World Air Transport
Sustainability Analysis
Dr. Terence R. Thompson
April, 2012
Problem Statement
Develop a quantitative model to assess the carbon footprint of
world aviation, including the following major factors:
•
•
Improvements in operations
•
Improvements in engine/airframe technology
•
Use of alternative fuels
•
Economic measures
2
DEMAND
3
Demand – World Aggregate
World-wide demand projected to increase substantially:
Overall 2010-2030 increase estimated by Airbus to be from ~5 to ~12.7 trillion RPKs.
Source: Airbus Global Market Forecast 2011-2031.
4
Demand – Inter-regional Flows
Growth is not uniform world-wide.
Source: Airbus Global Market Forecast 2011-2031.
5
Demand – Price Elasticity
Demand depends on price: D2/D1 = (P2/P1)^E, where D is demand, P is price,
and E is elasticity.
Different market segments have different elasticities. For example, business, leisure,
and personal matters have been estimated to have elasticities of ‑0.71, ‑1.22, and
‑0.96. Overall elasticity can be derived from such values coupled with demand
fractions for these categories (for example, 0.43, 0.47, and 0.10)*.
* Schafer, et al, 2009, pp.97,289; Gillen, 2008).
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Demand – Cost Per Unit Delivered
Unit cost has been declining, but is projected to decline at a slower rate:
Non-fuel costs continue decline, but fuel cost rises (modestly).
Source: Airbus Global Market Forecast 2011-2031.
7
OPERATIONAL IMPROVEMENTS
8
Fuel Benefits of Operational Improvements
Future schedule(s)
Schedule analysis
Estimates of excess time
by phase of flight (minutes)
Fuel rates for representative
aircraft by phase of flight
(kg/min)
Percentage of flights for N
aircraft categories;
Estimated total fuel
Fuel savings benefit
pool [kg fuel]
Fraction of fuel saved by
phase of flight across aircraft
categories
Estimates of difficulty of
implementation of operational
initiatives by phase of flight
Quantification of difficult and
partition of fuel benefit within
Improvement class
Benefit pool by phase of
flight [% improvement]
Estimated attainment of
fuel savings over time
[% improvement/yr]
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Overall Attainment of Fuel Benefits
• Initial net attainment of 6.6% improvement distributed as follows:
• ~0.72%/yr in years 2010-17
• ~0.20%/yr in years 2018-21
• ~0.10%/yr in years 2022-25
• 6.6% is the estimated net benefit that accumulates over the 15-year
span of implementation; nearly all of this is attained by 2020.
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ENGINE/AIRFRAME TECHNOLOGY
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Engine/Airframe Technology – Data Required
•
For each major technology level, performance and insertion into
future use. For example:
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NASA Technology Goals
CORNERS OF THE
TRADE SPACE
N+1 = 2015***
Technology Benefits Relative
To a Single Aisle Reference
Configuration
N+2 = 2020***
Technology Benefits Relative
To a Large Twin Aisle
Reference Configuration
N+3 = 2025***
Technology Benefits
Noise
(cum below Stage 4)‫‏‬
-32 dB
-42 dB
-71 dB
LTO NOx Emissions
(below CAEP 6)‫‏‬
-60%
-75%
better than -75%
Performance:
Aircraft Fuel Burn
-33%**
-50%**
better than -70%
-33%
-50%
exploit metro-plex* concepts
Performance:
Field Length
*** Technology Readiness Level for key technologies = 4-6
** RECENTLY UPDATED. Additional gains may be possible through operational improvements
* Concepts that enable optimal use of runways at multiple airports within the metropolitan area
N+3 emissions and fuel benefits were modelled as -80% and -75% respectively
Source:
http://www.aeronautics.nasa.gov/calendar/era_preconference_synopsis.htm
13
ALTERNATIVE FUELS
14
Alternative Fuels – Data Required
•
For each major pathway, we require life-cycle CO2 footprint and
fraction of total fuel provided in future. For example:
Fuel type
Relative
GHG
Intensity
Relative
SOx
Intensity
Relative
PM
Intensity
1.0
1.0
1.0
1.0
1.02a
0.02
0.8
Alternative
fuel 1 (coal &
biomass)
0.9
0.01
Alternative
fuel 2
(Hydrotreated
renewable jet
(HRJ) fuel)
0.6
0.01
Current
ULSJ
petroleum
based
Relative 2010
HC/VOC Usage
Intensity
2020
Usage
2030
Usage
2040
Usage
2050
Usage
95%
0%
0%
0%
0%
1.0
5%
87%
79%
69%
60%
0.25
1.0
-
2%
5%
10%
15%
0.25
1.0
-
11%
16%
21%
25%
1
0.97
0.95
0.92
0.9
Overall GHG
Intensity
a) Based on initial indications that ULS petroleum-based fuels will have a larger total life-cycle GHG intensity than conventional petroleumbased fuels [Hileman, et al. 2009b].
15
Alternative Fuels – Net Effects
NCF = Σi ( fi * ci )
16
ECONOMIC MEASURES
17
Economic Measures – Key Aspects
Taxes
Possible effects: demand, changes in insertion rates of new vehicles, adoption of
alternative fuels, and operational improvements.
Offsets
Possible effects: credits against CO2 emissions
Tradeable Permits
Possible effects: demand, changes in insertion rates of new vehicles, adoption of
alternative fuels, and operational improvements. (Well-designed permit systems allow
more flexibility than taxes and can achieve reduction goals at lower overall cost.)
Subsidies
Possible effects: changes in insertion rates of new vehicles, adoption of alternative
fuels, and operational improvements.
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INFLUENCE DIAGRAM
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Influence Diagram
Air Transport Demand
Engine/Airframe
Equipage
System Operation
Economic Measures
Aircraft Movement
Alternative Fuel Usage
Fuel Consumed
CO2eq Footprint
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