Sustainable Cities and Society最新文献

{"title":"Spatio-temporal assessment of outdoor thermal comfort dynamics in residential neighbourhoods using the TOPSIS method: A novel approach for arid climates","authors":"Archana Singh ,&nbsp;Tarush Chandra ,&nbsp;Sanjay Mathur ,&nbsp;Jyotirmay Mathur","doi":"10.1016/j.scs.2025.106379","DOIUrl":"10.1016/j.scs.2025.106379","url":null,"abstract":"<div><div>Understanding outdoor thermal comfort (OTC) in residential neighbourhoods is vital for climate-responsive urban planning, particularly in arid climates. While OTC has been studied at the urban–rural scale, intra-urban variations across different built forms remain underexplored. Urban areas in hot and arid regions experience significant thermal stress, yet effective methods for identifying thermally vulnerable zones are still lacking.</div><div>This study uses the Local Climate Zone (LCZ) classification to analyze air temperature variations in Jaipur, India, across the summer, winter, and autumn seasons. Empirical surveys were conducted over seven consecutive days in each season. The TOPSIS method was then applied to rank LCZs based on their proximity to optimal thermal conditions. This approach facilitated the identification of thermally vulnerable areas and efficient urban configurations. The novelty of this study is the use of the TOPSIS method to systematically and cost-effectively assess thermal comfort for urban climate planning.</div><div>Results indicate that LCZ 3₂ exhibited the most favorable thermal conditions in summer, whereas LCZ 2 experienced the highest thermal stress. In winter, LCZ 4₁ was the most thermally comfortable during the day, while LCZ 3₂ remained optimal at night. Seasonal comparisons revealed that temperature variations were more pronounced between LCZs than within them, with maximum UHI intensities reaching 11.35 °C in winter, 10.38 °C in summer, and 9.25 °C in autumn. Notably, LCZs with non-uniform building heights exhibited reduced diurnal temperature fluctuations, and LCZ 9, characterized by an organic configuration, outperformed the orthogonal LCZ 6.</div><div>The study underscores the need for thermal mapping as a strategic tool for urban climate adaptation, providing a novel methodological framework to mitigate thermal stress.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"126 ","pages":"Article 106379"},"PeriodicalIF":10.5,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143882966","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":"Potential links between the progress in environmental governance and the prevalence of mental disorder burden: New insight from a dynamic panel-data analysis for 197 countries","authors":"Jun-Yan Xi ,&nbsp;Li-Chang Chen ,&nbsp;Xue-Qi Li ,&nbsp;Jie Hu ,&nbsp;Wei Hu ,&nbsp;Jian-Jun Bai ,&nbsp;Yi-Ning Xiang ,&nbsp;Yu-Can Zhang ,&nbsp;Jia-Jia Wang ,&nbsp;Shi-Hao Wang ,&nbsp;Jing Gu ,&nbsp;Yuan-Tao Hao ,&nbsp;Xiao Lin","doi":"10.1016/j.scs.2025.106389","DOIUrl":"10.1016/j.scs.2025.106389","url":null,"abstract":"<div><h3>Background</h3><div>Little is known about the extent to which addressing the serious challenges of environmental governance can alleviate the burden of mental disorders. This study aims to examine the potential association between the Environmental Performance Indicator (<em>EPI</em>) and the burden of mental disorders.</div></div><div><h3>Methods</h3><div>We measured the burden of mental disorders [loss of healthy life expectancy (HLE) due to mental disorders] and the <em>EPI</em> [Climate Change Mitigation (CCH), Air Quality (AIR), Sanitation and Drinking Water (H2O), and Heavy Metals (HMT)] for 197 countries from 1995 to 2019. The dynamic panel model was used to investigate the dynamic relationships between the <em>EPI</em> and the burden.</div></div><div><h3>Results</h3><div>For every 1-point increase in CCH, AIR, H2O, and HMT, the loss of HLE due to mental disorders decreased by 31.839 (95 % confidence interval: 7.777∼55.900), 281.229 (137.504∼424.953), -188.598 (-367.575∼-9.621), and 331.589 (136.714∼526.465) person-years per 100,000 people, respectively.</div></div><div><h3>Conclusion</h3><div>The advancement of sanitation and drinking water within the <em>EPI</em> does not appear to have had a favorable impact on reducing the burden of mental disorders. Efforts to reduce toxic by-products that may form during water treatment and include them in the assessment of the <em>EPI</em> may have potential benefits in reducing the burden of mental disorders.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"126 ","pages":"Article 106389"},"PeriodicalIF":10.5,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143859661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Urban flood risk evaluation using social media data and Bayesian network approach: A spatial-temporal dynamic analysis in Wuhan city, China","authors":"Yihan Zhang ,&nbsp;Jian Fang ,&nbsp;Dingtao Shen ,&nbsp;Wentao Yang ,&nbsp;Xiaoli Wang ,&nbsp;Lili Lyu","doi":"10.1016/j.scs.2025.106388","DOIUrl":"10.1016/j.scs.2025.106388","url":null,"abstract":"<div><div>Under the dual impacts of urbanization and climate change, urban flooding has become one of the major threats to urban development, while the spatial-temporal evolution of urban flood risk remains unclear. In this study, we delineated the inundation areas of flooding in Wuhan from 2012–2023 using social media data and assessed urban flood risk through a Bayesian network based approach. Furthermore, future risks were evaluated considering various climate and land use scenarios. The results show that flood events are mainly concentrated in the central part of the city. Road density and impervious surfaces are identified as the primary factors influencing flooding. The proportion of high-risk areas will increase by an average of 3.13 % (from 14.66 % to 17.79 %) in 2100 under the SSP5–8.5 and SSP2–4.5 scenarios compared to the historical period. Land use alterations have a greater influence in the southern region. In contrast, variations in precipitation have a more substantial impact in the northern region and the influence of land use change is more significant compared to precipitation change. This study indicates that the Bayesian network model can effectively depict the complex process and probabilistic characteristics of urban floods. Integrated with future climate and land use scenarios, this approach would provide a scientific basis for the refined management of flood risk under climate change, thereby enhancing urban resilience.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"126 ","pages":"Article 106388"},"PeriodicalIF":10.5,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864021","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":"Energy consumption prediction for water-based thermal energy storage systems using an attention-based TCN-LSTM model","authors":"Jianjie Cheng ,&nbsp;Shiyu Jin ,&nbsp;Zehao Zheng ,&nbsp;Kai Hu ,&nbsp;Liang Yin ,&nbsp;Yawen Wang","doi":"10.1016/j.scs.2025.106383","DOIUrl":"10.1016/j.scs.2025.106383","url":null,"abstract":"<div><div>Predicting energy consumption in energy storage systems is crucial for optimizing system operation and promoting building energy sustainability. Nevertheless, due to the periodicity, intermittency, and strong nonlinearity of energy consumption in storage systems, conventional deep learning models often fail to fully capture the characteristics of energy consumption fluctuations, leading to an inability to balance both single-step and multi-step prediction accuracy. To address this issue, this paper improves the conventional Long Short-Term Memory (LSTM) model by integrating Temporal Convolutional Networks (TCN) with LSTM to optimize 1-hour single-step predictions and incorporates an attention mechanism to enhance 8-hour and 24-hour multi-step predictions, thereby proposing an Attention-TCN-LSTM prediction model. Utilizing data from an operational water-based thermal energy storage system for model training and testing, the model was compared with three neural networks and two machine learning benchmark models across three prediction time scales. The results demonstrate that, compared to the five benchmark models, the Attention-TCN-LSTM model reduced the Root Mean Square Error (RMSE) by 17.74 %-34.26 %, the Mean Absolute Error (MAE) by 19.68 %-38.60 %, the Mean Absolute Percentage Error (MAPE) by 0.12 %-2.65 %, and the Coefficient of Variation of RMSE (CVRMSE) by 9.65 %-17.27 %, while increasing the R-squared (R²) value by 3.54 %-9.36 %. These results highlight the model's higher prediction accuracy and stability, as well as shorter training times compared to conventional neural networks, underscoring its potential to enhance energy prediction and system performance.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"126 ","pages":"Article 106383"},"PeriodicalIF":10.5,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143906652","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":"Dynamic impacts of vegetation growth and urban development on microclimate and building energy consumption","authors":"Hanxun Fu,&nbsp;Yuanhao Jiao,&nbsp;Lirui Deng,&nbsp;Wei Wang","doi":"10.1016/j.scs.2025.106382","DOIUrl":"10.1016/j.scs.2025.106382","url":null,"abstract":"<div><div>Urban heatwaves have emerged as a critical global challenge, exacerbating extreme weather conditions and contributing to higher building energy consumption. These challenges become particularly acute during the initial phases of urban expansion. While numerous studies have independently investigated vegetation's effects on outdoor microclimates and building energy efficiency, the dynamic interactions between vegetation growth, urban development, and heatwave mitigation remain underexplored. This research examines these evolving interrelationships through integrated analysis of outdoor microclimate parameters and indoor energy performance in the context of climate change, using the new campus of Southeast University in China as a case study. Four scenarios are developed based on different stages of tree growth and urban construction: climate change only, as plan, stop construction, add trees in plan. Both simulations and experiments are conducted to assess the impact of the dynamic changes in these scenarios. The long-term impacts of these factors on microclimate and building energy consumption are assessed by ENVI-met and EnergyPlus tools. The results indicate that after 60 years, vegetation growth can reduce the average site temperature by approximately 3 °C, expand areas of enhanced thermal comfort, and reduce total building cooling energy consumption by 15.5 %. Comparative analysis of the scenarios reveals that preserving existing trees or implementing early-stage plantation can significantly mitigate heatwave and reduce cooling energy demand. This research provides valuable insights for future urban renewal and sustainable city development, offering practical guidance for urban planners to optimize urban environments and improve energy efficiency.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"126 ","pages":"Article 106382"},"PeriodicalIF":10.5,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864020","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":"Global perspectives on digital twin smart cities: Innovations, challenges, and pathways to a sustainable urban future","authors":"Maira Alvi,&nbsp;Hrishikesh Dutta,&nbsp;Roberto Minerva,&nbsp;Noel Crespi,&nbsp;Syed Mohsan Raza,&nbsp;Manoj Herath","doi":"10.1016/j.scs.2025.106356","DOIUrl":"10.1016/j.scs.2025.106356","url":null,"abstract":"<div><div>The integration of digital twin (DT) technology within smart city frameworks is becoming increasingly significant in today’s digital age. As urban areas evolve into smart ecosystems characterized by interconnected devices and data-driven management systems, digital twins provide a dynamic approach to managing these smart cities. This paper delivers an in-depth exploration of the role of digital twins in advancing smart city frameworks, surveying recent research, methodologies, and case studies that highlight their applicability in urban management, including sectors like mobility, healthcare, energy management, and environmental monitoring. Additionally, the paper delves into the foundational concepts of digital twins and digital twin smart cities, presenting a multilayered structure that emphasizes the role of each layer in creating a comprehensive urban digital twin platform. We also examine the ongoing global digital twin projects based on their development maturity, discuss the challenges of deploying these systems, and explores emerging tools such as synthetic sensing for areas with limited sensor infrastructure. By summarizing the state of the art, identifying research gaps, and discussing future directions, this review serves as a foundational reference for researchers and practitioners seeking to harness digital twin technology for more sustainable, efficient, and resilient smart cities.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"126 ","pages":"Article 106356"},"PeriodicalIF":10.5,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143843442","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":"Global warming likely compromises the annual performance of zero-energy buildings while the urban heat island effect exacerbates the impact","authors":"Yiman Zhao ,&nbsp;Xiaotian Ding ,&nbsp;Yifan Fan ,&nbsp;Yongling Zhao ,&nbsp;Jian Ge ,&nbsp;Jan Carmeliet","doi":"10.1016/j.scs.2025.106385","DOIUrl":"10.1016/j.scs.2025.106385","url":null,"abstract":"<div><div>Despite the significant impact of global warming and the urban heat island (UHI) effect on building energy demand, their combined effects are often overlooked, leading to inaccuracies in future energy performance evaluations of Zero-Energy Buildings (ZEBs). This study focused on an operational ZEB located in Virginia, USA, and investigated the impacts of global warming and UHI effect, using the Vatic Weather File Generator (VWFG) and Urban Weather Generator (UWG) models. Then, the influence of combined effect on the future energy demand is evaluated by Design Builder. Moreover, extreme climates are considered to assess the energy systems’ resilience. Results show that total energy demand for space heating and cooling is predicted to increase by 24% and 38% under the RCP4.5 and RCP8.5 scenarios from 2021 to 2100, driven by global warming and the UHI effect. For extreme climates under the RCP4.5 scenario, peak cooling and heating demands are expected to be 33% and 66% higher than the 80-year average, while rising to 39% and 71% under the RCP8.5 scenario, respectively. Furthermore, current climate-based designs are unlikely to enable renewable energy generation to meet zero-energy requirements by 2100. This framework is therefore essential for enhancing the accuracy and reliability of energy system design for ZEBs.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"126 ","pages":"Article 106385"},"PeriodicalIF":10.5,"publicationDate":"2025-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143852224","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":"Socioeconomic disparities in hurricane-induced power outages: Insights from multi-hurricane data in Florida using XGBoost","authors":"Alexys H. Rodríguez-Avellaneda ,&nbsp;Ryan Rodriguez ,&nbsp;Abdollah Shafieezadeh ,&nbsp;Alper Yilmaz","doi":"10.1016/j.scs.2025.106362","DOIUrl":"10.1016/j.scs.2025.106362","url":null,"abstract":"<div><div>This study explores the importance of socioeconomic factors in hurricane-induced power outages in Florida. An XGBoost regression framework that incorporates a comprehensive feature set, including diverse socioeconomic factors, hurricane hazards, and physical exposure, is introduced. To reduce random deviations in importance observed in prior single hurricane studies, data for 11 Florida hurricanes is processed and analyzed, sourced from various state and federal agencies. To further enhance the robustness of model findings, analysis was conducted on 66 independent repetition runs filtered from 250 model iterations to control for overfitting. An extended formulation of SHAP values across iterations is introduced to enable a nuanced assessment of feature importance. Results show that socioeconomic variables account for 19% of the model prediction. This finding underscores the presence and significance of social inequities in hurricane outages. The unemployment rate, percentage of disabled, and racial/ethnic minorities are found as the most important predictors. Two new variables – flooding and substations per county – are assessed in this study, but they are found to have no notable contribution to power outages. The findings of this study provide new insights into the interplay between socioeconomic conditions and power system performance, aiding outage prevention efforts by identifying socioeconomic inequalities in pre-existing conditions and system operations. The findings of this study highlight systemic socioeconomic vulnerabilities in power grid resilience, offering critical insights for policymakers to allocate resources and improve disaster response strategies. While the model is tailored for Florida, its structure could be adapted to assess power outage disparities in other hurricane-prone regions.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"126 ","pages":"Article 106362"},"PeriodicalIF":10.5,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143838618","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":"Collaborative governance for urban waste management: A case study using evolutionary game theory","authors":"Wenxuan Song ,&nbsp;Ehsan Elahi ,&nbsp;Guisheng Hou ,&nbsp;Pengmin Wang","doi":"10.1016/j.scs.2025.106380","DOIUrl":"10.1016/j.scs.2025.106380","url":null,"abstract":"<div><div>The rapid escalation in municipal solid waste generation presents a critical challenge, compounded by delays in implementing source-separated household waste management systems. This study addresses the lack of comprehensive stakeholder-oriented planning in government-led waste classification efforts—characterized by overreliance on administrative enforcement, imbalanced resource allocation, and inadequate coordination mechanisms—which has led to rising administrative costs and suboptimal outcomes. By employing an evolutionary game model, this study explores the dynamic interactions between key stakeholders—governments, property service enterprises, and residents—while incorporating subsidy and transfer payment mechanisms to establish a collaborative governance framework. The empirical analysis, grounded in data from Shanghai, China, reveals that a multi-agent collaborative model improves cost efficiency by 25 % compared to a government-only approach. The research findings indicate that when government subsidies exceed an 80 % distribution ratio to real estate service enterprises, a cooperative strategy is achieved, although it may lead to a non-cooperative state among residents. Reducing the cooperation costs of property service enterprises enhances their willingness to cooperate but has limited influence on residents. In contrast, residents' strategies are more sensitive to changes in government subsidies, and increasing subsidies led to evolutionary stability points characterized by dual and tripartite cooperation modes. These findings demonstrate how properly designed subsidy structures can address macro-level planning deficiencies by creating incentive alignment among stakeholders. The study also finds that reducing urban household garbage sorting costs by 30 % contributes to optimal tripartite cooperation. Although the study focuses on Shanghai, its findings apply to other cities with similar waste management policies, offering universal insights for improving urban waste classification systems. The study advocates for robust regulations and comprehensive monitoring systems to sustain long-term collaborative waste management practices.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"126 ","pages":"Article 106380"},"PeriodicalIF":10.5,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143850526","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":"Enhancing urban food production: A framework for optimal site selection and policy development","authors":"Mohammad Ismaeil Kamali ,&nbsp;Rouzbeh Nazari ,&nbsp;Maryam Karimi ,&nbsp;Mohammad Reza Nikoo","doi":"10.1016/j.scs.2025.106375","DOIUrl":"10.1016/j.scs.2025.106375","url":null,"abstract":"<div><div>According to the urbanization process, urban food production is a viable means of ensuring urban food security, and socio-economic development. This paper synthesized and reviewed the existing urban agriculture studies to identify the trends and gaps and suggested future research directions for increasing the efficiency of urban agriculture initiatives. We have also critically analyzed food accessibility using standards defined by the USDA. We investigate our query through a critical review of the historical research regarding urban agriculture. Also, this review discusses the integration of MCDM models with GIS in urban agriculture, considering its synergies, applications, and findings. Finally, we defined a framework to determine a suitable area for urban agriculture by considering the influential criteria. Drawing on several cases of spatial data and a variety of strict analytical frameworks, this study looks forward to offering the necessary insights needed for efficient practice in urban agriculture that will excite a paradigm shift toward more inclusive and sustainable urban development.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"126 ","pages":"Article 106375"},"PeriodicalIF":10.5,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868667","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}