Investigation of outdoor thermal comfort prediction models in South China: A case study in Guangzhou

Abstract

A suitable outdoor thermal environment can encourage people to partake in outdoor activities, which, in turn, reduces building energy consumption. This can be achieved by accurately predicting the outdoor thermal environment. Most existing prediction models of the outdoor thermal environment focus on the relationship between environmental parameters and human perception, while ignoring the effects of personal factors (e.g., clothing level and metabolic rate). This study explores the relationships between the microclimate environment, personal factors, and human perception of the thermal environment during each season. A field survey was conducted between July 2016 and June 2017, across all four seasons. Thermal environment parameters, including air temperature, relative humidity, wind speed, and globe temperature were recorded and analyzed together with questionnaire survey responses. The results indicated that air temperature has the most significant effect on thermal sensation. In colder or warmer conditions, the mean thermal sensation vote increases with the increase in clothing insulation. Notably, when people kept low metabolic rate activities, including seated and quiet, standing, and walking at 3.2 km/h, the effect of metabolic rate on thermal sensation are negligible. Considering the effect of seasonal differences on the thermal environment parameters, prediction models for each season were obtained using multiple linear regression (the R-squared are 0.560(annual), 0.255 (spring), 0.207 (summer), 0.176 (autumn), 0.145 (winter)). Except for wind speed, all other factors were found to have a positive effect on the prediction models, especially air temperature and mean radiation temperature.