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

Abstract

• There is spatial autocorrelation of CO 2 emissions in China's 336 cities. • Quantitative analysis of the coordination level between CO 2 emissions level and urban development. • The carbon emissions in China's cities are reclassified into six categories using cluster analysis. • The influencing factors of CO 2 emissions have spatial heterogeneity. 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 CO 2 emissions in 336 cities in 2019. The coupling degree and coupling coordination degree were used to measure the coordination level between the CO 2 emissions level and urban development by contemplating the urban development indicators. Depending on the coordination level and historical CO 2 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 CO 2 emissions. The results showed that the coordination level of CO 2 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 CO 2 emissions is spatially heterogeneous. In conclusion, this study divides China's cities and analyzes the key influencing factors of CO 2 emissions into different categories, providing a reference for cities to achieve CO 2 emissions reduction.