Influential factors and predictive models of indoor clothing insulation of rural residents: A case study in China's cold climate zone. (15th May 2022) - Zhao, Wei; Chow, David; Yan, Haiyan; Sharples, Steve
Abstract: Clothing adaptation is one of the most common and effective behavioural adaptations for achieving thermal comfort. The clothing adaptation of rural residents which differs from rural residents is seldom discussed in detail. This paper aims to investigate the influential factors for clothing insulation of rural residents in the cold region of China and to develop predictive clothing insulation models. Field surveys were carried out in 10 villages in Lankao County from December 2018 to February 2019 and from July 2019 to September 2019. Finally, 610 valid datasets were obtained. Results show that rural residents had mean clothing insulations of 1.81clo in winter and 0.42clo in summer. The influences of gender and age on indoor clothing insulation of rural residents differed between winter and summer. The influences of relative humidity and air velocity on the indoor clothing insulation of rural residents were negligible in both seasons. The indoor operative temperature and 7-days running mean temperature were important determinants of indoor clothing insulation of rural residents in both seasons. They exerted a similar degree of influence on clothing insulation, with the operative temperature being slightly stronger. The five-parameter logistic (5 PL) model was found to best fit with the variation trend of clothing insulation with temperature. Two 5 PL clothing insulation predictive models for general use were established by using operative temperature and 7-days running mean temperature as predictors respectively. The investigation of influential factors and predictive models of the clothing insulation of rural residents will benefit the thermal comfort research, building energy modelling and design in rural China. Highlights: Influences of key factors on rural residents' indoor clothing insulation. T op and T rm, 7 were significant for rural clothing level. Five-parameter logistic model to fit indoor clothing level with temperature.