1. High-Resolution Daily PM2.5 Exposure Concentrations in South Korea Using CMAQ Data Assimilation with Surface Measurements and MAIAC AOD (2015–2021)
- Author
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Jin-Goo Kang, Ju-Yong Lee, Jeong-Beom Lee, Jun-Hyun Lim, Hui-Young Yun, and Dae-Ryun Choi
- Subjects
long-term exposure concentrations ,multi-linear regression ,chemical transport model ,Meteorology. Climatology ,QC851-999 - Abstract
Particulate matter (PM) in the atmosphere poses significant risks to both human health and the environment. Specifically, PM2.5, particulate matter with a diameter less than 2.5 micrometers, has been linked to increased rates of cardiovascular and respiratory diseases. In South Korea, concerns about PM2.5 exposure have grown due to its potential for causing premature death. This study aims to estimate high-resolution exposure concentrations of PM2.5 across South Korea from 2015 to 2021. We integrated data from the Community Multiscale Air Quality (CMAQ) model with surface air quality measurements, the Weather Research Forecast (WRF) model, the Normalized Difference Vegetation Index (NDVI), and the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Optical Depth (AOD) satellite data. These data, combined with multiple regression analyses, allowed for the correction of PM2.5 estimates, particularly in suburban areas where ground measurements are sparse. The simulated PM2.5 concentration showed strong correlations with observed values R (ranging from 0.88 to 0.94). Spatial distributions of annual PM2.5 showed a significant decrease in PM2.5 concentrations from 2015 to 2021, with some fluctuation due to the COVID-19 pandemic, such as in 2020. The study produced highly accurate daily average high-resolution PM2.5 exposure concentrations.
- Published
- 2024
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