Abstract
Based on multiple linear regression (MLR) models, we estimated the PM2.5 at Seoul using a number of aerosol optical depth (AOD) values obtained from ground-based and satellite remote sensing observations. To construct the MLR model, we consider various parameters related to the ambient meteorology and air quality. In general, all AOD values resulted in the high quality of PM2.5 estimation through the MLR method: mostly correlation coefficients >~0.8. Among various polar-orbit satellite AODs, AOD values from the MODIS measurement contribute to better PM2.5 estimation. We also found that the quality of estimated PM2.5 shows some seasonal variation; the estimated PM2.5 values consistently have the highest correlation with in situ PM2.5 in autumn, but are not well established in winter, probably due to the difficulty of AOD retrieval in the winter condition. MLR modeling using spectral AOD values from the ground-based measurements revealed that the accuracy of PM2.5 estimation does not depend on the selected wavelength. Although all AOD values used in this study resulted in a reasonable accuracy range of PM2.5 estimation, our analyses of the difference in estimated PM2.5 reveal the importance of utilizing the proper AOD for the best quality of PM2.5 estimation.
Highlights
The negative effects of fine mode particles on human health have been significantly examined, and are more serious at the present time
For the Model 1 (M1) and Model 2 (M2) models, the performance of PM2.5 estimation seems largely dependent on the used aerosol optical depth (AOD); the cases of Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging Spectroradiometer (MISR) AOD show higher correlation and lower root mean square error (RMSE), but those of VIIRS and Ozone Monitoring Instrument (OMI) AOD show lower correlation and higher RMSE
Comparison between Model 3 (M3)-1 and M3-2 indicates that M3-1 can estimate PM2.5 slightly better, implying that the ground-based measurement of Planetary boundary layer height (PBLH) can better represent the local conditions of aerosol distribution
Summary
The negative effects of fine mode particles on human health have been significantly examined, and are more serious at the present time. In addition to the threat to the well-known respiratory and cardiovascular problems, people are currently concerned about the damage to mental health due to the high concentration of aerosols and even precursor gases [1]. This effect has usually been inspected based on the mass density of particulate matter (PM), especially PM having an aerodynamic diameter
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