Forecasting Air Pollution based on Monitoring Station with using Kalman Filter

In recent years, due to the dramatic increase of air pollutants preparation of right air pollution maps and the development of instantaneous air pollution monitoring systems attention of researchers has attracted. According to the data obtained from air pollution monitoring stations, they were not isolated from the error and some of their observations are missing; therefore, it is necessary to use a robust model to refine the data and predict the observations. In the present study, the data’s of three stations in Tehran of air pollutants corrected and predicted by Kalman filter. Results showed that an average accuracy of 92% for the Kalman filter.