Air quality prediction using remote sensing

Monitoring and protecting air quality has become one of the essential activities for every human in many urban and industrial areas today. The burning of fossil fuels, meteorological factors, traffic factors, and mechanical parameters are the primary sources of air pollutants. Due to the many adverse health effects on a large number of people, PM2.5 is considered as one of the major air pollutants and closely related to the higher range of Air quality index. In this project, the primary product of satellite remote sensing, Aerosol optical depth (AOD) data is used. The aerosol optical depth value is a good indicator of PM2.5 concentration in air. Aerosol optical depth tells us how much direct sunlight gets prevented from reaching the ground by these aerosol particles. From the dataset, AOD data is extracted, and the PM2.5 value calculated. Air quality maps are created for the resultant values, and possible health effects in humans are predicted. Thus this work creates awareness among people about the air quality degradation and its health effects. The proposed system also supports environmentalists, the government, and the pollution control board to frame regulations air quality standards based on issues of toxic air exposure and health-related hazards for human welfare.