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

Abstract NASA's Orbiting Carbon Observatories (OCO‐2 and OCO‐3) provide measurements of column‐averaged carbon dioxide concentrations (XCO 2 ) with sufficient spatial resolution and precision to constrain bottom‐up estimates of CO 2 fluxes at regional scales. We use Bayesian inversion methods assimilating satellite retrievals to improve estimates of CO 2 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 CO 2 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 CO 2 emissions during August 2020 to wildfires.

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Publication Details

Journal
Geophysical Research Letters
Published
2024-10-25
DOI
https://doi.org/10.1029/2024gl111150
Citations
9
Primary Topic
Atmospheric and Environmental Gas Dynamics
Type
article
Field-Weighted Citation Impact
2.54

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article

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

Dien Wu, Alexander Jay Turner, Seongeun Jeong, Nikhil Dadheech et al.
9 citations
Geophysical Research Letters
Atmospheric and Environmental Gas Dynamics
2.54
article

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

Dien Wu, Alexander Jay Turner, Seongeun Jeong, Nikhil Dadheech, Matthew S. Johnson, Sofia D. Hamilton, M. L. Fischer
article en
9 citations

Abstract

Abstract NASA's Orbiting Carbon Observatories (OCO‐2 and OCO‐3) provide measurements of column‐averaged carbon dioxide concentrations (XCO 2 ) with sufficient spatial resolution and precision to constrain bottom‐up estimates of CO 2 fluxes at regional scales. We use Bayesian inversion methods assimilating satellite retrievals to improve estimates of CO 2 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 CO 2 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 CO 2 emissions during August 2020 to wildfires.

Geophysical Research LettersVol. 51(20)
California Institute of Technology (US), Ames Research Center (US), Lawrence Berkeley National Laboratory (US), University of Washington (US)
U.S. Department of Energy, National Aeronautics and Space Administration, Ames Research Center, Lawrence Berkeley National Laboratory
Openalex Percentile: Top 10%
Atmospheric and Environmental Gas Dynamics
2.54
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Estimating Carbon Dioxide Emissions in Two California Cities Using Bayesian Inversion and Satellite Measurements — Dien Wu, Alexander Jay Turner, et al. · Geophysical Research Letters (2024) | TGRS Research Map | TGRS