Urban Climate最新文献

{"title":"Urban PM2.5 concentration monitoring: A review of recent advances in ground-based, satellite, model, and machine learning integration","authors":"Simone Lolli","doi":"10.1016/j.uclim.2025.102566","DOIUrl":"10.1016/j.uclim.2025.102566","url":null,"abstract":"<div><div>Urban aerosols, especially fine particulate matter (PM_2.5), significantly affect public health and environmental quality. Accurate high-resolution monitoring of PM_2.5 is essential for exposure assessment, regulatory enforcement, and policy development. This review synthesizes recent advances in the integration of ground-based observations, satellite remote sensing, Chemical Transport Models (CTMs), and Machine Learning (ML) techniques for characterizing the spatio-temporal distribution of urban aerosols. Ground-based sensors provide accurate surface-level measurements but lack broad spatial coverage. In contrast, satellite-retrieved Aerosol Optical Depth (AOD), proxy to retrieve PM_2.5 concentration at surface, offers extensive coverage, but with limitations related to cloud cover and temporal resolution. CTMs provide continuous 3D aerosol fields, though their accuracy is limited by uncertainties in emissions and meteorology. ML algorithms effectively integrate these heterogeneous data sources, capture complex nonlinear relationships, and improve PM_2.5 predictions. Case studies from multiple global regions demonstrate that integrated approaches achieve high accuracy (cross-validated <span><math><mrow><msup><mrow><mi>R</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>≈</mo><mn>0</mn><mo>.</mo><mn>80</mn></mrow></math></span>, Root Mean Square Error 2.5–<span><math><mrow><mn>3</mn><mo>.</mo><mn>0</mn><mspace></mspace><mi>μ</mi><mi>g</mi></mrow></math></span>/m<span><math><msup><mrow></mrow><mrow><mn>3</mn></mrow></msup></math></span>, Mean Absolute Error 2.1–<span><math><mrow><mn>2</mn><mo>.</mo><mn>7</mn><mspace></mspace><mi>μ</mi><mi>g</mi></mrow></math></span>/m<span><math><msup><mrow></mrow><mrow><mn>3</mn></mrow></msup></math></span>), enabling daily exposure estimates at fine spatial scales. These synergistic methods are increasingly being used in air quality policies, health risk assessments, and regulatory frameworks. Future directions include the development of physics-informed ML models, the deployment of Internet of Things (IoT)-enabled sensor networks, and the establishment of standardized uncertainty quantification frameworks. This review is intended for researchers and policy makers seeking a state-of-the-art perspective on urban aerosol monitoring.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102566"},"PeriodicalIF":6.9,"publicationDate":"2025-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144842716","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":"Cooling inequity: Investigating environmental equity in residents' access to cooling services from urban parks using an improved 2FSCA model","authors":"Shuangjiao Cai ,&nbsp;Lifeng Li ,&nbsp;Dongdong Gao ,&nbsp;Xianjun Zeng ,&nbsp;Zeqi Wang","doi":"10.1016/j.uclim.2025.102575","DOIUrl":"10.1016/j.uclim.2025.102575","url":null,"abstract":"<div><div>Since the early 21st century, urbanization has intensified the urban heat island effect, posing negative health impacts on residents. Urban parks played a critical role in mitigating local temperatures and served as a major strategy for addressing this problem. Despite the growth in the number of parks and green spaces, uneven distribution restricted equitable access to cooling services, especially for vulnerable groups. Furthermore, current assessments of the cooling benefits provided by urban parks failed to account adequately for variations in parks' service capacities and coverage areas. Thus, this study evaluated the cooling effect, park service, and direct cooling services, utilizing an improved Gaussian Two-Step Floating Catchment Area (G2SFCA) model to assess the accessibility of park cooling services. Special emphasis was placed on accessibility for vulnerable populations, including the low-income, elderly, and children, in order to investigate the spatial and social equity of park cooling services. A case study was conducted on Fuzhou Third Ring Road. Results indicate that cooling service levels varied across parks, with 28 out of 48 parks demonstrating above-average cooling capacities. These parks were typically large urban comprehensive parks or smaller parks with substantial service capacities in central urban areas. Additionally, the accessibility of park cooling services showed significant spatial differentiation, exhibiting a long-tail distribution where 39.12 % of areas had zero accessibility, and 74.9 % fell below the average. Lastly, marked disparities existed among different population groups in accessing cooling services, with low-income and elderly populations facing significant disadvantages in resource access, underscoring social inequities in cooling provision.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102575"},"PeriodicalIF":6.9,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144830931","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":"Spatiotemporal assessment of land use carbon emission in the Guangdong-Hong Kong-Macao Greater Bay Area:A hybrid static-dynamic model integrated with PLUS","authors":"Yingsheng Zheng ,&nbsp;Liang Su ,&nbsp;Qiuyun Zeng ,&nbsp;Shuli Zhou ,&nbsp;Shan Li ,&nbsp;Haobin Hong ,&nbsp;Haoqian Deng ,&nbsp;Wenjie Li","doi":"10.1016/j.uclim.2025.102574","DOIUrl":"10.1016/j.uclim.2025.102574","url":null,"abstract":"<div><div>Land use change critically shapes spatiotemporal carbon emission patterns in urban agglomerations, yet refined mechanistic analyses and multi-scenario simulations remain limited. Focusing on China's Guangdong-Hong Kong-Macao Greater Bay Area (GBA), this study combines PLUS land use modelling and scenario simulations with hybrid “static-dynamic” carbon models to dissect land‑carbon interactions across historical (2000−2020) and future scenarios (NDS, CRS, CES). Key findings are as follows: (1) A 93.46 % expansion of construction land drove a 218.50 % carbon surge during 2000–2020. Core cities exhibited divergent trends: Guangzhou's “decelerating growth,” Shenzhen's “peak-decline” transition, and Hong Kong's “U-shaped” fluctuations highlighted urban expansion versus low-carbon governance conflicts. (2) By 2030, carbon emissions rise by 3.7 % (NDS) and 0.9 % (CRS), while CES achieves a 1.7 % reduction through ecological space optimization, proving optimal for balancing development and decarbonization. (3) High-emission hotspots historically diffused from urban centers to peripheries, a trend suppressed under CES and CRS. This study establishes a “land use analysis-carbon emission assessment-multi scenario decision making” framework, revealing the long-term, multi-scenario evolution patterns and influencing mechanisms of land-carbon interactions in the highly heterogeneous urban agglomeration of GBA. The findings provide decision-making support and methodological references for low-carbon land use planning.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102574"},"PeriodicalIF":6.9,"publicationDate":"2025-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144842717","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":"Heat risk in the city of São Paulo: Interactions between SUHI and social inequality","authors":"Luiza Sobhie Muñoz ,&nbsp;Denise Helena Silva Duarte ,&nbsp;Rohinton Emmanuel","doi":"10.1016/j.uclim.2025.102568","DOIUrl":"10.1016/j.uclim.2025.102568","url":null,"abstract":"<div><div>Heat waves and urban heat islands, consequences of climate change and urbanization, are becoming more severe and frequent with a strong impact on heat risk. Understanding the spatial distribution of heat risk is essential to address climate adaptation. This work aims to develop a heat risk map for São Paulo, a subtropical city, the biggest in Latin America and the fourth largest in the world. The map was developed at the census tract scale, using public and open data and expert opinions, considering risk as a function of hazard, vulnerability and exposure conditions. The results show a strong relation between socio-economic aspects and heat risk and the necessity of integrated policies to reduce the risk. The novelty of the work is in the inclusion of housing type, urban morphology and vegetation proximity as parameters in a subtropical city. The spatially explicit identification of heat risk can contribute to both São Paulo and National Climate Plans and act as a planning tool to support municipal level climate adaptation decision-making. This is the first heat risk map developed in Brazil using this approach and parameters and the protocol can be replicated to other cities in the country.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102568"},"PeriodicalIF":6.9,"publicationDate":"2025-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144830929","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":"Analytical prediction of urban wind profiles in densely built-up areas using a combined method of WRF and a porosity model","authors":"Jue Wang,&nbsp;Ruoyu You","doi":"10.1016/j.uclim.2025.102578","DOIUrl":"10.1016/j.uclim.2025.102578","url":null,"abstract":"<div><div>Mesoscale modeling such as Weather Research and Forecasting (WRF) simulations are not sufficiently precise to predict wind profiles in densely built-up areas, and existing improvement methods remain computationally expensive and time-consuming. To efficiently and accurately estimate wind profiles in densely built-up areas, this study proposed a method that combines WRF with a porosity model. WRF provides the wind profile at the urban edge, and the porosity model calculates the airflow pressure drop across the selected urban area using a parametrized urban layout. The urban wind profile is then analytically determined with the momentum integral method. The performance of the proposed method was first evaluated in three generic urban layouts, with validated computational fluid dynamics (CFD) simulations used as benchmarks. The proposed method was then applied in a real urban layout to demonstrate its performance, and the Kowloon district of Hong Kong, with an area of <span><math><mn>2,350</mn><mspace></mspace><mi>m</mi><mo>×</mo><mn>643</mn><mspace></mspace><mi>m</mi></math></span>, was selected as the target area. The wind profile measured with a radiosonde in the same region was used as a benchmark. For comparison, the wind profile directly extracted from the WRF simulation within the densely built-up area was also included. The results showed that the method accurately estimated wind profiles in the generic urban layouts. In the real urban layout, the proposed method estimated the urban wind profile reasonably well in the densely built-up area with complex building configurations and performed better than WRF.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102578"},"PeriodicalIF":6.9,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144830930","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":"Resilience evolution of urban sub-districts to flooding: An analytical framework considering internal disaster dynamics","authors":"Daoyang Zheng ,&nbsp;Ling Zhu ,&nbsp;Zhiqiang Xie ,&nbsp;Junyu Lian ,&nbsp;Zhiyong Yuan ,&nbsp;Yifei Liu ,&nbsp;Shihan Bai ,&nbsp;Tong Xu ,&nbsp;Haibin Zhou ,&nbsp;Feng Xu","doi":"10.1016/j.uclim.2025.102572","DOIUrl":"10.1016/j.uclim.2025.102572","url":null,"abstract":"<div><div>As vital components of urban areas, urban sub-districts play a prominent role in flood prevention against the backdrop of global climate change and urbanization. The complexity of the internal composition of sub-districts across Chinese cities leads to varied flood resilience capabilities. Current methods primarily employ index systems and spatial overlay analysis to assess flood resilience, failing to reveal the impacts of inter-element coupling within sub-districts during disasters. This inadequacy results in sub-optimal evaluations of sub-district flood resilience. This paper develops a sub-district flood resilience framework based on the Pressure-State-Response (PSR) model and the dimensions of nature, society, economy, and infrastructure (PSR-NSEI). It employs the DEMATEL-AHP method to design expert surveys, exploring the coupling mechanisms of factors affecting flood resilience in sub-districts. The study reveals the evolution of flood resilience from 2010 to 2021 in 42 sub-districts of Kunming, China, and quantitatively assesses it using ArcGIS software. Findings include: (1) The coupled effects of various dimensions significantly influence flood resilience, with well-coupled mature sub-districts exhibiting higher resilience. (2) Infrastructure and economic dimensions have the most significant impact on the flood resilience level of sub-districts, with centrality values of 1.305 and 1.238, respectively, while the natural dimension is only at 1.086. (3) Natural and economic dimensions are most affected by internal interactions within sub-districts, with response values of −0.513 and − 0.060. (4) Compared to sub-districts with low resilience, those with medium resilience showed the most significant enhancement in resilience during the 2010–2021 period. This study further quantifies the coupling relationships of dimensions affecting floods, providing decision-making support for enhancing flood resilience in urban sub-districts in China.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102572"},"PeriodicalIF":6.9,"publicationDate":"2025-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144827073","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":"Investigating the impact of evapotranspiration from urban green space vertical structures on microclimate through energy and water vapor transfer dynamics","authors":"Qi Li ,&nbsp;Qiong Li ,&nbsp;Haotian Wu ,&nbsp;Sisi Chen ,&nbsp;Yasuyuki Ishida ,&nbsp;Akashi Mochida ,&nbsp;Zhixin Liu","doi":"10.1016/j.uclim.2025.102539","DOIUrl":"10.1016/j.uclim.2025.102539","url":null,"abstract":"<div><div>The vertical structure of urban green spaces (UGSs) affects evapotranspiration (ET), influencing the microclimate regulation effect. This study focuses on analyzing the impact of the vertical structure of a small UGS on microclimate through energy and water vapor transfer dynamics. We developed a UGS microclimate model based on the three-layer ET model and validated it using observational data. The results demonstrated strong consistency between the model estimates and observed data, with RMSEs of air temperature (<em>T</em>_a1.5), specific humidity (<em>q</em>_a1.5), and relative humidity (<em>RH</em>_1.5) of 0.6 °C, 0.4 g·kg⁻¹ and 2.1 %, respectively. ET from the shrub crown and soil surface played critical roles in regulating the microclimate of UGS. During hot periods, ET from the shrub crown contributed over 50 % of the total ET cooling effect in the UGS, primarily due to the significant turbulent exchange of energy and water vapor flux from the shrub crown to human height. Therefore, ground conditions beneath the tree crown should not be neglected when designing vegetation configurations in UGSs.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"62 ","pages":"Article 102539"},"PeriodicalIF":6.9,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144738189","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":"Integrating STIRPAT - Adaboost and data-driven for influencing factors analysis and scenario prediction of carbon emission during building materialization stage","authors":"Yang Liu ,&nbsp;Wenhong Luo ,&nbsp;Xiaoyuan Tang ,&nbsp;Xian-jia Wang","doi":"10.1016/j.uclim.2025.102555","DOIUrl":"10.1016/j.uclim.2025.102555","url":null,"abstract":"<div><div>The issue of carbon emissions (CE) from buildings has come into focus. Among them, CE during the building materialization stage (BMS) account for a large proportion. This paper takes the past 20 years of China's carbon emission data during the BMS as a case study. Firstly, we select influencing factors based on multi-source data according to IPAT identification, then use a machine learning method to conduct a secondary screening of the influencing factors in order of importance. Secondly, an analysis model of STIPAT influencing factors in the BMS is constructed. Multicollinearity is tested, the correlation coefficient is obtained by ridge regression modification. Thirdly, scenario analysis is then employed to set baseline, low-carbon, and high-carbon scenarios to predict and analyze future building CE. Finally, the AdaBoost was applied to test the accuracy of scenario predictions. The results show: (1) The top three influences on CE in BMS are CE per unit of completed area, energy consumption during the BMS, and number of employees in the construction industry. (2) Under the three conditions, CE showed a trend of first increase and then decrease. (3) The error values were all within 2 %, which can be carried to forecast CE in 2045 and after.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"62 ","pages":"Article 102555"},"PeriodicalIF":6.9,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779558","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":"Climate risk assessment in Slovakia: Key findings on urban areas","authors":"Renáta Farkas","doi":"10.1016/j.uclim.2025.102561","DOIUrl":"10.1016/j.uclim.2025.102561","url":null,"abstract":"<div><div>From global to local scale, climate change poses a significant challenge in the 21st century. Due to the specifics of the urban environment, the effects of climate change on cities are more prominent. However, Slovak research on urban climate risk, including vulnerability to climate change, is relatively fragmented and underdeveloped. Therefore, this paper aims to address this gap by conducting a comprehensive climate risk assessment encompassing all Slovak cities and multiple impacts of climate change (extreme heat, drought, extreme precipitation) while focusing on geographic patterns. Notably, our study provides a new typology and focuses on the most and least endangered Slovak cities by climate change. By incorporating climate risk levels and indices derived from socio-demographic, physical, and climatological data, this paper serves as a critical resource for fostering climate risk management capacity in Slovak cities, providing valuable insights for academia, policymakers, and urban planners.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"62 ","pages":"Article 102561"},"PeriodicalIF":6.9,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144779559","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":"The social, technological, economic, and political roles of information and communication technologies in extreme heat adaptation in urban Southeast Asia","authors":"Johanne Rei R. Castro,&nbsp;Laurence L. Delina","doi":"10.1016/j.uclim.2025.102556","DOIUrl":"10.1016/j.uclim.2025.102556","url":null,"abstract":"<div><div>Enhancing adaptation measures for extreme heat, especially in developing regions and tropical climates, is essential as climate change accelerates. In this context, information and communication technologies (ICTs) play key roles in these adaptation strategies. This paper presents a qualitative analysis of ICTs' role in facilitating extreme heat adaptation specifically in urban Southeast Asia. The analysis is based on 25 semi-structured expert interviews and utilises the social, technological, economic, and political (STEP) framework. Our analysis identifies several factors that drive the deployment of ICTs for adaptation, and it illustrates the ways in which ICTs integrate extreme heat adaptation with risk management initiatives. These initiatives include heat warning dissemination, raising awareness, and optimising energy consumption. Furthermore, we examine the external STEP factors that either facilitate or hinder these processes. In addition, we discuss strategies for leveraging ICTs to enhance responses to extreme heat adaptation effectively.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"62 ","pages":"Article 102556"},"PeriodicalIF":6.9,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144763890","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}