Pub Date : 2025-02-07DOI: 10.1016/j.eiar.2025.107858
Weisheng Lu, Bing Yang, Liang Yuan, Ziyu Peng
This study addresses the ongoing challenge of illegal dumping (‘fly-tipping’) in urban environments, specifically focusing on Hong Kong. Utilizing a substantial dataset of 1384 Fixed Penalty Notices issued from 2014 to 2021, the research presents a novel methodological approach that integrates Space Syntax Analysis (SSA) and Geographically Weighted Random Forest (GW-RF). The integration demonstrates robust predictive performance (R2 = 0.809), significantly outperforming traditional models. Our findings reveal three fundamental patterns: social-economic pressures serve as consistent underlying drivers, urban spatial configuration creates distinct opportunity patterns, and waste disposal infrastructure acts as a local modifier of dumping behavior. These insights challenge conventional assumptions about illegal dumping locations and effectiveness of uniform solutions. The study provides an evidence-based foundation for developing targeted interventions, suggesting that effective policies must consider both stable social-economic pressures and variable spatial-infrastructural conditions. This research not only deepens the understanding of fly-tipping in Hong Kong but also proposes a robust, adaptable analytical framework for other urban contexts, contributing to both urban theory and practice in environmental management.
{"title":"Understanding fly-tipping in urban areas: A social-economic-spatial combinatorial approach enabled by geographically weighted random forest","authors":"Weisheng Lu, Bing Yang, Liang Yuan, Ziyu Peng","doi":"10.1016/j.eiar.2025.107858","DOIUrl":"10.1016/j.eiar.2025.107858","url":null,"abstract":"<div><div>This study addresses the ongoing challenge of illegal dumping (‘fly-tipping’) in urban environments, specifically focusing on Hong Kong. Utilizing a substantial dataset of 1384 Fixed Penalty Notices issued from 2014 to 2021, the research presents a novel methodological approach that integrates Space Syntax Analysis (SSA) and Geographically Weighted Random Forest (GW-RF). The integration demonstrates robust predictive performance (R<sup>2</sup> = 0.809), significantly outperforming traditional models. Our findings reveal three fundamental patterns: social-economic pressures serve as consistent underlying drivers, urban spatial configuration creates distinct opportunity patterns, and waste disposal infrastructure acts as a local modifier of dumping behavior. These insights challenge conventional assumptions about illegal dumping locations and effectiveness of uniform solutions. The study provides an evidence-based foundation for developing targeted interventions, suggesting that effective policies must consider both stable social-economic pressures and variable spatial-infrastructural conditions. This research not only deepens the understanding of fly-tipping in Hong Kong but also proposes a robust, adaptable analytical framework for other urban contexts, contributing to both urban theory and practice in environmental management.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"112 ","pages":"Article 107858"},"PeriodicalIF":9.8,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143349723","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}
Pub Date : 2025-02-06DOI: 10.1016/j.eiar.2025.107854
Liwei Qu , Yang Li , Juan Guo , Lianghui Li , Bochao An
Despite escalating environmental regulations and intensifying decarbonization demand within the steel industry, comprehensive frameworks for emission disclosure remain under development. The sector is gradually incorporating requirements to report upstream emissions that are tied to raw material supply chains. This study presented a detailed carbon footprint assessment of seaborne metallurgical (met) coal trading by creating a global database of seaborne met coal export mines and optimizing both the trade matrix and mine-to-destination transportation network. Employing a bottom-up approach coupled with life cycle assessment (LCA) methodology, this study calculated carbon intensity (CI) of global seaborne met coal mines. The analysis reveals significant variability in CI, ranging from 63.4 to 665.5 kg CO2eq/t, with a global volume-weighted average of 217.6 kg CO2eq/t. The variability is influenced by factors including mine extraction methods, raw coal quality, transportation mode, and destination distance. The heterogeneity of CIs highlights substantial decarbonization potential. Forecasts of seaborne met coal demand through 2050 suggest that prioritizing low-carbon supply chain pathways alone could yield CO2eq reduction by an average of up to 230Mt, even in the absence of additional emission mitigation strategies
{"title":"Research on carbon intensity of global seaborne metallurgical coal exports and implications","authors":"Liwei Qu , Yang Li , Juan Guo , Lianghui Li , Bochao An","doi":"10.1016/j.eiar.2025.107854","DOIUrl":"10.1016/j.eiar.2025.107854","url":null,"abstract":"<div><div>Despite escalating environmental regulations and intensifying decarbonization demand within the steel industry, comprehensive frameworks for emission disclosure remain under development. The sector is gradually incorporating requirements to report upstream emissions that are tied to raw material supply chains. This study presented a detailed carbon footprint assessment of seaborne metallurgical (met) coal trading by creating a global database of seaborne met coal export mines and optimizing both the trade matrix and mine-to-destination transportation network. Employing a bottom-up approach coupled with life cycle assessment (LCA) methodology, this study calculated carbon intensity (CI) of global seaborne met coal mines. The analysis reveals significant variability in CI, ranging from 63.4 to 665.5 kg CO<sub>2</sub>eq/t, with a global volume-weighted average of 217.6 kg CO<sub>2</sub>eq/t. The variability is influenced by factors including mine extraction methods, raw coal quality, transportation mode, and destination distance. The heterogeneity of CIs highlights substantial decarbonization potential. Forecasts of seaborne met coal demand through 2050 suggest that prioritizing low-carbon supply chain pathways alone could yield CO<sub>2</sub>eq reduction by an average of up to 230Mt, even in the absence of additional emission mitigation strategies</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"112 ","pages":"Article 107854"},"PeriodicalIF":9.8,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143241686","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 : 2025-02-04DOI: 10.1016/j.eiar.2025.107851
Bin Xu
Government expenditure is the core measure of maintaining the welfare of the general public, especially low-income families. Therefore, to investigate the potential effect of government expenditure on energy poverty reduction, this paper first calculates the energy poverty index of 30 provinces in China, and then explore how government expenditure mitigates energy poverty. The estimation results of the spatial quantile model show that: (1) there exists a positive spatial autocorrelation in energy poverty, indicating that energy poor areas are often contiguous, such as Guizhou-Yunnan, and Qinghai-Gansu-Shanxi. (2) Government expenditure has a negative effect on energy poverty across all quantile provinces, meaning that government expenditure is advantageous for alleviating energy poverty. (3) Heterogeneity analysis reveals that both educational expenditure and resource exploration expenditure contribute to the alleviation of energy poverty. However, the impact of social security expenditure on poverty reduction is limited. (4) The mediating role of green technology innovation and green finance is prominent. Specifically, green technology innovation has a positive impact on energy poverty reduction in all quantile groups, while green finance only has a prominent effect on the provinces with lower energy poverty. Following the above results, this article proposes relevant policies to optimize government expenditure structure and reduce energy poverty.
{"title":"How government expenditure reduces energy poverty? Evidence from spatial quantile model","authors":"Bin Xu","doi":"10.1016/j.eiar.2025.107851","DOIUrl":"10.1016/j.eiar.2025.107851","url":null,"abstract":"<div><div>Government expenditure is the core measure of maintaining the welfare of the general public, especially low-income families. Therefore, to investigate the potential effect of government expenditure on energy poverty reduction, this paper first calculates the energy poverty index of 30 provinces in China, and then explore how government expenditure mitigates energy poverty. The estimation results of the spatial quantile model show that: (1) there exists a positive spatial autocorrelation in energy poverty, indicating that energy poor areas are often contiguous, such as Guizhou-Yunnan, and Qinghai-Gansu-Shanxi. (2) Government expenditure has a negative effect on energy poverty across all quantile provinces, meaning that government expenditure is advantageous for alleviating energy poverty. (3) Heterogeneity analysis reveals that both educational expenditure and resource exploration expenditure contribute to the alleviation of energy poverty. However, the impact of social security expenditure on poverty reduction is limited. (4) The mediating role of green technology innovation and green finance is prominent. Specifically, green technology innovation has a positive impact on energy poverty reduction in all quantile groups, while green finance only has a prominent effect on the provinces with lower energy poverty. Following the above results, this article proposes relevant policies to optimize government expenditure structure and reduce energy poverty.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"112 ","pages":"Article 107851"},"PeriodicalIF":9.8,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132707","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 : 2025-02-04DOI: 10.1016/j.eiar.2025.107845
Shu Su , Jiahui Feng , Wei Wang , Yue Jin , Dan Chong
Low-carbon community development is essential to enhance the sustainability of cities and societies. Residential form plays an important role in the carbon emissions of communities. This study explores how residential form affects the life cycle carbon emissions of residential buildings with temporal variations. Four types of residential form indicators (layout, building height, spacing, and building orientation) were integrated to develop 81 residential community geometry models. Their operational energy was simulated using Rhino and Grasshopper software, and life cycle carbon emissions were calculated. Several dynamic factors over time, including climate change, building envelope aging, dynamic carbon emission factors, and recycling rate improvement, were incorporated into the calculation process. A residential community was taken as the case study to assess the relationship between residential form indicators and life cycle carbon emissions. The results showed that variations in residential form led to differences of up to 13.21 %. The total carbon emissions considering dynamic factors were 15.01 % averagely lower than the corresponding static values, underscoring the meaning of involving dynamic variations. This study provides a scientific basis for designing low-carbon communities and promoting sustainable urban development.
{"title":"Dynamic prediction of lifecycle carbon emissions in residential communities: Insights into the role of residential form","authors":"Shu Su , Jiahui Feng , Wei Wang , Yue Jin , Dan Chong","doi":"10.1016/j.eiar.2025.107845","DOIUrl":"10.1016/j.eiar.2025.107845","url":null,"abstract":"<div><div>Low-carbon community development is essential to enhance the sustainability of cities and societies. Residential form plays an important role in the carbon emissions of communities. This study explores how residential form affects the life cycle carbon emissions of residential buildings with temporal variations. Four types of residential form indicators (layout, building height, spacing, and building orientation) were integrated to develop 81 residential community geometry models. Their operational energy was simulated using Rhino and Grasshopper software, and life cycle carbon emissions were calculated. Several dynamic factors over time, including climate change, building envelope aging, dynamic carbon emission factors, and recycling rate improvement, were incorporated into the calculation process. A residential community was taken as the case study to assess the relationship between residential form indicators and life cycle carbon emissions. The results showed that variations in residential form led to differences of up to 13.21 %. The total carbon emissions considering dynamic factors were 15.01 % averagely lower than the corresponding static values, underscoring the meaning of involving dynamic variations. This study provides a scientific basis for designing low-carbon communities and promoting sustainable urban development.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"112 ","pages":"Article 107845"},"PeriodicalIF":9.8,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132746","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 : 2025-02-03DOI: 10.1016/j.eiar.2025.107838
Chaoqing Chai , Ronghao Wen , Huadong Zhu , Yongheng He , Peixue Xing , Yuanyuan Li , Ying Sun , Zhenhao Liu , Haoyang Wang , Wenhao Niu , Weiwei Zheng , Guanghui Hou , Xiangbin Kong , Bangbang Zhang
Improved growth and closing gap of cropland green production efficiency (CGPE) are effective strategies to both enhance food production and reduce environmental risks by technology enhancement, particularly in ecologically fragile basins. This study develops a CGPE accounting framework that incorporates multi-dimensional environmental impacts, based on the crop full lifecycle management of cropland use. A unified assessment framework is proposed to examine the drivers influencing CGPE growth and gap from the perspective of the technology enhancement interface, specifically technical progress (TP) and diffusion (TD). Using a hybrid approach, this study integrates the three-stage super-efficiency input-output model, Malmquist–Luenberger index, Gini coefficient decomposition, and spatial Markov chain model to investigate which technology enhancement interface drives CGPE growth and gap in the Yellow River basin (YRB), across 707 counties. This study shows evidence that CGPE growth in the YRB from 2000 to 2022 at the county scale displayed a “U-shaped” trend with an elevated terminal point, which is primarily driven by TP; that the significant spatial heterogeneity in CGPE is observed, with a small regional gap in the lower reach but a notable imbalanced development in the upper-middle reaches despite the narrowing gap, mainly due to insufficient TP; and that there is a dynamic polarization tendency shifting from medium to low level and from medium high to the high level. Therefore, priority should be given to enhancing green production technology, promoting balanced technology diffusion, leveraging the role model of high-efficiency areas so as to concurrently achieve agricultural productivity and environmental sustainability.
{"title":"Assessing technology's influence on cropland green production efficiency in the Yellow River basin, China","authors":"Chaoqing Chai , Ronghao Wen , Huadong Zhu , Yongheng He , Peixue Xing , Yuanyuan Li , Ying Sun , Zhenhao Liu , Haoyang Wang , Wenhao Niu , Weiwei Zheng , Guanghui Hou , Xiangbin Kong , Bangbang Zhang","doi":"10.1016/j.eiar.2025.107838","DOIUrl":"10.1016/j.eiar.2025.107838","url":null,"abstract":"<div><div>Improved growth and closing gap of cropland green production efficiency (CGPE) are effective strategies to both enhance food production and reduce environmental risks by technology enhancement, particularly in ecologically fragile basins. This study develops a CGPE accounting framework that incorporates multi-dimensional environmental impacts, based on the crop full lifecycle management of cropland use. A unified assessment framework is proposed to examine the drivers influencing CGPE growth and gap from the perspective of the technology enhancement interface, specifically technical progress (TP) and diffusion (TD). Using a hybrid approach, this study integrates the three-stage super-efficiency input-output model, Malmquist–Luenberger index, Gini coefficient decomposition, and spatial Markov chain model to investigate which technology enhancement interface drives CGPE growth and gap in the Yellow River basin (YRB), across 707 counties. This study shows evidence that CGPE growth in the YRB from 2000 to 2022 at the county scale displayed a “U-shaped” trend with an elevated terminal point, which is primarily driven by TP; that the significant spatial heterogeneity in CGPE is observed, with a small regional gap in the lower reach but a notable imbalanced development in the upper-middle reaches despite the narrowing gap, mainly due to insufficient TP; and that there is a dynamic polarization tendency shifting from medium to low level and from medium high to the high level. Therefore, priority should be given to enhancing green production technology, promoting balanced technology diffusion, leveraging the role model of high-efficiency areas so as to concurrently achieve agricultural productivity and environmental sustainability.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"112 ","pages":"Article 107838"},"PeriodicalIF":9.8,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132695","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 : 2025-02-03DOI: 10.1016/j.eiar.2025.107841
Huiming Zhang , Shuyuan Wang , Kai Wu , Yueming (Lucy) Qiu , Shouyang Wang , Yongfan Zhao
We examine the nonlinear effects of temperature extremes on poverty in China from 2000 to 2020 using county-level panel data and temperature bins. The empirical strategy exploits within-country variation to isolate the impacts of heat waves and cold spells. We find extreme heat above 30 °C significantly increases poverty rates, while extreme cold below −12 °C reduces poverty. The impacts vary across counties with different industry focus and income levels. Agricultural mechanization, output, urbanization, industrial output, and health impacts are identified as significant mediating factors. The simulation results under the four pathways of the GFDL-ESM4 model indicate that the predicted increase in high-temperature days will aggravate county-level poverty, according to both medium-term (2021–2060) and long-term (2061–2100) projections. In particular, projections based on high fossil fuel energy consumption pathways suggest greater shocks to county-level economic development. Our results underscore the need for social security, rural development, and ecological adaptation policies to mitigate climate-induced poverty risks in China. This study provides new county-level evidence on the heterogeneous effects of climate extremes on poverty.
{"title":"Freezing or searing: Unraveling the impact of extreme temperatures on poverty in China","authors":"Huiming Zhang , Shuyuan Wang , Kai Wu , Yueming (Lucy) Qiu , Shouyang Wang , Yongfan Zhao","doi":"10.1016/j.eiar.2025.107841","DOIUrl":"10.1016/j.eiar.2025.107841","url":null,"abstract":"<div><div>We examine the nonlinear effects of temperature extremes on poverty in China from 2000 to 2020 using county-level panel data and temperature bins. The empirical strategy exploits within-country variation to isolate the impacts of heat waves and cold spells. We find extreme heat above 30 °C significantly increases poverty rates, while extreme cold below −12 °C reduces poverty. The impacts vary across counties with different industry focus and income levels. Agricultural mechanization, output, urbanization, industrial output, and health impacts are identified as significant mediating factors. The simulation results under the four pathways of the GFDL-ESM4 model indicate that the predicted increase in high-temperature days will aggravate county-level poverty, according to both medium-term (2021–2060) and long-term (2061–2100) projections. In particular, projections based on high fossil fuel energy consumption pathways suggest greater shocks to county-level economic development. Our results underscore the need for social security, rural development, and ecological adaptation policies to mitigate climate-induced poverty risks in China. This study provides new county-level evidence on the heterogeneous effects of climate extremes on poverty.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"112 ","pages":"Article 107841"},"PeriodicalIF":9.8,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132706","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 : 2025-02-03DOI: 10.1016/j.eiar.2025.107846
Tiago G. Morais , Manuel P. dos Santos , Lúcia Barão , Tiago Domingos , Ricardo F.M. Teixeira
Greenhouse gas (GHG) emissions of beef production are extremely variable depending on the livestock production system (LPS) used, with lack of clarity on the influencing factors. Here, we assess those factors using a mass balance model with regional case study data for Portugal. We show that the whole-system GHG emissions range for beef production from steers in beef herds is 15–124 kg CO2e per 100 g protein depending on LPS (confined, pasture-based or mixed), breed, age at slaughter, and adequacy and upstream impact of supplemental feed. If steers are adequately supplemented, then LPS that involve at least a stage of grazing for steers have the lowest emissions, regardless of supplemental feed impact. In case of suboptimal supplementation during grazing, confinement is optimal at intermediate to low feed impact. For high feed impact, slaughtering at weaning is optimal. Choosing the best LPS and slaughtering age reduces the range of emissions to 15–35 kg CO2e per 100 g protein.
{"title":"Grazing or confining — Decoding Beef's environmental footprint","authors":"Tiago G. Morais , Manuel P. dos Santos , Lúcia Barão , Tiago Domingos , Ricardo F.M. Teixeira","doi":"10.1016/j.eiar.2025.107846","DOIUrl":"10.1016/j.eiar.2025.107846","url":null,"abstract":"<div><div>Greenhouse gas (GHG) emissions of beef production are extremely variable depending on the livestock production system (LPS) used, with lack of clarity on the influencing factors. Here, we assess those factors using a mass balance model with regional case study data for Portugal. We show that the whole-system GHG emissions range for beef production from steers in beef herds is 15–124 kg CO<sub>2</sub>e per 100 g protein depending on LPS (confined, pasture-based or mixed), breed, age at slaughter, and adequacy and upstream impact of supplemental feed. If steers are adequately supplemented, then LPS that involve at least a stage of grazing for steers have the lowest emissions, regardless of supplemental feed impact. In case of suboptimal supplementation during grazing, confinement is optimal at intermediate to low feed impact. For high feed impact, slaughtering at weaning is optimal. Choosing the best LPS and slaughtering age reduces the range of emissions to 15–35 kg CO<sub>2</sub>e per 100 g protein.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"112 ","pages":"Article 107846"},"PeriodicalIF":9.8,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132692","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}
Pub Date : 2025-02-03DOI: 10.1016/j.eiar.2025.107844
Mengqi Niu, Yukun Wang
Based on a comprehensive county-level dataset covering 405 counties during 2007 to 2019, this paper investigates the impact of the Major Function-Oriented Zone Planning on environmental protection and economic development. By employing a time-varying difference-in-differences strategy, we utilize ecology-related development-restricted counties as the treatment group, whereas counties that do not fall within any specific functional category as the control group. Different from previous studies emphasizing that environmental protection and economic development are incompatible, we find that there is not only a notable improvement in ecological environment quality, but also the regional economic developed, as measured by the GDP per capita, in ecology-related development-restricted areas. To figure out how to achieve this balance, we first focus on the underlying mechanism of environmental enhancement. Our results indicate that improvement is primarily attributed to the withdrawal of polluting enterprises, the reduction in the supply of industrial land and the receipt of ecological transfer from the central government. Subsequently, the internal mechanisms analysis of economic growth reveals that the primary and tertiary industry have achieved significant growth, due to the enhancement of agricultural and livestock production and the expansion of local tourist attractions. Our findings provide valuable insights into the potential for achieving a win-win situation between environmental protection and economic development in the context of territorial space planning.
{"title":"Greening the economy: How territorial spatial planning policy promotes ecological and economic integration","authors":"Mengqi Niu, Yukun Wang","doi":"10.1016/j.eiar.2025.107844","DOIUrl":"10.1016/j.eiar.2025.107844","url":null,"abstract":"<div><div>Based on a comprehensive county-level dataset covering 405 counties during 2007 to 2019, this paper investigates the impact of the Major Function-Oriented Zone Planning on environmental protection and economic development. By employing a time-varying difference-in-differences strategy, we utilize ecology-related development-restricted counties as the treatment group, whereas counties that do not fall within any specific functional category as the control group. Different from previous studies emphasizing that environmental protection and economic development are incompatible, we find that there is not only a notable improvement in ecological environment quality, but also the regional economic developed, as measured by the GDP per capita, in ecology-related development-restricted areas. To figure out how to achieve this balance, we first focus on the underlying mechanism of environmental enhancement. Our results indicate that improvement is primarily attributed to the withdrawal of polluting enterprises, the reduction in the supply of industrial land and the receipt of ecological transfer from the central government. Subsequently, the internal mechanisms analysis of economic growth reveals that the primary and tertiary industry have achieved significant growth, due to the enhancement of agricultural and livestock production and the expansion of local tourist attractions. Our findings provide valuable insights into the potential for achieving a win-win situation between environmental protection and economic development in the context of territorial space planning.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"112 ","pages":"Article 107844"},"PeriodicalIF":9.8,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132645","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 : 2025-01-31DOI: 10.1016/j.eiar.2025.107843
Laurie D. Maynard , Jérôme Lemaître , Jean-François Therrien , Nicolas Lecomte
Wind energy presents a novel stressor to wildlife, sometimes resulting in habitat loss and reduced reproductive output. Vulnerability index is a powerful metric to estimate the susceptibility to harm from stressors. We aim to assess the regional-level exposure, sensitivity and vulnerability to wind farms of breeding Golden Eagles (Aquila chrysaetos). Our study focused on the Gaspé Peninsula (Québec, Canada), a region hosting a vulnerable population of Golden Eagles and 26 wind farms built in the last 25 years. Using nests monitoring and over 13 years of satellite tracking of eight breeding eagles, we show that eagles' exposure to wind farms increases with nest proximity, resulting in higher vulnerability for eagles nesting closer (≤20 km), especially during chick-rearing and post-fledging. Eagles nesting ≤20 km avoided wind farms, using them less than other similar areas, resulting in unused areas in the home range. Our sensitivity and vulnerability assessments revealed that wind farms are positioned in moderate to highly suitable habitats, indicating functional habitat loss. We monitored breeding before, during and after wind farm development, but reproductive outcomes did not significantly vary with development phases. However, overall breeding success in the region appeared to decline over the last two decades, possibly due to a combination of factors. Our study presents the behavioural effects of wind farms on breeding birds of prey while identifying areas most sensitive and nests most vulnerable to wind development in the region. This research underscores the need for pre-construction assessments and continued breeding monitoring for long-term assessment.
{"title":"Vulnerability and behavioural avoidance of Golden Eagles near wind farms during the breeding season","authors":"Laurie D. Maynard , Jérôme Lemaître , Jean-François Therrien , Nicolas Lecomte","doi":"10.1016/j.eiar.2025.107843","DOIUrl":"10.1016/j.eiar.2025.107843","url":null,"abstract":"<div><div>Wind energy presents a novel stressor to wildlife, sometimes resulting in habitat loss and reduced reproductive output. Vulnerability index is a powerful metric to estimate the susceptibility to harm from stressors. We aim to assess the regional-level exposure, sensitivity and vulnerability to wind farms of breeding Golden Eagles (<em>Aquila chrysaetos</em>). Our study focused on the Gaspé Peninsula (Québec, Canada), a region hosting a vulnerable population of Golden Eagles and 26 wind farms built in the last 25 years. Using nests monitoring and over 13 years of satellite tracking of eight breeding eagles, we show that eagles' exposure to wind farms increases with nest proximity, resulting in higher vulnerability for eagles nesting closer (≤20 km), especially during chick-rearing and post-fledging. Eagles nesting ≤20 km avoided wind farms, using them less than other similar areas, resulting in unused areas in the home range. Our sensitivity and vulnerability assessments revealed that wind farms are positioned in moderate to highly suitable habitats, indicating functional habitat loss. We monitored breeding before, during and after wind farm development, but reproductive outcomes did not significantly vary with development phases. However, overall breeding success in the region appeared to decline over the last two decades, possibly due to a combination of factors. Our study presents the behavioural effects of wind farms on breeding birds of prey while identifying areas most sensitive and nests most vulnerable to wind development in the region. This research underscores the need for pre-construction assessments and continued breeding monitoring for long-term assessment.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"112 ","pages":"Article 107843"},"PeriodicalIF":9.8,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143132691","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}
Pub Date : 2025-01-30DOI: 10.1016/j.eiar.2025.107840
Han Huang , Kun Sun , Ruyin Long
In the context of growing attention to environmental crises and sustainable development, the emotional expressions of social media users not only shape the formation of green consumption concepts but also facilitate the spread of related products and ideas. Understanding how information characteristics influence emotional expression and dissemination can enhance public guidance and emotional support for green consumption, thereby fostering a more effective green consumption culture. This study applies emotional contagion theory to conduct a comparative analysis of the dissemination mechanisms of emotional information across six domains: green clothing, green food, green housing, green transportation, green products, and green tourism. Using deep learning models, a cognitive-emotional evaluation framework, an extended Maslow's hierarchy of needs model, and social network analysis, the study extracts indicators such as sentiment classification, information demand hierarchy, and information presentation from textual data. These indicators are used to examine the breadth, depth, and influence of public sentiment in various green consumption networks. The results show that positive emotional information generally has a broader reach and stronger influence than neutral emotional information. Additionally, greater cognitive homogeneity tends to enhance the effectiveness of positive emotional information dissemination. The study also finds that dissemination behaviors vary across different green themes and information formats. Based on these findings, strategies for promoting positive sentiment and managing negative sentiment are proposed.
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