Journal of Cleaner Production最新文献

{"title":"Resource utilization of red mud with biochar to prepare high-efficiency denitration catalysts","authors":"Bo Song ,&nbsp;Zhenxing Shen ,&nbsp;Zitong Wang ,&nbsp;Guiling Zhou ,&nbsp;Qin Peng ,&nbsp;Hao Fan ,&nbsp;Jia Liu","doi":"10.1016/j.jclepro.2025.145386","DOIUrl":"10.1016/j.jclepro.2025.145386","url":null,"abstract":"<div><div>The preparation of denitration catalyst from red mud is one of the ways to realize high value resource utilization. Currently, the main challenges in preparing denitration catalysts from RM include high calcination temperatures with long durations, complex metal loading processes, and narrow high-efficiency temperature windows. In this study, the denitration catalyst R5B5-450 was prepared using RM and biochar through acidification, grinding, and calcination. This method can effectively improve the above problems. R5B5-450 achieved over 90 % NO conversion within the temperature range of 225–400 °C and demonstrated significant potential for application in treating real coal-fired flue gas. This work provides a reference for the effective utilization and reduction of RM while also contributing to reducing the production cost of denitration catalysts.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"502 ","pages":"Article 145386"},"PeriodicalIF":9.7,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725644","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":"Salinity alters N2O production pathway in lake sediments on the Qinghai–Tibet Plateau","authors":"Jing Wang, Hanxiao Zhang, Peilian Zhang, Xinghui Xia, Yong Liu, Yi Li, Shouliang Huo","doi":"10.1016/j.jclepro.2025.145402","DOIUrl":"https://doi.org/10.1016/j.jclepro.2025.145402","url":null,"abstract":"Qinghai–Tibet Plateau (QTP) with abundant lakes is considered as an important area for nitrous oxide (N₂O) emissions. Although lakes on the plateau occur on a gradient of salinity, how variable salinity affects the N₂O production pathways in natural lakes remains poorly understood, possibly leading to over- or underestimates when predicting N₂O budgets. In this study, we investigated 19 QTP lakes on a salinity gradient (freshwater, saline, hypersaline) to determine the effects of salinity on relative abundances of microbes involved in nitrogen (N) transformation processes, using 16S rRNA gene high-throughput sequencing of lake sediments combined with absolute abundance of functional genes in N₂O metabolism determined by quantitative real-time polymerase chain reaction and N species analyses. Our results revealed nitrogen species and contents varied with differences in salinity. At relatively high salinity, nitrification and assimilatory nitrate reduction were inhibited, whereas dissimilatory nitrate reduction to ammonium and N fixation were stimulated. Abundances of <em>nirK</em> and <em>nirS</em> genes in denitrification indicated nitrifier denitrification encoded by <em>nirK</em> gene was dominant in freshwater lakes, whereas incomplete denitrification encoded by <em>nirS</em> gene was prevalent in hypersaline lakes. The ratio of (<em>nirK</em>+<em>nirS</em>)/<em>nosZ</em> gene abundances implied the N₂O emission potential in hypersaline lakes was greater than that in freshwater lakes. Overall, the results suggest that salinity can alter the N₂O production pathway and affect N₂O emission budgets in lacustrine ecosystems.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"33 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734205","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":"Spatial optimization of manure and fertilizer application strategies to minimize nutrient surpluses and acidification rates in croplands of a typical Chinese county","authors":"Donghao Xu ,&nbsp;Gerard H. Ros ,&nbsp;Qichao Zhu ,&nbsp;Fusuo Zhang ,&nbsp;Wim de Vries","doi":"10.1016/j.jclepro.2025.145401","DOIUrl":"10.1016/j.jclepro.2025.145401","url":null,"abstract":"<div><div>Elevated inputs of mineral nitrogen (N) and phosphorus (P) fertilizer applications increased crop yield but enhanced eutrophication and soil acidification due to nitrate-induced base cation (BC) leaching in China. Increasing inputs of manure counteract soil acidification since it contains BC apart from N and P, but its use may enhance eutrophication by unwanted P accumulation in soils with a high P status. In addition, however, N and P fertilizer inputs can go down by improving management practices, increasing the N and P use efficiency (NUE and PUE). In this study, we assessed spatially explicit optimal manure and N and P fertilizer application rates, by balancing crop N and P demand with their inputs while using attainable NUE values for manure and fertilizer and enhancing PUE values by accounting for the legacy soil P pools, at 151 sites in Qiyang, a typical Chinese agricultural county. We evaluated the impacts on N and P surpluses and soil acidification rates (lime requirements) using the acidification model VSD+ and extrapolated these impacts to county-level. Historical acidification in paddy soils was mainly caused by natural acidification and crop removal, while in upland soils mineral fertilizers dominated the factors controlling acidification. Balancing N and P input with crop demand and recycling all available manure can nearly fulfil the crop P requirements, and reduced N and P fertilizer use by 74 % and 99 %, respectively. The N and P surpluses subsequently declined by 70–90 %, respectively, whereas the organic carbon (C) input increased by 48 % and the soil acidification rates for non-calcareous soils declined by 50 %. Recommendation systems for fertilizer and manure use, combining the flows of C, N, P and base cations are key to counteract soil acidification and substantially reduce environmental impacts while sustaining crop production.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"503 ","pages":"Article 145401"},"PeriodicalIF":9.7,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734202","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimising agri-food supply chains: Managing food waste through harvest and side-stream valorisation","authors":"Marloes Remijnse ,&nbsp;Sonja U.K. Rohmer ,&nbsp;Ahmadreza Marandi ,&nbsp;Tom Van Woensel","doi":"10.1016/j.jclepro.2025.145349","DOIUrl":"10.1016/j.jclepro.2025.145349","url":null,"abstract":"<div><div>The importance of reuse and valorisation as a means to enhance sustainable production practices, by reducing waste streams through the recovery of resources in the chain, is increasingly recognised. Confronted with new challenges in the context of climate change, the food and agricultural sector stands to benefit, in particular, from valorising (edible) side streams, such as unharvested crop parts and vegetable peels, that are often overlooked by consumers. Focusing on side-stream valorisation strategies within food processing facilities, this research develops a mixed-integer optimisation model to support decision-makers in determining an optimal product portfolio and processing configuration. This model is solved for two key performance indicators, considering both the economic and the environmental impact, in the form of total profit and exergy loss. Examining potential trade-offs between the two objectives, we present a real-life case study from a carrot processing company. We explore several scenarios and case settings to investigate the impact of various factors on the potential of side-stream valorisation. The findings from our analysis demonstrate that side-stream valorisation seems to be generally well aligned with profit maximisation, while it is not always beneficial from an environmental impact perspective.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"503 ","pages":"Article 145349"},"PeriodicalIF":9.7,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global smart cities classification using a machine learning approach to evaluating livability, technology, and sustainability performance across key urban indices","authors":"Aya Hasan Alkhereibi ,&nbsp;Rawan Abulibdeh ,&nbsp;Ammar Abulibdeh","doi":"10.1016/j.jclepro.2025.145394","DOIUrl":"10.1016/j.jclepro.2025.145394","url":null,"abstract":"<div><div>Smart cities have become an increasingly important response to urbanization challenges, integrating technology to enhance city infrastructure, services, and sustainability. This study aims to classify the highest 50 global smart cities based on key livability and technology indices, using advanced machine learning (ML) models to assess city performance comprehensively. The necessity of this research lies in its focus on identifying patterns and best practices among high-performing cities, offering actionable insights for urban planners and policymakers aiming to improve smart city initiatives. This approach is necessary for understanding and replicating best practices in urban management and smart city development. Focusing on high-ranking cities ensures the study analyzes robust and reliable data, avoiding noise and inconsistencies arising from lower-performing or less-documented cases. Drawing on data from the Smart Cities Index (SCI) and other economic and sustainability competitiveness metrics, the study uses various ML algorithms to categorize cities into performance classes, ranging from high-achieving Class 1 to emerging Class 3 cities. The methodology involves data preparation with imputation and normalization, followed by training 9 supervised ML models. The results show that Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Decision Tree are identified as the most effective classifiers. Furthermore, the results indicate that cities with well-integrated governance, infrastructure, and sustainability practices consistently rank higher, while cities in the lower classes face challenges in these areas. Policy implications suggest that cities aiming to enhance their smart city performance should prioritize comprehensive urban management strategies that balance technological infrastructure with sustainability and public service accessibility to drive more equitable and resilient urban growth.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"503 ","pages":"Article 145394"},"PeriodicalIF":9.7,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application to smart multi-energy system for supply-demand side management of a building based on power-to-gas-to-power concept: Technical, environmental, and economic assessment","authors":"Amir Ebrahimi-Moghadam, Majid Kheir Abadi, Nima Jafarian Yazdi, Mohammad Sheykhi, Mohammadsadegh Pahlavanzadeh","doi":"10.1016/j.jclepro.2025.145393","DOIUrl":"https://doi.org/10.1016/j.jclepro.2025.145393","url":null,"abstract":"Utilizing new concepts for the production and conversion of energy carriers leads to progress in reaching carbon neutrality targets. Green energy-integrated systems exposed to attention of energy scientists in recent years. In this study, a smart multi-energy system is proposed based on the hybrid utilization of solar and wind resources for producing green hydrogen. The produced green hydrogen is then blended with natural gas and used as an enviro-friendly fuel for internal combustion engine. Afterward, the heating potential of engine’s exhaust and jacket water are recovered to run some equipment for producing extra power, heat, and cold. A powerful techno-economic and environmental framework is developed in EES software to assess the feasibility of the proposed system. Also, to make the modeling even more accurate, the engine is simulated in GT-Power software and its outputs are linked with EES. Furthermore, to make the proposal applicable, a case study hotel building is considered and system’s effectiveness is demonstrated. The building is simulated with a full-detailed model and sustainable architectural elements are also considered in the simulation (green wall and photovoltaic facade). The analyses are done for three models (Model 1: 5 vol.% hydrogen blended into NG, Model 2: 10 vol.% hydrogen blended into NG, Model 3: 100% NG). Analyzing the system illustrated that R123 is identified as the most efficient fluid for ORC with energy and exergy efficiencies of 18.03% and 26.58%, respectively. Also, dynamic modeling results indicated that hybrid utilization of solar/wind ensures a reliable and consistent supply of clean energy, significantly reducing reliance on fossil fuels. So that, 7.05 ton/year of CO₂ emission is prevented by the hydrogen blending (in models 1 and 2) compared to the case where only methane is used as fuel. The payback period of the proposal, based on the discounted NPV approach, is obtained as 4.2 years proving its feasibility.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"18 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734092","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":"Beyond the Buzz: Unravelling the Barriers and Drivers of Electric Car Adoption in India - A Qualitative Study","authors":"Divya Singh, Ujjwal Kanti Paul","doi":"10.1016/j.jclepro.2025.145344","DOIUrl":"https://doi.org/10.1016/j.jclepro.2025.145344","url":null,"abstract":"The adoption of electric cars (ECs) is a potential alternative to internal combustion engine (ICE) cars in pursuit of a sustainable and environment-friendly future. However, the transition to electric mobility is inconsistent due to several challenges that impede the global adoption of EC. There is a tremendous chance of transformation in a developing country like India, where air pollution and escalating energy demands. The main objective of this qualitative study is to explore and identify the critical barriers and drivers <strong>of</strong> EC adoption in India. Twenty-seven in-depth interviews were conducted to gain insights into the Indian mindset and what they perceive and feel about the ECs. The four themes diverged by incorporating the ‘grounded theory’ approach: acceptability, affordability, accessibility, and awareness. This paper shows the importance of understanding the confluence of the marketing mix regarding EC adoption as it delves beyond a surface-level analysis. By examining the stature of EC adoption from a consumer perspective, the study provides insightful implications for automakers, policymakers, academicians, and all stakeholders who seek to advocate the broad usage of EC in India. The key findings reveal significant barriers and drivers under each identified theme influencing consumer behavior, including concerns about charging infrastructure, anxiety, and risk associated with this innovation, as well as the hefty acquisition cost of ECs and low level of awareness. While positive perceptions regarding the environmental benefits of these vehicles exist, trust-building in the technology remains crucial for widespread EC adoption.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"101 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734093","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":"Technological pathway exploration for simultaneous water conservation and carbon reduction for the titanium dioxide manufacturing plant in China","authors":"Yonghao Tan, Yuehong Zhao, Yongbing Xie, Xinhong Chen, Jianbo Zhang, Kui Wang, Hongbin Cao","doi":"10.1016/j.jclepro.2025.145400","DOIUrl":"https://doi.org/10.1016/j.jclepro.2025.145400","url":null,"abstract":"With the increasing global concerns on climate change and water scarcity, titanium dioxide manufacturing plants (TDMP) are facing the challenge of simultaneous water conservation and carbon reduction (SWCCR) in water networks with controllable comprehensive water-use costs. Such complex multi-objective optimization problems are usually studied in steel and petrochemical industries or in the macro region, but very few studies have been devoted to TDMP in the past decade. This paper proposes a novel multi-scale and multi-objective optimization model for the water-carbon-economy nexus specific to TDMP, accompanied by an effective solution methodology. The model was designed to explore the interaction between water conservation and carbon reduction under the condition of keeping controllable comprehensive water-use costs and to find the optimal technological pathway for industrial practice. Then a typical TDMP adopting the sulfuric acid technology was selected as the case study. The findings reveal that the plant can achieve SWCCR by integrating different technological measures to formulate the optimal technological pathway. When the plant put equal weight on water conservation and carbon reduction, the water consumption and carbon emissions were reduced by 8.48% and 21.11% respectively, with a 3.06% increase in comprehensive water-use cost per ton of product (813.55 RMB). Additionally, long-term projections of the optimal technological pathway toward the Carbon Neutrality goal were explored, highlighting the progressive augmentation of reclaimed water utilization. This study pioneers in filling the research gap on SWCCR in water networks with controllable comprehensive water-use costs for TDMP and offers valuable insights, thereby facilitating a greener and low-carbon transformation.","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"27 1","pages":""},"PeriodicalIF":11.1,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734200","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":"Supply chain carbon finance indexing with generative AI and advanced data analytics techniques","authors":"Pratyush Kumar Patro ,&nbsp;Enoch Quaye ,&nbsp;Adolf Acquaye ,&nbsp;Raja Jayaraman ,&nbsp;Khaled Salah","doi":"10.1016/j.jclepro.2025.145387","DOIUrl":"10.1016/j.jclepro.2025.145387","url":null,"abstract":"<div><div>Supply chain carbon finance plays a key role in providing financial incentives, supporting green projects, and promoting decarbonization of supply chains. Progress monitoring of such efforts requires robust indices that track carbon-intensive supply chain operations and assess carbon finance readiness. Current index generation methods use qualitative and optimization models such as AHP, DEA, etc., which introduce biases and overlook model variability and complexity, thereby affecting index reliability. Utilizing advanced Generative Adversarial Networks (GANs) and Principal Component Analysis (PCA), the main goal is to robust supply chain carbon finance index to assess the readiness of countries for carbon financing. Hierarchical cluster analysis is used to group countries, providing better insights for strategic decision-making. The results indicate that China, USA, UK, and India collectively accounting for over 50% of carbon finance needs. This study assesses each country's carbon finance readiness and identifies clusters of countries with similar readiness levels for targeted policy recommendations and tailored interventions. We propose a novel Carbon Finance Contribution Mechanism to decarbonise supply chains and equitably distribute the financial responsibility of emissions reductions between producing and consuming countries. The paper also highlights research opportunities in generative AI and machine learning for creating similar indices in supply chain domains.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"502 ","pages":"Article 145387"},"PeriodicalIF":9.7,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734201","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":"Regional disparities in Africa's renewable energy transition: Patterns and drivers","authors":"Mark Awe Tachega ,&nbsp;Yanjiao Chen ,&nbsp;Junjian Wang ,&nbsp;Pei Yang","doi":"10.1016/j.jclepro.2025.145396","DOIUrl":"10.1016/j.jclepro.2025.145396","url":null,"abstract":"","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"503 ","pages":"Article 145396"},"PeriodicalIF":9.7,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143734199","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}