Evaluation and modification of the weighting formulas for mean skin temperature of human body in winter conditions.

• Six original methods to estimate MST were compared in winter conditions. • The errors of the original method were increased in cold conditions. • The variations of local skin temperatures in winter conditions were analyzed. • Four new weighting formulas were proposed with errors reduced up to 77.6%. • A robust method with 4 points of chest, forearm, thigh, calf was recommended. The demands for cooling and heating in buildings were affected by the thermal state of occupants. As an important physiological parameter reflecting thermal state, the mean skin temperature (MST) of human body was generally calculated by using limited sites of local skin temperatures (LSTs) with corresponding weight factors. In a cold climate, the distribution of local skin temperatures (LSTs) might be highly varied due to the thermoregulation mechanism and uneven distribution of clothing insulation. However, the accuracy of the weighting formulas to estimate MST has not been examined in winter conditions by previous studies. In this study, climate chamber experiments were conducted using 20 subjects wearing 9 different winter clothing ensembles exposed for 100 min in three different air temperature 22 °C, 16 °C and 10 °C, respectively. Six original methods to estimate MST were compared to a reference method with 9 local points. Results show the errors of all these methods were increased in cold winter conditions compared to those in neutral winter condition. The variations of LSTs were analyzed and their relationships could be used to modify the weighting formulas. New simplified methods with different weight factors of LST were proposed and validated by using the data from the other two different studies in cold climates. Compared to the original methods, the errors were reduced up to 77.6% by using the new methods. Thus, this study provides reference information for thermal comfort studies about the optimal weighting formulas to estimate MST in winter conditions. [ABSTRACT FROM AUTHOR]