Sustainable Cities and Society最新文献

{"title":"Synergistic dynamics of the thermal-energy-carbon nexus in the Yangtze River Delta: Spatiotemporal measurement, mechanisms, and spatial econometric analysis","authors":"Zhonglin Tang ,&nbsp;Yaxin Rao ,&nbsp;Min Fu","doi":"10.1016/j.scs.2026.107125","DOIUrl":"10.1016/j.scs.2026.107125","url":null,"abstract":"<div><div>Urban agglomerations are increasingly facing the compounded challenges of escalating thermal stress, rising energy consumption, and intensifying carbon emissions under climate change and the green transition. This study develops an integrated Thermal-Energy-Carbon (TEC) framework to evaluate the Coupling Coordination Degree (CCD) of cities in the Yangtze River Delta (YRD) from 2000 to 2022, addressing the pressing issues of urban sustainability and green transformation. By combining spatial econometrics, threshold models, and GeoShapley decomposition, this study introduces a comprehensive approach to understanding the complex dynamics of urban systems in the context of climate change. The results reveal that: (1) although CCD has steadily improved, it remains at a moderate level with significant interprovincial disparities, highlighting uneven spatial progress in addressing environmental challenges. (2) Key drivers of coordination, including land urbanization (lnland), R&amp;D investment (lnrd), and patch density (lnPD), significantly enhance CCD, whereas foreign direct investment (lnopen) suppresses coordination and financial development (lnfin) shows a negative local effect. (3) Spillover effects are asymmetric, with lnrd, lnfin, and lnPD generating positive spillovers, while industrial structure (lnind), lnopen, and green patents (lngreen) impose negative externalities. (4) A double-threshold effect of economic development (lngdp) illustrates the stage-dependent influence of R&amp;D investment, following a “strengthening–weakening–restrengthening” dynamic. Additionally, XGBoost + GeoShapley-based contribution decomposition highlights the significant positive impact of lnland and lnrd on CCD in the non-spatial dimension, while unveiling the nonlinear and heterogeneous effects of these factors. This study offers novel methodological insights, integrating thermal, energy, and carbon, and provides guidance for low-carbon urban transformations in response to environmental challenges.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107125"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980780","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":"Machine learning and causal attribution of urban heat in the Phoenix metropolitan","authors":"Negar Rahmatollahi ,&nbsp;Zhi-Hua Wang ,&nbsp;Yihang Wang ,&nbsp;Xueli Yang","doi":"10.1016/j.scs.2026.107145","DOIUrl":"10.1016/j.scs.2026.107145","url":null,"abstract":"<div><div>Exacerbated thermal environment is one of the most critical challenges in urban development, which causes degradation of air quality, environmental health, and ecosystem services. While there are many existing studies of attributing urban heat to various environmental factors, the underlying causal relationship explainable by these contributors remains largely underexplored. In this study, we conducted machine learning (ML) attribution of urban heat (measured by the land surface temperature LST) to two broad categories of contributors, viz. (a) local landscape characteristics (surface albedo, vegetation coverage, building density, and measure of anthropogenic activities) and (b) meteorological conditions (precipitation, humidity, wind, pressure, solar radiation, and soil moisture), using the Phoenix metropolitan, AZ as a testbed. Furthermore, we quantified the underlying causation between these environmental factors and LST using convergent cross mapping (CCM). It was found that solar radiation and vegetation coverage (NDVI) are the two most important determinants, both statistically and causally, of urban thermal environment. We also identified the impact of water content variables (precipitation, humidity, and soil moisture) that is not captured by ML attribution but emerges as causally significant. These findings help to deepen our understanding of the underlying mechanism that regulates the urban heat and its complex interplay with other environmental factors, which, in turn, will be informative to sustainable urban planning practices.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107145"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980782","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":"Exploring the patterns and optimization of high-density settlements to achieve zero-carbon heating in hot summer and cold winter area","authors":"Yuqiu Liu,&nbsp;Zhengnan Zhou,&nbsp;Yichen Han,&nbsp;Chaohong Wang,&nbsp;Yingkai Lian,&nbsp;Haoran Chen,&nbsp;Wenqi Bai,&nbsp;Zhuoyang Jia","doi":"10.1016/j.scs.2026.107152","DOIUrl":"10.1016/j.scs.2026.107152","url":null,"abstract":"<div><div>In China’s hot summer and cold winter (HSCW) area, historical policies have resulted in the absence of central heating. However, intensifying extreme weather and rising living standards recently have led to a surge in heating energy consumption, accompanied by substantial carbon emissions. This study explores the feasibility of achieving zero-carbon heating (ZCH) in the HSCW area, specifically deriving heating energy from electricity generated by photovoltaic (PV) systems. This paper first measures indoor temperature, energy consumption data, and simulates PV generation across 20 residential areas in two typical cities in the HSCW area, Wuhan and Shanghai. Then, sensitivity analysis and machine learning regression with Shapley additive explanations are conducted between 14 morphology parameters and 3 primary energy indicators: ratio of energy consumption to indoor-outdoor temperature difference, available qualified PV generation for heating energy consumption, and ratio of qualified surface area. Subsequently, the study employed multi-objective optimization to balance the energy indicators of three residential area prototypes: tower, slab, and courtyard. Analysis of measured data reveals that the openness index has the most significant influence on heating energy consumption, while facade area has the greatest impact on PV indicators. However, the trend in morphological parameters optimized for the ZCH objective varies depending on building type and plot size. Conclusively, all residential types can realize ZCH, with achievable proportions at 61.00% of slab-style, 37.30% of courtyard-style, and 18.35% of tower-style. This research proposes novel approaches for reducing carbon emissions in the HSCW high-density settlements, thus providing references for related cases.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107152"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980949","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":"Integrated impacts of cool coatings, street orientations, and height variability on urban cooling in 3D high-rise building arrays: CFD simulation","authors":"Tianyi Guan ,&nbsp;Jian Hang ,&nbsp;Qingman Li ,&nbsp;Lan Chen ,&nbsp;Guanwen Chen ,&nbsp;Hanying Dong ,&nbsp;Zhiwen Luo","doi":"10.1016/j.scs.2026.107127","DOIUrl":"10.1016/j.scs.2026.107127","url":null,"abstract":"<div><div>Using cool coatings on building envelopes and modifying urban morphologies, such as street orientations and building height variability, are recognized as effective urban cooling strategies. However, few studies evaluate the integrated cooling performance of these strategies in three-dimensional (3D) high-rise building arrays. Moreover, most existing performance evaluations of cool coatings focus on temperature drop, while rarely considering coating costs. As a novel contribution, this study systematically investigates the combined impacts of cool coatings (cool roofs (CR), cool roofs &amp; walls (CR&amp;W), cool roofs &amp; east-west walls (CR&amp;EWW), and cool roofs &amp; high-rise walls (CR&amp;HW)), street orientations (north-south vs. east-west), and building height layouts (uniform-height vs. varied-height) on building surface temperature and pedestrian-level microclimate under three summer solar heating conditions (8 am, 12 pm, and 4 pm) using computational fluid dynamics simulations. Uniquely, cooling intensity (°C/m²) is proposed to quantify the average surface temperature drop per unit of cool-coated surface area by incorporating coating costs into cooling performance evaluation. Results indicate that cool coatings reduce direct sunlit surface temperatures by up to 7.5 °C, with ensemble-average building envelope drops of 0.36–1.63 °C, while their impacts on pedestrian-level air temperature (drop &lt; 0.3 °C) and wind velocity ratio (variation &lt; 0.06) are minimal. CR&amp;W, CR&amp;EWW, and CR&amp;HW cause significantly greater ensemble-average temperature drops than CR; however, when coating costs are considered, CR&amp;W is less cost-effective than other configurations. CR&amp;EWW and CR&amp;HW offer a good trade-off between cooling effect and coating costs. Moreover, north-south orientation generally shows superior cooling performance with cool coatings over east-west orientation. Height variability differentially influences the cool coating performance for high-rise and low-rise buildings. This study offers valuable insights for optimizing the spatial deployment of cool coatings in compact subtropical cities.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107127"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980945","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":"Connection of cold-wet islands to mitigate urban thermal risk","authors":"Aokang Xu ,&nbsp;Jing Shi ,&nbsp;Haoyuan Feng ,&nbsp;Xiangyun Meng","doi":"10.1016/j.scs.2026.107143","DOIUrl":"10.1016/j.scs.2026.107143","url":null,"abstract":"<div><div>Under the synergistic effects of global climate change and rapid urbanization, the urban heat island effect is intensifying, posing significant challenges to sustainable urban development and public health and safety. Research indicates that the cooling impact of isolated cooling units on the urban thermal environment is limited, whereas networked cooling systems offer superior cooling benefits by improving landscape connectivity and functional integration. This study focuses on the main urban area of Wuhan, integrating morphological spatial pattern analysis, landscape connectivity assessment, and circuit theory to develop a cold-wet network (CWN). Subsequently, CWN communities were delineated based on connectivity, and the network’s robustness was evaluated under multiple attack strategies. Key conclusions include: The concept of the wet island complements the cold island to form the cold-wet island (CWI), providing a more comprehensive definition of cooling zones; Co-optimizing the structural components of CWN (i.e., CWIs and cold-wet corridors) significantly enhances network efficiency; Differentiated management of CWN communities, through localized optimization and cross-community coordination, strengthens overall network resilience; An actual attack strategy based on “shape-scale” metrics offers a quantitative basis for prioritizing CWI protection; Adding CWIs improves CWN robustness under actual attack scenarios, suggesting that increasing cooling units is a viable strategy for mitigating urban heat. This study aims to alleviate heat stress in the main urban area of Wuhan while providing a theoretical framework for climate-adaptive urban planning and sustainable development.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107143"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980942","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":"AI-integrated framework for green space optimization and air quality improvement: a futuristic approach toward sustainable urban development","authors":"Saidur Rahaman ,&nbsp;Dongmei Cai ,&nbsp;Yuhan Cheng ,&nbsp;Xing Wei ,&nbsp;Xianda Gong","doi":"10.1016/j.scs.2026.107117","DOIUrl":"10.1016/j.scs.2026.107117","url":null,"abstract":"<div><div>Air pollution remains a critical concern in rapidly urbanizing cities, where accelerated development and the uneven distribution and limited accessibility of green spaces exacerbate environmental challenges. Although urban green spaces can mitigate pollution, their effectiveness is often constrained by inadequate planning and management strategies. To address these issues, this study proposes a multi-stage, scenario-driven green space optimization framework that applies data-driven modeling approaches to spatially assess and maximize pollutant-specific air quality benefits. The proposed methodology integrates remote sensing data, classification algorithms, vegetation indices, and hyperspectral and bioclimatic indicators to assess canopy health, structural characteristics, and guide species-level tree selection. Additionally, a GIS-based decision support system was developed to enable real-time, adaptive urban planning using sensor-linked air quality data. To validate the framework, a comprehensive case study was conducted in Hangzhou, China from 2014 to 2024, evaluating air quality, vegetation health, and key environmental drivers to promote sustainable urban development. The results demonstrated significant reductions in CO, PM_2.5, PM₁₀, NO₂, and SO₂ across most regions, while a slight increase in O₃ was observed, highlighting the complex dynamics of secondary pollutants. The Random Forest–based optimisation framework reveals a nonlinear response of pollutant concentrations to NDVI–LAI enhancement, with PM_2.5 and PM₁₀ showing the most spatially coherent reductions under +10–20 % greening, while gaseous pollutants exhibit weaker, spatially heterogeneous responses; temporal quadrant analysis further indicates sustained-improvement dominance for NO₂ and SO₂, contrasted by greater instability and trade-off behaviour for O₃ and PM₁₀. The novelty of this study lies in introducing an AI-based optimization framework that leverages machine learning and spatial–temporal diagnostics to identify where and how urban green spaces can most effectively reduce different air pollutants, offering a practical decision-support approach beyond traditional correlation analyses. Future research should emphasize practical implementation by incorporating socioeconomic, health, and accessibility metrics to support the development of sustainable cities and a climate-resilient society.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107117"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929046","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":"Beyond urban hierarchy: unveiling the spatial patterns of nonhierarchical carbon emissions","authors":"Jianyu Li,&nbsp;Mingxing Hu,&nbsp;Shumin Wang,&nbsp;Ziye Liu,&nbsp;Jingyue Huang","doi":"10.1016/j.scs.2026.107160","DOIUrl":"10.1016/j.scs.2026.107160","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107160"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146038973","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":"Towards sustainable social housing: An integrative life cycle and multi-criteria approach","authors":"Ximena Luque Castillo ,&nbsp;Lorena Yepes-Bellver ,&nbsp;Victor Yepes","doi":"10.1016/j.scs.2026.107164","DOIUrl":"10.1016/j.scs.2026.107164","url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107164"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146039041","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":"Anthropogenic heat amplification in industrial zones: Unraveling heat stress risk heterogeneity in river-sea dual-core cities","authors":"Yujie Li ,&nbsp;Jingfu Cao ,&nbsp;Mingcai Li ,&nbsp;Song Jiang ,&nbsp;Jie Yang ,&nbsp;Rui Xin ,&nbsp;Ping Qu ,&nbsp;Jing Chen ,&nbsp;Jing Wang","doi":"10.1016/j.scs.2026.107151","DOIUrl":"10.1016/j.scs.2026.107151","url":null,"abstract":"<div><div>River-sea dual-core cities exhibit marked climatic disparities between coastal and inland zones. A comprehensive analysis is therefore needed to reveal how urban form, geography, and industry jointly shape heat stress. Taking Tianjin as a representative case, this study employs an integrated approach that combines multi-source remote sensing, field surveys, and a dense meteorological station network to develop a practical assessment framework for these complex thermal dynamics. Our findings reveal three distinct thermal regimes governed by different mechanisms: compact urban cores experience intense dry heat driven by building density; coastal areas face significant humid heat stress due to marine influence and sea breeze dynamics; and specialized industrial zones create thermal anomalies that transcend conventional local climate zone (LCZ) classifications. The research demonstrates that while LCZ framework captures urban morphological variations, it requires substantial refinement to incorporate geographical context and industrial processes. Notably, our case study of the Wangkou industrial cluster shows that intensive energy consumption generates an average anthropogenic heat flux of 6.7<strong>–</strong>8.9 W/m², substantially reshaping local microclimates. This pattern challenges conventional urban classification systems. In response to these distinct thermal regimes, we recommend implementing zonal mitigation strategies, including cool infrastructure in urban cores, ventilation corridors in coastal areas, and specialized thermal regulations for industrial zones. This study proposes a transferable framework for assessing urban heat risks and offers scientific support for spatially-optimized, climate-resilient planning in similar cities globally.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107151"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980947","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":"Cold stress mitigation by urban trees: Computational fluid dynamics analysis of deciduous and evergreen effects in winter environments","authors":"Geon Kang ,&nbsp;Wonsik Choi ,&nbsp;Jeong-Hee Eum ,&nbsp;Jae-Jin Kim","doi":"10.1016/j.scs.2026.107131","DOIUrl":"10.1016/j.scs.2026.107131","url":null,"abstract":"<div><div>Extreme cold surges, increasingly observed in mid-latitude and subtropical cities, pose serious health and safety risks for pedestrians. While nature-based solutions such as urban trees are widely recognized for mitigating summer heat, their wintertime effects remain underexplored and inconsistent. Trees can simultaneously reduce convective heat loss by lowering wind speeds and diminish solar radiation, decreasing the mean radiant temperature (MRT) and potentially aggravating cold stress. This study employs a computational fluid dynamics (CFD) model, with one-way, offline coupling to a radiation model, to investigate how deciduous and evergreen trees influence pedestrian cold stress, evaluated using the Universal Thermal Climate Index (UTCI), in a high-density urban district of Daegu, South Korea, during a winter cold-surge event. Scenarios varied tree type and height to assess aerodynamic drag, shading, and cooling effects. Results show that wind speed was the dominant driver of UTCI (Pearson correlation coefficient, <em>R</em> ≈ –0.97), while air temperature (<em>R</em> ≈ 0.3) and MRT (<em>R</em> ≈ 0.15) acted as secondary modifiers. Evergreen trees reduced strong wind probabilities and alleviated severe cold stress (UTCI ≤ –13 °C) in exposed zones, with tall evergreens most effective during morning and nighttime. In contrast, in sheltered low-rise areas where winds were already weak, added shading lowered MRT and air temperature, leading to worsened thermal comfort in the afternoon. Deciduous trees had limited effects owing to low winter leaf area. These results emphasize that winter planting strategies must consider tree type, canopy height, and local morphology, with evergreens suited to wind-exposed corridors and deciduous or shorter trees more appropriate for sheltered zones.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107131"},"PeriodicalIF":12.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981020","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}