Abstract
Carbon emissions have increasingly been the focus of all governments as countries throughout the world choose carbon neutrality as a national development strategy. The analysis of the spatiotemporal dynamics of CO(2) emission has emerged as a significant research topic considering the dual-carbon goal. In this research, we explore the spatiotemporal changes of CO(2) emission at different scales based on nighttime light data. The Chinese Academy of Science's Earth Luminous Dataset, CO(2) emission data from Carbon Emission Accounts and Datasets, and basic national geographical data are used for analysis. A linear regression model between nighttime light data and CO(2) emission is constructed. Thereafter, the global Moran's I index of exploratory spatial data analysis is used to verify the spatial parameters of all provinces. The trend value method is utilized to analyze the changing trend of CO(2) emission at multiscale levels, covering the Chinese mainland, three major economic regions, and six largest agglomerations from 2012 to 2019. Experimental results show a significant positive correlation between the CO(2) emission and nighttime light data from 2012 to 2019. The nighttime light data could be used to effectively estimate the total CO(2) emission at the provincial and municipal levels in China. The growth rate of CO(2) emissions in China is stable and has decreased in 2015. Furthermore, the spatiotemporal dynamics of CO(2) emission in different agglomerations vary. Our work provides a scientific basis for the different provinces and cities to develop feasible emission reduction policies.