A method of predicting the dynamic thermal sensation under varying outdoor heat stress conditions in summer

被引:17
|
作者
Xu, Tiantian [1 ,2 ]
Yao, Runming [1 ,2 ]
Du, Chenqiu [1 ,2 ]
Huang, Xizhen [3 ]
机构
[1] Chongqing Univ, Joint Int Res Lab Green Bldg & Built Environm, Minist Educ, Chongqing 400045, Peoples R China
[2] Chongqing Univ, Natl Ctr Int Res Low Carbon & Green Bldg, Minist Sci & Technol, Chongqing 400045, Peoples R China
[3] Univ Reading, Sch Built Environm, Reading RG6 6DB, England
关键词
Dynamic thermal sensation; Urban heat stress; Physiological adjustment; Thermal perception response; Adaptive behavior; BODY SKIN TEMPERATURES; HUMAN HEALTH; URBAN PARK; HOT-SUMMER; COMFORT; ADAPTATION; CLIMATE; WINTER; STEPS; ENVIRONMENTS;
D O I
10.1016/j.buildenv.2022.109454
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Heat stress events in urban areas are increasing as a result of global warming and urban heat islands. In response to heat stress, outdoor activators naturally often move themselves to a less hot place. An understanding of human physiological responses in dynamic outdoor thermal environments is desired. This study aims to reveal the dynamic physiological adjustment and thermal perception response characteristics under varying outdoor heat stress conditions. A robust model for predicting dynamic thermal sensation outdoors has been developed. Experiments involving heat stress changes in a hot summer were conducted with 25 subjects. Three categories of data were collected including meteorological data, physiological parameters, and thermal perception. The results showed that lower-arm skin temperature (T-lowerarm) is more sensitive to changes in the outdoor thermal environment, and correlates closely with the thermal sensation vote (TSV). For a better practical application, based on the strong linear relationship between T-lowerarm and T-ty, the new dynamic outdoor thermal sensation model has been developed involving two parameters: T-lowerarm and delta T-lowerarm/delta t (the change rate of T-lowerarm). The validity of the model in transient outdoor conditions was verified. The algorithm can be integrated into a wearable armband to predict practical thermal sensation responses. This contribution will advance technologies based on the scientific findings to provide alert services to support human health and wellbeing, consequently increasing urban resilience and sustainability.
引用
收藏
页数:15
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