Urban Climate最新文献

{"title":"Integrated vegetation effects on thermal environment and air quality in urban street canyons","authors":"Wanqiao Che,&nbsp;Weimin Zhuang","doi":"10.1016/j.uclim.2025.102593","DOIUrl":"10.1016/j.uclim.2025.102593","url":null,"abstract":"<div><div>Climate change and rapid urbanization exacerbate urban environmental challenges, particularly the urban heat island effect (UHI) and air pollution. Urban street canyons are critical hotspots for both heat stress and traffic-related pollution. This thermo-pollutant coupling threatens public health, increases building energy consumption and carbon emissions, and hinders urban sustainability. Moving beyond single-pollutant approaches, this study proposed a nature-based solution integrating vertical greening with street trees. Utilizing a validated 3D street canyon multi-field coupling model, we analyzed thermal and pollution distributions under three scenarios: no greenery, street trees only, and street trees combined with vertical greenery. Computational fluid dynamics (CFD) simulations quantified vegetation impacts on wind flow, temperature distribution, and particle deposition, elucidating the regulatory mechanisms. Results demonstrated the high efficacy of integrated vegetation in co-mitigating heat and pollution. Street trees alone reduced near-building temperatures by an average of 0.2 °C through shading and transpiration. Adding vertical greenery enhanced cooling by up to 0.6 °C and promoted more uniform temperature distribution. For air pollution control, the combined system achieved a remarkable 95 % particle removal rate, significantly outperforming street trees alone (71 %) and reducing vertical pollution stratification. This study provides critical insights for urban nature-based design and offers a vegetation configuration paradigm for high-density streets to maximize environmental co-benefits. By addressing the coupled thermo-pollutant challenge, it can help enhance understanding of greening's regulatory role in complex urban systems and support sustainable urban development.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102593"},"PeriodicalIF":6.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048791","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":"Compounding effects of Lake and urbanization on summer precipitation in the Greater Chicago area","authors":"Jiali Wang ,&nbsp;Zhao Yang ,&nbsp;Theron Moustakes ,&nbsp;Haochen Tan ,&nbsp;Rao Kotamarthi ,&nbsp;Alberto Martili ,&nbsp;Robert Jackson ,&nbsp;Paytsar Muradyan ,&nbsp;Scott Collis ,&nbsp;Joseph O'Brien ,&nbsp;Dev Niyogi ,&nbsp;Ashish Sharma","doi":"10.1016/j.uclim.2025.102597","DOIUrl":"10.1016/j.uclim.2025.102597","url":null,"abstract":"<div><div>This study explores the impacts of Lake Michigan and Chicago's urbanization on precipitation patterns over the Greater Chicago Area using long-term observational gridded dataset and Weather Research and Forecasting (WRF) model ensemble simulations focused on an early summer rain event. Observational analysis reveals that the Chicago core urban area consistently experience more precipitation than the adjacent southern Lake Michigan region throughout the year, particularly before 2015. This disparity has narrowed since 2016 due to a more rapid increase in heavy precipitation over the lake compared to the urban area. Specifically, lake precipitation has risen by 18.6 mm per year, compared to11.5 mm per year over the urban area in warm-season (April–October). Additionally, the number of days with precipitation exceeding 5 mm has been rising at a rate of 0.82 days per year over the lake and 0.42 days per year over urban areas. Ensemble modeling experiments reveal that both urbanization and lake effects enhance precipitation over the urban area, primarily through convergence with sufficient moisture, driven by interactions between land and lake breezes, a warm surface layer, and a low lifted condensation level. In contrast, these factors suppress precipitation over the lake. The suppression results from Lake Michigan's stable environment, characterized by cooler surface temperatures, limited evaporation in early summer, and a high-pressure anomaly over the lake driven by urban heating, which creates upward motion over urban areas and downward motion over the lake, further influencing precipitation patterns.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102597"},"PeriodicalIF":6.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145093813","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 divergent effects of spatial structure of urban agglomerations on carbon emission reduction capacity","authors":"Yi Yang,&nbsp;Yiwen Zhao,&nbsp;Yuanyuan Zhang","doi":"10.1016/j.uclim.2025.102602","DOIUrl":"10.1016/j.uclim.2025.102602","url":null,"abstract":"<div><div>The adjustment of the spatial structure of urban agglomerations is an effective tool for improving carbon emission reduction. Given the complexity of sustainable environment and carbon emission reduction, urban low-carbon transformation faces challenges such as population agglomeration, factor mobility, and urban expansion. This study constructs a carbon emission reduction capacity indicator system and adopts Zipf's law to measure the centrality index of the spatial structure of urban agglomerations. The influence of spatial structure on carbon emission reduction capacity is verified using five Chinese national urban agglomerations in the Yellow River Basin. The results show that urban agglomerations are dominated by a polycentric spatial structure, with strong carbon emission reduction capacity in the middle and lower reaches and weak capacity in the upper reaches. Carbon emission reduction capacity presents an inverted U-shaped relationship with spatial structure, and functional specialization presents nonlinear mediating effects. Carbon emission reduction effects can be maximized through rational functional specialization of the spatial structure. The moderation of the increase in factor mobility shows a weakening effect. Thus, a moderately polycentric spatial structure of urban agglomerations should be optimized to promote production factor mobility through sustainable governance. Reasonable urban functional positioning and the coordinated management of carbon emission reduction among cities should be developed.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102602"},"PeriodicalIF":6.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019743","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 novel climate assessment framework for integrating adaptation into planning and design interventions on public real estate","authors":"Carmela Apreda ,&nbsp;Guglielmo Ricciardi ,&nbsp;Alfredo Reder ,&nbsp;Paola Mercogliano ,&nbsp;Gianluca Capri ,&nbsp;Matteo Mariotti ,&nbsp;Diana Giallonardo ,&nbsp;Giacomo Antonino ,&nbsp;Simona Domini ,&nbsp;Claudia Scaramella","doi":"10.1016/j.uclim.2025.102589","DOIUrl":"10.1016/j.uclim.2025.102589","url":null,"abstract":"<div><div>Public assets face significant risks from extreme temperatures, precipitation, windstorms and drought, necessitating targeted adaptation measures to safeguard infrastructure, ensure safety, and enhance resilience. The lack of systematic tools to integrate climate adaptation into the planning and design processes for public real estate underscores the need for innovative assessment frameworks.</div><div>This study introduces a novel climate assessment framework to support decision-making throughout the construction lifecycle – investment planning, design, and monitoring – by enabling the evaluation of AS IS and TO BE conditions of real estate assets, ensuring alignment with European regulations. Developed in collaboration with the Italian State Property Agency, it includes: (i) a pre-assessment tool to prioritize interventions during the investment planning based on climatic and non-climatic drivers; (ii) an assessment tool to quantify the vulnerability levels and adaptation goals during the design phase based on Key Performance Indicators (KPIs); (iii) guidelines to periodically monitor climate hazards and effectiveness of adaptation measures over time; and (iv) catalogue of adaptation measures categorized into grey (structural), green (nature-based), and blue (water-based) solutions.</div><div>Drawing from European climate policies, Green Building Rating Systems, and Resilience Rating Systems, the framework identifies KPIs tailored to climate-related hazards and physical attributes of the real estate assets. The framework marks a significant advancement toward a systematic and replicable tool for integrating climate adaptation into real estate interventions, aligning with EU climate objectives and offering practical applications for public and private stakeholders.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102589"},"PeriodicalIF":6.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144922616","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":"Multi-model fusion method for reconstructing the dry-wet time series of daily precipitation and its application","authors":"Deng Pengxin,&nbsp;Xu Changjiang,&nbsp;Bing Jianping,&nbsp;Wang Dong","doi":"10.1016/j.uclim.2025.102594","DOIUrl":"10.1016/j.uclim.2025.102594","url":null,"abstract":"<div><div>To effectively enhance the accuracy of precipitation forecasts generated by CMIP6 climate models, we propose a daily precipitation reconstruction method based on a multi-model fusion approach. This method utilizes multi-model precipitation data as input and employs a two-layer deep learning fusion model (LCNN) that integrates a LSTM with CNN to reconstruct and correct daily-scale precipitation estimates. The Hanjiang River Basin (HRB) has been selected as the experimental area for evaluating accuracy and analyzing the effectiveness of precipitation data from 96 uniformly distributed surface rainfall gauges within the basin. The evaluation results indicate that the constructed LCNN model for classifying and quantitatively predicting precipitation dry-wet time series can effectively correct precipitation errors. This enhancement is reflected in the improvement of key performance metrics: the CC, NSE, POD, and HSS increase from original values of 0.08, −0.30, 0.31, and 0.06 to 0.57, 0.16, 0.99, and 0.62, respectively. Concurrently, the FAR has been reduced to 0.44, and the RB values for most gauges have decreased from an original ±40 % to within ±18 %. These improvements significantly enhance the model's ability to detect dry-wet time series and reduce the quantitative estimation error of precipitation. Additionally, this method effectively captures the spatial distribution characteristics of precipitation in the HRB, which exhibit a pattern of high in the southwest and low in the northeast. This approach enhances the model's spatial detection capability and improves the accuracy of precipitation predictions. However, the method may show limited improvement in the quantitative estimation error for small-scale precipitation events (daily precipitation below 2 mm), suggesting the need for further research. The findings of this study can address the shortcomings of existing climate models, further enhance the predictive capabilities of precipitation models, and provide better foundations support for hydrological forecasting, flood control, and disaster mitigation in river basins.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102594"},"PeriodicalIF":6.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048789","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":"Analyzing residents' preferences for urban heatwave-adaptation facilities and associated demographic characteristics using a discrete choice experiment","authors":"Byeong Jin Park ,&nbsp;Shinwoo Kim ,&nbsp;Jae Hong Lee ,&nbsp;Hyemee Hwang ,&nbsp;Dong Kun Lee","doi":"10.1016/j.uclim.2025.102601","DOIUrl":"10.1016/j.uclim.2025.102601","url":null,"abstract":"<div><div>As climate change intensifies heatwaves, particularly in densely populated cities with urban heat islands, the need for effective adaptation strategies is growing. These strategies include nature-based cooling infrastructure, such as street trees, green roofs, and green walls, as well as technological cooling infrastructure, such as artificial shade structures, cool roofs, and cooling fog. However, given resource constraints and potential personal costs, a targeted approach that accounts for diverse population needs is essential. This study explores residents' preferences for urban heatwave-adaptation facilities through a discrete choice experiment in South Korea. It examines how demographic factors—including perceptions of the climate crisis, age, and outdoor activity levels—shape facility preferences. Findings reveal a strong preference for accessible facilities, especially artificial shade structures and street trees. Latent class analysis further revealed distinct groups with heightened preferences for various adaptation facilities, particularly sustainable heatwave-mitigation strategies. These findings suggest policy recommendations to improve the provision and accessibility of such measures. Further analysis shows that individuals with a heightened perception of the climate crisis tend to favor nature-based cooling infrastructure, while those with extensive outdoor activities show a generally lower preference for adaptation facilities. These results highlight the need to improve public awareness of heat risks and provide targeted adaptation measures, such as readily accessible cooling centers for those who spend considerable time outdoors, to enhance the effectiveness of heatwave-adaptation strategies. This study provides foundational data for developing strategies that address diverse community needs in mitigating urban heatwave impacts.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102601"},"PeriodicalIF":6.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048790","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":"Cognitive experiments on labelling uncertainty for LCZ mapping across heterogeneous megacities in China: Introducing multi-source geospatial data and LCZ subclasses","authors":"Xilin Zhou ,&nbsp;Jinyang Hu ,&nbsp;Shuting Yan ,&nbsp;Chuancheng Li","doi":"10.1016/j.uclim.2025.102599","DOIUrl":"10.1016/j.uclim.2025.102599","url":null,"abstract":"<div><div>World Urban Database and Access Portal Tools (WUDAPT) provides a prevailing workflow for mapping Local Climate Zones (LCZs) based on a supervised machine learning method. Yet, the low accuracy and numerous iterations caused by labelling uncertainty in heterogeneous urban context were still obstacles for its application. In this study, the cognitive experiments on labelling uncertainty for LCZ mapping were conducted over Wuhan, China. The multi-source geospatial data and LCZ subclasses cognition were introduced for pre-recognition on training areas (TAs). Sixty-four participants were randomly allocated into four equal-sized teams, with each team exclusively assessing the mapping accuracy of a designated scenario under a restricted protocol of nine iterations. Validated through randomized point sampling, the scenario set for mapping LCZ with subclass recognition show optimal performance, that it can achieve the overall accuracy (OA) of 83 % at five iterations, and reach up to OA of 89 %. This study highlights the critical role of LCZ subclasses cognition in improving mapping accuracy, and proposed an extended workflow of WUDAPT specific for heterogeneous megacities in China. The novel workflow improves LCZ classification accuracy while minimizing iterations in heterogeneous urban context, thereby supporting LCZ-based studies through reliable descriptions on the climate-related urban forms in Chinese megacities.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102599"},"PeriodicalIF":6.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145019745","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":"City-scale evaluation of urban ecohydrologic processes on surface energy balances, heat, and humidity","authors":"G. Aaron Alexander ,&nbsp;Daniel B. Wright ,&nbsp;Carolyn B. Voter ,&nbsp;Steven P. Loheide II","doi":"10.1016/j.uclim.2025.102596","DOIUrl":"10.1016/j.uclim.2025.102596","url":null,"abstract":"<div><div>Urban regions substantially modify both surface energy and hydrologic cycles. Despite the linkage between urban hydrology and energy cycles, modern coupled land-atmosphere models do not represent common urban hydrologic features like runoff routing from impervious to pervious surfaces or tree canopy that shades pavements. We compare three urban surface models in the Weather and Research Forecasting model across multiple hydrometeorological events in Milwaukee, Wisconsin: a widely used slab urban model (Noah-MP Bulk Parameterization; <em>Typical</em>), multiple land covers per grid cell (Noah-MP Mosaic; <em>Mosaic</em>), and a model which adds sub-grid water transfers between land cover types (Noah-MP HUE; <em>HUE</em>). Inclusion of urban hydrology and vegetation (<em>HUE</em>) increases albedo and emissivity, reducing available energy in our study region. Ambient soil moisture conditions cause divergent responses in <em>HUE</em> simulations: warming when soil water is limited and cooling when ample soil water is available for evapotranspiration. Comparison against observed 2m air temperature and specific humidity show increased skill in the <em>HUE</em> model simulations, especially compared to the <em>Typical</em> model. Noah-MP HUE presents a stride in understanding how urban hydrology influences city-scale meteorology and a pathway to examine urban hydrologic greening initiatives more wholistically in regional atmospheric models.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102596"},"PeriodicalIF":6.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145048787","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":"Characterizing surface and canopy urban heat islands and impacts of land use and land cover change in a third-pole city","authors":"Lingjing Zhu ,&nbsp;Chunchun Meng ,&nbsp;Qiyu Xie","doi":"10.1016/j.uclim.2025.102590","DOIUrl":"10.1016/j.uclim.2025.102590","url":null,"abstract":"<div><div>This study investigated the summer urban heat island (UHI) effects in Xining, a typical valley city on the Tibetan Plateau (TP), using the Weather Research and Forecasting (WRF) model coupled with a single-layer urban canopy model. Two groups of WRF simulations were conducted to explore the temporal variations of surface and canopy UHI (SUHI and CUHI) effects in July over past several decades, as well as the impact of land use and land cover change (LULCC) on UHIs. Results indicate a continuous enhancement of both SUHI and CUHI effects with urban expansion, nearly tripling from 1994 to 2018. At the diurnal scale, SUHI peaks before sunset due to surface energy balance processes, while CUHI peaks after sunset, influenced by the boundary layer development. LULCC plays an important role in intensifying the UHI effects, contributing more than 60 % by 2018. The amplified UHI effects driven by the LULCC strengthen local near-surface winds by modulating the mountain-valley wind patterns, further in turn enhancing UHI effects and creating a self-reinforcing mechanism. This paper provides an improved understanding of urban effects in high-altitude cities and establishes a strong foundation for further research on improving the urban environment and promoting sustainable urban development in the TP.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102590"},"PeriodicalIF":6.9,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144924959","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":"An integrated approach to optimal siting of air quality monitoring networks: Fuzzy based decision-making, multi-pollutant methodology, and health risk assessment","authors":"Nima Zolfaghari ,&nbsp;Ahmad Alahabadi ,&nbsp;Mehri Delsouz ,&nbsp;Hamed Adab","doi":"10.1016/j.uclim.2025.102588","DOIUrl":"10.1016/j.uclim.2025.102588","url":null,"abstract":"<div><div>The aim of this study is optimal siting of air quality monitoring networks (types A, B, and C) using fuzzy based multi-criteria decision-making and multi-pollutant methodology. Digital Glob and Landsat 8 satellites from Google Earth and Stichmap were used. After pre-processing, automobiles (QuickBird images), green space (NDVI), asphalt, buildings, and ground classes were separated. The produced layers were combined on the basis of the weight gained from Easy AHP. The weight of all criteria was combined by WLC method. In the fuzzy method, by selecting the fuzzy function and applying its middle point for each parameter in its raster layer in QGIS, the maps needed to locate the desired areas of stations were obtained. Based on investigated methods, as well as field visits, 10 priority points were proposed for air quality stations. The <em>Z</em>-score and <em>p</em>-value in nearest neighbor average method for fuzzy method (1.76 and 0.007) and AHP method (0.43 and 0.15) showed that the fuzzy method has the best pattern with99 % confidence in the distribution of the proposed points. Multi-pollutant methodology using XLSTAT and Map Algebra extension showed a good relationship of pollutants with layers of industrial units, commercial density, and vehicle density and suggests that most of the proposed stations in both methods with a priority of 1 to 10 are located in polluted areas of the city. The report of high pollution in the present study in some locations shows that the establishment of air quality measurement stations in Sabzevar city is a necessity.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"63 ","pages":"Article 102588"},"PeriodicalIF":6.9,"publicationDate":"2025-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144916334","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}