An Improved Method for Monitoring Fine Particulate Matter Mass Concentrations via Satellite Remote Sensing
Author(s) -
Hamed Karimian,
Qi Li,
Chengcai Li,
Lingyan Jin,
Junxiang Fan,
Ying Li
Publication year - 2015
Publication title -
aerosol and air quality research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.866
H-Index - 55
eISSN - 2071-1409
pISSN - 1680-8584
DOI - 10.4209/aaqr.2015.06.0424
Subject(s) - aerosol , environmental science , satellite , particulates , beijing , relative humidity , correlation coefficient , remote sensing , mass concentration (chemistry) , meteorology , humidity , atmospheric sciences , pollution , chemistry , geography , geology , statistics , mathematics , physics , ecology , organic chemistry , archaeology , astronomy , china , biology
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-PM_(2.5) 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 PM_(2.5) 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.
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