Sustainable Cities and Society最新文献

{"title":"A scalable and efficient framework for city-scale building energy modeling with microclimate considerations","authors":"Ke Liu ,&nbsp;Xiaodong Xu ,&nbsp;Deqing Lin ,&nbsp;Ran Zhang ,&nbsp;Linzhi Zhao ,&nbsp;Abudureheman Abuduwayiti ,&nbsp;Francesco Causone","doi":"10.1016/j.scs.2026.107187","DOIUrl":"10.1016/j.scs.2026.107187","url":null,"abstract":"<div><div>Urban building energy modeling (UBEM) is essential for supporting urban energy efficiency assessment and low-carbon policy making. This study proposes a scalable and efficient UBEM framework and applies it to Nanjing, China. Multi-source urban data were integrated to construct a unified urban building geodatabase. Building archetypes were developed based on building type and construction year, and modified weather files for each block were generated using the Urban Weather Generator (UWG). Through an automated workflow combining Python scripting and parallel computing, annual building energy simulations were conducted for 49,793 buildings across 1693 urban blocks. The comparative analysis reveals that neglecting microclimate effects results in an 11.4% underestimation of cooling demand and a 10.5% overestimation of heating demand, with the largest deviations occurring in high-density districts. The results also indicate notable variations in average energy use intensity (EUI) across building types, with healthcare and commercial buildings exhibiting the highest demand. Spatially, high-rise clusters in newly developed areas and large public facilities form major energy hotspots, whereas older low-rise residential areas show lower overall demand. A comparison with measured data showed that the simulated EUIs of public buildings were within ±20%, confirming the reliability of the framework. The proposed approach completed city-scale simulations within approximately 36 hours on standard hardware, highlighting its scalability and computational efficiency. Overall, this study provides a practical UBEM framework for identifying spatial patterns and energy hotspots of building energy use at the city scale, supporting energy-efficient urban planning and targeted mitigation strategies.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107187"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080992","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":"An interpretable stratified weighted network for uncovering spatially heterogeneous correlations between the built environment and nighttime urban vitality","authors":"Baoju Liu ,&nbsp;Zhiwei Zeng ,&nbsp;Kaiqi Chen ,&nbsp;Xiaoyong Tan ,&nbsp;Min Deng ,&nbsp;Zhiyuan Zhao ,&nbsp;Sheng Wu","doi":"10.1016/j.scs.2026.107194","DOIUrl":"10.1016/j.scs.2026.107194","url":null,"abstract":"<div><div>Understanding the correlations between the built environment and nighttime urban vitality (NTUV) is crucial for stimulating consumption and promoting sustainable urban development. However, existing models, influenced by spatial stratified and local heterogeneity, often suffer from local overfitting or underfitting, which makes it difficult to effectively capture the spatially heterogeneous correlations. In this study, we propose an interpretable stratified weighted network (SW-Net), which extends the traditional geographically weighted regression by introducing deep learning techniques. Specifically, the correlations are decomposed into shared patterns and local fluctuations. These components are estimated by the spatial stratification block and weight localization block in SW-Net, respectively, to model spatial stratified and local heterogeneity. SW-Net was applied to two case areas in Xiamen and Fuzhou and strongly outperformed eight baseline models. The results mainly show that (1) consumption activities are the key drivers of NTUV; (2) transportation infrastructure can facilitate nighttime human mobility and enhance NTUV; (3) nighttime cultural and tourism activities hold substantial potential to boost NTUV in both cities; and (4) a higher degree of land use mix does not necessarily lead to greater NTUV. The findings in this study can offer insights for advancing geographical relationship modeling and provide targeted policy suggestions for optimizing the built environment and enhancing NTUV.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107194"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147398998","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":"Moderating mechanisms of urban environment and vegetation structure in the cooling effect of urban green space: A case study of Glasgow","authors":"Jianhua Guo ,&nbsp;Weijia Wang ,&nbsp;Zhaowu Yu ,&nbsp;Siqi Jia ,&nbsp;Dong Liang ,&nbsp;Zhongchang Sun ,&nbsp;Huadong Guo","doi":"10.1016/j.scs.2026.107120","DOIUrl":"10.1016/j.scs.2026.107120","url":null,"abstract":"<div><div>Urban green spaces (UGS) play a vital role in alleviating surface urban heat island (SUHI) effects, yet the extent to which their cooling effects depend on vegetation structure, urban morphology, surface environmental conditions, and human activity remains insufficiently understood. This study addresses this gap by using interactive regression models to examine how these multidimensional factors jointly moderate the cooling effect of UGS in Glasgow, UK. Results reveal that the effectiveness of UGS cooling is enhanced by favorable vegetation characteristics: areas with taller canopies and higher tree cover ratios exhibit significantly stronger cooling effects, while increased grass coverage and greater spatial inequality of green space weaken the response. Built environments with greater building height and larger surface area, as well as more intense human activity measured by road density, population density, and nighttime light, reduce the marginal cooling effect of UGS. Meanwhile, higher land surface roughness enhances UGS cooling by promoting surface-atmosphere heat exchange, and the presence of surrounding surface water modifies the effectiveness of green space depending on spatial configuration. These findings underscore the context-dependent nature of UGS cooling and highlight the importance of integrating both internal vegetation structure and external urban context into the design of climate-resilient green infrastructure. Future planning should not focus solely on green space expansion but also prioritize optimizing spatial composition and embedding green systems within their surrounding built and natural environments to maximize ecosystem service gains.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107120"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399000","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":"Regulation of blue-green landscape fragmentation on day-night surface urban heat island: A case study of Kunming","authors":"Jiaxi Li ,&nbsp;Zihan Liu ,&nbsp;Zhenfeng Shao ,&nbsp;Huyan Fu","doi":"10.1016/j.scs.2026.107173","DOIUrl":"10.1016/j.scs.2026.107173","url":null,"abstract":"<div><div>Accelerating global urbanization has intensified the urban heat island (UHI) effect and exacerbated the fragmentation of blue-green landscapes (BGL) (i.e., water bodies and vegetation cover). While previous studies confirmed the mitigating impact of BGL on surface urban heat islands (SUHI), the dynamic influence mechanisms of their fragmentation on diurnal and seasonal SUHI intensity (SUHII) remain inadequately understood. Our study investigated Kunming, a representative plateau city, by integrating high-resolution land cover data with SUHII data. Using Pearson correlation analysis and generalized additive models, we systematically analyzed the diurnally differentiated impact mechanisms of six BGL fragmentation types (Intact, Interior, Dominant, Transitional, Patchy, and Rare) on the SUHII. The key findings: (1) BGL coverage reached 54.64 %, but the core area exhibited high fragmentation (Patchy + Transitional = 74.93 %). (2) SUHII showed spatial gradients (core &gt; middle &gt; expanded area), with stable nighttime values but significantly enhanced daytime intensity in summer. (3) Rare, Patchy, and Transitional types positively correlated with SUHII (<em>r</em> = 0.13 ∼ 0.60), while Dominant, Interior, and Intact types showed negative correlations (<em>r</em> = –0.03 ∼ –0.15). Crucially, their cooling effect demonstrated nonlinear enhancement when Intact/Interior exceeded 40 % coverage. Conversely, higher Patchy/Rare proportions exacerbated SUHII. (4) Patchy contributed most to diurnal SUHII (daytime: 56.47 %; nighttime: 51.59 %). The core and middle areas were dominated by highly fragmented types (Rare + Patchy &gt; 68.45 %), while the Transitional type shaped the expanded area. This study reveals the impact mechanism of BGL fragmentation on the SUHI, informing UHI mitigation via landscape optimization.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107173"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080596","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":"Unveiling the canopy heat trapping effect in green roofs: Thermo-dynamic mechanisms during subtropical urban heatwaves","authors":"Bingyin Chen ,&nbsp;Zhiquan Zhu ,&nbsp;Wanxue Zhu ,&nbsp;Xuemei Wang ,&nbsp;Weiwen Wang","doi":"10.1016/j.scs.2026.107177","DOIUrl":"10.1016/j.scs.2026.107177","url":null,"abstract":"<div><div>Amid accelerating global warming and intensifying urban heat islands, green roofs (GRs) are promoted as nature-based solutions for urban heat mitigation. However, their thermal performance in hot-humid subtropical climates remains underexplored, and observed warming phenomena are often overlooked. Here we use rooftop field experiments in Guangzhou, China, to compare GRs planted with Sedum spp. and Schefflera spp. against a bare roof during summer 2022 heatwaves. Combining high-frequency flux measurements, Bowen ratio energy-balance calculations and structural equation modelling, we analyse the mechanisms of roof–canopy thermal regulation. GRs reduced roof-surface temperature by 4–5 °C, associated with higher albedo (0.16–0.19 vs 0.10) and reduced net radiation (by 10–15 W m^-2). Yet at 30 cm height, daytime canopy air temperature over GRs was 0.5–0.7 °C warmer than over the bare roof, with this warming intensifying by 0.06–0.15 °C per 1 °C increase in ambient temperature above 30 °C. We term this vertically non-uniform response the canopy heat-trapping effect, and show that it arises from reduced within-canopy wind speeds and diminished latent heat fluxes under heat stress, which limit the upward export of cool air. These findings challenge the common assumption that GRs provide uniformly cooling effects, and highlight the need to explicitly consider canopy ventilation and plant physiological responses when designing GRs to enhance thermal resilience in heat-vulnerable subtropical cities.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107177"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080598","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":"Decentralized off-grid vehicle-to-building (V2B) operation: A reinforcement learning approach for optimal charge–discharge control of energy storage systems","authors":"Sanghoon Kim,&nbsp;Min Kyu Sim","doi":"10.1016/j.scs.2026.107169","DOIUrl":"10.1016/j.scs.2026.107169","url":null,"abstract":"<div><div>Recent advances in vehicle-to-everything (V2X) technology position electric-vehicle (EV) batteries as mobile energy-storage systems (ESSs), promising a new paradigm for power supply flexibility. However, prevailing centralized V2X operation scenarios and dynamic compensation schemes offer limited economic incentives for EV owners, hindering large-scale adoption. This study proposes a decentralized V2X scenario that treats EV owners as independent economic agents. It introduces a predetermined discharge tariff set at 70% of the contemporaneous time-of-use (ToU) electricity price, thereby offering clear, ex-ante profit expectations for all participants. Participations in V2X transactions are modeled as a time-dependent Poisson process. Within the proposed framework, we formulate an optimal ESS scheduling problem that minimizes the sum of electricity costs and ESS degradation costs for a commercial building equipped with photovoltaic (PV) generation, stationary ESS, and vehicle-to-building (V2B) interfaces. To solve this problem, we develop a world models-based reinforcement learning framework that performs multi-horizon forecasting of PV output and building load, using these forecasts as states to learn an optimal control policy. Compared with benchmark strategies, the proposed approach achieves a total cost reduction of up to 9.65% and attains near-global performance—within 1.57% of the optimality gap from the ideal strategy derived from perfect foresight data.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107169"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146006826","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":"Deployment of rooftop photovoltaic systems at the urban scale based on multi-objective optimization from the life cycle perspective","authors":"Xinrui Fu ,&nbsp;Qing Zhong ,&nbsp;Sophia Shuang Chen ,&nbsp;Xiaoshan Yang ,&nbsp;Jiajia Geng","doi":"10.1016/j.scs.2026.107197","DOIUrl":"10.1016/j.scs.2026.107197","url":null,"abstract":"<div><div>Solar photovoltaic (PV) systems are increasingly deployed on urban rooftops. The optimal deployment of solar PV systems in urban areas becomes important. Most optimization goals in the existing studies are expanding economic and environmental benefits. However, many studies take into account economic costs and benefits for only a few stages in the life cycle of solar PV systems, and the establishment of environmental benefit targets focuses more on the emission reduction stage. In addition, discrepant costs and benefits caused by building typology are often ignored in most optimization research at the city level. To address above limitations, this paper considers the whole life cycle of solar PV systems and introduces a multi-objective optimization framework for optimally deploying solar PV systems on different types of rooftops. Integrating building footprints and PV system parameters, the method determines the best locations and corresponding installed capacities of rooftop PV systems at the urban scale by simultaneously maximizing economic and environmental benefits. Various land use codes, power consumption modes, and key performance indicators are incorporated to evaluate the solutions of optimization. The approach enables scenario-based optimization of PV deployment considering evolving grid integration requirements. The method is applied to the six major urban districts of Nanjing, China. Results show that the optimized solar PV installed capacity can help meet 15 % of the household electricity demand and 7 % of industrial and commercial electricity demand. The investment payback periods of solar PV deployment on various types of buildings under different power consumption modes range from 6 to 13 years, while the energy payback periods remain consistently below 6 years. Different power consumption modes significantly influence the optimal installed capacity of an individual building. This study provides a comprehensive perspective on urban rooftop PV planning and offers practical insights for prioritizing rooftop PV development to achieve sustainable goals.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107197"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399433","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 “How does sun shading affect street commercial vitality? Evidence from street view images” [Sustainable Cities and Society, Volume 136, 1 January 2026, 107082]","authors":"Yuzheng Zhang ,&nbsp;Yan Lu ,&nbsp;Yiping Wang ,&nbsp;Xiaojian Chen","doi":"10.1016/j.scs.2026.107183","DOIUrl":"10.1016/j.scs.2026.107183","url":null,"abstract":"","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107183"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147399441","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 emission reductions from new energy vehicle adoption via integrated macro-micro data analysis","authors":"Tongtong Shang,&nbsp;Wei Wu,&nbsp;Pan Wu,&nbsp;Xiaoling Luo,&nbsp;Shan Han","doi":"10.1016/j.scs.2026.107167","DOIUrl":"10.1016/j.scs.2026.107167","url":null,"abstract":"<div><div>The transportation sector is a significant source of global carbon emissions, and widespread adoption of New Energy Vehicles (NEVs) is critical for mitigation. Existing studies, however, rely predominantly on macro-level scenario analyses and life cycle assessments (LCA), often lacking integration with real-world vehicle operation data to quantify the actual emission reduction impacts of growing NEV fleets. This study analyzes over one million traffic monitoring records from Chongqing (2019-2024) to characterize spatiotemporal evolution of urban road carbon emissions. We extract micro-scale travel characteristics based on travel distance and develop a K-ME-XGBoost-LSTM hybrid model to illuminate nonlinear relationships between NEV growth and traffic emissions. The results indicate that road network mileage, NEV penetration rate, travel distance, and travel speed are the primary determinants of emission levels. A critical finding is that significant emission reductions materialize only after NEV penetration exceeds a threshold of approximately 10%. Moreover, the mitigating effect on NOₓ emissions becomes progressively stronger than that on CO as the NEV share increases. Furthermore, within urban core areas, the adoption of NEVs effectively reduces the demand for long-distance travel using fuel-powered vehicles, thereby driving system-wide declines in emissions. Projections for the next five years (2025-2029) indicate that this positive emission reduction trajectory is likely to continue across multiple districts.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107167"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146080599","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":"Unravelling the non-linearity and spatial variation of the impact of urban landscape patterns on resident well-being: through an integrated CatBoost-SHAP and GTWR model","authors":"Jiao Liu ,&nbsp;Yaobin Liu ,&nbsp;Shuoshuo Li ,&nbsp;Guoen Wei ,&nbsp;Tongning Li","doi":"10.1016/j.scs.2026.107200","DOIUrl":"10.1016/j.scs.2026.107200","url":null,"abstract":"<div><div>Urban expansion constrained by topography and geomorphology has led to variations in urban landscape patterns (ULPs). Against the backdrop of ongoing global urbanization, adjusting ULPs to enhance residents' well-being (RWB) has become a key focus of SDG 11. This research uses rapidly urbanizing China as a case study to evaluate RWB across 285 cities from 2010 to 2022. A CatBoost-SHAP machine learning and GTWR models were employed to uncover the nonlinear relationships and spatiotemporal heterogeneity between ULPs and RWB. The findings reveal that: (1) From 2010 to 2022, the spatial distribution of RWB in China exhibited a \"peripheral uplift and central depression\" pattern, with regional disparities transitioning from \"spatial imbalance\" to \"regional coordinated development.\" (2) Among the ULPs factors, SHAPE-AM and CONTAG have the greatest impact on RWB, with contribution rates of 0.8% and 0.53%. Additionally, AI exhibits significant multi-threshold effects at 66.74, 76.68, and 87.87. (3) The interaction of low CONTAG and high LPI enhanced well-being, whereas the combination of low LPI and high SHAPE-AM suppressed it. (4) The influence of ULPs on RWB exhibited significant spatial clustering, forming \"patch-like\" groupings, with opposing effects observed in regions located on the second and third topographic steps. In terms of effect intensity, SHAPE-AM has the strongest influence on RWB, approximately 0.25, followed by SHDI, at around 0.05. This study offers empirical evidence to support customized strategies for enhancing RWB across various ULP conditions in China.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"138 ","pages":"Article 107200"},"PeriodicalIF":12.0,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147398999","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}