Urban Climate最新文献

{"title":"Geospatial assessment of tropical islands vulnerability and impact under extreme cyclonic conditions, mitigation and management for climate-resilient planning","authors":"R. Nishan Raja,&nbsp;V. Sachithanandam,&nbsp;Deviram Garlapati VNS,&nbsp;E.P. Nobi,&nbsp;N.V. Vinithkumar,&nbsp;G. Dharani,&nbsp;Balaji Ramakrishnan","doi":"10.1016/j.uclim.2026.103134","DOIUrl":"10.1016/j.uclim.2026.103134","url":null,"abstract":"<div><div>The Andaman Islands (AIs) face increasing impacts from tropical cyclones due to their geographic exposure and evolving land use patterns. Rapid coastal urbanisation, tourism growth, and infrastructure expansion have intensified risks to both human settlements and ecological systems. Understanding the spatial dynamics of cyclone risk in this fragile environment remains essential for informed decision-making. Hence, this study attempted a geospatial analysis of cyclone impacts and associated economic risk across islands, integrating land use data (2015–2025) and projections for 2030 and 2050, using a multi-criteria Analytic Hierarchy Process and machine learning techniques. Land Use Land Cover (LULC) was classified in Google Earth Engine using a Random Forest (RF) model, and future LULC was predicted using RF and an artificial neural network. Cyclone risk zones were classified into high, moderate, and low categories. GIS-based models revealed spatial variations in impact-related vulnerability, with high-impact zones restricted to three models, each covering about 4–5% (263.56–329.45 Sq. km) of the AIs. Economic loss assessments highlighted growing exposure in urbanising regions such as Sri Vijaya Puram, Swaraj Dweep, and Shaheed Dweep. Economic loss estimation, based on exposure overlays and scenario-based damage functions, indicates substantially higher potential losses by 2050 under high-impact cyclone scenarios, highlighting the need for risk-informed land-use planning, resilient infrastructure siting, early warning integration, and nature-based coastal protection. The proposed workflow is reproducible and transferable to other cyclone-prone small-island and coastal settings. The study concludes that AIs region, particularly their coastal urban agglomerations, are central to advancing multiple Sustainable Development Goals (SDGs).</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"69 ","pages":"Article 103134"},"PeriodicalIF":7.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148932991","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 hybrid simulation framework for modelling and analysing urban traffic pollution under key influencing factors","authors":"Antonio Navas-Orozco,&nbsp;María-José Morón-Fernández,&nbsp;Fernando Díaz-del-Río,&nbsp;Miguel Cárdenas-Montes,&nbsp;David Ragel-Díaz-Jara,&nbsp;José Morera-Figueroa,&nbsp;José-Luis Guisado-Lizar","doi":"10.1016/j.uclim.2026.103077","DOIUrl":"10.1016/j.uclim.2026.103077","url":null,"abstract":"<div><div>Traffic pollution in urban areas is a complex phenomenon influenced by vehicle emissions, wind patterns, and urban layouts. To address this complexity, this study introduces a comprehensive hybrid simulation framework that couples microscopic traffic dynamics with a pollution dispersion model. Our framework estimates emissions from individual vehicles (electric, petrol and diesel) and computes pollution levels at every position within the urban grid, enabling a detailed analysis of pollution evolution and supporting the development of effective mitigation strategies. Our main contributions include the joint modelling of exhaust and non-exhaust emissions (such as particulate matter from tyre, brake, road wear and dust resuspension), and a qualitative analysis of the non-linear role of wind and urban geometry in pollutant dispersion. Our key findings demonstrate that wind speed profoundly impacts total pollution levels. Furthermore, our analysis of urban planning strategies reveals that the spatial configuration of buildings plays a critical role in air quality: aligning buildings parallel with prevailing wind directions significantly enhances pollution dispersion , improving pollution levels by up to 26%, whereas orthogonal alignments create stagnation zones that trap contaminants. Similar findings are obtained using the real urban layout of the Sevillian district Nervión. These insights underscore the importance of synergizing traffic management with topology-aware urban design. Based on 16,800 large-scale simulations, our simulation framework’s statistical robustness is validated, and empirical relationships between traffic density, vehicle composition, wind effects, and pollution patterns are established, offering a scalable simulation framework tool for synthetic environments, easily extensible to real urban scenarios.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"69 ","pages":"Article 103077"},"PeriodicalIF":7.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148852885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model for predicting 2D spatial distribution of air pollutant concentrations in streets and roundabouts","authors":"María del Mar Durán del Amor,&nbsp;Antonia Baeza Caracena,&nbsp;Mercedes Llorens Pascual del Riquelme,&nbsp;Isabel Costa Gómez,&nbsp;Francisco Esquembre","doi":"10.1016/j.uclim.2026.103122","DOIUrl":"10.1016/j.uclim.2026.103122","url":null,"abstract":"<div><div>This paper presents an innovative methodology that combines Smart City concepts with atmospheric dispersion modelling for the control and management of traffic-related air pollution on urban environments. Road traffic has become one of the main anthropogenic sources of air pollution in cities, while municipal authorities often lack the resources or knowledge required to develop and implement advanced strategies, techniques and tools to manage air quality problems. To address this challenge, a calculation method was developed to model and predict two-dimensional spatial profiles of atmospheric concentrations, both along and across roads, in large avenues and roundabouts within urban centres. The model is based on the Gaussian dispersion formula and provides a simple, easy-to-apply and computationally efficient tool that does not require the use of complex software. Following a detailed prior field sampling campaign, it can be readily implemented in urban environments with limited technical resources. In addition, this novel methodology enables the identification of population risk areas and establishes a correlation between pollutant levels and traffic flow on each street and roundabout. Key characteristic parameters associated with traffic-derived emissions, such as critical distances and vehicle flow rates, can also be estimated. Furthermore, the model allows to identify optimal locations for atmospheric monitoring stations or devices on roads. The proposed strategy was applied and validated in the main avenues and roundabouts of a medium-sized city for VOCs, NO₂, PM₁₀ and PM_2.5. The results demonstrated that the model provides reliable predictions of pollutant spatial distributions and constitutes a useful, accessible and valuable tool for local or political decision-makers.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"69 ","pages":"Article 103122"},"PeriodicalIF":7.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148893628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Global cities under multiple climate hazards","authors":"Rita Nogherotto,&nbsp;Natalia Zazulie,&nbsp;Roshanka Ranasinghe,&nbsp;Trang Minh Duong,&nbsp;Felix Creutzig,&nbsp;Francesca Raffaele,&nbsp;Erika Coppola","doi":"10.1016/j.uclim.2026.103132","DOIUrl":"10.1016/j.uclim.2026.103132","url":null,"abstract":"<div><div>Cities concentrate population, infrastructure, and economic assets, yet climate risk is still often assessed at regional or national scales. Here we present the first global analysis of climate change emergence and coastal flood exposure across ∼11,000 urban areas, distinguishing four city typologies. Using the policy-relevant CORDEX-CORE ensemble of high-resolution regional climate models, we assess heat extremes, heavy rainfall, droughts, wildfire risk and heat stress. We show that many cities experience stronger changes than their surrounding regions, with the robusteness of this amplification varying across hazards and regions, and that heat extremes have already emerged in most cities. By mid-century, emergence becomes widespread across the analysed hazards, although with greater uncertainty for hydroclimatic indicators, while emissions mitigation delays emergence across regions and city types. We further show that coastal flood exposure is strongly shaped by socio-economic gradients under no-protection assumptions, while accounting for flood protection reduces wealth-dependent disparities. Our results highlight the need to move beyond a megacity-focused perspective and to include small and intermediate cities in global adaptation planning.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"69 ","pages":"Article 103132"},"PeriodicalIF":7.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148932996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Local Cooling Island Footprint: A direction-resolved framework for exposing the actual extent and assessment biases of urban park cooling","authors":"Weiwu Wang,&nbsp;Jie He,&nbsp;Zihao Guo","doi":"10.1016/j.uclim.2026.103124","DOIUrl":"10.1016/j.uclim.2026.103124","url":null,"abstract":"<div><div>As global warming and urbanization intensify urban heat islands, accurately quantifying the cooling effects of urban parks has become critical for climate adaptation. However, conventional assessments—based on Area of Interest (AOI) boundaries or fixed-width buffers—conflate administrative delineations with the actual distribution of cooling-capable blue-green spaces (BGS) and assume isotropic, omnidirectional cooling diffusion, introducing systematic assessment biases. This study introduces the Local Cooling Island Footprint (LCIF), a mechanistically grounded framework that delineates park cooling extent from BGS spatial configuration and temperature-distance decay relationships rather than administrative geometry. Applying Landsat 8/9 thermal data via Google Earth Engine to 15 parks across three Chinese megacities (Hangzhou, Wuhan, Chengdu), we extracted BGS boundaries from Tianditu imagery, built equal-area multi-ring buffers, and developed a 16-directional (22.5°) temperature-gradient framework, applying cubic polynomial fitting and inflection-point detection to delineate LCIF boundaries. The 16-directional models performed well (mean R² = 0.82; 95% of inflection points statistically significant). LCIF boundaries were smaller than AOI-based buffers in 87% of parks (mean Jaccard coefficient = 0.58); conventional buffers overestimated cooling area by 37.05% and cooling distance by 28.66%, while underestimating cooling efficiency by 0.1 °C/ha. Cooling intensity exhibited strong spatial autocorrelation (Moran's <em>I</em> = 0.93), with directionally asymmetric gradients, cold-spot clusters within core BGS, and hot-spot clusters along park peripheries. By replacing administrative with functional boundaries, LCIF corrects these biases, offering a transferable, direction-resolved tool for quantifying park ecosystem services and informing climate-adaptive blue-green infrastructure planning.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"69 ","pages":"Article 103124"},"PeriodicalIF":7.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148884549","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":"From Text to Insight: A Natural Language Processing framework for analysing community perceptions for urban climate resilience","authors":"Beatriz Paulino,&nbsp;Stefania Stellacci,&nbsp;Pedro Mariano,&nbsp;Catarina Ferreira da Silva","doi":"10.1016/j.uclim.2026.103133","DOIUrl":"10.1016/j.uclim.2026.103133","url":null,"abstract":"<div><div>Urban resilience strategies should reflect and strengthen community perceptions of environmental and climate risks. However, policymakers often struggle to engage diverse groups and incorporate insights from multiple and informal sources into resilience plans. This study presents a data-driven framework using Natural Language Processing to analyse community narratives regarding local risks and urban governance. By combining complementary analytical and visualisation techniques, we identify public concerns and perceptions and translate them into actionable urban resilience strategies. This approach is applied to a publicly owned neighbourhood in Lisbon facing aging infrastructure, limited access to services, energy poverty, and high unemployment. Primary data were collected from web-scraped sources and focus groups involving public authorities, local associations, and elderly inhabitants. Unsupervised topic modelling (BERTopic) was employed to identify key themes in digital narratives, including infrastructure quality, environmental conditions, and relations with local social institutions. Focus group transcripts were analysed through sentiment analysis, combining lexicon-based (VADER) and transformer-based (BART) models with expert validation and comparative assessment. Results show low levels of community awareness of environmental and climate risks and significant divergences between institutional and community perceptions of priorities, highlighting gaps in communication, institutional trust, and the perceived effectiveness of municipal renewal initiatives. In response, we propose soft co-design climate actions and targeted community awareness campaigns to strengthen risk perceptions and adaptive capacity. This framework offers transferable lessons for urban climate resilience by integrating insights from both digital and physical communities that are often underrepresented in formal decision-making, thereby supporting more inclusive local adaptation planning.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"69 ","pages":"Article 103133"},"PeriodicalIF":7.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148932989","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":"Thermal adaptation effects on activity-intensity moderation of outdoor thermal comfort: Evidence from local people vs. tourists in a mild-humid winter","authors":"Qiaochu Wang,&nbsp;Yang Zhang,&nbsp;Tianyu Xi,&nbsp;Yangsheng Cai,&nbsp;Xiaoyin Zhu,&nbsp;Chenxi Yang","doi":"10.1016/j.uclim.2026.103142","DOIUrl":"10.1016/j.uclim.2026.103142","url":null,"abstract":"<div><div>Previous studies mainly examined how activity intensity moderated the outdoor thermal comfort (OTC) of local people, whereas historical and cultural tourism districts also accommodate tourists whose thermal adaptation may differ from local people's. Although such differences may influence OTC, whether they affect how activity intensity moderates OTC remains largely unexplored. Through field surveys during mild-humid winters in Fuzhou, China, this study explored whether the moderating effect of activity intensity, from light-intensity activity (LIA) to moderate-intensity activity (MIA), on OTC differed between local people and tourists. Results showed: (1) The LIA-to-MIA transition reduced neutral Universal Thermal Climate Index (NUTCI) more for tourists than for local people. (2) At −1 °C UTCI, MIA produced higher mean thermal sensation vote (MTSV) and mean thermal comfort vote (MTCV) than LIA for both local people and tourists, with larger MIA–LIA differences in MTSV and MTCV for tourists than for local people. As UTCI increased, the MTCV advantage of MIA over LIA gradually diminished and slightly reversed in favor of LIA at high UTCIs for both local people and tourists. However, tourists retained this MIA-related MTCV advantage up to a higher UTCI than local people. (3) During the LIA-to-MIA transition, tourists exhibited a larger decrease in the upper boundary of thermal neutral zone than local people. Meanwhile, tourists showed similar thermal neutral zone widths under LIA and MIA, whereas local people showed a wider thermal neutral zone under MIA than under LIA. These findings provide activity-based OTC optimization strategies in historical and cultural tourism districts.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"69 ","pages":"Article 103142"},"PeriodicalIF":7.5,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148936237","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":"Spatial spillover effects of German clinker production on regional air pollution","authors":"Nargiz Ahmadova,&nbsp;Imke Rhoden,&nbsp;Stefan Vögele,&nbsp;Jochen Linßen","doi":"10.1016/j.uclim.2026.103067","DOIUrl":"10.1016/j.uclim.2026.103067","url":null,"abstract":"<div><div>The cement industry is a primary contributor to industrial air pollution, with clinker production representing the most emissions-intensive stage of manufacturing. In Germany, clinker production accounts for approximately 21.1% of total industrial nitrogen oxide emissions, yet its spatial dynamics remain under-researched. This study investigates the direct and spatial spillover effects of clinker production on nitrogen dioxide concentrations across 393 administrative districts from 2018 to 2022. Using a spatial Durbin model to account for regional dependencies, the results reveal that clinker production significantly increases nitrogen dioxide levels. Crucially, the findings indicate that spatial spillover effects on neighboring regions (0.021%) are more than four times larger than direct local impacts (0.005%). These results, which are statistically significant, meaning they differ from random noise, remain consistent across various robustness checks and confirm the presence of significant regional environmental externalities. The study suggests that effective mitigation of nitrogen oxides in Germany requires a shift from localized targets toward coordinated, multi-regional governance frameworks to internalize the transboundary costs of industrial pollution.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"68 ","pages":"Article 103067"},"PeriodicalIF":7.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148635863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prioritizing urban water loss prevention strategies using a multi-criteria decision-making framework: A case study of Istanbul","authors":"Selin Çelik,&nbsp;Başak Savun,&nbsp;Osman İsa Çelik,&nbsp;Cem Gazioğlu","doi":"10.1016/j.uclim.2026.103071","DOIUrl":"10.1016/j.uclim.2026.103071","url":null,"abstract":"<div><div>Urban water systems in rapidly growing metropolitan areas face mounting pressure from rising demand, climate variability, and infrastructure limitations. Istanbul exemplifies this challenge, with increasing water consumption, fluctuating reservoir storage, and recurring periods of critically low capacity, highlighting growing vulnerability. This study combines empirical characterization of urban water security conditions with an expert-based multi-criteria decision-making (MCDM) framework to evaluate strategies to reduce water losses and improve urban water management. Four strategies: network optimization, water reclamation and reuse, rainwater harvesting, and sustainable urban drainage systems were assessed using nine economic, technical, environmental, and social criteria derived from the normalized mean scores of 18 experts representing academia (<em>n</em> = 8), engineering and consultancy firms (<em>n</em> = 6), and professional chambers and NGOs (<em>n</em> = 4). Results indicate that rainwater harvesting is the most effective option with the highest TOPSIS score (0.7273), followed by network optimization (0.4667), water reclamation and reuse (0.3118), and sustainable urban drainage systems (0.2894). This ranking reflects strong performance across cost, feasibility, and environmental considerations. Sensitivity, uncertainty, Monte Carlo, and scenario-based weighting analyses confirmed the robustness of the prioritization under both expert-judgement variability and alternative policy priorities. The results emphasize the importance of decentralized, demand-side approaches in addressing urban water stress under increasing hydroclimatic variability and reduced supply reliability. The proposed framework links empirical water security characterization with expert-based MCDM and robustness analyses, providing a practical decision-support tool for prioritizing urban water management strategies in rapidly growing metropolitan regions.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"68 ","pages":"Article 103071"},"PeriodicalIF":7.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148635928","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":"Source apportionment and health risk assessment of PM2.5-bound heavy metals in peri-urban municipalities adjacent to megacities: Evidence from northern South America","authors":"Omar Ramírez,&nbsp;Jorge E. Pachón,&nbsp;Jesús D. de la Rosa","doi":"10.1016/j.uclim.2026.103078","DOIUrl":"10.1016/j.uclim.2026.103078","url":null,"abstract":"<div><div>Rapid urban expansion in municipalities surrounding major Latin American cities has increased concerns about the health risks associated with PM_2.5-bound heavy metals and metalloids (HMMs). This study investigated the concentrations, sources, and health risks of PM_2.5-bound HMMs in a peri-urban municipality within the Bogotá metropolitan region, Colombia. Fifty PM_2.5 samples were collected between November 2021 and May 2022 (16.7 L/min), and twelve HMMs (V, Cr, Co, Ni, Cu, As, Cd, Sb, Sn, Ba, Pb, and Zn) were quantified by ICP-MS. Monte Carlo simulations were used to assess variability and uncertainty in health risk estimates. The mean PM_2.5 concentration was 33.7 ± 7.2 μg/m³. Zinc, Ba, Pb, Sn, and Cu were the dominant elements, while enrichment factors revealed strong anthropogenic influence, particularly for Sb, Cd, and Sn (EF &gt; 85), indicating contributions from vehicular non-exhaust emissions and industrial activities. Positive Matrix Factorization identified five major sources: non-ferrous metal processing (27.4%), metal-enriched industrial emissions mixed with mineral dust (27.3%), industrial coal combustion (20.8%), heavy fuel oil combustion (18.7%), and traffic-related emissions influenced by brake wear (5.8%). Carcinogenic and non-carcinogenic risks were acceptable for both age groups but higher in adults. In both groups, Ni, As, and Cd dominated non-carcinogenic risk, whereas Cr(VI) accounted for approximately 85% of carcinogenic risk. Monte Carlo analysis confirmed Cr(VI) as the principal contributor to carcinogenic risk and uncertainty. The findings suggest that peri-urban municipalities near large urban centers may face degraded air quality from PM_2.5-bound HMMs, in areas with substantial industrial activity and limited monitoring capacity.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"68 ","pages":"Article 103078"},"PeriodicalIF":7.5,"publicationDate":"2026-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148692929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}