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

Abstract

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 Δ T lowerarm /Δt (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. • Experimental studies on heat stress were carried out under transient outdoor thermal environments. • The relationship between dynamic thermal sensation and physiological responses was revealed and quantified. • A dynamic outdoor thermal sensation model was developed with steady-state and dynamic terms. • The model can provide early overheating risk prediction during outdoor thermal exposure.