Preprints
https://doi.org/10.5194/acp-2020-864
https://doi.org/10.5194/acp-2020-864

  31 Aug 2020

31 Aug 2020

Review status: a revised version of this preprint is currently under review for the journal ACP.

On the relationship between tropospheric CO and CO2 during KORUS-AQ and its role in constraining anthropogenic CO2

Wenfu Tang1,2, Benjamin Gaubert2, Louisa Emmons2, Yonghoon Choi3,4, Joshua P. DiGangi3, Glenn S. Diskin3, Xiaomei Xu5, Cenlin He6, Helen Worden2, Simone Tilmes2, Rebecca Buchholz2, Hannah S. Halliday3,a, and Avelino F. Arellano1 Wenfu Tang et al.
  • 1Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
  • 2Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
  • 3NASA Langley Research Center, Hampton, VA, USA
  • 4Science Systems and Applications, Inc., Hampton, VA, USA
  • 5Department of Earth System Science, University of California, Irvine, CA, USA
  • 6Research Applications Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
  • anow at: US Environmental Protection Agency, Research Triangle Park, Durham, NC, USA

Abstract. While the complementarity of CO data in monitoring CO2 from fossil-fuel combustion (ffCO2) is widely known, a rigorous demonstration of its use in reducing uncertainties on top-down regional ffCO2 emissions is still warranted. Here, we report a case study investigating the regional covariation of observed and modeled abundances of CO, CO2, and ffCO2 and demonstrating its implication to joint CO:CO2 inversions. We use data from a recent aircraft field campaign (KORUS-AQ) conducted over Korea and neighboring regions on May 2016 for this case study. We use the Community Atmosphere Model with Chemistry (CAM-Chem) to simulate CO, CO2, ffCO2 and associated source tags, using a posteriori fluxes from global CO2 flux inversions and CO emissions independently calibrated against CO data. Among other model-data comparisons, CAM-Chem simulations show an underestimation in CO2 (1 ppm), CO (24 ppb) and ffCO2 (1 ppm) against aircraft measurements. These are all within the range of model and data uncertainties. Although the overall observed enhancement ratio, ΔCO⁄ΔCO2 (~ 13.3 &om; 0.21 ppb/ppm), is well captured by CAM-Chem (~ 13.8 ± 0.23 ppb/ppm), we find an overestimation (29 ppb/ppm) for air samples between 2 to 3 km, where East Asian influence is substantial (35 %). The contribution of ffCO2 from Korea and Japan is smaller (30 %) and localized below 3 km, suggesting that regional ffCO2 and background and non-ffCO2 cannot be neglected in interpreting observed enhancements in this region. These spatial variations translate in the joint CO:CO2 inversion to increases in a posteriori ffCO2 estimates from East Asia (27 % ± 24 %) and Korea and Japan (9 % ± 17 %). This is consistent (albeit larger in 1-sigma uncertainty) with our estimate using 14CO2 data (27 % ± 9 % and 10 % ± 3 %, respectively). In contrast, the inversion using only CO2 data shows a decrease by ~ 5 % ± 27 % in East Asia and ~ 6 % ± 19 % in Korea and Japan. Our results show that inversions using both CO2 and CO can be an effective approach in constraining ffCO2 when the regional variations of CO and CO2 relationships are appropriately accounted for. Although this further points to the potential of augmenting current observing system of CO2 with CO for global inverse analyses of ffCO2 from different regions of the globe, we highlight the need to verify the spatiotemporal distribution of the covariation of CO with CO2 in both regional and global models. We caution its use for constraining local ffCO2, unless the spatiotemporal a priori flux distribution and surface processes are reasonably represented, as they may confound the analysis. These have important implications on inversion studies using columnar data from satellite observations, especially for regions lacking necessary verification measurements.

Wenfu Tang et al.

 
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Status: final response (author comments only)
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Wenfu Tang et al.

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Short summary
A specific demonstration of the potential use of correlative information from carbon monoxide to refine estimates of regional carbon dioxide emissions from fossil fuel combustion.
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