Characterizing Uncertainties in Atmospheric Inversions of Fossil Fuel CO2 Emissions in California

Atmospheric inverse modelling has become an increasingly useful tool for evaluating emissions of greenhouse gases including methane, nitrous oxide and synthetic gases such as hydrofluorocarbons (HFCs). Atmospheric inversions for emissions of CO₂ from fossil fuel combustion (ffCO₂) are currently being developed. The aim of this paper is to investigate potential errors and uncertainties related to the spatial and temporal prior representation of emissions and modelled atmospheric transport for the inversion of ffCO₂ emissions in the U.S. state of California. We perform simulation experiments based on a network of ground-based observations of CO₂ concentration and radiocarbon in CO₂ (a tracer of ffCO₂), combining prior (bottom-up) emission models and transport models currently used in many atmospheric studies. The potential effect of errors in the spatial and temporal distribution of prior emission estimates is investigated in experiments by using perturbed versions of the emissions estimates used to create the pseudo data. The potential effect of transport error was investigated by using three different atmospheric transport models for the prior and pseudo data simulations. We find that the magnitude of biases in posterior state-total emissions arising from errors in the spatial and temporal distribution in prior emissions in these experiments are 1–15 % of posterior state-total emissions, and generally smaller than the 2-σ uncertainty in posterior emissions. Transport error in these experiments introduces biases of −10 % to +6 % in posterior state-total emissions. Our results indicate that uncertainties in posterior state-total ffCO₂ estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15 % or less for the ground-based network in California we consider. We highlight the need for temporal variations to be included in prior emissions, and for continuing efforts to evaluate and improve the representation of atmospheric transport for regional ffCO₂ inversions.