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Massachusetts Institute of Technology Multi-Airport Systems: Concepts, Historical Evolution and Strategies for Future Development Massachusetts Institute of Technology Multi-Airport Systems: Concepts, Historical Evolution and Strategies for Future Development Dr. Philippe A. Bonnefoy Postdoctoral Associate Department of Aeronautics & Astronautics [email protected] edu http: //web. mit. edu/bonnefoy/www/pb. html Lecture MIT 16. 781 J / 1. 231 J / ESD. 224 J Planning and Design of Airport Systems Oct 29 th 2009

Motivation Massachusetts Institute of Technology § Increasing demand for air transportation § Key infrastructure Motivation Massachusetts Institute of Technology § Increasing demand for air transportation § Key infrastructure constraints in the air transportation system Historical Evolution of Passenger Traffic (Revenue Passenger Kilometers - RPKs) from 1971 to 2007 • e. g. airport capacity constraints North America § Airport congestion problem • results in the generation and propagation of delays throughout the system Europe § Implications: • degradation of the passengers’ quality of travel experience, • economic impacts. Asia-Pacific Middle East § Air transportation system is a vital underlying infrastructure of a country’s economy § The development of multi-airport systems has proven to be a key mechanism by which demand is met at the regional level Latin America Africa * Data source: ICAO and IATA 2

Lecture Outline Massachusetts Institute of Technology § Definitions & Concepts § Overview of Multi-Airport Lecture Outline Massachusetts Institute of Technology § Definitions & Concepts § Overview of Multi-Airport Systems Worldwide • Multi-airport systems in numbers, • Geographical distribution, • Types (configurations, pax. vs. cargo) § Historical Patterns of Development & Drivers • Patterns of evolution • What drives traffic allocation • Role of low cost carriers (role of entries, evolution of models over time, parallel networks) § Development Strategies for Multi-Airport Systems • Uncertainty, volatility -> Planning challenges • Long term development • Real option approach § “Metroplex” Airspace Considerations • Multi-Airport Systems Capacity Estimation • Role of Next. Gen Technologies in Limiting Air Traffic Interactions 3

Outline Massachusetts Institute of Technology § Definitions & Concepts § Overview of Multi-Airport Systems Outline Massachusetts Institute of Technology § Definitions & Concepts § Overview of Multi-Airport Systems Worldwide • Multi-airport systems in numbers, • Geographical distribution, • Types (configurations, pax. vs. cargo) § Historical Patterns of Development & Drivers • Patterns of evolution • What drives traffic allocation • Role of low cost carriers (role of entries, evolution of models over time, parallel networks) § Development Strategies for Multi-Airport Systems • Uncertainty, volatility -> Planning challenges • Long term development • Real option approach § “Metroplex” Airspace Considerations • Multi-Airport Systems Capacity Estimation • Role of Next. Gen Technologies in Limiting Air Traffic Interactions 4

Definitions Massachusetts Institute of Technology § Multi-Airport System: • (Geographical basis): A set of Definitions Massachusetts Institute of Technology § Multi-Airport System: • (Geographical basis): A set of two or more significant airports that serve passenger traffic in a metropolitan region (without regard to ownership or political control of the individual airports) Ø Most common definition • (Ownership basis): A set of airports managed by one individual operator or authority Ø Ø Reference (ACI 2002) Not commonly used § Metroplex: • Large metropolitan area containing several cities and their suburbs (and airports) (e. g. Dallas/Fort Worth Metroplex) Definition refers to set of cities/suburbs but is also used by extension to set of airports Ø Often used in the context of future airspace management concepts (by NASA, FAA, etc. ) Ø 5

Definitions Massachusetts Institute of Technology § Airports within Multi-Airport Systems: (Bonnefoy 2008) • Primary Definitions Massachusetts Institute of Technology § Airports within Multi-Airport Systems: (Bonnefoy 2008) • Primary airport: An airport that serves more than 20% of the total passenger traffic in the multi-airport system • Secondary airport: An airport that serves between 1% and 20% of the total passenger traffic in the multi-airport system • Secondary (cargo) airport: An airport located in a metropolitan area and serves air cargo operators (e. g. Chicago/Rockford, Dallas/Alliance, Paris/Vatry, Brussels/Liege) Evolution of passenger traffic within the Boston multi-airport system Manchester Providence Boston Logan * Significant airport: an airport that serves more than 500, 000 passengers per year 6

More Complex Multi-Airport System Massachusetts Institute of Technology § New York Multi-Airport System * More Complex Multi-Airport System Massachusetts Institute of Technology § New York Multi-Airport System * Significant airport: an airport that serves more than 500, 000 passengers per year 7

Outline Massachusetts Institute of Technology § Definitions & Concepts § Overview of Multi-Airport Systems Outline Massachusetts Institute of Technology § Definitions & Concepts § Overview of Multi-Airport Systems Worldwide • Multi-airport systems in numbers, • Geographical distribution, • Types (configurations, pax. vs. cargo) § Historical Patterns of Development & Drivers • Patterns of evolution • What drives traffic allocation • Role of low cost carriers (role of entries, evolution of models over time, parallel networks) § Development Strategies for Multi-Airport Systems • Uncertainty, volatility -> Planning challenges • Long term development • Real option approach § “Metroplex” Airspace Considerations • Multi-Airport Systems Capacity Estimation • Role of Next. Gen Technologies in Limiting Air Traffic Interactions 8

Massachusetts Institute of Technology Primary & Secondary Airports in the United States § Total Massachusetts Institute of Technology Primary & Secondary Airports in the United States § Total of 20 primary and 17 secondary airports within 14 multi-airport systems identified in the United States (as of 2008) * 9

Multi-Airport Systems Worldwide Massachusetts Institute of Technology (as of 2008) § Set of 59 Multi-Airport Systems Worldwide Massachusetts Institute of Technology (as of 2008) § Set of 59 multi-airport systems • in 26 countries, corresponding to 82 primary airports and 54 secondary airports. • airports within these 59 systems served 47% of the total passenger traffic worldwide in 2006 Legend Multi-Airport System North America Europe Latin America & Caribbean Middle East Asia/Pacific 10

Multi-Airport Systems Worldwide (as of 2008) Massachusetts Institute of Technology § Set of 59 Multi-Airport Systems Worldwide (as of 2008) Massachusetts Institute of Technology § Set of 59 multi-airport systems • in 26 countries, corresponding to 82 primary airports and 54 secondary airports. • airports within these 59 systems served 47% of the total passenger traffic worldwide in 2006 Middle East Country Metropolitan Region Iran Israel UAE Tehran Tel Aviv Dubai Europe North America Country Metropolitan Region Canada United States United States United States United States Toronto Vancouver Boston Chicago* Cleveland Dallas* Detroit Houston Los Angeles Miami New York Norfolk Orlando Philadelphia San Diego San Francisco Tampa Washington Austria Belgium Danmark France Germany Germany Italy Italy Netherlands Norway Russia Spain Sweden Turkey United Kingdom Vienna Brussels* Copenhagen Paris* Berlin Dusseldorf Frankfurt Hamburg Stuttgart Bologna Milan Pisa Rome Venice Amsterdam Oslo Moscow Barcelona Gothenburg Stockholm Istanbul Belfast Glasgow London Manchester Latin America Country Metropolitan Region Argentina Brazil Mexico Buenos Aires Belo Horizonte Rio de Janeiro Sao Paulo Mexico Asia-Pacific Country Metropolitan Region Australia China Japan South Korea Thailand Melbourne Hong Kong Shanghai Taipei Osaka Tokyo Seoul Bangkok 11

Configurations of Multi-Airport Systems Massachusetts Institute of Technology (i. e. combinations of primary and Configurations of Multi-Airport Systems Massachusetts Institute of Technology (i. e. combinations of primary and secondary airports) § Several configurations of multi-airport systems were identified Ø Ø 1 primary 1 secondary airport • and cases of 2 primary airports • More complex as the number of primary and secondary airports increases • Most complex multi-airport systems; Los Angeles, London and New York Los Angeles N/A Manchester London N/A Amsterdam, Barcelona, Stockholm, Boston, Tampa Dusseldorf N/A Bologna, Brussels, Chicago, Copenhagen, Dallas, Dubai, Frankfurt, Gothenburg, Hamburg, Houston, Istanbul, Melbourne, Mexico, Orlando, Oslo, Rome, Stuttgart, Tehran, Tel Aviv, Toronto, Vancouver, Venice, Vienna Osaka, Paris, Berlin, Milan, Moscow, Glasgow, Sao Paulo, San Francisco New York Single Airport Systems Hong Kong, Shanghai, Taipei, Tokyo, Seoul, Bangkok, Pisa, Belfast, Buenos Aires, Belo Horizonte, Rio de Janeiro, Miami, Norfolk Washington 4 Number of secondary airports • Most frequent types composed of; N/A 3 2 1 0 N/A 0 1 2 Number of primary airports 3 12

Secondary (Cargo) Airport Massachusetts Institute of Technology § Similar development with air cargo business Secondary (Cargo) Airport Massachusetts Institute of Technology § Similar development with air cargo business models § Airports used predominantly for cargo activity (without significant passenger traffic) within or in the vicinity of multi-airport systems § Mixed passenger/cargo traffic with dominant cargo traffic • Fedex: Memphis, Manila/Subic Bay, San Francisco/Oakland • UPS: Louisville, Los Angeles/Ontario 13

Outline Massachusetts Institute of Technology § Definitions & Concepts § Overview of Multi-Airport Systems Outline Massachusetts Institute of Technology § Definitions & Concepts § Overview of Multi-Airport Systems Worldwide • Multi-airport systems in numbers, • Geographical distribution, • Types (configurations, pax. vs. cargo) § Historical Patterns of Development & Drivers • Patterns of evolution • What drives traffic allocation • Role of low cost carriers (role of entries, evolution of models over time, parallel networks) § Development Strategies for Multi-Airport Systems • Uncertainty, volatility -> Planning challenges • Long term development • Real option approach § “Metroplex” Airspace Considerations • Multi-Airport Systems Capacity Estimation • Role of Next. Gen Technologies in Limiting Air Traffic Interactions 14

Massachusetts Institute of Technology Multi-Airport Systems Have Evolved According to Two Fundamental Mechanisms § Massachusetts Institute of Technology Multi-Airport Systems Have Evolved According to Two Fundamental Mechanisms § Two fundamental evolutionary mechanisms: • Construction of new airport (with full or partial transfer of traffic), • Emergence of secondary airport through the use of existing airport (without restriction of initial role; civil or military). al in ig or e th rt of po e air nc ry ge a er rim p em e- C R rt po r ai w affic e r f n of t o n r io sfe t n uc a tr d tr s on an Single-airport system of ts e or an nc irp of ge a e rt er ary us rpo Em nd the ai co gh ing se rou xist th e e th of t le r rt ro po o g airp in y en ar ry th nd ima ng o r re ec p St s to a in Legend Original primary airport Emerged primary airport Former primary airport Secondary airport 15

Patterns of Evolution of Multi-Airport Systems across World Regions Massachusetts Institute of Technology § Patterns of Evolution of Multi-Airport Systems across World Regions Massachusetts Institute of Technology § Frequency of occurrence of mechanisms that govern the evolution of multiairport systems across world-regions Europe North America 19% Middle-East 81% 50 % Asia-Pacific 10 % Legend 90 % Construction of new airport Latin America 20 % Emergence of secondary airport through the use of an existing airport Note: Size of the bubble proportional to the number of airports involved 80 % 16

Location of Airports within Multi-Airport Systems: Massachusetts Institute of Technology Number of Airports (by Location of Airports within Multi-Airport Systems: Massachusetts Institute of Technology Number of Airports (by type) as a Function of Distance from the Center of the City § As multi-airport system develops new airports are emerge further away from the center of the city • In general, original airports tend be be located close to city center (within 20 miles) • Airports developed as second, third, etc. airports are generally located between 10 and 30 miles • Secondary airports that emerged from exiting exhibit greater distances from center of the city (rely on existing underutilized airport infrastructure) 17

Massachusetts Institute of Technology Drivers of Traffic Allocation within Multi-Airport Systems § Concentration of Massachusetts Institute of Technology Drivers of Traffic Allocation within Multi-Airport Systems § Concentration of traffic at primary airport Market Share § Allocation of flights is driven by S-shaped market share/frequency share (driven by consumer/passenger frequency preference) Frequency Share § In general, airlines have an incentive to allocate resources (i. e. flights) at the airport they already serve and compete directly with other airlines 18

Massachusetts Institute of Technology “Exception” to the Dynamic of Concentration of Traffic at Major Massachusetts Institute of Technology “Exception” to the Dynamic of Concentration of Traffic at Major Airports § Capacity and Access Constraints • Airport physical constraints (e. g. runways too short) Ø e. g. Belfast, Buenos Aires, Rio de Janeiro • Capacity constraints due to limited expansion capabilities Ø e. g. New York/La. Guardia, San Francisco/International, Paris/Orly, Bangkok/Don Mueang, etc. • Massive infrastructure investment requirements -> High marginal capacity cost Ø e. g. $6 to 20 billion for the Chicago O’Hare Modernization Program, $6. 5 billion for London Heathrow Terminal 5 § Development of Low-Cost Carriers • Historically, low-cost carriers have generally focused their development at secondary airports i. e. “Southwest model” * Data source: US Federal Aviation Administration (FAA) OPSNET data. Note: By the nature of the definitions of delays and reporting process, OPSNET data underestimates the true extent of delays. The use of this data in this figure is for airport to airport delay comparison purposes. 19

Massachusetts Institute of Technology Entry of Low-Cost Carriers Stimulates Demand Growth at Secondary Airports Massachusetts Institute of Technology Entry of Low-Cost Carriers Stimulates Demand Growth at Secondary Airports § “Southwest Effect”: offering of service at low fares that attract passengers who were previously using the primary airport and/or stimulate demand in the region and generate new traffic within the region (Bennett et al. 1993). Entry of Southwest (1998) Boston/Providence Entry of Southwest (1996) Boston/ Manchester 20

Stimulation of Demand by Low-Cost Carriers Massachusetts Institute of Technology (i. e. Low-Fare Airlines) Stimulation of Demand by Low-Cost Carriers Massachusetts Institute of Technology (i. e. Low-Fare Airlines) § Two cases of initial conditions at secondary airports (before LCC entry): • No traffic at the secondary airport (low-cost carrier was the first carrier to serve the secondary airport) • Secondary airport served by carriers with very limited service and high fares, the entry of low-cost carriers resulted in a decrease of average fares. -> Stimulated the emergence process. § Evolution of average yield for Boston/Logan (BOS), Boston/Manchester (MHT), and Boston/Providence (PVD) • Boston/Manchester (MHT): average aggregate yield dropped by 27% -> enplanements increased by 154% (between 1997 and 1999) 21

Massachusetts Institute of Technology Dynamics of Low-Cost Carrier Emergence at Secondary Airports Not Specific Massachusetts Institute of Technology Dynamics of Low-Cost Carrier Emergence at Secondary Airports Not Specific to the U. S. § Case of Frankfurt/Hahn (entry of Ryanair) Frankfurt/Hahn Entry of Ryanair (1999) § Case of Dubai/Sharjah (entry of Air Arabia) Entry of Air Arabia (2003) 22

Massachusetts Institute of Technology Entry of Low-Cost Carriers at Secondary Airports (Worldwide) § Clear Massachusetts Institute of Technology Entry of Low-Cost Carriers at Secondary Airports (Worldwide) § Clear dynamic in North America and Europe, § also observed to minor extent in the Middle-East, Latin American and Asia-Pacific. FKB - Ryanair (2003) BVA - Ryanair (1997) BGY - Ryanair (2004) BLK - Jet 2. com (base in 2005) BTS - Sky. Europe (2002) CRL - Ryanair (1988) CIA - Ryanair (2004) EDI – Ryanair EIN - Ryanair FRL - Ryanair (2002) GRO - Ryanair (2004) PIK - Ryanair (1994) GSE - Ryanair (2001) HHN - Ryanair (2002) LBA - Jet 2. com (2003) LPL - Ryanair (1987 -base in 2005) LBC - Ryanair (2005) - Wizzair (2006) MMX - Ryanair (1998 -2007) TRF - Ryanair (1997) REU - Ryanair (2004) NYO - Ryanair (1997) TSF - Ryanair (1998) NRN - Ryanair (2003) YHM - Westjet (2000) – Globespan (2007) YXX - Westjet (1997) MDW - Midway (1979) Southwest (1985) OAK - Southwest (1989) BUR - Southwest (1990) DAL - Southwest (1971) HOU - Southwest (1972) MHT - Southwest (1998) PVD - Southwest (1996) ISP - Southwest (1999) EWR - People Express (1980) BWI - Southwest (1993) FLL - Southwest (1996) TLC - Interjet (2005) - Volaris (2005) SHJ - Air Arabia (2003) DMK - One-Two-Go (2007) AVV - Jetstar (2004) 23

Massachusetts Institute of Technology Development of Parallel Networks by Low Cost Carriers § Emergence Massachusetts Institute of Technology Development of Parallel Networks by Low Cost Carriers § Emergence of a new primary and secondary airports in a metropolitan region results in the creation of new connections to the rest of the airport network • e. g. emergence of Boston/Providence resulted in development of new OD pairs: Ø Ø Ø Boston/Providence (PVD) to Chicago/O’Hare (ORD) a secondary to primary airport market Boston/Providence (PVD) to Chicago/Midway (MDW) a secondary-to-secondary airport market Routes parallel the primary-to-primary airport route; Boston/Logan (BOS) to Chicago/O’Hare (ORD). § Airlines compete at the network level rather than at airport level “Base network” “Semi-parallel network” * Date source: ETMS data for the time period from October 1 st 2004 to September 30 th 2005. “Parallel network” 24

Massachusetts Institute of Technology Variations across Low-Cost Carrier Business Model & Evolution § Range Massachusetts Institute of Technology Variations across Low-Cost Carrier Business Model & Evolution § Range of strategies and business models used by low-cost carriers Distribution of traffic (flight departures and arrivals) between primary and secondary airports for the top 30 low-cost carriers • Major low-cost carriers have focused on secondary airports • Number of air carriers that have focused their development on primary airports -> Difficult to be a low-cost at a primary airport (higher cost than at secondary airports) § Evolution of business models • e. g. Southwest Airlines recent entry into New York/La. Guardia, Boston/Logan, etc. -> Becoming a major network airlines after reaching a critical mass network * Data source: The Official Airline Guide (OAG), data from Oct 1 st 2004 to Sept 30 th 2005, traffic measured in number departures and arrivals. 25

Outline Massachusetts Institute of Technology § Definitions & Concepts § Overview of Multi-Airport Systems Outline Massachusetts Institute of Technology § Definitions & Concepts § Overview of Multi-Airport Systems Worldwide • Multi-airport systems in numbers, • Geographical distribution, • Types (configurations, pax. vs. cargo) § Historical Patterns of Development & Drivers • Patterns of evolution • What drives traffic allocation • Role of low cost carriers (role of entries, evolution of models over time, parallel networks) § Development Strategies for Multi-Airport Systems • Uncertainty, volatility -> Planning challenges • Long term development • Real option approach § “Metroplex” Airspace Considerations • Multi-Airport Systems Capacity Estimation • Role of Next. Gen Technologies in Limiting Air Traffic Interactions 26

Strategic Planning “Mistakes” Massachusetts Institute of Technology of Airports within Multi-Airport Systems Airport Name Strategic Planning “Mistakes” Massachusetts Institute of Technology of Airports within Multi-Airport Systems Airport Name Planning “Mistake” Outcome Washington/Dulles Airport was developed “too early” in the 1960 s - Low traffic for approx. 20 years - Now a viable primary airport in the Washington multi-airport system Montreal/Mirabel - Development of an oversized airport -Far from the city center while the original airport (i. e. Montreal/Trudeau) still had potential for capacity growth - Attempted to “force” the transfer of traffic to new airport -Airlines (e. g. Air Canada) preferred Toronto -Airport did not emerge as major airport -Montreal/Trudeau was improved making Mirabel less attractive -Now close for passenger operations London/Stansted Redeveloped in 1966 from a military base and later in 1984. Ryanair started offering service at London/Stansted in 1991 and contributed to the significant growth of traffic observed at London/Stansted since the beginning of the 1990 s Now a major secondary airport: Lowcost carriers now account for over 80% of the total passenger traffic. Osaka/Kansai Osaka/Itami did not close Limiting attractiveness of Osaka/Kansai 27

Strategic Planning Challenges: Massachusetts Institute of Technology Volatility of Traffic § Volatility of traffic Strategic Planning Challenges: Massachusetts Institute of Technology Volatility of Traffic § Volatility of traffic at secondary airports -> Planning Uncertainty § Secondary airports tend to exhibit higher volatility of traffic -> Higher investment risks (than existing primary airports that tend to exhibit more stable traffic and revenues) § Inherent difficulty of forecasting traffic

Massachusetts Institute of Technology Long Term Demand Future Airport Infrastructure Adequacy § Future demand Massachusetts Institute of Technology Long Term Demand Future Airport Infrastructure Adequacy § Future demand for air transportation will be led by countries such as India and China § Future adequacy of airport infrastructure: • China and India: high population/airport infrastructure ratios will require significant future development of airport infrastructure • United States and Europe have large number of existing airports that can accommodate future growth *Data source: ICAO Journal 2006, & CIA Handbook database 2005 29

Massachusetts Institute of Technology Long Term Development of Multi-Airport Systems § 420 metropolitan regions Massachusetts Institute of Technology Long Term Development of Multi-Airport Systems § 420 metropolitan regions worldwide with population greater than 1 million with: • Multi-airport systems, • Single airport systems in transition, • Single airport systems or no airport. § As Gross Regional Product (GRP) increases more metropolitan regions around the world will transition to multi-airport systems. 30

Multi-Airport Systems in Development Massachusetts Institute of Technology § Examples of single airport systems Multi-Airport Systems in Development Massachusetts Institute of Technology § Examples of single airport systems in transition • (i. e. systems that are exhibiting either plans or construction of new airports or have emerging secondary airports in the metropolitan region). Berlin/Finow Montreal/Plattsburg Lisbon/Alcochete Leipzig/Altenburg Warsaw/Modlin Beijing/2 nd airport Madrid/Don Quijote Las Vegas/Ivanpah New Delhi/Jewar Mumbai/Navi Legend Hyderabad/Intl Bangalore/Intl Manila/Subic. Bay & Macapal Cochin/Intl Kuala Lumpur/Intl & Subang Pattern of evolution of multi-airport systems Jakarta/ Soekarno-Hatta & Jakarta/ Halim Perdanakusuma Construction of new airport Emergence of secondary airport through the use of existing an airport Johannesburg/Lanseria Auckland/Whenuapai 31

Massachusetts Institute of Technology Closure of Airports: Lost Option for Future Emergence? § Original Massachusetts Institute of Technology Closure of Airports: Lost Option for Future Emergence? § Original primary airports that were closed after the transfer of traffic to a new airport § Original primary airports that remained opened (after loss of traffic) and then became or could become secondary airports

Strategies for Enabling the Future Development of Multi-Airport Systems Massachusetts Institute of Technology § Strategies for Enabling the Future Development of Multi-Airport Systems Massachusetts Institute of Technology § Need to develop flexible approaches to ensure feasibility of evolution paths and future development of multi-airport. Evolution patterns (i. e. tree) Necessary conditions Flexible strategies to allow future development Availability of usable land area in the metropolitan region (2) Partially develop the land or select sites that are less likely to exhibit downstream development blockage Availability of existing non-utilized airports in the metropolitan region Protect existing civil and military airports from closure C on st an ruc d tio tra n ns of fe n r o ew ft a ra ir ffi po c rt (1) Land banking strategies ts or rt rp po ai ir y ga ar tin nd xis co e se f an of o e se nc u ge the er gh Em rou th Existing single-airport system or multi-airport system 33

Massachusetts Institute of Technology Long Term Development of Metropolitan Area Airport Capacity; A Real Massachusetts Institute of Technology Long Term Development of Metropolitan Area Airport Capacity; A Real Option Strategy § Real option strategies for the development of metropolitan area airport capacity • Strategies with the potential to create the preconditions for a “win-win” situation for airport owners and local and regional governments in the long run; Ø Ø Ø (1) protecting existing under-utilized airport in the metropolitan region, (2) protecting existing airports through alternative uses such as military, national security activities, (3) reserving sites that can be developed as new greenfield airports in the future. 34

Outline Massachusetts Institute of Technology § Definitions & Concepts § Overview of Multi-Airport Systems Outline Massachusetts Institute of Technology § Definitions & Concepts § Overview of Multi-Airport Systems Worldwide • Multi-airport systems in numbers, • Geographical distribution, • Types (configurations, pax. vs. cargo) § Historical Patterns of Development & Drivers • Patterns of evolution • What drives traffic allocation • Role of low cost carriers (role of entries, evolution of models over time, parallel networks) § Development Strategies for Multi-Airport Systems • Uncertainty, volatility -> Planning challenges • Long term development • Real option approach § “Metroplex” Airspace Considerations • Multi-Airport Systems Capacity Estimation • Role of Next. Gen Technologies in Limiting Air Traffic Interactions 35

Analysis of the NY Metroplex Capacity Improvement Potential Illustration of Conflicting Departure and Approach Analysis of the NY Metroplex Capacity Improvement Potential Illustration of Conflicting Departure and Approach Paths within the NY Metroplex Massachusetts Institute of Technology (EWR Arr. 22 L – TEB Dep. 24) Teterboro La. Guardia Newark *Flight track data courtesy of Leo Prusak and NYNJ Port Authority 36

Analysis of the NY Metroplex Capacity Improvement Potential Illustration of Conflicting Departure and Approach Analysis of the NY Metroplex Capacity Improvement Potential Illustration of Conflicting Departure and Approach Paths within the NY Metroplex Massachusetts Institute of Technology (EWR Arr. 22 L - LGA Arr. 13 - TEB Arr. 19) Teterboro La. Guardia Newark *Flight track data courtesy of Leo Prusak and NYNJ Port Authority LAGUARDIA AREA - Standard Operating Procedure Manual “LGA ILS RWY l 3 approach: When EWR is using RWY 22 L/R approaches … and traffic conditions permit, LGA will provide a gap in their approach sequence for TEB arrivals or RWY 1/6 departures. When this procedure is not practical, the OSIC’s will coordinate to balance delays equitably”. 37

Analysis of the Metroplex Capacity: Massachusetts Institute of Technology Data Sources & Methodology § Analysis of the Metroplex Capacity: Massachusetts Institute of Technology Data Sources & Methodology § Data • Source: FAA Aviation System Performance Metrics (ASPM) based on ETMS and ARINC information • Cross sectional and time series analyses using: Ø Hourly data of airport operations (i. e. arrival and departure rates, configurations) for a time period covering 5 years from 2004 to 2008. § Scope of Analysis: 4 New York Airports • La. Guardia (LGA), Newark (EWR), JF Kennedy (JFK), Teterboro (TEB) § Methodology: • Data was filtered to retain stable airport configurations Ø Ø i. e. hours of operations of an airport or set of airports during which the configuration did not change - for which the previous and following hour of operations had identical configurations, Note: Metroplex was operated under stable (combined) configurations 43% of the time accounting for 37% of the total number of operations for 2007/2008. Illustration: LGA configuration 22 | 31 Pareto front 50% arr. 50% dep. • Developed and used a dominance search algorithm to compute Pareto front equations, • Identified operating point of 50% dep. – 50% arr. at the intersection of the Pareto front. 38

Estimation of the Metroplex Capacity Improvement Potential (i. e. Difference between the Massachusetts Institute Estimation of the Metroplex Capacity Improvement Potential (i. e. Difference between the Massachusetts Institute of Technology Capacity from Coupled Metroplex Operations and the Sum of Capacity from Decoupled* Airport Operations) Illustration with configuration: LGA 22 | 31 -- EWR 22 L | 22 R -- JFK 22 L | 22 R, 31 L -- TEB 19 | 24 CPs for Individual Airports Metroplex Capacity Profile (CP) Im Me pr tro ov p e le (e me x C. g nt ap. 2 P a 2% ot ci ) ent ty ia l TEB CP for estimated decoupled airport operations JFK CP for observed coupled metroplex operations LGA EWR JFK LGA * Note: The Pareto capacity of individual airport is used as a proxy for decoupled airport operation capacity (based on the assumption that given all sets of observed configurations of neighbor airports, at least one set of configuration exhibits little to no coupling) 39

Analysis of the NY Metroplex Capacity Improvement Potential Massachusetts Institute of Technology (in % Analysis of the NY Metroplex Capacity Improvement Potential Massachusetts Institute of Technology (in % improvement) for the top 35 most Frequent Configurations in the NY Metroplex System in 2007 -2008 Cumulative Frequency of Observation (in terms of hours of stable operating configurations) 40

Conclusions Massachusetts Institute of Technology § Significant number of multi-airport systems exist worldwide • Conclusions Massachusetts Institute of Technology § Significant number of multi-airport systems exist worldwide • Vary by location, configurations, etc. § Several fundamental mechanisms by which multi-airport systems can evolve • (1) the construction of new airports and transfer of traffic, • (2) the emergence of secondary airports through the use of existing non-utilized airports. § Factors that influence evolution and development exhibit differences and similarities identified across world regions • World region and country specific conditions matter § Need to develop flexible approaches to enable the future development of multiairport systems by; • (1) applying land banking strategies in regions where the set of existing non-utilized airports is weak and where projections of future demand are high, • (2) protecting existing airport infrastructure (both civil and military airports) in regions that face constraints for the development of new airports. § Need to also consider larger system-level issues in the planning process • Airspace level: Interaction between airports, airport configuration of new airports, etc. • Ground transportation level: Integration of airport and ground transportation networks 41

References (1) Massachusetts Institute of Technology § Bonnefoy, P. , (2008). Scalability of the References (1) Massachusetts Institute of Technology § Bonnefoy, P. , (2008). Scalability of the Air Transportation System and Development of Multi-Airport Systems: A Worldwide Perspective, Doctoral Dissertation, Massachusetts Institute of Technology, Cambridge, Mass. , http: //esd. mit. edu/people/dissertations/philippe_bonnefoy. pdf § Bonnefoy P. , de Neufville R. & Hansman R. J. , Evolution and Development of Multi-Airport Systems; A Papers Worldwide Perspective, Journal of Transportation Engineering, ASCE, (Accepted for publication - Jun. 2008), http: //web. mit. edu/bonnefoy/www/Doc/Bonnefoy_J_Tranp_Eng_MAS_2009_2. pdf § Bonnefoy, P. , (2007). Role of The Privatization of Airports in The Evolution and the Development of Multi-Airport Systems, Planning & Design of Airport Systems, Massachusetts Institute of Technology, December 14 th 2007. http: //ardent. mit. edu/airports/ASP_exercises/ASP%20 matl%20 for%20 posting%202007/Bonnefoy_Airport_Privatization_Paper. pdf § Bonnefoy, P. , Hansman R. J. , (2005). Emergence of Secondary Airports and Dynamics of Multi-Airport Systems, Master Thesis, Massachusetts Institute of Technology, Cambridge, Mass. § Cohas, F. (1993). Market-Share Model for a Multi-Airport System. Cambridge, MA: Department of Aeronautics and Astronautics and Technology and Policy Program, Massachusetts Institute of Technology. § de Neufville, R. , (1995). Management of Multi-Airport Systems: A Development Strategy, Journal of Air Transport Management, Vol. 2, No 2, 99 -110. § de Neufville, R. (2006). Accommodating Low Cost Airlines at Main Airports. Transportation Research Board. Washington, DC. http: //ardent. mit. edu/airports/de_Neufville_airport_papers. html. § de Neufville, R. (2007). Low-cost airports for low-cost airlines: flexible design to manage risks. Special Issue of Journal of Transportation Planning and Technology, http: //ardent. mit. edu/airports/de_Neufville_airport_papers. html. § de Neufville, R. (1995). Management of Multi-Airport Systems: A Development Strategy. Proceedings of Airports 95 Conference, (pp. 1 -13). Sydney, Australia, http: //ardent. mit. edu/airports/de_Neufville_airport_papers. html § de Neufville, R. (2004). Multi-Airport Systems in the Era of No-Frills Airlines. Transportation Research Board conference, (pp. 1 -19). Washington, DC, http: //ardent. mit. edu/airports/de_Neufville_airport_papers. html § de Neufville, R. (1995). Policy Guidelines for the Option of a Development of a Multi-Airport System, the basis of a Dynamic Strategic Plan to provide the capability for flexible response to future challenges. Paper to the Board and General Manager of Amsterdam Airport Schiphol, http: //ardent. mit. edu/airports/de_Neufville_airport_papers. html § de Neufville, R. (2005). The Future of Secondary Airports: Nodes of a parallel air transport network? English version of article prepared for the journal Cahiers Scientifiques du Transport , Issue 47, pp. 11 -38, http: //ardent. mit. edu/airports/de_Neufville_airport_papers. html 42

References (2) Massachusetts Institute of Technology § de Neufville, R. , & Odoni, A. References (2) Massachusetts Institute of Technology § de Neufville, R. , & Odoni, A. (2003). Airport Systems; Planning, Design and Management. New York, NY: Mc Graw Hill § European Parliament. (2007). The Consequences of the Growing European Low-Cost Airline Sector. Brussels, Belgium: European Parliament. § FAA. (2007). Capacity Needs in the National Airspace System: An Analysis of Airports and Metropolitan Area Demand Operational Capacity in the Future. Washington, DC: U. S. Department of Transportation (DOT) Federal Aviation Administration (FAA). § FAA. (2004). National Plan for Integrated Airport System. Washington, DC: U. S. Department of Transporation (DOT) Federal Aviation Administration (FAA). § Garriga, J. (2003). Airport Dynamics Towards Airport Systems. Airport Regions Conference (ARC), http: //www. airportregions. org/doc/Airport%20 Dynamics. pdf 43

Massachusetts Institute of Technology Questions & Comments 44 Massachusetts Institute of Technology Questions & Comments 44