Abstract
Based on energy consumption data of each province in China from 2000 to 2019, this paper uses spatial autocorrelation analysis and Spatial Durbin Mode to explore the spatial distribution pattern of China's regional carbon emissions and the impact of population, economy, industrial structure, energy structure and urbanization level on carbon emissions. The results demonstrate that: (1) Carbon emissions from energy consumption of different provinces all increased from 2000 to 2019, while carbon emission intensity decreased year by year. (2) There is a spatial aggregation effect of regional carbon emissions in China, the spatial distribution of carbon emissions mainly shows a pattern of high in the East and low in the west. (3) Economic growth, population, industrial structure, energy structure, and urbanization rate are the main driving factors to carbon emissions. Different carbon control methods should be selected according to the influence mechanism of various driving factors in different regions on carbon emissions.
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