Journal of Cleaner Production最新文献_第9页

Distributionally robust agricultural product origin warehouses location-allocation problem under decision-dependent demand uncertainty 决策依赖需求不确定性下的分布鲁棒农产品原产地仓库选址问题

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

Journal of Cleaner Production

Pub Date : 2026-01-31 DOI: 10.1016/j.jclepro.2026.147664

Yiwen Gao , Xifu Wang , Kai Yang , Mengru Shen , Zhongbin Zhao , Cheng Cheng

The construction of origin logistics infrastructure is essential for the sustainable development of agricultural supply chains. Against this background, we address the integrated location-allocation problem for agricultural product origin warehouses under decision-dependent demand uncertainty in a multi-product, multi-period setting. Specifically, we propose a two-stage distributionally robust optimization (DRO) model that captures demand uncertainty through a decision-dependent ambiguity set. We then transform the proposed DRO model into an exact mixed-integer linear programming formulation by leveraging duality theory and McCormick envelope techniques, which can be solved by the Gurobi solver. The computational results from an empirical study in Yunnan, China, indicate that, compared to the customer self-operated mode, the shared origin warehouse mode can reduce total construction area by 21 % and construction costs by 21.7 %, while achieving a utilization rate above 70 %. These findings demonstrate the benefits of cost-reduction and efficiency-enhancement of the shared origin warehouse mode in agricultural product distribution. Moreover, comparative analysis demonstrates the superior performance of the proposed method over traditional stochastic programming and conventional DRO models. This study presents an innovative modeling approach for addressing decision-dependent uncertainty in the sustainable development of agricultural supply chains.

原产地物流基础设施的建设对农业供应链的可持续发展至关重要。在此背景下，我们研究了多产品、多周期环境下决策依赖需求不确定性下农产品原产地仓库的综合选址问题。具体而言，我们提出了一个两阶段分布鲁棒优化（DRO）模型，该模型通过决策依赖的模糊集捕获需求不确定性。然后，我们利用对偶理论和McCormick包络技术将所提出的DRO模型转换为精确的混合整数线性规划公式，该公式可以用Gurobi求解器求解。云南实证研究计算结果表明，与客户自营模式相比，共享原产地仓库模式总建筑面积减少21%，建设成本减少21.7%，利用率达到70%以上。这些发现证明了共享原产地仓库模式在农产品配送中降低成本和提高效率的好处。对比分析表明，该方法优于传统的随机规划模型和传统的DRO模型。本研究提出了一种创新的建模方法来解决农业供应链可持续发展中的决策依赖不确定性。

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引用次数: 0

Optimizing collaborative management decision-making in large watersheds through seasonal dynamic water quality diagnosis 基于季节动态水质诊断的大流域协同管理决策优化

IF 11.1 1区环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL

Journal of Cleaner Production

Pub Date : 2026-01-31 DOI: 10.1016/j.jclepro.2026.147698

Yi-Lin Zhao, Han-Jun Sun, Jie Ding, Ji-Wei Pang, Nan-Qi Ren, Shan-Shan Yang

引用次数: 0

A novel solution pollination in orchards 果园传粉的新方法

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

Journal of Cleaner Production

Pub Date : 2026-01-31 DOI: 10.1016/j.jclepro.2026.147661

Feiran Wang , Lixing Xie , Yao Zhou , Jiangrui Dai , Likai Feng , Guoli Zhang , Zongcai Zhu , Yancun Zhao , Baolian Tian , Xiuli Shi , Donglan Lv , Muhammad Imran , Umer Ayyaz Aslam Sheikh , Hongmei Li-Byarlay , Shudong Luo

Pollination is vital for the successful reproduction of cross-pollinating fruit trees. However, traditional pollination methods are increasingly challenged by declining pollinator populations, insufficient pollen availability, labor shortages, and the impact of extreme weather conditions. To address these issues, the development of innovative, sustainable, and efficient pollination strategies is urgently needed. This study presents a novel solution pollination technique that integrates bee-collected pollen—an inherently low-waste, high-uniformity resource—with unmanned aerial vehicle (UAV) technology. Characterized by superior suspension stability and uniformity in solution, bee-collected pollen remains evenly dispersed for at least 15 min after preparation, thereby enhancing the operational efficiency of UAV-assisted pollination. Furthermore, the pollen is uniformly sprayed onto the stigmas with UAV, along with the suitable germination aids in the solution. The successful pollen deposition ensures effective germination on stigmas and a high fruit set in orchard pollination practice. This integrated approach offers a rapid, eco-friendly, and scalable solution to the global pollination crisis, contributing to resilient and sustainable orchard production systems worldwide.

授粉对异花授粉果树的成功繁殖至关重要。然而，传粉者数量减少、花粉供应不足、劳动力短缺和极端天气条件的影响日益挑战传统的授粉方法。为了解决这些问题，迫切需要开发创新、可持续和高效的授粉策略。本研究提出了一种将蜜蜂采集的花粉这种具有低浪费、高均匀性的资源与无人机技术相结合的新型解决方案授粉技术。蜜蜂采集的花粉具有优异的悬浮稳定性和溶液均匀性，制备后可保持均匀分散至少15 min，从而提高了无人机辅助授粉的操作效率。再用无人机将花粉均匀喷洒在柱头上，并在溶液中加入合适的助萌发剂。在果园授粉实践中，成功的花粉沉积保证了柱头有效发芽和高坐果。这种综合方法为全球授粉危机提供了一种快速、环保、可扩展的解决方案，有助于在全球范围内建立有弹性和可持续的果园生产系统。

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引用次数: 0

The complexity and uncertainty of deep-sea mining futures: Integrating systems framework with experts' opinion 深海矿业期货的复杂性与不确定性：系统框架与专家意见的整合

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

Journal of Cleaner Production

Pub Date : 2026-01-31 DOI: 10.1016/j.jclepro.2026.147542

Datu Buyung Agusdinata, Kim Nguyen

The accelerated transition to clean energy has intensified interest in alternative mineral sources, including deep-sea mining (DSM). The future of DSM remains highly uncertain and contentious due to a complex interplay of social, economic, ecological, geopolitical, supply chain, and technological factors. Despite the growing discourse on DSM, a systematic analysis that incorporates systems and future thinking perspectives remains underdeveloped. Additionally, opinions on DSM may be prone to biases, which could further complicate the discourse. To address these gaps, a causal loop diagram (CLD) tool was applied to represent a hypothesized DSM dynamics that include feedback loops such as “Resource nationalism”, “Market dynamics”, “Regulatory timing”, and “Sea ecosystems protection”. The study is the first adaptation of a Social–Ecological–Technological Systems (SETS) framework to the DSM context. It provides a structure to the key variables represented in the CLD model. The framework comprises 33 variables spanning 10 key dimensions. Using an expert survey involving 43 respondents across the globe, the study evaluates the perceived importance and uncertainty of these variables. The analysis identifies critical factors—those located on the high-importance/high-uncertainty Pareto front—as including local and global biodiversity impacts and the timing of DSM regulations and exploitation permits. The most uncertain variables, as reflected in their high mean uncertainty scores, relate to the supply and price of minerals, the technological feasibility of reducing ecological impacts, and ecological risks. The response variability across disciplinary domains was found to be systematically different in how experts from physical, natural, and social sciences prioritize these factors. Physical scientists assigned lower importance to ecological and social variables, while social scientists emphasized temporal dynamics and demand reduction more strongly. These results highlight key sources of uncertainty, disciplinary biases, and high-importance drivers and provide new insights to support scenario planning and stakeholder engagement in DSM governance.

向清洁能源的加速过渡加强了对包括深海采矿在内的替代矿物资源的兴趣。由于社会、经济、生态、地缘政治、供应链和技术因素的复杂相互作用，DSM的未来仍然高度不确定和充满争议。尽管对DSM的讨论越来越多，但结合系统和未来思维视角的系统分析仍然不发达。此外，对DSM的意见可能容易产生偏见，这可能使论述进一步复杂化。为了解决这些差距，应用因果循环图（CLD）工具来表示假设的DSM动态，包括反馈循环，如“资源民族主义”、“市场动态”、“监管时机”和“海洋生态系统保护”。该研究首次将社会-生态-技术系统（set）框架应用于DSM。它为CLD模型中表示的关键变量提供了一个结构。该框架包括33个变量，跨越10个关键维度。通过一项涉及全球43名受访者的专家调查，该研究评估了这些变量的感知重要性和不确定性。该分析确定了关键因素——那些位于高重要性/高不确定性帕累托前沿的因素——包括当地和全球生物多样性影响，以及DSM法规和开采许可的时机。最不确定的变量，反映在他们的高平均不确定性得分，涉及矿物的供应和价格，减少生态影响的技术可行性和生态风险。在物理、自然和社会科学专家如何优先考虑这些因素方面，不同学科领域的反应差异存在系统性差异。物理科学家对生态和社会变量的重视程度较低，而社会科学家则更强调时间动态和需求减少。这些结果突出了不确定性的关键来源、学科偏差和高度重要的驱动因素，并为支持DSM治理中的场景规划和利益相关者参与提供了新的见解。

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引用次数: 0

Electric-carbon market coupling and price transmission mechanism in China: An empirical analysis and development barriers study 中国电碳市场耦合与价格传导机制：实证分析与发展障碍研究

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.2026.147692

Jiajun Wu, Yanjun Shen, Ruitong Yang, Hang Fan, Yunjie Duan

Under the ‘dual-carbon’ goal, China's carbon market is crucial for steering the power sector toward a clean transition via price signals. However, the coupling of electricity and carbon markets remains incomplete. This study investigates their coupling mechanism, price transmission, and the incentive effect of carbon pricing. Using provincial data from 2013 to 2023, our empirical analysis quantifies the transmission efficiency of carbon prices to generator-side electricity tariffs at 0.765. Rolling regression further indicates a dynamic pass-through effect, which experienced temporary attenuation during major institutional transitions. We construct an ecosystem panorama of the coupled market, outlining interactions among supply, circulation, and demand sides. The case of Huaneng International Group demonstrates that carbon costs effectively drive corporate energy transition, reducing carbon intensity by 37 % and raising clean energy share to 31.24 %. Finally, we identify key systemic barriers: undeducted CCERs distort the grid emission factor, creating unaccounted carbon liabilities for exporters, while generators internalize costs from the carbon price's “tidal effect” rather than fully passing them through. These practices highlight imperfections in market design and its linkage to policy. Therefore, addressing these issues urgently requires establishing a unified environmental attributes registry and reforming the compliance cycle to ensure carbon costs are transparently and efficiently reflected in prices.

在“双碳”目标下，中国的碳市场对于通过价格信号引导电力行业向清洁转型至关重要。然而，电力和碳市场的耦合仍然不完整。本文研究了二者的耦合机制、价格传导以及碳定价的激励效应。使用2013年至2023年的省级数据，我们的实证分析量化了碳价格对发电侧电价的传输效率为0.765。滚动回归进一步表明了一种动态传递效应，这种效应在重大制度转型期间经历了暂时的衰减。我们构建了一个耦合市场的生态系统全景，概述了供应、流通和需求方面的相互作用。华能国际集团的案例表明，碳成本有效地推动了企业的能源转型，碳强度降低了37%，清洁能源占比提高到31.24%。最后，我们确定了关键的系统性障碍：未扣除的CCERs扭曲了电网排放因子，为出口商创造了无法计算的碳负债，而发电商则将碳价格的“潮汐效应”成本内部化，而不是完全转嫁。这些做法凸显了市场设计及其与政策联系的不完善之处。因此，解决这些问题迫切需要建立一个统一的环境属性注册表，并改革合规周期，以确保碳成本透明有效地反映在价格中。

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引用次数: 0

Does public data openness promote urban green innovation cooperation? Evidence from China 公共数据开放是否促进了城市绿色创新合作？来自中国的证据

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.2026.147697

Mengmeng Wang , Yunxin Wu , Xiaoying Su

Public data openness serves as a key measure to unlock the value of data assets, yet how it fosters urban green innovation cooperation remains underexplored. Using panel data from 253 Chinese prefecture-level cities between 2008 and 2022, this study employs a staggered difference-in-differences approach to identify the impact of public data openness on green innovation collaboration. The results show that: (1) public data openness significantly enhances the level of urban green innovation cooperation, a finding robust to various tests; (2) it promotes incremental innovation more strongly than radical innovation; (3) the mechanisms operate through industrial upgrading and heightened environmental awareness; and (4) it accelerates the transition of secondary and tertiary industries from resource-dependent to technology- and service-oriented models. This study provides new empirical evidence on the role of public data openness in driving green innovation.

公共数据开放是释放数据资产价值的关键举措，但如何促进城市绿色创新合作仍有待探索。本研究利用2008 - 2022年间中国253个地级市的面板数据，采用交错差中差方法来确定公共数据开放对绿色创新合作的影响。结果表明：(1)公共数据开放显著提高了城市绿色创新合作水平，这一发现对各种检验都具有稳健性；(2)对渐进式创新的促进作用强于突破性创新；(3)通过产业升级和环保意识提升实现机制运行；(4)加快了二、三产业由资源依赖型向技术型和服务型转变。本研究为公共数据开放在推动绿色创新中的作用提供了新的实证证据。

引用次数: 0

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