Analyzing the spatio-temporal variation of the CO2 emissions from district heating systems with “Coal-to-Gas” transition: Evidence from GTWR model and satellite data in China

Abstract

Understanding the spatio-temporal heterogeneous effects of socioeconomic and meteorological factors on CO2 emissions from combinations of different district heating systems with “Coal-to-Gas” transition can contribute to the development of future low-carbon energy systems that are efficient and effective. This work downscales city-level CO2 emissions to a 3 × 3 km2 gridded level in northern China during 2012 to 2018. By employing the Geographically and Temporally Weighted Regression (GTWR) model, nighttime light (NTL) data are adopted as a proxy of the level of urbanization, and the Temperature-Humidity-Wind (THW) Index is used as a proxy of meteorological factors in the downscaling model. The results show that, for more than 85% of the cities, urbanization significantly enhances the CO2 emissions of district heating systems, while the THW Index shows negative impacts on CO2 emissions. Significant spatial and temporal heterogeneity exists. The grids with the highest CO2 emissions from coal-fired boilers (grids with annual variation >0.59 Gg CO2/year) are mainly located in nonurban areas of the two megacities Beijing and Tianjin and also in the capital cities of each province. Urbanization has larger effects on the CO2 emissions of natural gas-fired boilers than of coal-fired boilers and combined heat and power (CHP). The average growth rate of CO2 emissions of gas-fired boilers in the urban areas of the study regions was approximately 4.7 times that of nonurban areas. The spatio-temporal heterogeneous impacts of urbanization on CO2 emissions should therefore be considered in future discussions of clean heating policies and climate response strategies.