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Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland
Authors:Alicja Kolasa-Wiecek
Institution:Department of Economics and Regional Research, Faculty of Economy and Management, Opole University of Technology, Wary(n)skiego 4,45-047 Opole, Poland
Abstract:The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO2 emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH4 emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (− 0.64) as the most important variables. The adjusted coefficient is suitable and equals R2 = 0.90. For N2O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N2O emission is the peat and wood fuel consumption.
Keywords:Greenhouse gases  Burning of fossil fuels  Energy sector  Backward stepwise regression modeling
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