Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Analysis of greenhouse gas emissions in the European Union member states with the use of an agglomeration algorithm

Treść / Zawartość
Warianty tytułu
Języki publikacji
The use of fossil fuels as sources of energy is related to the emission of pollutants into the atmosphere. The implementation of international commitments on reducing emissions requires their continuous monitoring. The main energy resources for electricity production in the world include fossil fuels, i.e. oil, coal and natural gas, and according to projections their dominant role in the market of energy resources will persist for at least the next two decades. The aim of this article is to analyse the level of differentiation of European Union member states in terms of emissions of four greenhouse gases and to identify groups of similar countries based on these criteria. Such studies will provide information that will enrich our knowledge about the contribution of each European Union country to the emissions of greenhouse gases. This article uses a taxonomic method - cluster analysis, namely the agglomerative algorithm, which enables the extraction of objects that are similar to each other from the data and then to merge them into groups. In this way, a number of homogeneous subsets can be obtained from one heterogeneous set of objects. European Union countries make up the objects of segmentation. Each of them are described by their level of greenhouse gas emissions, such as carbon dioxide, methane, nitrogen oxides and nitrous oxides. Groups of homogeneous countries are distinguished due to total emissions and due to the level of their emissions per capita. Analysis is based on annual Eurostat reports concerning greenhouse gas emissions.
Opis fizyczny
Bibliogr. 46 poz.
  • The Silesian University of Technology, Faculty of Mining and Geology, 44-100 Gliwice, ul. Akademicka 2, Poland
  • The Silesian University of Technology, Faculty of Mining and Geology, 44-100 Gliwice, ul. Akademicka 2, Poland
  • Bluszcz, A. (2016). Classification of the European Union member states according to the relative level of sustainable development. Quality & Quantity, 50(6), 2591-2605.
  • Bluszcz, A., & Kijewska, A. (2015). Challenges of sustainable development in the mining and metallurgy sector in Poland. Metallurgy, 54(2), 441-444.
  • CDIAC. (2016). Carbon dioxide information analysis center, Oak ridge national laboratory. Oak Ridge, Tenn., United States: US Department of Energy. Retrieved September 20, 2016 from
  • Ciepiela, D. (2011). Rynek, energia i klimat [Market energy and climate]. Nowy Przemysł, (5). Retrieved May 15, 2015 from,-7073_1_0_0_0_2.html.
  • Climate Policy of Poland. (2003). Strategies to reduce greenhouse gas emissions in Poland by 2020.Warsaw: The Ministry of the Environment. Retrieved March 20, 2015 from
  • Clinton, D., Button, E., Norring, C., & Palmer, R. (2004). Cluster analysis of key diagnostic variables from two independent samples of eating-disorder patients: Evidence for a consistent pattern. Psychological Medicine, 34, 1035-1045.
  • Dubiński, J., & Turek, M. (2014). Chances and threats of hard coal mining development in Poland - the results of experts research. Archives of Mining Science, 59(2), 395-411.
  • EC (2013). European Commission. EU Energy, Transport and GHG Emissions. Trends to 2050. Reference scenario 2013. Publication Office of the European Commission 2013. Retrieved March 20, 2015 from
  • EEA (2016). European Environment Agency, Retrieved January 27, 2017 from
  • Eurostat (2016) The source data for GHG emissions. Retrieved October 10, 2016 from
  • Figura, J. (2013). Taksonomia w polityce logistycznej państwa [Taxonomy in logistic State policy]. Katowice: Wydawnictwo Uniwersytetu Ekonomicznego w Katowicach.
  • Girão, P. S., Postolache, O., & Pereira, J. M. D. (2009). Data fusion, decision-making, and risk analysis: Mathematical tools and techniques. In F. Pavese, & A. B. Forbes (Eds.), Data, modeling for metrology and testing in measurement science (pp. 1-50). Boston: Birkhäuser.
  • Giudici, P. (2003). Applied data mining. Statistical methods for business and industry. West Susex: John Wiley & Sons.
  • Idso, C. D., Carter, R. M., Singer, S. F., & Soon, W. (2013). Scientific critique of IPCC's, summary for policymakers. Center for the study of carbon dioxide and global change. The Heartland Institute, Science and Environmental Policy Project. Retrieved March 20, 2015 fromóf_ipccśpm.pdf.
  • IEA (2016). International Energy Agency. CO2 Emissions from Fuel Combustion 2016 Edition. Retrieved September 20, 2016 from
  • Jonek-Kowalska, I. (2014). Risk management in the hard coal mining industry: Social and environmental aspects of colliers' liquidation. Resources Policy, 41, 124-134.
  • Jonek-Kowalska, I. (2015). Challenges for long-term industry restructuring in the Upper Silesian Basin. What has polish coal mining achieved and failed from a twenty-year perspective? Resources Policy, 44, 135-149.
  • Karbownik, A., & Stachowicz, J. (1994). Social aspects of restructuring hard coal mining in Poland. Resources Policy, 20(3), 198-201.
  • Karbownik, A., Turek, M., & Pawełczyk, E. (2001). Efekty realizacji rządowego programu reformy górnictwa węgla kamiennego w latach 1998-2001 [The effects of implementation of the government program of reform of coal mining in 1998-2001]. In J. Pyka (Ed.), Globalne i regionalne uwarunkowania nowoczesności przemysłu i usług [Global and regional conditions of modern industry and services]. Katowice: Wyd. Akademii Ekonomicznej im. Karola Adamieckiego.
  • Kijewska, A., & Bluszcz, A. (2016). Research of varying levels of greenhouse gas emissions in European countries using the k-means method. Atmospheric Pollution Research, 7(5), 935-944.
  • Kolasa-Więcek, A. (2013). The use of cluster analysis in the classification of similarities in variables associated with agricultural greenhouse gases emissions in OECD counties. Wieś i Rolnictwo, 1(158), 59-66.
  • Korban, Z., & Manowska, A. (2011). Wykorzystanie ciągów czasowych w procesie szacowania poziomu emisji dwutlenku węgla [The use of timesequences in the proces of estimating carbon dioxide emissions]. Mining and Geology, 6(4), 39-48.
  • Korski, J., Tobór-Osadnik, K., & Wyganowska, M. (2015). Perfect model of mining equipment user requirement by C. Conley. Management Systems in Production Engineering, 18(2), 94-97.
  • Korski, J., Tobór-Osadnik, K., & Wyganowska, M. (2016). Reasons of problems of the Polish hard coal mining in connection with restructuring changes in the period 1988-2014. Resources Policy, 48, 25-31.
  • Krause, E., Krzemień, A., & Smoliński, A. (2015). Analysis of assessment of a critical event during an underground coal gasification experiment. Journal of Loss Prevention in the Process Industries, 33, 173-182.
  • Krzemień, A., Więckol-Ryk, A., Duda, A., & Koteras, A. (2013). Risk assessment of a post - combustion and amine - based CO2 capture ready process. Journal of Sustainable Mining, 12(4), 18-23.
  • Laing, T., Sato, M., Grubb, & M., Comberti, C. (2013). Assessing the effectiveness of the EU Emissions Trading System. Centre for Climate Change Economics and Policy Working Paper No. 126 Grantham Research Institute on Climate Change and the Environment Working Paper No. 106. Retrieved January 27, 2017 from
  • Larose, D. T. (2005). Discovering knowledge in data. Introduction to data mining. Hoboken, New Jersey: John Wiley & Sons, Inc.
  • Lorek, E. (2011). Efektywność europejskiego i międzynarodowego systemu handlu emisjami jako instrumentu zrównoważonej gospodarki energetycznej [The effectiveness of European and international emissions trading system as an instrument for sustainable energy]. Przegląd Górniczy, 67(9), 103-106.
  • Lutyński, M. (2014). Impact of preparation and storage of activated carbon on the high pressure sorption of CO2. Bulletin of the Polish Academy of Sciences Technical Sciences, 62(1), 113-119, 10.2478/bpasts-2014-0013.
  • Lutyński, M., Sakiewicz, P., & Gonzalez, M. A. (2014). Halloysite as mineral adsorbent of CO2 - kinetics and adsorption capacity. Journal of the Polish Mineral Engineering Society, 15(1), 111-117.
  • Mikut, G. (2009). Zastosowanie technik analizy skupień i drzew decyzyjnych do segmentacji rynku [Application of cluster analysis and decision trees for segmentation of the market]. StatSoft Poland, 75-92. Retrieved March 20, 2015 from
  • Mooi, E., & Sarstedt, M. (2011). A concise guide to market research. Berlin-Heidelberg: Springer-Verlag.
  • Morzy, T. (2013). Eksploracja danych. Metody i algorytmy [Exploration of data. Methods and Algorithms]. Warszawa: PWN.
  • Pachauri, R. K., & Meyer, L. A. (2014). Climate Change 2014. Synthesis Report. Retrieved March 20, 2015 from
  • Punj, G., & Stewart, D.W. (1983). Cluster analysis in marketing research: Review and suggestions for application. Journal of Marketing Research, 20(2), 134-148.
  • Ranosz, R. (2008). Organization and trade on CO2 emission allowances market. Polityka Energetyczna - Energy Policy Journal, 11(2), 85-95.
  • Rao, C. R., Miller, J. P., & Rao, D. C. (Eds.). (2008). Handbook of Statistics: Epidemiology and medical statistics. North-holland. Elsevier.
  • Stanisz, A. (2007). Przystępny kurs statystyki z zastosowaniem STATISTICA PL na przykładach z medycyny. T. 3 Analizy wielowymiarowe [Accessible statistics course using STATISTICA PL with examples from medicine. Vol. 3. Multivariate Analyses]. Krakow: StatSoft.
  • Stańczyk, K., Dubiński, J., Cybulski, K., Wiatowski, M., Świądrowski, J., Kapusta, K., et al. (2010b). Underground coal gasification - international experiments and experiments in Barbara mine. Energy Policy, 13(2), 423-433.
  • Stańczyk, K., Kapusta, K., Wiatowski, M., Świądrowski, J., Smoliński, A., & Rogut, J. (2012). Experimental simulation of hard coal underground gasification for hydrogen production. Fuel, 91(1), 40-50.
  • Stańczyk, K., Smoliński, A., Kapusta, K., Wiatowski, M., Świądrowski, J., Kotyrba, A., et al. (2010a). Dynamic experimental simulation of hydrogen oriented underground gasification of lignite. Fuel, 89(11), 3307-3314.
  • Tan, P.-N., Steinbach, M., & Kumar, V. (2005). Introduction to data mining. Boston: Addison-Wesley. UNFCCC. (2008). Kyoto Protocol reference manual. On accounting of emissions and assigned amount. United Nations Framework Convention on Climate Change. Retrieved January 27, 2017 from
  • Wagner, R., Scholz, S. W., & Decker, R. (2005). The number of clusters in market segmentation. In D. Baier, R. Decker, & L. Schmidt-Thieme (Eds.), Data analysis and decision support (pp. 157-176). Heidelberg: Springer.
  • Wiatowski, M., Stańczyk, K., Świądrowski, J., Kapusta, K., Cybulski, K., Krause, E., et al. (2012). Semi-technical underground coal gasification (UCG) using the shaft method in experimental Barbara mine. Fuel, 99, 170-179.
  • Xia, X. H., Huang, G. T., Chen, G. Q., Zhang, Bo, Chen, Z. M., & Yang, Q. (2011). Energy security, efficiency and carbon emission of Chinese industry. Energy Policy, 39, 3520-3528.
Typ dokumentu
Identyfikator YADDA
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.