Estimating Carbon Dioxide Emissions in Two California Cities Using Bayesian Inversion and Satellite Measurements

Creators: Hamilton, Sofia D.¹; Wu, Dien²; Johnson, Matthew S.³; Turner, Alexander J.⁴; Fischer, Marc L.¹; Dadheech, Nikhil⁴; Jeong, Seongeun¹

1. Lawrence Berkeley National Laboratory
2. California Institute of Technology
3. Ames Research Center
4. University of Washington

Abstract

NASA's Orbiting Carbon Observatories (OCO‐2 and OCO‐3) provide measurements of column‐averaged carbon dioxide concentrations (XCO₂) with sufficient spatial resolution and precision to constrain bottom‐up estimates of CO₂ fluxes at regional scales. We use Bayesian inversion methods assimilating satellite retrievals to improve estimates of CO₂ fluxes in the South Coast Air Basin (SoCAB) which surrounds Los Angeles, and in the San Francisco Bay Area Air Basin (SFBA). We study 2020 to understand the impact of the COVID‐19 lockdowns and an active wildfire season. Our results indicated that a 50% (30%) reduction in CO₂ emissions relative to 2015 during the COVID‐19 lockdown period was consistent with OCO measurements for SFBA (SoCAB). We find that posterior wildfire emissions differed significantly from the prior at the scale of individual wildfires, though with large uncertainties, and that wildfire emissions in SFBA are significant, attributing 72% of the region's CO₂ emissions during August 2020 to wildfires.

Copyright and License

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Acknowledgement

Work at Lawrence Berkeley National Laboratory (LBNL) was supported by NASA's funding (80HQTR21T0101) through the Carbon Cycle Science Program, under Contract No. DE-AC02-05CH11231 with the U.S. Department of Energy. The authors thank the PI Computing Allowance Program at LBNL for computing allocations from the Lawrencium Cluster to conduct this work. Additional computing resources supporting this work were provided by the NASA High-End Computing Program through the NASA Advanced Supercomputing Division at NASA Ames Research Center. The views and opinions expressed herein by the authors do not necessarily state or reflect those of NASA, the United States Government, or the Regents of the University of California.

Funding

Work at Lawrence Berkeley National Laboratory (LBNL) was supported by NASA's funding (80HQTR21T0101) through the Carbon Cycle Science Program, under Contract No. DE-AC02-05CH11231 with the U.S. Department of Energy.

Data Availability

OCO-3 Level 2 v10.4r and OCO-2 Level 2 v11r data are available from (NASA EarthData, 2024). Vulcan version 3.0 data set is available at (Gurney et al., 2020a, 2020b). The CARB GHG Emission inventory is available at (California Air Resources Board, 2022). CalTrans PeMS data is available at (California Department of Transportation, 2022). OpenSky Network data is available at (Olive et al., 2022). Container throughput counts are available for the Port of Oakland at (Port of Oakland, 2022), Port of Los Angeles at (The Port of Los Angeles, 2022), and Port of Long Beach at (Port of Long Beach, 2022). CarbonTracker fluxes are available from (NOAA Global Monitoring Laboratory, 2024). SMUrF model data are available from (D. Wu et al., 2021b). Fire emissions data is available from (van Wees et al., 2022b). The inversion code is available at (Turner et al., 2020b). Posterior covariance code is available from the Supplement at (Yadav & Michalak, 2013).

Supplemental Material

Supporting Information S1.

Additional Information

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