Temporal dynamics and spatial differences of household carbon emissions per capita of China’s provinces during 2000–2019

To assess the characteristics of household carbon emissions per capita (HCPC), this paper divided China’s provinces into 4 groups based on the decoupling relationship between household consumption and related emissions. This classification helped to analyze the correlation and reflected the decoupling status between carbon emissions and household consumption and explored the effect of consumption growth on carbon emissions. Then, according to logarithmic mean divisia index (LMDI) model, HCPC in China’s provinces was decomposed into four drivers including carbon coefficient, energy structure, energy consumption, and population structure effect. Through multi-regional (M-R) analysis, temporal evolution and spatial differences of these four drivers in both national and provincial level were studied. This comparison method introduced temporal and spatial decomposition results into the same framework, which may provide a new perspective for analyzing carbon emission trends. The results showed that (a) the HCPC in all 30 provinces increased significantly especially in Inner Mongolia, Tianjin, Xinjiang, Heilongjiang, and Beijing. Energy consumption effect was the leading factor promoting HCPC growth. Energy structure and population structure also promoted HCPC growth slightly, and carbon coefficient was the effect which had inhibitory effect on HCPC growth at regional level. (b) Spatial differences of HCPC between regions narrowed during this period. This is mainly due to the rapid growth of HCPC in region IV. Energy consumption effect was the dominant factor for the spatial differences. Based on the results, this paper proposed to adopt more effective measures to improve energy efficiency, develop clean energy, and optimize energy structure, especially in the provinces with faster growth in carbon emissions.