Modeling of Ambient Air Pollutants through Artificial Neural Network in Industrial Area of Ujjain City

The aim of this study was modeling of ambient air pollutants through ANN, in industrial area of Ujjain city in India and the study was carried out on modeling of air pollutants like Sox, Nox, SPM and RSPM using Artificial Neural Network. The ANN system was run by giving the inputs of meteorological data’s and giving the outputs of concentration of various pollutants and accordingly the estimation of Errors was done by this study. The monthly data’s in year from 2006 -2012 of meteorological data like Temperature, Humidity, wind pressure and rainfall and the pollutants concentration were collected from the State Pollution Control Board. The ANN system used as shown in figure 1 analyses all these data’s and find the error coming during the experiment. The study estimated the Mean Square Error (MSE) from the inputs and outputs which were given to ANN in the industrial area of Ujjain City in India was found satisfactory being in the range of 0.01-0.03. The results shown here indicate that the neural network techniques can be useful tool in the hands of practitioners of air quality management and prediction. The models studied in this study are easily implemented, and they can deliver prediction in real time, unlike other modeling techniques.