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Life cycle assessment of a mallee eucalypt jet fuel
Biomass and Bioenergy 96 (2017) 162e171
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Research paper
Life cycle assessment of a mallee eucalypt jet fuel Enda Crossin School of Engineering, RMIT University, PO Box 71, Bundoora, Victoria, Australia
a r t i c l e i n f o
a b s t r a c t
Article history: Received 24 February 2016 Received in revised form 23 November 2016 Accepted 24 November 2016 Available online 2 December 2016
This study uses life cycle assessment to quantify and compare the greenhouse gas emissions and fossil fuel depletion impacts of a theoretical mallee jet fuel value chain, operating in the Great Southern region of Western Australia, with those of fossil-based jet fuel. Relative to fossil-based jet fuel, the mallee jet fuel was found to reduce greenhouse gas emissions by 40% and result in a net fossil fuel depletion benefit. Further greenhouse gas reductions could be achieved by optimizing the supply chain through measures such as capturing methane emissions for hydrogen production and utilizing co-produced biodiesel. The magnitudes of the environmental benefits are sensitive to a number of methodology assumptions, including the approach to potential food displacement and co-production. © 2016 Elsevier Ltd. All rights reserved.
Keywords: Life cycle analysis Biofuels Greenhouse gas Biomass Eucalyptus spp
1. Introduction The aviation industry contributes to an estimated 3.5%e4.9% of global radiative forcing impacts [1,2] associated with the combustion of aviation and jet fuels. Environmental pressures on the aviation sector [3] have contributed to the development of fuels based on biomass. A number of technologies can produce biomassbased jet fuels, including Fischer-Tropsch synthesis [4], hydroprocessing [5], and pyrolytic (pyrolysis) processing [6]. The biomass feedstock can include microalgae [7,8], oil-rich crops such as rapeseed and soybeans [9,10], and other crops, including corn and sugarcane [11]. Indirect land use change effects, including deforestation and displacement of food, together with low biomass yields and soil degradation are often cited as major environmental concerns associated with biomass production [11e13]. Plant biomass, produced on marginal or degraded lands, has been suggested as a way of limiting indirect land use change effects [12,14]. The use of lignoceullosic biomass can improve effective yields [13]. One potential lignoceullosic biomass is from harvested mallee eucalypt trees, including Eucalyptus loxphleba subspp. lissophloia and gratiae, Eucalyptus kochii subspp. plenissima, borealis and kochii, Eucalyptus polybractea, Eucalyptus myriadena, and Eucalyptus angustissima subsp. angustissima [15]. The mallee biomass can be processed to produce bio-oil and subsequently gasoline, diesel fuel, and kerosene-like fuel suitable for use jet in aircraft. After the
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biomass is harvested, the mallee eucalypts regenerate, allowing for ongoing harvests. A critical aspect to the implementation and approval for use biomass jet fuels is environmental performance [16]. Life cycle assessment (LCA) is one of the main methodologies used to quantify environmental performance of biomass fuel systems [13,17e22]. Previous LCAs on mallee biomass focus on energy balances of the biomass production activity in isolation of further processing [23,24] and it is not known if mallee jet fuel results in environmental benefits over the full life cycle. This paper addresses this knowledge gap by assessing the full life cycle environmental performance of jet fuel produced from mallee biomass (mallee jet fuel) relative to those produced from crude oil (fossil jet fuel). Drivers of environmental impacts are discussed, and effects of potential food displacement are critically evaluated. Opportunities for reduced environmental impact are outlined and variations in results with LCA approaches co-production are explored. Finally, limitations on the applicability of the outcomes are outlined together with directions for future research. 2. Methods The LCA study was undertaken in accordance with ISO 14044:2006 [25]. The LCA process includes defining the study goal and scope, establishing a life cycle inventory, translating environmental flows into quantified environmental impacts, and interpreting the relationship between process flows and environmental impacts. The study goal, scope, and inventory are described in this
E. Crossin / Biomass and Bioenergy 96 (2017) 162e171
section, while the environmental impacts and interpretation are reported in the results and discussion, respectively. Life cycle inventory modeling and life cycle impact assessment were performed using SimaPro 8.0.4.6 software. 2.1. Goal of the study The goal of the LCA study was to compare the climate change impacts and fossil fuel depletion impacts of jet fuel derived from mallee biomass and fossil fuels. The outcomes of this LCA were used by Future Farm Industries Cooperative Research Centre Ltd. (FFICRC) as part of a broader sustainability assessment report (not publicly available) submitted to the Roundtable on Sustainable Biomaterials. This LCA study was commissioned by the FFICRC, and involved participants from Airbus S.A.S. Manchester Metropolitan University, Virgin Australia Pty. Ltd., Enecon Pty. Ltd, Dynamotive Energy Systems Corporation, and IFP Energies Nouvelles. 2.2. Scope of the study 2.2.1. Description of product systems The mallee jet fuel system was based on a theoretical supply chain, operating over a thirty year period from 2022 to 2052. This theoretical supply chain was established as part of a business case, developed in 2011 by Renewable Oil Corporation Pty. Ltd. (ROC) in partnership with FFICRC [26]. The growing and harvesting schemes, and the location of processing facilities were modelled and selected by experts, based on technical and financial analyses, government regulations and the presence of existing infrastructure. Details of the theoretical supply chain are reported elsewhere [26]; however, an overview is provided below. The theoretical mallee jet fuel supply chain starts with the establishment of mallee crops in the Great Southern region of Western Australia, a region which currently produces canola, wheat and barley. Establishment of the mallee crop will involve the application of herbicides, soil preparation, site preparation and planting. Nutrient build-up in soils from prior agricultural activities means that fertilizers will not be typically needed prior to planting. The first harvest should typically occur six years after plantation, followed by subsequent harvests every four years. Following harvesting, the biomass will be transported by articulated road freight to one of two drying and pyrolysis processing facilities, located within a 100 km radius of supporting farms. At each of these facilities, the biomass will be ground and then stored. Following storage, the biomass moisture will be reduced using an electric rotary drum dryer, heated using a fraction of the outgoing dried biomass. The dried biomass will then be pyrolytically processed, producing non-condensable gases (NCGs), char and bio-oil. The bio-oil will be stored on site, before transportation to Kwinana via articulated road freight for upgrading. The bio-oil is typically unstable, low in energy density, and acidic [6], and requires upgrading for end-use. The IFP Energies Nouvelles process of upgrading biooil will be used and occurs in three steps: hydro-reforming (to UBA), hydro-treatment (to UBB) and fractionation to fuels. The hydro-reforming and hydro-treatment require compressed hydrogen inputs. The source for the hydrogen inputs are yet to be finalised, but were assumed to be steam-reformed natural gas. The current ASTM D7566 standards limit the use of jet biofuels to blends with traditional jet fuel of between 10% and 50% by volume [27]. However, it is anticipated that ASTM D7566 will allow for the certification of 100% synthetic jet fuel in the future [28]. As such, this study assumed that a 100% mallee jet fuel will be used. Following fractionation, the mallee jet fuel will be transported via articulated truck from Kwinana for intermittent storage at Perth Airport and subsequent use in aircraft.
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The alternative system assessed in the LCA study is based on conventional jet fuel production. This involves the exploration and extraction of crude oil from the Middle East, the transport of crude oil to a refinery in Kwinana, the processing and fractionation of crude oil to jet fuel, transport to the airport and intermittent storage, and finally combustion in a jet turbine for flight operations. 2.2.2. Function and functional unit The focus of this study was the use of jet fuel in an Airbus A330200 aircraft jet, which transports people over a distance. The delivery of the mallee jet fuel at Perth airport means that the aircraft can only refuel with mallee jet fuel at that location. Therefore, the environmental assessment is based on the functional unit of one flight, consisting of one typical Airbus A330-200 commercial passenger aircraft flight, operating twin Rolls Royce Trent 772B turbines, between Perth and Sydney (Kingsford Smith) airports. The operation of an Airbus A330-200 on the return leg (from Sydney to Perth) is outside the scope of this project. It is recognized that for comparison purposes, an alternative functional unit can be useful. As such, key results are also reported per MJ of jet fuel. 2.2.3. System boundary The system boundary outlines the processes to be included in the assessment, Fig. 1. These include farming, biomass processing, transport, aircraft operation, infrastructure, the production of electricity, natural gas, fertilizers and soil modifiers, herbicide and pesticides, reticulated water and wastewater treatment. Some infrastructure processes were excluded (e.g. factories, roads), along with human labour, wetting agents, surfactants and administration overheads. The estimated cut-off of elementary flows was 1% of the cumulative mass flows. 2.2.4. Allocation procedures The ISO 14044:2006 [25] hierarchal procedure for partioning was applied to handle processes with multpiple functions. Weidema's [29] system expansion approach was applied to avoid allocation in two processes: pyrolysis, where char is co-produced with bio-oil, and the upgrading of bio-oil, which produces coproduces UBA oil, methanol and acetic acid. The production of bio-oil was ascribed the environmental impacts of the pyrolysis process, as well as char storage. Environmental credits were applied to the pyrolysis process for the avoidance of coal production. No environmental credits were applied for avoided emissions from coal combustion as no char is combusted in the pyrolysis process. For the upgrading of bio-oil, the refined UBA oil was ascribed all process impacts, with credits applied for avoided acetic acid and methanol production. Mass allocation were applied to these processes in a sensitivity study. Energy allocation was applied to fractionation processes. Freight processes were allocated by mass. Energy and economic allocation was applied to the refining of unleaded petroleum products, in line with previous literature [30]. 2.2.5. Life cycle impact assessment methodology and types of impacts The scope of the environmental assessment was limited to climate change impacts and fossil fuel depletion. An assessment of eutrophication, land-use, soil salinity, indirect land use change and water stress impacts were outside the scope if this study, but were addressed in the FFICRC report. LCIA was performed for greenhouse gas emissions and fossil fuel depletion by multiplying environmental flows of the various resources and greenhouse gas emissions by their respective characterization factors. Characterization factors for greenhouse gas emissions were based on global warming potentials (GWPs) for a 100-year time horizon, as reported in the Intergovernmental Panel on Climate Change (IPCC) Fourth
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Fig. 1. System boundary for life cycle assessment.
Assessment Report (2007). The global warming potential for biogenic methane was adjusted to 22.25 kg kg1 of CO2-eq to account for biogenic carbon dioxide sequestration [31]. Biogenic carbon dioxide uptake (raw) and air emissions were both assigned a global warming potential of zero. The treatment of non-degraded biogenic carbon in soil, including below-ground carbon storage stemming from direct land use change, is assumed to be stored beyond the 100-year assessment period. To account for the proportion of the carbon dioxide uptake that was not released (i.e. stored as below ground carbon), inventories of carbon dioxide storage were assigned a characterization of 1 kg kg1 of CO2-eq, consistent with previous literature [32,33]. No correction factors were applied to the GWP of greenhouse gases emitted at altitude, consistent with other greenhouse gas protocols [34,35]. Fossil fuel depletion impacts were assessed using the ReCiPe endpoint indicator, which translates fossil fuel depletion into a measure (USD$) of increased resource extraction costs [36]. To facilitate future comparisons of fuel systems beyond this study, non-renewable cumulative energy demand were reported based on the CML Baseline method [37]. 2.2.6. Data and data quality requirements An assessment of the foreground data requirements was undertaken in accordance with the data quality indicators outlined in ISO 14044:2006 [25], including technology, precision, geography, time, consistency, reproducibility and completeness. The assessment of the minimum data quality required to fulfil the goal and scope of the study is provided in Table 1. An assessment of the
inventory data utilized was completed in accordance with ISO 14044:2006 [25] and are discussed in subsequent sections. 2.2.7. Interpretation approach used The interpretation approach used results from the life cycle inventory and LCIA to identify significant issues. Sensitivity studies included assessing alternative approaches to the handling of additional sheep farming and allocation, hydrogen production pathways and the supply of diesel fuel to transport systems within the system boundary. The uncertainty of the foreground data was quantified using error ranges (if available) or the pedigree matrix [38], which used qualitative judgements on the inventory data precision, completeness, and temporal, geographical and technological correlations. This foreground uncertainty data was coupled with existing uncertainties in background data to perform an uncertainty analysis, using one thousand (1000) Monte Carlo simulations. 2.3. Life cycle inventory This section focuses on reporting key inventory assumptions. Foreground life cycle inventory data was collated for and coupled with background life cycle inventory databases. The elementary flows required to deliver the functional unit are provided in Table 2. Full foreground inventory details are provided in the Supporting Information. Data for the establishment, harvesting, ongoing management, and below-ground biomass values for mallee were provided by the
E. Crossin / Biomass and Bioenergy 96 (2017) 162e171
165
Table 1 Minimum data quality requirements for inventory. Specific Technology (ST), Technology Mix (TM), not applicable (NA), very good (þþ), good (þ), average (AVG), WA (Western Australia). Inventory Item
Technology
Precision
Geography
Time
Representativeness
Consistency
Reproducibility
Completeness
Crude oil production Aircraft emissions Sea freight of crude oil Catalyst production and waste CO2 emissions from urea Fertiliser production Pesticide and herbicide production Road transport Electricity production and distribution Mallee farming - establishment Mallee farming e direct land-use change Mallee farming e ongoing management Mallee farming - harvesting Biomass grinding Biomass drying Pasture management and sheep farming N2O emissions from fertilisers Fast pyrolysis UBA/UBB upgrading Refining of Jet A-1 Refining of UBB to jet fuel Hydrogen production e steam reforming Hydrogen production - compression Reticulated water Aircraft fuel use
ST
þþ
Global
2034e35
þþ
þþ
þþ
>99%
TM
AVG
NA TM
þ AVG
ST
þþ
WA
WA (SWIS) WA e Great Southern
þ NA ST
þþ
WA - Kwinana
TM ST Perth to Sydney
Table 2 Reference flows required to deliver one flight for jet fuel systems. Output
Mallee jet fuel
Fossil jet fuel
Unit
Combusted fuel Biofuel Fossil-based jet fuel Synthetic UBB oil Hydrogen for upgrading bio-oil Bio-oil Dry biomass Wet biomass Mallee farming Land use change Additional sheep farming
17 184.64 17 184.64 e 16 976.28 1037.22 44 472.92 72 313.7 144 939.7 9.0588 0.302 69.2
17 184.64 e 17 184.64 e e e e e e e e
kg kg kg kg kg kg kg kg ha y ha p
FFICRC. The total mallee planation area was assumed to be 147.42 km2. Direct land use change from the plantation of mallee eucalypts calculated based on the difference in carbon intensity between the current (reference) carbon stock, CSR and the future (actual) carbon stock, CSA. CSR and CSA, consistent with European Union guidelines [39]. CSA was estimated using:
CSR ¼ ðSOC þ CVEG Þ A
(1)
where SOC is the standards soil organic carbon in topsoil, CVEG is the above and below ground vegetation carbon stock and A is the area. SOC was estimated using:
SOC ¼ SOCST FLU FMG FI
(2)
where SOCST is the standard soil organic carbon in the topsoil layer, determined by the climate region and soil type. The region's climate and soil characteristics correspond to an SOCST of 19 Mg ha1 of carbon [39]. FLU is the land use factor, FMG is the management factor and FI is the input factor. Currently, grazing land rotates between grassland and cropland. At any one time on average, 26.7% of grazing land is under grass, while 73.3% is under crop. CVEG, FLU, FMG and FI vary with farming practice and the
plantation type, values of which reported in the EU directive documents [39] and summarized in Table 3. Carbon stocks for the current (reference) land were determined by summing the carbon stocks for the grassland and cropland fractions. Carbon stocks for the future (actual) land were determined using:
CSA ¼ ðSOC AÞ þ CAGB þ CDOM þ CBG
(3)
where SOC and A are defined previously, CAGB is the above ground carbon, CDOM is the above ground dead organic matter and CBG is the below ground carbon. The sum of CAGB, CDOM and CBG is analogous to CVEG and values are reported in Table 3. Using this approach, carbon stocks due to direct land use change were estimated to increase by 6.49 Mg ha1. This carbon stock change, together with the impacts of crop establishment, were allocated equally over 30 years of farming activity, in line with European Union guidelines [39]. Following this thirty-year horizon, no further claims can be made on changes in the below-ground carbon. The mallee crops were assumed to be harvested six years after plantation, at a biomass yield of 60 Mg ha1, with subsequent harvests occurring every 4 years at a yield of 70 Mg ha1. Over a 30year period, the total harvest of green biomass was calculated as 480 Mg ha1, equating to an average yield of 68.57 Mg ha1. Onfarm diesel use for mallee crops was assumed to be 3.51 L Mg1 of harvested biomass, accounting for harvesting, haulage and shunting. Single superphosphate, potassium chloride (as potash) and urea fertilizers were assumed to be applied at rates of 198 kg ha1, 391 kg ha1 and 195 kg ha1 respectively after the first harvest, and 231 kg ha1, 456 kg ha1 and 195 kg ha1 respectively for subsequent harvests. The application of nitrogen-based fertilizers can result in emissions of nitrous oxide through nitrification, volatilization and denitrification processes, which are sensitive to a number of factors [40e43] including soil structure and particle size, climate conditions, nitrogen uptake by crops, soil conditions, fertilizer application rates and timing, and drainage conditions. This study used a nitrous oxide emission (direct and indirect) factor of 0.3% of applied nitrogen [44], equivalent to 1.7 kg ha1 and 1.98 kg ha1 of nitrous oxide air emissions for the initial and
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E. Crossin / Biomass and Bioenergy 96 (2017) 162e171
Table 3 Determination of changes in carbon stock due to direct land use change. Factor
Reference (current)
Future (actual)
Grassland Standard soil organic carbon in topsoil, SOCST Land use factor, FLU Management factor, FMG Input factor, FI Soil organic carbon, SOC Reference area, A Above-ground biomass, CAGB Dead organic matter, CDOM Below-ground biomass, CBG CVEG Fractional reference carbon stocks, CSR Total reference carbon stock, CSR Actual (future) carbon stock, CSA Change in carbon stock, C
Cropland
1
19 Mg ha (sandy soils) 1.0 1.14 (improved) 1.0 (Medium carbon input) 16.72 Mg ha1 0.267 ha e e e 0 4.47 Mg 22.61 Mg e 6.49 Mg ha1
subsequent fertilizer applications, respectively. Carbon dioxide air emissions from the application of urea used the default factor from the IPCC [45], equivalent to 287 kg ha1 and 334 kg ha1 of carbon dioxide air emissions for the initial and subsequent fertilizer applications, respectively. Historically, the yield of dry-sheep equivalent (DSE) in pastured areas in the region averages 7.64 ha y1. In this study, mallee plantations were assumed to displace some of this area. In order to accommodate potential reductions in sheep numbers, it was assumed that additional sheep could be accommodated within the remaining pastured land by increasing the stocking rate of DSE by 0.57 ha y1 to 8.21 ha y1. This approach ensures that the functional equivalency of sheep production is maintained. Process inputs for sheep farming were based on Ref. [46], while enteric, dung and urine emissions were based on [47e49]. Data for biomass and pyrolysis processing were provided by Enecon Pty. Ltd. (Australia) and Dynamotive Energy Systems (Canada). Electricity requirements for grinding the wet (45% moisture by mass) biomass was assumed to be 6.12 kWh Mg1 of wet biomass. The loss of wet biomass chips during intermediate storage were estimated to be 3% mass fraction [50]. The rotary drum drier was assumed to use 15.9% mass fraction of its dry biomass (10% moisture by mass) output for heat, with the remaining dry mass flowing into a pyrolysis unit. Supplementary electricity for running of motors was assumed to be 1.23 kWh Mg1 of dried biomass. The two pyrolysis units were assumed to process 200 Mg d1 of dry biomass, with yields of 30.8 Mg d1 of NCGs, 38.2 Mg d1 of char and 131.0 Mg d1 of bio-oil. The NCGs were assumed to be used as both a carrier gas for the incoming biomass, as well as for heat. The pyrolysis unit was assumed to combust 7.9 Mg d1 of bio-oil, resulting in a net bio-oil output of 123.1 Mg d1. The char was assumed to be sold (as the most profitable use) as a substitute for black coal, and not used for heat within the process. Processing data for upgrading of bio-oil to fuels were provided by IFP Energies nouvelles (France). Inputs for the production of 1 kg of upgrading bio-oil to UBB oil were assumed to be 2.62 kg of bio-oil and 61 g of hydrogen gas at 12.5 MPa. For every 1 kg of UBB oil produced, the upgrading process was assumed to co-produce 90 g of methanol and 147 g of acetic acid, to be sold as co-products. In addition to these product outputs, process emissions were assumed to be 1.113 kg of wastewater, 74 g methane, 222 g carbon dioxide and 35 g carbon monoxide gases. The methane gas was assumed to be captured for combustion and process heat, producing 204 g of carbon dioxide for every 1 kg of UBB oil, while the other gases were assumed to be emitted to air. The wastewater was assumed to be
Mallee 1
19 Mg ha1 (sandy soils) 1.0 1.1 0.95 (low carbon input) 19.86 Mg ha1 1 ha 0 Mg (harvested) 0.46 Mg [68] 8.79 Mg (peak at 20 years) 9.25 Mg e e 29.10 Mg
19 Mg ha (sandy soils) 0.8 1.1 (no tillage) 1.0 (medium carbon input) 21.66 Mg ha1 0.733 ha e e e 2.27 Mg 18.15 Mg
treated at a municipal wastewater facility. Inventory data for the fractionation of UBB oil to refined fuels are commercial-inconfidence and are thus not reported. The hydrogen for upgrading of bio-oil was assumed to be supplied from a methane stream-reformer (MSR). The work needed to compress hydrogen gas from 2 MPa to 12.5 MPa was estimated using the adiabatic compression equation:
g
2
p p V 4 1 W¼ g 1 0 0 p0
g1 g
3 15
(4)
where g is the adiabatic coefficient (1.41 for hydrogen), V0 is the initial volume and p0 and p1 refers to the initial and final pressures, respectively. At an initial pressure of 2 MPa and 20 C (typical outlet pressure of an MSR), 1.01 kg (assuming 0.01 kg is compressed, but then lost) of hydrogen gas has an initial volume of 0.6103 m3. Using these values and the final pressure of 12.5 MPa, and a compressor efficiency of 80% and 1% hydrogen losses in delivery, the electrical input required to deliver 1 kg of hydrogen was calculated as 1.026 kWh. No literature was available to validate the electricity requirements for this pressure increase. However, compression of hydrogen from 2 MPa to 44 MPa has been measured at between 2.0 and 2.2 kWh kg1 [51], which is similar to a calculated value 2.1 kWh kg1, using the approach above. Electricity impacts were based on a projection of a 2034e35 electricity grid mix for Western Australia's South-West Interconnected System (SWIS). Electricity demand from the SWIS grid is projected to increase from 28 TWh in 2008e09 to 46 TWh in 2034e35 [52]; an increase of 18 TWh. The increase in demand in 2034e35 is expected to be fulfilled through a new gasefired plant at Kwinana accounting for 12.96 TWh of this increase, with the remainder expected to be met by other new black coal and renewable energy projects [53]. These new projects were coupled with the existing SWIS grid mix to estimate the 2034e35 grid mix, Table 4. Transmission and distribution losses were estimated to be 5.3% [54]. The inventory for the production of fossil-based jet fuel production was based on an existing ecoinvent 2.2 process for exploration and extraction of crude oil in the Middle East. The inventory for crude oil refining at Kwinana was based on an existing study [30]. An overview of the transport network for both systems, including assumed transport distances and modes, is provided in Fig. 2. The mallee biomass was assumed to be harvested from farms
E. Crossin / Biomass and Bioenergy 96 (2017) 162e171 Table 4 Projected 2034e35 electricity mix for South-West Interconnected System. Source
Production (GWh)
Black coal Natural gas Oil products Other (combined cycle gas) Biogas Wind Solar PV Black coal (new projects) Wind (new projects) Natural gas (new projects) Total generation Transmission and distribution losses (5.3%) Electricity at consumer
10352.3 18115.7 1413.8 1029.4 111.7 441.1 112.8 2917.3 1193.9 12960.0 48648.0 2578.3 46069.7
within a 100 km radius of two pyrolysis processing units in Katanning. The average distance of any point in a circle to the centre is 2/3 the radius. Therefore, an average centroid transport distance of 66.6 km was assumed. The bio-oil was assumed to be transported by articulated truck to the upgrading facility in Kwinana. The mallee jet fuel was assumed to be transported by articulated truck from Kwinana to Perth Airport. For the fossil jet fuel, crude oil was assumed to be shipped from Dubai to Melbourne via Singapore. The refined jet fuel was assumed to be transported to an intermediate storage via pipeline, before being transported via articulated truck to Perth Airport. The hydrogen production and compression facility was assumed to be co-located with the upgrading facility. Sea freight distances were estimated using a port to port calculator [55], while other road freight distances were based on location data
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and mapping estimates using Google maps [56]. The mallee and fossil jet fuels considered in this study have the same energy and volumetric densities, as such, there are no differences in fuel-burn. The average fuel use for an Airbus A330-200 flight from Perth to Sydney was provided by Virgin Australia as 17184.6 kg. The fuel use of 2230 kg for landing and take-off (LTO) operations and associated greenhouse gas emissions associated were from IPCC guidelines [57]. Greenhouse gas emission factors for the remaining 14954.6 kg of fuel use at altitude were calculated using emissions factors from the Australian National Greenhouse Account Factors [58]. It was assumed that the fuels have an equivalent energy density of 43.1 MJ kg1. A qualitative assessment on the inventory data quality are reported in Table 5. In many instances, the minimum data quality requirements outlined in Table 1 were not met. However, it was considered that life cycle inventory data were complete and representative of the systems considered, and that the quality of this data was sufficient to fulfil the goals and scope of this study, which is reflected in the peer review that deemed this study as compliant to the requirements of ISO14044:2006.
3. Results and discussion 3.1. Baseline scenario Disaggregated life cycle impact assessment results are reported in Table 6. The greenhouse gas impacts of the mallee jet fuel are 35.56 Mg of CO2-eq per flight; 40% lower than 59.43 Mg of CO2-eq per flight for the fossil jet fuel. These greenhouse gas emissions are equivalent to 48.0 g MJ1 and 80.2 g MJ1 of CO2-eq for the mallee
Fig. 2. Overview of distribution network for fossil jet fuel and mallee jet fuel.
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E. Crossin / Biomass and Bioenergy 96 (2017) 162e171
Table 5 Disaggregated life cycle impact results. Process
Direct land use change Additional sheep farming Biomass farming and harvesting Biomass processing to bio-oil Co-production credits H2 production and compression Upgrading/refining of bio-oil to fuel Crude supply and refining to jet fuel Fuel delivery to airport Combustion Infrastructure, inc. catalyst prod. Total
Greenhouse gas emissions
Fossil fuel depletion
Cumulative non-renewable energy demand
Mg of CO2-eq per flight
Increased cost, $ per flight
MJ per flight
Mallee jet fuel
Fossil jet fuel
Mallee jet fuel
Fossil jet fuel
Mallee jet fuel
Fossil jet fuel
7.19 14.76 4.85 8.86 2.62 11.00 4.95 e 0.15 0.06 0.74 35.56
e e e e e e e 4.89 0.03 54.51 e 59.43
e 16.10 60.82 129.55 653.21 273.64 103.60 e 2.11 e 11.66 55.72
e e e e e e e 892.84 0.44 e e 893.28
e 9903 50 428 107 190 547 847 222 302 84 577 e 1767 e 84 577 58 896
e e e e e e e 363 747 676 e e 748 039
Table 6 Qualitative data quality assessment of foreground inventory; very good (þþ), good (þ), average (0), poor (), very poor ( ), not applicable (NA). Inventory Item
Geographical Time Technology Foreground coverage coverage precision
Consistency Reproducibility Completeness Representativeness (minimum of time and geographical coverage)
Crude oil production Aircraft emissions Sea freight of crude oil Catalyst production and waste CO2 emissions from urea Fertilizer production Pesticide and herbicide production Road transport Electricity production and distribution Mallee farming - establishment Mallee farming e direct land-use change Mallee farming e ongoing management Mallee farming - harvesting Biomass grinding Biomass drying Pasture management and sheep farming N2O emissions from fertilizers Fast pyrolysis UBA/UBB upgrading Refining of UBB to jet fuel Hydrogen production e steam reforming Hydrogen production e compression Reticulated water Aircraft fuel use
þþ þ þþ 0 þ þþ þþ þþ þ 0 þþ þ þ 0 0 0 þ 0 0 0 0 0 þ þ
þþ þþ þþ þþ þþ þþ þþ þþ þþ þþ 0 0 0 0 þþ 0 0 þþ þþ
and fossil jet fuels, respectively. The greenhouse gas impacts of the mallee jet fuel are dominated by the additional impacts of sheep farming, accounting for 14.76 Mg of CO2-eq per flight (10.9 g MJ1 of CO2-eq), as well as the production and supply of compressed hydrogen for upgrading, accounting for 11.00 Mg of CO2-eq per flight (8.1 g MJ1 of CO2-eq). These two processes account for over 50% of the mallee jet fuel greenhouse gas impacts and are the focus of the discussion on the mallee jet fuel system. In addition to the greenhouse gas reductions, the bio-fuel system shows reduced fossil fuel depletion impacts, decreasing from a total burden of 893.28$ per flight (1.2 103$ MJ1) to a net benefit of 55.72$ per flight (7.5 105$ MJ1), Table 6. Similarly, the cumulative nonrenewable energy demand (CED) indicator, Table 6, reduced from 748 039 MJ1 per flight (1.01 MJ MJ1) to 58 896 MJ1 per flight (0.08 MJ MJ1). Over 99.9% of both the fossil fuel depletion impacts and CED indicator values were driven by the extraction, supply and production of crude oil reserves in the Middle East. The Monte Carlo uncertainty results are reported in Table 7 and indicate a high level of confidence in the comparative outcomes.
NA þ þþ þ NA NA 0 þ 0 þ 0 0 0 þ e Confidential þ þ þ þ
þþ þþ þþ 0 þþ þþ þþ þþ þ þþ þþ 0 þþ 0 þ þþ þþ þþ þþ þþ 0 0 þ þþ
þþ þþ þþ 0 þþ þ þ þþ þ þþ þþ þþ þþ þþ þþ þ þþ þþ þþ þþ þþ þ þþ
þþ þþ 0 þþ þþ þþ þþ þþ 0 0 þþ
The absolute uncertainty of the individual systems will be higher than the comparative uncertainty, due to shared uncertainty. As such, the outcomes in Table 7 should not be interpreted as confidence in the environmental assessments of the individual systems. 3.2. Sensitivity studies A critical component of the impacts of the mallee jet fuel is associated with the additional sheep farming. In Australia, sheep Table 7 Comparative uncertainty Monte Carlo simulation results of jet fuel systems. Indicator
Percentage of runs where mallee jet fuel has lower indicator values than for fossil jet fuel
Greenhouse gas emissions Fossil fuel depletion Non-renewable cumulative energy demand
95.6% 99.9% 99.9%
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and lamb numbers declined from a peak of 117.491 million in the 1997e98 financial year (July to June) to a low of 68.085 million in the 2009e10 financial year, before increasing to 74.722 million in 2011e12 [59e61]. Historical trends for the state of Western Australia were similar, declining from a peak of 27.477 million in 1997e98 to a low of 14 million in 2010e11 [59,62]. Over the 1997e2012 period, the number of slaughtered lambs in Australia fell within a range of between 15 and 21 million per year [63]. The reduction in sheep numbers and continual demand for meat is attributable to reductions in the value of wool, relative to meat [64]. The Organisation for Economic Co-operation and Development and the United Nations' Food and Agriculture Organization project that demand for sheep meat will increase at an annual rate of 1.3% to 2022, driven by population increases, and increased per-capita sheep meet production in the developing world [65]. Australia is projected to fulfill much of this demand increase [65]. These factors support the assumption in this study of accounting for increased sheep stocking rates. On the contrary, it is not certain that the sheep farming within the Great Southern region will fill this demand, in part, due to changes in climatic conditions which may make sheep farming more economical in other areas. If supply were to come from other areas, then a reduction in sheep numbers in the Great Southern may occur independently of the plantation of mallee eucalypts. In this case, the removal of the additional sheep from the mallee jet fuel improves the comparative greenhouse gas benefits from 40% to 65%, decreasing greenhouse gas emissions from 35.56 Mg of CO2-eq per flight (g MJ1 of CO2-eq) to 25.76 Mg of CO2eq per flight (g MJ1 of CO2-eq). Given these counter arguments, the applicability of the additional sheep to the mallee jet fuel system is uncertain and further analysis of potential sheep displacement, including potential indirect land use change impacts, is warranted. Approximately 92% of the greenhouse emissions from hydrogen production and compression are associated with the methane steam-reforming process, with emissions of carbon dioxide from the reforming process driving emissions. The greenhouse gas impact of steam-reformed hydrogen was determined to be 9.64 kg kg1 of CO2-eq, and is in line with emission factors reported elsewhere [66]. The recovery of the hydrogen bound within the direct biogenic methane emissions from the bio-oil upgrading processes could reduce the reliance on steam-reformed hydrogen by approximately 30%, reducing the hydrogen production emission factor to 7.37 kg kg1 of CO2-eq. The resultant greenhouse gas profile of the mallee jet fuel would subsequently reduce from 35.56 Mg of CO2-eq per flight (48.0 g MJ1 of CO2-eq) to 33.18 Mg of CO2-eq per flight (44.8 g MJ1 of CO2-eq); a 44% greenhouse gas reduction relative to the fossil jet fuel. A material flow analysis indicated that fossil-based diesel use within the Great Southern Region of the mallee-supply chain (e.g. for road freight) is approximately 1337 L per flight, the quantity of which is more than the biodiesel co-produced with the mallee jet fuel. This use of fossil-based diesel accounts for 3.65 Mg of CO2-eq per flight (4.9 g MJ1 of CO2-eq) and could be reduced to 0.38 Mg of CO2-eq per flight (0.5 g MJ1 of CO2-eq) through the use of the coproduced biodiesel. The resultant profile of the mallee jet fuel would reduce to 32.29 Mg of CO2-eq per flight (43.6 g MJ1 of CO2eq); a 46% greenhouse gas reduction relative to the fossil-based fuel. A greenhouse gas reduction of 50% could be achieved if the biodiesel and alternative hydrogen production pathway were utilized in combination. The net fossil fuel depletion benefit of the mallee jet fuel system is largely driven by total co-production credit of 653.21$ per flight (8.8 104$ MJ1). This credit is comprised of 443.06$ (6.0 104$ MJ1) from the avoidance of black coal production, stemming from the co-production of char during
169
pyrolysis, and 63.34$ and 146.81$ from the co-production of methanol and acetic acid, respectively, during the upgrading to UBB oil. If co-products are allocated based on a mass basis rather than avoided through system expansion, then the mallee jet fuel system shows fossil fuel depletion burdens of 503.05$ (6.8 104$ MJ1), a 43.6% reduction relative to the fossil-based system. The greenhouse gas results of the mallee jet fuel are also affected by the allocation method, decreasing from 35.56 Mg of CO2-eq per flight (48.0 g MJ1 of CO2-eq) using system expansion to 34.87 Mg of CO2-eq per flight (47.1 g MJ1 of CO2-eq) using mass allocation. Regardless of the allocation approach, the mallee jet fuel system shows reduced greenhouse gas and fossil fuel depletion impacts. When the allocation method was changed, the non-renewable CED indicator also change from 58 896 MJ1 (0.08 MJ MJ1) to 283 895 MJ per flight (0.38 MJ MJ1). Caution should be taken in translating the CED values reported in this study to energy return on investment (EROI), due to flow classification and underpinning database issues which are not yet resolved in LCA [67]. 4. Conclusions The theoretical mallee jet fuel demonstrated potential to reduce both greenhouse gas emissions and reliance on fossil fuels, whilst maintaining sheep production. The magnitudes of the environmental benefits are sensitive to the treatment of potential sheep displacement and allocation of co-products. The capture and use of wastewater methane for hydrogen production, and utilizing coproduced biodiesel within the supply chain can further reduce environmental burdens. The uncertainty in projecting future system means that the results of this study may change. When considering the full environmental impacts, other indicators including biodiversity, soil salinity and potential indirect land use change should be explored. Acknowledgments This work was funded by Airbus through the Future Farm Industries Co-operative Research Centre Limited. The author acknowledges data input from IFP Energies nouvelles, Dynamotive Energy Systems Corporation and Enecon Pty. Ltd. Prof. Annette Cowie is acknowledged for conducting an independent ISO14044:2006 peer-review of the original LCA study (not publically available, but upon which this article is based). Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.biombioe.2016.11.014. References [1] D.S. Lee, D.W. Fahey, P.M. Forster, P.J. Newton, R.C.N. Wit, L.L. Lim, et al., Aviation and global climate change in the 21st century, Atmos. Environ. 43 (22e23) (2009) 3520e3537. [2] J.E. Penner, D.H. Lister, D.J. Griggs, D.J. Dokken, M. McFarland, Summary for Policymakers. Aviation and the Global Atmosphere. A Special Report of Working Groups I and III of the Intergovernmental Panel on Climate Change, Intergovernmental Panel on Climate Change, Geneva, 1999, p. 23. [3] IPCC, Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, IPCC, Geneva, Switzerland, 2007, p. 104. [4] E. Corporan, M.J. DeWitt, V. Belovich, R. Pawlik, A.C. Lynch, J.R. Gord, et al., Emissions characteristics of a turbine engine and research combustor burning a FischerTropsch jet fuel, Energy fuels 21 (5) (2007) 2615e2626. [5] X. Hui, K. Kumar, C.-J. Sung, T. Edwards, D. Gardner, Experimental studies on the combustion characteristics of alternative jet fuels, Fuel 98 (2012) 176e182.
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Research paper
Life cycle assessment of a mallee eucalypt jet fuel Enda Crossin School of Engineering, RMIT University, PO Box 71, Bundoora, Victoria, Australia
a r t i c l e i n f o
a b s t r a c t
Article history: Received 24 February 2016 Received in revised form 23 November 2016 Accepted 24 November 2016 Available online 2 December 2016
This study uses life cycle assessment to quantify and compare the greenhouse gas emissions and fossil fuel depletion impacts of a theoretical mallee jet fuel value chain, operating in the Great Southern region of Western Australia, with those of fossil-based jet fuel. Relative to fossil-based jet fuel, the mallee jet fuel was found to reduce greenhouse gas emissions by 40% and result in a net fossil fuel depletion benefit. Further greenhouse gas reductions could be achieved by optimizing the supply chain through measures such as capturing methane emissions for hydrogen production and utilizing co-produced biodiesel. The magnitudes of the environmental benefits are sensitive to a number of methodology assumptions, including the approach to potential food displacement and co-production. © 2016 Elsevier Ltd. All rights reserved.
Keywords: Life cycle analysis Biofuels Greenhouse gas Biomass Eucalyptus spp
1. Introduction The aviation industry contributes to an estimated 3.5%e4.9% of global radiative forcing impacts [1,2] associated with the combustion of aviation and jet fuels. Environmental pressures on the aviation sector [3] have contributed to the development of fuels based on biomass. A number of technologies can produce biomassbased jet fuels, including Fischer-Tropsch synthesis [4], hydroprocessing [5], and pyrolytic (pyrolysis) processing [6]. The biomass feedstock can include microalgae [7,8], oil-rich crops such as rapeseed and soybeans [9,10], and other crops, including corn and sugarcane [11]. Indirect land use change effects, including deforestation and displacement of food, together with low biomass yields and soil degradation are often cited as major environmental concerns associated with biomass production [11e13]. Plant biomass, produced on marginal or degraded lands, has been suggested as a way of limiting indirect land use change effects [12,14]. The use of lignoceullosic biomass can improve effective yields [13]. One potential lignoceullosic biomass is from harvested mallee eucalypt trees, including Eucalyptus loxphleba subspp. lissophloia and gratiae, Eucalyptus kochii subspp. plenissima, borealis and kochii, Eucalyptus polybractea, Eucalyptus myriadena, and Eucalyptus angustissima subsp. angustissima [15]. The mallee biomass can be processed to produce bio-oil and subsequently gasoline, diesel fuel, and kerosene-like fuel suitable for use jet in aircraft. After the
E-mail address: [email protected]. http://dx.doi.org/10.1016/j.biombioe.2016.11.014 0961-9534/© 2016 Elsevier Ltd. All rights reserved.
biomass is harvested, the mallee eucalypts regenerate, allowing for ongoing harvests. A critical aspect to the implementation and approval for use biomass jet fuels is environmental performance [16]. Life cycle assessment (LCA) is one of the main methodologies used to quantify environmental performance of biomass fuel systems [13,17e22]. Previous LCAs on mallee biomass focus on energy balances of the biomass production activity in isolation of further processing [23,24] and it is not known if mallee jet fuel results in environmental benefits over the full life cycle. This paper addresses this knowledge gap by assessing the full life cycle environmental performance of jet fuel produced from mallee biomass (mallee jet fuel) relative to those produced from crude oil (fossil jet fuel). Drivers of environmental impacts are discussed, and effects of potential food displacement are critically evaluated. Opportunities for reduced environmental impact are outlined and variations in results with LCA approaches co-production are explored. Finally, limitations on the applicability of the outcomes are outlined together with directions for future research. 2. Methods The LCA study was undertaken in accordance with ISO 14044:2006 [25]. The LCA process includes defining the study goal and scope, establishing a life cycle inventory, translating environmental flows into quantified environmental impacts, and interpreting the relationship between process flows and environmental impacts. The study goal, scope, and inventory are described in this
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section, while the environmental impacts and interpretation are reported in the results and discussion, respectively. Life cycle inventory modeling and life cycle impact assessment were performed using SimaPro 8.0.4.6 software. 2.1. Goal of the study The goal of the LCA study was to compare the climate change impacts and fossil fuel depletion impacts of jet fuel derived from mallee biomass and fossil fuels. The outcomes of this LCA were used by Future Farm Industries Cooperative Research Centre Ltd. (FFICRC) as part of a broader sustainability assessment report (not publicly available) submitted to the Roundtable on Sustainable Biomaterials. This LCA study was commissioned by the FFICRC, and involved participants from Airbus S.A.S. Manchester Metropolitan University, Virgin Australia Pty. Ltd., Enecon Pty. Ltd, Dynamotive Energy Systems Corporation, and IFP Energies Nouvelles. 2.2. Scope of the study 2.2.1. Description of product systems The mallee jet fuel system was based on a theoretical supply chain, operating over a thirty year period from 2022 to 2052. This theoretical supply chain was established as part of a business case, developed in 2011 by Renewable Oil Corporation Pty. Ltd. (ROC) in partnership with FFICRC [26]. The growing and harvesting schemes, and the location of processing facilities were modelled and selected by experts, based on technical and financial analyses, government regulations and the presence of existing infrastructure. Details of the theoretical supply chain are reported elsewhere [26]; however, an overview is provided below. The theoretical mallee jet fuel supply chain starts with the establishment of mallee crops in the Great Southern region of Western Australia, a region which currently produces canola, wheat and barley. Establishment of the mallee crop will involve the application of herbicides, soil preparation, site preparation and planting. Nutrient build-up in soils from prior agricultural activities means that fertilizers will not be typically needed prior to planting. The first harvest should typically occur six years after plantation, followed by subsequent harvests every four years. Following harvesting, the biomass will be transported by articulated road freight to one of two drying and pyrolysis processing facilities, located within a 100 km radius of supporting farms. At each of these facilities, the biomass will be ground and then stored. Following storage, the biomass moisture will be reduced using an electric rotary drum dryer, heated using a fraction of the outgoing dried biomass. The dried biomass will then be pyrolytically processed, producing non-condensable gases (NCGs), char and bio-oil. The bio-oil will be stored on site, before transportation to Kwinana via articulated road freight for upgrading. The bio-oil is typically unstable, low in energy density, and acidic [6], and requires upgrading for end-use. The IFP Energies Nouvelles process of upgrading biooil will be used and occurs in three steps: hydro-reforming (to UBA), hydro-treatment (to UBB) and fractionation to fuels. The hydro-reforming and hydro-treatment require compressed hydrogen inputs. The source for the hydrogen inputs are yet to be finalised, but were assumed to be steam-reformed natural gas. The current ASTM D7566 standards limit the use of jet biofuels to blends with traditional jet fuel of between 10% and 50% by volume [27]. However, it is anticipated that ASTM D7566 will allow for the certification of 100% synthetic jet fuel in the future [28]. As such, this study assumed that a 100% mallee jet fuel will be used. Following fractionation, the mallee jet fuel will be transported via articulated truck from Kwinana for intermittent storage at Perth Airport and subsequent use in aircraft.
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The alternative system assessed in the LCA study is based on conventional jet fuel production. This involves the exploration and extraction of crude oil from the Middle East, the transport of crude oil to a refinery in Kwinana, the processing and fractionation of crude oil to jet fuel, transport to the airport and intermittent storage, and finally combustion in a jet turbine for flight operations. 2.2.2. Function and functional unit The focus of this study was the use of jet fuel in an Airbus A330200 aircraft jet, which transports people over a distance. The delivery of the mallee jet fuel at Perth airport means that the aircraft can only refuel with mallee jet fuel at that location. Therefore, the environmental assessment is based on the functional unit of one flight, consisting of one typical Airbus A330-200 commercial passenger aircraft flight, operating twin Rolls Royce Trent 772B turbines, between Perth and Sydney (Kingsford Smith) airports. The operation of an Airbus A330-200 on the return leg (from Sydney to Perth) is outside the scope of this project. It is recognized that for comparison purposes, an alternative functional unit can be useful. As such, key results are also reported per MJ of jet fuel. 2.2.3. System boundary The system boundary outlines the processes to be included in the assessment, Fig. 1. These include farming, biomass processing, transport, aircraft operation, infrastructure, the production of electricity, natural gas, fertilizers and soil modifiers, herbicide and pesticides, reticulated water and wastewater treatment. Some infrastructure processes were excluded (e.g. factories, roads), along with human labour, wetting agents, surfactants and administration overheads. The estimated cut-off of elementary flows was 1% of the cumulative mass flows. 2.2.4. Allocation procedures The ISO 14044:2006 [25] hierarchal procedure for partioning was applied to handle processes with multpiple functions. Weidema's [29] system expansion approach was applied to avoid allocation in two processes: pyrolysis, where char is co-produced with bio-oil, and the upgrading of bio-oil, which produces coproduces UBA oil, methanol and acetic acid. The production of bio-oil was ascribed the environmental impacts of the pyrolysis process, as well as char storage. Environmental credits were applied to the pyrolysis process for the avoidance of coal production. No environmental credits were applied for avoided emissions from coal combustion as no char is combusted in the pyrolysis process. For the upgrading of bio-oil, the refined UBA oil was ascribed all process impacts, with credits applied for avoided acetic acid and methanol production. Mass allocation were applied to these processes in a sensitivity study. Energy allocation was applied to fractionation processes. Freight processes were allocated by mass. Energy and economic allocation was applied to the refining of unleaded petroleum products, in line with previous literature [30]. 2.2.5. Life cycle impact assessment methodology and types of impacts The scope of the environmental assessment was limited to climate change impacts and fossil fuel depletion. An assessment of eutrophication, land-use, soil salinity, indirect land use change and water stress impacts were outside the scope if this study, but were addressed in the FFICRC report. LCIA was performed for greenhouse gas emissions and fossil fuel depletion by multiplying environmental flows of the various resources and greenhouse gas emissions by their respective characterization factors. Characterization factors for greenhouse gas emissions were based on global warming potentials (GWPs) for a 100-year time horizon, as reported in the Intergovernmental Panel on Climate Change (IPCC) Fourth
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Fig. 1. System boundary for life cycle assessment.
Assessment Report (2007). The global warming potential for biogenic methane was adjusted to 22.25 kg kg1 of CO2-eq to account for biogenic carbon dioxide sequestration [31]. Biogenic carbon dioxide uptake (raw) and air emissions were both assigned a global warming potential of zero. The treatment of non-degraded biogenic carbon in soil, including below-ground carbon storage stemming from direct land use change, is assumed to be stored beyond the 100-year assessment period. To account for the proportion of the carbon dioxide uptake that was not released (i.e. stored as below ground carbon), inventories of carbon dioxide storage were assigned a characterization of 1 kg kg1 of CO2-eq, consistent with previous literature [32,33]. No correction factors were applied to the GWP of greenhouse gases emitted at altitude, consistent with other greenhouse gas protocols [34,35]. Fossil fuel depletion impacts were assessed using the ReCiPe endpoint indicator, which translates fossil fuel depletion into a measure (USD$) of increased resource extraction costs [36]. To facilitate future comparisons of fuel systems beyond this study, non-renewable cumulative energy demand were reported based on the CML Baseline method [37]. 2.2.6. Data and data quality requirements An assessment of the foreground data requirements was undertaken in accordance with the data quality indicators outlined in ISO 14044:2006 [25], including technology, precision, geography, time, consistency, reproducibility and completeness. The assessment of the minimum data quality required to fulfil the goal and scope of the study is provided in Table 1. An assessment of the
inventory data utilized was completed in accordance with ISO 14044:2006 [25] and are discussed in subsequent sections. 2.2.7. Interpretation approach used The interpretation approach used results from the life cycle inventory and LCIA to identify significant issues. Sensitivity studies included assessing alternative approaches to the handling of additional sheep farming and allocation, hydrogen production pathways and the supply of diesel fuel to transport systems within the system boundary. The uncertainty of the foreground data was quantified using error ranges (if available) or the pedigree matrix [38], which used qualitative judgements on the inventory data precision, completeness, and temporal, geographical and technological correlations. This foreground uncertainty data was coupled with existing uncertainties in background data to perform an uncertainty analysis, using one thousand (1000) Monte Carlo simulations. 2.3. Life cycle inventory This section focuses on reporting key inventory assumptions. Foreground life cycle inventory data was collated for and coupled with background life cycle inventory databases. The elementary flows required to deliver the functional unit are provided in Table 2. Full foreground inventory details are provided in the Supporting Information. Data for the establishment, harvesting, ongoing management, and below-ground biomass values for mallee were provided by the
E. Crossin / Biomass and Bioenergy 96 (2017) 162e171
165
Table 1 Minimum data quality requirements for inventory. Specific Technology (ST), Technology Mix (TM), not applicable (NA), very good (þþ), good (þ), average (AVG), WA (Western Australia). Inventory Item
Technology
Precision
Geography
Time
Representativeness
Consistency
Reproducibility
Completeness
Crude oil production Aircraft emissions Sea freight of crude oil Catalyst production and waste CO2 emissions from urea Fertiliser production Pesticide and herbicide production Road transport Electricity production and distribution Mallee farming - establishment Mallee farming e direct land-use change Mallee farming e ongoing management Mallee farming - harvesting Biomass grinding Biomass drying Pasture management and sheep farming N2O emissions from fertilisers Fast pyrolysis UBA/UBB upgrading Refining of Jet A-1 Refining of UBB to jet fuel Hydrogen production e steam reforming Hydrogen production - compression Reticulated water Aircraft fuel use
ST
þþ
Global
2034e35
þþ
þþ
þþ
>99%
TM
AVG
NA TM
þ AVG
ST
þþ
WA
WA (SWIS) WA e Great Southern
þ NA ST
þþ
WA - Kwinana
TM ST Perth to Sydney
Table 2 Reference flows required to deliver one flight for jet fuel systems. Output
Mallee jet fuel
Fossil jet fuel
Unit
Combusted fuel Biofuel Fossil-based jet fuel Synthetic UBB oil Hydrogen for upgrading bio-oil Bio-oil Dry biomass Wet biomass Mallee farming Land use change Additional sheep farming
17 184.64 17 184.64 e 16 976.28 1037.22 44 472.92 72 313.7 144 939.7 9.0588 0.302 69.2
17 184.64 e 17 184.64 e e e e e e e e
kg kg kg kg kg kg kg kg ha y ha p
FFICRC. The total mallee planation area was assumed to be 147.42 km2. Direct land use change from the plantation of mallee eucalypts calculated based on the difference in carbon intensity between the current (reference) carbon stock, CSR and the future (actual) carbon stock, CSA. CSR and CSA, consistent with European Union guidelines [39]. CSA was estimated using:
CSR ¼ ðSOC þ CVEG Þ A
(1)
where SOC is the standards soil organic carbon in topsoil, CVEG is the above and below ground vegetation carbon stock and A is the area. SOC was estimated using:
SOC ¼ SOCST FLU FMG FI
(2)
where SOCST is the standard soil organic carbon in the topsoil layer, determined by the climate region and soil type. The region's climate and soil characteristics correspond to an SOCST of 19 Mg ha1 of carbon [39]. FLU is the land use factor, FMG is the management factor and FI is the input factor. Currently, grazing land rotates between grassland and cropland. At any one time on average, 26.7% of grazing land is under grass, while 73.3% is under crop. CVEG, FLU, FMG and FI vary with farming practice and the
plantation type, values of which reported in the EU directive documents [39] and summarized in Table 3. Carbon stocks for the current (reference) land were determined by summing the carbon stocks for the grassland and cropland fractions. Carbon stocks for the future (actual) land were determined using:
CSA ¼ ðSOC AÞ þ CAGB þ CDOM þ CBG
(3)
where SOC and A are defined previously, CAGB is the above ground carbon, CDOM is the above ground dead organic matter and CBG is the below ground carbon. The sum of CAGB, CDOM and CBG is analogous to CVEG and values are reported in Table 3. Using this approach, carbon stocks due to direct land use change were estimated to increase by 6.49 Mg ha1. This carbon stock change, together with the impacts of crop establishment, were allocated equally over 30 years of farming activity, in line with European Union guidelines [39]. Following this thirty-year horizon, no further claims can be made on changes in the below-ground carbon. The mallee crops were assumed to be harvested six years after plantation, at a biomass yield of 60 Mg ha1, with subsequent harvests occurring every 4 years at a yield of 70 Mg ha1. Over a 30year period, the total harvest of green biomass was calculated as 480 Mg ha1, equating to an average yield of 68.57 Mg ha1. Onfarm diesel use for mallee crops was assumed to be 3.51 L Mg1 of harvested biomass, accounting for harvesting, haulage and shunting. Single superphosphate, potassium chloride (as potash) and urea fertilizers were assumed to be applied at rates of 198 kg ha1, 391 kg ha1 and 195 kg ha1 respectively after the first harvest, and 231 kg ha1, 456 kg ha1 and 195 kg ha1 respectively for subsequent harvests. The application of nitrogen-based fertilizers can result in emissions of nitrous oxide through nitrification, volatilization and denitrification processes, which are sensitive to a number of factors [40e43] including soil structure and particle size, climate conditions, nitrogen uptake by crops, soil conditions, fertilizer application rates and timing, and drainage conditions. This study used a nitrous oxide emission (direct and indirect) factor of 0.3% of applied nitrogen [44], equivalent to 1.7 kg ha1 and 1.98 kg ha1 of nitrous oxide air emissions for the initial and
166
E. Crossin / Biomass and Bioenergy 96 (2017) 162e171
Table 3 Determination of changes in carbon stock due to direct land use change. Factor
Reference (current)
Future (actual)
Grassland Standard soil organic carbon in topsoil, SOCST Land use factor, FLU Management factor, FMG Input factor, FI Soil organic carbon, SOC Reference area, A Above-ground biomass, CAGB Dead organic matter, CDOM Below-ground biomass, CBG CVEG Fractional reference carbon stocks, CSR Total reference carbon stock, CSR Actual (future) carbon stock, CSA Change in carbon stock, C
Cropland
1
19 Mg ha (sandy soils) 1.0 1.14 (improved) 1.0 (Medium carbon input) 16.72 Mg ha1 0.267 ha e e e 0 4.47 Mg 22.61 Mg e 6.49 Mg ha1
subsequent fertilizer applications, respectively. Carbon dioxide air emissions from the application of urea used the default factor from the IPCC [45], equivalent to 287 kg ha1 and 334 kg ha1 of carbon dioxide air emissions for the initial and subsequent fertilizer applications, respectively. Historically, the yield of dry-sheep equivalent (DSE) in pastured areas in the region averages 7.64 ha y1. In this study, mallee plantations were assumed to displace some of this area. In order to accommodate potential reductions in sheep numbers, it was assumed that additional sheep could be accommodated within the remaining pastured land by increasing the stocking rate of DSE by 0.57 ha y1 to 8.21 ha y1. This approach ensures that the functional equivalency of sheep production is maintained. Process inputs for sheep farming were based on Ref. [46], while enteric, dung and urine emissions were based on [47e49]. Data for biomass and pyrolysis processing were provided by Enecon Pty. Ltd. (Australia) and Dynamotive Energy Systems (Canada). Electricity requirements for grinding the wet (45% moisture by mass) biomass was assumed to be 6.12 kWh Mg1 of wet biomass. The loss of wet biomass chips during intermediate storage were estimated to be 3% mass fraction [50]. The rotary drum drier was assumed to use 15.9% mass fraction of its dry biomass (10% moisture by mass) output for heat, with the remaining dry mass flowing into a pyrolysis unit. Supplementary electricity for running of motors was assumed to be 1.23 kWh Mg1 of dried biomass. The two pyrolysis units were assumed to process 200 Mg d1 of dry biomass, with yields of 30.8 Mg d1 of NCGs, 38.2 Mg d1 of char and 131.0 Mg d1 of bio-oil. The NCGs were assumed to be used as both a carrier gas for the incoming biomass, as well as for heat. The pyrolysis unit was assumed to combust 7.9 Mg d1 of bio-oil, resulting in a net bio-oil output of 123.1 Mg d1. The char was assumed to be sold (as the most profitable use) as a substitute for black coal, and not used for heat within the process. Processing data for upgrading of bio-oil to fuels were provided by IFP Energies nouvelles (France). Inputs for the production of 1 kg of upgrading bio-oil to UBB oil were assumed to be 2.62 kg of bio-oil and 61 g of hydrogen gas at 12.5 MPa. For every 1 kg of UBB oil produced, the upgrading process was assumed to co-produce 90 g of methanol and 147 g of acetic acid, to be sold as co-products. In addition to these product outputs, process emissions were assumed to be 1.113 kg of wastewater, 74 g methane, 222 g carbon dioxide and 35 g carbon monoxide gases. The methane gas was assumed to be captured for combustion and process heat, producing 204 g of carbon dioxide for every 1 kg of UBB oil, while the other gases were assumed to be emitted to air. The wastewater was assumed to be
Mallee 1
19 Mg ha1 (sandy soils) 1.0 1.1 0.95 (low carbon input) 19.86 Mg ha1 1 ha 0 Mg (harvested) 0.46 Mg [68] 8.79 Mg (peak at 20 years) 9.25 Mg e e 29.10 Mg
19 Mg ha (sandy soils) 0.8 1.1 (no tillage) 1.0 (medium carbon input) 21.66 Mg ha1 0.733 ha e e e 2.27 Mg 18.15 Mg
treated at a municipal wastewater facility. Inventory data for the fractionation of UBB oil to refined fuels are commercial-inconfidence and are thus not reported. The hydrogen for upgrading of bio-oil was assumed to be supplied from a methane stream-reformer (MSR). The work needed to compress hydrogen gas from 2 MPa to 12.5 MPa was estimated using the adiabatic compression equation:
g
2
p p V 4 1 W¼ g 1 0 0 p0
g1 g
3 15
(4)
where g is the adiabatic coefficient (1.41 for hydrogen), V0 is the initial volume and p0 and p1 refers to the initial and final pressures, respectively. At an initial pressure of 2 MPa and 20 C (typical outlet pressure of an MSR), 1.01 kg (assuming 0.01 kg is compressed, but then lost) of hydrogen gas has an initial volume of 0.6103 m3. Using these values and the final pressure of 12.5 MPa, and a compressor efficiency of 80% and 1% hydrogen losses in delivery, the electrical input required to deliver 1 kg of hydrogen was calculated as 1.026 kWh. No literature was available to validate the electricity requirements for this pressure increase. However, compression of hydrogen from 2 MPa to 44 MPa has been measured at between 2.0 and 2.2 kWh kg1 [51], which is similar to a calculated value 2.1 kWh kg1, using the approach above. Electricity impacts were based on a projection of a 2034e35 electricity grid mix for Western Australia's South-West Interconnected System (SWIS). Electricity demand from the SWIS grid is projected to increase from 28 TWh in 2008e09 to 46 TWh in 2034e35 [52]; an increase of 18 TWh. The increase in demand in 2034e35 is expected to be fulfilled through a new gasefired plant at Kwinana accounting for 12.96 TWh of this increase, with the remainder expected to be met by other new black coal and renewable energy projects [53]. These new projects were coupled with the existing SWIS grid mix to estimate the 2034e35 grid mix, Table 4. Transmission and distribution losses were estimated to be 5.3% [54]. The inventory for the production of fossil-based jet fuel production was based on an existing ecoinvent 2.2 process for exploration and extraction of crude oil in the Middle East. The inventory for crude oil refining at Kwinana was based on an existing study [30]. An overview of the transport network for both systems, including assumed transport distances and modes, is provided in Fig. 2. The mallee biomass was assumed to be harvested from farms
E. Crossin / Biomass and Bioenergy 96 (2017) 162e171 Table 4 Projected 2034e35 electricity mix for South-West Interconnected System. Source
Production (GWh)
Black coal Natural gas Oil products Other (combined cycle gas) Biogas Wind Solar PV Black coal (new projects) Wind (new projects) Natural gas (new projects) Total generation Transmission and distribution losses (5.3%) Electricity at consumer
10352.3 18115.7 1413.8 1029.4 111.7 441.1 112.8 2917.3 1193.9 12960.0 48648.0 2578.3 46069.7
within a 100 km radius of two pyrolysis processing units in Katanning. The average distance of any point in a circle to the centre is 2/3 the radius. Therefore, an average centroid transport distance of 66.6 km was assumed. The bio-oil was assumed to be transported by articulated truck to the upgrading facility in Kwinana. The mallee jet fuel was assumed to be transported by articulated truck from Kwinana to Perth Airport. For the fossil jet fuel, crude oil was assumed to be shipped from Dubai to Melbourne via Singapore. The refined jet fuel was assumed to be transported to an intermediate storage via pipeline, before being transported via articulated truck to Perth Airport. The hydrogen production and compression facility was assumed to be co-located with the upgrading facility. Sea freight distances were estimated using a port to port calculator [55], while other road freight distances were based on location data
167
and mapping estimates using Google maps [56]. The mallee and fossil jet fuels considered in this study have the same energy and volumetric densities, as such, there are no differences in fuel-burn. The average fuel use for an Airbus A330-200 flight from Perth to Sydney was provided by Virgin Australia as 17184.6 kg. The fuel use of 2230 kg for landing and take-off (LTO) operations and associated greenhouse gas emissions associated were from IPCC guidelines [57]. Greenhouse gas emission factors for the remaining 14954.6 kg of fuel use at altitude were calculated using emissions factors from the Australian National Greenhouse Account Factors [58]. It was assumed that the fuels have an equivalent energy density of 43.1 MJ kg1. A qualitative assessment on the inventory data quality are reported in Table 5. In many instances, the minimum data quality requirements outlined in Table 1 were not met. However, it was considered that life cycle inventory data were complete and representative of the systems considered, and that the quality of this data was sufficient to fulfil the goals and scope of this study, which is reflected in the peer review that deemed this study as compliant to the requirements of ISO14044:2006.
3. Results and discussion 3.1. Baseline scenario Disaggregated life cycle impact assessment results are reported in Table 6. The greenhouse gas impacts of the mallee jet fuel are 35.56 Mg of CO2-eq per flight; 40% lower than 59.43 Mg of CO2-eq per flight for the fossil jet fuel. These greenhouse gas emissions are equivalent to 48.0 g MJ1 and 80.2 g MJ1 of CO2-eq for the mallee
Fig. 2. Overview of distribution network for fossil jet fuel and mallee jet fuel.
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E. Crossin / Biomass and Bioenergy 96 (2017) 162e171
Table 5 Disaggregated life cycle impact results. Process
Direct land use change Additional sheep farming Biomass farming and harvesting Biomass processing to bio-oil Co-production credits H2 production and compression Upgrading/refining of bio-oil to fuel Crude supply and refining to jet fuel Fuel delivery to airport Combustion Infrastructure, inc. catalyst prod. Total
Greenhouse gas emissions
Fossil fuel depletion
Cumulative non-renewable energy demand
Mg of CO2-eq per flight
Increased cost, $ per flight
MJ per flight
Mallee jet fuel
Fossil jet fuel
Mallee jet fuel
Fossil jet fuel
Mallee jet fuel
Fossil jet fuel
7.19 14.76 4.85 8.86 2.62 11.00 4.95 e 0.15 0.06 0.74 35.56
e e e e e e e 4.89 0.03 54.51 e 59.43
e 16.10 60.82 129.55 653.21 273.64 103.60 e 2.11 e 11.66 55.72
e e e e e e e 892.84 0.44 e e 893.28
e 9903 50 428 107 190 547 847 222 302 84 577 e 1767 e 84 577 58 896
e e e e e e e 363 747 676 e e 748 039
Table 6 Qualitative data quality assessment of foreground inventory; very good (þþ), good (þ), average (0), poor (), very poor ( ), not applicable (NA). Inventory Item
Geographical Time Technology Foreground coverage coverage precision
Consistency Reproducibility Completeness Representativeness (minimum of time and geographical coverage)
Crude oil production Aircraft emissions Sea freight of crude oil Catalyst production and waste CO2 emissions from urea Fertilizer production Pesticide and herbicide production Road transport Electricity production and distribution Mallee farming - establishment Mallee farming e direct land-use change Mallee farming e ongoing management Mallee farming - harvesting Biomass grinding Biomass drying Pasture management and sheep farming N2O emissions from fertilizers Fast pyrolysis UBA/UBB upgrading Refining of UBB to jet fuel Hydrogen production e steam reforming Hydrogen production e compression Reticulated water Aircraft fuel use
þþ þ þþ 0 þ þþ þþ þþ þ 0 þþ þ þ 0 0 0 þ 0 0 0 0 0 þ þ
þþ þþ þþ þþ þþ þþ þþ þþ þþ þþ 0 0 0 0 þþ 0 0 þþ þþ
and fossil jet fuels, respectively. The greenhouse gas impacts of the mallee jet fuel are dominated by the additional impacts of sheep farming, accounting for 14.76 Mg of CO2-eq per flight (10.9 g MJ1 of CO2-eq), as well as the production and supply of compressed hydrogen for upgrading, accounting for 11.00 Mg of CO2-eq per flight (8.1 g MJ1 of CO2-eq). These two processes account for over 50% of the mallee jet fuel greenhouse gas impacts and are the focus of the discussion on the mallee jet fuel system. In addition to the greenhouse gas reductions, the bio-fuel system shows reduced fossil fuel depletion impacts, decreasing from a total burden of 893.28$ per flight (1.2 103$ MJ1) to a net benefit of 55.72$ per flight (7.5 105$ MJ1), Table 6. Similarly, the cumulative nonrenewable energy demand (CED) indicator, Table 6, reduced from 748 039 MJ1 per flight (1.01 MJ MJ1) to 58 896 MJ1 per flight (0.08 MJ MJ1). Over 99.9% of both the fossil fuel depletion impacts and CED indicator values were driven by the extraction, supply and production of crude oil reserves in the Middle East. The Monte Carlo uncertainty results are reported in Table 7 and indicate a high level of confidence in the comparative outcomes.
NA þ þþ þ NA NA 0 þ 0 þ 0 0 0 þ e Confidential þ þ þ þ
þþ þþ þþ 0 þþ þþ þþ þþ þ þþ þþ 0 þþ 0 þ þþ þþ þþ þþ þþ 0 0 þ þþ
þþ þþ þþ 0 þþ þ þ þþ þ þþ þþ þþ þþ þþ þþ þ þþ þþ þþ þþ þþ þ þþ
þþ þþ 0 þþ þþ þþ þþ þþ 0 0 þþ
The absolute uncertainty of the individual systems will be higher than the comparative uncertainty, due to shared uncertainty. As such, the outcomes in Table 7 should not be interpreted as confidence in the environmental assessments of the individual systems. 3.2. Sensitivity studies A critical component of the impacts of the mallee jet fuel is associated with the additional sheep farming. In Australia, sheep Table 7 Comparative uncertainty Monte Carlo simulation results of jet fuel systems. Indicator
Percentage of runs where mallee jet fuel has lower indicator values than for fossil jet fuel
Greenhouse gas emissions Fossil fuel depletion Non-renewable cumulative energy demand
95.6% 99.9% 99.9%
E. Crossin / Biomass and Bioenergy 96 (2017) 162e171
and lamb numbers declined from a peak of 117.491 million in the 1997e98 financial year (July to June) to a low of 68.085 million in the 2009e10 financial year, before increasing to 74.722 million in 2011e12 [59e61]. Historical trends for the state of Western Australia were similar, declining from a peak of 27.477 million in 1997e98 to a low of 14 million in 2010e11 [59,62]. Over the 1997e2012 period, the number of slaughtered lambs in Australia fell within a range of between 15 and 21 million per year [63]. The reduction in sheep numbers and continual demand for meat is attributable to reductions in the value of wool, relative to meat [64]. The Organisation for Economic Co-operation and Development and the United Nations' Food and Agriculture Organization project that demand for sheep meat will increase at an annual rate of 1.3% to 2022, driven by population increases, and increased per-capita sheep meet production in the developing world [65]. Australia is projected to fulfill much of this demand increase [65]. These factors support the assumption in this study of accounting for increased sheep stocking rates. On the contrary, it is not certain that the sheep farming within the Great Southern region will fill this demand, in part, due to changes in climatic conditions which may make sheep farming more economical in other areas. If supply were to come from other areas, then a reduction in sheep numbers in the Great Southern may occur independently of the plantation of mallee eucalypts. In this case, the removal of the additional sheep from the mallee jet fuel improves the comparative greenhouse gas benefits from 40% to 65%, decreasing greenhouse gas emissions from 35.56 Mg of CO2-eq per flight (g MJ1 of CO2-eq) to 25.76 Mg of CO2eq per flight (g MJ1 of CO2-eq). Given these counter arguments, the applicability of the additional sheep to the mallee jet fuel system is uncertain and further analysis of potential sheep displacement, including potential indirect land use change impacts, is warranted. Approximately 92% of the greenhouse emissions from hydrogen production and compression are associated with the methane steam-reforming process, with emissions of carbon dioxide from the reforming process driving emissions. The greenhouse gas impact of steam-reformed hydrogen was determined to be 9.64 kg kg1 of CO2-eq, and is in line with emission factors reported elsewhere [66]. The recovery of the hydrogen bound within the direct biogenic methane emissions from the bio-oil upgrading processes could reduce the reliance on steam-reformed hydrogen by approximately 30%, reducing the hydrogen production emission factor to 7.37 kg kg1 of CO2-eq. The resultant greenhouse gas profile of the mallee jet fuel would subsequently reduce from 35.56 Mg of CO2-eq per flight (48.0 g MJ1 of CO2-eq) to 33.18 Mg of CO2-eq per flight (44.8 g MJ1 of CO2-eq); a 44% greenhouse gas reduction relative to the fossil jet fuel. A material flow analysis indicated that fossil-based diesel use within the Great Southern Region of the mallee-supply chain (e.g. for road freight) is approximately 1337 L per flight, the quantity of which is more than the biodiesel co-produced with the mallee jet fuel. This use of fossil-based diesel accounts for 3.65 Mg of CO2-eq per flight (4.9 g MJ1 of CO2-eq) and could be reduced to 0.38 Mg of CO2-eq per flight (0.5 g MJ1 of CO2-eq) through the use of the coproduced biodiesel. The resultant profile of the mallee jet fuel would reduce to 32.29 Mg of CO2-eq per flight (43.6 g MJ1 of CO2eq); a 46% greenhouse gas reduction relative to the fossil-based fuel. A greenhouse gas reduction of 50% could be achieved if the biodiesel and alternative hydrogen production pathway were utilized in combination. The net fossil fuel depletion benefit of the mallee jet fuel system is largely driven by total co-production credit of 653.21$ per flight (8.8 104$ MJ1). This credit is comprised of 443.06$ (6.0 104$ MJ1) from the avoidance of black coal production, stemming from the co-production of char during
169
pyrolysis, and 63.34$ and 146.81$ from the co-production of methanol and acetic acid, respectively, during the upgrading to UBB oil. If co-products are allocated based on a mass basis rather than avoided through system expansion, then the mallee jet fuel system shows fossil fuel depletion burdens of 503.05$ (6.8 104$ MJ1), a 43.6% reduction relative to the fossil-based system. The greenhouse gas results of the mallee jet fuel are also affected by the allocation method, decreasing from 35.56 Mg of CO2-eq per flight (48.0 g MJ1 of CO2-eq) using system expansion to 34.87 Mg of CO2-eq per flight (47.1 g MJ1 of CO2-eq) using mass allocation. Regardless of the allocation approach, the mallee jet fuel system shows reduced greenhouse gas and fossil fuel depletion impacts. When the allocation method was changed, the non-renewable CED indicator also change from 58 896 MJ1 (0.08 MJ MJ1) to 283 895 MJ per flight (0.38 MJ MJ1). Caution should be taken in translating the CED values reported in this study to energy return on investment (EROI), due to flow classification and underpinning database issues which are not yet resolved in LCA [67]. 4. Conclusions The theoretical mallee jet fuel demonstrated potential to reduce both greenhouse gas emissions and reliance on fossil fuels, whilst maintaining sheep production. The magnitudes of the environmental benefits are sensitive to the treatment of potential sheep displacement and allocation of co-products. The capture and use of wastewater methane for hydrogen production, and utilizing coproduced biodiesel within the supply chain can further reduce environmental burdens. The uncertainty in projecting future system means that the results of this study may change. When considering the full environmental impacts, other indicators including biodiversity, soil salinity and potential indirect land use change should be explored. Acknowledgments This work was funded by Airbus through the Future Farm Industries Co-operative Research Centre Limited. The author acknowledges data input from IFP Energies nouvelles, Dynamotive Energy Systems Corporation and Enecon Pty. Ltd. Prof. Annette Cowie is acknowledged for conducting an independent ISO14044:2006 peer-review of the original LCA study (not publically available, but upon which this article is based). Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.biombioe.2016.11.014. References [1] D.S. Lee, D.W. Fahey, P.M. Forster, P.J. Newton, R.C.N. Wit, L.L. Lim, et al., Aviation and global climate change in the 21st century, Atmos. Environ. 43 (22e23) (2009) 3520e3537. [2] J.E. Penner, D.H. Lister, D.J. Griggs, D.J. Dokken, M. McFarland, Summary for Policymakers. Aviation and the Global Atmosphere. A Special Report of Working Groups I and III of the Intergovernmental Panel on Climate Change, Intergovernmental Panel on Climate Change, Geneva, 1999, p. 23. [3] IPCC, Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, IPCC, Geneva, Switzerland, 2007, p. 104. [4] E. Corporan, M.J. DeWitt, V. Belovich, R. Pawlik, A.C. Lynch, J.R. Gord, et al., Emissions characteristics of a turbine engine and research combustor burning a FischerTropsch jet fuel, Energy fuels 21 (5) (2007) 2615e2626. [5] X. Hui, K. Kumar, C.-J. Sung, T. Edwards, D. Gardner, Experimental studies on the combustion characteristics of alternative jet fuels, Fuel 98 (2012) 176e182.
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