Urban Climate最新文献

{"title":"Lost water bodies and a flooded city – Counterfactual scenarios of the extreme Chennai flood highlight the potential of nature-based solutions","authors":"N. Nithila Devi ,&nbsp;Abinesh Ganapathy ,&nbsp;André Felipe Rocha Silva ,&nbsp;Sergiy Vorogushyn ,&nbsp;Heiko Apel ,&nbsp;Heidi Kreibich ,&nbsp;Laurens Jozef Nicolaas Oostwegel ,&nbsp;Soumendra Nath Kuiry ,&nbsp;Nivedita Sairam","doi":"10.1016/j.uclim.2025.102454","DOIUrl":"10.1016/j.uclim.2025.102454","url":null,"abstract":"<div><div>In rapidly growing cities, unregulated urban expansion may encroach water bodies and floodplains, leading to frequent flooding. Chennai's traditional water bodies, known as ‘<em>tanks</em>’, act as nature-based solutions (NbS) for flood mitigation. Since the early 1900s, urbanization has led to the loss of 13.6 million m³ of tank storage within the city. The remaining tanks, holding 174.7 million m³ of water outside the city, are now at risk. We construct two counterfactual scenarios – what if (1) the lost tanks from the early 1900s had been protected during the urbanization (<em>with tanks</em>), and (2) the existing tanks upstream of the city were also lost (<em>u/s no tanks</em> - <em>u/s</em> denotes upstream). These scenarios are analyzed against the current situation (<em>baseline</em>), using the extreme 2015 flooding. The analysis reveals that in <em>u/s no tanks</em>, the potential flood damages rose by 44 % compared to the <em>baseline</em>. Conversely, flood damages decreased by 17 % in the <em>with tanks</em>. The population at risk increases by 40.5 % in <em>u/s no tanks</em>, while it decreases by 25.3 % in <em>with tanks</em> compared to the <em>baseline</em>. Thus, this study highlights the multi-dimensional impact of water bodies in flood control by examining the case of a rapidly expanding city.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102454"},"PeriodicalIF":6.0,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144072190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 multi-scale mapping approach of local climate zones: A case study in Hong Kong","authors":"Maoping Wang ,&nbsp;Ran Wang ,&nbsp;Wanlu Ouyang ,&nbsp;Zheng Tan","doi":"10.1016/j.uclim.2025.102446","DOIUrl":"10.1016/j.uclim.2025.102446","url":null,"abstract":"<div><div>The spatial scale of Local Climate Zone (LCZ) mapping significantly affects classification accuracy and the understanding of the relationship between land surface characteristics and urban climates. Traditional “one-size unit” mapping often fails to capture actual climatic conditions and inconsistencies between LCZs, limiting its ability to precisely identify urban heat island effects. Using Hong Kong as a case study, this study investigated optimal LCZ mapping scales (LCZ-scales) based on homogenous Land Surface Temperature (LST) representation within individual LCZs through semi-variogram modelling. The impact of immediate surroundings on LCZ-scales and LST was examined using Spearman correlation analysis and Generalized Linear Models. A multi-scale LCZ map was developed and its accuracy in classifying land use and representing climate conditions was evaluated using Analysis of Variance (ANOVA). Results show that, first, optimal mapping scales vary across LCZ types: 260–390 m for built types and 320–425 m for land cover types, forming a multi-scale mapping approach. Second, LCZ-scales for LCZ 1, 2, 5, A-B, C, D, E, F and G can be refined depending on surrounding LCZ configurations. Third, the “surrounding effect” on LST highlighted detailed UHI-mitigation strategies—generally, maintaining proximity to vegetation and water bodies within 900 m and 1200 m and beyond 900 m from LCZ 1 and 10 can effectively mitigate urban heat. Fourth, the multi-scale LCZ map better recognizes homogeneous land surface patterns and differentiates thermal characteristics than the “one-size unit” LCZ map. The findings of this study can inform climate-responsive urban planning, especially in urban–rural transition zones.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102446"},"PeriodicalIF":6.0,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071555","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Field effect and coupling influences of urban park cold islands under varying wind speeds and heat island gradients","authors":"Chunyu Li ,&nbsp;Yu Zhang ,&nbsp;Hong Liang ,&nbsp;Yang Yu ,&nbsp;Siyu Long ,&nbsp;Yuting Sun ,&nbsp;Tong Wang ,&nbsp;Kai Wang ,&nbsp;Qian Cao","doi":"10.1016/j.uclim.2025.102447","DOIUrl":"10.1016/j.uclim.2025.102447","url":null,"abstract":"<div><div>Urban parks effectively mitigated the urban heat island (UHI) effects. The field extent and boundary of cold island effects, influenced by internal landscape characteristics of parks, external urban morphology and regional climatic factors, determined cooling service magnitude. The study used buffer analysis to calculate the park's cold island effect, introduced fundamental concepts and delineation methodologies of the cold island rose and cold island effect field. Ultimately, the study explored the coupling relationship between the park's cold island effect and its internal landscape, external urban morphology, across various wind speeds and heat island gradients. It was found that the parks located in the warmer zone of the urban heat island gradient showed greater maximal cooling distances (L_MAX) and intensities (CPCI). L_MAX and CPCI were more influenced by internal landscape metrics than external urban morphological metrics. The 3–4 m/s of wind speed was a threshold discriminating the effects of wind speed on cold island effects. Below this threshold, greater L_MAX and CPCI were shown for the upwind area; exceed, downwind area did. UHI could be alleviated by utilizing the internal landscape features of the park, arranging the external urban form, and increasing urban ventilation corridors based on urban wind and thermal conditions.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102447"},"PeriodicalIF":6.0,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071556","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Trends in PM10 and PM2.5 air pollution and related health risk in Tehran over the last two decades","authors":"Khatereh Anbari ,&nbsp;Pierre Sicard ,&nbsp;Behzad Jamshidi ,&nbsp;Hasan Raja Naqvi ,&nbsp;Rajab Rashidi ,&nbsp;Mohammad Veysi Sheikhrobat ,&nbsp;Yusef Omidi Khaniabadi","doi":"10.1016/j.uclim.2025.102450","DOIUrl":"10.1016/j.uclim.2025.102450","url":null,"abstract":"<div><div>In this study, we have analyzed PM₁₀ and PM_2.5 mean concentrations over 20-year (2003−2022) and 16-year (2007–2022) period, respectively obtained from air quality monitoring stations installed in 22 districts across Tehran, one of the most populated cities in the world. By applying the Mann-Kendall test, the results showed that the annual PM₁₀ mean concentrations increased by 0.27 % per year, while the annual PM_2.5 mean concentrations declined by −1.27 % per year. The annual PM₁₀ and PM_2.5 mean concentrations have largely exceeded, on average 2 times, the 2021 World Health Organization (WHO) air quality guidelines for human health protection (i.e., 15 and 5 μg m⁻³ for PM₁₀ and PM_2.5). During the study period, the daily PM₁₀ concentrations &lt;50 μg m⁻³ were 4.3 % of time, 95.5 % of time between 50 and 200 μg m⁻³, and 0.2 % of time exceeding 200 μg m⁻³. The hazard quotient (HQ) values of non-carcinogenic risk due to PM₁₀ and PM_2.5 exposure for all age groups were &gt; 1, showing potential health risk for children and adults. The local authorities should consider implementing measures, such as blue and green infrastructure, to reduce the levels of air pollution and mitigate related human health risks.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102450"},"PeriodicalIF":6.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144067407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Platform urbanism for resident safety: A real-time predictive microclimate risk monitoring and alert system","authors":"Sk Tahsin Hossain ,&nbsp;Tan Yigitcanlar ,&nbsp;Kien Nguyen ,&nbsp;Yue Xu","doi":"10.1016/j.uclim.2025.102445","DOIUrl":"10.1016/j.uclim.2025.102445","url":null,"abstract":"<div><div>Urban microclimates significantly impact public health, liveability, and emergency preparedness, yet traditional weather alert systems often rely on centralised data that fails to capture the spatial variability of conditions within cities. This study presents an innovative platform that integrates ArcGIS GeoEvent Server with AIoT-driven predictive analytics to deliver hyper-localised weather alerts. The platform's adaptable design enables the incorporation of location-specific AI/ML-based predictive models and context-aware notifications, tailored to at-risk populations based on their location, health conditions, and disabilities. Featuring three GeoEvent Services and two ArcGIS Notebook Schedules, the system facilitates real-time data ingestion, processing, predictive modelling, and dissemination. A case study in Brisbane, Australia, demonstrates its capacity to address microclimatic variability, revealing significant differences in thermal stress and precipitation patterns across suburbs. Unlike traditional city-wide alerts, the platform provides targeted notifications prioritising vulnerable groups such as children, elderly, and individuals with chronic conditions or disabilities. This approach enhances urban resilience and offers a scalable framework for applications in health monitoring, emergency response, and public safety.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102445"},"PeriodicalIF":6.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948720","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Vulnerable groups in severe heat: A study assessing the impacts of climate and Pocket Park visitations pre-post the pandemic","authors":"Pai Liu ,&nbsp;Zipeng Guo ,&nbsp;Yang Song ,&nbsp;Jessica Fernandez","doi":"10.1016/j.uclim.2025.102444","DOIUrl":"10.1016/j.uclim.2025.102444","url":null,"abstract":"<div><div>Urbanization and climate change are intensifying disparities in access to green spaces, particularly for vulnerable populations such as low-income groups and older adults in areas with sever heat. COVID-19 and its aftereffects exacerbate this inequity of urban land use, especially for these populations. While previous studies explored park uses and the effects of climate, limited study have investigated how small scale urban park visitation patterns are shaped by the combined influence of park features and climate conditions using large scale smart phone mobility data, especially across different phases of a disruptive event like a pandemic. This study examines how pocket parks—small, neighborhood-based green spaces—serve as critical resources for these groups in high-density urban areas, focusing on Austin, Texas, as a case study. By analyzing visitation patterns before and during the pandemic using geospatial data and novel smartphone mobility data retrieved from Advan from 2018 to 2021, the research reveals an increasing trend of low-income groups and older adults relying heavily on pocket parks due to limited access to larger green spaces and private outdoor areas during the pandemic. Older adults and low-income groups were more sensitive to precipitation, wind, and maximin temperature during the pandemic as these factors closely associated with virus transmission. Park features that contribute to micro-climate regulation and health promotion reported higher significance to these visitors than areas designed for group activities since such features can decrease the effects of extreme heat and the risks of infection. These results underscore the need for equitable urban land use policies that prioritize the development and maintenance of pocket parks in underserved communities, especially under severe urban climate. By addressing both social and environmental vulnerabilities, this study contributes actionable insights for urban planners and policymakers striving to create inclusive and resilient cities with consideration of public health.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102444"},"PeriodicalIF":6.0,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Mapping stormwater inundation potential in data-scarce urban areas: A machine learning approach for Kolkata, India","authors":"Sasanka Ghosh ,&nbsp;Mampi Pal ,&nbsp;Deb Kumar Maity ,&nbsp;Ankita Biswas ,&nbsp;Arijit Das ,&nbsp;Rohan Ghosal","doi":"10.1016/j.uclim.2025.102451","DOIUrl":"10.1016/j.uclim.2025.102451","url":null,"abstract":"<div><div>Kolkata is a major fastest-growing city in India facing severe stormwater inundation yearly. However, it is difficult to identify stormwater inundation areas due to the unavailability of past inundation data on a large scale. This study focused on developing a methodology using Sentinel image and Machine Learning (ML) techniques for identifying inundation potential areas to minimize past inundation data availability problems. Stormwater inundation potential areas of the Kolkata Municipal Corporation (KMC) area are identified from Sentinel data derived inundation area locations and eight influencing factors using three ensemble Machine Learning (ML) models i.e. Random Forest (RF), Bagged CART and Extreme Gradient Boosting (EGB). The validation of these identified inundation potential areas is performed based on a separate stormwater event and field verification of inundated areas. The results show that the EGB (87.34 %) outperforms RF (87.09 %) and Bagged CART (84.46 %) due to its advantage of adding a large number of weak models to improve the result. EGB indicates 30.1 % of areas with high to very high inundation potential, especially in the western part adjacent to Hooghly River, the Eastern part adjacent to East Kolkata Wetland (EKW) and some areas of northern Kolkata. This higher potentiality is mainly due to topographic conditions, built-up density and age-old drainage network. This identified inundation potential areas will help the decision-makers to identify high-priority zones for developing plans to minimize this issue. This developed methodology will also help to identify the inundation potentiality of other inundation data-scare cities of the World.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102451"},"PeriodicalIF":6.0,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948729","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Carbon reduction in the AI era: How does urban digital intelligence transformation facilitate low-carbon development?","authors":"Xing Guo,&nbsp;Jiajun Xu","doi":"10.1016/j.uclim.2025.102449","DOIUrl":"10.1016/j.uclim.2025.102449","url":null,"abstract":"<div><div>Under the backdrop of global climate governance and China's dual carbon objectives, this research explores how urban digital intelligence transformation (DIT) aids low-carbon development. By using city-level panel data from China (2016–2021) and applying the difference-in-differences (DID) approach, we assess the influence of Artificial Intelligence Innovation Development Pilot Zones (AIIDPZs) on carbon emission intensity (CEI). Results demonstrate that AIIDPZs significantly reduce CEI, primarily through technological progress and energy efficiency improvements. Heterogeneity analysis reveals stronger effects in non-resource-based cities, eastern areas, high-GDP cities, and areas with advanced internet infrastructure, while resource-dependent and less-developed regions exhibit limited benefits. Further, public participation and stringent environmental regulations amplify the policy's effectiveness, underscoring the importance of “technology-society-institution” collaborative governance. Notably, AIIDPZs achieve emission reductions without increasing industrial pollution, balancing technological innovation with environmental sustainability. This research offers fresh perspectives on the role of urban DIT in fostering low-carbon development and offers empirical support for policymaking.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102449"},"PeriodicalIF":6.0,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143948730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the decoupling effect and driving mechanism of carbon emissions at macroscale: An empirical study from Wuhan metropolitan area","authors":"Yunhao Fang ,&nbsp;Liyuan Zhao","doi":"10.1016/j.uclim.2025.102434","DOIUrl":"10.1016/j.uclim.2025.102434","url":null,"abstract":"<div><div>Addressing global climate change and reducing carbon dioxide emissions are critical priorities for sustainable development. Exploring the decoupling effect of carbon emissions at the macro scale is essential for understanding regional disparities, optimizing spatial resource allocation, and guiding coordinated low-carbon transitions across diverse geographical contexts. Using the Wuhan Metropolitan Area as a case study, this research first measured the spatiotemporal characteristics of carbon emissions in 2010, 2015, and 2020, and then analyzed their correlations with economic development intensity and land use intensity. Subsequently, the decoupling effect of carbon emissions was assessed for the periods 2010–2015 and 2015–2020. Furthermore, employing a random forest model and considering natural and social factors, the study explored the driving mechanisms of carbon emission decoupling effects. Finally, the study applied the K-means clustering algorithm to develop a cross-city co-decoupling strategy for carbon emissions at the metropolitan scale. The results reveal that: (1) During 2010–2020, the total carbon emissions in the Wuhan Metropolitan Area exhibited an increasing trend, with high-carbon-emission regions demonstrating a significant expansion. (2) Over the same period, economic development intensity and land use intensity were positively correlated with carbon emissions, and their interaction had a synergistic effect that exacerbated emissions. (3) The decoupling effects of carbon emissions differed between economic and land use dimensions, with contraction at the economic level and expansion at the land use level. Both natural and social factors influenced decoupling effects, with natural factors accounting for 24.85 %–31.72 % and social factors for 68.28 %–75.15 % of the variation, driven by fractional vegetation cover and residential, industrial, and transportation activities, respectively. (4) The Wuhan Metropolitan Area can be classified into four types of low-carbon regulatory zones: comprehensive carbon reduction zones, transportation-residential reduction zones, industrial reduction zones, and residential reduction zones. Specific strategies were developed within each zone to achieve co-decoupling of carbon emissions.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102434"},"PeriodicalIF":6.0,"publicationDate":"2025-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937830","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 farms as green infrastructure for urban heat mitigation","authors":"Katherine Klink","doi":"10.1016/j.uclim.2025.102440","DOIUrl":"10.1016/j.uclim.2025.102440","url":null,"abstract":"<div><div>Urban impervious surfaces are a significant contributor to the urban heat island (UHI). Efforts to mitigate the UHI often focus on reducing impervious surface area by adding green infrastructure, especially trees. Urban farms are another type of green infrastructure that provide green space in the form of pervious soils and actively transpiring crops. Using six years of hourly temperature measurements in and near an urban farm in St. Paul, Minnesota, USA, the goal of this study is to examine whether an urban farm, characterized by a high proportion of green space and a low proportion of tree-covered green space, can effectively contribute to urban heat mitigation. Results show that mean monthly temperatures at the farm do not differ significantly from nearby locations with a higher proportion of tree-covered green space. In contrast, mean monthly minimum temperatures at the farm in July and August are cooler by about 1 °C than the broader urbanized area, with no significant differences in mean monthly maximum temperatures. These results suggest that the urban farm potentially can reduce the nocturnal UHI without exacerbating the daytime UHI. Further research, including in other geographical/climatological contexts, will help elucidate the heat mitigation potential of urban agriculture as green infrastructure.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"61 ","pages":"Article 102440"},"PeriodicalIF":6.0,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143937799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}