Spatiotemporal variations and driving forces of per capita carbon emissions from energy consumption in China

The carbon emissions vary over space and time in China, as well as driving forces. It is particularly important to analyze the spatiotemporal variations and driving factors of China’s per capita carbon emissions. This study adopted global Moran’ I and local indicators of spatial association to analyze the spatial autocorrelation of per capita carbon emissions in China during 2004–2019 and discussed the driving factors of per capita carbon emissions by geographically and temporally weighted regression model. The results demonstrated a positive spatial correlation between inter-provincial per capita carbon emissions, but this correlation has gradually decreased since 2008. The High-High clusters were concentrated in the Bohai Economic Rim and the Low-Low clusters were mainly located in the south. Driving factors of per capita carbon emission at the provincial level have spatiotemporal heterogeneity. From 2004 to 2019, per capita GDP, urbanization rate, and energy intensity are the main contributors to per capita carbon emissions, and the role of per capita GDP is weakening, while urbanization rate and energy intensity change in the opposite direction. Foreign direct investment is the main disincentive in most regions. These findings provided a reference for emission reduction policies implemented in different regions.