Insights into the spatiotemporal heterogeneity, sectoral contributions and drivers of provincial CO2 emissions in China from 2019 to 2022

CO2 emissions (CEs) pose a growing threat to environmental changes and global warming, attracting extensive attention. Here, we leveraged near-real-time monitoring data spanning 2019 to 2022 to investigate spatiotemporal heterogeneity, sectoral contributions, provincial spatial correlation, and driving factors influencing CEs at the provincial level in China. Our analysis, integrating Moran's Index analysis, Spearman correlation analysis, and the Geographically Weighted Regression model, unveiled China's consistent world-leading CEs, surpassing 10,000 Mt over the study period. Spatially, CEs exhibited a heterogeneous distribution, with markedly higher emissions in eastern and northern regions compared to western and southern areas. Temporally, CEs displayed significant fluctuations, peaking in the fourth quarter before declining in subsequent quarters. Chinese New Year and COVID-19 had the biggest effects on CEs, with average daily reductions of -20.8 % and -18.9 %, respectively, compared to the four-year average and the same period in 2019. Sectoral analysis highlighted the power and industry sectors as primary contributors to CEs in China, jointly accounting for 37.9 %-40.2 % and 43.5 %-46.4 % of total CEs, respectively. Spatial clustering analysis identified a distinct High-High agglomeration region, predominantly encompassing provinces such as Inner Mongolia, Shandong and Jiangsu. Furthermore, total energy consumption and electricity consumption emerged as significant drivers of CEs, exhibiting correlation coefficients exceeding 0.9, followed by exhaust emissions, population size, and gross domestic product. Moreover, the influence of drivers on provincial CEs exhibited notable spatial heterogeneity, with regression coefficients displaying a decreasing gradient