<p>Industrial carbon dioxide (ICO₂) are the largest source of CO₂ emissions in China, and understanding ICO₂ spatiotemporal dynamics is crucial for effective carbon reduction as the country aims to achieve carbon neutrality in the coming decades. Most current studies mapping and analyzing ICO₂ emissions at the city or regional scale lack the spatial resolution necessary to inform carbon mitigation policies. Here we developed a panel data model to map ICO₂ emissions at a 1&#xa0;km spatial resolution using integrated nighttime light (NTL) data and energy consumption statistic data from 2000 to 2020 for mainland China. Spatiotemporal variability in ICO₂ emissions revealed large spatial heterogeneity, with high concentrations in eastern China and lower levels in the west. The gap in ICO₂ emission density between eastern and western China decreased over time. Spatiotemporal trends in ICO₂ emissions were classified into four growth patterns, high growth (HG), low growth (LG), negative growth (NG) and high negative growth (HNG). The national increase in ICO₂ emissions was attributed to emissions from 372 municipal cities, with contributions from two or more growth patterns based on local variations analysis. Furthermore, spatial clustering of ICO₂ emissions was observed over the years. ICO₂ emissions are strongly correlated with industrial structures, with the secondary sector accounting for the largest source for ICO₂ emissions. The findings enhance the understanding of the variations in ICO₂ emissions both across and within cities, provide critical insights of the differentiated roles from the cities on the national ICO₂ emissions, and support optimizing industrial structures and implementing effective carbon reduction measures.</p>