Developing an adapted UTCI (Universal Thermal Climate Index) for the elderly population in China's severe cold climate region

This paper proposes an adapted UTCI (Universal Thermal Climate Index) that can reasonably evaluate the outdoor thermal conditions in China. The proposed adapted UTCI gives a better understanding of the severe cold region's outdoor thermal comfort. To develop the adapted UTCI for this evaluation in China, we first calibrated a CFD (Computational Fluid Dynamics) model based on the site measurements. Second, we introduced machine learning to reduce the CFD simulation for an entire winter season. Once the CFD and machine learning was able to find the entire winter season's outdoor condition, these values were used to calculate the UTCI measure for the test site and then were compared with the questionnaires collected at the test site. Third, based on the comparison between the UTCI and the questionnaires, it was possible to develop the UTCI adaptation for the older population who live in this severely cold region. Lastly, we used the UTCI adaptation to identify some key factors of urban spatial variables that impact on outdoor thermal comfort. The test results showed that the UTCI adaptation result shows a better rest of a 5.00 % difference compared to the original UTCI result of 10.28 % from the survey result. In terms of spatial variables, SC (Site Coverage), ABF (Average of Building Footprint), PA (Pervious Area), shows an average p-value of 0.01, 0.025, 0.032 that it is a statistically significant influence on outdoor thermal conditions. Findings can provide information for further study on residential planning and design in the severely cold climate in northern China.