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Article

Modelling the Interaction between Air Pollutant Emissions and Their Key Sources in Poland

1
Institute of Environmental Engineering and Biotechnology, Faculty of Natural Sciences and Technology, University of Opole, Kominka 6, 46-020 Opole, Poland
2
Department of Dairy and Process Engineering, Poznań University of Life Sciences, Wojska Polskiego 31, 60-624 Poznań, Poland
3
Department of Biosystems Engineering, Poznań University of Life Sciences, Wojska Polskiego 50, 60-627 Poznań, Poland
*
Author to whom correspondence should be addressed.
Academic Editor: Attilio Converti
Energies 2021, 14(21), 6891; https://doi.org/10.3390/en14216891
Received: 4 September 2021 / Revised: 8 October 2021 / Accepted: 18 October 2021 / Published: 20 October 2021
(This article belongs to the Special Issue Feature Papers in Energy, Environment and Well-Being)
The main purpose of this study is to investigate the relationships between key sources of air pollutant emissions (sources of energy production, factories which are particularly harmful to the environment, the fleets of cars, environmental protection expenditure) and the main environmental air pollution (SO2, NOx, CO and PM) in Poland. Models based on MLP neural networks were used as predictive models. Global sensitivity analysis was used to demonstrate the significant impact of individual network input variables on the output variable. To verify the effectiveness of the models created, the actual data were compared with the data obtained through modelling. Projected courses of changes in the variables under study correspond with the real data, which confirms that the proposed models generalize acquired knowledge well. The high MLP network quality parameters of 0.99–0.85 indicate that the network generalizes the acquired knowledge accurately. The sensitivity analysis for NOx, CO and PM pollutants indicates the significance of all input variables. For SO2, it showed significance for four of the six variables analysed. The predictions made by the neural models are not very different from the experimental values. View Full-Text
Keywords: air pollution; fuel combustion; hard coal; energy industry; transportation; emissions; modelling; neural networks; MLP air pollution; fuel combustion; hard coal; energy industry; transportation; emissions; modelling; neural networks; MLP
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MDPI and ACS Style

Kolasa-Więcek, A.; Suszanowicz, D.; Pilarska, A.A.; Pilarski, K. Modelling the Interaction between Air Pollutant Emissions and Their Key Sources in Poland. Energies 2021, 14, 6891. https://doi.org/10.3390/en14216891

AMA Style

Kolasa-Więcek A, Suszanowicz D, Pilarska AA, Pilarski K. Modelling the Interaction between Air Pollutant Emissions and Their Key Sources in Poland. Energies. 2021; 14(21):6891. https://doi.org/10.3390/en14216891

Chicago/Turabian Style

Kolasa-Więcek, Alicja, Dariusz Suszanowicz, Agnieszka A. Pilarska, and Krzysztof Pilarski. 2021. "Modelling the Interaction between Air Pollutant Emissions and Their Key Sources in Poland" Energies 14, no. 21: 6891. https://doi.org/10.3390/en14216891

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