Research on the Spatio-temporal Distribution Characteristics and Cluster Analysis of Carbon Emissions in Chinese Cities

Cities are the most important source of greenhouse gas emissions, and urban carbon emission reduction has become an important measure of global response to climate change. Understanding the spatio-temporal evolution and clustering characteristics of urban carbon emissions are the prerequisite for realizing carbon emission reduction policies and implementation. In this paper, 296 municipal units in China have taken as the study area. This researches have used the Moran's index and K-means clustering to study the spatio-temporal distribution characteristics and clustering characteristics of urban carbon emissions. The STIRPAT model has used to analyze the influencing factors of urban carbon emissions with different clustering characteristics. The results showed that: ①During 2005 to 2020, there was a growing trend of urban carbon emission in China, and there was a big gap between the high and low values of urban carbon emission, with most of the cities concentrating in the middle value. The same was true for the per capita carbon emission. ② The overall distribution of urban carbon emissions in China has characterized by high in the east and low in the west, with east and north China being the main carbon emission regions.③ The carbon emissions of Chinese cities have obvious spatial differences and significant spatial correlation characteristics. Based on the cluster analysis of urban carbon emissions, 296 cities have classified into low-carbon demonstration cities, low-carbon development cities, resource-dependent cities and energy-consuming cities. Four types of cities were put forward corresponding low-carbon development suggestions combined with influencing factors.