Journal of Cleaner Production最新文献

{"title":"Recycling of Spent Lithium Nickel Cobalt Manganese Oxides via Sulfuric Acid Roasting: Revealing the Product Evolution Mechanism","authors":"Yuqi Cai, Xin Qu, Fengyin Zhou, Jianye Ma, Muya Cai, DanFeng Wang, Hongya Wang, Jingjing Zhao, Zhiyu Zheng, Dihua Wang, Huayi Yin","doi":"10.1016/j.jclepro.2025.145620","DOIUrl":"https://doi.org/10.1016/j.jclepro.2025.145620","url":null,"abstract":"To mitigate the environmental impacts of spent lithium-ion batteries and enhance the sustainability of relative industry, the recovery of lithium nickel cobalt manganese oxide (LiNi_xCo_yMn_zO₂) cathode materials is of paramount importance. Sulfation roasting is a powerful recycling method of LiNi_xCo_yMn_zO₂ cathode but industrially restricted by the generation of AB₂O₄-type spinel transition metal oxides, sulfides or sulfur oxides (SO_x), and the product formation process (especially of transition metal sulfides) is not well understood. In this paper, we reveal the intermediate reactions and products of the roasting process. We investigate the impacts of sulfide generation on recycling and make certain attempts to eliminate the hazardous side reactions. The temperature and graphite are two key parameters determining the formation of sulfides and the roasting products evolved from sulfates to oxides and then to sulfides with the temperature increasing. Under optimized experimental conditions, we suppress the generation of sulfides and AB₂O₄-type spinel oxides and obtain a Li leaching efficiency of over 98%, minimal SO_x emission and negligible loss of transition metals (less than 3%), achieving the clean and effective recycling of LiNi_xCo_yMn_zO₂ cathode materials.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"56 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143893851","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":"Disentangling gross primary productivity drivers of forested areas in China and its climate zones from 1990 to 2018","authors":"Chenxi Zhu ,&nbsp;Guojie Wang ,&nbsp;Yuhao Shao ,&nbsp;Wen Dai ,&nbsp;Qiang Liu ,&nbsp;Shuangao Wang ,&nbsp;Ana Cristina Costa ,&nbsp;Pedro Cabral","doi":"10.1016/j.jclepro.2025.145616","DOIUrl":"10.1016/j.jclepro.2025.145616","url":null,"abstract":"<div><div>Gross primary productivity plays a critical role in global carbon balance. However, quantifying the effects of different drivers still constitutes a challenge due to the different modeling techniques and data used. This study employs spatiotemporal analysis, machine learning, and statistical approaches to measure the significance of forest gross primary productivity drivers in China and its climate zones from 1990 to 2018. The results show that the annual average forest gross primary productivity in China was 914.74 gC m⁻² y⁻¹ during the study period and showed a significantly increasing trend (<em>p</em> &lt; 0.01) at a rate of 4.09 gC m⁻² y⁻¹. Forest gross primary productivity had a southeast-northwest downward spatiotemporal trend with significantly different distributions within the six climate zones, except in the arid and semi-arid zones. A Random Forest model did better than an eXtreme Gradient Boosting model when 10 explanatory variables were used. These variables included the novel forest fragmentation index and climate zones, which helped explain the effects of forest structure and climate characteristics of the climate zones better. The most important forest gross primary productivity drivers in China were mean annual temperature (26.2 %), mean annual precipitation (18.6 %), solar radiation (11 %), forest fragmentation index (8.8 %), and elevation (8.1 %). Using Chatterjee's correlation coefficient, this study provides, for each climate zone, its unique signature regarding the order and importance of the drivers of forest gross primary productivity. This study helps us understand what factors affect forest gross primary productivity in China and its climate zones better by showing how they work using machine learning. These findings may help China reach its carbon neutrality goals.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"509 ","pages":"Article 145616"},"PeriodicalIF":9.7,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143885021","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":"Geostatistical models, recovery, revalorization and economic potential in mine tailings: a comprehensive bibliometric and systematic review","authors":"Marco A. Cotrina-Teatino,&nbsp;Jairo J. Marquina-Araujo","doi":"10.1016/j.jclepro.2025.145617","DOIUrl":"10.1016/j.jclepro.2025.145617","url":null,"abstract":"<div><div>This study presents a comprehensive bibliometric and systematic review of geostatistical models, recovery, revalorization, and the economic potential of mine tailings, spanning research from 1990 to 2024. Using a mixed methods approach that combines bibliometric analysis, text mining, and content analysis, the review explores the evolution of key topics, identifies major trends, and outlines critical areas for future research. Three primary themes were identified: (1) the application of geostatistical models for evaluating tailings, (2) the recovery and revalorization of minerals from tailings, and (3) the economic potential and mineral concentration models in tailings deposits. The key findings emphasize the necessity of advancing geostatistical modeling techniques, particularly the application of transitive kriging, which has demonstrated significant potential for modeling complex deposits with greater precision. Furthermore, there is a growing interest in the recovery of strategic minerals, such as rare earth elements (REEs) and cobalt, from under-researched tailings, with studies indicating the economic feasibility of reprocessing these materials. Based on these findings, future research should focus on five critical areas: (i) the development of software for transitive kriging in the modelling of complex tailings deposits, (ii) the integration of geological covariates into predictive mineral concentration models, (iii) the exploration of strategic minerals from under-explored tailings, (iv) dynamic economic models for tailings revalorization, and (v) the optimization of advanced concentration technologies for the recovery of precious metals. These insights provide a foundation for advancing sustainable practices and maximizing the economic and environmental value of mine tailings.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"509 ","pages":"Article 145617"},"PeriodicalIF":9.7,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143889758","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":"How “Symbiosis” Influences the Connected Response of Group Purchasing Behavior in Green Housing?","authors":"Qianwen Li, Tingyu Qian, Ruyin Long, Chuanwang Sun","doi":"10.1016/j.jclepro.2025.145608","DOIUrl":"https://doi.org/10.1016/j.jclepro.2025.145608","url":null,"abstract":"Within the framework of the dual-carbon target, it has become imperative to realize the sustainable development of the construction industry. Green housing, as an innovative concept, plays a pivotal role in advancing the emission reduction target by significantly reducing building energy consumption. This study examines the stabilization strategies of individual-group responses to green housing payment behaviors under different scenarios and analyzes four evolutionary game models: individual independent and symbiotic purchases under policy incentives and without policy incentives, to explore consumer acceptance of green housing and symbiosis-driven behaviors that promote the popularity and market expansion of green housing. The results of the study show that the benefits of symbiotic purchasing (including economic and non-economic advantages) exceed independent purchasing regardless of the presence or absence of policy incentives. From a symbiotic perspective, economic incentives can prompt independent individuals to increase their willingness to pay for green housing, thereby accelerating the popularization of green housing. In addition, lowering interpersonal costs accelerates symbiotic purchasing, and incentives further facilitate the process. Additionally, reducing interpersonal costs accelerates the formation of symbiotic purchases, while incentive policies further enhance this process. Based on these conclusions, comprehensive policy recommendations are proposed to promote green housing adoption and ensure sustainable development in the construction industry.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"18 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2025-04-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143889792","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":"Never Forget – The importance of acceptance in the production and introduction of alternative fuels","authors":"Julia Offermann,&nbsp;Linda Engelmann,&nbsp;Martina Ziefle","doi":"10.1016/j.jclepro.2025.145609","DOIUrl":"10.1016/j.jclepro.2025.145609","url":null,"abstract":"<div><div>The increasing emissions in the mobility sector pose a substantial challenge to modern society, with a considerable contribution to climate change. The transportation industry, which is heavily reliant on fossil fuels, is a significant contributor to greenhouse gas emissions, which in turn exacerbates global warming and environmental degradation. It is imperative to address this issue in order to achieve sustainability and reduce the carbon footprint. The production of alternative fuels has the potential to reduce the reliance on conventional fossil energy sources, such as gasoline or diesel, by repurposing carbon dioxide emissions. These innovative fuels offer a sustainable energy solution and help to mitigate the adverse effects of carbon emissions. The acceptance of these fuels by future consumers is a necessary prerequisite for the sustainable adoption and success of such fuels. A substantial number of empirical studies have been conducted in recent years, primarily focusing on a single fuel or its production process in great detail. Nevertheless, a comprehensive overview that compares the acceptance of alternative fuels and their origin, and that investigates different acceptance contexts, influencing factors, as well as relationships and interdependencies, is currently lacking. This paper addresses this research gap by presenting the results of meta-analyses of 25 empirical studies focusing on carbon removal, relevant production routes for alternative fuels, and different fuel types. The findings from these studies demonstrate that the context exerts a significant influence on the acceptance of these processes. Furthermore, the parameters that influence acceptance vary depending on the context, and the acceptance of these processes can be influenced by the passage of time. The insights also demonstrate that demographic factors are not a determining factor in acceptance. Instead, attitudinal characteristics, particularly risk perception and environmental awareness, influence acceptance in general and acceptance of alternative vehicle fuel in particular. Furthermore, the study has derived relevant acceptance requirements for fuel development, product use, and legislation regarding fuel development and introduction. The insights thus enable the derivation of design and information guidelines, as well as implications for future research on alternative fuels and their production pathways.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"509 ","pages":"Article 145609"},"PeriodicalIF":9.7,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143880844","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":"Cleaner hydrogen production by microwaves: Experimental investigation and comparative assessment","authors":"Dogan Erdemir ,&nbsp;Ibrahim Dincer","doi":"10.1016/j.jclepro.2025.145602","DOIUrl":"10.1016/j.jclepro.2025.145602","url":null,"abstract":"<div><div>Sustainable development goals of the United Nations require cleaner energy solutions and carbon-free fuels. Hydrogen, in this regard, appears to be a unique candidate for all, and its production in a cleaner manner is critically important, which is the prime focus in the present paper. This study focuses on the newly designed experimental investigations into microwave-driven water dissociation for cleaner hydrogen production, specifically exploring the effect of various tungsten-based electrode materials and steam inlet conditions on hydrogen production. The evaluation is conducted in two main sections, assessing hydrogen production at the water dissociation level and the overall system. Some of the key observations include a positive correlation between steam inlet temperature and hydrogen production for all electrode materials, with lanthanated tungsten demonstrating superior performance. When only the water dissociation is considered, lanthanated tungsten electrodes exhibit the most favorable energy consumption, showcasing the minimum energy requirement for hydrogen production. Incorporating the overall energy and exergy efficiencies, the lanthanated tungsten emerges as the top performer, followed by ceriated tungsten, attributed to their superior arc stability. The energy requirement per kg of hydrogen varies from 51.98 kWh/kg to 56.66 kWh/kg for varying steam inlet temperatures from 104 °C to 120 °C. The highest energy and exergy efficiencies are recorded to be 64.1 % and 62.3 %, respectively, for lanthanated tungsten electrodes at 120 °C steam inlet temperature. When all energy inputs (steam generation, preheating, condenser pump, and microwave generator) are considered, the overall energy and exergy efficiencies are found to be 35.1 % and 34.2 %, respectively. The energy needed for 1 kg of hydrogen production is recorded to be 94.87 kWh/kg. Consequently, the lanthanated tungsten electrode stands out as a superior performer, offering valuable implications for advancing microwave hydrogen production technologies.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"509 ","pages":"Article 145602"},"PeriodicalIF":9.7,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143880541","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":"Digitalization in the circular economy: Synergistic impact of big data analytics, green internet of things, and ambidextrous green innovation","authors":"Khalid Mehmood ,&nbsp;Pradeep Kautish ,&nbsp;Md Rashid ,&nbsp;Yatish Joshi ,&nbsp;Yaser Iftikhar","doi":"10.1016/j.jclepro.2025.145610","DOIUrl":"10.1016/j.jclepro.2025.145610","url":null,"abstract":"<div><div>Net-zero goals have prompted the manufacturing sector to rethink strategies for the circular economy and Industry 4.0 (I4.0). Big data analytics (BDA) capabilities and the green internet of things (GIoT) are influential in enhancing green innovations and net-zero performance. Additionally, data-driven lean and green practices have gained significant attention and adoption in real-world operations. Consequently, scholars in the field of operations management have directed their focus towards examining the pivotal role played by advanced information technologies, particularly BDA and GIoT. This study adopts the dynamic capabilities view paradigm to construct the conceptual model and to explore the relationships therein. Samples are sourced from small and medium-sized enterprises (SMEs) within the high-tech manufacturing sector, employing a three-wave time-lagged design. Hypothesis testing is conducted using PROCESS macro, and conclusions are subsequently derived. The study results demonstrate that BDA capabilities and GIoT significantly impact both exploratory and exploitative ambidextrous green innovation. Moreover, data driven lean and green practices (DLGPs) amplify the effect of ambidextrous green innovation on net-zero based green performance (NZGP), underscoring the critical role of merging digital and sustainable practices in enhancing environmental and operational outcomes in the manufacturing sector.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"509 ","pages":"Article 145610"},"PeriodicalIF":9.7,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143885427","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":"Improving gap-filling methods for CH4 fluxes of eddy covariance data by combining marginal distribution sampling and machine learning algorithm over paddy fields","authors":"Linhua Ma, Qianan Yu, Yuanlai Cui, Bo Liu, Wenxiang Tian, Bin Liao, Luguang Liu, Wei Dong, Jie Huang","doi":"10.1016/j.jclepro.2025.145615","DOIUrl":"https://doi.org/10.1016/j.jclepro.2025.145615","url":null,"abstract":"Accurate gap-filling CH₄ fluxes from eddy covariance measurements over paddy fields is important in assessing agriculture carbon balance and greenhouse gas emission and therefore contribute to agriculture cleaner production. However, as a type of highly managed wetland, the mechanisms of CH₄ emission from paddy field are different from those from natural wetlands. This study improved the methods to process CH₄ fluxes data from paddy fields. Adding gross primary production (GPP) into the Moving Point test (MP) method enables it to calculate the threshold of friction velocity (U_c*) in the paddy fields. The order of calculated U_c* for all sites is: TWT (0.27 m s^-1) &gt; MSE (0.20 m s^-1) &gt; CRK (0.12 m s^-1) &gt; HRC (0.11 m s^-1) &gt; RIP (0.10 m s^-1) &gt; HRA (0.09 m s^-1) &gt; NC (0.08 m s^-1) &gt; CAS (0.05 m s^-1). GPP is 2.5 hours ahead of CH₄ fluxes, incorporating the asynchrony phenomenon improves the gap-filling performance at all 8 sites, with the R² increases by 6.3%-16.1%, RMSE decreases by 8.0%-26.8%, MAE decrease by 10.5%-25.2%. Replacing soil moisture condition with the ‘on-off switch’ effect of water table only improves the gap-filling performance at CRK, HRA, HRC, MSE and NC sites, with the R² increase by 7.2%, 8.1%, 10.4%, 3.8%, 7.1%, and the improvement of gap-filling accuracy was positively correlated with times of alternate wetting and drying cycles during the growing season. The gap-filling effect of six machine learning algorithms were in order: Adaboost&gt; XGBoost &gt; RF &gt; BPNN &gt; SVM and KNN, with the MDS method worse than the RF. By solving the uneven distribution of CH₄ fluxes, integrating the MDS method into machine learning algorithm could improve the performance of gap-filling, with R² increased by 0.02-0.06, MAE decreased by 0.13%-7.88%. Overall, the study is benefit for data processing of CH₄ fluxes over paddy fields.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"17 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143880539","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":"CirDEF: Standardised information framework to address the information needs of circularity indicators","authors":"Ravindu Kahandawa ,&nbsp;Ruchini Senarath Jayasinghe ,&nbsp;Kasun Gomis","doi":"10.1016/j.jclepro.2025.145611","DOIUrl":"10.1016/j.jclepro.2025.145611","url":null,"abstract":"<div><div>Circularity indicators are widely used to assess progress toward sustainability through circular economic practices. However, the diverse data requirements for these indicators often result in inconsistencies, overlaps and misinterpretations when evaluating circularity. This study addresses the absence of a unified, standardised approach to defining and applying circularity indicators, by developing a framework, named “CirDEF”. This standardised and holistic information framework supports the varied information needs of circularity indicators across system scales, indicator types, and stakeholder contexts. A systematic literature review was conducted, analysing 75 resources to identify existing circularity indicators. The resulting standardised information framework structured around input, process, and output model incorporated with key attributes such as business, time, dimensional, impact, and performance. This allows for the creation of a holistic platform that can redefine existing circularity indicators and improve decision-making. The framework was validated through expert interviews using face, content, and construct validation methods, to ensure theoretical and practical relevance. CirDEF enables dynamic, context-specific circularity assessments by allowing users to apply any relevant circularity indicators instead of relying on fixed indicators. This adaptability supports real-time decision-making, traceability, and proactive implementation of the circular economy. By resolving ambiguities, overlaps, and the static measurement limitations, CirDEF serves as a comprehensive system that facilitates data-driven decisions and aligns with SDGs. This is the first study of its kind to provide a thorough resource for academics, industry practitioners, and policymakers, enabling a holistic evaluation of circularity indicators through a standardised information framework across various processes and life cycles on a global scale.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"510 ","pages":"Article 145611"},"PeriodicalIF":9.7,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143880840","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 hybrid BWM-DGRA approach for enhancing the resilience and sustainability of the ports","authors":"Sara Valipour Parkouhi ,&nbsp;Hamidreza Fallah Lajimi ,&nbsp;Alireza Arab ,&nbsp;Hadi Rezaei Vandchali","doi":"10.1016/j.jclepro.2025.145588","DOIUrl":"10.1016/j.jclepro.2025.145588","url":null,"abstract":"<div><div>Ports are critical hubs within global logistics networks, playing a pivotal role in international trade by facilitating the flow of goods. Their operations continuously evolve to adapt to shifts in global trade dynamics and changes in related fields, such as shipping. Modern challenges, including increased environmental awareness, pressures of social responsibility, climate change, pandemics, and the need for economically sustainable operations, have significantly impacted port activities and have the potential to disrupt the global economy. To address these challenges, ports must integrate resilience and sustainability approaches that not only mitigate vulnerabilities but also enhance their performance and adaptability. This study aims to present a segmentation model from the approach of resilience and sustainability. The model is applied to assess Iranian ports. Initially, resilience and sustainability attributes were identified through a literature review. Subsequently, expert opinions were used to finalize 9 resilience and 18 sustainability attributes. The weights of these attributes were determined using the Best-Worst Method (BWM). Based on this, \"Flexibility\" was found to be the most important resilience attribute, while \"Loading and Unloading\", \"Pollutant emissions\", and \"Employment rate\" were most important for sustainability. Finally, the ports' positions within the segmentation model were determined using the Grey Dynamic Relational Analysis (DGRA) method. As a result, based on the standard deviation obtained for each port, 14 ports were placed in four segments. In this study, based on the segmentation model, the reason for each port's position in this segmentation model is assessed from the perspectives of resilience and sustainability. Additionally, suggestions are provided for the improvement of these ports based on their position in these two approaches.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"509 ","pages":"Article 145588"},"PeriodicalIF":9.7,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143885022","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}