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Appendix E
Conservation Supply Data for Three Transportation Sectors

This appendix provides information on the calculation method used to determine cost-effectiveness for three transportation sectors: light-duty vehicles, heavy trucks, and aircraft.

Light-Duty Vehicles

Light-duty vehicle efficiencies were emphasized in Chapter 23 as the largest and most thoroughly studied transportation sector. Table E.1 shows the amount of fuel used by each type of vehicle for different modes of operation. As discussed in Chapter 23, the long trend to reduce operating costs via technology improvements while maintaining or improving other vehicle attributes is shown in Figure 23.1b. The fuel economy index (FEI), the product of vehicle mass and fuel economy in miles per gallon, controls for the fact that vehicle mass increased throughout the interval shown on the left-hand side of Figure 23.1b. This parameter, used to judge passenger cars for many decades, is a better indicator of powertrain efficiency than fuel economy alone. In the last decade the trend in the FEI, having the same units but measured at a differently specified test condition, is shown increasing at a similar rate. The recent trend was maintained, however, in a period of decreasing car mass and changing market demands for increased performance.

Research on the knocking properties of fuel in 1913 by Ricardo and later by Kettering provided the basis for many of the gains through 1970 (Amann, 1989). In recent times, applications of new computer technology to engine control, and applications of refined design techniques and new materials for weight reduction, have led to improved fuel economy (see Table E.2).

As the hedonic models of Atkinson and Halvorsen (1984, 1990) show,



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Page 727 Appendix E Conservation Supply Data for Three Transportation Sectors This appendix provides information on the calculation method used to determine cost-effectiveness for three transportation sectors: light-duty vehicles, heavy trucks, and aircraft. Light-Duty Vehicles Light-duty vehicle efficiencies were emphasized in Chapter 23 as the largest and most thoroughly studied transportation sector. Table E.1 shows the amount of fuel used by each type of vehicle for different modes of operation. As discussed in Chapter 23, the long trend to reduce operating costs via technology improvements while maintaining or improving other vehicle attributes is shown in Figure 23.1b. The fuel economy index (FEI), the product of vehicle mass and fuel economy in miles per gallon, controls for the fact that vehicle mass increased throughout the interval shown on the left-hand side of Figure 23.1b. This parameter, used to judge passenger cars for many decades, is a better indicator of powertrain efficiency than fuel economy alone. In the last decade the trend in the FEI, having the same units but measured at a differently specified test condition, is shown increasing at a similar rate. The recent trend was maintained, however, in a period of decreasing car mass and changing market demands for increased performance. Research on the knocking properties of fuel in 1913 by Ricardo and later by Kettering provided the basis for many of the gains through 1970 (Amann, 1989). In recent times, applications of new computer technology to engine control, and applications of refined design techniques and new materials for weight reduction, have led to improved fuel economy (see Table E.2). As the hedonic models of Atkinson and Halvorsen (1984, 1990) show,

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Page 728 TABLE E.1 Transportation Energy Use by Mode, 1987       Energy Use (trillion Btu) Thousand Barrels per Day Crude Oil Equivalenta Percentage of Total Highwayb 16,213.5 7,658.1 73.6 Automobiles 8,862.9 4,186.2 40.3 Motorcycles 24.6 11.6 0.1 Buses 156.8 74.1 0.7   Transit 74.3 35.1 0.3   Intercity 21.6 10.22 —c   School 60.9 8.8 0.3 Trucks 7,169.2 3,386.2 32.6   Light trucksd 4,031.9 1,904.4 18.3   Other trucks 3,137.3 1,481.8 14.2 Off-Highwayb (heavy duty)e 665.2 314.2 3.0 Construction 209.9 99.1 1.0 Farming 455.3 215.1 2.1 Nonhighwayb 4,490.6 2,121.0 20.4 Air 1,893.9 894.5 8.6   General aviationƒ 139.1 65.7 0.6   Domestic air carriers 1,564.2 738.8 7.1   International air carriers 190.6g 90.0 0.9 Water 1,326.0 626.3 6.0   Freight 1,095.7 517.5 5.0     Domestic trade 370.7 175.1 1.7     Foreign trade 725.0 342.4 3.3     Recreational boats 230.3 108.8 1.0 Pipeline 775.0 366.1 3.5   Natural gas 562.9 265.9 2.6   Crude petroleum 91.0 43.0 0.4   Petroleum product 67.4 31.8 0.3   Coal slurry 3.7 1.7 —c   Water 50.0 23.6 0.2 (continued on page 729)

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Page 729 (Table E.1 continued from page 728)         Energy Use (trillion Btu) Thousand Barrels per Day Crude Oil Equivalenta Percentage of Total Nonhighway—continued       Rail 495.7 234.1 2.2   Freighth 471.9 197.4 1.9   Passenger 77.8 36.7 0.3     Transit 41.0 19.4 0.2     Commuter rail 21.4 10.1 —c       Intercity 15.4 7.3 —c Military Operations 647.3 305.7 2.9   TOTALi 22,016.6 10,399.0 100.0 aBased on British thermal unit (Btu) content of a barrel of crude oil. bCivilian consumption only; military consumption shown separately. cNegligible. dTwo-axle, four-tire trucks. e1985 data. fAll aircraft in the U.S. civil air fleet except those operated under CFR parts 121 and 127 (i.e., air carriers larger than 30 seats or having a payload capacity of more than 7500 pounds). General aviation includes air taxis, commuter air carriers, and air travel clubs. gThis figure represents an estimate of the energy purchase in the United States for international air carrier consumption. hIncludes Class 1, 2, and 3 railroads. iTotals may not include all possible uses of fuels for transportation (e.g., snowmobiles). SOURCE: Davis et al. (1989). consumers choose vehicles as a bundle of attributes that include style, comfort, performance, safety, fuel economy, and price. By definition, externalities associated with pollution and some safety issues are not a component of this bundle. Atkinson and Halvorsen calculate the demand elasticities for the attribute of personal safety, however, and their estimate of the revealed preference for this attribute provides a value of life ranging between $2.4 million and $6 million. Similarly, their results indicate that a significant number of consumers place a great value on performance. Safety and performance are directly related to the mass and power of a vehicle, and fuel economy is inversely related to these variables. Although the literature on fuel economy (Bleviss, 1988) identifies vehicles having good performance (11 seconds, 0 to 60 mph) and exceptional fuel economy (81 highway miles or 63 city miles per gallon (mpg)), these prototypes are not subject to price or production constraints. Given a price constraint and the laws of physics, the consumer is forced to trade off desired attributes against one another.

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Page 730 TABLE E.2 Comparison of Vehicle Fuel Economy Technology Estimates Technology Office of Technology Assessment Fuel Economy Gain (percent)a Domestic Industry Fuel Economy Gain (percent)a Shackson and Leach Fuel Economy Gain (percent)b Front wheel drive 12.0   5.0   Drivetrain efficiency   Nil     Package weight (1 TWC)   2.0 3.5 Four-cylinder/four-valve 7.5 3.7 Not considered Four- or five-speed automatic CVT 7.5 3.4 15.0 Electronic transmission control 1.5 0.2 Not considered Aerodynamics 3.4 3.0 6.0 Tires 0.5 0.5 2.0 Accessories 1.0 1.0 6.0 Engine improvements         Overhead camshaft 6.0 1.1     Roller cams 1.5 2.2     Low-friction rings/pistons 1.5 1.5 7.0   Throttle body fuel injection (over carburetor) 3.0 2.4     Multiport fuel injection (over TBI) 7.0 1.3   Technologies proposed in Shackson and Leach study now implemented         Lubricants     2.0   Design parameters NA NA 5.0   Manual transmission improvements     5.0   Material substitutions     13.0 NOTE: TWC = test weight class; NA = not applicable; CVT = continuously variable transmission; TBI = throttle body injection. a Berger et al. (1990). b Shackson and Leach (1980).

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Page 731 When forecasting cost-effective greenhouse gas reductions for future years, several uncertainties should be recognized. Figure E.1 makes clear that, given consumer preferences, the relative sizes of the automobile and lightduty truck markets are highly interactive and there has been a tendency to shift toward less efficient light-duty trucks. In addition, the number of person-miles traveled by each sector depends strongly on fuel price and other product attributes. On-road fuel economies are typically lower than those predicted by the EPA (Environmental Protection Agency) fuel economy test procedure as they depend on differences in highway speed, congestion, urban-rural travel mix, and average trip length. To provide a generous estimate of greenhouse gas reductions, a relatively low composite fuel economy baseline of 19.7 mpg will be used for the combined fleet of automobiles and light-duty trucks. Travel projections from the MOBILE3 Emission Model for the year 2000 were used (the MOBILE3 model is an emissions planning document that has been used by EPA to project vehicle miles traveled, emission levels, and grams per mile). The CO2 emitted from the tailpipe of a vehicle must be adjusted for three additional global impacts. The first is the fact that other greenhouse gases such as CH4 and N2O often accompany CO2 emissions from the transportation sector. In addition, the processing and transportation of these fuels introduce greenhouse gases into the atmosphere. In the case of gasoline, for every 311 g of CO2 emitted, approximately 78 g of CO2 equivalent is emitted as CH4 and 38 g as N2O. In addition, image FIGURE E.1 Components of change in light-duty vehicles.

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Page 732 CO2 emissions and venting during the processing and distribution of gasoline bring the total greenhouse gas emissions to between 455 and 507 g CO2 equivalent (see Tables 3 and 6 of Unnasch et al., 1989). The CO2 emission values in each table provided in this appendix are therefore multiplied by 1.55 to obtain CO2 equivalence for both the cost-effectiveness and the emission reduction axis in each figure. Ten years ago, a fuel economy technology plan for automobiles and light-duty trucks was designed by the Energy Productivity Center of the Mellon Institute. The data from this study have been used in the calculations summarized in Table E.3 (Shackson and Leach, 1980) and plotted in Figure E.2 using the least-cost supply curve framework proposed by the Lawrence Berkeley Laboratory (Wright et al., 1981). For each technology, an estimate of consumer purchase cost in 1990 dollars was used as the numerator in the cost-effectiveness ratio. Reductions in fuel consumption produced by each technology were used to estimate the corresponding 10-year benefit stream for the denominator (i.e., reduced greenhouse gas emissions in tons of CO2 equivalent).1 Because the benefit stream is directly proportional to vehicle usage, which falls rapidly with age, it is appropriate to discount the benefit terms for each interval between the time of purchase and the time benefits are realized. The effect of discounting is to depreciate future benefits and thereby raise the calculated cost-effectiveness values. For the cost-effectiveness calculations in this study, the CO2-equivalent emissions avoided were discounted at 3, 6, 10, and 30 percent, and were used in plotting the four curves in Figure E.2. The discount rates of 3, 6, and 10 percent represent a societal perspective, while 30 percent is closer to the discount rate chosen by a consumer when selecting a vehicle. Because the technologies save fuel, the cost-effectiveness values were credited with $1.00/gal for discount rates of 3, 6, and 10 percent and $1.25/gal for the 30 percent rate—hence the negative values on the conservation supply curves. The horizontal axis in Figure E.2 represents an estimate of the cumulative annual reductions in greenhouse gas emissions as though each device were employed in the 1989 fleet. These quantities were not discounted (see Table E.3). The 24 technologies analyzed by Shackson and Leach are ordered by their cost-effectiveness in Table E.3—hence the monotonic increase in the curve in Figure E.2. As mentioned above, many of these most cost-efficient technologies were introduced, in part, during the 1975 to 1982 vehicle production era. The most expensive were not offered on the market by the industry. As the industry moved along the learning curve throughout the decade, old technologies became available at lower cost, and as the cost of fuel increased, new technologies became attractive to the consumer. Furthermore, these

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Page 733 TABLE E.3 Automobile and Light Truck Data (Shackson and Leach, 1980) Technologya Efficiency Gain (%) Cost to Consumer (1979 $) Cost to Consumer (1990 $) Cost Effectiveness ($/%) Penetration (%) Cumulative Improvement (%) Cumulative Cost (1990 $) Fleet Fuel Economy (mpg) 1. Weight Reduction 3.50 0.00 0.000 0.000 100.00 3.50 0.00 20.39 2. Aerodynamic Design 4.00 0.00 0.000 0.000 100.00 7.50 0.00 21.18 3. Lubrication 2.00 10.00 17.906 8.953 100.00 9.50 17.91 21.57 4. Access. Ld. 6.00 50.00 89.532 14.922 100.00 15.50 107.44 22.75 5. Red. Roll. 2.00 20.00 35.813 17.906 100.00 17.50 143.25 23.15 6. Impr. Man. 5.00 50.00 89.532 17.906 10.00 18.00 152.20 23.25 7. Front Wheel Drive 5.00 50.00 89.532 17.906 80.00 22.00 223.83 24.03 8. Des. Param. 5.00 50.00 89.532 17.906 70.00 25.50 286.50 24.72 9. TorqLoc. 5.00 60.00 107.438 21.488 40.00 27.50 329.48 25.12 10. Aero. Adds. 2.00 30.00 53.719 26.860 60.00 28.70 361.71 25.35 11. Eng. Des. 5.00 75.00 134.298 26.860 20.00 29.70 388.57 25.55 12. Material Substitution 1.50 25.00 44.766 29.844 100.00 31.20 433.33 25.85 13. 4Sp. Auto. 10.00 190.00 340.220 34.022 90.00 40.20 739.53 27.62 14. Material Substitution 8.00 200.00 358.127 44.766 100.00 48.20 1,097.66 29.20 15. Material Substitution 3.50 100.00 179.063 51.161 100.00 51.70 1,276.72 29.88 16. DISC 20.00 600.00 1,074.380 53.719 15.00 54.70 1,437.88 30.48 17. Engine Design 5.00 160.00 286.501 57.300 100.00 59.70 1,724.38 31.46 18. Vehicle Downsizing 12.00 400.00 716.253 59.688 100.00 71.70 2,440.63 33.82 19. Oper. Par. 5.00 175.00 313.361 62.672 100.00 76.70 2,753.99 34.81 20. Vehicle Downsizing 4.00 400.00 716.253 179.063 100.00 80.70 3,470.25 35.60 21. Turbocharging 5.00 650.00 1,163.912 232.782 32.00 82.30 3,842.70 35.91 (continued on page 734)

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Page 734 (Table E.3 continued from 733) Technologya Annual Fuel Savings (million gallons) Annual Savings (Million Tons CO2 Equivalent) 3% (Marginal Tons CO2 Equivalent) 3% ($/ton CO2 Equivalent) $1.00 credit 6% (Marginal Tons CO2 Equivalent) 6% ($/ton CO2 Equivalent) $1.00 credit 10% (Marginal Tons CO2 Equivalent) 1. Weight Reduction 3,243.08 44.99 2.20 -72.08 1.94 -72.08 1.67 2. Aerodynamic Design 6,690.87 92.82 2.34 -72.08 2.06 -72.08 1.77 3. Lubrication 8,320.31 115.42 1.11 -55.88 0.98 -53.73 0.84 4. Access. Ld. 12,870.04 178.54 3.09 -43.07 2.72 -39.21 2.34 5. Red. Roll. 14,283.36 198.15 0.96 -34.73 0.85 -29.76 0.73 6. Impr. Man. 14,629.20 202.94 0.23 -33.92 0.21 -28.84 0.18 7. Front Wheel Drive 17,293.90 239.91 1.81 -32.46 1.60 -27.18 1.37 8. Des. Param. 19,486.17 270.32 1.49 -29.94 1.31 -24.33 1.13 9. TorqLoc. 20,684.86 286.95 0.81 -19.23 0.72 -12.20 0.62 10. Aero. Adds. 21,386.19 296.68 0.48 -4.33 0.42 4.68 0.36 11. Eng. Des. 21,960.72 304.65 0.39 -3.17 0.34 6.01 0.30 12. Material Substitution 22,806.09 316.38 0.57 5.98 0.51 16.37 0.43 13. 4Sp. Auto. 27,498.45 381.47 3.18 24.11 2.81 36.92 2.41 14. Material Substitution 31,190.97 432.70 2.50 70.89 2.21 89.92 1.90 15. Material Substitution 32,683.99 453.41 1.01 104.72 0.89 128.26 0.77 16. DISC 33,909.95 470.42 0.83 121.70 0.73 147.50 0.63 17. Engine Design 35,850.85 497.34 1.32 145.52 1.16 174.49 1.00 18. Vehicle Downsizing 40,047.83 555.56 2.85 179.50 2.51 212.99 2.16 19. Oper. Par. 41,628.32 577.49 1.07 220.20 0.95 259.10 0.81 20. Vehicle Downsizing 42,829.74 594.16 0.81 806.78 0.72 923.77 0.62 21. Turbocharging 43,295.55 600.62 0.32 1,106.65 0.28 1,263.55 0.24 (continued on page 735)

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Page 735 (Table E.3 continued from page 734) Technologya 10% ($/ton CO2 Equivalent) $1.00 credit 30% (Marginal Tons CO2 Equivalent) 30% ($/ton CO2 Equivalent) $1.25 credit 6% Equivalent Fuel Cost ($/gallon) 30% Equivalent Fuel Cost ($/gallon) 1. Weight Reduction -72.08 0.49 -90.10 0.00 0.00 2. Aerodynamic Design -72.08 0.52 -90.10 0.00 0.00 3. Lubrication -50.70 0.25 -17.31 0.16 0.65 4. Access. Ld. -33.79 0.69 40.24 0.29 1.17 5. Red. Roll. -22.77 0.21 77.74 0.38 1.50 6. Impr. Man. -21.70 0.05 81.38 0.39 1.53 7. Front Wheel Drive -19.77 0.40 87.94 0.40 1.59 8. Des. Param. -16.45 0.33 99.26 0.43 1.69 9. TorqLoc. -2.31 0.18 147.38 0.54 2.13 10. Aero. Adds. 17.35 0.11 214.32 0.69 2.72 11. Eng. Des. 18.90 0.09 219.57 0.70 2.77 12. Material Substitution 30.97 0.13 260.66 0.79 3.14 13. 4Sp. Auto. 54.91 0.71 342.14 0.98 3.87 14. Material Substitution 116.66 0.56 552.33 1.45 5.75 15. Material Substitution 161.32 0.23 704.33 1.79 7.11 16. DISC 183.74 0.19 780.64 1.97 7.79 17. Engine Design 215.19 0.29 887.67 2.21 8.75 18. Vehicle Downsizing 260.04 0.63 1,040.34 2.55 10.12 19. Oper. Par. 313.77 0.24 1,223.21 2.96 11.75 20. Vehicle Downsizing 1,088.13 0.18 3,853.92 8.91 35.34 21. Turbocharging 1,484.00 0.07 5,206.33 11.95 47.40 (continued on page 736)

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Page 736 (Table E.3 continued from page 735) NOTES: Cost in 1990 = Cost in 1979 × Consumer Price Index (1990)/CPI (1979) = 130/72.6 × D (cost to consumer in 1979). Cumulative improvement = the sum of (penetrations × efficiency gains). Cumulative cost = previous cost + new component cost × %penetration. Fuel economy = (1 + %improvement) × 19.7. Annual fuel savings = (1,889.28 billion miles traveled in 2000) × [(1/19.7) - (1/mpg)]. Tons of CO2 equivalent avoided = 0.00895 × 1.55 × annual fuel savings. At 3%, marginal tons of CO2 equivalent for change in mpg = .00895 × 1.55 × ten years of vehicle miles traveled (discounted at 3%) × delta reciprocal mpg = .00895 × 1.55 × 92383 × ((1/mpg(i) - 1/mpg (i - 1)). At 6%, marginal tons of CO2 equivalent for change in mpg = .00895 × 1.55 × ten years of vehicle miles traveled (discounted at 6%) × delta reciprocal mpg = .00895 × 1.55 × 81530 × ((1/mpg(i) - 1/mpg(i - 1)). At 10%, marginal tons of CO2 equivalent for change in mpg = .00895 × 1.55 × ten years of vehicle miles traveled (discounted at 10%) × delta reciprocal mpg = .00895 × 1.55 × 69980 × ((1/mpg(i) - 1/mpg(i - 1)). At 30%, marginal tons of CO2 equivalent for change in mpg = .00895 × 1.55 × ten years of vehicle miles traveled (discounted at 30%) × delta reciprocal mpg = .00895 × 1.55 × 20560 × ((1/mpg(i) - 1/mpg(i - 1)). Corresponding $/ton of CO2 = marginal cost/marginal tons of CO2 equivalent - fuel credit @ $1.00 per gallon = (change in cumulative cost/marginal tons of CO2 equivalent) - 111.73/1.55. aAccess. Ld. = accessory load reduction; Red. Roll. = reduced rolling resistance; Impr. Man. = improved manual transmission; Des. Param. = engine design parameters; TorqLoc=torque converter lock-up; Aero. Adds = aerodynamic add-on equipment; Eng. Des. = engine design parameters; 4Sp. Auto. = four-speed automatic with torque converter lock-up; DISC = diesel and direct injected stratified charge engines; and Oper. Par. = engine operating parameters.

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Page 737 image FIGURE E.2 Annual CO2 reduction (Shackson and Leach (1980) analysis). technologies became attractive to larger segments of the market and their penetration was increased. Such a portfolio of technologies, similar to that proposed by Shackson and Leach, has been proposed by DOE (Difiglio et al., 1990). The bulk of the fuel economy gains proposed by DOE are achieved by introducing known technologies to most models in the fleet. While cautioning the reader on the firmness of the benefits and costs of the DOE portfolio of technologies, Ledbetter and Ross (1989) have also used a supply curve framework for the analysis of these data. The conservation supply curve data (utilizing the cost and fuel economy values for 17 technologies in Table 5 of Ledbetter and Ross) have been used to generate the curve in Figure E.3 for the four different perspectives of this study (see Table E.4). Comparison of the cost-effectiveness values in Figures E.2 and E.3 shows significant differences. The differences do not result as much from differences in the technology portfolios as from differences in the estimates of the costs and benefits of individual technologies. The disagreement between those who design and build cars and those who have generated the DOE data lies in the estimation, measurement, and aggregation of the fuel economy gain made possible by the technologies themselves when their

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Page 748 TABLE E.7 Heavy-Heavy Truck Data (Energy and Environmental Analysis, Inc., 1984) Technology Efficiency Gain Cost to Consumer (1979 $) Cost to Consumer (1990 $) Cost Effectiveness ($/%) Penetration (%) Cumulative Improvement (%) Cumulative Cost (1990 $) Fleet Fuel Economy (mpg) 1 BodyAero 9.00 540.00 675.65 75.07 100.00 9.00 675.65 7.29 2 FanDrives 4.00 252.00 315.30 78.83 100.00 13.00 990.95 7.56 3 Drivetrn 3.00 190.00 237.73 79.24 100.00 16.00 1,228.68 7.76 4 Access. 2.00 128.00 160.15 80.08 100.00 18.00 1,388.84 7.89 5 Lubric. 1.50 97.00 121.37 80.91 100.00 19.50 1,510.20 7.99 6 AeroDev. 6.00 400.00 500.48 83.41 58.00 22.98 1,800.48 8.23 7 Radials 6.00 1,080.00 1,351.30 225.22 70.00 27.18 2,746.39 8.51 8 Spd. Cont. 5.00 1,335.00 1,670.36 334.07 50.00 29.68 3,581.57 8.68 9 Adv. Rad. 6.00 2,070.00 2,589.99 431.67 70.00 33.88 5,394.56 8.96 Technology Annual Fuel Savings (million gallons) Annual Savings (million tons CO2 Equivalent) 3% (Marginal tons CO2 Equivalent) 3% ($/ton CO2 Equivalent) $1.00 credit 6% (Marginal tons CO2 Equivalent) 6% ($/ton CO2 Equivalent) $1.00 credit 10% (Marginal tons CO2 Equivalent) 10% ($/ton CO2 Equivalent) $1.00 credit 1 BodyAero 1,181.39 16.39 98.33 -65.21 83.76 -64.02 71.89 -62.69 2 FanDrives 1,646.04 22.83 38.68 -63.93 32.94 -62.51 28.28 -60.93 3 Drivetrn 1,973.51 27.38 27.26 -63.36 23.22 -61.84 19.93 -60.15 4 Access. 2,182.56 30.28 17.40 -62.88 14.82 -61.28 12.72 -59.49 5 Lubric. 2,334.77 32.39 12.67 -62.50 10.79 -60.84 9.26 -58.98 6 AeroDev. 2,673.57 37.09 28.20 -61.79 24.02 -60.00 20.62 -58.00 7 Radials 3,057.79 42.42 31.98 -42.51 27.24 -37.36 23.38 -31.63 8 Spd. Cont. 3,274.67 45.43 18.05 -25.82 15.38 -17.77 13.20 -8.80 9 Adv. Rad. 3,620.80 50.23 28.81 -9.15 24.54 1.80 21.06 13.99 (continued on page 749)

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Page 749 (Table E.7 continued from page 748) Technology 30% (Marginal tons CO2 Equivalent) 30% ($/ton CO2 Equivalent) $1.25 credit 1 BodyAero 21.12 -59.12 2 FanDrives 8.31 -52.15 3 Drivetrn 5.85 -49.50 4 Access. 3.74 -47.26 5 Lubric. 2.72 -45.50 6 AeroDev. 6.06 -42.18 7 Radials 6.87 47.60 8 Spd. Cont. 3.88 125.29 9 Adv. Rad. 6.19 202.87 NOTES: Average fuel economy = 6.69 mpg. All equations and notes the same as Table D.3 except for the following: Cost in 1990 = Cost in 1984 × CPI (1990)/CPI(1984)-130/103.9 Fleet fuel economy = 6.69(1 + cumulative improvement/100) Fuel saved = (95720 million miles traveled in 2000) × (1/6.69-1/mpg), estimate for heavy trucks in Mobile 3 Marginal Tons of CO2 @ 3% = 6 × 92383 miles × .00895 × 1.55 × (1/mpg(i)-1/mpg(i-1)) Marginal Tons of CO2 @ 6% = 6 × 81530 miles × .00895 × 1.55 × (1/mpg(i)-1/mpg(i-1)) Marginal Tons of CO2 @ 10% = 6 × 69800 miles × .00895 × 1.55 × (1/mpg(i)-1/mpg(i-1)) Marginal Tons of CO2 @ 30% = 6 × 20560 miles × .00895 × 1.55 × (1/mpg(i)-1/mpg(i-1)) Truck data taken from Table 3-1 of Environmental and Energy Analysis (EEA) (1984). When cost-effectiveness data were not in the EEA report, the mileage at either 50% or 90% of vehicles providing "cost-effectiveness" was used from the equation on page 3-1 of the EEA report. This "SAVINGS" was then considered at least as great as the cost of technology.

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Page 750 image FIGURE E.4 Annual CO2 reduction (light-heavy trucks). image FIGURE E.5 Annual CO2 reduction (medium-heavy trucks).

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Page 751 image FIGURE E.6 Annual CO2 reduction (heavy-heavy trucks). Leone and Parkinson (1990), which differ on the relative importance of market and regulatory mechanisms. Cross-sectional data sets for several nations are now emerging to provide additional insight into consumer preferences (see Schipper, 1991). Similarly, the wide range of values in the conservation supply curves based on the Shackson and Leach and the Ledbetter and Ross studies may well be reconciled with these emerging data. In light of these remaining uncertainties, it is interesting to examine the automobile and light truck conservation supply curves in the context of fuel prices and consumer preference for new car fuel economy. To examine the interactions of consumer choice and technology, the panel has plotted conservation supply information in a format that allows a comparison with consumer decision making. Results from Tables E.3, E.4, and E.8 derived from Shackson and Leach (1980), Ledbetter and Ross (1989), and Difiglio et al. (1990), respectively, are plotted in Figure E.7. Values

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Page 752 TABLE E.8 A Supply Curve for Light-Duty Vehicles Fuel Economy Technologies (Difiglio et al., 1990) Technology Optionsa Cumulative Cost (1990 $) Fleet Fuel Economy (mpg) Annual Fuel Savings (million gallons) Annual Savings (Million tons CO2 Equivalent) 3% (Marginal tons CO2 Equivalent) 3% ($/ton CO2 Equivalent) $1.00 credit 6% (Marginal tons CO2 Equivalent) 6% ($/ton CO2 Equivalent) $1.00 credit 1 0.00 20.77 0.00   0.00 -72.08 0.00 -72.08 2 274.56 24.31 13,241.79 183.70 8.98 -41.52 7.93 -37.45 3 425.57 26.38 19,359.97 268.57 4.15 -35.70 3.66 -30.85 4 562.85 28.00 23,491.05 325.88 2.80 -23.10 2.47 -16.57 5 864.86 30.31 28,628.68 397.15 3.49 14.58 3.08 26.11 6 915.20 31.00 30,020.82 416.46 0.94 -18.78 0.83 -11.69 7 1,121.12 31.77 31,496.47 436.93 1.00 133.63 0.88 161.01 8 1,430.00 32.46 32,764.76 454.53 0.86 286.94 0.76 334.73 9 1,830.40 33.31 34,243.30 475.04 1.00 327.14 0.89 380.28 10 2,516.80 34.00 35,398.27 491.06 0.78 804.02 0.69 920.64 11 3,374.80 34.77 36,627.63 508.12 0.83 956.78 0.74 1,093.74 12 4,919.20 35.62 37,918.59 526.03 0.88 1,691.50 0.77 1,926.26 (continued on page 753)

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Page 753 (Table E.8 continued from page 752) Technology Optionsa 10% ($/ton CO2 Equivalent) $1.00 credit 30% (Marginal tons CO2 Equivalent) 30% ($/ton CO2 Equivalent) $1.25 credit 6% Equivalent Fuel Cost ($/gallon) 30% Equivalent Fuel Cost ($/gallon) 1 -72.08 0.00       2 -31.73 2.00 65.26 1.23 0.31 3 -29.30 0.92 388.67 1.46 0.37 4 -25.45 0.62 830.41 1.97 0.50 5 -13.29 0.78 1,042.99 3.49 0.88 6 -12.76 0.21 4,282.57 2.14 0.54 7 -2.81 0.22 4,960.44 8.27 2.09 8 12.85 0.19 7,396.44 14.44 3.64 9 31.94 0.22 8,128.27 16.05 4.05 10 66.28 0.17 14,362.20 35.23 8.68 11 107.23 0.19 18,111.84 41.30 10.43 12 777.68 0.19 20,730.88 70.92 17.89 NOTE: Average vehicle fuel economy = 27/1.3 mpg. aNumbers represent combinations of fuel economy technologies phased in as shown in Table 1 and Figure 3 of Difiglio et al. (1990).

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Page 754 image FIGURE E.7 Cost of gasoline and efficiency for a 30 percent discount rate. for the average new-car fleet efficiencies, along with the average fuel prices for Japan, Sweden, the United Kingdom, the United States, and West Germany, are also plotted as squares on the same figure. The automobile fleet fuel economy values were reduced by a factor of 1.3 since increased urban congestion, higher highway speeds, and a larger fraction of total miles being driven in urban areas are projected to increase the difference between the EPA fuel economy test and actual on-road fuel economy from 15 percent in 1987 to 30 percent in 2010 (Ledbetter and Ross, 1990). Although Difiglio et al. (1990) estimated a 17 percent difference in the year 2000, their fuel economy values were also reduced by the factor 1.3 to be consistent with the other adjustments in Figure E.7. Since the Shackson and Leach (1980) supply curve was for a fleet that included light trucks, no adjustment was made to their base fuel economy of 19.7 mpg. The perspective in Figure E.7 is that of a consumer expecting a 10-year benefit stream using a 30 percent discount rate on future benefits. If the consumers in these five nations had no preference between purchasing fuel economy technology and avoiding the cost of gasoline, they would choose a set of technologies on one of the three curves. If, on the other hand, consumers valued other attributes in their vehicles sacrificed by fuel economy

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Page 755 technologies, they would choose a level of fuel economy lower (i.e., to the left) of the curve in Figure E.7. If a 30 percent discount rate and a 10-year lifetime are valid assumptions, consumers in the United States and West Germany choose a level of fuel economy appropriate for their fuel prices, provided the Shackson and Leach curve is an accurate indication of the cost of technology. The fact that three other nations lie a significant distance from the steepest supply curve indicates either that their vehicle use patterns are dramatically different or that the technology cost-effectiveness information is inappropriate. To summarize the relative magnitude of the values along with their uncertainties, a sample of average values from two different regions of two different analyses is presented below. The discontinuity in the slope of the Difiglio curve at approximately 31 mpg (on-road fuel economy) is the point at which sales shifts in the vehicle mix are required to gain higher average fuel economy levels. Difiglio has labeled this point the ''maximum technology" point for the year 2000.
2 The panel has chosen the region beyond this point as the region in which life-style adjustments are incurred. Up to this point, the costs of attributes lost or compromised by fuel efficiency technologies are ignored even though consumers consider them substantial. The average cost-effectiveness values, as distinct from marginal cost-effectiveness values, which increase significantly as one moves past 25 mpg, are summarized in Table E.9 as a function of the discount rate for the three cost curves (see calculations in Tables E.3 through E.8). The costs are constrained, however, by the fact that the panel has not considered cumulative costs exceeding $3850 (1990 dollars) from the Shackson and Leach study, and Ledbetter and Ross did not go beyond cumulative costs of $609 (1990 dollars). To provide a visual impression of the relative magnitudes and their uncertainties, Figure E.8 illustrates values derived for the discount rate of 6 percent for light duty vehicles. One should keep in mind that data for the automobile and light truck calculations were from three sources, thereby providing the indication of uncertainty. Notes 1. Throughout this report, tons (t) are metric; 1 Mt = 1 megaton = 1 million tons; 1 Gt = 1 gigaton = 1 billion tons. 2. Subsequent to the preparation of these results, K. G. Duleep (co-author with Difiglio and Green) has refined the estimate of the "maximum technology" point. Duleep estimates that in 1996 all available technologies could produce a CAFE mpg of 29.3 (22.5 on-road) and in 2001 all available technologies could produce a CAFE mpg of 36.0 (27.7 on-road) (Plotkin, 1991).

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Page 756 TABLE E.9 Implementation Cost of Vehicle Efficiency Improvements   Net Implementation Cost ($/t CO2 equivalent) Emission Reduction (Mt CO2 equivalent/yr)   d=3% d=6% d=10% d=30% NO CHANGE IN FLEET MIX           Full-Cycle Emission Accounting         Light vehicle, Ledbetter and Ross -52 -50 -46 -2 379 Light vehicle, Shackson and Leach -10 -1 +10 +191 389 Light vehicle, Difiglio -26 -22 -13 +128 397 Heavy truck -42 -38 -32 +45 61 Aircraft retrofit     +230   13 Consumption Emission Accounting         Light vehicle, Ledbetter and Ross -81 -78 -71 -3 245 Light vehicle, Shackson and Leach -16 -2 +16 +296 251 Light vehicle, Difiglio -40 -34 -20 +198 256 Heavy truck -65 -59 -50 +70 39 Aircraft retrofit     +357   8 CHANGE IN FLEET MIX           Full-Cycle Emission Accounting         Light vehicle, Ledbetter and Ross +13 +25 +41 +293 35 Light vehicle, Shackson and Leach +306 +356 +427 +1,609 108 Light vehicle, Difiglio +527 +657 +777 +2,820 129 Consumption Emission Accounting         Light vehicle, Ledbetter and Ross +20 +39 +64 +454 23 Light vehicle, Shackson and Leach +474 +552 +663 +2,494 70 Light vehicle, Difiglio +887 +1,018 +1,204 +4,370 83

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Page 757 image FIGURE E.8 Potential emission reduction from light-duty vehicles. References Amann, C. A. 1989. The automotive spark-ignition engine—An historical perspective. In History of the Internal Combustion Engine, ICE, Volume 8, Book No. 100294-1989, E. F. C. Somerscales and A. A. Zagotta, eds. American Society of Mechanical Engineers. Atkinson, S. E., and R. Halvorsen. 1984. A new hedonic technique for estimating attribute demand: An application to the demand for automobile fuel efficiency. Review of Economics and Statistics 66(3):416–426. Atkinson, S. E., and R. Halvorsen. 1990. Valuation of risks to life: Evidence from the markets for automobiles. Review of Economics and Statistics 72(1):137–142. Berger, J. O., M. H. Smith, and R. W. Andrews. 1990. A system for Estimating Fuel Economy Potential due to Technology Improvements. Ann Arbor, Mich: The University of Michigan, School of Business Administration. Bleviss, D. 1988. The New Oil Crisis and Fuel Economy Technologies. New York: Quorum Books.

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Page 758 Bussmann, W. V. 1990. Potential Gains in Fuel Economy: A Statistical Analysis of Technologies Embodied in Model Year 1988 and 1989 Cars. Intra-Industry Analysis of Fuel Economy Efficiencies. Carlsmith, R. S., W. U. Chandler, J. E. McMahon, and D. J. Santini. 1990. Energy Efficiency: How Far Can We Go? Report ORNL/TM-11441. Prepared for the Office of Policy, Planning and Analysis, U.S. Department of Energy. Oak Ridge, Tenn.: Oak Ridge National Laboratory. Davis, S. C., D. B. Shonka, G. J. Anderson-Batiste, and P. S. Hu. 1989. Transportation Energy Data Book: Edition 10. Report ORNL-6565 (Edition 10 of ORNL-5198). Prepared for the U.S. Department of Energy. Oak Ridge, Tenn.: Oak Ridge National Laboratory. Difiglio, C., K. G. Duleep, and D. L. Greene. 1990. Cost effectiveness of future fuel economy improvements. The Energy Journal 11(1):65–86. Energy and Environmental Analysis (EEA). 1984. Documentation of market penetration forecasts. In Historical and Projected Emissions Conversion Factor and Fuel Economy for Heavy Duty Trucks, 1962–2002. Arlington, Va.: Energy and Environmental Analysis, Inc. Godek, P. E. 1990. The Corporate Average Fuel Economy Standard 1978–1990. Working Paper, October 1990. Greene, D. L. 1989. CAFE or Price?: An Analysis of the Effects of Federal Fuel Economy Regulations and Gasoline Price on New Car MPG, 1978–89. Prepared for the Office of Policy Integration, Office of Policy, Planning and Analysis, U.S. Department of Energy. November 1989. Washington, D.C.: U.S. Department of Energy. Ledbetter, M., and M. Ross. 1989. Supply curves of conserved energy for automobiles. Draft paper prepared for Lawrence Berkeley Laboratory by the American Council for an Energy-Efficient Economy, Washington, D.C. Leone, R. A., and Parkinson, T. W. 1990. Conserving energy: Is there a better way? Paper prepared for the Association of International Automobile Manufacturers. Plotkin, S. E. 1991. Testimony before Senate Committee on Energy and Natural Resources. Washington, D.C.: Office of Technology Assessment. March 20, 1991. Schipper, L. 1991. Energy saving in the U.S. and other wealthy countries: Can the momentum be maintained? Draft. International Energy Studies, Energy Analysis Program, Applied Science Division, Lawrence Berkeley Laboratory. Shackson, R. H., and H. J. Leach. 1980. Using Fuel Economy and Synthetic Fuels to Compete with OPEC Oil. Pittsburgh, Pa.: Carnegie-Mellon University Press. Unnasch, S., C. B. Moyer, D. D. Lowell, and M. D. Jackson. 1989. Comparing the Impact of Different Transportation Fuels on the Greenhouse Effect. Prepared by the Acurex Corporation for the California Energy Commission. April 1989. Sacramento: California Energy Commission. Wright, J., A. Meier, M. Maulhardt, and A. H. Rosenfeld. 1981. Supplying Energy Through Greater Efficiency: The Potential for Conservation in California's Residential Sector. Report LBL-10738, EEB 80-2. January 1981. Berkeley, Calif.: Lawrence Berkeley Laboratory.