Results from the revised GHG emissions model

So that the new results may be compared easily with the earlier results (DeLuchi, 1991), the table numbers here generally are the same as those in DeLuchi (1991).

Energy efficiency of vehicles.

Vehicle efficiency is one of the most important calculated parameters in the GHG emissions model, because it linearly determines fuelcycle emissions of CO2. In the model, the efficiency of the vehicle is determined by the mi/BTU efficiency of the AFV engine or powertrain relative to that of the baseline gasoline or diesel vehicle, the weight of the vehicle, and other parameters. The weight of the vehicle, in turn, is a function of the driving range, the characteristics of the fuel storage systems, and other factors.

The input parameters for the calculation of vehicle energy use are discussed above. The calculated weight results are shown in Table 2b, and the calculated overall efficiency and fuel-use results are shown in Table 2c. The efficiency of the EV relative to efficiency of the baseline gasoline vehicle has increased, and as a result fuelcycle GHG emissions from EVs are significantly lower.

The single most important parameter here is the energy conversion efficiency of the vehicle: the relative thermal efficiency in the case of AF ICEVs, and relative powertrain efficiency in the case of EVs. Driving range and vehicle weight are less important because they affect vehicle efficiency only indirectly. (Over the typical range of variation of both driving range and fuel-storage characteristics, the fuelcycle CO2-equivalent emissions vary by only 1-2%.)

Energy intensity of fuelcycles

Table 3a presents the new calculated energy intensities by stage of the fuelcycle, in BTUs of process energy used at each stage per BTU of fuel made available to end users. These results differ from the original Table 3 results (DeLuchi, 1991) because, as discussed above, the underlying assumptions and representations of process efficiency have changed. The most significant changes are those relating to the energy requirements of fuel production (e.g., methanol production from natural gas); less significant are those relating to the energy requirements of fuel and feedstock transport.

Table 3b is new: it shows BTUs of process energy consumed per vehicle mile of travel.

Kinds of process fuel used

Table 4 summarizes the calculated and input breakdown of the kinds of energy used at each stage of the fuelcycle. As noted above, this table has been broken into three parts: one for feedstocks, one for fuels, and one for distribution of liquid fuels. Virtually all of the changes calculated here have only a minor effect on fuelcycle CO2-equivalent emissions. (An exception is the change in the mix of fuels used to provide process heat at corn-to-ethanol plants.)

Leaks of methane and CO2

The data and methods used to estimate leaks from natural-gas systems, venting and flaring of gas associated with oil production, and methane emissions from coal mines have been completely revised. As a result, calculated venting and flaring emissions from oil wells have increased by a minor amount, calculated leaks from natural-gas systems have increased substantially, and calculated emissions from coal mining have decreased substantially. Table XVI shows calculated leaks from coal mining, and Table XIX shows parameters in the estimation of leaks from NG systems.

The increase in the calculated leakage rate from NG systems increases fuel-cycle emissions by about 7 g/mi, or 2%. The decrease in calculated methane emissions from coal mining decreases CO2-equivalent emissions from the coal-to-electricity fuelcycle by about 2%.

Electricity generation: efficiency and mix of fuels,

As discussed above, I have projected the efficiency of electricity generation and the mix of fuels used for generic national power through the year 2015. Tables 6a and 6b show the new projected efficiencies and fuel mixes.

For most years, the projected generation efficiency is higher than that assumed in the original report (Appendix D), and as a result emissions from fuelcycles that consume a lot of electricity (such as the EV fuelcycle) are lower.

The new national marginal recharging mix for EVs has more coal and less gas than does the old one, and hence by itself results in higher fuelcycle GHG emissions from EVs.

Fuelcycle emissions from the use of electricity

As discussed above, I have updated most of the emission factors for power plants. Table 6c shows the new CO2-equivalent emissions from power plants, by pollutant, and total fuelcycle emissions from the end use of electricity. The changes to the emission factors for utility boilers have only a minor effect on the CO2-equivalent fuelcycle emissions.

Emissions per unit of fuel delivered, by fuel-cycle stage

Table 7 shows the new calculated CO2-equivalent emissions per unit of energy delivered to end users, by stage of the fuelcycle. These results are useful mainly for the purpose of estimating GHG emissions from non-transportation fuelcycles. For example, one can use the g/106-BTU results for the NG fuelcycle to estimate emissions from use of NG for home heating. (One still must estimate emissions from final end-use combustion of the gas in the home, of course.)

Gram-per-mile emissions by vehicle/fuel/feedstock combination, and stage of the fuelcycle.

Table 9 presents the new final g/mi results by vehicle/fuel/feedstock, and stage of the fuelcycle. These can be compared with the results of the earlier analysis (Tables 9 and 12 of Volume 1).

Gram-per-106 BTU emissions by stage and feedstock/fuel combination.

Table 10 shows the calculated emissions of each individual greenhouse-gas -- without the equivalency factors applied -- in grams per 106 BTU of product made available to end users. Note that Table 10 here shows the actual mass emissions, not the CO2-equivalents, of the different greenhouse gases, whereas the old Table 10 (DeLuchi, 1991) shows the CO2 equivalents. One can calculate CO2 equivalents from the data of the new Table 10 simply by multiplying actual emissions by the CO2-equivalency factors (Table I).

These unweighted emissions, by stage of the fuelcycle, can be used as part of an analysis of criteria-pollutant emissions.

Summary of major remaining uncertainties

The CO2-equivalency factors for all non-CO2 greenhouse gases still are uncertain, and a major source of uncertainty in all of the fuelcycles.

In all fuelcycles, the efficiency of energy end use is important and still uncertain. In particular, in the EV cycle, the major uncertainty remains the relative energy use of EVs, although the new energy-use model described above has helped to narrow that uncertainty. The effect of the mix of fuels used to generate power is reasonably well reflected in the regional results.

There also is non-trivial uncertainty in the composition and cycle life of batteries for EVs. The cycle life is important because the shorter the cycle life (in miles of travel), the higher the g/mi lifetime emissions.

In natural-gas fuelcycles, the biggest uncertainties are methane emissions from vehicles, and leakage from natural gas systems. However, the detailed analysis documented in Delucchi and Lipman (1996) has helped to reduce this uncertainty.

In the corn-to-ethanol cycle, the biggest uncertainties are the effects of additional corn demand on land use, and the estimation of the emissions displaced by the production of the coproducts.

In the wood-to-ethanol cycle, the biggest uncertainty is the amount of the electricity co–product displacement credit.

Acknowledgment

Partial funding for this work was provided by Argonne National Laboratory and the Energy Information Administration of the U. S. Department of Energy. The usual disclaimers apply.

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