A Study Mass Extinction Efficiency (MEE) Calculation and Variability Analysis by Aerosol Source Identification: Application of Horizontal Scanning Lidar and HYSPLIT Model

South Korea faces complex air quality challenges arising from domestic emission sources driven by industrialization and urbanization, as well as seasonally influenced long-range transport pollutants from overseas. In particular, springtime dust storms and wintertime heating emissions both domestic and foreign converge to create a multifaceted air pollution environment. To effectively understand and manage these issues, accurately determining the Mass Extinction Efficiency (MEE) based on optical observations is essential. In this study, we refined MEE calculations by integrating LiDAR-based observations with ground-level measurements, analyzed variability as a function of aerosol origin, and simultaneously assessed the potential for indirect evaluation of atmospheric composition. Using a horizontal SCANNING LiDAR, we derived high-resolution, two-dimensional extinction coefficients near the surface and combined these data with hourly Particulate Matter (PM) observations from the AirKorea monitoring network. Employing the Ångström exponent to differentiate coarse mode particles (Ångström exponent ≈ 0) from fine mode particles (Ångström exponent ≈ 3), we calculated extinction coefficients for total, coarse, and fine aerosols. We then derived MEE values through three approaches: total extinction coefficient relative to PM10, coarse extinction coefficient relative to (PM10 – PM2.5), and fine extinction coefficient relative to PM2.5. To analyze aerosol origins, we used the HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) model of NOAA(National Oceanic and Atmospheric Administration), which allowed us to evaluate mesoscale and regional source contributions and investigate their impact on MEE variability. Data from December 2021 to the present revealed substantial variations in MEE values depending on aerosol source regions and compositions. By offering a refined analytical framework tailored to South Korea’s unique climatic and geographical characteristics, this study provides valuable insights for improved air quality monitoring and predictive modeling.

"This research was supported by Particulate Matter Management Specialized Graduate Program through the Korea Environmental Industry & Technology Institute(KEITI) funded by the Ministry of Environment(MOE)"