Research on coordination level and influencing factors spatial heterogeneity of China's urban CO2 emissions

Abstract Cities play a critical role in achieving China's carbon emissions peak and carbon neutrality goals, but the policies of cities should be tailored to their developmental levels and local conditions. This study first analyzed the spatial autocorrelation of CO2 emissions in 336 cities in 2019. The coupling degree and coupling coordination degree were used to measure the coordination level between the CO2 emissions level and urban development by contemplating the urban development indicators. Depending on the coordination level and historical CO2 emissions of the city, the urban regions were reclassified with the density peak (DP) clustering algorithm. Finally, a multiscale geographically weighted regression (MGWR) model was used to explore the spatial heterogeneity of the influencing factors of the total CO2 emissions. The results showed that the coordination level of CO2 emissions in Shenzhen, Chengdu, and Guangzhou is relatively high; China's urban carbon emissions can be divided into six categories; and the impact on GDP per capita, population, and the proportion of secondary industries on CO2 emissions is spatially heterogeneous. In conclusion, this study divides China's cities and analyzes the key influencing factors of CO2 emissions into different categories, providing a reference for cities to achieve CO2 emissions reduction.