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Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions (2010)

Chapter: Chapter 1 - Defining the Issues: Defining the Problem

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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
×
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
×
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
×
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
×
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
×
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
×
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
×
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
×
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
×
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
×
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
×
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
×
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Suggested Citation:"Chapter 1 - Defining the Issues: Defining the Problem." National Academies of Sciences, Engineering, and Medicine. 2010. Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions. Washington, DC: The National Academies Press. doi: 10.17226/14363.
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19 1.1 Introduction This chapter presents an overview and introduction to the four major themes developed in the project. It introduces the two study areas in terms of their geography, demographics, and propensity to make shorter distance air trips within and between their mega-regions. It reveals a significant difference in the nature of the demand/capacity/delay characteristics between the East and West Coast study areas. The chapter describes what the researchers believe to be a present crisis in aviation systems capacity and provides a method of under- standing the economic scale of that crisis. The chapter also documents the economic and environmental cost of doing nothing—letting the present system in the mega-regions con- tinue to degenerate (see highlights of Chapter 1 in Exhibit 1.0). Chapter 1 is organized in the following order: • Section 1.1 summarizes the structure and main themes of the chapter. • Section 1.2 presents a set of definitions concerning the geographic scale of the two study areas covered in this research and the size of the airports that serve them. • Section 1.3 summarizes the airport congestion issue in the two mega-regions from a systems point of view and a cus- tomer point of view. The amount of congestion experi- enced is documented for a cross section of large and smaller airports in the two study areas, and the overall problem revealed on the East Coast is compared with that on the West Coast. • Section 1.4 identifies the nature of the capacity problem that has been revealed over the past several years, culmi- nating in the “perfect storm” of the summer of 2007, as described by the research team and the Federal Aviation Administration (FAA). It presents the results of an early outreach effort to define the nature of the present capacity problem in the mega-regions. • Section 1.5 summarizes the perceived 2007 costs to airport travelers from congestion and airport delays, including a C H A P T E R 1 Defining the Issues: Defining the Problem • There is a major problem in the provision of effective aviation capacity in the coastal mega-regions and the economic impacts of doing nothing are significant. • Using a range of economic assumptions, the “cost” of present air travel delay in the coastal mega-regions ranges from a low of about $3 billion per year to a high of over $9 billion per year (2007). • Using the same range of assumptions, the “cost” of air travel delay in the future would range from about $9 billion to about $20 billion, if none of the present capacity constraints were addressed—that is, the cost of doing nothing (2025). • Much of the aviation industry’s capacity forecasting assumes that, by one means or another, a process of up-gauging of air- craft will occur: the research team found no support for the assumption that systematic up-gauging of aircraft will occur without some form of public policy intervention. • The number of air trips within the West Coast study area is vastly higher than the number of air trips within the East Coast study area, even though their geographic area is similar. • The present amount of air travel delay is vastly higher in the East Coast study area than in the West Coast study area, even though the intra-area volumes are much lower. Exhibit 1.0. Highlights and key themes included in Chapter 1.

procedure for assigning a “value of time” (VOT) to the delay experienced. • Section 1.6 concludes Chapter 1 with an analysis of the eco- nomic and environmental impact of doing nothing about the issues raised in this research. 1.1.1 Overview In the first half of this project, the research team exam- ined the issue of aviation planning to deal with the capacity issues raised for the year 2025 for key airports in congested mega-regions, where warning flags have already been raised in the FACT 2 report (1). What the team found was of major concern. In interviews4 with airport managers, managers of the fore- casting process, and other leaders in the field, it became clear that in almost every case,5 in one manner or another, the opti- mistic assumptions about the amount of capacity to be avail- able in 2025 were based on the intuitive belief that, as demand grows over time, this will be matched by a voluntary pro- gram of up-gauging of the size of aircraft flown to the subject airport—a matter currently almost entirely under the control of the airlines, not the airport managers. For example, the team had a productive interview at one of the most important airports in the study area, generally covering issues of airport productivity. At the end of the inter- view, one of the hosts pointed out an entire wall of architec- tural designs for additional new passenger terminals at the airport, commenting, “Up-gauging? Everything on this wall is based on the assumption of up-gauging! Without that, we will not need any more terminal capacity. They can’t get through the runways!” The best and most analytic approach to the subject comes in the development by the MITRE group of an aircraft assign- ment submodel as part of their comprehensive multistep process of assigning aviation trips in the 2025 forecasts. Logically, it could be argued that even this state-of-the-art method is premised on the concept that airlines will, for one motivation or another, choose to place a given number of pas- sengers on a smaller number of aircraft. The model assumes such actions on the part of the major players in its 2025 allo- cation of aircraft to segments within markets. In short, when examining the possible breakdown of the aviation system in 2025, the research team essentially docu- mented that the breakdown at key mega-region airports was already present in the base year of 2007. In case after case, air- line managers were scheduling more small planes than could reasonably operate on time under any weather conditions of less than perfect visibility. The interviews with airport man- agers on the West Coast reported the same concern as those on the East Coast. In the interpretation the research team presented in 2008, the team concluded that no one had the authority for getting effective capacity out of the runways and supporting facilities in major mega-region airports. The airport managers believe they have not been given an effective legal mandate to lower congestion. In some cases, efforts ended up in court. And a given airline scheduling manager—perhaps convinced of the social virtue of flying fewer, larger planes—is forced to act under the assumption that her/his competitors will simply take the released slots and use them to perpetuate the use of smaller aircraft. In short, no single entity is accountable for a problem with economic impacts calculated in the billions of dol- lars per year, as discussed in Section 1.5. Without a solution to this problem, the research team would have to conclude the 2025 capacity predictions included in the FACT 2 report to be optimistic, as documented in Section 1.6. It is important to reiterate that the FACT 2 report (1) con- cluded that there would be considerable capacity problems in the coastal mega-regions, even assuming the success of the current national Next Generation Air Transportation (NextGen). This initiative centers on technologies and pro- cedures that will boost airspace and airport capacity. A num- ber of airports are also planning airfield improvements that will increase capacity. However, the boosts in capacity from such actions will not adequately meet all future demand at all airports in the National Airspace System (NAS). According to the FACT 2 report, many of the most congested airports in the coastal mega-regions will continue to need additional capacity to meet demand even with the capacity benefits of NextGen. Therefore, the innovations presented in this study, such as demand management, are vital, irrespective of the capacity gains promised by NextGen or airfield improve- ments. The reader is referred to Chapter 5, which focuses on capacity management rather than expansion. For a discussion about how NextGen issues might impact the individual air- ports, see Appendix B. 1.1.2 Four Conclusions of This Research This report is structured around the presentation of the four main conclusions of the project. They are presented in the following order: 1. Under the present relationship between the airports and the airlines, there is a serious lack of usable aviation capacity in the mega-regions. Chapter 1 builds the case that there is a growing problem in the mega-regions, and that the eco- 20 4 The airport activity summary sheets are presented in Appendix C. 5 An exception to this sentence might be the process described in Chapter 5, where innovative work undertaken by Massport in cooperation with the FAA is specifically dealing with the issue of need for up-gauging of aircraft.

nomic and environmental cost of doing nothing is signifi- cant. The chapter concludes that a new approach is needed. 2. To gain access to alternative forms of short-distance trip- making capacity, the aviation capacity planning system could benefit from becoming more multimodal. Chapter 2 reviews the extent to which aviation planning is inherently intertwined with the planning and analysis of capacity increases in other longer distance modes, specifically high- speed rail (HSR) and highway planning. 3. To gain better utilization of existing underused capacity at smaller airports in the region, the aviation capacity planning system could benefit from becoming more multijurisdic- tional. Chapter 3 analyzes the market potential of some smaller scale regional airports to provide additional capac- ity to the systems in the mega-regions, provided that the operating carriers decided to take advantage of their pres- ence. The chapter examines the importance of gathering and analyzing data on a multi-airport, super-regional basis, and shows examples of how such new regional aviation planning tools could be used. 4. No one has the authority and accountability for the manage- ment of congestion at mega-region airports. Chapter 5 sug- gests that capacity in the mega-regions will be significantly increased only when the managers are empowered to solve the problem. The chapter concludes that the management of existing resources could be improved, and that this rep- resents the single most important element in a larger strat- egy to deal with potential aviation capacity issues in the coastal mega-regions. 1.2 Understanding the Scale of the Mega-regions and Their Airports 1.2.1 Range of Scale of the Study Area Airports Table 1.1 illustrates that the two coastal study areas contain some of the biggest airports in the United States, including Los Angeles (LAX) and New York (JFK). The two study areas also contain airports of concern and interest to multimodal planning that are currently very small and possibly under- utilized, such as Allentown, PA. The reader should be aware that the passenger summaries used in the Airports Council International–North America (ACI-NA) surveys (2) are com- prehensive and include more passengers than are included in the U.S. Department of Transportation’s (DOT) Airline Ori- gin and Destination Survey, from the Office of Airline Infor- mation of the Bureau of Transportation Statistics (DB1B) (3), which forms the backbone of most of the analysis contained in this report. The uses, and limitations, of various databases are discussed in Section 4.6 of this report. Table 1.1 also pro- vides the three-letter codes, as set by the International Air Transport Association (IATA), for most airports referred to in this report. The base year for this analysis is 2007, which was a critical year for aviation in the mega-regions (as dis- cussed in Section 1.4.3). The research team is aware that since that time, air passenger volumes have decreased by varying levels. This report, however, is based on a consistent use of one base-year assumption; most industry analysts believe that growth over the next 20-year planning period will indeed reappear at some point. 1.2.2 Geographic Scale of the Mega-regions The East Coast study area generally includes the states from New England to Virginia. The West Coast study area includes all of California and Clark County, NV. In Chapter 4 of this report, flows are examined on a finer geographic scale, which emphasizes actual market areas. In general, when data are pre- sented at a high level of aggregation, entire states are included; when data are presented on an airport-by-airport basis, only the catchment areas of those specific airports are included. Thus, the term East Coast study area includes all of the geography contained in the states between Maine and Virginia. The term Eastern Mega-region refers to the areas covered by the Boston region airports to the north and to the areas of Richmond and Norfolk, VA, to the south. The western edge of the Eastern Mega-region incorporates Syracuse, NY, and Harrisburg, PA. The term West Coast study area includes all of the state of California and Clark County (Las Vegas) NV. The term North- ern California Mega-region refers to the Bay Area region and the Sacramento region. The term Southern California Mega- region refers to the Los Angeles Basin area, the San Diego region, and Clark County (NV) together. Distances. The two maps (Figures 1.1 and 1.2) are pre- sented at similar scale: in the East Coast study area, the north- ernmost mega-region airport, MHT (Manchester, NH), is about 487 miles from the farthest airport, RIC (Richmond, VA). In the West Coast study area, the distance from the Sacramento airport to the San Diego airport is 480 airline miles. Population. In terms of population, the two study areas are not so similar. The East Coast study area has about 69 mil- lion inhabitants; the West Coast study area has about 38 mil- lion. This difference will become far more dramatic later in this chapter, where the numbers of internal aviation trips within each study area are compared. The results are startling and point to real differences in the transportation behavior of the two coastal regions. 21

22 Rank in ACI-NA Survey Airport Name and Code Total Passengers 2007 3 LOS ANGELES (LAX) 61,896,075 6 NEW YORK (JFK) 47,716,941 7 LAS VEGAS (LAS) 46,961,011 11 NEWARK (EWR) 36,367,240 13 SAN FRANCISCO (SFO) 35,792,707 17 PHILADELPHIA (PHL) 32,211,439 20 BOSTON (BOS) 28,102,455 21 NEW YORK (LGA) 25,026,267 22 WASHINGTON DULLES (IAD) 24,525,487 25 BALTIMORE/WASHINGTON (BWI) 21,498,091 28 WASHINGTON REAGAN (DCA) 18,670,924 29 SAN DIEGO (SAN) 18,336,761 33 OAKLAND (OAK) 14,846,832 40 SACRAMENTO (SMF) 10,748,982 41 SAN JOSE (SJC) 10,658,389 43 SANTA ANA (SNA) 9,979,699 55 ONTARIO (ONT) 7,207,150 58 HARTFORD/SPRINGFIELD (BDL) 6,519,181 61 BURBANK (BUR) 5,921,336 68 MANCHESTER (MHT) 3,892,630 71 NORFOLK (ORF) 3,718,399 72 RICHMOND (RIC) 3,634,544 80 ALBANY (ALB) 2,874,277 82 LONG BEACH (LGB) 2,758,362 83 SYRACUSE (SYR) 2,360,878 121 ALLENTOWN (ABE) 847,526 180 PALMDALE (PMD) 12,022 Table 1.1. Airport codes and passenger activity summary from ACI-NA 2007 survey (2). Figures 1.1. and 1.2. The geographic extent of the East Coast study area and the West Coast study area (scale is constant) (3).

1.3 Scale of Air Travel within the Two Study Areas This section deals with the city-pair volumes of existing air travel, which are perhaps better described as “metro-region pair” passenger volumes between “families of airports.” Clas- sic origin–destination (OD) “desire lines” are presented for the East Coast study area and the West Coast study area, making possible a revealing comparison of the aviation passenger volumes between the two coastal areas. 1.3.1 Metro-area to Metro-area Pair Air Passenger Flows within the Eastern Mega-region Figure 1.3 summarizes air passenger travel within the East Coast study area between January and December 2007. It can be best understood as a desire line diagram showing the flows between airports of origin to the airports of destination of somewhat under 10 million air trips. Trip makers between, say, Manchester, NH (MHT) and Richmond, VA (RIC) may under- take this trip by transferring at a point such as Newark (EWR), LaGuardia (LGA), or Philadelphia (PHL). From the vantage point of OD analysis, they are portrayed here as flows between the Boston region family of airports and the Richmond/Norfolk family of airports. These East Coast aviation flows are examined on an airport-by-airport basis in Chapter 4 of this report. 1.3.2 Metro-area to Metro-area Pair Air Passenger Flows within the West Coast Study Area Figure 1.4 summarizes air passenger travel within the West Coast study area between January and December 2007. It can be best understood as a desire line diagram showing the flows between airports of origin to the airports of destination of about 20 million air trips. As in Figure 1.3, flows are expressed from their airport of origin to their airport of destination without reference to possible use of transfers or connections. These lines represent the flow of airport passengers between the large metropolitan areas and other large metropolitan areas. These West Coast aviation flows are examined on an airport-by-airport basis in Chapter 4 of this report. 23 Note: The absence of a line between two areas means that the number of air trips is insignificant. Figure 1.3. Air passenger flows between metro regions in 2007: East Coast (4). Note: The absence of a line between two areas means that the number of air trips is insignificant. Figure 1.4. Air passenger flows between metro regions in 2007: West Coast (4).

1.3.3 Implications of Scale between the Two Study Areas The first observation about the two study areas is that the West Coast generates about twice the volume of short dis- tance air passengers than does the East Coast. And within the West Coast study area, it is the air trips between the Bay Area family of airports to the north and the Los Angeles Basin fam- ily of airports to the south that dominate the travel. The Los Angeles region, served by LAX, Burbank, John Wayne, Long Beach, and Ontario together, generates some 8 million trips to or from the Bay Area region, which is served by the airports of San Francisco (SFO), Oakland (OAK), and San Jose (SJO). In terms of coast-versus-coast comparison, the volume of air travelers between the Los Angeles region and the Bay Area region is 5.3 times the air traveler volume between the New York region family of airports and the Washington/Baltimore family of airports. It is 4.7 times the volume between the Boston region family of airports and the New York region family of airports. It is also clear that air travelers on the West Coast have a short-distance trip generation rate that is more than three times that of air travelers on the East Coast. Chap- ter 2 will discuss in some detail the extent to which this dif- ference in reliance on air travel can be traced back to a massively higher dependence on rail in the East Coast study area, particularly in and out of the New York region. 1.4 The Problem of Airport Congestion in the Mega-regions The research team has estimated that the phenomenon of aviation congestion associated with 11 of the largest airports in the two coastal study areas resulted in passenger-perceived delays calculated in the billions of dollars in 2007, as docu- mented in Section 1.5. 1.4.1 Comparing Congestion Delay between East and West Coast Mega-regions Importantly for the interpretations needed in this research, those delays were not evenly divided between the two coasts. Figure 1.5 shows the sharp differences in the delay patterns of the two coast study areas. The “Total Delay Index” (Figure 1.5 and Table 1.2) has been calculated by the research team as the average frequency of delay multiplied by the average duration of delay, plus the average frequency of cancellation multiplied by a value of 3 hours delay per cancellation. It is expressed as number of minutes of delay per total airport passenger. The index was calculated from Bureau of Transportation Statis- tics (BTS) Transtats data (5), for the 12 months between Jan- uary and December 2007. The difference in the severity of the problem between coasts is somewhat surprising, given the widespread belief that delays are ubiquitously distributed around the country. But, it is clear that what SFO experienced in 2007 is quantita- tively similar to the delay experienced at MHT and Providence, RI (PVD), which are regarded as East Coast airports with excess capacity and minimal delays. The economic impact of the aviation delays at the larger airports is presented in Section 1.5 for 2007 and Section 1.6 for 2025. 1.4.2 Where Is the Lack of Capacity? From a nationwide perspective, there is no lack of airport capacity at which to provide hubbing operations. But inter- connecting hub airport congestion is not the dominant factor in many of the project study areas where the most serious con- gestion occurs at the OD airports. In those cases where hub- bing activity occurs, as at EWR or Washington Dulles (IAD), the hubbing carriers have options to shift connecting traffic to 24 East Coast Airports West Coast Airports M in ut es p er p as se ng er tr ip Figure 1.5. Total delay index for East Coast and West Coast airports, expressed as minutes per passenger trip (5).

other hub airports in their systems. The ability to shift connect- ing traffic to other airports makes congestion at connecting hubs more of an individual airline problem than a broad pub- lic policy issue. In recent years, airlines have closed fully func- tional hubs at St. Louis and Pittsburgh, following the earlier abandonment of hubbing operations at places such as Kansas City and Raleigh-Durham. In the current round of airline mergers, connecting hubs such as Cincinnati and Memphis are now experiencing significant reductions in activity. The coun- try has plenty of hub capacity available, in the event that carri- ers hubbing in the mega-regions choose to shift connecting traffic away from those areas in favor of accommodating addi- tional OD traffic. The research question then turns to whether decreasing domestic feeder services at coastal airports would or would not damage their support of important longer distance services. Chapter 4 of this report presents an analysis of the role of longer distance flights needing to be fed by shorter distance flights, presented on an airport-by-airport basis. Having made large investments in airport capacity, opera- tors of airports in Kansas City, Raleigh-Durham, St. Louis, and, more recently, Pittsburgh had no effective control over airline decisions to abandon those airports as connecting hubs in their systems, thereby negating the substantial invest- ments in capacity at those locations. In the summer of 2000, SFO suffered significant delays due in large measure to the decision by an airline to substantially increase the SFO–LAX market with high-frequency shuttle flights. In the summer of 2001, LGA airport was brought to a standstill by airlines’ scheduling increases permitted by mandated relaxation of pre-existing slot controls under the high-density rule. 1.4.3 Capacity Issue Reaches a Crisis: The Summer of 2007 Many of the factors associated with excessive demands on aviation came together in the summer of 2007, in what might be seen as a “perfect storm” of capacity failure. The decision by one airline to build a major domestic hub at JFK was fol- lowed by a competitive response by other major airlines at JFK. Those combined airline decisions turned that airport from a major international gateway with congestion during limited hours of international activity to the most congested airport in the United States, requiring federal intervention in the form of flight limitations. In general, major study area air- ports have 30–50% of their runway capacity devoted to oper- ations in small regional jet or turboprop aircraft in response to airlines’ scheduling decisions over which the airport oper- ators have no control. The events of the summer of 2007 were summed up by the FAA, in the Federal Register of January 17, 2008, as follows: Market competition spurred by new-entrant, low-cost carri- ers and the competitive response by legacy airlines have gen- erated much of the increase in air travel demand. Among the trends are new and expanded route networks to lesser-served markets connecting major hubs with regional jet service. The additional service in some cases provides no net increase in seats between origins and destinations but provides more operations in the system with greater numbers of smaller capacity aircraft. The experience of summer 2007 shows that congestion is a problem today. Airlines at New York JFK International Airport increased their scheduled operations by 41 percent between March 2006 and August 2007. As a result, the number of arrival delays exceeding one hour increased by 114 percent in the first ten months of fiscal year 2007, compared to the same period the pre- vious year. During June and July 2007, on-time arrival perfor- mance at JFK was only 59 percent. Moreover, delays resulting from operations at New York metropolitan area airports alone can account for up to one-third of the delays throughout the entire national system. The congestion in the New York airspace has ripple effects across the national airspace system, causing flight delays, cancellations, and/or missed connections. These delays impose economic and social costs on airline passengers and ship- pers; airlines incur extra costs for fuel, flight crews, and schedulers. Delays are likewise beginning to increase at San Francisco (6). 25 Total Delay Index for East and West Coast Airports, 2007 Airport Delay Index Airport Delay Index Newark 32.6 SFO 18.7 LaGuardia 29.5 LAX 13.3 JFK 27.7 LAS 13.2 Philadelphia 23.5 Burbank 12.3 Dulles 23.0 John Wayne 12.0 Boston 22.3 San Diego 11.7 Reagan National 20.1 Long Beach 11.3 Providence 19.3 OAK 10.9 Manchester 18.2 Ontario 10.5 Bradley 17.3 San Jose 10.4 BWI 14.5 Table 1.2. Total delay index (5).

1.4.4 Defining the Problem: Looking for Solutions To examine the problem of capacity and demand manage- ment6 and implications of reducing congestion at airports, members of the research team organized a session in January 2008 at the 87th Annual Meeting of the Transportation Research Board (TRB) to discuss capacity issues at the New York airport system and airport capacity issues nationwide. This session received input from an airport operator, an air- line representative, a manager with a federal perspective, an aviation research academic, and aviation consultants. As the session unfolded, it was clear that different experts and stake- holders approach the subject of capacity and demand man- agement in a different way. Such a finding illuminated the complexity of the multiple interpretations of the problem. Discussions about capacity and congestion focused on issues regarding the number of operations per hour at congested air- ports. Multiple—not necessarily mutually exclusive—solutions were presented and debated such as operational caps, market- based mechanisms, technology enhancements, and multimodal solutions. Main themes involved (a) the balance between offering passenger service in terms of flight frequency and destinations in a congested region and reducing delays and unreliability that a congested airport or region can present and (b) who should be at the table to determine solutions to capacity and congestion problems. 1.4.4.1 The Balance Between Capacity Management and Passenger Service The balancing of passenger access times or schedule delay penalties with actual delay savings becomes a central theme for resolution. On the one hand, the passenger values high- frequency services. At the same time, that passenger may be totally unaware that the lack of reliable services at the airport stems, in part, from the proliferation of high-frequency, low- capacity aircraft. Thus it becomes important to consider both capacity management and passenger service when developing solutions. This is noted in the debate over operational caps, on up-gauging, as well as in a discussion of multimodal solutions to reduce redundancy in flights. Consistent with the themes developed in this early outreach section, Chapter 5 elaborates on these themes, leading to suggestions in Chapter 6. At the TRB session, it was noted that restricting the num- ber of operations per hour, or managing airport access to reduce congestion, gives an initial insight into the complex way stakeholders view passenger service and capacity man- agement. The airport managers and airlines spoke out against the idea of the federal government setting airport caps. Air- port management spoke as being responsible for the entry point of passengers to their city; the airlines were concerned about the government engineering their business plans. In the panel discussion, the airport operators noted their desire to “accommodate demand of folks who want to come to and leave our region.” It is for this reason then that the airport operators rejected the operational caps imposed, a sentiment the airline representative supported. There is an interesting balance between providing fre- quency and providing reliability. Excessive frequency leads to low reliability, and vice versa. At the session, the aviation research academic noted this delicate balance: to solve the problem we have to start looking at the demand side of the equation and find ways to reduce demand or to moderate demand into the busiest airports. . . . If you try to control demand in aviation that means the airlines have fewer flights into the busiest airports. This does not mean that passenger service has to be diminished, or that passengers have to take fewer trips. More directly challenging the employment of very high frequency at the expense of reliability, the aviation research academic followed up with a situation where “there are three airlines that provide hourly service between LaGuardia and Washington National airport.” In response to comments like these, the airline representative stated that “somebody’s demanding those services, whether it is because airlines offer superior service to (rail service) or it beats driving.” Further- more, not mentioned with this reasoning is that the airlines defend their market share by providing frequency; abandon- ment of service does not immediately lead to a reduction in flights, as a competing airline can enter into the schedule at any time. The impact of lowering overall volume on the num- ber of flights scheduled is examined in Chapter 2, which pres- ents a case study of the impact of a decline of air passengers between Boston and the New York airports. This discussion among multiple stakeholders shows how there is not a clear path to choose in balancing flexibility and reliability. The following section addresses the need to involve multiple stakeholders in developing a solution. 1.4.4.2 Multiple Stakeholder Solutions To sum up the challenges of providing and managing capacity and bringing all stakeholders to the table, the staff member from the FAA explained, “the administration does not have the luxury of one solution that will benefit one seg- ment of society. We must balance all concerns.” To find and agree on solutions to capacity, delay, and congestion issues, there are complex roles and responsibilities that must be deter- 26 6 As discussed in Chapter 5, the term “demand management” is used to describe strategies to limit delays that occur if too many aircraft are scheduled to arrive at an airport during a particular time. Under this use of the term, demand manage- ment is not meant to refer to any program designed to decrease the number of trips made.

mined. As he explained it, the administration was trying to take into account “a number of different perspectives but always with an eye to reducing disruption to the system.” These per- spectives span those of the panelists. The roles these multiple voices should play were discussed. The airport operator said that in finding a solution, “we can’t do it unilaterally. The airport operator should have a strong voice, and . . . complement the administration.” This is because “the airport operator is in the best position to know what is right and wrong for their airport.” The airline repre- sentative noted that a solution must “take into consideration the investment being made at the airports (by airlines). . . . Historic investments, historic operations, are something that we need to recognize.” An aviation consultant echoed that statement, adding, “there are clear distributional issues between the airports and the airlines.” 1.5 Costs to Travelers of Airport Congestion and Delays Airport congestion causes air passengers to incur addi- tional costs in several forms. Routine peak-period conges- tion increases the time between boarding and takeoff, and this additional time is built into airlines’ schedules for con- gested airports. According to a recent DOT report (7), the average taxi-out time (i.e., time between leaving the gate and takeoff) increased by almost 3 min per flight between 1995 and 2007 (21% increase), whereas taxi-in times increased by approximately 1.5 min (25% increase) over the same period. Although some of these changes could be the result of sev- eral factors, airport congestion is certainly among the most prominent causes. 1.5.1 Delay Times at the Mega-region Airports Six of the coastal mega-region airports are on the list of those with the 10 longest average 2007 taxi-out times—in order from longest: JFK, EWR, LGA, PHL, BOS, and IAD. JFK had over 37 min on average, IAD just under 20 min. These com- pare with the average across all airports of 13.8 min in 1995 and 16.7 min in 2007. The patterns are similar with taxi-in times, though the range is considerably smaller and only JFK, EWR, and LAX among the coastal mega-region airports are among the 10 longest. Although it is arguable as to the portion of these delays that is directly attributable to airport congestion, it is clear that they represent considerable costs to the airlines and, in turn, to the air passengers both directly (through extra time spent traveling) and indirectly (through higher fares charged for these flights to cover costs). See Figure 1.6. Regular increases in taxi-out and taxi-in times due to con- gestion can be accommodated by adjusting scheduled flight times, but at a cost to passengers of additional travel time and to the airlines of additional crew, equipment, and fuel costs. However, the larger cost of airport congestion is more likely attributable to the additional random delays beyond scheduled times. These are caused by a confluence of depar- ture schedules that create flight operations at or near maxi- mum airport capacity and any event that reduces capacity. The “unexpected” delays result in additional costs to passengers 27 Figure 1.6. The perceived cost of delay per trip to or from major mega-region airports in 2007(5). Mega-region Airports Pe rc ei ve d Co st o f D el ay (d oll ars )

and to the airlines. All of these costs can be quantified to some degree and, in fact, represent considerable costs in total. 1.5.1.1 Understanding the Role of Airport Congestion The U.S. DOT’s BTS compiles both on-time performance data and information about the causes of delays that result in late arrivals. For calendar year 2007, those data indicate that, nationally, weather delays directly caused only slightly more than 5% of the late arrivals while “air carrier delays,” “aircraft arriving late,” and “national aviation system delays” accounted for virtually all of the remaining 95% of delayed arrivals. Although airport and air traffic congestion are not listed explicitly as the ultimate sources of those three major types of delay, over the 5 years between 2003 and 2007, boardings at the 12 largest airports in the coastal mega-regions increased by 25% in total, departures increased by 18%, and the percent of on-time commercial flights declined by over 10 points. This indicates a strong association between airport traffic and flight delays. 1.5.1.2 Conclusions of the U. S. Senate Report According to a May 2008 report (8) from the U. S. Senate’s Joint Economic Committee Majority Staff (JEC), flight delays in 2007 imposed a cost of over $40 billion per year on passen- gers, the airlines, and the U.S. economy and resulted in a release of an additional 7.1 million metric tons of carbon dioxide (CO2). The report’s authors describe the impact of the “stag- gering levels of delays” as “large and far-reaching” and express concerns that the delays will worsen without “reforms to the system.” The study described in that report uses reasonable methods to derive its estimates but does not directly address three questions whose answers are important for this coastal mega-regions airport study: 1. What portion of this impact is incurred at the airports in the coastal mega-regions? 2. What are the full costs to coastal mega-region travelers of the delays? 3. How might these costs change in the future? 1.5.2 Costs of Delays at the Major Mega-region Airports The answer to the first of these questions is relatively straight- forward. The Senate JEC report (8) calculates the impacts of delays across the entire domestic air system, but also details delays at 60 of the largest airports, including all of the major mega-region airports. On the basis of these data, the pro rata share for the mega-regions of the $40.7 billion/year impact cited in the Senate JEC report is approximately $7.7 billion/year, of which $2.3 billion is due to passengers’ lost time, $3.6 is due to airlines’ increased cost, and the remaining $1.8 billion is due to economic spillover effects. One could argue that air- lines’ increased costs are largely passed along to passengers in the form of higher fares,7 and so the net cost to passengers is likely closer to $6 billion/year (the sum of the passengers’ travel time losses and increases in air fares resulting from increased airline costs). 1.5.2.1 Quantifying the Economic Value of Delays The Senate JEC report (8) quantifies the increased travel times that passengers incur as a result of delays. However, it explicitly excludes the additional delays that result from missed connections and from the inconvenience imposed on travelers as a result of delays. The effects on passengers of unscheduled flight delays include elements such as loss of productive time, missed flight connections, missed ground connections, missed meetings, and the general inconvenience associated with the necessary schedule adjustments. All of these effects cannot be measured directly, but there are ways of estimating passengers’ perceived costs. One recent study, conducted by Resource Systems Group, Inc., (RSG), employed special survey and mod- eling techniques to measure the trade-offs (also called marginal rates of substitution) between the various components of ser- vice associated with air itineraries (9). The survey used an approach known alternatively as “stated choices” in the trans- portation literature or “choice-based conjoint” in the market research literature. See, for example, Louviere et al. (10). In this approach, survey respondents are presented with a set of choice alternatives from which they are asked to select the one that they would most likely choose under the specified conditions. For the study of air itineraries, the survey questionnaire asked respondents to describe their most recent domestic air trip, and then it created a set of realistic alternative flight itineraries with associated arrival and departure airports, car- riers, schedules, flight times, aircraft types, fares, and percent on-time performance. Much as they would when faced with alternatives generated by travel agents or online flight search engines, respondents were asked to choose their most pre- ferred itinerary from those shown. The data from this type of survey can be used to statistically estimate coefficients of a choice model and, from that model, rates of trade-off among 28 7 Carriers may not assign costs directly to the flight and airport combinations that are experiencing the delays, and thus peak-period passengers may not see higher fares associated with frequently delayed flights. Conversely, passengers on flights that operate at off-peak times from uncongested airports may pay higher fares as a result of the operational costs incurred on the other delayed peak-period flights from congested airports. However, the net effect is still that the costs are likely passed on to the passengers in the aggregate.

the attributes of the flight itineraries can be calculated. When these trade-offs are calculated relative to fares, they are called “willingness to pay” and can be interpreted as the amount of additional fare that a passenger is willing to pay to get differ- ent levels of that attribute. 1.5.2.2 Establishing the Value of Time The most commonly calculated willingness to pay for trans- portation services is the Value of Time (VOT), which is simply the amount that an individual is willing to pay to save a unit of time. VOTs range considerably across individuals and individ- uals’ circumstances. Generally, air travelers have higher VOTs than do travelers of other modes, in part because they have already opted to use a faster but more expensive mode. The RSG study found that the average VOT for domestic air travelers is approximately $70/hour for travelers on business trips and $31/hour for non-business trips. For the air travel market, which is split roughly between 40% business and 60% non-business, the weighted average VOT is approximately $47/hour. That is, air passengers on average are willing to spend an additional $47 in higher fares to save an hour of travel time or, conversely, will be willing to accept an hour of addi- tional travel time for a fare reduction of $47. The FAA uses a value of time of $28.60/hour (in 2000 dol- lars) for regulatory and facilities cost-benefit analyses based on guidance provided in the following documents: “APO Bulletin APO-03-1—Treatment of Values of Travel Time in Economic Analysis,” FAA Office of Aviation Policy and Plans, March, 2003, and “Revised Departmental Guidance—Valuation of Travel Time in Economic Analysis,” Office of the Secretary of Transportation Memorandum, February 11, 2003. This translates to $35/hour in 2007 dollars—still lower than the value used in this analysis. The primary difference is that the FAA value is based on percentages of average wage rates, whereas the values used here are those applied by travelers in their choices among alternative air travel itineraries. Thus, the use of an alternative method for calculating the VOT might lower the “costs” stated in Table 1.3 and Table 1.4 by about one quarter. Applying this lower VOT with the use of the year 2003 benchmark results in a “low-range” estimate of roughly $2.9 billion for 2007. The time delays, while significant, do not account for the additional perceived costs of missed meetings, missed ground connections, and general inconveniences associated with delayed arrivals. Those effects were measured separately in the RSG survey using the FAA’s standard on-time metric as a surrogate. That study found that business travelers are willing to pay on average approximately $38 per flight segment for each 10-point improvement in on-time performance (over the range of 50–90%). The equivalent measure for non-business travelers is $6 for each 10-point improvement in on-time performance. The several-fold difference in willingness of business travelers to pay for flights with high on-time per- formance is not surprising given that they are (a) generally traveling on much tighter schedules and (b) the economic consequences of disruptions to those schedules are generally more direct than for non-business travelers. Using, as before, a 40% business and 60% non-business weighting, the average passenger-perceived value of 10 points of on-time perfor- mance for a given flight is approximately $19. As noted previously, between the years 2003 and 2007, the average on-time performance at the 12 largest coastal mega- region airports decreased on average by over 10 points. Apply- ing the 2003 on-time performance benchmark, this means that the aggregate perceived cost across all boardings at the 12 airports of the performance decline in 2007 is approximately $3.9 billion/year. The absolute cost of the delays (compared 29 Airport On-time 2003 (%) On-time 2007 (%) 2003 Boardings 2007 Boardings 2007 Flight Costs (2003 On-time Benchmark) ($) 2007 Flight Costs (100% On-time Benchmark) ($) Baltimore, MD (BWI) 83 77 10,200,000 11,000,000 138,000,000 483,000,000 Boston, MA (BOS) 83 75 11,100,000 13,800,000 209,000,000 643,000,000 Las Vegas, NV (LAS) 85 76 17,800,000 23,100,000 379,000,000 1,030,000,000 Los Angeles, CA (LAX) 89 80 27,200,000 30,900,000 526,000,000 1,148,000,000 New York, NY (JFK) 83 69 15,900,000 23,600,000 633,000,000 1,377,000,000 New York, NY (LGA) 84 72 11,400,000 12,500,000 299,000,000 671,000,000 Newark, NJ (EWR) 83 68 14,800,000 18,200,000 519,000,000 1,104,000,000 Philadelphia, PA (PHL) 79 70 12,100,000 15,900,000 289,000,000 908,000,000 San Diego, CA (SAN) 88 83 7,700,000 9,400,000 98,000,000 307,000,000 San Francisco, CA (SFO) 89 76 14,400,000 17,600,000 438,000,000 805,000,000 Washington, DC (DCA) 88 77 6,900,000 9,100,000 183,000,000 392,000,000 Washington, DC (IAD) 82 74 8,200,000 11,900,000 182,000,000 577,000,000 157,500,000 197,000,000 3,894,000,000 9,445,000,000 Table 1.3. 2007 Airport flight delay cost estimates (4, 5).

to 100% on-time) is over $9.4 billion/year. When this is added to the $6 billion on-time costs and airline costs8 that are likely added to passenger fares as calculated in the Senate JEC report (8), the total comes to $15.4 billion/year in passen- gers’ lost value due to delays at the 12 largest mega-region airports. This amounts, on average, to $78 per passenger- trip at these airports. Of this, passengers would be willing to pay a fare that is $48 higher, on average, to avoid the time delays and additional inconveniences associated with delayed flights. The remaining $30/passenger is the amount that the airlines need to add to fares in order to compensate for their higher costs due to delays. The aggregate costs are shown in Table 1.3. 1.6 The Costs of Doing Nothing It was requested that this project devote additional atten- tion to the economic and environmental implications of continuing on with the present pattern of degradation in service quality in the mega-regions. In conformance with this request, the research team has created a new analytical proce- dure that would examine the implications of having attained no solutions to the issues discussed in this project. The reader should be aware that these calculations are not based on the same set of assumptions as the FACT 2 study (1), which did explicitly deal with changes in capacity and operations that might (or might not) come into play between now and 2025. Rather, the work of the research team predicts the future con- ditions based strictly on the scenario that solutions are not found and implemented (see Figure 1.7). To reiterate, the assumptions made in this section are simply that the number of flight operations will increase in proportion to the number of passengers (as projected in the FACT 2 study and assuming no significant changes in aver- age aircraft sizes) and that delays will increase also in pro- portion (as estimated from statistical regressions of past delays vs. flight volumes). Since FACT 2 passenger volumes are used as a base for these calculations, the relevant FACT 2 growth assumptions are incorporated. In addition, it is assumed that there are not significant airport capacity enhancement projects at the major airports nor any signif- icant capacity increase from NextGen initiatives nor any policy intervention to reduce delays—in other words, a “do nothing” assumption. 1.6.1 Future Costs of Delays at the Mega-region Airports The FAA’s FACT 2 report (1) projects air traffic volumes out to the year 2025. It does not, however, forecast the likely delays associated with those volumes and with status quo policies. There are, of course, many factors that could affect future delays, not the least of which are the rates of progress on NextGen implementation, changes in airport and airspace configurations, and some of the policies described later in this report. However, historical data can provide an indication of how on-time performance at each airport has affected flight volumes given current and past conditions and operating policies. Monthly on-time performance and traffic volume data were obtained from U.S. DOT/BTS data (5) for the period 2002–September 2008 (the most recent month for which these data were available at the time of the analysis). These data were used to develop a simple regression model with on-time performance as the airport-dependent variable 30 Airport On-time 2003 (%) On-time 2025 (%) 2003 Boardings 2025 Boardings 2025 Flight Costs (100% On-time Benchmark) ($) 2025 Flight Costs (2003 On-time Benchmark) ($) Baltimore, MD (BWI) 83 61 10,200,000 14,900,000 613,000,000 1,078,000,000 Boston, MA (BOS) 83 53 11,100,000 21,100,000 1,212,000,000 1,874,000,000 Las Vegas, NV (LAS) 85 54 17,800,000 32,900,000 1,899,000,000 2,828,000,000 Los Angeles, CA (LAX) 89 63 27,200,000 38,800,000 1,898,000,000 2,681,000,000 New York, NY (JFK) 83 58 15,900,000 27,800,000 1,343,000,000 2,220,000,000 New York, NY (LGA) 84 54 11,400,000 18,800,000 1,082,000,000 1,640,000,000 Newark, NJ (EWR) 83 48 14,800,000 25,000,000 1,617,000,000 2,418,000,000 Philadelphia, PA (PHL) 79 62 12,100,000 16,700,000 533,000,000 1,184,000,000 San Diego, CA (SAN) 88 63 7,700,000 14,400,000 667,000,000 989,000,000 San Francisco, CA (SFO) 89 66 14,400,000 20,800,000 910,000,000 1,344,000,000 Washington, D.C. (DCA) 88 60 6,900,000 12,400,000 639,000,000 923,000,000 Washington, D.C. (IAD) 82 79 8,200,000 12,800,000 82,000,000 504,000,000 157,500,000 256,300,000 12,496,000,000 19,682,000,000 Table 1.4. 2025 Airport flight delay cost estimates (1, 4, 5). 8 It is unclear from the document cited what fuel burn assumptions were made for the time that the aircraft is on the ground and not at the gate. However, this is a small portion of the overall delay-related fuel burn.

and the number of scheduled flight departures as the primary independent variable.9 This equation was used, along with the FACT 2 airport traffic forecasts, to estimate on-time perfor- mance in 2025 at those traffic volumes. The results are shown in Table 1.4. Between the years 2003 and 2025, the average on-time performance at the 12 largest coastal mega-region airports is estimated to decrease on average by 25 points. This assumes status quo operating conditions (no capacity increases, etc.) and assumes air traffic growth as projected in the FACT 2 report. Applying the 2003 on-time performance benchmark, this means that the aggregate perceived cost of missed flight con- nections and other costs across all boardings at the 12 airports of the performance decline in 2025 is over $12 billion/year.10 The absolute cost of the delays (compared to 100% on-time)11 is almost $20 billion/year. Assuming that the Senate JEC delay costs scale up proportionally, the airline and time delay costs would reach $14 billion/year. When these costs are added together, the total comes to $34 billion/year in passengers’ lost value due to delays at the 12 largest mega-region airports. This amounts, on average, to over $130 per passenger trip at these airports in 2025, assuming that status quo operations prevail. Assuming also that the Senate JEC estimates for delay-related fuel consumption scale directly with increases in delays, these delays would generate an additional 17 million metric tons of CO2 per year. It is important to note that this represents the implied costs of doing nothing. The FAA’s Airport Cost Analysis Guidance suggests that aircraft operators might begin to modify sched- ules, adjust aircraft size, and take other actions to reduce delays. However, one of the theses of this ACRP research is that airlines in fact will not modify schedules and adjust air- craft sizes (up-gauge) of their own accord, absent policies that explicitly incentivize such actions. It is assumed that each air- line, acting in its own individual interest, uses airport capacity in a way that consumes rather than protects airport capacity. The problem lies with the concept that the aircraft operator may have a greater tolerance for delay than the policy makers seeking to establish a proper balance of throughput and sys- tem delay. Chapter 5 explores this issue further, leading to the suggestions presented in Chapter 6. 1.6.1.1 Implication for the Themes of this Research The magnitude of the effects of delayed flights both on passengers and on carriers should constitute a strong incen- tive to address at least one of the root causes: congestion caused by flight schedules that approach or exceed airport capacity. Most experienced travelers are well aware of the locations and patterns of flight delays from their own per- sonal experience and may further inform themselves using information from the numerous online sites that offer both 31 Figure 1.7. The cost of doing nothing: Increase in passenger delay costs 2007–2025, assuming no resolution of key issues. Co st in B illi on s Airports Note: Based on Tables 1.3 and 1.4. 9 The actual regression equation used percent of flights delayed as the dependent variable. It included constants to represent the unique conditions at each airport and the weather conditions in each month. It included departures as both a lin- ear effect and the ratio of monthly departures to the maximum number of monthly departures from that airport as a quadratic effect. 10 All 2025 costs cited here are in 2007 dollars. If the lower VOT used in FAA studies were applied to the 2003 benchmark assumption, a low-range estimate of about $9 billion would result. 11 The research team agrees with the FAA that a 100% on-time standard for air service is not realistically attainable. The report provides estimates of passenger- perceived costs using 2003 delay levels as a “realistic” benchmark, but also shows the total cost of all delays for completeness and for comparison to the other costs as calculated in the JEC study (8).

historical and real-time flight performance data.12 However, less-experienced air travelers, who constitute the majority in most air markets, do not necessarily apply similar knowl- edge when choosing among alternative travel itineraries. Few of the major consumer-oriented online booking sites pro- vide on-time performance information for the flight itiner- aries that they create.13 As a result, a flight during a peak period with very low on-time performance will, in advance, appear undifferentiated from other flights with higher on-time performance. 1.6.2 Environmental Effects of Doing Nothing As noted in the Senate JEC report (8), airport delays cur- rently result in an additional 7.1 million metric tons per year of CO2 emissions in the United States, with 1.3 million tons from the major coastal mega-regions airports alone. On the basis of aviation data published by the FAA (11), these represent approximately 3.6% of the total greenhouse gas (GHG) emissions in the aviation sector. However, future increases in delays could substantially increase the total delay-related emissions and their fraction of total aviation emissions. As described previously, increases in delays as a result of growth in air traffic could result in delay-related emissions growing to 17 million metric tons per year across the United States. This translates to over 3.2 million per year in the major coastal mega-region airports—more than dou- bling that impact. The 2025 projections of GHG emissions (which are in turn based on the air traffic forecasts in the FACT 2 report) assume that mega-region airports will continue to function in much the same way as they do now, that air travel patterns will remain similar to the current ones, and that the fleet mix does not change substantially. Of course, any or all of these assumptions could be affected by deliberate policy changes or by unanticipated events with resulting impacts on GHG emissions. The coastal mega-region airports may well be able to reduce delays or at least prevent them from increasing to the extent that would be indicted by the simple extrapolation to the FACT 2 traffic levels. Any such improvements would obviously have a direct effect on the delay-related emissions. However, the changes could also affect the ways that the airports serve travelers, patterns of air travel, and fleet mixes in ways that could either amplify or diminish these effects. For example, regional initiatives to promote other modes as alternatives for the shorter distance markets could do the following: • Cause some diversion of air trips to other modes. Esti- mates of changes in GHG emissions from diversion to other modes range from a factor of three or more reduc- tion for diversions to rail or intercity bus (12) to a much more modest 15–20%, depending on assumptions about vehicle types, occupancies, and other factors that affect the relative fuel efficiencies (11). • Result in net changes in trip patterns. Alternative modes such as rail and bus are most competitive for shorter dis- tance trips for which air is generally the least efficient, for a given aircraft type. For a given type of aircraft, there is almost a factor of two difference in GHG emissions per passenger-mile between short-haul and the most energy- efficient medium-haul flights (11). This is largely a result of the take-off and landing stages, which represent rela- tively large energy expenditures that are approximately the same regardless of the flight length. • Affect aircraft mix. The shorter trips that are the most likely to be diverted to alternative modes are also those that are most likely to be served by smaller regional jets and propjets. The effects of shifting shorter trips to alter- native modes depend on the types of aircraft that are being reduced in the airports’ mix. Figure 1.8 describes the relative fuel consumption levels for different aircraft types and trip (stage) lengths, derived from Smirti and Hansen (13). In this example, which compares a stan- dard 137-seat narrow body jet, a 72-seat turboprop, and a 42-seat regional jet, the fuel consumption rates per seat-mile are lowest for the turboprop and highest by a factor of up to five for the regional jets. Reductions in smaller regional jet aircraft trips at an airport most likely will result in significant fuel—and thus GHG—reductions. On the other hand, reductions in relatively fuel-efficient turboprop trips would have more modest effects on GHG emissions. Overall, there are clearly significant opportunities for reducing GHG emissions both as a direct result of reducing delays and indirectly as a result of shifts that could occur from changed air traffic patterns. 1.7 Conclusion Chapter 1 concludes with a concern that the amount of 2025 aviation capacity assumed by leaders in the aviation community and reflected in the FACT 2 study (1) may be based, as least in part, on the working assumption that, as demand increases, a voluntary program of aircraft up-gauging can be expected to take place. Given the overall decrease in 32 12 For example, DOT’s BTS maintains monthly online flight performance data and dedicated sites such as flightstats.com offer detailed ratings of flights by OD pair, carrier, and even flight number along with real-time tracking of flights. 13 When this report was written, most of the available websites did not offer online performance data for each alternative itinerary presented in flight searches.

the average number of passengers per plane over the past decade, the research team believes that this assumption needs more analytic attention. The research team addresses this in Chapter 5 after presenting a review of both multimodal and multijurisdictional issues facing the industry. The concern that more help may be needed in finding long-distance trip-making capacity merely increases the need of forging a better level of integration with HSR planning and better use of procedures developed for highway planning. Chapter 2 explores both. A lack of immediate answers for how to get more capacity from the overcrowded airports should lend support for local and regionally based initiatives to find more usable capacity at underused airports in the two study areas. This need for greater multijurisdictional planning to solve the air capacity problem is discussed in Chapter 3. 33 Figure 1.8. Fuel consumption rates for representative aircraft (14).

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TRB Airport Cooperative Research Program (ACRP) Report 31: Innovative Approaches to Addressing Aviation Capacity Issues in Coastal Mega-regions examines the aviation capacity issues in the two coastal mega-regions located along the East and West coasts of the United States. The report explores integrated strategic actions to that could potentially address the constrained aviation system capacity and growing travel demand in the high-density, multijurisdictional, multimodal, coastal mega-regions.

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