Sustainable Cities and Society最新文献

{"title":"Analyzing the impact of urban morphology on urban land surface temperature from the perspective of spatial configuration and explainable machine learning: A case study of seven cities","authors":"Bo Wan,&nbsp;Ningjie Shen,&nbsp;Haijian Zhang,&nbsp;Qiang Sheng","doi":"10.1016/j.scs.2026.107165","DOIUrl":"10.1016/j.scs.2026.107165","url":null,"abstract":"<div><div>Urbanization has led to frequent heatwaves and urban heat islands (UHIs). While the impact of building density and other factors on land surface temperature (LST) has been studied, the mechanisms of spatial configuration remain unclear. We conducted a comparative study across seven cities (Beijing, Hangzhou, Nanjing, Shanghai, Wuhan, Zhengzhou and Changsha), integrating summer LST data with multidimensional morphological indicators. We applied both linear and machine learning models, and used SHAP (Shapley Additive exPlanations) to interpret the contribution and thresholds of variables. The results show that incorporating spatial configuration significantly improves explanatory power, and machine learning outperforms linear models. High-intensity development generally increases LST, while vegetation and mixed land use reduce LST, both exhibiting threshold effects: tree canopy cover beyond approximately 15% shows diminishing marginal cooling effects, and proximity to water bodies within 300 meters creates significant cooling (cold island) effects. Spatial configuration has a critical and nonlinear influence on LST, offering an evidence base for multidimensional, synergistic heat island mitigation and urban planning decisions.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107165"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080597","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":"Diagnosing urban heat vulnerability through multiscale spatial modelling: Evidence from Istanbul for climate-resilient cities","authors":"Yusuf Eminoğlu ,&nbsp;Hüseyin Murat Çelik","doi":"10.1016/j.scs.2026.107190","DOIUrl":"10.1016/j.scs.2026.107190","url":null,"abstract":"<div><div>Urban heat vulnerability poses significant and escalating risks, especially in rapidly urbanizing metropolitan areas such as Istanbul. This study introduces an advanced, spatially explicit framework—the Surface Urban Heat Island Vulnerability Index (SUHI VI)—to accurately quantify and map neighborhood-level heat vulnerability across the Istanbul metropolitan region. The SUHI-VI integrates thirteen carefully selected variables spanning exposure (e.g., land surface temperature, impervious surface ratio), sensitivity (e.g., poverty rate, elderly and young population ratios, illiteracy rate), and adaptive capacity (e.g., tree canopy height, vegetation indices, access to green spaces, healthcare facilities, and income levels). The methodological innovation lies in employing a supervised Principal Component Analysis (PCA), which aligns component weighting with empirically observed urban heat anomalies, significantly enhancing both interpretability and practical applicability. Spatial modeling techniques including Multiscale Geographically Weighted Regression (MGWR) and Local Indicators of Spatial Association (LISA) revealed pronounced spatial heterogeneity in vulnerability determinants, highlighting central districts like Esenyurt, Bağcılar, and Gaziosmanpaşa as critical hotspots characterized by compounded demographic pressures and infrastructural deficits. Conversely, peripheral districts such as Şile and Beykoz displayed considerably lower vulnerability due to favorable ecological conditions and higher adaptive capacities. A spatially explicit policy matrix was subsequently developed, combining vulnerability levels and diagnostic model uncertainty to prioritize targeted adaptation strategies effectively. This replicable and scalable framework offers a robust decision-support tool for urban resilience planning, providing actionable insights for equitable and climate adaptive urban governance, applicable to other complex metropolitan regions.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107190"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399066","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":"Corrigendum to “Urban ecological risk and social vulnerability assessment for equitable climate resilience planning in Siliguri, India” [Sustainable Cities and Society, 136 (2026), 107113]","authors":"Alok Das ,&nbsp;Sayanti Poddar ,&nbsp;Javed Mallick ,&nbsp;Hoang Thi Hang ,&nbsp;Swapan Talukdar","doi":"10.1016/j.scs.2026.107176","DOIUrl":"10.1016/j.scs.2026.107176","url":null,"abstract":"","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107176"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399440","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":"Driving factors of summer diurnal land surface temperature in built-up blocks and planning support tool: A case from four Bohai Rim cities","authors":"Jun Zhao ,&nbsp;Fei Guo ,&nbsp;Mingxuan Luo ,&nbsp;Hongchi Zhang","doi":"10.1016/j.scs.2026.107170","DOIUrl":"10.1016/j.scs.2026.107170","url":null,"abstract":"<div><div>The relationship between urban spatial structure and thermal environment has been extensively investigated, with substantial progress in geographic coverage and the number of case cities. However, cross-city analyses of nonlinear diurnal thermal environment responses to built-up environment indicators in temperate and cold coastal cities require further case-based evidence. And the translation of scientific mechanism into actionable planning parameters remains insufficiently explored. In response, this study takes four Bohai Rim coastal cities as cases and employs the urban block as the analysis unit to develop a novel multi-objective optimization framework. By coupling an adaptive Non-dominated Sorting Genetic Algorithm III (NSGA-III) with interpretable eXtreme Gradient Boosting (XGBoost), the developed framework quantifies the drivers of both diurnal land surface temperature (LST) and its diurnal temperature amplitude (DTA), as well as the interactions among key parameters. Based on this, it derives feasible regulatory ranges for key urban planning indices, thereby translating thermal response mechanisms into actionable planning controls. The results indicate pronounced threshold effects in the influence of individual parameters on LST. The main findings are as follows: (1) Aspect ratio (AR), normalized difference vegetation index (NDVI), and normalized difference built-up index (NDBI) exert prominent effects on the DTA; (2) Socio-demographic and other factors exhibit strong interactions with nighttime LST; (3) The planning-support model indicates that urban form by vertical compactness (e.g., high floor area ratio (0.5–4.04), medium-to-high average height (&gt; 12 m)), low building density (0.13–0.26), and open type effectively balance diurnal LST. This study bridges mechanistic analysis with planning practice, offering a scalable decision-support framework for climate-adaptive urban design.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107170"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080996","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":"Modeling the synergistic impact of intelligent transport systems and citizen engagement on urban outcomes: A simulation-based analysis using artificial neural networks","authors":"Zhao Jiang ,&nbsp;Dan Chen ,&nbsp;Maryam Soltani-Parsa ,&nbsp;Sh. Baghaei","doi":"10.1016/j.scs.2026.107193","DOIUrl":"10.1016/j.scs.2026.107193","url":null,"abstract":"<div><div>This study shows the synergistic effects of Intelligent Transportation Systems (ITS) and citizen engagement on key urban outcomes—namely, traffic congestion, air quality, and economic activity—within the context of smart city development. While conceptual links between smart transportation and urban performance are acknowledged, quantitative analyses of the interplay between technological infrastructure and social factors remain scarce. We developed a simulation-based approach using an Artificial Neural Network (ANN) model trained on a synthetically generated dataset comprising over 50 scenarios that represent varying levels of ITS implementation and citizen engagement (0–100%). The ANN architecture consisted of two input neurons, one hidden layer with five neurons, and three output neurons, which was validated through k-fold cross-validation. Results demonstrate positive synergies: both factors contribute to improvements, but citizen engagement has a disproportionately strong influence on air quality and economic activity. Sensitivity analysis confirms the robustness, while a comparison with linear regression validates the ANN's superior performance in capturing nonlinear relationships. We propose specific target thresholds for planners and discuss implications for sustainable urban mobility, particularly in developing contexts where rapid urbanization demands efficient resource allocation. The study concludes that smart transportation policies must couple technological deployment with robust community participation strategies to maximize urban outcomes. The results show significant synergistic effects, as the ANN model achieved high predictive accuracy (R²: 0.92, 0.89, 0.85) and suggest a potential inflection point near 60% citizen engagement, beyond which the simulated economic and environmental benefits accelerate more markedly.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107193"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147398997","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":"Integrating energy hubs into smart cities using a decentralized optimization framework: Advancing the transition to low-carbon urban energy systems","authors":"Fan Liu ,&nbsp;Wenbiao Liang ,&nbsp;Emad Nematbakhsh ,&nbsp;Cheng-To Lin","doi":"10.1016/j.scs.2026.107201","DOIUrl":"10.1016/j.scs.2026.107201","url":null,"abstract":"<div><div>The integration of energy hubs into interconnected energy and carbon management systems is a pivotal step toward achieving decarbonized, sustainable, and intelligent urban energy infrastructures. This paper proposes a bi-level distributed optimization framework that enables the coordinated operation of multi-energy hubs while ensuring system-wide efficiency. At the lower level, the model captures the techno-economic behaviors of industrial agents, including flexible production lines, multi-energy storage units, and vehicle-to-grid (V2G)-enabled parking facilities, under uncertainty. A Conditional Value at Risk (CVaR)-based strategy is employed to mitigate operational and environmental risks. The upper level, supervised by a smart grid operator, ensures network-constrained dispatch and balanced energy-carbon flows using a DistFlow-based representation of the distribution network. Coordination between the two levels is achieved through an adaptive Alternating Direction Method of Multipliers (ADMM) that dynamically adjusts penalty parameters to accelerate convergence while minimizing communication needs, an essential feature for privacy-preserving smart city architectures. Simulation results on a modified 118-bus distribution system with 34 industrial energy hubs indicate reductions of up to 21.78% in total operating costs and 18.72% in carbon emissions, while substantially enhancing robustness against system uncertainty. Furthermore, the additional implementation on a 594-bus distribution system with 285 industrial energy hubs confirms the scalability of the proposed adaptive ADMM algorithm to large-scale multi-hub networks. Overall, the proposed architecture offers a scalable and intelligent solution for the coordinated operation of multi-energy systems in sustainable smart city environments.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107201"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399002","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":"Measuring the cumulative cooling effects from 3D building and tree shading in high-rise and high-density urban environments","authors":"Yuchen Xie ,&nbsp;Bin Chen","doi":"10.1016/j.scs.2026.107188","DOIUrl":"10.1016/j.scs.2026.107188","url":null,"abstract":"<div><div>Building and tree shading are crucial strategies to mitigate urban heat islands and reduce heat exposure, thereby playing a vital role in improving thermal environments and promoting urban sustainability. However, previous studies have primarily focused on microscale simulations or simple measurements of shadow indices, lacking a systematic understanding of the synergistic shading effects and shadow morphology in the complex urban context. Moreover, the spatial coupling between different shading types and human heat exposure patterns remains insufficiently explored. To address these issues, this study integrated multi-source remote sensing data and shading simulation with statistical models to examine the relationships between land surface temperature (LST) and various shading types and morphologies across different Local Climate Zones (LCZ) and seasons. We further proposed to employ geographically weighted machine learning models to characterize nonlinear effects of key shadow types and morphologies and examine heat exposure risk for vulnerable population groups based on the Shadow Exposure Index (SEI). Results show that building shading achieves highest cooling in high-density urban areas, whereas tree shading is more effective in open, vegetated zones. The spatial pattern and continuity of shading resources are critical, while double shading can synergistically enhance cooling, excessive aggregation of shadows may lead to diminishing returns due to restricted evaporation. Shade resources and heat exposure are highly unevenly distributed, with vulnerable groups facing greater risks. These findings could provide a scientific basis for accurately allocating shading resources, optimizing urban thermal management, and promoting social and environmental justice.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107188"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399068","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":"Quantifying the nonlinear interactions of 2D/3D building and green space morphology on land surface temperature across different urban functional zones","authors":"Haiyan Luo ,&nbsp;Rui Zhou ,&nbsp;Chunlin Li ,&nbsp;Qun Ma ,&nbsp;Xuening Fang ,&nbsp;Yina Hu ,&nbsp;Xinlin Lv ,&nbsp;Zining Dong ,&nbsp;Yujing Tian ,&nbsp;Shubo Fang","doi":"10.1016/j.scs.2026.107175","DOIUrl":"10.1016/j.scs.2026.107175","url":null,"abstract":"<div><div>Rapid urbanization and global warming have exacerbated the deterioration of the urban thermal environment and its adverse effects. Urban spatial pattern, as an important approach to regulating the urban thermal environment, has increasingly drawn academic attention for its influence on land surface temperature (LST). Although numerous studies in this field, quantitative research on the comprehensive effects and nonlinear interactions of 2D/3D building and green space morphology on LST remains scarce, particularly from urban functional zones (UFZs) perspective. Therefore, this research took Shanghai as a case study and utilized multi-source datasets, such as building outlines, green space distribution, and canopy height, to quantify the combined and interactive effects of building and green space morphology on LST across various UFZs, applying the XGBoost-SHAP model. The results indicated that (1) LST varied with UFZs. Biophysical parameters and building morphology accounted for a greater proportion of the effects on LST. The main factors influencing LST differed significantly across distinct UFZs, but showed some similar laws. (2) Within different UFZs, the influence of the dominant factors on LST showed significant spatial differences and threshold effects. Among them, BCR was the main warming factor, with thresholds of 24.64 %, 36.25 %, 23.22 %, and 33.64 % respectively in residential, commercial, public service, and industrial zones. Conversely, NDVI was the primary cooling factor with thresholds of 0.35, 0.23, 0.37, and 0.29, respectively. (3) The LST in different UFZs was affected by the interaction between building and green space morphology metrics. The synergistic interaction between high FAR and high BCR contributed to the reduction of LST in residential and commercial zones. In areas with high BCR, the cooling effects could be achieved in the commercial zone (when BH_SD was &lt;15 m), in public service zone (when MTH was &lt;3 m), and industrial zone (when NDVI and BSA was both greater than 0.2, and MBH exceeded 10 m). Our research findings can provide more targeted scientific evidence and decision support for the pattern optimization and planning design of buildings and green spaces aimed at improving the urban thermal environment.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107175"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080990","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":"Thermal resilience in the built environment: A critical review","authors":"Yingyue Li ,&nbsp;Eirini Tsouknida ,&nbsp;Tom Collins ,&nbsp;Ashley Bateson ,&nbsp;Rui Tang ,&nbsp;Esfandiar Burman","doi":"10.1016/j.scs.2026.107180","DOIUrl":"10.1016/j.scs.2026.107180","url":null,"abstract":"<div><div>With the increasing frequency and severity of extreme weather events including heatwaves and cold snaps, enhancing thermal resilience has become a critical priority for the built environment. Existing studies offer advanced knowledge on building overheating risk, resilient cooling, and related adaptation strategies, but often remain fragmented and focused on isolated topics. Despite this growing body of research, no comprehensive review has yet synthesized these developments. This paper presents a comprehensive review of more than 100 peer‑reviewed journal articles on thermal resilience in the built environment, covering definitions, application domains, disturbance categories, scenario construction, and performance evaluation methods. The review critically examines current research trends from a broader perspective and reveals the diversity in current approaches. This paper further proposes a cross-scale framework linking urban and building thermal resilience and offers practical recommendations for different stakeholders. It also advocates integrating climate resilience with net-zero targets for the transition to a robust and future-ready built environment.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107180"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081081","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":"Recent advancements in blockchain-enabled Digital Twins for sustainable energy systems in urban development: A review","authors":"Farzaneh Mohammadi ,&nbsp;Seyed Hamid Montazeri ,&nbsp;Fatemeh Sadat Ayatollahi ,&nbsp;Masoud Emamian Verdi ,&nbsp;Samaneh Danaeifar ,&nbsp;Zahra Dehghani Arani ,&nbsp;Hamid Reza Pilehvar Javid ,&nbsp;Fatemeh MotieShirazi ,&nbsp;Rosa Tayebli ,&nbsp;Samaneh Mohammadisharmeh ,&nbsp;Danial Buruni ,&nbsp;Mohammad Hossein Alizadeh Roknabadi ,&nbsp;G.B. Gharehpetian","doi":"10.1016/j.scs.2026.107179","DOIUrl":"10.1016/j.scs.2026.107179","url":null,"abstract":"<div><div>Urban environments are sophisticated ecosystems with detailed energy needs, and identifying solutions that improve both efficiency and security is essential for sustainable development. Digital twin (DT) technology has emerged as a promising tool for optimizing energy efficiency in smart cities. However, its widespread adoption is hindered by concerns over data integrity, interoperability, and cybersecurity. Blockchain (BC) technology offers a compelling solution by providing decentralization, transparency, and a tamper-proof data architecture. While existing studies recognize the potential of DTs, their scope remains limited; they neither address how BC-enabled DTs can solve critical shortcomings nor sufficiently explore specialized applications within sustainable urban energy systems. Therefore, this review paper aims to explore how BC enables DTs for sustainable energy systems in urban development by addressing the following research goals: identifying the main categories, architectures, and design models of BC-enabled DTs; evaluating their SWOT analysis; pinpointing unresolved research gaps in their integration; and outlining future opportunities to enhance their effectiveness. A structured literature review using the Web of Science was conducted, resulting in the selection of 481 documents. A SWOT analysis then examines the combined potential of these technologies across key sustainable energy domains. The paper further highlights the role of urban DTs in supporting smart city development across urban planning, mobility, water systems, climate resilience, and governance. Our analysis reveals that BC-enhanced DTs can significantly improve data security, operational transparency, and system resilience, while also identifying persistent challenges such as scalability, regulatory alignment, and technical integration. Major outcomes indicate a growing trend toward AI-augmented, decentralized DT architectures, though interdisciplinary collaboration and standardized frameworks remain underdeveloped. The paper concludes by outlining critical research gaps and future directions, emphasizing the need for holistic architectures, policy-supportive ecosystems, and real-world pilot implementations to advance sustainable urban energy systems.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107179"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146081083","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}