Spatial Heterogeneity of Regional Carbon Emissions and Its Driving Factors in China

Abstract

Using Exploratory Spatial Analysis and Geographically Weighted Regression Model, this paper studies and analyses the global and local spatial self-correlation of regional carbon emissions in China from 1997 to 2017, as well as the spatial heterogeneity characteristics of driving factors. The results show that: (1) The impacts of economic development, energy consumption and population on regional carbon emissions in China are all positively correlated, but there are heterogeneity in the impact of different regions. (2) The proportion of the tertiary industry has a negative correlation with the regional carbon emissions in China. The impact of the industrial structure in the western region is significantly lower than that in the eastern and central regions. (3) The influence degree of the four driving factors on China’s regional carbon emissions is: population> industrial structure> energy consumption> economic development.