Environmental Impact Assessment Review最新文献_第10页

Environmental challenges in advanced treatment of high-salinity mine water: A life cycle assessment perspective 高矿化度矿井水深度处理的环境挑战：生命周期评价视角

IF 11.2 1区社会学 Q1 ENVIRONMENTAL STUDIES

Environmental Impact Assessment Review

Pub Date : 2025-10-31 DOI: 10.1016/j.eiar.2025.108249

Mengqing Li , Xianfeng Tan , Jianguo Fan , Hongnian Chen , Tianzuo Zhang , Changting Li , Shuo Wang , Jinglan Hong

The treatment of high-salinity mine water (HSMW) is essential to prevent salt dispersion and protect surrounding ecosystems. However, this process involves significant energy and resource consumption, and its potential environmental impacts have not been adequately and systematically quantified. To fill this gap, this study employed a life cycle assessment approach to quantify, compare, and analyze the environmental impacts of two commonly used HSMW treatment processes: a nanofiltration-based process (S-1) and an electrodialysis-based process (S-2). Key contributing processes and substances were subsequently identified. The results indicated that S-1 exhibited lower potential environmental impacts than S-2, particularly in the categories of carcinogens and mineral resource scarcity. Most environmental burdens were concentrated in the fossil resource scarcity category (midpoint level) and resource category (endpoint level), accounting for 49.8 % and 80.2 % of total impacts in S-1, and 35.6 % and 79.3 % in S-2, respectively. Coal, oil, and carbon dioxide emissions were the key contributing substances to the overall environmental impacts. Electricity generation, chemical production, and the direct discharge of treated water were identified as the major contributing processes. Accordingly, three recommendations are proposed to mitigate environmental impacts: promoting the transition from coal-based to renewable power generation, encouraging resource recovery and by-product generation, and implementing classified treatment and graded utilization of HSMW.

高盐矿井水的治理是防止盐扩散和保护周边生态系统的重要手段。然而，这一过程涉及大量的能源和资源消耗，其潜在的环境影响尚未得到充分和系统的量化。为了填补这一空白，本研究采用了生命周期评估方法来量化、比较和分析两种常用的HSMW处理工艺的环境影响：基于纳滤的工艺（S-1）和基于电渗析的工艺（S-2）。随后确定了主要的促进过程和物质。结果表明，S-1的潜在环境影响低于S-2，特别是在致癌物和矿产资源稀缺方面。大部分环境负担集中在化石资源稀缺类别（中点水平）和资源类别（终点水平），分别占S-1和S-2总影响的49.8%和80.2%和35.6%和79.3%。煤、石油和二氧化碳的排放是造成整体环境影响的主要物质。发电、化工生产和处理后的水的直接排放被确定为主要的贡献过程。在此基础上，提出了促进煤炭发电向可再生能源发电过渡、鼓励资源回收和副产品发电、实施水煤化废水分类处理和分级利用等三点建议，以减轻环境影响。

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引用次数: 0

Unveiling the challenges and opportunities of sustainable development goals in China: Untangling the main causal relationships 揭示中国可持续发展目标的挑战与机遇：理清主要因果关系

IF 11.2 1区社会学 Q1 ENVIRONMENTAL STUDIES

Environmental Impact Assessment Review

Pub Date : 2025-10-31 DOI: 10.1016/j.eiar.2025.108246

Ting Zhou , Chunlin Huang , Fanglei Zhong , Xiaoyu Song , Jinliang Hou , Ying Zhang

Accelerating progress toward the Sustainable Development Goals (SDGs) requires a clear understanding of key causal relationships at both national and sub-national levels, which is crucial for identifying key impediments and opportunities to enhance policy coherence across sectors. However, current research on the causal interactions between SDGs and their indicators at sub-national level remains limited. This study first utilizes Multi-spatial Convergence Cross Mapping (MCCM) and network analysis methods to construct causal networks of SDGs and their indicators in China and its 31 provinces from 2000 to 2020. It analyzed the primary causal features of China's SDGs in terms of synergy and trade-off effects, as well as their spatial differences. The results show that, from 2000 to 2020, the causalities among the SDGs followed a 5:2 ratio between synergistic and trade-off effects, establishing a solid foundation for SDGs implementation. In 28 provinces, the main synergistic causality involved SDG4 and SDG17, and the bidirectional causality between them being the key causal feature in 18 provinces. The main trade-off causality across 13 provinces involved SDG12 and SDG15, indicating that trade-off between resource use, ecological protection and other SDGs remained a major challenge in achieving SDGs. Additionally, neighboring provinces exhibited similar causal loop characteristics, and prioritizing high-frequency indicators including SDG4.c.1, SDG17.8.1, SDG4.2.2, SDG9.c.1, SDG4.a.1, and SDG11.7.1 within synergistic loops were key for SDGs development. This study provides comprehensive insights into future development priorities of China and its administrative regions, offering valuable guidance for promoting policy coherence and achieving systematic coordination of the SDGs.

加快实现可持续发展目标的进程需要清楚地了解国家和国家以下各级的主要因果关系，这对于确定加强各部门政策一致性的主要障碍和机会至关重要。然而，目前在次国家层面对可持续发展目标及其指标之间因果关系的研究仍然有限。本研究首先利用多空间收敛交叉映射（MCCM）和网络分析方法构建了2000 - 2020年中国及31个省份可持续发展目标及其指标的因果网络。从协同效应和权衡效应两个方面分析了中国可持续发展目标的主要因果特征及其空间差异。结果表明，从2000年到2020年，可持续发展目标之间的因果关系在协同效应和权衡效应之间的比例为5:2，为可持续发展目标的实施奠定了坚实的基础。在28个省份中，主要的协同因果关系涉及SDG4和SDG17，两者之间的双向因果关系是18个省份的关键因果特征。13个省份的主要权衡因果关系涉及可持续发展目标12和可持续发展目标15，表明资源利用、生态保护和其他可持续发展目标之间的权衡仍然是实现可持续发展目标的主要挑战。此外，邻近省份表现出类似的因果循环特征，并优先考虑包括SDG4.c在内的高频指标。1、SDG17.8.1, SDG4.2.2, SDG9.c。1, SDG4.a。协同循环内的SDG11.7.1是可持续发展目标实现的关键。本研究对中国及其行政区域未来的发展重点提供了全面的见解，为促进政策一致性和实现可持续发展目标的系统协调提供了有价值的指导。

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引用次数: 0

Achieving the synergy of health improvements and carbon emission reductions: can food price subsidy policies work in China? 实现健康改善与碳减排的协同效应：食品价格补贴政策在中国能否奏效？

IF 11.2 1区社会学 Q1 ENVIRONMENTAL STUDIES

Environmental Impact Assessment Review

Pub Date : 2025-10-30 DOI: 10.1016/j.eiar.2025.108240

Shuang Yuan , Yu Wang , Lei Li , Mengtian Xue , Yuandong Zhao , Qiran Zhao , Shenggen Fan

Current dietary patterns in China pose challenges to both public health and environmental sustainability. Food price subsidies are widely recognized as effective tools to improve dietary quality, yet their environmental implications remain underexplored. Using household data from the Urban Household Survey (UHS, 2015) and the Fixed Observation Rural Survey (FORS, 2015 and 2021), this study estimates the price elasticities of 11 food categories with an EWL-QUAIDS model, and further evaluates the health and environmental effects of six targeted subsidy scenarios. Net changes in carbon emissions and DALYs are assessed by incorporating substitution and complementary effects captured by cross-price elasticities. Three policy optimization schemes are proposed: health-oriented, environment-oriented, and synergistic co-benefit schemes. The simulation results show that food subsidies in urban households fail to achieve synergistic co-benefits, whereas in rural households, soybean subsidies emerge as the only scenario delivering both health and environmental gains, with estimated health, carbon, and net benefits ranging from 0.21 to 15.51 CNY/capital/year under subsidy rates of 5 % to 50 % (e.g., 7.68, 0.95, and 8.55 CNY, respectively, at a 25 % subsidy rate). Subgroup analysis across household clusters confirms the broad applicability of the findings. Further simulations of 15 paired-subsidy scenarios indicate that combinations involving soybeans consistently play a central role in generating joint benefits in rural areas. These findings highlight the importance of explicitly integrating environmental considerations into food subsidy policies, adopt differentiated urban–rural strategies, and promoting targeted subsidies, particularly in rural areas, where soybean foods show strong potential to achieve synergistic health and environmental benefits and accelerate sustainable food system transitions.

中国目前的饮食模式对公众健康和环境可持续性都构成了挑战。食品价格补贴被广泛认为是改善膳食质量的有效工具，但其对环境的影响仍未得到充分探讨。本研究利用城市住户调查（UHS, 2015）和固定观察农村调查（FORS， 2015和2021）的住户数据，利用EWL-QUAIDS模型估计了11种食品类别的价格弹性，并进一步评估了6种定向补贴情景的健康和环境影响。碳排放和DALYs的净变化是通过纳入交叉价格弹性所捕获的替代和互补效应来评估的。提出了以健康为导向、以环境为导向、以协同效益为导向的三种政策优化方案。模拟结果表明，城市家庭的粮食补贴无法实现协同协同效益，而在农村家庭中，大豆补贴是唯一能够同时实现健康和环境效益的方案，在补贴率为5%至50%的情况下，健康、碳和净效益的估计范围为0.21至15.51元/资本/年（例如，在补贴率为25%的情况下，分别为7.68元、0.95元和8.55元）。跨家庭集群的亚组分析证实了研究结果的广泛适用性。对15种配对补贴情景的进一步模拟表明，涉及大豆的组合在农村地区产生共同效益方面始终发挥着核心作用。这些发现强调了将环境因素明确纳入食品补贴政策的重要性，采取差异化的城乡战略，并促进有针对性的补贴，特别是在农村地区，大豆食品显示出实现健康和环境协同效益的巨大潜力，并加速可持续粮食系统转型。

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引用次数: 0

Integrating participatory GIS, remote sensing, and explainable machine learning to assess forest provisioning services 整合参与式地理信息系统、遥感和可解释的机器学习来评估森林供应服务

IF 11.2 1区社会学 Q1 ENVIRONMENTAL STUDIES

Environmental Impact Assessment Review

Pub Date : 2025-10-30 DOI: 10.1016/j.eiar.2025.108245

Kamaldeen Mohammed , Daniel Kpienbaareh , Rachel Bezner Kerr , Jinfei Wang , Isaac Luginaah , Esther Lupafya , Laifolo Dakishoni , Mwapi Mkandawire

Forests play a vital role in supporting rural livelihoods by providing essential resources such as food, fuelwood, and medicine. Ensuring the sustainable utilization of these resources while balancing environmental protection requires a data-driven approach that integrates advanced technologies and local knowledge to inform forest management. This study synthesizes data from Participatory Geographic Information System (PGIS) of 66 forest plots and 1864 trees, multisource remote sensing (i.e., radar and optical) and explainable machine learning to assess forest provisioning supply for community forests management. Key findings from the inventory include the multifunctional roles of trees for medicinal, food and culinary uses. Vegetation Indices such as Transformed Soil Adjusted Vegetation Index (TSAVI) and Normalized Difference Index 45 (NDI45) were identified as useful predictors of forest provisioning supply, capturing essential attributes of vegetation dynamics using random forest (R² = 0.76, RMSE = 4.51). Radar-derived texture metrics were equally relevant and can be especially useful under challenging climatic conditions, such as persistent cloud covers. The Shapley Additive Explanations (SHAP) and Partial Dependence Plots (PDP) revealed threshold relationships between Sentinel-2 indices and forest provisioning, with notable thresholds observed at NDI45 = 0.3 and TSAVI = 0.59. These thresholds signal possible ecological tipping points associated with forest health and productivity. Also, Independent Conditional Expectations (ICE) and Locally Interpretable Model-agnostic Explanations (LIME) provided site-specific explanations on the association between remote sensing indices and forests provisioning capacity, underscoring the spatial heterogeneity of forest ecosystems. The study fills an important research gap by providing a framework that integrates interpretable and explainable modelling with participatory geospatial methods, aiming to inform community-based forests management and support data-driven landscape and site-specific forest ecosystem management in the Miombo woodlands.

森林通过提供粮食、薪材和药品等基本资源，在支持农村生计方面发挥着至关重要的作用。在平衡环境保护的同时确保这些资源的可持续利用，需要采用数据驱动的方法，将先进技术和当地知识结合起来，为森林管理提供信息。本研究综合了参与式地理信息系统（PGIS）的66个森林样地和1864棵树的数据，多源遥感（即雷达和光学）和可解释的机器学习，以评估社区森林管理的森林供应。该清单的主要发现包括树木在药用、食品和烹饪方面的多功能作用。植被指数如转化土壤调整植被指数（TSAVI）和归一化差异指数45 （NDI45）被认为是森林供应供应的有效预测因子，它们捕捉了随机森林植被动态的基本属性（R2 = 0.76, RMSE = 4.51）。雷达衍生的纹理指标同样相关，在具有挑战性的气候条件下尤其有用，例如持续的云层覆盖。Shapley加性解释（SHAP）和部分依赖图（PDP）揭示了Sentinel-2指数与森林供应之间的阈值关系，在NDI45 = 0.3和TSAVI = 0.59处存在显著阈值。这些阈值标志着与森林健康和生产力有关的可能的生态临界点。此外，独立条件期望（ICE）和局部可解释模型不可知解释（LIME）为遥感指数与森林供应能力之间的关联提供了特定地点的解释，强调了森林生态系统的空间异质性。该研究提供了一个框架，将可解释和可解释的模型与参与式地理空间方法相结合，填补了一个重要的研究空白，旨在为基于社区的森林管理提供信息，并支持Miombo林地数据驱动的景观和特定地点的森林生态系统管理。

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引用次数: 0

Unlocking key industrial CCUS potential at county-level: a triad of county-focused source-sink matching methods 释放县域关键产业CCUS潜力：以县域为重点的源汇匹配方法

IF 11.2 1区社会学 Q1 ENVIRONMENTAL STUDIES

Environmental Impact Assessment Review

Pub Date : 2025-10-30 DOI: 10.1016/j.eiar.2025.108236

Xiaojuan Xiang , Shiyu Zhou , Yue Yao , Kai Li , Xian Zhang , Jing-Li Fan

Carbon capture, utilization, and storage (CCUS) is critical for deep decarbonization of the fossil energy sector, but its feasibility depends on spatial matching between carbon emission sources and storage sinks. High-resolution administrative-level CCUS deployment planning is currently lacking in existing studies, particularly regarding detailed county-level analyses. To address this gap, this study develops three novel county-focused CCUS source-sink matching methods that integrate 1267 carbon emission counties (including 2858 multi-industry facilities) with 649 onshore storage counties and 661 offshore 40 km × 40 km storage sites in China. Using these methods, county-level CCUS mitigation potential and spatial layout were quantified across three deployment tiers: in-situ, cross-county, and offshore storage. Results reveal a significant spatial mismatch between sources and sinks in China, limiting CCUS viability to 533 counties. Three-tier strategies can supply 36.15 GtCO₂ cumulative mitigation during 2030–2060, about 2.9 times China's energy-related CO₂ emissions in 2024. Contributions from in-situ, cross-county, and offshore storage are 22.0 %, 37.3 % and 40.7 %, respectively. Notably, in-situ storage counties are widely distributed, mostly concentrated in northern China (75 %), while cross-county cooperation mainly occurs in 140 counties in the North China-Central China-East China junction zone and Northeast China. Offshore storage unlocks additional decarbonization potential for eastern coastal 162 counties. This study provides valuable references for optimizing CCUS deployments in China and offers transferable models other fossil-dependent economies.

碳捕集、利用与封存（CCUS）是实现化石能源行业深度脱碳的关键，但其可行性取决于碳排放源与封存汇之间的空间匹配。目前的研究缺乏高分辨率的行政级别CCUS部署规划，特别是关于详细的县级分析。为了解决这一差距，本研究开发了三种新的以县为中心的CCUS源汇匹配方法，该方法将中国1267个碳排放县（包括2858个多产业设施）与649个陆上储存县和661个海上40公里× 40公里储存地点相结合。使用这些方法，对三个部署层（原位、跨县和海上存储）的县级CCUS缓解潜力和空间布局进行了量化。结果表明，中国CCUS的源汇不匹配，限制了其在533个县域的生存能力。在2030-2060年期间，三层战略可累计缓解36.15亿吨二氧化碳，约为中国2024年能源相关二氧化碳排放量的2.9倍。原位储存、跨县储存和海上储存的贡献分别为22.0%、37.3%和40.7%。值得注意的是，原位储存县分布广泛，主要集中在华北地区（75%），而跨县合作主要发生在华北-华中-华东结合区和东北地区的140个县。海上储存为东部沿海162个县释放了额外的脱碳潜力。该研究为优化CCUS在中国的部署提供了有价值的参考，并为其他依赖化石燃料的经济体提供了可移植的模型。

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引用次数: 0

Impact of sustainable safety climate on poor compliance with personal protective equipment in oil and gas construction projects: quantitative analysis and best sustainable practices 可持续安全气候对石油和天然气建设项目中个人防护装备不合规的影响：定量分析和最佳可持续实践

IF 11.2 1区社会学 Q1 ENVIRONMENTAL STUDIES

Environmental Impact Assessment Review

Pub Date : 2025-10-28 DOI: 10.1016/j.eiar.2025.108211

M.K.S. Al-Mhdawi, Alan O'Connor

The purpose of this paper is to explore the role of Sustainable Safety Climate (SSC) in mitigating the negative impact of poor PPE compliance in the Oil and Gas (O&G) construction industry using fuzzy set theory; and to develop sustainability-driven best practices guidelines for PPE compliance A multi-stage mixed-methods research methodology was adopted in this study for data collection and processing. This included: (1) a focus group session to identify the key SSC dimensions and the key factors contributing to poor PPE compliance; (2) the fuzzy Analytic Hierarchy Process to rank the key SSC dimensions; (3) a questionnaire survey followed by a hierarchical fuzzy-based approach to quantify the level of significance of the poor PPE compliance factors and to examine the mitigating role of SSC in reducing the negative effects of PPE poor compliance; and (4) semi-structured interviews to develop sustainability-driven best practice guidelines for PPE compliance. The study identified 35 contributing factors to poor PPE compliance, grouped into 10 categories, and 11 SSC dimensions. Using a hierarchical fuzzy-based model, the analysis revealed that the three most effective dimensions in mitigating these factors were: the integration of safety and productivity, strategies focused on preventive and resilient risk management, and strong leadership commitment. Among these, leadership commitment showed the highest overall impact, reducing the negative effects of poor compliance by an average of 41.71%. The integration of safety and productivity followed with a 38.69% reduction, while preventive and resilient strategies achieved 38.39%. Each dimension also demonstrated unique strengths. Preventive and resilient approaches were most effective in addressing physical discomfort, reducing factors like PPE weight and bulkiness by 65.10%. Leadership had the greatest influence on logistical-related factors, cutting insufficient PPE availability by 56.91%. Meanwhile, efforts to balance safety with productivity achieved a 53.58% reduction in cultural-related factors, particularly those related to workforce diversity. To this end, this study offers a novel theoretical framework linking SSC to PPE compliance and provides a practical, fuzzy-based decision-making model for safety managers in high-risk industries. The proposed sustainable best practice guidelines offer actionable strategies for integrating ethical governance, peer-led engagement, and long-term safety planning into daily operations. These findings contribute to academic discourse by extending safety climate theory with sustainability principles and offer industry practitioners evidence-based tools to enhance occupational safety in complex construction environments.

本文的目的是利用模糊集理论探讨可持续安全气候（SSC）在减轻石油和天然气（O&；G）建筑行业PPE符合性差的负面影响中的作用；本研究采用多阶段混合方法研究方法进行数据收集和处理。这包括：(1)焦点小组会议，以确定SSC的关键维度和导致PPE符合性差的关键因素；(2)采用模糊层次分析法对SSC关键维度进行排序；(3)采用问卷调查法，运用层次模糊法量化PPE符合性差因素的显著性水平，并考察SSC在减轻PPE符合性差负面影响方面的缓解作用；(4)半结构化访谈，以制定可持续性驱动的PPE合规最佳实践指南。该研究确定了35个导致PPE合规性差的因素，分为10类和11个SSC维度。使用基于层次的模糊模型，分析显示缓解这些因素的三个最有效的维度是：安全和生产力的整合，侧重于预防性和弹性风险管理的战略，以及强有力的领导承诺。其中，领导承诺的整体影响最高，平均减少了41.71%的不良合规带来的负面影响。其次是安全和生产力的整合，减少了38.69%，而预防性和弹性策略则减少了38.39%。每个维度也展示了独特的优势。预防性和弹性方法在解决身体不适方面最有效，将个人防护装备重量和体积等因素减少了65.10%。领导层对后勤相关因素的影响最大，减少了56.91%的个人防护用品供应不足。同时，通过努力平衡安全和生产力，与文化有关的因素，特别是与劳动力多样性有关的因素减少了53.58%。为此，本研究提供了一个新颖的理论框架，将安全责任与PPE符合性联系起来，并为高风险行业的安全管理者提供了一个实用的、基于模糊的决策模型。拟议的可持续最佳实践指南为将道德治理、同行主导的参与和长期安全规划纳入日常运营提供了可操作的策略。这些发现有助于通过将安全气候理论与可持续性原则相结合来扩展学术论述，并为行业从业者提供基于证据的工具来提高复杂建筑环境中的职业安全。

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引用次数: 0

Hidden risks in greening: Unveiling the impact of bare land changes on landscape ecological risks in arid and semi-arid regions of China 绿化的隐患：揭示中国干旱半干旱区裸地变化对景观生态风险的影响

IF 11.2 1区社会学 Q1 ENVIRONMENTAL STUDIES

Environmental Impact Assessment Review

Pub Date : 2025-10-28 DOI: 10.1016/j.eiar.2025.108244

Li Yin , Wei Wei , Hongrui Li , Liming Bo

Ongoing desertification control efforts in China's arid and semi-arid regions (CASAR) have led to the most prominent “greening” worldwide. However, few studies have examined this greening process from the perspective of bare land change (BLC), and fewer have explored whether this positive greening process induces negative landscape ecological risk (LER). This study links BLC to LER by analyzing the interannual variations and structural transitions of BLC using time-series remote sensing data and developing a conflict-disturbance-function framework to assess LER. We further employed the contribution rate and interpretable machine learning models to explore the multidimensional impacts of BLC on LER and proposed an integrated zoning strategy based on BLC intensity and LER clustering patterns. Our results indicate that although both bare land extent and LER exhibited a rise–fall trajectory from 1990 to 2023 under large-scale ecological interventions, intense bare land turnover persisted. While such engineering-driven restoration may be ecologically promising in the long term, it also poses short-term risks of landscape fragmentation and elevated LER. Among all transitions, from bare land to grassland direction had the strongest impact on LER, exhibiting pronounced nonlinearity and spatial heterogeneity. Advancing ecological succession beyond grassland toward more mature ecosystems is essential for stabilizing BLC dynamics and mitigating LER. The zoning strategy combining the BLC and LER trends supports the dual goals of bare land reduction and ecological risk mitigation. Although certain regions exhibit clear improvements, desertification control in CASAR still faces substantial challenges. This study enriches the theoretical framework for BLC–LER interactions, providing a scientific basis for combating desertification in arid and semi-arid regions.

中国干旱半干旱区（CASAR）正在进行的荒漠化治理工作导致了世界上最突出的“绿化”。然而，很少有研究从裸地变化（BLC）的角度来考察这一绿化过程，更少有人探讨这一积极的绿化过程是否会导致负景观生态风险（LER）。本研究利用时序遥感数据分析BLC的年际变化和结构转变，并建立冲突-扰动-函数框架来评估LER，将BLC与LER联系起来。我们进一步利用贡献率和可解释机器学习模型探讨了BLC对LER的多维影响，并提出了基于BLC强度和LER聚类模式的综合分区策略。结果表明，在大规模生态干预下，尽管1990 - 2023年裸地面积和土地利用效率均呈上升-下降趋势，但裸地周转率持续升高。虽然这种工程驱动的恢复从长远来看可能具有生态前景，但它也带来了景观破碎化和LER升高的短期风险。其中，从裸地向草地方向的转变对LER的影响最大，表现出明显的非线性和空间异质性。将生态演替从草地向更成熟的生态系统推进，对于稳定BLC动态和缓解LER至关重要。结合BLC和LER趋势的分区策略支持减少裸露土地和减轻生态风险的双重目标。尽管某些地区取得了明显的进展，但该地区的荒漠化防治仍面临重大挑战。该研究丰富了BLC-LER相互作用的理论框架，为干旱半干旱区防治荒漠化提供了科学依据。

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引用次数: 0

Large-scale analysis of environmental and circularity metrics in construction products through automated data extraction using large language models 通过使用大型语言模型的自动数据提取，对建筑产品中的环境和循环度量进行大规模分析

IF 11.2 1区社会学 Q1 ENVIRONMENTAL STUDIES

Environmental Impact Assessment Review

Pub Date : 2025-10-27 DOI: 10.1016/j.eiar.2025.108243

Roger Vergés , Kàtia Gaspar , Núria Forcada

The selection of construction products significantly impacts building practices as well as environmental and biodiversity outcomes. However, current Environmental Product Declarations (EPDs) lack standardized circularity metrics and contain highly heterogeneous, manufacturer-dependent data, which severely limits sector-wide assessments and data-driven decision-making. Existing methods fail to systematically extract and structure this fragmented information at scale, creating a critical barrier to benchmarking circularity-related metrics, such as circular origin, dismantlability potential, and end-of-life pathways, and environmental performance across construction products. This study addresses this gap by introducing a novel Large Language Model (LLM)-based approach for the reliable extraction and standardization of data from diverse EPDs. Applying this method to 8463 products reveals three key findings: (i) manufacturers deprioritize circular end-of-life pathways; (ii) environmental and biodiversity impacts vary substantially both within and across product categories based on material composition; and (iii) a “circularity paradox” persists, whereby products sourced circularly often end up in landfills. Methodologically, this research establishes the first scalable procedure for comprehensive benchmarking of circularity-related metrics and environmental performance in construction products. Practically, it identifies critical intervention points including the standardization of circularity and environmental reporting in EPDs, the promotion of digital product passports, and the reinforcement of industrial symbiosis with transformation companies. For policymakers, the results highlight how existing regulatory shortcomings perpetuate linear economic models and obstruct consistent, equitable reporting, highlighting the urgent need for more stringent, standardized disclosure requirements to enable nuanced environmental comparisons.

建筑产品的选择显著影响建筑实践以及环境和生物多样性的结果。然而，目前的环境产品声明（epd）缺乏标准化的循环度量，并且包含高度异构的、依赖于制造商的数据，这严重限制了全行业的评估和数据驱动的决策。现有的方法无法系统地大规模提取和构建这些碎片化的信息，从而对循环相关指标（如循环起源、可拆解性潜力、寿命终止路径和建筑产品的环境绩效）进行基准测试造成了重大障碍。本研究通过引入一种新颖的基于大型语言模型（LLM）的方法来解决这一差距，该方法可以可靠地从不同的epd中提取和标准化数据。将此方法应用于8463种产品，揭示了三个关键发现：(i)制造商不优先考虑循环寿命终止途径；（ii）环境和生物多样性影响在产品类别内部和不同产品类别之间因材料组成而有很大差异；（三）“循环悖论”仍然存在，即循环采购的产品往往最终被填埋。在方法上，本研究为建筑产品的循环相关指标和环境绩效的综合基准建立了第一个可扩展的程序。实际上，它确定了关键的干预点，包括epd循环和环境报告的标准化，数字产品护照的推广，以及加强与转型公司的产业共生。对于政策制定者来说，研究结果凸显了现有的监管缺陷如何使线性经济模型永世不化，并阻碍了一致、公平的报告，凸显了迫切需要更严格、标准化的披露要求，以便进行细致的环境比较。

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引用次数: 0

Forecasting China’s carbon prices using a TVFEMD-DLinear framework incorporating climate policy uncertainty 利用考虑气候政策不确定性的TVFEMD-DLinear框架预测中国碳价格

IF 11.2 1区社会学 Q1 ENVIRONMENTAL STUDIES

Environmental Impact Assessment Review

Pub Date : 2025-10-27 DOI: 10.1016/j.eiar.2025.108242

Haozhen Li , Feng Gao , Na Zuo , Xin Gao , Tianming Shao , Xunzhang Pan

Amid climate policy uncertainty (CPU), accurate carbon price forecasting is crucial for the efficient operation of the emission trading scheme (ETS). Machine learning is one of the most popular data-driven approaches to carbon price forecasting. However, relatively few studies have incorporated CPU into machine learning-based carbon price forecasting for China's ETS. This study integrates China's CPU into a hybrid forecasting framework that combines time-varying filter for empirical mode decomposition (TVFEMD) with the decomposition-linear (DLinear) model. A series of multi-model experiments are designed to examine the effect of CPU in forecasting China's carbon prices and to evaluate the performance of the TVFEMD-DLinear framework. The results indicate that incorporating CPU significantly improves forecasting accuracy. Across all models, experiments with the inclusion of CPU show average reductions of 13 % in MAE and 12 % in RMSE compared to those without CPU. Among all experiments, the proposed TVFEMD-DLinear framework incorporating CPU achieves the best predictive performance, yielding the lowest MAE, MAPE, RMSE, and MSPE, as well as the highest R². Statistical evidence from the Diebold-Mariano test further supports these findings. In addition, sensitivity analyses on hyperparameters and carbon markets confirm the robustness of the proposed framework's predictive performance. This study underscores the necessity of incorporating CPU into carbon price forecasting in China and provides an effective tool for future forecasting efforts.

在气候政策不确定性（CPU）的背景下，准确的碳价格预测对于碳排放交易计划（ETS）的有效运行至关重要。机器学习是碳价格预测中最流行的数据驱动方法之一。然而，相对较少的研究将CPU纳入基于机器学习的碳价格预测中。本研究将中国的CPU整合到一个结合时变滤波器经验模态分解（TVFEMD）和分解-线性（DLinear）模型的混合预测框架中。本文设计了一系列多模型实验来检验CPU在预测中国碳价格中的作用，并评估了TVFEMD-DLinear框架的性能。结果表明，加入CPU显著提高了预测精度。在所有模型中，与没有CPU的模型相比，包含CPU的实验显示MAE平均降低13%，RMSE平均降低12%。在所有实验中，结合CPU的TVFEMD-DLinear框架的预测性能最好，MAE、MAPE、RMSE和MSPE最低，R2最高。来自Diebold-Mariano测试的统计证据进一步支持了这些发现。此外，对超参数和碳市场的敏感性分析证实了所提出框架预测性能的稳健性。本研究强调了将CPU纳入中国碳价格预测的必要性，并为未来的预测工作提供了有效的工具。

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引用次数: 0

Ecological effects and strategies of Spartina alterniflora Loisel. removal in China 互花米草的生态效应与对策。在中国搬迁

IF 11.2 1区社会学 Q1 ENVIRONMENTAL STUDIES

Environmental Impact Assessment Review

Pub Date : 2025-10-24 DOI: 10.1016/j.eiar.2025.108238

Zhanbin Luo , Fu Chen , Xi-En Long , Jing Ma , Jiyou Wei , Yudi Guo , Yanfeng Zhu , Yongjun Yang , Xiaoping Ge , Yanyan Kang , Ming Zou , Lei Liu , Xuyue Pan , Sihua Huang , Lijie Pu

Huge removal projects of Spartina alterniflora Loisel. have recently been carried out in China, which is of great significance for mitigating the biological invasion. However, these removal projects might lead to secondary soil and water loss, short-term biodiversity degradation, and ecosystem imbalance. Based on this perspective, this study synthesized the development timeline, invasion causes, advantages and disadvantages of removal projects, and remediation strategies. The results showed that the development timeline of S. alterniflora has gone through five stages: exploration and experimentation, coastal guardian, positive vs negative, ecological killer, biosecurity reclamation. Due to the high reproductive and favorable external environment of S. alterniflora, it has developed into an invasive species that threatens the coastal ecosystems. Moreover, after large-scale removal projects, it might threaten the ecosystem stability in the short term while promote biodiversity in the long term. During the removal projects, there should be developed in adopting a location-specific management approach, employing diverse approaches alongside ecological restoration, reducing costs by optimizing effectiveness, promoting technological innovation and resource reutilization. This study would provide new perspectives for managing S. alterniflora and the ecological restoration of ecosystems affected by similar invasive species.

互花米草大型清除工程。这对减轻生物入侵具有重要意义。然而，这些清除工程可能导致次生水土流失、短期内生物多样性退化和生态系统失衡。基于这一视角，本研究综合了迁移项目的发展时间、入侵原因、利弊以及修复策略。结果表明，互花草的发展经历了探索与试验、海岸守护者、正面与负面、生态杀手、生物安全围垦五个阶段。由于互花草繁殖力强，外部环境有利，已发展成为威胁沿海生态系统的外来入侵物种。此外，大规模的清除工程可能在短期内威胁生态系统的稳定性，但在长期内促进生物多样性。在搬迁过程中，应坚持因地制宜、因地制宜、因地制宜、因地制宜、因地制宜、因地制宜、因地制宜、因地制宜、因地制宜、因地制宜、因地制宜。该研究将为互花草的管理和受类似入侵物种影响的生态系统的生态恢复提供新的视角。

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引用次数: 0