Satellite-Based Estimation of Hourly PM(2.5) Concentrations Using a Vertical-Humidity Correction Method from Himawari-AOD in Hebei - Zeng, Qiaolin (Sensors (Basel), 2018)
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 ([Formula: see text]) was fitted at each site (in a total of 137 matched sites). Meanwhile, assuming that there was little change in [Formula: see text] at a certain scale, the nearest [Formula: see text] 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/m(3)) 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/m(3). 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.