Economia
& Energia 
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Energy Demand for the Domestic Sector Emission of Greenhouse Effect Gases in the Domestic Sector e&e’s methodology for the Energy Matrix Projection Emission Coefficients Matrix Calculation e&e
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PROJECTION OF ENERGY USE IN THE RESIDENTIAL SECTOR (Conclusion)PROJECTION OF RESIDENTIAL ENERGY USE IN THE 2000 / 2020 PERIOD. Using the data of the attached spreadsheet 1, two versions of the projection were prepared, the first one using the logistic linear curve (graphic 6) by an inverse transformation of the linear curve and the second one using the correlation EE = f (Urban Pop., PIB) The results are shown in the table below. The average shift between the two projections is 3%. Equivalent Energy
Equivalent Energy CONVERSION OF EQUIVALENT ENERGY INTO FINAL ENERGY. The conversion is necessary for calculating emissions due to the difference of coefficients among the various energy sources. In principle, one can use the participation of each energy source in the equivalent energy or project separately the equivalent energy of each one of them and return to final energy. Since electricity does not produces emissions in its use, it is sufficient to project the gas final demand (including LPG, natural gas and pipelined gas) in which LPG is presently largely dominant and will still dominate in the next decades, due to the elevated cost of pipelined gas installation in residences. LPG. The graphics below show the estimation sequence of the curve concerning LPG demand variation. The maximum estimated demand is 7.72 Mtoe/year.
Graphic 7 – Variation rate of LPG residential demand
Graphic 8  Logistic linear curve of LPG demand The projected demand from the logistic linear curve is shown in the table and graphic below.
Graphic 9 – LPG residential consumption. In order to evaluate the relative importance of the urban population and of the income on LPG consumption, a function of the above mentioned variables was fitted to the consumption data between 1975 and 1988. The double linear correlation equation is LPG (Mtoe)= 0,0658 Urban Pop.. (million) + 0,00074 GNP (B $_{94 })  2,988 that shows that the urban population is the predominant variable.
WOOD AND CHARCOAL . Graphic 10 below shows the evolution of wood and charcoal consumption between 1970 and 1998. In order to calculate the emissions, the residual consumption of 6 Mtoe/year will be considered. The results of conversion to final energy were used in the emission calculations (Spreadsheet 2).
The emission of atmospheric pollutants in the Residential Sector is not yet regulated in Brazil,. Therefore calculation will be based on the coefficients adopted by the Intergovernmental Panel on Climate Change  IPCC, for noncontrolled emissions (default values) converted from kg/TJ to kg/toe by considering 1 toe = 0.0452 TJ. The following table summarizes the values of interest. Emission coefficients  kg/toe
The emission of CO2 by biomass fuels is not considered by the IPCC. For the gaseous fuels, its calculation is based on the carbon balance using the carbon emission factors given in table 2 of the IPCC Guidelines. For these fuels the emission coefficients shown in the attached spreadsheet 2 were obtained by weighting the original coefficients with the participation in the final consumption. Graphic 11 below shows the evolution of biomass fuels emissions between 1970 and 1998.
Graphic 12  Emissions from Biomass The emissions of gaseous fuels (LPG, NG and pipelined gas) in thousand tons are shown in graphic 13.
Graphic 13 – Gaseous fuels emissions (1.000 t). 