Prediction of Air Pollution with Polynomial Regression Model

This paper analyzes the future prediction of two pollutants, NO2 and SO2, in the cities of Kolkata and Bangalore, and investigates why the NO2 and SO2 level predictions for Bangalore are much better than those for Kolkata.A Polynomial Regression Model has been employed for this purpose.Four CSV files have been created, containing historical data of NO2 and SO2 for both cities.The Polynomial Regression Model was used for training and testing, with 80% of the data used for training and the remaining 20% for testing.The model was trained on the processed data and evaluated using metrics such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) to assess its performance.Finally, the results were interpreted to understand the patterns and factors influencing NO2 and SO2 pollution levels, and the findings were found to be in very good agreement .