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One important goal of the Copernicus CO 2  monitoring (CO2M) mission is to quantify CO 2  emissions of large point sources. We analyzed the feasibility of such quantifications using synthetic CO 2  and NO 2  observations for a constellation of CO2M satellites. Observations were generated from kilometer-scale COSMO-GHG simulations over parts of the Czech Republic, Germany and Poland. CO 2  and NO X  emissions of the 15 largest power plants (3.7–40.3 Mt CO 2  yr −1 ) were quantified using a data-driven method that combines a plume detection algorithm with a mass-balance approach. CO 2  and NO X  emissions could be estimated from single overpasses with 39–150% and 33–116% uncertainty (10–90th percentile), respectively. NO 2  observations were essential for estimating CO 2  emissions as they helped detecting and constraining the shape of the plumes. The uncertainties are dominated by uncertainties in the CO2M observations (2–72%) and limitations of the mass-balance approach to quantify emissions of complex plumes (25–95%). Annual CO 2  emissions could be estimated with 23–119% and 18–65% uncertainties with two and three satellites, respectively. The uncertainty in the temporal variability of emissions contributes about half to the total uncertainty. The estimated uncertainty was extrapolated to determine uncertainties for point sources globally, suggesting that two satellites would be able to quantify the emissions of up to 300 point sources with &amp;lt;30% uncertainty, while adding a third satellite would double the number to about 600 point sources. Annual NO X  emissions can be determined with better accuracy of 16–73% and 13–52% with two and three satellites, respectively. Estimating CO 2  emissions from NO X  emissions using a CO 2 :NO X  emission ratio may thus seem appealing, but this approach is significantly limited by the high uncertainty in the emission ratios as determined from the same CO2M observations. The mass-balance approach studied here will be particularly useful for estimating emissions in countries where power plant emissions are not routinely monitored and reported. Further reducing the uncertainties will require the development of advanced atmospheric inversion systems for emission plumes and an improved constraint on the temporal variability of emissions using additional sources of information such as other satellite observations or energy demand statistics.

Quantifying CO2 Emissions of Power Plants With CO2 and NO2 Imaging Satellites