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9.6.3. Traffic Demand
Total traffic demand projected for the year 2050 for three of the long-range scenarios is shown in Figure 9-26. The values shown for the FESG model projection do not include military or general aviation traffic. Military and general aviation fuel burned and emissions were estimated separately for the year 2050; they were 3.1 and 1.8% of total fuel burned, respectively (Fa1,2). The demand values shown for the EDF model include military as well as freight demand, with projected billion tonne-km values converted to RPK. The DTI model includes passenger, freight, and business jet traffic but excludes military operations. The WWF model includes passenger and freight only, but a demand value for 2041 was not published.
Although the FESG and EDF models use the same IS92 economic scenarios (IS92 population scenarios also are inputs to the EDF model), the traffic demand projections for 2050 from the EDF model are higher than those of the FESG model by a factor of 1.2 to almost 4, depending on the scenario. The DTI model, which does not directly depend on the IS92 scenarios, projects a traffic demand about 80% that of the FESG high case (Fe1,2). Clues to the reasons behind the large differences in projected traffic demand between the FESG and EDF models can be found by examining the details of the results of each model. The EDF model projects passenger business and personal traffic in five world regions, plus military and freight traffic. To make comparisons between the two models, the 45 traffic demand flows (allocated from the global growth projection) in the FESG model were assigned to the five regions used in the EDF model. Demand flows between two of the EDF-defined regions were allocated by assigning 50% of the FESG traffic demand to each region.
On the previous page, Figure 9-27 shows a comparison of traffic demand in 1990 and 2050 from the FESG and EDF models, with demand sorted by region and/or type. The EDF base case demand (Eab) is compared with the Fa1,2 demand scenario. Large differences in the distribution of demand between the two models are apparent: The FESG model assigns the largest share of passenger traffic in 2050 to the OECD area, whereas the EDF model assigns the largest share to the China-Africa area (with personal travel making up the bulk of the demand).
Table 9-22 provides data on passenger demand from the EDF and FESG models by region in 1990 and 2050 and regional distribution of world GNP and population over the same time periods. The basis of both models in this comparison is the IS92a GNP and population scenario. In 1990, the demand distributions of both models are roughly the same and reflect to a great extent the regional distribution of GNP. In 2050, the regional demand distribution from the FESG model reflects the shift in GNP distribution, demonstrating the economics-driven basis of the FESG model. The 2050 FESG values also show that the market share tool has probably underestimated the share of demand in region 4; percentage of GNP has increased from 1990 to 2050, but percentage of demand has decreased.
In contrast, the 2050 demand distribution from the EDF model differs greatly from the distribution of GNP in 2050 and reflects the population-driven basis of much of the EDF model.
The differences between the FESG and EDF models are further illustrated in Figures 9-28 and 9-29, which show the cumulative distribution of traffic growth over time for the IS92a scenario. Figure 9-28 shows the growth and regional proportions of traffic demand as projected by the FESG model. The shares of demand reflect the GDP of each region. Figure 9-29 shows the cumulative distribution of demand for the five regions as projected by the EDF model. The EDF model, unlike the FESG model, projects
business and personal passenger demand separately (business demand is a function of GNP; personal demand is a function of population); both sectors of demand are shown in the figure. Notable is the lack of projected growth in personal demand in region 1 (OECD less Japan). Driven by projected slow growth and eventual decline in OECD population, demand growth in this sector is projected to be less than 1% per year after 2005 and negative after 2035. Notable also is the relative lack of growth projected for region 2 (Asian newly industrialized countries + Japan). The effect of the population-driven personal demand sector is shown by the rapid growth in regions 3 (China + rest of Asia) and 4 (Africa, Latin America, Middle East). Personal demand in these two regions is projected by the EDF model to grow at rates exceeding 12% per year for 25 years (region 3) and 10% per year for 20 years (region 4) to create 75% of total passenger demand in 2050 (up from 19% in 1990). This value contrasts with the 21% of total passenger demand projected for these two regions in the FESG model, based on the two regions' 33% share of GNP.
A list of NOx emissions index projections is given in Table 9-23 for the three long-term models (IS92a scenarios).
The fleet EI(NOx) in 1992 was calculated as 12.0 (NASA), 13.8 (ANCAT/EC2), and 13.9 (DLR).
Expectations for the development of NOx technology are quite different among the models. The two FESG model NOx technology estimates were based on ICCAIA technology projections for new aircraft (Sutkus, 1997) and estimates of how quickly such new technology would enter the fleet (Greene and Meisenheimer, 997). The assumptions in the DTI model were that regulatory pressures would require reductions in NOx emissions, and the fleet emissions index would be forced down as the engine industry responded with specific technology developments through 2035. These developments assumed the introduction of emission control technology that would produce engine emissions indices appropriate to those anticipated for staged combustor and ultra-low NOx combustor technology-the latter of the type being developed for HSCT applications [EI(NOx) =5]. Ultra-low NOx technology concepts now being developed may not be suitable for future high pressure ratio subsonic engine designs, so achieving fleet NOx emission levels assumed in the DTI and EDF models may be very difficult (see Section 7.5).
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