دانلود مقاله ISI انگلیسی شماره 46578
ترجمه فارسی عنوان مقاله

روش رگرسیون چندگانه گام به گام مدل سازی انتشار گاز گلخانه ای در بخش انرژی در لهستان

عنوان انگلیسی
Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
46578 2015 8 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Journal of Environmental Sciences, Volume 30, 1 April 2015, Pages 47–54

ترجمه کلمات کلیدی
گازهای گلخانه ای - احتراق سوختهای فسیلی - بخش انرژی -
کلمات کلیدی انگلیسی
Greenhouse gases; Burning of fossil fuels; Energy sector; Backward stepwise regression modeling
پیش نمایش مقاله
پیش نمایش مقاله  روش رگرسیون چندگانه گام به گام مدل سازی انتشار گاز گلخانه ای در بخش انرژی در لهستان

چکیده انگلیسی

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.