Environmental Impact Assessment Review最新文献

{"title":"The key factor in shaping the historical and future PM2.5 urban-rural pattern in China","authors":"Wenchao Han ,&nbsp;Jiachen Meng ,&nbsp;Wenze Li ,&nbsp;Cheng Yuan ,&nbsp;Lulu Yuan ,&nbsp;Yufan Dai ,&nbsp;Yi Qing ,&nbsp;Xiaolin Wu ,&nbsp;Miaomiao Cheng ,&nbsp;Jian Gao","doi":"10.1016/j.eiar.2025.108147","DOIUrl":"10.1016/j.eiar.2025.108147","url":null,"abstract":"<div><div>Since 2000, rapid urbanization and emissions reduction efforts in China have significantly reshaped emissions, underlying surfaces, and meteorological conditions, altering the PM_2.5 urban-rural distribution. However, the relative contributions of various factors to historical PM_2.5 urban-rural patterns and the sensitive factor shaping future patterns remain unclear. This study quantified the relative contributions of emissions, urban landscape patterns (ULP), and meteorology to PM_2.5 urban-rural differences (URD-PM_2.5) across 299 Chinese cities from 2000 to 2020, and further identified the dominant drivers changing historical URD-PM_2.5 and the sensitive factor reshaping future URD-PM_2.5. The results show that URD-PM_2.5 evolution from 2000 to 2020 can be divided into two typical periods: the Stable High-level Period (SHP, 2000–2013), and the Rapid Decline Period (RDP, 2013–2020). During these periods, the relative contribution of emissions to URD-PM_2.5 consistently increased (nationally from 29 % to 45 %), while that of meteorology decrease continuously (nationally from 49 % to 34 %). And emissions gradually replaced meteorology as the dominant driver during RDP. The relative contribution of ULP remained stable. Furthermore, URD-PM_2.5 in 173 cities was observed to become increasingly sensitive to emissions, 110 cities in southern and southwestern China are increasingly sensitive to ULP, while 16 cities in northeastern China are increasingly sensitive to meteorology. These findings highlight the different contributions of emissions and meteorology to PM_2.5 urban-rural patterns at different periods, and suggest more scientifically targeted policies tailored to specific cities' conditions are needed according to their sensitive factors in future to collaboratively‌ improve urban-rural air quality.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108147"},"PeriodicalIF":11.2,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144908545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Spatiotemporal dynamics and planning responses to address carbon balance and land-use mixtures in megacities: A case study of Wuhan, China","authors":"Peiyi Jiang ,&nbsp;Chen Wen ,&nbsp;Zidi Ma ,&nbsp;Fei Dai","doi":"10.1016/j.eiar.2025.108139","DOIUrl":"10.1016/j.eiar.2025.108139","url":null,"abstract":"<div><div>Cities undergoing rapid urbanization often experience complex land-use changes that impact the ecological environment and significantly influence the carbon balance. Investigating how carbon balance interacts with land-use mixture is vital for guiding effective land resource management and promoting low-carbon development. Wuhan, as an industrial megacity in central China, faces the challenge of shifting toward green and low-carbon growth. This research aims to measure and track the evolution of carbon sinks, carbon emissions, and land-use mixture from 2000 to 2020, while analyzing their spatial clustering patterns. It also integrates landscape pattern metrics and ecosystem services to assess their effects on carbon balance. Based on identified correlations, a dual strategy of reducing emissions and enhancing sinks is proposed. Key findings include: 1) rapid urbanization and the dominance of built-up land lead to significant loss of ecological spaces and carbon sinks, as well as increased carbon emissions 2) contiguous blue-green spaces maintain the highest habitat quality and cooling capacity, which are positively related to carbon sinks; 3) carbon sinks, carbon emissions, and the land-use mixture demonstrate notable spatial clustering; 4) stable correlations exist among these indicators, with land-use mixture weakly negatively correlated with carbon sinks and positively correlated with carbon emissions. This study provides a foundation for managing carbon balance in Wuhan, and offers insights for similar megacities.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108139"},"PeriodicalIF":11.2,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144909063","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analysis of the dynamic evolution, regional differences, and influencing factors of green total factor productivity in grain: The case of China","authors":"Fanzhen Kong ,&nbsp;Huiguang Chen ,&nbsp;Shengwang Bao","doi":"10.1016/j.eiar.2025.108141","DOIUrl":"10.1016/j.eiar.2025.108141","url":null,"abstract":"<div><div>Increasing green total factor productivity of grain (GGTFP) is crucial for overcoming resource and environmental constraints and achieving the SDGs. However, targeted research on GGTFP remains limited. This study employed the global Malmquist-Luenberger (GML) index method based on the super-SBM function to calculate China's GGTFP from 2003 to 2023, analyzed the spatiotemporal evolution and regional differences, and explored the influencing factors of GGTFP from the “production-living-ecology” (PLE) functional perspective. Results showed that: (1) China's GGTFP fluctuated upward from 2003 to 2023, driven mainly by green technological change, with a weak “catching-up effect” from technological efficiency. (2) Spatial distribution became more concentrated, and the “convergence effect” within grain functional areas was strengthened. (3) The centers of gravity of GGTFP in China's 31 provinces migrated toward the northwest as a whole, with intensified spatial agglomeration. (4) Regional differences in GGTFP gradually diminished from 2003 to 2023, with transvariation density as the primary source. (5) Ecological function was the dominant influencing factor, followed by production function, which exhibited spatiotemporal heterogeneity and “threshold effects”. Therefore, some policy implications are proposed regarding refined management, intensive utilization, and multi-objective trade-offs and synergies in policy-making. These findings can offer valuable insights into global sustainable grain production, coordinated development of grain functional areas, and food security from the supply side.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108141"},"PeriodicalIF":11.2,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144908543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Toward sustainability: Analyzing the role of NEVs in inclusive green growth through nighttime light data","authors":"Yixin Huang ,&nbsp;Haozhou Gao ,&nbsp;Zhuyang Liu ,&nbsp;Pengjie Lu ,&nbsp;Jin Tao","doi":"10.1016/j.eiar.2025.108137","DOIUrl":"10.1016/j.eiar.2025.108137","url":null,"abstract":"<div><div>Amid the global transition to green and low-carbon development, new energy vehicles (NEVs) are a key pathway to promoting sustainable development. This study investigated 124 county-level administrative units in Guangdong Province (including two province-administered cities) from 2019 to 2023. An Inclusive Green Growth Index (IGGI) and a New Energy Vehicle Promotion Degree (NEVPD) indicator were developed based on nighttime light (NTL) data and statistical yearbook data. By employing both a coupling coordination model and spatial econometric analysis, the study systematically evaluated the synergistic relationship and spatial effects between these two indices. The results indicate that: (1) estimations based on NTL data were reliable and supported regional research on inclusive green growth; (2) Both NEVPD and IGGI exhibited sustained growth trajectories from 2019 to 2023, with steadily improving coupling coordination levels and a year-by-year reduction in extremely uncoordinated areas. Regional disparities also gradually narrowed. (3) Spatial model results revealed that NEV promotion facilitated local inclusive green growth and also generated positive spillover effects on neighboring regions; (4) Significant spatial disparities remained in Guangdong's regional development. Coupling coordination effects were markedly stronger in the Pearl River Delta than in Eastern, Western, and Northern Guangdong, highlighting the persistent regional imbalance. These findings offer potential government policies for advancing inclusive green transition, promoting regional development balance, and expanding the NEV market to achieve sustainable regional development.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108137"},"PeriodicalIF":11.2,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144914018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review on the effects of climate change and pollution on Vibrio infection dynamics","authors":"Iraitz Jauregui ,&nbsp;Aline Chiabai ,&nbsp;Marc B. Neumann","doi":"10.1016/j.eiar.2025.108126","DOIUrl":"10.1016/j.eiar.2025.108126","url":null,"abstract":"<div><div>Considering their high virulence responsible for causing pandemics and life-threatening infections, their worldwide ubiquity in coastal aquatic environments, and their special sensitivity to climate change, waterborne <em>Vibrio</em> infections are considered one of the main global and emergent public health risks in the 21st century. To advance existing siloed reviews that focus either on clinical, environmental, or policy dimensions, or just address climate change or pollution separately, this paper presents a narrative literature review integrating key disciplines such as environmental microbiology, infectious disease ecology, climate change science, and ecotoxicology, to provide an overview of the key shared mechanisms through which climate change and pollution influence <em>Vibrio</em> infection dynamics. Around 120 peer-reviewed articles published between 1990 and 2025, written in English, and accessible in full text were selected that helped identify the following key shared mechanisms: (i) an increase in <em>Vibrio</em> proliferation and distribution (ii) activation of <em>Vibrio</em> virulence (iii) activation of resistance mechanisms and increase in horizontal gene transfer (HGT) and (iv) alteration of the immune system and gut microbiome of the hosts. The findings of the review are synthesized within the DPSEEA (Driving force, Pressure, State, Exposure, Effect, Action) framework to capture and communicate the complexity regarding <em>Vibrio</em> infection dynamics. Therefore, the resulting model can be used as a tool of knowledge synthesis to help, on the one hand, researchers from different fields such as environmental scientists, microbiologists and ecotoxicologists and on the other hand, local agents, policymakers and public health professionals interact, supporting stakeholder engagement, raising awareness, and fostering transdisciplinary collaboration. Lastly, from a methodological point of view, the proposed model improves the DPSEEA framework, with special relevance for infectious diseases, with the inclusion of an additional fundamental missing component in traditional DPSEEA models, the “host health status”, where susceptibility outcomes influenced by alteration of the state of the host's health are then conceptualized as an integral part.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108126"},"PeriodicalIF":11.2,"publicationDate":"2025-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144908557","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Revealing the dynamic biological flow between eastern and western China from the perspective of ecological network","authors":"Haowei Mu ,&nbsp;Shanchuan Guo ,&nbsp;Kaixuan Pan ,&nbsp;Bo Yuan ,&nbsp;Zhou Fang ,&nbsp;Xingang Zhang ,&nbsp;Xuecao Li ,&nbsp;Peijun Du","doi":"10.1016/j.eiar.2025.108138","DOIUrl":"10.1016/j.eiar.2025.108138","url":null,"abstract":"<div><div>China is one of the most biodiversity-rich countries, yet the ecological gap between its eastern and western regions, driven by geographical barriers, restricts species migration and disrupts ecosystem connectivity. However, the potential of biological flow to bridge this divide remains poorly understood. To address this, we developed a dynamic biological flow framework, combining ecological networks with two new tools, Ecological Linkage Tool Direction and Biological Flow, to quantify species migration directions and intensities across the Middle Spine of Beautiful China. Within and beyond ecological sources, we analyze dynamic biological flow and network structure at node, link, and graph levels. We also simulate changes in network efficiency under various corridor and habitat degradation scenarios. Among the 13,800 ecological corridors, 27 % are oriented east-west (EW), yet the region exhibits a net negative habitat inflow, with 48 % of migrating species potentially failing to reach target habitats. Biological flows outside habitats follow west-to-east (21 %) and north-to-south (18 %) patterns, with the highest migration losses occurring in the north-to-south direction. The regional network efficiency is 0.053. The failure of ecological network in the Inner Mongolia Pastoral Area reduces efficiency by 24 %, intra-patch EW corridors by 57 %, and inter-patch west-to-east corridors by 13 %. Species-specific analyses of the red panda (<em>Ailurus fulgens</em>) and Chinese horseshoe bat (<em>Rhinolophus sinicus</em>) reveals that habitat distribution determines dynamic flow direction, while species-specific adaptability influences flow intensity. This study quantifies dynamic biological flow patterns, overcoming the limitations of widely used static distribution-based conservation planning, more accurately reflecting species migration traits.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108138"},"PeriodicalIF":11.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neighbourhoods for healthy ageing: Examining the nonlinear effect of neighbourhood environments on older adults' functional ability","authors":"Yuqi Liu ,&nbsp;Yiru Li ,&nbsp;Mengdi Wu ,&nbsp;Yi Lu","doi":"10.1016/j.eiar.2025.108115","DOIUrl":"10.1016/j.eiar.2025.108115","url":null,"abstract":"<div><div>An effective response to population ageing is crucial for ensuring global social sustainability. Improving the age-friendliness of neighbourhoods and maintaining the functional ability of older adults are key strategies in addressing the challenges posed by population ageing. However, the nonlinear effect of neighbourhood environments on the functional ability of older adults is largely unexplored. This study performed empirical analysis using multi-source geospatial data and questionnaire survey data from Guangzhou, China. Results of generalized additive mixed models revealed that the population density, branch road proportion, and street traffic volume exerted a positive influence on the older adults' functional ability, and when the values were outside the optimal range, the positive association became negative. In addition, the accessibility of facilities, street safety, visible sky features, and water areas exerted a positive impact on functional ability. Meanwhile, high-density urban environment characteristics, namely building density, road density, and the number of public transportation stops, exerted a negative impact. This study contributes to person–environment fit theory by revealing the optimal levels of environmental attributes for the functional ability among older adults, as well as by comprehensively examining impacts from two spatial scales – neighbourhood and streetscape environments – and by revealing the heterogeneous effects from income and age. Furthermore, it recommends evidence-based planning and targeted governance strategies for building age-friendly neighbourhoods in China and other high-density Asian cities.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108115"},"PeriodicalIF":11.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895900","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Seasonal synergistic management of urban heat island effect and PM₂.₅ pollution: Insights from interpretable LightGBM-SHAP machine learning model","authors":"Qiqi Liu ,&nbsp;Tian Hang","doi":"10.1016/j.eiar.2025.108129","DOIUrl":"10.1016/j.eiar.2025.108129","url":null,"abstract":"<div><div>Urban heat island (UHI) effect and fine particulate matter (PM_2.5) have emerged as two major challenges in urban environmental management, with their interactions further exacerbating threats to global public health. However, strategies for the synergistic management of these two challenges remain limited. To address this gap, we proposed a new synergistic management framework incorporating temporal and spatial dimensions and empirically apply it to Guangdong-Hong Kong-Macao Greater Bay Area (GBA). We analyzed the seasonal spatial distribution of UHI effect and corresponding PM_2.5 concentrations, identifying their spatial synergy using bivariate spatial analysis. Furthermore, an interpretable LightGBM-SHAP machine learning model was applied to explore the key driving factors and underlying mechanisms jointly influencing UHI and PM_2.5. The results showed that spatially synergistic regions of UHI and PM_2.5 were mainly concentrated in the central and northwestern parts of the GBA, particularly in Guangzhou, Foshan, and Zhaoqing. The spatial synergy peaked in summer with a coverage of 73.73 %, highlighting the need for prioritized intervention during this season, while it declined markedly to 46.95 % in winter. Across all seasons, building density (BD) and building shape index (BSI) were identified as key drivers with positive synergistic effects, whereas green space ratio (GSR) and mean annual precipitation (MAP) exhibited negative synergistic impacts. Additionally, factors such as nighttime light (NL), blue space ratio (BSR), edge density (ED), and built-up land ratio (BLR) showed synergistic influence in specific seasons. This study can provide support for the development of more targeted and seasonally adaptive strategies for the synergistic management of urban thermal environments and air quality.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108129"},"PeriodicalIF":11.2,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144893242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Order-level data reveal the impact of enterprises' behavior on their profits in China's national ETS","authors":"Ling Tang ,&nbsp;Shuangyue Qian ,&nbsp;Jianhui Ruan ,&nbsp;Yan Huang ,&nbsp;Ruxing Wan ,&nbsp;Bofeng Cai ,&nbsp;Gang Yan","doi":"10.1016/j.eiar.2025.108136","DOIUrl":"10.1016/j.eiar.2025.108136","url":null,"abstract":"<div><div>China's national carbon emissions trading system (ETS) has become the largest carbon market worldwide and is considered an effective policy tool for addressing the challenges of climate change. ETS significantly affects corporate profitability and revenue generation, but research on this aspect remains limited. This study employs mediation and moderation effect models, using unit-level monitoring and order-specific trading data from the first compliance phase of national ETS (including 5520 units from 2162 power firms) in China, to estimate the impact of enterprises' responses to the ETS. The results highlight several important insights. First, enterprises' positive responses to the market (such as using high-quality fuel) are positively correlated with revenue and profit (i.e. net sales and compliance rate), with carbon intensity playing a significant mediating role in this relationship. Second, heterogeneity analysis reveals variations across different types of units and regions, with smaller units and those in western regions exhibiting greater sensitivity to compliance. Third, compared to the less experienced national market, pilot markets show a greater propensity to sell allowances and ensure compliance with emission targets. This study provides a more micro-level perspective on how China's ETS influences enterprises and offers policy-relevant evidence to inform decision-making.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108136"},"PeriodicalIF":11.2,"publicationDate":"2025-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144895899","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing flood prediction in the Lower Mekong River Basin by scale-independent interpretable deep learning model","authors":"Yangzi Qiu ,&nbsp;Xiaogang Shi ,&nbsp;Xiaogang He","doi":"10.1016/j.eiar.2025.108130","DOIUrl":"10.1016/j.eiar.2025.108130","url":null,"abstract":"<div><div>Climate change has increased the frequency and intensity of extreme floods in the Lower Mekong River Basin (LMB). This study leverages the Long Short-Term Memory (LSTM) model to evaluate its performance in predicting river discharge across the LMB and to identify the key variables contributing to flood prediction through SHapley Additive exPlanation (SHAP) and Universal Multifractal (UM) analyses, in a scale-dependent and scale-independent manner, respectively. The performance of the LSTM model is satisfactory, with Nash–Sutcliffe Efficiency (NSE) values exceeding 0.9 for all subbasins when using all input features. The model tends to underestimate the largest peak flows in the midstream subbasins that experienced extreme rainfall events. According to SHAP, soil-related variables are important contributors to discharge prediction, with their impacts partially manifested through interactions with precipitation and runoff. Furthermore, the dominant contributing variables influencing flood prediction vary over time: soil-related variables and vegetation-related variables played a more significant role in earlier years, whereas hydrometeorological variables became more dominant after 2017. The UM analysis investigates the scaling behaviours of contributing variables, showing that hydrometeorological-related variables have a greater influence on predicting extreme discharge across the small temporal scales. Additionally, the UM analysis indicates that the model's performance improves as the temporal variability in extremes of the combined features decreases across 1 to 16 days. Overall, this study provides a comprehensive assessment of the LSTM model's performance in discharge prediction, emphasising the impact of the variability in the extremes of combined features through the scale-independent interpretation. These findings will offer valuable insights for stakeholders to improve flood risk management across the LMB.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108130"},"PeriodicalIF":11.2,"publicationDate":"2025-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144892097","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}