Assessment of MODIS Data in Monitoring the Concentrations of PM2.5 and PM10 Pollutants with Emphasis on Meteorological Variables

Document Type : Research Paper


1 , Irrigation Engineering Department, Faculty of Agricultural Engineering and Technology, University College of Agriculture and Natural Resources, University of Tehran,

2 Assistant Prof., Irrigation & Reclamation Engrg. Dept. University of Tehran Karaj, Iran.

3 Assistant professor, Department of Water Engineering, Faculty of Agriculture, Urmia University, Urmia, Iran


In this study, the function of the MODIS (Moderate Resolution Imaging Spectroradiometer) sensor to estimate the concentration of PM2.5 and PM10 pollutants in Tehran was assessed by using the data obtained from this sensor. In this study, linear and non-linear models for estimating the concentration of aerosols were presented in six meteorological and ground pollution monitoring stations in Tehran province. The results of the models were compared to the ground station observations by using statistical tests and the most appropriate model was elected from the regressions. The developed model (based on aerosol optical depth which was extracted from MOD04-L2 products of TERRA satellite MODIS sensor), 24-hour precipitation, average water vapor pressure, and sunshine) showed high accuracy, very low RMSE, and rather high R2 in Tehran province (R2 = 0.75 and RMSE= 7.47 ug / m3) and stations. In this model, PM2.5 concentration and sunshine hours have a negative correlation, also the positive relationship to other variables is observed. The results demonstrated that utilizing meteorological variables and attention to the prevailing atmospheric phenomena enhance the performance of MODIS sensor data in estimating PM2.5 pollutant concentration. Undesirable as MODIS sensor data might be in terms of certainty and accuracy, they are undoubtedly beneficial considering elimination defect of ground-based pollution monitoring stations in estimating aerosols concentration and complement each other suitably.


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