Hamed Karimian1, Qi Li1, Chengcai Li2*, Lingyan Jin1, Junxiang Fan1, Ying Li3
1) Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China
2) Department of Atmospheric and Oceanic Sciences, School of Physics, Peking University, Beijing, 100871, China
3) Division of Environment, the Hong Kong University of Science and Technology, Hong Kong, China
Correspondence to: Chengcai LI (ccli@pku.edu.cn)
Abstract
Ground level monitoring of Particulate Matter (PM) is limited by spatial coverage and resolution, in spite of possessing high temporal resolution and accuracy. Atmospheric Aerosol Optical Depth (AOD), a product of space-borne remote sensing, has shown significant potential for estimating ground level PM concentrations. Several approaches have been used to improve the correlation between AOD-PM by providing corrections for the aerosol vertical profile and ground level humidity. However, the effects of the vertical profile of humidity and aerosol size on the AOD-PM relationship requires further study. In this paper, we propose a method for developing an AOD-PM2.5 relationship by retrieving the vertical profile of relative humidity via ground observation data and aerosol size distribution in Beijing. Moreover, a series of Hanel growth coefficients (γ) are applied to determine the specific value, which maximizes the correlation. The results show that applying our proposed method can improve the correlation from R = 0.610 to R = 0.707 for Terra and R = 0.707 to 0.752 for Aqua. The best correlations were obtained for γ = 1.2 and 1.3 for Terra and Aqua, respectively. A good correlation (R = 0.8) between ground based and MODIS based PM2.5 measurements, together with employing MODIS to predict true air pollution levels (65% accuracy), suggests that the vertical profile of RH derived via ground level observation and aerosol size should be considered and applied to models in future studies, which utilize satellite data for air pollution monitoring and controlling.
Citation: Hamed Karimian, Qi Li, Chengcai Li, Lingyan Jin, Junxiang Fan, Ying Li, 2016: An Improved Method for Monitoring Fine Particulate Matter Mass Concentrations via Satellite Remote Sensing. Aerosol and Air Quality Research, doi: 10.4209/aaqr.2015.06.0424
Download at http://aaqr.org/VOL16_No4_April2016/14_AAQR-15-06-OA-0424_1081-1092.pdf
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