Sustainable Cities and Society最新文献

{"title":"High-resolution spatiotemporal dynamic simulation and driving force analysis of carbon emissions in coastal cities: The case of Ningbo City","authors":"Guangxin Cui ,&nbsp;Xusheng Cheng ,&nbsp;Yanwei Sun ,&nbsp;Chao Gao ,&nbsp;Zheng Duan ,&nbsp;Tian Ruan","doi":"10.1016/j.scs.2026.107195","DOIUrl":"10.1016/j.scs.2026.107195","url":null,"abstract":"<div><div>Coastal port cities are key regions for carbon emissions (CEs) research in China, due to their industrial density, frequent transportation, and diverse human activities. Taking Ningbo City as a case study, this study employed a top-down accounting method and integrated multiple sources of geospatial data to reveal the spatiotemporal distribution characteristics of CEs from four sectors, including industrial, residential, logistical, and commercial, from 2013 to 2022. Monte Carlo simulation was further applied to assess uncertainty. The driving factors were analyzed using the Logarithmic Mean Divisia Index (LMDI) decomposition model. The findings show that the total CEs in Ningbo City increased steadily, with the spatial pattern evolving from early single-core aggregation to coastal multi-center expansion. The industrial sector is the primary source, with emissions concentrated in ports and coastal industrial zones. Residential and commercial emissions exhibit a multi-point distribution and low-value expansion pattern, while logistical emissions have remained relatively stable and are primarily concentrated in the urban area. Economic development is the core driver of CEs growth, while energy intensity and carbon emission factors have had an inhibitory effect. This study provides a theoretical basis and practical support for high-resolution urban CEs monitoring and low-carbon policy formulation in coastal cities.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107195"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399070","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Augmenting urban planning with computer vision: A review of the state-of-the-art","authors":"Raveena Marasinghe ,&nbsp;Tan Yigitcanlar ,&nbsp;Xinyu Fu ,&nbsp;Steven Jige Quan","doi":"10.1016/j.scs.2026.107209","DOIUrl":"10.1016/j.scs.2026.107209","url":null,"abstract":"<div><div>Computer Vision (CV) offers powerful methods for analysing built environments, yet its integration into planning workflows remains fragmented. This study conducts a systematic review of CV applications in urban planning using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, synthesising prevailing models, methods, and application domains. The review identifies five dominant CV research clusters in urban contexts (built environment analysis, urban sensing and data acquisition, smart mobility, methodological advances, and 3D urban modelling) and synthesises that CV is primarily used to extract physical and perceptual urban features, support diagnostic analytics, and enable emerging visualisation and generative design workflows. Advances in deep learning, convolutional neural networks, and emerging foundation models (including vision transformers and diffusion-based generative systems) are expanding capability across diverse CV tasks and lowering barriers to adoption. Building on an inductive synthesis of application patterns across the reviewed studies, the paper proposes an Urban Visual Intelligence (UVI) hierarchy that clarifies how imagery is translated into progressively more planning-relevant outputs, from observation and diagnosis to associative explanation, forecasting, and intervention prototyping. The review also highlights constraints related to data representativeness, transferability, interpretability, privacy and generative unreliability, underscoring the need for stronger validation and governance as outputs become more decision relevant. Overall, the review consolidates how CV is reshaping urban analytics and offers a structured basis for responsible integration into planning practice.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107209"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CFD simulation of mixed convection and pollutant dispersion in street canyons: A comparative assessment of LES, RANS, and SAS","authors":"Weiheng Liang,&nbsp;Xing Zheng","doi":"10.1016/j.scs.2026.107126","DOIUrl":"10.1016/j.scs.2026.107126","url":null,"abstract":"<div><div>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 <span><math><mi>k</mi></math></span>–<span><math><mi>ɛ</mi></math></span> (SKE), the realizable <span><math><mi>k</mi></math></span>–<span><math><mi>ɛ</mi></math></span> (RKE), and the shear stress transport <span><math><mi>k</mi></math></span>–<span><math><mi>ω</mi></math></span> 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 (<span><math><mrow><mi>N</mi><mi>M</mi><mi>S</mi><mi>E</mi></mrow></math></span>) 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 <span><math><mrow><mi>N</mi><mi>M</mi><mi>S</mi><mi>E</mi></mrow></math></span> 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 <span><math><mrow><mi>N</mi><mi>M</mi><mi>S</mi><mi>E</mi></mrow></math></span> 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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107126"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reconstruction of Pedestrian-Level pollutant distributions in urban street canyon using physics-informed neural network","authors":"Liang Ma ,&nbsp;Tengfei An ,&nbsp;Runhan Zhao ,&nbsp;Wenli Liu","doi":"10.1016/j.scs.2026.107141","DOIUrl":"10.1016/j.scs.2026.107141","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107141"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From cooling pathways to practical acclimating design: Urban park regulating potentials under Extreme Heat Events","authors":"Jinchen Wang ,&nbsp;Yan Sun ,&nbsp;Qiping Lu ,&nbsp;Qi Yang","doi":"10.1016/j.scs.2026.107146","DOIUrl":"10.1016/j.scs.2026.107146","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107146"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Topological and source–sink integrated analysis of urban thermal environment networks in a megacity: Longitudinal insights from Guangzhou","authors":"Liang Tang ,&nbsp;Runyu Shao ,&nbsp;Xinran Zhou ,&nbsp;Yali Zhang ,&nbsp;Ziyi Chen ,&nbsp;Long Yang ,&nbsp;Hui Li","doi":"10.1016/j.scs.2026.107156","DOIUrl":"10.1016/j.scs.2026.107156","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107156"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980213","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coastal city pollution from time-varying traffic emissions: A high-resolution WRF-CFD comparison of dynamic sea-land breeze and static prevailing wind","authors":"Jiajian He ,&nbsp;Yihang Lu ,&nbsp;Yanming Kang ,&nbsp;Yuqian Gu ,&nbsp;Ke Zhong ,&nbsp;Yiqi Wang","doi":"10.1016/j.scs.2026.107147","DOIUrl":"10.1016/j.scs.2026.107147","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107147"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Household investment behavior and environmental impact: How family financial decisions influence carbon emissions in China","authors":"Tianzuo Wen ,&nbsp;Will W. Qiang ,&nbsp;Haowen Luo ,&nbsp;Harry F. Lee ,&nbsp;Shenjing He","doi":"10.1016/j.scs.2026.107128","DOIUrl":"10.1016/j.scs.2026.107128","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107128"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urban flood susceptibility decoded: A GeoAI workflow for urban flood-prone area delineation and mitigation mechanism inference","authors":"Junhao Wu ,&nbsp;Yuanpeng Tang ,&nbsp;Ling Ma ,&nbsp;Dongfang Liang ,&nbsp;Ioannis Brilakis ,&nbsp;Svetlana Besklubova","doi":"10.1016/j.scs.2026.107157","DOIUrl":"10.1016/j.scs.2026.107157","url":null,"abstract":"<div><div>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 (<span><math><mrow><msup><mrow><mi>R</mi></mrow><mn>2</mn></msup><mo>&gt;</mo><mn>0.98</mn><mo>,</mo><mrow><mspace></mspace></mrow><mi>A</mi><mi>U</mi><mi>C</mi><mo>≈</mo><mn>1.00</mn><mo>,</mo></mrow></math></span> and <span><math><mrow><mi>S</mi><mi>M</mi><mi>A</mi><mi>P</mi><mi>E</mi><mo>&lt;</mo><mn>13</mn><mo>%</mo><mo>)</mo></mrow></math></span>. 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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107157"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980948","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How to identify urban heat inequity? A systematic literature review of scales, indicators, pathways, and future directions","authors":"Yue Lin,&nbsp;Hui Zeng","doi":"10.1016/j.scs.2026.107130","DOIUrl":"10.1016/j.scs.2026.107130","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107130"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}