Relationship of MISR component AODs with black carbon and other ground monitored particulate matter composition
2015
Zeeshan, Muhammad | Nguyễn, Thị Kim Oanh
This study assessed the relationship between the satellite Aerosol Optical Depths (AODs) and the ground monitored concentrations of particulate matter (PM) mass and its major constituents (black carbon–BC, organic carbon–OC, sulfates and nitrates), respectively. Both component AOD and total AOD products of Multi–angel Imaging Spectro Radiometer (MISR) were used for comparison along with the AOD product of the Moderate Resolution Imaging Spectroradiometer (MODIS). The ground PM data available during the period from 2004 to 2010 at the Asian Institute of Technology (AIT), a suburb site of the Bangkok Metropolitan Region, was used. MODIS and MISR AODs were validated against Sun photometer AOD, monitored at the Pimai AERONET station which showed strong linear regression with high R2 values of 0.87 and 0.92, respectively. The correlation coefficients between MODIS and MISR AODs and PM mass concentrations, respectively, were improved after exclusion of observations with cloud cover above 3/10. The R values (square root of determination coefficient R2) for linear relationships between PM10 and MODIS AOD were accordingly increased from 0.33 to 0.58 for MODIS AOD and from 0.25 to 0.54 for MISR AOD, while those for PM2.5 were improved from 0.30 to 0.55 for MODIS AOD and from 0.31 to 0.43 for MISR AOD. The stepwise regression was conducted to analyze the relationship between MISR component AODs and the mass concentration of PM10 and PM2.5, respectively, as well as their constituents. Higher R values were obtained for all regression equations using MISR component AODs as compared to those using total AOD. MISR component AODs showed higher capacity for monitoring daily BC (R=0.74–0.75) and sulfates (R=0.72), as compared to nitrates (R=0.52–0.54) and hourly OC (R=0.47). The potential of MISR component AODs for ambient PM monitoring should be explored and applied in other regions.
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