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Chapter 6
TRANSPORTATION SECTOR¹
6.1 INTRODUCTION
The U.S. transportation sector includes highway, air, rail, shipping, pipeline, and off-road transport
as well as miscellaneous categories such as recreational boats and military fuel consumption. In
1997, the sector consumed about 25 quads of primary energy, 27 percent of total U.S. energy
consumption. In the same year, the sector had carbon emissions of 478 million metric tons (MtC).
32 percent of the U.S. total carbon emissions. In the face of strong continuing demand for
transportation services, slow turnover of fleets, gasoline's dominance of light-duty vehicle fueling
infrastructure, and low energy prices that provide only modest incentives for improved efficiency,
U.S. transportation energy consumption and greenhouse emissions are expected to grow robustly
over the next few decades.
In this chapter, we estimate the impacts on transportation energy consumption and greenhouse
emissions of a series of new government policies, embedded in two scenarios of increasing public
concern over global warming and other environmental issues. The Energy Information
Administration's (EIA's) 1999 Annual Energy Outlook (AE099) Reference Case represents a
"Business-as-Usual" (BAU) future with no policy changes (EIA, 1998). The two policy-driven
scenarios are created by rerunning the EIA's NEMS model with extensive changes to its input and
some changes in its code to reflect the new policies and changed social conditions in the scenarios.
The chapter is organized as follows. We first discuss some inherent limitations of estimating
technological and market impacts of future policy measures. We then review the current status and
trends in energy use and greenhouse gas (GHG) emissions in the U.S. transportation sector. Brief
discussions of key technologies that seem likely to have major impacts over the next few decades
come next. Supplementary material is presented in Appendix C-3. This is followed by a description
of the BAU scenario. The next section addresses policies that could advance clean energy
technologies and their acceptance, including a discussion of the barriers these policies are intended
to overcome. How the policy pathways were implemented in the context of the NEMS model is the
subject of Section 6.4. After that, we present in turn the Moderate and Advanced scenarios and the
resulting NEMS-CEF projections. Several sensitivity cases were run to test the impacts of
assumptions about key technologies and policies on the forecast results. The chapter concludes
with some observations about where additional analysis might produce more valuable insights,
followed by a attempt to summarize the key conclusions of the chapter.
6.1.1 Uncertainties and Limitations
In our view, it is critical that the reader understands the strong uncertainties associated with these
analyses. First, the results depend critically on the costs and performance of technologies that
remain under development, and these costs and performance values are highly uncertain. The
effect of this uncertainty on our results is mitigated somewhat, however, by the existence of a
portfolio of technologies under development or in the early stages of commercialization that will
compete for market dominance in the future. Historically, large reductions in cost and
improvements in performance have occurred for a number of transportation technologies, and we
believe it is reasonable to assume that some members of the portfolio will experience future cost
reductions and performance improvements of a similar magnitude.
Second, there is no accepted analytical method to forecast the results of increases in research and
development funding (EIA, 1999, p. xv), a crucial component of our policy strategy, and we are
forced to rely essentially on judgment. The outcome of an RD&D program depends on the amount
of effort invested, on the intelligence with which the effort is applied, and, to a substantial extent, on
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luck. As noted above, however, the existence of a substantial portfolio of technologies in the R&D
"pipeline" offers a level of redundancy that adds to the probability of substantial improvements in
performance and cost-effectiveness in several technologies. There are reasons to be optimistic.
We note that since the Five-Lab Study, significant advances have been achieved in fuel cell
technology, and two major automotive manufacturers have announced commercial introductions of
hybrid vehicles five to ten years sooner than we had expected. At the same time, it is not reasonable
to assume that all technologies can achieve the advances needed for market success. The best we
can do is make an educated guess about which seem most likely to achieve breakthroughs, but we
readily acknowledge the uncertainties in such judgments.
Third, consumer-purchasing behavior will obviously play a critical role in determining the future
market share of crucial technologies, and how consumers will respond to new technologies is
uncertain. Forecasters generally use market surveys to project consumer behavior, but much of
the data about consumer preferences for new technologies comes from consumer responses to
theoretical questions about whether they would purchase vehicles whose characteristics they know
little about and have minimal experience with. Surveys of this sort are unreliable. Also, consumer
preferences have undergone drastic changes at times; for example, recent sharp increases in
consumer preference for safety features and for vehicles with proven records of high levels of
safety. Similar changes are possible in the future but cannot be reliably predicted.
Fourth, the policies we examine in each scenario are assumed to be compatible with the qualitative
scenario descriptions (and conversely, we leave out some policies because we assume they are
incompatible with the descriptions), but the connection between societal conditions and public policy
is by no means straightforward or non-controversial. For example, it is far from clear how far the
Federal government will go in trying to force future improvements in automobile and light truck
fuel economy. For several years the Congress, acting through the appropriations process, has
expressly forbidden the Department of Transportation (DOT) from even analyzing potential
changes in Corporate Average Fuel Economy (CAFE) rules. Further, the industry appears to be
unalterably opposed to increased CAFE standards. However, according to recent trade press
reports, there is some (minority) sentiment in Congress to increase these standards. And some of
our reviewers believe that regardless of public opinion about global warming, the U.S. market entry
of practical hybrid-electric vehicles (scheduled to be introduced by 2000) and large increases in
Japanese and European fleet fuel economy (responding to Kyoto initiatives) will lead to public
demands that U.S. policy bring similar changes to the U.S. fleet. We have responded to the
ambiguity in future policy shifts by assuming no change in CAFE rules for the Moderate scenario
and examining two policy possibilities in the Advanced Scenario: Voluntary Agreements between
the government and auto industry as a "base" Advanced policy, and still more stringent CAFE
standards as a sensitivity case.
Translating policies to NEMS model inputs often involves subjective judgments. As discussed below
and in Appendix A, some of the modeling changes are close representations of the policies of
conditions, for example reduced technology costs in the model to reflect a policy of technology
subsidies or tax credits. Others are less analytical representations of the policies, for example,
earlier technology introduction and reduced costs in the model to represent the effect of increases
in research and development funding. The projected changes in dates of introduction and costs are
based on industry announcements, technical analyses by government, private, and academic
sources, consumer surveys, and other sources.
In the end, we must use our own judgment about these matters, tempered by external expert review.
We are careful to be explicit about the assumptions we make about technology, consumer
preferences, producer behavior and policies. All changes we have made to the NEMS model and
its data inputs are documented in Appendix A.²
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The primary focus of this analysis is on energy consumption and GHG emissions, but the policies
and technologies embodied in the two scenarios will also reduce oil imports, emissions of criteria air
pollutants, other environmental damages associated with fossil fuel use.
6.1.2 Overview of the Sector
The U.S. transportation sector is dominated by highway travel, which consumes 75 percent of the
total energy used by the sector and accounts for 75 percent of the sector's carbon emissions. In the
highway sector, light-duty passenger travel is dominant, accounting for 74 percent of highway
energy consumption and carbon emissions, and 56 percent of total transportation energy
consumption and carbon emissions. Figures 6.1 and 6.2 show the modal breakout of carbon
emissions and energy consumption, respectively.
The characteristics of the various flects in the sector and recent trends in energy use provide
important clues to the likely future energy use in the sector and the potential for reducing GHG
emissions. Some critical points:
New light-duty passenger vehicles have been adopting fuel-efficient technologies over the past
decade and a half, but increasing vehicle size, weight and especially performance have nullified
the fuel economy gains these technologies might have brought.
Important new technologies that enter the fleet include port fuel injection, 4 valves/cylinder
engines, variable valve control, structural redesign using supercomputers, growing use of high
strength steel and steel substitutes such as aluminum and plastics, and low rolling resistance
tires.
Counteracting trends include the growing sales share of light-duty trucks, especially Sport Utility
Vehicles which now comprise 46 percent of light-duty vehicle sales, up from 17 percent in 1980;
horsepower to weight ratios 45 percent higher than in 1980, a 20 percent increase in weight over
1980 vehicles (Heavenrich and Hellman, 1999); greater shares of 4-wheel drive installed on 47
percent of 1999 model year light trucks, and other luxury features, and continued increases in
the stringency of emissions and safety standards.
As a result of a decade of low gasoline prices, consumer surveys show that today's auto
purchasers generally are uninterested in fuel economy.
The "potential technology" portfolio for automobiles has been enhanced substantially by the
Partnership for a New Generation of Vehicles (PNGV), a government/industry joint research
and development program (NRC, 1999). PNGV's effects are both direct and indirect - in
addition to its own advances, it has stimulated competitive developments in Europe and Japan.
Freight transport now consumes about 30 percent of U.S. transportation energy, with freight
energy use but not gross ton miles dominated by heavy truck carriage (over 50 percent of
energy use, about one-quarter of ton-miles) (Davis, 1998, table 2.13), the most energy-intensive
mode aside from air freight. Air freight and freight truck energy use are the most rapidly
growing freight modes because of the U.S. economy's shift towards higher value (and more
time-sensitive) goods. A countervailing trend is greater use of multi-modal shipments, advanced
by the rationalization of U.S. freight railroads and the benefits of improved computerized
information systems.
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Fig. 6.1 1997 Transportation Carbon Emissions by Mode (477.9 MtC total)
Other
Marine
1%
6%Pipeline Fuel
Rail
2%
3%
Air
13%
Light-Duty Vehicles
Freight Trucks
56%
17%
Commercial Light
Trucks
2%
Fig. 6.2 1997 Transportation Energy Use, by Mode (25 Quads total)
Other
1%
Marine
Pipeline Fuel
Rail
5%
3%
2%
Air
14%
Light-Duty Vehicles
56%
Freight Trucks
17%
Commercial Light
Trucks
2%
6.1.3 Examples of Promising Technologies
The transportation sector has a wide variety of available and emerging technologies - the
technology "portfolio" noted above - that offer the potential to reduce significantly the energy use
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and GHG emissions associated with transportation services. Some of the most promising are
described below.
Cellulosic Ethanol. About one billion gallons of ethanol produced from corn is currently used
annually in U.S. transportation markets as a blend stock for gasoline (Davis, 1998). Although the
efficiencies and fuel choices used over the fuel cycle in producing this ethanol vary widely (e.g.,
fuel choices for powering the distillery can be corn stover, natural gas, or coal), recent studies show
that the use of this ethanol provides a moderate GHG advantage over gasoline of about 20 percent
or SO (Wang, 1999). Processes to produce ethanol from cellulose - from woody biomass or
municipal wastes - for use as a gasoline blending agent or neat fuel offer to reduce greenhouse
gases about 80 percent compared to gasoline (Wang et al., 1999). A Department of Energy (DOE)
program at the National Renewable Energy Laboratory has been working intensively to improve the
efficiency and cut the costs of producing ethanol to about half of current level (RNEL, 1999).
Program success could allow significant quantities of cellulosic ethanol to enter the market over the
next decade, though a critical factor in its commercialization will be the world market price of oil.
Land requirements could ultimately limit cellulosic ethanol production. About 15 billion gallons of
ethanol (1.2 Quads) could be produced annually by converting municipal and agricultural wastes
with minimal land requirements (Lynd, 1997). If about 35 million of the roughly 60 million acres
idled by Federal programs were used for energy crops, about 25-32 billion gallons, or about 3-4
Quads of ethanol could be produced annually (assumptions: 8.4 dry tons/acre/year crop
productivity, 107.7 gallons of ethanol/ton yield) (Lynd, 1997). If only 10 billion gallons of ethanol
were produced annually, this would leave 200 million dry tons of biomass for other uses, such as
biomass power.
Hybrid Electric Drivetrains. A hybrid electric drivetrain combines an internal combustion engine
or other fueled power source with an electric drivetrain including an electric motor and battery (or
other electrical power source, e.g., an ultracapacitor). Potential efficiency gains involve recapture
of braking energy (with motor used as generator, captured electricity stored in the battery); potential
to downsize the engine, using the motor/battery as power booster; potential to avoid idling losses by
turning off the engine or storing unused power in the battery; and increasing average engine
efficiency by using the storage and power capacity of the electric drivetrain to keep the engine
operating away from low efficiency modes. Toyota recently introduced a sophisticated hybrid
subcompact auto, the Prius, in Japan and will introduce a version into the U.S. market within a
year; Honda also has announced the impending introduction of its two-seater Insight hybrid (Wald,
1999). Ford, GM, and Daimler/Chrysler all have hybrids in advanced development (Reuters, 1998;
Jost, 1998; Bucholz, 1999a, 1999b).
Hybrids can be built in various configurations that trade off fuel efficiency, performance, and cost
(for example, the most efficient configurations would downsize the engine, which would reduce the
vehicle's towing capability). The most fuel-efficient configurations potentially could boost fuel
economy by as much as 50 percent or so at near-constant performance under average driving
conditions. Hybrids attain their greatest efficiency advantage - potentially greater than 100 percent
- over conventional vehicles in slow stop-and-go traffic, so that their first applications might be
urban taxicabs, transit buses, and service vehicles such as garbage trucks. Estimates of fuel
economy improvement potentials for hybrid of medium trucks in urban driving range from 30
percent to 170 percent (An et al., 2000).
Lower Weight Structural Materials. The use of alternative materials to reduce weight has been
historically restrained by cost considerations, manufacturing process technology barriers, and the
difficulty of these materials in meeting automotive requirements for criteria such as surface finish
quality, predictable behavior during crash tests, or reparability. The last few years have seen
significant developments in overcoming such barriers, through design changes such as a space
frame-based structure, advanced new manufacturing technology for plastics and aluminum, and
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improved modeling techniques for evaluating deformablity and crash properties. Ford has
displayed an advanced lightweight prototype (the P2000 Diata) that is a mid-size car with a weight of
only 2000 pounds, as compared to vehicles weighing 3200 pounds today (Ford, 1997). Equipped
with a direct-injection diesel engine it gets 63 mpg (Jost, 1998b). The Auto Aluminum Alliance, a
working group within USCAR, has set a goal of 40 percent weight reduction via substitution of
aluminum and is developing advanced manufacturing, repair and recycling technologies to attain
that goal. Some aluminum intensive luxury cars have already been introduced (for example, the
Audi A8) and Ford is known to be considering the introduction of such a vehicle in the mass
market.
Direct Injection Gasoline and Diesel Engines. Direct injection lean burn gasoline engines have
already been introduced in Japan and Europe, but have been restricted here by a combination of
tight emission standards and high sulfur content in gasoline. Mitsubishi for example, now
manufactures 10 gasoline direct-injection (GDI) models in Japan, which reportedly reduce fuel
consumption by 20 percent, with a 10 percent increase in power output (Demmler, 1999). The
catalytic converters capable of reducing NO, emissions from lean burn engines are very sensitive
to fuel sulfur content, and no simple remedy has been found. Recently, Environmental Protection
Agency (EPA) has proposed new Tier 2 standards that require the introduction of low sulfur
gasoline, and have also increased the stringency of NO, standards for 2004 and beyond. While the
sulfur reduction allows GDI engines to be introduced, it is not yet clear that fuel efficiency benefits
can be retained at the new NO, levels. Preliminary evaluations suggest that benefits may be in the
12 to 15 percent range rather than the 16 to 20 percent range available in Japan and Europe, but
even this assumes some advances in after-treatment technology. Engine costs, however, seem
quite moderate, in the range of $200 to $300 more than a conventional engine. Evidence that
emissions barriers are being broken down can be inferred from GM's intention to introduce a
family of GDI light truck engines in 2001 (Robinson, 1999). An 8-10 percent fuel economy benefit
is anticipated at a cost of $265 to $370 per truck.
Direct injection diesel engines have long been available for heavy trucks, but recently have become
suitable for automobiles and light trucks as noise and emission problems have been reduced. These
new engines are about 40 percent more fuel efficient, on a per gallon basis, than conventional
gasoline engines (OTA, 1995) and about 25 percent more efficient on the basis of carbon emissions
over the fuel cycle (Wang, 1999b). California's new emission regulations require diesels to attain
the same (low) NO, levels as gasoline engines, as well as stringent particulate levels; these and
potential new federal standards present a challenge to diesel's viability (see Box 6.1).
Box 6.1 Diesel's Future Viability
The future viability of diesel engines in the light-duty fleet, and perhaps in the heavy-duty fleet as
well, will depend on the interplay of emission standards for NO, and particulates and progress in
diesel fuels, engine design, and emissions after-treatment technology (Mark and Morey, 1999). It
will also depend on consumer acceptance, which is by no means guaranteed. Diesels have been
selling well - and obtaining a price premium that appears to exceed that dictated by cost difference -
in the light truck fleet. Diesels have a miniscule share of automobile sales, however, and may have
to overcome consumer reluctance based on past mechanical failures and performance
shortcomings. New turbocharged direct injection diesels bear little resemblance to diesels of the
past, but their future acceptance by auto purchasers must be considered uncertain.
Emissions requirements are growing far more stringent for diesels (as for gasoline-fueled vehicles
as well). California's new light-duty Low Emission Vehicle (LEV) NO standard for 2004 is 0.05
g/mi, versus 0.3 g/mi today, and applies equally to gasoline and diesel vehicles; its new 2004
particulate standard for diesels is .01 g/mi, versus .08 g/mi today. Federal "Tier 2" standards, now
being promulgated, are expected to be similar, though they may provide some added flexibility that
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could help diesels. And the potential for still more stringent standards arises from the continuing
research on the effects of diesel exhaust on health. Current knowledge is limited by deficiencies in
several areas: quantitative measures of exposure to humans; data over a wide population; and
confirming data on disease mechanisms (Nauss, 1999). If ongoing research yields strongly negative
results, pressure will grow to restrict diesel emissions still more. An important issue here, however,
is the extent to which potentially conflicting societal goals, in this case reduced health-associated
emissions and reduced GHG emissions and oil use, are actually being weighed against each other
in making policy choices about emissions standards. The National Research Council (NRC), in its
recent PNGV review report (NRC, 1999), states "the responsible government agencies participating
in the PNGV have pursued their specific agency objectives without taking into account the
interdependency of these issues." In other words, NRC fears that the new EPA emissions
standards may remove highly efficient compression ignition direct injection (CIDI) engines from
the PNGV's list of options without accounting for the damage this would do to the U.S. potential to
reduce greenhouse gases.
In the face of the new standards and the potential for additional emissions requirements, diesel's
viability depends strongly on advances in several areas (Howden, 1999; Lyons, 1999):
Fuels: especially economical reduction of sulfur to at least 30 ppm and possibly considerably
lower; also changes in density, aromatics and polycyclics content, cetane, etc.
Engine design: particularly in combustion chamber design, improved exhaust gas recirculation,
improved fuel injection.
NO, after-treatment: e.g., lean-burn catalysts, NO, traps (absorbers), non-thermal plasma
systems.
Particulates after-treatment: e.g., regenerative PM traps and oxidation catalysts.
The PNGV currently is working on all of these systems, as are private companies in Europe, Japan,
and the United States.
Further improvements in diesel technology also offer substantial promise in heavy-duty
applications, especially heavy trucks but also including marine and rail applications. Current DOE
research programs are aiming at achieving maximum efficiencies of about 50 percent in heavy-
duty diesels, with low emissions (U.S. DOE, 1997).
Both gasoline and diesel direct injection engines have been shown to emit relatively large quantities
of fine particles, even when total particulate weight is low. Current emissions standards are weight-
based, but continuing research on particulate matter (PM) health effects conceivably could lead to
new standards based on the number of particles rather than their weight. Such standards could
pose a challenge to all direct injection engines.
Fuel Cells. Fuel cells have received considerable attention recently, with both Ford and
Daimler/Chrysler (1999) announcing their intention to introduce such vehicles by the 2004 model
year. Nissan has announced plans to introduce a methanol-reforming fuel cell vehicle in the
Japanese market between 2003-2005 (Bucholz, 1999). General Motors Europe announced that it
will have a fuel-cell-powered car ready for the European market by 2004 (Birch, 1999a) and
Renault is planning a 2005 introduction date for its fuel cell car (Birch, 1999b). Fuel cells have
been virtually the "Holy Grail" of clean powertrain technology, promising zero or near-zero
emissions with very high efficiency. The recent optimism has been driven by strong advances in
technology performance, including rapid increases in specific power that now allow a fuel cell
powertrain to fit into the same space as a conventional engine without sacrificing performance
(Griffiths, 1999). However, fuel cells remain extremely expensive, and long-term costs are by no
means clear; further, important technical roadblocks remain, e.g., operation in extreme weather
conditions. Manufacturers are expressing optimism, however. For example, General Motors
Europe has been quoted as believing that within 5-10 years after introduction the use of modular
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construction, falling costs and scale economies will make it possible to sell fuel cell vehicles at a
lower price than cars with internal combustion engines (Birch, 1999a).
Another central issue is the fuel choice. Fuel cells need hydrogen, either carried onboard or
produced by reforming methanol or gasoline. Carrying hydrogen may yield the cheapest and most
fuel-efficient vehicle, but there is no hydrogen distribution and refueling infrastructure. A gasoline
vehicle overcomes the infrastructure problem but is the most expensive and least efficient vehicle;
further, developing an adequate gasoline processor remains a critical task, with significant
improvements required in processor weight and size, cost, response time, efficiency, and output of
carbon monoxide, which can poison the fuel cell stack (NRC, 1999). Methanol may be a reasonable
compromise, though it too requires a substantially improved fuel processor and, as yet, has no real
infrastructure for distribution. Although vehicle fuel economy depends on far more than just the
power plant, it appears that a fuel cell vehicle using methanol, with a lightweight, low drag body and
low rolling resistance tires, should be capable of achieving 65 mpg (gasoline equivalent). Gasoline
powered fuel cell vehicles using equivalent body structure, tires, and other components should be
capable of about 60 mpg whereas similar fuel cell vehicles powered by compressed hydrogen could
get 90 mpg. Both hydrogen and liquid fuel versions are likely to be initially more expensive than an
equivalent conventional automobile.
Aircraft Technology. Several major technologies offer the opportunity to improve the energy
efficiency of commercial aircraft by 40 percent or more. The Aeronautics and Space Engineering
Board of the NRC (1992, p. 49) concluded that it was feasible to reduce fuel burn per seat mile for
new commercial aircraft by 40 percent by about 2020. Of the 40 percent, 25 percent was expected
to come from improved engine performance, and 15 percent from improved aerodynamics and
weight. A reasonable preliminary goal for reductions in NO, emissions was estimated to be 20-30
percent. Technologies such as laminar flow control to reduce drag, greater use of composite
materials to reduce weight, and advanced propulsion concepts such as ultra-high bypass turbofan
and propfan engines could all contribute.
Noting that the energy efficiency of new production aircraft has improved at an average rate of 1-2
percent per year since the dawn of the jet era, a recent IPCC (Lewis and Niedzwiecki, 1999) expert
panel concluded that a significant though somewhat lower rate of improvement could be expected
through 2050. The panel predicted about a 20 percent improvement in seat-kilometers per kg of
fuel for 1997-2015 (Table 6.1).
The "blended wing body" is a revolutionary airframe design that transforms an aircraft into
essentially a flying wing, resembling the military's stealth aircraft in appearance. The extension of
the cabin into the wing allows the drag associated with the traditional aircraft body to be reduced,
and permits some weight reduction, as well. With this radical new design, fuel burn could be
"reduced significantly relative to that of conventionally designed transports" (Lewis and
Niedzwiecki, 1999, p. 7-13). With an aggressive R&D effort, an initial version could enter service in
2020 (ibid).
Table 6.1 Historical and Future Improvements In New Production
Aircraft Energy Efficiency (Percent)
Time Period
Airframe
Propulsion
Total
%/Year
1950-1997
30
40
70
1.13
1997-2015
10
10
20
1.02
1997-2050
25
20
45
0.70
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Source: Lewis and Niedzwiecki, 1999, table 7.1.
6.2 BUSINESS-AS-USUAL SCENARIO
In the BAU scenario for the transportation sector, we accepted the sectoral assumptions of the
AEO99 Reference Case scenario despite some disagreements we have with certain portions of it,
which are discussed in Section 6.2.2. The CEF-NEMS baseline scenario results have some slight
differences with the AEO99 results because of the effect of changes made to the Reference Case in
other economic sectors. These differences are quite small, less than one percent, and we will not
discuss them.
6.2.1 Policies in the BAU Scenario
The CEF-NEMS baseline scenario (and the AOE99 Reference Case scenario) adopts the following
policies:
1. Emissions standards: Tier 2 vehicle emission standards have not yet been promulgated by EPA
and are not included in the scenario. These standards could have strong impacts on
transportation technology introduction and market share, for example, stringent NO, standards
could hinder widespread introduction of efficient direct injection diesel engines into the light-
duty fleet unless major advances in emissions control are achieved.
2. Alternative fuel requirements: EPACT rules for purchase of alternative fuel vehicles by fleet
operators, including Federal and fuel provider fleets, are included. California's Low Emission
Vehicle Program, which includes requirements for zero emission vehicles (10 percent of sales
by 2003), is assumed in place. Massachusetts and New York are assumed to have delayed their
programs to conform to the California 2003 limits.
3. Kyoto Protocol: Potential policy actions that may be taken to satisfy the Kyoto Protocol are not
included. However, Climate Change Action Plan programs are assumed to be in place and
successful. These are: reform Federal subsidy of employer-provided parking; adopt a
transportation system efficiency plan; promote telecommuting; and develop fuel economy labels
for tires. The first three are assumed to achieve a 1.6 percent reduction in vehicle miles
traveled (vint) by 2010; the tire labels are assumed to achieve a 4 percent/vehicle improvement
in fuel efficiency for those vehicles switching to more efficient tires.
4. Fuel economy standards: no further increase in current auto and light truck standards.
6.2.2 Alterations to the EIA Base Case
As noted above, we made no alterations to the EIA Reference Case, although we do have concerns
about various aspects of that Case. Two key concerns:
1. Vehicle performance projections. In the light-duty fleet, the last decade and a half has seen
substantial increases in acceleration performance and corresponding increases in average
horsepower and horsepower/weight values in the fleet. EIA has assumed that these factors will
continue to increase over the lifetime of the estimate, leading ultimately to passenger cars
averaging 250 horsepower by 2020. These performance increases dampen substantially the
efficiency impact of new technologies forecast to enter the fleet during this period, so that the
average new car fuel economy is forecast to increase from 27.9 mpg in 1997 to only 32.1 mpg
in 2020 despite the penetration of a substantial amount of new efficiency technology. Some
industry analysts consider this small an increase unrealistic in the face of programs like the
PNGV, whose goal is to triple light-duty vehicle fuel economy, as well as the impending
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introduction of hybrid electric vehicles such as Toyota's Prius and Honda's Insight. On the
other hand, current CAFE standards have appeared to act as a floor holding up fleet fuel
economy at its current levels, and other analysts question whether fleet fuel economy will
increase at all given expected continuation of very low fuel prices and the clear low valuation of
fuel economy held by recent vehicle purchasers.
2. Travel projections. EIA is projecting a growth rate in car and light truck travel of 2.0 percent
over 1997-2010, and 1.6 percent/yr over 1997-2020, versus a 1974-1995 growth rate of 2.8
percent/yr that has been remarkably robust except for brief periods during the oil crises. The
slowdown presumably results from projections and assumptions about changes in population,
aging of the population. female driving, and income, as well as the CCAP programs noted
earlier. Interestingly, EIA states that the female/male-driving ratio reaches 100 percent by
2010 (from 56 percent in 1990) and that (recent) increased driving among retirees is taken into
account - factors that should boost vmt. This issue is discussed in greater detail in Appendix E-
2.
6.2.3 Results
Table 6.2 presents 10-year results for travel, efficiency, and energy used by mode, and energy used
by fuel.
In the Baseline, carbon emissions grow from 478 MtC in 1997 to 696 MtC in 2020, a growth of 45.9
percent over the period. Similarly, energy use rises from 25.0 Quads in 1997 to 36.8 Quads in 2020,
a 47.2 percent growth (Figure 6.3).
The reasons for this strong growth in both energy use and carbon emissions are straightforward:
the demand for travel is forecast to increase inexorably (though generally more slowly than the
historic rate), whereas travel energy efficiency is forecast to increase only modestly over the period
(Figures 6.4 and 6.5). Specifically, the 1997-2020 vmt, smt (seat-miles traveled), and tint (ton-miles
transported) growth and efficiency improvements by transportation modes are:
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Table 6.2 Results of BAU Scenario
1997
2010
2020
Level of Travel by Mode (Billion)
Light Duty Vehicles (vehicle miles traveled)
2301
2886
3303
Commercial Light Trucks (vehicle miles
69
91
104
traveled)
Freight Trucks (vehicle miles traveled)
177
243
270
Air (seat miles demanded)
1049
1813
2462
Rail (ton miles traveled)
1229
1516
1698
Marine (ton miles traveled)
756
877
961
Energy-Efficiency Indicator by Mode
New Vehicle (MPG)
24
25.5
26.5
New Car (MPG)
27.9
31.7
32.1
New Light Truck (MPG)
20.2
20.8
22
Light-Duty Fleet (MPG)
20.5
20.3
21.4
New Commercial Light Truck (MPG)
19.9
19.8
21
Stock Commercial Light Truck (MPG)
14.6
15
15.6
Aircraft (seat miles/gallon)
51
55.7
59.6
Freight Truck (MPG)
5.6
6.1
6.3
Rail (ton miles/kBtu)
2.7
2.9
3.1
Site Energy Use by Mode (Quadrillion Biu)
Light-Duty Vehicles
13.9
18.1
19.6
Commercial Light Trucks
0.6
0.8
0.8
Freight Trucks
4.2
5.3
5.7
Air
3.4
5.2
6.4
Rail
0.5
0.6
0.7
Marine
1.3
1.6
2.0
Pipeline Fuel
0.7
0.9
1.0
Other
0.2
0.3
0.3
Total
24.9
32.8
36.4
Energy Use by Fuel Type (Quadrillion Biu)
Distillate Fuel
4.6
6.0
6.6
Jet Fuel
3.3
5.1
6.3
Motor Gasoline
15.1
18.7
19.9
Residual Fuel
0.8
1.0
1.3
Liquefied Petroleum Gas
0.0
0.2
0.2
Other Petroleum
0.3
0.3
0.4
Petroleum Subtotal
24.10
31.32
34.67
Pipeline Fuel Natural Gas
0.7
0.9
1.0
Compressed Natural Gas
0.0
0.3
0.4
Renewables (E85)*
0.0
0.1
0.1
Methanol
0.0
0.1
0.1
Liquid Hydrogen
0.0
0.0
0.0
Electricity
0.1
0.2
0.2
Total Site Energy
24.9
32.8
36.4
Electricity Related Losses
0.1
0.3
0.4
Total Primary Energy
25.0
33.1
36.8
*The CEF-NEMS model reports renewables blended with gasoline as "Motor Gasoline." For an accounting
of cellulosic ethanol blended with gasoline, please see the discussion in section 6.5.1.
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Fig. 6.3 Projected Growth in Transport Energy Use, 1996-2020, EIA Reference Case
40
35
E
30
N
E
25
R
G 20
Y
U 15
S
E 10
5
0
1996
2010
2020
Fig. 6.4 Transportation Efficiency Indicators: Fractional Increase, 1996-2020
1.4
III 1996
1.3
2010
=
1.2
2020
1.1
1
0.9
0.8
NEW CAR MPG
NEW LT TRUCK
LT DUTY FLEET
AIRCRAFT, S-
FREIGHT TRUCK
RAIL, T-M/103 BTU
DOM ESTIC SHIP,
MPG
MPG
W/GAL
MPG
T-M/103 BTU
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Fig. 6.5 Projected Travel Growth, 1996 - 2020, EIA Reference Case
2.5
1996
2
2010
FRACTIONAL INCREASE
2020
1.5
1
0.5
0
LGHT-
FREIGHT
AIR
RAIL
MARNE
DUTY
TRUCK
TRAVEL,
TRAVEL,
TRAVEL,
TRAVEL,
TRAVEL,
VMT
TON-
VMT
VMT
VMT
MILES
MODE
TRAVEL, %
EFFICIENCY, %
Light-duty vehicles
43.5 (vmt)
10.4/4.4 (new/stock)
Freight trucks
52.5 (vmt)
12.5 (stock)
Air
136.7 (smt)
16.9 (stock)
Rail
39.3 (tint)
14.8 (stock)
Marine
27.1 (tmt)
6.3 POLICY IMPLEMENTATION PATHWAYS
6.3.1 Definition of Pathways
We have modeled two policy implementation pathways. The Moderate scenario contains policies
that would fit a changed political climate that would allow low-cost and non-coercive policies aimed
at reducing GHG emissions from the sector. The Advanced scenario contains policies that would fit
a political climate that would allow somewhat more aggressive policies, including Voluntary
Agreements that result from at least the threat of new, higher CAFE standards (a Sensitivity Case
examines the effect of such standards). Table 6.3 lists the policies for the two scenarios.
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Table 6.3 Transportation Policy Pathways
Moderate Scenario
Advanced Scenario
50% increase in government/industry
100% increase in government/industry
R&D investment
R&D investment
Tax credit for high efficiency vehicles
Same
Acceleration of air traffic management
Same
improvements
Program to promote investment in
Same
cellulosic ethanol production
Invigorated government fleet program
Same, more rigorous requirements
promoting alternative fuels and efficiency
No change in LDV fuel economy
Voluntary Agreements to improve fuel
standards
economy, for LDVs, freight trucks, and
Telecommuting stimulation - Note: we
aircraft (Sensitivity Case: new CAFE
don't discuss emission and fuels
standards
standards in this section, they're in Table
6.5
Same
Assumed carbon emissions cap and
permit trading equivalent to about
$50/mtC
Variabilization polices (Pay-at-the-Pump
auto insurance)
Intelligent traffic systems controls
The choice of policy options to be included in the scenarios reflects our assessment of the political
feasibility and likely effectiveness of a wide variety of potential policies under the conditions defined
in the scenario descriptions. Obviously this type of assessment is extremely subjective and
uncertain: seasoned politicians routinely miscalculate their ability to get proposed legislation
enacted into law, and legislative surprises are a fact of life in political circles. As noted above, a case
can be made that the policies we selected for light-duty vehicles - golden carrot awards in the form
of the tax credits for high efficiency vehicles suggested by the Administration and, for the Advanced
scenario, a Voluntary Agreement between automakers and the U.S. government to increase light-
duty fleet fuel economy - are either too ambitious ("U.S. automakers will never willingly adopt
Voluntary fuel economy targets") or too cautious ("why not include CAFE standards?"). As noted,
we do explore the impact of new CAFE standards in a Sensitivity Case within the Advanced
scenario. The polices we have examined are as follows:
Air Traffic Management Improvements. The EPA and FAA have a joint program aimed at
rationalizing air traffic management to substantially reduce the time spent waiting "on line" on the
ground and circling around airports while waiting for landing slots. This program, known as
CNS/ATM (Communications, Navigation, and Surveillance/Air Traffic Management) involves
substantial changes in flight procedures coupled with installation of a network of ground and
airborne technologies involving digital communication and computer interpretation of flight
instructions, and satellite systems that precisely locate aircraft. Successful implementation of this
program will substantially reduce both energy losses and emissions of criteria pollutants. A recent
FAA analysis estimates savings in energy use of up to 6 percent for North America (FAA, 1998); we
have adopted a five percent savings as our target level for 2020. Additional benefits beyond reduced
fuel cost and greenhouse emissions include significant reductions in criteria emissions (9 percent
for NOx, 12 percent for CO, and 18 percent for HC), improved aircraft utilization, timesavings for
passengers, and other benefits.
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CNS/ATM involves six technology groups:
P-FAST - Passive final approach spacing tool, designed to narrow the allowable gaps between
aircraft.
SMA - Surface movement advisor, a tool designed to more efficiently move aircraft from
touchdown to gate or gate to takeoff.
CDM - Collaborative decision making, designed to find optimal reroutings when aircraft meet
unexpected conditions and must change flight plans.
TMA - Traffic Management Advisor, another collaborative decision-making tool that will
predict delays at an airport and reschedule traffic at other airports to avoid overloading the first
airport.
URET - User request evaluation tool, which performs after-the-fact analysis of flight
performance
CTAS - Center Terminal Automation System, incorporating parts of P-FAST and TMA for
smaller airport operations.
FAA has adopted promotion of CNS/ATM as a goal of its Strategic Plan ("Achieve progress toward
global implementation of satellite-based communication, navigation, surveillance, and air traffic
management (CNS/ATM) by assisting planning and implementation efforts in each world
region. "(FAA, 1996)). However, there currently is no formal mechanism for implementing this
program, and the FAA budget appears insufficient to include the large capital investments needed.
In a BAU environment, with continuing low prices for jet fuel, implementation would likely be slow
despite its benefits. If FAA analysis is correct, however, the program should easily pay for itself in
fuel savings, improved aircraft utilization, and other savings. Therefore, we expect rapid
implementation to fit easily within both the Moderate and Advanced scenarios.
Carbon Permit Program. Carbon permit programs define acceptable levels of carbon emissions
and allocate these emissions to carbon emitters by auctioning permits or allocating the permits to
individual sources, with trading allowed. The impact of a carbon permit program that results in a
$50/metric ton price for carbon in 2020, a price that translates to about $0.12/gallon of gasoline
given gasoline's carbon content, is reflected in the Advanced scenario. This modest increase in
gasoline price - about 10 percent if prices remain low - will have a small impact on transportation
demand and carbon emissions.
Studies done in the 1970s and early 1980s of fuel price effects on fuel demand (Dahl, 1986) found
that fuel demand was very responsive to fuel price over the long term - that a 10 percent increase
in price would cause a drop in fuel use of approximately the same percentage. with half the drop
coming from improved vehicle efficiency and half from reduced travel. More recent estimates,
discussed in Plotkin and Greene (1997) project only about a 5 to 6 percent decrease in fuel use from
a 10 percent price increase. Thus, a 50 cents per gallon increase in gasoline price - about the level
added by the combination of carbon permit system and 2010 "Pay-at-the-Pump" (PATP) insurance
policy discussed below (added to a baseline $1.25/gallon) might be expected to reduce gasoline use
by perhaps 20 percent over the long run. The latter values reflect the full experience in gasoline
markets over the past three decades and should be more credible.
Cellulosic Ethanol Commercialization Program. The use of cellulosic ethanol in vehicles would be
extremely useful in reducing GHG emissions because, over the fuel cycle, such use generates a
small fraction of the emissions generated by the equivalent use of gasoline - about 10 or 20 percent
depending on assumptions. The DOE has an active research program aiming to develop
commercializable processes for producing ethanol from energy crops, forest and agricultural
residues, and municipal wastes (NREL, 1999). If successful, cellulosic ethanol would first be used
as a blending agent with gasoline, with added value as an octane enhancer and oxygenate, and then,
if priced low enough, as a neat fuel.
Current market incentives for ethanol use include exemption from most federal taxes on gasoline
for the ethanol portion of gasoline/ethanol blends, mandated oxygenate levels in Federal
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reformulated gasoline (RFG) required in ozone nonattainment areas (and other areas that have
joined the RFG program), alternative fuel fleet requirements mandated by EPACT, and CAFE
credits associated with the sale of alternative fucl vehicles. The latter two incentives affect vehicle
production and sales only, and do not currently have any effect on ethanol production.
In the scenarios, we envision full extension of the current "gasohol" tax break and a program of
loan guarantees, tax breaks, or subsidies to reduce or eliminate the added risk of investment in new
ethanol plants. In addition, we envision substantial reductions in the cost of cellulosic ethanol
production (to 50 percent of current corn ethanol costs (based on Bowman and Leiby. 1998 and
NREL, 1999) resulting from focused research on ethanol production processes associated with
increases in transportation R&D funding in both scenarios. Key research areas are:
1. improvement in pretreatment efficiency to minimize enzyme requirements,
2. development of less expensive enzymes,
3. improved plant design to minimize costs and improve efficiency,
4. continued development of specialized energy crops, and
5. research and surveys to identify lands best suited to growing energy crops
Tax Credit for High Efficiency Vehicles. A set of tax credits has been proposed for purchasers of
significantly more fuel-efficient vehicles. The proposed schedule is shown in Table 6.4, where
efficiency improvement levels are matched with vehicle technologies. The tax credits will be phased
out as sales increase much beyond 50,000 units per year.
Table 6.4 Schedule of High Fuel Economy Tax Credits and Associated Technologies
MPG Increase
Technology
Credit
1/3
Gasoline hybrid
$1,000
2/3
Diesel-electric
$2,000
Twice
Gasoline and methanol fuel cell
$3,000
Three times
Hydrogen fuel cell
$4,000
The modeled tax credits reflect the Administration's early tax proposals. The current
Administration proposal has changed the credits to reflect the "degree of electrification" of the
powertrain rather than the efficiency gain. We have not attempted to model this latest proposal.
Invigorated Government Fleet Programs. EPACT regulations require Federal and State vehicle
fleets and some private fleets (of alternative fuel suppliers) to introduce alternative fuel vehicles on
a rigorous schedule. AEO99 assumes that the EPACT schedules will be met. However, these fleets
are well behind schedule in their compliance, and few if any analysts believe that full compliance
will occur. Consequently, in accepting the AEO99 Reference Case as our Baseline Case, we are
implicitly assuming that a shift in government policy concerning fleet vehicle purchases will allow
full compliance; BAU would not yield compliance with EPACT schedules.
R&D Spending Increase. The Federal government, primarily the DOE, currently spends several
hundred million dollars annually in support of the development of advanced vehicle technology,
including fuel cells, hybrid drivetrains, advanced diesel power plants, advanced materials, and so
forth. Other agencies, e.g., Department of Transportation (DOT), National Aeronautics and Space
Administration (NASA), Department of Defense (DoD), and so forth, sponsor additional research in
other transportation areas. Traditionally, Federal R&D funding for aircraft and highway vehicle
technology has been much greater than in other areas, e.g., funding in rail and maritime freight
hauling has been minimal.
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The most prominent Federal transportation R&D program in recent years has been the PNGV. a
joint federal/industry program under which both partners have contributed about $300 million/year.
The NRC has concluded that the PNGV has made substantial progress in reaching its goal of an (up
to) 80 mpg family car, for example, the three industry partners now have prototype family-size cars
capable of about 60 mpg on the EPA test cycle. However, NRC also concluded that PNGV has
significant challenges remaining, in particular emissions and cost problems with direct-injection
engines, high costs for power electronics and electric motors, cost and performance problems with
high-power batteries for hybrid vehicles, and immature technology for multi-fuel processing for
fuel cells. The Council's overall conclusion is that the dollar amounts provided to the PNGV are
"far below the level needed to meet the challenges on a timely basis" (NRC, 1999). An increase in
funding for this and other highway vehicle programs under the auspices of DOE's Office of
Transportation Technologies (OTT) may allow better results from the ongoing R&D programs in
the form of earlier commercialization of new technologies, reduction in first costs, and increased
performance (in fuel economy and other consumer attributes). Similar increases in programs
under other federal agencies, e.g., NASA, DoD, DOT. etc. should provide similar results.
Box 6.2 describes some key characteristics of a 50 or 100 percent increase in Federal transportation
R&D spending.
Box 6.2 Increased Transportation R&D Investment
The Federal government currently spends several hundred million dollars per year on research
aimed primarily at improving energy efficiency and reducing GHG emissions in the transportation
sector. The U.S. DOE is a major sponsor of this R&D, with its OTT contributing $244 million to the
effort in FY99.
To be effective, a 50 or 100 percent increase in this federal transportation R&D budget will require
both a careful targeting of funds to critical research areas, and a gradual rampup of funds to allow
for careful planning, assembly of research teams, and expansion of existing research teams and
facilities. Well-focused and intelligently managed technology R&D programs average societal rates
of return on the order of 50 percent per year (PCAST, 1997). The Moderate and Advanced
scenario proposals envision a 5-year rampup time.
Examples of promising research areas for increased funding include:
Light Duty Highway Vehicles
Direct injection engines, particularly NOx after-treatment for GDI engines, NOx and PM
emissions reduction in CIDI engines.
Proton exchange membrane fuel cell systems, particularly reforming liquid fuels. hydrogen
storage options, contaminant removal from reformate, fuel cell balance of plant, and systems
integration.
High power energy storage systems for hybrids, including reactivation of research on
ultracapacitors and flywheels.
Power electronics and electric motors.
Advanced lightweight materials, particularly vehicle manufacturing technologies and vehicle
design.
Fuels, esp. lower cost, more energy-efficient production of cellulosic ethanol, hydrogen, and
clean liquid fuels from natural gas.
Advanced onboard storage technologies for hydrogen (see above) and natural gas.
Electric vehicle batteries, especially lithium polymer but also cost reduction and performance
enhancement of nickel metal hydride batteries, safety and electrolyte and cathode performance
for lithium-ion batteries.
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Medium-duty delivery vehicles and transit buses
Hybrid-electric drivetrains
Advanced TDI diesel engines, especially emission control.
Natural gas storage and system design
Advanced lightweight materials
Heavy-duty highway vehicles
Advanced diesel engines and emission controls
Advanced aerodynamic drag reduction technologies
Ultra-low rolling resistance tires
Accessory load reduction strategies
Low friction drivetrains
Air travel
Laminar flow control and other advanced aerodynamic technologies
Blended wing-body aircraft
Unducted fan engines
Thermodynamic improvements to turbine engines
NOₓ control technologies
Maritime
Compressed and liquefied natural gas onboard diesel-powered coastal vessels
Molten carbonate fuel cell propulsion, with liquefied natural gas as a fuel
PEM fuel cell propulsion with hydrogen fuel
Rail travel
Fuel cell propulsion systems
Advanced electric motors
Oxygen-enrichment systems for locomotive diesel engines
Advanced diesel engines
Advanced rail lubrication systems
Intermodal/rail competitiveness research, including improved door-to-door service
management and improved equipment management through advanced command, control,
communication, and information systems.
Sectoral analysis
Further development of the transport sector models in the National Energy Modeling
System
Telecommunications Programs. Telecommuting involves the substitution of telecommunications
services for commuting in the workplace; that is, workers would work out of home or satellite offices
and communicate with their offices via computers. The primary candidates for telecommuting
appear to be white collar workers with a managerial and professional specialty, or workers in sales
and clerical jobs, e.g., workers who deal primarily with creating, distributing, or using information
(OTA, 1994). Over 50 percent of U.S. jobs fit this description, e.g. upward of 70 million jobs could
theoretically be candidates for telecommuting. DOT projections indicate there could be as many as
50 million telecommuters by 2020 (U.S. DOT, 1993). Aside from commuting trips,
telecommunications will also affect other trip categories, e.g. shopping (internet sales, for example).
Although telecommuting will eliminate many work trips, it can have "take back" effects such as
stimulation of sprawl (workers can live in rural areas if they don't commute, or commute only once
or twice a week). Further, telecommuting clearly will have different receptions from workers
depending on their family situations, personalities, and other factors. At moderate levels of
telecommuting, and where it is largely voluntary, telecommuting's reception should be quite positive
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since it allows workers freedom from commuting and greater flexibility in dealing with family
requirements. On the other hand, some analysts believe that there may be a backlash to increased
telecommuting due to negative impacts on workers including lack of communication, social
isolation, loss of benefits, lack of career advancement, and stress from mixing work and home life
(OTA, 1994). Obviously, the design of the specific programs will have a great impact on the
willingness of workers to participate.
A 1994 DOE study on the direct and indirect impacts of expanded telecommuting estimated that, by
2010, telecommuting could save about one percent of total motor fuel use (Greene, et al, 1994). The
DOE study adopted the earlier DOT study's estimate of 30 million telecommuters by 2010,
telecommuting 3 to 4 days per week, and assumed that 80 percent of them would be working at
home. Although the direct impact of this level of telecommuting was estimated to be the avoidance
of nearly 70 billion miles of commuting per year, DOE estimated that about half of the potential fuel
savings would be lost to increases in travel demand due to improved traffic flow and the travel
impacts of increased urban sprawl caused by the telecommuting.
Some public policy measures have been proposed to promote telecommuting, notably Regulation
XV, proposed by the Southern California Air Quality Management District in 1987 but not enacted,
that would have required larger employers (with over 100 employees) to adopt plans for alternative
commuting options, and the travel demand management funding provided by ISTEA at the Federal
level (OTA, 1994). Policies that would promote telecommuting include eased IRS provisions to
allow "teleworkers" to more easily deduct computer and telecommunications equipment as a
business expense on personal income taxes, and tax credits for businesses' startup costs for
telecommuting programs, e.g., worker training and equipment costs. Policy changes at the local
level include easing of restrictions on home-based work and amendment of zoning requirements to
allow a reduction in the minimum number of parking spaces in office buildings, to account for
telecommuting (OTA, 1994).
Intelligent Traffic Systems Controls. Intelligent traffic systems controls, including intelligent
roadway signing, staggered freeway entry, and electronic toll collection, are being introduced into
U.S. cities, and their use is expanding. In the Advanced scenario, both increased R&D and
government investment in these systems above anticipated levels lead to a wider range of systems
available and faster expansion of their use.
Voluntary Agreements. As discussed more extensively in the Industry chapter, voluntary
agreements are "agreements between government and industry to facilitate voluntary actions with
desirable social outcomes." Such agreements are more common outside of the United States; the
most relevant for this case is the agreement between the European automobile manufacturers'
association, ACEA, and the European Union to cut carbon dioxide emitted from car exhausts by 25
percent/vehicle over the next 10 years (EC & ACEA, 1999). This pledge would increase average
new car fuel efficiency from 30.6 mpg today to 40.7 mpg by 2008. Among the car companies
agreeing to this are subsidiaries of American manufacturers. In the Advanced scenario, we
assume that all manufacturers of light-duty and heavy-duty highway vehicles will commit to
voluntary standards to increase fuel economy. The light-duty standards are 40 mpg in 2010 and 50
mpg in 2020 for automobiles, and 26 mpg in 2010 and 33 mpg in 2020 for light trucks. Heavy-duty
standards are not specified at this time.
Obviously, the precise form of any voluntary standards would be determined in negotiations
between the industry and the Federal government. We presume that such standards would allow
"trading" of mpg credits among companies and would make no distinctions between domestic and
import flects, to avoid market distortions. Whether standards are in the form of a single target value
applying to every company or a variable target that accounted for market segment differences
among companies would affect the identify of "winners and losers" among the companies, but
would likely not affect the industry-wide outcome very much.
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"Variabilization" Policies. The objective of variabilization policies is to transfer the incidence of
what are currently fixed costs of motor vehicle operation to variable costs. Perhaps the most
significant of these proposed policies is "Pay-at-the-Pump" (PATP) automobile insurance. If only
about one-fourth of the total cost of automobile insurance were variabilized by means of a tax on
gasoline, it would amount to $0.25 to $0.50/gallon additional cost. Other potential targets of
variabilization are free parking, or road revenues currently raised by property or general sales
taxes. We propose to focus in this analysis on PATP, as representative of this class of policies
because it produces a substantial change in fuel prices and is readily modeled in NEMS.
Numerous variations on the basic idea of PATP have been proposed (El-Gassier, 1990; Sugarman.
1991; Dougher and Hogarty, 1994; Gruenspecht et al., 1994; Khazzoom, 1997) with the intent to
approximate a per-mile insurance fee by means of a surcharge on gasoline. Since at least some of
the risk drivers impose on other travelers is proportional to miles driven, PATP could effectively
internalize at least a portion of a public safety externality, thereby increasing economic efficiency
(Kavalec and Woods, 1997). Whether this can be achieved depends on a number of complex
factors, including the efficiency of the existing system. Charging per gallon is an imprecise way of
charging per mile because of the large variation in mpg across the vehicle fleet. On the other hand,
larger, heavier vehicles, which generally represent the less fuel-efficient portion of the fleet, impose
greater risks on other travelers and thus should pay larger insurance premiums. To date, these
issues remain largely unresolved. However, one clear benefit of PATP will be an elimination of
some part of the problem of uninsured drivers, since PATP can automatically provide partial
coverage to all drivers.
Our design for the PATP fee is simple. For the year 2003 to 2012, a surcharge of $0.34 per gallon
of gasoline equivalent energy is added to the price of all motor fuels. From 2013 on, the surcharge
is increased in one large step to $0.51 per gallon of gasoline equivalent energy to roughly correct
for the increasing efficiency of the light-duty vehicle fleet.
6.3.2 Barriers to Energy Efficiency
Barriers to increased energy efficiency and reduced GHG emissions in transportation energy use
include external costs and benefits, imperfect information, and imperfect competition. Fuel prices
and transportation services do not reflect total social costs such as air pollution and climate change.
Uncertainty about the costs and benefits to consumers of increased efficiency, caused by
uncertainty about future fuel prices and a lack of explicit information about the incremental costs of
higher efficiency may lead to under-investment in fuel economy technology. The inability of
companies to capture the full benefits of advances in the science and technology of efficiency leads
to under-investment in R&D. And the financial risks to manufacturers posed by the introduction of
new technologies requiring substantial design changes that may or may not be well received by
consumers can lead to the under-adoption of new technology in an oligopolistic market.
Underpriced Fuels and Transportation Services. A strong case can be made that energy fuels are
underpriced, because market prices do not take full account of a variety of social costs associated
with fuel use, and especially oil use (transportation is 95 percent dependent on petroleum products
for fuel). Those externalities most directly tied to fuel use are greenhouse gases from direct fuel
use by vehicles; air, water, and land pollution, including greenhouse gases, associated with
discovering, extracting, processing, and distributing gasoline and other transportation fuels; and the
energy security and economic impacts associated with the uneven geographic distribution of oil
resources, that is, military expenditures associated with Persian Gulf political instability; monopsony
costs associated with artificially high oil prices; and the costs to the U.S. and world economies
associated with occasional oil price shocks.
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Transportation services also are underpriced, for reasons that include but go beyond underpriced
transportation fuels. Social costs more closely tied to transportation services than to energy use
include air pollution - excluding greenhouse gases - associated with vehicle use, environmental
impacts associated with transportation infrastructure, societal costs associated with transportation
accidents (especially on the highways), the costs of highway congestion, and so forth. These costs
as well as the costs of petroleum use in transportation have been examined by a number of analysts,
most notably Delucchi (1997), and for the United States probably run into the hundreds of billions of
dollars annually.
Imperfect Information. In making vehicle purchases, consumers and businesses experience
difficulty in making rational choices about trading off the costs and benefits of different levels of
energy efficiency. One cause is the difficulty in determining the true costs of higher efficiency
despite the information on fuel economy posted on new autos and light trucks. Vehicle purchasers
are rarely given explicit choices in efficiency coupled with explicit price differences associated with
these choices. Instead, these price differences are buried in base prices or in the price of complete
subsystems such as engines, with efficiency differences always coupled with substantive
differences in other critical consumer attributes such as acceleration performance, level of luxury,
vehicle handling, and so forth. Additionally, properly trading off fuel savings versus changes in
vehicle price involves trading off the time-discounted value of the fuel savings against the present
cost of the vehicle - a calculation that many vehicle purchasers are not familiar with. Note,
however, that if consumers were extremely concerned about energy savings and determined to
base their purchasing decisions on them, automakers and dealers would have a strong incentive to
provide them with the information that is now lacking in the marketplace, as well as with vehicle
choices that provided clearer tradeoffs. It can be argued that the lack of such information and
choices is simply the consequence of consumer disinterest in improved fuel economy in the context
of low fuel prices.
It is also worth noting that new car purchasers - who have a dominant influence on the design
decisions of automakers - are not representative of the driving public, many of whom purchase
their vehicles secondhand. In particular, new car purchasers are substantially wealthier than
average drivers, which should skew their purchase preferences away from considerations of fuel
use and towards considerations of ride quality, power, and other vehicle qualities.
Another potential source of difficulty in making rational vehicle choices is the substantial
uncertainty associated with future fuel prices. Over the past two decades, the price of a barrel of oil
has varied by fourfold, reaching highs in the early 1980s and lows within a few years thereafter.
Recently, oil prices have been near historic lows, but energy analysts widely acknowledge that
disturbances to oil markets could cause future prices to escalate rapidly to multiples of today's
prices (and stay there for periods ranging from a few weeks to a few years). Also, there is growing
controversy about the potential for oil resource shortages, coupled with higher prices, possibly
beginning within the lifetime of most vehicles purchased today.
Difficulty in Capturing the Market Benefits of Technology Advances. Another barrier to firms'
investments in research to develop energy efficient technology is the ability of other firms to
appropriate technological advances. By this we mean that increases in knowledge of new designs
and technology are easily transferred to other industry entities without necessarily benefiting the
individuals or company that provided the research investment that lead to the innovation. Further,
companies that absorb the market risk of introducing new technology generally will not reap the full
benefits of trailblazing new markets because the attention and car owner trust brought about by a
successful market launch may be transferable to a competitor's version of the new technology.
Both attributes tend to yield under-investment in technology development and reluctance to
introduce new technologies in areas where markets are not well established.
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Risks to Manufacturers. Redesigning motor vehicles for substantial fuel economy improvements
requires massive capital investments. In an intensely competitive car market a negative reaction by
consumers, even to subtle aspects of a new technology, could result in massive financial losses to
manufacturers. Manufacturers will therefore be understandably reluctant to commit to rapid,
sweeping design changes to improve fuel economy, a matter of relatively small concern to
motorists.
Table 6.5 outlines the programs and policies adopted in the two scenarios, and the barriers they
address.
6.4 METHODOLOGY FOR ANALYZING POLICY IMPACTS
This section outlines the methods used to translate the policies of the Moderate and Advanced
scenarios to inputs and changes to the CEF-NEMS model. A detailed description of each
modification to NEMS input data or source code can be found in Appendix A-3.
6.4.1 Policy: Air Traffic Management Improvements
This policy is expected to achieve a five percent reduction in air traffic fuel use. This is simulated
by increasing the rate of increase in the efficiency of existing stock, an effect historically due
primarily to retrofitting existing airframes with newer, more efficient engines. The intention here is
to reflect a general improvement in aircraft operating efficiency due to more effective flight
planning and reductions in excessive time spent waiting in the air or waiting on the ground due to
traffic congestion. Specifically, the annual rates of change in fleet-wide efficiency were increased
from 0.18 percent to 0.34 percent for wide-body aircraft, and from 0.44 percent to 0.60 percent for
narrow-body planes.
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Table 6.5 Policies to Address Barriers to Efficiency Improvements in Transportation
Barriers to Efficiency Improvement
Underpriced
Underpriced
Rationa
Technology
Manufacturers
Policies
Scenari
Fuels
services
I
fungibility
risk
o
choices
R&D
Both
X
X
X
spending
increase
Voluntary
Advance
X
X
X
agreements
d
PATP
Both
X
X
Tax credits
Both
X
X
X
for efficient
vehicles
Air traffic
Both
X
X
mgmt
Government
Both
X
X
X
fleets
Cellulosic
Both
X
ethanol
Emissions
Both
X
X
X
X
and fuels
standards
Cap and
Advance
X
trade
d
Tele-
Both
X
commuting
Intelligent
Advance
X
X
Traffic
d
Systems
6.4.2 Carbon Permit Program
The carbon permit program is implemented at the national, multi-sector level, not within the
transportation sector modules. The procedure is described in Chapter 3. A charge of $50 per
metric ton of carbon is imposed as a way of simulating the effect of a tradable permit program.
6.4.3 Cellulosic Ethanol Commercialization Program
Several key assumptions were added to NEMS to reflect the success of research to reduce the costs
of cellulosic ethanol and programs to promote its use. The AEO99 Reference Case continues tax
credits for ethanol but in nominal dollars so that the value of the credits in constant dollars
decreases gradually with time. We retain this assumption in all scenarios. The AEO99 also
includes risk premiums for investment in cellulosic ethanol production to reflect the uncertainties
associated with the market for a new fuel supported, in part. by government subsidies. We assume
that a loan guarantee or subsidy program is created by the federal government to eliminate these
added risks, so that funds can be borrowed for investment in ethanol production at prime rates.
Finally, the AEO99 assumes that by 2020 the costs of producing ethanol from cellulose can be
reduced by 20 percent over the current costs of production from corn. We assume that a 50
percent cost reduction is possible by 2020, more in line with the goals of the DOE's R&D program.
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6.4.4 Tax Credit for High Efficiency Vehicles
The tax credit was implemented in NEMS by reducing the low-volume prices of alternative fuel
vehicles by the amounts indicated in Table 6.4 above. In matching low-volume prices only, we are
assuming that the tax credits will be phased out as sales increase much beyond 50,000 units per
year. The gasoline hybrid is an exception, since it is handled by the FEM subroutine rather than
the AFVM. The FEM does not allow for phasing out of the credit with increasing sales volume, and
so the $1,000 credit is maintained throughout.
6.4.5 Invigorated Government Fleet Programs
The principal effect of invigorated government fleet programs for alternative fuel vehicles is
reflected in increased retail availability of alternative fuels. The availability of alcohol fuels and
hydrogen were increased gradually from negligible levels today to 50 percent by 2020. Details are
provided in Appendix A-3.
6.4.6 R&D Spending Increase
The effect of increased spending on research, development, and demonstration is represented by:
1. Advancing the introduction dates for new technology (for light-duty vehicles by 30 percent in
the Moderate case and, with the additional incentive of the voluntary standards for higher fuel
economy, by 40 percent in the Advanced case),
2. Adding a few new technologies (two advanced materials technologies for light-duty vehicles, two
new technologies for heavy-duty vehicles, and a wing-body aircraft design for the air mode),
3. Incrementally reducing the cost, and
4. Increasing the mpg performance of selected technologies.
Details of the changes made to the original NEMS assumptions are provided in Appendix A-3.
NEMS currently has the capability of modeling a large but not unlimited number of fuel efficiency
technologies. There are technologies we have not modeled, and within those modeled, only some
are assumed to undergo significant price reductions under the Moderate and Advanced scenarios.
This is not to imply that we have perfect foresight of which technologies will be commercially
successful, and which will respond substantially to increases in research emphasis. Clearly we do
not, and we imagine that, were the societal conditions and policies postulated in the scenarios
actually to come about, the U.S. fleet of transportation vehicles would be far from a perfect match of
the fleet characteristics projected by CEF-NEMS in this exercise. While we have made our
technology assumptions with care, we recognize that some we have included will not be realized
while others we have excluded will succeed in the marketplace. It is entirely possible, for example,
that significant improvements in natural gas vehicle storage technologies, coupled with changes in
gas availability and other factors, could lead to a far greater penetration of the fleet by natural gas
vehicles than is projected here. Similarly, a breakthrough in lithium-polymer battery technology,
perhaps coupled with greater-than-expected cost reductions in power electronics and electric
motors, could lead to a larger penetration of the fleet by electric vehicles. And inadequate progress
in emission controls for diesel vehicles, or further tightening of fine particulate matter standards
based on new health effects research or greater demands by the public, could lead to far smaller
penetration of diesel technology (we explore this possibility in a "no diesel" sensitivity run of the
Advanced scenario, below). We cannot overcome these uncertainties. However, as noted earlier,
there exists a large enough portfolio of promising efficiency technologies to provide some
comforting redundancy. By using the great deal of information available about the status of the
technology portfolio and the historic record of technological progress for similar technologies, we
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believe we can make a reasonable estimate of the likely overall effect of increased R&D even if we
get the precise details wrong.
6.4.7 Telecommuting Programs
As discussed previously, the 1999 AEO vmt projection reflects a rate of growth (1.6 percent/yr.) that
is quite low by historical standards (3.1 percent from 1970-96; 3.0 percent from 1986-96), and we
believe a higher rate, perhaps closer to 2.0 percent, would be more realistic. In a sense, then, it
could be argued that some transportation demand management programs, including telecommuting
programs, are already implicitly included in the Reference Case. And even given the
implementation of vmt reduction programs that could credibly be implemented under the definitions
of the Moderate and Advanced scenarios, we are skeptical that they could reduce vmt enough to
achieve the EIA 1.6 percent rate of increase. Thus, we have chosen not to further reduce this rate
in the scenarios, but simply to consider the 1.6 percent rate in the two policy scenarios to be
somewhat more realistic than the same rate in the Reference Case.
6.4.8 Intelligent Traffic Control Systems
To simulate the effect of increased usage of ITS systems in the Advanced scenario, we reduced by
one percentage point the degradation factor in NEMS that translates EPA values of fuel economy
into "on-road" values. The factor accounts for congestion and other factors that increase fuel
usage over the value that would be computed using the EPA values.
6.4.9 Voluntary Agreements
In the advanced case only, voluntary fuel economy targets are implemented with changes to NEMS
inputs intended to simulate greater manufacturer attention to fuel economy relative to other vehicle
attributes. The dates for first introduction of future fuel economy technologies were foreshortened
by 40 percent. However, no date was moved closer to the present than 2003. The weight increases
projected in the AEO99 Reference Case (20 percent for passenger cars and 30 percent for light
trucks) were reduced to actual increases through 1998 for both vehicle types. In addition, for the
Moderate scenario, the AEO99 factors that relate the demand for performance to changes in
vehicle horsepower were changed to (lower) factors developed by Energy and Environmental
Analysis, Inc. (EEA), which helped develop this version of NEMS; for the Advanced scenario, the
EEA factors were cut in half to reflect the pressure on automakers to restrict power increases in
order to be able to comply with the Voluntary Agreement. As a result, in both scenarios, the
demand for larger engines was considerably reduced, though horsepower increases were still
allowed through 2020. Given the substantial reductions in vehicle weight in this scenario, there is
still scope for significant increases in performance as measured by the ratio of horsepower to
weight. Similar changes were made to accelerate the introduction of fuel economy technology in
heavy-duty vehicles, as described in detail in Appendix A-3.
Finally, the EIA Reference Case assumption that consumers estimate the value of fuel economy
based on only the first four years of fuel savings, discounted to present value at 8 percent real, was
changed to a discounting of fuel savings over the full 12 years of expected vehicle life at a 15
percent per year, real discount rate. The function of these parameters in the NEMS models is to
represent manufacturers' decisions about how consumers will perceive the value of fuel economy,
rather than to actually represent consumers' decision-making. Thus, these changes are intended
to reflect changes in manufacturers' willingness to adopt fuel economy technology driven by their
commitment to a Voluntary Agreement rather than a change in consumers' attitudes towards
higher mpg.
6.4.10 "Variabilization Policies" (Pay-at-the-Pump Insurance)
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For the Advanced scenario only, variabilization policies were simulated by adding a Pay-at-the-
Pump insurance surcharge to all motor fuels. This surcharge pays for a minimum level of liability
insurance for all motor vehicles, leaving the net cost of highway travel roughly constant. What is
usually paid as part of an annual or semi-annual fixed cost, now is "variabilized" and paid for with
the purchase of fuel.
6.4.11 New CAFE Standards (Sensitivity Case)
The NEMS Transportation Sector Model permits the specification of alternative CAFE standards
for passenger cars and light trucks. 3 We specified identical standards for domestic and imported
vehicles, and set the non-compliance fine to $150 per mpg by which a manufacturer's corporate
average fuel economy falls below the standard. If one of the vehicle categories fails to meet the
standard in any year, NEMS adds the fine to the dollar value of higher fuel economy in its
technology selection subroutine, increasing the market penetration of fuel economy technologies.
In addition, NEMS advances the first date of technology adoption by one year, to reflect the belief
that manufacturers faced with a known standard will accelerate the introduction of technologies, if
necessary.
The CAFE constraint operates only on the NEMS submodel dealing with gasoline-fueled vehicles;
alternative fueled vehicles are treated separately in NEMS. This means that obtaining a given level
of fleetwide fuel economy requires some trial and error, because typically the part of the fleet that is
alternatively fueled will have a different average fuel economy than the gasoline-fueled fleet. For
example, obtaining a 65 mpg CAFE for the automobile fleet required the use of a 55 mpg target
CAFE in the gasoline vehicle submodel.
6.5 SCENARIO RESULTS
6.5.1 Moderate Scenario
In the Moderate scenario, primary energy consumption increases from 25.0 Quads in 1997 to 34.1
Quads in 2020, a 36.4 percent increase or about 7 percent less than the energy consumption
projected in the Baseline Case. Similarly, carbon emissions increase from 478 MtC in 1997 to 646
MtC in 2020, a 35.1 percent increase and about 7 percent less than in the Baseline Case.
Table 6.6 presents the 10-year results in travel, energy efficiency, and energy consumption for the
several transportation modes, and energy consumption by fuel type. Table 6.7 presents carbon
emissions by mode and fuel type.
The seven percent drop (from the Baseline) in energy consumption and carbon emissions has a
few key components:
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Table 6.6 Results of Moderate Scenario
1997
2010
2020
Level of Travel by Mode (Billion)
Light Duty Vehicles (vehicle miles traveled)
2301
2892
3320
Commercial Light Trucks (vehicle miles
69
91
104
traveled)
Freight Trucks (vehicle miles traveled)
178
245
272
Air (seat miles demanded)
1050
1818
2471
Rail (ton miles traveled)
1235
1508
1664
Marine (ton miles traveled)
757
882
967
Energy Efficiency Indicator by Mode
New Vehicle (MPG)
24
27.4
30.5
New Car (MPG)
27.9
34.7
38.0
New Light Truck (MPG)
20.2
22.1
24.8
Light-Duty Fleet (MPG)
20.5
20.9
23.3
New Commercial Light Truck (MPG)
19.9
21.1
23.5
Stock Commercial Light Truck (MPG)
14.6
15.3
16.5
Aircraft (seat miles/gallon)
51.1
56.7
62.6
Freight Truck (MPG)
5.6
6.5
7.6
Rail (ton miles/kBtu)
2.7
3.1
3.5
Site Energy Use by Mode (Quadrillion Biu)
Light-Duty Vehicles
13.9
17.7
18.2
Commercial Light Trucks
0.6
0.7
0.8
Freight Trucks
4.2
5.0
4.8
Air
3.4
5.1
6.1
Rail
0.5
0.6
0.6
Marine
1.3
1.6
2.0
Pipeline Fuel
0.7
0.8
0.9
Other
0.2
0.3
0.3
Total
24.9
31.9
33.7
Energy Use by Fuel Type (Quadrillion Biu)
Distillate Fuel
4.6
5.7
6.1
Jet Fuel
3.3
5.0
6.0
Motor Gasoline
15.1
18.1
17.8
Residual Fuel
0.8
1.0
1.3
Liquefied Petroleum Gas
0.0
0.1
0.2
Other Petroleum
0.3
0.3
0.4
Petroleum Subtotal
24.10
30.38
31.75
Pipeline Fuel Natural Gas
0.7
0.8
0.9
Compressed Natural Gas
0.0
0.2
0.3
Renewables (E85)*
0.0
0.1
0.2
Methanol
0.0
0.2
0.3
Liquid Hydrogen
0.0
0.0
0.0
Electricity
0.1
0.2
0.2
Total Site Energy
24.9
31.9
33.6
Electricity Related Losses
0.1
0.3
0.5
Total Primary Energy
25.0
32.2
34.1
*The CEF-NEMS model reports renewables blended with gasoline as "Motor Gasoline." For an accounting
of cellulosic ethanol blended with gasoline, please see the discussion in section 6.5.1.
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Table 6.7 Transportation Carbon Emissions: Moderate Scenario
(million metric tons C)
1997
2010
2020
Carbon emissions by mode (MiC)
Light Duty Vehicles (vehicle miles traveled)
267.0
337.6
348.0
Commercial Light Trucks (vehicle miles
11.3
14.2
15.2
traveled)
Freight Trucks (vehicle miles traveled)
82.4
95.3
91.0
Air (seat miles demanded)
63.3
97.5
117.2
Rail (ton miles traveled)
12.3
13.6
14.2
Marine (ton miles traveled)
27.3
33.5
40.6
Pipeline Fuel
10.6
12.1
12.7
Other
3.8
7.2
7.1
Total
477.9
611.0
646.0
Carbon emissions by fuel type (MiC)
Other
91.6
113.4
121.5
Jet Fuel
63.3
96.7
116.4
Motor Gasoline
289.7
347.5
340.3
Residual Fuel
15.9
21.7
27.6
Liquefied Petroleum Gas
0.7
2.3
2.7
Other Petroleum
3.0
3.6
3.9
Petroleum Subtotal
464.1
585.1
612.5
Pipeline Fuel Natural Gas
10.6
12.1
12.7
Compressed Natural Gas
0.2
3.0
3.8
Renewables (E85)*
0.0
0.0
0.0
Methanol
0.0
2.9
5.3
Liquid Hydrogen
0.0
0.0
0.0
Electricity
3.0
7.8
11.7
Total
477.9
611.0
646.0
Greater improvement in light-duty fuel economy. Light-duty fleet mpg improves by 2.8
versus 0.9 in the BAU scenario (Table 6.6). This results primarily from the estimated
efficiency improvements and cost reductions achieved by the 50 percent increase in
R&D funding in the Moderate scenario. The model year 2020 mpg values attained are,
respectively, 38.0 mpg (versus 32.1 mpg in the Baseline scenario) for autos and 24.8
mpg (vs. 22 mpg) for light trucks.
Improved freight truck efficiency. Freight truck mpg rises to 7.6 mpg in 2020 from 5.6
mpg in 1997 (vs. 6.3 mpg in the Baseline), yielding a 16 percent reduction in freight
truck fuel consumption in 2020 (Table 6.6). This improvement results from the
vigorous R&D push for advanced heavy duty diesel technology, as well as a variety of
other technologies.
A modest drop in projected air travel energy use from improvements in operational
efficiency, resulting from a more rapid implementation of current plans for operational
advances.
The light-duty fleet experiences significant changes in composition from the baseline fleet. In
particular, diesel sales increase substantially - for 2020, over 2,100,000 vehicles/yr in the Moderate
scenario VS. less than 200,000/yr in the Baseline scenario. Also, alternative fuel vehicles expand
much more rapidly than in the Baseline. By 2020:
Alcohol flex-fuel ICEs sell 1,175,000 units/yr VS. about 317,000/yr in the Baseline
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Alcohol ICEs sell 350,000/yr VS. 92,000/yr
Both diesel-electric hybrids and fuel cell vehicles of all types play essentially no role, VS.
a modest role (e.g., 29,000 diesel electric hybrids sold/yr in 2010) in the Baseline. This is
a result of changes to the NEMS Alternative Fuel Vehicles model parameters (see
Appendix A-3 for details) rather than a result of changed conditions in the scenario.
Cellulosic Ethanol - Moderate. When the cost of cellulosic ethanol begins to decline after 2005,
ethanol use increases rapidly (Figure 6.6). While some of the ethanol is used as a neat fuel,
primarily by flexible-fuel cars and light trucks, the vast majority is blended with gasoline to increase
its octane and oxygen content. Light-duty vehicles consume 16.50 quads of motor "gasoline" in the
Moderate Case in 2020, of which 0.46 quads (2.8 percent) is actually ethanol. Because of ethanol's
lower energy content per volume, 4.1 percent of gasoline is ethanol, by volume. These projections
do not take into account the potential impacts of a ban on MTBE, which could greatly increase
demand for ethanol as a gasoline blending stock.
Fig. 6.6 Use of Ethanol for Motor Fuel
MODERATE CASE
8
7
6
Billions of Gallons
5
4
3
2
1
0
1995
2000
2005
2010
2015
2020
6.5.2
Advanced
Scenario
In the Advanced scenario, primary energy consumption increases from 25.0 Quads in 1997 to 28.9
Quads in 2020 (Table 6.8), a 16 percent increase; the 2020 transportation energy consumption is
about 21 percent less than the Baseline 2020 value. Carbon emissions increase from 478 MtC in
1997 to 545 MtC in 2020, a 14 percent increase; the 2020 emissions are about 23 percent less than
in the Baseline. The slightly smaller percentage increase in carbon emissions than in energy
consumption implies that the Advanced scenario has managed to reduce carbon intensity somewhat
from the level in the Baseline scenario, due to increased use of cellulosic ethanol and other
alternative fuels.
Table 6.8 presents the 10-year results in travel, energy efficiency, and energy consumption for the
several transportation modes, and energy consumption by fuel. Table 6.9 breaks down carbon
emissions by mode and fuel type.
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Table 6.8 Results of the Advanced Scenario
1997
2010
2020
Level of Travel by Mode (Billion)
Light Duty Vehicles (vehicle miles traveled)
2301
2829
3184
Commercial Light Trucks (vehicle miles
69
90
103
traveled)
Freight Trucks (vehicle miles traveled)
178
246
273
Air (seat miles demanded)
1067
1781
2425
Rail (ton miles traveled)
1237
1345
1421
Marine (ton miles traveled)
758
883
968
Energy Efficiency Indicator by Mode
New Vehicle (MPG)
24
32.8
41.6
New Car (MPG)
27.9
41.5
51.4
New Light Truck (MPG)
20.2
26.4
33.9
Light-Duty Fleet (MPG)
20.5
22.8
28.3
New Commercial Light Truck (MPG)
19.9
24.3
29.2
Stock Commercial Light Truck (MPG)
14.6
16
18.7
Aircraft (seat miles/gallon)
52
59.9
65.8
Freight Truck (MPG)
5.6
6.8
9
Rail (ton miles/kBtu)
2.8
3.4
3.9
Site Energy Use by Mode (Quadrillion Btu)
Light-Duty Vehicles
13.9
15.9
14.4
Commercial Light Trucks
0.6
0.7
0.7
Freight Trucks
4.2
4.8
4.0
Air
3.4
4.8
5.8
Rail
0.5
0.5
0.5
Marine
1.3
1.6
2.0
Pipeline Fuel
0.7
0.9
0.9
Other
0.2
0.3
0.3
Total
24.9
29.5
28.6
Energy Use by Fuel Type (Quadrillion Biu)
Distillate Fuel
4.6
5.9
5.7
Jet Fuel
3.3
4.7
5.7
Motor Gasoline
15.1
16.1
13.7
Residual Fuel
0.8
1.0
1.3
Liquefied Petroleum Gas
0.0
0.1
0.1
Other Petroleum
0.3
0.3
0.4
Petroleum Subtotal
24.10
28.13
26.83
Pipeline Fuel Natural Gas
0.7
0.9
0.9
Compressed Natural Gas
0.0
0.2
0.2
Renewables (E85)*
0.0
0.0
0.0
Methanol
0.0
0.1
0.2
Liquid Hydrogen
0.0
0.0
0.1
Electricity
0.1
0.2
0.2
Total Site Energy
24.9
29.5
28.5
Electricity Related Losses
0.1
0.3
0.4
Total Primary Energy
25.0
29.8
28.9
*The CEF-NEMS model reports renewables blended with gasoline as "Motor Gasoline." For an accounting
of cellulosic ethanol blended with gasoline, please see the discussion in section 6.5.1.
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Table 6.9 Transportation Carbon Emissions: Advanced Scenario
1997
2010
2020
Carbon emissions by mode (MiC)
Light Duty Vehicles (vehicle miles traveled)
267.0
304.5
274.3
Commercial Light Trucks (vehicle miles
11.3
13.4
13.1
traveled)
Freight Trucks (vehicle miles traveled)
82.4
91.7
76.5
Air (seat miles demanded)
63.3
91.4
110.2
Rail (ton miles traveled)
12.3
11.5
10.9
Marine (ton miles traveled)
27.3
33.3
40.2
Pipeline Fuel
10.6
12.2
13.1
Other
3.8
7.0
6.6
Total
477.9
565.1
544.9
Carbon emissions by fuel type (MIC)
Other
91.6
116.0
113.3
Jet Fuel
63.3
90.6
109.4
Motor Gasoline
289.7
308.2
261.9
Residual Fuel
15.9
21.6
27.5
Liquefied Petroleum Gas
0.7
2.1
2.2
Other Petroleum
3.0
3.6
3.9
Petroleum Subtotal
464.1
542.1
518.2
Pipeline Fuel Natural Gas
10.6
12.2
13.1
Compressed Natural Gas
0.2
2.8
3.2
Renewables (E85)*
0.0
0.0
0.0
Methanol
0.0
1.8
3.0
Liquid Hydrogen
0.0
0.0
0.0
Electricity
3.0
6.2
7.4
Total
477.9
565.1
544.9
The 21 and 23 percent drops (from the Baseline) in energy consumption and carbon emissions,
respectively, have the following components:
Improvements in light-duty fuel economy. The on-road fuel economy of the fleet
improves by 7.8 mpg by 2020, VS. 0.9 mpg in the Baseline (Figure 6.7). New car mpg
(Figure 6.8) increases to 51.4 mpg by 2020 (vs. 32.1 mpg Baseline) and light truck mpg
(Figure 6.9) increases to 33.9 mpg (vs. 22.0 mpg). These increases in fuel economy
result from the combination of Voluntary Agreements, tax credits for high efficiency
vehicles (as originally proposed by the Administration), a significant economic incentive
afforded by the increase in gasoline prices associated with carbon credits and the PATP
price add-on, and technology cost reductions and performance improvements
associated with a doubling of the R&D budget.
Freight truck efficiency gains. Freight truck efficiency rises to 9 mpg in 2020 from
about 5.6 mpg in 1997, VS. 6.3 mpg in the 2020 Baseline and 7.6 mpg in the 2020
Moderate scenario. This yields a 30 percent reduction in energy consumption from the
2020 Baseline and a 17 percent reduction from the Moderate scenario results.
Further modest improvements in aircraft and rail energy efficiency.
A drop in railroad freight movement. From the Baseline level of 1,698 billion ton miles
in 2020 rail freight traffic decreases to 1426 billion ton-miles in the Advanced scenario
due to reduction in coal use, and therefore shipments to power plants.
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Inter
estin
g changes in the light-duty fleet composition occur in the Advanced scenario, including:
Fuel cell vehicles achieve a significant market share after 2015 (Figure 6.10). In 2020,
2.2 million fuel cell passenger cars and light trucks are sold in the Advanced scenario
(10 percent of light-duty vehicles sold that year). About 0.9 million are passenger cars
while 1.3 million are light trucks.. By 2020 there are 9.4 million fuel cell vehicles in a
total population of 255 million light-duty vehicles.
Hydrogen fuel cell vehicles, which according to our assumptions are cheaper and more
energy efficient, are the most successful, accounting for 1.0 million of the 2.2 million
total sales in 2020. In 2020, there are 3.9 million hydrogen fuel cell vehicles on the road
consuming 0.1 quads of hydrogen annually.
Hybrid vehicles have an earlier impact, accounting for 13 percent of light-duty vehicle
sales in 2010 and 15 percent in 2020.
Even in 2020, the 47 percent of new light-duty vehicles are powered solely by gasoline
internal combustion engines.
TDI diesels continue to play a major role in the light-duty vehicle fleet, with sales
exceeding 1 million after 2005 and standing at 2.6 million per year in 2020. By 2020,
there are 30 million TDI diesel light-duty vehicles on the road which, together with 7
million diesel-electric hybrids, comprise almost 15 percent of the light-duty vehicle
population.
Diesel-electric hybrids achieve a modest market share early on, and retain it through
2020. New light-duty vehicle sales exceed 350,000 by 2007, peak at over 700,000 in
2013, and decrease to just over 380,000 in 2020 as the fuel cell vehicles begin to
succeed.
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The enormous growth of vehicle horsepower is restrained in the Advanced scenario. In
1998, the average horsepower of new passenger cars sold in the United States was 155
(NHTSA, 1999). In the BAU case, passenger car horsepower increases to 251 by 2020
(Figure 6.11). Light truck horsepower increases even more, from 189 in 1998 to 293 in
2020. The Advanced Case foresees much more modest increases, to 174 hp for cars
and 199 hp for light trucks. However, vehicle weight decreases in the advanced
scenario by about 12 percent for passenger cars, so that vehicle acceleration
performance would still be about 25 percent faster than today's cars.
Cellulosic Ethanol - Advanced. Use of ethanol for motor fuel increases from 1.1 billion gallons in
1999 to 3.9 billion in 2010, to 6.4 billion gallons in 2015, and 7.3 in 2020 (Figure 6.12). Ethanol's
share of the gasoline market also increases from 3.8 percent in 2015 to 4.7 percent in 2020 (5.3
percent to 6.6 percent, by volume). The much lower demand for gasoline in the Advanced scenario
depresses demand for ethanol. Comparison of Tables 6.6 and 6.7 shows that gasoline use in the
Advanced scenario is down 12 percent in 2010 and 24 percent in 2020 versus the Moderate
scenario. Ninety-five percent of the demand for ethanol as a motor fuel is for gasoline blending.
Once again, these projections do not account for the potential impact of an MTBE BAU, which
would tend to increase demand for ethanol as a blending stock.
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Fig. 6.12 Ethanol Use for Motor Fuel
8.00
7.00
Billions of Gallons of Ethanol
6.00
5.00
4.00
3.00
2.00
1.00
0.00
2010
2015
2020
6.5.3 Advanced Scenario Sensitivity Cases
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No Diesel Case. In both the Moderate and Advanced scenarios, the market shares of advanced
diesel engines increase significantly. The diesel's acceptability in the future will depend on its
ability to meet stringent emissions standards. It is by no means certain that a practical, clean diesel
able to meet increasingly stringent standards, can be developed. At present, diesels produce more
NO, and particulate emissions than gasoline engines of comparable power. Unless these emissions
can be reduced to acceptable levels, the light-duty diesel will not have a place in a clean energy
future (see, e.g., Mark and Morey, 1999).
This is an excellent example of the uncertainties inherent in projecting future transportation energy
use and GHG emissions. It might appear that the success of diesel technology is crucial to
achieving both scenarios' reductions in energy use and GHG emissions, since except for the fuel
cell, no single technology offers larger fuel economy benefits. The TDI diesel achieves a full 40
percent fuel economy improvement over a conventional gasoline vehicle of the same size and
performance, while the diesel-electric hybrid increases miles per gallon by approximately two
thirds. To examine the dependence of the scenarios' outcome on diesel technology, we ran a
sensitivity case based on the Advanced scenario but removing the light-duty diesel from the vehicle
mix. In comparing this new case to the original scenario, both sets of results are from
"unintegrated runs," that is, the runs are not precisely the same as those shown in the previous
section because the effects of changes in other sectors on the transportation sector are not
incorporated. This should have little effect on the results.
In the (unintegrated) Advanced scenario, sales of TDI diesels increase from 60 thousand in 1999 to
2.2 million annually in 2010 and over 3.1 million in 2020 (Figure 6.13). Sales of diesel-electric
hybrids in the scenario grow from 0 in 2002 to peak at over 800,000 units in 2013. Diesel sales
contribute to an overall increase in combined new passenger car and light truck fuel economy from
24.0 MPG in 2000 to 33.5 MPG in 2010 and 41.9 MPG in 2020. In the unintegrated Advanced
scenario, energy use by all light duty vehicles increases from 14.5 in 1999 to 15.5 quads in 2010,
then falls to 14.1 quads in 2020.
We simulated the absence of light-duty diesel technologies by raising their prices in the Advanced
scenario by $10,000 per vehicle after 2003. The NEMS AFV model responded by reducing their
predicted sales to 0. Figure 6.14 shows how vehicle sales have changed in this scenario. The
effects on light-duty vehicle fuel economy and energy use, however, were relatively modest. With
no diesels, the fuel economy of light-duty vehicles increased from 24.0 in 2000 to 31.4 in 2010 and to
40.5 in 2020, just 1.4 MPG below the scenario with advanced diesels (Figure 6.15). Energy use by
all light-duty vehicles increased to 15.7 quads in 2010, then declined to 14.6 in 2020, just 0.5 quads
higher than the Advanced scenario (Figure 6.16).
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The relatively modest impact of removing the diesel option can be attributed to three factors.
Although diesel sales are substantial, they are still a minority of passenger car and light truck
sales. With 24 percent of 2020 light-duty vehicle sales, the impact of these high-efficiency
vehicles on sales-weighted harmonic mean fuel economy is attenuated.
Second, removal of the diesels causes an increase in the sales of other high-efficiency
technologies, for example, fuel cells. Sales of fuel cells and battery electric vehicles in 2020
increase from 2.7 million in the Advanced scenario to 4.3 million in the No Diesels scenario.
This substitution of other advanced technologies for the diesel mitigates the impact of its loss.
Third, diesel cars and light trucks are a much smaller fraction of the on-road vehicle population
than of new vehicle sales. Even a twenty-year forecast does not allow sufficient time for both
market maturation and turnover of the vehicle stock. Thus the impacts in 2020 of withdrawing
diesels is smaller than it would be in the longer run.
This sensitivity case suggests that the Advanced scenario results are relatively robust to the success
or failure of a single technology, even one as important as the diesel. Similar results can be seen in
tests of sensitivity to fuel cell cost assumptions discussed below. Instead, the scenario is dependent
on a combination of technological advances and scenarios, brought about by a general level of
technological success and societal commitment to developing clean energy technologies and energy
sources.
CAFE Sensitivity Case. In this section we report the results of a stand-alone sensitivity case to
illustrate the potential impacts of mandatory fuel economy standards. According to economic
theory, voluntary environmental standards require at least the threat of mandatory standards to be
taken seriously by firms (Segerson and Miceli, 1998). While such theories often omit the
importance to firms of less tangible economic incentives for accepting voluntary standards, such as
creating and maintaining a positive public image, the possibility of more stringent mandatory
standards is undoubtedly a strong incentive for firms to commit to voluntary standards. For this
reason, and because mandatory standards are now in effect in the United States and played a major
role in the light-duty vehicle fuel economy improvements achieved over the past 25 years (e.g.,
Greene, 1998), it is appropriate to assess how mandatory standards might influence the levels of
fuel efficiency, fuel consumption and carbon emissions in the Advanced scenario.⁵
For this case, we simulate a new combined passenger car and light truck standard beginning in the
Imposing CAFE constraints tends to increase the use of advanced fuel economy technologies in
passenger cars and trucks. This, in turn, increases the cost of the vehicles, perhaps beyond levels
that would be cost-effective on the basis of fuel savings to the consumer. The results of the CAFE
Sensitivity Case clearly illustrate this effect. In the Advanced scenario, gasoline hybrids comprise
12.7 percent of gasoline vehicle sales in 2010 and 23.0 percent in 2020. In the CAFE Case, this
jumps to 31.1 percent and 56.6 percent, respectively (Table 6.10). Use of direct injection gasoline
engines also increases markedly, as do the market shares of advanced materials (primarily
aluminum and plastics) and advanced drag reduction technologies.⁷
Table 6.10 Market Penetrations of Selected Fuel Economy Technologies
in Passenger Cars in the CAFE Scenario
Technology
2010 Advanced
2010 CAFE
2020
2020 CAFE
Advanced
Gasoline Hybrid
12.7%
31.1%
23.0%
56.6%
Gasoline Direct Injection 4-
9.5%
16.5%
22.9%
36.1%
cyl.
Gasoline Direct Injection 6-
5.3%
11.1%
13.2%
27.5%
cyl.
Advanced Materials
0.0%
28.5%
34.2%
69.9%
Advanced Drag Reduction
8.2%
9.5%
36.5%
58.6%
This greater use of fuel economy technologies does increase the average price of new vehicles.
For example, for gasoline-powered vehicles,* the cost of fuel economy technologies in the
Advanced scenario averages $811 per passenger car in 2010 and $1,548 in 2020, versus $1,337 in
2010 and $2,383 in 2020 in the CAFE case. For light trucks, the CAFE case requires $1,365 worth
of fuel economy technologies in 2010 and $3,305 in 2020, as compared with $1,028 and $2,040 in the
Advanced scenario. The approximate values of fuel savings for the resulting changes in mpg are
summarized in Tables 6.11 and 6.12 (these estimates should be considered rough approximations,
since it was not practical to exactly replicate the NEMS model's accounting for technology notes
and horsepower adjustments). Even with the higher CAFE standards, the total value of fuel
economy savings by consumers exceeds their cost in 2010. In 2020, however, estimated costs
exceed estimated benefits, at a 15 percent annual discount rate." In comparison to a base
passenger car at 27.6 mpg, the 44.2 mpg 2010 CAFE case vehicle would emit 4.8 fewer MtC per
year at a net savings because reductions in fuel costs outweigh the added vehicle cost. The 53 mpg
2020 vehicle would emit 6.4 fewer MtC annually, at an average net cost of $16/MtC. The marginal
costs of carbon reduction are much higher, however. The costs per ton of C saved by model year
2020 versus 2010 vehicles is about $300. The estimates for light trucks show a similar pattern.
6.5.4 Impacts on U.S. Oil Dependence
Transportation is not the sole user of petroleum in the U.S. economy, but it is the dominant user. In
1998, the U.S. transportation sector accounted for over 66 percent of U.S. petroleum consumption.
Moreover, transportation uses nearly all the high-value, light products that drive petroleum
markets. In the reference case, the transportation sector's dominance of petroleum demand
actually increases to 71 percent of U.S. consumption by 2020. Here we briefly review the impacts
of changes in all sectors on U.S. oil dependence. Changes in the transportation sector, however,
are by far the most important.
Policies and technologies implemented in the Moderate and Advanced scenarios significantly
reduce U.S. petroleum consumption and, consequently, imports. Total U.S. oil consumption rises to
24.5 mmbd in the BAU scenario, but falls to 19.4 mmbd in the Advanced scenario (Figure 6.19). In
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the
BAU
Fig. 6. 19 U.S. Primary etroleum Consumption
30
25
20
15
10
5
0
2000
2005
2010
2015
2020
scenario, U.S. petroleum imports rise from 10.6 million barrels per day (mmbd) in 2000 to 15.9
mmbd in 2020. Of this, 4.0 mmbd are in the form of petroleum products, 12.0 mmbd are crude oil.
Total imports are 14.0 mmbd in the Moderate scenario, of which only 2.2 mmbd are products. In
the Advanced scenario, only 11.0 mmbd are imported in 2020. Under BAU, U.S. oil imports
increase from 49 percent of U.S. demand today, to 65 percent in 2020. In the Advanced scenario
the share of imports also increases, but to only 56 percent.
The 1.9 mmbd reduction in imports in the Moderate scenario, and 4.9 mmbd reduction in the
Advanced scenario reduce the U.S. bill for imported oil in 2020 from $135 B/year to $89 B/year
(Figure 6.20). Thus, the change in balance of payments is $45 B in favor of the U.S. The assumed
price of imported oil
in both the BAU and Advanced scenarios is $22.73. Because even the integrated runs do not
estimate the impacts of reductions in U.S. oil demand on world oil prices, the benefits of reduced
consumption in the form of lower prices for both imported and domestic oil are not available.
Today. world oil prices are held at higher than competitive market levels by the exercise of market
power by the OPEC cartel. Apart from impacts on the Gross Domestic Product, monopolistic
pricing of oil produces a transfer of wealth from oil consumers to oil producers. This is also likely to
be true throughout the BAU scenario, since OPEC's share of the world oil market increases from
39 percent in 2000 to 51 percent in 2020. If one assumes that the price of oil in competitive world oil
markets would be about $10 per barrel (see, e.g., Greene et al., 1998, p. 58) then the annual transfer
of wealth from U.S. oil consumers to world oil exporters would be $74 B in the BAU scenario and
$51 B in the Advanced scenario, for a net annual savings of $23 B to U.S. consumers in avoided
wealth transfer. Note that while this wealth transfer is not an economic loss from a global
perspective, it is a real loss from the perspective of the U.S. economy.
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Fig. 6. 20 U.S. Expenditures on Imported Petroleum
160
140
120
100
Billions of 1997
80
60
40
20
0
2000
2005
2010
2015
2020
6.5.5. Costs of Light-Duty Vehicle Fuel Economy Improvements
The benefits of fuel savings, reduced GHG emissions, lower levels of air pollution, improved energy
security, and so on, should be weighed against the full costs of achieving these benefits, discounted
over the forecast period. Unfortunately, not only are the full benefits difficult to measure, but
estimating costs are also problematic for two reasons. First, as we have noted above, estimates of
the future costs of technologies are rare and always uncertain. Second, the CEF-NEMS model
outputs do not provide sufficient information to estimate costs for modes other than light-duty
highway vehicles, and even in that case only a partial estimate can be made. As we suggest below,
enhancing the model's ability to produce cost estimates should be a high priority.
Estimates of the costs of fuel economy improvement can be made for light-duty gasoline vehicles
only. This is unfortunate, because a significant fraction of the MPG gains achieved by light-duty
vehicles in the Advanced scenario can be attributed to what the CEF-NEMS classifies as Alternative
Fuel Vehicle technologies: the TDI Diesel, fuel cell vehicles, etc. No way has been found to
compute the incremental costs of increased AFV market success using existing CEF-NEMS
outputs. (In theory, the value to consumers of these technologies exceeds their costs or they would
not have purchased them.) Costs for gasoline vehicles, however, can be calculated by combining
outputs describing the market shares of fuel economy technologies by vehicle class with the input
data on their costs and fuel economy improvement potentials. A spreadsheet was constructed to
make these computations and the results are presented here for the Advanced scenario, and the
CAFE sensitivity case. Assumptions about vehicle use, discount rates, etc. match those used in the
CEF-NEMS model for the Advanced scenario. These spreadsheet calculations do not account for
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synergies among technologies as the NEMS model does. This should produce a very small
overestimate of the overall fuel economy benefit.
Given that the CEF-NEMS model explicitly trades off the price of technologies against the value of
their fuel savings in estimating market shares, it should not be a surprise to find that, overall, the
value of fuel savings exceeds the costs of achieving it in both 2010 and 2020 for both passenger cars
and light trucks. As shown in Table 6.11, the passenger car MPG increase from 27.6 in 2000 to 38.1
in 2010 is worth $1,285 to consumers in present value, but cost them only $811. By 2020, however,
the difference is reduced: $1,780 in present value benefits versus $1,548 in initial costs. For light
trucks, the cost comparisons are even more favorable. For $1,028 in vehicle price, light truck
owners receive $1,921 present value worth of fuel savings in 2010. In 2020, $2,040 in initial
expenditure returns $2,625 present value savings.
The vehicle lifetime carbon emissions reductions attributable to fuel economy improvements are
also shown in Table 6.11. Key assumptions are constant miles driven and no discounting of future
carbon emissions. Since the value of fuel savings to consumers exceeds the cost in every case, the
average cost per metric ton of carbon reductions is always negative. The marginal costs of C
savings achieved in 2020 versus 2010, on the other hand, are considerable, $174/MtC for cars and
$156/MtC for light trucks. However, the cost to consumers includes taxes and PATP insurance,
which together adds some $0.70 to the price per gallon. The value to society of fuel savings would
not include these components but should include other societal costs of gasoline use, which we have
discussed above.
Table 6.12 shows the same calculations for the CAFE Sensitivity Case. These results were
discussed above.
6.5.6 Fuel Cell Sensitivity Cases
Of all the technologies considered for the transportation sector, fuel cell vehicles combine the most
promise for increasing energy efficiency and reducing greenhouse gas emissions with the greatest
uncertainty with respect to their cost and performance. Recent dramatic improvements in both
areas may explain why several manufacturers have announced commercial introduction of fuel
cell vehicles in the 2003-2005 period. When the "5-Lab" study was conducted just two years ago,
such a prediction seemed to us too unlikely to be included even in our High-Efficiency,
technologically optimistic scenario. Yet fuel cell technology still has a long way to go before it can
compete with conventional internal combustion engines. In the sensitivity cases presented here we
measure the impacts of fuel cell system costs, and particularly the rate of reduction in costs, on
predicted market success.
Cost is critical to fuel cell success in the CEF-NEMS model. Fuel cell vehicles costing several
thousand dollars more than conventional vehicles have negligible impacts in our BAU and
Moderate scenarios. But when costs approach those of gasoline ICE vehicles in the Advanced
scenario, sales levels rise to 2.5 million units per year in 2020. Beginning with the "stand-alone"
Advanced case, we estimated impacts on fuel cell sales of two alternative assumptions, both based
on the fuel cell cost analysis of Directed Technologies, Inc. (1998), described in appendix A-3. The
DTI study predicted that a hydrogen fucl cell vehicle mass-produced around the year 2005 would
cost approximately $2,200 more than a comparable gasoline vehicle. DTI's estimated fuel cell
system cost is actually $4,650, but a $2,475 credit is given for avoided costs of ICE drivetrain
components." In all our scenarios and sensitivity cases we assume that year 2005 fuel cell system
costs are twice the 2005 mass-production levels based on the DTI estimates,
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Table 6.11 Costs and Value of Fuel Savings for Light-Duty Gasoline Vehicle Fuel Economy Improvements, Advanced Scenario
Fuel Economy Improvement
Technology Cost
BASE
2010
2020
2010
2020
Passenger Cars
% Gain
33.4%
54.1%
All Changes
$1,488
$2,227
MPG
27.6
38.1
44.1
Fuel Economy Technologies
$811
$1,548
Annual Fuel Savings
$308
$427
Present Value Fuel Savings
$1,285
$1,780
C
Emissions
Reductions
3.6
5.0
Cost per tonne C
-$131
-$46
(mtC)
Marginal Cost per mtC 2010 to 2020
$174
Light Trucks
% Gain
35.6%
57.4%
All Changes
$1,629
$2,641
MPG
19.6
27.7
32.1
Fuel Economy Technologies
$1,028
$2,040
Annual Fuel Savings
$460
$629
Present Value Fuel Savings
$1,921
$2,625
C
Emissions
Reductions
5.4
7.4
Cost per tonne C
-$166
-$80
(mtC)
Marginal Cost per mtC 2010 to 2020
$156
Assumptions
Rate of
On-Road
Vehicle
Discount
Gasoline
Gasoline
Miles/Yea
Decrease
MPG
Lifetime
Rate
Price $/gal.
Price
r
in Annual Use
Factor
$/gal.
15,640
6.7%
0.85
12
15.0%
$1.67
$1.71
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Table 6.12 Costs and Value of Fuel Savings for Light-Duty Gasoline Vehicle Fuel Economy Improvements, CAFE Sensitivity Case
Fuel Economy Improvement
Technology Cost
BASE
2010
2020
2010
2020
Passenger Cars
% Gain
53.6%
85.3%
All Changes
$2,036
$3,110
MPG
27.6
43.9
53.0
Fuel Economy Technologies
$1,337
$2,383
Annual Fuel Savings
$414
$547
Present Value Fuel Savings
$1,728
$2,281
C
Emissions
Reductions
4.8
6.4
Cost per tonne C
-$81
$16
(mtC)
Marginal Cost per mtC 2010 to 2020
$317
Light Trucks
% Gain
43.5%
85.2%
All Changes
$1,906
$3,928
MPG
19.6
29.3
37.8
Fuel Economy Technologies
$1,365
$3,305
Annual Fuel Savings
$518
$773
Present Value Fuel Savings
$2,161
$3,224
C
Emissions
Reductions
6.1
9.0
Cost per tonne C
-$131
$9
(mtC)
Marginal Cost per mtC 2010 to 2020
$294
Assumptions
Rate of
On-Road
Vehicle
Discount
Gasoline
Gasoline
Miles/Yea
Decrease
MPG
Lifetime
Rate
Price $/gal.
Price
I'
in Annual Use
Factor
$/gal.
15,640
6.7%
0.85
12
15.0%
$1.67
$1.71
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but that prices decline rapidly at first and then more slowly according to a learning curve.
Conventional drivetrain costs are assumed to remain constant.
Three alternative learning curves were assumed: (1) the Moderate scenario curve in which costs
decline to 1.0 times the 2005 mass-production cost levels, (2) the Advanced scenario curve in which
costs decline to 0.7 times the 2005 mass-production level by 2020, and (3) a "Fuel Cell Success"
curve in which costs decline to 0.6 times the 2005 mass-production level (Figure 6.21). In the Fuel
Cell Success case, a gasoline fuel cell vehicle costs $1,000 less than a conventional gasoline ICE
vehicle in 2020, a hydrogen or methanol fucl cell vehicle costs $1,100 less. In addition, in the Fuel
Cell Success case we assume that fuel cell vehicles have equivalent passenger and cargo space to
gasoline ICE vehicles, full availability of hydrogen by 2020, and equivalent maintenance costs for
gasoline and methanol fuel cells, 25% lower maintenance costs for hydrogen fuel cell vehicles.
The results of these changes are striking. Assuming Moderate scenario fuel cell costs but all other
Advanced scenario policies results in negligible fuel cell vehicle sales (180,000 units) even by 2020
(Figure 6.22). The Fuel Cell Success case assumptions increase annual sales to close to over 2
million units in 2015 and almost 4 million units in 2020. A 25% market share that is still headed
upward in 2020. In the Advanced case, 15% of the fuel cell vehicles sold in 2010 are powered by
hydrogen; in 2020 hydrogen's share increases to 49%. In the Fuel Cell Success case, two thirds of
the fuel cell vehicles sold in 2020 are powered by hydrogen.
Clearly, the success of fuel cell vehicles is highly uncertain at the present time. Despite dramatic
progress in the past five years, automotive fuel cell technology still has a long way to go before it will
be competitive with conventional gasoline vehicles in terms of both cost and performance. These
sensitivity cases illustrate just how sensitive market success is likely to be to cost. Much will also
depend on how consumers react to the less readily quantified differences between fuel cell and
conventional vehicles, such as noise, vibration, reliability, and so on.
6.6 REMAINING ANALYSIS NEEDS
The transportation sector analysis would benefit by three types of improvements:
Additional CEF-NEMS runs that explore the sensitivity of results to changed technology
assumptions and that "tease out" the individual effects of new policies from the effects of a
changed "state of society" reflected in the scenario descriptions, and the specific effects of
individual policies;
Enhancing certain CEF-NEMS reporting capabilities; and
Development of new methodologies to evaluate the impacts of new technologies and policies.
6.6.1 Additional Model Runs
Time and resource constraints prevented us from conducting a number of useful CEF-NEMS runs
for the transportation sector. Among the more important runs are:
1. "Changed baseline" runs that maintain the EIA Reference Case's "no new policies"
assumption but that include modifications made in the CEF-NEMS model, such as those to the
Alternative Fuels Model coefficients, and allow for a higher growth rate for vehicle travel. The
new baseline run would: (1) clarify what portion of the reductions in greenhouse gases and
other effects are caused by the alterations made to the CEF-NEMS model, and (2) allow policies
to be evaluated against a more widely accepted view of future vehicle travel growth.
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2. Runs that selectively remove key policies one at a time, to ascertain their individual impacts.
3. Additional sensitivity runs, similar to the "no diesel" run, to test the sensitivity of GHG
reductions and costs thereof to the success or failure of the set of technologies considered.
These will measure the effects of different technology assumptions, e.g. lower or higher costs
for key technologies, changes in the portfolio of successful technologies, changes in the dates of
introduction, etc., on the outcomes.
6.6.2 Add to CEF-NEMS Bookkeeping Capabilities
The NEMS model provides an impressive amount of output, describing a vast array of the model's
calculations. However, for the purposes of the CEF Study, several additional outputs are needed.
The most important of these are:
Calculation of the costs of fuel economy improvements for both Fuel Economy Model and
Alternative Fuel Model calculations. Most but not all of the data necessary to make these
calculations is available from existing NEMS outputs as standards tables or as options. In addition,
several assumptions must be made and the calculations are complex and time consuming.
Modifications to the CEF-NEMS model code could provide precise, automated computation of
the costs for passenger cars and trucks.
Reporting of renewable ethanol use in the transportation sector tables. At present, use of ethanol
as a blending stock is reported in the "Motor Gasoline" totals in transportation sector tables. It
would also be desirable to identify renewable ethanol as coming from corn versus cellulosic
feedstocks.
Accounting for transportation use of hydrogen and for the processes used to produce the
hydrogen. At present, hydrogen used by motor vehicles is reported as "liquid hydrogen," which
is not the only form in which it may be used. Also, the production of hydrogen for use in the
transport sector is not accounted for in the CEF-NEMS.
Although the NEMS model documentation implies that emissions of criteria pollutants are
estimated for transportation, that capability is currently not implemented due to difficulties in
maintaining its currency. Given the changing state of knowledge in this field, as well as the
continuously evolving status and outlook for emissions regulations, maintaining an up-to-date
capability to forecast transportation emissions is a major effort. Fortunately, there are on-going
research programs on this subject, most notably at Argonne National Laboratory and at the
University of California, Davis, that could be drawn upon for annual updating of emissions
factors. As the CEF Study works to fulfill its goal of considering the full range of environmental
benefits of clean energy technologies, this issue must be addressed.
6.6.3 Development of New Methods
The Clean Energy Futures Study could benefit from the development or implementation of
improved analytical methods in several areas, especially:
More rigorous and explicit methods of harmonizing assumptions about technological advances
and policy contexts across the sectors. Over the past 25 years, analysts of different sectors of
the economy have developed sometimes surprisingly different methods for forecasting
technological change and assessing its impacts. This often leads to striking differences across
sectors in key areas such as the degree of optimism about technological progress or the political
will to impose binding policies.
More rigorous methods for assessing the impacts of multiple technologies based on fundamental
technological breakthroughs. Methods are need that will allow for the connections among
alternative technologies to be taken into account. For example, an advance in storage
technologies for compressed hydrogen might also have implications for other vehicles using
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gaseous fuels; advances in electrochemical energy storage would have implications for both
hybrid and battery electric vehicles. Improved methods for deriving the implications of
technological advances on a range of alternative vehicle technologies are needed.
More explicit methods for linking R&D effort to technological change should be implemented.
Admittedly, this linkage is not well understood and would be difficult to predict in any case.
Nonetheless, more rigorous, explicit linkages should be developed, with the goal of making
assumptions clearer and more readily comparable to historical experience.
Technology adoption for gasoline versus alternative fuel vehicles is handled differently in the
current CEF-NEMS model. A few of the differences have been addressed in changes made to
the CEF-NEMS Alternative Fuels Model, described in appendix A-3. An improved methodology
is needed to treat technological changes for light-duty vehicles in an integrated framework, so
that policies such as feebates or fuel economy standards can be effectively addressed, and so
that technological potentials can be consistently assessed.
Technology adoption algorithms for freight trucks and aircraft should be enhanced to follow the
methods used for light-duty vehicles. Within the CEF-NEMS Transportation Sector Model,
technology adoption is handled very differently across modes of transport. In general,
mechanistic technology penetration curves for freight trucks and aircraft are triggered when
fuel prices exceed a target level (this statement is an oversimplification, but captures the
essence of the method). For light-duty vehicles, the trade-off between initial cost and future fuel
costs is explicitly represented (other attribute trade-offs are also represented to varying degrees),
and differences among consumers' evaluations of these trade-offs are recognized. The method
used for light-duty vehicles is not only believed to be theoretically superior, but also allows for
more rigorous policy analysis.
6.7 SUMMARY AND CONCLUSIONS
Energy use and carbon emissions from transportation have grown steadily over time and appear
likely to continue to grow without new policies or sharp changes in fuel prices and availability. The
direct physical causes of this growth have been:
Travel demand has continued to grow strongly as incomes and population have risen; for
example, personal vehicle vmt grew by 2.8 percent/yr during 1974-1995..
Light-duty fuel economy has stagnated over the past decade (and perhaps would have fallen
without the presence of fuel economy standards).
Vehicle technology has changed over time, but much of the technology has been used for
purposes other than higher efficiency.
Several factors will strongly influence future levels of transportation energy use and GHG
emissions. On the favorable side, a variety of technology options currently are available to reduce
energy use and emissions, and a substantial portfolio of advanced technologies is under
development. Obtaining large emissions reductions will require counteracting a number of factors,
however:
Inexpensive fuel and consequent disinterest in fuel economy among light-duty vehicle
purchasers
Fuel efficiency tradeoffs with vehicle characteristics that are of interest to vehicle purchasers -
acceleration performance, vehicle size, consumer features such as 4-wheel drive, and so forth.
Time required for redesign, retooling, and fleet turnover; the full benefits of new technologies
take years to develop.
High costs and/or important technological and market risks associated with some of the most
promising fuel economy technologies.
In other words, both market factors and the status of technology options are crucial to reducing
transportation energy use and greenhouse emissions. Policies that change market incentives for
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consumers and vehicle manufacturers, and policies that can boost technology development are
both crucial to meeting Kyoto targets.
We have examined the impacts of a number of transportation policy changes on future
transportation energy use and greenhouse emissions. The accuracy of the forecasts presented
here is dependent on the assumptions we have made about future potentials for technology change
across a range of future transportation technologies currently under development, and about the
effectiveness of various policies. Although we have chosen these assumptions with care, we admit
readily that technology forecasting is a highly uncertain art, and further that the outcomes of some
of the chosen policies, particularly increased R&D funding, should be interpreted more as educated
guesses than as precisely calculated results. Nevertheless, we note that the types of improvements
we project are in line with historical improvements in transportation technology. Further, our
sensitivity results show that the results are robust in the face of failure of a key technology; this is a
critical result because we cannot claim that our choice of technological "winners" is necessarily the
correct one.
The results show that transportation energy use and greenhouse emissions will continue to grow at
a rapid rate without substantive policy changes. For the Baseline scenario, energy use rises from
25 Quads in 1997 to 36.8 Quads in 2020, and carbon emissions rise from 478 MtC to 696 MtC during
the same period - increases of over 45 percent. In the Moderate scenario, which focuses primarily
on advancing technology development and does not attempt to strongly influence markets,
transportation energy use still grows to 34.1 Quads in 2020, and carbon emissions to 646 MtC in
2020, in both cases growth of more than one third from 1997 levels. Only in the Advanced scenario,
where policies focus on both developing technology and influencing markets, does growth in energy
use and greenhouse emissions slow markedly. In that scenario, transportation energy use rises
only 16 percent by 2020, to 28.9 Quads, and carbon emissions rise only 12 percent, to 534 MtC. As
noted, these results are not affected markedly by the elimination of an important technology, the
direct injected diesel, because other technologies increase their market share when the diesel is
eliminated.
Significant emissions reductions from transportation will take time. Even the Advanced scenario
does not come close to reducing transport sector greenhouse emissions in proportion with the Kyoto
goal of sub-1990 emissions by 2010, and such levels are not even achieved by 2020. This is partly
because technological adoption and fleet turnover are slow processes in this sector, and partly
because even the higher fuel prices associated with the carbon permits and "pay at the pump"
insurance have not curbed the steady growth of transport demand. Understanding how demand for
mobility is likely to evolve and how it can be influenced without sacrificing accessibility is an
important area that needs further investigation. Even in the Advanced scenario in the year 2020,
key technologies such as hybrid vehicles, fuel cell vehicles, blended wing-body aircraft, and more,
are a minority of new vehicle sales and a far smaller minority of vehicle populations. If these
technologies are the beginning of a revolution in transportation technology, that revolution will have
only just begun by 2020.
6.8 REFERENCES
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Class 3-7 Heavy Vehicles," draft report, Center for Transportation Analysis, Argonne National
Laboratory, Argonne, Illinois (forthcoming).
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Bowman, D. and P. Leiby, 1998. Methodology for Constructing Aggregate Ethanol Supply Curves,
Draft, Revision 3, Oak Ridge National Laboratory, Oak Ridge, Tennessee, August 24.
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5761.
Bucholz, K. 1999b. "In Search of Earth-favoring Vehicles," Automotive Engineering, Vol 107, No
2, pp. 45-46.
Dahl, C.A., 1986. "Gasoline Demand Survey," The Energy Journal, Vol 7 No 1, pp. 67-82.
Daimler/Chrysler, 1999. Press Release of March 17, "DaimlerChrysler's NECAR4 Represents a
Crucial Step Toward Production; and Hydrocarbon Online, "Ford, Daimler-Benz and Ballard to
Develop Fuel-Cell Technology for Future Vehicles," 12/22/1997.
Davis, S.C., 1998. Transportation Energy Data Book, Edition 18, Center for Transportation
Analysis, Oak Ridge National Laboratory, ORNL-6941, September.
Delucchi, M.A., 1997. The Annualized Social Cost of Motor-Vehicle Use in the U.S., 1990-1991:
Summary of Theory, Data, Methods and Results, UCD-ITS-RR-96-3(1), Institute of Transportation
Studies, University of California at Davis, Davis, California, June.
Demmler, A., 1999. "Smallest GDI Engine," Automotive Engineering, Vol 107, No 3, p. 40.
Dougher, R.S. and T.F. Hogarty, 1994. "Paying for Automobile Insurance at the Pump: A Critical
Review", Research Study #076, American Petroleum Institute, Washington, D.C., December.
El-Gassier, M., 1990. "The Potential Benefits and Workability of Pay-As-You-Drive Automobile
Insurance", State of California Energy Resource Conservation and Development Commission,
Docket NO. 89-CR-90, In the Matter of 1990 Conservation Report. Sacramento, California, June 8.
Energy Information Administration, 1999. Analysis of the Climate Change Technology Initiative,
SR/O1AF/99-01, Washington, DC, April.
Energy Information Administration, 1998. Annual Energy Outlook 1999, with Projections to 2020,
U.S. Department of Energy, DOE/EIA-0383(99), Washington, DC, December.
European Commission and Association des Constructeurs Europeans d' Automobiles (EC &
ACEA), 1999. "CO2 Emissions from Cars: The EU Implementing the Kyoto Protocol," available at
http://europa.eu.int/comm/dg11/climat/acea.pdf, European Commission, Brussells, Belgium.
Federal Aviation Administration, 1996. FAA 1996 Strategic Plan.
Federal Aviation Administration, 1998. The Impact of National Airspace Systems (NAS)
Modernization on Aircraft Emissions, DOT/FAA/SD-400-98/1, September.
Ford Motor Co, 1997. "Ford's High mileage P2000 Diata Debuts at NAIAS," Daily Press
Conference Conference, January 8.
Greene, D.L., Hillsman, A., and J.M Nilles, 1994. Energy, Emissions, and Social Consequences of
Telecommuting, DOE/PO-0021, Office of Policy, U.S. Department of Energy, Washington, DC,
May.
Greene, D.L., D.W. Jones, and P.N. Leiby, 1998. "The Outlook for U.S. Oil Dependence," Energy
Policy, vol. 26, no. 1, pp. 55-69.
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Griffiths, J., 1999. "The Clean, Mean Electric Machine," Financial Times, March 29, p. 12.
Gruenspecht, H., G.R. Schmitt and T. Wenzel, 1994. "Background Paper: Pay-at-the-Pump for
Inspection and Registration Fees and Insurance." Unpublished manuscript, U.S. Department of
Energy, Office of Policy, Washington, D.C.
Heavenrich, R.M. and K.H. Hellman, 1999. Light-Duty Automotive Technology and Fuel
Economy Trends Through 1999, EPA420-R-99-018, U.S. Environmental Protection Agency, Ann
Arbor, Michigan, September.
Howden, K.C., 1999. "Partnership for a New Generation of Vehicles Compression-Ignition, Direct-
Injection Combustion/Aftertreatment R&D and Fuels Testing," Diesel Emissions Forum, April 14-
15, Pentagon City, Virginia
Jost, K., 1998a. "Chrysler Unveils Second-Generation ESX2 Hybrid," Automotive Engineering, Vol
106, No 2, pp. 187-188.
Jost, K., 1998b. "Drivable P2000 Pioneer of Ford's Clean Vehicle Fleet," Automotive Engineering.
Vol 106, No 2, p. 176.
Kavalec, C. and J. Woods, 1997. "Toward Marginal Cost Pricing Of Accident Risk: The Energy,
Travel And Welfare Impacts Of Pay-At-The Pump Auto Insurance", unpublished manuscript,
Department of Economics, University of California at Davis, Davis, California.
Khazzoom, J.D., 1997. "Impact of Pay-at-the-Pump on Safety Through Enhanced Vehicle Fuel
Efficiency," The Energy Journal, Vol 18, No 3, pp. 103-133.
Lewis, J.S. and R. W. Niedzwiecki, 1999. "Aircraft Technology and its Relation to Emissions",
chapter 7 in, Aviation and the Global Atmosphere, Intergovernmental Panel on Climate Change,
Cambridge University Press, Oxford.
Lynd, L.R., 1997. "Cellulose Ethanol: Technology in Relation to Environmental Goals and Policy
Information," in DeCicco, J. and Delucchi, M. (eds.) Transportation, Energy and Environment:
How Far Can Technology Take Us? ACEEE, Washington, DC.
Lyons, J.M., 1999. "The Effect of Diesel Fel Properties on Emissions from Current and Future
Technology Engines," Diesel Emissions Forum, April 14-15, Pentagon City, Virginia.
Mark, J. and C. Morey, 1999. Diesel Passenger Vehicles and the Environment, Union of
Concerned Scientists, Berkeley, California, April.
National Renewable Energy Laboratory, 1999. Bioethanol Multi-Year Technical Plan: Fiscal Year
2000 and Beyond, Office of Fuels Development, U.S. Department of Energy, Washington, DC, July.
National Research Council, Aeronautics and Space Engineering Board, 1992. Aeronautical
Technologies for the Twenty-First Century, National Academy Press, Washington, D.C.
National Research Council, Board on Energy and Environmental Systems, 1999. Review of the
Research Program of the Partnership for a New Generation of Vehicles: Fifth Report, Washington,
D.C.
Nauss, K.M., 1999. "Diesel Emissions: Health Effects Issues," Diesel Emissions Forum, April 14-
15, Pentagon City, Virginia.
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Plotkin, S.E. and D.L. Greene, 1997. "Prospects for Improving the Fuel Economy of Light-Duty
Vehicles," Energy Policy, Vol 25, Nos. 14-15, pp. 1179-1188.
President's Committee of Advisors on Science and Technology (PCAST), 1997. Federal Energy
Research and Development for the Challenges of the Twenty-First Century, Report to the
President, Washington, DC.
Reuters, 1998. "Toyota Sees Selling 13,000 Gas-Electric Cars in the U.S.," 6:53 a.m., August 26,
1998.
Robinson, A., 1999. "GM May Develop Direct-Injection for New Engines," Automotive News, June
14,p.3.
Segerson, K. and T.J. Miceli, 1998. "Voluntary Environmental Agreements: Good or Bad News for
Environmental Protection?" Journal of Environmental Economics and Management, Vol 36, No 2,
pp. 109-130.
Sugarman, S.D., 1991. "The case for pay-at-the-pump car insurance", The Sacramento Bee,
Forum, Sunday, June 9.
U.S. Congress, Office of Technology Assessment (OTA), 1995. Advanced Automotive Technology:
Visions of a Super-Efficient Family Car, OTA-ETI-638 (Washington, DC: U.S. Government
Printing Office, September).
U.S. Congress, Office of Technology Assessment (OTA), 1994. Saving Energy in U.S.
Transportation, OTA-ETI-589 (Washington, DC: U.S. Government Printing Office, July).
U.S. Department of Energy. 1997. OHVT Technology Roadmap, Office of heavy Vehicle
Technologies, Office of Transportation Technology, DOE/OSTI-11690, October.
U.S. Department of Transportation, National Highway Traffic Safety Administration (NHTSA),
1999. "Production Weighted Data from Manufacturers' Fuel Economy Reports," tables supplied by
Orron Kee, January 14, 1999.
U.S. Department of Transportation, Office of the Secretary, 1993. Transportation Implications of
Telecommuting, U.S. Government Printing Office, Washington, DC, April.
Wald, M.L., 1999. "Looking Under the Hood of a Hybrid Honda," Technology Section, New York
Times, October 1.
Wang, M.Q., 1999b. Personal communication.
Wang, M.Q., Saricks, C.L., and D.J. Santini, 1999. Effect of Fuel Ethanol Use on Fuel Cycle
Energy and Greenhouse Gas Emissions, Center for Transportation Research, Argonne National
Laboratory, ANL-ESD-38, January.
6.9 ENDNOTES
I
Authors: David Greene, Oak Ridge National Laboratory, and Steven Plotkin, Argonne National Laboratory.
Consultant: K.G. Duleep, Energy and Environmental Analysis, Inc.
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2
These changes would have been far more difficult to make and the chances for mistakes would have been
greatly increased had we not had the benefit of the expert advice and full cooperation of the NEMS model
experts at the EIA. We are grateful for their invaluable assistance with the use of NEMS. Any remaining
errors are, of course, our responsibility.
3
We attempted to use this feature in the 1997 "5-Lab" study, but found that it did not function properly.
With the assistance of Mr. Dan Mezler of EEA, Inc., we were able to identify and correct a "bug" in the
program so that the CAFE features functioned as intended. This is apparently the first instance of the use of
CAFE constraints in the NEMS model.
4
To illustrate how the weighted harmonic mean may differ from intuition, consider two types of cars, one
getting 40 MPG, the other 60 mpg, 50 percent higher. If the 60 MPG car has a market share of 17.5 percent,
the fleet average MPG is just under 42.5, only 2.5 MPG higher than if no 60 MPG cars were sold.
5
In this section, as in the "No-Diesel" case, we compare results not to the integrated Advanced Scenario,
but to a stand-alone version which is only slightly different but more directly comparable to the sensitivity
cases which are all run in stand-alone mode.
6 The NEMS model, AE099 version allows separate passenger car and light truck standards to be specified,
but only for gasoline-powered vehicles. Details of the modifications to NEMS inputs to simulate the
combined standard are provided in Appendix A-3.
7
Advanced materials include NEMS materials categories V-VII. Advanced drag is Drag Reduction V.
8
We have not been able to devise a way to calculate the additional costs of alternative fuel technologies
using outputs produced by NEMS. In principle, the AFV purchases are the outcome of market decisions by
consumers, so that in the context of NEMS, the value of the AFVs to consumers exceeds their cost. Thus, in
focusing on the cost of gasoline vehicle technologies, we are focusing on the only area where, at least in
theory, costs could exceed direct benefits to consumers.
1)
These estimates were computed by adding up the market share-weighted fuel economy improvement
benefits of each technology and multiplying one plus the sum times an adjusted base mpg. The base year
1997 mpg was adjusted to account for factors such as increased weight and horsepower and safety and
emissions mandates that would otherwise cause mpg to decrease over the period in question. The estimates
are only approximate in that no adjustment was made for synergies among technologies. Had these been
taken into account, the estimated fuel economy gain and therefore the value of fuel economy improvements
would have been slightly smaller.
10 Use of the term discount rate is somewhat inappropriate in this context, since what it actually represents is
the consumers' rate of return on capital, taking into consideration that the consumer's investment in fuel
economy technology is a depreciating asset.
11 In our opinion, the DTI study underestimates the mark-ups that will be applied to fuel cell manufacturing
costs. Our fuel cell cost estimates are therefore somewhat higher than DTI's estimates.
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Chapter 7
THE ELECTRICITY SECTOR¹
7.1 INTRODUCTION
7.1.1 Overview of the Electric Sector
In 1997, the generation of electricity in the U.S. consumed the equivalent of 34 quads of primary
energy, or 36% of all the energy used in the U.S. Ofthis, 23 quads was provided by fossil fuels, with
18.6 quads from coal, 3.4 from natural gas and 0.9 from petroleum. This fossil fuel use produced
532 million metric tonnes of carbon (MtC), 11.6 million metric tons of sulfur dioxide emissions, and
5.3 million metric tons of nitrogen oxide emissions. These values do not include the contributions
from cogeneration, which would raise the values evenhigher.
There are essentially four mechanisms to reducing theimpact of the electric sector in these areas.
These include:
1) reducing the demand for electricity,
2) increasing the efficiency of individual fossil-fired power plants and transmission,
3) reducing or sequestering the emissions from these plants, and
4) switching to less- or non-carbon intensive sources of generation.
Significant opportunities exist to reduce the demand for electricity. These opportunities are
addressed in the end-use chapters of this report. This chapter will focus on the other three
mechanisms and the policies that could effect them.
7.1.2 Restructuring of the U.S. Electric Sector
Identification and evaluation of policy pathways to reduce emissions in the electric sector is both
facilitated and complicated by the current restructuring of the sector. The U.S. electricity industry is
being transformed from a highly-regulated, vertically-integrated, industry to a largely competitive
deintegrated industry, at least in the generation sector. Transmission and distribution functions are
expected to remain largely cost-of-service regulated. Because this transformation is far from
complete, it is difficult to predict the structure and operational characteristics the sector will possess
in the future, much less the impact that alternative policies could have on thesecharacteristics.
Clearly, the set of players will expand from the historical set of utilities and regulators to include
distribution companies, independent system operators, generation companies, power brokers,
energy service companies, etc. The decisions made by the profit-maximizing owners of individual
generating units are likely to be quite different than the cost-minimizing decisions made in the past
by utility owners of large generation and transmission systems. In unregulated markets
characterized by short-term matching of offers to sell electricity with demand for electricity, and
without guaranteed returns, investors in generation will evaluate opportunities on a shorter time
scale with risk considered largely through higher costs of capital, and returns based on marginal
pricing. With cost minimization essential, there already has been a reduction in R&D efforts and
demand-side management programs by utilities preparing for the competitive environment. Some
utilities are also divesting themselves of generation assets and becoming regulated
transmission/distribution companies providing open access to all generators as mandated by the
Federal Energy Regulatory Commission (FERC) in response to the 1992 Energy Policy Act.
Finally, states are beginning slowly to mandate such restructuring; the Clinton Administration is
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7.1
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pushing legislation to facilitate it; and consumers are beginning to express preferences not only for
low-cost power, but for environmentally-clean power.
Other factors are also forcing the U.S. electricity industry to change. These factors include low
natural gas prices, substantial improvements in the efficiency of gas-fired combustion turbines and
combined cycle systems, broad public sentiment favoring deregulation of economic sectors
wherever possible, and heightened interest and concern for the environment and its protection.
7.1.3 Technology Opportunities
Policies and market structure donot generate emissions or consume imported oil, technologies do.
Thus, policies put forth in the hope of meeting national goalsare intended to encourage the use of
"clean energy" technologies. Table 7.1 summarizes these technology opportunities for the electric
sector along with issues that may stall their development. Because of the age of the current fleet of
power plants (2/3 were built before 1970), there is a great opportunity for these new, more effcient
technologies to be deployed as existing plants are retired and replaced. Combined heat and power or
cogeneration plants are not shown in Table 7.1 since they are treated in the buildings and industry
end-use chapters of this report.
Table 7.1 Electric Sector Technology Opportunities
Technology
1997
1997 avg.
Possible future improvement
Issues/comments
gen
grams
market
carbon /
share
kWh
Coal boilers
56%
260
New plant efficiency could be
Few new coal plants are
as high as a third greater
currently planned
than the efficiency of existing
Existing plants are cheapest
plants
source of fossil power
Existing plant efficiency
Refurbishments are costly
could be improved but to a
Depending on pending
lesser extent
environmental constraints,
older plants may be retired
Carbon sequestration
Seq. in early research stage
Coal IGCC
~0
210
Possible combination with
Close to commercial
fuel cell yields high
efficiency and carbon
3 commercial
separation achieving near
demonstration plants
zero carbon and criteria air
operating in U.S.
pollutant emissions
Gas Turbine
<5%
170
New plant efficiency >40%
Largely peak load (with
efficiency; current plants
some intermediate), thus
=32%
has lower impact on total
emissions
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Technology
1997
1997 avg.
Possible future improvement
Issues/comments
gen
grams
market
carbon /
share
kWh
Gas
<4%
100
Market share can be
Designed for intermediate
combined
substantially increased over
and base load; could
cycle
time
replace retiring coal plants
New plant efficiencies could
and inefficient gas plants
increase to 60% to 70% with a
Large resource base
ternary cycle; current
Fuel deliverability and cost
models are 43% -57%
may become issue in future
efficient
With carbon separation could
achieve near zero carbon
Fuel cells
0%
>=0
Can be combined with other
First cost needs to be
dependin
cycles
reduced further
g on fuel
With carbon separation could
Technology improvements
source
achieve carbon and criteria
needed
air pollutant emissions near
zero
Nuclear
20%
0
Improved efficiency and life
Public concern with safety
extension of current plants
Spent fuel storage and
possible at low cost
disposal could limit future
New small plants may better
operations
meet market needs
More than 50% of plants
require license renewal by
2020
Hydro
10%
0
Increased efficiency and
Large potential (60 GW)
enhanced environmental
Concerns with environ-
performance with advanced
mental impacts from public
technology
and natural resource
management agencies
Wind
<1%
0
Costs competitive on kWh
1998 growth rate of 35%
basis in near future in some
worldwide
markets
Intermittency may limit
role
Biomass
<1%
~0 for
Use can be increased
Requires waste collection
cofiring
biomass
relatively easily to 2-4% of
infrastructure; negligible
portion
coal generation
coal plant retrofits required
at low levels of biomass to
coal.
Geothermal
Resource identification
Competitive today at good
Hydrotherma
<1%
0
resource site; resources
1
limited
Photovoltaics
0
0
75% cost reductions possible
2020 potential in buildings
in long term (EPRI 1997)
assuming net metering
Solar thermal
<1%
0
Limited cost-reduction
Only southwestern U.S.
potential
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7.2 POLICY IMPLEMENTATION PATHWAYS
Deployment of these "clean energy technologies" can be accelerated by overcoming market
barriers and failures through policy interventions. For the BAU scenario, no policies beyond those
currently in place are assumed, consistent with the EIA's assumptions in AEO99. Policiesevaluated
as part of the Moderate and Advanced scenarios are shown in Table 7.2. A brief description of each
follows the table with specific parameter values in Appendix C-4. In addition, other policies that may
be useful but could not be accurately modeled quantitatively in CEF-NEMS are discussed in
Section 7.2.2. Some sensitivities to the scenarios were run that modified the below policies or added
approximations of other policies. These are discussed in Section 7.5.3.
7.2.1 Policy Pathways Quantitatively Analyzed
Table 7.2 Electricity Policy Pathways Analyzed
Moderate Scenario
Advanced Scenario
1.5 /kWh production tax credit (PTC) for
Same, for all non-hydro renewable
wind and biomass power to 2004. 1.0/kWh
electricity options to 2004.
credit for biomass cofiring.
Renewable Portfolio Standard - represented
by 1.5c/kWh PTC in 2005-2008 to model cap
in administration proposal
Wind deployment facilitation
Same
Enhanced R&D - represented by the
Additional technology advances beyond
electric technology cost and performance of
those of the Moderate scenario
the AE099 high renewables and high fossil
Include sequestration option.
cases
Up to 1% net metering.
Up to 5% net metering.
Full national restructuring in 2008.
Same.
SO₂ ceiling reduced in steps by 50% between
2010 and 2020 to represent tighter PM
standards
Carbon cap with assumed consequent permit
price of $50 per metric ton of carbon,
starting in 2002 with full value by 2005.
Production tax credit. In the Advanced scenario, a production tax credit of 1.5/kWh (1992$) is
assumed for the first 10 years of operation from all non-hydro renewable electric generators
installed through 2004. The tax credits lower the cost of production; the additional cost to the
Treasury is discussed in section 7.5.4. In the Moderate scenario, only wind and biomass power
qualify, consistent with the President's Climate Change Technology Initiative proposals. In addition,
for both scenarios a lc/kWh credit is given for cofired biomass during the years 2000-2004.
Renewable Portfolio Standard (RPS). The President's proposed (April 1999) legislation on
competition in the electric sector includes amandate to generate 7.5% of all electricity sales from
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either wind, biomass, solar, or geothermal for the years 2010 through 2015. However, a 1.5/kWh
cap on the price premium for the renewable power is established. If the price difference between
renewable energy and other alternatives is more than the cap, then it could comeinto play and
lower the portfolio percentage which could end up less than 7.5%. Although CEF-NEMS has the
capability to include an RPS, it cannot directly model the 1.5 cents/kWh cap and it has problems
combining RPS with marginal-cost-based rates. As a surrogate to the CEF-NEMS method of
modeling the RPS, we extended the PTC of 1.5/kWh to capacity added between 2005 and 2008.
Because the biomass cofiring tax credit only applies in the years specified, as opposed to the
following ten years, it was extended to 2014. We calculated the added cost and carbon saved due to
the tax credit extension and determined it to be between $60 and $70/tC. For this reason, the credit
was only applied in the Advanced scenario.
Policies to facilitate wind deployment. There are a number of issues associated with wind
deployment and operation within a competitive electric market that could be mitigated through
focussed policies. These include policies to facilitate siting on Federal land (for example, reducing
the National Environmental Protection Act (NEPA) filing requirements which currently require
avian, archeological, and flora/fauna studies), to expedite challenge procedures and limit liabilities
for all sites (for example, there is concern that criminal charges could be pressed for the death of
any endangered avian species), to design independent system operator protocols to accommodate
wind intermittency (for example, the establishment of a trading market to firm up intermittent power
sources), etc'.
Enhanced R&D. Federal R&D budgets for renewable and fossil generation technologies are
assumed to increase 50% in the Moderate scenario, and 100% in the Advanced scenario. The
Moderate scenario funding increases together with industry learning are assumed to yield
technology cost and performance equal to that of the EIA's high renewables and high fossil cases
defined in EIA's 1999 Annual Energy Outlook (EIA, 1998a). EIA states in the AEO99 that the
values used for the high fossil cases in the AEO99 were chosen "to reflect potential improvements
in costs and efficiencies as a result of accelerated research and development." However, in recent
comments they have said that these were simple sensitivities and not reflective ofenhanced R&D.
The high renewables values were based on "more optimistic Department of Energy renewable
energy assumptions... (EIA, 1998a) These renewable assumptions are consistent with the
EPRI/DOE Renewable Energy Technology Characterizations report (EPRI 997). In the Advanced
scenario, the renewable technology cost and performance assumptions remained the same as those
in the Moderate scenario, while the fossil generator data were based on information received from
the DOE Office of Fossil Energy, consistent with their Vision 21 performance goals (DOE/FE 1999,
Parsons 1998, Dye 1999).
The advanced nuclear technology was modified for the Moderate and Advanced scenarios. In the
Moderate scenario, the fifth-of-a-kind cost of advanced nuclear technology was kept the same as in
the BAU (and AEO99 reference) case, but to reflect a policy that the advanced nuclear plants would
be jointly developed with international partners, the cost of the initial plants were not increased as
much². In the Advanced scenario, the capital cost of the advanced nuclear was reduced by roughly
10% to represent improvements in the construction cost through advanced designs and R&D.
Specific correlations between R&D amounts and technology improvements were not used in this
study. Rather, recognized technology targets by experts were used to establish the potential
1 To reflect these policies, changes were made to the model's parameters for all three scenarios, including the
BAU. However, the changes did not affect the BAU scenario because the constraints on wind capacity
caused by these parameters were not limiting its growth. Consequently, these changes can be thought to apply
only to the Moderate and Advanced scenarios.
2 The Technical Optimism factor was reduced from 1.19 to 1.00. Technical optimism factors are a multiplier
of the capital cost of the first few plants that gradually decline to unity by the fifth plant.
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improvements with higher improvements assumed with increased funding. More precise
technology achievements as a function of research funding over a long time period are difficult if
not impossible to attain.
Net metering. Consistent with the President's recently (4/19/99) proposed legislation on competition
in the electric sector (DOE 1999), this policy assumes a minimal level of net metering is allowed by
the states. It is applicable only to systems of 20 kW or less in residential and commercial
applications. Net metering means that on-site generation exceeding site loads can be fed back to the
grid at values equal to the purchase price, i.e. the meter can be run "backwards" when on-site
generation exceeds on-site loads. Net metering creates incentives for distributed generation which
can have environmental and reliability benefits through higher efficiencies and reduced
transmission and distribution requirements. Allowing customers to resell power at the retail price
means that distribution costs are not recovered by the distribution company, requiring those costs to
be recovered from sales to other customers. For this reason, net metering may face resistance and
limits are often placed on the maximum amount of net metering allowed. The current analysis
allows net metering of only residential buildings using PV.
Restructuring. This policy assumes that all states implement competitive wholesale markets for
electric power by 2008 in the Advanced scenario and the Moderate scenario. This translates to
pricing based on marginal costs instead of regulated, average-cost-based rates. This is as opposed to
the BAU case, in which marginal cost-based pricing is applied in the fiveregions of California, New
York, New England, the Mid-Atlantic Area Council (consisting of Pennsylvania, Delaware, New
Jersey, and Maryland), and the Mid-America Interconnected Network (consisting of Illinois and
parts of Wisconsin and Missouri). Restructuring can cause other changes to the market, such as
higher costs of capital, lower reserve margins, and flatter load shapes. It also allows the non-
quantified benefits of choice of supplier and competition. This maycreate dynamic efficiencies that
spur development of lower cost and higher value energy services to customers. Arecent study by
the Northeast Midwest Institute gives more details on the potential for efficiency improvements in a
restructured market (Kaarsberg 1999). Market forces are already at work in today's environment
changing the generation mix to more efficient and cleaner plants. Forexample, the top two types of
plants built in 1998 were combined cycle gas turbines and wind plants.
Stricter particulate matter (PM) emission standards. This policy assumes that PM standards are
tightened in response to increasing concerns of their impact on health and the environment. The
CEF-NEMS does not include PM emissions, however, one of the major precursors to the formation
of small (< 10 microns) particulates is SO₂, which can be constrained in CEF-NEMS. Following the
example of the EPA's analysis of mercury and particulate emissions (EPA 1999), we restricted SO2
emissions to 50% below the current requirements. However, we delayed the ramping down to
between 2010 and 2020, in part to shift policy impacts to the latter part of the studyperiod.
Carbon cap and trade. In the Advanced scenario a cap is assumed on carbon emissions from all
sectors of the economy. The cap is announced in 2002, implemented in 2005, and continued
indefinitely. See chapter 2 for more details.
7.2.2 Additional Policy Pathways
There are additional electric-sector policies and opportunities (see Table 7.3) not included in our
scenarios that we either modeled in our sensitivity analyses (see section 7.5.3) or which are
discussed only qualitatively in this section. These include green power markets, distributed power
markets, other market diffusion policies for renewable energy, various nuclear issues, emissions
regulation mechanisms, hydroelectric power expansion, transmission and distribution (T&D)
technology improvements, fuel switching from coal to gas, and efficient coal technology incentives.
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Table 7.3 Additional Electricity Policy Pathways
Policy/Opportunity Areas
Potential Policies
Market Issues
Green Power market formation and
standards
Distributed power market facilitation
Renewable Market Diffusion
Supply Push policies (see Table 7.5 for
details)
Demand Pull policies
Regulatory policies
International Market policies
Renewable Portfolio Standard
Hydroelectric Power Expansion
Increased R&D
Extend renewable incentives to hydro
Nuclear Issues
Additional relicensing streamlining
Spent Fuel Disposal resolution
Ownership flexibility
Decommissioning fund tax treatment
Emissions Regulation
Output-based allowance distribution
Stricter emissions limits
Transmission & Distribution Technology
Increased funding of high temperature
Improvements
superconducting technologies
Clean Coal and Coal-to-Gas Technology
Recovery of sunk costs in a switch from coal
Development
to gas
Production tax credits for efficient coal
Investment tax credit for efficient coal
Pool for risk-sharing of technology
development
Market Issues. Green power markets represent agrowing opportunity for renewables. Evidence to
date shows that green products have had some success in markets newly opened to competition
(Wiser 1999). Niche markets clearly exist for green power. Residential demand has been most
prominent, though nonresidential demand has been more significant than many expected.
Nonetheless, it will clearly take time for the green market to mature, and there remain legitimate
concerns about the ability of customer-driven markets to support significant amounts of renewable
energy. Unfortunately, there is currently insufficient data with which to predict the long-term
prospects for green power sales with any accuracy (Wiser 1999). This analysis does notpresume to
explicitly forecast the impetus that green marketing alone can provide, but rather we assume that
green marketing together with other programs will spur the development of a renewable energy
infrastructure and a consumer awareness and comfort with the technology.
Distributed power markets also represent an opportunity for dispersed generation. The primary
candidate technologies include reciprocating engines, gas-fired turbines, fuel cells, and
photovoltaics. To a limited extent we have captured some of this potential in our modeling of
photovoltaics in the buildings sector. However, there also exists a large market for non-customer
owned generation within the distribution system. Such generation could have a wide range of
impacts on carbon emissions and local air pollution. On the positive side, distributed generation
technologies may be non-emitters, like photovoltaics, or lower emitters, like fuel cells. Emissions
would also be reduced since less generation would be required due to the absence of losses in the
transmission of power. On the other hand, more emissions might result from the use of smaller
less-efficient combustion turbines, and criteria pollutant emissions would be moved closer to
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population centers. These opposing impacts together with the difficulty of modeling this very site-
specific opportunity has kept us from assessing this opportunity or the facilitatingpolicies that could
spawn it.
Combined heat and power (cogeneration) has been included in the industrial sector (Section 5.5.4)
instead of the electric sector yet represents a significant contributor to the overall electricity output
of the country. In addition, district energy systems that distribute steam to buildings can also be
made to cogenerate electricity and provide additional capacity. Table 7.4 shows the amount of
capacity that could be available from these two sources. These sources are represented as
reductions in demand, separate cogeneration within CEF-NEMS, or as a separate stand-alone
analysis and are not included in the production numbers in this chapter.
Table 7.4 Cogeneration capacity from industrial and district energy sources (GW)
2010
2020
BAU
Mod.
Adv.
BAU
Mod.
Adv.
Industrial cogeneration*
4
14
29
9
40
76
District Energy Systems*
12
19
33
50
* From Table 5.10
** From Box 4.1 (Spurr 1999)
Renewable Market Diffusion. Another category of options not explicitly considered here focuses on
the process by which renewable technologies enter the market place. Since renewabletechnologies
are not widespread in the market, they face a number of barriers common to all emerging
technologies. These barriers include lack of information about the technologies, uncertainty about
technology performance, and incompatibility with existing infrastructure. These market barriers
can be addressed by a wide variety of policies. These include direct policies such as those shown in
Tables 7.2 and 7.3 above, as well as more indirect policies like information programs that affect the
diffusion process strongly in its early stages.
The range of these diffusion-related policies is illustrated by the results (see Table7.5) of a recent
scenario-based workshop, which focused on policies to encourage the significant penetration of
renewable technologies in the U.S. in the next several decades. Many of these policies interact with
each other to accelerate the diffusion process. As shown by Table 7.2, in this study we have
quantified only the major policies that directly impact the economics of renewable technologies. A
related working paper (Kline and Laitner, 1999) examines the issues involved in assessing the
impact of the more indirect policies related to marketdiffusion.
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Table 7.5 Renewable Market Diffusion Policies from Scenario Workshop
Supply Push
Demand Pull
Large scale public/private partnerships
Green power certification
in RD&D
Power source disclosure requirements
Expand Climate Wise and Energy Star
Public/private partnerships for biofuels
programs into renewable energy
(and other technologies)
technologies
Competition to develop new user-side
Refine and disseminate renewable
infrastructure to support renewables
energy resource data
Government purchases of renewables
Standardized procedures for selling and
Popular marketing campaign (e.g.
interconnecting intermittent
Popular Mechanics)
renewables to the electric grid
Demonstrations of hybrids in
distributed applications
Other large-scale demonstrations
through public/private partnerships
Regulatory Measures
International Markets
System Benefit Charges and guidance
International demonstrations by
to accelerate renewable energy
public/private partnerships
penetration.
Promote (first quantify) environmental
Develop, promote methodology for
benefits of renewable energy
evaluating distributed generation
technologies to developing countries
benefits of renewables
Integrate renewables into emissions
enforcement procedures
Outreach/education for state
legislatures
Outreach to federal agencies
Push dissemination of atmospheric
research results
Nuclear Issues. A third set of policies that we have not analyzed quantitatively relates to nuclear
power. Such policies include a definitive resolution to the spent fuel storage/disposal issue, licensing
reform in the area of ownership requirements, and federal mechanisms to ensure full funding of
nuclear plant decommissioning without penalties due to corporate restructurings or ownership
transfers. These polices can be reflected in the analysis through further lowering of relicensing
costs or ongoing O&M costs, but additional analysis is needed to quantify them. Further discussion
can be found in Appendix E-3.
Spent fuel storage/disposal policy. Many nuclear plants are faced with a near-term problem
of lack of storage space for their spent nuclear fuel. Some state regulations stipulate that a
nuclear power plant cannot operate if it does not have sufficient on-site storage capacity.
Uncertainty about how and when the federal government will meet its obligation to provide
storage and disposal facilities for used nuclear fuel represents one of the most significant
business risk factors for nuclear power plants. The Department of Energy has been
conducting an exhaustive scientific assessment of a permanent disposal site at Yucca
Mountain, NV, but it is more than 12 years behind schedule, and no site has been selected
for an interim storage facility. While resolution of this issue is needed for the permanent
storage of wastes, lack of a disposal facility will not cause premature shutdowns in and of
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itself. Alternative technical solutions to avoid shutdowns are available but require
acceptance by the stakeholders involved.
Licensing reform regarding foreign ownership requirements Sections 103d and 104d of the
Atomic Energy Act prohibits foreign ownership of commercial nuclear facilities. In the
evolving power market such restrictions impact competition. They could be removed, except
where they pertain to national security concerns. As a barrier to entry, these restrictions
limit the number of potential investors in U.S. nuclear assets, resulting in a downward bias
in the value of such assets and a likelihood of premature shutdown. Existing owners that are
not willing to continue operating a plant but unable to sell it to those most willing to, may
choose to retire the plant instead.
Federal mechanisms to ensure full funding of nuclear plant decommissioning. Because
decommissioning of nuclear power plants is a public health and safety issue, a federal
mandate and mechanism could be established to ensure recovery of unfunded
decommissioning obligations-via a non-bypassable charge-when a nuclear asset is sold.
In addition, the Internal Revenue Code could be amended to ensure that, with the sale of a
nuclear asset, the transfer of decommissioning funds are not taxed as capital gains. Without
these mechanisms, nuclear plant economics are negatively affected.
Emissions Regulation Mechanisms. Other possible policies that could support non-emitting
generators hinge on the economic recognition of their clean air compliance value. One suchpolicy,
an output-based emission standard, would allocate emissions allowances to all producers on the
basis of their electricity production output, rather than the fuel input used. This change in the
distribution of allowances would force emitters to purchase from non-emitters the required
allowances for their production. Non-emitters would benefit both from the sale of their allowances
and the higher marginal prices for electricity (since emitters would include the cost of allowances in
their variable costs.) The impact would depend on the relative demand and supply of allowances,
and consequent market price. The difficulty in modeling the inter-sectoral and cross-sectoral
trading needed for such an approach limits our ability to analyze it.
Hydroelectric Power Expansion. Hydropower is often characterized as either a fully developed
energy resource that needs no new attention in national energy strategies or as an energy source
that should be discouraged because of its adverse environmental effects. Neither of these points of
view are completely accurate. While hydropower currently supplies about 98% of the electric
generation from renewables, it still can provide significant, additional benefits to control of
greenhouse gas (GHG) emissions. There are approximately 60 GW of undeveloped hydropower
available in the U.S., distributed across three types of projects: 1) equipment upgrades at existing
hydropower facilities, 2) new development of generation facilities at existing dams, and 3) new
development at new dams or diversions. With advanced technologies that are becoming available
(e.g., fish-friendly turbines), the first two of these types of projects would have net benefits terms
of improved environmental performance and GHG reductions. The third category of undeveloped
resource is more problematic, because of the new construction involved. However, the estimate of
those hydropower resources employed an environmental screen by state resource managers to
exclude sensitive and protected sites (Rinehart et al. 1997) (i.e., environmentally unsuitable sites are
not included in this estimate).
The magnitude of undeveloped hydropower is relatively large, especially with respect to near-term
potential. Approximately half of this resource could be developed by 2010 if hydropower is included
among the renewables targeted for encouragement. New initiatives for conducting life-cycle
analysis and defining low-impact hydropower are being developed by scientific organizations,
environmental groups, and energy marketers, for marketing hydropower as "green" energy in the
retail power market.
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To achieve new, environmentally preferable hydropower, continued federal funding for RD&D
projects is needed. DOE's Advanced Hydropower Turbine Systems Program has been successful
in the development of innovative technologies that will enhance the environmental performance of
hydropower projects and in attracting both interagency cooperation and industry cost-sharing. On
the policy side, environmentally preferable hydropower needs to have full access to the market
incentives for other renewables, if hydropower's GHG contributions are to be realized.
Estimating supply functions for hydropower is inherently difficult because of the highly site-specific
nature of development costs (e.g., FERC 1988). Resource studies to date (e.g., Rinehart et al. 1997;
DOE Hydropower Assessment Program 1999) have not included the type of information needed to
provide the level of economic analysis possible with other renewables. Additional federal and/or
private resources should be invested in an expanded hydropower resource assessment, so that its
true potential can be factored into national planning. Any newresource assessment should be done
in cooperation with both the industry and environmental groups. Indications are that the
hydropower industry is ready and willing to participate.
One example of the unresolved controversies that plague the hydropower industry is the fate of
hydroelectric generation during the relicensing process at non-federal projects. Every 30 to 50
years, non-federal hydropower projects must obtain a new operating license from FERC. This
relicensing process is an opportunity to add new environmental operating constraints, such as
minimum flow requirements or fish ladders or screens. It is also atime when generating equipment
can be upgraded or decommissioning can be considered. A basic question ishow is contemporary
relicensing affecting the total generating capacity of hydropower in the U.S.? Answers range from
an average of 8% loss in capacity (Hunt and Hunt 1997) to less than 1% change. Anecdotal
evidence from individual proceedings indicates that many opportunities to upgrade equipment at
relicensing are being foregone, probably due to local economic decisions and regulatory
uncertainty. The latter has drawn attention from Congress. Pending legislation designed to resolve
some of this uncertainty may be enacted, but the cost of relicensing will remain high.
Environmental mitigation costs are also quite high in relicensing, but there are no definitive studies
that can quantify these costs. Hydropower is a resource that should be tapped to the extent feasible,
both environmentally and economically, in order to address GHG controls, especially on thenear
term.
Other new policy options that could be pursued for hydropower include the following:
regulatory reform to ensure that environmental mitigation requirements in relicensing are
justified,
incentives for equipment upgrades of existing facilities for both power production and
enhancements to environmental performance, and
development of objective criteria for evaluating the environmental performance of
hydropower projects in relation to other regional energy projects.
T&D Technology Development. Electric power T&D systems transfer generated power from
central power stations and distributed generators to customers elsewhere on the power grid. Energy
losses in the U.S. T&D system were 7.2% of total generation in 1995, representing 2.5 quads of
energy and 36.5 MtC of carbon emissions (DOE National Laboratory Directors 1997). High voltage
direct current transmission, high temperature superconducting (HTS) cables and transformers,
more efficient line transformers, and real-time control using automated controls could all improve
the efficiency of the T&D system. Projections indicate that the most significant impacts of these
technologies (20-25 MtC savings per year) will occur beyond 2020, as existing equipment is replaced
and new technologies are available for capacity expansion. However, some savings, 3-6 MtC/yr,
could occur if currently available technologies become more economical and accepted. Domestic
research is aimed at improving HTS cables and transformers through longer cable lengths atlower
cost and improved cryogenic refrigeration. Several demonstrations are already underway,
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including a replacement of distribution lines in a crowded urban location in Detroit, MI (EPRI
1999).
Coal Technology Development. Carbon emissions at existing coal-fired power plants could be
reduced through efficiency improvements (via clean coal technologies) or reliance on carbon
capture/ sequestration technology (when it becomes commercially economic). Anotheroption is to
convert such plants from coal to natural gas. Some fuel switching is already occurring, where coal-
fired power plants are being purchased and converted to natural gas combined cycle (NGCC)
facilities (e.g., Detroit Edison converted its 200 MWe Connors Creek plant, which became
operational in June 1999). Such conversions reduce not only carbon emissions but also criteria air
pollutants, and permit capacity expansion in airsheds that would otherwise prohibit new generating
capacity. Electric generating companies compare the projected cost of continued operation (of the
coal-fired power plant) with additional compliance equipment against the cost of switching to gas to
meet future electric load and environmental requirements.
In general, the economics of switching from a plant designed to use an inexpensive fuel (coal) for a
more expensive one (gas), while requiring significant capital expenditures, are not favorable. Also,
space restrictions, access to natural gas pipelines, and local permitscan preclude such conversions.
In addition to these site factors, the sunk cost in the coal-fired power plant (e.g., boiler, coalhandling
equipment, emissions control equipment) could make such aconversion uneconomic. Such sunk
costs may not be recoverable, either in a regulated rate-of-return environment or competitive power
market (via a competitive transition or stranded cost charge). In a regulated market the equipment
may be declared no longer "used and useful" so it would be withdrawn from the rate base. In a
competitive power market, the investment represents a sunk cost that does not enter into future
"going forward" costs when compared against the value of switching togas.
A potential policy pathway is to reimburse generators who switch to gas for the coal-related sunk
costs, either through a tax credit or an electricity surcharge, such as a stranded cost or competitive
transition charge. A potential problem with such a policy is the possibility of "free riders,"
- generators who take advantage of the reimbursement but would have switched anyway based
solely on economic criteria. Such a policy option would require further examination before it could
be recommended (or implemented).
Carbon emissions reduction could also be accomplished through deployment of more efficient coal
technologies-that either replace retirement-age pulverized coal-fired boilers, or serve new load
growth instead of less efficient technologies. While coal-byits nature-has a high carbon content,
clean coal technologies (CCT) have a lower carbon emissions rate than pulverized coal (PC)boilers
used today. For example, a 34% efficient pulverized coal boiler has a carbon emission rate of 260
g/kWh, while a 42% efficient integrated coal gasification combined cycle (IGCC) facility has a rate
20% lower, or 210 g/kWh. So for every Gigawatt-hour (GWh) of electricity generated by IGCC
(relative to a PC boiler) 50 metric tons of carbon would be avoided (not emitted). By 2020, advanced
coal-fired plants may achieve 60% efficiency through R&D, reducing their carbon emission rate to
150 g/kWh, and saving 110 tons per GWh relative to an average current-day coal plant.
However, most CCTs are not currently considered "commercial" for power generation
applications, so their capital and operating costs have a technology risk premium. (In the AE099 the
risk premium -the difference in capital cost between the first-of-a-kind and fifth-of-a-kind plant-
is equivalent to $515/kW.) This technology risk premium makes CCTs more expensive than the
current technology of choice, natural gas combined cycle (NGCC).
A number of studies have examined alternative incentive mechanisms to accelerate the deployment
of CCTs (see Spencer 1996 for a review). Three studies derived the level of CCT incentives
necessary to be cost-competitive with NGCC (South, et al, 1995; Spencer, 1996; and CURC, 1998).
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The Coal Utilization Research Council (CURC) determined that the following incentives are
necessary for the first 1,500 MW ofeach type of CCT:
Investment tax credit: tax credit equal to 20% of owner's equity investment, applicable to first 4
years of construction.
Production tax credit: tax credit based on design average net heat rate, with an incentive (0.70 -
1.30 cents/kWh depending on heat rate) for years 1-5, and a lower incentive (0.45-1.10
cents/kWh depending on heat rate) for years 6-10. The production tax credit would apply to the
years 1-10 of operation.
Financial Risk Pool: the Federal government would establish a financial risk pool applicable in
years 1 thru 3 of operations to offset costs arising from technology non-performance (relative to
design) during start-up and initial operation. The total amount of recoverable costs is limited to
5% of total project installed cost.
While these financial incentives are needed to make CCTs competitive with NGCC (using a cash
flow analysis), the level of incentives exceed the carbon value targets inherent in the Moderate and
Advanced scenarios of this study. For example, a production tax credit of0.25¢/kWh over 10 years
is equivalent to $24/tC, and a 0.50¢/kWh production tax credit is equal to $48/tC. Thus,
implementation of the full set of incentives proposed by CURC would translate into a carbon value
greater than $200/tC. This value could be reduced depending on the amount of additional capacity
that these incentives would spur after they have expired.
7.2.3 Barriers Analysis
Barriers to the potential improvements in electricity technology have been broadly classified in
Table 7.6 and defined just below the table. Also listed are some of the policies to be analyzed using
the CEF-NEMS model. The mark in the cells of the table mark where a potential policy responds to
the barrier identified.
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Table 7.6 Barriers and Policies
Produc-
Wind
En-
Net
Nation-
Stricter
Carbon
tion Tax
Facilita-
hanced
metering
wide
Air
Cap and
Credit
tion
R&D
Restruc-
Emissio
Trade
turing
n
1) Generation
costs do not
X
X
include all costs of
X
X
emissions
2) Regulated
market structure
X
X
X
does not reward
innovation well
3) Regulated
market structure
X
X
X
limits competition
4) Public benefits
of R&D are not
X
captured by
investors
5) System
planning and
operations do not
X
X
X
handle non-
dispatchability well
1) Emissions costs: The absence of full costs of emission damages from fossil generators distorts
the electricity generation markets towards fossil fuels. Existing control costs are embedded in
the cost of electricity. While current EPA regulations enforcing the Clean Air Act and other
Federal legislation impose control costs on the marginal emitter of criteria pollutants like SO2
and NOx, these control costs are not the same as the damage costs. And inasmuch as the
regulations allow some older fossil generators to continue to emit, not all existing fossil
generators incur operating cost penalties. Furthermore, there are several emissions produced
by fossil fuel combustion that are not capped today. These include carbon, mercury, and
smaller particulates (2.5 micron). No costsare currently included to account for damages from
these pollutants.
2) Innovation rewards: The traditional, regulated electricity market allows utilities a reasonable
return on their investment, as defined by regulators. With a relatively low-risk return based on
capital investment, there is little monetary incentive to lower costs or improve efficiencies.
Guaranteed returns can even provide an incentive to hang on to non-cost-effective plants until
they are fully amortized, and to replace cost-effective plants that are fully amortized. The
industry has relied on regulatory pressure to keep costs down, and to use regulatory lag to
reward innovation.
3) Competition: In addition, the regulated electricity market established exclusive franchises that
limited the amount of competition. The "regulatory compact" of limited competition for
regulated rates worked well to keep prices reasonable and extend the benefits of electrification to
all, especially when economies of scale were large and thus large monopolists could lower
prices better than small firms. However, this system lessened the opportunity for innovation
through competition.
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4) R&D: While the traditional regulated utility structure did not strongly drive innovation, it did
provide capital for research and development. In today's more competitive electric sector, R&D
funding has decreased dramatically. The barrier to increased R&D is the publicgoods aspect of
R&D. Companies will not fund the optimal societal level of basic R&D of new technologies,
since many of the benefits of such research will flow to their competitors and to other parts of
the economy. This is true of many industries, and is one of the main rationales forgovernment-
funded long-term, pre-competitive research in industries that have a vital role in the U.S.
economy.
5) Non-dispatchability: The electric system requires extensive control over thelevel of production
in order to match demands precisely. Intermittent sources and generation sources outside of the
direct control of the system operators are not easily incorporated into system planning and
operations. Consequently, there has been a devaluing of their contribution to the system, which
has created a barrier to their widespread acceptance.
7.3 METHODOLOGY
7.3.1 Modifications to CEF-NEMS for the BA U Scenario
Besides the policy scenarios to be analyzed, a new Business As Usual (BAU) scenario was
established for this CEF study. The BAU scenario was developed through limited modifications to
the AEO99 Reference scenario. These modifications to the Electricity Market Module (EMM) of
CEF-NEMS were made to represent technologies and markets more realistically. A brief general
description of the EMM can be found in Chapter 3. The changes for the electric sector to the BAU
scenario are documented below:
Wind. In CEF-NEMS some of the EMM constraints imposed by NEMS on wind market penetration
have been altered. These changes were made to more accurately reflect what the authorsfeel to be
the current market for wind. These changes did not deal with the actual operation of a wind plant
(e.g., operating cost, capacity factor) but with market-related growth limitations imposed in NEMS.
While these changes were made for all three scenarios, i.e., including the BAU scenario, they had
no impact on the BAU scenario results because very little wind penetrates in that scenario and
therefore the constraints in the EMM linear program are not binding. Thus these modifications
could alternatively be considered to reflect a set of policy changes in the Moderate and Advanced
scenario that facilitates wind deployment (see Table 7.2) The constraints modified are listed below in
Table 7.7 and described in detail in Appendix C-4.
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Table 7.7 Modifications to NEMS Constraints on Wind
NEMS EMM
CEF-NEMS EMM
Maximum construction of IGW in a region in
Deleted
a single year
Short-term supply elasticity: 70% increase in
Reduced to 5% penalty for annual national
capital costs for national growth above 14% per
growth between 20 and 30% and 15% penalty
year
above 30% growth.
Intermittency: Max wind generation < 10%
Replaced by capital cost multiplier below
regional generation
Capital cost increased by a factor of 3 for 90%
Capital cost increased by as much as 60% as
of all wind resource due to site access,
regional market penetration rises from 10% to
intermittency, & market factors
20%
Biomass cofiring. All the scenarios shown here, including the BAU scenario, allow biomass cofiring
of coal plants (the AEO99 reference case did not).
Nuclear. For the AEO99, "In the reference case, it is first assumed that a retrofit costing $150 per
kilowatt will be required after 30 years of operation to operate the plant foranother 10 years." (EIA,
1998b) If its "going forward" cost, including the 10-year $150/kWe incremental capital charge, is
less than the minimum cost of new baseload capacity, then the nuclear unit is assumed to continue
in operation through its 40-year license period. If not, then the plant isassumed to be retired at the
30-year date. The $150/kWe charge is intended to account for large equipment replacement
expenditures, such as, for example, a steam generator in the case of a pressurized water reactor
(PWR). If a PWR has had a steam generator replaced in the severalyears prior to year 30 then the
$150 charge is not applied. In addition, in the AEO99 reference case, "A more extensive capital
investment ($250 per kilowatt) is assumed to be required to operate a nuclear unit for 20 years past
its current license expiration date." (EIA 1998b) It is assumed that the operating license will be
extended from 40 to 60 years if the sum of the going-forward cost and a capitalization of thelife
extension cost over 20 years is less than the minimum cost of constructing replacement baseload
capacity. Otherwise the plant is retired.
The nuclear plant refurbishment and relicensing costs have been modified in the CEF-NEMS to
reflect more closely the empirical estimate of $180/kW forthese activities. (See Appendix E-3 for the
calculation.) This entailed retaining the $150/kW charge at year30, but reducing the year 40 charge
to $50/kW to approximate the total $180/kW charge for life extension and license renewal. Recent
comments from EIA state that the $150/kW and $250/kW costs are not capital expenditures but are
to represent age-induced increases in operating costs.
Geothermal. Construction of geothermal capacity is modeled on a site-by-site basis within NEMS. If
any capacity is added to a site, there is a waitingperiod constraint before any additional capacity can
be added at that site. In the AEO99, this waiting period was set at six years, greatly slowing the speed
that any geothermal could be added. In addition, the NEMS model uses a logit function for
allocating capacity additions between technologies. This serves to avoid the "knife-edge" problem of
one technology receiving all capacity additions even if it is just slightly below the cost of others.
However, the function can cause a very small amount of capacity to be added at all geothermal
sites. The waiting period then forecloses any additions for another six years, thereby greatly
reducing the amount of geothermal capacity that can be built over the study period. For the
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scenarios in this study, we changed the length of the waiting period to zero SO that capacity can be
added the next year if it is economical to do SO.
7.3.2 Policy Modeling within CEF-NEMS
As discussed in Chapter 3, most of the results developed for the electric sector were modeled almost
entirely in the EMM of CEF-NEMS. A brief general description of the EMM can be found in
Chapter 3. Table 7.8 shows the analysis approach used for policies specific to the electric sector.
The detailed parameter settings that varied between the Moderate and Advanced scenarios can be
found in Appendix C-4 along with details on their derivation. Policies were not examined
individually, but rather as a set within each of the three scenarios - BAU, Moderate, Advanced.
Table 7.8 Modeling of Policies
Policy
Modeling Approach
Production Tax Credit
For each renewable technology, the present value of the 10 year tax
credit is levelized over plant lifetime and inserted as the EMM parameter
for tax credits
Renewable Portfolio
The PTC for non-hydro renewables (above) was extended from 2004 to
Standard
2008. The biomass cofiring tax credit was extended to 2014.
Expanded R&D
Two steps are involved: 1) To estimate how much expanded R&D will
improve a technology's cost and performance, existing, published
estimates of future technology improvements were used. 2) These
estimates were inserted into the technology parameters of the EMM that
characterize each technology.
Net metering
CEF-NEMS competes fuel cells and PV with retail electricity prices in the
residential sector. Limits can be placed on the amount of sales displaced
by such on-site generation
Restructuring
Marginal cost pricing is used in EMM for all regions
Discount rates are increased in EMM
Amortization periods are shortened in EMM
Reserve margins are decreased in EMM
Tighter SO₂ limits
The allowed ceiling for SO₂ was reduced from 895 million tons in 2010 to
448 million tons in 2020 in steps of 45 million tons per year
Carbon Cap and Trade
Within CEF-NEMS, fuel costs are raised based on the expected price of
carbon allowances. These costs are used in all sectors' analyses. not just
the electric sector.
7.4 SCENARIO RESULTS
7.4.1 Overview
The scenarios as described have been run through the CEF-NEMS model, in conjunction with the
scenarios defined in the end-use sectors. The key results of the three scenarios are shown in the
following tables and figures.
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Table 7.9 Generation by Scenario by Electric Generators (TWh) (No cogeneration)
2010
2020
Fuel
1990
1997
BAU
Mod.
Adv.
BAU
Mod.
Adv.
Total
2850
3190
3920
3680 (-6%)
3520 (-14%)
4420 3800 (-12%) 3440 (-22%)
Note: BAU = Business-as-Usual scenario; Mod. = Moderate scenario; Adv. = Advanced scenario.
Numbers in parentheses represent the percentage change compared to the BAUscenario.
Table 7.10 Primary Energy Use by Scenario and Fuel in the Electric Sector
(quadrillion Btu) (No cogeneration)
2010
2020
Fuel
1990
1997
BAU
Mod.
Adv.
BAU
Mod.
Adv.
Coal
16.1
18.6
21.2
20.2 (-4%)
14.4 (-32%)
22.4
20.7 (-8%)
10.9 (-51%)
Natural Gas
2.88
3.4
6.6
5.0 (-24%)
6.1 (-9%)
8.8
5.9 (-34%)
7.2 (-18%)
Distillate
0.02
0.1
0.0
0.0 (-0%)
0.0 (-33%)
0.0
0.0 (-33%)
0.0 (-33%)
Residual
1.23
0.8
0.2
0.1 (-26%)
0.1 (-37%)
0.2
0.1 (-20%)
0.1 (-47%)
Nuclear
6.20
6.7
6.2
6.2 (-0%)
6.7 (9%)
5.6
4.9 (-11%)
6.4 (15%)
Hydro
*
*
3.6*
3.6
3.3
3.3 (-0%)
3.3 (0%)
3.3
3.3 (-0%)
3.3 (0%)
Non-hydro
*
0.8
1.5
2.3 (55%)
3.8 (161%)
2.3
3.2 (41%)
4.6 (98%)
renew
energy**
Electricity
0
0.3
0.3
0.3 (-0%)
0.3 (6%)
0.3
0.3 (-0%)
0.3 (0%)
Imports
Total
30.07
34.3
39.3
37.5 (-5%)
34.8 (-11%)
42.9
38.6 (-10%)
32.8 (-24%)
Note: BAU = Business-as-Usual scenario; Mod. = Moderate scenario; Adv. = Advanced scenario.
Numbers in parentheses represent the percentage change compared to the BAUscenario.
* 1990 Hydro includes non-hydro renewable energy.
** Hydro, solar, and wind primary energy use assume a fossil-fuel heat rate equivalent of 10,280
Btu/kWh. Nuclear plants assume avalue of 10,623 Btu/kWh.
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Table 7.11 Generation by Scenario and Fuel in the Electric Sector
(TWh) (No cogeneration)
2010
2020
Fuel
1990
1997
BAU
Mod.
Adv.
BAU
Mod.
Adv.
Coal
1800
2020
1940 (-4%)
1400 (-31%)
2170
2000 (-8%)
1060 (-51%)
Petroleum
80
22
17 (-23%)
14 (-36%)
18
15 (-17%)
11 (-39%)
Natural Gas
300
890
680 (-24%)
880 (-1%)
1270
830 (-35%)
1140 (-10%)
Nuclear
630
580
580 (0%)
630 (9%)
520
460 (-11%)
600 (15%)
Power
Renewables
390
410
460 (13%)
590 (45%)
440
500 (13%)
630 (42%)
Hydro
350
320
320 (0%)
320 (-0%)
320
320 (0%)
320 (0%)
Wind
3
8
37 (386%)
140 (1760%)
9
51 (495%)
160 (1770%)
Biomass
4
26
37 (43%)
47 (83%)
31
26 (-17%)
48 (55%)
- Dedicated
4
11
15 (35%)
22 (100%)
19
16 (-12%)
32 (69%)
- Cofired
0
15
22 (49%)
25 (70%)
13
10 (-24%)
17 (33%)
Geothermal
16
24
37 (55%)
50 (109%)
47
67 (41%)
67 (41%)
Other
15
28
28 (0%)
28 (0%)
31
31 (0%)
31 (0%)
Other
-3
-1
-1 (0%)
-1 (0%)
-1
-1 (0%)
-1 (0%)
Total
3190
3920
3680 (-6%)
3520 (-10%)
4420
3800 (-14%)
3440 (-22%)
Net Imports
32
30
30 (0%)
32 (7%)
27
28 (4%)
30 (0%)
Note: BAU = Business-as-Usual scenario; Mod. = Moderate scenario; Adv.= Advanced scenario.
Numbers in parentheses represent the percentage change compared to the BAUscenario.
Table 7.12 Carbon Emissions by Scenario and Fuel in the Electric Sector
(MtC) (No cogeneration)
2010
2020
Fuel
1990
1997
BAU
Mod.
Adv.
BAU
Mod.
Adv.
Petroleum
26.8
17.6
4.6
3.4 (-26%)
2.9 (-37%)
3.7
3.0 (-19%)
2.1 (-43%)
Natural Gas
41.2
44
95
72 (-24%)
87 (-9%)
127
85 (-33%)
98 (-23%)
Coal
409
471
545
521 (-4%)
370 (-32%)
578
531 (-8%)
282 (-51%)
Total
477
532
645
597 (-7%)
460 (-29%)
709
622 (-12%)
382 (-46%)
Note: BAU = Business-as-Usual scenario; Mod. = Moderate scenario; Adv.= Advanced scenario.
Numbers in parentheses represent the percentage change compared to the BAU scenario.
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Table 7.13 Capacity of Selected Technologies in the Electric Sector
(GW) (No cogeneration)
2010
2020
1990
1997
BAU
Mod.
Adv.
BAU
Mod.
Adv.
Coal Steam
300
305
307
303
262
320
305
225
Other Fossil Steam
144
139
81
76
56
77
56
33
Combined Cycle
8
16
126
107
122
199
134
149
Combustion
46
78
149
142
135
184
145
133
Turbine/Diesel
Nuclear Power
100
99
78
78
87
72
64
83
Renewable
82
88
93
103
136
98
111
145
Hydro
75
78
79
79
79
79
79
79
Wind
2
2
3
12
43
4
15
47
Biomass
2
2
2
3
4
3
3
5
Geothermal
3
3
4
5
7
7
9
9
Other
I
4
5
5
5
5
5
5
Other
18
20
22
22
22
22
22
22
Total
698
744
855
831
819
971
837
789
Note: BAU = Business-as-Usual scenario; Mod. = Moderate scenario; Adv.= Advanced scenario.
Table 7.14 Other Air Emissions in the Electric Sector (No cogeneration)
2010
2020
1990
1997
BAU
Mod.
Adv.
BAU
Mod.
Adv.
SO₂ Emissions (MtSO₂)
15.6
11.6
8.4
8.3
8.5
8.2
8.2
4.3
Allowance Price ($/ton)
-
77
224
211
98
114
96
161
NO Emission (MtNOx)
7.5
5.3
3.7
3.5
2.7
3.8
3.5
2.2
Note: BAU = Business-as-Usual scenario; Mod. = Moderate scenario; Adv.= Advanced scenario.
Table 7.15 Electric Sector Fuel and End-Use Electric Prices ($/MBtu)
2010
2020
1997
BAU
Mod.
Adv.
Adv.
BAU
Mod.
Adv.
Adv.
w/o C
w/o C
Petroleum
2.88
3.79
3.78
5.01
3.94
4.19
4.16
5.56
4.49
Products
Natural Gas
2.70
3.01
2.67
3.40
2.68
3.04
2.53
3.09
2.37
Coal
1.27
1.06
1.05
2.34
1.05
0.93
0.92
2.20
0.91
Electricity (c/kWh)
6.9
6.1
5.6
6.6
5.9
5.5
5.3
6.1
5.5
Note: BAU = Business-as-Usual scenario; Mod. = Moderate scenario; Adv.= Advanced scenario.
Advanced scenario prices include carbon values.
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Fig. 7.1 Total Generation Including Cogeneration (TWh) (No cogeneration)
5000
4500
4000
3500
3000
TWh
2500
BAU scenario
2000
-
Moderate scenario
1500
Advanced scenario
1000
500
0
1995
2000
2005
2010
2015
2020
Fig. 7.2 BAU Scenario Total Generation by Fuel (TWh) (No cogeneration)
BAU scenario
5000
4500
4000
Other
3500
Geothermal
Biomass
3000
TWh
Wind
2500
Hydro
2000
Nuclear Power
1500
Natural Gas
1000
Petroleum
500
Coal
0
1995 1998 2001 2004 2007 2010 2013 2016 2019
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Fig. 7.3 Moderate Scenario Total Generation by Fuel (TWh) (No cogeneration)
Moderate scenario
5000
4500
4000
3500
Other
Geothermal
3000
TWh
Biomass
2500
Wind
2000
Hydro
1500
Nuclear Power
1000
Natural Gas
500
Petroleum
Coal
0
1995 1998 2001 2004 2007 2010 2013 2016 2019
Fig. 7.4 Advanced Scenario Total Generation by Fuel (TWh) (No cogeneration)
Advanced scenario
5000
4500
4000
Other
3500
Geothermal
3000
Biomass
TWh
2500
Wind
2000
Hydro
1500
Nuclear Power
1000
Natural Gas
Petroleum
500
Coal
0
1995 1998 2001 2004 2007 2010 2013 2016 2019
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Fig. 7.5 Gas-fired Generation Weighted Average Heat Rate (Btu/kWh)
12000
10000
8000
BTU/kWh
6000
BAU scenario
4000
Moderate scenario
Advanced scenario
2000
0
1995
2000
2005
2010
2015
2020
Fig. 7.6 Biomass Cofired Generation (% of Coal Generation)
2.0%
1.8%
1.6%
1.4%
BAU
% Coal Generation
1.2%
Moderate
1.0%
Advanced
0.8%
0.6%
0.4%
0.2%
0.0%
2000
2005
2010
2015
2020
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Fig. 7.7 Wind Capacity (GW)
50
45
40
35
30
BAU scenario
GW
Moderate scenario
25
Advanced scenario
20
15
10
5
0
2000
2005
2010
2015
2020
Fig. 7.8 Dedicated Biomass Capacity (GW)
6
BAU scenario
5
Moderate scenario
Advanced scenario
4
GW
3
2
1
0
2000
2005
2010
2015
2020
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Fig. 7.9 Geothermal Capacity (GW)
10
9
8
7
6
GW
5
4
3
BAU scenario
Moderate scenario
2
Advanced scenario
1
0
2000
2005
2010
2015
2020
7.4.2 BAU Scenario
The BAU scenario, as described above, has similar results to the AEO99 in total generation, but
lower carbon emissions. Total generation by 2020 is 26 TWh lower and total generation capacity is 3
GW lower in the BAU scenario. These are less than 0.7% different from the AEO99 results.
However, the mix of generation changed because of the change in the nuclear relicensing cost,
biomass cofiring, and geothermal expansion described in section 7.3.1. Nuclear capacity in the BAU
case in 2020 totaled 72 GW instead of the 49 GW in the AEO99 Reference case. Geothermal
capacity increased from 3.5 GW to 6.7 GW. As a result, fossil and biomass capacities were reduced
by 29 GW and total carbon emissions dropped 5.1%, from 745 MtC to 709 MtC.
Within the electric sector, no changes were made to the policies implemented within the AEO99.
The major policies in AEO99 with regard to the electric sector are the Clean Air Act Amendments
of 1990, the Energy Policy Act of 1992, EPA's Ozone Transport Rule for 22 Northeast and Midwest
states, and electricity restructuring in five regions. These five regions are California, New York,
New England, the Mid-Atlantic Area Council (consisting of Pennsylvania, Delaware, New Jersey,
and Maryland), and the Mid-America Interconnected Network (consisting of Illinois and parts of
Wisconsin and Missouri).
Besides nuclear relicensing costs, the main changes to the electric sector BAU scenario are in the
modeling of wind, biomass cofiring, and geothermal as described above. The changes to wind had
very little impact on the BAU scenario, because the changes mainly loosened constraints on the
amount wind could grow. These constraints were not the limiting factor for wind in the BAU
scenario. Biomass cofiring was not included in the AEO99 reference case, but is allowed in the
BAU scenario of this study. While biomass use was higher in the years 1998-2017, by 2020 biomass
use was higher in the AEO99 than in the BAU scenario. This is largely due to the increase in
generation from nuclear power.
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7.4.3 Moderate Scenario
The inputs for the Moderate scenario were altered to model thepolicies defined in section 7.2. The
1.5c/kWh Production Tax Credit for wind and biomass through 2004, le/kWh for biomass cofiring
through 2004, complete restructuring of the national electricity market by 2008, and enhanced
R&D programs were all included.
The Moderate scenario shows a 5% decline in primary fuel consumption by 2010 and 10% by 2020
as compared to the BAU scenario (Table 7.10). These are mainly due to the decrease in demand
from the end-use sectors. (In this discussion, declines are relative to whatthe values are in the BAU
scenario, not in absolute terms.) Total end-use demand declined by 6% and 12% in the two years,
respectively (Table 7.9). Total carbon emissions declined 7% and 12% compared to the BAU
scenario (Table 7.12). Overall capacity declined in response to the lower demand (Table 7.13), but
most of the decline was in the combined cycle (down 65 GW in 2020) and combustion turbine (down
39 GW) capacities. Coal capacity only declined 5% or 15GW, while nuclear capacity declined by 8
GW from the BAU amount. On the other hand, wind increased by 11 GW over the BAU case by
2020, to 15 GW because of the incentives and improved technologies.
SO₂ emissions remain at the cap in the Moderate scenario but the allowance price needed to keep
emissions at the cap drops between 6% and 16% (Table 7.14). With lower demands and improved
new technologies, it is easier to meet the limits so the market price of allowances declines. NO
levels decline as well.
Fuel prices decline in the Moderate scenario versus the BAU scenario because of the lower
demands (Tables 7.10 and 7.15). Similarly, electricity prices are down by 8% in 2010 and 4% in
2020.
7.4.4 Advanced Scenario
The Advanced scenario's inputs were modified to incorporate the additional changes described in
section 72. In the Advanced scenario, demand for generation (not including cogeneration) is lower
than the BAU scenario by 14% and 22% in 2010 and 2020, respectively (Table 7.9). As a
consequence, primary fuel consumption declines 11% and 24% (Table 7.10), while carbon
emissions decline 29% and 46% (Table 7.12). (In this discussion, declines are relative to what the
values are in the BAU scenario, not in absolute terms.) These declines show the large impact of
carbon allowances, improved technologies, and the renewable production tax credits. Coal-fired
generation declines 51% by 2020 with capacity declining from 320 GW in the BAU scenario to 225
GW in the Advanced scenario (Tables 7.11 and 7.13). The average capacity factor of coal also drops
from 77% (base load) to 54% (intermediate load) as carbon allowances raise the variable cost ofcoal
production. Oil and gas average capacity factors increase from 32% to 42% since they are less
affected by the carbon-related costs. This capacity factor would be higher, but with the increase in
wind capacity, some of the gas capacity is used to firm the wind power and SO might have a lower
capacity factor.
The Advanced scenario has a more rapid advance in theaverage efficiency of gas-fired generation
(Fig. 7.5). The average heat rate declines more quickly as 25 GW more combined cycle capacity is
brought on in the years 2000-2005 than in the BAU scenario, while 6 GW of less-efficient
combustion turbines are not built. An additional 10 GW of inefficient gas and oil-fired steam
capacity is retired. Furthermore, the additions are more heavily weighted towards the advanced gas
technologies. While in reality, some of the improvements in the advanced technologies would be
incorporated into the conventional technologies, in these scenarios only the advanced technologies
were improved. If the conventional technologies were changed as well, overall efficiency could be
higher or lower than these results. Efficiency could be higher because more technologies would be
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improved, but lower because the improved conventional technologies may be more economic and
displace some of the advanced technology that was added inthis scenario.
The heat rate is further improved because of changes in the use of inefficient plants. With the
advent of the carbon allowances requirement, inefficient gas and oil steam plants are used more
infrequently and 10 GW are retired by 2005. By 2020, 47 GW more of these plants are retired than
in the BAU scenario. Heat rates for new gas technologies decline further (approaching 70%
efficient, or 4875 Btu/kWh, for combined cycle plants with fuel cells as a ternary cycle), but the
average heat rate does not decline asmuch, reaching only 54% efficient by 2020.
Other air emissions (SO₂ and NO.) are reduced in the Advanced scenario, compared to the BAU
scenario (Table 7.14). SO₂ emissions (as a surrogate for PM emissions) were further restricted over
the years 2011-2020, culminating in a 50% reduction from the BAU ceiling in the final year.
Because of the lower demands and new technologies, the new ceiling was metwith little increase in
the permit price. Its highest value was $185/ton in 2016. An Advanced scenario sensitivity without
the lowered ceiling had the permit price dropping to zero because emissions were below the existing
ceiling by 2020.
Wind capacity grows to 16 GW installed by 2005, due in part to the PTC, carbon limits, and
improving economics of wind. To conform with the requirements of the RPS, it continues to grow
after the PTC expires, rising to 43 GW in 2010 and 47 GW in 2020. This growth represents over
34% of all new capacity built between 2005 and 2020 and 10% of capacity builtpost-2010.
Biomass use grows as well, both dedicated capacity and cofiring. Cofiring grows rapidly between
2000 and 2005, displacing approximately 1.8% of coal generation (Fig. 7.6). The 1 c/kWh cofiring
production tax credit improves the cost-effectiveness of biomass between 2000 and 2014. Starting
around 2005, the carbon charge provides a similar inducement, especially since biomass directly
displaces coal. Dedicated biomass generation grows slowly, but cofiring remains at relatively the
same percentage of coal production. Consequently, as coal production declines, so does cofiring.
Total non-cogeneration biomass production peaks in 2015 at 52 TWh, then declines to 48 TWh in
2020 (Table 7.11).
As shown by the demand sensitivity analysis of section 7.5.3, the generation from clean sources like
renewables can be sensitive to the overall growth in electricity capacity. If the end-use demand
policies of the Advanced scenario are not implemented or are not as effective as estimated here,
larger electricity demand will spur additional electric capacity growth and more opportunities for
clean energy supply technologies. Similarly, if advances infossil generation technologies are not as
much as expected in the two scenarios, wind capacity increases (Table 7.17).
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7.5 DISCUSSION OF RESULTS
While electric sector-specific technologies and policies (discussed below) are important to the
results, a critical factor is the change in non-cogenerating electricity demands by the buildings and
industry sectors under the various scenarios (Fig. 7.1.) (Industrial cogeneration and district energy
systems can play a large role in the reduction of electricitydemand growth for this sector, providing
from 70 to 120 GW of capacity that would otherwise need to be provided by this sector.) The electric
sector is only a middleman in that it transforms energy from one form toanother for use by others.
While it may control the types of primary energy used to make electricity, the growth or lack of
growth in demand plays an important role in the amount ofprimary energy and type of technologies
used. Advanced technologies are limited to the relatively fixed amount of capacity expansion needed
to meet demand over a given scenario plus any retirements. Incentives to accelerate their
deployment have less success if demand growth is low, unless other incentives for accelerated
retirement of existing capacity are also used.
Another critical factor that is external to the sector is the price of fuels (Table7.15.) Coal prices stay
relatively the same between the BAU and Moderate scenarios. In the Advanced scenario, the
carbon charge of $50/tC increases the price of coal by $1.30/MBtu. This raises the price by 120% to
145% and is a major cause in the lowering of coal use. Natural gas prices decline by 11% to 16% in
the Moderate scenario because of a lowering of demand for gas inall sectors (12% by 2020). Even
in the Advanced scenario including carbon charges, prices rise only 13% in 2010 and by 2% in 2020
over the BAU scenario. Subtracting the carbon charges, the raw prices for gas drop significantly
from the BAU prices.
7.5.1 Key Technologies
A number of changes were made to each of the production technologies. In the BAU scenario,
wind, biomass cofiring, geothermal and nuclear plant modeling fundamentals were changed. In the
Moderate scenario the most significant change happened to the renewable technologies. Capital and
operating costs, and capacity factors were adjusted based on EIA's estimates of the High
Technology scenarios of the AEO99. EIA's High Technology for fossil plants are largely devoted to
lowering the cost of the technology rather than improving the efficiency. Capital costs in the
Moderate scenario were lower based on EIA estimates of theimpact of enhanced R&D. Values for
renewables were largely unchanged between the Moderate and Advanced scenarios. Fossil
technologies in the Advanced scenario includes more radical advances in fossil technologies such
as ternary cycles for coal and gas combined-cycle plants. These raise the efficiency greatly by
using a fuel cell as a front-end cycle before the other components. Carbon sequestration was also
allowed within the model in conjunction with advanced fossil technologies after 2010 (through a
$50/tC increase in operating cost.) However, the parameters for the advanced technologies differ
most greatly from the Moderate scenario in the latter part of the study period. With overall demand
relatively flat post-2010, there is less call for new capacity and less opportunity for these advances to
make a significant impact (Fig. 7.1 and Table 7.13).
The importance of advanced coal technologies such as IGCC are largely dependent on the cost of
fuel (including any carbon allowance cost) and overall demand. In the BAU scenario, 15 GW of
IGCC is brought on-line by 2020, along with 5 GW of conventional coal. In the Moderate scenario,
however, gas prices in 2020 are 13% lower than in the BAU scenario (due to lower gas demands);
only 5 GW of IGCC and 1.6 GW of conventional coal are added. In the Advanced scenario demand
is lower still and coal prices more than double due to the carbon allowance cost. No IGCC capacity
is brought online and just the 1.4 GW of conventional coal that is already planned.
Of the renewable technologies, wind received the most benefit from improvements in technology
and other policies. Its capacity in 2020 grows from 4 GW in the BAU scenario to 15 GW in the
Moderate scenario to 47 GW in the Advanced scenario (Fig. 7.7). There is a large growth of wind
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through 2008 because of the PTC and the RPS (to 11 GW in the Moderate and 39 GW in the
Advanced scenarios). In the Advanced scenario, economics (and the carbon chage) cause wind to
continue to grow beyond these levels in later years. In the Moderate scenario additional growth is
more modest.
PV also plays a role with penetration in buildings spurred by the Million Solar Roofs (MSR)
Program at DOE and the adoption of net metering policies. The MSR has collected commitments
for over 900,000 roof-top photovoltaics and active solar hot water units by 2010. These commitments
are also a reflection of the public's interest in green power, a range of benefits associated with
distributed generation, and the continuing improvement in the economics of solar technologies. In
the CEF Advanced scenario, the economics of PV are improved by 2020 to the point that over 2.6
million PV rooftop systems are estimated to generate approximately 17 TWh/year. This trend could
became a signficant factor in U.S. carbon reductions after 2020 as the technology continues to
improve.
Geothermal capacity showed more rapid growth in the two policy scenarios, with capacity 38% to
77% higher by 2010 for the Moderate and Advanced scenarios, respectively (Fig. 7.9). However,
growth in the BAU scenario continues at a steady pace such that the ratios of capacity between the
three scenarios narrow.
7.5.2 Key Policies
The key policy driving the changes within the electric sector is the carbon allowance in the
Advanced scenario. The carbon allowance plays a role in two ways. First, because of its larger
impact on carbon-intensive fuels such as coal and inefficient oil and gas plants, no unplanned coal
plants were added and 83 GW of coal capacity was retired by 2020 in the Advanced scenario. In
addition, 112 GW of other fossil steam (oil and gas) were retired. (These compare to 20 GW of coal
added and 6 GW coal and 68 GW of other fossil steam capacity retired in the BAU scenario.)
Second, the carbon allowance directly impacts the variable cost of production, therebycausing the
remaining carbon-intensive technologies to lower their capacity factor. Nuclear power better
maintained its cost-effectiveness. Even without changes in the relicensing cost of nuclear power
beyond that in the BAU scenario, the Advanced scenario had 11 GW more of nuclear power in
2020, with generation up 15%.
Sensitivity cases run for the Advanced scenario without the carbon allowance show 62% more
generation from coal in 2020 than in the Advanced scenario, 22% less generation from gas, and
41% less generation from non-hydro renewables. Wind is the renewable energy form most
impacted by the carbon cap, with capacity in 2020 lower by 55% (or 26 GW) without the cap.
Restructuring also plays a significant role but with potentially contrary impacts. By removing
incentives for regulated utilities to retain capital investments that are no longer cost effective,
deregulation creates incentives for inefficient coal or other plants to retire when carbon emissions
are constrained and/or gas plants represent a more cost-effective option. (Economic retirements
were allowed in all three scenarios.) At the same time, however, real-time pricing becomes a more
important factor in the market, and the system load factorincreases. This means that less-utilized
plants (i.e. peakers and intermediate plants) may be called upon for a higherpercentage of time and
be more profitable. If coal plants are on the margin for a region, theywill be used more. Less new
capacity is needed to meet peak demands because of customer shifts in peak load requirements. In
the Advanced scenario, while generation dropped 2.3% between 2010 and 2020, generation capacity
declined by 3.7% (Table 7. land Table 7.13).
As mentioned in the section above, the PTC (either as apolicy in and of itself or as a surrogate for
the RPS) plays an important role in the growth of renewable capacity. By creating growth in wind
through 2004 or 2008, a strong base of capacity is developed that leads to further growth but at a
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slower pace after the PTC and RPS expire. In the Advanced scenario, wind generation grows by
over 1700% between 2000 and 2008. Wind capacity represents 23% of all additions in that period, but
accounts for a smaller 14% of the new capacity additions between 2008 and 2020. Since all capacity
additions decline in this latter period, there is only a 20% growth of wind capacity post 2008 (Fig.
7.7). Geothermal and dedicated biomass capacity also see an impact from the PTC and RPS, but not
as pronounced (Fig. 7.8 and 7.9). In the Advanced scenario they both roughly double through 2008
and then grow another 35% through 2020. In the Moderate scenario, where the PTC stops in 2004
and there is no carbon allowance nor RPS, growth is more modest. Wind roughly triples in that
time. Biomass grows 40% during the PTC but only 20% from 2005 to2020. Geothermal, on the other
hand, shows a more steady growth: 18% through 2004 and 150% more by 2020.
7.5.3 Uncertainties and Sensitivity Analyses
Sensitivity analyses are used to determine the impact of specific policies in connection with the
basket of policies that define each scenario. The relative importance of the renewable portfolio
standard, technology advances, and carbon allowances have beenexamined.
RPS Sensitivity. [NOT UPDATED YET] The RPS has a significant impact. When we removed the
RPS from the Advanced scenario, generation by non-hydro renewables fell to only 5.2% in 2010
(versus the prescribed 7.5%) and to only 4% in 2020 (versus 8.9% in the Advanced with RPS). Most
of the reduction occurred in wind generation which fell from 154 TWh in 2020 to 98 TWh.
Removing the RPS also decreases geothermal generation 13% in 2020 from 70 TWh to 61 TWh,
and biomass (both biomass cofiring and biomass gasification) 8% from 48 TWh to 44 TWh. Without
the RPS, both gas and coal generation increase, with coal showing almost a 5% increase in
generation in 2020 compared to the Advanced scenario with RPS. While significant renewables are
still present without the RPS, it certainly increases generation from renewables, even beyond the
RPS expiration date.
Fossil-fuel Technology Sensitivities. [NOT UPDATED YET] The technology advances used in
these scenarios are based on projections by various experts of the potential cost and efficiency
improvements. However, they are not necessarily what will occur; other experts have been more or
less optimistic. Sensitivity analyses has been conducted to examine a less optimistic future for the
cost and performance of IGCC and Gas CC plants. The parameters that were changed are listed in
Table 7.16. Further explanation of the values is in Appendix C-4. Renewables were not modified in
this sensitivity so are not included in the table. Table 7.17 shows the capacity changes for 2020 in
the Moderate and Advanced scenarios that result when future improvements in these technologies
are reduced.
Table 7.16 Fossil Technology Capital Cost and Heat Rate Sensitivities
5" Plant Capital Cost
(1997 $/kW)
Heat Rate (Btu/kWh)
Base
Year for Heat
Sensitivity
Base
Sensitivity
Rate
IGCC Moderate
942
1000
8333-6968
8400-7500
2000-2010
IGCC Advanced
942
900
6440-5690
7449-6800
2010-2020
Gas CC BAU
405
475
6927-6350
7200-6800
2000-2015
Gas CC Moderate
348
450
6919-6255
6749-6200
2000-2015
Gas CC Advanced
348
425
5539-4874
6199-5700
2010-2020
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Table 7.17 Changes in 2020 Capacity (GW) and Carbon Emissions (MMTC) with Less Optimistic
Projections of Future IGCC and Gas Combined Cycle Cost and Performance
Technology
Moderate
Advanced
Scenario
Scenario
Coal Steam
-2 (-1%)
+4 (2%)
Other Fossil Steam
+5 (8%)
-4 (-14%)
Gas Combined Cycle
-25 (-19%)
-34 (-24%)
Combustion Turbine
+8 (6%)
+10 (8%)
Nuclear
+8 (12%)
+2 (3%)
Wind
+3 (19%)
+11 (24%)
Biomass
+0.4 (14%)
+2 (35%)
Geothermal
+1 (13%)
+1 (15%)
Carbon emissions (MtC)
-3 (-1%)
+1 (0%)
Numbers in parentheses represent the percentage change
compared to the basic Moderate and Advanced scenarios
As expected gas combined cycle capacity shows the largest decrease in capacity due to lower
optimism with respect to the future improvements in gas combined cycle cost and performance
improvements. Also as expected, competing technologies like nuclear and renewables benefit when
their competitors cost more. Somewhat unexpectedly, carbon emissions decrease in 2020 as more
nuclear remains on line in the Moderate scenario. In the Advanced scenario, almost the same
amount of coal capacity retires. The lower SO₂ ceiling continues as the limiting factor. With higher
cost advanced technologies, the market price for SO₂ credits increases from $165/ton in the regular
Advanced scenario to $179/ton in the Advanced sensitivity scenario in 2020. Electricity prices also
increase over the regular scenarios by about 0.1c/kWh in both the Moderate and Advanced
sensitivities. Because of the availability of advanced technologies for renewables and combustion
turbines and the continued availability of relicensed nuclear plants as backstops, less R&D success
for combined cycle and IGCC technologies does not have a major impact on the overallresults.
Renewable Technology Sensitivities. Another set of sensitivities was performed with higher
renewable energy technology costs. Wind capital cost was raised 20% and biomass capital cost was
raised 25%. based on the uncertainty range listed in the EPRI study Renewable Energy Technology
Characterizations (EPRI 1997). As a consequence, wind capacity in the Advanced scenario
declined 46% from 47 GW to 25 GW in 2020. Dedicated biomass declined 25%, from 5.1 GW to 3.8
GW (not including cogeneration.) Biomass cofiring remains slightly higher over time because of the
increased availability of biomass and coal capacity, but overall biomass generation declined 15%, or
7 TWh. Coal-fired generation increased by 6%, or 69 TWh while gas generation increased 9 TWh.
Because of the reduction in renewables and concomitant increase in fossil generation, carbon
emissions were 20 MtC (5%) higher. Whereas in the fossil technology sensitivity above, non-fossil
technologies buffered the carbon impact of less R&D success, the lack of R&D success for non-
carbon renewables had a more pronounced impact on carbon emissions.
Carbon Cap and Trade Policy Sensitivity. Although the impact of carbon allowances was described
in section 7.5.2 above, to further examine their importance we ran the Advanced scenario but
without any carbon caps and allowances, still keeping the other supply and demand policies. This
makes a large impact on the use of coal; generation is 62%higher than in the Advanced scenario in
2020. Coal capacity is 29% higher, at 291 GW. This is still below the capacity in 1997, with only 3
GW added but 17 GW retired over the time period.
Natural gas, nuclear, and non-hydro renewables all have reductions in their generation by 20% to
30% as they are displaced by coal. Wind is hardest hit, with capacity reduced by 55% down to 21
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GW. The 1.5c/kWh PTC does not have the impact on renewable generation in that total generation
by 2010 represents only 5.0% of generation, rather than 7.6%. This means that a RPS of 7.5% with a
cap of 1.5 /kWh would not reach the full portfolio standard level. Carbon emissions increase by 45%
to 553 MtC. Overall demand increased by only 4% in 2010 and 3% in 2020 over the Advanced
scenario, so the large increase in coal and carbon output are mainly due to the change in the
relative price of fuels.
The SO₂ emissions cap policy is still in place so that emissions in 2020 are at 4.6 Mt SO₂, (S02 caps
have been halved from the Phase II Clean Air Act Amendment requirements to reduce particulate
matter emissions) 0.4Mt higher than in the Advanced scenario. In addition, the price of an SO₂
emissions allowance almost triples to $445/ton without the carbon cap. The price of coal is
$0.92/MBtu, $1.27/MBtu below the price in the Advanced scenario. However, this price is slightly
above the Advanced scenario's price with the $50/tC carbon allowance charge removed. Electricity
prices are lower, being only 5.2c/kWh by 2020. This is lower by 0.9c/kWh from the Advanced
scenario, and is 0.4c/kWh lower than the Advanced scenario even with the carbon charge removed
from the fuel component (Table 7.15). One reason for this is the Advanced scenario had much
more new construction, which increased the capital component of the electricity price by0.3¢/kWh.
Nuclear Sensitivities. One reason for the lack of penetration of new nuclear capacity is the capital
cost of new technology. Learning may eventually make plants cost-competitive, but the cost of the
first plant precludes their development. This has been called "lock-out" (EIA 1999). In CEF-NEMS
there are two factors that raise the capital cost of the first plants, as compared to the fifth-of-a-kind
plant that is entered. One is the Technical Optimism factor, which raises the cost of the firstnuclear
plant by 19% above the input fifth-of-a-kind plant cost, decreasing with subsequent plants. For the
Moderate and Advanced scenarios we removed this factor, justifying the removal by assuming a
policy of joint development with other nations so that plants elsewhere in the world provided the
technical knowledge to avoid the increase. The second factor is the learning factor, which raises the
first plant's capital cost by an additional 28% with subsequent plants having a lower factor. The
learning factor continues tolower the cost of plants beyond the fifth as capacity grows.
As a sensitivity to the Advanced scenario, we removed the learning curve factor for the first four
advanced nuclear plants (in addition to the Advanced scenario's 10% reduction in capital cost and
removal of the 19% technical optimism factor.) This removal could be reflective of a policy of
subsidizing the construction cost of the first four plants to make them the same as the fifth one. We
also slightly modified the construction schedule so that costs are spread more evenly over the
plant's construction period. These changes succeeded in lowering the average capital cost of the
first plant from $1822/kW to $1427/kW in 1997$. However, this still did not make nuclear cost-
competitive with advanced gas combined cycle plants or wind capacity (with the production credit).
The national average levelized cost for nuclear capacity in the 2005-2010 time-frame was
$39/MWh, while advanced gas CC plants had a peak cost of around $35/MWh in 2006 that then
declined over time. In three regions of the country (California/Nevada, Rocky Mountains, and
Florida) nuclear capacity had lower costs than gas CC for one or more years between 2004 and
2008. However, during those years renewable incentives were in place and in these regionswind or
geothermal capacity were the lowest cost options. Consequently, the renewable technologies were
selected instead of gas or nuclear.
As a further analysis of the cost of new nuclear technologies in comparison to gas-fired combined
cycle, the two were compared in a series of cases outside of the CEF-NEMS model by varying their
fuel price, capital costs, and efficiencies for the year 2020. A cost model comparing the life-cycle
cost was used that has previously been used in analyses of future technology cost comparisons
(Delene, et al. 1999). A reference nuclear plant was defined with values similar to those of theCEF-
NEMS runs, and a consequent levelized cost of $44.6/MWh. (The levelized costs in 2020 for a fifth-
of-a-kind plant from the BAU, Moderate, and Advanced scenarios were around $46, $45, and
$41/MWh, respectively.) A reference gas combined cycle plant was defined that had a lower
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efficiency (50%) and higher capital cost (615$/kW) than that used in the Advanced scenario,
resulting in a levelized cost of $36.6/MWh. In addition to calculating the levelized costs for
comparison of the two technologies, the cost model was used to estimate a breakeven carbon
allowance cost. For the reference cases, a carbon allowance charge of $80.4/tC will equalize the
cost of the nuclear and gas combined cycle plants. Table 7.18 shows the results for the various
cases.
Table 7.18 Sensitivity Analysis of Nuclear and Gas Levelized Costs
Levelized Cost
($/MWH)
Breakeven
Gas CC (or
Carbon
Nuclear
Coal
Charge ($/tC)
PFBC)*
1. Reference
44.6
36.6
80.4
2. Gas price escalated post-2020 at 0.8%
44.6
38.9
56.9
3. EIA AEO99 high economic growth gas price
44.6
39.3
52.8
4. EIA AEO99 high growth plus 1.3%/yr gas
44.6
43.8
escalation
8.0
5. Case 4 plus 10% reduction in nuclear capital
41.6
43.8
-21.8
cost
6. CEF Advanced scenario gas price and CC
44.6
25.4
272
technology
7. Coal-fired PFBC instead of Gas CC
44.6
37.5
33.8
*
The levelized price for the fossil technologies do not include any cost for a carbon charge.
The reference case uses a gas price of $3.24/MBtu, as in the 1999 AEO. Case 3 uses a gas price of
$3.63/MBtu, from the High Economic Growth case in the 1999 AEO. Cases 2 and 4 are similar to
Cases 1 and 3 except the price of gas wasassumed to escalate at 0.8% and 1.3% above inflation for
the subsequent years. Case 5 shows the impact of reducing the capital cost of the nuclear plant by
10%, as in the Advanced scenario. Case 6 represents the gas technology for 2020 as in the
Advanced scenario, with a heat rate of 4874Btu/kWh (70% efficient). Gas prices match the
Advanced scenario price of $2.36/MBtu (not including the carbon charge.) The final case shows the
levelized cost of an advanced pressurized fluidized bed combustor using coal. More details on the
parameters and results can be found in Appendix E-8.
The results show the sensitivity to gas prices, capital costs, plant efficiencies, andescalation rates, at
the same time showing that there are a combination of factors that would makenuclear power more
economic than gas CC. If gas prices rise (due either to supply and demand and/or arboncharges),
and technology advances for combined cycle plants don't occur, then an advanced nuclear plant
can be competitive. However, if gas CC can reach its efficiency targets, then nuclear power may
find it difficult to compete. Also, other supply sources such as renewables and demand reductions
through efficiency provide additional competition in the energy marketplace.
Gas Price Sensitivity Because natural gas plays such an important role for new capacity a set of
sensitivities to modify the gas price were run on the BAU and the Advanced scenarios. CEF-NEMS
does not allow the direct input of gas prices, so instead we reduced the technological progress to
zero for oil/gas drilling/exploration and reduced technological progress rates by 50% for
unconventional gas recovery and enhanced oil recovery. As a result, gas prices increase gradually
till by 2020 they are about 12% or 38¢/MBtu higher (Fig. 7.10).
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The most dramatic impact is on the amount of gas consumed, as expected. Gas consumption for
electric generation is down by 12% to 13% by 2020 in the two scenarios. In both cases, coal is used
to make up most of the reduction in generation, 81% in the BAU and 72% in the Advanced scenario.
Demand reduction is next and equals 10% of the reduction in gas generation in the BAU and 16%
in the Advanced scenario. Renewables have a largerimpact in the Advanced scenario, replacing
12% of the lost gas generation, with 9% of that from added wind capacity (4 GW). In the BAU
scenario, an additional I.IGW of nuclear is relicensed (making up 5% of the lost generation), but no
new nuclear plants are built. The Advanced scenario sees no change innuclear generation, despite
the 10% reduction in capital cost for new plants. Apparently, existing coal plants (non-retirement),
energy efficiency, and renewable resources are the marginal supplies that are brought on if gas
prices rise.
Fig. 7.10 Gas prices to electric generators with and without restrictions on technological progress
($/MBtu)
4.00
3.50
3.00
2.50
$/MBtu
2.00
BAU
1.50
BAU-Hi Gas Price
1.00
Advanced
Adv - Hi Gas Price
0.50
0.00
2000
2005
2010
2015
2020
Demand Sensitivity With the relatively flat electricity demand growth of the Advanced scenario,
there is little demand for new electric capacity. This reduces the opportunities for clean energy
supply technologies to enter the generation mix. We examined the impact of removing all the
demand-side policies in the Advanced scenario. In this case, electricity demand is 16% greater in
2020 than in the Advanced scenario and, as shown by the percentage changes, non-hydro
renewables and natural gas generation are impacted proportionately more than coal. However
because the other clean sources, nuclear and hydro, arenot impacted, the overall carbon impact is
almost directly proportional to the energy impact.
Table 7.19 2020 Demand Reduction Impacts in the Advanced Scenario (w/o cogeneration)
Advanced
Advanced scenario
Scenario
minus demand policies
Electricity Demand (TWh)
3442
3996 (+16)*
Coal Generation (TWh)
1065
1213 (+14)
Gas Combined Cycle Generation (TWh)
1134
1428 (+25)
Non-hydro Renewables Generation
306
420 (+37)
(TWh)
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Nuclear and Hydro generation (TWh)
923
924
Electric Sector Carbon (MMTC)
382
440 (+15)
* Percentage change from the Advanced scenario
7.5.4 Policy Costs
Estimating the costs of policies in the electric sector is complicated by the fact that the electricity
demand varies considerably between the different scenarios. The total electricity bill in the
Moderate scenario is considerably less than that of either the BAU or the Advanced scenarios, as
shown in Table 7.20. This is due to a reduction in demand and the absence of a cost for carbon
allowances. The cost per kWh is also less in the Moderate scenario than in the BAU scenario due
largely to the decrease in the cost of natural gas to the electric sector that results from lower gas
demand in the end-use sectors. Similarly, the total national electric bill is less in the Advanced
scenario than in the BAU scenario because of the lower electricity demand. However the cost per
kWh in the Advanced scenario is higher than that of either of the other scenarios largely because of
the cost of carbon allowances, which are $50/tonne from 2005 through 2020.
We have also approximated the direct energy costs of the more significant individual policies. The
cost of carbon allowances to electric generators in the Advanced scenario is $23 billion per year in
2010 and falls slightly to $19 billion/year in 2020 with reductions in carbon emissions. These carbon
allowance costs are also reflected in the total national electricitybill and represent about 10% of that
bill. The cumulative undiscounted cost over the years 2005 through 2020 is$352 billion. There is no
carbon allowance cost in the BAU or Moderate scenario because there is no assumed carbon cap
and trade system in those scenarios. Clearly, the carbon allowance cost is the highest costpolicy for
the electric sector. However, much of these costs would be recycled back into the economy
depending on the design of the carbon trading mechanism. This is further discussed in Section
1.4.5.
The cumulative undiscounted cost over the years 2000 through 2018 of the renewable energy PTC
was estimated to be $5 billion and $30 billion in the Moderate and Advanced scenarios, respectively.
(The Advanced scenario extended the PTC as a surrogate of an RPS.) The cost in the Advanced
scenario is appreciably larger because the credit is assumed to apply to all non-hydro renewables
(not just wind and biomass as in the Moderate case), because the credit applies to capacity built
through 2008 and cofiring through 2014, and because the carbon cap and trade program in the
Advanced scenario encourages more renewable energy. Table 7.20 shows the cost for the specific
years of 2010 and 2020. While the credit is assumed to be available only to renewable energy
generators constructed between 2000 and 2008 (2004 in the Moderate scenario), those plants are
assumed to receive a credit for the first 10 years of production. Thus the annual costs shown in
Table 7.20 for the year 2010 are non-zero. All plants receiving the credit have completed their first
10 years of production by 2020, SO Table 7.20 shows no annual cost for that year.
The electricity-specific incremental cost of R&D programs has not been estimated in this chapter.
The R&D expenditure increases are consolidated in the overall analyses (chapters land 2) and are
not broken out by sector. Clearly, some R&D investments would only help the electricity sector
(e.g., nuclear, wind), but others (e.g., biomass, fuel microturbines) would help more than one.
Use of a PTC as a surrogate for the RPS gives higher costs than the RPS as proposed by the
administration. It matches the ceiling cost that the administration proposal includes, but effectively
costs out all renewables at that ceiling price. In reality, some of the renewables will cost less,
incrementally, than 1.5¢/kWh above the marginal cost of production. Some are economical without
any credit, which is often described as the "free rider" problem; production that is economic
without any subsidies receives them anyway. Another reason that the costs shown in Table 7.20 are
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slightly higher than an RPS is that the percentage of production from renewables in2010 is 7.6% of
total non-cogeneration production, which is higher than the proposed 7.5%.
These costs do not include a systems benefit charge that may be added to all electrical sales. This
charge is collected by state organizations to assist in funding energy efficiency or other energy-
related public benefits programs.
Additional administrative and macroeconomic costs to the economy as a whole associated with the
policies evaluated in the electric sector are addressed in Chapter 8.
Table 7.20 Annual Cost of Policies in the Electric Sector (1997$)
2010
2020
1997
BAU
Mod.
Adv.
BAU
Mod.
Adv.
Total electricity bill ($B/yr)
216
234
202
227
238
198
207
Cost per kWh (cents/kWh)
6.9
6.1
5.6
6.6
5.5
5.3
6.1
Carbon allowance payments
()
0
0
23
0
()
19
$B/yr)
Production tax credit cost ($B/yr)
0
0
0.4
0.6
0
0
0
Renew Portfolio Standard ($B/yr)
0
0
0.0
2.2
0
0
0
Note: BAU = Business-as-Usual scenario; Mod. = Moderate scenario; Adv.= Advanced scenario.
a
Cost shown is the incremental cost for extension of the PTC to 2008 and the biomass cofiring
credit to 2014.
7.6 CONCLUSIONS
In the Advanced scenario carbon emissions from the electric sector are substantially reduced from
those of the BAU scenario - 29% in 2010 and 46% in 2020. Just under half of this reduction is due
to lower demand for electricity as a result of efficiency improvements in the end-use sectors. While
in the Advanced scenario demand fell 22% by 2020, fossil fuel use declined 42%, mostly (37%
points) due to reductions in coal use. The difference is made up by nuclear and non-hydro
renewables, which were 15% and 40%, respectively, larger than in the BAU scenario
The carbon reductions (relative to the BAU) in the electric sector in the Moderate scenario are
considerably more modest - 7% in 2010 and 12% in 2020. Without a carbon cap and trade policy in
the Moderate scenario, the reduction in demand for electricity relative to the BAU was met almost
entirely by not building new gas-fired generators. Consequently, in 2020 there is slightly more
carbon produced per kWh in this scenario than in the BAU. The reduction in new gas generation
more than offset the impact on carbon from using 8% less coal and 41% more generation from non-
hydro renewables.
These results highlight the importance of the carbon cap and trade policy. Without it we don't see
the reductions in coal usage, nor the construction of new gas fired plants. The carbon cap andtrade
policy works together with the R&D-driven technology improvements, RPS and the production tax
credit for renewables to significantly increase renewable generation, primarily wind, in the
Advanced scenario. While the carbon cap and trade policy does increase the average price per kWh
of electricity, the electricity bill is actually smaller in both the Moderate and Advanced scenarios
than in the BAU due to reductions in the demand for electricity.
7.7 REFERENCES
Electricity - DRAFT
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Coal Utilization Research Council, 1998, Incentives for Clean Coal Technology Research and
Development and Deployment Program (May).
Delene, J. G., J. Sheffield, K.A. Williams, R. L. Reid, S. Hadley 1999, An Assessment of the
Economics of Future Electric Power Generation Options and the Implications for Fusion,
ORNL/TM-1999-243, Oak Ridge National Laboratory, September.
DOE Hydropower Assessment Program, http://www.inel.gov/national/hydropower/state/stateres.htm
DOE National Laboratory Directors, 1997, Technology Opportunities to Reduce U.S. Greenhouse
Gas Emissions, <http://www.ornl.gov/climate_change/>, September.
Dye, Richard, Office of Fossil Energy, U.S. Department of Energy, personal communication,
March 12, 1999.
EPRI (Electric Power Research Institute) and Office of Utility Technologies, Energy Efficiency
and Renewable Energy, 1997, Renewable Energy Technology Characterizations, EPRI TR-109496,
U.S. Department of Energy, Washington, DC, December.
EPRI 1999, "Powering Up Superconducting Cable", EPRI Journal, Electric Power Research
Institute, Palo Alto, CA, Spring.
EIA (Energy Information Administration) 1998a, Annual Energy Outlook 1999 with Projections to
2020, DOE/EIA-0383(99), http://www.eia.doe.gov/oiaf/aeo99/homepage.html, U.S. Department of
Energy, Washington, D.C. December.
EIA (Energy Information Administration) 1998b, Assumptions to the Annual Energy Outlook 1999
with Projections to 2020, DOE/EIA-0554(99), <http://www.eia.doe.gov/oiaf/assum99/introduction
.html>, U.S. Department of Energy, Washington, D.C., December.
EIA (Energy Information Administration) 1999, Issues in Midterm Analysis and Forecasting 1999,
EIA/DOE-0607(99), U.S. Department of Energy, Washington, D.C. August.
EPA (Environmental Protection Agency) 1999, Analysis Of Emissions Reduction Options For The
Electric Power Industry, Office of Air and Radiation, U.S. Environmental Protection Agency,
Washington, DC, March. <http://www.epa.gov/capi/multipol/mercury.htm>
Federal Energy Regulatory Commission (FERC), 1988, PURPA benefits at new dams and
diversions. Final Staff Report, Federal Energy Regulatory Commission, Office of Hydropower
Licensing, Washington, D.C.
Hunt, R.T., and J.A. Hunt. 1997. Hydropower resources at risk: the status of hydropower regulation
and development 1997. Richard Hunt Associates, Inc., Annapolis, Maryland, July.
Kaarsberg, Tina, Julie Fox Gorte and Richard Munson, "The Clean Air-Innovative Technology
Initiative Link: Enhancing Efficiency in the Electricity Industry", Northeast-Midwest Institute
Press, Washington, D.C., December, 1999. <http://www.nemw.org/tinabook.htm>
Kline, David and John "Skip" Laitner, 1999, "Policies to Enhance Technology Diffusion and
Market Transformation," forthcoming in Proceedings of the 20th Annual North American
Conference, U.S. Association for Energy Economics and International Association for Energy
Economics, August.
Electricity - DRAFT
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Office of Fossil Energy, 1999, Coul and Power Systems: Strategic Plan & Multi-Year Program
Plans, U.S. Department of Energy, Washington, D.C., January.
Office of Policy, 1999, Supporting Analysis for the Comprehensive Electricity Competition Act,
DOE/PO-0059, U.S. Department of Energy, Washington, DC, May.
Parsons Power Group Inc., 1998, Decarbonized Fuel Production Facilities including 1. Baseline
Plant with ATS Expander and FGD, 2. Plant to Produce Syngas from Coal and 3. Baseline Plant
with Transport Gasifier, Draft Letter Report, Office of Fossil Energy, U.S. Department of Energy,
Washington, DC, September.
Rinehart, B. N., J. E. Francfort, G. L. Sommers, G. F. Cada, and M. J. Sale, 1997, DOE
Hydropower Program biennial report 1996-1997, DOE/ID-10510, U.S. Department of Energy,
Idaho Falls Operations Office, Idaho Falls, ID.
South, D.W., K.A. Bailey and E. Bodmer, 1995. Analysis of Incentives to Accelerate First-of-a-Kind
(FOAK) Clean Coal Technologies, prepared for U.S. Department of Energy (October).
Spencer, D.F, 1996, An Analysis of Cost Effective Incentives for Initial Commercial Deployment of
Advanced Clean Coal Technologies, prepared for U.S. Department of Energy (May).
Wiser, Ryan, Jeff Fang, Kevin Porter, and Ashley Houston, 1999, Green Power Marketing in Retail
Competition: An Early Assessment, Ernest Orlando Lawrence Berkeley National Laboratory,
LBNL-42286, National Renewable Energy Laboratory, NREL/TP.620.25939, February.
<http://www.eren.doe.gov/greenpower/viser_emaa.html>
I Authors: Stanton W. Hadley (ORNL), Walter Short (NREL). David South (Energy Resources International).
Lowell Reid (ORNL), and Michael Sale (ORNL)
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Chapter 8
THE LONGER-TERM, GLOBAL CONTEXT
The analysis reported in this study covers a near-term time frame - the next two decades - and focuses
primarily upon domestic energy challenges and issues. These constraints were imposed because we
wanted to illuminate specific technology and policy opportunities for the United States today. This
requires detailed bottoms-up modeling of the U.S. energy sectors for which we used the CEF-NEMS
model. While insightful for the near-to-mid term, this engineering-economic approach is not applicable
to energy markets in the longer term due to increasing uncertainties in technology and market
developments further out in time.
The absence of a long-term, international, integrated-assessment perspective could conceivably lead to
short-sighted conclusions. More specifically, there is a danger that the CEF scenarios are not responsive
to energy needs, environmental conditions, and technology opportunities that emerge after 2020. We
have guarded against this danger primarily by positioning our results as scenarios. As such, they show
one detailed picture of what can be done in the U.S. in the near term. While there is some uncertainty
around the impacts of the policies in the CEF scenarios, they can at a minimum be considered to set a
rough yardstick against which other options can be compared.
By focusing on the near-term, U.S. policy perspective, the CEF scenarios show the importance of taking
advantage of stock turnover to increase efficiency and clean fuel use. Capitalizing on stock turnover
opportunities is especially important for equipment with long operating lives. The lifetimes of energy
supply technologies, energy distribution systems, and many other infrastructures such as refineries,
industrial complexes, highway infrastructures, and new subdivisions and shopping malls, are five decades
or longer. At most one or two replacements can occur over the course of a half-century. As a result,
decisions made over the next two decades that impact these infrastructures will have far-reaching
implications. Missed opportunities to put efficient and cleaner stock in place when old stock is replaced
or refurbished can perpetuate excess emissions for a long time.
However to further reduce the risk that our near-term U.S. focus will be contextually misinterpreted, this
chapter qualitatively explores longer-term, global issues, uncertainties, and opportunities in an effort to
redress any limitations introduced by the CEF focus.
8.1 LONG-TERM GLOBAL ENERGY AND ENVIRONMENT ISSUES
Many of the issues addressed in this CEF report at the national level are at least as prominent at the
international level. The recent PCAST report on international energy innovation says, "The problems and
opportunities related to oil, energy-technology markets. nuclear proliferation. climate change, and
development/security interactions are all inherently global" (PCAST 1999).
While the U.S. has made huge strides towards reducing its local air pollution problems. internationally
the health impacts of local air pollution are staggering and growing as urban populations swell. Many
countries do not have access to or cannot afford the SOx and NOx control technologies, cleaner natural
gas fuels, nor low-sulfur coal available to the U.S. The same PCAST study states. "acceptable outcomes
all require major innovations in energy technology in order to lower the emissions intensity of energy
supply with respect to greenhouse gases, particulate matter, and gaseous precursors of regional smogs,
hazes, and acid deposition (SOx, NOx. hydrocarbons)" (PCAST 1999).
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These local pollution problems prevalent around the globe will only exacerbate as the third of the world's
population currently without access to commercial energy and electricity are connected to the grid and
begin to demand access to fossil fuels for heating, cooling, and transportation. These increased demands
on international fossil fuel supplies will produce higher prices if not outright conflict over access to oil
and gas resources. Again the PCAST report states, "Attempts to fuel the bulk of developing-country
economic growth with conventional coal and oil technologies would create a collision between economic
aspirations and the environmental underpinnings of well-being, with the potential to wreck both"
(PCAST 1999).
8.2 LONG-TERM GLOBAL ENERGY UNCERTAINTIES
The uncertainties associated with the global, long-term context are illustrated vividly by the six global
energy scenarios developed by Nakicenovic, Grubler, and McDonald (1998) for the International Institute
for Applied Systems Analysis (IIASA) and the World Energy Council (WEC). Their six scenarios portray
a wide array of global economic conditions and energy developments over the next half-century. They
range from a tremendous expansion of coal production to strict limits, from a phase-out of nuclear energy
to a substantial increase, from carbon emissions in 2100 that are only one-third of today's levels to
increases by more than a factor of three. Only two of the six scenarios could be considered over the long
term to be clean energy futures.
Carbon emissions vary tremendously across the scenarios and across each of the 11 world regions that are
modeled. In the North American region (including the United States and Canada), carbon emissions grow
rapidly to 2,740 MtC in 2050 in Case A2, with its stepped-up exports of unconventional hydrocarbons
and coal-based synfuels. Scenario A3's combination of high economic growth (1.6% annually. as in all of
the "A" cases) and a focus on renewables and nuclear power results in North American carbon emissions
essentially holding steady at approximately 1990 levels. Case B, with its more cautious forecast of
economic growth, rates of technological change, and energy availability also results in small increases in
carbon emissions.
Only in Case C are there substantial carbon reductions. In this case, ambitious policy measures accelerate
energy efficiency improvements and develop and promote environmentally benign, decentralized energy
technologies. This case describes a challenging pathway of transition away from the current dominance of
fossil sources. In scenario C1, nuclear power proves a transient technology that is eventually phased out
entirely by the end of the 21st century. In scenario C2. a new generation of nuclear reactors is developed
that is inherently safe and small scale-100 to 300 MWe-and finds widespread social acceptability. By
2020, the carbon emission levels in Case C are well below those of the Advanced scenario, and they
continue to decline in subsequent decades despite an annual economic growth rate of 1.1% (Fig. 8.1).
Despite these vast differences over the long-term, these IIASA/WEC scenarios all retain vestiges of the
current system that makes their energy mix through 2020 appear quite similar to one another and to that
of the CEF scenarios. The most notable difference in 2020 is the high level of efficiency assumed in the
CI and C2 scenarios, which far surpasses the energy reductions of the CEF scenarios. Maybe as
important, like the CEF scenarios, all the IIASA/WEC scenarios include consistent trends for North
America toward increasing reliance on natural gas and significant declines in traditional environmental
pollutants, largely from coal. Coal use is the one option that is shrinking the most in the CEF (and
HASA/WEC scenarios CI and C2). However even this carbon-intensive fuel could retain market share
while mitigating carbon through sequestration. Such an outcome would be dependent on intensive
successful R&D on carbon separation and sequestration technologies. These and other technology needs
and opportunities for the long term are discussed in the next subsection.
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Figure 8.1 Primary Energy Use for Six Global Energy Scenarios and the CEF Scenarios
200
Renewable Energy
180
Nuclear Power
Coal
160
Natural Gas
A1
A :
A3
Primary Energy Use (Quadrillion Btu)
Petroleum
140
A1
A2
A3
B
B
BAL
120
Moderal
Advance
100
C1
C2
80
60
C1
C2
40
20
0
2020
2020
2050
Global Energy Perspec
Scenarios for a Clean Ene
Global Energy Perspec
(North America)
Future (United States
(North America)
8.3 ENERGY R&D OPPORTUNITIES FOR THE LONG TERM
Just as there are many energy and environment issues and uncertainties in the long-term global context,
there are also many opportunities. For example, while this report emphasizes energy solutions to climate
change, as pointed out in Chapter 2, there are also a host of potential solutions associated with adaptation
that do not directly involve energy. These
range from geoengineering approaches that
Box 8.1 PCAST Conclusion
reduce the sunlight reaching the earth's
surface to fortification of our physical,
The United States faces major energy-related
informational, and institutional
challenges as it enters the twenty-first century.
infrastructures. Such approaches deserve
Our economic well-being depends on reliable,
consideration and R&D alongside the
affordable supplies of energy. Our environmental
energy solutions proffered here.
well-being-from improving urban air quality to
abating the risk of global warming-requires a
The RD&D and investment decisions made
mix of energy sources that emits less carbon
now and in the immediate future will
dioxide and other pollutants than today's mix
determine which long-term options become
does. Our national security requires secure
available after 2020 and which are
supplies of oil or alternatives to it. as well as
foreclosed. Given the uncertainties
prevention of nuclear proliferation. And for
associated with long-term global
reasons of economy, environment, security, and
conditions, it is important, as PCAST
stature as a world power alike, the United States
(1997) argues, for the U.S. to keep all of its
must maintain its leadership in the science and
energy RD&D options open (Box 8.1).
technology of energy supply and use.
To effect a technology-based solution to
- Federal Energy Research and
the nation's energy-related challenges,
Development for the Challenges of the
Twenty-first Century by the President's
Committee of Advisors on Science and
Longer Term and Global Context DRAFT
Technology (PCAST, 1997) Italics
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added for emphasis.
many promising efficient and clean energy technologies require considerable applied R&D before they
are commercially feasible. Still other technologies are only at the conceptual stage but can be developed
with further research. The importance of these long-term efforts is highlighted by key emerging
technologies that were largely left out of the CEF-NEMs analysis. While the specifics of these long-term
advancements are not now known (else they would become short-term advancements), we can even now
see trends that will continue to yield energy advancements after 2020. We describe these in five general
areas below:
Advanced renewable technologies
Small, inherently safe nuclear power
Fossil fuel growth
Efficiency and distributed energy innovations
Carbon sequestration
8.3.1 Advanced Renewable Energy Technologies
With the substantial improvements in renewable energy technologies used in the Advanced Scenario, it
might be thought that there is little room for continued improvement after 2020. However, there are two
overarching reasons to believe that renewable energy will continue to evolve and grow as a source of
energy not only in the near term, but well through the middle of the next century. First, renewables
contribute towards the solution of the long-term national issues of climate change mitigation and the
economic exhaustion of domestic fossil fuel resources, and towards several nearer term issues like local
air pollution, rural development and international economic competitiveness. As these needs become
more pronounced, the interest in, commitment to, and development of renewables will accelerate.
Second, much of the emergence of renewables will require time as it depends on:
Basic as well as applied research
learning through increased production over time
infrastructure development
technology developments outside of the renewables field itself and the translation of those
developments to renewables.
We examine each of these time-delayed factors below for individual renewable energy technologies.
Wind. Due to continuous improvements over the last two decades, wind is one of the renewable energy
technologies closest to being economically competitive today. As a result we are seeing significant
learning-by-doing at the international level as installations increase and prices fall. Improvements will
continue in the near term through R&D on higher towers. light weight blades with advanced airfoil
designs, direct drive systems, etc. While these improvements may be refined in the longer term, wind
will also benefit for some time from technology advances in other areas. For example, improvements in
short-term weather forecasting increase dispatchers' ability to plan for wind generation. Intermittently-
available technologies, like wind and photovoltaics, will also benefit from improvements in real time
information control systems for dispatching and metering.
Photovoltaics. Current incarnations of this technology are penetrating a host of niche markets yielding
significant improvements through learning-by-doing. At the same time, basic materials and film
deposition research may lead to totally new approaches further out in the future. PV may also benefit
over the long term from events as diverse as semiconductor industry advances, artificial photosynthesis
breakthroughs, growing demand for personal vehicle transportation in developing countries, and
electricity storage advances.
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Biomass renewable energy technologies can also be expected to experience long-term improvements in
the development of both the biomass resource and the conversion technologies required to produce
power, fuels and other products. As genetic engineering matures over the next several decades, its
application to biomass energy resources can be expected to significantly improve the economics of all
forms of biomass energy. Improvements in the resource economics should also lead to increased RD&D
in the conversion technologies with an emphasis on the integrated production of ethanol, electricity, and
chemical products from the same conversion plant. Similarly, improvements in fuel cells and Stirling
engines can be expected to increase the value and demand for biogas. At the same time, near-term
biomass markets in corn-ethanol and the cofiring of coal-fired power plants are planting the seeds for the
basic infrastructure required for the long-term and yielding improvements through learning-by-doing.
Hydrogen. Fuel cell improvements will also drive the energy economy towards hydrogen. Although not
actually an energy source, hydrogen is an energy carrier that advantages many renewable energy forms. It
can be stored thereby eliminating the drawbacks of intermittent renewable electric technologies. It can be
produced by renewables - electrolysis from renewable-generated electricity, direct
photoelectrochemistry, and biogas reforming. And it can be transported by pipeline from remote
renewable resource locations to load centers. Hydrogen from methane reforming will become more
attractive as carbon sequestration becomes viable, providing a global-climate-change benefit from
reforming as well as the hydrogen itself.
8.3.2 Nuclear Expansion
While new nuclear capacity does not play a role in the generation mix through the years of study, 2000-
2020 (under the supply and demand scenarios used in this study), there is the potential for it to be a
contributor to the energy mix later in the century. In its 1997 report (PCAST 1997), the PCAST Energy
Research and Development Panel determined that restoring a viable nuclear energy option to help meet
our future energy needs is important and that a properly focused R&D effort should be implemented by
DOE to address the principal obstacles to achieving this option. These obstacles include issues involving
proliferation, economics, nuclear waste. and safety. In response. the DOE has established the Nuclear
Energy Research Initiative (NERI) with its primary mission being the long-term advancement of nuclear
energy science (NERI 1999). NERI R&D will address both innovative technologies that can be developed
and implemented over the next 10 years and revolutionary technologies that will be implemented over the
next 30 years. The primary areas of its research are described below.
Proliferation-Resistant Reactor and Fuel Technologies. Research will be conducted to develop
concepts, strategies, and technologies to further reduce or eliminate the potential for proliferation of
nuclear fuel materials from nuclear energy systems. Research in new fuel cycles that reduce plutonium
buildup. produce less waste, and have the least proliferation potential will be considered. New reactor
concepts and plant configurations. large and small, that eliminate access to the nuclear fuel will be
evaluated and developed.
New High-Efficiency Reactor Designs. Scientific and engineering R&D of new and more efficient
nuclear reactor concepts to achieve significant increases in performance and economics are required.
Innovative reactor and power conversion concepts are needed that offer the prospects of higher
efficiency, improved performance, design simplification, enhanced safety, and low cost. Research will
include development of reactor design advancements and alternative reactor core concepts; passive safety
systems and components; innovative reactor concepts for electrical, nonelectrical or cogeneration
purposes; technologies and design concepts incorporating construction and operations simplicity and cost
reduction features; specialized new applications such as process heat/electricity systems to compete in the
global market; and research to evaluate direct energy conversion technologies.
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Advanced Low Power Reactor Designs and Applications. R&D will be initiated for innovative, small,
compact, and easily deployable power reactor designs employing passive safety systems and long life
cores for use in developing countries or for specialized applications. Potential applications include
electricity generation, process heat, medical isotope production, or nuclear research. The ultimate
objective is to develop small reactor systems, primarily for export, that need no on-site refueling for the
life of the reactor, employ high safety margins and passive safety features, automated operation,
minimized waste production, and high cost effectiveness.
New Technologies for On-Site and Surface Storage of Nuclear Waste. Research will be performed to
develop innovative technologies and techniques for the on-site and surface storage of commercial spent
fuel and high level waste and strategies for reduction in high-level waste generation. Research will be
conducted in the areas of interim storage and transport, transmutation, separation science, and waste form
characteristics and integrity.
Advanced Nuclear Fuel. New and innovative scientific and engineering R&D in advanced nuclear fuels
is necessary to achieve measurable improvements in the performance of nuclear fuel with respect to
safety, waste production, and economics to enhance the viability of nuclear reactor systems.
Fusion energy is also an important, albeit long-range element of the nation's energy strategy because of its
many potential advantages as an energy resource. These advantages of fusion include: an almost limitless
supply of fuel (primarily isotopes of hydrogen); greatly reduced radioactivity compared with fission
(there are no long-lived gaseous radioactive products); and negligible atmospheric pollution compared
with fossil fuels. The successful application of practical fusion energy technologies at some point in the
21st century could help to enhance the Nation's energy. provide an environmentally acceptable alternative
to fossil-fuel combustion, and help ensure continued economic growth through reliable electricity supply.
Nuclear power can play a major role in the nation's future electricity supply given the issues raised within
the PCAST report are successfully addressed.
8.3.3 Fossil Energy Growth
Continued improvements in efficiency and environmental acceptability could enable fossil energy to play
a growing role in the U.S. and world's energy mix while pursuing the goals of a clean energy future. The
DOE has developed a new approach to 21st century energy production from fossil fuels called the "Vision
21 EnergyPlex" (FETC 1999). This vision integrates advanced concepts for high-efficiency power
generation and pollution control into a new class of fuel-flexible facilities capable of co-producing
electric power, process heat and high value fuels and chemicals with virtually no emissions of air
pollutants. If this research is successful, electric power generations added after 2015 could be 50% more
efficient than today's best technologies. It will be capable of a variety of configurations to meet differing
market needs, including both distributed and central power generation.
Many of the initial building blocks for "Vision 21" are emerging from DOE's advanced technology
programs. These will be integrated with further advances in several areas described below.
Gas Separation Technologies. To make a future "Vision 21" plant the most cost-effective and efficient
plant possible, lower-cost means will be needed to produce oxygen for the gasification process. R&D will
be conducted on innovative membranes. some adapted from declassified uranium enrichment processes
(developed for national defense purposes), to replace the costly cryogenic air separation used today.
Similarly, advanced membranes could offer a better way to separate a pure stream of hydrogen from the
coal-derived gases that could then be used by a fuel cell or in a coal-to-liquids process. Gas separation
technologies are also being investigated for separating CO₂ effluents from combustion streams for
sequestration in deep aquifers, depleted oil and gas wells, or ocean depths and sediments.
Longer Term and Global Context - DRAFT
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Fuel-Flexible Gasification. Coal gasification is an ideal core technology for "Vision 21" because it
produces a gas stream that can be combusted for electric power, or used as a source of hydrogen for a fuel
cell or chemical process, or processed as a fuel gas for industrial plants. To enhance the fuel flexibility of
"Vision 21," R&D will be conducted to determine how best to gasify fuel mixtures, such as coal and
biomass or fuel-rich wastes.
Fuel Cell/Turbine Hybrids. To date, R&D has focused largely on fuel cells and turbines as separate
power generating devices, but in the future, combining the two may offer significant efficiency and
economic benefits. A key focus of "Vision 21" will be on integrating these technologies and adapting
them to run on multiple types of fuel feedstocks.
High-Performance Combustion. One possible "Vision 21" configuration might rely on combustion
rather than gasification. In this design, advanced technologies such as pressurized fluidized bed
combustion and high-temperature heat exchangers (such as those being developed in the Fossil Energy
indirectly-fired cycle program) will be a key focus of future R&D.
If the "Vision 21" concept can be coupled with low-cost carbon sequestration (the capturing and
permanent storage of carbon dioxide and other greenhouse gases - see section 8.3.5), the result will be a
future energy facility with virtually no environmental impacts outside of its "footprint."
8.3.4 Efficiency and Distributed Energy Innovations
This section provides a sampling of some of the major advances that could occur with a sustained
commitment to energy efficiency R&D. Many of these examples are drawn from the "II-lab study" by
DOE National Laboratory Directors (1997) and a report by the Committee on Energy Research and
Technology of the International Energy Agency (1999).
Buildings. Major transformations are possible in the energy features of buildings as the result of applied
technology R&D and in the underlying basic sciences. Inasmuch as most of these are best applied to new
construction, their ultimate market penetration will occur well after the 2020 time frame of the CEF
scenarios, since the building stock turns over very slowly. These could include:
Virtual elimination of space heating in many climates, by means of building shells with very high
resistance to heat loss or gain involving high insulation walls, ceilings, and floors and triple pane
windows with transparent heat-reflecting films; wide use of passive designs; mass-produced
components (walls, ceilings) with very low infiltration rates; large savings in furnaces and ducts.
Multi-functional equipment and integrated systems design offers the opportunity for a quantum leap
in efficiency improvement: an integrated water heating/space cooling system that uses heat pumping
to meet space heating, air conditioning, and water heating needs could be 70% more efficient than the
current combined efficiencies of today's systems.
Advanced lamp technology combined with lighting controls, task lighting. and greater use of natural
light, reducing lighting energy requirements to 10 to 15% of today's levels.
Dramatic decline in refrigerator/freezers energy use through use of high insulating walls and doors,
efficient compressors, advanced motors, etc.; entirely new ways of storing and cooling food could
further reduce energy requirements.
Longer Term and Global Context DRAFT
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Advanced building control systems incorporate smart technology to closely match energy and water
supply and ambient conditions with need.
As energy conversion technologies evolve, many residential and low-rise commercial buildings could
become net producers of energy as roofs incorporate photovoltaic panels and fuel cells and
microturbines generate more power than is required on site.
Industry. There is, and will long continue to be, attention to improving the energy efficiency of specific
devices used in industrial applications. There are countless examples: more efficient chemical
separations, highly efficient motors, efficient processes for energy-intensive industries (e.g., iron and
steel, aluminum, and cement production). R&D will yield improvements in these areas for years and
decades to come.
Nonetheless, these are not the ways in which major gains in energy efficiency will come about in industry
in the longer term. It has long been recognized that the very substantial gains in energy efficiency will
result from changes in systems rather than individual devices. The development of advanced control
technology - and the application of control technology to industrial systems - has the potential to
dramatically reduce industrial energy use.
For example, improvements in motors can yield efficiency gains of a few percent. Redesign of motor
systems have already shown savings of 20 to 60% (and higher) in various applications. Variable speed
drives for many motor applications yields very substantial savings. The development and use of
advanced controls will make possible the control of both the motor and the systems that the motor drives
(fans, pumps, compressors, etc.). It is likely that advanced controls will, over time, make possible the
widespread transformation of motor systems. As motors presently consume more than 50% of U.S.
electricity, advances in this area have the potential to yield dramatic impacts on industrial energy use.
Heat cascading, in which the heat output of one process is used as the input to another process (that
requires the heat at a lower temperature than the first process), and this is continued throughout a series of
such processes, can be shown in principle to yield significant energy savings. Such an approach in
practice would mean the co-locating of different industries, equipment design and sizing to permit new
types of integration among industrial processes, and the very precise control of liquid and fluid transfers
among different industrial processes.
Other examples of radical energy savings that may be possible over the longer term include
Redesign of industrial products for recycling and reuse, in which the life-cycle of a product
becomes a primary focus of the design, manufacture, distribution, use, and collection of the
product. This is in contrast with the current approach in which manufacturing cost alone is the
prime economic criterion for the product.
Development of micro-machines to carry out functions of existing machinery.
Transportation. In the long term, additional advances hold the promise of spectacular reductions in
energy use, greenhouse gas emissions, and air pollution from the transportation sector. Advanced fuel cell
technology combined with an infrastructure for supplying hydrogen, for instance, offer the potential for a
pollution-free propulsion system, depending on how the hydrogen is produced.
For heavy-duty diesel engines, there is a strong coupling between efficiency and NOx and other
emissions. Many engine design options currently available to manufacturers for emissions reduction
involve a fuel economy penalty. Significant technological advances are needed to allow the trend toward
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higher diesel engine efficiency to continue in the face of increasing concern over diesel engine non-CO₂
emissions.
Technology opportunities also exist in other transportation modes. Particularly promising options for the
long-term include railroad electrification, high-speed rail for medium-distance, inter-city travel. fuel cells
on ships, blended wing bodies for airplanes, and hydrogen as a clean aircraft fuel.
Land use and infrastructure investment options offer powerful strategies for reducing the energy- and
carbon-intensity of today's transportation sector. Advances in information technology and a variety of
policy levers offer the potential to develop urban spatial structures that decrease the demand for travel
while maintaining accessibility.
8.3.5 Sequestration of Carbon
There are numerous ways of removing CO₂ from the atmosphere and storing it or keeping anthropogenic
carbon emissions from reaching the atmosphere by capturing and diverting them to secure storage. A
range of these options is described in a recent report (DOE. 1999) and is summarized below. These are
organized in terms of the principal sequestration sinks that they employ - oceans, terrestrial ecosystems,
geological formations, and vegetation. Some of these options are available today - such as improved
agricultural practices and wetlands protection. Others are available in the near-term because they can
provide important secondary benefits, such as improving ecosystems during reforestation and enhancing
oil recovery through CO₂ injection. Most, however, are long-term carbon management options that
require considerable research to ensure their successful development and acceptance.
Ocean sequestration represents a large potential sink for CO₂. Two approaches appear to be particularly
promising. First, relatively pure CO₂ streams that have been generated by a power plant or industrial
facility can be injected directly into the ocean and trapped in ice-like solids called clathrates. Second, the
net oceanic uptake from the atmosphere could be enhanced through methods such as iron fertilization.
There is evidence that natural iron fertilization of the Southern Ocean was responsible for significant
reductions in atmospheric concentrations of CO₂ following the onset of past ice ages. Iron fertilization is
believed to enhance biological productivity of certain ocean regions, effectively transporting atmospheric
CO₂ as biomass to lower regions of the ocean which have limited interaction with the atmosphere. These
approaches will require better understanding of marine ecosystems to enhance the effectiveness of
applications and avoid undesirable consequences.
Terrestrial ecosystems (forests, vegetation, soils, farm crops, pastures, tundra, and wetlands) act as huge
natural biological scrubbers for CO₂. Their carbon sequestration potential can be significantly increased
by careful manipulation to enhance the natural carbon cycle. The potential for terrestrial ecosystems to
remove and sequester more carbon from the atmosphere could be increased by reducing oxidation of soil
carbon, enhancing soil texture to trap more carbon, and protecting wetlands.
Three principal types of geological formations have the potential for sequestering large amounts of CO2.
They are active and uneconomical oil and gas reservoirs; saline aquifers; and deep coal formations which
cannot be mined. About 70 oil fields worldwide use injected CO₂ for enhanced oil recovery. CO₂
sequestration is already being practiced in a sub-seabed reservoir in the North Sea of Norway. The United
States appears to have sufficient capacity, diversity, and broad geographical, distribution of potential
reservoirs to use geologic sequestration for at least several decades.
Advanced biological processes could be developed and implemented to limit emissions and capture and
sequester carbon. Bacteria and other organisms could be used to remove carbon from fuels and to recycle
carbon from man-made waste streams. Crop wastes and dedicated crops could be used as feedstocks for
Longer Term and Global Context - DRAFT
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biological and chemical conversion processes to manufacture fuels and chemicals. In addition, advanced
crop species and cultivation practices could be designed to increase the uptake of atmospheric CO₂ by
terrestrial and aquatic biomass while at the same time decreasing CO₂ emissions to the atmosphere from
soils and terrestrial and aquatic biomass.
In the long-term, carbon sequestration could play a significant role. In fact, low-cost carbon sequestration
techniques could enable the nation's continued reliance on its vast fossil fuels resources for large-scale
energy production. They could also expand the world's long-run options for managing carbon emissions.
8.4 CONCLUSIONS
The CEF scenarios address U.S. energy and environmental issues for the next 20 years. They are not
long-term, global, integrated assessments. Their scope is limited because we wanted to illuminate
specific technology and policy opportunities for the United States today. We positioned our results as
scenarios to reduce the risk that they will be contextually misinterpreted. They should be considered as
one detailed picture of what can be done in the U.S. in the near term and as a rough yardstick against
which other energy technology and climate change options can be compared.
The CEF scenarios emphasize the importance of optimizing decisions at the point of major stock turnover
to increase efficiency and clean energy use. This is not inconsistent with continuing research on other
technology options and climate change solutions. In fact, given the uncertainties in global economic
trends, export markets, energy technology development, air quality, and global climates, an expanded
R&D effort in most technology arenas would appear to be warranted. There is a broad range of longer-
term technology options which, with successful research, would provide additional pathways to address
the nation's energy-related challenges.
8.5 REFERENCES
Federal Energy Technology Center (FETC). 1999. Vision 21 Program Plan: Clean Energy Plants for the
21" Century, U.S. Department of Energy, Washington, DC. April.
International Energy Agency. 1999. The Role of Technology in Reducing Energy-Related Greenhouse
Gas Emissions, U.S. Department of Energy, Washington, DC, March, draft.
Nakicenovic, N., A. Grubler, and A. McDonald, Eds. 1998. Global Energy Perspectives, Cambridge
University Press, Cambridge, UK.
DOE National Laboratory Directors. 1997. Technology Opportunities to Reduce U.S. Greenhouse Gas
Emissions (Oak Ridge, TN: Oak Ridge National Laboratory). September.
NERI (Nuclear Energy Research Initiative). 1999, Overview of NERI Program,
<http://neri.ne.doe.gov/default.html>
PCAST (President's Committee of Advisors on Science and Technology). 1999. Powerful Partnerships:
The Federal Role in International Cooperation on Energy Innovation, Executive Office of the President,
Washington, D.C., June.
PCAST (President's Committee of Advisors on Science and Technology). 1997. Federal Energy
Research and Development for the Challenges of the Twenty-First Century, Executive Office of the
President, Washington, D.C., November.
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U.S. Department of Energy (DOE). 1999. Working Paper on Carbon Sequestration Science and
Technology. U.S. Department of Energy, Washington, D.C. April.
I Authors: Marilyn A. Brown (ORNL). Walter Short (NREL), Stan Hadley (ORNL). and Mark D. Levine (LBNL).
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ACRONYMS
AEO
Annual Energy Outlook
AER
Annual Energy Review
AFV
alternative-fueled vehicle
AFVM
Alternative Fuel Vehicle Model
ANL
Argonne National Laboratory
ASHRAE
American Society of Heating, Refrigeration, and Air-conditioning Engineers
BAU
business as usual
BTS
Office of Building Technology, State and Community Programs
Btu
British thermal unit
CAFÉ
corporate average fuel economy
C
carbon
CC
combined cycle
CCTI
Climate Change Technology Initiative
CEF
Clean Energy Future
CHP
combined heat and power
CIDI
compression ignition (diesel) direct injection
CO₂
carbon dioxide
CRADA
cooperative research and development agreement
CT
combustion turbine
DOE
U.S. Department of Energy
DOT
U.S. Department of Transportation
EERE
Office of Energy Efficiency and Renewable Energy
EIA
Energy Information Administration
EPA
U.S. Environmental Protection Agency
EPACT
Energy Policy Act of 1992
ESPC
Energy Savings Performance Contract
FAA
Federal Aviation Administration
FEM
Fuel Economy Model
FEMP
Federal Energy Management Program
FY
fiscal year
GDI
gasoline direct injection
GDP
gross domestic product
GHG
greenhouse gas
g/mi
grams per mile
GW
gigawatt
HVAC
heating ventilation, and air-conditioning
ICE
internal combustion engine
IGCC
integrated gasification combined cycle
IPCC
International Panel on Climate Change
kWh
kilowatt-hour
LBNL
Lawrence Berkeley National Laboratory
LDV
light-duty vehicle
LEV
low emission vehicle
MBtu
million Btu
MEC
model energy code
mmbd
million barrels of oil per day
MtC
million metric tons of carbon
MW
megawatt
Acronyms - DRAFT
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mpg
miles per gallon
mph
miles per hour
NAECA
National Appliance Energy Conservation Act of 1987
NEMS
National Energy Modeling System
NOₓ
nitrogen oxides
NREL
National Renewable Energy Laboratory
OIT
Office of Industrial Technologies
OPEC
Organization of Petroleum Exporting Countries
OPT
Office of Power Technologies
ORNL
Oak Ridge National Laboratory
OTT
Office of Transportation Technologies
PATH
Partnership for Advanced Technology in Housing
PATP
"pay at the pump" auto insurance
PM
particulate matter
PNGV
Partnership for a New Generation of Vehicles
PNNL
Pacific Northwest National Laboratory
ppm
parts per million
PTC
production tax credit
PV
photovoltaic
Quad
quadrillion Btu (10^15 Btu)
R&D
research and development
RD&D
research, development and demonstration
RPS
renewable portfolio standard
SEAB
Secretary's Energy Advisory Board
SO₂
sulfur dioxide
tBtu
trillion Btu
TDI
turbocharged direct injection
TWh
TerraWatt-hour
VMT
vehicle miles traveled
VOC
volatile organic compounds
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GLOSSARY
Barrel (petroleum): A unit of volume equal to 42 U.S. gallons.
Biomass: Any organic matter available on a renewable or a recurrent basis, including agricultural crops
and residues, wood and wood residues, urban and animal residues, and aquatic plants.
Bioenergy: Energy derived from biomass as electricity or heat, or combinations of heat and power; in the
form of liquid or gaseous fuels, it is often referred to as biofuels.
British Thermal Unit (Btu): One British thermal unit, or BTU, is roughly equivalent to burning one
kitchen match. It is the quantity of heat required to raise the temperature of one pound of water one
degree Fahrenheit. (one Blu = 1055 Joules)
Carbon Dioxide (CO₂): A colorless, odorless, non-poisonous gas that is a normal part of the ambient
air. Carbon dioxide is a product of fossil fuel combustion.
Climate Change: The change in weather patterns and surface temperatures that appears to be occurring
as the result of large increases in greenhouse gas concentrations in the earth's atmosphere.
Cogeneration: The production of electrical energy and another form of useful energy (such as heat or
steam) through the sequential use of energy.
Combined Cycle: An electric generating technology in which electricity is produced from otherwise lost
waste heat exiting from one or more gas (combustion) turbines. The exiting heat is routed to a
conventional boiler or to a heat recovery steam generator for utilization by a steam turbine in the
production of electricity. Such designs increase the efficiency of the electric generating unit.
Criteria Pollutant: A pollutant determined to be hazardous to human health and regulated under the
Environmental Protections Agency's (EPA) National Ambient Air Quality Standards. The 1970
amendments to the Clean Air Act require EPA to describe the health and welfare impacts of a pollutant as
the "criteria" for inclusion in the regulatory regime.
Crude Oil: A mixture of hydrocarbons that exists in the liquid phase in natural underground reservoirs
and remains liquid at atmospheric pressure after passing through surface separating facilities. Crude oil
production is measured at the wellhead and includes lease condensate.
Discount Rate: The interest rate used to assess the value of future cost and revenue streams; an essential
factor in assessing true returns from an investment in energy efficiency, as well as opportunity costs
associated with not making that investment. In this report, we always use real discount rates that do not
include inflation. To obtain the equivalent nominal discount rate including inflation, simply add the
percentage annual inflation rate to the real discount rate
Distillate Fuel Oil: The lighter fuel oils distilled off during the refining process. Included are products
known as ASTM grades numbers 1 and 2 heating oils, diesel fuels. and number 4 fuel oil. The major uses
of distillate fuel oils include heating, fuel for on- and off-highway diesel engines, and railroad diesel fuel.
Electric Utility Restructuring: With some notable exceptions, the electric power industry historically
has been composed primarily of investor-owned utilities. These utilities have been predominantly
vertically integrated monopolies (combining electricity generation, transmission, and distribution). whose
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prices have been regulated by State and Federal government agencies. Restructuring the industry entails
the introduction of competition into at least the generation phase of electricity production, with a
corresponding decrease in regulatory control. Restructuring may also modify or eliminate other
traditional aspects of investor-owned utilities, including their exclusive franchise to serve a given
geographical area, assured rates of return, and vertical integration of the production process.
Energy: The capacity for doing work as measured by the capability of doing work (potential energy) or
the conversion of this capability to motion (kinetic energy). Energy has several forms, some of which are
easily convertible and can be changed to another form useful for work. Most of the world's convertible
energy comes from fossil fuels that are burned to produce heat that is then used as a transfer medium to
mechanical or other means in order to accomplish tasks. Electrical energy is usually measured in
kilowatthours, while heat energy is usually measured in British thermal units.
Energy Service Company (ESCo): A company which designs, procures, finances, installs, maintains,
and guarantees the performance of energy conservation measures in an owner's facility or facilities.
Energy Saving Performance Contract (ESPC): An agreement with a third party in which the overall
performance of installed energy conservation measures is guaranteed by that party.
Ethanol: A denatured alcohol (C₂H₃OH) intended for motor gasoline blending.
Externalities: Benefits or costs, generated as a byproduct of an economic activity, that do not accrue to
the parties involved in the activity.
Fluorescent Lamps: Fluorescent lamps product light by passing electricity through a gas. causing it to
glow. The gas produces ultraviolet light; a phosphor coating on the inside of the lamp absorbs the
ultraviolet light and produces visible light. Fluorescent lamps produce much less heat than incandescent
lamps and are more energy efficient. Linear fluorescent lamps are used in long narrow fixtures designed
for such lamps. Compact fluorescent light bulbs have been designed to replace incandescent light bulbs in
table lamps, floodlights. and other fixtures.
Fossil Fuel: Any naturally occurring organic fuel formed in the Earth's crust, such as petroleum. coal,
and natural gas.
Fuel Cells: One or more cells capable of generating an electrical current by converting the chemical
energy of a fuel directly into electrical energy. Fuel cells differ from conventional electrical cells in that
the active materials such as fuel and oxygen are not contained within the cell but are supplied from
outside.
Gas-Turbine Electric Power Plant: A plant in which the prime mover is a gas turbine. A gas turbine
typically consists of an axial-flow air compressor and one or more combustion chambers which liquid or
gaseous fuel is burned. The hot gases expand to drive the generator and then are used to run the
compressor.
Global Warming: Global warming is the increase in global temperatures that the earth has been
experiencing this century. Gases that are thought by many to contribute to global warming through the
greenhouse effect include carbon dioxide, methane, nitrous oxides, chlorofluorocarbons (CFCs), and
halocarbons (the replacements for CFCs). Carbon dioxide emissions are primarily caused by the use of
fossil fuels for energy.
Greenhouse Gas: Any gas that absorbs infrared radiation in the atmosphere.
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Heat Pump: A device that extracts available heat from one area (the heat source) and transfers it to
another (the heat sink) to either heat or cool an interior space. Geothermal heat pumps can operate more
efficiently than the standard air-source heat pumps, because during winter the ground does not get as cold
as the outside air (and during the summer. it doe not heat up as much).
Independent Power Producer (IPP): A wholesale electricity producer (other than a qualifying facility
under the Public Utility Regulatory Policies Act of 1978), that is unaffiliated with franchised utilities.
Unlike traditional utilities, IPPs do not possess transmission facilities that are essential to their customers
and do not sell power in any retail service territory where they have a franchise.
Kerosene: A petroleum distillate that is used in space heaters, cook stoves, and water heaters; it is
suitable for use as an illuminant when burned in wick lamps (see Watthour).
Kilowatt (kW): One thousand watts of electricity (see Watt).
Kilowatthour (kWh): One thousand watthours.
Light Truck: Two-axle, four-tire trucks with a gross vehicle weight less than 10.000 pounds.
Liquefied Natural Gas (LNG): Natural gas (primarily methane) that has been liquefied by reducing its
temperature to -260°F at atmospheric pressure.
Liquefied Petroleum Gas (LPG): Ethane, ethylene, propane, propylene, normal butane, butylene. and
isobutane produced at refineries or natural gas processing plants.
Megawatt (MW): One million watts of electricity (see Watt).
Methanol: A light volatile alcohol (CH₃OH) used for motor gasoline blending.
Natural Gas: A mixture of hydrocarbons (principally methane) and small quantities of various
nonhydrocarbons existing in the gaseous phase or in solution with crude oil in underground reservoirs.
Nitrogen Oxides (NO,): A product of combustion of fossil fuels whose production increases with the
temperature of the process. It can become an air pollutant if concentrations are excessive.
Nuclear Electric Power: Electricity generated by an electric power plant whose turbines are driven by
steam generated in a reactor by heat from the fissioning of nuclear fuel.
Oxygenates: Any substance which, when added to motor gasoline, increases the amount of oxygen in
that motor gasoline blend.
Ozone: Three-atom oxygen compound (0₃) found in two layers of the Earth's atmosphere. One layer of
beneficial ozone occurs at 7 to 18 miles above the surface and shields the Earth from ultraviolet light.
Several holes in this protective layer have been documented by scientists. Ozone also concentrates at the
surface as a result of reactions between byproducts of fossil fuel combustion and sunlight, having harmful
health effects.
Particulates: Visible air pollutants consisting of particles appearing in smoke or mist.
Petroleum: A generic term applied to oil and oil products in all forms.
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Photovoltaic Cell: An electronic device consisting of layers of semiconductor materials fabricated to
convert incident light directly into electricity (direct current).
Photovoltaic Module: An integrated assembly of interconnected photovoltaic cells designed to deliver a
selected level of working voltage and suited for incorporation in photovoltaic power systems.
Primary Energy: The energy that is embodied in resources as they exist in nature (e.g., coal, crude oil,
natural gas, or sunlight). For the most part, primary energy is transformed into electricity or fuels such as
gasoline or charcoal. These. in turn, are referred to as secondary or site energy.
Propane: A normally gaseous straight-chain hydrocarbon (C₃H₈). It is a colorless paraffinic gas that is
extracted from natural gas or refinery gas streams.
Quadrillion Btu (Quad): Equivalent to 10 to the 15th power Btu (1 quad = 1.055 X 10e 18 joules).
Renewable Energy: Energy obtained from sources that are essentially inexhaustible (unlike, for
example, the fossil fuels, of which there is a finite supply). Renewable sources of energy include
conventional hydroelectric power, wood, waste, geothermal, wind, photovoltaic, and solar thermal
energy.
Standard Industrial Classification (SIC): A set of codes developed by the Office of Management and
Budget which categorizes industries according to groups with similar economic activities.
Turbine: A machine for generating rotary mechanical power from the energy of a stream of fluid (such
as water, steam, or hot gas). Turbines convert the kinetic energy of fluids to mechanical energy through
the principles of impulse and reaction, or a mixture of the two.
Watt (Electric): The electrical unit of power. The rate of energy transfer equivalent to one ampere of
electric current flowing under a pressure of one volt at unity power factor.
Watthour (Wh): The electrical energy unit of measure equal to I watt of power supplied to, or taken
from, an electric circuit steadily for one hour.
Wind Energy: The kinetic energy of wind converted into mechanical energy by wind turbines (i.e.,
blades rotating from a hub) that drive generators to produce electricity.
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LIST OF APPENDICES
A
ALTERNATIONS TO NEMS
A-1
BUILDINGS: Summary of Changes to the CEF-NEMS Model
A-1.1
A-2
INDUSTRY: NEMS Input Data and Scenario Input
A-2.1
A-3
TRANSPORTATION: Alterations to NEMS for Sector Policies
A-3.1
A-4
ELECTRICITY
A-4.1
B
POLICY IMPLEMENTATION PATHWAYS
B-1
BUILDINGS
B-1.1
B-2
INDUSTRY: Program Descriptions and Scenario Definitions
B-2.1
B-3
TRANSPORTATION
B-3.1
B-4
ELECTRICITY (forthcoming paragraph)
B-4.1
C
TECHNOLOGY ASSUMPTIONS
C-1
BUILDINGS
C-1.1
C-2
INDUSTRY
C-2.1
C-3
TRANSPORTATION
C-3.1
C-4
ELECTRICITY
C-4.1
D
DETAILED RESULTS
D-1
BUILDINGS
D-1.1
D-2
INDUSTRY
D-2.1
D-3
TRANSPORTATION
D-3.1
D-4
ELECTRICITY
D-4.1
D-5
INTEGRATED RESULTS
D-5.1
E
ANCILLARY STUDIES
E-1
Estimates of Administrative Costs for Energy Efficiency Policies and Programs
E-1.1
E-2
On the Potential Impacts of Land Use Change Policies on Vehicle Miles of Travel
E-2.1
E-3
Nuclear Power Plant Analysis
E-3.1
E-4
Estimating Bounds on the Macroeconomic Effects of the CEF Policy Scenarios
E-4.1
E-5
Combined Heat and Power Analysis
E-5.1
E-6
The Cost-Effective Emission Reduction Potential of Non-Carbon Dioxide
Greenhouse Gases within the United States and Abroad
E-6.1
E-7
Repowering/Fuel Substitution Analysis
E-7.1
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