Exploring the Impact of Digital Economy on Carbon Emission Intensity: Empirical Analysis Based on Panel Data of Chinese Cities

China’s urban low-carbon transition requires clearer city-level evidence on whether and how digitalization mitigates carbon emission intensity. Using panel data for 288 Chinese prefecture-level and above cities from 2013 to 2022, this study constructs a multidimensional Digital Economy Index and measures carbon emission intensity using EDGAR emissions and GDP at constant 2013 prices. We employ two-way fixed effects, instrumental variables, System GMM, robustness checks, mediation analysis, heterogeneity tests, and a Spatial Durbin Model. The results show that digital economy development significantly reduces urban carbon emission intensity, and this conclusion remains robust across alternative measurements, lag specifications, sample adjustments, fixed-effect structures, and endogeneity corrections. Mechanism analysis indicates that industrial structure rationalization and upgrading are key transmission channels, whereas technological innovation may generate short-term adjustment costs consistent with a “green paradox.” The carbon-reduction effect is stronger in old industrial base cities, cities with weaker initial innovation foundations, and cities with lower initial population density. Spatial analysis shows that digitalization generates significant carbon-reduction spillovers under geographical proximity, while economic-linkage-based spillovers are more complex. These findings provide theoretical and policy implications for digitally enabled and regionally coordinated urban decarbonization.