Decomposition analysis of regional differences in China's carbon emissions based on socio-economic factors

Abstract

Developing policies and setting carbon reduction targets for various regions in China are important actions to narrow the gap of regional carbon emissions. This study reports on the differences in carbon emissions in the eastern, central, and western regions of China from 2005 to 2021 using the Theil index, and decomposes carbon emissions into emission intensity, industrial structure, economic scale, and population size effects using the Logarithmic Mean Divisia Index. In order to analyze the impact of socio-economic factors on carbon emissions, the industrial structure and emission intensity effects are divided into six socio-economic sectors. The major outcomes reported that: (1) the regional differences account for 70 % of the total carbon emissions difference, and the eastern region reported the most significant carbon emission difference; (2) the emission intensity and the economy scale are the top two effects on carbon emissions. The economic scale effect always drives an increase in carbon emissions, while emission intensity promotes a decrease in carbon emissions. The industrial structure effect shows a gradually decreasing trend in all regions, especially in the eastern region, the effect has turned negative since 2013. This is due to the proposed industrial transformation and upgrading in China since 2013, which has promoted the reconstruction of competitive advantages for high polluting heavy industry enterprises and accelerating the green transformation of industrial technology; (3) the industry sector contributes to the highest carbon emissions, followed by the transportation sector. Both sectors are the top two emitters and should be targeted for carbon reduction. The carbon emissions were generated based on the terminal energy consumption. The contribution effects of multiple industries and the differences in carbon emissions as affected by the driving factors and economic mechanisms among different regions in China were analyzed.