Considering transient UTCI and thermal discomfort footprint simultaneously to develop dynamic thermal comfort models for pedestrians in a hot-and-humid climate

A well-being and sustainable urban environment consist of a series of pedestrian walkways for either commuting, exercising, or leisure use. The environmental thermal condition, which affects a person's thermal comfort, of the linear walking paths will inherently influence people's usage probability. The outdoor thermal environment and the human physiological response are both important determinants of thermal comfort during the dynamic process of walking. The traditional assessment of thermal comfort is based on the heat balance of the human body with steady environmental conditions that are rarely true in the constantly changing outdoor environments due to the context of urban morphology. In this research, we propose a novel method by integrating the traditional static thermal comfort index with the dynamic thermal comfort footprint and taking the spatiotemporal variations of thermal comfort conditions during the walking activity into consideration to develop dynamic thermal comfort prediction models for pedestrians. On-site thermal walking experiments with both subjective thermal questionnaires and objective physical thermal condition measurements were conducted on a university campus in different seasons to help establish the models. The proposed models were afterward validated against the measured values and showed that they can predict the dynamic thermal comfort of the pedestrians with satisfactory accuracy. With the proposed model, one could assess the dynamic thermal comfort conditions of a particular walk path with the Universal Thermal Climate Index (UTCI) and help to seek strategies in designing a thermally acceptable pedestrian walkway.

Automated summary

This research proposes a method to predict the dynamic thermal comfort of pedestrians by integrating static thermal comfort index with dynamic thermal comfort footprint, taking into consideration the spatiotemporal variations of thermal comfort during the walking activity. On-site experiments were conducted in different seasons to establish and validate the models, showing satisfactory accuracy in predicting pedestrians' dynamic thermal comfort.