Journal of Cleaner Production最新文献

{"title":"Expanding discourse and advocating stances: Social bots action strategies in carbon neutrality discussions","authors":"Yan Dongqi ,&nbsp;Ren Wujiong ,&nbsp;Yao Junchen ,&nbsp;Wu Yuduo ,&nbsp;He Yuan ,&nbsp;Hongzhong Zhang","doi":"10.1016/j.jclepro.2026.147591","DOIUrl":"10.1016/j.jclepro.2026.147591","url":null,"abstract":"<div><div>Social bots have become increasingly visible actors in online environmental communication. This study analyzes Twitter communications collected over a three-month period during and after the 27th Conference of the Parties (COP27) to examine the behavioral patterns, emotional dynamics, and interactions among social bots, ordinary human accounts, and media accounts in carbon neutrality discourse. A mixed computational approach combining sentiment analysis, Structural Topic Modeling (STM), and longitudinal time series analysis was employed. Based on the cleaned and categorized dataset, the results show that social bots account for 27.59 % of the total tweets, indicating a substantial presence in carbon neutrality discussions. Compared with ordinary human accounts, social bots rely more heavily on recirculating existing content and exhibit distinct interaction patterns and social network characteristics relative to both human and media accounts. Content generated by social bots is predominantly climate activism oriented (77.81 %) and characterized by slogan-driven messaging, automated amplification, and affective mobilization. In terms of thematic orientation, social bots tend to focus on business-economic related topics, including electric vehicles policies, collaborations and opportunities, as well as carbon neutrality and public opinions. Interactional assessments uncover a tripartite interaction paradigm in which social bots amplify human and media voices, while humans react to bot-promoted topics. This study reveals that social bots not only contribute to, but may also steer the salience of carbon neutrality issues by shaping public discourse and influencing policy agendas.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"544 ","pages":"Article 147591"},"PeriodicalIF":10.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077297","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":"Nonlinear relationships between land surface temperature and influencing factors along the urban–rural gradient from a seasonal–diurnal perspective: A SHAP-based framework in the Gui'an region","authors":"Chuyi Guo ,&nbsp;Yuchi Yang ,&nbsp;Wei Yang","doi":"10.1016/j.jclepro.2026.147634","DOIUrl":"10.1016/j.jclepro.2026.147634","url":null,"abstract":"<div><div>Understanding the spatiotemporal differentiation of land surface temperature (LST) across urban-rural gradients and its complex driving mechanisms is critical for advancing urban thermal dynamics research and informing climate mitigation strategies. However, existing studies focus on linear analyses or singular temporal scales, neglecting the seasonal-diurnal evolution of LST and its nonlinear interactions within diverse topographical conditions. This study investigates the Guiyang-Anshun region, a representative karst terrain area, and develops an analytical framework to explore the driving mechanisms of LST through a “seasonal-diurnal” spatiotemporal perspective. Urban-rural gradient zones are delineated using nighttime light data (NTL) quantile regression, combined with Bayesian-optimized XGBoost models and SHAP to systematically uncover nonlinear driving patterns and spatial interactions. Key findings include: (1) The Gui'an region exhibits obvious urban-rural LST gradients, with urban cores exhibiting significant diurnal temperature differences and intense summer fluctuations, while suburban and rural areas experience smaller fluctuations and greater thermal stability; (2) LST influencing mechanisms display significant temporal variability across seasonal-diurnal scales; (3) The relative importance of factors shifts across the urban-rural gradient zones, with natural factors gaining prominence as urbanization decreases, reflecting a transition from “anthropogenic-driven” to “terrain-ecological control” mechanisms; (4) The influence of factors exhibit notable nonlinear and threshold effects, demonstrating varying effectiveness and response intensities across regions; (5) Interaction analyses reveal that LST variation arise from comprehensive multi-factor coupling interactions, rather than linear superposition of individual variables. This study provides a novel framework for understanding the intricate dynamics of LST and offers practical guidance for sustainable urban planning and climate adaptation.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"544 ","pages":"Article 147634"},"PeriodicalIF":10.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071767","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":"Effect of palladium loading on catalytic performance and product selectivity during diclofenac degradation by Pd0@anaerobic activated sludge","authors":"Xiaodi Li ,&nbsp;Jingzhou Zhou ,&nbsp;Lin Yang ,&nbsp;Si Pang ,&nbsp;Yi Yang ,&nbsp;Defu Gan ,&nbsp;Junxia He ,&nbsp;Penghui Shi ,&nbsp;Siqing Xia","doi":"10.1016/j.jclepro.2026.147676","DOIUrl":"10.1016/j.jclepro.2026.147676","url":null,"abstract":"<div><div>Anaerobic activated sludge (AAS) was used to fabricate a biomass-supported palladium nanocatalyst (Pd⁰@AAS) with varied Pd loading via a green biosynthesis route that eliminates the need for toxic reagents and high energy input. This catalyst was subsequently evaluated for the catalytic degradation of diclofenac (DCF). The degradation pathway was systematically elucidated, focusing on the influence of Pd loading on product selectivity, reaction kinetics, and corresponding ecotoxicological outcomes. Pd⁰@AAS detoxified DCF via two key steps: hydrodechlorination of DCF to 2-anilinophenylacetic acid (APA), followed by aromatic ring hydrogenation of APA. After 4 h, low Pd loading (1.1 wt%) resulted in high selectivity toward APA (89.7 %), whereas high Pd loading (10.6 wt%) promoted complete hydrogenation, reducing APA selectivity to 0 %. Ecotoxicity estimates indicated that hydrodechlorination effectively eliminated acute toxicity, whereas full hydrogenation was required to eliminate chronic toxicity. Kinetic analysis showed that the hydrodechlorination rate constant increased with Pd loading (1.1–10.6 wt%), yet catalyst-specific activity (normalized to Pd concentration) reached a plateau at Pd loading 5.3 wt%, beyond which nanoparticle aggregation limited further enhancement—indicating that higher Pd loadings are economically impractical for dechlorination alone. In contrast, both the reaction rate constant and catalyst-specific activity of hydrogenation increased strongly across the same Pd loading range. The values at 10.6 wt% were 2.7-fold and 30-fold higher than those at 5.3 wt% and 2.7 wt%, respectively. This difference underscores a greater reliance on contiguous Pd⁰ active sites for hydrogenation of aromatic rings. These findings guide the optimization of biomass-supported Pd⁰ nanocatalysts for cost-effective and ecologically safe remediation of halogenated aromatic pollutants.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"544 ","pages":"Article 147676"},"PeriodicalIF":10.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077298","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":"Novel Styrofoam-sludge biochar for Pb and Zn adsorption: Bioavailability and reduction in maize-cultivated contaminated soils","authors":"Muhammad Ubaid Ali ,&nbsp;Mehr Ahmed Mujtaba Munir ,&nbsp;Ruilian Yu ,&nbsp;Gongren Hu ,&nbsp;Balal Yousaf ,&nbsp;Sajid Ali ,&nbsp;Muhammad Adnan ,&nbsp;Cheng Liping ,&nbsp;Xiangliang Pan ,&nbsp;Ming Hung Wong","doi":"10.1016/j.jclepro.2026.147548","DOIUrl":"10.1016/j.jclepro.2026.147548","url":null,"abstract":"<div><div>The present study aimed to evaluate raw and Styrofoam-modified sewage sludge biochar (SSB1-3) for the remediation of Pb(II)- and Zn(II)-contaminated soils. The properties of biochar, such as pH, surface area, porosity, aromaticity, and functional group abundance, were significantly enhanced by co-pyrolysis, along with a reduced input energy and secondary metal contamination. The enhanced properties facilitated synergistic metal immobilization mechanisms, such as cation-π interactions, pH-driven precipitation, surface complexation, ion exchange, and mineral-associated bindings, transforming metals into a more stable form. The metal sequestration and microbial activity increased due to biochar-derived humic-like dissolved organic matter, generating a joint chemical–biological pathway for metals immobilization. The binding of Pb and Zn to DOM, which includes humic and fulvic acid-like components, reduces the bioavailability of these metals in soils, thereby decreasing the extractable fractions of Pb and Zn by forming stable complexes with humic substances. Adsorption kinetics and isotherms revealed fast, spontaneous, and chemisorption-dominated Pb(II) and Zn(II) uptake. Sample SSB3 exhibited the highest sorption capacity due to the enrichment of the reactive sites. Reduced metal bioavailability, limited translocation within the maize plant, and increased plant biomass were the key features observed following SSB3 application. Overall, represents a sustainable and cost-effective amendment, presenting an integrated approach to stabilize heavy metals and improve soil quality in contaminated environments. These results open up prospects for integrating biochar produced from the co-pyrolysis of sewage-sludge and Styrofoam as an environmentally friendly and low-cost adsorbent in the treatment of contaminated soil and/or water to reduce metal toxicity.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"544 ","pages":"Article 147548"},"PeriodicalIF":10.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071102","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":"Machine learning-optimized efficient CO2-to-CO conversion in a novel catalyst-free spark discharge plasma","authors":"Guangdong Yang ,&nbsp;Tao Jiang ,&nbsp;Jing Wen ,&nbsp;Tangxia Yu ,&nbsp;Changqing Li ,&nbsp;Lan Zhang ,&nbsp;Mingze Ma","doi":"10.1016/j.jclepro.2026.147603","DOIUrl":"10.1016/j.jclepro.2026.147603","url":null,"abstract":"<div><div>Catalyst-free spark-discharge plasma offers a promising new route for CO₂ utilization via the reverse water–gas shift (RWGS) reaction, yet strong coupling among power, residence time, composition, and reactor geometry complicates deployment-relevant optimization. An improved coaxial quartz-tube spark-discharge reactor is considered, and a structured dataset of 500 operating points is compiled by varying discharge power, total flow rate, H₂/CO₂ molar ratio, and inner-tube diameter across engineering-relevant levels. To avoid inflated generalization caused by random splits on grid-like datasets, ten regressors are screened using leave-one-condition-out grouped cross-validation, and an artificial neural network (ANN; multilayer perceptron, MLP) surrogate is selected and tuned under the strict leave-one-diameter-out protocol with early stopping. Hyperparameter tuning improves grouped predictive accuracy to R² = 0.909 for CO₂ conversion and R² = 0.970 for energy efficiency. Model credibility is further supported by bootstrap resampling, applicability-domain diagnostics, and external interpolation validation on 15 off-grid points (R² = 0.907 for conversion and 0.959 for efficiency), with most observations captured within the 95 % prediction band. Operating-window maps identify a peak conversion of 89.76 % at 70 W, H₂/CO₂ = 3.0, 200 mL/min and an inner-tube diameter of 7 mm, and a peak energy efficiency of 19.12 % at 40 W, H₂/CO₂ = 1.0, 1000 mL/min and 7 mm, under bench-scale laboratory conditions. Shapley Additive Explanations (SHAP) interpretation provides process-relevant attribution of nonlinear effects and clarifies interaction-driven regime dependence within the validated domain. The resulting workflow enables specification-driven, electricity-aware screening to finalize reactor configuration and operating windows for downstream syngas applications.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"544 ","pages":"Article 147603"},"PeriodicalIF":10.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077207","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":"Thermal and mechanical performance of 3D-printed excavated soil wall solidified by alkali-activated slag","authors":"Jianyu Shen ,&nbsp;Yaofei Cheng ,&nbsp;Jianzhuang Xiao ,&nbsp;Bo Wang ,&nbsp;Shuisheng Li","doi":"10.1016/j.jclepro.2026.147594","DOIUrl":"10.1016/j.jclepro.2026.147594","url":null,"abstract":"<div><div>Wall fabrication is an important approach for achieving high-value utilization of excavated soil (ES). To address the issues of inadequate mechanical performance and durability in conventional earthen walls, this study employs alkali-activated technology and 3D printing techniques to fabricate wall specimens. Four types of 3D-printed soil-based walls (PSW) with different solidification formulations, block configurations, and internal filling conditions were designed. Their mechanical properties were systematically investigated, and their thermal performance as wall materials was validated. The thermal and mechanical properties of PSWs were systematically investigated. Comparative analysis revealed that the actual compressive strength of PSW decreased by 6.2 %–39.0 % compared to 3D-printed mortar walls, yet still satisfies the mechanical requirements for low-rise building structures. The equivalent thermal conductivity of PSW ranged from 0.099 to 0.108 W/(K·m), representing a 14.1 %–21.0 % reduction compared to 3D-printed mortar walls. Structural optimization through inclined rib incorporation reduced thermal conductivity by 17.0 % and improved compressive strength by 6.1 %. Furthermore, cavity filling with insulating materials (e.g., polyurethane foam) achieved a 62.7 % reduction in thermal conductivity, enabling compliance with thermal requirements for severe cold regions. PSW demonstrated significant sustainability advantages, with reductions in cost and carbon emissions by 11.5 %–27.4 % and 72.7 %–80.8 %, respectively. This research demonstrates the technical feasibility and environmental-economic benefits of 3D-printed solidified soil walls, highlighting their potential for sustainable construction applications.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"544 ","pages":"Article 147594"},"PeriodicalIF":10.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077208","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 new cleaner production process: Microstructure, properties and solar power furnace firing mechanism of anorthite ceramic thin plate","authors":"Xiaohong Xu ,&nbsp;Tong Liu ,&nbsp;Jianfeng Wu ,&nbsp;Saixi Qiu ,&nbsp;Yu Zhang ,&nbsp;Ziwei Zhang ,&nbsp;Dong Wang","doi":"10.1016/j.jclepro.2026.147691","DOIUrl":"10.1016/j.jclepro.2026.147691","url":null,"abstract":"<div><div>To address the high energy consumption in traditional ceramic thin plates firing, this study explores for the first time the application of concentrated solar energy in fabricating anorthite ceramics. Using diopside, wollastonite, and α-Al₂O₃ as raw materials with Co₂O₃ as a light absorber, solar firing was compared with electric furnace firing. Results show that solar firing completes firing under low-temperature and short-duration conditions, yielding a sample with a water absorption of 0.10 %, porosity of 0.24 %, bulk density of 2.53 g cm⁻³, bending strength of 94.12 MPa, Vickers hardness of 7.50 GPa, and fracture toughness of 2.51 MPa m^1/2, comparable to the furnace-fired sample. The study reveals that concentrated solar energy converts light to heat by exciting lattice vibrations. Its rapid heating and cooling promote oxygen vacancy formation, accelerates lattice diffusion and grain boundary migration, thereby reducing the firing activation energy for firing and enhancing densification. This work overcomes the limitations of conventional firing and confirms the feasibility of solar firing for anorthite ceramics, providing both theoretical and practical foundations for clean production of high-performance, low-carbon ceramic thin plates.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"544 ","pages":"Article 147691"},"PeriodicalIF":10.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146077294","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 multi-phase phenological framework for reducing spectral confusion in disturbed forests: A case study from Vietnam","authors":"Zibin Liu ,&nbsp;Guizhen Wang ,&nbsp;Kai Jia ,&nbsp;Hongyan Lai ,&nbsp;Zirong Ruan ,&nbsp;Xincheng Wang ,&nbsp;Kecheng Peng ,&nbsp;Ting Yun ,&nbsp;Bangqian Chen","doi":"10.1016/j.jclepro.2026.147694","DOIUrl":"10.1016/j.jclepro.2026.147694","url":null,"abstract":"<div><div>Accurate forest mapping in Southeast Asia remains challenging due to spectral confusion in disturbed landscapes, where conventional classification approaches inadequately capture the temporal vegetation dynamic that distinguish natural forests from spectrally similar non-forest vegetation. To address this limitation, this study proposes a multi-phase phenological diagnostic framework (Green leaf period-Senescence defoliation foliation period-Leaf budding period; GRN-SDF-LBD) integrating canopy stability, dry-season moisture stress, and leaf regeneration patterns across seasonal transitions. The machine learning-integrated system, combining multi-temporal Sentinel-2/Landsat images, achieved 93.79 % accuracy, surpassing three widely-used products (ESA WorldCover, Dynamic World, and ESRI Sentinel-2 Land Cover; 84.62–90.44 %). This study reveals that existing products exhibit a consistent pattern of classification error characterized by forest consumer's accuracies of 55.58–87.13 % in disturbed areas, with classification decision boundaries significantly shifted toward the forest category. The phenology-based feature fusion framework proposed in this study effectively enhances forest misclassification control, reducing forest misclassification probability by 8.82 %–30.18 % compared to benchmark products. Among all phenological indicators, dry-season moisture dynamics (quantified through Land Surface Water Index, LSWI) contribute most significantly to classification accuracy. Spatial distribution analysis reveals that existing products significantly overestimate forest area in low-slope, disturbance-sensitive regions (slope &lt;5°), with deviation rates ranging from 33 % to 54 %. In Vietnam alone, this overestimation results in a false forest area report of 1.04 × 10⁶ to 1.7 × 10⁶ ha in low-slope regions. This framework enables precise forest boundary delineation in high-disturbance landscapes by capturing ecological process differences that are inadequately characterized by conventional spectral approaches, offering actionable insights for REDD + monitoring and deforestation-free supply chain governance under the Paris Agreement.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"544 ","pages":"Article 147694"},"PeriodicalIF":10.0,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071103","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":"Assessment and optimization model for sustainable grain production in China's major grain-producing areas from the perspective of water-carbon-land","authors":"C.B. Wu ,&nbsp;S.Y. Xing ,&nbsp;X.W. Zhuang ,&nbsp;G. Niu ,&nbsp;G.H. Huang","doi":"10.1016/j.jclepro.2026.147685","DOIUrl":"10.1016/j.jclepro.2026.147685","url":null,"abstract":"<div><div>Global warming, water scarcity, and limited land resources collectively constitute the most pressing challenges confronting sustainable agricultural development. Understanding nexus system optimization methods and their decision-making potential is crucial for sustainable resource management and mitigating adverse environmental impacts, especially in agriculture. Despite notable advancements in research on assessment and optimization models for the water-food-carbon-land nexus system, the integration of assessment model with optimization model has lagged behind. This study therefore developed a crop production sustainable potential index (CPSPI) assessment model that couples the water-carbon-land systems, and a multi-objective optimization model of sustainable grain production that weighs economy-resources-ecology. Additionally, two sustainable assessment systems, WFCNI (water-food-carbon nexus index) and CPSPI, were employed to quantify the sustainability level of the optimization results, thereby identifying potential optimal strategies and ultimately enhancing the overall sustainability of the optimized strategies. The results demonstrate a 1.5 %–24.3 % reduction in CPSPI across nine MGPA provinces, primarily driven by the adverse effects of blue water utilization efficiency and energy-related carbon emissions, especially in Anhui (−24.3 %), which pose a significant sustainability challenge. In general, the CPSPI is above 0.5 in eight provinces, indicating a favorable potential for sustainable production. Under the integrated sustainability assessment systems of WFCNI and CPSPI, three optimization programs (OP), OP4, OP6 and OP9, are selected. The three optimization scenarios achieved water savings of 9.7 %–12.4 % and emission reductions of 7.5 %–11.3 % for MGPA grain production. OP4 exhibited the most substantial comprehensive improvement in MGPA, achieving a 2.3 % enhancement in water footprint use efficiency, an emission reduction of approximately 452 million m³, and a 234 CNY increase in economic benefits per ton of carbon emission. The optimization model enables MGPA provinces to make scientific and reasonable decisions by weighing the integrated benefits of optimization, the national agricultural development strategy, and sustainable development goals. This framework additionally offers a reference for the sustainable assessment and optimization of crop production in other national key grain production regions.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"543 ","pages":"Article 147685"},"PeriodicalIF":10.0,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071769","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 adaptive technology portfolio optimization framework for port carbon and pollutants mitigation","authors":"Juncheng Wu ,&nbsp;Xianhao Guo ,&nbsp;Shitao Peng ,&nbsp;Shaojie Song","doi":"10.1016/j.jclepro.2026.147665","DOIUrl":"10.1016/j.jclepro.2026.147665","url":null,"abstract":"<div><div>Air pollution reduction and carbon mitigation at ports are essential for improving regional environmental quality and addressing climate change. Conventional emission abatement technologies often rely on expert judgment and lack adaptability to diverse emission profiles, limiting their effectiveness across varied port facilities. This research proposes a novel framework using a generative adversarial network (GAN) that integrates conditional GAN architecture, adaptive technology portfolio optimization, and multi-criteria decision analysis to generate customized port emission reduction solutions. The model was trained and validated using expert knowledge repositories and historical implementation data from case-study terminals. The results demonstrate clear performance improvements, achieving 85 % concordance with expert recommendations while delivering a 10.4 % enhancement in emission reduction performance compared with conventional approaches. The model shows higher synergistic emission reduction metrics and generates technology portfolios, including equipment electrification, shore power systems, and clean fuel applications. This GAN-based methodology advances environmental management by integrating data-driven approaches with domain expertise to optimize technology selection for sustainable port development.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"543 ","pages":"Article 147665"},"PeriodicalIF":10.0,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071779","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}