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

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.

The adjoint of CMAQ

An adjoint model for the internationally used Community Multiscale Air Quality (CMAQ) modeling platform of the U.S. EPA is developed. The adjoint version for CMAQ (CMAQ-ADJ) provides the user community with forward (decoupled direct method or DDM) and backward (adjoint) sensitivity analysis capabilities. Current implementation is for gas-phase processes. Discrete adjoints are implemented for all processes with the exception of horizontal advection, for which, because of inherent discontinuities in the advection scheme, the continuous approach is superior. The adjoint of chemistry is constructed by interfacing CMAQ with the kinetic pre-processor, which provides for increased flexibility in the choice of chemical solver and facilitates the implementation of new chemical mechanisms. The adjoint implementation is evaluated both on a process-by-process basis and for the full model. In general, adjoint results show good agreement with brute-force and DDM sensitivities. As expected for a continuous adjoint implementation in a nonlinear scheme, the agreement is not perfect for horizontal transport. Sensitivities of various air quality, public health, and environmental metrics with respect to emissions are calculated using the adjoint method. In order to show applicability to regional climate studies, as an example, the sensitivities of these metrics with respect to local temperatures are calculated.