Development of a health data-driven model for a thermal comfort study

Abstract

The objective of this study is to develop a thermal comfort model by incorporating public health datasets and influencing parameters associated with both health and thermal comfort. There are three systematic influencing parameters identified in this study: socioeconomic development, population density, and annual mean temperature. The thermal comfort neutral temperatures predicted with the new model are in good agreement with the measured field data, and the correlation coefficient is 0.91.The current study introduces large-scale spatial data and longitudinal health-temperature data from the public health field for contributing to thermal comfort research. For instance, the required numbers of intensive field experiments and modeling works regarding thermal comfort can be reduced. Moreover, studies on the impacts of certain factors (such as variations in time, gender, and age) on thermal comfort have not reached any conclusive results, mainly owing to a lack of large demographic datasets. Recent findings from the public health field indicate that there are observable variations in health-temperature data in response to climate changes. There are no significant health-temperature differences between genders, although females are more inclined to use resources for better environmental management. Other factors are also discussed in this study, such as age and the prevalence of air conditioners.