Pub Date : 2026-06-01Epub Date: 2026-02-16DOI: 10.1016/j.eiar.2026.108348
Chengkuan Wu , Xuemei Zheng , Ning Zhang
Data is a critical production factor in the digital age, and its role in reducing pollution is gaining importance. In this context, we explore how data-sharing policies influence firms' emission intensity, using the creation of public data disclosure platforms (PDDPs) in China's prefecture-level cities as a quasi-natural experiment. Based on panel data on Chinese listed firms from 2007 to 2022, difference-in-differences (DID) estimations suggest that data sharing leads to a reduction of about 1% in firms' SO2 emission intensity. This decrease is primarily driven by improved resource allocation, increased environmental investment, and enhanced green innovation. Heterogeneity analysis reveals that the emission-reducing effect of data sharing is more pronounced among firms without political connections, those located in highly marketized provinces, and those in technology-intensive industries. Extended analysis reveals that the effectiveness of data sharing is driven primarily by the quality and practical application of the data itself, rather than the quality of the platform or accompanying assurance mechanisms. Moreover, firms' digital technology positively influences the effectiveness of data sharing in reducing emissions. Overall, this study emphasizes the pivotal role of data sharing in alleviating pollution and provides policy implications for other developing countries that face significant pressure to mitigate emissions.
{"title":"Digital governance and environmental protection: Evidence from China's data-sharing policies","authors":"Chengkuan Wu , Xuemei Zheng , Ning Zhang","doi":"10.1016/j.eiar.2026.108348","DOIUrl":"10.1016/j.eiar.2026.108348","url":null,"abstract":"<div><div>Data is a critical production factor in the digital age, and its role in reducing pollution is gaining importance. In this context, we explore how data-sharing policies influence firms' emission intensity, using the creation of public data disclosure platforms (PDDPs) in China's prefecture-level cities as a quasi-natural experiment. Based on panel data on Chinese listed firms from 2007 to 2022, difference-in-differences (DID) estimations suggest that data sharing leads to a reduction of about 1% in firms' SO<sub>2</sub> emission intensity. This decrease is primarily driven by improved resource allocation, increased environmental investment, and enhanced green innovation. Heterogeneity analysis reveals that the emission-reducing effect of data sharing is more pronounced among firms without political connections, those located in highly marketized provinces, and those in technology-intensive industries. Extended analysis reveals that the effectiveness of data sharing is driven primarily by the quality and practical application of the data itself, rather than the quality of the platform or accompanying assurance mechanisms. Moreover, firms' digital technology positively influences the effectiveness of data sharing in reducing emissions. Overall, this study emphasizes the pivotal role of data sharing in alleviating pollution and provides policy implications for other developing countries that face significant pressure to mitigate emissions.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108348"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384952","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 : 2026-06-01Epub Date: 2026-02-23DOI: 10.1016/j.eiar.2026.108396
Xinyu Chen , Xuan Wang , Xiaoping Jia , Siqi Wang , Raymond R. Tan , Bohong Wang , Fang Wang
Enhanced weathering (EW) of basalt is a promising negative emission technology (NET) for carbon dioxide removal (CDR), yet its large-scale sustainability remains uncertain, particularly in energy-intensive economies like China. This work develops an environmentally extended input-output (EEIO) model to evaluate the economic and environmental impacts of basalt EW deployment under China's carbon neutrality pathway. This framework integrates life-cycle emissions from mining, comminution, transportation, and cropland application, quantifying trade-offs between CDR potential and process-related carbon footprints. The results reveal a critical “amplified-offset” effect: at a 20% emissions reduction target, electricity-sector emissions surge by 9.8 Gt CO₂e due to energy-intensive comminution, inflating deployment requirements to 521% of theoretical estimates and offsetting a large fraction of the sequestration benefits. Spatial analysis uncovers regional disparities, with the Yangtze Plain and North China Plain offering optimal conditions, whereas other regions require 76–172% more resources due to significantly longer transport distances and the spatial mismatch between basalt quarries and farmland. Optimizing particle size (<10 μm) balances dissolution kinetics and energy consumption, while even finer grinds deliver net-negative returns. For the EW system, grid decarbonization is pivotal; clean electricity reduces deployment needs by 76%, and heavy-duty trucks lower transport emissions by 60%. This study underscores that basalt EW's viability in China hinges on decarbonized power supply, logistics optimization, and optimized particle-size control. Without these measures, supply-chain emissions may outweigh CDR gains. These results highlight the need for integrated policy and technological development to achieve scalable CDR deployment.
{"title":"Sustainability analysis of basalt enhanced weathering in China under the carbon neutrality pathway","authors":"Xinyu Chen , Xuan Wang , Xiaoping Jia , Siqi Wang , Raymond R. Tan , Bohong Wang , Fang Wang","doi":"10.1016/j.eiar.2026.108396","DOIUrl":"10.1016/j.eiar.2026.108396","url":null,"abstract":"<div><div>Enhanced weathering (EW) of basalt is a promising negative emission technology (NET) for carbon dioxide removal (CDR), yet its large-scale sustainability remains uncertain, particularly in energy-intensive economies like China. This work develops an environmentally extended input-output (EEIO) model to evaluate the economic and environmental impacts of basalt EW deployment under China's carbon neutrality pathway. This framework integrates life-cycle emissions from mining, comminution, transportation, and cropland application, quantifying trade-offs between CDR potential and process-related carbon footprints. The results reveal a critical “amplified-offset” effect: at a 20% emissions reduction target, electricity-sector emissions surge by 9.8 Gt CO₂e due to energy-intensive comminution, inflating deployment requirements to 521% of theoretical estimates and offsetting a large fraction of the sequestration benefits. Spatial analysis uncovers regional disparities, with the Yangtze Plain and North China Plain offering optimal conditions, whereas other regions require 76–172% more resources due to significantly longer transport distances and the spatial mismatch between basalt quarries and farmland. Optimizing particle size (<10 μm) balances dissolution kinetics and energy consumption, while even finer grinds deliver net-negative returns. For the EW system, grid decarbonization is pivotal; clean electricity reduces deployment needs by 76%, and heavy-duty trucks lower transport emissions by 60%. This study underscores that basalt EW's viability in China hinges on decarbonized power supply, logistics optimization, and optimized particle-size control. Without these measures, supply-chain emissions may outweigh CDR gains. These results highlight the need for integrated policy and technological development to achieve scalable CDR deployment.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108396"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384958","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 : 2026-06-01Epub Date: 2026-02-09DOI: 10.1016/j.eiar.2026.108379
Kaige Lei , Jiaming Zhang , Yan Li , Xinhui Feng , Jiayu Yang , Li Hou , Jianguo Liu
Agricultural trade can balance regional supply and demand but also induces spatial transfers of ecological pressure. However, few studies have combined the spatial transfers of ecological pressures with economic benefits to explore spatial mismatch and inequality. Understanding this relationship can reveal underlying reasons for the dilemma between economic development and ecological conservation. This study uses China as an example, combines the Lund-Potsdam-Jena Dynamic Global Vegetation Model with an environmentally extended multiregional input-output model to track spatial flows of Human Appropriation of Net Primary Productivity (HANPP) across provinces and establishes an Ecological Pressure Inequality index to quantify inequality by comparing them with value-added flows in time and space. The results show that northeast China bored net HANPP from central and western region, but it still need transferred 17.36 million yuan to those regions in 2012, in contrast, central China bore only 16.59% of the net HANPP yet still receiving 45.02% of the net value-added, revealing a significant spatial mismatch. After 2015, despite the increase in net HANPP transferred from western region to the northeast region, the net value added transferred to the northeast has been declining. At the provincial level, Anhui, Hunan, and Sichuan provinces transitioned toward dual-benefit positions, gaining economic advantages while offloading ecological pressure, whereas Jilin remained in a loss–loss state, suffering both ecological and economic deficits. Distant trade contributes more significantly to ecological inequality than adjacent trade. Stratified analysis reveals that variations in transportation accessibility, fiscal priority, and mechanization jointly characterize the structural heterogeneity of the mismatch across provinces. The study also emphasizes that distant trade cross-regional governance requires attention in ecological compensation. The methodology and insights offer valuable guidance for addressing similar sustainability challenges in other countries experiencing rapid economic development and regional disparities.
{"title":"Spatial mismatch and inequality between ecological pressure and economic benefits embodied in agricultural trade","authors":"Kaige Lei , Jiaming Zhang , Yan Li , Xinhui Feng , Jiayu Yang , Li Hou , Jianguo Liu","doi":"10.1016/j.eiar.2026.108379","DOIUrl":"10.1016/j.eiar.2026.108379","url":null,"abstract":"<div><div>Agricultural trade can balance regional supply and demand but also induces spatial transfers of ecological pressure. However, few studies have combined the spatial transfers of ecological pressures with economic benefits to explore spatial mismatch and inequality. Understanding this relationship can reveal underlying reasons for the dilemma between economic development and ecological conservation. This study uses China as an example, combines the Lund-Potsdam-Jena Dynamic Global Vegetation Model with an environmentally extended multiregional input-output model to track spatial flows of Human Appropriation of Net Primary Productivity (HANPP) across provinces and establishes an Ecological Pressure Inequality index to quantify inequality by comparing them with value-added flows in time and space. The results show that northeast China bored net HANPP from central and western region, but it still need transferred 17.36 million yuan to those regions in 2012, in contrast, central China bore only 16.59% of the net HANPP yet still receiving 45.02% of the net value-added, revealing a significant spatial mismatch. After 2015, despite the increase in net HANPP transferred from western region to the northeast region, the net value added transferred to the northeast has been declining. At the provincial level, Anhui, Hunan, and Sichuan provinces transitioned toward dual-benefit positions, gaining economic advantages while offloading ecological pressure, whereas Jilin remained in a loss–loss state, suffering both ecological and economic deficits. Distant trade contributes more significantly to ecological inequality than adjacent trade. Stratified analysis reveals that variations in transportation accessibility, fiscal priority, and mechanization jointly characterize the structural heterogeneity of the mismatch across provinces. The study also emphasizes that distant trade cross-regional governance requires attention in ecological compensation. The methodology and insights offer valuable guidance for addressing similar sustainability challenges in other countries experiencing rapid economic development and regional disparities.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108379"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146170885","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 : 2026-06-01Epub Date: 2026-02-11DOI: 10.1016/j.eiar.2026.108384
Yinghan Zhao , Zijun Wang , Zongsen Wang , Tingyi Xue , Yangyang Liu , Zhongming Wen , Ercha Hu , Haijing Shi , Zhenqian Wang , Zhaoqi Wang , Peidong Han
Soil moisture (SM) is a fundamental variable in terrestrial ecosystems, critically influencing hydrological cycles, ecological processes, and plant growth. Despite its importance, the complex interrelationships among vegetation, climate, and SM across different drought gradients are not yet fully understood. This study provides a systematic analysis of the spatiotemporal dynamics of surface (SMsurf) and root-zone soil moisture (SMroot) in China from 2001 to 2021 across different aridity gradient (Defined by the ratio of potential evaporation to precipitation). We employed an integrated analytical framework, combining Random Forest algorithms for driver importance assessment with Partial Least Squares Structural Equation Modeling (PLS-SEM) to elucidate the direct and indirect causal pathways. Our results reveal a significant nationwide increasing trend in both SMsurf and SMroot, with growth rates of 0.0013 and 0.0014 m3/m3/year, respectively. The most rapid increase occurred in semi-arid regions. Solar-Induced Chlorophyll Fluorescence (SIF) was identified as a significant positive driver of this growth. In contrast, vapor pressure deficit (VPD) was the primary climatic factor constraining SM at the national scale. A key finding is the stark contrast in dominant drivers across aridity gradients: temperature was the predominant factor controlling SM variations in arid and semi-arid regions, while VPD dominated in dry sub-humid and humid regions. The influence of potential evapotranspiration (Ep) shifted from positive in arid regions to negative in wetter zones. The PLS-SEM analysis further uncovered distinct mechanistic pathways: precipitation directly influenced SM in arid regions, whereas in semi-arid regions, wind speed and radiation mediated their effects indirectly through temperature. Overall, environmental and climatic factors primarily exerted their influence on SM by modulating vegetation greening, which served as a pivotal mediator. These findings elucidate the differential mechanisms governing vegetation-climate-SM interactions across aridity gradients. Our findings elucidate the complex and differential causal relationship and mechanism of the change in vegetation-climate-drought on soil moisture across different aridity gradients, providing the theoretical support for constructing sustainable vegetation restoration strategies for water resources and the effective utilization of soil moisture resources in arid and semi-arid regions in China.
{"title":"Quantifying the changes in soil moisture caused by vegetation greening and climate change across different drought gradient in China","authors":"Yinghan Zhao , Zijun Wang , Zongsen Wang , Tingyi Xue , Yangyang Liu , Zhongming Wen , Ercha Hu , Haijing Shi , Zhenqian Wang , Zhaoqi Wang , Peidong Han","doi":"10.1016/j.eiar.2026.108384","DOIUrl":"10.1016/j.eiar.2026.108384","url":null,"abstract":"<div><div>Soil moisture (SM) is a fundamental variable in terrestrial ecosystems, critically influencing hydrological cycles, ecological processes, and plant growth. Despite its importance, the complex interrelationships among vegetation, climate, and SM across different drought gradients are not yet fully understood. This study provides a systematic analysis of the spatiotemporal dynamics of surface (SMsurf) and root-zone soil moisture (SMroot) in China from 2001 to 2021 across different aridity gradient (Defined by the ratio of potential evaporation to precipitation). We employed an integrated analytical framework, combining Random Forest algorithms for driver importance assessment with Partial Least Squares Structural Equation Modeling (PLS-SEM) to elucidate the direct and indirect causal pathways. Our results reveal a significant nationwide increasing trend in both SMsurf and SMroot, with growth rates of 0.0013 and 0.0014 m<sup>3</sup>/m<sup>3</sup>/year, respectively. The most rapid increase occurred in semi-arid regions. Solar-Induced Chlorophyll Fluorescence (SIF) was identified as a significant positive driver of this growth. In contrast, vapor pressure deficit (VPD) was the primary climatic factor constraining SM at the national scale. A key finding is the stark contrast in dominant drivers across aridity gradients: temperature was the predominant factor controlling SM variations in arid and semi-arid regions, while VPD dominated in dry sub-humid and humid regions. The influence of potential evapotranspiration (Ep) shifted from positive in arid regions to negative in wetter zones. The PLS-SEM analysis further uncovered distinct mechanistic pathways: precipitation directly influenced SM in arid regions, whereas in semi-arid regions, wind speed and radiation mediated their effects indirectly through temperature. Overall, environmental and climatic factors primarily exerted their influence on SM by modulating vegetation greening, which served as a pivotal mediator. These findings elucidate the differential mechanisms governing vegetation-climate-SM interactions across aridity gradients. Our findings elucidate the complex and differential causal relationship and mechanism of the change in vegetation-climate-drought on soil moisture across different aridity gradients, providing the theoretical support for constructing sustainable vegetation restoration strategies for water resources and the effective utilization of soil moisture resources in arid and semi-arid regions in China.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108384"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146170892","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 : 2026-06-01Epub Date: 2026-01-31DOI: 10.1016/j.eiar.2026.108361
Yanhui Yu , Rui Li , Shicong Zhang , Chanyuan Li , Haitong Zhe Sun , Weiguang Cai
Residential building carbon emissions (RBCE) account for a significant share of China's total carbon emissions and are a key focus for achieving the country's dual carbon goals. While many studies have addressed RBCE at national or provincial levels, there is still a lack of systematic assessment at the city level, especially concerning its spatiotemporal patterns, peaking status, and driving mechanisms. This study develops a method to estimate and evaluate city-level RBCE and applies it to a dataset of 290 cities in China from 2005 to 2022. We assess RBCE peaking status across cities and explore the drivers behind different emission stages. Results show that RBCE in Chinese cities has continued to rise overall, with strong regional disparities influenced by population distribution, climate zones, and energy structure. As of 2022, only 13% of cities had peaked in RBCE, and nearly half of these were due to passive decline. Declines in energy intensity were the main contributor to emissions reductions in cities that actively peaked, while growth in building area and electrification contributed to further increases. Urban and rural areas show clear differences in their peaking patterns, suggesting the need for differentiated carbon control strategies. This study provides valuable data and policy insights to support city-level carbon peaking pathways in China's building sector.
{"title":"Who peaks, and why? City-level residential building carbon emission peaking patterns and driving mechanisms in China","authors":"Yanhui Yu , Rui Li , Shicong Zhang , Chanyuan Li , Haitong Zhe Sun , Weiguang Cai","doi":"10.1016/j.eiar.2026.108361","DOIUrl":"10.1016/j.eiar.2026.108361","url":null,"abstract":"<div><div>Residential building carbon emissions (RBCE) account for a significant share of China's total carbon emissions and are a key focus for achieving the country's dual carbon goals. While many studies have addressed RBCE at national or provincial levels, there is still a lack of systematic assessment at the city level, especially concerning its spatiotemporal patterns, peaking status, and driving mechanisms. This study develops a method to estimate and evaluate city-level RBCE and applies it to a dataset of 290 cities in China from 2005 to 2022. We assess RBCE peaking status across cities and explore the drivers behind different emission stages. Results show that RBCE in Chinese cities has continued to rise overall, with strong regional disparities influenced by population distribution, climate zones, and energy structure. As of 2022, only 13% of cities had peaked in RBCE, and nearly half of these were due to passive decline. Declines in energy intensity were the main contributor to emissions reductions in cities that actively peaked, while growth in building area and electrification contributed to further increases. Urban and rural areas show clear differences in their peaking patterns, suggesting the need for differentiated carbon control strategies. This study provides valuable data and policy insights to support city-level carbon peaking pathways in China's building sector.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108361"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146170829","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 : 2026-06-01Epub Date: 2026-01-19DOI: 10.1016/j.eiar.2026.108345
Xinjun He , Yiping Fang , Xueyuan Huang , Liang Emlyn Yang , Yun Xu , Jia Liu , Yang Guo , Anqi Zhu
In mountainous regions worldwide, more than 1.1 billion people face the threat of flash floods, a risk exacerbated by climate change and intensified human activity, highlighting the urgent need for effective flash flood risk governance systems. This study examines flash flood risk governance in rural mountainous China by linking an institutional analysis of a state-led, multi-level governance system with a household-level assessment of governance effectiveness. Drawing on survey data from 811 households in flash flood-prone villages, we construct a latent index of flood safety cognition, grounded in the psychometric paradigm and institutional trust theory, and estimate a structural equation model to identify how mitigation measures at government, community and household scales jointly influence this outcome. Government-led measures have the strongest positive effect on flood safety cognition, while community and household actions also contribute but to a lesser extent. Structural interventions such as dikes, river channel restoration, infrastructure upgrades and resettlement, together with timely emergency relief, significantly enhance perceived safety.Community institutions such as village regulations and traditional knowledge reinforce these effects. By contrast, house foundation elevation is negatively associated with safety cognition, reflecting reverse causality and selection among the most exposed and constrained households rather than failure of the measure itself. Robustness checks and sensitivity analyses confirm that these patterns are stable. Beyond the model results, the analysis offers a dialectical perspective on China's flash flood governance system, highlighting both the strengths of strong leadership, responsibility arrangements and fiscal transfers and the tensions created by upgraded responses, early warning precision gaps and fragmented multi-hazard governance. The study suggests that lessons from this case are best understood as transferable principles, including multi-level accountability with matched authority and resources, integration of flood risk governance into broader development agendas, explicit attention to compound risks and the combination of structural measures with community institutions, nature-based solutions and regulated public-private partnerships.
{"title":"Flash flood risk governance system in China and its governance effectiveness","authors":"Xinjun He , Yiping Fang , Xueyuan Huang , Liang Emlyn Yang , Yun Xu , Jia Liu , Yang Guo , Anqi Zhu","doi":"10.1016/j.eiar.2026.108345","DOIUrl":"10.1016/j.eiar.2026.108345","url":null,"abstract":"<div><div>In mountainous regions worldwide, more than 1.1 billion people face the threat of flash floods, a risk exacerbated by climate change and intensified human activity, highlighting the urgent need for effective flash flood risk governance systems. This study examines flash flood risk governance in rural mountainous China by linking an institutional analysis of a state-led, multi-level governance system with a household-level assessment of governance effectiveness. Drawing on survey data from 811 households in flash flood-prone villages, we construct a latent index of flood safety cognition, grounded in the psychometric paradigm and institutional trust theory, and estimate a structural equation model to identify how mitigation measures at government, community and household scales jointly influence this outcome. Government-led measures have the strongest positive effect on flood safety cognition, while community and household actions also contribute but to a lesser extent. Structural interventions such as dikes, river channel restoration, infrastructure upgrades and resettlement, together with timely emergency relief, significantly enhance perceived safety.Community institutions such as village regulations and traditional knowledge reinforce these effects. By contrast, house foundation elevation is negatively associated with safety cognition, reflecting reverse causality and selection among the most exposed and constrained households rather than failure of the measure itself. Robustness checks and sensitivity analyses confirm that these patterns are stable. Beyond the model results, the analysis offers a dialectical perspective on China's flash flood governance system, highlighting both the strengths of strong leadership, responsibility arrangements and fiscal transfers and the tensions created by upgraded responses, early warning precision gaps and fragmented multi-hazard governance. The study suggests that lessons from this case are best understood as transferable principles, including multi-level accountability with matched authority and resources, integration of flood risk governance into broader development agendas, explicit attention to compound risks and the combination of structural measures with community institutions, nature-based solutions and regulated public-private partnerships.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108345"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146025605","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 : 2026-06-01Epub Date: 2026-03-02DOI: 10.1016/j.eiar.2026.108398
Shahin Jalili , Georgios Leontidis , Malcolm Stone , Richard Neilson
Decommissioning of offshore energy infrastructure in the North Sea presents a significant environmental challenge for operators, the supply chain, government agencies, and society. Considering the UK's 2050 net zero target, it is essential to understand the offshore oil and gas (O&G) decommissioning sector's contribution to overall emissions. Such insight is crucial for evaluating decommissioning projects and informing policy development aimed at reducing emissions and achieving net zero goals. This study proposes a bottom-up emissions and energy assessment (EEA) approach for decommissioning offshore O&G platform topside and jacket structures. The approach quantifies the greenhouse gas (GHG) emissions and energy demand associated with offshore and onshore activities during the decommissioning phase. It leverages detailed, site-specific operational data to improve the precision and reliability of these assessments and is underpinned by the latest available data from the North Sea O&G decommissioning industry. The approach is validated through application to decommissioning of platform topsides and jackets in the Brent and Tern fields. Numerical comparisons reveal acceptable differences between the energy demand and CO2 emission estimates from this study and those reported in North Sea industry reports. The study also presents insights into the reliable EEA of decommissioning projects.
{"title":"Bottom-up emissions and energy assessment for decommissioning offshore platform structures in the North Sea: Brent and Tern case studies","authors":"Shahin Jalili , Georgios Leontidis , Malcolm Stone , Richard Neilson","doi":"10.1016/j.eiar.2026.108398","DOIUrl":"10.1016/j.eiar.2026.108398","url":null,"abstract":"<div><div>Decommissioning of offshore energy infrastructure in the North Sea presents a significant environmental challenge for operators, the supply chain, government agencies, and society. Considering the UK's 2050 net zero target, it is essential to understand the offshore oil and gas (O&G) decommissioning sector's contribution to overall emissions. Such insight is crucial for evaluating decommissioning projects and informing policy development aimed at reducing emissions and achieving net zero goals. This study proposes a bottom-up emissions and energy assessment (EEA) approach for decommissioning offshore O&G platform topside and jacket structures. The approach quantifies the greenhouse gas (GHG) emissions and energy demand associated with offshore and onshore activities during the decommissioning phase. It leverages detailed, site-specific operational data to improve the precision and reliability of these assessments and is underpinned by the latest available data from the North Sea O&G decommissioning industry. The approach is validated through application to decommissioning of platform topsides and jackets in the Brent and Tern fields. Numerical comparisons reveal acceptable differences between the energy demand and CO<sub>2</sub> emission estimates from this study and those reported in North Sea industry reports. The study also presents insights into the reliable EEA of decommissioning projects.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108398"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147384886","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 : 2026-06-01Epub 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":"2026-06-01","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 : 2026-06-01Epub 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":"2026-06-01","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 : 2026-06-01Epub Date: 2026-02-12DOI: 10.1016/j.eiar.2026.108388
Yifei Jia , Zhaofang Chen , Xinghao Lu , Yuncai Wang
Rapid urbanization in China has contributed to intensified ecological stress on urban green spaces (UGS). However, conventional static or single-dimensional approaches struggle to capture the compounding, dynamic nature of this stress, specifically overlooking the crucial roles of marginal sensitivity and multi-factor interactive mechanisms. To address this gap, this study proposes a novel Quantity-Intensity framework that dynamically quantifies stress by integrating calculus tools: Total Stress Quantity (TSQ) for cumulative loss and Stress Intensity (SIc) for marginal sensitivity. We applied this framework, coupled with the XGBoost-SHAP model, to multi-source remote sensing data across 358 Chinese cities (2000−2020). The analysis reveals a nationwide amplification of stress—97% of cities experienced increased TSQ (averaging +26%) and 99% exhibited heightened SIc (averaging +49%). Spatially, stress effects were strongly mediated by climate, with the most pronounced impacts in temperate southern regions. Crucially, the model identified key thresholds via marginal effects, such as stress alleviation when heat island intensity (ΔLST) > 7 °Cin arid regions. Notably, indicators interaction effects frequently surpassed individual contributions, with the synergies between climate factors and between economic and morphological indicators being particularly influential. This study provides a paradigm shift from static assessment to dynamic mechanistic analysis, offering a robust methodology for identifying stress thresholds to support climate-adaptive urban governance and sustainable UGS management.
{"title":"Marginal and interactive effects of rapid urbanization stress on green spaces in China","authors":"Yifei Jia , Zhaofang Chen , Xinghao Lu , Yuncai Wang","doi":"10.1016/j.eiar.2026.108388","DOIUrl":"10.1016/j.eiar.2026.108388","url":null,"abstract":"<div><div>Rapid urbanization in China has contributed to intensified ecological stress on urban green spaces (UGS). However, conventional static or single-dimensional approaches struggle to capture the compounding, dynamic nature of this stress, specifically overlooking the crucial roles of marginal sensitivity and multi-factor interactive mechanisms. To address this gap, this study proposes a novel Quantity-Intensity framework that dynamically quantifies stress by integrating calculus tools: Total Stress Quantity (TSQ) for cumulative loss and Stress Intensity (SIc) for marginal sensitivity. We applied this framework, coupled with the XGBoost-SHAP model, to multi-source remote sensing data across 358 Chinese cities (2000−2020). The analysis reveals a nationwide amplification of stress—97% of cities experienced increased TSQ (averaging +26%) and 99% exhibited heightened SIc (averaging +49%). Spatially, stress effects were strongly mediated by climate, with the most pronounced impacts in temperate southern regions. Crucially, the model identified key thresholds via marginal effects, such as stress alleviation when heat island intensity (ΔLST) > 7 °Cin arid regions. Notably, indicators interaction effects frequently surpassed individual contributions, with the synergies between climate factors and between economic and morphological indicators being particularly influential. This study provides a paradigm shift from static assessment to dynamic mechanistic analysis, offering a robust methodology for identifying stress thresholds to support climate-adaptive urban governance and sustainable UGS management.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"119 ","pages":"Article 108388"},"PeriodicalIF":11.2,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146170534","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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