Environmental Impact Assessment Review最新文献

{"title":"Assessing the effectiveness of SDGs implementation in reducing intra-urban spatial inequality: A spatiotemporal heterogeneous modeling in China","authors":"Weishi Zhang ,&nbsp;Yitong Han ,&nbsp;David G. Streets ,&nbsp;Can Wang ,&nbsp;Ying Xu","doi":"10.1016/j.eiar.2025.108118","DOIUrl":"10.1016/j.eiar.2025.108118","url":null,"abstract":"<div><div>Local governments have initiated independent policies to contribute to implementing the Sustainable Development Goals (SDGs). However, the spatiotemporally heterogeneous impacts of the implementation of SDGs (SDGI) on intra-urban development inequality have not been given sufficient attention. This study examines the spatiotemporally heterogeneous effects of locally implemented SDGI on intra-urban development inequality in China (SDG 10). Firstly, we utilize nighttime light (NTL) satellite data and the grid population data to estimate the intra-urban Gini coefficients as a proxy for intra-urban spatial development inequality. Then we employ natural language processing (NLP) technologies to assess the intensity of SDGI as implemented by local governments. Secondly, a System Generalized Method of Moments (GMM) model is applied, followed by the Geographically and Temporally Weighted Regression (GTWR) model, to evaluate the spatial and temporal heterogeneous effects of SDGI on urban inequality. Third, we employ the BP Neural Network approach to validate the analysis results. The GTWR model results show that the temporal variations in the narrowing effect of SDGI follow a U-shaped trend. The median (25 %, 75 %) estimations of the SDGI coefficients are −0.007(−0.004,0.005) in 2012, then reaching a peak value of −0.072 (−0.087, −0.061) by 2018, while decreased to be −0.026 (−0.042, −0.027) in 2022. Urbanization and infrastructure development, which served as control variables, were found to significantly reduce inequality, whereas foreign direct investment (FDI) and higher unemployment rates tended to exacerbate intra-urban spatial inequality. The performances of SDGI on reducing urban inequality have shown significant spatial heterogeneity. Cities with higher SDGI intensity demonstrated a higher narrowing effect on urban inequality in the southwest, maybe due to clean energy investments and ecological compensation programs. The narrowing effects from SDGI were limited in highly developed first-tier cities, cities experiencing population outflows, and cities with higher sustainable development costs. Cities with higher SDGI intensity and narrowing effects reached their peak year of reducing inequality 1–2 years earlier. These findings highlight the importance of an earlier SDGI in narrowing urban equality and provide policy implications for decision-makers to address intra- and inter-city inequality for a sustainable development future.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"117 ","pages":"Article 108118"},"PeriodicalIF":11.2,"publicationDate":"2025-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144933565","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":"Global daily 1 km gapless XCO₂ (2003−2023) derived from multi-satellite observations and a spatiotemporal deep learning framework","authors":"Jiawei Wang","doi":"10.1016/j.eiar.2025.108146","DOIUrl":"10.1016/j.eiar.2025.108146","url":null,"abstract":"<div><div>In recent years, atmospheric CO₂ concentrations have continued to rise, driving global warming and precipitating severe environmental and ecological crises. Spatiotemporal monitoring of column-averaged dry-air mole fractions of CO₂ (XCO₂) from satellite observations is indispensable for quantifying carbon sources and sinks, evaluating mitigation efforts, and elucidating the global carbon cycle. However, existing satellite XCO₂ products are severely limited by narrow swaths, adverse meteorological interference, and inconsistent spatiotemporal coverage across different platforms, resulting in sparse retrievals with substantial gaps. This study developed a spatiotemporal deep learning framework that couples ConvLSTM temporal modules with a U-Net spatial backbone, enhanced by residual connections and channel- and spatial-attention blocks. Using the column-averaged dry-air mole fraction of XCO₂ data of SCIAMACHY, GOSAT, and OCO-2, we derived the first gapless, daily global terrestrial XCO₂ dataset at 1 km resolution spanning 2003–2023. The results showed outstanding performance under three cross-validation strategies—sample-based, grid-based (spatial), and daily-based (temporal)—with R² = 0.996/0.963/0.952, RMSE = 0.46/0.62/0.73 ppm, and MAPE = 0.085 %/ 0.096 %/ 0.101 %, respectively. Moreover, independent validation against in situ TCCON measurements also confirms excellent agreement (R² = 0.988, RMSE = 1.10 ppm, MAPE = 0.216 %). Compared to previous efforts, this framework delivers significant improvements in both spatiotemporal resolution and predictive accuracy. The resulting full-coverage estimates reveal a global terrestrial XCO₂ increase of 2.22 ppm yr⁻¹ over the study period, with markedly larger seasonal amplitudes in the Northern Hemisphere. The high spatiotemporal fidelity captures rapid, fine-scale XCO₂ fluctuations—such as urban–suburban gradients and diurnal evolutions—that remain unresolved by previous coarser datasets. This seamless and high-quality dataset will provide a robust foundation for future global and regional “dual‑carbon” policy implementation and climate-change research. The dataset can be freely accessed at <span><span>https://doi.org/10.11888/Atmos.tpdc.302399</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"117 ","pages":"Article 108146"},"PeriodicalIF":11.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144922451","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":"Redistribution through urban food hubs: A comprehensive sustainability assessment","authors":"Andrea Casson ,&nbsp;Giulia Valentini ,&nbsp;Andrea Rizzuni ,&nbsp;Abhishek Dattu Narote ,&nbsp;Giovanni Scotti ,&nbsp;Riccardo Guidetti ,&nbsp;Valentina Giovenzana","doi":"10.1016/j.eiar.2025.108149","DOIUrl":"10.1016/j.eiar.2025.108149","url":null,"abstract":"<div><div>Urban food hubs are a novel operational model for surplus food redistribution, and an increasingly implemented policy instrument to mitigate synergically food waste and food insecurity. However, there is still need to assess comprehensively their sustainability impacts across the environmental, social and economic dimensions. This study focuses on Milan, a frontrunner city in the implementation of innovative food policies, where urban food hubs aim to generate positive impacts in food waste reduction and food insecurity mitigation through a neighborhood-based and quick redistribution model. Methodologically, the study performs a comprehensive, multi-dimensional (environmental, social and economic) sustainability evaluation using life cycle assessment, net economic benefit calculation and social sustainability indicators evaluation. Results show that one food hub offers annual net savings of 107 t of CO₂ equivalent and generates substantial environmental benefits across different environmental dimensions. Robustness checks and sensitivity analyses are carried out considering different degrees of displacement impacting the level of substitution of redistributed products. Regarding the social dimension, one food hub recovers every year approximately 140,000 meals for 3000 beneficiaries, and successfully integrates fresh food (fruit, vegetables, fresh proteins) as key nutritional components. At the same time, the economic value of recovered food is 12.21 times the costs sustained to recover and redistribute it. The results also unpack the environmental impact of each phase of the process, from avoided production until redistribution. These results quantify and provide a framework to assess the environmental, economic and social sustainability of food hubs as an urban food policy instrument.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"117 ","pages":"Article 108149"},"PeriodicalIF":11.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144926136","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":"Provincial P-Electricity CEF accounting and inter-regional coordinated emission reduction in cooperative game theory——Evidence from China (2010–2022)","authors":"Xu Wenbo ,&nbsp;Li Wanyue ,&nbsp;Zhang Xuehua ,&nbsp;Xu He","doi":"10.1016/j.eiar.2025.108152","DOIUrl":"10.1016/j.eiar.2025.108152","url":null,"abstract":"<div><div>In advancing “the dual-control policy on total carbon emissions and carbon emission intensity (abbreviated as the Dual Carbon Control Policy)”, China's power sector faces two major challenges. First, the accounting of carbon emissions per unit of electricity production for regional carbon reduction remains inaccurate, making it difficult to precisely reflect the carbon efficiency of regional electricity production. Second, the presence of spillover effects hinders the implementation of certain effective carbon reduction measures, thereby constraining the overall improvement of carbon efficiency. To address the first challenge, we conduct the provincial electricity carbon emission factor from the production perspective (abbreviated as P-Electricity CEF). To tackle the second challenge, we propose a spatiotemporal agglomeration analysis method that integrates the quadrant method with spatial techniques, aiming to uncover the impact of inter-regional electricity flows and their scale effects on carbon efficiency. Additionally, a spatial econometric model is employed to identify spillover effects and influencing factors. Furthermore, a cooperative game model is constructed to internalize spillover effects, balancing the interests of different stakeholders, and facilitating inter-regional coordinated emission reduction. Empirical results of provincial P-Electricity CEF in China from 2010 to 2022 reveal the following findings: (1) Accounting for the full-account P-Electricity CEF provides a more accurate representation of regional carbon efficiency in the power sector, and better supporting production-side emission reduction efforts. The calculated results are slightly higher than previously published findings but exhibit an overall downward trend, with a decline of approximately 20 %. (2) Scale effects influence variations in electricity production carbon efficiency and show significant spatial agglomeration characteristics. (3) Energy structure, general industrial and commercial electricity price, electricity price for large industry, scale effect, electricity price for residents, and economic level, affect electricity production carbon efficiency, with the first four factors exhibiting significant spillover effects. (4) Achieving inter-regional coordinated emission reduction requires careful consideration of spillover effects, influencing factors, and the balance of multi-party interests, for which a cooperative game approach offers a viable solution.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"117 ","pages":"Article 108152"},"PeriodicalIF":11.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144922450","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":"Approval of transport infrastructure projects and systemic differences in EIA approaches: A comparative study of two central European countries","authors":"Petra Dvořáková ,&nbsp;Lenka Lackóová ,&nbsp;Zdeněk Keken ,&nbsp;Lenka Wimmerová","doi":"10.1016/j.eiar.2025.108145","DOIUrl":"10.1016/j.eiar.2025.108145","url":null,"abstract":"<div><div>Environmental Impact Assessment (EIA) is recognized globally as one of the most effective tools for protecting the environment. However, evaluating the effectiveness of EIAs is constantly at the forefront of the scientific and professional community. This study focused on differences in the approach to the EIA process for motorway projects in two neighbouring countries, Czechia and Slovakia, by analysing key elements of the process, using road ecology as a context. The study found not only differences in the number of proposed mitigation and follow-up monitoring measures, but also significant discrepancies in how these requirements are transferred and integrated across the individual stages of the EIA process. In addition, differences in the approach of experts to the design of mitigation measures and in the participation of the public in the EIA process were confirmed. These results suggest that the quality of the EIA process depends on dynamic feedback between the initial assessment and post-implementation monitoring. Recommendations are made to improve professional practice.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108145"},"PeriodicalIF":11.2,"publicationDate":"2025-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144920099","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":"Database-assisted Social Life Cycle Assessment for innovations: Lessons learnt from application","authors":"Julieta Díez-Hernández ,&nbsp;Israel Carreira-Barral ,&nbsp;Óscar López-de-Foronda ,&nbsp;Sonia Martel-Martín","doi":"10.1016/j.eiar.2025.108151","DOIUrl":"10.1016/j.eiar.2025.108151","url":null,"abstract":"<div><div>The imperative to integrate social impact metrics into early-stage innovation assessments reflects a broader shift toward holistic value creation. This study introduces a novel, database-assisted Social Life Cycle Assessment (S-LCA) framework specifically tailored for emerging, low Technology Readiness Level (TRL) innovations. By adapting conventional S-LCA methodologies to the uncertain and dynamic context of novel technologies, exemplified through a case study on silver nanowire production within the EU-funded DIAGONAL project (GA 953152), our approach offers a pioneering strategy to quantify latent social risks and supply chain ethical dilemmas. In contrast to traditional S-LCA applications aimed at fully scaled products, our innovative method bridges theoretical constructs with practical imperatives by synthesizing generalized datasets with dynamic, context-sensitive variables. Our findings underscore that, while S-LCA can illuminate previously overlooked social risks, static assumptions and overly generic data may inadvertently constrain engagement with vulnerable regions. Consequently, we propose a reimagined role for S-LCA emphasizing methodological adaptability and nuanced stakeholder consideration. This redefined framework not only advances scholarly debate on the operationalization of S-LCA for emerging technologies but also provides practitioners with actionable insights to inform decision-making within innovation ecosystems.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108151"},"PeriodicalIF":11.2,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144917883","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":"Surface urban heat island disparities and the role of urban form across the urban-rural gradient","authors":"Zhou Zhou,&nbsp;Yong Liu","doi":"10.1016/j.eiar.2025.108144","DOIUrl":"10.1016/j.eiar.2025.108144","url":null,"abstract":"<div><div>Urban Heat Island (UHI) poses serious challenges to urban sustainability, energy efficiency, and public health. Despite growing concerns, the interactions across urban-rural zones and the factors driving Surface UHI Intensity (SUHII) remain insufficiently understood. This study investigates SUHII dynamics along urban-rural gradients in 258 Chinese cities using Geographical Convergent Cross Mapping (GCCM) and interpretable machine learning. To capture spatial variations, four zones were defined based on urban land density: urban core, inner urban, suburban, and urban fringe. Results show a clear thermal gradient, with SUHII decreasing from 2.589 °C in the urban core to 1.265 °C at the fringe. Northern cities, especially those in the middle temperate zone, exhibit the highest SUHII in the urban core, reaching up to 3.374 °C. GCCM analysis reveals asymmetric predictive influence: the suburban zone has a cooling influence on the core, while the core's heating effect diminishes with distance. Machine learning analysis highlights that the influence of urban form factors varies along the gradient. Two-dimensional (2D) factors consistently play a more prominent role than three-dimensional (3D) ones. In the inner urban zone, the impervious surface fraction is the most influential factor, with a significantly positive effect. At the fringe, patch density becomes dominant, showing a negative correlation with SUHII. Additionally, building footprint coverage at the fringe has a significantly positive effect on SUHII once it exceeds 6 %. In the urban core, 3D factors are more critical. Average building height begins to reduce SUHII once it surpasses 17 m. Similarly, building volume density exhibits a positive effect up to 17 m³/m², beyond which the influence reverses. These findings underscore the need for zone-specific strategies to mitigate SUHII.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108144"},"PeriodicalIF":11.2,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144917884","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":"Impact of energy transition policy and technology shocks on the coal power workforce and China's economic development","authors":"Yuanke Zhao ,&nbsp;Guoqing Shi ,&nbsp;Chen Yang ,&nbsp;Yiming Zheng ,&nbsp;Shimaa Abdelaziz","doi":"10.1016/j.eiar.2025.108142","DOIUrl":"10.1016/j.eiar.2025.108142","url":null,"abstract":"<div><div>Energy transition presents both challenges and opportunities for the coal power workforce in carbon-intensive industries. This study integrates coal power, renewable energy, and workforce employment transition into a New Keynesian framework by constructing a dynamic stochastic general equilibrium (DSGE) model. The model evaluates the short- and long-term impacts of renewable energy technology (RET), carbon tax policy (CTP), carbon emission reduction technology (CERT), and renewable energy subsidy policy (RESP) on the coal power workforce and macroeconomic performance. Simulation results indicate that, in the short term, improvements in RET increase overall economic output, investment, and inflation, while reducing coal power workforce output, employment, and wages. CTP decreases total output and consumption and raises production costs, with a noticeable time lag in its impact on coal power workforce employment. CERT and RESP reduce coal power workforce output and increase employment in the renewable energy sector. In the long term, energy transition policies and technologies facilitate varying degrees of employment transition within the coal power workforce and promote overall economic development. These findings improve the understanding of how coordinated policy and technological measures can support economic decarbonisation and advance environmental sustainability.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108142"},"PeriodicalIF":11.2,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144914019","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 complex relationship between urbanization and soil erosion by water in China","authors":"Wei Li ,&nbsp;Keke Li ,&nbsp;Jingyu Wang ,&nbsp;Wenxing Yang ,&nbsp;Zhongci Deng ,&nbsp;Yuemin Yang ,&nbsp;Cai Li ,&nbsp;Zhiyi Li ,&nbsp;Zhen Wang","doi":"10.1016/j.eiar.2025.108148","DOIUrl":"10.1016/j.eiar.2025.108148","url":null,"abstract":"<div><div>Urbanization alters land use patterns, reducing soil erosion through surface hardening, while simultaneously increasing erosion due to enhanced agricultural activities and surface disturbance. However, the complex relationship between urbanization and soil erosion remains insufficiently studied. This study uses a system dynamics (SD) model and a future land use simulation (FLUS) model to simulate the land use pattern in China and quantifies the effects of urbanization on soil erosion by integrating the Revised Universal Soil Loss Equation (RUSLE) with a counterfactual non-urbanization scenario analysis. Further, a multiregional input-output analysis (MRIO) is used to investigate the cross-regional effects of urbanization. The findings suggest that urbanization generally reduces soil erosion in most provinces, especially in key agricultural regions and areas highly vulnerable to erosion, such as Liaoning, Jilin, and Sichuan. The reduction is primarily attributed to changes in steep-slope cropland, highlighting the need for targeted management strategies in these areas. Moreover, our study also indicates that provinces with higher economic development indirectly contribute to soil erosion in other provinces due to consumption patterns under the actual and non-urbanization scenarios. Although urbanization mitigated the overall cross-regional impact on erosion in terms of absolute quantity (decreased 14.54 million tonnes), it intensified the erosion inflow of Hunan (1.94 %), Guangdong (3.53 %), and Fujian (2.63 %) from Guangxi and Sichuan. Our research highlights the comprehensive impacts of urbanization on soil erosion, providing new insights on soil erosion prevention from a complex social-ecological system perspective and policy making at national and provincial scales.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108148"},"PeriodicalIF":11.2,"publicationDate":"2025-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144914020","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":"Incorporating Indigenous perspectives: an impact assessment of renewable energy development on wildlife conservation","authors":"Yingxin Wang ,&nbsp;Jian Sun ,&nbsp;Michael E. Meadows ,&nbsp;Tien Ming Lee","doi":"10.1016/j.eiar.2025.108143","DOIUrl":"10.1016/j.eiar.2025.108143","url":null,"abstract":"<div><div>Transition to renewable energy is crucial for achieving the goal of carbon neutrality for the Tibetan Plateau. However, little is known about the potential impacts of the energy transition on wildlife conservation in the region, especially from the perspective of Indigenous pastoralists. Here, we employ an approach that integrates spatial overlap analysis, household interviews, and localized experiments to assess the impacts of renewable energy development on wildlife from local to regional scales. The results show that current renewable energy infrastructure, including solar and wind farms, rarely overlaps with wildlife distribution, and renewable energy development currently has negligible impacts on wildlife habitats. However, it is likely that original wildlife habitats across large continuous ranges will become fragmented by the increasing use of photovoltaics (PV) and wind farms in the future. Household interviews revealed a striking disparity in the level of concern about the impacts of renewable energy on wildlife between local pastoralists and the results obtained from spatial overlay analyses and site-based empirical assessments. Specially, 65.2 % of local pastoralists concur that renewable energy will damage wildlife habitats,and 65.5 % agree it will impact wildlife migration, which can be attributed to their limited understanding of renewable energy projects and their potential impacts. Random Forest models reveal that factors such as ethnicity, pasture size, and household demographics have a significant influence on regional disparities in pastoralists' attitudes. We recommended a roadmap to integrate policy, action, and research that simultaneously advances wildlife conservation, renewable energy, and socio-economic development. The study advocates the development of management practices promoting the implementation of wildlife-friendly wind and solar farms that are compatible with the perspectives and needs of local pastoralists.</div></div>","PeriodicalId":309,"journal":{"name":"Environmental Impact Assessment Review","volume":"116 ","pages":"Article 108143"},"PeriodicalIF":11.2,"publicationDate":"2025-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144909062","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}