Application of DIAL/HSRL and CATCH algorithm-based methodologies for surface PM2.5 concentrations during the KORUS-AQ campaign

Abstract

Particulate matter with an aerodynamic diameter of equal to or less than 2.5 mu m (PM2.5) has been found to have a serious adverse effect on human health and the environment. While the importance of measuring PM2.5 has been demonstrated, doing so remotely remains challenging. In this study, methodologies for the assessment of aerosol PM2.5 and chemical composition based on a combination of regional and global models and active remote sensing were evaluated against surface observations from the KORUS-AQ campaign. The model outputs from the Community Multiscale Air Quality (CMAQ) and GEOS-Chem were used and were available at the KORUS-AQ campaign data archive. For remote sensing, aerosol extinction and derived aerosol types available from NASA Langley Airborne Differential Absorption Lidar (DIAL)/High Spectral Resolution Lidar (HSRL) flying onboard DC-8 aircraft were used. A revised version of the algorithm, which incorporates size-specific aerosol dry mass extinction efficiencies for sulfate, nitrate, and ammonia as well as organic matter, is also presented. The PM2.5 concentration estimates were compared with measurements taken at the ground stations. The estimated mean absolute error between the ground station measurements and the remote-sensing-based methodologies was significantly lower compared to the models. The data analysis has shown that uncertainties in relative humidity values, the presence of particles larger than 2.5 mu m in diameter, and the abundance of black carbon and organic matter in Asian aerosol were unlikely to explain the differences between measured and predicted surface PM2.5. Local meteorology was found to play a key role influencing the spatiotemporal variability of aerosols and the most important factor determining the agreement between the estimated and ground site-measured PM2.5. The lowest mean absolute error was found for the May 1-16 period, when aerosols were well mixed within the mixing layer and homogeneous across the temporal (1 h) and spatial (8 km) scales used in this study. Under these conditions, the methodologies presented here could give reasonable estimates of PM2.5 concentration and derived chemical composition over South Korea when HSRL data are available.