Based on the natural discontinuity method, kernel density estimation, Dagum Gini coefficient, exploratory spatial data analysis and other methods, this paper explores the temporal-spatial characteristics of China’s urban carbon emissions from 2000 to 2017, and investigate the influencing factors of China’s urban carbon emissions by using the decomposition model of the spatial Dubin model. The main conclusions are as follows: (1) China’s urban carbon emissions are steadily rising, but the growth rate of carbon emissions is slowing down gradually; The two-level differentiation of carbon emission distribution in the eastern and central regions are obvious, while that in the western and northeastern regions are not obvious. (2) There is a significant spatial autocorrelation of China’s urban carbon emissions, and the local agglomeration features are obvious, which are mainly “high-high agglomeration” and “low-low agglomeration”. (3) In terms of carbon emission factors, technological innovation, foreign investment, and government intervention can reduce carbon emissions in the eastern region; Government intervention has a mitigation effect on carbon emissions in the central region; Infrastructure construction and technological innovation can reduce carbon emissions in the western region; The industrial structure has a mitigation effect on carbon emissions in the northeastern region. The main research values are as follows: It is helpful to comprehensively understand the dynamic distribution, regional differences and spatial agglomeration characteristics of China’s urban carbon emissions, and then investigate the driving factors of carbon emissions in different regions, so as to provide a scientific basis for each region to further implement the “double carbon” strategy, promote the coordinated emission reduction of cities, and jointly build a green development path.