Journal of Cleaner Production最新文献_第9页

Advancing cleaner grain production: How can land certification promote the decoupling between grain production and carbon emissions? 推进清洁粮食生产：土地认证如何促进粮食生产与碳排放脱钩？

IF 1 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Journal of Cleaner Production

Pub Date : 2026-01-30 DOI: 10.1016/j.jclepro.2026.147686

Miao Miao , Wei Lu , Bingyin Yu , Yin Wang , Xukang Yin

Ensuring food security and promoting sustainable agricultural development have emerged as global strategic priorities. Promoting the decoupling between grain production and carbon emissions (GCD) to achieve cleaner grain production represents a critical pathway for addressing these challenges. Although academic research has explored the relationship between food security and agricultural carbon mitigation, the mechanism through which land certification facilitates cleaner grain production remains inadequately revealed. This study investigates China's rural land certification program(LCP), which is the largest land tenure reform in the world, as a policy framework. Based on panel data from 231 prefecture-level cities in China between 2012 and 2022, this study employs a staggered difference-in-differences (DID) approach to systematically evaluate the causal effects of LCP on the GCD. Empirical results demonstrate that LCP significantly promotes GCD, a conclusion that remains robust across various checks. Mechanism analysis reveals dual transmission pathways: first, the policy reduces transaction costs to facilitate land transfer and labor migration, thereby generating economies of scale; second, it strengthens supply-demand matching efficiency in agricultural outsourcing services, creating economies of specialization. The synergistic interaction of these mechanisms further optimizes production factor allocation and accelerates the decoupling process. This research contributes to following dimensions: enhancing the accounting framework for carbon emissions in grain production, expanding the environmental impact assessment of land property rights systems, and strengthening the theoretical understanding of GCD. Furthermore, it provides an operational policy paradigm for developing countries to coordinate food security with low-carbon transition through property rights reform, offering valuable insights for improving global climate governance systems.

确保粮食安全和促进可持续农业发展已成为全球战略重点。促进粮食生产与碳排放脱钩，以实现更清洁的粮食生产，是应对这些挑战的重要途径。虽然学术研究已经探讨了粮食安全和农业碳减排之间的关系，但土地认证促进更清洁粮食生产的机制仍然没有充分揭示。本研究将中国的农村土地认证计划（LCP）作为一个政策框架来研究，这是世界上最大的土地权属改革。本研究基于2012 - 2022年中国231个地级市的面板数据，采用交错差中差（DID）方法系统评估了城市政策对城市消费水平的因果影响。实证结果表明，LCP显著促进了GCD，这一结论在各种检查中仍然是稳健的。机制分析揭示了双重传导路径：一是政策降低交易成本，促进土地流转和劳动力迁移，从而产生规模经济；二是提高农业外包服务的供需匹配效率，形成专业化经济。这些机制的协同作用进一步优化了生产要素配置，加速了脱钩过程。本文的研究成果主要体现在：完善粮食生产碳排放核算框架，拓展土地产权制度环境影响评价，加强对GCD的理论认识。此外，它还为发展中国家通过产权改革协调粮食安全与低碳转型提供了一个操作政策范例，为完善全球气候治理体系提供了宝贵的见解。

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引用次数: 0

Topic clustering and sentiment evolution fusion analysis of the Chinese online public opinion on driverless taxis: A case study of Baidu's “Apollo Go” 中国无人驾驶出租车网络舆情的话题聚类与情感进化融合分析——以b百度的《阿波罗Go》为例

IF 1 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Journal of Cleaner Production

Pub Date : 2026-01-30 DOI: 10.1016/j.jclepro.2026.147695

Xiaochun Zhao, Ce Gao, Ying Zhou

With the continuous advancement and rapid commercialization of autonomous driving technology, driverless taxis have emerged as a critical research focus in the field of intelligent transportation. Given the substantial volume of textual data generated alongside this technological development, analyzing public opinion trends and emotional responses at different stages of driverless taxi adoption is essential for informing effective policy dissemination and social interventions. This study examines Baidu's “Apollo Go” as a case study to investigate the evolution of public discourse and sentiment regarding driverless taxis. Specifically, we employ BERTopic for topic modeling to extract key public opinion topics and integrate them with SnowNLP sentiment analysis to construct a topic-sentiment fusion framework. This framework captures the progression of public opinion through its initiation, peak, and stabilization phases. The topic clustering analysis reveals that public discourse evolves from early curiosity and caution to heated debates over social and economic impacts, and finally to normalized daily discussions. Combined with sentiment analysis, the results indicate that although safety incidents and employment issues continue to trigger negative emotions, public attitudes have gradually shifted from cautious observation to increasing positivity. Importantly, the findings highlight the sustainable role of driverless taxis: by advancing shared mobility, electrification, and intelligent scheduling, together with growing social acceptance, they can support cleaner production, cut carbon emissions, and improve urban transport efficiency. Based on these findings, this study not only provides a nuanced understanding of public acceptance pathways but also suggests directions for building trust, improving governance, and advancing the sustainable integration of driverless taxis into urban mobility transitions.

随着自动驾驶技术的不断进步和快速商业化，无人驾驶出租车已成为智能交通领域的一个重要研究热点。考虑到伴随这项技术发展而产生的大量文本数据，分析无人驾驶出租车采用不同阶段的民意趋势和情绪反应对于有效的政策传播和社会干预至关重要。本研究以b百度的《阿波罗Go》为例，探讨了关于无人驾驶出租车的公众话语和情绪的演变。具体而言，我们使用BERTopic进行主题建模，提取关键舆情主题，并将其与SnowNLP情感分析相结合，构建主题-情感融合框架。该框架记录了公众舆论在初始阶段、高峰阶段和稳定阶段的发展。话题聚类分析表明，公共话语从早期的好奇和谨慎，到对社会和经济影响的激烈辩论，最后到常态化的日常讨论。结合情绪分析，结果表明，虽然安全事故和就业问题继续引发负面情绪，但公众态度逐渐从谨慎观察转向越来越积极。重要的是，研究结果强调了无人驾驶出租车的可持续作用：通过推进共享出行、电气化和智能调度，以及越来越多的社会接受度，它们可以支持更清洁的生产，减少碳排放，提高城市交通效率。基于这些发现，本研究不仅提供了对公众接受途径的细致理解，而且为建立信任、改善治理和推动无人驾驶出租车可持续融入城市交通转型提供了方向。

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引用次数: 0

Expanding discourse and advocating stances: Social bots action strategies in carbon neutrality discussions 扩大论述和倡导立场：社交机器人在碳中和讨论中的行动策略

IF 1 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Journal of Cleaner Production

Pub Date : 2026-01-30 DOI: 10.1016/j.jclepro.2026.147591

Yan Dongqi , Ren Wujiong , Yao Junchen , Wu Yuduo , He Yuan , Hongzhong Zhang

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.

社交机器人已经成为在线环境交流中越来越明显的参与者。本研究分析了在第27届缔约方大会（COP27）期间和之后的三个月期间收集的推特通信，以检查社交机器人、普通人账户和媒体账户在碳中和话语中的行为模式、情感动态和互动。采用情感分析、结构主题模型（STM）和纵向时间序列分析相结合的混合计算方法。根据清理和分类的数据集，结果显示社交机器人占推文总数的27.59%，这表明在碳中和讨论中存在大量存在。与普通的人类账号相比，社交机器人更依赖于现有内容的再循环，并且相对于人类账号和媒体账号都表现出不同的互动模式和社交网络特征。社交机器人生成的内容主要以气候行动主义为导向（77.81%），其特点是口号驱动的信息传递、自动放大和情感动员。在主题导向方面，社交机器人更倾向于关注与商业经济相关的话题，包括电动汽车政策、合作与机遇、碳中和和公众舆论等。互动评估揭示了一种三方互动模式，其中社交机器人放大了人类和媒体的声音，而人类则对机器人推广的话题做出反应。这项研究表明，社交机器人不仅有助于，而且可能通过塑造公共话语和影响政策议程来引导碳中和问题的突出性。

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引用次数: 0

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 基于季节-日视角的城乡梯度地表温度与影响因子的非线性关系——以贵安地区为例

IF 1 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Journal of Cleaner Production

Pub Date : 2026-01-30 DOI: 10.1016/j.jclepro.2026.147634

Chuyi Guo , Yuchi Yang , Wei Yang

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.

了解地表温度在城乡梯度上的时空分异及其复杂的驱动机制，对于推进城市热动力学研究和为气候减缓策略提供信息至关重要。然而，现有的研究主要集中在线性分析或单一时间尺度上，忽视了不同地形条件下地表温度的季节-日变化及其非线性相互作用。本文以具有代表性的喀斯特地形区贵阳-安顺地区为研究对象，构建了基于“季-日”时空视角的地表温度驱动机制分析框架。利用夜间灯光数据（NTL）分位数回归，结合贝叶斯优化的XGBoost模型和SHAP模型，系统地揭示了城乡梯度区域的非线性驱动模式和空间相互作用。主要发现包括：(1)贵安地区地表温度城乡梯度明显，城市核心区昼夜温差显著，夏季波动剧烈，郊区和农村波动较小，热稳定性强；(2)地表温度影响机制在季节-日尺度上表现出显著的时间变异性；③城乡梯度区各因素的相对重要性发生变化，随着城市化程度的降低，自然因素的相对重要性越来越突出，反映了城乡梯度区从“人为驱动”向“地形生态控制”的转变；(4)各因子的影响表现出显著的非线性和阈值效应，在不同区域表现出不同的有效性和响应强度；(5)相互作用分析表明，地表温度变化是多因素综合耦合相互作用的结果，而不是单个变量的线性叠加。该研究为理解地表温度的复杂动态提供了一个新的框架，并为可持续城市规划和气候适应提供了实践指导。

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引用次数: 0

Effect of palladium loading on catalytic performance and product selectivity during diclofenac degradation by Pd0@anaerobic activated sludge 负载钯对Pd0@anaerobic活性污泥降解双氯芬酸催化性能和产物选择性的影响

IF 1 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Journal of Cleaner Production

Pub Date : 2026-01-30 DOI: 10.1016/j.jclepro.2026.147676

Xiaodi Li , Jingzhou Zhou , Lin Yang , Si Pang , Yi Yang , Defu Gan , Junxia He , Penghui Shi , Siqing Xia

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.

厌氧活性污泥（AAS）通过绿色生物合成途径制备了具有不同Pd负载的生物质负载钯纳米催化剂（Pd0@AAS），消除了对有毒试剂和高能量输入的需要。该催化剂随后对双氯芬酸（DCF）的催化降解进行了评价。系统阐述了Pd的降解途径，重点研究了Pd负载对产物选择性、反应动力学和相应的生态毒理学结果的影响。Pd0@AAS通过两个关键步骤解毒DCF: DCF加氢脱氯生成2-苯胺苯基乙酸（APA），然后APA芳香环加氢。4小时后，低Pd负荷（1.1 wt%）导致对APA的高选择性（89.7%），而高Pd负荷（10.6 wt%）促进了完全氢化，将APA的选择性降低到0%。生态毒性评估表明，氢脱氯可以有效消除急性毒性，而完全氢化则可以消除慢性毒性。动力学分析表明，随着Pd负载的增加，氢脱氯速率常数增加（1.1-10.6 wt%），但催化剂特异性活性（与Pd浓度标准化）在Pd负载5.3 wt%时达到平台，超过该值，纳米颗粒聚集限制了进一步的增强，这表明高Pd负载仅用于脱氯在经济上是不切实际的。相反，在相同的Pd负载范围内，反应速率常数和催化剂特异性加氢活性均显著增加。10.6 wt%的值分别比5.3 wt%和2.7 wt%的值高2.7倍和30倍。这种差异强调了芳香环的氢化更依赖于连续的Pd0活性位点。这些发现指导了优化生物质负载的Pd0纳米催化剂，以实现成本效益和生态安全的卤代芳香族污染物修复。

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引用次数: 0

Novel Styrofoam-sludge biochar for Pb and Zn adsorption: Bioavailability and reduction in maize-cultivated contaminated soils 新型泡沫聚苯乙烯污泥生物炭吸附铅和锌：玉米污染土壤的生物有效性和降低

IF 1 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Journal of Cleaner Production

Pub Date : 2026-01-30 DOI: 10.1016/j.jclepro.2026.147548

Muhammad Ubaid Ali , Mehr Ahmed Mujtaba Munir , Ruilian Yu , Gongren Hu , Balal Yousaf , Sajid Ali , Muhammad Adnan , Cheng Liping , Xiangliang Pan , Ming Hung Wong

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.

本研究旨在评价原料和泡沫乙烯改性污泥生物炭（SSB1-3）对铅(II)-和锌（II）污染土壤的修复效果。生物炭的pH值、比表面积、孔隙度、芳香性和官能团丰度等性能均显著提高，同时减少了输入能量和二次金属污染。增强的性能促进了协同金属固定机制，如阳离子-π相互作用、ph驱动沉淀、表面络合、离子交换和矿物相关结合，将金属转化为更稳定的形式。由于生物炭衍生的腐殖质样溶解有机物增加了金属的固存和微生物活性，形成了金属固定的化学-生物联合途径。DOM中含有腐植酸和黄腐酸类成分，Pb和Zn与DOM的结合降低了这些金属在土壤中的生物利用度，从而通过与腐植酸物质形成稳定的配合物降低了Pb和Zn的可提取部分。吸附动力学和等温线显示快速、自发和化学吸附为主的Pb（II）和Zn（II）的吸收。由于活性位点的富集，样品SSB3表现出最高的吸附能力。施用SSB3后观察到的主要特征是金属生物利用度降低，玉米植株内部转运受限，植物生物量增加。总体而言，代表了一种可持续的、具有成本效益的修正方法，提出了一种稳定重金属和改善污染环境土壤质量的综合方法。这些结果为将污水污泥和泡沫聚苯乙烯共热解产生的生物炭作为一种环保和低成本的吸附剂用于污染土壤和/或水的处理以降低金属毒性开辟了前景。

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引用次数: 0

Machine learning-optimized efficient CO2-to-CO conversion in a novel catalyst-free spark discharge plasma 机器学习优化的新型无催化剂火花放电等离子体中co2到co的高效转换

IF 1 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Journal of Cleaner Production

Pub Date : 2026-01-30 DOI: 10.1016/j.jclepro.2026.147603

Guangdong Yang , Tao Jiang , Jing Wen , Tangxia Yu , Changqing Li , Lan Zhang , Mingze Ma

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.

无催化剂火花放电等离子体通过逆向水气转换（RWGS）反应为二氧化碳利用提供了一条有前景的新途径，但功率、停留时间、成分和反应器几何形状之间的强耦合使部署相关的优化变得复杂。研究了一种改进的同轴石英管火花放电反应器，并通过不同的放电功率、总流量、H2/CO2摩尔比和跨工程相关水平的内径，编制了500个工作点的结构化数据集。为了避免网格数据集随机分裂造成的膨胀泛化，采用留一条件分组交叉验证筛选了10个回归量，并在严格的留一条件提前停止协议下选择和调整了人工神经网络（ANN; multilayer perceptron， MLP）代理。超参数调优将分组预测精度提高到R2 = 0.909的二氧化碳转换和R2 = 0.970的能源效率。模型可信度进一步得到了bootstrap重采样、适用性域诊断和15个离网点的外部插值验证（R2 = 0.907，转换R2 = 0.959，效率R2 = 0.959）的支持，大部分观测值都在95%的预测范围内。在实验条件下，操作窗口图确定在70 W， H2/CO2 = 3.0, 200 mL/min，内径为7 mm时，峰值转化率为89.76%，在40 W， H2/CO2 = 1.0, 1000 mL/min， 7 mm时，峰值能效为19.12%。Shapley加性解释（SHAP）解释提供了非线性效应的过程相关属性，并澄清了验证域中相互作用驱动的状态依赖。由此产生的工作流程能够实现规范驱动、电力感知筛选，最终确定下游合成气应用的反应器配置和操作窗口。

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引用次数: 0

Thermal and mechanical performance of 3D-printed excavated soil wall solidified by alkali-activated slag 碱活性渣固化3d打印开挖土壁的热力学性能研究

IF 1 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Journal of Cleaner Production

Pub Date : 2026-01-30 DOI: 10.1016/j.jclepro.2026.147594

Jianyu Shen , Yaofei Cheng , Jianzhuang Xiao , Bo Wang , Shuisheng Li

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.

造墙是实现开挖土高价值利用的重要途径。为了解决传统土墙力学性能和耐久性不足的问题，本研究采用碱活化技术和3D打印技术制作墙体样品。设计了四种具有不同凝固配方、块体结构和内部填充条件的3d打印土基墙（PSW）。系统地研究了它们的力学性能，并验证了它们作为墙体材料的热工性能。系统地研究了聚丙烯酸甲酯的热性能和力学性能。对比分析表明，与3d打印砂浆墙体相比，PSW的实际抗压强度降低了6.2% ~ 39.0%，但仍能满足低层建筑结构的力学要求。PSW的等效导热系数范围为0.099至0.108 W/(K·m)，与3d打印砂浆墙相比，降低了14.1%至21.0%。通过加入斜肋进行结构优化，导热系数降低了17.0%，抗压强度提高了6.1%。此外，用绝缘材料（如聚氨酯泡沫）填充空腔，导热系数降低了62.7%，符合严寒地区的热要求。PSW显示出显著的可持续性优势，成本和碳排放量分别降低11.5% - 27.4%和72.7% - 80.8%。本研究展示了3d打印固化土墙的技术可行性和环境经济效益，突出了其在可持续建筑应用中的潜力。

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引用次数: 0

A new cleaner production process: Microstructure, properties and solar power furnace firing mechanism of anorthite ceramic thin plate 一种新的清洁生产工艺：钙长石陶瓷薄板的显微结构、性能及太阳能电炉烧成机理

IF 1 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Journal of Cleaner Production

Pub Date : 2026-01-30 DOI: 10.1016/j.jclepro.2026.147691

Xiaohong Xu , Tong Liu , Jianfeng Wu , Saixi Qiu , Yu Zhang , Ziwei Zhang , Dong Wang

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.

针对传统陶瓷薄板烧制过程中存在的高能耗问题，本研究首次探索了聚光太阳能在钙长石陶瓷生产中的应用。以透辉石、硅灰石和α-Al2O3为原料，以Co2O3为吸光剂，对太阳能烧制与电炉烧制进行了比较。结果表明：在低温短时间条件下，太阳能烧制完成了烧制，得到的样品吸水率为0.10%，孔隙率为0.24%，容重为2.53 g cm−3，抗弯强度为94.12 MPa，维氏硬度为7.50 GPa，断裂韧性为2.51 MPa m2 /2，与电炉烧制样品相当。研究表明，聚光太阳能通过激发晶格振动将光转化为热。它的快速加热和冷却促进了氧空位的形成，加速了晶格扩散和晶界迁移，从而降低了烧结活化能，增强了致密化。本工作克服了传统烧制的局限性，证实了太阳能烧制钙长石陶瓷的可行性，为高性能、低碳陶瓷薄板的清洁生产提供了理论和实践基础。

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引用次数: 0

A multi-phase phenological framework for reducing spectral confusion in disturbed forests: A case study from Vietnam 减少受干扰森林光谱混淆的多阶段物候框架：以越南为例

IF 1 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Journal of Cleaner Production

Pub Date : 2026-01-30 DOI: 10.1016/j.jclepro.2026.147694

Zibin Liu , Guizhen Wang , Kai Jia , Hongyan Lai , Zirong Ruan , Xincheng Wang , Kecheng Peng , Ting Yun , Bangqian Chen

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 <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.

由于受干扰景观中的光谱混淆，东南亚的精确森林制图仍然具有挑战性，传统的分类方法无法充分捕捉到区分天然林与光谱相似的非森林植被的时间动态。为了解决这一问题，本研究提出了一个多阶段物候诊断框架（绿叶期-衰老脱叶期-叶片出芽期；GRN-SDF-LBD），整合了冠层稳定性、旱季水分胁迫和季节转换中的叶片再生模式。结合多时间点Sentinel-2/Landsat图像的机器学习集成系统达到了93.79%的精度，超过了三种广泛使用的产品（ESA WorldCover， Dynamic World和ESRI Sentinel-2 Land Cover； 84.62 - 90.44%）。研究发现，现有产品在受干扰地区呈现出一致的分类误差模式，森林消费者的分类准确率为55.58 ~ 87.13%，分类决策边界明显向森林类偏移。本研究提出的基于物候的特征融合框架有效增强了对森林误分类的控制，与基准产品相比，可将森林误分类概率降低8.82% ~ 30.18%。在所有物候指标中，旱季水分动态（通过陆地地表水指数量化）对分类精度的贡献最大。空间分布分析表明，现有产品在低坡度、扰动敏感区（坡度<；5°）显著高估了森林面积，偏差率在33% ~ 54%之间。仅在越南，这种高估导致低坡地区的森林面积报告为1.04 × 106至1.7 × 106公顷。该框架通过捕捉传统光谱方法无法充分表征的生态过程差异，能够在高干扰景观中精确划定森林边界，为《巴黎协定》下的REDD +监测和无毁林供应链治理提供可操作的见解。

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引用次数: 0