Pub Date : 2025-02-21DOI: 10.1016/j.eiar.2025.107866
Siqi Yu , Xinyu Yang , Zhongyao Cai , Liyang Guo , Ping Jiang
The government plays a significant role in environmental management in China. By using data from 274 Chinese prefecture-level cities spanning 2008 to 2020, this study innovatively explores the influence of government environmental attention (GEA) on cutting PM2.5 and CO2 emissions. Unlike previous works, this study focuses on three aspects. First, GEA is quantified, and its significant impact on driving emission reductions is analyzed using the spatial Durbin model. This method captures spatial spillover effects and inter-regional dependencies, offering a more precise and comprehensive understanding of strategic government preferences for reducing air pollutant emissions. Second, this study uncovers spatial heterogeneity in the effectiveness of GEA, underscoring the necessity for region-specific policies and the accelerated construction of national carbon emission trading scheme. Additionally, this study reveals the moderating effect of local government officials' personal characteristics on the linkage between GEA and emission reduction outcomes. To maximize the co-benefits of controlling both air pollution and carbon emissions effectively, policies are recommended based on outcomes of study, such as the measure of collaborative control should be promoted, the heterogeneity of regional development should be addressed in future policy design and implementation.
{"title":"Analysis of the government environmental attention on tackling air pollution and greenhouse gas emissions through a spatial econometric approach","authors":"Siqi Yu , Xinyu Yang , Zhongyao Cai , Liyang Guo , Ping Jiang","doi":"10.1016/j.eiar.2025.107866","DOIUrl":"10.1016/j.eiar.2025.107866","url":null,"abstract":"<div><div>The government plays a significant role in environmental management in China. By using data from 274 Chinese prefecture-level cities spanning 2008 to 2020, this study innovatively explores the influence of government environmental attention (GEA) on cutting PM<sub>2.5</sub> and CO<sub>2</sub> emissions. Unlike previous works, this study focuses on three aspects. First, GEA is quantified, and its significant impact on driving emission reductions is analyzed using the spatial Durbin model. This method captures spatial spillover effects and inter-regional dependencies, offering a more precise and comprehensive understanding of strategic government preferences for reducing air pollutant emissions. Second, this study uncovers spatial heterogeneity in the effectiveness of GEA, underscoring the necessity for region-specific policies and the accelerated construction of national carbon emission trading scheme. Additionally, this study reveals the moderating effect of local government officials' personal characteristics on the linkage between GEA and emission reduction outcomes. To maximize the co-benefits of controlling both air pollution and carbon emissions effectively, policies are recommended based on outcomes of study, such as the measure of collaborative control should be promoted, the heterogeneity of regional development should be addressed in future policy design and implementation.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"113 ","pages":"Article 107866"},"PeriodicalIF":9.8,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454259","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 : 2025-02-20DOI: 10.1016/j.eiar.2025.107868
Yanan Ren , Mei Wang , Jinping Tian , Lyujun Chen
The EU's Carbon Border Adjustment Mechanism (CBAM) is the first global carbon tariff policy to be implemented. Current impact assessments of CBAM face non-compliance issues, namely, carbon tariff measurements do not strictly follow CBAM regulations, which may shake the foundation for credible impact assessment. However, the effects of non-compliant measurements on national carbon tariff estimates remain unquantified. In line with CBAM's provisions, we identify four key carbon tariff determinants: commodity scope, embedded emission scope, greenhouse gas (GHG) portfolio, and the EU's carbon price. We also review prevalent non-compliant measurement practices in the existing literature. By constructing 144 scenarios that combine the commonly employed settings for these four factors, we conducted a retrospective case analysis of China—one of the EU's pivotal trading partners—both at the sectoral and overall level. The compliant calculations reveal a carbon tariff of 614.4 million euros levied on China's exports to the EU in 2022, accounting for 3.5 % of the corresponding trade volume. Scenario analysis reveals that non-compliant measurements could misestimate China's overall carbon tariff costs and ad valorem carbon tariff rates, with deviations ranging from a 74.4 % underestimation to a 382.7 % overestimation, and from a 63.5 % underestimation to a 392.2 % overestimation, respectively. These variations highlight the potential future impact after policy alterations. While sectoral variations do exist, we find that the most significant contributors to misestimations are commodity scope, emission scope, and carbon price, with the GHG portfolio having a relatively minor effect. This research underscores the necessity of compliant carbon tariff methodology and outlines prioritization for enhanced measurement precision and implications for evidence-based policy design.
{"title":"Non-compliant measurement leads to significant misestimation in national carbon tariff: Methodology and a retrospective case study of China","authors":"Yanan Ren , Mei Wang , Jinping Tian , Lyujun Chen","doi":"10.1016/j.eiar.2025.107868","DOIUrl":"10.1016/j.eiar.2025.107868","url":null,"abstract":"<div><div>The EU's Carbon Border Adjustment Mechanism (CBAM) is the first global carbon tariff policy to be implemented. Current impact assessments of CBAM face non-compliance issues, namely, carbon tariff measurements do not strictly follow CBAM regulations, which may shake the foundation for credible impact assessment. However, the effects of non-compliant measurements on national carbon tariff estimates remain unquantified. In line with CBAM's provisions, we identify four key carbon tariff determinants: commodity scope, embedded emission scope, greenhouse gas (GHG) portfolio, and the EU's carbon price. We also review prevalent non-compliant measurement practices in the existing literature. By constructing 144 scenarios that combine the commonly employed settings for these four factors, we conducted a retrospective case analysis of China—one of the EU's pivotal trading partners—both at the sectoral and overall level. The compliant calculations reveal a carbon tariff of 614.4 million euros levied on China's exports to the EU in 2022, accounting for 3.5 % of the corresponding trade volume. Scenario analysis reveals that non-compliant measurements could misestimate China's overall carbon tariff costs and ad valorem carbon tariff rates, with deviations ranging from a 74.4 % underestimation to a 382.7 % overestimation, and from a 63.5 % underestimation to a 392.2 % overestimation, respectively. These variations highlight the potential future impact after policy alterations. While sectoral variations do exist, we find that the most significant contributors to misestimations are commodity scope, emission scope, and carbon price, with the GHG portfolio having a relatively minor effect. This research underscores the necessity of compliant carbon tariff methodology and outlines prioritization for enhanced measurement precision and implications for evidence-based policy design.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"113 ","pages":"Article 107868"},"PeriodicalIF":9.8,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143453559","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 : 2025-02-19DOI: 10.1016/j.eiar.2024.107797
Szilárd Erhart , Bálint Menyhért , Kornél Erhart , Andrea Hagyó
While every protected and conserved area can be exposed to pollution, some may suffer more. We develop methods to analyze their freshwater biodiversity risks from industrial sites around Europe. This study is novel as it is the first attempt at linking the European Pollutant Release and Transfer Register to the geographic data of Natura 2000 sites. Furthermore, we applied the improved characterization factors in the Environmental Footprint database published by the European Commission Joint Research Centre. The proximity of biggest industrial facilities to Natura 2000 sites, which is the largest network of protected areas in the world, can affect freshwater biodiversity risks in Europe and globally. We quantify hazards in the recent past and at the Natura 2000 site level. We find that European protected natural areas are exposed to more eutrophication and biodiversity risks mostly from the Sewerage and water treatment sector in the most industrialised European regions especially in the Benelux states, Southern Germany, in Northern Italy and South-West France. 370 of the E-PRTR facilities were located less than 500 m away from the border of Natura 2000 sites with protected freshwater species, 126 of which less than 100 m away and 51 within Natura 2000 sites. River basin districts of the Danube, Ebro and the Elbe were estimated to be most affected by pollutant releases with ecotoxicity and eutrophication impact potential in 2019. Approximately 3 % of industrial facilities reporting to the E-PRTR pollutant releases into water are closer to foreign Natura 2000 sites with freshwater fish or amphibian species than to the closest Natura 2000 site in the country where they are located. All this calls for improved monitoring and respective prevention measures in some key regions of Europe along with coordinated international biodiversity loss mitigation efforts.
{"title":"Freshwater biodiversity risk exposure of Natura 2000 sites to industrial pollution","authors":"Szilárd Erhart , Bálint Menyhért , Kornél Erhart , Andrea Hagyó","doi":"10.1016/j.eiar.2024.107797","DOIUrl":"10.1016/j.eiar.2024.107797","url":null,"abstract":"<div><div>While every protected and conserved area can be exposed to pollution, some may suffer more. We develop methods to analyze their freshwater biodiversity risks from industrial sites around Europe. This study is novel as it is the first attempt at linking the European Pollutant Release and Transfer Register to the geographic data of Natura 2000 sites. Furthermore, we applied the improved characterization factors in the Environmental Footprint database published by the European Commission Joint Research Centre. The proximity of biggest industrial facilities to Natura 2000 sites, which is the largest network of protected areas in the world, can affect freshwater biodiversity risks in Europe and globally. We quantify hazards in the recent past and at the Natura 2000 site level. We find that European protected natural areas are exposed to more eutrophication and biodiversity risks mostly from the Sewerage and water treatment sector in the most industrialised European regions especially in the Benelux states, Southern Germany, in Northern Italy and South-West France. 370 of the <em>E</em>-PRTR facilities were located less than 500 m away from the border of Natura 2000 sites with protected freshwater species, 126 of which less than 100 m away and 51 within Natura 2000 sites. River basin districts of the Danube, Ebro and the Elbe were estimated to be most affected by pollutant releases with ecotoxicity and eutrophication impact potential in 2019. Approximately 3 % of industrial facilities reporting to the <em>E</em>-PRTR pollutant releases into water are closer to foreign Natura 2000 sites with freshwater fish or amphibian species than to the closest Natura 2000 site in the country where they are located. All this calls for improved monitoring and respective prevention measures in some key regions of Europe along with coordinated international biodiversity loss mitigation efforts.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"113 ","pages":"Article 107797"},"PeriodicalIF":9.8,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437935","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In the context of urban renewal, the renovation of Chinese traditional building facades is very important for realizing the renewal of architectural functions and enhancing the urban style. It is of great theoretical and practical significance to assess the visual quality of commercial renovation of Chinese traditional building facades and explore its relationship with the visual features of facades scientifically. Traditional methods based on manual questionnaire surveys and data analysis suffer certain limitations in terms of cost, time, and measurement scale; meanwhile, the research results obtained are prone to be easily influenced by the respondent's subjective preference. In this study, the CRTBFD (Commercial Renovation of Traditional Building Facades Dataset) was firstly constructed, which contained 560 images of commercial renovation of traditional building facades. On account of this dataset, a classification model based on deep learning, Swin-HV (Swin transformer for Historical and cultural atmosphere and Visual preference), was developed. The model can assess and predict the visual quality of commercial renovation of traditional building facades from two aspects: historical and cultural atmosphere and visual preference. In addition, an object detection model called TBFE-YOLO (YOLO for Traditional Building Facade Elements) was proposed, capable of identifying nine traditional building facade elements from reconstructed images. Finally, Spearman's rank correlation coefficient was used to analyze the correlation between visual quality assessment and these nine facade elements, while Grad-CAM++ was employed to further visualize the model's decision-making process. The results show that the Swin-HV model achieves high precision in predicting historical and cultural atmosphere and visual preference assessment. Moreover, it is found that the visual quality assessment of commercial renovation of traditional building facades is closely related to the elements of traditional building facades. The method proposed in this study serves as a reference for urban planning, building conservation, and reuse, while also deepening the understanding of commercial renovation of traditional building facades.
{"title":"A deep learning-based study on visual quality assessment of commercial renovation of Chinese traditional building facades","authors":"Jingjing Zhao , Chenping Han , Yijing Wu , Changsheng Xu , Xing Huang , Xiwu Qi , Yangming Qi , Liang Gao","doi":"10.1016/j.eiar.2025.107862","DOIUrl":"10.1016/j.eiar.2025.107862","url":null,"abstract":"<div><div>In the context of urban renewal, the renovation of Chinese traditional building facades is very important for realizing the renewal of architectural functions and enhancing the urban style. It is of great theoretical and practical significance to assess the visual quality of commercial renovation of Chinese traditional building facades and explore its relationship with the visual features of facades scientifically. Traditional methods based on manual questionnaire surveys and data analysis suffer certain limitations in terms of cost, time, and measurement scale; meanwhile, the research results obtained are prone to be easily influenced by the respondent's subjective preference. In this study, the CRTBFD (Commercial Renovation of Traditional Building Facades Dataset) was firstly constructed, which contained 560 images of commercial renovation of traditional building facades. On account of this dataset, a classification model based on deep learning, Swin-HV (Swin transformer for Historical and cultural atmosphere and Visual preference), was developed. The model can assess and predict the visual quality of commercial renovation of traditional building facades from two aspects: historical and cultural atmosphere and visual preference. In addition, an object detection model called TBFE-YOLO (YOLO for Traditional Building Facade Elements) was proposed, capable of identifying nine traditional building facade elements from reconstructed images. Finally, Spearman's rank correlation coefficient was used to analyze the correlation between visual quality assessment and these nine facade elements, while Grad-CAM++ was employed to further visualize the model's decision-making process. The results show that the Swin-HV model achieves high precision in predicting historical and cultural atmosphere and visual preference assessment. Moreover, it is found that the visual quality assessment of commercial renovation of traditional building facades is closely related to the elements of traditional building facades. The method proposed in this study serves as a reference for urban planning, building conservation, and reuse, while also deepening the understanding of commercial renovation of traditional building facades.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"113 ","pages":"Article 107862"},"PeriodicalIF":9.8,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437989","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 : 2025-02-17DOI: 10.1016/j.eiar.2025.107865
Xiuyun Yang , Meng Chen , Qiuping Chen
This study delves into the complexities of development projects and explores the concept of social licence to operate (SLO) as a means to secure community support and mitigate conflicts in China, where the conditions for obtaining SLO are poorly understood. By applying the SLO pyramid model and measurement scales and employing the fsQCA method, we focus on six key conditions: economic fairness, procedural fairness, government conflict resolution capacity, the project implementer's trustworthiness, the reactivity of affected residents, inherent project risks, and the causal pathways influencing SLO levels. Our findings suggest that two causal pathways—risk mitigation and public interest projects with fair implementation—are crucial for achieving high-level SLO. Additionally, the regional context and stakeholder interactions are pivotal for SLO success, with governance dysfunction and community–developer friction being pathways to low SLO levels. We exemplify each pathway with detailed, context-specific case studies to ensure explanatory power. This study significantly contributes to the understanding of the dynamic interactions among various factors and offers practical recommendations for policymakers and stakeholders to enhance SLO in development projects.
{"title":"Securing a social licence for development projects: A fuzzy-set qualitative comparative analysis of land expropriation cases in China","authors":"Xiuyun Yang , Meng Chen , Qiuping Chen","doi":"10.1016/j.eiar.2025.107865","DOIUrl":"10.1016/j.eiar.2025.107865","url":null,"abstract":"<div><div>This study delves into the complexities of development projects and explores the concept of social licence to operate (SLO) as a means to secure community support and mitigate conflicts in China, where the conditions for obtaining SLO are poorly understood. By applying the SLO pyramid model and measurement scales and employing the fsQCA method, we focus on six key conditions: economic fairness, procedural fairness, government conflict resolution capacity, the project implementer's trustworthiness, the reactivity of affected residents, inherent project risks, and the causal pathways influencing SLO levels. Our findings suggest that two causal pathways—risk mitigation and public interest projects with fair implementation—are crucial for achieving high-level SLO. Additionally, the regional context and stakeholder interactions are pivotal for SLO success, with governance dysfunction and community–developer friction being pathways to low SLO levels. We exemplify each pathway with detailed, context-specific case studies to ensure explanatory power. This study significantly contributes to the understanding of the dynamic interactions among various factors and offers practical recommendations for policymakers and stakeholders to enhance SLO in development projects.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"113 ","pages":"Article 107865"},"PeriodicalIF":9.8,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429627","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 : 2025-02-16DOI: 10.1016/j.eiar.2025.107864
Hongqin Fan , Zhenhua Huang , Yixin Xie
Retrofitting construction equipment is widely recognized as an effective strategy to reduce diesel emissions. However, limited research exists on comprehensive models for assessing the cost-effectiveness of retrofitting—a critical metric in developing successful retrofitting programs. This study addresses this gap by developing a novel model that integrates life-cycle analysis and public health effects. The model consists of three key components: calculating the life-cycle average annualized cost (LCAAC) associated with employing retrofitting technologies, quantifying the corresponding reduction in public health effects emissions equivalent (PHEEE), and analyzing cost-effectiveness. The model's applicability is demonstrated through a case study on 6428 pieces of construction equipment in Hong Kong, grouped into 71 categories for analysis. The study finds that retrofitting achieves an average of 4873.34 kg PHEEE reduced per million HK$ spent. Among the categories, excavators with rated power between 300 and 600 hp. and compliant with US Tier 1 emission standards (labeled as E-HP7-T1) are identified as the most cost-effective to retrofit. Notably, the study highlights that fuel penalties associated with retrofitting—often overlooked in traditional assessment—constitute 53.86 % of total costs, significantly influencing cost-effectiveness outcomes. From a life-cycle and public health effects perspective, this model enables a more accurate cost-effectiveness assessment. It equips policymakers with tools to prioritize retrofitting investments that maximize emissions reductions and health benefits. Additionally, it offers valuable insights to construction fleet managers for improving retrofitting efficiency, particularly through strategies to mitigate fuel penalties.
{"title":"Cost-effectiveness assessment of retrofitting construction equipment for reducing diesel emissions—A life cycle and public health effects perspective","authors":"Hongqin Fan , Zhenhua Huang , Yixin Xie","doi":"10.1016/j.eiar.2025.107864","DOIUrl":"10.1016/j.eiar.2025.107864","url":null,"abstract":"<div><div>Retrofitting construction equipment is widely recognized as an effective strategy to reduce diesel emissions. However, limited research exists on comprehensive models for assessing the cost-effectiveness of retrofitting—a critical metric in developing successful retrofitting programs. This study addresses this gap by developing a novel model that integrates life-cycle analysis and public health effects. The model consists of three key components: calculating the life-cycle average annualized cost (LCAAC) associated with employing retrofitting technologies, quantifying the corresponding reduction in public health effects emissions equivalent (PHEEE), and analyzing cost-effectiveness. The model's applicability is demonstrated through a case study on 6428 pieces of construction equipment in Hong Kong, grouped into 71 categories for analysis. The study finds that retrofitting achieves an average of 4873.34 kg PHEEE reduced per million HK$ spent. Among the categories, excavators with rated power between 300 and 600 hp. and compliant with US Tier 1 emission standards (labeled as <em>E</em>-HP7-T1) are identified as the most cost-effective to retrofit. Notably, the study highlights that fuel penalties associated with retrofitting—often overlooked in traditional assessment—constitute 53.86 % of total costs, significantly influencing cost-effectiveness outcomes. From a life-cycle and public health effects perspective, this model enables a more accurate cost-effectiveness assessment. It equips policymakers with tools to prioritize retrofitting investments that maximize emissions reductions and health benefits. Additionally, it offers valuable insights to construction fleet managers for improving retrofitting efficiency, particularly through strategies to mitigate fuel penalties.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"113 ","pages":"Article 107864"},"PeriodicalIF":9.8,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143420064","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 : 2025-02-13DOI: 10.1016/j.eiar.2025.107863
Yupeng Fan , Chao Zhang , Chuanglin Fang
Urban development is inherently connected to resource flows across city boundaries, which are associated with environmental impacts. To understand these dynamics, urban metabolism (UM) research conceptualizes cities as living systems and examines their complex interactions with surrounding environments.UM draws on diverse perspectives and methodologies, exploring not only material and energy flows but also broader systemic relationships within and beyond urban boundaries. However, much of the existing research focuses on intra-city metabolic processes, creating a critical gap in understanding how external metabolic activities influence internal urban systems. This study addresses this gap by proposing an innovative cross-scale urban metabolism model to investigate the interactions between internal and external metabolic systems, using Shanghai and the Yangtze River Delta (YRD) as a case study. By combining material flow analysis and ecological network analysis, the study uncovers the intricate structure of resource exchange and their effects on urban sustainability. The YRD region processes 3517 million tons of material flow distributed across 274 pathways, with Shanghai accounting for 7.3 % of the total metabolic flow. External metabolic activities substantially enhance the symbiosis, coordination, and stability of Shanghai's metabolic system. This study underscores the necessity of cross-scale urban metabolism research for understanding the broader urban-environment interactions critical to sustainability. By elucidating the role of external systems in optimizing urban metabolic processes, it offers valuable insights for guiding urban planning, resource management, and environmental policymaking, contributing to the sustainable development of cities like Shanghai.
{"title":"Informing urban sustainability through cross-scale urban metabolism: Insights from Shanghai and the Yangtze River Delta","authors":"Yupeng Fan , Chao Zhang , Chuanglin Fang","doi":"10.1016/j.eiar.2025.107863","DOIUrl":"10.1016/j.eiar.2025.107863","url":null,"abstract":"<div><div>Urban development is inherently connected to resource flows across city boundaries, which are associated with environmental impacts. To understand these dynamics, urban metabolism (UM) research conceptualizes cities as living systems and examines their complex interactions with surrounding environments.UM draws on diverse perspectives and methodologies, exploring not only material and energy flows but also broader systemic relationships within and beyond urban boundaries. However, much of the existing research focuses on intra-city metabolic processes, creating a critical gap in understanding how external metabolic activities influence internal urban systems. This study addresses this gap by proposing an innovative cross-scale urban metabolism model to investigate the interactions between internal and external metabolic systems, using Shanghai and the Yangtze River Delta (YRD) as a case study. By combining material flow analysis and ecological network analysis, the study uncovers the intricate structure of resource exchange and their effects on urban sustainability. The YRD region processes 3517 million tons of material flow distributed across 274 pathways, with Shanghai accounting for 7.3 % of the total metabolic flow. External metabolic activities substantially enhance the symbiosis, coordination, and stability of Shanghai's metabolic system. This study underscores the necessity of cross-scale urban metabolism research for understanding the broader urban-environment interactions critical to sustainability. By elucidating the role of external systems in optimizing urban metabolic processes, it offers valuable insights for guiding urban planning, resource management, and environmental policymaking, contributing to the sustainable development of cities like Shanghai.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"112 ","pages":"Article 107863"},"PeriodicalIF":9.8,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403674","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 : 2025-02-13DOI: 10.1016/j.eiar.2025.107859
Chong Xu , Yashu Qin , Jianda Li , Jiandong Chen
As the second largest greenhouse emission, the spatiotemporal decoupling CH4 emission from economic growth and future trends received limited attentions, resulting in reduced policy effectiveness towards climate change mitigation. To fill the gaps, the study presented an in-depth investigation on the spatiotemporal decoupling CH4 emission and economic growth nexus and corresponding drivers based on the developed spatiotemporal decoupling models in a case of 289 Chinese cities classified by economic structure and population size over 2005–2022. Further, several advanced deep learning models were employed for projecting city-level CH4 emissions. The results suggested that, first, CH4 emission intensity and GDP per capita were the largest drivers contributing to both temporal changes and spatial differences in CH4 emission. Second, the spatiotemporal decoupling states and corresponding drivers between CH4 emission and GDP exhibited a certain extent of heterogeneity across different types of cities. For instance, in large industrial cities, CH4 emissions were more closely linked to energy consumption patterns, while in service-oriented cities, resources support may play a more prominent role. Third, multiple forecasting models suggest overall increasing trends for city-level CH4 emission by 2030 across the country. The study highlighted the importance of reducing CH4 emission from socioeconomic perspectives while being cautious about multi-model-based policy formulations towards carbon neutrality for countries like China.
{"title":"Spatiotemporal decoupling CH4 emission from economic growth and future trend in categorized Chinese cities","authors":"Chong Xu , Yashu Qin , Jianda Li , Jiandong Chen","doi":"10.1016/j.eiar.2025.107859","DOIUrl":"10.1016/j.eiar.2025.107859","url":null,"abstract":"<div><div>As the second largest greenhouse emission, the spatiotemporal decoupling CH4 emission from economic growth and future trends received limited attentions, resulting in reduced policy effectiveness towards climate change mitigation. To fill the gaps, the study presented an in-depth investigation on the spatiotemporal decoupling CH4 emission and economic growth nexus and corresponding drivers based on the developed spatiotemporal decoupling models in a case of 289 Chinese cities classified by economic structure and population size over 2005–2022. Further, several advanced deep learning models were employed for projecting city-level CH4 emissions. The results suggested that, first, CH4 emission intensity and GDP per capita were the largest drivers contributing to both temporal changes and spatial differences in CH4 emission. Second, the spatiotemporal decoupling states and corresponding drivers between CH4 emission and GDP exhibited a certain extent of heterogeneity across different types of cities. For instance, in large industrial cities, CH4 emissions were more closely linked to energy consumption patterns, while in service-oriented cities, resources support may play a more prominent role. Third, multiple forecasting models suggest overall increasing trends for city-level CH4 emission by 2030 across the country. The study highlighted the importance of reducing CH4 emission from socioeconomic perspectives while being cautious about multi-model-based policy formulations towards carbon neutrality for countries like China.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"112 ","pages":"Article 107859"},"PeriodicalIF":9.8,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395063","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 : 2025-02-12DOI: 10.1016/j.eiar.2025.107860
Ana Fernández-Ríos, Jara Laso, Rubén Aldaco, María Margallo
Eating habits are continuously evolving, shaped by cultural convictions, socioeconomic factors, and new market trends. This study examines the rise in ‘superfoods' – ‘exotic’ natural foods with scientifically proven superior nutritional profiles – and their environmental interactions when used to fill nutritional gaps within common diets. Focusing on three well-established patterns - the Mediterranean (MD), vegan (VD), and Healthy Eating Plate (HEP) diets – the nutritional quality is measured using the Spanish Nutrient Rich Diet 9.2 (sNRD9.2) model, and environmental impacts are assessed through life cycle assessment (LCA) on a weekly per capita basis. Results show that ‘superfoods' boost nutritional quality by 3.5 %, 4.7 %, and 5.6 % for MD, VD, and HEP diets, respectively, yet increase environmental burdens in five to six of seven categories. However, a combined analysis of nutritional and environmental outcomes reveals contrasting effects: when nutritional improvements are factored in, environmental indicators show reductions of up to 28 % for water scarcity, 8.3 % for acidification, and 5.3 % for global warming. While these results suggest some benefits, heightened impacts in other areas call for further optimization of production systems. Challenges also persist in integrating unfamiliar foods into diets, underscoring the need for a balanced approach to sustainability.
{"title":"Environmental and nutritional performance of ‘superfood’-enriched diets: A comparative analysis of three dietary recommendations","authors":"Ana Fernández-Ríos, Jara Laso, Rubén Aldaco, María Margallo","doi":"10.1016/j.eiar.2025.107860","DOIUrl":"10.1016/j.eiar.2025.107860","url":null,"abstract":"<div><div>Eating habits are continuously evolving, shaped by cultural convictions, socioeconomic factors, and new market trends. This study examines the rise in ‘superfoods' – ‘exotic’ natural foods with scientifically proven superior nutritional profiles – and their environmental interactions when used to fill nutritional gaps within common diets. Focusing on three well-established patterns - the Mediterranean (MD), vegan (VD), and Healthy Eating Plate (HEP) diets – the nutritional quality is measured using the Spanish Nutrient Rich Diet 9.2 (sNRD9.2) model, and environmental impacts are assessed through life cycle assessment (LCA) on a weekly per capita basis. Results show that ‘superfoods' boost nutritional quality by 3.5 %, 4.7 %, and 5.6 % for MD, VD, and HEP diets, respectively, yet increase environmental burdens in five to six of seven categories. However, a combined analysis of nutritional and environmental outcomes reveals contrasting effects: when nutritional improvements are factored in, environmental indicators show reductions of up to 28 % for water scarcity, 8.3 % for acidification, and 5.3 % for global warming. While these results suggest some benefits, heightened impacts in other areas call for further optimization of production systems. Challenges also persist in integrating unfamiliar foods into diets, underscoring the need for a balanced approach to sustainability.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"112 ","pages":"Article 107860"},"PeriodicalIF":9.8,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143395062","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 : 2025-02-11DOI: 10.1016/j.eiar.2025.107861
Shiyi Wang, Yan Li, Xinhui Feng, Er Yu, Jiayu Yang
Carbon metabolism, a fundamental process in regulating the Earth's climate, is profoundly influenced by land use changes and is essential for developing strategies to mitigate global warming. This study formulates a three-pronged theoretical framework for assessing and responding to land use-based carbon metabolism. To address the limitations of existing research confined by jurisdictional boundaries, this framework designs a dual-node carbon metabolism network based on land uses and cities, thereby transitioning the research paradigm from intra-city analysis to regional integration. This approach reveals the intertwined impacts of land use changes and inter-city interactions on carbon metabolism while offering insights into how urban ecological relationships shape regional carbon environments. Moreover, it expands the temporal span of carbon metabolism assessment, incorporating both the retrospective evaluation for 1995–2020 and simulations of carbon evolution across different nodes in 2030. Concentrating on the Hangzhou metropolitan area in China, the study indicates that carbon metabolism exhibits uneven patterns across various dimensions. For carbon exchange between terrestrial and atmospheric systems, carbon emissions reached 49.79 × 108 t in 2020, while carbon sequestration was only 218.88 × 104 t. For terrestrial carbon exchanges, carbon flows are more responsive to inter-city interactions than to land use changes. The dominant Control/Exploitation ecological relationship elucidates that the environmental benefits of land use changes and inter-city linkages have yet to be maximized. From a long-term perspective, intervening in and balancing inter-jurisdictional land use patterns during the transition of decarbonization is necessary. Through developing this practical and replicable framework, this study identifies pivotal strategies for low-carbon development at the city-regional scale, aiding in a deeper and multi-dimensional understanding of urban carbon assessment.
{"title":"A multifaceted assessment and response framework for land use-based carbon metabolism: From Intra-City to Inter-City dynamics","authors":"Shiyi Wang, Yan Li, Xinhui Feng, Er Yu, Jiayu Yang","doi":"10.1016/j.eiar.2025.107861","DOIUrl":"10.1016/j.eiar.2025.107861","url":null,"abstract":"<div><div>Carbon metabolism, a fundamental process in regulating the Earth's climate, is profoundly influenced by land use changes and is essential for developing strategies to mitigate global warming. This study formulates a three-pronged theoretical framework for assessing and responding to land use-based carbon metabolism. To address the limitations of existing research confined by jurisdictional boundaries, this framework designs a dual-node carbon metabolism network based on land uses and cities, thereby transitioning the research paradigm from intra-city analysis to regional integration. This approach reveals the intertwined impacts of land use changes and inter-city interactions on carbon metabolism while offering insights into how urban ecological relationships shape regional carbon environments. Moreover, it expands the temporal span of carbon metabolism assessment, incorporating both the retrospective evaluation for 1995–2020 and simulations of carbon evolution across different nodes in 2030. Concentrating on the Hangzhou metropolitan area in China, the study indicates that carbon metabolism exhibits uneven patterns across various dimensions. For carbon exchange between terrestrial and atmospheric systems, carbon emissions reached 49.79 × 10<sup>8</sup> t in 2020, while carbon sequestration was only 218.88 × 10<sup>4</sup> t. For terrestrial carbon exchanges, carbon flows are more responsive to inter-city interactions than to land use changes. The dominant Control/Exploitation ecological relationship elucidates that the environmental benefits of land use changes and inter-city linkages have yet to be maximized. From a long-term perspective, intervening in and balancing inter-jurisdictional land use patterns during the transition of decarbonization is necessary. Through developing this practical and replicable framework, this study identifies pivotal strategies for low-carbon development at the city-regional scale, aiding in a deeper and multi-dimensional understanding of urban carbon assessment.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"112 ","pages":"Article 107861"},"PeriodicalIF":9.8,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387208","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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