Inequality and its driving forces in residential CO2 emission: Perspective of energy use pattern

The complex geographic situation and various development levels have created differences in residential energy use patterns, inequalities problems in residential CO2 emissions among regions present a dilemma for policy-makers. Therefore, this study investigated residential CO2 emissions inequality and its driving factors to provide empirical support for the allocation of regional emission reduction quotas. Using the residential data of pro-vincial scale in China during 1997-2019, this research presents a complete decomposition from the perspective of energy use pattern and income disparities. The findings showed that the national residential CO2 emissions inequality decreased between 1997 and 2008, and then stabilized. The energy intensity effect was the main effect that decreased the inequality, while the energy use pattern increased it. For most inland regions, the within-group inequity was mainly due to energy input per income, while the inequality of coastal regions could be explained by the differences in income per capita. Regarding energy use inequality, the energy intensity effect was the main reason behind the inequality in heat and fuel energy use, but it had a smaller influence on the electricity consumption inequality. The Kaya-Theil decomposition model could be applied to investigate regional inequality in emissions, and the results help to design targeted differentiate mitigation measures for regional residential sector.

Automated summary

This study analyzes residential CO2 emissions inequality and its driving factors in China, using provincial-level residential data. The findings show that national residential CO2 emissions inequality decreased between 1997 and 2008 and then stabilized. The main factor that decreased inequality was the energy intensity effect, while the energy use pattern increased it. The Kaya-Theil decomposition model can be applied to investigate regional inequality in emissions and design targeted mitigation measures for the residential sector.