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A hybrid framework for assessing outdoor thermal comfort in large-scale urban environments
Landscape and Urban Planning ( IF 7.9 ) Pub Date : 2024-12-12 , DOI: 10.1016/j.landurbplan.2024.105281 Siqi Jia, Yuhong Wang, Nyuk Hien Wong, Qihao Weng
Landscape and Urban Planning ( IF 7.9 ) Pub Date : 2024-12-12 , DOI: 10.1016/j.landurbplan.2024.105281 Siqi Jia, Yuhong Wang, Nyuk Hien Wong, Qihao Weng
Given the challenges posed by rapid urbanization and global warming, outdoor thermal comfort has become crucial for urban livability. However, there is a lack of field survey-based research on large-scale thermal comfort assessment across continuous urban spaces. To address this gap, this study developed a framework for assessing outdoor thermal comfort. A total number of 668 onsite observations from field studies during the daytime on typical summer days were collected and used for model development. The sites were distributed in diverse local climate zones (LCZs) of Hong Kong, enabling the prediction of outdoor thermal comfort across the city under different urban settings. A neural network model was trained for predicting daytime outdoor thermal comfort based on both meteorological and morphological variables. Universal Thermal Climate Index (UTCI) was used to indicate objective measures of human thermal comfort. The model was then applied to wider urban layouts and dynamic climatic conditions. The results revealed that during extreme hot conditions, approximately 74.8% of areas experienced strong to extreme heat stress, with thermal sensations classified as hot or very hot, while the remaining 25.3% fell under moderate heat stress. High levels of thermal stress were observed in urban layouts of low-rise buildings, with LCZ 3 showing the highest extreme heat stress percentage at 61.3%, followed closely by LCZ 6 at 57.6%. In both LCZs, over 90% of areas faced strong to extreme thermal stress. These findings are crucial for identifying urban regions with high thermal stress. The framework could be valuable for cities with similar climate and geographical contexts.
更新日期:2024-12-12