State-wide California 2020 carbon dioxide budget estimated with OCO-2 and OCO-3 satellite data

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 and OCO-3, respectively) CO₂ observations with a Gaussian process (GP) machine learning inverse model, a Bayesian nonparametric approach well suited for integrating the unique spatiotemporal characteristics of these satellite observations, to estimate subregional CO₂ fluxes. Utilizing the GEOS-Chem chemical transport model (CTM) to simulate column-average CO₂ concentrations (XCO₂) for 2020 in California – a period marked by the coronavirus disease (COVID-19) pandemic, drought conditions, and significant wildfire activity – we estimated the 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 state-wide sector-specific and total CO₂ emissions. GP inverse model results suggest that annual posterior median fossil fuel emissions were consistent with prior estimates (317.8 and 338.4 Tg CO₂ yr⁻¹, respectively; 95 % confidence level) and that posterior NEE fluxes had less carbon uptake compared to prior fluxes (−36.8 vs. −99.2 Tg CO₂ yr⁻¹, respectively; 95 % confidence level). Posterior fire CO₂ emissions were estimated to be 68.0 Tg CO₂ yr⁻¹, which was much lower than 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.