LaGuardia Airport Systems
Operations Study:
Impact of Airport System Operations in the
Presence of Airline Aircraft Upguaging
Dec 2, 2005
June, 6 2007
July 20 2007
Prepared By:
Lance Sherry (Ph.D.), Liya Wang (Ph.D.),
Melanie Larson (MSc Candidate), Sasha Klein (Ph.D.),
Jeffrey Wang (Ph.D. Candidate), Terry Thompson
(Metron Aviation)
CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH
Airport “System” Operations
CATSR
Facilities, Procedures, Technology
•Flight Arr/Dep
Schedule
(includes fleet
mix)
2
•Actual Flight
Arr/Dep
Airport
• Discrete Event Sim (TAAM)
• Queueing Model (GreenSim)
Performance (and Equity)
•Seat Capacity, Flight Capacity
•Delays (Taxi-in, Taxi-out, Departure Queue)
• Gate Utilization
• ADOC
• Fuel, Emissions, Noise
•Passenger
Arrival/Depart
ure Schedule
Objective
• Assess the overall impact on “airport system”
performance (e.g. available seats, delays, emissions,
noise)
• in the presence of a nominal high demand schedule (e.g.
total scheduled flights of 1125 between 0700 and 2159
local time)
• with a fleet mix containing increased levels of narrowbodied aircraft and fewer regional jets
• “Airport System” Performance Metrics:
– Pax throughput, Flight Delays, Fuel-burn, Emissions, Noise
3
CATSR
Overall Results
CATSR
1. Airport pax throughput can improved by upguaging
•
Marginal impact on Flight Delays
– under assumptions of capacity limits, schedule “bunching” and
fleet mix
•
Impact on Emissions and Noise
– Not proportional to schedule or delay reduction
– Highly dependent on fleet-mix (engine-type)
2. Future regulations should consider
•
Manage schedule to avoid schedule “peaking”
– Multiple capacities throughout day (buffer for delays from peak
hours)
•
Manage fleet-mix
– Arrival/Departure separation distance determines capacity
– Emissions and Noise impact determined by engine-type
4
Organization
• Study 2.1
• Delays & Gate Utilization
• Discrete Event Simulation (TAAM)
• Study 2.2
• Delays, Fuel, ADOC, Emissions, Noise
• Queueing Simulation (GreenSim)
5
CATSR
LaGuardia Airport Systems Operations Study:
Impact of Airport System Operations in the Presence of Airline Aircraft Upguaging
Phase 2.1 (Delays, Gate Utilization)
CENTER FOR AIR TRANSPORTATION SYSTEMS RESEARCH
Method
CATSR
• Analysis was conducted running simulation experiments
• Used Total Airport & Airspace Modeler (TAAM)
• LGA airport model for TAAM provided to GMU/CATSR by
the PANYNJ and Leigh-Fisher Associates.
• LGA airport model was enhanced to support this study
• Complete set of data files is available to all parties on request.
7
Method - Simulation Scenarios
RWY Config
Day
061404 (ETMS)
22
13
A22/D13
041905 (GRA)
081105 (ETMS)
061404 (ETMS)
31
A22/D31
041905 (GRA)
081105 (ETMS)
8
Fleet mix
Baseline
12% less RJs
25% less RJs
Baseline
Upgauged
Upg (757s to A321s)
Baseline
12% less RJs
25% less RJs
Baseline
12% less RJs
25% less RJs
Baseline
Upgauged
Upg (757s to A321s)
Baseline
12% less RJs
25% less RJs
CATSR
CATSR
9
CATSR
10
Summary of Results (a)
Run
Config
Number
of
Schedule Flights
in
TAAM
Fleet Mix
CATSR
Total
Avg
Avg
Est'd
Available Seats Annual Pax Delay
Seats
per
per
excluding
GA
per Day Flight
Flight
Avg Average
Delay Standoff
per Time per
Seat
Flight
Est'd
PeakCarriers Most
Time
Affected by
Gate
Gate Shortages
Shortage
Minutes
1
2
3
4
5
6
ETMS
6/14/2004
(filled to
75 ops/hr)
A22/D13
(Peak
sustained GRA 0419
AAR/ADR
= 39.5)
1206
Baseline
111279
92
24,795,807
16.0
15.4
0.9
1
None
1208
12% RJ to NB
114456
95
25,461,499
17.8
17.6
0.9
1
None
1208
25% RJ to NB
118192
98
26,292,597
16.9
16.8
0.7
1
None
1178
Baseline
113142
96
25,810,172
11.4
10.5
1.0
1
None
1190
Upgauged
135165
114
30,523,169
15.2
14.9
1.5
2
COM, EGF, USA
Upg, 757to321 133075
112
30,051,202
13.0
12.9
1.6
2
COM, EGF, USA
1190
1222
Baseline
113851
93
25,036,751
19.0
17.8
2.6
4
USExp, COM
1222
12% RJ to NB
117305
96
25,796,314
17.5
16.6
2.7
4
USExp,EGF,COM
1222
25% RJ to NB
122567
100
26,953,470
18.6
18.0
2.6
4
USExp,EGF,COM
1206
Baseline
111279
92
24,795,807
23.5
22.4
1.7
2
COM, EGF
1208
12% RJ to NB
114456
95
25,461,499
25.1
23.8
1.5
2
COM, EGF
A22/D31
13
(Peak
14 sustained GRA 0419
AAR/ADR
15
= 38)
1208
25% RJ to NB
118192
98
26,292,597
27.0
26.1
2.2
3
COM, EGF
1178
Baseline
113142
96
25,810,172
16.0
14.2
0.9
1
None
1190
Upgauged
135165
114
30,523,169
23.0
21.8
2.5
4
COM, EGF, USA
Upg, 757to321 133075
112
30,051,202
21.2
20.0
2.5
3
COM, USA, EGF
16
1222
Baseline
113851
93
25,036,751
27.8
25.1
3.0
4
USExp,EGF,COM
1222
12% RJ to NB
117305
96
25,796,314
27.3
25.0
2.9
4
USExp,EGF,COM
1222
25% RJ to NB
122567
100
26,953,470
24.8
22.7
2.4
3
USExp,EGF,COM
7
8
ETMS
8/11/2005
9
10
11
12
1711
18
ETMS
6/14/2004
(filled to
75 ops/hr)
ETMS
8/11/2005
1190
Summary of Results (b)
Run
Config
Number
of
Schedule Flights
in
TAAM
Fleet Mix
CATSR
Total
Avg
Avg
Est'd
Available Seats Annual Pax Delay
Seats
per
per
excluding
GA
per Day Flight
Flight
Avg Average
Delay Standoff
per Time per
Seat
Flight
Est'd
PeakCarriers Most
Time
Affected by
Gate
Gate Shortages
Shortage
Minutes
1
2
3
4
5
6
ETMS
6/14/2004
(filled to
75 ops/hr)
A22/D13
(Peak
sustained GRA 0419
AAR/ADR
= 39.5)
1206
Baseline
111279
92
24,795,807
16.0
15.4
0.9
1
None
1208
12% RJ to NB
114456
95
25,461,499
17.8
17.6
0.9
1
None
1208
25% RJ to NB
118192
98
26,292,597
16.9
16.8
0.7
1
None
1178
Baseline
113142
96
25,810,172
11.4
10.5
1.0
1
None
1190
Upgauged
135165
114
30,523,169
15.2
14.9
1.5
2
COM, EGF, USA
Upg, 757to321 133075
112
30,051,202
13.0
12.9
1.6
2
COM, EGF, USA
1190
1222
Baseline
113851
93
25,036,751
19.0
17.8
2.6
4
USExp, COM
1222
12% RJ to NB
117305
96
25,796,314
17.5
16.6
2.7
4
USExp,EGF,COM
1222
25% RJ to NB
122567
100
26,953,470
18.6
18.0
2.6
4
USExp,EGF,COM
1206
Baseline
111279
92
24,795,807
23.5
22.4
1.7
2
COM, EGF
1208
12% RJ to NB
114456
95
25,461,499
25.1
23.8
1.5
2
COM, EGF
A22/D31
13
(Peak
14 sustained GRA 0419
AAR/ADR
15
= 38)
1208
25% RJ to NB
118192
98
26,292,597
27.0
26.1
2.2
3
COM, EGF
1178
Baseline
113142
96
25,810,172
16.0
14.2
0.9
1
None
1190
Upgauged
135165
114
30,523,169
23.0
21.8
2.5
4
COM, EGF, USA
Upg, 757to321 133075
112
30,051,202
21.2
20.0
2.5
3
COM, USA, EGF
16
1222
Baseline
113851
93
25,036,751
27.8
25.1
3.0
4
USExp,EGF,COM
1222
12% RJ to NB
117305
96
25,796,314
27.3
25.0
2.9
4
USExp,EGF,COM
1222
25% RJ to NB
122567
100
26,953,470
24.8
22.7
2.4
3
USExp,EGF,COM
7
8
ETMS
8/11/2005
9
10
11
12
1712
18
ETMS
6/14/2004
(filled to
75 ops/hr)
ETMS
8/11/2005
1190
Gate Activity (TAAM Simulation) - excerpt
Example: A22/D13, 04/19 (GRA) Upgauged
6 am
gtCTBA02
gtCTBA03
gtCTBA04
gtCTBA05
gtCTBA06
gtCTBA07
gtCTBB01
gtCTBB02
gtCTBB03
gtCTBB04
gtCTBB05
gtCTBB06
gtCTBC01
gtCTBC03
gtCTBC04
gtCTBC05
gtCTBC08
gtCTBC09
gtCTBC10
gtCTBC11
gtCTBC12
gtCTBD01
gtCTBD02
gtCTBD03
gtCTBD04
gtCTBD05
gtCTBD06
gtCTBD07
gtCTBD08
13
gtCTBD09
. . . . . . . . . . . .
COA
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ACA
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MDW
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ATA/FFT
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Spirit, JBU
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AAL/EGF
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UAL
TAAM
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Average Delay & Standoff Time / Flight
06/14/04 Sample (ETMS)
CATSR
A22/D31, 0614 (2004)
30.0
Avg Delay / Flight, mins
Avg Standoff Time / Flight
25.0
15.0
2.0
10.0
1.0
5.0
0.0
0.0
Baseline
12% RJ to NB 25% RJ to NB
4.0
3.0
15.0
2.0
10.0
1.0
5.0
0.0
0.0
Baseline
12% RJ to NB
Runway configuration, impacts taxiway, and
gate utilization
14
5.0
20.0
Delay
3.0
Standoff Time
Delay
25.0
4.0
20.0
Avg Delay / Flight, mins
Avg Standoff Time / Flight
30.0
5.0
25% RJ to NB
Standoff Time
A22/D13, 0614 (2004)
Average Delay & Standoff Time / Flight
04/19 Sample (GRA)
CATSR
A22/D31, 04/19 (GRA 2005)
Avg Delay / Flight, mins
Avg Standoff Time / Flight
30.0
25.0
2.0
10.0
1.0
5.0
0.0
0.0
Baseline
Upgauged
Upg, 757to321
4.0
3.0
15.0
2.0
10.0
1.0
5.0
0.0
0.0
Baseline
Upgauged
Upg, 757to321
Runway configuration and Fleet-mix, impacts
taxiway, and gate utilization
15
5.0
20.0
Delay
15.0
Standoff Time
Delay
3.0
Avg Standoff Time / Flight
25.0
4.0
20.0
Avg Delay / Flight, mins
30.0
5.0
Standoff Time
A22/D13, 04/19 (GRA 2005)
00
22
4::0
00
23 0
5::0
000
06:
:000
0
7:
00
8:
00
9:
00
10
:0
0
11
:0
0
12
:0
0
13
:0
0
14
:0
0
15
:0
0
16
:0
0
17
:0
0
18
:0
0
19
:0
0
20
:0
0
21
:0
0
22
:0
0
23
:0
0
20
00
00
00
00
00
00
00
00
Demand - Base
21
:
20
:
19
:
18
:
17
:
16
:
15
:
14
:
00
11
45
13
:
00
00
00
00
00
:0
0
:0
0
12
:0
0
13
:0
0
14
:0
0
15
:0
0
16
:0
0
17
:0
0
18
:0
0
19
:0
0
20
:0
0
21
4: :00
2200
5: :00
2300
6: :00
0
0: 0
7: 00
00
8:
00
9:
00
10
:0
0
11
:0
0
12
:0
0
13
:0
0
14
:0
0
15
:0
0
16
:0
0
17
:0
0
18
:0
0
19
:0
0
20
:0
0
21
:0
0
22
:0
0
23
:0
0
10
9:
8:
7:
00
00
70000
0
12
:
00
0
0
0
0
6:
5:
25
11
:
10
:
9:
0
8:
0
7:
0
6:
0
0
0
4:
60000
5:
0
4:
0
Understanding Differences in Delays
04/19 (GRA) Timetable, Baseline vs. Upgauged
50
50
ARR
DEP
45
40
40
35
35
30
30
25
Delay / Flight
20
15
10
80000
5
5
70000
Delays - Base
0
60000
0
16
Delays - Upgauged
50000
50000
40000
40000
30000
30000
20000
20000
10000
10000
CATSR
ARR
DEP
Demand - Upgauged
15
80000
10
Standoff (secs)
Gate (secs)
Taxiway (secs)
Sequencing (secs)
Runway (secs)
0
Randomized Simulations
20 Runs per scenario (ATD, acft perf randomized)
At congested airports like LGA, small
variations in traffic demand or
throughput can lead to large
fluctuations in delays
LGA Movements
Example for 04/19 schedule,
upgauged, A22/D31 runway
configuration, is shown
17
LGA Delays
CATSR
Effect of Randomization on Delays
CATSR
LGA Avg Delay Per Flight - Six Randomized Multi-Runs (20 Iterations Each)
Primary parameter randomized is departure time
35.0
A22/D31
Delay per flight, minutes
30.0
25.0
A22D13 Base
A22D13 Upgauged
A22D13 757to321
A22D31 Base
A22D31 Upgauged
A22D31 757to321
20.0
15.0
10.0
5.0
0.0
A22/D13
•below airport average
•lower variability
1
2
3
4
5
6
7
8
9
10 11 12 13 14 15 16 17 18 19 20
Run #
•Average Delay Per Flight for 20 Randomized TAAM Runs for
the 6 (04/19, GRA) Cases
18•Comparison with actual data: average delay/flight at LGA was
19.5 min in Aug 2005
Average Delay & Standoff Time / Flight
08/11/05 Sample (ETMS)
CATSR
A22/D13, 08/11 (2005)
25.0
15.0
2.0
10.0
1.0
5.0
0.0
0.0
Baseline
12% RJ to NB 25% RJ to NB
5.0
4.0
20.0
Delay
Delay
3.0
19
25.0
4.0
20.0
Avg Delay / Flight, mins
Avg Standoff Time / Flight
30.0
5.0
3.0
15.0
2.0
10.0
1.0
5.0
0.0
0.0
Baseline
12% RJ to NB
25% RJ to NB
Standoff Time
Avg Delay / Flight, mins
Avg Standoff Time / Flight
Stoandoff Time
30.0
A22/D31, 08/11 (2005)
Summary of Results (Delays)
CATSR
Upgauging could raise LGA’s annual Pax throughput
by about 3-4M
• Equivalent to increase of about 15-20 seats per aircraft (9296 to 110-114)
Moderate upgauging does not lead to increased
delays
• And, gate utilization would improve slightly
More aggressive upgauging may lead to some
increase in delays
• Could be mitigated in part if 757s were replaced by B737900, A321
• Could also be mitigated by better scheduling of flights
20
Summary Results (Gates)
At peak-demand times, LGA can be short of about
3-4 gates
• Gate shortages are highly “local” (carrier and time specific)
• Some un-used gates are always present, even at peakdemand times
Some carriers appear to have occasional
overscheduling issues
• Comair, American Eagle, USAirways Express
21
CATSR
LaGuardia Airport Systems Operations Study:
Impact of Airport System Operations in the Presence of Airline Aircraft Upguaging
CATSR
Phase 2.2 (Fuel, Emissions, Noise)
22
Airport Queueing Model
CATSR
λA
G / G / ∞ / ∞ / FCFS
G / G / ∞ / ∞ / FCFS
µ AR
µ AT
µ DR
µ DT
λD
23
G / G / 1 / ∞ / FCFS
G / G / ∞ / ∞ / FCFS
Functional Block Diagram
24
CATSR
Design of Experiment
•
3 Scenarios
1. ETMS Schedule (4/19/2005 - Baseline)
2. GRA Schedule (Upguage, no frequency
reduction)
3. Max Efficiency (Upguage with frequency
reduction)
25
•
A22/D13
•
Used average of 500 replications
CATSR
Results – Schedule & Capacity
CATSR
Baseline
Upguage, No Frequency
Reduction (GRA)
% Change
Upguage with
Frequency
Reduction
% Change
Daily Arrival
Demand
597
597
0.0%
492
-17.6%
Departure
Demand/day
597
597
0.0%
492
-17.6%
Hourly Arrival
Demand
35
35
0.0%
29
-17.6%
Hourly
Departure
Demand
35
35
0.0%
29
-17.6%
Total Arrival
Seats
57401
68362
19.1%
58150
1.3%
Total
Departure
Seats
57401
68459
19.3%
58153
1.3%
Total Seats
114802
136821
19.2%
116303
1.3%
96
114
18.8%
118
22.9%
AvgSeats/fligh
t
26
Results - Delays
CATSR
Baseline
Upguage, No
Frequency
Reduction (GRA)
% Change
Upguage with
Frequency Reduction
% Change
Taxi-in (mean, stdEV)
(6.9, 3.6)
(7.0, 3.6)
--
(6.8, 3.4)
--
Taxi-out (mean, stdEV)
(18.9, 5.8)
(19.4, 6.1)
--
(17.8, 4.9)
--
Total Taxi-in Delays
(min)
1430.62
1450.48
1.4%
1109.45
Average Taxi-in
Delays (min)
2.40
2.43
1.4%
2.25
Total Taxi-out Delays
(min)
4327.11
4586.87
6%
3016.27
Average Taxi-out
Delays (min)
7.25
7.68
6%
6.13
Total Delay (min)
5757.73
6037.35
4.9%
4125.72
-28.3%
Maximum Queue Size
10.00
11.00
10%
9.00
-10.0%
Mean Queue Size
2.17
2.42
11%
1.23
-43.3%
Mean Queue Time(min)
2.49
2.77
11%
1.71
-31.3%
27
Note: Airport only taxi & gate), not include arrival delays
-22.4%
-6.2%
-30.3%
-15.4%
Results – Fuel & Emissions
% Chg
Baseline
Upguage, No Frequency
Reduction (GRA)
Fuel(ton)
158.1
185.9
17.6%
CO(kg)
3733.3
4032.2
8.0%
HC(kg)
465.2
433.7
-6.8%
NOx(kg)
642.7
776.3
20.8%
SOx(kg)
158.1
185.9
17.6%
4999.3
5428.1
8.6%
TotalEm(kg)
28
Upguage with
Frequency
Reduction
152.0
3700.5
449.5
588.1
152.0
4890.1
CATSR
% Chg
-3.9%
-0.9%
-3.4%
-8.5%
-3.9%
-2.2%
% Change from Baseline
Results - Summary
30
19
20
10
1
CATSR
17.6
1
20.8
8.1
4.9
0
-10
-20
-30
Arrivals
Seats
Delays
(mins)
Fuel
-3.9
Emissions
-8.5
(Nox)
-17.6
-28.3
-40
Upgauge, no Frequency Reduction
Upguage with Frequency Reduction
29
ADOC
-25.3
Results – NOx & Fleet Mix
“Type I”
300
Avg Seats per Aircraft
CATSR
A300-600
250
“Type II”
B767-400
“Type III”
A321
200
150
B717
E190
100
F100
B737-500
50
E170
B190
CRJ7
DH8A
SF34
0
0
20
40
60
80
100
120
140
160
NOx/FuelBurn
30
Migrating
to “Cat I” has Positive Emissions Implications
Results – Taxi NOx Rate & Fleet Mix
CATSR
NOx Production Rate As Function of Number of Seats
NO x P roduction Ra te (g/m in)
2,50
Worse than average
B767-400
2,00
B727-200
1,50
A320
B717-200
B757-200
B737-700
1,00
CRJ-700
SF-340
0
50
B767-200
MD-80
A319
0,50
0,00
Better than average
F100
100
150
200
250
Number of Seats
Given choice of delaying one of two aircarft,
pick the one with more NOx per passengers.
31
A300-600
300
Noise Effects
CATSR
• DNL measure of noise
– Dosage to population centers in
region
– FAA regional noise model
– Used in NYNJPHL airspace
project
Arrival (22) and Departure (13)
Tracks
32
• Portion of each flight distributed
over all annual distribution of
trajectories for A22/D13
DNL Geographic Distributions
Baseline
DNL Values at
Population Centroids
> 65 db
60-65 db
55-60 db
50-55 db
45–50 db
< 45 db
- red
- yellow
- green
- light blue
- dark blue
- magenta
Upguage & Maintain Frequency
33
CATSR
•DNL geographical
distribution around
LGA.
• The circles highlight
one area in which there
was change
– Larger aircraft
low and slow
Upguage & Decrease Frequency
Population Exposure at DNL Levels
CATSR
Population
9000000
Slight changes in
contours (peninsula tips)
8000000
Baseline
7000000
6000000
Upguage/
Maintain
Freq
5000000
4000000
3000000
Upguage/
Reduced
Freq
2000000
1000000
34
>7
0d
B
65
-7
0d
B
60
-6
5d
B
55
-6
0d
B
50
-5
5d
B
45
-5
0d
B
<4
5d
B
0
Population Exposed at Different DNL Levels
(Cont’d)
180000
130000
80000
30000
-20000
Baseline
60-65dB
65-70dB
DNL
Upguage/ Main Freq
>70dB
Augment/Decrease Freq
Total Population at Levels
Above 60 dB DNL
35
CATSR
• Small changes in DNL
levels > 60 dB.
• Changes do not trigger
the standard FAA rules for
« significant impact »
– 1.5dB above 65dB
– Hence, all colored
zones on the
Impact Graph
contain zero
population.
•changes for locations
recieving more than 65 dB
are about 0.5-1.0 dB
Upgauge/Maintain Freq
Impact FAA Significance Criteria
36
CATSR
Sensitivity of Noise Impacts
•
Noise is sensitive to:
1. Night events 21:59 to 7:00
–
Baseline & Upguage Reduce Frequency
•
•
–
597 departures with 551 day and 46 night
597 arrivals with 548 day and 49 night
Upgauge/No Frequency Reduction:
•
•
597 departures with 548 day and 49 night
597 arrivals with 539 day and 58 night
2. Aircraft/engine fleet composition
– Age factor
37
CATSR
Conclusions
•
Upguaging without Frequency change
•
•
Proportional increase in seat capacity
Marginal impact on delays
– Fleet mix (i.e. separation distance)
– Schedule “peaking”
•
Proportional increase in fuel-burn & ADOC
– Derived from fleet mix
•
Proportional increase in Emissions (NOx)
– Fleet mix (i.e. engine-type)
•
•
Little impact on noise
Upguaging with Frequency Reduction
•
•
•
Maintain seat capacity
Significant reduction in delays
Reduced fuel burn and ADOC
– Derived from delays
•
Marginal reduction in fuel-burn
– Dependent on fleet-mix
•
38
Maintains noise contours
CATSR
Conclusions
CATSR
• Airport pax throughput improved by upguaging
• Marginal impact on delays
– under assumptions of capacity limits, schedule “peaking” and fleet
mix
• Impact on Emissions and Noise not proportional to
schedule or delay reduction
– Highly dependent on fleet-mix (engine-type)
• Future regulations should consider
– Multiple capacities throughout day (buffer for delays from peak
periods)
– Emissions and Noise by fleet mix
39