Seasonal ARIMA Approach for Forecasting Air Pollution of Chennai City in India

IJEP 43(4): 321-329 : Vol. 43 Issue. 4 (April 2023)

Imran Nadeem and P.S. Sheik Uduman*

B.S. Abdur Rahman Crescent Institute of Science and Technology, Department of Mathematics, Chennai, Tamil Nadu – 600 048, India


Air pollution is one of the hazards posing a severe threat at the global level in recent years. The forecasting of air pollutants is crucial for the implication of a policy that safeguards the environment from further deterioration in a metropolitan city, like Chennai. The study aims to forecast the rising level of air pollutants from the 15 years of monthly data of each pollutant monitored at the commercial and industrial sites of Chennai city. In addition, the study compared the actual air pollutants concentration with the admissible limit as defined by national ambient air quality standards of India for determining the level of pollution at all five stations. This study aims to employ seasonal autoregressive integrated moving average (SARIMA) approach using Box-Jenkins methodology based on the database monitored at the five sites of Chennai city for forecasting the rising level of RSPM, SO2 and NO2. The evaluation of model statistics obtained in our study shows RMSE values lie in the range of 1.52-23.55, MAPE values lie between 6.43-16.73 and R2 values lie between 84-94% for all the 15 best-fitted models by employing SARIMA approach. The forecasting of the three most prevalent pollutants in the main areas of Chennai city is quite beneficial for forming a policy to handle the pollution level in a better way.


Air pollutant, Ljung-box test, Seasonal ARIMA approach, Time series analysis


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