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Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland 被引量:4
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作者 Alicja Kolasa-Wiecek 《Journal of Environmental Sciences》 SCIE EI CAS CSCD 2015年第4期47-54,共8页
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 activ... 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 N2 O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N2 O emission is the peat and wood fuel consumption. 展开更多
关键词 Greenhouse gases Burning of fossil fuels Energy sector Backward stepwise regression modeling
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