Satellite-Based Estimation of Hourly PM2.5 Concentrations Using a Vertical-Humidity Correction Method from Himawari-AOD in Hebei

Abstract

<b>A</b>bstract: Particulate matter with an aerodynamic diameter less than 2.5 μm (PM_2.5) is related to various adverse health effects. Ground measurements can yield highly accurate PM_2.5 concentrations but have certain limitations in the discussion of spatial-temporal variations in PM_2.5. Satellite remote sensing can obtain continuous and long-term coverage data, and many previous studies have demonstrated the relationship between PM_2.5 and AOD (aerosol optical depth) from theoretical analysis and observation. In this study, a new aerosol product with a high spatial-temporal resolution retrieved from the AHI (the Advance Himawari Imager) was obtained using a vertical-humidity correction method to estimate hourly PM_2.5 concentrations in Hebei. The hygroscopic growth factor (fRH) was fitted at each site (in a total of 137 matched sites). Meanwhile, assuming that there was little change in fRH at a certain scale, the nearest fRH of each pixel was determined to calculate PM_2.5 concentrations. Compared to the correlation between AOD and PM_2.5, the relationship between the "dry" mass extinction efficiency obtained by vertical-humidity correction and the ground-measured PM_2.5 significantly improved, with r coefficient values increasing from 0.19⁻0.47 to 0.61⁻0.76. The satellite-estimated hourly PM_2.5 concentrations were consistent with the ground-measured PM_2.5, with a high r (0.8 ± 0.07) and a low RMSE (root mean square error, 30.4 ± 5.5 μg/m³) values, and the accuracy in the afternoon (13:00⁻16:00) was higher than that in the morning (09:00⁻12:00). Meanwhile, in a comparison of the daily average PM_2.5 concentrations of 11 sites from different cities, the r values were approximately 0.91 ± 0.03, and the RMSEs were between 13.94 and 31.44 μg/m³. Lastly, pollution processes were analyzed, and the analysis indicated that the high spatial-temporal resolution of the PM_2.5 data could continuously and intuitively reflect the characteristics of regional pollutants (such as diffusion and accumulation), which is of great significance for the assessment of regional air quality.