Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Energy and climate issues are an essential part of the sustainable development process of the EU countries. They are also one of the primary objectives of international policy, as evidenced by their inclusion in Agenda 2030, adopted by the UN in 2015 among the Sustainable Development Goals. The implementation of these goals is also taking place in the EU countries. Although climate protection and energy transition activities have been undertaken in the EU for years, individual countries significantly vary in this regard. The aim of the research, the results of which are presented in this paper, was to analyze similarities between the EU countries in terms of sustainable energy and climate development. The analysis was conducted for all EU countries, based on 14 indicators characterizing energy and climate sustainability, in energy, climate, social and economic dimensions. Kohonen’s artificial neural networks were used for analysis. The research was conducted for data from the period between 2009-2018. The results showed that in the studied period (10 years), significant differences were found between the EU countries. A high level of energy and climate development was reported for Sweden, Denmark, Austria and France, among other states, and a low level for e.g., the Czech Republic, Poland and Bulgaria.
Wydawca
Rocznik
Tom
Strony
86--96
Opis fizyczny
Bibliogr. 15 poz., fig., tab.
Twórcy
autor
- Silesian University of Technology, Poland
Bibliografia
- 1. A European Green Deal (2019) [online]. Available at: https://ec.europa.eu/info/strategy/priorities-2019-2024/european-green-deal_en (accessed on 11 January 2021).
- 2. Brodny, J. and Tutak, M. (2019). Analysis of the diversity in emissions of selected gaseous and particulate pollutants in the European Union countries. Journal of Environmental Management, 231, pp. 582-595.
- 3. Brodny, J. and Tutak, M. (2020a). Analyzing Similarities between the European Union Countries in Terms of the Structure and Volume of Energy Production from Renewable Energy Sources. Energies, 13, 913.
- 4. Brodny J. and Tutak M. (2020b). 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, 13, 1925.
- 5. Brodny J., Tutak M., Saki S.A. (2020). Forecasting the Structure of Energy Production from Renewable Energy Sources and Biofuels in Poland. Energies 13, 2539.
- 6. Eurostat [online]. Available at: https://ec.europa.eu/eurostat/web/main/data/statistics-a-z/abc (accessed on 15 May 2021).
- 7. Kohonen T. (1990). The self-organizing map. Proc. IEEE, 78, pp. 1464-1480.
- 8. Im H. and Kim Y. (2020). The Electrification of Cooking Methods in Korea – Impact on Energy Use and Greenhouse Gas Emissions. Energies, 13, 680.
- 9. Markovska N. and Taseska V. (2009). Pop-Jordanov, J. SWOT analyses of the national energy sector for sustainable energy development. Energy, 34, pp. 752-756.
- 10. Muczyński A. (2009). Grupowanie nieruchomości wspólnot mieszkaniowych z wykorzystaniem sieci Kohonena. Acta Sci. Pol., Administratio Locorum, 8(4), pp. 5-15.
- 11. Treaty of Lisbon Amending the Treaty on European Union and the Treaty Establishing the European Community (2007) [online]. Available at: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:12007L/TXT (accessed on 11 January 2021).
- 12. Tutak M., Brodny J., Siwiec D., Ulewicz R., Bindzár P. (2020). Studying the Level of Sustainable Energy Development of the European Union Countries and Their Similarity Based on the Economic and Demographic Potential. Energies 13, 6643.
- 13. Tutak M., Brodny J., Bindzár, P. (2021) Assessing the Level of Energy and Climate Sustainability in the European Union Countries in the Context of the European Green Deal Strategy and Agenda 2030. Energies 14, 1767.
- 14. United Nations. General Assembly Transforming Our World: The 2030 Agenda for Sustainable Development. New York. (2015) [online]. Available at: https://sdgs.un.org/2030agenda (accessed on 15 March 2021).
- 15. Zhou Q., Wang Y., Jiang P., Shao X., Choi S.K., Hu J., Cao L., Meng X. (2017). An active learning radial basis function modeling method based on self-organization maps for simulation-based design problems. Knowl.-Based Syst., 131, pp. 10-27.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-7fef502b-75d8-44bd-9159-3259279e4349