Cálculo del módulo resistente

We believe our findings are conservative—tending to understate the quantity and overstate the cost of oil-displacing alternatives—for four main reasons:

1. We assume little future technological innovation—just what’s already in the commercialization pipeline. This is likely to understate future opportunities dramatically, much as if we sought to solve problems in 2004 by using only the technologies already being commercialized in 1979 (like IBM’s first personal computer, which came on the market two years later). Though our broad conclusions don’t depend on the biggest breakthroughs now emerging in oil-displacing technologies (such as cheap ultralight autobodies and cheap durable fuel cells), we do consider those at least as plausible as any conceivable further advances in finding and lifting oil, and probably far more so.

2. We uncritically adopt EIA’s official projection that in 2025, 20% more Americans—348 million people—will use 40% more energy and 44%

more oil than 289 million Americans used in 2002. This extrapolation

Structure and methodology This Report

204. From EERE 2003. The car/light-truck data, which

1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025

0

Figure 7: Transportation Petroleum Use by Mode (1970–2025) Of the growth EIA projected in January 2004 for U.S. oil consumption during

2000–25, graphed here by the U.S. Department of Energy, 55% was for light trucks, 15% heavy vehicles, 7% aircraft, and only 3% automobiles.²⁰⁴

Total oil used for transportation surpassed domestic oil production (crude oil plus lease condensate) starting in 1987, and is projected to be

twice domestic production by 2010.

Source: Transportation Energy Data Book: Edition 23, DOE/ORNL-6970, October 2003; and EIA Annual Energy Outlook 2004, January 2004.

This Report Conservatisms and conventions

reflects a far from deprived future: a 96% higher GDP, 97% bigger per-sonal disposable income, 22% larger labor force, 80% higher industrial output, 81% more freight trucking, 41% more commercial floorspace, and 25% more and 6% bigger houses. Each person will drive 33% and fly 48% more miles. Total light-vehicle miles rise 67%. Average

horsepower rises 24% for new cars and 18% for new light trucks, while light-vehicle efficiency improves 3 mpg for new models and 1.2 mpg, or 6%, for the operating fleet, and light-vehicle annual sales grow 27%. EIA’s forecast also assumes a 29.4% (1.5%/y) drop in pri-mary energy intensity during 2002–25, encouraged by slightly costlier energy (except electricity, which gets 4% cheaper). Every indicator of consumer choice and material standard of living rises steeply, though one might wonder about such quality-of-life indicators as inequities, social tensions, dissatisfaction, and traffic congestion (which in 2001 wasted 3.6 billion hours and 5.7 billion gallons, worth $70 billion, in 75 U.S. urban areas²⁰⁶). We also assume that the required expansions of infrastructure (driving and flying space, refineries, pipelines, etc.) will all occur smoothly, undisturbed by any unbudgeted costs or ill effects.

3. We omit many oil-saving options that are individually often large and collectively immense, and we don’t analyze some others that are indi-vidually small but collectively significant. The main transportation options we deliberately omit, many important, include:

•

• Improving land-use (e.g., by not subsidizing nor mandating sprawl, or by smart-growth initiatives) so people needn’t travel so much to get where they want to be, or ideally are already there;²⁰⁷

•

• Telecommuting and other substitutions of telecommunications for physical mobility;

•

• Shifting passenger transportation modes, e.g., from road or air to rail, car to public transit,²⁰⁸or driving to walking and biking;

•

• Increasing passenger load factors, except by HOV lanes and normal airline methods;

•

• Restructuring the airline industry (through authentic gate and slot competition) to permit fair competition between hub-and-spokes airlines and a Southwest-Airlines-like hubless point-to-point pat-tern that reduces unnecessary aircraft movements, travel time, mis-connections, hub congestion, and oligopoly rents;²⁰⁹

•

• Innovative public transit vehicles such as Curitiba-style²¹⁰express buses or Cybertran^®-style²¹¹ultralight trains;

•

• Improved freight logistics,²¹²and innovative vehicles such as containerized airships,²¹³although we do include continued grad-ual expansion of road/rail freight intermodality.

Conservatism #2 as fast as population is not necessary, desirable, or economic, and that more thoughtful land-use pat-terns can reduce cost and crime, increase social cohesion and economic vitality, reduce travel needs by tens of percent (even more with the drop in

“induced travel” when fewer roads must be built), and increase real-estate values and profits.

208. Shifting from cars to, say, transit buses may or may not save fuel, depend-ing on efficiencies and load factors: e.g., ORNL 2003, Table 2.11.

209. A Dutch pilot study suggests point-to-point flight patterns could serve the same origin-destination network with ~17% less fuel: Peeters et al. 1999, summarized in Peeters, Rietveld, & Schipper 2001.

210. Hawken, Lovins, &

Lovins 1999, Ch. 14.

211. See

www.cybertran.com.

212. Such as the software and hardware suite described at Trans-Decisions 2003. A further step could be applying to civilian logistics the

213. These are being com-mercialized by German

4. Instead, we adopt only options that provide EIA’s projected 2025 mobility “transparently” to the user, with no change of lifestyle or loss of convenience—other than those entailed by the congestion implicit in EIA’s enthusiastic traffic forecasts. Similarly, beyond any changes implicit in EIA’s growth forecast, we assume no shifts in where, when, or how people use buildings (just more of everything including

sprawl); no savings in the materials that industry processes and fabri-cates (due to materials-frugal and longer-lived product design or closed materials loops, except plastics recycling); and no changes in when people choose to use electricity (even though price signals to do so, and “smart meters” and other technologies to make demand response convenient, are rapidly emerging).

Using the technical conventions in Box 5, we next present our analysis and findings of what each of the four oil-displacing options can do by itself in each of the two technology suites. We’ll combine them successive-ly, showing how each leaves less oil to be displaced by later options (pp.

123–125, 227–230). Having contrasted Conventional Wisdom and State of the Art technologies, each incorporating all four oil-displacing options in integrated form, we’ll finally discuss their implementation, global context, and strategic implications.

Conservatisms and conventions This Report

We adopt only options that provide EIA’s projected 2025 mobility

“transparently”

to the user, with no change of lifestyle or loss of convenience.

Units and conversions: We use customary U.S.

units, plus international (metric) units in paren-theses where readers from countries other than the United States, Liberia, and Myanmar are most likely to want them. Year is abbreviated “y”, day “d”, hour “h”, second “s”. Tons are U.S.

short tons (2,000 lb); tonnes are metric (1,000 kg).

Thousand (10³) is “k”, million (10⁶) is “M” (the worldwide scientific, not the U.S. engineering, convention), and billion (10⁹) is “b”. We use industry-standard conversion constants, includ-ing EIA’s²¹⁴for fuels. By industry and EIA conven-tion, we express fossil-fuel prices, energy con-tent, and efficiency at the Higher Heating Value (which includes the energy needed to evaporate water created by combustion), but we use the Lower Heating Value for hydrogen (120 MJ/kg).

Economic assumptions: Unless otherwise noted, all monetary quantities are converted to constant 2000 U.S. dollars (2000 $) using the GDP implicit price deflator.²¹⁵All discounting—to present value or to levelize cost streams, where noted—applies a 5%/year real discount rate. Pages 189–190 dis-cuss the spread between this conservatively high social rate and much higher implicit consumer discount rates; pp. 16 and 101, risk-adjustment.

(The federal government uses 3.29%/y for most long term projects, and 3.0%/y for its own ener-gy-efficiency investments.) Prices in our analysis exclude sales and ownership taxes on vehicles and all taxes on retail fuels, because those taxes are transfer payments, not real resource costs.

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214. EIA 2003c, Appendix A.

215. BEA 2004.

5: Conventions

(details are described in the Technical Annex, Ch. 4)

Data sources: U.S. energy data not otherwise cited are from the U.S. Energy Information Administration (EIA, www.eia.doe.gov), typi-cally the Annual Energy Review 2002, Annual Energy Outlook 2004, or sectoral yearbooks.

Transportation data not otherwise cited are from Oak Ridge National Laboratory’s Transportation Energy Data Book 23 (2003, ORNL-6970,

www-cta.ornl.gov/data), which relies heavily on U.S. Department of Transportation data.

Road-vehicle efficiency metric: Unless other-wise stated, we measure fuel economy in the

“adjusted” USEPA (combined city/highway driving cycle) miles per U.S. gallon (mpg) of gasoline or equivalent—the same figure used for sales stick-ers, but 10%/22% below the city/highway “labo-ratory” mpg measured in EPA testing and used for Corporate Average Fuel Economy (CAFE) regulation. (When calculating the corresponding oil usage or savings, we use EIA’s “degradation factor” to obtain “on-road” mpg.) Fuel intensity is expressed in gal/mi or L/100 km (liters per 100 kilometers).

Hydrocarbon definitions: As in EIA statistics,

“petroleum” is the sum of crude oil, lease con-densate, and natural gas plant liquids. Thus liquefied petroleum gas (LPG) is “petroleum”

whether it was derived from producing oil or nat-ural gas, and whether it is used as a fuel or as a feedstock. “Oil” is used in this report to refer to “petroleum” or “refined petroleum products”

or both, according to context (production or use).

We include all non-fuel (feedstock) oil

consump-tion. We adopt EIA’s convention of accounting for oxygenate production and consumption as petro-leum-based (even though most of it is not²¹⁶), with one noted exception on p. 1 (see note 15).

Petroleum processing: U.S. statistics measure oil by volume (1 barrel ≡ 1 bbl ≡ 42 U.S. gallons = 159 L), but refining heavy crude oil into lighter refined products expands its volume while con-suming energy and money. We convert from end-use fuel savings back to equivalent crude-oil refinery inputs not by relative volume but by using their EIA-compiled relative energy content as the best measure of utility. We don’t adjust that conversion for refineries’ energy use because that’s counted as part of industrial energy consumption. We conservatively convert the cost of saved fuel back to 2000 Refiner’s Acquisition Cost (RAC) solely on the short-run margin, i.e., by deducting only the 2000-average cash operating costs needed to refine the crude oil and deliver it to the point in the value chain where the savings occur. (These cash operating costs include EIA’s estimate of incremental investment to comply with low-sulfur regula-tions, but aren’t adjusted for any deferral or avoidance by reducing demand.) This value-chain addback thus calculates the RAC of crude oil that would have produced and delivered that saved fuel in the short run from existing industry physical assets, taking no credit for avoided future refining or delivery capacity. Thus an RAC of $26.08/bbl (2000 $), EIA’s projected 2025 crude-oil price, breaks even against saving 76¢/gal pre-tax retail gasoline. The difference between 76¢

and the pretax retail price reflects all embedded costs from refinery to filling station. Our oil dis-placements could avoid further investment for new refineries, pipelines, delivery fleets, etc.

For this reason, and because our conversion isn’t risk-adjusted, it understates oil

displace-(continued on next page) This Report Conservatisms and conventions

216. EIA’s 2000 “oil“ consumption includes 0.25 Mbbl/d (in crude-oil energy equivalent) of biomass-derived ethanol and natural-gas-derived MTBE. We obtain the sources of MTBE in 1996, which we assume also for 2000, from Wang 1999, who says that over 90% of MTBE’s isobutylene and methanol components originate in natural-gas processing plants rather than from petroleum. EIA thus understates the degree of biomass- and natural-gas-for-oil substitution that has already occurred to produce these oxygenates.

5: Conventions (continued)

Box 5: Conventions (continued) This Report

ments’ implied value. Our supply-curve graphs show both RAC $/bbl and retail ¢/gal (of the fuel being displaced—gasoline, diesel fuel, or jet fuel), but due to the value-chain addback and the energy-per-unit-volume conversion, their relationship isn’t simply the standard conversion factor of 42 gal/bbl.

Cost of Saved Energy: We express the cost of saving a unit of oil as a Cost of Saved Energy (CSE), calculated at the point in the value chain where it occurs, then converted (as just

described) to equivalent short-run RAC per bar-rel of crude oil. We calculate CSE using the standard formula developed at Lawrence Berkeley National Laboratory. This divides the marginal cost of buying, installing, and maintain-ing the more efficient device by its discounted stream of lifetime energy savings. Using the standard annuity formula, the dollar cost of sav-ing 1 bbl then equals Ci/S[1–(1+i)^–n], where C is installed capital cost ($), i is annual real dis-count rate (assumed here to be 0.05), S is the rate at which the device saves energy (bbl/y), and n is its operating life (y). Thus a $100 device that saved 1 bbl/y and lasted 20 y would have a CSE of $8/bbl. Against a $26/bbl oil price, a 20-y device with a 1-y simple payback would have a CSE of $2.1/bbl. Engineering-oriented analysts conventionally represent efficiency “resources”

as a supply curve, rather than as shifts along a demand curve (economists’ convention). CSE is methodologically equivalent to the cost of supplied energy, such as refined petroleum

products: the value of the energy saved isn’t part of the CSE calculation, which shows only the cost of achieving the saving. Whether that saving is cost-effective depends on whether its CSE is more or less than the cost of the energy it saves, and on what costs are counted (private internal vs. full societal). Except as noted, our CSEs are compared on the short-run margin with EIA’s RAC of $26.08 (2000 $) in 2025, exclud-ing externalities and downstream capital costs.

CSEs can be negative if capital charges are more than offset by saved maintenance cost, avoided equipment, etc.

Rebound: People may drive more miles in more-efficient light vehicles because their fuel cost per mile drops. Although their decision to do so indicates that they value the increased mobility more than the cost of the fuel consumed, they will use more fuel, and we’re calculating oil use, not economic welfare. Older estimates of ~10%

rebound, or even up to 30% long-term, now appear overstated, and are about halved by the latest econometric evidence.²¹⁷Variabilized insurance payment (p. 218) and the need to replace lost gasoline tax revenues by equivalent user fees (pp. 212–213) offset 73% of the ¢/mile reduction from 2025 State of the Art ’s 69% fuel savings. This reduces the long-run driving rebound to 3.3%. Intelligent Highway Systems (p. 78) then save 1.8% of light-vehicle fuel, leav-ing a 1.5% net rebound.²¹⁸We’re comfortable neglecting that because of a larger unanalyzed issue with EIA’s Reference Case: it assumes each driver travels 36% more miles in 2025 than in 2000, yet that extra driving time, exacerbated by congestion, will collide with other priorities in people’s already-saturated time budgets—

and with their 64% higher per-capita disposable incomes, they’ll value time even more highly than they do today.²¹⁹

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217. Small & Van Dender 2004. The authors’ findings, used here by kind permission, should not be ascribed to their research sponsors (nor should our findings). Their calculated long-run elasticity should decline further with increasing income. Even from an economic wel-fare perspective, net rebound effects are small enough to have been neglected by NAS/NRC 2001a, p. 89.

218. Details are in Technical Annex, Ch. 4. We count Intelligent Highway Systems here rather than in the supply curve of oil-saving potential because its cost is hard to determine (note 380, p. 78).

219. See next page.

This Report Box 5: Conventions (continued)

Interaction between efficiency improvements:

Successive energy savings don’t add; they multi-ply. That’s because each leaves less energy use to be saved by the next. We count this effect fully. Some savings incur additional costs or, more often, synergistic benefits: e.g., better aerodynamics or tires can reduce the weight and size of a vehicle’s engine. We count such effects carefully for light vehicles, by relying on an archetypical design specifically optimized for that purpose, and partially (tending to understate oil savings) for heavy trucks and for aircraft.

Turnover of capital stocks: The following analy-sis first presents the technical potential as if all the efficiency improvements and supply substitutions shown were (by magic) fully adopt-ed by 2025. This helps readers to understand the size of the “efficiency resource” independent of how quickly it can actually be captured. Later, on pp. 178–212, we contrast actual adoption trajectories if we passively wait for capital stocks to turn over normally with those achiev-able under innovative policies that accelerate turnover. Thus turnover rates aren’t fixed; they’re a policy variable. See Technical Annex, Ch. 21, for a fuller discussion of stock turnover and of related issues about the degree of adoption.

The simulated effects of our proposed policies to accelerate adoption of advanced technology vehicles are summarized graphically on pp.

180–181.

219. Like EIA, we have not explicitly analyzed rebound for trucks or aircraft, both because they’re much smaller oil-users and because of the lack of literature. However, trucking demand tends to be driven by industrial production, which doesn’t go up just because trucks become more efficient. Airlines can rarely pass through higher fuel costs today, but if competition did allow them to pass through future fuel savings, that might increase flying somewhat. Meanwhile, howev-er, there will be increased competition from efficient high-speed rail, videoconferencing, etc.; and in our view, travel hassle is likely to con-strain the already-high EIA forecasts of air travel from rising further.