| 3.4.6 Technological and Economic Potential 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 Japans 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). 
   
    |  Figure 3.10: Passenger car fuel economy cost curves.
 |  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 Energys (DOEs) National 
  Laboratories (Interlaboratory Working Group, 1997) assessed the economic market 
  potential for carbon reductions, using the EIAs 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).
 |   
    |  |   
    |  | 1990 | 2010 | 2020 | 2030 |   
    |  |   
    | Business as usual (MtC) | 432 | 598 | 665 | 741 |   
    | Technology potential (%) |  | 712 | 1517 | 2740 |   
    |  |   
    |  | 1990 | 2010 
   |   
    |  |  | Baseline | Efficiency | High efficiencya |   
    |  |   
    | Transport emissions (MtC) | 432 | 616 | 543 | 513 |   
    | Reduction (%) |  |  | 12 | 17 |   
    |  |   
    |  |  
 
   
    | Table 3.14: Projected transportation 
      efficiencies of 5-Laboratory Study (Interlaboratory Working Group, 1997).
 |   
    |  |   
    |  |  | 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 |   
    |  |   
    |  |  Eleven of the US DOEs 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 4070 
  million metric tons of carbon (MtC) by 2010, 100180MtC by 2020 and 200300MtC 
  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 |   
    |  |   
    |  | Dutch
     | Hanover
     | EU
     |   
    |  |   
    | Base and target years (length of scenario in years)
 | 1995, 2020 (25 years)
     | 1990, 2010 (20 years)
     | 1990, 2000 (10 years)
     |   
    | CO2 emissions in target year: baseline (Mt)
 | 36.643.3 | 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) 1113, (II) 311,
 (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 |   
    |  |  
 |