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The Use of Artificial Neural Networks to Analyze Greenhouse Gas and Air Pollutant Emissions from the Mining and Quarrying Sector in the European Union

Author

Listed:
  • Jarosław Brodny

    (Faculty of Organization and Management, Silesian University of Technology, 44-100 Gliwice, Poland)

  • Magdalena Tutak

    (Faculty of Mining, Safety Engineering and Industrial Automation, Silesian University of Technology, 44-100 Gliwice, Poland)

Abstract

The European Union (EU) is considered one of the most economically developed regions worldwide. It was driven by the mining industry for several decades. Despite certain changes in this area, a number of mineral and energy resources are still being mined in the EU. Nevertheless, mining activities are accompanied by many unfavorable phenomena, especially for the environment, such as greenhouse gas and air pollutant emissions. The great diversity of the EU countries in terms of the size of the “mining and quarrying” sector means that both the volume and structure of these emissions in individual countries varies. In order to assess the current state of affairs, research was conducted to look at the structure and volume of these emissions in individual EU countries. The aim of the study was to divide these countries into homogenous groups by structure and volume of studied emissions. In order to reflect both the specificity and diversity of the EU countries, this division was based on the seven most important gases (CO 2 , CH 4 , N 2 O, NH 3 , NMVOC, CO, NO x ) and two types of particulate matter (PM 2.5, PM 10) emitted into the atmosphere from the sector in question. The volume of studied emissions was also compared to the number of inhabitants of each EU country and the gross value added (GVA) by the mining and quarrying sector. This approach enabled a new and broader view on the issue of gas and air pollutant emissions associated with mining activities. The artificial Kohonen’s neural networks were used for the analysis. The developed method, the analyses and the results constitute a new approach to studying such emissions in the EU. Research that looks only at the emission of harmful substances into the environment in relation to their absolute values fail to fully reflect the complexity of this problem in individual EU countries. The presented approach and the results should broaden the knowledge in the field of harmful substance emissions from the mining and quarrying sector, which should be utilized in the process of implementing the new European climate strategy referred to as “The European Green Deal”.

Suggested Citation

  • Jarosław Brodny & Magdalena Tutak, 2020. "The Use of Artificial Neural Networks to Analyze Greenhouse Gas and Air Pollutant Emissions from the Mining and Quarrying Sector in the European Union," Energies, MDPI, vol. 13(8), pages 1-31, April.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:8:p:1925-:d:345456
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    References listed on IDEAS

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    2. Davidescu, Adriana AnaMaria & Popovici, Oana Cristina & Strat, Vasile Alecsandru, 2022. "Estimating the impact of green ESIF in Romania using input-output model," International Review of Financial Analysis, Elsevier, vol. 84(C).
    3. Vitor Joao Pereira Domingues MARTINHO, 2023. "Energy Crops: Assessments In The European Union Agricultural Regions Through Machine Learning Approaches," Regional Science Inquiry, Hellenic Association of Regional Scientists, vol. 0(1), pages 29-42, June.
    4. Adiqa Kausar Kiani & Wasim Ullah Khan & Muhammad Asif Zahoor Raja & Yigang He & Zulqurnain Sabir & Muhammad Shoaib, 2021. "Intelligent Backpropagation Networks with Bayesian Regularization for Mathematical Models of Environmental Economic Systems," Sustainability, MDPI, vol. 13(17), pages 1-19, August.
    5. Sergey Zhironkin & Elena Dotsenko, 2023. "Review of Transition from Mining 4.0 to 5.0 in Fossil Energy Sources Production," Energies, MDPI, vol. 16(15), pages 1-35, August.
    6. Huaiting Luo & Wei Zhou & Izhar Mithal Jiskani & Zhiming Wang, 2021. "Analyzing Characteristics of Particulate Matter Pollution in Open-Pit Coal Mines: Implications for Green Mining," Energies, MDPI, vol. 14(9), pages 1-19, May.
    7. Olga Zhironkina & Sergey Zhironkin, 2023. "Technological and Intellectual Transition to Mining 4.0: A Review," Energies, MDPI, vol. 16(3), pages 1-37, February.

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