Evaluation and improvement of human heat tolerance in built environments: A review. (November 2019)

• Record Type: Journal Article
• Authors: Zhu, Neng; Chong, Daokun
• Is Part Of: Sustainable cities and society. Volume 51(2020)
• Publication Date: 2019-11
• Subjects: HR heart rate -- Tc core temperature -- Tr rectal temperature -- Td dry bulb temperature -- Tw wet bulb temperature -- Tb black globe temperature -- RH relative humidity -- ESI environmental stress index -- THI temperature-humidity index -- new ET new index-equivalent temperature -- PSI physiological strain index -- PeSI perceptual strain index -- HA heat acclimation -- TPC thermal protective clothing -- Ts skin temperature -- VO2 max maximal oxygen uptake -- CHSI cumulative heat strain index -- RPE ratings of perceived exertion -- RTS ratings of thermal sensation -- PHI perception heat index -- HIS heat stress index -- CTI comprehensive temperature index -- ET effective temperature -- HSP heat stress protein; Built environments -- Hyperthermal environments -- Human heat tolerance -- Evaluation indexes -- Heat acclimation; Sustainable urban development -- Periodicals; Sustainable buildings -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.76
• DOI: 10.1016/j.scs.2019.101797
• Languages: English
• ISSNs: 2210-6707

Abstract

Highlights: Future evaluation indexes should give priority to human subjective perceptions. Machine learning based on big data should be adopted in heat tolerance assessment. Efficient HA training regimens should be determined for manual laborers. HA should be considered in the design and control of indoor thermal environments. Field investigations should be conducted to test the existing findings' validity. Abstract: Hyperthermal environments in public or industrial buildings impose substantial heat stress on the human body. To ensure human health in built environments, research has focused on the interactions between the heat tolerance and environments. This paper summarizes the progress in the literature concerning the evaluation and improvement of heat tolerance in three areas: environmental and physiological parameters, heat tolerance evaluation indexes, and heat acclimation (HA). This review leads to four conclusions: (1) Future indexes should give top priority to subjective perceptions to diminish individual differences; (2) machine learning techniques based on big data should be adopted to deal with complex correlations between hot environments and heat tolerance; (3) an optimal HA training regimen should be determined for workers to improve their heat tolerance and HA should be considered in the design and control strategies of indoor thermal environments for energy conservation; and (4) more field investigations should be conducted to modify laboratory-based findings. This review provides a comprehensive understanding of built environments and health and guidelines for future research.