Temporal-spatial characteristics of energy-based carbon dioxide emissions and driving factors during 2004-2019, China

China is committed to developing a low-carbon economy that will contribute to achieving the national strategic target of carbon peak and carbon neutrality. However, changes in energy-based carbon dioxide (CO2) emissions at both long-term and global-local scales remain poorly revealed. This study explored the temporal-spatial dis-tribution characteristics of energy-based CO2 emissions calculated by the Intergovernmental Panel on Climate Change (IPCC) carbon emissions coefficient method during the period of 2004, 2010 and 2019, covering 30 provinces in China. Then, this presented study examined the impact degree of socio-economic factors concerning energy-based CO2 emissions at the global and local levels using the expanded Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model and geographically weighted regression (GWR) model, respectively. The results indicated that the total CO2 emissions have significant spatial spillover effect in northeast region, where the cluster pattern of high total CO2 emissions and high CO2 emissions from coal mainly occur. Moreover, both urbanization and Gross Domestic Product (GDP) are significantly responsible for the in-crease in CO2 emissions. This proposed research framework can be promoted to explore the temporal-spatial characteristics of energy-based CO2 emissions in the city, the county, and even town levels to successfully realize CO2 emissions reduction.

Automated summary

This study explores the temporal-spatial distribution characteristics of energy-based CO2 emissions in China and finds significant spatial spillover effects in the northeast region. Urbanization and GDP are identified as important factors contributing to CO2 emissions increase. This research framework can help achieve CO2 emissions reduction.