Accurate estimates of fossil fuel CO2(FFCO2) emissions are of great importance for climate prediction and mitigation regulations but remain a significant challenge for accounting methods relying on economic statistics and emission factors. In this study, we employed a regional data assimilation framework to assimilate in situNO2observations, allowing us to combine observation-constrained NOxemissions coemitted with FFCO2and grid-specific CO2-to-NOxemission ratios to infer the daily FFCO2emissions over China. The estimated national total for 2016 was 11.4 PgCO2·yr–1, with an uncertainty (1σ) of 1.5 PgCO2·yr–1that accounted for errors associated with atmospheric transport, inversion framework parameters, and CO2-to-NOxemission ratios. Our findings indicated that widely used “bottom-up” emission inventories generally ignore numerous activity level statistics of FFCO2related to energy industries and power plants in western China, whereas the inventories are significantly overestimated in developed regions and key urban areas owing to exaggerated emission factors and inexact spatial disaggregation. The optimized FFCO2estimate exhibited more distinct seasonality with a significant increase in emissions in winter. These findings advance our understanding of the spatiotemporal regime of FFCO2emissions in China.