Journal of Cleaner Production最新文献

{"title":"Battery energy storage system sizing optimization in smart microgrid with virtual energy storage system and behind-the-meter photovoltaic systems","authors":"Dongxiao Wang ,&nbsp;Changhong Xie","doi":"10.1016/j.jclepro.2025.146765","DOIUrl":"10.1016/j.jclepro.2025.146765","url":null,"abstract":"<div><div>With the increase of rooftop photovoltaic (PV) penetration, battery energy storage system (BESS) sizing optimization with risk aversion can keep system stable operation, maximize the operator net profit, and avoid exposure to high risk. Based on time-of-use (TOU) tariff, a two-stage BESS sizing optimization method with risk aversion is presented considering the participation of virtual energy storage system (VESS) in the smart microgrid with behind-the-meter rooftop PV systems. In the first stage, VESS and BESS modelling are established. The netload scenarios are categorized and further reduced to provide fundamental data for BESS sizing, which are disaggregated into PV power generation and load to analyse residential electricity consumption behaviour. In the second stage, the optimal size of BESS is determined through maximizing the operator's net profit considering the risk of netload variability due to the uncertainties of PV and load. The optimal energy resources dispatching strategy is formulated via meeting various constraints in the smart microgrid, where VESS is applied to participate in various demand response programmes based on user requirements. Simulation results show that the proposed method achieves a win-win situation for the operator and residents, and the effectiveness and superiority of proposed method are verified through the comparison experiments. Sensitivity analysis reveals that the optimal BESS size with risk aversion is influenced by TOU tariff, load and PV generation change, and the degree of risk aversion.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"528 ","pages":"Article 146765"},"PeriodicalIF":10.0,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145203340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unlocking nature-based solution potential: Life cycle assessment of groundwater remediation at operating industrial sites","authors":"Han Xu ,&nbsp;Deyi Hou","doi":"10.1016/j.jclepro.2025.146697","DOIUrl":"10.1016/j.jclepro.2025.146697","url":null,"abstract":"<div><div>While life cycle assessment (LCA) has been extensively applied for environmental impact quantification in brownfield remediation, its systematic implementation in guiding groundwater contamination control at operational industrial facilities, where large-scale in-situ remediation is often constrained by ongoing activities, remains less explored. This study seeks to deal with this challenge by conducting a cradle-to-grave LCA of three benzene-contaminated groundwater remediation strategies at an operational industrial site in northeastern China: (1) vertical barriers (VB), (2) pump-and-treat (PT), and (3) a novel nature-based solution (NBS) leveraging phytoremediation with integrated biomass valorization. Results reveal that the baseline NBS scenario (2.63 × 10⁴ kg CO₂-eq, excluding biomass valorization) reduces life cycle greenhouse gas (GHG) emissions by three orders of magnitude compared to traditional VB (1.01 × 10⁷ kg CO₂-eq) and PT (1.44 × 10⁷ kg CO₂-eq) scenarios, showcasing its remarkable sustainability potential. Process-specific optimization pathways, particularly enhanced biomass utilization and carbon storage strategies, further lower GHG emissions to achieve net-positive carbon impacts (−180 kg CO₂-eq/m³ fiber), thus amplifying green sustainability. The LCA also identified critical process contributors for each of these remediation alternatives and proposed targeted optimization strategies to further minimize environmental burdens across life cycle stages. Overall, by bridging material innovation, adaptive wellfield design, biomass valorization, and life cycle carbon quantification, this study provides scientific support, new perspectives and practical approaches to advance green and sustainable remediation for benzene-contaminated groundwater.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"528 ","pages":"Article 146697"},"PeriodicalIF":10.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145195174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Towards circular textiles: Life cycle assessment of homewear produced from regenerative cotton and post-industrial waste versus conventional cotton","authors":"Teresa M. Mata ,&nbsp;Inês Ruge ,&nbsp;Hernâni Dias ,&nbsp;Isabel Batista ,&nbsp;Tércio Pinto ,&nbsp;Ricardo Figueiredo ,&nbsp;Alberto Figueiredo ,&nbsp;António A. Martins","doi":"10.1016/j.jclepro.2025.146738","DOIUrl":"10.1016/j.jclepro.2025.146738","url":null,"abstract":"<div><div>The textile industry is a major contributor to global and local environmental impacts, particularly due to high water consumption, greenhouse gas emissions, and land use. These impacts are driven by several factors, most notably cotton cultivation and energy-intensive processes such as spinning and dyeing. To address these sustainability challenges, the Life Cycle Assessment (LCA) methodology provides a comprehensive framework for evaluating products and processes in the textile sector. In this study, LCA is applied to assess the environmental performance of a homewear set produced from a yarn blend consisting of 30 % recycled post-industrial cellulosic waste and 70 % virgin cotton sourced from regenerative agriculture. A comparative analysis was conducted with a similar homewear set composed entirely of conventional cotton, globally sourced and dyed using traditional methods, to assess the potential benefits of using more sustainable materials. The functional unit (FU) is defined as one medium-sized homewear set, consisting of a sweatshirt and pants. The life cycle inventory was primarily based on primary data gathered directly from the manufacturer's supply chain, complemented with secondary data from the literature and recognized databases where necessary. Overall, primary data covered approximately 90 % of the product system. Environmental impacts were assessed using the ReCiPe 2016 (v1.03) method at the midpoint level under the egalitarian perspective, focusing on seven impact categories relevant to the textile sector. Results show that cotton cultivation is the most impactful life cycle stage, contributing 32.0 % to climate change, 92.5 % to water consumption, and 33.9 % to land use. Other significant contributors include knit finishing processes (24.1 % of climate change impact) and spinning (18.9 % of climate change). The homewear set incorporating recycled and regenerative materials demonstrated a 53.9 % lower climate change impact compared to the conventional alternative, increasing to 81.5 % when carbon offsetting in the cotton cultivation stage was considered. Water consumption decreased substantially, from 4.66 m³/FU to 1.54 m³/FU. Despite these improvements, further efforts are needed to reduce fossil energy use and mitigate ecotoxicity. These findings highlight the potential of incorporating recycled content, regenerative agricultural practices, and renewable energy to reduce the environmental footprint of textile products while maintaining quality, thereby supporting sustainability goals and guiding future research and development in sustainable textile production.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"528 ","pages":"Article 146738"},"PeriodicalIF":10.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183419","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A sustainable flow electrode capacitive deionization approach for efficient decontamination and uranium recovery from strongly acidic mining wastewater","authors":"Zhipeng Tang ,&nbsp;Yongmei Li ,&nbsp;Kaixuan Tan ,&nbsp;Chunguang Li ,&nbsp;Zhenzhong Liu ,&nbsp;Chong Zhang ,&nbsp;Haiwei Shi ,&nbsp;Le Ouyang ,&nbsp;Longcheng Liu","doi":"10.1016/j.jclepro.2025.146724","DOIUrl":"10.1016/j.jclepro.2025.146724","url":null,"abstract":"<div><div>The effective removal and recovery of uranium (U) from mining wastewater is of vital importance for environmental protection and the sustainable development of nuclear power industry. In this study, we applied flow electrode capacitive deionization (FCDI) to the treatment of uranium-contaminated groundwater generated after acid in-situ leaching (AISL). While FCDI has been previously explored for nutrient and heavy metal removal, as well as preliminary uranium extraction, this work uniquely demonstrates its effectiveness in strongly acidic, sulfate-rich mining wastewater, achieving &gt;95 % uranium removal and &gt;80 % recovery under optimal conditions. Theoretical calculations and experimental results reveal that U and coexisting ions in feedwater migrate rapidly to the cathode and anode during charging. UO₂²⁺ is electrochemically reduced to insoluble UO₂ on the carbon particles in the cathode, while UO₂(SO₄)₂²⁻ is decomposed into UO₂(SO₄) or UO₂²⁺ and SO₄²⁻ in the anode. After polarity reversal, the coexisting ions quickly transport into the spacer, while uranium is trapped in the cathode and anode, enabling selective uranium recovery. Long-term cycling tests using real mining wastewater confirms the FCDI system's high stability and material durability over 12 charging-discharging cycles. This study demonstrates FCDI as a promising technology for simultaneous uranium remediation and resource recovery from strongly acidic groundwater.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"528 ","pages":"Article 146724"},"PeriodicalIF":10.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Aquaponics and the crossroads of profitability and sustainability viewed through sensitivity and risk modeling","authors":"Victor Lobanov ,&nbsp;Joe Pate ,&nbsp;François Latrille ,&nbsp;Alyssa Joyce","doi":"10.1016/j.jclepro.2025.146674","DOIUrl":"10.1016/j.jclepro.2025.146674","url":null,"abstract":"<div><div>Aquaponics integrates aquaculture effluent with hydroponic crop production, offering a resource- and water-efficient alternative to conventional agriculture. However, its economic viability remains contested, with many commercial operations having short lifespans. This study develops a financial modelling framework to evaluate aquaponics profitability and sustainability by analyzing the sensitivity of Net Present Value (NPV) and Internal Rate of Return (IRR) to variations in aquaculture, hydroponics, and facility operational parameters. A 73-parameter financial model was built. Sensitivity and elasticity analyses ranked parameters by their influence on NPV and IRR over realistic ranges. Monte Carlo simulations estimated the likelihood of positive returns, while Latin Hypercube Sampling of truncated normal distributions identified parameter combinations yielding optimal outcomes. Life Cycle Analysis (LCA) and Green Asset Ratio (GAR) were applied to assess environmental impacts and eligibility for sustainable financing.</div><div>Labor, managerial efficiency, production yield and market price were dominant profitability drivers; plant revenues influenced profitability more than fish. The mean five-year NPV was −21,991 ± 54,800 $USD; IRR was 4.8 ± 12.2 %, with only ∼25 % of simulations yielding positive values. The high variability suggests persistent operational vulnerability. LCA showed electricity as the largest contributor to GWP (∼20,000 kg CO₂-eq y⁻¹ median) followed by infrastructure maintenance. Moreover, the profile of profitable scenarios diverged from non-profitable ones. GAR scores ranged from 46 to 94 %, indicating suitability for EU green-finance instruments to buffer risk. This stochastic modelling approach enables researchers to target parameters for optimization, operators to address process constraints, and investors to assess risk–return trade-offs. Applied here to aquaponics, the methodology is transferable to other circular systems as a risk assessment tool.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"528 ","pages":"Article 146674"},"PeriodicalIF":10.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Forecasting high-resolution PM2.5 concentrations in southeastern China by combining high-resolution satellite data and numerical simulation with machine learning","authors":"Zeyue Li ,&nbsp;Yang Liu ,&nbsp;Jianzhao Bi ,&nbsp;Xuefei Hu","doi":"10.1016/j.jclepro.2025.146759","DOIUrl":"10.1016/j.jclepro.2025.146759","url":null,"abstract":"<div><div>PM_2.5 is a significant air contaminant that presents a serious risk to human health. Accurate PM_2.5 forecasts with high spatial resolution are essential for decision-makers to implement effective mitigation strategies and prevent harmful public exposure to PM_2.5. Current methods often rely on spatial data of limited precision, like outputs from spatial interpolation and chemical transport models (CTMs), resulting in PM_2.5 forecasts that either have inaccurate spatial patterns or completely omit spatial details. For this research, we developed a novel approach to demonstrate the feasibility of employing 1 km satellite AOD data to generate 1 km resolution PM_2.5 forecasts in southeastern China up to five days in advance by integrating machine learning models, CTM simulations, and 1 km resolution satellite AOD measurements. Our forecast framework integrated with satellite AOD data demonstrated superior performance, surpassing the precision of the original CTM forecast data, as evidenced by both spatial cross-validation and overall validation results. In addition, incorporating satellite AOD into the forecasting model could enhance the spatial resolution of PM_2.5 forecasts. The model enables the production of PM_2.5 forecasts featuring both accurate spatial representation and high spatial resolution.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"528 ","pages":"Article 146759"},"PeriodicalIF":10.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145195399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phosphorus availability-leaching trade-offs under long-term organic substitution: Synergistic microbial activation and adsorption capacity decline","authors":"Yinjie Zhang ,&nbsp;Wei Gao ,&nbsp;Shaowen Huang ,&nbsp;Chenyang Li ,&nbsp;Lantao Li ,&nbsp;Jiwei Tang ,&nbsp;Mingyue Li ,&nbsp;Peipei Li ,&nbsp;Yilun Wang ,&nbsp;Chao Ai","doi":"10.1016/j.jclepro.2025.146744","DOIUrl":"10.1016/j.jclepro.2025.146744","url":null,"abstract":"<div><div>Partial substitution of chemical fertilizers with manure enhances soil phosphorus (P) availability; yet, the trade-off between P supply and leaching risks under varying substitution rates remains unclear, particularly with regard to microbial-driven P transformation and soil P retention capacity. Here, we combined ³¹P NMR, sequential extraction, and microbiology techniques in a 15-years field experiment with an in-situ lysimeter to investigate P dynamics. Five treatments were applied: no N input (NoN), only chemical NPK (CN), and manure substitution for chemical N at 25 % (CNM1), 50 % (CNM2), and 75 % (CNM3), with equal NPK amounts. Compared to CN, manure substitution significantly increased the vegetable yield and P uptake, 15-year average yields of tomato and celery increased by 6.7 %–12.7 % and 10.5 %–15.4 %. Compared with NoN and CN, manure substitution increased the contents of soil labile and moderately labile P, orthophosphate monoesters and diesters, microbial biomass C and P, and alkaline phosphatase activity in both the tomato and celery seasons. CNM3 increased soil <em>phoD</em> and <em>Bradyrhizobium</em> abundance<em>,</em> sharply decreased P adsorption capacity, and increased total P leaching by 20.5 %–23.7 %, while CNM2 resulted in higher complexity and connectivity of <em>phoD</em>-harboring microbial networks and significantly decreased P leaching by 6.3 %–30 %. Manure substitution enhanced labile P by decreasing soil pH, promoting organic C accumulation, and upregulating the <em>phoD</em> gene. High manure substitution exacerbated P leaching predominantly by reducing P adsorption capacity and stimulating microbial mineralization of organic P. These findings provide new insights into understanding the roles of organic substitute strategies in soil P dynamics, and moderate amount substitution (≤50 %) enhances P availability while mitigating leaching, providing a critical strategy for sustainable P management.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"528 ","pages":"Article 146744"},"PeriodicalIF":10.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145195177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Bayesian network-based bi-level multi-objective programming model for uncertainty agricultural water management and allocation optimization","authors":"Lingzi Wang ,&nbsp;Rengui Jiang ,&nbsp;Yong Zhao ,&nbsp;Jiancang Xie ,&nbsp;Xiao Zhang ,&nbsp;Ganggang Zuo ,&nbsp;Simin Wang ,&nbsp;Xixi Lu","doi":"10.1016/j.jclepro.2025.146734","DOIUrl":"10.1016/j.jclepro.2025.146734","url":null,"abstract":"<div><div>Water resource management in irrigation districts is of pivotal importance for safeguarding agricultural production, promoting regional economic development, and maintaining social stability. The development of a scientific and reasonable water allocation model has emerged as a pivotal research area in the context of sustainable development of irrigation districts, particularly in the context of climate change. This study explores the use of a combination of methodologies for agricultural water management under uncertainty conditions, including Bayesian network, interval parameter programming, and a bi-level multi-objective programming model approach. The Bayesian network has been demonstrated to quantify the nonlinear effects of precipitation, temperature, evaporation, and other factors on water diversion. The bi-level multi-objective programming model is designed to balance economic efficiency and social equity between the macro and micro decision-making levels. A case study conducted in Jiaokou Irrigation District, Shaanxi Province of China, demonstrated the adaptability of the model under different scenarios. The findings indicate that the aggregate benefits of the irrigation district under the normal scenario can amount to 3.30 × 10⁹ yuan. The fluctuation in the mean value of water diversion is less than about 15 %. The Gini coefficient is maintained within the range of 0.02–0.29. This study rationally and dynamically allocates water resources through multi-model coupling, achieving scientific management of agricultural water resources. It offers novel concepts and specialized technical assistance for the harmonized implementation of the Sustainable Development Goals at the irrigation district level, with the objective of addressing the progressively intricate challenges posed by water scarcity and uncertainty.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"528 ","pages":"Article 146734"},"PeriodicalIF":10.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An integrated biorefinery approach based on spent coffee grounds valorization","authors":"Antonio M. Pérez-Merchán ,&nbsp;Ramón Moreno-Tost ,&nbsp;Irene Malpartida-García ,&nbsp;Cristina García-Sancho ,&nbsp;Josefa M. Mérida-Robles ,&nbsp;Pedro Maireles-Torres","doi":"10.1016/j.jclepro.2025.146716","DOIUrl":"10.1016/j.jclepro.2025.146716","url":null,"abstract":"<div><div>Spent coffee grounds (SCGs) are an abundant lignocellulosic biomass with significant potential for industrial valorization, with great social and environmental benefits, due to their rich composition in cellulose, hemicellulose and lignin. In this study, the organosolv process, a method widely used in the paper industry, was employed to efficiently fractionate SCGs into their primary components. Hemicellulosic liquors containing up to 25 wt% sugars, predominantly galactose and mannose, were successfully extracted and subsequently dehydrated to produce 5-hydroxymethylfurfural (5-HMF), reaching a maximum yield of 90 % within 15 min of reaction time. The residual cellulose and lignin fractions were characterized by X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR), confirming their effective separation. These findings highlight the viability of SCGs as a sustainable feedstock for biorefinery applications, contributing to waste valorization and the development of a circular economy.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"528 ","pages":"Article 146716"},"PeriodicalIF":10.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145195175","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impacts of multiple climate factors and vegetation changes on evapotranspiration in southwest China from 1982 to 2018","authors":"Yanjun Wang ,&nbsp;Xiaorong Huang ,&nbsp;Yi Ao","doi":"10.1016/j.jclepro.2025.146741","DOIUrl":"10.1016/j.jclepro.2025.146741","url":null,"abstract":"<div><div>Evapotranspiration (<em>ET</em>), as an essential element of the global water cycle, serves as a crucial connection for the transfer of water, carbon, and energy between the land biosphere and the atmosphere. This research concentrated on the dynamic variations in <em>ET</em> over 1982–2018 in Southwest China (SWC), investigating the driving mechanisms behind <em>ET</em> changes, particularly climate variability and vegetation dynamics. We selected long-term remote sensing and reanalysis datasets to evaluate <em>ET</em> dynamics in SWC. After validation against eddy covariance observations, the GLASS <em>ET</em> dataset with the highest accuracy was chosen for further analysis. The spatial patterns of <em>ET</em> across SWC and its various geomorphological subdivisions were analyzed. Overall, <em>ET</em> exhibited a north-to-south increasing trend, with more than 80 % of the areas in each geomorphological subdivision showing a significant upward trend in <em>ET</em>. Subsequently, ridge regression was employed to analyze the relative contributions of temperature (<em>T</em>), solar radiation (<em>Rs</em>), specific humidity (<em>H</em>), precipitation (<em>P</em>), wind speed (<em>U</em>), and leaf area index (<em>LAI</em>) to <em>ET</em> variability. <em>T</em> and <em>H</em> were found to be the dominant factors influencing <em>ET</em> changes, with their relative contributions exceeding 20 % during both study periods (1982–1999 and 2000–2018). Furthermore, the dominant drivers of <em>ET</em> changes exhibited phase-dependent variations across different geomorphological subdivisions. Additionally, the relative contribution of vegetation factors (<em>LAI</em>) to <em>ET</em> increased across all subregions. Ridge regression effectively addressed the multicollinearity issue among environmental factors, offering greater stability compared to traditional multiple linear regression. Finally, a double-log elasticity model was used to further quantify and validate the effects of different driving factors on <em>ET</em>, enhancing the credibility of the results. The elasticity coefficient for <em>T</em> was the highest and positive, while the elasticity coefficient for <em>H</em> was the highest and negative. These findings enhance the understanding of <em>ET</em> change mechanisms in SWC and are essential for elucidating regional vegetation-hydrology-climate interactions.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"528 ","pages":"Article 146741"},"PeriodicalIF":10.0,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145183427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}