Emission factor uncertainties

The default emission factors, derived in this chapter are based on a statistical analysis of available data on fuel characteristics. The analysis provides lower and upper limits of the 95 percent confidence intervals as provided in Table 1.2 for net calorific values and Table 1.3 for carbon contents of fuels.

The uncertainty ranges, provided in Table 1.4 are calculated from this information, using a Monte Carlo analysis (5 000 iterations). In this analysis, lognormal distributions, fitted to the provided lower and upper limits of the 95 percent confidence intervals were applied for the probability distribution functions.

For a few typical examples, the resulting probability distribution functions for the default final effective CO2 emission factors are given below in Figure 1.3.

Figure 1.3 Some typical examples of probability distribution functions (PDFs) for the effective CO2 emission factors for the combustion of fuels.

Natural Gas u o e s a

Emission factor (kg/TJ)

Landfill Gas

Emission factor (kg/TJ)

Motor Gasoline

Gas/Diesel Oil u

Emission factor (kg/TJ)

Emission factor (kg/TJ)

Jet Kerosene

Residual Fuel Oil

Emission factor (kg/TJ)

Emission factor (kg/TJ)

Anthracite

Anthracite

Emission factor (kg/TJ)

CJl CJl

Emission factor (kg/TJ)

Other Bituminous Coal

Emission factor (kg/TJ)

Coke Oven Coke and Lignite Coke

Wood/Wood Waste

krifl

Emission factor (kg/TJ)

Emission factor (kg/TJ)

The uncertainty information as presented in Table 1.4 can also be used when comparing country-specific emission factors with the default ones. Whenever a national specific emission factor falls within the 95 percent confidence interval, it could be regarded as consistent with the default value. In addition, one would expect the uncertainty range of country-specific values for application in that country to be smaller than the range provided in Figure 1.3. Uncertainties in emission factors for non-CO2 emission factors are treated in the subsequent chapters for the different source categories separately.

1.6 QA/QC AND COMPLETENESS

1.6.1 Reference Approach

As carbon dioxide emissions from fuel combustion dominate greenhouse gas emissions in many countries, it is worthwhile to use an independent check providing a quick and easy alternative estimate of these emissions. The Reference Approach provides a methodology for producing a first-order estimate of national greenhouse gas emissions based on the energy supplied to a country, even if only very limited resources and data structures are available to the inventory compiler. Since the Reference Approach is a top-down approach and in that respect is relatively independent of the bottom-up approach as described in the Tier 1, 2 and 3 methods of this chapter, the Reference Approach can be seen as a verification cross-check. As such it is part of the required QA/QC for the energy sector. The Reference Approach is described in full detail in Chapter 6 of this Volume.

The Reference Approach requires statistics on the production of fuels, on their external trade, as well as on changes in their stocks. It also requires a limited amount of data on the consumption of fuels used for non-energy purposes where carbon may need to be excluded.

The Reference Approach is based on the assumption that, once carbon is brought into a national economy in the form of a fuel, it is either released into the atmosphere in the form of a greenhouse gas, or it is diverted (e.g., in increases of fuel stocks, stored in products, left unutilised in ash) and does not enter the atmosphere as a greenhouse gas. In order to calculate the amount of carbon released into the atmosphere, it is not necessary to know exactly how the fuel was used or what intermediate transformations it underwent. In view of this, the methodology may be described as top-down in contrast to the bottom-up methodologies applied in a sectoral approach.

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