Urban Climate最新文献

Computed indoor light conditions due to outdoor skyglow at night 计算夜间室外天光导致的室内光照条件

IF 6.9 2区工程技术

Urban Climate Pub Date : 2025-10-11 DOI: 10.1016/j.uclim.2025.102650

Héctor Antonio Solano Lamphar , Ladislav Komar , Miroslav Kocifaj

{"title":"Computed indoor light conditions due to outdoor skyglow at night","authors":"Héctor Antonio Solano Lamphar , Ladislav Komar , Miroslav Kocifaj","doi":"10.1016/j.uclim.2025.102650","DOIUrl":"10.1016/j.uclim.2025.102650","url":null,"abstract":"<div><div>Light pollution poses a significant challenge in the built environment, negatively impacting human health. One key aspect is light trespass, where light extends beyond its intended target, such as windows, causing annoyance, disrupted sleep patterns, and a diminished quality of life for residents. While shielded outdoor lighting can address direct light trespass, mitigating light trespass from skyglow presents complexities due to its unshieldable nature. This study explores the impact of skyglow-induced light trespass on indoor environments, aiming to develop a tool for quantifying its effects on human health in future studies. Using an innovative analytical approach, we simulated and measured skyglow within a specific built environment, considering window sizes and bed positions. Results indicate that room orientation, bed-window separation distance, and bed depth below the window significantly influence vertical diffuse illuminance. Surprisingly, the maximum illuminance occurs at a specific depth within the room, influenced by the interaction between window solid angle and sky segment brightness. Optimizing bedroom configurations can effectively minimize diffuse illuminance from skyglow, mitigating its negative impacts on human health. Importantly, this effect varies significantly when transitioning from urban city edges to suburban areas.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"64 ","pages":"Article 102650"},"PeriodicalIF":6.9,"publicationDate":"2025-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261830","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}

引用次数: 0

Uneven PM2.5 pollution risk: Dynamic analysis of spatial drivers and differentiated policy research in typical shrinking cities in China 非均衡性PM2.5污染风险：中国典型萎缩城市空间驱动因素动态分析与差别化政策研究

IF 6.9 2区工程技术

Urban Climate Pub Date : 2025-10-10 DOI: 10.1016/j.uclim.2025.102652

Fan Liang , Ming Lu , Kojiro Sho

{"title":"Uneven PM2.5 pollution risk: Dynamic analysis of spatial drivers and differentiated policy research in typical shrinking cities in China","authors":"Fan Liang , Ming Lu , Kojiro Sho","doi":"10.1016/j.uclim.2025.102652","DOIUrl":"10.1016/j.uclim.2025.102652","url":null,"abstract":"<div><div>To advance sustainable urban transitions in shrinking cities, a potential driving indicator system applicable to PM<sub>2.5</sub> concentrations in shrinking cities was constructed. Based on the Optimal Parameters-based Geographical Detector model, the study explores the effective drivers of spatial elements on PM<sub>2.5</sub> concentration in shrinking cities and the changes in these drivers, and proposes differentiated strategies. The results show that the PM<sub>2.5</sub> pollution in shrinking cities exhibits substantial volatility; the duality caused by urban shrinkage still tends towards negative effects; and the dynamics and instability of the driving forces limit the usefulness of analysis approaches based on averages. Among the assessed driving forces, the scale factors are relatively stable, the structural factors are volatile, and the connectivity factors show an upward trend. Based on the change patterns of the effectiveness of the core driving factors, the forces driving PM<sub>2.5</sub> concentration in shrinking cities can be divided into incremental, elastic, long-term, and weakening driving forces. Considering the change characteristics of the effective driving forces of the spatial elements, various policy concepts are proposed to strengthen the differentiation and pertinence of different strategies. These findings advance spatial-level sustainable development in shrinking cities, while establishing evidence-based governance frameworks that synergize environmental remediation with socially inclusive urban transition trajectories.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"64 ","pages":"Article 102652"},"PeriodicalIF":6.9,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261831","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}

引用次数: 0

Modeling regulating ecosystem services and environmental impact through urban green space expansion: A case study of Manila City 通过城市绿地扩张调节生态系统服务和环境影响的模型——以马尼拉市为例

IF 6.9 2区工程技术

Urban Climate Pub Date : 2025-10-10 DOI: 10.1016/j.uclim.2025.102641

Wencelito Palis Hintural , Mark Bryan Carayugan , Byung Bae Park

{"title":"Modeling regulating ecosystem services and environmental impact through urban green space expansion: A case study of Manila City","authors":"Wencelito Palis Hintural , Mark Bryan Carayugan , Byung Bae Park","doi":"10.1016/j.uclim.2025.102641","DOIUrl":"10.1016/j.uclim.2025.102641","url":null,"abstract":"<div><div>Urban green space expansion is increasingly recognized as a vital strategy for enhancing ecosystem services (ES) and mitigating environmental impacts in rapidly urbanizing tropical cities. However, quantitative, scenario-based simulations of such benefits remain limited, particularly in Southeast Asia. This study addressed this gap by examining the potential environmental contributions of urban vegetation expansion across the six congressional districts of Manila City, Philippines using three baseline measurement years (i.e., 2018, 2021, and 2024). Linear mixed modeling was employed to evaluate inter-district-level changes in carbon sequestration, pollution removal, hydrological regulation, and associated reductions in global warming potential and fine particulate matter formation under present vegetation cover and simulated green cover introductions on bare ground (S1), grass or herbaceous areas (S2), impervious buildings (S3), and impervious road peripheries (S4). Results showed significant differences in regulating ES across scenarios (<em>p</em> < 0.001), with notable gains in carbon sequestration and hydrological regulation. The simulations also projected enhanced PM<sub>2.5</sub> removal rates, albeit highly variable across districts and scenarios, and should be interpreted as temporary and supplementary, offering limited benefits compared to direct emission reduction strategies. S1 to S3 yielded the most substantial modeled reductions in global warming potential, though spatial heterogeneity remained evident, particularly for air quality benefits. Significant interaction effects (<em>p</em> < 0.05) between greening scenario and district for avoided CO<sub>2</sub> equivalent emissions reinforce the need for context-specific planning that aligns greening strategies with local biophysical and atmospheric conditions. These findings emphasize the importance of spatially nuanced green infrastructure planning in maximizing urban environmental co-benefits.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"64 ","pages":"Article 102641"},"PeriodicalIF":6.9,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261880","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}

引用次数: 0

An open-data based framework for identifying spatial patterns of heat stress by synthetizing climatopes and local climate zones 一个基于开放数据的框架，通过综合气候和局部气候带来识别热应力的空间模式

IF 6.9 2区工程技术

Urban Climate Pub Date : 2025-10-10 DOI: 10.1016/j.uclim.2025.102645

Weilin Liao , Tingan Zhu , Shi Yin

{"title":"An open-data based framework for identifying spatial patterns of heat stress by synthetizing climatopes and local climate zones","authors":"Weilin Liao , Tingan Zhu , Shi Yin","doi":"10.1016/j.uclim.2025.102645","DOIUrl":"10.1016/j.uclim.2025.102645","url":null,"abstract":"<div><div>The urban climate map (UCMap) and Local Climate Zone (LCZ) are the most popular conceptual frameworks for urban climatic evaluation and application. The UCMap is a planning-oriented tool for visualizing climatic issues spatially and offering guidelines, while LCZ illustrates the correlation between urban geometric morphology and its climate characteristics. However, they differ in data sources, classification standards, and planning implementation. This study uses Guangzhou, a subtropical high-density city in southern China, as a case. Firstly, an open-data-based workflow is established for delineating the Climatope-map (a representative of UCMap) based on the German standard (VDI 3787-Part 1) and LCZs across the city in a resolution of 100 m. Then, a hybrid climatope-LCZ map is developed by synthesizing these two systems spatially. The resultant map reveals marked variations in both land surface temperature and apparent temperature across the zones after comparing with climatic datasets. Approximately 5.93 % of Guangzhou's total area is identified as having a high heat stress hazard. This hazard is predominantly concentrated in the city center, urban subcenters, and industrial clusters, characterized by high-rise urban morphology, namely LCZ in 1/2/3. Finally, a set of urban climatic planning recommendations for various synthesized zones is proposed according to the guidelines in VDI 3787-Part 1. This study not only offered a feasible workflow for developing a hybrid climatope-LCZ map in a data-poor region but also exhibited the capacity of the map for rapid and precise heat stress hazard assessment, which will be a valuable tool for supporting stakeholders in responding to the challenges from climate change.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"64 ","pages":"Article 102645"},"PeriodicalIF":6.9,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261832","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}

引用次数: 0

An integrated ML-powered geospatial analysis of surface urban heat island and its mitigation in Riyadh City, Saudi Arabia 沙特阿拉伯利雅得市地表城市热岛及其缓解的综合ml驱动地理空间分析

IF 6.9 2区工程技术

Urban Climate Pub Date : 2025-10-10 DOI: 10.1016/j.uclim.2025.102642

Ali S. Alghamdi

{"title":"An integrated ML-powered geospatial analysis of surface urban heat island and its mitigation in Riyadh City, Saudi Arabia","authors":"Ali S. Alghamdi","doi":"10.1016/j.uclim.2025.102642","DOIUrl":"10.1016/j.uclim.2025.102642","url":null,"abstract":"<div><div>Understanding the spatiotemporal dynamics of surface urban heat islands (SUHI) and the influence of land features on their formation is crucial for effective climate-resilient urban policies. Using warm-season ECOSTRESS and Landsat data for Riyadh City, this study aimed to provide information on daytime and nighttime land surface temperatures (LSTs) and diurnal ranges, estimate SUHI intensity, and quantify the local influences of four key land features on LSTs. A geospatial modeling framework that leverages the predictive power of machine learning (ML) was applied. The city had a daytime surface urban cool island (SUCI) and a SUHI at night. While SUCI intensity varied from −0.3 to −1.6 °C, SUHI intensity varied from 2.8 to 3.4 °C, depending on how the non-urban reference area is defined. The city exhibited a smaller LST diurnal range than the surrounding desert. Seven ML models were explored and CatBoost and XGBoost demonstrated the best performance for daytime and nighttime LSTs, respectively. Surface albedo, bare ground, built-up surfaces, and vegetation cover have strong predictive modeling power and are important for mitigating LST. However, location was the most important feature for predicting LSTs, indicating that any mitigation action should be location-targeted within the city rather than a one-size-fits-all approach. All the land features demonstrated nonlinear interactions with LSTs, indicating that effective mitigation strategies must target the ranges in which interventions produce the most cooling effects. The findings can play a crucial role in shaping effective climate-resilient urban policies for the city and other hot desert cities worldwide.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"64 ","pages":"Article 102642"},"PeriodicalIF":6.9,"publicationDate":"2025-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261834","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}

引用次数: 0

A comprehensive study on heavy pollution episode over urban city Hyderabad using observations and WRF-CAMx simulations 基于观测和WRF-CAMx模拟的海德拉巴城市重污染事件综合研究

IF 6.9 2区工程技术

Urban Climate Pub Date : 2025-10-09 DOI: 10.1016/j.uclim.2025.102646

T.V. Ramesh Reddy, T. Narayana Rao, V. Jayachandran, S. Satheesh Kumar

{"title":"A comprehensive study on heavy pollution episode over urban city Hyderabad using observations and WRF-CAMx simulations","authors":"T.V. Ramesh Reddy, T. Narayana Rao, V. Jayachandran, S. Satheesh Kumar","doi":"10.1016/j.uclim.2025.102646","DOIUrl":"10.1016/j.uclim.2025.102646","url":null,"abstract":"<div><div>High pollution Episodes (HPEs) are increasing in urban conglomerations, posing a serious threat to human health and modifying regional weather patterns. One such episode occurred in Hyderabad during 21–27 December 2023, when the air quality index in Hyderabad alarmingly rose to over 200, reaching an “unhealthy” status. In order to understand underlying processes causing such episodes, both observations (ceilometer, automatic weather station, radiosonde data) and air quality model simulations for the period from 15 to 31 December 2023 have been used. Air quality simulations were conducted using CAMx v7.2, driven by meteorological inputs from WRF v4.2 and emissions from the EDGAR-HTAP 3.0 inventory. The daily mean surface PM<sub>2.5</sub> concentrations exceeded 100 <span><math><mo>µ</mo><mi>g</mi><mo>/</mo><mi>m</mi><mo>³</mo></math></span> during the HPE days at several locations in Hyderabad. The first two days (21 to 22 December) of the HPE were associated with low surface temperatures, low specific humidity, and weak wind speeds, and the cold dry air being denser remains close to ground, favouring the formation of HPE. Pollutants persisted due to the lowering of PBL due to higher aerosol (aerosol-PBL feedbacks). During the HPE days, the ceilometer backscattered density (BSD) showed increased backscattering counts at night due to aerosol accumulation within the PBL. WRF-CAMx simulations show that transboundary pollutants contribute a major part (30 to 40 %) of pollution in Hyderabad. During the HPE days, the maximum contribution of pollutants was observed from the eastern boundary, and the impact extended to the northwest part of the city. Among local emission sources, the industrial sector contributes 20 to 30 %, followed by the residential sector at 15 to 25 %, the transport sector at 8 to 10 %, while the remainder comes from agriculture and other sectors.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"64 ","pages":"Article 102646"},"PeriodicalIF":6.9,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261835","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}

引用次数: 0

Urban ecological risk assessment under water resources constraints: Framework development and application in Chinese cities 水资源约束下的城市生态风险评价：框架构建与应用

IF 6.9 2区工程技术

Urban Climate Pub Date : 2025-10-08 DOI: 10.1016/j.uclim.2025.102649

Zixu Jia , Tao Lin , Yuqin Liu , Hongkai Geng , Junmao Zhang , Yicheng Zheng , Xiangzhong Guo , Meixia Lin , Yuan Chen , Wenhui Liu , Jing Lin

{"title":"Urban ecological risk assessment under water resources constraints: Framework development and application in Chinese cities","authors":"Zixu Jia , Tao Lin , Yuqin Liu , Hongkai Geng , Junmao Zhang , Yicheng Zheng , Xiangzhong Guo , Meixia Lin , Yuan Chen , Wenhui Liu , Jing Lin","doi":"10.1016/j.uclim.2025.102649","DOIUrl":"10.1016/j.uclim.2025.102649","url":null,"abstract":"<div><div>Rapid urbanization is intensifying the pressure on urban ecological systems, leading to a rise in urban ecological risks (UER). While traditional risk assessment frameworks, such as the Hazard-Exposure-Vulnerability (HEV) model, have been widely used, they often overlook a critical dimension: water resource constraints (W). This oversight results in a simplified understanding of UER, especially in water-scarce regions. Our study addresses this research gap by developing a novel UER<sub>HEVW</sub> framework that integrates water resource constraints directly into the classic UER<sub>HEV</sub> model. We constructed the UER<sub>HEVW</sub> index and applied it to 371 cities in China. The results indicated that integrating water resource constraints substantially altered risk patterns, with 16.13 % of the cities increasing by at least one risk category. Shanghai, Chengdu, Kashgar and several cities in the Pearl River Delta experienced upgrades of up to two classes. Such shifts highlight newly identified risk hotspots, particularly in cities with high population density and high water consumption. Furthermore, this study found that urban green space factors, such as the proportion of forest and grassland area, played a significant role in mitigating ecological risks. Therefore, strategies for addressing urban ecological risks should not be limited to simply restricting urbanization processes, but should also focus on enhancing the resilience of urban ecosystems through green space planning and other measures. Given that the complexity and multi-dimensional nature of urban ecological risks make them difficult to identify intuitively, a systematic diagnostic framework that integrates water resource constraints is crucial for precise identification and effective risk management.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"64 ","pages":"Article 102649"},"PeriodicalIF":6.9,"publicationDate":"2025-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261878","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}

引用次数: 0

Health-centred climate adaptation: Insights from local governments in western Sydney, Australia 以健康为中心的气候适应：来自澳大利亚西悉尼地方政府的见解

IF 6.9 2区工程技术

Urban Climate Pub Date : 2025-10-07 DOI: 10.1016/j.uclim.2025.102617

Nicky Morrison , Patrick Harris , Erica McIntyre

{"title":"Health-centred climate adaptation: Insights from local governments in western Sydney, Australia","authors":"Nicky Morrison , Patrick Harris , Erica McIntyre","doi":"10.1016/j.uclim.2025.102617","DOIUrl":"10.1016/j.uclim.2025.102617","url":null,"abstract":"<div><div>Climate change poses a clear and growing threat to human health. While local governments are widely recognised as the key level of government responsible for climate change adaptation, they have faced challenges in effectively addressing this critical issue. This research focuses on Western Sydney, a rapidly growing urban region in Australia that is frequently affected by extreme weather events. We conducted stakeholder interviews and document analysis, using an adaptive capacity framework to identify the barriers and enablers to implementing climate- and health-related strategies across the region. A range of barriers were identified, both spatially proximate and contemporary, as well as remote and legacy-related. The central finding was the critical need for increased collaboration within and between agencies, and with the communities they serve, in order to overcome adaptation barriers and implement solutions. This collaboration is seen as essential in addressing numerous immediate and current challenges, including the inconsistent framing of climate and health issues in local strategies, limited knowledge-sharing, and siloed working practices. Collaboration can also help address historical and more systemic barriers, particularly the prioritisation of economic development over climate resilience and the insufficient allocation of federal and state resources to local governments. Ultimately, fostering collaboration among professionals, communities, and political stakeholders is crucial for building adaptive capacity and implementing effective climate adaptation strategies. These strategies can mitigate climate-related health impacts throughout the region and ensure that communities are better prepared for future challenges.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"64 ","pages":"Article 102617"},"PeriodicalIF":6.9,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261881","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}

引用次数: 0

Integrating local climate considerations into dormitory energy optimization: An explainable machine learning and multi-objective design approach 将当地气候因素纳入宿舍能源优化：一种可解释的机器学习和多目标设计方法

IF 6.9 2区工程技术

Urban Climate Pub Date : 2025-10-07 DOI: 10.1016/j.uclim.2025.102629

Wenyuan Wang , Li Zhu , Tianyue Zhang , Xingzhe Zhu , Kangen Chen , Yujiao Huo

{"title":"Integrating local climate considerations into dormitory energy optimization: An explainable machine learning and multi-objective design approach","authors":"Wenyuan Wang , Li Zhu , Tianyue Zhang , Xingzhe Zhu , Kangen Chen , Yujiao Huo","doi":"10.1016/j.uclim.2025.102629","DOIUrl":"10.1016/j.uclim.2025.102629","url":null,"abstract":"<div><div>Low-carbon, energy-efficient, and comfortable design has become a global trend in the development of the building industry. However, traditional multi-objective optimization methods often rely on simulation, which significantly reduces decision-making efficiency during the early design stages of urban residential areas. This study proposes a multi-objective optimization framework that couples Bayesian Optimization with an ensemble learning algorithm, aiming to improve the Energy Use Intensity (EUI), Photovoltaic Generation potential (PVG), and Universal Thermal Climate Index (UTCI) of university dormitories, and employing explainable artificial intelligence (AI) methods to analyze the impact of each factor on EUI, PVG, and UTCI. The framework is validated through a case study of a university dormitory area in Tianjin, China. Results show that the BO-ensemble learning algorithm achieves high predictive accuracy, with R<sup>2</sup> values of 0.99, 0.98, and 0.92 for EUI, PVG, and UTCI. SHapley Additive exPlanations (SHAP) analysis further reveals the contribution of each factor to the prediction model. Compared with the original design, performance improvements are substantial: EUI is reduced by 12.8 %, PVG is increased by 20.68 %, and UTCI is reduced by 2.8 %. Clustering analysis identifies optimal design schemes for different optimization objectives, with Cluster 3 (C3) offering the best trade-off among EUI, PVG, and UTCI. The proposed BO-ensemble based multi objective optimization framework provides a new perspective and method for sustainable dormitory design in university campuses.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"64 ","pages":"Article 102629"},"PeriodicalIF":6.9,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261879","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}

引用次数: 0

Application of ANN-ML in evaluating indoor thermal comfort of trio-typology residential building ANN-ML在三型态住宅室内热舒适性评价中的应用

IF 6.9 2区工程技术

Urban Climate Pub Date : 2025-10-06 DOI: 10.1016/j.uclim.2025.102625

Akpa Boniface Ajayi, Yingzi Zhang, Hamada Mostafa, Lixing Chen

{"title":"Application of ANN-ML in evaluating indoor thermal comfort of trio-typology residential building","authors":"Akpa Boniface Ajayi, Yingzi Zhang, Hamada Mostafa, Lixing Chen","doi":"10.1016/j.uclim.2025.102625","DOIUrl":"10.1016/j.uclim.2025.102625","url":null,"abstract":"<div><div>Rapid urbanization in regions like Abuja, Nigeria, poses significant challenges in achieving sustainable indoor thermal comfort, particularly when integrating traditional building techniques. This study evaluates adaptive thermal comfort in trio-typology residential buildings (TTRB), namely; modern (BDG1), traditional (BDG2), and compressed earth (BDG3), using an artificial neural network machine learning (ANN-ML) model. Environmental parameters were monitored over seven days during the rainy and dry seasons, alongside 230 occupant surveys capturing thermal sensation (TSV) and preference (TPV) votes. A simulation of a three-bedroom model was conducted using Design Builder software to assess natural ventilation (NV) performance. The ANN-ML model predicted TSV and thermal comfort (Tc) at 70 % training, 15 % validation, and 15 % testing under controlled conditions.</div><div>Results revealed rainy season temperatures ranged from 23.6 °C to 29.3 °C, while dry season temperatures spanned 25.0 °C to 35.3 °C. Thermal comfort zones were established at 27.4 °C (rainy season) and 20.54 °C (dry season). During the rainy season, 47.3 % of occupants reported feeling “slightly cool,” while 33.6 % felt “slightly warm.” in the dry season, 41.8 % perceived morning conditions as “cool,” with 63.6 % preferring warmer temperatures. The ANN-ML analysis demonstrated high accuracy in predicting occupant thermal comfort in NV buildings, confirming its reliability for such assessments. The findings highlight the potential of traditional building techniques to significantly enhance indoor thermal comfort. This study underscores the importance of integrating passive design strategies and machine learning models to optimize sustainable building performance in tropical climates.</div></div>","PeriodicalId":48626,"journal":{"name":"Urban Climate","volume":"64 ","pages":"Article 102625"},"PeriodicalIF":6.9,"publicationDate":"2025-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145261883","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}

引用次数: 0