Investigating biases and uncertainties of air quality model used in GMAP 2021 field campaign

<p>The GEMS MAP of Air Pollution (GMAP) 2021 field campaign for South Korea was conducted in October-November 2021 to understand the changes in air quality after the KORUS-AQ field study and to support efficient pollution management for ozone and aerosol. Extensive aircraft and ground network observations from the campaign offer an opportunity to reduce model-observation disagreements. This study examines these issues using model evaluation against the GMAP 2021 observations and intercomparisons between models. Four regional and one global chemistry transport model using identical anthropogenic emissions participated in the model intercomparison study. Based on the KORUSv5.0 emission inventory that supported the KORUS-AQ campaign, GMAP/SIJAQv2.0 emission inventory was developed to reflect the latest emission trends of major countries affecting South Korea&#8217;s air quality.</p><p>From the results of the model using Global Forecast System (GFS) and final (FNL) Operational Global Analysis data during and after the campaign, the accuracy of the modeling results using FNL was higher than that of GFS, which is a result of informing that the accurate meteorological input data is important for the prediction of aerosol and ozone. In comparisons of simulated versus observed (AirKorea network) CO, O₃, NO₂, SO₂, and PM_2.5 concentrations in surface air averaged for the campaign period, the models successfully reproduced observed pollutants in surface air but similar to the results in KORUS-AQ showed low biases for carbon monoxide (CO), implying that there were possible missing CO sources in the inventory in East Asia. Observations show the highest values in the Seoul Metropolitan Area (SMA) and industrial regions except for O₃, which is strongly titrated by high NOx levels from traffic emissions. Relative contributions to air quality in South Korea by local and long-range transport pollution influences were classified using the Brute Force Method (BFM) for the campaign period. Observed aerosol chemical composition at the Olympic Park ground site showed that inorganic components (nitrate, sulfate, ammonium) contributed to PM_2.5 by 83% during the transboundary dominant case. On the other hand, in the case of local dominant, the contribution of organic carbonaceous aerosol was 42% to PM_2.5, indicating a clear difference between the two cases. In model simulations, there is a difference in the ratio between organic and inorganic aerosol, but the difference between the two cases was well simulated. And models showed a tendency to simulate Elemental Carbon (EC) at a concentration more than twice as high as observed due to the effect of emissions. From the model evaluation, we find that ensemble results of multiple models show the most consistent results with observations during the campaign period. In addition to improving the accuracy of individual models and emission inventory, evaluation of model accuracy according to ensemble techniques is necessary to improve forecast results.</p><p>&#160;</p><p>This research was supported by the FRIEND(Fine Particle Research Initiative in East Asia Considering National Differences) Project through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (Grant No.: 2020M3G1A1114615)</p>