Figure 3.10: Passenger car fuel economy cost curves.
This section addresses the technological potential to cost-effectively increase energy efficiency in transport and thereby reduce GHG emissions. Most studies concentrate on light-duty vehicles because of their 50% share of energy use and GHG emissions, and on technology or fuel pricing policies. Technical efficiency improvements, in the absence of complementary fiscal policies, are subject to a “rebound effect” in that they reduce the fuel cost of travel. Rebound effects in the USA amount to about 20% of the potential GHG reductions (Greene, 1999). In Europe, where fuel prices are higher, rebound effects may be as large as 40% (Michaelis, 1997). Most assessments take the rebound effect into account when estimating technical efficiency impacts. Fewer studies address policies such as land use planning, investment in or subsidy of particular transport modes, or information.
An Asian four-country study of the technological and economic potential to reduce GHG emissions considered five types of options for GHG mitigation in transport: (1) improving fuel efficiency, (2) improving transportation system efficiency, (3) behavioural change, (4) modal split changes, and (5) technological change (Bose, 1999b). The Indian study concluded that abatement costs for transport were high relative to options available in other sectors, and projected little change in transport for emissions constraints less than a 20% reduction from the baseline. The Bangladesh study, using a different methodology, concluded that a wide array of near-term technology options had no net cost, but that the cost of 4-stroke engines for 3-wheeled vehicles fell between US$48 and US$334/tC reduced, depending on the application. The Thailand study found that lean-burn engines would improve efficiency by 20% at a negative net cost of US$509/tC. The Korean study also concluded that several “no regrets” options were available, including use of continuously variable transmissions, lean-burn engines, and exclusive bus lanes.
Recognizing that transportation energy consumption and CO2 emissions increased by 16% from 1990 to 1995, and that carbon emissions may be 40% higher in 2010 than in 1990 if measures are not taken, the government of Japan has strengthened energy efficiency standards based on a “Front Runners” approach, which sets standards to meet or exceed the highest energy efficiency achieved among products currently commercialized (MITI/ANRE, 1999). These require a 22.8% improvement over 1995 new gasoline car fuel economy in 1/km by 2010, and a 13.2% improvement for gasoline light-duty freight vehicles (Minato, 1998). For diesel-fuelled vehicles the corresponding requirements are 14.9% and 6.5% by 2005. Technological improvements in other modes are expected to produce efficiency improvements of 7% for railways, 3% for ships, and 7% for airlines over the same period (Minato, 1998). Cost-effective technical potentials have also been reported by Kashiwagi et al. (1999), who cite 27.7 PJ of energy savings in Japan’s transport sector achievable at US$0.044/kWh, or less.
There are significant barriers to the kinds of fuel economy improvements described above, and substantial policy initiatives will be needed to overcome them. In Europe, for example, the European automobile manufacturers’ association, ACEA, and the European Union have agreed to voluntary standards to reduce carbon emissions from new passenger cars by 25% over the next 10 years. The European standards will require reducing average fuel consumption of new cars from 7.7 to 5.8 l/100 km, creating a strong incentive to adopt advanced fuel economy technologies. A survey of 28 European countries identified 334 separate measures countries were taking to reduce CO2 emissions from transport (Perkins, 1998).
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At least nine recent studies have assessed the economic potential for technology to improve light-duty vehicle fuel economy (Weiss et al., 2000; Greene and DeCicco, 1999; Michaelis, 1997). The conclusions of eight of the studies are summarized in the form of quadratic fuel economy cost curves describing incremental purchase cost versus the improvement in fuel economy over a typical 8.4 l/100 km passenger car (Figure 3.10). Most of the technology potential curves reflect a short-run perspective, considering what can be achieved using only proven technologies over a 10-year period. The two most pessimistic (which reflect a 1990 industry view of short-term technology potential) indicate that even a reduction from 8.4 to 6.5 l/100 km would cost nearly US$2000. The curves labelled “ACEEE Level 3” and “UK DOT Low-Cost” are limited to proven technologies, but allow substantial trade-offs in performance, transmission-management and other features that may affect customer satisfaction. The curves labelled “5-lab” and “OTA 2015” include the benefits of technologies in development, but not yet commercialized (NRC, 1992; DeCicco and Ross, 1993; US DOE/EIA, 1998). The most optimistic of these suggest that an improvement to less than 5.9 l/100 km is possible at an incremental cost of less than US$1000 per vehicle (1998 US$). The Sierra Research (Austin et al., 1999) curve is intended to pertain to the year 2020, but reflects industry views about technology performance, and excludes certain key technologies such as hybrids and fuel cell vehicles that could have dramatic impacts over the next 20 years.
Three of the studies (OTA, 1995b; DeCicco and Ross, 1993; National Laboratory Directors, 1997) considered more advanced technologies such as those described above (e.g., direct-injection engines, aluminium-intensive designs, hybrid vehicles, fuel cells). These concluded that by 2015, consumption rates below 4.7 l/100 km could be attained at costs ranging from under US$1000 to US$1500 per vehicle. These long-run curves span a range similar to fuel consumption/cost curves for European passenger cars reported by Denis and Koopman (1998, Figure 3), except that the base fuel consumption rate is 7 l/100 km as opposed to 8.5 in the USA, and improvements to the range of 4 to 5 l/100 km were judged achievable at incremental costs of 2000 to 700 ECU, respectively (1990 ECU).
A lifecycle analysis of the greenhouse gas impacts of nine hybrid electric and fuel cell vehicles was compared to a 1996 vehicle and an “evolved 2020” baseline vehicle for the year 2020 by Weiss et al. (2000). The study concluded that a hybrid vehicle fuelled by compressed natural gas could reduce GHG emissions by almost two-thirds relative to the 1996 reference vehicle, and by 50% compared with an advanced 2020 internal combustion engine vehicle. Other technologies capable of 50%, or greater lifecycle GHG reductions versus the 1996 reference vehicle included: gasoline and diesel hybrids, battery-electric, and hydrogen fuel cell vehicles.
A recent study by five of the US Department of Energy’s (DOE’s) National Laboratories (Interlaboratory Working Group, 1997) assessed the economic market potential for carbon reductions, using the EIA’s National Energy Modelling System. Transport carbon emissions were projected to rise from 487 MtC in 1997 to 616 MtC by 2010 in the baseline case. In comparison to the baseline case, use of cost-effective technologies reduced carbon emissions by 12% in 2010 in an “Efficiency” case (Table 3.13). More optimistic assumptions about the success of R&D produced a reduction of 17% by 2010. The authors noted that lead times for cost-effectively expanding manufacturing capacity for new technologies and the normal turnover of the stock of transport equipment significantly limited what could be achieved by 2010. Efficiency improvements in 2010 for new transportation equipment were substantially greater (Table 3.14). New passenger car efficiency increased by 36% in the “Efficiency” case and by 57% in the more optimistic case (Brown et al., 1998).
| Table 3.13: Estimated technological
potential for carbon emissions reductions in the US transportation sector (Brown et al., 1998). |
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 |
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|
1990
|
2010
|
2020
|
2030
|
||
| |
|||||
| Business as usual (MtC) |
432
|
598
|
665
|
741
|
|
| Technology potential (%) |
|
7–12
|
15–17
|
27–40
|
|
|
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|
1990
|
2010
|
||||
|
|
Baseline
|
Efficiency
|
High efficiencya
|
||
|
|||||
| Transport emissions (MtC) |
432
|
616
|
543
|
513
|
|
| Reduction (%) |
|
|
12
|
17
|
|
| |
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| a Includes US$50/tC permit cost. | |||||
| Table 3.14: Projected transportation
efficiencies of 5-Laboratory Study (Interlaboratory Working Group, 1997). |
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|
2010
|
|||||
| Determinants |
1997
|
Baseline
|
Efficiency
|
HE/LCa
|
|
| |
|||||
| New passenger car l/100 km |
8.6
|
8.5
|
6.3
|
5.5
|
|
| New light truck l/100 km |
11.5
|
11.4
|
8.7
|
7.6
|
|
| Light-duty fleet l/100 kmb |
12.0
|
12.1
|
10.9
|
10.1
|
|
| Aircraft efficiency (seat-l/100 km) |
4.5
|
4.0
|
3.8
|
3.6
|
|
| Freight truck fleet l/100 km |
42.0
|
39.2
|
34.6
|
33.6
|
|
| Rail efficiency (tonne-km/MJ) |
4.2
|
4.6
|
5.5
|
6.2
|
|
| |
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| a HE/LC, high-energy/low-carbon. b Includes existing passenger cars and light trucks |
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Eleven of the US DOE’s National Laboratories completed a comprehensive assessment of the technological potential to reduce GHG emissions from all sectors of the US economy (National Laboratory Directors, 1997). This study intentionally made optimistic assumptions about R&D success, and did not explicitly consider costs or other market factors. The study concluded that the technological potential for carbon emissions reductions from the US transport sector was 40–70 million metric tons of carbon (MtC) by 2010, 100–180MtC by 2020 and 200–300MtC by 2030. These compare to total US transportation carbon emissions of 473MtC in 1997 (note that this base year estimate differs from that for the Interlaboratory Working Group). The report suggested the following technological potentials for carbon emissions reductions by mode of transport over the next 25 years: (1) light-duty vehicles with fuel cells, 50%–100%; (2) heavy trucks via fuel economy improvements, 20%–33%; and (3) air transport, 50%. It is difficult to interpret the practical implications of these conclusions, however, since no attempt was made by this study to estimate achievable market potentials.
Three European studies of the technical-economic potential for energy savings and CO2 reduction were reviewed by van Wee and Annema (1999). Generally, the studies focused on technological options, such as improving the fuel efficiencies of conventional cars and trucks, promotion of hybrid vehicles, switching trucks and buses to natural gas, and electrifying buses, delivery trucks, and mopeds. Only the study for Hanover included investment in improved public transport as a major policy option. The results, summarized in Table 3.15, suggest that emissions reductions of 8% to as much as 42% over business-as-usual projections may be possible.
The effects of a variety of fiscal and regulatory policies on CO2 emissions from road passenger vehicles have been estimated for Europe over a 15-year forecast horizon (Jansen and Denis, 1999; Denis and Koopman, 1998). These studies, both using the EUCARS model developed for the European Commission, concluded that CO2 reductions on the order of 15% over a baseline case could be achieved in the 2011 to 2015 time period at essentially zero welfare loss. Among the more effective policies were fuel taxes based on carbon content, fuel consumption standards requiring proportional increases for all cars, and the combination of fuel-consumption based vehicle sales taxes with a fuel tax. When reductions in external costs and the benefit of raising public revenues are included in the calculation of social welfare impacts, the feebate (a policy combining subsidies for fuel efficient vehicles and taxes on inefficient ones) and fuel tax policy combination was able to achieve CO2 reductions of 20% to 25% in the 2011 to 2015 time period at zero social cost (Jansen and Denis, 1999).
| Table 3.15: Assumptions and results of three European studies | |||
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Dutch
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Hanover
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EU
|
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| Base and target years (length of scenario in years) |
1995, 2020 (25 years)
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1990, 2010 (20 years)
|
1990, 2000 (10 years)
|
| CO2 emissions in target year: baseline (Mt) |
36.6–43.3 | 1.9 | 649.8 |
| Annual percentage growth in baseline emissions (Mt) | 0.4% to 1.4% per year | 0.6% per year | 1.7% per year |
| Solution scenario | (I) Best technical means, (II) Intensifying current policy, (III) Non-conventional local transport technologies |
(A) Local/regional, (B) National |
(R) Reasonable restrictive, (T) Target orientation |
| Base and target years (length of scenario, in years) |
1995, 2020 (25 years) | 1990, 2010 (20 years) | 1990, 2000 (10 years) |
| CO2 emission reduction (transport sector - Mt) |
(I) 11–13, (II) 3–11, (III) 18 |
(A) 0.16 and (B) 0.34 | (R) 84 and (T) 177 |
| Reduction of total transport emissions (including non-road transport) relative to baseline in target year | (I) 30%, (II) 8%–25%, (III) 42% |
(A) 8% and (B) 18% | (R) 13% and (T) 25% |
| Economic evaluation Net annual costs |
Not quantified, though asserted to be <€0 /tC | Not quantified | Not quantified |
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Other reports in this collection |
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