Satellite-Based Estimation of Hourly PM2.5 Concentrations Using a Vertical-Humidity Correction Method from Himawari-AOD in Hebei - Qiaolin Zeng; Liangfu Chen; Hao Zhu; Zifeng Wang; Xinhui Wang; Liang Zhang; Tianyu Gu; Guiyan Zhu; Yang Zhang (Sensors, 2018)
Particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) is related to various adverse health effects. Ground measurements can yield highly accurate PM2.5 concentrations but have certain limitations in the discussion of spatial-temporal variations in PM2.5. Satellite remote sensing can obtain continuous and long-term coverage data, and many previous studies have demonstrated the relationship between PM2.5 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 PM2.5 concentrations in Hebei. The hygroscopic growth factor ( f ( RH ) ) was fitted at each site (in a total of 137 matched sites). Meanwhile, assuming that there was little change in f ( RH ) at a certain scale, the nearest f ( RH ) of each pixel was determined to calculate PM2.5 concentrations. Compared to the correlation between AOD and PM2.5, the relationship between the “dry” mass extinction efficiency obtained by vertical-humidity correction and the ground-measured PM2.5 significantly improved, with r coefficient values increasing from 0.19–0.47 to 0.61–0.76. The satellite-estimated hourly PM2.5 concentrations were consistent with the ground-measured PM2.5, 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 PM2.5 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 PM2.5 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.