[Spatial-temporal Evolution and Heterogeneity of Carbon Emissions at County-level in China]

Counties are the key spatial units in achieving the reduction and control of carbon emissions. It is of great significance to study and reveal the spatial-temporal evolution characteristics and influencing mechanism of carbon emissions for realizing the "carbon peak and carbon neutral" goal. In this study, the spatial-temporal evolution and heterogeneity of carbon emissions at the county level in China from 2000 to 2017 were analyzed by using mathematical statistics and panel data regression modeling, and the influencing mechanism was explored. The results showed that: ① from 2000 to 2017, the annual growth rate of carbon emissions was 7.12%, which experienced the three stages of "sharp rise, slow rise, and high fluctuation" and finally stabilized at approximately 90×10⁸ t. At the county scale, there was a significant positive spatial autocorrelation. ② The general panel regression model showed that GDP, construction land area, population, per capita GDP, and per capita deposit balance of financial institutions were significantly correlated with carbon emissions, and the former three had the strongest promoting effect on carbon emissions. ③ The goodness of fit of the geographically and temporally weighted regression model was high, and the direction and intensity of the other impact factors changed greatly in spatial-temporal characteristics, except that GDP showed a stable promoting effect globally. The results showed that carbon emission levels and main influencing factors varied among counties in China. This study revealed the heterogeneity of carbon emissions at the county level, which is helpful to optimize the spatial-temporal implementation path of the "dual carbon" target.