Application of High Spectral Resolution Lidar (HSRL)-based Methods for Estimating PM2.5 during the KORUS-AQ Campaign

BETHANY SUTHERLAND, Nicholas Meskhidze, Sharon P. Burton, Johnathan Hair, Chris Hostetler, Richard Ferrare, NC State University

     Abstract Number: 328
     Working Group: Aerosol Physical Chemistry and Microphysics

Abstract
The amount and composition of ambient PM_2.5 has important ramifications for air quality and human health as well as climate science; therefore, much effort has been directed towards developing improved methods of remotely estimating both its concentration and chemical speciation. Here we follow up Meskhidze et al. (2021) by applying the CMAQ-HSRL-CH and HSRL-CH methodologies developed therein for estimating speciated PM_2.5 concentrations on data acquired during the Korea-United States Air Quality (KORUS-AQ) field study. The CMAQ-HSRL-CH method uses information about aerosol composition from the aerosol types derived from HSRL retrievals (Burton et al. 2012) and the CATCH algorithm (Dawson et al. 2017) and iteratively updates CMAQ model predicted concentrations. The HSRL-CH method relies solely on the HSRL retrievals and aerosol types to estimate PM_2.5 concentrations. In this study, we have updated the Meskhidze et al. (2021) HSRL-CH method to include size specific mass extinction coefficients and contribution from Rayleigh scattering following the revised IMPROVE algorithm (Pitchford et al., 2007). We also apply HSRL-based PM_2.5 data correction algorithms to GEOS-Chem model outputs, in addition to the CMAQ model. The results of our study show that over the Korean Peninsula model simulations (i.e., CMAQ and GEOS-Chem) and remotely-sensed data based algorithms show worse agreement with the ground station measurements compared to what was previously found over the eastern coast of the United States. For different methodologies, the r² value was reduced by roughly 50% while the normalized mean error increased by ~40%. The contributions of differing aerosol composition, complexity in the vertical structure of aerosol layers, fluctuation of mixing layer height, presence of coarse aerosols, and the effect of varying meteorological regimes on the results are investigated.

References:
[1] Burton et al. 2012 https://doi.org/10.5194/amt-5-73-2012
[2] Dawson et al. 2017 https://doi.org/10.1002/2017JD026913
[3] Meskhidze et al. 2021 https://doi.org/10.1016/j.atmosenv.2021.118250
[4] Pitchford et al. 2007 https://doi.org/10.3155/1047-3289.57.11.1326