Sustainable Cities and Society最新文献_第4页

Towards sustainable social housing: An integrative life cycle and multi-criteria approach 迈向可持续社会住房：综合生命周期和多标准方法

IF 12 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2026-01-15 DOI: 10.1016/j.scs.2026.107164

Ximena Luque Castillo , Lorena Yepes-Bellver , Victor Yepes

Structural systems for social housing must address pressing challenges of affordability, rapid execution, and long-term sustainability. However, choosing the most appropriate alternative requires balancing economic, environmental, social, and technical dimensions under uncertainty. This study applies a hybrid multi-criteria decision-making (MCDM) framework that combines the Best–Worst Method (BWM), fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), and the Measurement of Alternatives and Ranking according to COmpromise Solution (MARCOS) to evaluate five construction systems: Light Steel Frame (LSF), bolt-connected sandwich panels (LBSPS), reinforced concrete walls (RCW), monolithic reinforced concrete (RCF-M), and cast-in-place reinforced concrete (RCF-CP). The framework combines life cycle-based assessments—LCA, LCC, and SLCA— with causal analysis to capture interdependencies among criteria and generate transparent sustainability rankings. Results consistently position LSF as the top performing alternative, reflecting its balance between efficiency, durability, and reduced maintenance. Social aspects collectively accounted for nearly 40% of the total weight, surpassing economic and environmental dimensions, highlighting the central role of labor conditions, community impacts, and functionality in sustainable housing. Sensitivity analyses demonstrated stable rankings and validated the hybrid framework under alternative MCDM methods and diverse scenario perturbations. The findings provide actionable insights for housing policy in developing contexts, where industrialized systems and participatory evaluation processes can jointly advance resource efficiency, affordability, and social well-being.

社会住房的结构体系必须解决可负担性、快速执行和长期可持续性等紧迫挑战。然而，选择最合适的替代方案需要在不确定性下平衡经济、环境、社会和技术层面。本研究采用混合多准则决策（MCDM）框架，结合最佳最差方法（BWM），模糊决策试验和评估实验室（DEMATEL），以及根据折衷方案（MARCOS）的替代方案测量和排名（MARCOS）来评估五种建筑体系：轻钢框架（LSF），螺栓连接夹芯板（LBSPS），钢筋混凝土墙（RCW），整体钢筋混凝土（RCF-M）和现浇钢筋混凝土（RCF-CP）。该框架将基于生命周期的评估（lca、LCC和SLCA）与因果分析相结合，以捕捉标准之间的相互依赖关系，并生成透明的可持续性排名。结果一致表明LSF是性能最好的替代方案，反映了它在效率、耐用性和减少维护之间的平衡。社会方面合计占总权重的近40%，超过了经济和环境方面，突出了劳动条件、社区影响和功能在可持续住房中的核心作用。敏感性分析显示了稳定的排名，并验证了混合框架在不同的MCDM方法和不同的情景扰动下的有效性。研究结果为发展中国家的住房政策提供了可行的见解，在发展中国家，工业化体系和参与式评估过程可以共同提高资源效率、可负担性和社会福祉。

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引用次数: 0

Toward greener, smarter, and more resilient cities: Assessing the impact of dual pilot policies of forest city and smart city on urban climate resilience in China 迈向更绿色、更智慧、更有韧性的城市：评估森林城市和智慧城市双试点政策对中国城市气候韧性的影响

IF 12 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2026-01-15 DOI: 10.1016/j.scs.2026.107155

Yaobin Liu , Sheng Hu , Shuoshuo Li , Weifeng Deng

Climate risks threaten the sustainable development of urban economies, societies, and ecosystems. Urban climate resilience (UCR) is difficult to comprehensively improve through single policies. Forest cities and smart cities are typical examples of nature-based and technology-driven solutions, which have been extensively studied for their environmental impacts. However, it remains uncertain whether dual pilot policies (DPP) for forest cities and smart cities can synergistically enhance UCR. Based on the social-ecological-technological systems (SETS) perspective, this paper employs the staggered DID models to examine the policy synergetic effects of DPP on UCR. Results show that DPP increases UCR by an average of 5.43%. DPP establishes comprehensive adaptation mechanisms, including expanding green spaces, developing digital infrastructure, and promoting green technological innovation. The policy effect is more pronounced in inland cities, small cities, and cities with lower climate risks. While boosting the local UCR, DPP also improves the average UCR by 27.00% in neighboring areas. Our research highlights the synergistic governance between ecological and technological systems. It provides empirical evidence for climate adaptation through green and smart transformations in rapidly urbanizing regions.

气候风险威胁着城市经济、社会和生态系统的可持续发展。城市气候适应能力（UCR）难以通过单一政策全面提升。森林城市和智慧城市是基于自然和技术驱动的解决方案的典型例子，它们对环境的影响得到了广泛的研究。然而，森林城市和智慧城市的双重试点政策（DPP）是否能协同提高UCR仍不确定。基于社会-生态-技术系统（set）视角，采用交错DID模型考察了DPP对UCR的政策协同效应。结果表明，DPP使UCR平均提高5.43%。DPP建立了包括扩大绿色空间、发展数字基础设施、推动绿色技术创新在内的综合适应机制。政策效应在内陆城市、小城市和气候风险较低的城市更为明显。在提高当地UCR的同时，DPP还使周边地区的平均UCR提高了27.00%。我们的研究强调生态系统和技术系统之间的协同治理。它为快速城市化地区通过绿色和智能转型适应气候变化提供了经验证据。

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引用次数: 0

Urban flood susceptibility decoded: A GeoAI workflow for urban flood-prone area delineation and mitigation mechanism inference 城市洪水易感性解码：用于城市洪水易发地区划定和减灾机制推断的GeoAI工作流程

IF 12 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2026-01-14 DOI: 10.1016/j.scs.2026.107157

Junhao Wu , Yuanpeng Tang , Ling Ma , Dongfang Liang , Ioannis Brilakis , Svetlana Besklubova

Under the combined pressures of intensified extreme rainfall and accelerating impervious urban expansion, pluvial flooding has emerged as a dominant threat to urban safety and sustainability. Conventional flood-susceptibility models have faced challenges in handling highly sparse, long-tailed target distributions and in providing physical interpretability, which has limited the fine-scale delineation of flood-prone cells and the development of differentiated mitigation strategies. To address this issue, an integrated GeoAI-based framework was developed to systematically links urban surface characteristics with socio-hydrological processes for advancing flood-risk governance. The proposed framework synthesizes 25 natural and socio-economic variables to holistically capture flood-generation mechanisms across diverse city contexts. Through a two-stage feature distillation process, the ten most critical drivers shaping flood susceptibility in each city were identified. These drives underpin a novel zero-inflated convolutional self-attention network (ZI-Geo-CNN), which generated high-resolution susceptibility maps for six major Chinese cities with exceptional accuracy (

R^{2} > 0.98, A U C \approx 1.00,

and

S M A P E < 13 %)

. Post‑hoc analysis using Shapley Additive Explanations (SHAP) quantified each driver’s relative contribution, revealing universal controls alongside economy–infrastructure couplings. Based on shared and differentiated patterns of factor importance across cities, this study compared dominant patterns across cities and discussed several indicative adaptation directions. Overall, the framework breaks the accuracy–interpretability trade-off for sparse, long-tailed flood data and furnishes a replicable GeoAI workflow that can be applied consistently across cities through city-specific training, calibration, and interpretation, thereby providing an evidence-informed basis for resilient drainage planning under non-stationary climates.

在极端降雨加剧和不透水城市扩张加速的双重压力下，雨水泛滥已成为城市安全和可持续发展的主要威胁。传统的洪水敏感性模型在处理高度稀疏的长尾目标分布和提供物理可解释性方面面临挑战，这限制了对洪水易发细胞的精细描绘和制定差异化减灾战略。为了解决这一问题，开发了一个基于geoai的综合框架，系统地将城市地表特征与社会水文过程联系起来，以推进洪水风险治理。拟议的框架综合了25个自然和社会经济变量，以全面捕捉不同城市背景下的洪水产生机制。通过两阶段特征提炼过程，确定了影响城市洪水易感性的10个最关键驱动因素。这些驱动支撑着一种新型的零膨胀卷积自关注网络（ZI-Geo-CNN），该网络以优异的精度（R2>0.98,AUC≈1.00,SMAPE<13%）生成了中国六个主要城市的高分辨率敏感性地图。使用Shapley加性解释（SHAP）的事后分析量化了每个驱动因素的相对贡献，揭示了经济与基础设施耦合的普遍控制。基于城市要素重要性的共享和分化格局，比较了城市要素重要性的主导格局，探讨了城市要素重要性适应的指示性方向。总体而言，该框架打破了稀疏的长尾洪水数据的准确性和可解释性之间的权衡，并提供了可复制的GeoAI工作流程，可以通过城市特定的培训、校准和解释在城市中一致应用，从而为非固定气候下的弹性排水规划提供了证据基础。

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引用次数: 0

Co-optimization of expansion planning and dual-mode operations for regional integrated energy systems considering resilience enhancement under multiple uncertainties 多不确定条件下考虑弹性增强的区域综合能源系统扩容规划与双模式运行协同优化

IF 12 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2026-01-14 DOI: 10.1016/j.scs.2026.107124

Bo Jiang , Hongtao Lei , Wenhua Li , Kai Xu , Yajie Liu , Tao Zhang

With rising energy demand and advances in energy conversion technologies, expansion planning for existing integrated energy systems is increasingly urgent, which is essential for improving efficiency and supply stability while reducing long-term costs. Additionally, the rising frequency of extreme disasters underscores the necessity of incorporating resilience alongside economic considerations in planning processes. To address these dual requirements of economic performance and resilience, this paper proposes a multi-objective two-stage stochastic programming model. In the first stage (planning stage), the model aims to minimize total costs while maximizing a standardized resilience index (RI) to determine the optimal expansion plan for the integrated energy system. In the second stage (operation stage), the model simulates both normal and fault modes to evaluate operational costs and RI values, feeding the results back to further improve the planning stage. Operational strategies aimed at either economic performance or resilience are developed for the two modes to effectively manage the model’s computational complexity. To efficiently solve the proposed multi-objective model, a diversity-enhanced evolutionary algorithm with a knowledge-guided offspring generation method (DeEA/K) is employed, yielding a uniformly distributed Pareto front. The experimental results demonstrate that the proposed method can achieve high-quality multi-objective expansion planning solutions, and the algorithm exhibits strong performance on mixed-integer optimization problems.

随着能源需求的增加和能源转换技术的进步，现有综合能源系统的扩展规划日益紧迫，这对于提高效率和供应稳定，同时降低长期成本至关重要。此外，极端灾害发生的频率越来越高，凸显了在规划过程中将复原力与经济因素结合起来的必要性。为了解决经济绩效和弹性的双重要求，本文提出了一个多目标两阶段随机规划模型。在第一阶段（规划阶段），该模型的目标是最小化总成本，同时最大化标准化弹性指数（RI），以确定综合能源系统的最佳扩展计划。在第二阶段（运行阶段），该模型模拟正常和故障模式，以评估运行成本和RI值，并将结果反馈给进一步改进规划阶段。为了有效地管理模型的计算复杂性，针对这两种模式开发了以经济性能或弹性为目标的操作策略。为了有效地求解该多目标模型，采用了一种基于知识引导的后代生成方法（DeEA/K）的多样性增强进化算法，得到均匀分布的Pareto前沿。实验结果表明，该方法可以获得高质量的多目标扩展规划解，并且在混合整数优化问题上表现出较强的性能。

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引用次数: 0

To be integrated or not? Understanding continuance behavioral intention towards integrated ride-hailing services: Empirical evidence from Nanjing, China 整合还是不整合？理解对综合网约车服务的持续行为意向：来自中国南京的实证证据

IF 12 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2026-01-14 DOI: 10.1016/j.scs.2026.107159

Ke Lu , Jingfang Hu , Tingyu Shang , Yuan Xu

Despite explosive growth of integrated ride-hailing services (IRHS), the impact on long-term behavioral pattern has been little examined. This study intends to investigate travelers’ continuance behavioral intention towards IRHS, using a theoretical framework based on Expectation Confirmation Model (ECM). Moreover, four IRHS-specific feature variables are included, such as compatibility, hassle cost, convenience, and security. Further, this study introduces habit as moderating variable. Moreover, socio-demographic factors are considered as control variables, including gender, age, income, and educational level. With data collected from Nanjing, China, an empirical analysis is conducted using hybrid approach of Partial Least Square Structural Equation Modelling (PLS-SEM) and Artificial Neural Network (ANN). The findings indicate that perceived usefulness, satisfaction, and expectation confirmation are key determinants. Noteworthily, perceived usefulness exhibits as more important than expectation confirmation. Further, it shows that all IRHS-specific features play crucial roles. Specifically, compatibility and hassle cost show stronger influence on expectation confirmation, while convenience and security affect more on perceived usefulness. Habit acts as a moderator within relationships between expectation confirmation and satisfaction, and satisfaction and continuance behavioral intention. Additionally, travelers’ continuance intention is negatively related to age and education level. These findings shed valuable insights for understanding the general pattern of travelers’ behavior, and add practical value for platforms and policymakers.

尽管综合网约车服务（IRHS）呈爆炸式增长，但对长期行为模式的影响却很少得到研究。本研究采用基于期望确认模型（ECM）的理论框架，探讨旅游者对出境旅游的继续行为意愿。此外，还包括四个特定于irhs的特性变量，如兼容性、麻烦成本、便利性和安全性。进一步，本研究引入习惯作为调节变量。此外，社会人口因素被认为是控制变量，包括性别、年龄、收入和教育水平。采用偏最小二乘结构方程模型（PLS-SEM）和人工神经网络（ANN）的混合方法，对南京市的数据进行实证分析。研究结果表明，感知有用性、满意度和期望确认是关键的决定因素。值得注意的是，感知有用性比期望确认更重要。此外，它表明所有irhs特定的特征都起着至关重要的作用。其中，兼容性和麻烦成本对期望确认的影响更大，而便利性和安全性对感知有用性的影响更大。习惯在期望确认与满意、满意与持续行为意愿之间的关系中起调节作用。此外，旅行者的继续旅游意愿与年龄和受教育程度呈负相关。这些发现为理解旅行者行为的总体模式提供了有价值的见解，并为平台和政策制定者增加了实用价值。

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引用次数: 0

Beyond urban hierarchy: unveiling the spatial patterns of nonhierarchical carbon emissions 超越城市等级：揭示非等级碳排放的空间模式

IF 12 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2026-01-14 DOI: 10.1016/j.scs.2026.107160

Jianyu Li, Mingxing Hu, Shumin Wang, Ziye Liu, Jingyue Huang

Against the background of sustainable development, the effective management of urban carbon emissions has become a critical governance issue. However, under the urban hierarchical framework, the tasks of controlling carbon emissions and pursuing sustainable development are significantly complex. Some categories of emissions often exhibit characteristics of nonhierarchical emissions (NHEs) that are detached from the urban hierarchy. For the innovation, different from ordinary hierarchy-based research, the purpose of NHEs is to uncover the spatial mechanism of carbon emissions that are not constrained by administrative or economic hierarchies. Based on prefecture-level city data from four selected years in China (2010, 2015, 2019, and 2022), this study employs a spatial error model (SEM) and local spatial autocorrelation analysis (LISA) to capture the geographical distribution of NHE across the country. Furthermore, a core distance metric is employed to investigate the spatial distribution patterns of NHEs and their relationships with regional core cities. The study finds that the NHEs related to consumption are more strongly associated with a significant polarization effect. These cities are located in the area around the core cities, where population agglomeration leads to unique spatial patterns in specific categories of carbon emissions. In contrast, production-oriented NHEs are in the inner land. These categories of emissions often exhibit NHEs due to differences in resource endowments among cities. These findings provide a foundation for the localized governance of carbon emissions in noncore cities and introduce a place-based research perspective into carbon emission management.

在可持续发展的背景下，城市碳排放的有效管理已成为一个关键的治理问题。然而，在城市层级框架下，控制碳排放和追求可持续发展的任务非常复杂。某些类别的排放往往表现出与城市等级分离的非等级排放（NHEs）特征。在创新方面，不同于一般基于层级的研究，NHEs的目的在于揭示不受行政或经济层级约束的碳排放空间机制。基于2010年、2015年、2019年和2022年4年中国地级市数据，采用空间误差模型（SEM）和局部空间自相关分析（LISA）捕捉全国NHE的地理分布。此外，本文还采用核心距离度量，探讨了国家卫生系统的空间分布格局及其与区域核心城市的关系。研究发现，与消费相关的国民健康指数与显著的极化效应关系更为密切。这些城市位于核心城市周边区域，人口集聚导致其在特定碳排放类别上具有独特的空间格局。相比之下，以生产为导向的国家卫生机构位于内陆地区。由于城市间资源禀赋的差异，这些类别的排放往往表现出NHEs。这些研究结果为非核心城市碳排放的本地化治理提供了基础，并为碳排放管理引入了基于地的研究视角。

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引用次数: 0

Integrating ensemble machine learning and SAR-based geospatial modelling for inclusive and equitable urban flood resilience 集成集成机器学习和基于sar的地理空间建模：包容和公平的城市洪水抵御能力

IF 12 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2026-01-14 DOI: 10.1016/j.scs.2026.107158

Javed Mallick , Hoang Thi Hang , Alok Das , Sayanti Poddar , Chander Kumar Singh

Urban flooding has become a major challenge in fast-growing cities worldwide, disrupting mobility, damaging infrastructure, and increasing social vulnerability. In Bengaluru, where rapid urban expansion and inadequate drainage exacerbate monsoon floods, this study develops an integrated and data-driven framework to map flood susceptibility and exposure between 2020 and 2025. The main objective is to generate a scientifically validated, high-resolution, and explainable flood-risk assessment model combining radar-based detection, machine learning, and social-infrastructure exposure analytics. Multi-temporal Sentinel-1 dual-polarisation (VV and VH) SAR data were used to detect flood events through backscatter change analysis, ensuring accurate mapping even under cloudy conditions. An ensemble of five algorithms-Random Forest, Histogram-based Gradient Boosting, XGBoost, Quadratic Discriminant Analysis, and Gaussian Naïve Bayes-was trained and optimized to capture complex spatial relationships between floods and controlling parameters. Explainable AI (SHAP, permutation, ablation) to identify key drivers for transparent planning. Probability calibration and reliability curves to check and correct forecast bias infrastructure and demographic overlays to quantify who and what is exposed. Results show that the ensemble delivered AUC = 0.985 with accuracy 78–83%, precision 0.78–0.83, recall 0.79–0.83, and F1 ≈ 0.80 across six independent flood events; calibration improved reliability with well-aligned predicted vs observed probabilities. Spatially, 32.63 km² were mapped as Very High and 61.73 km² as High susceptibility, with stable hotspots in Electronic City, Bommanahalli, Mahadevapura, and Bellandur-Varthur. Road exposure was dominated by local streets (62,402 segments) and tertiary roads (3505 segments), indicating neighbourhood-scale disruption; female and schedule caste (SC) populations showed disproportional exposure in central/eastern wards, while schedule tribe (ST) exposure was lower but non-negligible on the periphery. This analysis enable ward-wise prioritisation of drain upgrades, permeable retrofits, safe-route planning, and targeted protection of at-risk groups, aligning with the Sendai Framework and sustainable development goals (SDG)-11/13.

城市洪水已成为全球快速发展城市面临的主要挑战，它扰乱了交通，破坏了基础设施，并增加了社会脆弱性。在班加罗尔，快速的城市扩张和排水不足加剧了季风洪水，本研究开发了一个综合的数据驱动框架，以绘制2020年至2025年期间的洪水易感性和暴露程度。主要目标是将基于雷达的探测、机器学习和社会基础设施暴露分析相结合，生成一个经过科学验证的、高分辨率的、可解释的洪水风险评估模型。多时相Sentinel-1双极化（VV和VH） SAR数据用于通过后向散射变化分析来检测洪水事件，确保即使在多云条件下也能准确测绘。随机森林、基于直方图的梯度增强、XGBoost、二次判别分析和高斯Naïve贝叶斯五种算法的集合进行了训练和优化，以捕获洪水与控制参数之间的复杂空间关系。可解释的人工智能（SHAP，排列，消融），以确定透明规划的关键驱动因素。概率校准和可靠性曲线，以检查和纠正预测偏差基础设施和人口覆盖，以量化暴露的人员和内容。结果表明：6个独立洪水事件的AUC = 0.985，准确度78 ~ 83%，精密度0.78 ~ 0.83，召回率0.79 ~ 0.83,F1≈0.80；校准提高了可靠性，预测概率与观测概率对齐良好。在空间上，32.63 km²为非常高敏感区，61.73 km²为高敏感区，热点稳定分布在Electronic City、Bommanahalli、Mahadevapura和Bellandur-Varthur。道路暴露主要是本地街道（62,402段）和三级道路（3505段），表明社区规模的破坏；女性和时间表种姓（SC）人群在中部/东部地区的暴露程度不成比例，而时间表部落（ST）人群在外围地区的暴露程度较低，但不可忽略。该分析能够根据仙台框架和可持续发展目标(SDG)-11/13，对下水道升级、透水改造、安全路线规划和有针对性地保护风险群体进行定向优先排序。

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引用次数: 0

The compounding effects of pollution reduction and low-carbon policy synergies on urban economic resilience and environmental performance 污染减排和低碳政策协同效应对城市经济弹性和环境绩效的复合效应

IF 12 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2026-01-14 DOI: 10.1016/j.scs.2026.107162

Xi Wang , Hua Shang , Xiaofei Lv , Sai Yuan

The synergistic governance effects of multi-objective environmental regulations are crucial for achieving coordinated economic and ecological development. Nevertheless, existing investigations have primarily focused on their singular effects on either the environment or the economy, while their synergistic governance effects require further validation. Utilizing urban data from China spanning 2007 to 2023, we construct a policy synergies variable for pollution reduction and low-carbon (PPCR) based on the Key Air Quality Control Zone Policy (KACP) and the Low-Carbon City Pilot Policy (LCCP). Then, we employ the Difference-in-Differences (DID) model to investigate the composite effects of PPCR on urban economic resilience (EOR) and environmental performance (PCR). The findings indicate that PPCR significantly enhances both EOR and PCR, with this conclusion demonstrating robustness. Meanwhile, the mechanism analysis reveals that the primary channels fostering EOR are the high-skilled talent siphoning and labor productivity-driven effects. Energy structure optimization and circular economy initiatives serve as significant pathways for PPCR to enhance PCR. Furthermore, the enabling role of PPCR is even stronger in cities with non-resource-based economies and strong public-oriented environmental regulations (PER).

多目标环境规制的协同治理效应是实现经济与生态协调发展的关键。然而，现有的调查主要集中在它们对环境或经济的单一影响上，而它们的协同治理效应需要进一步验证。本文利用2007 - 2023年中国城市数据，基于重点空气质量控制区政策（KACP）和低碳城市试点政策（LCCP），构建了污染减排与低碳（PPCR）政策协同变量。在此基础上，采用差分模型研究了PPCR对城市经济弹性（EOR）和环境绩效（PCR）的综合影响。结果表明，PPCR显著提高了EOR和PCR，这一结论具有稳健性。同时，机制分析表明，提高采收率的主要渠道是高技能人才的吸纳和劳动生产率的驱动效应。能源结构优化和循环经济倡议是PPCR增强PCR的重要途径。此外，在非资源型经济和强有力的公共导向环境法规（PER）的城市，PPCR的促进作用甚至更强。

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引用次数: 0

Exploring diurnal spatiotemporal heterogeneity in urban heat exposure: A novel perspective from urban form-function coupling 探索城市热暴露的日时空异质性：从城市形式-功能耦合的新视角

IF 12 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2026-01-14 DOI: 10.1016/j.scs.2026.107161

Aihemaiti Namaiti , Suiping Zeng , Weijie He , Xiang Liu , Jian Zeng

Understanding the spatiotemporal heterogeneity of diurnal urban heat exposure is crucial for addressing urban heat governance challenges. However, most studies focus on either urban form or function, lacking an integrated perspective to fully capture heat exposure heterogeneity. This study, using Nanchang, a typical Chinese “furnace city,” as a case study, proposes a novel form-function coupling framework. Through K-means clustering’s flexibility and local adaptability, it divided the study area into 12 homogeneous form-function clusters. By integrating high-resolution ECOSTRESS LST and mobile signaling data, it assessed diurnal heat exposure levels and their heterogeneity with precision. The High-Risk Contribution Index (HCI) was introduced to quantify each cluster’s contribution to high heat exposure risk. Results showed that the 12 clusters, based on form-function coupling, exhibited distinct heat exposure patterns, effectively capturing urban heat exposure heterogeneity. Kruskal-Wallis H tests and post hoc multiple comparisons confirmed highly significant differences in heat exposure among clusters across all time points (H values 3713.242–4367.439, p<0.001), with 71.21 %–80.30 % of pairwise comparisons showing significant differences (p<0.05). Three contribution patterns emerged: (1) consistently high contribution (clusters 8, 9, 10, 11, 12; average HCI >2; high-density commercial and residential zones), requiring priority intervention; (2) consistently low contribution (clusters 1, 2, 3, 4; average HCI <0.6; ecological zones), needing protection to leverage their “cool source” role; and (3) diurnal variation (clusters 6, 7; daytime HCI >1, nighttime <1; influenced by industrial activity timing), requiring flexible interventions based on production schedules. These findings provide a replicable paradigm for precise, dynamic, and localized urban heat exposure governance and offer a theoretical-methodological framework for similar cities, enhancing the scientific rigor and practicality of heat governance strategies.

了解城市日热暴露的时空异质性对于解决城市热治理挑战至关重要。然而，大多数研究都集中在城市形态或功能上，缺乏一个完整的视角来充分捕捉热暴露的异质性。本研究以中国典型的“炉城”南昌为例，提出了一种新的形式-功能耦合框架。通过K-means聚类的灵活性和局部适应性，将研究区域划分为12个同质的形式-功能聚类。通过整合高分辨率ECOSTRESS LST和移动信号数据，该研究精确评估了日热暴露水平及其异质性。引入高风险贡献指数（HCI）来量化每个集群对高热暴露风险的贡献。结果表明，基于形式-功能耦合的12个集群表现出不同的热暴露模式，有效地捕捉了城市热暴露的异质性。Kruskal-Wallis H检验和事后多重比较证实，在所有时间点上，集群之间的热暴露差异非常显著（H值为3713.242-4367.439,p<0.001）， 71.21% - 80.30%的两两比较显示显著差异（p<0.05）。出现了三种贡献模式：(1)持续高贡献（集群8、9、10、11、12；平均HCI >2；高密度商业和住宅区），需要优先干预；(2)持续低贡献（集群1、2、3、4；平均HCI为0.6；生态区），需要保护以发挥其“冷源”作用；(3)日变化（集群6,7；白天HCI >；1，夜间HCI <1；受工业活动时间影响），需要基于生产计划的灵活干预。这些发现为精确、动态和本地化的城市热暴露治理提供了可复制的范例，并为类似城市提供了理论方法框架，增强了热治理策略的科学严谨性和实用性。

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引用次数: 0

Topological and source–sink integrated analysis of urban thermal environment networks in a megacity: Longitudinal insights from Guangzhou 特大城市热环境网络的拓扑与源汇综合分析：来自广州的纵向观察

IF 12 1区工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY

Sustainable Cities and Society

Pub Date : 2026-01-13 DOI: 10.1016/j.scs.2026.107156

Liang Tang , Runyu Shao , Xinran Zhou , Yali Zhang , Ziyi Chen , Long Yang , Hui Li

Under the dual pressures of global climate change and rapid urbanization, the thermal environment of high-density megacities has become increasingly complex, with intensified heat risks and spatial heterogeneity. Taking Guangzhou as a case study, this research integrates multi-temporal remote sensing data to construct a cold-source–heat-sink network and proposes an analytical paradigm of “network framework–spatial dynamics–targeted implementation” to uncover the spatiotemporal evolution and ventilation-coupling mechanisms of urban thermal systems. From 2004 to 2023, Guangzhou exhibited a three-stage thermal evolution pathway—“aggregation–fragmentation–reconstruction.” Cold sources first contracted and later re-expanded, shifting from fragmented patches to renewed agglomeration, while core heat sinks continuously enlarged and merged northward, intensifying the urban heat island effect. Circuit-based modeling revealed a 38% decline in source–sink corridors and an increase in ventilation pinch points from 11 to 23, forming high-resistance bottlenecks that weakened cold–heat coupling across urban transition zones. Topological diagnostics further showed that the thermal network evolved from a “multi-core–high-connectivity” configuration to a “centralized–vulnerable” structure, followed by a stage of “localized recovery–structural rebuilding.” The identified three-stage trajectory highlights the coupled reorganization of cold/heat sources and ventilation corridors, offering a dynamic perspective on the mechanisms underlying urban heat risk formation. This study advances the theoretical understanding of cold–heat interaction networks, demonstrates the synergistic value of combining circuit theory with topological metrics, and proposes a four-tier coordinated regulation strategy—cold-source preservation, heat-sink mitigation, corridor optimization, and node restoration—to support refined thermal governance and resilience enhancement in megacities.

在全球气候变化和快速城市化的双重压力下，高密度特大城市热环境日益复杂，热风险和空间异质性加剧。以广州市为例，整合多时相遥感数据构建冷源-热汇网络，提出“网络框架-空间动态-目标实施”的分析范式，揭示城市热系统的时空演化与通风耦合机制。2004 - 2023年，广州呈现“聚集-破碎-重建”的3阶段热演化路径。冷源先收缩后再膨胀，从破碎的斑块到重新聚集，核心散热器不断扩大并向北融合，加剧了城市热岛效应。基于电路的模型显示，源汇走廊减少了38%，通风夹点从11个增加到23个，形成了高阻力瓶颈，削弱了城市过渡区内的冷热耦合。拓扑诊断进一步表明，热网络从“多核高连通性”结构演变为“集中脆弱”结构，随后是“局部恢复-结构重建”阶段。确定的三阶段轨迹突出了冷/热源和通风走廊的耦合重组，为城市热风险形成的机制提供了动态视角。本研究推进了对冷热相互作用网络的理论认识，论证了电路理论与拓扑指标相结合的协同价值，并提出了四层协调调节策略——冷源保护、热汇缓解、走廊优化和节点恢复——以支持特大城市的精细热治理和弹性增强。

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引用次数: 0