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Preprints
https://doi.org/10.5194/acp-2020-599
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-599
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 30 Jun 2020

Submitted as: research article | 30 Jun 2020

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This preprint is currently under review for the journal ACP.

Correcting model biases of CO in East Asia: impact on oxidant distributions during KORUS-AQ

Benjamin Gaubert1, Louisa K. Emmons1, Kevin Raeder2, Simone Tilmes1, Kazuyuki Miyazaki3, Avelino F. Arellano Jr.4, Nellie Elguindi5, Claire Granier5,6, Wenfu Tang7, Jérôme Barré8, Helen M. Worden1, Rebecca R. Buchholz1, David P. Edwards1, Philipp Franke9, Jeffrey L. Anderson2, Marielle Saunois10, Jason Schroeder11, Jung-Hun Woo12, Isobel J. Simpson13, Donald R. Blake13, Simone Meinardi13, Paul O. Wennberg14, John Crounse14, Alex Teng14, Michelle Kim14, Russell R. Dickerson15,16, Hao He15,16, and Xinrong Ren15,17 Benjamin Gaubert et al.
  • 1Atmospheric Chemistry Observations and Modeling, National Center for Atmospheric Research, Boulder, CO, USA
  • 2Computational and Information Systems Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
  • 3Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
  • 4Dept. of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
  • 5Laboratoire d’Aérologie, CNRS, Université de Toulouse, France
  • 6NOAA Chemical Sciences Laboratory-CIRES/University of Colorado, Boulder, CO, USA
  • 7Advanced Study Program, National Center for Atmospheric Research, Boulder, CO, USA
  • 8European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading, RG2 9AX, UK
  • 9Forschungszentrum Jülich GmbH, Institut für Energie und Klimaforschung IEK-8, 52425 Jülich, Germany
  • 10Laboratoire des Sciences du Climat et de l’Environnement, LSCE-IPSL (CEA-CNRS-UVSQ), Université Paris-Saclay, 91191 Gif-sur-Yvette, France
  • 11California Air Resources Board, Sacramento, CA, USA
  • 12Department of Advanced Technology Fusion, Konkuk University, Seoul, South Korea
  • 13Department Chemistry, University of California, Irvine, Irvine, CA 92697, USA
  • 14California Institute of Technology, Pasadena, CA, USA
  • 15Department of Atmospheric and Oceanic Science, University of Maryland, College Park, MD, USA
  • 16Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA
  • 17Air Resources Laboratory, National Oceanic and Atmospheric Administration, College Park, MD, USA

Abstract. Global coupled chemistry-climate models underestimate carbon monoxide (CO) in the Northern Hemisphere, exhibiting a pervasive, negative bias against measurements peaking in late winter and early spring. While this bias has been commonly attributed to underestimation of direct anthropogenic and biomass burning emissions, chemical production and loss via OH reaction from emissions of anthropogenic and biogenic VOCs play an important role. Here we investigate the reasons for this underestimation using aircraft measurements taken in May and June 2016 from the Korea United States Air Quality (KORUS‐AQ) experiment in South Korea and the Air chemistry Research In Asia (ARIAs) in the North China Plain (NCP). For reference, multispectral CO retrievals (V8J) from the Measurements of Pollution in the Troposphere (MOPITT) are jointly assimilated with meteorological observations using an Ensemble Adjustment Kalman Filter (EAKF) within the global Community Atmosphere Model with Chemistry (CAM-chem) and the Data Assimilation Research Testbed (DART). With regard to KORUS-AQ data, CO is underestimated by 42 % in the Control-Run and by 12 % with the MOPITT assimilation run. The inversion suggests an underestimation of anthropogenic CO sources in many regions, by up to 80 % for Northern China, with large increments over the Liaoning province and the North China Plains (NCP). Yet, an often-overlooked aspect of these inversions is that correcting the underestimation in anthropogenic CO emissions also improves the comparison with observational O3 datasets, and observationally constrained box model simulations of OH and HO2. Running a CAM-chem simulation with the updated emissions of anthropogenic CO reduces the bias by 29 % for CO, 18 % for ozone, 11 % for HO2 and 27 % for OH. Longer lived anthropogenic VOCs whose model errors are correlated with CO are also improved while short-lived VOCs, including formaldehyde, are difficult to constrain solely by assimilating satellite retrievals of CO. During an anticyclonic episode, better simulation of O3, with an average underestimation of 5.5 ppbv and a reduction in the bias of surface formaldehyde and oxygenated VOCs can be achieved by separately increasing by a factor of two the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to wide spread NOx controls, can improve pollution ozone over East Asia.

Benjamin Gaubert et al.

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Data sets

The Korea-United States Air Quality Field Study (KORUS-AQ) KORUS-AQ https://doi.org/10.5067/Suborbital/KORUSAQ/DATA01

MOPITT Beta Derived CO (Near and Thermal Infrared Radiances) V108 Deeter and the MOPITT team https://doi.org/10.5067/TERRA/MOPITT/MOP02J_L2.108

Model code and software

Community Earth System Model https://github.com/ESCOMP/cesm https://doi.org/10.5065/D67H1H0V

The Data Assimilation Research Testbed (Version Manhattan). NCAR DAReS team https://doi.org/10.5065/D6WQ0202

Benjamin Gaubert et al.

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Short summary
This study investigates carbon monoxide pollution in East-Asia during Spring using a numerical model, satellite remote sensing and aircraft measurements. We found an underestimation of emissions source. Correcting the emission bias can improve air quality forecasting of carbon monoxide and other species including ozone. Results also suggest that controlling VOC and CO emissions, in addition to wide spread NOx controls, can improve pollution ozone over East Asia.
This study investigates carbon monoxide pollution in East-Asia during Spring using a numerical...
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