Abstract: It is difficult to demonstrate air pollution spatial distribution as it is related to weather conditions, location, topography, and the area. Air pollution is studied by remote sensing techniques less than other techniques due to lack of sensors capable of detecting emissions, and hence, Aerosol Optical Depth (AOD) method is used for investigation. Aerosol optical depth is a measure of the extinction of the solar beam by dust and haze. In this study, the linear regression analysis was used to develop a relationship between AOD measures by MODIS and daily air pollution (CO, O3, NO2, SO2 and PM2.5) in six consecutive years (2011-2016) at 22 stations in Tehran. Matrix correlation between AOD values and air pollution parameters indicated a significant relationship for O3 and NO2 with regression squared from 0.631 to 0.764, respectively. Linear regression between AOD and the parameters was separately developed and pollution maps were produced for CO, O3, NO2 and PM2.5 parameters within 2011-2016. Spatial distribution map of the aforementioned gases revealed that NO2 and CO were higher than the regular standards in the studied region during 2011-2016; PM2.5 was desirable in the northern areas; however, its concentration was larger than the standard level in southern and central regions. Comparison of pollution maps and land surface temperature (LST), picked up by MODIS satellite, indicated that the correlation between PM2.5 and temperature is R = 0.55; in addition, it largely influences higher air pollution increases in Tehran comparing other gases.
Keywords: Air pollution, aerosol optical depth (AOD), MODIS satellite, PM2.5
