State-wide California 2020 Carbon Dioxide Budget Estimated with OCO-2 and OCO-3 satellite data

Abstract. Satellite observations are instrumental in observing spatiotemporal variability in carbon dioxide (CO₂) concentrations which can be used to derive fluxes of this greenhouse gas. This study leverages NASA’s Orbiting Carbon Observatory-2 and -3 (OCO-2/3) CO₂ observations with a Gaussian Process (GP) machine learning inverse model, a Bayesian non-parametric approach well-suited for integrating the unique spatiotemporal characteristics of these satellite observations, to estimate sub-regional CO₂ fluxes. Utilizing the GEOS-Chem chemical transport model (CTM) which simulates column-average CO₂ concentrations (XCO2) for 2020 in California – a period marked by the Coronavirus disease (COVID-19) pandemic and significant wildfire activity – we estimated state-wide CO₂ emission rates constrained by OCO-2/3. This study developed prior fossil fuel emissions to reflect reduced activities during the COVID-19 pandemic, while net ecosystem exchange (NEE) and fire emissions were derived based on satellite data. GEOS-Chem source-specific XCO2 concentrations for fossil fuels, NEE, fire, and oceanic sources were simulated coincident to OCO-2/3 XCO2 retrievals to estimate statewide sector-specific and total CO₂ emissions. GP inverse model results suggest annual posterior median fossil fuel emissions were consistent with prior estimates (317.8 and 338.4±46.4 Tg CO₂ yr^-1, respectively) and that posterior NEE fluxes had less carbon uptake compared to prior fluxes (-36.8±32.8 vs. -99.2 Tg CO₂ yr^-1, respectively). Posterior fire CO₂ emissions were estimated to be 68.0±50.6 Tg CO₂ yr^-1 which was much lower compared to a priori estimates (103.3 Tg CO₂ yr^-1). The total median annual CO₂ emissions for the state of California in 2020 were estimated to be 349.6 Tg CO₂ yr^-1 (range of 272.8 – 428.6 Tg CO₂ yr^-1; 95 % confidence level), aligning closely with the prior total estimate of 342.5 Tg CO₂ yr^-1. This study, for the first time, demonstrates that OCO-2/3 XCO2 observations can be assimilated into inverse models to estimate state-wide, source-specific CO₂ fluxes on a seasonal- and annual-scale.