Verifying national inventory-based combustion emissions of CO₂ across the UK and mainland Europe using satellite observations of atmospheric CO and CO₂

Abstract. Under the Paris Agreement, countries report their anthropogenic greenhouse gas emissions in national inventories, used to track progress towards mitigation goals, but they must be independently verified. Atmospheric observations of CO₂, interpreted using inverse methods, can potentially provide that verification. Conventional CO₂ inverse methods infer natural CO₂ fluxes by subtracting a priori estimates of fuel combustion from the a posteriori net CO₂ fluxes, assuming that a priori knowledge for combustion emissions is better than for natural fluxes. We describe an inverse method that uses measurements of CO₂ and carbon monoxide (CO), a trace gas that is co-emitted with CO₂ during combustion, to report self-consistent combustion emissions and natural fluxes of CO₂. We use an ensemble Kalman filter and the GEOS-Chem atmospheric transport model to explore how satellite observations of CO and CO₂ collected by TROPOMI and OCO-2, respectively, can improve understanding of combustion emissions and natural CO₂ fluxes across the UK and mainland Europe, 2018–2021. We assess the value of using satellite observations of CO_2, with and without CO, above what is already available from the in situ network. Using CO₂ satellite observations lead to small corrections to a priori emissions that are inconsistent with in situ observations, due partly to the insensitivity of the atmospheric CO₂ column to CO₂ emission changes. When we introduce satellite CO observations, we find better agreement with our in situ inversion and a better model fit to atmospheric CO₂ observations. Our regional mean a posteriori combustion CO₂ emission ranges 4.6–5.0 Gt a^-1 (1.5–2.4 % relative standard deviation), with all inversions reporting an overestimate for Germany’s wintertime emissions. Our national a posteriori CO₂ combustion emissions are highly dependent on the assumed relationship between CO₂ and CO uncertainties, as expected. Generally, we find better results when we use grid-scale based a priori CO₂:CO uncertainty estimates rather than a fixed relationship between the two species.