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
bonnefoy@mit.edu
http://web.mit.edu/bonnefoy/www/pb.html
Lecture
MIT 16.781J / 1.231J / ESD.224J Planning and Design of Airport Systems
Oct 29th 2009
Motivation
Massachusetts Institute of Technology
 Increasing demand for air transportation
Historical Evolution of Passenger Traffic
 Key infrastructure constraints in the air
transportation system
(Revenue Passenger Kilometers - RPKs)
from 1971 to 2007
1,500
• e.g. airport capacity constraints
• results in the generation and propagation of
delays throughout the system
 Implications:
• degradation of the passengers’ quality of
travel experience,
• economic impacts.
 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
Revenue Passenger Kilometers (billion)
 Airport congestion problem
North America
1,250
1,000
Europe
750
500
Asia-Pacific
Middle East
250
Latin America
0
1970
Africa
1980
1990
2000
2010
* Data source: ICAO and IATA
2
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 NextGen Technologies in Limiting Air Traffic Interactions
3
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 NextGen Technologies in Limiting Air Traffic Interactions
4
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)

Most common definition
• (Ownership basis): A set of airports managed by one individual operator
or authority


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
Often used in the context of future airspace management concepts (by NASA, FAA,
etc.)
5
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
Millions
40
Manchester
Providence
35
30
Passengers
• 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
25
20
15
10
Boston Logan
5
0
1976
* Significant airport: an airport that serves more than 500,000 passengers per year
1981
Boston/Logan
1986
1991
Boston/Providence
1996
2001
2006
Boston/Manchester
6
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 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 NextGen Technologies in Limiting Air Traffic Interactions
8
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
(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
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
• 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
Country
Metropolitan Region
Canada
Canada
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
United States
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
Germany
Germany
Germany
Italy
Italy
Italy
Italy
Italy
Netherlands
Norway
Russia
Spain
Sweden
Sweden
Turkey
United Kingdom
United Kingdom
United Kingdom
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
Brazil
Brazil
Mexico
Buenos Aires
Belo Horizonte
Rio de Janeiro
Sao Paulo
Mexico
Asia-Pacific
Country
Metropolitan Region
Australia
China
China
China
Japan
Japan
South Korea
Thailand
Melbourne
Hong Kong
Shanghai
Taipei
Osaka
Tokyo
Seoul
Bangkok
11
Configurations of Multi-Airport Systems
(i.e. combinations of primary and secondary airports)
Massachusetts Institute of Technology
 Several configurations of
multi-airport systems were
identified


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 models
 Airports used predominantly for cargo activity (without significant passenger
traffic) within or in the vicinity of multi-airport systems
Metropolitan
Country
Region
Cargo (only) airports within Multi-Airport Systems
LGG
EBLG
Brussels
Belgium
AFW
KAFW Dallas
United States
IATA Code ICAO Code
Airport Name
Total Freight in 2005
(metric tons)
325,712
220,134
52
33
1,639,323
37,670
78
83
Brussels/Liege
Dallas/Alliance
Cargo (only) airports in the vicinity of Multi-Airport Systems (beyond 60 miles)
RFD
KRFD
Chicago
United States
Chicago/Rockford
XCR
LFOK
Paris
France
Paris/Vatry
Distance from the center of
metropolitan region (miles)
 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 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 NextGen Technologies in Limiting Air Traffic Interactions
14
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).
Single-airport
system
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
 Frequency of occurrence of mechanisms that govern the evolution of multiairport systems across world-regions
Europe
North America
19%
19%
Middle-East
81%
81%
50
%
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 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)
Number of airports
30
20
Closed Airport
Original Airport
Construction New Airport
10
Emergence Existing
Airport
0
0
5
10
15
20
25
30
35
40
45
Distance from city center (in miles)
50
55
60
17
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 Airports
 Capacity and Access Constraints
• Airport physical constraints (e.g. runways
too short)

e.g. Belfast, Buenos Aires, Rio de Janeiro
• Capacity constraints due to limited
expansion capabilities

e.g. New York/LaGuardia, San
Francisco/International, Paris/Orly,
Bangkok/Don Mueang, etc.
• Massive infrastructure investment
requirements -> High marginal capacity
cost

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.
Percentage of delayed operations in 2000
0%
Boston/Logan
Boston/Manchester
Boston/Providence
5%
6.3%
1.2%
2.4%
0.4%
2.8%
0.3%
Los Angeles/Intl
Los Angeles/Santa Ana
Los Angeles/Ontario
Los Angeles/Burbank
Los Angeles/Long Beach
0.5%
0.1%
0.1%
0.0%
2.2%
1.1%
0.4%
15.0%
New York/LaGuardia
New York/Newark
New York/Kennedy
New York/Islip
0.1%
Norfolk/Intl
Norfolk/News Williamsburg
0.1%
0.0%
Orlando/Intl
Orlando/Sanford
0.0%
San Francisco/Intl
San Francisco/Oakland
San Francisco/San Jose
Tampa/Intl
Tampa/Sarasota
Tampa/St Petersburg
Washington/Dulles
Washington/Reagan
Washington/Baltimore
20%
4.7%
Houston/Intercontinental
Houston/Hobby
Miami/Intl
Miami/Fort Lauderdale
15%
0.3%
0.2%
Chicago/O'Hare
Chicago/Midway
Dallas/Fort Worth
Dallas/Love Field
10%
8.1%
3.8%
0.6%
5.7%
0.2%
0.6%
0.2%
0.0%
0.0%
1.9%
0.8%
0.7%
Primary airports
Secondary airports
19
Massachusetts Institute of Technology
Entry of Low-Cost Carriers Stimulates Demand
and Growth at Secondary Airports
Millions
30
25
8
6
20
Passengers
Passengers
Millions
 “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).
15
10
Entry of Southwest
(1998)
Boston/Providence
Entry of Southwest
(1996)
4
Boston/
Manchester
2
5
0
1975
1985
Boston/Logan
1995
2005
Boston/Providence
0
1990
1995
2000
2005
Boston/Manchester
20
Stimulation of Demand by Low-Cost Carriers
(i.e. Low-Fare Airlines)
Massachusetts Institute of Technology
 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)
0.24
0.24
0.22
PVD
Average Yield at the airport level
($ per flown miles) adjusted to 2003
Average Yield at the airport level
($ per flown miles) adjusted to 2003
Entry of Southwest
MHT
0.2
0.18
0.16
0.14
Boston Logan BOS
Manchester MHT
0.12
Providence PVD
1994
1995
Providence PVD
0.2
0.18
0.16
0.14
0.12
0.1
0.1
1993
Manchester MHT
0.22
1996
1997
1998
1999
2000
0
500000
1000000
1500000
2000000
Annual traffic (enplanem ents)
2500000
3000000
21
Dynamics of Low-Cost Carrier Emergence at
Secondary Airports Not Specific to the U.S.
Massachusetts Institute of Technology
60
Millions
Millions
 Case of Frankfurt/Hahn (entry of Ryanair)
50
5
4
Frankfurt/Hahn
Passengers
Passengers
40
30
20
10
3
2
1
0
1975
1985
1995
Frankfurt/Main
Entry of Ryanair
(1999)
0
2005
1990
Frankfurt/Hahn
1995
2000
2005
Millions
 Case of Dubai/Sharjah (entry of Air Arabia)
35
30
Passengers
25
20
Entry of Air Arabia
(2003)
15
10
5
0
1970
1975
1980
Dubai/Intl
1985
1990
1995
2000
2005
2010
Dubai/Sharjah
22
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 - Jet2.com (base in 2005)
BTS - SkyEurope (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 - Jet2.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 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:



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 1st 2004 to September 30th 2005.
“Parallel network”
24
Massachusetts Institute of Technology
Variations across Low-Cost Carrier Business
Model & Evolution
 Range of strategies and business
models used by 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/LaGuardia,
Boston/Logan, etc.
-> Becoming a major network airlines
after reaching a critical mass network
Distribution of traffic (flight departures and arrivals)
between primary and secondary airports for the top 30
low-cost carriers
Airline name
Ryanair
SkyEurope
ATA Airlines
Southwest Airlines
Transavia Airlines
easyJet Airline
Jet2.com
Frontier Airlines
America West Airlines
Air Berlin
jetBlue Airways
WestJet
Flybe British
Norwegian Air Shuttle
germanwings
AirTran Airways
dba
Independence Air
Spirit Airlines
bmibaby
Virgin Express
Meridiana
Gol Transportes Aereos
Virgin Blue
Maersk Air
Lion Airlines
Bangkok Airways
AVIACSA
Transasia
Flynordic
Percent Operations at
Primary Airports
5%
30%
38%
47%
59%
61%
68%
75%
75%
83%
87%
89%
89%
90%
92%
92%
93%
95%
95%
96%
98%
99%
100%
100%
100%
100%
100%
100%
100%
100%
Percent Operations at
Secondary Airports
95%
70%
62%
53%
41%
39%
32%
25%
25%
17%
13%
11%
11%
10%
8%
8%
7%
5%
5%
4%
2%
1%
0%
0%
0%
0%
0%
0%
0%
0%
* Data source: The Official Airline Guide (OAG), data from Oct 1st 2004 to Sept 30th 2005, traffic measured in number departures and arrivals.
25
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 NextGen Technologies in Limiting Air Traffic Interactions
26
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
1960s
- 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 1990s
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 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 and
Future Airport Infrastructure Adequacy
 Future demand for air
transportation will be led
by countries such as India
and China
8
India
9
7
5
China
6
0
Austria
Australia
Cyprus
United States
Finland
Canada
Greece
Malta
U.K.
Czech Rep
France
Europe
Luxembourg
Singapore
Belgium
Germany
Portugal
Ireland
Hungary
South Africa
Brazil
Spain
1
Netherlands
2
Italy
3
Japan
4
Poland
*Data source: ICAO Journal 2006,
& CIA Handbook database 2005
Population / # Airports
(with runways longer than 5000ft)
• 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
Millions
 Future adequacy of airport
infrastructure:
29
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 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/2nd airport
Madrid/Don Quijote
Las Vegas/Ivanpah
New Delhi/Jewar
Mumbai/Navi
Legend
Hyderabad/Intl
Bangalore/Intl
Manila/SubicBay & 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
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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
Massachusetts Institute of Technology
Strategies for Enabling the Future Development
of Multi-Airport Systems
 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
(1) Land banking strategies
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
Existing
single-airport
system or
multi-airport
system
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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;



(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 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 NextGen Technologies in Limiting Air Traffic Interactions
35
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. 22L – TEB Dep. 24)
Teterboro
Teterboro
LaGuardia
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 Paths within the NY Metroplex
Massachusetts Institute of Technology
(EWR Arr. 22L - LGA Arr. 13 - TEB Arr. 19)
Teterboro
LaGuardia
Newark
*Flight track data courtesy of Leo Prusak and NYNJ Port Authority
LAGUARDIA AREA - Standard Operating Procedure Manual
“LGA ILS RWY l3 approach:
When EWR is using RWY 22L/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
 Data
• Source: FAA Aviation System Performance Metrics (ASPM) based on ETMS and ARINC
information
• Cross sectional and time series analyses using:

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
• LaGuardia (LGA), Newark (EWR), JF Kennedy (JFK), Teterboro (TEB)
 Methodology:
• Data was filtered to retain stable airport configurations


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 of Technology
Capacity from Coupled Metroplex Operations and the Sum of
Capacity from Decoupled* Airport Operations)
Illustration with configuration: LGA 22 | 31 -- EWR 22L | 22R -- JFK 22L | 22R, 31L -- TEB 19 | 24
CPs for Individual Airports
Metroplex Capacity Profile (CP)
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
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
• 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 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 14th 2007.
http://ardent.mit.edu/airports/ASP_exercises/ASP%20matl%20for%20posting%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 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. (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
and 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%20Dynamics.pdf
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Massachusetts Institute of Technology
Questions
&
Comments
44