Environmental and Economic Assessment of Alternative
Transportation Fuels
by
Mitch Russell Withers
B.S. Chemical Engineering, 2012
Brigham Young University
Submitted to the Department of Aeronautics and Astronautics
in partial fulfillment of the requirements for the degree of
Master of Science in Aeronautics and Astronautics
MASSACHUSETTS INTTE.
OF TECHNOLOGY
JUN 16 2014
at the
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
LIBRARIES
June 2014
C Massachusetts Institute of Technology 2014. All rights reserved.
Author ...................
Signature redacted
Department of Aeronautics and Astronautics
May 22, 2012
I /
Certified by ...........
A
3iqnature redacted
V
V
.................. .. . .............................
Steven R.H. Barrett
Assistant Professor of Aeronautics and Astronautics
Signature redacted
Accepted by ..............
.........................................................
Paolo C. Lozano
Associate Professor of Aeronautics and Astronautics
Chair, Graduate Program Committee
2
Environmental and Economic Assessment of Alternative
Transportation Fuels
by
Mitch Russell Withers
Submitted to the Department of Aeronautics and Astronautics on
May 22, 2014 in partial fulfillment of the requirements for the degree of
Master of Science in Aeronautics and Astronautics
Abstract
Alternative fuels have the potential to mitigate transportation's impact on the environment and enhance
energy security. In this work, we investigate two alternative fuels: liquefied natural gas (LNG) as an
aviation fuel, and middle distillate fuel derived from woody biomass for use in aviation or road transport.
The use of LNG as a supplemental aircraft fuel is considered in the context of the Lockheed Martin C130H and C-130J transport aircraft. We estimate the cost of retrofitting these aircraft to use LNG and the
savings from reduced fuel expenses. We evaluate the societal impacts of LNG within a cost-benefit
framework, taking into account resource consumption, human health impacts related to air quality, and
climate damage. We find that aircraft operators can save up to 14% on fuel expenses (retrofit costs
included) by employing LNG retrofits, with a 95% confidence interval of 2-23%. Society can also benefit
by 12% (3-20%) from LNG use as a result of improved surface air quality, lower resource consumption,
and climate neutrality relative to conventional fuel. These results are highly dependent on fuel prices, the
quantity and cost of the LNG retrofits, and the frequency and length of missions.
Woody biomass harvested from old-growth forests produces a large carbon debt when used as a feedstock
for transportation fuel. Managed forests are an attractive alternative for inexpensive biomass production
with the potential to reduce this carbon debt. We study the effect of forest management practices on the
carbon debt payback time resulting from harvesting woody biomass from managed forests for middle
distillate fuel production. We also calculate the breakeven time in terms of radiative forcing, temperature
change, and economic damages. We find that biofuels produced over a period of 30 years have higher
CO 2 emissions than fossil fuels for 59 years, higher radiative forcing for 42 years, higher temperature
change for 48 years, and higher cumulative discounted (1-2%) economic damages for more than 100
years. These damages never break even at discount rates above 2%. Payback times can be reduced by
increasing the age at which biomass is harvested. When biofuel production is sustained indefinitely,
greater climate benefits are achieved over the next 100 years by instead producing long-lived wood
products like lumber.
Thesis Supervisor: Steven R.H. Barrett
Title: Assistant Professor of Aeronautics and Astronautics
3
Acknowledgements
I would like to appreciate the following individuals and organizations for their assistance and support.
First, Dr. Steven Barrett, Dr. Robert Malina, Mr. Philip Wolfe, and Mr. Christopher Gilmore for their
assistance and feedback in preparing this work. BP and Lockheed Martin for their financial support of this
research. Mr. Jonathan Gibbs and Mr. Chris Trigg for their contributions to the analysis of liquefied
natural gas. Finally, to Jessica, for giving me hope and courage in the face of struggle and hardship.
4
Table of Contents
A bstra ct ........................................................................................................................................................ 3
Acknow ledgem ents ..................................................................................................................................... 4
Table of Contents ........................................................................................................................................ 5
List of Figures .............................................................................................................................................. 7
List of Tables ............................................................................................................................................... 9
1 Introduction ............................................................................................................................................ 11
2 Liquefied Natural G as as an Alternative Aviation Fuel ..................................................................... 12
2.1 Introduction ..................................................................................................................................... 12
2.1.1 Drop-in Fuels ............................................................................................................................ 12
2.1.2 Electric Propulsion ................................................................................................................... 13
2.1.3 Cryogenic Fuels ........................................................................................................................ 13
2.2 M ethods ............................................................................................................................................ 15
2.2.1 Aircraft Retrofit Design and Evaluation ................................................................................ 15
2.2.2 Cost Estim ation ........................................................................................................................ 21
2.2.3 Environm ental M odeling ......................................................................................................... 29
2.3 Results .............................................................................................................................................. 35
2.3.1 O perator Case .......................................................................................................................... 35
2.3.2 Societal Case ............................................................................................................................. 40
2.4 Conclusion ....................................................................................................................................... 46
3 M iddle Distillate Fuel from W oody Biom ass ....................................................................................... 47
3.1 Introduction ..................................................................................................................................... 47
3.2 M ethods ............................................................................................................................................ 48
3.2.1 Forest Carbon M odel ............................................................................................................... 48
3.2.2 Clim ate Im pact M odel ............................................................................................................. 50
3.3 Results .............................................................................................................................................. 50
3.3.1 Breakeven Tim e........................................................................................................................ 50
3.3.2 Harvest Age .............................................................................................................................. 53
3.3.3 W ood Products & O peration Tim e ........................................................................................ 53
3.4 Conclusion ....................................................................................................................................... 54
4 Conclusion .............................................................................................................................................. 55
5 References ............................................................................................................................................... 56
6
List of Figures
Figure 2-1: Hybrid aircraft configuration with two engines modified to burn either natural gas or jet fuel.
....................................................................................................................................................................
15
Figure 2-2: LN G fuel delivery schem atic. ............................................................................................
18
Figure 2-3: Minimum selling price of C-130H and C-130J LNG retrofits as a function of the number of
24
aircraft retro fitted ........................................................................................................................................
Figure 2-4: Projections for natural gas and jet fuel spot prices in the US, from EIA history and
projections [46]. Thin lines indicate EIA low and high oil price scenarios...........................................25
Figure 2-5: LNG supply pathways considered in well-to-tank greenhouse gas analysis.......................32
Figure 2-6: Mean operator savings relative to conventional jet fuel for LNG and FT cases for both
aircraft types as a function of fuel burn. LNG case assumes 10 retrofitted aircraft are operated at 70%
37
utilization. Error bars represent 95% confidence intervals. ....................................................................
Figure 2-7: Operator savings relative to conventional jet fuel for LNG and FT cases for both aircraft
types as a function of mission fuel burn. LNG case assumes 45 retrofitted aircraft are operated at 20%
37
utilization. Error bars represent 95% confidence intervals .....................................................................
Figure 2-8: Contours of constant savings as a function of the number of retrofits and the utilization rate,
in black. Shown for the C-130J at 12,000 kg of mission fuel burn. Blue dashed lines show levels of
38
constant FAU (product of utilization rate and number of retrofitted aircraft). .....................................
Figure 2-9: Sensitivity results for LNG aircraft operators for the C-130H for 10 aircraft and 70%
39
u tilizatio n. ...................................................................................................................................................
Figure 2-10: LNG well-to-wake GHG emissions in terms of 100-yr and 20-yr global warming potentials.
41
....................................................................................................................................................................
Figure 2-11: Global temperature changes due to operating C-130H (10-15 years) and C-130J (20-30
42
years) aircraft using conventional jet fuel, LNG, or FT jet fuel. ...........................................................
Figure 2-12: Mean societal benefit relative to conventional jet fuel for LNG and FT cases for both
aircraft types as a function of fuel burn. LNG case assumes 10 retrofitted aircraft are operated at 70%
44
utilization. Error bars represent 95% confidence intervals. ....................................................................
Figure 2-13: Mean societal benefit relative to conventional jet fuel for LNG and FT cases for both
aircraft types as a function of fuel burn. LNG case assumes 45 retrofitted aircraft are operated at 20%
44
utilization. Error bars represent 95% confidence intervals. ....................................................................
Figure 2-14: Societal cost sensitivity results for the C-130H for 45 aircraft and 20% utilization......45
Figure 3-1: (a) Net CO 2 emissions, (b) change in anthropogenic radiative forcing, (c) temperature change,
and (d) economic damages from middle distillate biofuel and equivalent conventional fuel (energy) use.
All plots are normalized relative to the maximum value for biomass over 1000 years..........................51
Figure 3-2: Breakeven times for (a) net C02 emissions, (b) radiative forcing, (c) temperature change, and
52
(d) undiscounted economic damages for different BAU and biomass harvest ages..............................
Figure 3-3: Breakeven times for (a) net C02 emissions, (b) radiative forcing, (c) temperature change, and
(d) undiscounted economic damages as a function of operation time with varying amounts of long-lived
wood products in the BAU forest. BAU harvest age and biomass harvest age are held equal at 30 years. 54
7
8
List of Tables
17
Table 2-1: Material physical properties and calculated tank specifications............................................
Table 2-2: Probability distributions of fuel burn penalties for Monte Carlo analysis............................20
Table 2-3: Representative recurring and non-recurring cost breakdown by parts for a typical commercial
23
aircraft. F rom M arkish [6 1]. .......................................................................................................................
Table 2-4: Cost of retrofitting major C-130 aircraft parts for use with LNG, expressed as a percent of the
work required to design and build a completely new aircraft part.........................................................23
25
Table 2-5: Probability distributions for retrofit price estimation. ..........................................................
Table 2-6: Assumptions used in DCFROR analyses of GTL and liquefaction facilities. Adapted from
26
P earlso n et al. [5 6 ]. .....................................................................................................................................
28
Table 2-7: Probability distributions for fuel price Monte Carlo simulations. ........................................
Table 2-8: Probability distributions of societal fuel costs for Monte Carlo simulations........................29
30
Table 2-9: Probability distributions for air quality health impact calculations. ....................................
Table 2-10: Percent change in emissions from the jet fuel case to LNG and FT cases, independent of
aircraft type. LNG case includes the contribution of 50% jet fuel by energy content. FT case includes the
31
contribution of 50% jet fuel by volume. Emissions included from both LTO and cruise. ............
35
Table 2-11: Probability distributions for APMT climate damage calculations.....................................
Table 2-12: Total societal cost of C-130 operations for a) the 10-aircraft 70% utilization case, and b) the
45-aircraft and 20% utilization case. Fuel and retrofit costs are discounted at 3%, climate costs at 2%, and
air quality health im pacts at 3% ..................................................................................................................
43
Table 3-1: Relevant parameters for carbon cycle model (for details on model application, see Ref. 113).
Growth parameters were fitted to mimic growth rates of Loblolly pine (Pinus taeda) under industrial
9
m anagem ent practices.................................................................................................................................4
9
10
1 Introduction
Transportation fuels predominantly come from petroleum sources, raising concern regarding energy
security, climate change, and degradation of air quality. Alternative transportation fuels have received
considerable attention as a means for diversifying energy supplies and mitigating transportation's impact
on the environment. In this work, liquefied natural gas (LNG) is investigated as a potential alternative fuel
for aviation. Middle distillate fuel derived from Fischer-Tropsch conversion of woody biomass is also
investigated as an alternative fuel for road transportation or aviation.
Apart from demonstration flights using synthetic fuels, jet fuel currently comes exclusively from
petroleum. Jet fuel demand in the United States is projected to increase by 48.7% by 2033 compared to
2012 [1], while worldwide demand is forecasted to increase by 86.0-105.9% [2], which would lead to
increased dependence on petroleum reserves, if no alternative fuels are introduced.
The current contribution of aviation to total anthropogenic radiative forcing is estimated at -5% although
significant uncertainties remain [3,4]. It has also been estimated that aviation emissions result in -10,000
premature mortalities per year globally due to degradation of air quality [5]. Given the expected increase
in air traffic, greenhouse gas emissions and health impacts are expected to increase in the absence of
significant mitigation measures.
In 2013, natural gas is 70-80% cheaper than jet fuel on an energy basis. As an alternative aviation fuel,
natural gas may reduce operating costs. We present the economic and environmental case for liquefied
natural gas (LNG) as a supplemental fuel for military aircraft. We perform a cost-benefit analysis, taking
into account aircraft retrofit costs as well as economic damages due to climate change and air quality
degradation.
Greenhouse gas (GHG) emissions from transportation are expected to cause 10-20% of the global mean
temperature rise over the next century [6]. Alternative transportation fuels produced from biomass
feedstocks have recently received attention as a means of mitigating this climate impact [7,8,9]. Fuels
derived from biomass have the potential to reduce GHG emissions compared to their conventional
counterparts since the carbon released during combustion was initially removed from the atmosphere
during biomass growth. However, for biomass which grows slowly, climate benefits of fuels derived from
it may not be realized immediately because stored carbon is initially released during combustion but
reabsorbed slowly during regrowth [10]. In this case, the choice of time horizon becomes critical, and a
different approach may be more appropriate [11,12].
We analyze the dynamic life cycle impacts of Fischer-Tropsch middle distillate fuel using managed pine
forests as a feedstock source. We quantify emissions and climate impacts in terms of the time required for
these metrics to break even with conventional fossil fuels. This breakeven time is different for different
climate metrics, such as carbon dioxide (C0 2) emissions, radiative forcing, temperature change, and
economic damages.
11
2 Liquefied Natural Gas as an Alternative Aviation Fuel
2.1 Introduction
There are many alternative energy sources for aviation, each with varying degrees of required
modifications to the aircraft. Drop-in alternatives need no aircraft modifications and can be used with the
current aviation system, including existing distribution and refueling infrastructure. Conversely, electric
propulsion (with batteries or fuel cells) requires a complete redesign of the propulsion system and
generally the airframe itself. Cryogenic fuels, such as liquid hydrogen (LH 2) and liquefied natural gas
(LNG), can in some cases be used with minimal changes to the aircraft, depending on the application
[13].
2.1.1 Drop-in Fuels
Synthetic jet fuels (biomass-derived or otherwise) are typically intended to be "drop-in" fuels, i.e. fuels
that are sufficiently chemically similar to conventional (petroleum-derived) jet fuel that existing
infrastructure and aircraft can be used [14]. Nevertheless, there are important technical issues that must be
addressed. For example, conventional jet fuel is known to soften and swell the nitrile elastomers found in
O-ring seals within the engine [15], a chemical property that depends heavily on the presence of aromatic
components in the fuel. Because synthetic jet fuel usually contains few or no aromatics, there is concern
that it may cause O-rings to shrink and fail [16]. As a result of this limitation, alternative jet fuel blends
are currently certified to a maximum of 50% synthetic fuel by volume [17]. Synthetic jet fuel containing
aromatics can also be produced (synthetic kerosene with aromatics, or SKA) to maintain seal swelling
behavior, though these fuels have yet to be certified [18].
A number of different feedstock-to-fuel pathways have been assessed in terms of life cycle greenhouse
gas emissions using the metric CO 2 equivalent (CO 2e) where non-CO 2 emissions are converted to a CO 2
basis using their global warming potentials [7]. For example, life cycle emissions associated with the
production and use of hydro-processed esters and fatty acid (HEFA) jet fuel from soybean oil have been
estimated at 27.3-59.2 gCO 2e/MJ, which is 69-31% lower than the conventional jet fuel baseline of 87.5
gCO 2e/MJ [19]. In addition, measurements of emissions associated with biomass-derived jet fuels show
reductions in pollutants of concern to air quality and human health. For example, a 40% blend of
biomass-derived fuel was found to reduce overall particulate matter (PM) number-based emissions by
35% over the full landing and take-off cycle compared to conventional jet fuel [20].
Notwithstanding potential benefits of biomass-derived jet fuels, such fuels face a number of challenges
including high production costs [21], scalability limits due to feedstock availability [22], environmental
and other implications of large-scale land use change [23,24], water use associated with biomass
cultivation [25,26], and the time required to scale-up biomass cultivation and conversion facilities [27]. In
addition to biomass as ajet fuel feedstock, non-conventional fossil feedstocks for drop-in jet fuel have
also been investigated. These alternatives-specifically shale oil-derived jet fuel and Fischer-Tropsch
(FT) conversion of coal or natural gas into liquid fuels-have been shown to result in increased life cycle
greenhouse gas emissions [19].
12
2.1.2 Electric Propulsion
Fully electric propulsion for manned aircraft is still in its infancy, and large-scale commercial and military
applications have been regarded as being twenty years away [28]. Nevertheless, several advancements
have recently been made with unmanned aerial vehicles (UAVs) and light sport aircraft, which have
lower specific energy and specific power requirements [29,30,31]. Current battery and fuel cell
technologies are characterized by low energy and power densities, making them well suited for
applications with low speeds and payloads.
Battery-electric propulsion is limited by the energy storage density of rechargeable batteries.
Conventional jet fuel stores 43 MJ/kg, while typical Li-ion batteries store only 0.4-0.6 MJ/kg [32]. Fully
electric aircraft concepts call for batteries with energy density of at least 3.6 MJ/kg [28]. Fuel cells
powered by compressed hydrogen can provide this energy density, or up to 36 MJ/kg if hydrogen is
stored as a liquid. However, because of their characteristically low specific power, fuel cells are limited to
low-weight, highly-constrained designs. Although fully electric manned aircraft are technologically
limited, fuel/electric hybrid aircraft are currently being tested and developed, with potential application to
military or commercial aircraft [33]. Hybrid aircraft integrate electric motors with internal combustion
engines in various configurations to increase the overall efficiency of the aircraft [34].
The environmental benefits of electric propulsion include zero in-flight emissions of greenhouse gases or
pollutants that affect air quality. For battery-powered flight, ground-based electricity generation becomes
a greater concern as an emission source. With the current grid electricity mix, a fully electric aircraft
would still derive much of its energy from fossil fuel combustion. Nevertheless, electricity production is
more suitable for carbon capture and sequestration, enabling a wide range of engineering options for
reducing greenhouse gas emissions [35].
The average retail price of electricity for end use customers in 2012 was 9.87#/kWh [36], while the jet
fuel spot price averaged $3.06/gal [37]. At these prices, electricity is 19% more expensive than jet fuel per
unit energy. However, it should be noted that electric energy provides more work output than fuel
combustion, especially when coupled with highly efficient electric motors [38]. Therefore, fuel cost
savings relative to conventional jet fuel are feasible. Electricity has the added benefit of a well-established
distribution infrastructure, and there would be little modification required at airports for battery charging.
2.1.3 Cryogenic Fuels
In aircraft application, natural gas and hydrogen must be stored on the aircraft as cryogenic liquidsliquefied natural gas (LNG) or liquid hydrogen (LH 2)-to maximize energy storage density. Both of these
fuels have a higher specific energy than jet fuel but a lower mass density. This results in a reduction in
aircraft operating weight and a loss of cargo space to fuel storage. Cryogenic fuel storage in wing tanks is
not recommended for safety reasons and heat transfer limitations. Since LNG and LH 2 are not drop-in
fuels, aircraft modifications and additional infrastructure investment are required [39,40]. Specifically,
modifications to the aircraft engines, fuel systems, and fuel storage are necessary.
NASA has studied fundamental technical aspects of using LNG in for-purpose designed aircraft, and no
technical barriers were found that would prevent the use of natural gas as an alternative aviation fuel [41].
A first flight test of an aircraft retrofitted to run on LNG and LH 2 (TU- 155) was conducted by the
13
Tupolev Aircraft Company in the Soviet Union in 1989 [42]. In that case, a single engine was modified to
operate with the cryogenic fuel. Similarly, it can be advantageous to retrofit existing aircraft to use
cryogenic fuels as only a fraction of the total mission fuel. This provides access to the lower fuel prices
and potential environmental benefits while maintaining flexibility of aircraft use independent of the local
fuel availability.
Current methods of hydrogen (H 2) production rely on steam reforming of natural gas, leading to a high
energy and greenhouse gas footprint compared to conventional jet fuel. However, H 2 can be produced
from water and any energy resource, allowing for the possibility of H 2 production from renewable power
(such as solar or wind) [43]. Water vapor emissions and contrail impacts of hydrogen-powered flight have
been discussed [42,44], and the additional climate effect is expected to be relatively small. Combustion of
hydrogen eliminates sulfur and soot emissions and may also reduce NOx formation [45]. Natural gas has
23% lower CO 2 combustion emissions than conventional jet fuel on a per-unit energy basis [46,47]. In
addition, natural gas combustion is expected to result in reduced emissions of particulate matter and SO 2
[19,21].
Because liquid hydrogen is expensive to produce, it is not an economically viable option compared to
LNG or conventional jet fuel at current market conditions. Liquid hydrogen could be supplied from
biomass at $6.70/gal ofjet fuel equivalent (JFE) or renewable electricity at $9/gal JFE [48]. In contrast,
natural gas is 70-80% cheaper than jet fuel on a per-unit energy basis. This has the potential to translate
into lower operating costs, which could motivate the use from an aircraft operator view.
Given the US military's current dependence on petroleum fuels, there is increased interest in using
alternative fuels to increase energy security and independence and decrease operating costs. In particular,
the US Air Force represents a candidate for alternative jet fuel options. Natural gas is an abundant
resource in the US with production volumes estimated to increase through 2035 to 800 billion cubic
meters, a 23% increase from 2011 levels. With the US becoming a net exporter of natural gas [49], use of
natural gas in military or commercial aviation may contribute to enhanced energy security and
independence.
In this work we assess the use of liquefied natural gas (LNG) as a supplemental aircraft fuel in the near
term with a military context for the C- 130 transport aircraft. We are interested in the impact of LNG use
in aircraft from two perspectives:
1.
In the operator perspective, we determine the net costs or savings for an aircraft
operator using LNG as a supplemental fuel. Since LNG is not a drop-in fuel, it will
require aircraft modifications (retrofit), which increases purchasing expenses [39]. In
our analysis we compare these additional expenses to potential fuel expense savings
from using LNG as a supplemental fuel. We also assess Fischer-Tropsch (FT) jet fuel,
which uses natural gas as a feedstock, but-as a drop-in alternative fuel--does not
require any modification to the aircraft.
2. In the societal perspective, we quantify the net benefit or cost to society of using LNG
or FT jet fuel in terms of resource consumption, climate damage, and human health
effects related to air quality.
14
We assess the societal and operator impacts of using LNG to conventional jet fuel usage in the context of
modifying a fleet of C- I30J and C-I 30H transport aircraft for military use in the United States.
2.2 Methods
2.2.1 Aircraft Retrofit Design and Evaluation
Although no aircraft modifications are required in order to use FT jet fuel (blended with Jet A), several
changes to the fuel system are necessary in order to burn LNG effectively in the engines as well as to
store the cryogenic fuel. This section provides a brief overview of the potential design modifications
required for a C-130 aircraft.
Our proposed fuel system modification allows two of the four engines to operate on either natural gas or
jet fuel. Therefore, the aircraft can operate by using jet fuel and LNG simultaneously or by using jet fuel
only when the LNG supply is below a minimum level. This hybrid LNG/jet fuel aircraft configuration is
shown in Figure 2-1. The two inboard engines have the capability to burn either jet fuel or LNG while the
outboard engines can operate on jet fuel only. LNG is carried within cylindrical cryogenic tanks that
replace the two external tanks that normally carry jet fuel.
Jet Fuel
LNG
LNG/Jet
LLNG Fuel Lines
Figure 2-1: Hybrid aircraft configuration with two engines modified to burn either natural gas or jet fuel.
Two versions of the C- 130, the C-I 30J and the C-i 30H are considered because of their widespread
adoption and the assumed differences in retrofit costs. The C-130J model is currently in production and in
service with the US Air Force. It was introduced in the late 1990s with improved engines, performance,
and operating costs as well as cargo volume and avionics upgrades over previous C-130 models [50]. The
C-130H is an older model of the C-130. The C-130H is still in widespread use and its engine has been
modified to work with natural gas as a stationary power plant for electricity generation, designated as the
Rolls Royce 501 model.
15
Several design modifications must be made to the C-130J and C-130H so that they can operate on both
LNG and jet fuel. LNG is a cryogenic fuel that requires dual-layer vacuum insulated tanks, typically made
of stainless steel or titanium. The aircraft requires a fuel system that adequately vaporizes the liquid fuel
and raises it to the appropriate operating pressure for the combustor. Therefore, separate fuel lines are
needed to carry LNG to the engines. The engine combustor must be modified to handle the combustion of
natural gas while maintaining the ability to burn jet fuel. Systems changes for the engine and fuel supply
controllers are also necessary. No changes to the rotating turbomachinery, however, are expected to be
required.
In this section, we describe the retrofit requirements for fuel containment and fuel delivery. We also
discuss engine modifications and the effect of the retrofit fuel system on aircraft performance.
2.2.1.1 Fuel Containment
Natural gas is stored inside the aircraft as a liquid in order to maximize the energy content per volume.
Liquefied gas can be stored at a lower pressure than compressed natural gas, allowing the aircraft to use a
lighter containment tank to hold the fuel. However, because LNG is a cryogenic liquid, there are special
requirements for tank shape, insulation and location. Tank requirements and the proposed engineering
designs for meeting those requirements are discussed below.
Tank shape
The shape and structural design of the liquid containment tank must be suitable for accommodating
pressure loads, providing sufficient thermal insulation, and minimizing thermal conduction. Spherical and
cylindrical shapes are well suited to these requirements because they can take pressure loads evenly along
the perimeter of the tank cross-section. Their high volume-to-surface area ratios minimize the tank
contact with the fluid, helping to mitigate issues related to thermal conduction. Cylindrical tank shapes
are chosen for this analysis because they have more favorable aerodynamic drag characteristics and fit
most easily within the proposed storage spaces.
Tank structure and insulation
The tank requires insulation to minimize conductive, convective, and radiative heat transfer to the fuel. As
heat transfers to the tank, the cryogenic liquid maintains a constant temperature by slowly boiling, a
process known as auto-refrigeration. As long as the pressure inside the tank is held constant (usually by
controlled venting of excess vapor), the temperature of the liquid remains unchanged. If venting does not
occur, the temperature and pressure inside the tank can increase to dangerous levels. Minimizing the rate
of heat transfer to the tank extends the maximum holding time of the fuel. A dual-walled, vacuuminsulated vessel is used to limit heat entry: the inner layer is in direct contact with the liquid, while the
outer layer is connected to the rest of the aircraft, exposed to ambient conditions. Reflective mylar inside
the vacuum layer is used to limit radiative heat transfer.
The structural requirements for the containment tank determine the material thickness and the associated
weight of the tank. The tank must be able to withstand the maximum pressure due to a 72-hour normal
heat flux at the tank's maximum fuel capacity without venting or exceeding the maximum operating
pressure as specified by a National Fire Protection Agency regulation (NFPA 57) [51]. The maximum
16
absolute working stress must also be less than the working stress of the material to prevent structural
failure. If the pressure within the tank becomes exceedingly high, pressure relief devices open and allow
the tank to vent high pressure gases.
To determine the maximum pressure that can occur after 72 hours, we estimate the rate of heat transfer to
the tank and determine the corresponding temperature change. Since the fuel is at its saturation point, the
final pressure is equal to the vapor pressure of the fluid at its final temperature. Heat transfer is a result of
two main mechanisms: conduction and radiation. The total rate of heat transfer to the fuel is the sum of
the two effects. For the 72-hour heat flux calculation, the outside temperature is assumed to be 298 K and
the temperature of the LNG inside the tank is assumed to be 120 K. This corresponds to an initial tank
pressure of 28 psi.
The estimated rate of heat transfer is 180 W, resulting in 48 MJ of heat entry over the 72-hour period.
With a tank capacity of 2960 kg, the net increase in internal energy is 16 kJ/kg. This raises the
temperature by 8 K and the pressure by 20 psi, yielding an absolute pressure of 48 psi inside the tank.
Therefore, the maximum operating pressure should be chosen greater than or equal to 48 psi. Cryogenic
fuel tank designers should note that higher LNG storage temperatures require higher operating pressures,
which increase the required wall thickness, resulting in a heavier tank. The pressure relief device is
typically selected to be 30 psi above the maximum operating pressure [52], thus the device pressure is set
at 78 psi. We choose a safety factor of 1.5 which leads to a design pressure near 120 psi for the inner tank.
The outer tank is expected to only experience low pressures (up to 14.7 psi difference between the
atmosphere and the vacuum layer) but it is designed to withstand the same pressure as the inner vessel
(120 psi) in order accommodate any pressure load from the inner tank.
Table 2-1: Material physical properties and calculated tank specifications.
Working
Stress
Material
Thickness
(MPa)
(in)
Titanium
160
Stainless Steel
128
Material
Density
Empty
Tank Mass
Fuel Mass
Fuel Line
Mass
(kg/M 3)
(kg)
(kg)
(kg)
0.15
4510
920
2960
19
0.18
7860
1990
2960
32
The material thickness and tank weight can be found by sizing the material thickness such that the
working stress is larger than the stress encountered resulting from the absolute tank pressure. Two
materials-titanium and stainless steel-are considered because they have melting points above the flame
temperature as required by NFPA 57 [51]. Additional considerations are the resulting structure weight
and material thickness. Titanium is a lightweight material with a high working stress but is expensive and
difficult to manufacture. Stainless steel is a heavier material but is available at a lower cost and is
generally easier to manufacture. Material properties and tank specifications are shown in Table 2-1 for
both materials. Although stainless steel tanks have a significant weight penalty, titanium tanks would add
a significant component to the LNG retrofit cost. Therefore, we assume stainless steel tanks are used for
LNG storage when analyzing aircraft performance and fuel burn in the remainder of this report.
17
Fuel containmentlocation
The tank location should be chosen to reduce the drag penalty without compromising payload volume or
structural integrity. Ideally, this location also minimizes the intensity of aircraft modifications. The use of
existing wing tanks reduces the need to add additional support structures and eases the recertification of
any aerodynamic changes. Storage inside the wing is not preferred for cryogenic liquids for three reasons:
1) the large surface area contact with the fuel promotes heat transfer and necessitates more thermal
insulation, 2) the thickness of the wing may not be sufficient for vacuum insulation, and 3) pressurization
changes and burst hazards from a thermal leak could create a catastrophic safety condition. A burst event
with a wing mounted or fuselage tank would be less likely to impact the wing structure [53].
2.2.1.2 Fuel Delivery
The fuel delivery system is designed to vaporize LNG and carry it to the engines at the rate commanded
by the throttle while maintaining constant pressure in the containment tank. A simplified schematic of the
fuel delivery system is shown in Figure 2-2. For each LNG tank, the fuel delivery system consists of two
tank-mounted pumps, two delivery lines, a heat exchanger, and an engine mounted high-pressure pump.
The two tank-mounted pumps remove LNG and its boil-off vapor from the tank, where the rate of
removal also serves to regulate the pressure of the tank. The ability to actively remove vapor from the
tank can also be used to prevent venting when the aircraft is parked by funneling the vapor to an electric
generator or a fuel cell if the pressure exceeds allowable levels.
Heat
Exchangers
High Pressure
Compressor
C
PMP
LNG Boil-off
jne...srmO*
LNG
I NAW
W7gy
-
I~
Low Pressure
Jet A Feed Line
Pump
Adapted from http://www.cap-nyIS3.org/forcosthrust.htm
Figure 2-2: LNG fuel delivery schematic.
18
Boil-off vapor and the LNG are carried by separate lines to the heat exchangers. These lines extend from
the containment tanks to the engines and are also used for refueling the LNG tanks. LNG is vaporized in a
heat exchanger using ambient air, heat from engine oil, or bleed air. The heat exchangers bring both vapor
streams up to the necessary temperature, and the fuel is combined as a single stream and delivered to the
high-pressure engine compressor, which raises the pressure to the level required for injection into the
combustor. The engine controller regulates the flow of natural gas based on throttle setting. Tank pressure
is maintained by extracting vapor formed in the liquid pump and re-injecting it back into the tank.
For cryogenic fuels, the fuel system must maintain a safe operating condition onboard the aircraft.
Different control strategies are required for an idle or parked aircraft and an aircraft that is in flight. When
the aircraft is idle or parked, the tank pressure steadily increases as it takes in heat. When the tank
pressure approaches its maximum pressure, the control system can vent boil-off gas to an engine or
generator to create electricity as opposed to allowing fuel to escape into the atmosphere.
While the aircraft is in flight, the goal of the control system is to supply the desired fuel flow to the engine
and maintain the tank pressure within specified margins. In addition, the system must provide a constant
proportion of boil-off gas and LNG to the fuel delivery system regardless of the tank pressure. Some
control systems only supply boil-off gas to the system when the tank pressure is too high; however, this
can cause inconsistencies in the heating value of the fuel delivered to the engines. As boil-off gas forms, it
is enriched in methane, and the remaining tank liquid is enriched in the heavier hydrocarbons present in
LNG. This lowers the heating value of the tank liquid while raising the heating value of the boil-off gas.
Consequently, supplying boil-off gas in inconsistent amounts during flight would result in less predictable
thrust levels and less accurate mission planning because of the changing energy content in the remaining
fuel. Besides consistent boil-off gas use, this issue can also be addressed by filtering of the natural gas to
99% methane instead of only 95% prior to liquefaction [54], but this approach increases the price of the
fuel at the pump.
To keep the tank pressure from dropping (due to removal of both boil-off gas and liquid fuel), vapor
produced in the low-pressure pump or the LNG heat exchanger can be recycled back to the tank.
Appropriate measures should be taken to maintain thermal equilibrium between any recycled vapor and
the liquid fuel.
2.2.1.3 Engine Modifications
Changes to the fuel injection, combustion system, and engine control software must be made to
accommodate natural gas combustion within the engine. Only one fuel type is combusted at any given
time, except when switching between fuels. Additional fuel injectors for natural gas must be added
around the combustor. The same fuel injectors for jet fuel cannot be used for natural gas because they are
designed to work on liquid substances and mixing the two fuels before injection could cause
unanticipated heat and safety problems [52]. Combustion of natural gas yields a different flame
temperature than jet fuel, necessitating a modification of the combustion liner [55]. Modifications to the
amount of air that is allowed to enter the combustion chamber may also be needed to ensure that flame
temperatures stay within their expected values during the operation or to allow for a more optimal
combustion profile for LNG. Engine control software must also be tuned and re-certified to provide a
smooth transition between the two fuels and to accurately demand the correct fuel flow rate for a given
thrust output.
19
Aero-derivative gas turbines are aircraft engines that have been modified by engine manufacturers to
work on the ground as electricity generators. These engines are often modified for use with diesel fuel as
well as natural gas. As mentioned previously, an aero-derived version of the Allison T56/Rolls Royce 501
engine used on the C-130H has already been developed. Aircraft engines that have already been modified
as aero-derivatives are attractive candidates for LNG aircraft because a portion of the engine R&D and
manufacturing learning curve costs have already been absorbed by the engine manufacturer. However,
such engines may still require additional modifications to ensure that the additional fuel injectors can fit
within an aircraft's engine nacelle. Alternatively, the aerodynamic shape of the engine nacelle can be
modified or the larger components in the fuel manifold can be moved into available space under or in the
wing to avoid nacelle modifications.
2.2.1.4 Aircraft Performance
The additional LNG fuel system components and external tanks add to the aircraft's operating empty
weight and mission weight. The maximum takeoff weight, however, is unchanged, leaving the LNG
configuration with less available empty weight for payload and fuel. While the weight and range penalty
of carrying the LNG fuel system is offset in part by the lighter weight of the LNG fuel on longer
missions, the lower energy density of LNG exacerbates the range penalty because less energy can be
stored in the same volume.
Based on these design modifications, mission performance of the C-130J is assessed with a computer
code that calculates the change in fuel burn and energy efficiency between the LNG and jet fuel aircraft
for equivalent levels of productivity (equivalent payloads and mission distances). Due to the additional
weight and drag of the LNG tanks and fuel system, the LNG configuration suffers an overall 3% energy
efficiency penalty compared to the unmodified C-130, meaning that it will require a fuel load containing
3% more energy in order to fly the same payload and range mission.
Given restrictions in modeling capability, the efficiency penalty for the C-130H could not be similarly
calculated. The modern C-130J is more fuel efficient than the C-130H; therefore, we assume an additional
10% fuel requirement for the C-i 30H based on engineering judgment. Except during missions with high
range and payload demands, the unmodified C-1 30 need not carry external fuel tanks. In contrast, the
LNG retrofits carry the weight and drag penalties of the external tanks regardless of mission length. These
considerations are reflected in the fuel burn requirements for each scenario. Since these fuel burn
penalties are uncertain, we provide probability distributions in Table 2-2 which are used in a Monte Carlo
analysis when calculating operation expenses and societal costs.
Table 2-2: Probability distributions of fuel burn penalties for Monte Carlo analysis.
Model or Input Value
Distribution
LNG Weight/Drag Penalty
C-130H Extra Fuel Burn
Triangular
Triangular
Low
Mode
High
1%
3%
10%
5%
15%
Type
5%
20
UtilizationRate
Potential savings from LNG retrofits depend on the number of aircraft retrofitted as well as the frequency
and length of missions for which they are used. Rather than make an assumption about specific mission
requirements, we perform our analysis over a range of missions. Given the versatility of the C-130 as a
transport aircraft, there is a wide array of possible payload-range combinations. However, different
payload and range combinations can lead to equivalent fuel requirements. Therefore, instead of explicitly
modeling the entire payload-range domain, we consider the single dimension of mission fuel burn
between 2,000 and 20,000 kg of jet fuel (or the equivalent amount of energy in LNG or FT jet). This
range of fuel burn can represent anything from a simple landing and takeoff exercise to a long-distance,
high-payload mission.
Mission frequency depends on the demands of the aircraft operator, and therefore is inherently unknown.
To address this unknown, we treat two scenarios: I) the aircraft operator purchases 10 aircraft retrofits
and uses them more frequently than non-retrofitted aircraft in the fleet, and 2) the operator purchases 45
aircraft retrofits and uses them at the same rate as other non-retrofitted aircraft in the fleet. We present the
utilization rate as the percentage of time the aircraft is in operation (including refueling, taxi time, landing
and takeoff, and hours in flight), with 100% utilization corresponding to nonstop operations (24 hours a
day, 365 days a year). A utilization rate of 50% would correspond to 12 hours of operations every day of
the year.
Combat C-130s average 600 flight hours per year, which (with refueling and ground operations added)
corresponds to a utilization rate near 10%. We assume that C-130 retrofits using LNG are to be used as
training aircraft and are therefore likely to have higher utilization rates. The 10-aircraft scenario assumes
a high utilization rate of 70% (600-5200 flight hours per aircraft per year, depending on mission length);
the 45-aircraft scenario a rate of 20% (200-1500 flight hours per aircraft per year). The results presented
in this paper impose no maximum aircraft lifetime flight hours, which may be an important limitation for
high utilization rates.
The last C-130H was delivered in 1998, which means the current fleet of C-130H aircraft is already more
than 15 years old. Therefore, we assume that LNG retrofits of the C-130H will operate for 10-15 more
years. In contrast, the C-130J is still being produced, and the entire fleet is less than 20 years old.
Therefore, C-130J retrofits are assumed to operate for 20-30 more years. These operating lifetimes are
applied in a Monte Carlo framework as uniform distributions for each aircraft.
2.2.2 Cost Estimation
We approach the LNG operator perspective by first calculating the minimum selling price for the retrofit
package assuming a certain baseline internal rate of return for the aircraft manufacturer. In order to
calculate this price, we make additional assumptions concerning aircraft retrofitting research and
development (R&D) costs, costs for the actual manufacturing of the retrofit, the number of aircraft to be
retrofitted, and the delivery schedule. We apply this data to a discounted cash-flow rate of return
(DCFROR) approach as done, for example, in Pearlson et al. [56].
We also analyze market projections for jet fuel and natural gas in order to establish realistic assumptions
about future prices. A bottom-up approach is then applied to calculate the at-pump prices of LNG and FT
21
jet fuel based on the expected future price of raw natural gas and the additional costs of liquefaction,
Fischer-Tropsch conversion, transportation, and storage.
While the operator case is primarily concerned with expenses and revenues (i.e. cash flows), the societal
case deals instead with the use of resources, such as labor, land, and capital. The use of other natural
resources, such as clean air, clean water, crude oil, and natural gas, is also included, where relevant.
Resources are valued at their shadow prices-their societal opportunity cost (for inputs) and the utility
derived from consuming them (for outputs) [57]. Usually, we take market prices as a proxy for shadow
prices if they represent marginal costs and marginal utility in market equilibrium. However, market prices
usually reflect taxation and seller profit margins. Taxes and profits both constitute monetary transfers
(from the consumer to the producer or the government) with no corresponding use of resources. To find
the actual cost of a good, we need to remove the profit margins and taxes. Alternatively, we can turn to
published resource-cost data from industry and government reporting agencies. For many environmental
goods, no (efficient) market or market price exists. There is, however, a well-established set of
monetization techniques that can be applied to infer the societal value of these goods [58]. Details of the
methodology employed are provided in the following sections.
2.2.2.1 Aircraft Retrofit Costs
Aircraft retrofit costs include engineering development, aircraft certification, and manufacturing efforts
required for the modified hybrid aircraft. We estimate the cost of the LNG retrofit by first calculating the
cost of designing and building a fleet of completely new C-130 equivalents. Then we divide the cost into
the individual contributions of each major aircraft part. Finally, we determine the retrofit cost by
estimating the amount of effort required to retrofit each part as a fraction of the work required to create a
completely new part.
Several models exist for estimating the production cost of aircraft; we use the Development and
Procurement Costs of Aircraft (DAPCA) IV model developed by RAND Corporation in 1987 under
contract from the USAF. This model estimates the costs of research, development, testing, evaluation
(RDT&E) and production by the engineering, tooling, manufacturing, and quality control groups.
Development support, flight-test, and manufacturing material costs are also estimated. The DAPCA IV
model is chosen for this application because of its reliability in estimating the costs of military transport
aircraft. The key equations and results from the model are reported by Raymer [59]. The DAPCA IV
equations express costs in 1999 USD, and these values are converted to 2012 USD using an industry
average of the producer price index (PPI) from the Bureau of Labor Statistics [60]. We take the sum of
the engineering, development support, and flight test costs as representative of the total non-recurring
costs. The remaining cost components, including tooling, manufacturing labor and materials, quality
control, engine production, and avionics, are regarded as recurring costs.
The next step in determining the LNG retrofit cost is to divide the total aircraft cost into the individual
contribution of each major aircraft system. Markish gives the percent contribution of each aircraft part as
a fraction of both recurring and non-recurring costs [61], shown in Table 2-3. These data represent
average values for commercial aircraft. They are taken to be reasonable for this application because the
versatile C-130 has also served as a starting point for civil aircraft development (such as the L-100).
22
Table 2-3: Representative recurring and non-recurring cost breakdown by parts for a typical commercial
aircraft. From Markish 1611.
Aircraft Part
Recurring
Non-recurring
Wing
27%
20%
Empennage
10%
9%
Fuselage
28%
37%
Landing gear
3%
1%
Installed Engines
9%
8%
Systems
6%
17%
8%
11%
Equipment
-
6%
Final Assembly
The LNG retrofit requires more effort for some aircraft parts than for others. For example, the
empennage, fuselage, and landing gear should remain unaffected by the retrofit. However, significant
changes to the engines and systems are needed, as well as some modifications to the wings and external
fuel tanks. The wing will require only minor modifications to the ribs to make room for the LNG fuel
lines. System modifications include reprogramming the flight computer and engine software to correctly
manage the fuel flow. Equipment modifications include redesigning the external fuel tanks to carry LNG
and adding fuel system components to deliver the LNG to the engines. We estimate the costs of
retrofitting each of these parts as a fraction of the new aircraft components calculated using the DAPCA
IV model and the data from Markish. These estimates are shown in Table 2-4. Percentage efforts for the
retrofit are based on industry advice and engineering judgment. We consider the inherent uncertainty of
the retrofit price explicitly in Section 2.3.1.2 by analyzing the sensitivity of the operator case to changes
in the retrofit price.
Table 2-4: Cost of retrofitting major C-130 aircraft parts for use with LNG, expressed as a percent of the
work required to design and build a completely new aircraft part.
C-130J-30
C-130H
System
Non-recurring
Recurring
Non-recurring
Recurring
5%
2%
5%
2%
-
-
-
-
-
-
-
-
Engine
10%
12%
20%
24%
Systems
12%
12%
12%
12%
Equipment
5%
5%
5%
5%
-
10%
-
5%
Wing
Empennage
Fuselage
Landing Gear
Final Assembly
Using these values, we estimate the total research and development (non-recurring) and production
(recurring) costs of the LNG retrofits. Costs are expected to be higher for the J-30 aircraft because its
23
engine has not gone through a natural gas aero-derivative modification by the manufacturer. The C-i 30J30 is also a more technologically advanced aircraft with higher nominal production costs.
In order to estimate the final selling price of the retrofits, we use the cost estimates from the above
calculations as inputs for the DCFROR model in the form of annual expenses and revenues. The nonrecurring cost is treated as a one-off expense by the aircraft manufacturer in the year preceding retrofit
production. We assume that 4 aircraft are retrofitted. in year 1, with 10 aircraft retrofitted in each of the
following years. Due to a learning curve effect, the actual expense associated with each retrofit decreases
with every aircraft produced. The learning curve function describes the cost of each successive unit as a
function of the first unit cost:
Cn = Clnlog 2 (b),
where C, is the cost of unit n, C, is the cost of the first unit, and b is the learning curve slope. We use a
learning curve slope of 90%, which is consistent with recommendations by both Raymer and Markish.
Since the total recurring cost is the sum of the costs for all aircraft, we solve for the first unit cost,
1l
Total Recurring Cost
Z r ln10 2 (b)
where r is the total number of retrofits. This allows us to calculate the production cost of each individual
unit. These costs translate into annual expenses based on the production rates identified above. Annual
revenue is a function of the (still unknown) retrofit selling price, which is constant for each retrofit.
Applying an internal rate of return (IRR) of 10% and a typical corporate tax rate of 35% on net income,
we solve for the selling price that gives a net present value of zero for the project. The results of these
calculations provide the price curves shown in Figure 2-3.
$50
S
-
~$40
'.
C-130H
C-130J
---
.~$30
CL
a $20
$10
0
0
10
20
30
40
50
Number of Retrofits
Figure 2-3: Minimum selling price of C-130H and C-130J LNG retrofits as a function of the number of
aircraft retrofitted.
24
The retrofit price calculations are subject to uncertainty from the DAPCA model predictions as well as
other input variables. We quantify this uncertainty in a Monte Carlo framework by defining probability
distributions for the inputs. Table 2-5 shows the distributions relevant to the retrofit price uncertainty. The
bounds for the DAPCA IV model are given by RAND, while the remaining distributions are estimates
based on industry experience, engineering judgment, and recommendations from literature.
Table 2-5: Probability distributions for retrofit price estimation.
Model or Input Value
Distribution
Type
Low
Mode
High
DAPCA IV cost model
Manufacturer IRR
Corporate tax rate
Retrofits in I't year
Yearly retrofit production
Learning curve slope
Triangular
Uniform
Uniform
Uniform
Uniform
Uniform
-30%
9%
30%
3
8
85%
Model
10%
35%
4
10
90%
+43%
11%
40%
5
12
95%
2.2.2.2 Fuel Prices
In the United States, natural gas is 70-80% cheaper than conventional jet fuel on an energy basis. Current
projections (see Figure 2-4) indicate that this fraction is expected to remain between 50-85% over the next
three decades. However, there are additional costs associated with converting natural gas to LNG or FT
jet fuel. For LNG, this includes the cost of liquefaction, distribution, and storage. For FT jet fuel, costs are
primarily a function of the capital and operating expenses of a Fischer-Tropsch conversion facility.
Because there is an existing global market for conventional jet fuel, we use published at-pump prices.
However, at-pump prices for LNG and FT are not readily available as these are still emerging markets. In
this section, we describe the methods used to determine the at-pump price of each fuel.
$50
1
-
$40
$30
$6
Natural Gas
Jet fuel
$5
,o
$3
$20
$10
- ----
-
-$2
0$1
LAW
$0
$0
2000
2010
2020
2030
2040
Year
Figure 2-4: Projections for natural gas and jet fuel spot prices in the US, from EIA history and projections
1461. Thin lines indicate EIA low and high oil price scenarios.
25
We are interested in fuel price projections over the lifespan of the retrofit aircraft, including the time
required to produce the retrofits. Therefore, the price projections from Figure 2-4 are averaged over the
next 15 years. Based on these results, we take a nominal price of $2.99/gal for conventional jet fuel in the
US as representative for the time period of interest. Sensitivities to changes in the price of jet fuel are
explored in detail in Section 2.3.1.2.
LNG
To estimate the at-pump price of LNG, we use cost models and literature data to calculate the surcharges
on the natural gas feedstock price resulting from liquefaction, distribution, and storage. We assume that
LNG can be sourced from large-scale liquefaction facilities near the gas field and distributed to the airport
by rail in an intermodal container. Short trucking components (as from the rail station to the airport) are
also included in the price analysis. This supply route is shown in Section 2.3.2.1 to have the lowest
environmental impact among other possible pathways.
Current LNG export contracts link the price of LNG to the Henry Hub spot price of natural gas. The
freight-on-board (FOB) price is usually taken as the Henry Hub spot price plus a liquefaction fee.
Liquefaction fees of $3/MMBtu are typical for large-scale US export contracts. Since fuel demand for our
fleet of C-130s is far below the bulk exports of these industrial liquefiers, we should expect the
liquefaction fees to be no less than $3/MMBtu.
We use the DCFROR approach to predict the minimum selling price of LNG at the liquefaction facility.
We use a set of baseline financial assumptions applicable to commercial-scale fuel production facilities.
Except where indicated, the same assumptions are used for all minimum selling price calculations using
this approach. These assumptions are listed in Table 2-6.
Table 2-6: Assumptions used in DCFROR analyses of GTL and liquefaction facilities. Adapted from Pearlson
et al. 1561.
Baseline DCFROR Assumptions
Value and Units
Fixed Capital Investment
Variable $
Working Capital (% of FCI)
5%
Facility Lifetime
20 yrs
Equity
20%
Loan Interest
5.5%
Loan Term
10 yrs
Depreciation Period
10 yrs
Construction Period
3 yrs
% Spent in Year -3
8%
% Spent in Year -2
60%
% Spent in Year -1
32%
Internal Rate of Return
15%
Corporate Income Tax Rate
40%
Inflation
2%
26
We model a liquefaction facility with a capacity of 8 million metric tons per year (mmtpa) with a fixed
capital investment of $5.6 billion. This represents a liquefaction facility sized for bulk LNG exports
(liquefying about 100 times the amount of LNG used annually in our fleet of retrofitted C-130s) and is
typical of facilities currently under construction on the Gulf Coast. We assume 3% of the incoming
natural gas is used to power the compressors used in the liquefaction process. We take a feedstock price
of $4.22/MMBtu, subject to the inflation rate listed in Table 6. The resulting minimum selling price of
LNG is $10.32/MMBtu, representing a liquefaction fee of roughly $6/MMBtu.
Distribution costs of LNG are estimated by calculating the cost of shipping a forty-foot equivalent unit
(FEU) by rail. Rail shipping prices for the US are reported near $0.60 per container-mile [62]. The
liquefaction facility is expected to be located close to the gas field and the rail shipping distance is taken
as 450 miles. Additional costs are included for transloading the LNG shipping unit from the train to a
truck, since there is a logistical difficulty in getting the fuel from the train into an airport storage container
without a small trucking component. Intermodal LNG containers have been designed to facilitate such
transfers between different transportation modes. Overall, transportation of LNG adds $0.30/MMBtu to
the price.
Storage of LNG at the airport requires specialized holding tanks and handling equipment. Depending on
the storage capacity, holding tanks cost $1-3MM (based on vendor quotes and own calculations). The perMMBtu cost depends on the throughput of fuel and the lifetime of the tank. We size the storage tank with
enough capacity for 10 days of operations. For the purposes of the DCFROR model, the storage facility is
financed with 100% equity (either by the airport itself or by a private entity selling storage services). LNG
storage and handling adds $0.82/MMBtu to the price of LNG, giving a final at-pump price of LNG of
$11.29/MMBtu.
FT Jet Fuel
The at-pump price of FT jet fuel is predominantly a function of the capital and operating costs associated
with a gas-to-liquid (GTL) conversion facility. Carter [21] collected data from proposed, constructed, and
cancelled FT projects to find a correlation between facility size and capital cost. Based on this correlation,
we model a GTL facility with a production capacity of 118,000 bpd (similar to Shell's Pearl GTL plant)
with a fixed capital investment of $13.2 billion. The feedstock price for natural gas is the same as in the
LNG case. The resulting minimum selling price of FT jet fuel is $3.73/gal.
Each of these price estimates is subject to uncertainty. Therefore, we model each price with a triangular
distribution, using the high and low EIA estimates from Figure 4 as upper and lower bounds for each
distribution (see Table 2-7). The LNG price distribution is the sum of several input distributions that
affect the at-pump price.
27
Table 2-7: Probability distributions for fuel price Monte Carlo simulations.
Model or Input Value
Distribution
Low
Mode
High
Triangular
$2.13
$3.56
$1.00
$4.07
$2.99
$3.73
$1.40
$4.22
$4.40
$4.42
$1.80
$4.40
Triangular
$3.13
$6.10
$8.66
Triangular
$0.25
$0.30
$0.38
Triangular
$0.61
$0.82
$1.02
Type
Jet fuel price ($/gal)
FT jet fuel price ($/gal)
LNG price ($/gal JFE)
Natural gas price
($/MMBtu)
Liquefaction price
($/MMBtu)
LNG transport price
($/MMBtu)
LNG storage price
($/MMBtu)
Triangular
Triangular
--
2.2.2.3 Societal Costs of Fuel and Retrofits
Ford [63] provides profit margins for crude oil producers and refiners as a function of retail fuel prices. At
retail prices corresponding to current values, large oil producers have profit margins of 26.4%, while
refiners have profit margins of 7.9%. We apply these profit margins, along with a 40% corporate income
tax rate on those profits, to the 2012 average price of Brent Crude, which is $111.63 per barrel. The
resulting societal cost of crude oil is $70.37/bbl. The 2012 average price of a barrel of jet fuel was
$128.35, giving a price differential of $16.72/bbl between jet fuel and crude oil. Removing the refiner's
profit margin and taxes, the cost of refining crude oil into jet fuel is $14.87/bbl. We include a $3/bbl cost
for pipeline distribution [64], resulting in a final jet fuel cost of $88.24/bbl or $2.09/gal.
The EIA reports that the average cost of natural gas extraction is $5.74/MMBtu [65]. However, the
average Henry Hub spot price of natural gas has been below this value since 2009, suggesting that natural
gas sells at a loss, subsidized internally by the co-production of crude oil. This implies that natural gas,
due to its abundance, is currently valued by society less than the resources required to extract it. We take
the EIA estimate and add a $0.26/MMBtu charge for pipeline distribution, resulting in a delivered cost of
$6/MMBtu for raw natural gas. Then, removing the taxes and internal rates of return from the DCFROR
model, we find that the cost of liquefaction is $2.13/MMBtu. Using the same procedure for FT, we find
that the cost of GTL conversion is $10.59/MMBtu. With shipping and storage costs included, the total
societal cost of LNG is $8.48/MMBtu. The societal cost of FT fuel is $16.59/MMBtu or $2/gal. Since
these cost estimates are also uncertain, we model each as a triangular distribution for our Monte Carlo
analysis, similar to the distributions in at-pump prices shown earlier. Distribution parameters are shown in
Table 2-8.
28
Table 2-8: Probability distributions of societal fuel costs for Monte Carlo simulations.
Model or Input Value
Low
Mode
High
Triangular
$1.51
$2.09
$2.84
Triangular
$1.68
$2.00
$2.49
Triangular
$0.76
$1.06
$1.32
Distribution
Type
Jet fuel societal cost
($/gal)
FT jet fuel societal cost
($/gal)
LNG societal cost ($/gal
JFE)
The DAPCA IV model gives the cost of aircraft retrofits directly, with no taxes or profit margins
assumed. Therefore, we take the output of the model as the actual cost of the aircraft retrofits.
2.2.3 Environmental Modeling
Aircraft emissions impact surface air quality through the formation of ozone and particulate matter (PM).
PM with diameter less than 2.5 [Im (PM 2.5) can be generated either by direct emission (e.g. engine soot) or
by way of gaseous precursors (e.g. NO, and SO 2), which can be oxidized to form additional PM 2 .5.
Increases in ground-level ozone and PM 2. and subsequent population exposure can lead to a higher
frequency of human health incidences, such as morbidity or mortality [66]. In this analysis, we estimate
the air quality impacts of using LNG and FT jet as aviation fuels, including benefits associated with
reduced cruise emissions on surface air quality [5].
Hileman et al. [67] have shown that alternative fuels derived from biomass have the potential to mitigate
the climate impacts of aviation. Compared to biofuels, LNG is an inexpensive option, but its climate
impact is unclear. In order to determine the full range of climate and air quality impacts resulting from
LNG use in aviation, it is first necessary to determine the total amount of emissions associated with the
assumed operating fleet. Total emissions can then be mapped to climate warming (or cooling) as well as
surface air quality impacts. Typically, emissions are calculated on a full life cycle basis, i.e. the sum of all
greenhouse gas emissions (GHGs) over every step in the fuel pathway. This includes emissions from
extracting, transporting, processing, delivering, and finally burning the fuel in the engine. Below, we
describe how the life cycle analysis of LNG is performed.
2.2.3.1 Human Health Impacts & Air Quality
Changes in surface air quality (population weighted pollutant concentrations) are related to the number of
expected premature mortalities through a linear concentration response function (CRF) and are monetized
using a value of statistical life (VSL) approach as described in detail by Barrett et al. [98]. The CRF is
based on the recent EPA expert elicitation study [68]. The slope of this linear relationship (the CRF
3
coefficient) describes a 1% increase in the mortality rate in the US for each I pg/m increase in annual
average concentrations of surface air pollutants [69]. This concentration response function, however, is
only valid within the US. It is expanded to other countries by scaling the CRF coefficient based on
country-specific mortality statistics related to air quality.
The VSL should not be considered the value assigned to a human life. Rather, the VSL is a reflection of
an individual's willingness to pay for a reduction in mortality risk. It can be calculated by comparing
29
occupations that are identical except for the risk of death while at work (revealed preferences approach)
or by eliciting an individual's willingness to pay for decreases in risk of death (stated preferences
approach). Since changes in air quality cause changes in mortality risk for the exposed population, the
VSL is an appropriate measure of the societal value of that change.
For the US, the VSL recommended by the EPA is applied ($7.4 million in 2006, updated to $8.4MM for
2012) [70]. The methodology described in Barrett et al. [98] is used to determine VSLs for other countries
where the US VSL is scaled by the income ratio relative to the country of interest. Health impacts are
distributed according to the EPA lag structure, which describes the temporal delay in human health
impacts, as outlined in Barrett et al. [98]. Air quality impacts are discounted at a rate of 3%, which is
considered to be most representative of the return rate for individuals within the population. Uncertainty
in the VSL is modeled as a Weibull distribution, with a scale parameter of 7.75 and a shape parameter of
1.51 [71]. The concentration response function for air quality impacts is treated as a triangular
distribution, with lower and upper bounds also from Ref. 98 (see Table 2-9).
Table 2-9: Probability distributions for air quality health impact calculations.
Model or Input Value
Air Quality CRF
US VSL
Distribution
Type
Triangular
Weibull
Low
(Scale)
0.40%
(7.75)
Mode
(Shape)
1.06%
(1.51)
High
1.80%
The sensitivity method of Koo et al. [72] is used to relate aircraft emissions changes to changes in human
health risk, expressed as changes in premature mortality rate. As described in Koo et al., sensitivities of
health impacts to anthropogenic emissions are calculated using the GEOS-Chem adjoint model [73].
These sensitivities represent the expected change in health impacts given a small change in aircraft
emissions at any particular spatial location (i.e. change in expected premature mortality per kg change in
emissions). Thus, the health benefit associated with LNG use can be approximated through the use of
these sensitivities. Because the C-130 has the range capability to fly over the geographical breadth of the
US, we take the spatial average of these sensitivities for the entire country at a representative cruise
altitude of 22,000 ft. Region-specific VSLs account for the effect of cruise emissions impacts in other
countries. Landing and takeoff (LTO) emissions are calculated separately by scaling from current values
for aviation human health impacts reported by Ashok et al. [74].
LTO and cruise emissions are treated separately as they are fundamentally different in their impact on
surface-level air quality. While LTO impacts are seen on a regional scale, such as in the immediate
vicinity of the airport, cruise emissions impacts can be observed on a hemispherical scale. These larger
impact areas are due to the transport characteristics in the upper troposphere, which generally cause rapid
transport of emissions and pollutants to the east at latitudes of most flights [5]. This allows for health
impacts to span multiple continents. For instance, Koo et al. showed that the majority of health impacts
from US aviation cruise emissions are realized outside the US.
We only consider air quality impacts derived from aircraft combustion emissions, because the spatial
distribution of well-to-tank emissions is unknown. Table 2-10 shows the percent change in combustion
emissions for the LNG and FT cases relative to conventional jet fuel. Significant reductions in all
emissions types are observed. Since the LNG hybrid can bum at most 50% LNG on a particular mission,
30
100% reduction of any emission is not possible. It should also be noted that these benefits diminish for
longer missions, because more jet fuel is consumed once all LNG on board has been consumed. Since FT
jet fuel is blended up to 50% by volume with conventional fuel, these emissions changes are expected to
be constant regardless of mission fuel burn.
Table 2-10: Percent change in emissions from the jet fuel case to LNG and FT cases, independent of aircraft
type. LNG case includes the contribution of 50% jet fuel by energy content. FT case includes the contribution
of 50% jet fuel by volume. Emissions included from both LTO and cruise.
LNG
Emission
FT
CO
-41
-2
NOX
-31
-7
Black Carbon
-14
-13
SOx
-49
-49
Hydrocarbons
-47
0
Applying the methodology described above, we calculate the number of avoided premature mortalities
associated with using LNG and FT jet fuel compared to standard jet fuel, as well as the discounted
monetized impact. All alternative fuel scenarios result in an air quality benefit relative to the jet fuel case.
Monetized impacts are higher in the US, which is a result of the higher VSL in the regions affected by US
cruise emissions.
2.2.3.2 Life Cycle Greenhouse Gas Emissions
We consider 6 different LNG supply pathways (as shown in Figure 2-5) and down-select to a single
pathway on which to base the remainder of our analysis. To determine the relative environmental impact
of each pathway, we perform a life cycle analysis on all pathways in order to identify the most beneficial
one. We discuss the life cycle approach in terms of both well-to-tank and tank-to-wake emissions. The
total well-to-wake GHG inventory is the sum of the emissions associated with these two portions. This
information is then used in a simplified climate model to calculate the resulting global temperature
change and the monetized damages associated with that change.
We consider LNG supply pathways from domestic natural gas as well as imported liquefied natural gas.
Although imported LNG pathways forfeit some energy security benefits, they are considered because they
reduce the infrastructure cost burden. Because the LNG arrives at the port in liquid form, no domestic
liquefaction facilities are required. Instead, the costs of non-domestic liquefaction are included in the
LNG price at the receiving port.
The natural gas recovery and processing step encompasses all processes in the extracting and filtering of
natural gas to a level that is acceptable for pipeline transport (see Figure 2-5). Imported pathways receive
LNG by ship and then distribute it to the airport by truck (pathway A) or rail (pathway B). Pathway C
requires a small-scale liquefaction facility (micro-liquefaction) at or near the airport which re-liquefies
pipeline gas sourced from LNG import terminals. A matching scenario with micro-liquefaction at or near
the airport with domestic natural gas is also considered (pathway D). Domestic pathways E and F rely on
31
large-scale liquefaction at the gas field before distribution of LNG to the airport by truck or rail,
respectively.
Natural gas
recovery and
processing
Imported
Liquefaction
(CNG 4 LNG)
Storage at
liquefaction
facility
Truck
transport
(LNG)
+
Storage at
tairport
airpo
A
Imported LNG/
Truck transport
Sarge
Storage at
Rail transport
(LNG)
transport
(LNG)
Storage at
Pipeline
airport
Micro-
Storage at
Regasification
reevn
temnl(LG(CG
C
transport
(CNG)
CNG)
+
liquefaction
NG
(CN
(CNG 4 LNG)
+
Soaea
B
Imported LNG/
Rail transport
C
Imported LNG/
Pipeline transport
airport
irport
D
Domestic NG/
Pipeline transport
Liquefaction
(CNG
NG)
Liquefaction
(CNG 4 LNG)
....... .... ----.
.
--.-...
..--.
..--... .- --.
.-.--....
-.-.-.
....--
Truck
transport
(LNG)
E
Storage at
+airport
Rail transport
Storage at
(LNG)
airport
.. ... ..-.... .. .... ... .. --
Domestic NG/
Truck transport
F
Domestic LNG/
Rail transport
Figure 2-5: LNG supply pathways considered in well-to-tank greenhouse gas analysis.
GHG emissions associated with each pathway are calculated and aggregated as CO 2 equivalent per unit
energy of fuel (gCO 2e/MJ). This is done on a 20- and 100-year global warming potential (GWP) basis.
Uncertainties in process-specific emissions are estimated based on available literature and engineering
judgment. The pathways are assumed to utilize the existing LNG, natural gas, and crude oil infrastructure
in each country considered.
The primary source for emissions data is the Greenhouse Gases, Regulated Emissions, and Energy Use in
Transportation (GREET) Model [47], which is modified and supplemented to estimate methane leakage
from distribution and storage processes and to account for emissions from micro-liquefaction and
regasification processes. The micro-liquefaction process assumes a facility capable of producing 300
tonnes/day of LNG where electricity comes from the local grid [7]. A turbo-expander cycle is also
assumed, which requires 625-700 kWh of electricity per tonne of LNG production. (We note that other
more efficient liquefaction technologies could potentially be employed, reducing liquefaction GHG
emissions by >10% [39]).
Methane leakage is considered for all LNG pathways because it is a strong greenhouse gas. GREET
accounts for methane leakage during the natural gas recovery, processing, and pipeline transport
32
segments. Additional sources of leakage are considered from storage at the bulk liquefaction facility,
receiving (regasification) terminal, and the airport as well as leakage during LNG truck and rail transport.
Methane leakage is a significant uncertainty, especially in the distribution phase of the life cycle. Leakage
rates from transmission can be region-specific, as described by Howarth et al. [75]. GREET, citing the
work of Burnham et al. [76], assumes a leakage of 0.4% for regional transmission pipelines and an
additional 0.3% for local distribution pipelines. However, the work of Burnham et al. is specific to the US
and estimated lower rates than the majority of other published works on the topic. Kirchgessner et al. [77]
reported leakage in the US from transmission lines at 0.3-0.8%. Lelieveld et al. [78] studied pipeline
leakage in Russia, and estimated transmission pipeline leakage at 0.4-1.6% with a most likely value of
0.7%, and an additional 0.5-0.8% on distribution pipelines. Leakage may also be estimated by
determining the amount of unaccounted gas (UAG). UAG is the difference between the amount of gas
measured at the wellhead and the amount purchased, where total global UAG is estimated as 2.5-10%
[75]. Kirchgessner et al. [77], however, argued against the use of UAG in estimating pipeline leakage,
citing additional loss factors such as gas theft, pressure and temperature variations, billing cycle
differences, and meter inaccuracies. Total life cycle methane leakage in GREET ranges from 2% for shale
gas recovery to 2.7% for conventional wells, with a weighted average of U.S. production at 2.5%. Since
variations in transmission leakage are small compared to leakage from gas recovery and processing, we
treat the GREET values as representative. Also, bulk liquefaction facilities are likely to be built near to
gas fields, minimizing the impact of transmission losses.
Tank-to-wake emissions include emissions from fuel combustion and possible methane leakage from the
LNG aircraft. The fuel energy for each aircraft and aircraft mission is determined, accounting for aircraft
trajectory and aerodynamic characteristics in order to explore the implications of aircraft design choices
on the mission envelope, fuel burn, and total emissions.
The energy-specific combustion emission values for each fuel are taken from GREET, with values for
ground-based natural gas turbines used to represent LNG combustion emissions [47]. These values are
72.8 gCO 2/MJ for jet fuel, 71.5 gCO 2/MJ for the FT 50/50 blend, and 56.3 gCO 2/MJ for LNG.
A natural gas power plant turbine was used as a surrogate for the emissions characteristics of a natural gas
aircraft turbine because it shares the same thermodynamic cycle, common turbomachinery components,
and incorporates the same combustor modifications to support natural gas combustion that would be
needed in an aircraft turbine. General Electric, Pratt and Whitney, and Rolls Royce have produced power
plants that use turbomachinery and combustor designs common to the aircraft engines they are derived
from, with modifications applied to the combustion liner [55]. Ground-based turbine emissions were also
taken from GREET [47].
2.2.3.3 Economic Damages Due to Climate Change
Climate change impacts are estimated using the climate module of the Aviation environmental Portfolio
Management Tool (APMT) suite [79]. APMT models the ecological, health and welfare impacts due to a
given aviation emissions scenario in terms of the net present value of damages. The model evaluates these
damages based on the change in the mean surface temperature of the earth, which results from the net
radiative forcing of aviation-attributable greenhouse gas emissions. APMT uses an impulse-response
approach [80], treating aircraft emissions as pulses each year over the operation period of interest.
33
Different APMT impact modules and capabilities have been used to address the public health impacts of
ultra-low sulfur jet fuel [98], to determine climate and air quality damage metrics specific to aviation [81],
and to examine localized health and welfare impacts of aviation operations [82]. APMT uses the
probabilistic formulation of the non-linear Dynamic Integrated Climate Economy (DICE) 2007 damage
functions to monetize temperature effects [83,84]. Damage functions relate temperature change to the
change in global societal welfare, often expressed as a percentage of GDP. These functions are often
based on economic and scientific projections from large integrated assessment models, and then fit to
emissions projections from simplified climate models [85]. The DICE 2007 damage curve is derived from
estimates of individual damage curves for twelve regions of the globe and includes losses from damage to
agriculture, sea-level rise, adverse health impacts, non-market damages, and estimates of potential costs
of catastrophic damages. DICE 2007, like many comprehensive damage functions, is the subject of
criticism for failing to monetize some damages such as loss of resource endowment or damage to fragile
ecosystems [86].
We model the change in the atmospheric concentration and the radiative forcing of methane from direct
methane emissions using the approach of Wigley et al. [87]. Here, we build on the well-to-tank modeling
work of Mahashabde [88]. Background emissions of reactive gases are projected through year 2100 using
scenarios from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios
[89]. The concentration model utilizes a simple mass-balance approach for concentration with the
methane concentration growth rate from 2000-2005 calibrated to match that of the IPCC 4th Assessment
Report [90]. The radiative forcing model includes induced changes in radiative forcing from stratospheric
water vapor. Economic, technological, and population assumptions are aligned with those used to model
the temporal evolution of combustion emissions. The temperature and societal welfare impacts from the
radiative forcing attributable to aviation-related direct methane emissions are then calculated utilizing the
appropriate components of the APMT-Impacts climate model. The resulting model calculates a mean
marginal cost of a ton of methane to be $300-$680 in 2007$ for discount rates of 5%-2%. For
comparison, Marten and Newbold calculate a mean marginal cost of a ton of methane of $370-$1100 for
the same discount rates using a wider distribution of climate sensitivities and some differing assumptions
[91].
As discussed above, there is uncertainty regarding the amount of methane emissions during natural gas
recovery, processing, and transportation. We take the GREET values for shale gas recovery (2.0%) and
conventional gas recovery (2.7%) as the lower and upper bounds, with the weighted average for the U.S.
(2.5%) as typical. Distributions for the climate model parameters, such as climate sensitivity, NO, effects,
radiative forcing (RF) of sulfates and soot, ocean mixing depth and heat capacity, and damage coefficient,
were taken from ICAO CAEP [92] and are shown in Table 2-11. Aircraft NO, emissions perturb
atmospheric ozone and methane, influencing the RF of these greenhouse gases. To capture uncertainties
arising from experimental or model differences, RF estimates from three sources are used in APMT:
Stevenson et al. [93], Wild et al. [94], and Hoor et al. [95]. To aid in sensitivity analysis, several climate
model parameters are grouped into low, mid, and high categories.
34
Table 2-11: Probability distributions for APMT climate damage calculations.
Low
Mode
High
2.0%
(Mean)
2.5%
(Std Dev)
2.7%
(2.66)
(1.3)
Low
2
Stevenson et
al.
-29.3
0.56
Mid
3
Wild et al.
High
4.5
Hoor et al.
-4.8
3.4
0.79
20.7
Triangular
0.253
0.441
0.631
Triangular
6.39
1.26
25.2
Triangular
500
1000
2000
Input Value
Distribution
Methane Leakage (wt. %)
Type
Triangular
[GREET]
Damage coefficient (*103)
Normal
Climate Model Parameters
Triangular
Climate sensitivity (K)
Discrete
NOx effects
uniform
Triangular
Sulfate RF
Triangular
Soot RF
Mixed layer heat capacity
(GJ/Km2 )
Deep ocean heat capacity
(GJ/Km 2)
Mixing depth (in)
A discount rate can be applied exogenously to the monetized damages to convert future damage and
benefit streams to present value. Here, we apply a constant discount rate of 2%, which we consider to be
most appropriate for climate change, because of the irreversibility of environmental changes and the
intergenerational effects from long-lived gases [97]. Nevertheless, the discount rate for climate change
impacts remains an area of considerable debate [96].
Aircraft contrails form when water vapor in the exhaust stream condenses at low temperature and
pressure. Contrails can enhance warming by inducing the formation of high-altitude cirrus clouds.
However, because atmospheric temperature and pressure are generally higher at C- 130 flight altitudes
than at flight altitudes of commercial airliners, contrail formation is less frequent. We omit contrail
formation from our analysis, although we note that potentially significant reductions in contrail optical
depth may result from LNG combustion, with corresponding reductions in warming [42, 44].
2.3 Results
2.3.1 Operator Case
The operator case investigates the drivers of profitability from offering retrofitted C-130s that utilize LNG
for a hypothetical US Air Force use case. A market for the retrofit may exist if savings in fuel costs from
using the LNG aircraft completely offset the additional expense that the operator has to pay for the
retrofit.
Finally, we calculate the total operator expenses for each fuel scenario. Total expenses include the price
of aircraft retrofits, where applicable, as well as fuel consumption. An appropriate discount rate is applied
to future expenses. We apply certain mission profiles and usage rates as discussed in Section 2.2.1.
35
The outcome of the operator case is highly dependent on future LNG and jet fuel price differences as well
as the expenses for the aircraft retrofits. We therefore report the sensitivity of the results to changes in
these input variables. We also quantify the impact of other assumptions on the profitability of the LNG
retrofit. All monetary values reported in this section are adjusted to 2012 US dollars.
2.3.1.1 Operator Expenses
Operator expenses are discounted at a rate of 3% per year. This can be interpreted as the time value of
money. This discount rate reflects the social rate of time preference rather than the interest or profit from
an average long-term loan or investment (or market-average opportunity cost) because a military operator
is a public and not a private entity [97]. Note that only the mission expenses that change between the
different fuel cases are presented here (i.e. expenses related to fuel and aircraft retrofits only). Fuel prices
are held constant over the entire operating period at their 15-year averages as estimated in Section 2.2.2.2.
Figure 2-6 shows the mean operator fuel savings for the 10-aircraft 70% utilization case as a function of
mission fuel burn. Missions consuming 12-13 metric tons of fuel result in maximum savings relative to jet
fuel, which is a consequence of the LNG hybrid retrofit design. The proposed LNG tanks carry up to
6,000 kg of fuel, and since only two engines are powered by natural gas, missions requiring more than 1213 metric tons of fuel will consume all of the LNG on board. After this point, excess jet fuel is consumed,
which means the operator is not realizing any additional decrease in fuel expenses despite the initial
investment for the aircraft retrofit. Shorter missions use an equal proportion of jet fuel and LNG, which
should result in consistent savings. However, the turnaround time between missions becomes a greater
fraction of operation time for shorter missions (i.e. at lower levels of mission fuel burn). This results in
less overall fuel consumption, which translates to fewer savings to offset the retrofit expense. Overall,
both the H and J models of the C-130 offer net fuel savings regardless of mission type, with a local
maximum of 14% for the C-130J and 12% for the C-130H. At the 95% confidence level there is
uncertainty of about ± 10-15 percentage points, which suggests there is a small risk of operator savings
dropping below zero.
Operators using Fischer-Tropsch jet fuel spend 17% more on fuel than on conventional jet fuel. Because
there is no initial retrofit expense, and because FT fuel is blended to 50% regardless of mission length,
this extra expense is constant for all missions. The 95% confidence interval spans extra fuel expenses
from 2% to 37%, implying with a high degree of certainty that FT fuel is economically undesirable
without major departures from projected prices and current technology.
Figure 2-7 shows the mean operator fuel savings for the 45-aircraft 20% utilization scenario. Again, we
see the maximum savings for LNG retrofits between 12 and 13 metric tons of fuel burn. Here, the spread
between the H and J models is greater, about 5 percentage points, as compared to the 2 point difference
for the 10-aircraft 70% utilization case. This is related to the production rate of retrofits. With such a large
number of aircraft, the last retrofit takes place 3-4 years after the first. All aircraft are assumed to exit
service at the same point, regardless of when they are retrofitted; therefore, the last aircraft retrofits yield
fewer lifetime savings than the first. Since the C-130H is only allowed 10-15 years of operation, there is
much less time available for the final aircraft to recover their retrofit expenses through fuel savings.
36
40%
30%
LNG (H)
LNG (J)
----
---+-- FT (H)
--FT (J)
4--
S20%
*510%
-0
10%
-10%
o -20%
-
-30%
--
-40%
0
20000
15000
10000
5000
25000
Mission Fuel Burn (kg JFE)
Figure 2-6: Mean operator savings relative to conventional jet fuel for LNG and FT cases for both aircraft
types as a function of fuel burn. LNG case assumes 10 retrofitted aircraft are operated at 70% utilization.
Error bars represent 95% confidence intervals.
40%
---
30%
+-- LNG (H) --- +-- FT (H)
A--- LNG (J) ---A--- FT (J)
20%
10%
0%
0
-10%
-20%
IW
-30%
AL
I
j
I
-40%
0
5000
10000
15000
20000
25000
Mission Fuel Burn (kg JFE)
Figure 2-7: Operator savings relative to conventional jet fuel for LNG and FT cases for both aircraft types as
a function of mission fuel burn. LNG case assumes 45 retrofitted aircraft are operated at 20% utilization.
Error bars represent 95% confidence intervals.
37
In the 45-aircraft 20% utilization case, overall savings relative to jet fuel are also lower, with maximum
savings of 10% for the C-130J and 5% for the C-130H. Although the price per aircraft is lower for a high
number of retrofits (see Figure 3), the utilization rate was too low to take advantage of the fuel
savings
offered by LNG. This is surprising when we consider that, on a fleet basis, the 45-aircraft 20% utilization
case actually achieves more flight hours than the 10-aircraft 70% utilization case. The product of
fleet
size and utilization rate is a useful metric for comparing fleet aircraft use:
45 aircraft
20% utilization rate = 9
10 aircraft
70% utilization rate = 7
This metric, which we call fleet aircraft utilization (FAU), corresponds to the total
fuel bum for the fleet,
while the utilization rate by itself represents the fuel burn per aircraft. There is a tradeoff between the fuel
savings of high utilization and the decreasing retrofit price with each additional aircraft. In Figure 2-8, we
illustrate this tradeoff by evaluating fuel savings for the C-I 30J at various utilization rates and fleet sizes.
Again, the product of fleet size and utilization rate is useful: here we overlay lines of constant FAU.
Along these lines, higher net fuel savings are realized when the demand for aircraft flight hours is
satisfied with fewer aircraft operating at a higher utilization rate.
50Or-40
IN
L_
30
I2
0
E.
20
4)
10
0'
0%
20%
60%
40%
Utilization Rate
80%
100%
Figure 2-8: Contours of constant savings as a function of the number of retrofits and the utilization rate,
in
black. Shown for the C-130J at 12,000 kg of mission fuel burn. Blue dashed lines show levels of constant FAU
(product of utilization rate and number of retrofitted aircraft).
38
2.3.1.2 Sensitivity Analysis
In this section, we show how operator expenses vary with changes to input parameters relevant to the
operator case. Where applicable, we show sensitivities corresponding to the distributions used in the
Monte Carlo analysis.
Figure 8 shows the local sensitivity results for the operator case for the C-130H. Operator fuel savings are
very sensitive to the price spread between jet fuel and LNG. A perturbation in the average price ofjet fuel
by $1/gal affects fuel savings by 10-15 percentage points. Since natural gas price projections show little
variation, the LNG retrofit is a wager that jet fuel prices will remain high relative to natural gas. The
retrofit price is also influential, but at different magnitudes. The retrofit price influences savings by about
1 percentage point per $1 MM change in selling price.
-15%
-10%
-5%
0%
10%
5%
Number of Retrofits
5
10
Operation Time (years)
25%
20%
15%
30%
15
13
15
10%
Aircraft Utilization
7096 8096
Mission Fuel Burn (kg)
22,000
2,200
LNG Weight/Drag Penalty
13,200
3%i 1%
C-130H Extra Fuel Burn
15% 5%1 1094
LNG Storage Price ($/MMBtu)
$1.02
$082
LNG Rail Price ($/MMBtu)
$0.38
$0.30
Liquefaction Price ($/MMBtu)
$8.66
Natural Gas Price ($/MMBtu)
$4.40
Retrofit Price ($MM)
$19.3MM
Jet Fuel Price ($/gal)
t2.13
-15%
-10%
$6410
$4.22
$0.61
$0.25
$3.13
$4.07
$-13MM
$9.41MtO
I-S2,9
20%
15%
10%
5%
0%
-5%
LNG Operator Savings Relative to Jet Fuel
S4.08
25%
30%
Figure 2-9: Sensitivity results for LNG aircraft operators for the C-130H for 10 aircraft and 70% utilization.
The number of retrofits and the utilization rate are also important, and the tradeoff between these
parameters was illustrated in Figure 7. In this case (10 aircraft 70% utilization), fuel savings are
insensitive (1-2 percentage points) to small changes in utilization rate and somewhat sensitive to changes
in the number of retrofits (3-7 percentage points). In the other 45 aircraft 20% utilization case (not
shown), the opposite is true.
39
The effect of mission fuel burn is demonstrated in Figures 5 and 6. The sensitivities in Figure 8 are
evaluated at a baseline of 13,200 kg of fuel burn, which corresponds to maximum savings. This means
that any perturbation of mission fuel burn causes a decrease in savings.
2.3.2 Societal Case
The societal case for the use of LNG as a supplemental fuel for the C- 130 is conducted within a costbenefit framework. We quantify the costs and benefits to society which result from using LNG or FT jet
fuel in aviation compared to conventional jet fuel. Although there are many factors influencing overall
societal welfare, we limit our analysis to resource consumption, climate damage, and human health
impacts related to surface air quality. A comprehensive analysis of another alternative aviation fuel using
similar societal cost-benefit techniques has been performed previously by Barrett et al. [98]. Cost-benefit
analysis requires identification of the important economic and environmental impacts associated with
each scenario and mapping of these impacts from physical metrics to monetized values. Monetized values
allow for different types of impacts to be compared on a consistent basis and are useful for conducting a
full system assessment. In our analysis, we consider the societal costs of retrofitting the aircraft,
producing and consuming fuel, and air quality and climate impacts. Results of this analysis are provided
in the following sections.
2.3.2.1 Climate Impact
Life Cycle Greenhouse Gas Emissions
Well-to-wake emissions calculated using the methods described earlier are shown for the LNG pathways
in Figure 2-10 on both 20- and 100-year time scales. In general, CO 2 equivalent GHG emissions are larger
for the 20-year scale because methane is a short-lived species resulting in higher radiative forcing than
CO 2 . This results in a 20-yr global warming potential for methane that is 72 (relative to C0 2) while the
100-yr GWP is 25.
All LNG pathways have a baseline amount of methane leakage that occurs during natural gas recovery.
After this, methane leakage is most problematic during pipeline transport. Pathways involving microliquefaction have the largest emissions because they include significant pipeline transportation to the
micro-liquefaction facility. The lowest environmental impact is achieved by transporting LNG by truck or
rail in order to avoid pipeline leakage. In the United States, the lowest GHG emissions are achieved with
the domestic rail pathway.
From this analysis, we conclude that the domestic rail pathway is the choice that results in lowest GHG
emissions, and we apply this pathway in the remainder of this analysis. We use these results to investigate
the relative environmental impact of LNG aircraft in terms of climate change and air quality-related
public health impacts, compared to aircraft using only conventional jet fuel or FT jet fuel. The climate
and air quality impact methodology and results are presented in the following sections.
40
IAA
120
-
m Combustion
00
Leakage
m Truck Transport
E
80
* Tanker Transport
* Rail Transport
" Regasification
60
I
" Microliquefaction
* Bulk Liquefaction
O NG Pipeline Transport
40
" NG Processing
" NG Processing Combustion
20
E NG Recovery
0
100
100 20
100 20
C
imported/
B
imported/
imported/
Truck
Rail
Pipeline
20
A
100 20
100 20
D
Domestic/
Pipeline
E
Domestic/
Truck
100 20
F
Domestic/
Rail
Figure 2-10: LNG well-to-wake GHG emissions in terms of 100-yr and 20-yr global warming potentials.
Climate Impact Modeling
Although the above life cycle analysis allows us to identify the environmentally preferable LNG pathway,
the appropriateness of the global warming potential as a policy metric is debatable. It has been shown that
the choice of metric can have a drastic impact on cost-benefit results, especially for decadal gases like
methane [99]. Furthermore, it has been shown that GWP may not translate directly to expected damages
and may undercount the risk premium of extreme damages [100].
We define the GHG emissions inputs to APMT based on the life cycle analysis presented above. Given
the atmospheric lifetimes of CO 2 and methane, the source of these emissions is irrelevant for their impact
(i.e. processing CO 2 emissions can be treated the same as CO 2 emissions from fuel combustion). Other
non-direct-combustion emissions, such as NO, and SO,, are not included on a life cycle basis because
APMT is not designed to model ground-based emissions for these short-lived gases. Therefore, we
include only combustion emissions for these species.
Climate damages are considered out to a time horizon of 800 years, which is typical for this type of
analysis. It should be noted that methane cycle projections are available only for the first 100 years,
resulting in the intrinsic assumption that methane effects are negligible after a century. Global surface
41
temperature changes for the same scenarios for the first 200 years are presented in Figure 2-11. Methane
emissions contribute mainly to the differences in temperature change over the first 30-50 years, while
CO 2 emissions are responsible for the long-term variations in temperature change. For LNG, warming due
to methane leakage outweighs the impact of lower combustion CO 2 emissions for the first few decades of
implementation. Because future societal costs are discounted relative to current societal costs, the
monetized impacts of this temperature profile are less favorable to LNG.
x 106
-
5
C
4
Jet A (H)
LNG (H)
-FT-Jet 50/50 (H)
-Jet A (J)
-- LNG (J)
-- FT-Jet 50/50 (J)
E 2
0.1
0
A
0
50
100
Years
150
200
Figure 2-11: Global temperature changes due to operating C-130H (10-15 years) and C-130J (20-30 years)
aircraft using conventional jet fuel, LNG, or FT jet fuel.
2.3.2.2 Total Societal Cost
The total societal cost for each fuel scenario in the C-130 fleet is calculated as the sum of all costs
determined above. A lower total cost compared to conventional jet fuel is analogous to an overall societal
benefit. Here we present nominal cost-benefit outcomes, but explore the sensitivity of these values to
variations in the air quality, climate, and economic impact in Section 2.3.2.3. Total societal costs from the
above analysis are represented in Table 2-12.
For LNG, the combined societal cost of the fuel and the retrofit labor and materials is 10-12% less than
the cost of conventional jet fuel. Since fuel costs make up 60-70% of the total cost considered in this
analysis, this provides the largest contribution to overall societal benefits. LNG use would result in a I 2% increase in monetized climate damages compared to jet fuel. This is mainly attributable to the nearterm warming effects of fugitive methane emissions, as discussed above. Still, there are environmental
concerns that are not directly related to climate. LNG combustion significantly improves human health
impacts related to air quality, with a 30% reduction in monetized damages. These air quality benefits,
42
together with the reduced fuel cost, completely outweigh the slight increase in climate damage from
LNG.
Table 2-12: Total societal cost of C-130 operations for a) the 10-aircraft 70% utilization case, and b) the 45aircraft and 20% utilization case. Fuel and retrofit costs are discounted at 3%, climate costs at 2%, and air
quality health impacts at 3%.
Jet
C-130J
LNG
FT
1224
372
1068
379
1164
436
136
1111
229
1824
158
1605
205
1805
4.9%
-16.1%
10.3%
1.8%
-
12.7%
-1.9%
30.8%
12.0%
4.9%
-17.4%
10.4%
1.1%
C-130H
LNG
a)
Cost ($MM)
Jet
FT
Fuel & Retrofit
Climate
777
204
696
205
739
237
151
1132
105
1006
10.4%
-0.7%
30.6%
11.1%
Air Quality
Total
% Savings from jet fuel
Fuel & Retrofit
Climate
Air Quality
Total
Jet
C-130J
LNG
FT
1415
442
1309
451
1347
519
145
1194
265
2121
183
1943
237
2104
4.8%
-16.3%
10.3%
1.6%
-
7.5%
-2.1%
30.8%
8.4%
4.8%
-17.6%
10.4%
0.8%
C-130H
LNG
b)
Cost ($MM)
Jet
FT
Fuel & Retrofit
Climate
828
223
808
225
789
260
162
Air Quality
1213
Total
% Savings from jet fuel
Fuel & Retrofit
Climate
Air Quality
Total
113
1145
2.5%
-0.8%
30.6%
5.6%
For FT jet fuel, there is a 5% benefit derived from differences in the societal valuation of each fuel,
mainly due to the abundance of natural gas compared to crude oil. However, the GTL life cycle not only
has methane leakage problems similar to LNG, but also a more energy- and C0 2-intensive fuel production
process. As a result, monetized climate damages are 16-17% higher than for conventional fuel. With air
quality improvements of 10%, the total societal benefit of FT fuel is only 1-2% relative to jet fuel.
Figure 2-12 shows the mean societal benefit relative to jet fuel for the 10-aircraft 70% utilization case as a
function of mission fuel burn. Figure 2-13 shows the same for the 45-aircraft 20% utilization case. Here,
the trends in societal benefits mirror the trends in the operator case. Net societal benefits for LNG,
however, are slightly lower than the corresponding operator savings. Even though the price spread
between LNG and jet fuel is roughly the same as the societal cost spread (LNG is about 50% cheaper), the
societal case takes into account environmental damages, making fuel costs a smaller portion of the overall
societal cost. Additionally, the societal costs of fuels are less than the fuel prices since taxes, interest, and
profit margins have been removed.
43
20%
15%
10%
C
5%
-i
0%
(,
-5%
-10%
-- +--LNG (H)
-15%
--
A---
LNG (J)
----
FT (H)
--- A--- FT (J)
-20%
0
5000
10000
15000
20000
25000
Mission Fuel Burn (kg JFE)
Figure 2-12: Mean societal benefit relative to conventional jet fuel for LNG and FT cases for both aircraft
types as a function of fuel burn. LNG case assumes 10 retrofitted aircraft are operated at 70% utilization.
Error bars represent 95% confidence intervals.
20%
15%
10%
4U'
0
4..
5%
-
-r--
0%
-5%
-10%
-- +-- LNG (H)
-15%
---
&--
LNG (J)
----
FT (H)
--- A-- FT (J)
-20%
0
5000
10000
15000
20000
25000
Mission Fuel Burn (kg JFE)
Figure 2-13: Mean societal benefit relative to conventional jet fuel for LNG and FT cases for both aircraft
types as a function of fuel burn. LNG case assumes 45 retrofitted aircraft are operated at 20% utilization.
Error bars represent 95% confidence intervals.
44
In contrast to LNG, the societal benefits of FT fuel are higher than the corresponding operator savings.
While the price of FT jet fuel is about 25% higher than conventional fuel, the societal cost of FT fuel is
actually 5% lower than conventional fuel. The price of FT fuel is escalated by the high interest payments
required to cover the fixed capital investment for a GTL facility.
2.3.2.3 Sensitivity Analysis
In this section, we quantify how the net societal impact varies in response to changes in input parameters.
As in the operator case, each parameter's distribution has a different effect on the results of the Monte
Carlo simulation. Here we show the changes in societal benefits from varying each parameter while
holding all others constant. Where applicable, we show sensitivities corresponding to the distributions
used in the Monte Carlo analysis. Figure 2-14 shows the sensitivity results for the C-I 30H for 45 aircraft
at 20% utilization. These results are representative of the trends for the other aircraft, fleet size, and
utilization rate scenarios (not shown).
-15%
-10%
Number of Retrofits
15%
10%
5%
1
0%
-5%
20%
25%
30%
25%
30%
40 *S 5s)
Operation Time (years)
10
Aircraft Utilization
20% 30%
10%
Mission Fuel Burn (kg)
15
13
13,200
22,000 2,200
Climate Model Parameters
Low
Climate Damage Coefficient
High
Mid
4.OE-03 2.7E-03 14E-03
Methane Leakage (g/MM~tu)
58$
Air Quality CRF
550
0.4% 1%
US VSL ($MM)
LNG Cost ($/MMBtu)
Retrofit Cost ($MM)
$7.4MM
$10.65
$8.48
-
$16M
-I-
~1.51
-15%
-10%
1.8%
$1MM,
$237MM
Jet Fuel Cost ($/gal)
431
II
k.51
0%
-5%
$2.09
I
5%
$12 M
--
$6.05
$116MM
S2.84
I
10%
15%
20%
LNG Societal Benefit Relative to Jet Fuel
Figure 2-14: Societal cost sensitivity results for the C-130H for 45 aircraft and 20% utilization.
Similar to the operator case, the net societal benefit is very sensitive to changes in the cost ofjet fuelabout 1 percentage point per $0.10/gal change in cost. Retrofit costs are also an important factor. Every
$1 0MM increase in the total retrofit cost decreases the societal benefit by about 1 percentage point.
Monetized health impacts from air quality vary by 2-3 percentage points over the range of the VSL and
45
the concentration response function. Climate model parameters have very little influence (less than 1-2
percentage points) on the net societal benefit because there is a very small difference between the baseline
monetized climate damages of LNG and jet fuel.
These sensitivities were evaluated at a mission fuel burn corresponding to maximum societal benefit,
similar to the operator case. Shorter and longer missions decrease the societal benefit by half a percentage
point per 1,000 kg change in mission fuel burn.
For the 45-aircraft 20% utilization case, the societal outcome varies strongly with changes in utilization
rate. A drop in utilization from 20% to 10% moves the societal impact from a 7% benefit to a 7% net cost
relative to jet fuel. This is similar to the behavior described in Figure 7 and emphasizes the same
conclusion from the operator case: benefits hinge on the correct selection of aircraft and utilization to
meet the demands of the fleet, with the optimum result occurring with the lowest number of aircraft and
the highest possible utilization rate.
2.4 Conclusion
Monte Carlo analysis has shown that mean operator fuel savings up to 14% are possible for the C-130J,
with a 95% confidence interval of 2-23%. For the C-130H, mean savings up to 12% can be achieved, with
a confidence interval of -1% to 22%. Operator savings depend on the number of retrofitted aircraft as well
as the length and frequency of missions flown. For a given flight hour requirement, savings are higher
when fewer retrofits are purchased and used more frequently. This is shown to affect savings by as much
as 15 percentage points. Mid-range and mid-payload missions provide the greatest opportunity to displace
jet fuel with LNG, while long-range missions burn excess jet fuel and provide less return on retrofit
investment. Mission length influences savings by as much as 8 percentage points.
These operator savings correspond to mean societal benefits up to 12% for the C-130J, with a confidence
interval of 3%-20%. For the C-130H, societal benefits of 11% can be achieved, with a confidence interval
of 1%-19%. Societal benefits are realized in the form of reduced human health damages due to air quality
(30%), as well as reduced consumption of scarce resources (10%). Monetized climate damages from LNG
are within 1-2% of damages from conventional jet fuel, which is negligible compared to other societal
impacts.
Under current conditions, FT jet fuel does not have the potential to reduce operator expenses. The GTL
conversion surcharge is too high to make FT fuel price-competitive with conventional jet fuel and results
in a 17% increase in operator expenses. Although FT fuel improves air quality health impacts by 10%
relative to conventional fuel, it causes 16-17% more climate damage. These effects offset each other,
leading to a marginal societal benefit (1-2% relative to conventional fuel).
Sensitivity analysis shows that apart from operation characteristics, the main drivers which influence the
operator case are the price spread between jet fuel and LNG, and the price of the LNG retrofit. A jet fuel
price change of $1/gal affects fuel savings by 10-15 percentage points, while each $1MM change in the
retrofit price influences savings by about 1 percentage point. Similarly, the societal case is highly
sensitive to the cost spread of jet fuel and LNG as well as the retrofit cost. The societal case is less
sensitive to changes in inputs to the air quality and climate damage models, only varying by 1-3
percentage points at the limits of the probability distributions.
46
3 Middle Distillate Fuel from Woody Biomass
3.1 Introduction
Woody biomass is a readily available feedstock that can be converted to transportation fuel. In the near
term, using fuels from woody biomass harvested from old-growth forests is more greenhouse gas
intensive than fossil fuels, because old-growth forests store large amounts of carbon and, if left
undisturbed, are net carbon sinks [101]. Cutting down old-growth forests for energy production releases
the stored carbon and eliminates the carbon sink. If the forest is replanted, this "carbon debt" can be
repaid, but over a long time dictated by the rate of regrowth. In contrast, managed forests are expected to
have lower carbon debts because they store less carbon and are going to be cut down anyway [102]. The
actual magnitude of this carbon debt depends on management practices before and after conversion to
biofuel production.
The time required to "pay back" the carbon debt is a useful metric for evaluating the potential of
alternative fuels to provide near-term climate benefits [103]. Before the payback time is reached,
alternative fuels exacerbate climate change; only after the carbon debt is repaid do climate benefits begin
to accrue. Given that climate change is expected to have severe socioeconomic impacts over the next 100
years [104], it is important to identify the timescales of expected climate benefits when making policy
decisions. The carbon debt payback time has been used in several studies to illustrate the consequences of
using woody biomass from old-growth forests for alternative energy [105,106,107,108]. The payback
time is not strictly a climate metric but a comparative value; it only measures the emissions of one
scenario relative to another. Thus, the payback time depends not only on the dynamic behavior of
emissions but also the type of fossil energy displaced. This is similar to other life cycle analysis (LCA)
methods which attempt to eliminate the need for a specific time horizon [109]. Instead of quantifying the
GWP for a fixed time horizon, a relevant time horizon is calculated based on the GWPs of the alternative
fuel and the displaced fuel.
The carbon debt payback time indicates the parity point for emissions, but it does not give any indication
of the payback time in terms of climate response and associated economic impacts. The earth's response
to emissions is dynamic, which means that the payback time for emissions tends to be different than the
payback times for radiative forcing, temperature change, and economic damages. Emitted CO 2 is
continually removed from the atmosphere and stored in oceans and forests. This is a slow process, but it
has a timescale on the same order as forest growth. Therefore, the perturbation to the atmospheric CO 2
concentration (equivalently radiative forcing) breaks even before the carbon debt is fully repaid.
Increased radiative forcing causes an increased heat flux to the surface of the earth. However, due to heat
transfer and turbulent mixing between the ocean mixed layer and the deep ocean, the temperature of the
ocean surface does not increase immediately. As a result, changes in the earth's mean surface temperature
lag behind perturbations in radiative forcing. The timescale of this delay depends on the heat and mass
transfer properties of the ocean layers. It follows that the breakeven time for temperature change occurs
after the radiative forcing breakeven time.
Finally, economic damages due to climate change in any given year in the future are estimated as a
function of the square of the mean global temperature rise and the global GDP [83]. Therefore, yearly
47
economic damages break even with fossil fuels at the same time as temperature change, but the sum of
damages up to that point is still higher for the alternative fuel. This cumulative damage debt is not paid
off until after the temperature change breaks even, depending on the rate of economic growth and the
magnitude of the difference in temperature changes between the two scenarios.
A discount rate can be applied to convert future economic damages and to a present value, though the
appropriate discount rate for climate damages is a subject of considerable debate [96]. Discount rates of
1-3% are recommended when intergenerational effects are to be considered [97,110], while higher
discount rates place relatively higher value on the welfare of the current generation. It follows that higher
discount rates move the breakeven point for economic damages further into the future.
Managed forests for biofuel production have not been studied sufficiently to determine the circumstances
under which they provide climate benefits and when those benefits will be realized. The carbon debt
payback time alone tends to overestimate the payback time for climate response and underestimate the
payback time for economic impacts. Using multiple breakeven metrics provides a broad perspective for
climate policies affecting forest management by addressing impacts in terms of emissions, climate, and
the global economy. This study explores the relationship between the carbon debt payback time and the
payback times for radiative forcing, temperature change, and economic damages in the context of
management practices for dedicated plantations of Loblolly pine in the southeastern United States.
3.2 Methods
We estimate the dynamic carbon emissions from biofuels harvesting by performing a comparative
analysis with a business-as-usual forestry scenario. Forest carbon pools are computed using an analytical
model of stand growth, harvest, and decay of litter and wood products. The resulting emissions profile is
then used as the input to a climate response model to determine radiative forcing, temperature change and
economic damage as a function of time.
3.2.1 Forest Carbon Model
We track the carbon pools in managed forests by adapting the carbon flow model found in Refs. 111, 112
and 113. Specifically, we analyze plantations of Loblolly pine (Pinus taeda) in the southeastern United
States. Live tree carbon mass B is computed deterministically from the sigmoidal function
Bm
B(t) = 1+ be-rt Ym
where t is the stand age, B, is the maximum stand carbon content, and b, r, and y, are empirical
parameters that depend on tree species and management practices (see Table 3-1). Over the lifetime of the
stand, the trees shed branch, root and foliage debris which accumulate on or under the forest floor. As
these litter pools decompose, a small fraction of the carbon is converted to soil organic matter (i.e.
humification) and the remainder is oxidized and released to the atmosphere as CO 2. We assume that any
methane (CH 4) formation from biomass decomposition is negligible, since CH 4 is typically only a
byproduct of decomposition in oxygen-depleted zones [114]. Soil organic matter decomposes at a slower
rate than aboveground biomass. All decomposition processes are treated with first order decay rates,
which are given in Table 3-1.
48
When the stand is harvested, a significant fraction of tree mass is left behind as stem residues, roots, and
branches (i.e. stumps and slash). We assume that these residues are left to decompose on site to provide
ground cover and nutrients for future planting. Harvested material is taken offsite for processing, where it
may be turned into wood products, such as lumber and paper, or converted to liquid fuel. We allow for
conversion to long- and short-lived wood products to represent lumber and paper, respectively. Each
stand is replanted in the year following harvest.
Table 3-1: Relevant parameters for carbon cycle model (for details on model application, see Ref. 113).
Growth parameters were fitted to mimic growth rates of Loblolly pine (Pinus taeda) under industrial
management practices.
Symbol
Units
Value
Definition
Bm
Mg C ha-'
273
C content of old-growth trees
b
30
Empirical growth parameter in equation I
r
ym
yr-1
Mg C ha- 1
0.204
7
Initial relative growth rate of C storage in trees
Vertical shift of growth function
kb
yr-1
yr-1
yr-'
0.1
0.33
0.33
0.004
0.1
0.16
First order decomposition rate of branch litter*
First order decomposition rate of fine root litter*
First order decomposition rate of foliage litter*
First order decomposition rate of soil organic matter*
First order decomposition rate of woody root litter*
Fraction of C loss from pool i that is transferred to soil organic matter*
kf
k,
km
yr~1
k,
yr- 1
Pi
-
Fraction of felled biomass left on site as branch debris
0.186
0.2
Fraction of felled biomass left on side as woody root debris
Fraction of harvested material converted to long-lived wood products
0.35
0.01
First order decomposition rate of long-lived wood products
First order decomposition rate of short-lived wood products
yr-1
0.33
kPP
*Values taken directly from Ref. 113.
hb
-
hw
fWP
kwp
yr-1
In order to calculate the carbon emissions from converting managed forests to biofuels production, we
first establish a plantation history by running the forest model under a business-as-usual (BAU) scenario
for a sufficient time to reach a periodic steady state condition. We use this condition to initialize two
scenarios: 1) a continued BAU scenario and 2) a biofuels scenario. We take the difference in total stored
carbon between the BAU scenario and the biofuels scenario at any time in the future as indicative of total
emissions.
In the BAU scenario, forest owners maximize profitability by growing larger-diameter trees, which can be
converted into higher-valued wood products (i.e. sawtimber). This approach tends to require growth
periods of 25-40 years and does not maximize the mass output of product. We ignore any pre-commercial
thinning for simplicity. Each BAU stand is harvested at age 30, or every 31 years (due to the 1-year break
between harvest and replanting). Based on the U.S. average, the BAU forest converts 35% of its harvest
material to long-lived wood products (decomposition rate of 1% per year), with the remainder converted
to short-lived wood products (decomposition rate of 33% per year) [115].
Biofuels producers maximize profitability by minimizing feedstock cost, which means increasing mass
output and reducing collection area. Therefore, biofuels producers seek younger stands for biomass
harvest. We assume stands are harvested for biomass at age 14, or every 15 years. The effect of this
assumption is investigated in our sensitivity analysis.
49
The biofuels scenario requires a distinct stand of trees to be harvested each year in order to supply a
constant stream of feedstock material. Therefore, in any given year of biofuels production, there must be
an appropriately-aged stand available for harvest. It follows that the total carbon debt at any time in the
future is the sum of the carbon debt attributable to each stand harvested in any prior year. For example, if
a stand is harvested every T years, then T distinct stands are required to maintain feedstock supply. After
T years of harvesting, each plot will have been harvested once; the first plot will contain trees aged T-1
(ready for harvest in year T+1), the second plot will contain trees aged T-2, etc. The total carbon debt at
any time t is then
Z
D(i)
i=t-T,
i> 0
where D(i) is the carbon debt in year i attributable to a single stand.
In the biofuels case, the harvested material is converted to liquid fuels at an energy conversion efficiency
of 37%, which is representative of a Fischer-Tropsch process. This liquid fuel can be a substitute for
conventional diesel or jet fuel, which have life cycle GHG footprints of-90 gCO 2e/MJ [116]. We assume
that biofuels are produced for 30 years, after which all stands are returned to the BAU harvest scenario.
Sensitivity to this operation time period is investigated.
3.2.2 Climate Impact Model
Climate impacts are again estimated using the climate module of the Aviation environmental Portfolio
Management Tool (APMT) suite [79]. APMT is used in this application to treat only CO 2 emissions; the
computation of any non-CO 2 emissions and impacts is disabled. Thus, emissions from biomass
decomposition and fuel combustion are handled equivalently. For this work, APMT is configured to use
the economic and emissions projections from the IPCC Fourth Assessment Report (AR4) SRES scenario
B2 [89]. The effect of the choice of background scenario is assessed as a sensitivity.
In order to determine the breakeven point of economic damages, we report time-dependent damages as
the sum of the yearly damages up to each point in time. This allows us to quantify the cumulative
economic damage due to climate change as a function of time and, when discounting is applied, returns
the net present value (NPV) of climate damage as time approaches infinity. We also include the sum of
undiscounted damages in order to identify the lower bound of the breakeven point.
3.3 Results
3.3.1 Breakeven Time
Figure 3-1 shows dynamic profiles of CO 2 emissions, radiative forcing, temperature change, and
economic damages for the biofuels scenario. Net CO 2 emissions break even with conventional fuel after
64 years, which is about 40 years earlier than indicated for boreal forests in Ref. 108. Radiative forcing
breaks even after only 34 years, which is just 4 years after the forest is returned to the BAU scenario,
while temperature changes break even after 41 years. Undiscounted economic damages break even 94
years in the future. At a 1% discount rate, damages break even after 119 years, and after 265 years for a
50
2% discount rate. At discount rates above 2% (not shown), the NPV of damages from biofuels is greater
than that of fossil fuels (i.e. breakeven time =
oo).
1
1
Conventional
-
0.8
Biofuel
Biofuel
(moving ave.)
0.S
E
0 0.4
Z0 .2
n
1
b
0 .8
0.6
04
0
)
0.8 C
0.6
0.4
0.2
I
d)
0.8ridiscounted
Ur*dk"un*d
I 0.6-
1116
0.40.2-
0
#A okWsomount Raft
'04
2% DISunt Rate
100
200
300
Year
Figure 3-1: (a) Net CO 2 emissions, (b) change in anthropogenic radiative forcing, (c) temperature change, and
(d) economic damages from middle distillate biofuel and equivalent conventional fuel (energy) use. All plots
are normalized relative to the maximum value for biomass over 1000 years.
51
Due to the periodic nature of emissions from harvest cycles, multiple breakeven times are possible (this
almost occurs in Figure 3-la). To avoid this situation and maintain consistency across all possible
scenarios, it is appropriate to use the central moving average of the biofuel results to evaluate breakeven
times. The BAU harvest period (31 years) sets the period of the moving average. The moving average
adjusted breakeven times are 59 years for net CO 2 emissions, 42 years for radiative forcing, and 48 years
for temperature change. Breakeven times for economic damages are the same. All breakeven times
reported in the remainder of this work are given in terms of the moving average.
These payback times indicate that the temperature change resulting from the managed forest carbon debt
will be greater than the temperature change caused by fossil fuels for nearly 50 years. In addition, society
will sustain greater economic damages than it would have with fossil fuels for at least 100 years.
Because economic damages depend on global GDP, the economic growth projection has a strong effect
on breakeven time. Economic damages shown in Figure 3-1 are based on the SRES B2 economic growth
scenario. When SRES Al B is employed instead, the breakeven times for discount rates of 0%, 1% and
2% drop from 94, 119, and 265 years to 84, 98, and 132 years, respectively. These breakeven times shift
to 93, 114, and 212 years with SRES A2 and to 89, 107, and 167 years with SRES BI. Breakeven times
for CO 2 emissions, radiative forcing, and temperature change are unchanged, despite any differences in
the background emissions scenario.
Net CO 2 Emissions
Radiative Forcing
40
120
35
110
I
30
ci
25
I
a
100
ci
I
20
90
ci
E
0
15
80
25
30
35
BAU Harvest Age (yr)
Temperature Change
40
25
30
35
BAU Harvest Age (yr)
Economic Damages
40
70
80
.35
I
50
30
40
25
20
ci
4
30
50-0
25
35
30
BAU Harvest Age (yr)
25
40
35
30
BAU Harvest Age (yr)
40
20
Figure 3-2: Breakeven times for (a) net C02 emissions, (b) radiative forcing, (c) temperature change, and (d)
undiscounted economic damages for different BAU and biomass harvest ages.
52
3.3.2 Harvest Age
One of the main contributors to carbon debt is the difference between the time-averaged mass of carbon
stored in the BAU forest and the forest managed for biofuels. This difference arises primarily from the
change in harvest age from 30 years to 14 years. This change is a management decision made by the
biofuels producer (or forest manager) to minimize transportation costs and to maximize biomass
productivity. Therefore, we investigate the response of breakeven times when this assumption is relaxed.
Figure 3-2 shows the change in breakeven time for greenhouse gases, radiative forcing, temperature
change, and undiscounted economic damages as a function of both BAU harvest age and biomass harvest
age. Regardless of the BAU harvest age, substantial reductions in breakeven time are achieved by
increasing the biomass harvest age. Keeping the biomass harvest age the same as the BAU harvest age
reduces the breakeven time due to economic damages from 94 years to less than 50 years. In such a case,
the time-averaged amount of live tree carbon is the same in both scenarios, and the carbon debt is only a
result of foregone sequestration in wood products.
3.3.3 Wood Products & Operation Time
Another contributor to carbon debt is the foregone carbon sequestration by trees in the BAU forest. In
contrast to old-growth forests, carbon is not sequestered permanently in managed forests but is stored in
different types of wood products, such as lumber, paper, or wood fuel. Paper and wood fuel have short
lifetimes, so the ability of a managed forest to sequester carbon depends mainly on the fraction of
harvestable material that is converted to long-lived wood products like lumber. When this harvestable
material is converted to fuel (and immediately burned) instead of a building or a piece of furniture, more
CO 2 released to the atmosphere.
We initially assumed that biofuels are produced over a period of 30 years, after which the forests are
returned to the BAU scenario, and long-lived wood products are again produced. If a sustainable biofuels
industry is desired, then the operation time must be extended. However, the longer the forest is harvested
for biomass, the larger the magnitude of the foregone sequestration of carbon in wood products.
Therefore, extending the operation period also extends the breakeven time.
To isolate the effect of foregone sequestration, we now keep the biomass harvest age the same as the
BAU harvest age, 30 years. As shown previously, this eliminates the carbon debt caused by differences in
the amount of live tree carbon between the BAU and biofuel scenarios. Figure 3-3 shows how the
breakeven time varies with operation time for different fractions of long-lived wood products produced in
the BAU scenario. When none of the wood products are long-lived, CO 2 emissions, radiative forcing, and
temperature change all break even within about 10 years and undiscounted damages break even within 20
years, even with sustained operations. However, ifjust half of the wood products are long-lived, the
undiscounted damages break even after 100 years. This indicates that a managed forest producing a large
amount of lumber is better than a managed forest harvested only for woody biomass for mitigating the
economic damages from climate change over the next century.
53
Net CO 2 Emissions
Radiative Forcing
300
.2 0
0.8
10.81
0.6
0.6
0.4
0.4
0.2
1 0.2
250
200
0
100
200
300
aw
zUU
Operation Time (yr)
Economic Damages
100
Operation Time (yr)
Temperature Change
150
1
I.
0.8
0.
o.6
U.0.6
100
0.4
0.4
0.2
0.2
0
0
300
200
100
Operation Time (yr)
50
300
200
Operation Time (yr)
100
Figure 3-3: Breakeven times for (a) net C02 emissions, (b) radiative forcing, (c) temperature change, and (d)
undiscounted economic damages as a function of operation time with varying amounts of long-lived wood
products in the BAU forest. BAU harvest age and biomass harvest age are held equal at 30 years.
3.4 Conclusion
Carbon debt payback time alone does not fully describe the environmental performance of an alternative
fuel. It underestimates the breakeven time of economic damages and overestimates the breakeven time of
temperature change and radiative forcing. An analysis of payback times indicates that the temperature
change resulting from the managed forest carbon debt exceeds the temperature change caused by fossil
fuels for nearly 50 years. In addition, society sustains greater economic damages than it would have with
fossil fuels for at least 100 years.
Payback times can be reduced by keeping the biomass harvest age equal to the business-as-usual harvest
age. However, if sustained biofuel production is desired, managed forests which generate large volumes
of long-lived wood products provide a greater benefit over the next 100 years than managed forests
harvested for biomass. When long-lived products are the main output of a managed forest, it has greater
climate benefits than sustained biofuel production for 200-300 years.
54
4 Conclusion
This analysis has shown that LNG use in aviation has the potential to reduce operator expenses, even with
the cost burden of new infrastructure and aircraft. LNG use can also provide a net societal benefit by
reducing fuel costs and air quality-related mortalities. Additionally, if LNG is sourced from domestic
natural gas, there are additional energy independence and security benefits.
There are important uncertainties in the environmental analysis of LNG and FT fuel, in particular the
magnitude of methane leakage and the effects of LNG on contrail formation. Reducing methane leakage
would improve the climate impacts of LNG and FT fuel relative to conventional fuel, and contrail
warming effects are also expected to decrease due to LNG combustion at high altitude. Potential areas of
additional research include monetization of the energy independence/security benefits to the US of
displacing conventional jet fuel with natural gas for military use. In addition, the low cost of LNG could
reduce operating costs of commercial airlines. This would require investigation of the costs of added
infrastructure, safety regulations, and retrofits for commercial aircraft.
We have shown that there is a significant carbon debt associated with the production of middle distillate
fuel from woody biomass when the feedstock is harvested from managed forests. In addition, the time
required to repay the carbon debt does not fully describe the environmental impact of biofuels. Economic
damages take longer to repay, while radiative forcing and temperature changes actually break even before
CO 2 emissions. These breakeven times imply that biofuels derived from managed forest biomass are not a
favorable option for mitigating the impacts of climate change within the next 100 years.
This analysis has shown that payback times can be reduced by keeping the same harvest age for biomass
as in the business-as-usual scenario. However, it is more advantageous in the short term to use managed
forests to store atmospheric carbon in long-lived wood products, such as buildings and furniture. When
long-lived products are the main output of a managed forest, it has greater climate benefits than sustained
biofuel production for 200-300 years.
Further research is required to understand the economic consequences of displacing wood products from
the market by harvesting trees for biomass. By competing with lumber and paper industries, it is possible
that old-growth forests will be converted to managed forests, which would be a type of indirect land use
change.
55
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