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 volatile organic compounds (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 Plain (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 2 the modeled biogenic emissions for the plant functional types found in Korea. Results also suggest that controlling VOC and CO emissions, in addition to widespread NO x controls, can improve ozone pollution over East Asia.

Highlights

  • Carbon monoxide (CO) is a good tracer of biomass burning (Crutzen et al, 1979; Edwards et al, 2004, 2006) and anthropogenic emission sources (e.g., Borsdorff et al, 2019)

  • In order to evaluate the carbon monoxide (CO) sink and the impact of the assimilation of Measurements of Pollution in the Troposphere (MOPITT) CO retrievals on the HOx levels, we used the OH and HO2 calculated with the National Aeronautics and Space Administration (NASA) Langley Research Center (LaRC) 0-D time-dependent photochemical box model (Schroeder et al, 2020)

  • This suggests that weather patterns and direct anthropogenic emissions explain some of the CO variability during the campaign

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Summary

Introduction

Carbon monoxide (CO) is a good tracer of biomass burning (Crutzen et al, 1979; Edwards et al, 2004, 2006) and anthropogenic emission sources (e.g., Borsdorff et al, 2019). Since long-range transport is important, the forecasted CO and water vapor during KORUS-AQ can be improved by assimilating soil moisture from the NASA SMAP satellite (Soil Moisture Active Passive) over China (Huang et al, 2018) They stress the importance of error sources stemming from chemical initial and boundary conditions as well as emissions for modeling CO during two studied pollution events.

Field campaign observations
The ARIAs campaign
Model configuration and improvements
Sensitivity test on the biogenic emissions
Chemical data assimilation system
MOPITT assimilation
Ensemble design
Variable localization and parameter estimation
Simulation overview
Assimilation results: evaluation of the posterior CO during KORUS-AQ
VOCs state vector augmentation
Chemical response from MOPITT-DA
Comparison of anthropogenic emission estimates
Mean profile during ARIAs and KORUS-AQ
Weather-induced dynamical change in CO during KORUS-AQ
Phase 2 case study: the anticyclonic phase
Phase 3 case study: low-level transport and haze development
Conclusions
CH4 emissions from the Global Carbon Project CH4
The HO2 uptake by aerosol particles
Findings
Results on HO2 uptake and methane emissions
Full Text
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