Agra City Air Quality Index forecasting and future prediction using the ARIMA time series model

Author(s)	Mr. Shubham Kumar Shrma, Prof. Dr. Dr. Peer Javaid Ahmad
Country	India
Abstract	Air is one of the most essential parts for life to continue on Earth. Air pollution continuously rises due to weather, traffic, non-renewable energy use, and industrial reasons. These elements have an impact on the well-being and success of all species on Earth, thus it is necessary to regularly assess the state of the air quality in our surroundings. The Air Quality Index (AQI), which measures the quality of the air, is affected by several different factors, including the growth of Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Particulate Matter (PM2.5, and PM10). The present study uses an Autoregressive Integrated Moving Average (ARIMA) model for the forecasting and future prediction of monthly AQI, several individual factors such as the accumulation of NO2, SO2, PM2.5, and PM10 in Agra City. The forecast's low accuracy for the best ARIMA model is evaluated using the following measurements: Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Percentage Error (MPE), and Root Mean Square Error (RMSE). Additionally, the study predicts the AQI in Agra City for the next 15 months using the most suitable ARIMA model.
Keywords	AQI, PH2.5, PH10, NO2, SO2, ARIMA.
Field	Mathematics > Statistics
Published In	Volume 7, Issue 2, March-April 2025
Published On	2025-04-30
DOI	https://doi.org/10.36948/ijfmr.2025.v07i02.43595
Short DOI	https://doi.org/g9g76w

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