Abstract
Abstract. This study suggests a new modeling framework using a hybrid Eulerian–Lagrangian-based modeling tool (the Screening Trajectory Ozone Prediction System, STOPS) for a prediction of an Asian dust event in Korea. The new version of STOPS (v1.5) has been implemented into the Community Multi-scale Air Quality (CMAQ) model version 5.0.2. The STOPS modeling system is a moving nest (Lagrangian approach) between the source and the receptor inside the host Eulerian CMAQ model. The proposed model generates simulation results that are relatively consistent with those of CMAQ but within a comparatively shorter computational time period. We find that standard CMAQ generally underestimates PM10 concentrations during the simulation period (February 2015) and fails to capture PM10 peaks during Asian dust events (22–24 February 2015). The underestimation in PM10 concentration is very likely due to missing dust emissions in CMAQ rather than incorrectly simulated meteorology, as the model meteorology agrees well with the observations. To improve the underestimated PM10 results from CMAQ, we used the STOPS model with constrained PM concentrations based on aerosol optical depth (AOD) data from the Geostationary Ocean Color Imager (GOCI), reflecting real-time initial and boundary conditions of dust particles near the Korean Peninsula. The simulated PM10 from the STOPS simulations were improved significantly and closely matched the surface observations. With additional verification of the capabilities of the methodology on emission estimations and more STOPS simulations for various time periods, the STOPS model could prove to be a useful tool not just for the predictions of Asian dust but also for other unexpected events such as wildfires and oil spills.
Highlights
Particulate matter (PM) is one of the key air pollutants in the lower atmosphere
Screening Trajectory Ozone Prediction System (STOPS) v1.5 has been implemented into Community Multi-scale Air Quality (CMAQ) v5.0.2 for PM10 simulations over the east Asia during Asian dust events and we investigated the possibility of using STOPS to enhance the accuracy of PM10 forecasting
During the entire simulation period (February 2015), the standard CMAQ underestimated PM10 concentrations compared to surface observations and failed to capture the PM10 peaks of Asian dust events (22–24 February 2015)
Summary
Particulate matter (PM) is one of the key air pollutants in the lower atmosphere. Numerous studies have reported its adverse effects on human health and the environment (Park et al, 2005; Heo et al, 2009; Jeon et al, 2015). Dust emissions from Mongolia and the Gobi Desert (Chun et al, 2001; Kim et al, 2008; Heo et al, 2009) cause extraordinarily severe yellow sand storms that often cover the entire sky over Korea during the spring and late winter These result in reduced visibility (Chun et al, 2001) and increased mortality due to cardiovascular and respiratory diseases (Kwon et al, 2002), and their adverse effects are more evident in Published by Copernicus Publications on behalf of the European Geosciences Union
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