Sustainable Cities and Society最新文献_第7页

CFD simulation of mixed convection and pollutant dispersion in street canyons: A comparative assessment of LES, RANS, and SAS 街道峡谷中混合对流和污染物扩散的CFD模拟：LES、RANS和SAS的比较评估

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

Sustainable Cities and Society

Pub Date : 2026-03-01 Epub Date: 2026-01-06 DOI: 10.1016/j.scs.2026.107126

Weiheng Liang, Xing Zheng

Computational fluid dynamics (CFD) is a crucial technique for investigating urban wind and thermal environments. However, a clear understanding of the performance of different CFD approaches for wind and buoyancy-driven conditions in urban canyons remains lacking. This study systematically evaluates the performance of various CFD approaches for a street canyon with heated walls by comparing them with wind tunnel experimental data. The CFD approaches include three Reynolds-averaged Navier–Stokes (RANS) models: the standard

k

–

ɛ

(SKE), the realizable

k

–

ɛ

(RKE), and the shear stress transport

k

–

ω

model (SST); scale-adaptive simulations (SAS) with Courant–Friedrichs–Lewy (CFL) numbers less than 1 (SAS-CFL1) and 20 (SASCFL20); and large eddy simulation (LES). CFD simulation results for velocity, air temperature, and pollutant concentration are validated against WT measurement data. The findings indicate that the LES simulation achieves the highest accuracy across all flow variables evaluated, with normalized mean square error (

N M S E

) values of 0.15 for velocity, 0.12 for temperature, and 0.64 for pollutant concentration. Although the two SAS simulations exhibit slightly lower accuracy than LES, they maintain similar and satisfactory performance, with the SAS-CFL20 yielding

N M S E

values of 0.16 for velocity, 0.26 for air temperature, and 0.90 for pollutant concentration. The three RANS models, however, exhibit significant inaccuracies, with the SKE model yielding

N M S E

values of 0.47 for velocity, 0.41 for temperature, and 2.04 for pollutant concentration. These inaccuracies are primarily due to the overestimation of buoyancy effects near heated walls, which notably enlarges the thermal-induced vortex and subsequently altering flow directions near the pollutant emission source. Among the evaluated CFD approaches, the SAS-CFL20 is approximately 15 times faster than the LES, presenting a favorable balance between accuracy and computational efficiency. These findings highlight the potential of the SAS-CFL20 for practical applications in future urban thermal environment studies.

计算流体力学（CFD）是研究城市风热环境的一项重要技术。然而，对于不同CFD方法在城市峡谷中风和浮力驱动条件下的性能，人们仍然缺乏清晰的认识。本文通过与风洞实验数据的比较，系统地评估了不同CFD方法在带加热壁的街道峡谷中的性能。CFD方法包括三种reynolds -average Navier-Stokes （RANS）模型：标准k - ε (SKE)、可实现k - ε (RKE)和剪切应力输运k - ω模型（SST）；CFL数小于1 （SAS- cfl1）和20 （SASCFL20）的尺度自适应模拟（SAS）；和大涡模拟（LES）。CFD模拟速度、空气温度和污染物浓度的结果与WT测量数据进行了验证。研究结果表明，LES模拟在所有评估的流量变量中都达到了最高的精度，流速的归一化均方误差（NMSE）为0.15，温度为0.12，污染物浓度为0.64。尽管两种SAS模拟的精度略低于LES，但它们保持了相似且令人满意的性能，SAS- cfl20对速度的NMSE值为0.16，对气温的NMSE值为0.26，对污染物浓度的NMSE值为0.90。然而，三个RANS模型表现出明显的不准确性，其中SKE模型的速度NMSE值为0.47，温度NMSE值为0.41，污染物浓度NMSE值为2.04。这些不准确性主要是由于对热壁附近浮力效应的高估，这明显地扩大了热诱导涡，并随后改变了污染物排放源附近的流动方向。在所评估的CFD方法中，SAS-CFL20比LES快约15倍，在精度和计算效率之间取得了良好的平衡。这些发现突出了SAS-CFL20在未来城市热环境研究中的实际应用潜力。

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引用次数: 0

Reconstruction of Pedestrian-Level pollutant distributions in urban street canyon using physics-informed neural network 基于物理信息神经网络的城市街道峡谷行人级污染物分布重建

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

Sustainable Cities and Society

Pub Date : 2026-02-01 Epub Date: 2026-01-09 DOI: 10.1016/j.scs.2026.107141

Liang Ma , Tengfei An , Runhan Zhao , Wenli Liu

Rapid urban expansion, coupled with an increasing number of motor vehicles, has rendered street canyons critical zones for PM_2.5 accumulation. However, the limited density of on-site monitoring and the considerable computational cost of conventional computational fluid dynamics simulations impede accurate and real-time assessment of pollution exposure at the pedestrian level. This study proposes a framework termed PINN-RAS, which integrates a physics-informed neural network (PINN) with a residual-softmax adaptive sampling (RAS) strategy. This framework enables the reconstruction of fine-scale pollution distributions based on sparse observational data. First, the incorporation of physical constraints enables the PINN model to maintain predictive robustness as the proportion of training data decreases progressively from 80% to 5%. It captures dominant vortices and pollutant gradients within the canyon, with overall R² values consistently exceeding 0.8. Second, under simulated measurement noise, the model demonstrates strong local error convergence. Prediction errors remain confined to narrow boundary regions, achieving an R² of 0.81, which outperforms baseline models including convolutional neural and long short-term memory networks. Third, the RAS strategy dynamically allocates sampling points in regions with high residuals and sharp concentration gradients, thereby enhancing coverage of critical zones. The reconstruction model achieves an R² of 0.85, while the mean squared error and mean absolute error are reduced to 0.11 and 0.16, respectively, thereby enabling finer-scale reconstruction using an equivalent data proportion. This method provides a cost-effective and efficient solution for real-time, high-resolution air quality assessment and facilitates precise health risk assessment and control at the pedestrian level.

快速的城市扩张，加上机动车数量的增加，使得街道峡谷成为PM2.5聚集的关键区域。然而，有限的现场监测密度和传统计算流体动力学模拟的可观计算成本阻碍了对行人水平污染暴露的准确和实时评估。本研究提出了一个名为PINN-RAS的框架，该框架将物理信息神经网络（PINN）与残数软最大值自适应采样（RAS）策略集成在一起。该框架能够基于稀疏观测数据重建精细尺度的污染分布。首先，当训练数据的比例从80%逐渐下降到5%时，物理约束的加入使PINN模型保持预测稳健性。它捕获了峡谷内的优势涡和污染物梯度，总体R2值始终超过0.8。其次，在模拟测量噪声下，该模型具有较强的局部误差收敛性。预测误差仍然局限于狭窄的边界区域，实现R2为0.81，优于包括卷积神经和长短期记忆网络在内的基线模型。第三，RAS策略在残差高、浓度梯度大的区域动态分配采样点，从而提高关键区域的覆盖率。重建模型的R2为0.85，均方误差和平均绝对误差分别降至0.11和0.16，从而可以使用等效的数据比例进行更精细的重建。该方法为实时、高分辨率的空气质量评估提供了一种经济高效的解决方案，有助于在行人层面进行精确的健康风险评估和控制。

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引用次数: 0

From cooling pathways to practical acclimating design: Urban park regulating potentials under Extreme Heat Events 从降温通道到实际适应性设计：城市公园在极端高温事件下的调节潜力

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

Sustainable Cities and Society

Pub Date : 2026-02-01 Epub Date: 2026-01-10 DOI: 10.1016/j.scs.2026.107146

Jinchen Wang , Yan Sun , Qiping Lu , Qi Yang

Rapid urbanisation and global warming have intensified the frequency and severity of extreme heat events (EHEs), posing substantial challenges in urban areas. The urban park cool island effect (PCI) could aid in the mitigation of and adaptation to EHEs. However, its cooling intensity and underlying mechanisms in metropolitan regions under different heat extremes are unclear. To address this, we quantitatively assessed the PCI effect between EHEs and non-EHEs of two summer periods and identified universal PCI pathways. PCI effects were quantified across 109 urban parks within the Fifth Ring Road of Beijing using the equal radius and turning point methods. We then employed structural equation modelling (SEM) to elucidate the causal pathways among various factors during EHEs and non-EHEs. We found that: (1) the PCI of 109 urban parks was significantly stronger during EHEs than during non-EHEs, with PCI intensity varying from 0 to 10 °C, and the PCI exhibiting spatial heterogeneity along the urban–rural gradient; (2) urban park cooling service followed universal pathways between different EHE periods (June 2021 and July 2022) and present different pattern from four non-EHE periods.; (3) the differences between the SEM models were primarily driven by external impervious surfaces, vegetation cover, and three-dimensional building height in the park surrounding areas. This study not only reveals the PCI potentials under different heat extremes, but also deepens our understanding of PCI pathways, providing methodological and theoretical references for urban park extremes-adaptation planning and construction.

快速城市化和全球变暖加剧了极端高温事件（EHEs）的频率和严重程度，给城市地区带来了重大挑战。城市公园冷岛效应（PCI）有助于缓解和适应环境污染。然而，在不同极端高温条件下，其冷却强度及其机制尚不清楚。为了解决这个问题，我们定量评估了两个夏季EHEs和非EHEs之间的PCI效应，并确定了普遍的PCI途径。采用等半径法和拐点法对北京市五环内109个城市公园的PCI效应进行了量化。然后，我们采用结构方程模型（SEM）来阐明在EHEs和非EHEs中各种因素之间的因果关系。研究发现：(1)109个城市公园在生态环境污染期间的PCI显著强于非生态环境污染期间，PCI强度在0 ~ 10℃范围内变化，且PCI呈现出城乡梯度的空间异质性；(2)城市公园降温服务在不同EHE时段（2021年6月至2022年7月）具有普遍的路径，与4个非EHE时段呈现不同的格局；(3) SEM模型间的差异主要受公园周边不透水地表、植被覆盖和三维建筑高度的影响。本研究不仅揭示了不同极端高温条件下的PCI潜力，而且加深了我们对PCI路径的认识，为城市公园极端适应规划和建设提供了方法和理论参考。

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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 : 2026-02-01 Epub 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

Coastal city pollution from time-varying traffic emissions: A high-resolution WRF-CFD comparison of dynamic sea-land breeze and static prevailing wind 时变交通排放造成的沿海城市污染：动态海陆风和静态盛行风的高分辨率WRF-CFD比较

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

Sustainable Cities and Society

Pub Date : 2026-02-01 Epub Date: 2026-01-10 DOI: 10.1016/j.scs.2026.107147

Jiajian He , Yihang Lu , Yanming Kang , Yuqian Gu , Ke Zhong , Yiqi Wang

Rapid urbanization has intensified traffic-related air pollution in street networks, particularly in coastal cities frequently affected by mesoscale sea-land breeze (SLB) circulations. Conventional air-quality assessments commonly adopt simplified steady-state ‘prevailing wind’ assumptions, failing to capture the dynamic and diurnal evolution of SLB circulations. This methodological simplification can weaken the effectiveness of pollution-mitigation strategies or even make them counterproductive. To address this limitation, a high-temporal-resolution WRF-CFD coupled model is employed to integrate time-evolving SLB meteorological fields with time-varying traffic emissions, assessing the pollutant dispersion under the SLB and summer prevailing wind (SPW) conditions. The results show that under SLB conditions, street-level pollutant concentrations become decoupled from traffic emission patterns, exhibiting opposing trends during morning and evening rush hours compared to the predictable behavior under SPW. Weak morning land breezes hinder pollutant dispersion, increasing concentrations by 1.4 times compared to SPW, whereas strong evening sea breezes enhance ventilation, reducing concentrations by 43 %. Moreover, the midday collision of sea and land breezes generates a low-ventilation ‘convergence zone’, causing severe pollution episodes even during off-peak traffic hours. During this convergence period, the average pollution concentration under SLB is over 1.4 times higher than during SPW, with peak concentrations reaching nearly twice those of SPW. Although daily average concentrations are similar under both weather conditions, the SLB-induced convergence effect can cause short-term rapid pollutant accumulation, significantly amplifying pedestrian exposure risks. Consequently, for air quality assessment in coastal cities, the main findings show that SLB-induced meteorological dynamics (e.g., the midday convergence) can be a more critical determinant of acute pollution events than traffic volume itself, challenging the conventional prevailing steady-state assumption. The developed framework also provides an essential tool for designing meteorology-responsive dynamic traffic management and street-level air quality alert systems, enabling targeted control strategies under different weather conditions to reduce exposure risks.

快速城市化加剧了街道网络中与交通有关的空气污染，特别是在经常受到中尺度海陆风（SLB）环流影响的沿海城市。传统的空气质量评估通常采用简化的稳态“盛行风”假设，未能捕捉到SLB环流的动态和日演变。这种方法上的简化会削弱减少污染战略的有效性，甚至使其产生反效果。为了解决这一问题，采用高时间分辨率WRF-CFD耦合模型，将时变SLB气象场与时变交通排放相结合，评估SLB和夏季盛行风条件下的污染物扩散。结果表明，在SLB条件下，街道污染物浓度与交通排放模式脱钩，在早高峰和晚高峰时段与SPW条件下的可预测行为相反。早晨微弱的陆风阻碍了污染物的扩散，使浓度增加了1.4倍，而晚上强烈的海风增强了通风，使浓度减少了43%。此外，正午的海风和陆风碰撞会产生低通风的“辐合区”，即使在非交通高峰时段也会造成严重的污染。在此辐合期，SLB条件下的平均污染浓度是SPW条件下的1.4倍以上，峰值达到SPW条件下的近2倍。尽管两种天气条件下的日平均浓度相似，但slb诱导的辐合效应会导致污染物短期快速积累，显著放大行人暴露风险。因此，对于沿海城市的空气质量评估，主要研究结果表明，slb诱导的气象动力学（例如，正午辐合）可能是急性污染事件的一个更关键的决定因素，而不是交通量本身，挑战了传统的普遍稳态假设。制定的框架也为设计气象响应的动态交通管理和街道空气质量警报系统提供了重要工具，使我们能够在不同天气条件下采取有针对性的控制策略，以减少暴露风险。

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引用次数: 0

Household investment behavior and environmental impact: How family financial decisions influence carbon emissions in China 家庭投资行为与环境影响：中国家庭财务决策对碳排放的影响

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

Sustainable Cities and Society

Pub Date : 2026-02-01 Epub Date: 2026-01-06 DOI: 10.1016/j.scs.2026.107128

Tianzuo Wen , Will W. Qiang , Haowen Luo , Harry F. Lee , Shenjing He

The relationship between household financial behavior and carbon emissions is a critical yet underexplored component of sustainable urban development. This study investigates the impact of household investment behaviors on direct carbon emissions, leveraging panel data from 152 Chinese prefecture-level cities between 2015 and 2019. Using a robust two-way fixed effects model, the analysis reveals a significant inverted U-shaped relationship between household investment volume and carbon emissions. While initial investment accumulation correlates with rising emissions, further growth facilitates a transition toward emission reduction. Crucially, Household Investment Intensity (HII), defined as the ratio of investment to household income, serves as a key negative moderator; households with higher investment intensity exhibit a stronger capacity to decouple financial growth from carbon emissions. Mechanism analysis indicates that this reduction is not driven by the suppression of consumption volume, but rather by a decrease in the carbon intensity of consumption. This suggests a "Green Quality Effect" where investment returns enable a structural shift toward low-carbon services and energy-efficient goods. Furthermore, spatial heterogeneity analysis highlights a development threshold, as the emission-reducing effect of investment is significantly more pronounced in economically developed eastern regions compared to central and western areas. These findings underscore the role of financial decisions in shaping low-carbon lifestyles. Policy implications suggest that financial institutions and policymakers should prioritize optimizing household asset structures and designing green financial products to foster sustainable consumption patterns.

家庭金融行为与碳排放之间的关系是可持续城市发展中一个关键但尚未得到充分探索的组成部分。本研究利用2015年至2019年中国152个地级市的面板数据，研究了家庭投资行为对直接碳排放的影响。利用稳健的双向固定效应模型，分析发现家庭投资量与碳排放之间存在显著的倒u型关系。虽然最初的投资积累与排放量上升有关，但进一步的增长有助于向减排过渡。至关重要的是，家庭投资强度（HII），即投资与家庭收入的比率，是一个关键的负向调节因子；投资强度越高的家庭将经济增长与碳排放脱钩的能力越强。机制分析表明，这种减少不是由消费量的抑制驱动的，而是由消费碳强度的降低驱动的。这表明了一种“绿色质量效应”，即投资回报使向低碳服务和节能产品的结构性转变成为可能。此外，经济发达的东部地区投资减排效应明显强于中西部地区，存在发展阈值。这些发现强调了财务决策在塑造低碳生活方式中的作用。政策启示表明，金融机构和政策制定者应优先优化家庭资产结构，设计绿色金融产品，以促进可持续消费模式。

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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 : 2026-02-01 Epub 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

How to identify urban heat inequity? A systematic literature review of scales, indicators, pathways, and future directions 如何识别城市热不平等？对量表、指标、途径和未来方向进行系统的文献综述

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

Sustainable Cities and Society

Pub Date : 2026-02-01 Epub Date: 2026-01-07 DOI: 10.1016/j.scs.2026.107130

Yue Lin, Hui Zeng

Urban extreme heat adversely affects human health, well-being, and sustainable urban development, with disproportionately severe impacts on underdeveloped regions and vulnerable groups. Consequently, urban heat inequity has become a central issue in climate justice research. This study systematically reviews the indicators and methodological approaches used in 114 global empirical studies, maps their development through bibliometric analysis, and breaks down the methodology frameworks into three components for in-depth review: heat indicators, socioeconomic indicators, and analytical pathways. The study synthesizes and compares the commonalities and differences across these works, yielding the following key findings: 1) Geographically and scale-wise, studies on tropical low-income regions are severely lacking, as are micro-scale studies. 2) Heat indicators are diverse and fragmented, falling into five categories: heat environment, heat effect, heat adaptation, heat exposure indicator, and integrated heat index. 3) Socioeconomic indicators, shaped by data availability and local context, amount to ten types. Among these, income, age, and ethnicity are the most prevalent and occupy a central position in the co-occurrence network of socioeconomic indicators. 4) Four core analytical pathways are identified—intuitive comparison, regression, equity indices, and indicator ranking—each with a distinct focus in detecting heat inequity. Overall, as the first review focusing on methodologies and indicator systems in heat inequity research, this study clarifies current methodological approaches and indicator characteristics, highlights limitations such as geographical and scale imbalances, indicator fragmentation, and overreliance on single analytical pathways, and offers guidance for future studies in terms of case selection, indicator system construction, and methodological design.

城市极端高温对人类健康、福祉和城市可持续发展产生不利影响，对不发达地区和弱势群体的影响尤为严重。因此，城市热不平等已成为气候正义研究的核心问题。本研究系统回顾了114项全球实证研究中使用的指标和方法，通过文献计量分析绘制了它们的发展图，并将方法框架分解为三个组成部分：热指标、社会经济指标和分析途径。该研究综合并比较了这些研究的共性和差异，得出以下主要发现：1)在地理和尺度方面，热带低收入地区的研究严重缺乏，微观尺度的研究也是如此。2)热指标多样化、碎片化，主要分为热环境指标、热效应指标、热适应指标、热暴露指标和综合热指标5类。3)受数据可用性和当地环境影响的社会经济指标共有十种。其中，收入、年龄和种族是最普遍的，在社会经济指标共现网络中占据中心位置。4)确定了直观比较、回归、公平指数和指标排序四种核心分析途径，每一种分析途径在检测热不平等方面都有不同的重点。总体而言，本研究首次对热不平等研究的方法和指标体系进行综述，明确了当前热不平等研究的方法方法和指标特征，突出了地域和尺度不平衡、指标碎片化、过度依赖单一分析途径等局限性，并在案例选择、指标体系构建和方法设计等方面为今后的研究提供了指导。

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引用次数: 0

Research on the construction and evaluation of urban emergency management capability index system from the perspective of digital intelligence empowerment 数字智能赋能视角下城市应急管理能力指标体系构建与评价研究

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

Sustainable Cities and Society

Pub Date : 2026-02-01 Epub Date: 2026-01-12 DOI: 10.1016/j.scs.2026.107148

Fangming Cheng , Nannan Zhao , Chang Su , Di Wang , Xiaokun Chen

With the connection and empowerment of digital intelligence technology to urban emergency management, the urban emergency management model is undergoing a process of reconstruction and transformation. However, there is currently a lack of scientific and effective capability evaluation systems and methods. This paper constructs an evaluation system comprising five first-level indicators—root-cause governance, risk prevention and control, emergency rescue and recovery, comprehensive support, and digital emergency capability—along with 14 secondary indicators and 45 tertiary indicators. It analyzes the scope of emergency management capabilities and pathways for digital intelligent empowerment. Employing an interval trapezoidal type-2 fuzzy and the matter-element extension cloud model to address subjective fuzziness, the paper establishes a comprehensive evaluation model for case analysis and improvement research. This framework and model provide support for building intelligent and agile emergency management systems.

随着数字智能技术对城市应急管理的连接和赋能，城市应急管理模式正在经历重构和转型的过程。然而，目前缺乏科学有效的能力评估体系和方法。本文构建了由根因治理、风险防控、应急救援与恢复、综合保障、数字化应急能力5个一级指标、14个二级指标、45个三级指标组成的评价体系。它分析了应急管理能力的范围和数字智能赋权的途径。采用区间梯形2型模糊和物元可拓云模型解决主观模糊性，建立了案例分析和改进研究的综合评价模型。该框架和模型为构建智能、敏捷的应急管理系统提供了支持。

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引用次数: 0

Spatial patterns and climate adaptation mechanisms of street-house systems in Chongqing traditional settlements 重庆传统聚落街巷系统的空间格局与气候适应机制

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

Sustainable Cities and Society

Pub Date : 2026-02-01 Epub Date: 2026-01-11 DOI: 10.1016/j.scs.2026.107150

Pengcheng Liu , Xu Li , Haitian Lu , Li Yan

Global warming and loss of regional cultural expression present dual challenges. A research gap persists: the passive, low-energy experience of traditional settlements remains untransformed into quantifiable design guidelines. This study focused on typical traditional settlements in Chongqing, China (a hot-summer and cold-winter region). It adopted an integrated "street-house" system perspective to analyse how spatial elements influence wind and thermal environmental performance, and distilled climate-adaptive spatial form characteristics and rules to provide operable guidance for climate-adaptive urban design. First, a literature review and field surveys identified the spatial elements for subsequent quantitative analysis. Second, the study used a combined approach of orthogonal/full factorial experiments and numerical simulations to quantify contribution rates, nonlinear relationships, and interaction effects of selected spatial elements on wind and thermal environmental performance, laying a foundation for spatial pattern formulation. Results indicated street orientation dominated the wind environment (contribution rates of 76.7% for street and 98.7% for building) and height-to-width ratio dominated the thermal environment (55.1% and 66.4% for street and building, respectively). Second-floor cantilevered balconies and eaves also significantly affected the thermal environment. The wind environment exhibited two significant interaction effects: street orientation × through-flow doors and windows, and street height-to-width ratio × eaves width. The thermal environment had no significant interaction effects. The study further analysed contradictory and synergistic characteristics of spatial morphological elements in climate adaptation, extracting patterns addressing summer and winter needs. These findings deepened understanding of climate adaptability in traditional settlements, and provided quantitative basis and pattern references for climate-adaptive urban planning.

全球变暖和区域文化表达的丧失带来了双重挑战。一个研究缺口仍然存在：传统住区的被动、低能耗体验仍未转化为可量化的设计准则。本研究以中国重庆（夏热冬冷地区）典型传统聚落为研究对象。采用综合“街屋”系统视角，分析空间要素对风热环境性能的影响，提炼气候适应性空间形态特征和规律，为气候适应性城市设计提供可操作性指导。首先，通过文献综述和实地调查，确定了后续定量分析的空间要素。其次，采用正交/全因子试验与数值模拟相结合的方法，定量分析了空间要素对风热环境性能的贡献率、非线性关系和交互效应，为空间格局的构建奠定了基础。结果表明：街道朝向主导风环境（街道贡献率为76.7%，建筑贡献率为98.7%），高宽比主导热环境（街道贡献率为55.1%，建筑贡献率为66.4%）；二层的悬挑阳台和屋檐也显著影响了热环境。风环境表现出两个显著的相互作用效应：街道朝向×通流门窗，街道高宽比×屋檐宽度。热环境的交互作用不显著。进一步分析了气候适应空间形态要素的矛盾和协同特征，提取了满足夏季和冬季需求的模式。这些发现加深了人们对传统聚落气候适应性的认识，为气候适应性城市规划提供了定量依据和模式参考。

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引用次数: 0