Developing a new heat strain evaluation index to classify and predict human thermal risk in hot and humid environments. (January 2022)

• Record Type: Journal Article
• Authors: Zhao, Pan; Zhu, Neng; Chong, Daokun; Hou, Yingzhen
• Is Part Of: Sustainable cities and society. Volume 76(2022)
• Publication Date: 2022-01
• Subjects: Human thermal risk -- Classification method -- Prediction model -- Evaluation index -- Dehydration rate -- Multiple linear regression; HAHEs hot and humid environments -- HTR human thermal risk -- HRI heat-related illness -- PSI physiological strain index -- PeSI perceptual strain index -- HSCI heat strain classification index -- WBGT wet-bulb globe temperature -- Ta air temperature -- Tor oral temperature -- HR heart rate -- DR dehydration rate -- BWL body weight loss -- TS thermal sensation -- RPE ratings of perceived exertion -- RH relative humidity -- LH labour hour -- IIPW intensity index of physical work; Sustainable urban development -- Periodicals; Sustainable buildings -- Periodicals; Urban ecology (Sociology) -- Periodicals; 307.76
• DOI: 10.1016/j.scs.2021.103440
• Languages: English
• ISSNs: 2210-6707

Abstract

Highlights: The effect of water-salt metabolism was considered in heat strain evaluation. A heat strain evaluation index incorporating the dehydration rate was proposed. Human thermal risk in hot and humid environments was classified into five levels. A prediction model of human thermal risk in hot and humid environments was built. Abstract: Hot and humid environments (HAHEs) can jeopardize the health and safety of humans. Accurately evaluating and predicting heat strain contribute to reducing the human thermal risk (HTR). Nevertheless, the traditional evaluation indexes ignore the importance of water-salt metabolism system in resisting heat, and the sweating rate cannot fully reflect heat strain. Furthermore, extant methods of classification and prediction of HTR have defects in objectivity, accuracy, and practicability. To fill these gaps, an experimental study with 24 conditions and 120 person-times was conducted in a climate chamber. During the experiment, the subjects' oral temperature, heart rate, and dehydration rate were recorded. Based on the experimental data, two principal components with explained variance of 92.773% were extracted by principal component analysis, and with the determination of weightings, a new evaluation index of heat strain in HAHEs was proposed. The HTR was further classified into five levels, from "no risk" to "extremely severe risk" using the K-means cluster. Moreover, a prediction model of the HTR in HAHEs with the goodness of fitting of 0.782 was established using the multiple linear regression, and the weightings of predictors were determined. The results of this study could provide a reference for safety and health at work.