Estimating multi-temporal anthropogenic heat flux based on the top-down method and temporal downscaling methods in Beijing, China

Abstract

Anthropogenic heat is a dominant component in the urban surface energy system and a key to understanding urban thermal environments. The top-down method was widely used to estimate anthropogenic heat flux (AHF) using statistical energy consumption data and proxies. However, there are several limitations. First, the coarse resolutions of current proxies cannot capture the heterogeneous AHF. Besides, the temporal resolution is generally low (annual) in most AHF studies using the top-down method. This study estimated AHFs from three sectors and their monthly and hourly patterns in Beijing, China by developing a new framework. We first used a new proxy of building volume to obtain the AHF from buildings. Then, we estimated the AHF from vehicles and human metabolism using road density and population density, respectively. Finally, the monthly and hourly (workday and non-workday) AHFs were derived using temporal downscaling methods. The results show that the historic buildings in the urban center have a relatively low AHF. Areas with high AHF mainly distribute in the region between the 2nd and 4th ring-road and industrial zones outside the 5th ring-road. The magnitude of AHF varies among months, with the maximum monthly AHF at the district level reaching 68.1 W/m2 in January. AHF in January workdays is significantly higher than that in January non-workdays during 7:00 h to 20:00 h. The estimated AHF in this study can better capture multi-temporal AHF through the top-down method and temporal downscaling methods. The improved AHF data help policymakers design various strategies to improve urban thermal environments under sustainable development goals.