The relationship between urbanization and carbon emissions affects economic development, industrial structure, residents' income and the enhancement of comprehensive national strength. It is of great practical significance to study the relationship between urbanization and carbon emissions. At the same time, carbon emissions have increased sharply in recent years. How to reduce carbon emissions while developing urbanization is an urgent problem to be solved. In this paper, the panel data of 30 provinces in China from 2000 to 2019 except Hong Kong, Macao, Taiwan and Tibet were used as samples to construct the static panel STIRPAT model and the spatial Dobbin model. The static panel STIRPAT model shows that both industrial structure and energy intensity variables have a positive impact on carbon emissions. Energy intensity and GDP per capital have the largest impact on carbon emissions, followed by population variables. The spatial Dobbin model shows that both the core explanatory variables and the control variables significantly affect carbon emissions, and the regression coefficients are positive. The analysis of the spatial spillover effect shows that the control variables are significant except for the level of science and technology, and the population variables and per capital GDP have negative spatial spillover effect on the carbon emissions of neighboring areas. There are positive spatial spillover effects of industrial structure and energy structure on carbon emissions in neighboring regions. Finally, according to the empirical results, put forward the targeted suggestions.