Mapping nighttime PM2.5 from VIIRS DNB using a linear mixed-effect model. (April 2018) - Fu, D.; Xia, X.; Duan, M.; Zhang, X.; Li, X.; Wang, J.; Liu, J.
Abstract: Estimation of particulate matter with aerodynamic diameter less than 2.5 μm (PM2.5 ) from daytime satellite aerosol products is widely reported in the literature; however, remote sensing of nighttime surface PM2.5 from space is very limited. PM2.5 shows a distinct diurnal cycle and PM2.5 concentration at 1:00 local standard time (LST) has a linear correlation coefficient (R) of 0.80 with daily-mean PM2.5 . Therefore, estimation of nighttime PM2.5 is required toward an improved understanding of temporal variation of PM2.5 and its effects on air quality. Using data from the Day/Night Band (DNB) of the Visible Infrared Imaging Radiometer Suite (VIIRS) and hourly PM2.5 data at 35 stations in Beijing, a mixed-effect model is developed here to estimate nighttime PM2.5 from nighttime light radiance measurements based on the assumption that the DNB-PM2.5 relationship is constant spatially but varies temporally. Cross-validation showed that the model developed using all stations predict daily PM2.5 with mean determination coefficient (R 2 ) of 0.87 ± 0.12, 0.83 ± 0.10, 0.87 ± 0.09, 0.83 ± 0.10 in spring, summer, autumn and winter. Further analysis showed that the best model performance was achieved in urban stations with average cross-validation R 2 of 0.92. In rural stations, DNB light signal is weak and was likely smeared by lunar illuminance that resulted in relatively poor estimation of PM2.5 . The fixed and random parameters of the mixed-effect model in urban stations differed from those in suburban stations, which indicated that the assumption of the mixed-effect model should be carefully evaluated when used at a regional scale. Highlights: A novel method is established to estimate nighttime PM2.5 from VIIRS DNB data. Nighttime PM2.5 is estimated with determination coefficient of exceeding 0.8. Potentials and limitations of this method are discussed.