EDF has produced projections of total traffic demand, fuel use, and emissions through 2100 (Vedantham and Oppenheimer, 1994, 1998). The EDF projections use a logistic model to simulate the stages of demand growth in aviation markets, focusing particularly on demand growth in developing countries (where aviation has only recently become a commonplace travel mode). Two sets of aviation demand scenarios-base-level and high-level-describe traffic under each of the six IPCC 1992 scenarios (IS92a through IS92f) for global expectations of gross national product (GNP), population, and emissions (Leggett et al., 1992). Data produced are regional and global totals.
The model logic incorporates the assumption (based on observation) that latent demand in a region previously not served by airlines will result in an initial period of rapid growth; once an airport network is in place, business and personal habits will incorporate the new transport option, causing a period of continuing strong growth rates. Barring unforeseen developments, the experience of some OECD nations suggests that aviation demand will eventually reach maturity, and relative growth rates will slow as the market approaches saturation. Continued growth of GNP and population imply continuing, albeit slow, growth in demand, even over the very long term.
Figure 9-20: EDF global aviation demand
EDF uses a logistic model with a time-varying capacity to model the dynamics in several sectors of rapid expansion, continued growth, and eventual slowdown in growth rates without imposing a zero growth-rate ceiling. Growth rates and market capacities for different regions of the world were chosen after a review of economic and aviation market history in industrial nations. The demand model is consistent with the history of the U.S. domestic market.The EDF model sorts the nations of the world into five economic groups (see Table 9-18). For each of the five economic groups, the three sectors of civil business passenger, civil personal passenger, and civil freight are modeled as logistics with time-varying market capacities. The civil business passenger and civil freight sectors experience logistic expansion toward a time-varying capacity level that is proportional to the nation's GNP.
The model assumes that expansion in business travel is accompanied by expansion in personal travel, which includes tourism and leisure visits.Personal travel by air has high income elasticity, and aviation demand will increase rapidly when a poor nation experiences an economic boom and per capita income increases. Depending on the income distribution, there can be significant demand for aviation even in countries with very low per capita incomes (Atkinson, 1975). As incomes rise and seat prices (as well as cargo costs) fall, growth in aviation demand will result from the penetration of aviation services into lower income brackets (Boeing, 1993). The civil personal passenger sector experiences logistic expansion toward a time-varying capacity level proportional to the nation's population (the model does not account for possible feedback relationships between GNP and population). The military and general aviation sectors do not experience logistic expansion; both sectors grow nominally, at the same rate as global GNP. The mathematical basis of the model and further details on the assumptions are given by Vedantham and Oppenheimer (1994, 1998).
The base-demand and high-demand sets include expected start date for market expansion, market capacity levels, and maturity period length. These assumptions for the two demand sets reflect implicit assumptions about diverse social factors, including travel trends in developing countries (Gould, 1996), penetration of future telecommunications technologies, and development of competing modes of transportation. Assumptions on start dates of aviation market expansion for rapidly developing economies, slowly developing economies, and post-Communist economies reflect EDF's own assessment of near-term economic expectations and were not made in relation to IPCC scenarios. Prior to the start date, demand is assumed to grow nominally, at the same rate as global GNP. The base-demand and high-demand sets include assumptions on market capacity levels based on multiples of 2 (base-demand) and 3 (high-demand) relative to the 1990 demand levels for Economic Group 1 (OECD less Japan), because these markets are closest to maturity today.
EDF's analysis of the history of the U.S. domestic market concluded that there was approximately a 70-year period from start of market expansion to maturity. The model assumes that nations that are building their airport infrastructure today may well attain market maturity faster because they will benefit from technological improvements and some fraction of their populace will be more familiar with lifestyle and business habits that incorporate aviation. Another region-specific assumption was that markets in the post-Communist economies may mature faster because they have undergone industrialization.
Table 9-19: Excerpt of EDF results-demand, fuel use, CO2, % of global CO2, and NOx.
|IS92a Base (Eab)||Demand (109 RPK)||2,171||3,629||6,115||9,339||23,256|
|Fuel Use (Tg)||179||258||374||544||1,143|
|CO2 (Tg C)||154||222||322||468||983|
|Percentage of Global CO2||2.1%||2.6%||3.8%||6.8%|
|IS92a High (Eah)||Demand (109 RPK)||2,171||5,801||9,954||18,332||41,392|
|Fuel Use (Tg)||179||395||610||1,123||2,086|
|CO2 (Tg C)||154||340||525||966||1794|
|Percentage of Global CO2||2.1%||4.1%||7.9%||12.4%|
|IS92c Base (Ecb)||Demand (109 RPK)||2,171||3,447||5,337||7,802||16,762|
|Fuel Use (Tg)||179||243||325||455||837|
|CO2 (Tg C)||154||209||280||391||720|
|Percentage of Global CO2||2.1%||2.8%||4.5%||9.6%|
|IS92d High (Edh)||Demand (109 RPK)||2,171||5,729||9,647||17,619||33,655|
|Fuel Use (Tg)||179||390||592||1,082||1,689|
|CO2 (Tg C)||154||336||510||932||1,453|
|Percentage of Global CO2||2.1%||4.5%||10.0%||16.2%|
|IS92e High (Eeh)||Demand (109 RPK)||2,171||5,964||10,850||20,202||46,362|
|Fuel Use (Tg)||179||408||668||1,234||2,297|
|CO2 (Tg C)||154||351||574||1,061||1,975|
|Percentage of Global CO2||2.1%||3.9%||7.0%||9.8%|
The six IPCC scenarios for GNP and population, combined with the two demand sets described above, provide a total of 10 demand projections (because the IS92a and IS92b scenarios share the same GNP and population expectations). Figure 9-20 shows five of the global demand scenarios; sharp upswings when different regions start expansion are clearly visible. Annotations attached to the curves are shorthand nomenclatures for the scenarios used in this report.
Figure 9-21: EDF CO2 emissions projections.
Figure 9-22: EDF NOx emissions projections.
Under the IS92a scenario (the IPCC base case), the base-demand level in 2050 is higher than the 1990 level by a factor of 10.7 and has an average annual demand growth rate of 4.03% over the 60-year forecast period (forecasts to 2100 are given by Vedantham and Oppenheimer, 1998). For the base-demand set, the range of traffic demand expected for different population and GNP estimates spans a factor of almost 5 in 2050; the full range across all 10 scenarios spans a factor of more than 20. Assumptions about rates of expansion and maturity have a sizable impact: The high-demand projection for the IS92a scenario in 2050 is 78% higher than the base-demand value.
The 10 demand scenarios produced by the EDF model are synthesized with expectations for fuel efficiency improvement and changes in emissions indices to produce fuel use, CO2 emissions, and NOx emissions scenarios.
Although fuel efficiency has increased steadily over the past few decades, improvements in fuel efficiency are becoming less dramatic over time. The technology projections of the EDF model use a constant-capacity logistic that extrapolates Greene's (1992) forecast for a base-case annual increase of 1.3% in fleet-wide fuel efficiency from 1989 to 2010. Significant differences in fuel efficiency exist today across regions, and there may be a tendency toward higher fuel efficiency in wealth ier regions. The EDF model assumes differences in fuel efficiency across economic groups and builds projections on the assumption that the technology gap between wealthier and poorer nations will close over time.
The NOx emissions scenarios reflect changes in EI(NOx) based on a constant-capacity logistic that extrapolates a best-fit approximation to the 1993 NASA numbers for EI(NOx) in 1990 and 2015 (Stolarski and Wesoky, 1993). The model does not reflect specific technology choices for fuel efficiency or changes in EI(NOx), although the fleet EI(NOx) of 6.9 that results from the extrapolation is in the ultra-low technology regime. Results for all scenarios are summarized in Table 9-19.
Figure 9-21 shows CO2 emissions scenarios [which assume a constant EICO2) of 3.16]. Under the base IS92a scenario, CO2 emissions grow at an annual rate of 3.2% to reach 983 Tg C in 2050-an increase of a factor of 6.6. For all scenarios, projected CO2 emissions climb rapidly after 2015. For the IS92c scenario (which reflects low population and GNP growth) under both demand sets, the level of CO2 emissions in 2100 is lower than that in 2050, reflecting a successful catch-up effect whereby technological improvements have compensated for demand growth (Vedantham and Oppenheimer, 1998). Comparing the EDF scenarios for aviation's CO2 emissions projections with the IPCC scenarios for total anthropogenic CO2 emissions (including emissions from energy consumption and deforestation) provides a benchmark measure of the environmental importance of the aviation sector. For the base-demand IS92a scenario, aviation's share of global CO2 emissions rises from its current value of 2.1% to a level of 3.8% in 2025 and 6.8% in 2050. Across all scenarios, aviation's share of global CO2 emissions ranges between 3.3 and 10% in 2025 and between 5.6 and 17.6% in 2050. These scenarios imply that aviation may become a significant contributor to global CO2 emissions.
Figure 9-22 shows the NOx emissions scenarios; these scenarios incorporate the effects of fuel efficiency improvements as well as changes in EI(NOx). For the base-demand IS92a scenario, NOx emissions rise sharply from almost 2 Tg (as NO2) in 1990 to 7.9 Tg in 2050. Because total NOx emissions are reduced as a result of fuel efficiency improvements and EI(NOx) reduction, technological improvement can compensate for a greater fraction of demand growth than in the case of CO2 emissions.
Table 9-19 presents an excerpt of EDF model results of traffic demand, fuel burned, and emissions of CO2 and NOx through the year 2050 for the several sets of assumptions. The three-letter designators for the EDF scenarios (e.g., Eab, Eeh) are used throughout this report.
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