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1 PG Student Civil Engg Dept. BMSCE, Bengaluru, India 2 Professor Civil Dept. BMSCE, Bengaluru, India 3 Phd Student Civil Engg Dept. BMSC, Bengaluru, India AbstractThe statistical models are used in the prediction of air pollution parameter by using different models. The Autoregressive Integrated Moving Average (ARIMA) model is used in the analysis of SO2 NO2 and PM10. The collected data is to be maintained in chronological order. The daignostic check of the model is carried out by using ACF and PCF values. Based on the ACF and PCF values the order of the model is identified, which give the best fitting model for that particular air pollution parameter. The SO2 showing the decreasing pattern with time and is much more within the permissible limit. The NO2 not showing any much more variation but is within the permissible limit. The PM10 is initially high and has value more than the permissible value with showing increasing in its trend. KeyWords-Autoregressive Integrated Moving Average, Autocorrelation Function, Partial Autocorrelation Function.

FORECASTING OF AMBIENT AIR QUALITY FOR VICTTORIYA HOSPITAL AREA BENGALURU