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Highlights • We mapped city-level CO 2 emissions simulated by DMSP/OLS nighttime light imagery. • City-level CO 2 emissions were featured as spatial agglomerations. • The GWR revealed significant spatial heterogeneity in the impacts of different factors. • Private car ownership, PCGDP, energy consumption positively affected CO 2 emissions both globally and locally. • The reminder factors studied in the GWR were found to bi-directionally affect CO 2 emissions. Abstract Cities produce over 70% of the global CO 2 emissions that result from energy use, and thus play a key role in climate mitigation and adaptation. While the factors influencing CO 2 emissions have been subject to extensive study, via research that has explored the path of developing a low-carbon economy, little work has been undertaken at the city level as a result of a deficiency in data availability. Addressing this gap, this study firstly estimated CO 2 emissions of cities in China using Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime light imagery. We then analyzed spatial variations in the estimated CO 2 emissions at the city level, using a spatial analytical model, finding significant spatial autocorrelation in CO 2 emissions. Subsequently, we compared the effects of different socioeconomic factors on CO 2 emissions, using both global and local regression models. The results from the global regression model revealed that private car ownership, economic growth, and energy consumption were the major factors promoting CO 2 emissions in China's cities, while population density had an effect in reducing CO 2 emissions. The use of a Geographically Weighted Regression (GWR) model provided more detailed results, revealing significant spatial heterogeneity in the impacts of different factors. Economic growth, private car ownership, and energy consumption all posed positive effects on CO 2 emissions while the remainder of the factors studied were found to pose a bidirectional impact on CO 2 emissions in different areas of China. Economic growth and private car ownership were to found to exert the strongest positive effects in the cities of western and central China, and energy consumption was shown to significantly and positively influence CO 2 emissions in the southernmost part of China. Urban expansion and road density were identified as key promoting factors in CO 2 emissions in the northeast of China; and the industrial structure demonstrated significantly positive effects in relation to CO 2 levels in cities located in the Beijing-Tianjin-Hebei region. The role of foreign direct investment (FDI) was not found to be significant in most cities expect Guangdong, where a significant positive relationship appeared. [ABSTRACT FROM AUTHOR]