Modelling Residential Outdoor Thermal Sensation in Hot Summer Cities: A Case Study in Chongqing, China

Abstract

Exposure to extreme heat is a significant public health problem and the primary cause of weather-related mortality, which can be anticipated by accurately predicting outdoor thermal sensation. Empirical models have shown better accuracy in predicting thermal sensation than the most frequently used theoretical thermal indices, which have ignored adaptability to local climate and resulted in underestimating or overestimating the neutral levels of residents. This study proposes a scheme to build an empirical model by considering the multiple linear regression of thermal sensation and microclimatic parameters during summer in Chongqing, China. Thermal environment parameters (air temperature, relative humidity, wind speed, and surface temperature) were recorded and analyzed, together with 375 questionnaire survey responses referring to different underlying surfaces. The results found that the proposed model predicted neutral sensations as warm and 19.4% of warm sensations as hot, indicating that local residents adapted to warm or even hot sensations. In addition, the empirical model could provide references for local pedestrians’ daytime path choices. Residents might feel more comfortable staying beside a pond from 8:00 to 11:00 or sheltering under trees from 08:00 to 14:00 and 17:00 to 19:00. Masonry offered a comfortable microclimate between 10:15 and 11:00, and residents on the lawns were comfortable from 17:30 to 19:00. However, asphalt should be equipped with cooling infrastructures in order to cool thermal sensation.