Lu , Baoqing Hu , Yurou Liang , Jiaxin Li","doi":"10.1016/j.eiar.2026.108344","DOIUrl":"10.1016/j.eiar.2026.108344","url":null,"abstract":"<div><div>Topography critically shapes the distribution of Rural Settlements (RS). However, previous studies have often neglected the systematic role of topographic gradients, typically focusing on macro scales, which obscures the nuanced patterns and underlying mechanisms at the village level. To address this, we developed a two-dimensional elevation-slope framework to reconstruct the 40-year evolution of China's RS at the administrative village scale. We then quantified its morphological changes at the village level and employed a Geographically Weighted Machine Learning (GWML) framework, which integrates geographically weighted principles with machine learning capabilities to capture the spatial heterogeneity and non-linear effects of the driving factors. Our findings reveal a highly uneven RS distribution. By 2020, 78.49% of the settlement area was concentrated in Low elevation-Low slope (L-L) regions, comprising just 21.74% of China's landmass. Over the past four decades, expansion has trended towards higher elevations and steeper slopes, though patterns and land sources varied significantly by terrain. Plains expansion was dominated by edge-expansion onto Cultivated Land, whereas in topographically complex regions, it was more dispersed with diverse sources. Furthermore, settlement density in L-L villages was over a hundredfold greater than in High elevation-High slope (H<img>H) villages. The optimal Geographically Weighted Random Forest (GWRF) model shows that expansion in plains is driven by land use intensity and village scale, while in complex terrains, it is governed by ecological constraints or economic density. This study systematically dissects the dynamic patterns and morphological differentiation of rural settlements under topographic constraints, offering scientific insights for rural revitalisation and regional planning.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108344"},"PeriodicalIF":11.2,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025613","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}
Pub Date : 2026-01-20DOI: 10.1016/j.eiar.2026.108347
Xi Tian , Jingxian Di , Fei Peng , Zhikang Hu , Jinliang Xie , Guoen Wei , Ziqian Xia , Huanhuan Xiong , Anwar Khan , Yaobin Liu
China is actively promoting the second-use of retired power batteries to maximize their residual value. However, the economic viability and environmental benefits across application scenarios remain unclear, constraining rational selection and scale-up. Previous studies use heterogeneous economic scopes and environmental accounting boundaries, limiting cross-scenario comparability. To address this gap, a unified framework integrating economic and environmental dimensions was established. The equivalent annual method (EAM) was employed to convert each scenario's costs and benefits to a common annual basis, and life cycle assessment (LCA) with consistent system boundaries and functional units was applied to enable quantitative comparison across eight second-use application scenarios. The results show that: (1) Economically, the energy storage-thermal power joint frequency regulation (ETJFR) scenario achieves the highest profitability, with an annual economic profit of 1380 CNY/kWh, whereas the renewable energy power station scenario performs worst. (2) Environmentally, the industrial park scenario delivers the largest benefit, with a global warming potential (GWP) reduction of 436 kg CO2-eq/kWh. By contrast, the ETJFR scenario shows net increases across all six indicators. (3) Sensitivity analysis indicates that remaining cycle life is critical for the renewable energy power station scenario. Moreover, improvements in charge-discharge efficiency can substantially enhance environmental performance. Overall, the analysis reveals a key trade-off between the economic advantage of the ETJFR scenario and the environmental benefits of the industrial park scenario, which can inform future second-use scenario selection.
中国正在积极推动退役动力电池的二次利用，使其剩余价值最大化。然而，各种应用场景的经济可行性和环境效益仍不清楚，这限制了合理选择和扩大规模。先前的研究使用异质经济范围和环境会计边界，限制了跨情景的可比性。为了解决这一差距，建立了一个综合经济和环境方面的统一框架。采用等效年度方法（EAM）将每个场景的成本和收益转换为共同的年度基础，并应用具有一致系统边界和功能单元的生命周期评估（LCA）来实现8个二次使用应用场景的定量比较。结果表明：(1)经济效益方面，储能-火电联合调频（ETJFR）情景的年经济效益最高，为1380元/千瓦时，而可再生能源电站情景的年经济效益最差。(2)在环境方面，工业园区方案的效益最大，其全球变暖潜能值（GWP）减少了436 kg co2当量/千瓦时。相比之下，ETJFR情景显示所有六项指标均有净增长。(3)敏感性分析表明，剩余循环寿命对可再生能源电站方案至关重要。此外，充放电效率的提高可以大大提高环境绩效。总体而言，分析揭示了ETJFR情景的经济优势与工业园区情景的环境效益之间的关键权衡，这可以为未来的二次利用情景选择提供信息。
{"title":"Comparative assessment of economic and environmental impacts across eight second-use scenarios for retired lithium iron phosphate batteries in China","authors":"Xi Tian , Jingxian Di , Fei Peng , Zhikang Hu , Jinliang Xie , Guoen Wei , Ziqian Xia , Huanhuan Xiong , Anwar Khan , Yaobin Liu","doi":"10.1016/j.eiar.2026.108347","DOIUrl":"10.1016/j.eiar.2026.108347","url":null,"abstract":"<div><div>China is actively promoting the second-use of retired power batteries to maximize their residual value. However, the economic viability and environmental benefits across application scenarios remain unclear, constraining rational selection and scale-up. Previous studies use heterogeneous economic scopes and environmental accounting boundaries, limiting cross-scenario comparability. To address this gap, a unified framework integrating economic and environmental dimensions was established. The equivalent annual method (EAM) was employed to convert each scenario's costs and benefits to a common annual basis, and life cycle assessment (LCA) with consistent system boundaries and functional units was applied to enable quantitative comparison across eight second-use application scenarios. The results show that: (1) Economically, the energy storage-thermal power joint frequency regulation (ETJFR) scenario achieves the highest profitability, with an annual economic profit of 1380 CNY/kWh, whereas the renewable energy power station scenario performs worst. (2) Environmentally, the industrial park scenario delivers the largest benefit, with a global warming potential (GWP) reduction of 436 kg CO<sub>2</sub>-eq/kWh. By contrast, the ETJFR scenario shows net increases across all six indicators. (3) Sensitivity analysis indicates that remaining cycle life is critical for the renewable energy power station scenario. Moreover, improvements in charge-discharge efficiency can substantially enhance environmental performance. Overall, the analysis reveals a key trade-off between the economic advantage of the ETJFR scenario and the environmental benefits of the industrial park scenario, which can inform future second-use scenario selection.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108347"},"PeriodicalIF":11.2,"publicationDate":"2026-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025614","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}
Pub Date : 2026-01-19DOI: 10.1016/j.eiar.2026.108349
Yunsheng Bai , Gengyuan Liu , Yang Guo , Nan Zhang , Frederick Kwame Yeboah , Pei Wang , Zhaobo Liu , Liang Dong
This paper explores the conceptual and practical expansion of industrial symbiosis (IS) to the realm of industry-city integration (ICI), and further proposes industry-city co-prosperity as a new paradigm for sustainable urban-industrial development. A systematic literature review was conducted. This review analyzed 132 selected studies to trace the evolution from firm-centered IS network to multi-scalar urban-industrial synergies. The results indicate that traditional IS, while successful in enabling resource-sharing among firms, remains limited by spatial confinement and administrative boundaries. ICI bridges this gap by redefining the city as a functional node of industrial and talent chains, extending symbiotic practices to cross-regional metabolic flows and social integration. A typology of three distinct governance models for ICI (Top-Down Planning, Self-Organizing, and Government-Promotion) is developed and a multi-dimensional comparative analysis of international cases under each model is conducted. The findings reveal that no single model is sufficient; instead, a hybrid governance architecture is essential to overcome administrative silos and foster emerging circular service industries. The paper concludes that aligning industrial development with urban sustainability requires moving beyond resource efficiency toward a state of dynamic, functional synergy and inclusive governance.
{"title":"From symbiosis to co-prosperity: Redefining industry-city integration for urban resilience","authors":"Yunsheng Bai , Gengyuan Liu , Yang Guo , Nan Zhang , Frederick Kwame Yeboah , Pei Wang , Zhaobo Liu , Liang Dong","doi":"10.1016/j.eiar.2026.108349","DOIUrl":"10.1016/j.eiar.2026.108349","url":null,"abstract":"<div><div>This paper explores the conceptual and practical expansion of industrial symbiosis (IS) to the realm of industry-city integration (ICI), and further proposes industry-city co-prosperity as a new paradigm for sustainable urban-industrial development. A systematic literature review was conducted. This review analyzed 132 selected studies to trace the evolution from firm-centered IS network to multi-scalar urban-industrial synergies. The results indicate that traditional IS, while successful in enabling resource-sharing among firms, remains limited by spatial confinement and administrative boundaries. ICI bridges this gap by redefining the city as a functional node of industrial and talent chains, extending symbiotic practices to cross-regional metabolic flows and social integration. A typology of three distinct governance models for ICI (Top-Down Planning, Self-Organizing, and Government-Promotion) is developed and a multi-dimensional comparative analysis of international cases under each model is conducted. The findings reveal that no single model is sufficient; instead, a hybrid governance architecture is essential to overcome administrative silos and foster emerging circular service industries. The paper concludes that aligning industrial development with urban sustainability requires moving beyond resource efficiency toward a state of dynamic, functional synergy and inclusive governance.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108349"},"PeriodicalIF":11.2,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025612","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}
Pub Date : 2026-01-19DOI: 10.1016/j.eiar.2026.108342
Luming Yan , Ruilian Zhang , Ming Ji , Yujian Li
This study investigates the impact of China's Social Stability Risk Assessment (SSRA) policy on the effectiveness of social governance. By analyzing policy implementation across various administrative regions and evaluating governance outcomes using a comprehensive index framework, the paper assesses whether SSRA contributes to proactive conflict resolution, enhanced public participation, and improved administrative coordination. Empirical evidence from regional case studies and statistical analyses suggests that the SSRA policy positively correlates with improvements in social governance, particularly in regions with strong institutional capacities and transparent risk evaluation mechanisms. However, the policy's effectiveness is uneven across jurisdictions, highlighting the importance of local governance conditions and policy enforcement quality. The findings offer insights into the role of preventive governance tools in maintaining social stability and enhancing state-society relations in transitional governance contexts.
{"title":"Does social stability risk assessment improve social governance level in China?","authors":"Luming Yan , Ruilian Zhang , Ming Ji , Yujian Li","doi":"10.1016/j.eiar.2026.108342","DOIUrl":"10.1016/j.eiar.2026.108342","url":null,"abstract":"<div><div>This study investigates the impact of China's Social Stability Risk Assessment (SSRA) policy on the effectiveness of social governance. By analyzing policy implementation across various administrative regions and evaluating governance outcomes using a comprehensive index framework, the paper assesses whether SSRA contributes to proactive conflict resolution, enhanced public participation, and improved administrative coordination. Empirical evidence from regional case studies and statistical analyses suggests that the SSRA policy positively correlates with improvements in social governance, particularly in regions with strong institutional capacities and transparent risk evaluation mechanisms. However, the policy's effectiveness is uneven across jurisdictions, highlighting the importance of local governance conditions and policy enforcement quality. The findings offer insights into the role of preventive governance tools in maintaining social stability and enhancing state-society relations in transitional governance contexts.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108342"},"PeriodicalIF":11.2,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025611","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}
Pub Date : 2026-01-19DOI: 10.1016/j.eiar.2026.108334
Yuchen Hu , Renke Wei , Ke Yu , Zhouyi Liu , Qi Zhou , Huan Zhang , Meng Zhang , Chenchen Wang , Lujing Zhang , Baolin Xue , Guoqiang Wang , Gang Liu , Shen Qu
Municipal wastewater treatment plants (MWWTPs) provide clean water for urban areas, but due to the significant use of energy and chemicals, the actual environmental implications remain concerning. An evaluation framework for assessing environmental benefits and resource loads is established using monthly operational data from more than 6200 MWWTPs in China from 2007 to 2020 to determine the sustainable potential of this industry and the determinants. A quantile random forest model is used to objectively obtain the plants' sustainability scores without being affected by differences in treatment conditions. The scores are characterized by major pollutant removal performance, representing environmental benefits, and by electricity and chemical consumption performance, representing resource loads. Each plant is provided with an efficient tool that enables it to clarify its actual contribution and to achieve precise improvements. The results show that pollutant removal is improved by large treatment capacities and rational sequence adjustments, whereas resource consumption is reduced through flexible operational responses and favorable ambient temperatures. Socioeconomic drivers play a regulatory role in the context of natural climate conditions. This grid-level evaluation study quantitatively clarified the actual impacts of MWWTPs by considering both the interactions among internal indicators and the effects of external macro-regional factors, thereby providing a data-driven reference for developing targeted improvement measures for individual plants and for policy makers to promote the sustainable development of the industry.
{"title":"Evaluating the environmental benefits and resource loads of municipal wastewater treatment plants in China","authors":"Yuchen Hu , Renke Wei , Ke Yu , Zhouyi Liu , Qi Zhou , Huan Zhang , Meng Zhang , Chenchen Wang , Lujing Zhang , Baolin Xue , Guoqiang Wang , Gang Liu , Shen Qu","doi":"10.1016/j.eiar.2026.108334","DOIUrl":"10.1016/j.eiar.2026.108334","url":null,"abstract":"<div><div>Municipal wastewater treatment plants (MWWTPs) provide clean water for urban areas, but due to the significant use of energy and chemicals, the actual environmental implications remain concerning. An evaluation framework for assessing environmental benefits and resource loads is established using monthly operational data from more than 6200 MWWTPs in China from 2007 to 2020 to determine the sustainable potential of this industry and the determinants. A quantile random forest model is used to objectively obtain the plants' sustainability scores without being affected by differences in treatment conditions. The scores are characterized by major pollutant removal performance, representing environmental benefits, and by electricity and chemical consumption performance, representing resource loads. Each plant is provided with an efficient tool that enables it to clarify its actual contribution and to achieve precise improvements. The results show that pollutant removal is improved by large treatment capacities and rational sequence adjustments, whereas resource consumption is reduced through flexible operational responses and favorable ambient temperatures. Socioeconomic drivers play a regulatory role in the context of natural climate conditions. This grid-level evaluation study quantitatively clarified the actual impacts of MWWTPs by considering both the interactions among internal indicators and the effects of external macro-regional factors, thereby providing a data-driven reference for developing targeted improvement measures for individual plants and for policy makers to promote the sustainable development of the industry.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108334"},"PeriodicalIF":11.2,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145993552","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}
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