Antony, Ebin, Lakshmi, Keerthi, Kumar, Sunil, Theeyancheri, Nishanth, Kunnath, Jalaja, Kumar, Satheesh, Sabitha Paul, Annie. (1404). Forecasting the Short-Term Changes of Surface Ozone and NO2 during a Festival Event Using Stochastic and Neural Network Models. , 11(3), 576-592. doi: 10.22059/poll.2025.377011.2387
Ebin Antony; Keerthi Lakshmi; Sunil Kumar; Nishanth Theeyancheri; Jalaja Kunnath; Satheesh Kumar; Annie Sabitha Paul. "Forecasting the Short-Term Changes of Surface Ozone and NO2 during a Festival Event Using Stochastic and Neural Network Models". , 11, 3, 1404, 576-592. doi: 10.22059/poll.2025.377011.2387
Antony, Ebin, Lakshmi, Keerthi, Kumar, Sunil, Theeyancheri, Nishanth, Kunnath, Jalaja, Kumar, Satheesh, Sabitha Paul, Annie. (1404). 'Forecasting the Short-Term Changes of Surface Ozone and NO2 during a Festival Event Using Stochastic and Neural Network Models', , 11(3), pp. 576-592. doi: 10.22059/poll.2025.377011.2387
Antony, Ebin, Lakshmi, Keerthi, Kumar, Sunil, Theeyancheri, Nishanth, Kunnath, Jalaja, Kumar, Satheesh, Sabitha Paul, Annie. Forecasting the Short-Term Changes of Surface Ozone and NO2 during a Festival Event Using Stochastic and Neural Network Models. , 1404; 11(3): 576-592. doi: 10.22059/poll.2025.377011.2387

Forecasting the Short-Term Changes of Surface Ozone and NO2 during a Festival Event Using Stochastic and Neural Network Models

Pollution
دوره 11، شماره 3، پاییز 2025، صفحه 576-592    اصل مقاله (2.56 M)
نوع مقاله: Original Research Paper
شناسه دیجیتال (DOI): 10.22059/poll.2025.377011.2387
نویسندگان
Ebin Antony1؛ Keerthi Lakshmi2؛ Sunil Kumar1؛ Nishanth Theeyancheri* 2؛ Jalaja Kunnath3؛ Satheesh Kumar4؛ Annie Sabitha Paul5
1Department of Information Technology, Kannur University, Kannur, India
2Department of Physics, Sree Krishna College Guruvayur, Kerala, India- 680102
3Department of Applied Science and Humanities, Nehru College of Engineering and Research Centre, Pampady, Thrissur, Kerala-680588
4Department of Atomic and Molecular Physics, Manipal Academy of Higher Education, Karnataka, India- 576104
5Department of Applied Sciences, Govt. Engineering College Kannur, Kerala India-670563
چکیده
Air pollution is one of the most destructive environmental issues on the local, regional, and global level. Its negative influences go far beyond ecosystems and the economy, harming human health and environmental sustainability. By these facts, efficient and accurate modelling and forecasting the concentration of air pollutants are vital. Hence, this work explores investigate the time series components of surface ozone (O3) and its precursor nitrogen dioxide (NO2) and develops a model for predicting O3 variations produced by intense fireworks during the Vishu festival over Kannur. Time series methods using Stochastic and Recurrent Neural Network (RNN) and Seasonal Autoregressive Integrated Moving Average (SARIMA) models are considered the most accurate tools for estimating air pollution trends due to their logical flexibility. Model performance is evaluated based on statistical measurements indicating an increasing trend in O3 concentration of 0.11 ppb/year and NO2 of 0.18 ppb/year. Based on the analysis, we found that the SARIMA model shows better accuracy with a Mean Squared Error (MSE) of 0.55 and a Root Mean Squared Error (RMSE) of 0.74. The broader implications of this study highlight the applicability of advanced time series forecasting techniques for air quality monitoring during short-term pollution events.
کلیدواژه‌ها
Ozone؛ NO2؛ Fire bursting؛ Forecasting؛ ANN؛ SARIMA
مراجع
آمار
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