Sustainable Cities and Society最新文献

{"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":"2026-01-06","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":"Rooftop PV layout generation and optimization model for large-scale building cluster","authors":"Rui Miao ,&nbsp;Haoqing Zhu ,&nbsp;Yi Zhang ,&nbsp;Kanghua Li ,&nbsp;Yuan Yuan ,&nbsp;Pengyuan Shen ,&nbsp;He Qi","doi":"10.1016/j.scs.2026.107129","DOIUrl":"10.1016/j.scs.2026.107129","url":null,"abstract":"<div><div>Rooftop photovoltaic (PV) deployment at the cluster scale is critical for advancing urban decarbonization, yet existing methods often oversimplify available area estimation, neglect engineering constraints, and struggle to balance energy, economic, and environmental objectives. To address these gaps, this study proposes an integrated model comprising three modules: (1) high-fidelity identification of available rooftop area by explicitly excluding shadow area, obstacles with buffer zones, and maintenance pathways; (2) automated generation of 3D engineering-feasible PV layouts; and (3) a hybrid single- and multi-objective optimization with TOPSIS-based decision-making. Applied to a 245-building cluster in Shenzhen, the model identified 23,982 m² of available area (46.51 % ratio), more conservative than typical utilization-factor assumptions. It generated detailed 3D, module-level PV layouts for 198 buildings, enabling high-fidelity PV output simulation accounting for site-specific orientation, tilt, and shading. Across all budget levels, the optimized solutions outperformed 30,000 random alternatives, with internal rates of return ranging from 16.1 % to 19.2 %. Under the high-budget scenario, the CEB-optimal solution, which utilizes all technically feasible rooftops, achieves a 10-year cumulative energy yield of 61.61 GWh and carbon emission reductions of 27,725.59 t CO₂. By decoupling layout generation from optimization, the framework reduces computational complexity and enables efficient generation of optimized deployment solutions. The proposed framework facilitates large-scale rooftop PV deployment and contributes to the decarbonization of urban energy systems.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107129"},"PeriodicalIF":12.0,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929042","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":"2026-01-06","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":"Extreme wind events at the pedestrian level of an actual urban morphology: Statistical correlation and space-time evolution","authors":"Wei Wang,&nbsp;Yezhan Li,&nbsp;Naoki Ikegaya","doi":"10.1016/j.scs.2026.107121","DOIUrl":"10.1016/j.scs.2026.107121","url":null,"abstract":"<div><div>Extreme wind events at the pedestrian level in urban areas pose significant safety risks. While most previous studies have emphasized the statistical (“static”) aspect, the parameters that best characterize extreme values remain unclear, and few have explored their spatiotemporal (“dynamic”) evolution. To address these gaps, this study investigates both aspects using large-eddy simulation (LES) within a realistic urban morphology. The analysis integrates statistical correlations with spatiotemporal evolution to provide a comprehensive understanding of extreme winds in complex urban environments. Correlation results show that skewness has the strongest relationship with gust and peak factors, underscoring its potential for improving statistical models. Higher-order moments (up to the sixth) are mainly positively correlated with gust and peak factors, but their weak or moderate association with exceedance wind speed suggests that extreme events are mainly governed by the combined effects of mean flow and standard deviation, rather than gust or peak factors alone. Turbulence measures such as integral time scale, and peak frequency exhibit only marginal links to extremes. The spatiotemporal evolution is examined through conditional space–time proper orthogonal decomposition (CST-POD). Although the first CST-POD mode aligns well with conditional averages, over 75% of the energy resides in higher modes. Reconstructing weaker events requires multiple modes, particularly in sheltered regions, whereas dominant low-order modes near tall buildings allow accurate reconstruction with fewer modes. This study advances understanding of extreme winds by integrating statistical and dynamical perspectives, offering insights for improved urban wind risk assessment.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107121"},"PeriodicalIF":12.0,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145981021","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":"Ensuring reliable district heating systems: Identifying critical components under independent and cascading failure scenarios","authors":"Ding Mao ,&nbsp;Sai Xu ,&nbsp;Jay Wang ,&nbsp;Linhua Shen ,&nbsp;Wei He","doi":"10.1016/j.scs.2026.107118","DOIUrl":"10.1016/j.scs.2026.107118","url":null,"abstract":"<div><div>Urban district heating systems are vital infrastructures of sustainable cities, providing efficient and centralized thermal energy to residential and industrial users. However, these systems consist of numerous interdependent components that are prone to faults, which can disrupt heat supply and compromise service reliability. Identifying critical components to maintain system stability is crucial for enhancing the resilience and sustainability of urban energy infrastructure. Critical components are generally determined by evaluating the consequences of failures, which involves simulating all possible fault scenarios, a process that is computationally expensive and time-consuming. To address this challenge, we propose a comprehensive component importance identification framework. This framework incorporates two methods: the Importance Calculation Method (ICM), which operates under normal system conditions, and the Failure-Simulation-Based Method (FSM), which simulates failure consequences. These methods evaluate component criticality under both independent and cascading failure scenarios, incorporating topological and functional perspectives. To validate the proposed framework, gridded heating system models of varying scales, comprising 4-, 9-, 16-, and 25-node configurations, were developed. Applying the framework to these models revealed a strong correlation between ICM and FSM results: the topological importance index in ICM showed a high correlation with FSM’s functional consequence indices (<em>ρ</em> &gt; 0.75), while the functional importance indices achieved even higher correlations (<em>ρ</em> = 0.94–0.97). Finally, the framework was applied to a real-world district heating system in China, where it successfully identified critical pipes and demonstrated the effectiveness and practical value of the proposed ICM through comparison with traditional fault-simulation-based methods.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"137 ","pages":"Article 107118"},"PeriodicalIF":12.0,"publicationDate":"2026-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145929043","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":"Achieving sustainable development in coastal cities: Exploring the synergies between urban resilience and high-quality development","authors":"Tian Jing ,&nbsp;Huihui Wang ,&nbsp;Yunsong Yang ,&nbsp;Yemin Jin ,&nbsp;Weijun Yu ,&nbsp;Yuhao Zhong","doi":"10.1016/j.scs.2025.107112","DOIUrl":"10.1016/j.scs.2025.107112","url":null,"abstract":"<div><div>Coastal cities play a pivotal role in national economic growth and regional development, yet they are increasingly challenged by climate change, rapid urbanization, and environmental degradation. Balancing urban resilience (UR)―the capacity to withstand and adapt to shocks-with high-quality development (HQD)―the pursuit of sustainable, inclusive, and innovation-driven growth-has become a critical issue in achieving long-term coastal sustainability. This study proposes an integrated methodological framework that combines multi-dimensional evaluation, coupling coordination (CCD) modeling, and spatiotemporal regression analysis to quantitatively assess and interpret the dynamic interactions between UR and HQD in 55 Chinese coastal cities from 2010 to 2020, revealing their spatial heterogeneity, temporal evolution, and key driving mechanisms. Furthermore, a complex network analysis is employed on the UR–HQD coordination system to identify structural linkages and evolutionary patterns of their synergistic interaction over time. The results reveal pronounced spatial heterogeneity in the UR-HQD coordination degree, with the Yangtze River Delta and Pearl River Delta showing stable and high levels of synergy, while northern and southeastern coastal areas remain relatively weak. The overall coupling level has improved over time but still reflects persistent regional disparities. Green infrastructure investment, urbanization rate, and healthcare coverage emerged as key drivers enhancing synergy, whereas excessive resource dependence and ecological pressure hindered balanced development. The network analysis reveals an optimization of internal linkages toward more adaptive structures, characterized by a trade-off where rising modularity and local transitivity improve cluster robustness while reducing global integration efficiency. These findings offer empirical insights into the dynamic co-evolution of resilience and development and provide a reference for adaptive governance and coordinated policy design in coastal urban transformation.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"136 ","pages":"Article 107112"},"PeriodicalIF":12.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145927032","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":"BIKE (Bicycle Integration Key Elements) Index: Benchmarking urban bikeability and cycling readiness. Evidences from European capitals","authors":"Alejandro Quintero Gómez,&nbsp;Pablo Calvo-Bascones","doi":"10.1016/j.scs.2025.107096","DOIUrl":"10.1016/j.scs.2025.107096","url":null,"abstract":"<div><div>This study introduces the BIKE Index, a multi-dimensional and reproducible framework for evaluating urban cycling conditions across cities, developed in response to the lack of standardized tools for assessing bikeability in urban areas. The index integrates four key dimensions into a composite score: Cycling Infrastructure, Cyclist Services, Environmental Constraints, and Safety and Street Quality. The dimensions are derived from open data sources, and consistent geospatial methods, including urban perimeters derived from Local Administrative Units and a standardized set of 210 cycling routes per city.</div><div>The methodology is applied to thirteen European capital cities using harmonized data from OpenStreetMap, OpenRouteService, Eurostat, Google maps, and E-OBS climate datasets. The results reveal significant disparities in cycling conditions, with scores ranging from Amsterdam (best) to Rome (worst). While infrastructure emerges as the primary differentiator, services, environmental factors, and safety also play critical roles. These findings suggest that creating cycling-friendly cities requires coordinated progress across all four dimensions. The BIKE Index offers a transparent and scalable methodology for benchmarking cycling conditions, enabling consistent comparisons and supporting evidence-based planning and policy making strategies.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"136 ","pages":"Article 107096"},"PeriodicalIF":12.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145927033","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":"A network-based framework for cost-effective Green–Grey retrofitting of urban drainage systems","authors":"Ge Yang ,&nbsp;Bowei Zeng ,&nbsp;Wenjie Chen ,&nbsp;Guoru Huang","doi":"10.1016/j.scs.2025.107101","DOIUrl":"10.1016/j.scs.2025.107101","url":null,"abstract":"<div><div>Urban drainage retrofitting is often constrained by limited understanding of where and why subsystems fail. This study presents a network-based framework that links hydraulic diagnosis with cost-effective intervention planning. Using graph-based community detection, the drainage system was partitioned into 123 Urban Hydrological Response Units, enabling subsystem-scale assessment of pressure–capacity imbalance. Results show that only 9% of the network generated 83% of overflow (Gini = 0.65), a pattern stable across 5-, 20-, and 50-year storms. The Pressure–Capacity Index revealed two dominant failure mechanisms—impervious-driven runoff (71%) and upstream accumulation (28%). Evaluation of 45 retrofit scenarios showed that targeting upstream-loaded areas reduced unit costs by 52.5% compared with uniform deployment (0.68 vs. 1.43<span><math><mrow><mo>×</mo><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>4</mn></mrow></msup></mrow></math></span> CNY<!--> <!-->m⁻³ for 20-year storms). Grey upgrades were the most economical (0.30–0.90<span><math><mrow><mo>×</mo><mn>1</mn><msup><mrow><mn>0</mn></mrow><mrow><mn>4</mn></mrow></msup></mrow></math></span> CNY<!--> <!-->m⁻³), outperforming green and hybrid measures by factors of 9–15. Function-oriented strategies maintained higher resilience under intensified storms (9–15% performance loss) than hotspot-based approaches (35–45%). Pareto analysis identified diminishing returns beyond a 44-million-CNY investment for system-wide grey upgrades, whereas targeted interventions required only 20.08 million CNY to achieve comparable benefits. Relying solely on standard municipal datasets, the proposed framework enables cities to diagnose network vulnerabilities and design phased, mechanism-based retrofitting pathways under climate-exacerbated rainfall extremes.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"136 ","pages":"Article 107101"},"PeriodicalIF":12.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145885077","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 micro-environmental conditions of urban agrivoltaics: Advancing sustainable green spaces and agriculture in temperate cities","authors":"Caroline Merheb ,&nbsp;Joshua S. Caplan ,&nbsp;Cara Rydzewski ,&nbsp;Pralad Phuyal ,&nbsp;Jordan Macknick ,&nbsp;Nicholas Davatzes ,&nbsp;Sujith Ravi","doi":"10.1016/j.scs.2025.107091","DOIUrl":"10.1016/j.scs.2025.107091","url":null,"abstract":"<div><div>Agrivoltaics, the integrated land use combining renewable energy production and agriculture, can potentially address key challenges faced by urban communities, including limited access to vacant land, fresh produce, and electricity. However, urban agrivoltaics has rarely been considered a viable solution, primarily due to a lack of experimental systems demonstrating the functionality of urban food production or green spaces alongside solar energy production. To evaluate the potential of solar photovoltaics to help mitigate heat stress on urban agriculture and green spaces in a temperate climate, we examined the microclimatic changes introduced by an urban agrivoltaics system (UrAV) when combined with vegetable crops and turfgrass, respectively. Accordingly, we installed an experimental setup instrumented with environmental sensors to compare full-sun conditions with those of an agrivoltaics system designed for urban environments. We found minimal differences for both land cover types between the control and agrivoltaics sites in air and soil temperature. However, during periods of intensified summer heat, temperatures beneath the panels cooled due to reductions in wind speed and relative humidity, which impeded the movement of hot, moist air and reduced reference evapotranspiration. Further, soil moisture in UrAV was highly spatially heterogeneous, influenced by the layout of the photovoltaic panels and their support structure, which redistributed rainfall and controlled where solar radiation could penetrate and drive evapotranspiration. Overall, our results suggest that PV-induced environmental changes in temperate climates are compatible with cultivating turfgrass or appropriate crops. These findings can help planners and designers integrate agrivoltaics into community gardens, farms, and green spaces in temperate cities.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"136 ","pages":"Article 107091"},"PeriodicalIF":12.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145885089","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":"Heat-resilient neighborhoods: Design tool for arid cities","authors":"María Belén Sosa ,&nbsp;Erica Correa","doi":"10.1016/j.scs.2025.107093","DOIUrl":"10.1016/j.scs.2025.107093","url":null,"abstract":"<div><div>This work explores the critical role of urban planning and design in creating heat-resilient neighborhoods in arid cities. As global warming intensifies, cities in hot and arid regions face increasingly extreme temperatures that pose significant challenges to public health, infrastructure, and overall quality of life. The study examines a range of design strategies that urban planners can use to mitigate heat stress and increase resilience in these environments. Focusing on the development of a user-friendly design tool, the study offers practical solutions to help neighborhoods adapt to arid climates while improving thermal livability. The tool emphasizes heat-reducing urban planning strategies by quantifying the impact of feasible interventions to achieve efficient and sustainable neighborhood designs. The study was conducted in Mendoza - Argentina, an arid city in South America. The methodology included: (i) <em>in-situ</em> microclimate monitoring campaigns, (ii) simulation of 128 scenarios using Envi-MET software, (iii) development of statistical models, and (iv) development of the FORMA3T tool. The application of urban cooling design tools provides a responsible approach to planning that ensures the resilience of neighborhoods in arid cities. By providing data-driven and context solutions, this tool enables urban designers to make informed decisions that mitigate heat stress, improve quality of life, and promote long-term environmental sustainability.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"136 ","pages":"Article 107093"},"PeriodicalIF":12.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145885170","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}