Life Cycle and Techno-Economic Analysis of Fischer-Tropsch Renewable Diesel and Jet Fuel Production

by

Hajar Pourbafrani

A thesis submitted in conformity with the requirements for the degree of Master of Applied Science

Chemical Engineering and Applied Chemistry University of Toronto

© Copyright by Hajar Pourbafrani 2016

ii

Life Cycle and Techno-economic Analysis of Fischer-Tropsch

Renewable Diesel and Jet Fuel Production

Hajar Pourbafrani

Master of Applied Science

Chemical Engineering

University of Toronto

2016

Abstract

Three different possible scenarios of renewable diesel and renewable jet fuel production from

hybrid poplar through gasification combined with Fischer-Tropsch synthesis are studied in terms

of process efficiency, life cycle greenhouse gas emissions, and techno-economic feasibility. The

process modeling results indicate that it is technically possible to produce both renewable diesel

and renewable jet fuel from this feedstock. The product yields are highly dependent on the

process configuration in each scenario. Producing renewable diesel and jet fuel through this

process results in low greenhouse gas emissions compared to conventional petroleum-based

diesel and jet fuel, approximately a 95% reduction in emissions. The levered rate of return on

investment associated with each scenario is highly dependent on not only the price of the fuel

products and co-products but also the feedstock price.

iii

Acknowledgments

Firstly, I would like to express my sincere gratitude to my supervisors, Professor Bradley A.

Saville and Professor Heather L. MacLean for providing me the opportunity to work in such a

nurturing environment that allowed me to grow professionally. Your patience, motivation, and

continuous supports are priceless to me. Specially, your last contribution on revising and editing

my thesis.

I would like to specially thank, my brother, Dr. Mohammad Pourbafrani for encouraging and

supporting me.

Thank you also to the Department of Chemical Engineering and Applied Chemistry, University

of Toronto Institute for Aerospace Studies (UTIAS), the NSERC CREATE program and the

BioZone research group.

A special thanks to my family for their love and support that I receive from them all the time.

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Table of Contents

Acknowledgments .......................................................................................................................... iii

Table of Contents ........................................................................................................................... iv

List of Tables ................................................................................................................................. vi

List of Figures .............................................................................................................................. viii

Chapter 1 Introduction .................................................................................................................... 1

1.1 Renewable Jet Fuel ............................................................................................................. 1

2 Chapter 2 .................................................................................................................................... 7

2.1 Different stages involved in renewable jet fuel supply chain ............................................. 7

2.1.1 Feedstock ................................................................................................................ 7

2.1.2 Sustainability ........................................................................................................... 8

2.1.3 Aviation Fuel Certification ..................................................................................... 8

2.1.4 Renewable Jet Fuel Production Technology ........................................................... 8

2.2 Life Cycle Greenhouse Gas Emissions of Renewable Jet Fuel .......................................... 9

2.3 Renewable diesel .............................................................................................................. 10

2.4 Techno-economic Analysis ............................................................................................... 14

3 Methods .................................................................................................................................... 17

3.1 Life Cycle Assessment ...................................................................................................... 17

3.1.1 Goal and Scope Definition .................................................................................... 17

3.1.2 System Boundary .................................................................................................. 18

3.1.3 Co-product Treatment Procedures ........................................................................ 20

3.2 Process Description ........................................................................................................... 22

3.2.1 Feedstock Production ............................................................................................ 25

3.2.2 Hybrid Poplar to Renewable Jet Fuel/Diesel ........................................................ 28

3.2.3 Product Transportation, Distribution and Use ...................................................... 33

v

4 Process Modeling ..................................................................................................................... 35

4.1 Techno-Economic Analysis .............................................................................................. 40

4.1.1 Equipment Cost ..................................................................................................... 41

5 Results ...................................................................................................................................... 43

5.1 Process Simulation Results ............................................................................................... 43

5.1.1 Product Distribution .............................................................................................. 43

5.1.2 Mass Balance of Gasification Unit ....................................................................... 45

5.1.3 Energy Use ............................................................................................................ 47

5.2 Life Cycle Assessment Results ......................................................................................... 49

5.3 Utilizing LPG and its impact on LCA .............................................................................. 54

5.4 Cost Estimating and Cash Flow Analysis Results ............................................................ 55

5.5 Carbon Tax Sensitivity Analysis ...................................................................................... 60

6 Conclusions .............................................................................................................................. 62

References ..................................................................................................................................... 63

vi

List of Tables

Table 1-1. Biojet Fuel Demand and Growth Projections for Carbon Neutral Growth, 2020 to

2035 [12] ......................................................................................................................................... 3

Table 2-1. Diesel Fuel Properties Recorded by UOP [11] ............................................................ 12

Table 2-2. Comparison of Techno-economic Results of Biofuel Plants in the Literature [43-47] 16

Table 3-1. Overview of the Co-product Treatment Strategies and the Calculation Methods [50] 21

Table 3-2. Ontario Electricity Grid Mix, IESO Supply Overview, 2014 ..................................... 23

Table 3-3 GHG Intensity of Different Sources [62] ..................................................................... 24

Table 3-4. Poplar Production Data from the GREET Model [49]. Values are per dry tonne of

biomass. ........................................................................................................................................ 26

Table 3-5. Physical Characteristics of Hybrid Poplar [57] ........................................................... 27

Table 3-6. Main Reactions in the Gasifier .................................................................................... 29

Table 3-7. Fischer-Tropsch Reactions .......................................................................................... 30

Table 3-8. Fischer-Tropsch Product Distribution in Different Reactors ...................................... 31

Table 4-1. Syngas Composition from Aspen Plus Modeling ....................................................... 36

Table 4-2. Different Types of Reactors Used to Model Various Process Stages ......................... 37

Table 4-3. Main Economic Assumptions for nth Plant Scenarios ................................................. 40

Table 4-4. Fuel product prices in 2008 and 2015 (Source: EIA [63]) .......................................... 42

Table 5-1. Simulation Results using Aspen Plus Software (Million m3/year). Plant Capacity is

1.4 Million tonnes dry Biomass per Year. .................................................................................... 43

Table 5-2. Aspen Simulation Results Using Aspen Plus software. Plant capacity is 1.4 million

tonnes dry biomass per year. ......................................................................................................... 44

vii

Table 5-3. The Mass Balance for the Gasification Unit: Luk et al. (2015) [57] ........................... 47

Table 5-4. Natural Gas and Electricity Consumption in the Different Scenarios ......................... 49

Table 5-5. Share of GHG Emissions for Each Product Based on Energy Allocation Method for

the Three Scenarios ....................................................................................................................... 49

Table 5-6. Life cycle GHG emissions associated with the three scenarios compared to petroleum

diesel and jet fuel pathway from GREET [49] ............................................................................. 53

Table 5-7. Estimated Installed Cost of Units and Equipment for Plant Capacity of 1.4 Million dry

tonnes Hybrid Poplar per Year, 2014 USD [47, 58, 59] ............................................................... 55

Table 5-8. Estimated Indirect Cost, Fixed capital cost, and Total Capital Investment (TCI) for 1.4

Million tonnes dry Poplar, Based on 2014 USD ........................................................................... 56

Table 5-9. Cash Flow Analysis Results and Estimated Levered Rates of Return on Investment for

Different Scenarios in 2008 and 2015 .......................................................................................... 58

Table 5-10. Carbon Credit Sensitivity Analysis for Fischer-Tropsch Renewable Jet Fuel

Production ..................................................................................................................................... 60

viii

List of Figures

Figure 1-1. Simplified diagram of activities involved in renewable jet fuel production ................ 5

Figure 3-1. Life Cycle Assessment Boundary for Renewable Jet Fuel (or Renewable Diesel)

Production from Poplar ................................................................................................................. 19

Figure 3-2. Scenarios for Maximizing the Production of Renewable Diesel and Jet Fuels: FT

synthesis and separation units, cracking unit and isomerization unit are noted by red, blue and

green boxes, respectively. ............................................................................................................. 33

Figure 4-1. Gasifier model Source: Luk et al. (2015) [57] ........................................................... 35

Figure 4-2. Baseline FT Scenario includes gasification, FT reactor, and separation columns ..... 38

Figure 4-3. Maximum Diesel Scenario: The Baseline FT scenario is followed by a cracking unit

and separation columns to maximize the renewable diesel stream ............................................... 38

Figure 4-4. Maximum Jet Fuel Scenario: An isomerization unit is added to the Maximum Diesel

Scenario to convert the produced diesel fuel to jet fuel ................................................................ 39

Figure 5-1. Block Flow Diagram of Gasification Unit: Luk et al. [57] ........................................ 46

Figure 5-2. Greenhouse Gas Emissions Associated with Renewable Diesel for the Different Life

Cycle Stages of Fischer-Tropsch Pathway for the Maximum Diesel Scenario. ........................... 50

Figure 5-3. Greenhouse Gas Emissions Associated with Renewable Jet Fuel for the Different

Life Cycle Stages of Fischer-Tropsch Pathway for the Maximum Jet Fuel Scenario .................. 52

Figure 5-4. Life cycle GHG emissions of different jet fuel production pathways: three different

scenarios in the current study; Fischer-Tropsch jet fuel from biomass which is hybrid poplar

(Biomass-FTJ); Hydroprocessed Renewable jet (HRJ); and petroleum jet fuel. *Data obtained

from GREET [49] ......................................................................................................................... 54

Figure 5-5. Effect of Feedstock Price on Levered Rate of Return on Investment, Assuming 60%

equity ............................................................................................................................................. 59

ix

1

Chapter 1 Introduction

1.1 Renewable Jet Fuel

Reducing the negative environmental impacts associated with the burning of fossil fuels is an

ongoing challenge. Anthropogenic greenhouse gas (GHG) emissions, such as those resulting

from fossil fuel combustion, are linked to climate change. According to the National Aeronautics

and Space Administration (NASA) and the National Oceanic and Atmospheric Administration

(NOAA), the earth’s 2015 surface temperatures were the warmest since modern record keeping

began in 1880 [1]. Taking action to lessen climate change impacts can be accomplished by

reducing our use of fossil fuels through the use of more efficient technologies, energy

conservation, and replacing fossil fuels with lower GHG intensity fuels. Biofuels have the

potential to lower life cycle GHG emissions relative to petroleum fuels. However, the GHG

intensity of biofuel production can vary widely based on feedstock, process technology

geographical location of the biofuel plant and type of produced biofuel (ethanol, biomethane,

diesel and jet fuel) [2-8].

Renewable jet fuel is a hydrocarbon based jet fuel produced from renewable material such as

lignocellulosic biomass (e.g., agricultural residues, short rotation forestry crops). It is considered

to be a fuel with large potential future demand, considering the expected increase in worldwide

air traffic and concerns related to the use of fossil based fuels [9]. According to Boeing, air

traffic will increase from 6000 billion-person miles in 2014 to 16,000 billion-person miles in

2034 [9]. The International Air Transportation Association (IATA) estimated that annual growth

in aviation industry demand, revenue passenger kilometers or RPKs, is about 5% [10]. A target

for IATA is a reduction in the net aviation carbon dioxide emissions of commercial airlines of

50% by 2050 relative to 2005. This is an ambitious target and to meet it will require a major

increase in fuel efficiency of aircraft as well as a considerable increase in the production and

utilization of biojet fuel.

Currently, there is limited production of renewable jet fuel and producers are performing most of

the ongoing research and development. Honeywell UOP is one of the leading technology in

renewable jet fuel production and Honeywell UOP independently uses this technology to

2

produce more than 1 million gallons of renewable jet fuel for U.S. military and commercial

aviation partners [11]. In addition, commercial facilities such as Altair use the UOP technology

to produce a mixture of renewable diesel and renewable jet fuel. Renewable jet fuel production

is expected to increase substantially. For example, in Canada, according to a feasibility study on

the Canadian biojet fuel supply chain [12], the annual biojet volume required to meet carbon

neutral growth should be about 54 million liters in 2020 and increase to 920 million liters in

2035. A goal of Carbon Neutral Growth was defined by the international aviation sector to cap

CO2 emissions. Carbon Neutral Growth beginning in 2020 is a necessary step to enable the CO2

emission reductions in the 2035-2050 timeframe. Table 1-1 shows the biojet requirements to

achieve Carbon Neutral Growth by 2035, to reach the targeted 50% reduction by 2050 [12]. The

US Federal Aviation Administration also has a goal of using 1 billion gallons (3.8 billion liters)

of biojet fuel each year in civil aviation from 2018. These numbers indicate that the market for

renewable biojet fuel is expected to grow significantly.

3

Table 1-1. Biojet Fuel Demand and Growth Projections for Carbon Neutral Growth, 2020

to 2035 [12]

Carbon Neutral

Growth in Year

Jet Demand

(Billion Liter)

Jet Growth

(Billion Liter)

Biojet Needed for

CNG (Billion Liter)

Biojet (%)

2020 7.55 0.11 0.05 0.7

2021 7.67 0.23 0.11 1.5

2022 7.78 0.35 0.17 2.2

2023 7.90 0.46 0.23 2.9

2024 8.02 0.58 0.29 3.6

2025 8.14 0.70 0.35 4.3

2026 8.24 0.80 0.40 4.8

2027 8.35 0.91 0.45 5.4

2028 8.47 1.03 0.51 6.0

2029 8.58 1.14 0.56 6.6

2030 8.69 1.25 0.62 7.1

2031 8.80 1.37 0.68 7.7

2032 8.93 1.49 0.74 8.2

2033 9.05 1.61 0.80 8.8

2034 9.18 1.74 0.86 9.4

2035 9.30 1.87 0.92 9.9

4

In addition to renewable jet fuel, renewable diesel offers an opportunity to make aviation

biofuels more available and more affordable. Because renewable diesel is usually considered as

an intermediate product in the jet fuel production pathway, further biorefinery upgrading

processes are required to maximize renewable jet fuel production and convert renewable diesel

to renewable jet fuel. Renewable diesel is a hydrocarbon based diesel, and chemically similar to

petroleum diesel; however, it contains low amounts of sulfur and carbon compared to petroleum

diesel, which reduces greenhouse gas emissions. Biodiesel, which can be derived from the same

feedstock as renewable diesel, has a different molecular structure than renewable diesel and

contains esters. This difference in molecular structure results in different properties for

renewable diesel and biodiesel. These properties are further discussed in Section 1-4. In addition,

renewable diesel (but not biodiesel) can be considered as one of the promising renewable fuels as

it can be blended at low levels with petroleum jet fuel [13].

In December 2014, Boeing completed the world’s first flight with a portion of the fuel being

renewable diesel produced from vegetable oils. The company powered its ecoDemonstrator 787

flight test airplane with a blend of 15 percent renewable diesel and 85 percent petroleum jet fuel

in the left engine [13].

In general, the production of renewable jet fuel from different feedstocks is a function of

feedstock availability in the specific region, and financial and environmental metrics. There are

different pathways to produce renewable jet fuel. These pathways include gasification combined

with Fisher-Tropsch (FT) synthesis, hydroprocessing of esters and fatty acids (HEFA), direct

conversion of sugars to hydrocarbons, and the alcohol to jet fuel process. The FT pathway

converts biomass into synthesis gas or syngas. Then, syngas is converted to liquefied

hydrocarbon in a FT reactor, in the presence of a catalyst. This liquefied hydrocarbon goes

through further distillation and purification stages to separate different fuels based on their

carbon range numbers. On the other hand, in a hydroprocessing process, the oleochemicals are

converted to jet fuel via deoxygenation with hydrogen and cracking. Alcohol to jet is another

possible technology with three main stages of dehydration, oligomerization and hydrogenation.

In this pathway, ethanol is converted to jet fuel.

Figure 1-1 illustrates activities associated with renewable jet fuel production and use, starting

with feedstock. The feedstock can go through different processes to produce renewable jet fuel.

5

This fuel is then typically blended with petroleum jet fuel and transported to the fueling facility.

The emissions of CO2 resulting from the combustion of the renewable jet fuel and biogenic CO2

emissions during fuel production are assumed to be entirely balanced by the carbon sequestered

during feedstock growth. This assumption is in line with that of other studies [14-16].

FlightCO2

Transportation

Feedstock

Feedstock Treatment

&Processing

Biorefinery

Distribution to the Airport

ASTM Approval

Figure 1-1. Simplified diagram of activities involved in renewable jet fuel production

6

Different studies have evaluated and estimated the economic feasibility of liquid bio-based fuel

production. They mainly analyzed the techno-economic aspects of gasoline and diesel

production, rather than jet fuel production. For example, Karittha et al. [17] investigated the net

present value (NPV) of renewable diesel production from rice straw through gasification and

Fischer-Tropsch synthesis. They showed that project life, interest rate, electricity and diesel costs

can significantly affect the NPV of the plant [17]. Another study by Trippe et al. completed a

techno-economic assessment of the production of gasoline from FT synthesis using residual

wood. They found that the production cost of biomass-derived gasoline and diesel was 76%

higher compared to the petroleum counterparts in 2011[18]. Our literature review shows a gap in

techno-economic analysis of renewable jet fuel production. In the current economic analysis, we

compared different configurations in which either renewable diesel production or jet fuel

production is maximized as two promising aviation fuels [19-22].

A number of studies have investigated the life cycle GHG emissions from hydroprocessing of

oilseeds, pyrolysis, gasification and FT synthesis, and advanced fermentation of biomass [22–

25]. These investigations demonstrate that renewable jet fuel and renewable diesel have the

potential to significantly reduce GHG emissions. The literature survey (see Chapter 2) shows that

although that there are a number of LCA of renewable jet fuel and renewable diesel production

technologies from different feedstocks and pathways, there is no study of renewable jet fuel and

renewable diesel production from hybrid poplar feedstock through a combined gasification and

Fisher-Tropsch process.

Therefore, the work in the thesis is novel as it examines the mass and energy balances of the

entire renewable jet fuel and renewable diesel fuel processes, estimates the life cycle GHG

emissions and costs of producing these fuels and compares results with reference petroleum-

based fuels.

The overall objective of the thesis is to;

• Estimate the life cycle GHG emissions associate with renewable diesel and jet fuel

production from hybrid poplar through the gasification and Fischer-Tropsch processes

• Evaluate the financial performance of the gasification combined with Fischer-Tropsch

processes in order to produce renewable diesel and renewable jet fuel

7

2 Chapter 2

2.1 Different stages involved in renewable jet fuel supply chain

2.1.1 Feedstock

There are various biomass feedstock options for renewable jet fuel production: vegetable oil and

animal fat, sugar and starch, and lignocellulosic biomass are three main categories. Currently,

renewable jet fuels from vegetable oil, sugar, and starches are available. In addition, the

conversion technology to convert these feedstocks to jet fuel are technically feasible and

commercialized. The conversion technology is known as Hydroprocessed Esters and Fatty Acids

(HEFA) technology. The Hydroprocessed Renewable Jet (HRJ) fuel produced from vegetable

oils and animal fats has been approved by ASTM D7566 [26] and it is currently commercialized

by different companies such as Neste Oil, UOP and Altair. Altair has signed an agreement with

United Airlines to supply a minimum of 57 million liters (ML)per year of renewable jet fuel to

the airline [12]. However, there has been concern regarding potential effects on food markets

when producing biofuel from vegetable oil feedstock [20].

Lignocellulosic biomass, which includes agricultural and forest residues as well as various

energy crops, including hybrid poplar, does not compete with food markets. However, the

conversion technologies for renewable jet fuel production from lignocellulosic feedstock are still

under development and not yet at commercial scale. There are several studies that have reported

potential lignocellulosic crops that can be grown on marginal land [14- 25, 27]. Hybrid poplar is

a promising biomass feedstock for producing renewable jet fuel. In addition to the availability of

hybrid poplar feedstock, it also has the highest biomass yields of studied short rotation crops

[REF]. Marsal et al. [28] found that the average biomass yield of poplar, on an unfertilized plot,

in research sites in Guelph, is about 12.07 oven dry tonnes (odt) per hectare per year. On the

other hand, the biomass yields of willow and switchgrass are about 9.74 odt per hectare per year

and 5.94 odt per hectare per year, respectively.

Algae oil is another feedstock that does not compete for land with food crops because it can be

grown on marginal land. However, algae suitable for biofuel production is not currently available

in commercial quantities, and its production is very energy intensive [29]. Feedstock choice

8

affects the environmental and techno-economic performance of renewable diesel and jet fuel

production; feedstocks differ in terms of cost, availability, conversion technologies that can be

employed to convert them to renewable diesel and jet, and environmental performance.

2.1.2 Sustainability

The biojet supply chain should meet sustainability criteria, namely: ecological, social, and

economic criteria. Currently, both governmental and non-governmental initiatives are supporting

the development of sustainability criteria and standards for biofuels. Government Engagement

Governments may support the development of the biojet supply chain in different ways. At the

present time, some methods are defined to minimize or eliminate potential risks. These methods

include research support and investigations on combining the available feedstocks and

technologies. The government can also support and help the supply chain development by

facilitating market access by implementing renewable fuel standards, defining mandates, and

fuel tax credits for biorefineries. The Renewable Fuel Standard (RFS) developed by the U.S. is

one example of the government support on this matter [30]. The Renewable Fuel Standard

(RFS2) is a federal program that requires transportation sectors to buy a minimum volume

(mandate) of renewable fuels. Under the RFS2 program the volume of renewable fuels needed to

be blended into transportation fuel increases to 66 billion liters by 2022 [30].

2.1.3 Aviation Fuel Certification

All aviation fuel must meet specified fuel quality standards and specifications. Once a new fuel

is introduced as an aviation fuel, it must meet the ASTM D1655 specification for aviation turbine

fuels [31]. Renewable jet fuels must be certified by another separate and more recent ASTM

standard, ASTM D7566 [26], which is the standard specification for aviation turbine fuel

containing synthesized hydrocarbons. A fuel certified by ASTM D7566 also meets the

specifications of ASTM D1655.

2.1.4 Renewable Jet Fuel Production Technology

A technology platform starts with the first stage of preparing the feedstock and includes all

processes that convert the feedstock to jet fuel. The technology platforms vary in terms of

suitable feedstocks, environmental, and economic performance. Currently, an approved bio-

9

based jet fuel can be blended with petroleum jet fuel up to a certain percentage as stated under

ASTM [26, 31], although it is possible in the future that renewable jet fuels may not need to be

blended. The bio-based jet fuel produced from HEFA and FT synthesis have received approval

to be blended with conventional jet fuel up to 50%. This limitation is defined not only to ensure

jet fuel combustion performance but also to ensure the compatibility of the blended jet fuel with

current engines and technologies. HEFA and FT pathways are certified platforms to produce

renewable jet fuels for commercial aviation. Other technologies are still at the research and

development (R & D) levels, although some have also been approved under ASTM.

In general, jet fuel production from oilseeds is based on bio oil extraction followed by

hydroprocessing. Jet fuel production from lignocellulosic biomass is more complex and is based

on pyrolysis or gasification combined with FT synthesis. The production of jet fuel from these

two processes is environmentally favorable compared to hydro processing of seed oil such as

palm and canola oils, due in part to lesser inputs associated with feedstock production [14-15].

2.2 Life Cycle Greenhouse Gas Emissions of Renewable Jet Fuel

A number of studies have investigated the life cycle GHG emissions of hydroprocessing of

oilseeds, pyrolysis, gasification and FT synthesis, and advanced fermentation of biomass [15–

18]. These investigations demonstrate that renewable jet fuels have the potential to significantly

reduce GHG emissions. According to [19], the global warming potential (GWP) of oilseed-based

jet fuels through the HEFA pathway is about 41 – 70 % lower than petroleum-based jet fuel. The

GWP of biojet fuel from pyrolysis of corn stover is reported to be 55 to 68% lower than

petroleum-based jet fuel [17, 18]. Biojet fuel produced from biomass through the FT pathway is

reported to have a GWP by 81–89 % lower than petroleum-based jet fuel, if CO2 is sequestered

at the biorefinery using a carbon capture system [18]. Agusdinata et al. [24] projected a median

GWP reduction of 74 %, compared to petroleum-based jet fuel, for hydroprocessed and FT biojet

fuels in 2050. Moreover, Staples et al. [32] predicted a GWP reduction of 130–0.2 % for the

advanced fermentation of biomass in comparison with petroleum-based jet fuel. This large range

of GWP reduction is a result of varied feedstock type and different biomass conversion methods.

Budsberg et al. [33] recently examined renewable jet fuel production from poplar. This paper is

based on enzymatic hydrolysis of poplar and the production of acetic acid. The acetic acid is

10

further converted to biojet fuel through hydrogenation and oligomerization. They argued that the

amount of CO2 equivalent associated with the lignin gasification biojet fuel pathway ranges from

32 to 73 gram per MJ of jet fuel.

The above results indicate potentially large reductions in GWP compared to the baseline

petroleum jet fuel; however, these GWP values do not include land use change-related

emissions. Land use change emissions, both direct and indirect, have often not been considered

in biofuel LCA studies, due to uncertainties in land use change models, especially for oilseed

feedstocks [34]. The direct land use change emission refers to land already used for a specific

purpose for example growing food and whose future use will achieve the same result. On the

other hand, the indirect land use change emission refers to land whose ultimate purpose is

essentially changed from its previous use. For example, growing energy crops on agricultural

land may displace existing food-crop production, and causes land use change in another location.

This indirect land use change might occur in a neighboring area or even in another country where

an area of high biodiversity and high level of stored carbon might be cleared to make more land

available for growing crops. If land use change emissions for oilseeds are applied to the oilseed

LCA studies, the GWP of the biofuels will increase significantly, according to [33]. Stratton et

al. [23] assessed different LCA simulations in which land use change emissions are included in

some of the scenarios. They found that when oilseed simulations include land use change

emissions, the GWP is estimated to increase by 22 % up to 2000 %. Adding direct land use

change emissions to biojet fuels fermented from switchgrass can increase GWP values by 2.9 to

12.2 g CO2 equivalent (eq). per MJ of jet fuel according to [35].

2.3 Renewable diesel

Among the various alternative fuel options, biodiesel and renewable diesel have been gaining

popularity. Although both types of diesel are derived from biomass, they are two distinctly

different fuels.

Biodiesel is defined as mono alkyl esters of long-carbon-chain fatty acids derived from

renewable lipid feedstock. Biodiesel is produced by a transesterification process in which the

vegetable oils or animal fats react with a short-chained aliphatic alcohol, either methanol or

ethanol, in the presence of an alkaline catalyst, normally potassium hydroxide. Glycerol is a

byproduct of this transesterification process. Biodiesel is defined under the standard of ASTM

11

D6751 [36] as a fuel comprised of mono-alkyl esters of long-chain fatty acids derived from

vegetable oils or animal fats. Biodiesel is also referred to fatty acid methyl ester (FAME) or rape

seed methyl ester (RME) in Europe. Biodiesel is chemically different from petroleum diesel and

renewable diesel because it contains oxygen atoms. This leads to different physical properties for

biodiesel. Biodiesel can be used in its pure form or blended with petroleum diesel as an additive.

Biodiesel is used in ground transportation vehicles, but, due to its cold flow properties, would not

be suitable for aviation.

Renewable diesel, green diesel or second generation diesel are derived from biological sources,

and refer to a fuel with a similar chemical structure as petroleum diesel; the resulting alkanes in

renewable diesel are not esters, and thus distinct from biodiesel. The Department of Energy

(DOE) with the Internal Revenue Service (IRS) and the Environmental Protection Agency (EPA)

has defined the specification for renewable diesel [37]. Although the chemical structure of

renewable diesel is similar to that of petroleum diesel, an additive is needed to address the

lubricity issue associated with fuels that lack oxygen (or sulfur). Table 2-1 provides a list of

different specifications for biodiesel and renewable diesel.

12

Table 2-1. Diesel Fuel Properties Recorded by UOP [11]

Properties Petroleum Diesel Biodiesel Renewable Diesel

Cetane number 40-55 50-65 75-90

Energy Density, MJ/kg 43 38 44

Density, g/ml 0.83-0.85 0.88 0.78

Energy Content, MJ/L 35 33 35

Sulfur ppm <10 <1 <1

NOX emissions Baseline +10 -10 to 0

Cloud point, -5 -5 to +15 -20 to +20

Oxidative Stability Baseline Poor Excellent

Cold flow properties Baseline Poor Poor

Lubricity Baseline Excellent Baseline

Boeing has announced that it will support efforts to approve renewable diesel for commercial

aviation use. Renewable diesel can be produced from different technologies: hydrothermal

processing, hydroprocessing, and indirect liquefaction. In the hydrothermal processing

technology, biomass reacts with water at an elevated temperature and pressure to form oils and

residual solids. Conversion typically occurs at 300 to 315 and 100 to 170 standard

13

atmosphere (atm), to keep the water primarily as a liquid. After the reaction, the organics are

separated from the water, and a distillate cut for diesel use is produced. This technology is being

commercialized in the United States by Changing World Technology, which states that its

product meets the requirements of ASTM D975 and uses the term “thermal depolymerisation” to

describe the process. This terminology originated in a patent by P.T. Baskis [35].

Renewable diesel can also be produced from fatty acids by traditional hydroprocessing

technology (HEFA). Hydroprocessing conversion temperatures are typically 320 to 370oC, and

pressures are typically 40 to 100 atm. Solid catalysts are employed to increase reaction rates,

improve selectivity for certain products, and optimize hydrogen consumption. The starting

biomass-derived oils can be the same as for biodiesel. The triglyceride-containing oils can be

hyroprocessed either as a co-feed with petroleum or as a dedicated feed. The product is a

premium renewable diesel fuel containing no sulfur and having a high cetane number of 90 to

100. NESTE in Finland and Petrobras in Brazil already produce renewable diesel from this

technology.

The third technology is indirect liquefaction or gasification followed by the FT pathway. In this

process, biomass is converted to a synthesis gas or syngas. Then, the syngas is catalytically

converted to liquids. The production of liquids is accomplished using FT synthesis. The proper

selection of catalysts and conditions yields a product stream rich in diesel specification

distillates. The production of FT liquids is a commercial technology, but most FT diesel today is

produced using natural gas and coal. FT diesel fuel can meet the requirement of ASTM D975.

This process is further described in this study as it has been simulated in Aspen Plus software.

Fischer Tropsch diesel (FTD) is interchangeable with conventional diesel and is fully compatible

with existing diesel engines and infrastructure, which are conducive to implementation in the

short term [38]. In addition to a high cetane number, FTD does not contain sulfur and nitrogen

and has the potential for blending with diesel at any ratio with little to no modification of diesel

engines [39].

Xie et al. (2011) studied the LCA renewable diesel production from forest residues, employing

the Fischer Tropsch technology [40]. Two co-product allocation methods, energy and market

value were used in their work. Their results suggest that Fischer-Tropsch Diesel (FTD) has

significantly lower GHG emissions compared to petroleum diesel. The GHG emissions of FTD

14

are close to zero based on energy allocation. In their study, they assumed that hydrocarbon

residues remaining from the separation of diesel are utilized in electricity generation, and the

electricity produced satisfies the electricity requirements in the plant.

Tonini and Astrup (2012) investigated the LCA of FTD and found that the GHG emissions of

FTD are comparable with those of diesel from lignocellulosic biomass [41]. The high GHG

emission of FTD was due to the impact of land use. Petersen et al. (2015) reviewed the life cycle

GHG emissions of renewable diesel production from sugarcane bagasse [42]. They compared the

life cycle GHG emissions of renewable diesel with GHG emissions associated with ethanol

production from baggase. Their findings show that the GHG emissions of renewable diesel

production through Fischer-Tropsch were about 60% of the GHG emissions associated with

bioethanol production. The main reasons for the lower greenhouse gas emissions of renewable

diesel production were that no chemicals were used in the FTD process, and the higher energy

efficiency of renewable diesel production. Moghaddam et al. (2015) studied the environmental

impacts of conversion of biogas to FTD, methanol and dimethyl ether [43]. Their study showed

that the life cycle GHG emissions of FTD from biogas were 17.0 gCO2eq. /km, which is

significantly lower than fossil diesel GHG emissions of about 136 gCO2eq. /km.

2.4 Techno-economic Analysis

Once a biofuel is introduced, it must be economically feasible to be utilized in commercial scale

applications. A techno-economic analysis is a feasibility analysis in which technical aspects of a

project are combined with economic aspects. In recent decades, with increasing attention on bio-

based fuels, many techno-economic studies have been conducted on power generation and

different biofuel production platforms. These studies may, to different extents, utilize the

connection between the process and the cost of producing renewable fuels.

However, the accuracy of results from these studies is often limited by the quality of the process

design and capital cost data; a good study may be accurate to within +/- 30% of the actual capital

or production cost [44].

A number of studies have estimated the cost to produce alternative transportation fuels, mainly

renewable gasoline, from gasification combined with biomass to liquid units, such as FT. The

15

projected cost ranges from $12/GJ to $16/GJ, corresponding to a price of $0.43/L to $0.54/L of

gasoline equivalent [45-48]. These studies and their assumptions are further discussed below.

Another study conducted by Larson et al. estimated the final cost of renewable gasoline

produced from switchgrass at $0.14 per liter of gasoline equivalent [35].

Williams et al. [45] conducted a study on a biomass-to-methanol plant based on gasification with

the capacity of 1,650 dry metric tonnes of biomass per day. The production cost of methanol

from this plant is estimated at $15/GJ and $0.06/L of methanol. At that time, the methanol

obtained from natural gas had a lower production cost compared to biomass-based methanol, at

$0.16 per liter of methanol. William et al. argued that if a carbon tax credit was considered for

the lifecycle carbon emissions, then the biomass-based methanol could become competitive with

natural gas derived methanol at a tax of approximately $90 per tonne of carbon, assuming the

price of natural gas is $4.5/GJ and the price of biomass is $2.5/GJ.

Table 2-2 compares four studies in which bio-based fuel production through gasification have

been studied. A range of cost year, plant size, and feedstock cost illustrate the diversity of

characteristics and assumptions used in the techno-economic studies. Moreover, the capital

investment costs of the studies differ significantly. For example, Philips et al. estimated a capital

cost of $192 million, with the capacity of 2000 dry tonne hybrid poplar per day [47]; however,

this is only one half of the capital cost estimated in the study conducted by Hamelinck et al., at

$387 million, with the capacity of 576 dry tonnes of willow biomass per day [46]. Both studies

assumed similar plant sizes. Therefore, the reason for such a considerable variation is likely due

to the different technologies (ethanol vs FT) and a different level of technology development

[47]. Hamelinck et al. and Larson et al. evaluated similar technologies, albeit at different scales.

The capital cost projected by Larson et al. is approximately 40% higher, even though the

biomass throughput is about 2.6 times greater in the study by Larson et al. While some

economies of scale are expected, the fairly small capital cost difference suggest that other

factors, such as technology assumptions, may also be a factor.

16

Table 2-2. Comparison of Techno-economic Results of Biofuel Plants in the Literature [43-

47]

William et al.

[43]

Phillips et al.

[46]

Hamelinck et al.

[44]

Larson et al.

[45]

Cost year 1991 2005 2000 2003

Plant size (dry

metric ton per

year)

1650 2000 1741 4540

Feedstock Generic biomass Poplar Poplar Switchgrass

Fuel Output Methanol Ethanol FT Liquid Diesel, gasoline

Feedstock Cost

($/dry tonne)

41 35 33 46

Capital

investment

($MM)

N/A 191 387 541

17

3 Methods

This research involves the life cycle assessment and process modeling of two bio-based fuels:

renewable jet fuel and renewable diesel. In this study, renewable diesel and renewable jet fuel

are considered to be produced from the same pathway, gasification and Fischer-Tropsch

synthesis. Both are produced simultaneously, with different ratios, and therefore, when one of

them is selected as the primary product, the other will be a co-product of the process. The

process is modeled in three different scenarios (described in Section 4), to maximize production

of either renewable diesel or renewable jet fuel.

3.1 Life Cycle Assessment

Life cycle inventory analysis models are developed to quantify GHG emissions from the life

cycle stages, including feedstock delivery, biorefinery processes, fuel and product transportation,

fuel distribution and product usage (Figure 3-1). A description of LCA methods can be found

elsewhere [48]. The life cycle assessment includes goal and scope definition, inventory analysis

and interpretation. The life cycle GHG emissions calculated in this study are compared with the

results of other pathways, such as petroleum based and hydro-processed renewable jet fuel (HRJ)

from the LCA modeling tool, GREET [49].

3.1.1 Goal and Scope Definition

The aim of this work is to compare the life cycle GHG emissions generated during production

and use of renewable jet fuel and diesel with the baseline emissions of conventional jet fuel and

diesel, respectively. The process is further described in section 4.2. The scope of this study

covers the full life cycle of renewable jet fuel and diesel, including feedstock production,

transportation, and fuel production in the biorefinery and fuel use. The geographical location is

considered as Ontario province, Canada.

The functional unit is used to normalize the environmental impacts based on a function of the

product system. In this work, our functional unit is 1 MJ of renewable jet fuel and diesel.

Emissions of selected GHGs (CO2, CH4, and N2O) are reported as carbon dioxide equivalents

(CO2eq.) based on 100-year global warming potentials (IPCC, 2006).

18

3.1.2 System Boundary

The system boundary of this study includes hybrid poplar production, feedstock transportation,

the biorefinery, fuel transport and final use of jet fuel in aircraft and diesel in a heavy-duty truck.

The system boundary is presented in Figure 3-1. The life cycle GHG emissions of renewable jet

fuel and diesel production from poplar is estimated in this study, and different stages of the life

cycle will be discussed in detail further in this chapter.

19

Poplar

(Delivery and

Treatment)

Gasification Unit

Fischer-Tropsch

and

Upgrading Unit

Renewable Jet fuel (or

diesel)

Transportation

and

Distribution

Aircraft (or Truck)

(End Use)

Energy

CO2 eq

Co-products

Energy

EnergyCO2 eq

CO2 eq

CO2 eq

Figure 3-1. Life Cycle Assessment Boundary for Renewable Jet Fuel (or Renewable Diesel)

Production from Poplar

20

3.1.3 Co-product Treatment Procedures

There are different allocation methods to assign GHG emissions to co-products, such as mass,

energy and market value. The biorefinery products are liquefied petroleum gas (LPG), naphtha

kerosene (jet fuel cut), diesel and wax. The emissions from hybrid poplar production,

transportation, and the biorefinery can be distributed between products using either energy, mass

or market value allocation. In mass allocation, the energy and emissions are assigned to the

product based the ratio of the product’s mass to the mass of all of the products. Table 3-1

presents a list of the co-product treatment strategies and the calculation methods.

21

Table 3-1. Overview of the Co-product Treatment Strategies and the Calculation Methods

[50]

Method

Eqn. 3-1. Mass

allocation

Eqn. 3-2. Energy

allocation

Eqn. 3-3. Market

based allocation

Eqn. 3-4. System

expansion

R product – the ratio of the output product displacing the conventional product

Energy allocation assigns the GHG emissions based on the ratio of energy content of the primary

product to the sum of energy contents of all the products. This method is useful when all

products are fuels. Market value allocation is based on the ratio of market value of products to

the sum of the market value of all the products.

The International Organization for Standardization (ISO) [48] recommends using the system

expansion approach instead of an allocation method. System expansion is a method used to

account for energy use and emissions of a co-product based on the conventional product that it is

22

displacing. In this approach, all GHG emissions are assigned to a primary product and the credit

for replacing the conventional product(s) with the process by-product is added. For example, if

we use system expansion for jet fuel, all other products, including LPG, naphtha, diesel and wax

are considered as by-products. The GHG emissions of hybrid poplar production, feedstock

transportation, biorefinery and transportation of products are all assigned to jet fuel. Then, a

credit for replacing each of these by-products with their “equivalent” product is assigned to jet

fuel.

In this work, since all the products are fuels, it is reasonable to use an energy allocation method.

Furthermore, the jet fuel portion in the final product is relatively small in some cases, and use of

system expansion may result in misleading results as the magnitude of the co-product credit will

be high. Therefore, an energy allocation method is used to distribute the GHG emissions of

poplar production, harvesting, transportation and biorefinery stage to the products, including

LPG, naphtha, diesel and wax. Energy allocation is based on the higher heating value of the

product. This allocation method treats all the products as energy products. The higher heating

values (HHV) for LPG, naphtha, jet fuel, diesel and wax are 50, 48, 46, 44, and 42 MJ/kg,

respectively [49].

3.2 Process Description

The GHG emissions associated with feedstock production include the GHG emitted from diesel

burning in heavy-duty trucks to transport the feedstock, the agricultural machinery to harvest and

chip the poplar and the GHG emissions associated with fertilizer used. The biorefinery processes

consume natural gas and electricity to convert the feedstock to renewable diesel and renewable

jet fuel. Then, the fuel products are distributed by heavy-duty truck to end use in the aircraft of

truck.

The natural gas used in the process is assumed to be obtained from the natural gas supply chain

and all the upstream activities from gas recovery, gas processing, and transmission and

distribution are included in life cycle emissions associated with burning this fuel to produce the

energy during different stages of the gasification combined with Fischer-Tropsch process.

23

Furthermore, it is assumed that the required electricity for the process is obtained from the

Ontario grid. This assumption affects the GHG emissions associated with the process, dictated

by the carbon intensity of the electrical grid. The Ontario grid composition is shown in Table 3-

2.

Table 3-2. Ontario Electricity Grid Mix, IESO Supply Overview, 2014

Source Ontario grid composition (%)

Nuclear 52.9

Hydro 30.6

Natural gas 11.5

Other Renewable sources 5

Table 3-2 indicates that about 89 % of the total grid electricity is provided by nuclear, hydro and

renewable sources that are considered low carbon-intensity sources of energy. Table 3-3

illustrates the GHG intensity of different sources of energy.

24

Table 3-3 GHG Intensity of Different Sources [62]

Technology tonnes CO2 eq. /GWh

Coal 888

Oil 733

Natural gas 499

Solar 85

Nuclear 29

Hydro 26

Wind 26

Life cycle assessment (LCA) and techno-economic analysis of renewable diesel and renewable

jet fuel production from hybrid poplar through the gasification and Fisher-Tropsch (FT)

processes are examined in this thesis. The Baseline FT Scenario, Maximum Diesel Scenario and

Maximum Jet Scenario are simulated using theAspen Plus software. The mass and energy

balance results obtained from the software have been used to estimate the life cycle GHG

emissions associated with fuel production and sizing of the equipment to do the cost estimation.

The mass and energy use of the three different scenarios are calculated based on the results of

Aspen Plus software, according to required amount of electricity for different equipment such as

pumps, compressors and natural gas in boilers and furnaces. Then, based on the emissions

factors from the GREET model, the amount of GHG emissions has been estimated. This chapter

details the methods associated with the process modeling and LCA components (other than those

included in Chapter 3) as well as the techno-economic analysis.

25

3.2.1 Feedstock Production

Hybrid poplar, a short-rotation forestry feedstock, is selected as the feedstock due to its diversity

and expanding availability for biofuel production in Canada. This well-established crop presents

good characteristics for the biofuel industry as well. In general, hybrid poplar requires little

fertilizer input and has the ability to regrow after multiple harvesting activities. It also has a high

rate of biomass production [51]. In addition, when used in a gasification system, the

lignocellulosic material in the wood can be fractionated without extensive pretreatment, which

results in lower energy intensity in the feedstock preparation stage [52]. Furthermore, hardwoods

do not exhibit the recalcitrance reported in softwoods [53]. Research has shown that these trees

can be grown on marginal lands, and consequently, the land use change emissions associated

with this type of crop have been reported to be negligible [51-56]. Therefore, using hybrid poplar

as the feedstock for biorefinery industries generally avoids land use concerns existing for

oilseeds and food crops.

This work utilizes the latest release of the GREET Fuel-Cycle model [49] for hybrid poplar

farming data, which is used as a proxy for hybrid poplar short rotation forestry. GREET is the

U.S. Department of Energy’s model that includes the data to perform life cycle assessment of

conventional and alternative transportation fuels and is developed at Argonne National

Laboratory. However, although this study focuses on Canada, we used the GREET model as it

provides the user with detailed data for different biojet fuel and diesel production pathways. Data

and results based on using GREET can reasonably be assumed to be relevant for Canada, in this

study. Canada has different growing conditions, different assumptions regarding transport

distances, and different assumption about energy inputs such as natural gas and electricity;

however, these inputs can be adjusted in the model to account for the natural gas production and

electricity generation mix in Canada. The data include impacts as a result of onsite energy use

and feedstock transportation as well as from fertilizer (nitrogen, phosphorus, potassium and

calcium) and pesticide (herbicide and insecticide) use. The relevant quantities of different

fertilizers, energy use and GHG emissions data are presented in Table 3-4. We have not included

the effects of land use change related to tree farming, which are expected to be negligible. The

assumed proximate analysis, ultimate analysis and biochemical components of the delivered

whole tree hybrid poplar are listed in Table 3-5. These data are obtained from the National

26

Renewable Energy Laboratory (NREL) databank of biomass components [55] and have been

used in the Aspen Plus modeling of the current study.

Table 3-4. Poplar Production Data from the GREET Model [49]. Values are per dry tonne

of biomass.

Tree

Farming

Fertilizer Production Pesticide Production Wood

Delivery

(km)

Total

N P2O5 K2O CaCO3 Herbicide Insecticide

Quantity (kg) 1000 3.0 1.0 2.0 2.4 0.2 0.0 50 n/a

CH4 (g) 34 62 1 3 0 8 0 21 131

N2O (g) 0 5 0 0 0 0 0 0 6

CO2 (g) 23 8 1 1 0 3 0 14 50

GHG (kg CO2

eq.)

24 12 1 1 0 3 0 15 55

Petroleum Use

(MJ)

273 5 4 4 0 19 0 171 478

Fossil Energy

Use (MJ)

308 146 8 8 0 39 0 193 709

Total Energy

Use (MJ)

309 148 8 8 0 41 0 193 717

27

Table 3-5. Physical Characteristics of Hybrid Poplar [57]

Proximate Analysis

Moisture content 50%

Volatile Matter 84%

Fixed Carbon 15%

Ash 0.87%

Ultimate Analysis

Carbon 51%

Hydrogen 6.0%

Oxygen 42%

Nitrogen 0.17%

Sulfur 0.09%

Ash 0.92%

Higher Heating Value 20 MJ/kg

Biochemical Components

Cellulose 47.3%

Hemicellulose 20.9%

Lignin 24.8%

28

3.2.2 Hybrid Poplar to Renewable Jet Fuel/Diesel

The poplar feedstock is harvested and transported to the biorefinery. To calculate the required

energy for feedstock transportation to the plant, it has been assumed that the feedstock is

delivered by trucks that use petroleum diesel. The trucks are loaded to maximum road limits. The

transportation of poplar to the plant requires about 1.7 kJ energy per dry tonne of biomass [49]. It

is assumed that the average distance between the poplar fields and the plant is about 100 km

[49].

Then it is chipped and transported to a gasifier, which operates at 700-1000 ˚C, and 1-10

pressure bar. The energy and related GHG emissions for feedstock chipping are both included in

total energy use and life cycle GHG emissions. Gasification is an exothermic process that

partially oxidizes carbon based feedstock with a limited amount of oxygen. This limited amount

of oxygen avoids burning carbon compounds and as a result, carbon is converted to synthesis gas

that includes carbon monoxide, hydrogen, carbon dioxide, methane and other combustible gases.

One of the significant advantages of gasification is that it can be used to process a variety of

heterogeneous feedstocks, including biomass and municipal solid waste (MSW). Different

reactions including dehydration, pyrolysis, oxidation and reduction take place in the gasifier.

Table 3-6 presents a list of the main reactions taking place in a gasifier to produce syngas.

29

Table 3-6. Main Reactions in the Gasifier

Stoichiometric Reactions

Partial oxidation of carbon

Water-gas-shift reaction

Water-gas reaction

Methanation reaction

Boudouard reaction

Steam methane reforming reaction

The Fischer-Tropsch catalysts are highly sensitive to the composition of syngas and the slightest

amount of contaminants, such as sulfur and heavy metals, would decrease the catalyst activity

significantly. Intermediate gas cleaning is necessary to avoid catalyst poisoning. After

contaminants are removed, the clean syngas is converted to liquid hydrocarbons through a

Fischer-Tropsch (FT) reactor. The FT process was originally developed by Franz Fischer and

Hans Tropsch in 1923 to make liquid fuel from coal. The Sasol technology commercially

produces synthetic fuels from coal and natural gas in South Africa. The synthetic jet fuel

produced from the FT pathway is approved by ASTM D7566, which allows blending of up to

50% of FT jet fuel with petroleum jet fuel, considering its compatibility with current technology

and engines.

Two different types of reactions happen in the FT reactor: first, the main reactions include alkane

production, alkene production, and water-gas shift reactions. Secondly, side reactions produce

30

alcohols and the Boudouard reactions to produce CO2. These reactions are presented in Table 3-7

Long chain hydrocarbons are the main products of the FT reactor.

Table 3-7. Fischer-Tropsch Reactions

Main Reactions

Alkanes

Alkenes

Water-gas shift

Side Reactions

Alcohols

Boudouard

The FT reactor operates at 535 K and 15 bar in presence of catalysts based on nickel and cobalt.

A number of studies were found on detailed reactions of the FT process, and the corresponding

yield from each type of reactor employed in the process [58-61]. Based on these findings, the FT

product distribution and the operating conditions of three different types of reactors are listed in

Table 3-8. Table 3-8 indicates that a slurry bed reactor has a higher conversion compared to the

fixed bed and riser reactors. The product distribution is also markedly different between the three

different types of reactors. A particular disadvantage of the slurry reactor is the higher

percentage of waxy compounds produced, which requires downstream processing in order to

31

enhance alkane yields. However, the slurry reactor has the advantage of a lower operation

pressure, which favors reactor economics and catalyst stability. For this study, a slurry reactor is

considered, based on the yields of products.

Table 3-8. Fischer-Tropsch Product Distribution in Different Reactors

Conditions Fixed bed

reactor

Riser reactor Slurry reactor

Temperature (K) 503 595 535

Pressure (bar) 25 23 15

Conversion (%) 60-66 85 87

Product (wt %)

CH4 2.0 10.0 6.8

C2H4 0.1 4.0 1.6

C2H6 1.8 4.0 2.8

C3H6 2.7 12.0 7.5

C3H8 1.7 1.7 1.8

C4H8 2.8 9.4 6.2

C4H10 1.7 1.9 1.8

C5-C11 18 40.0 18.6

C12-C18 14 7.0 14.3

C19+(wax) 52 4.0 37.6

Others 3.2 6 1

32

The next step after the FT reactor is to separate different hydrocarbons based on their carbon

ranges. When using a slurry reactor, about 40% of total mass product is wax, and the remaining

portion contains LPG, naphtha, jet fuel, and diesel streams. The wax stream is converted to

lighter hydrocarbons such as naphtha, jet fuel, and diesel by applying a thermal cracker unit, thus

increasing the overall yields of diesel, naphtha and jet fuel. Furthermore, an isomerization unit

can be added to convert diesel-range molecules to kerosene, key for satisfying the cold-flow

properties for renewable jet fuel.

In this thesis, three different possible scenarios for FT jet fuels are developed and compared (see

Figure 3-2). The first scenario (Baseline FT Scenario) includes a gasification unit followed by a

standard FT reactor and the distillation columns in which the synthetic fuels are separated based

on their boiling point. The second scenario includes the units from the first scenario, but adds a

cracking unit to convert the waxy product into lighter hydrocarbons, mainly diesel. The amount

of renewable diesel produced in this scenario is larger, and it is therefore called the Maximum

Diesel Scenario. In the third scenario, an isomerization unit is added to enhance the amount of jet

fuel production, by partially cracking and isomerizing some diesel to jet fuel. This is the

Maximum Jet Fuel Scenario. The methane recovered from the distillation column and the

cracking unit is converted to synthesis gas using a reformer unit. The synthesis gas produced is

recycled to the FT reactor, increasing yields.

33

Gasification

Unit

FT Reactor

and Separation

Columns

Cracking

Unit

Isomerization

Unit

Reformer UnitFeedstock

Clean Syngas

Wax

Methane

Diesel

Diesel

Recycle-Syngas

Jet Fuel

Light Gases

Naphtha

Wax

Diesel

Naphtha

Jet Fuel

Jet Fuel

Figure 3-2. Scenarios for Maximizing the Production of Renewable Diesel and Jet Fuels:

FT synthesis and separation units, cracking unit and isomerization unit are noted by red,

blue and green boxes, respectively.

3.2.3 Product Transportation, Distribution and Use

The jet fuel produced is assumed to be transported using trucks and utilized in an airplane. The

average distance is assumed to be 50 km based on the GREET model assumptions [49]. A single

aisle aircraft is assumed to consume the FT jet fuel. The GREET model [49] estimates the

amount of GHG emissions resulting from combusting FT jet fuel in different types of aircraft.

For the renewable diesel analysis, it is assumed that the renewable diesel is utilized in heavy-

34

duty trucks [49], although, as noted previously, use of low levels of renewable diesel in aircraft

has been proposed for ASTM approval.

35

4 Process Modeling

Aspen Plus has been used widely in the simulation of biofuel processes. The National Renewable

Energy Laboratory (NREL) has been a pioneer in utilizing Aspen Plus to model ethanol

production from lignocellulosic biomass [55, 56]. The physical property databank developed by

NREL [57] is used in this modeling. The gasifier was previously modeled in our research group

[54]. In this model, the gasification process is modeled in three different reactors, including a

Yield reactor, a Gibbs reactor and a stoichiometric reactor (Figure 4-1).

Figure 4-1. Gasifier model Source: Luk et al. (2015) [57]

Due to the high initial moisture content of hybrid poplar, a dryer is added before the gasifier. In

this configuration, the biomass is dried and its moisture content is reduced to 20% to be utilized

in the gasifier; the dried biomass is then sent to an oxygen-blown gasifier. The biomass is

converted to syngas, and is used to generate electricity and steam. The pressure of the gasifier is

30 bar and the temperature of the product syngas is about 800°C. The oxygen and nitrogen

required in gasification are provided by employing an air separation unit. The generated syngas

is cooled to 350°C and will be further cleaned. After removing the contaminants, the clean

syngas is sent to a Fischer-Tropsch (FT) reactor. Table 4-1 presents the amount of each

component in the syngas, as calculated by the Aspen Plus software.

36

Table 4-1. Syngas Composition from Aspen Plus Modeling

Components % Mole/dry base syngas

H2 27.6

CO 9.4

CO2 40

CH4 13

Other gases 10

The thermodynamic model used for the modeling is a combination of Non-Random Two Liquid

model (NRTL) and Redlich-Kwong (RK) models. The mixture of gases and liquids is non-ideal;

the NRTL model will calculate the fugacity of liquid phases and the RK model calculates the

fugacity of vapor phases. Using these models, the enthalpy of each phase and stream is

calculated. We selected these models based on the literature and previous NREL simulations

[55, 56].

37

Snapshots of the models developed in Aspen Plus are shown in Figures 4-2 to 4-4. We used

different types of reactor models such as the yield reactor and the conversion reactor in Aspen

Plus to model FT, cracking, and isomerization units. A summary of reactor models is shown in

Table 4-2. Detailed modeling of each scenario was performed and process models include heat

integration to minimize energy use of the entire process.

Table 4-2. Different Types of Reactors Used to Model Various Process Stages

Process Stage Aspen model

Gasification Unit Yield, Gibbs and Stoichiometric

FT reactor Yield

Cracking Stage Yield

Isomerization Stage Yield

Distillation Columns PetroFrac

38

Figure 4-2. Baseline FT Scenario includes gasification, FT reactor, and separation columns

Figure 4-3. Maximum Diesel Scenario: The Baseline FT scenario is followed by a cracking

unit and separation columns to maximize the renewable diesel stream

39

Figure 4-4. Maximum Jet Fuel Scenario: An isomerization unit is added to the Maximum

Diesel Scenario to convert the produced diesel fuel to jet fuel

40

4.1 Techno-Economic Analysis

The techno-economic analyses are based on the process modeling developed in Aspen Plus and

the mass and energy balances of the three scenarios described in Section 4.1. The Aspen Icarus

Process Evaluator software and literature have been used to estimate the cost of each key unit of

equipment. The capital investment (assumed equal to total direct cost) and indirect costs are

determined and a discounted cash flow analysis is performed in an Excel spreadsheet to

determine the rate of return on investment associated with the three scenarios. Table 4-3 lists the

major economic assumptions. It is considered as nth plant scenarios to assume that the technology

is enough developed and mature by that time to minimize the cost associated with developing the

technology in primary plants. Because the gasification and Fischer-Tropsch technologies have

been used for many years to produce liquid fuels from coal and natural gas, we considered all

three scenarios enough mature and developed to be assumed as the nth plant scenarios.

Table 4-3. Main Economic Assumptions for nth Plant Scenarios

Parameter Assumption

Depreciation Linear

Financing 60% equity

Bank Interest 7%

Loan Period 10 years

Lifetime of Plant 15 years

Construction Time 1 year

Income tax rate 35%

Natural Gas Cost $0.11/m3

Electricity cost $0.10/kWh

Feedstock Cost $40 per dry tonne of hybrid poplar

Working capital 15% of fixed capital investment

Land purchase 6% of total purchased equipment

Plant availability 310 days per year (85%)

41

4.1.1 Equipment Cost

The size and the cost for unit operations and equipment involved in each scenario are estimated

using the Aspen Icarus Process Evaluator software, based on the Aspen Plus simulation data and

literature review. The cost of unique equipment such as the gasifier, FT reactor, cracking,

reformer and the isomerization units are estimated based on literature [47, 58].

The costs of different sizes of equipment are estimated from Equation 4-1 in which “n”

represents a scaling factor between 0.6 and 1.0, depending on the type of equipment. For this

study, we considered an average value of 0.8. According to Equation 4-1, the cost of new

equipment is dependent on the cost of reference equipment, a scaling stream and the scaling size

factor. The reference equipment refers to the equipment from literature with a specific capacity

and size [59].

All purchased equipment costs estimated by Aspen Icarus include an installation factor that

accounts for piping, electrical, and other costs required for installation. Basically, the purchased

equipment cost is multiplied by the installation cost. This value is 1.94 for different equipment

and units, according to a National Energy Technology Laboratory study by Swanson et al. [47].

The Chemical Engineering Plant Cost Index is used to bring the cost to 2014 U.S. dollars

whenever a source for an estimated cost is from previous years. The Chemical Engineering Plant

Cost Index used for this study can be found in the Appendix.

Indirect costs were estimated as Pro-ratable costs and include fringe benefits, burdens, and

insurance of the construction contractor, accounting for 10% of total capital investment (TCI).

Field expenses refer to rental, field services, temporary construction facilities, and supervision,

assumed to equal 20% of the total capital investment. Cost of engineering and incidentals,

construction of the home office and purchasing required facilities are covered in “Home/Office”

costs. The contingency accounts for unexpected cost escalation and scope changes during the

project. Any other costs, such as those related to the permits, insurance, import of equipment or

42

chemicals, shipping, transportation, commissioning and start-up costs are all included in the

“Others” category [60-62].

All of the co-products produced in the different scenarios are fuels, and it is assumed that they

are all sold to the market. The prices of the fuels were determined from the U.S. Energy

Information Administration (EIA) website [63]. To address price fluctuations of petroleum fuels,

we used the prices of fuel from two different years. The first is 2008, in which oil experienced a

significant increase in price, and the second is 2015, in which the price of oil is low. For the light

gases and liquefied petroleum gas (LPG) produced in all three scenarios, it is assumed that the

price is equal to the price of propane. The naphtha and wax price are considered to be the same

as that for U.S. Gulf-Coast gasoline and U.S. Gulf-Coast residual oil prices, respectively. The

U.S. Gulf-Coast Ultra-Low sulfur No. 2 diesel prices are used. Table 4-4 presents prices for

LPG, naphtha, jet fuel, diesel and wax in 2015 and 2008.

Table 4-4. Fuel product prices in 2008 and 2015 (Source: EIA [63])

Product Fuel Price ($/L )

(2015)

Fuel Price ($/L )

(2008)

LPG 0.08 0.43

Naphtha 0.40 0.81

Jet fuel 0.23 0.78

Diesel 0.24 0.86

Wax 0.19 0.70

43

5 Results The results of the process simulation, including product distribution, life cycle energy use and

life cycle GHG emissions are presented in this section. The financial results are also presented,

in section 5.4. As discussed in chapter 3, three scenarios are considered: (i) Baseline FT

Scenario: standard FT system using a slurry reactor, (ii) Maximum Diesel Scenario that includes

a cracking unit to increase liquid fuel yields by cracking waxy compounds, and (iii) Maximum

Jet Fuel Scenario that adds an isomerization unit, which converts some of the diesel from (ii) into

jet-range hydrocarbons with suitable cold flow properties.

5.1 Process Simulation Results

5.1.1 Product Distribution

The process was simulated in Aspen Plus and the mass and energy balances obtained (Table

5-1). The results are presents in millions of cubic meters of fuel product per year. It is shown that

the light hydrocarbons represent the largest share of total volume among the products. The yields

of products have been calculated on a dry basis, as presented in Table 5-2.

Table 5-1. Simulation Results using Aspen Plus Software (Million m3/year). Plant Capacity

is 1.4 Million tonnes dry Biomass per Year.

Product Baseline FT Maximum Diesel

Scenario

Maximum Jet Fuel

Scenario

Million m3/year Million m3/year Million m3/year

LPG+LG 41.09 41.09 41.09

Naphtha 0.10 0.13 0.12

Jet Fuel 0.01 0.01 0.05

Diesel 0.05 0.15 0.13

Wax 0.18 0.06 0.06

44

Table 5-2. Aspen Simulation Results Using Aspen Plus software. Plant capacity is 1.4

million tonnes dry biomass per year.

Product Baseline FT Scenario Maximum Diesel

Scenario

Maximum Jet Fuel

Scenario

tonnes/tonne of dry

biomass

tonnes/tonne of dry

biomass

tonnes/tonne of dry

biomass

LPG+LG 0.06 0.06 0.06

Naphtha 0.05 0.07 0.06

Jet Fuel 0.006 0.006 0.009

Diesel 0.03 0.09 0.08

Wax 0.11 0.04 0.04

The Baseline Fischer-Tropsch Scenario yields approximately 41 million m3/year of light

hydrocarbons and 0.18 million m3/year of wax products. However, this scenario has the lowest

yield of jet fuel product, only 0.01 million m3/year. As expected, adding a cracking unit for the

Maximum Diesel Scenario increases the production of diesel, up to 0.15 million m3/year from

0.05. This unit also leads to an increase of about 0.03 million m3/year in naphtha production;

however, the volume of jet fuel remains the same as the previous scenario. The reason is that the

cracking unit, operating at 700 , breaks heavier hydrocarbons such as wax and converts more

than half of the wax product from the baseline scenario into lighter hydrocarbons, mainly diesel,

jet fuel and naphtha.

In the Maximum Jet Fuel Scenario, the isomerization system increases the jet fuel product yield

from 0.01 million m3 per year to 0.05 million m3 per year, while reducing the yield of diesel and

naphtha.

According to Table 5-2, a pathway with gasification combined with FT synthesis can produce

about 9 kg of jet fuel per tonne of dry biomass, in the Max Jet Scenario. The amount of diesel

produced varies in all three scenarios, accounting for 0.05, 0.15, 0.13 tonnes per tonne of dry

biomass in the Baseline FT, Max Diesel and Max Jet Scenarios, respectively.

45

In this thesis, the process modeling has been developed to increase the quantity of the desired

product, either jet fuel or diesel. Zhu Y. et al. [39] simulated two different FT platforms in which

the gasification process changed: directly heated gasification and indirectly heated gasification.

Their results indicate that using direct heated gasification can increase the amount of diesel

produced from 0.096 to 0.112 million m3 per year compared to an indirect gasification process,

with the same capacity (91 tonnes of dry hybrid poplar per hour). Further improvements in the

yield of diesel and jet fuel may be possible by including technologies to convert the large share

of LPG, LG and naphtha into the desired products. However, adding these upgrading units

results in increasing the cost of the process.

5.1.2 Mass Balance of Gasification Unit

For the gasification process, the Aspen Plus model developed by Luk et al. [57] was used. This

model is shown in Figure 5-1. They considered an updraft gasifier in which biomass is fed from

the top of the gasifier unit and the oxygen is blown from the bottom of the gasifier unit. In this

model, it is assumed that the energy for the drying process is provided by burning biomass.

46

Drying Syngas Cooling

Air Separation

Gasification

PoplarDry

Poplar

Steam

O2

N2

SyngasCooled

Syngas

Tar

Air

Figure 5-1. Block Flow Diagram of Gasification Unit: Luk et al. [57]

The hybrid poplar which has been dried to remove 30% of total moisture is sent to another dryer,

which again reduces the moisture content by 20%. Then, the dry poplar is sent to a gasifier unit

in which the oxygen is blown into the process from an air separation unit. The biomass is

converted to different components within the syngas stream. This stream mainly includes carbon

dioxide, carbon monoxide, hydrogen, methane and water. The yield of the process is 0.36 tonnes

of CO per dry tonne of hybrid poplar, and 0.04 tonnes of hydrogen per dry tonne of hybrid

poplar.

47

Table 5-3. The Mass Balance for the Gasification Unit: Luk et al. (2015) [57]

Component Streams (tonne/hr)

Poplar Dried

Poplar

Steam Air N2 O2 Syngas Tar Cooled

Syngas

Dry hybrid

poplar

188.5 188.5 0 0 0 0 0 0 0

Water 188.9 47.2 49.8 0 0 0 84.8 0 84.8

CO 0 0 0 0 0 0 68.0 0 68.0

CO2 0 0 0 0 0 0 180.5 0 180.5

CH4 0 0 0 0 0 0 21.8 0 21.8

H2 0 0 0 0 0 0 7.0 0 7.0

N2 0 0 0 209 18.5 2.0 20.8 0 20.8

O2 0 0 0 64 0.2 62.2 0 0 0

C2H4-C2H6 0 0 0 0 0 0 1.5 0 1.5

H2S + tar 0 0 0 0 0 0 0 0.4 0

Others 0 0 0 0 0 0 2.4 0 2.4

Total 377.8 236.2 49.8 273 18.7 81.9 386.8 0.4 386.8

From the table, it can be seen that about 40% of dry poplar is converted to mixture of carbon

monoxide and hydrogen, which sets a limit on the overall yield of liquid fuel from the

downstream FT process.

5.1.3 Energy Use

The main energy inputs for the process are in the forms of electricity, natural gas and biomass for

drying. Energy requirements were optimized as much as possible via heat integration. Biomass is

used in the dryer to remove the moisture from the feedstock. Natural gas is used in reboilers to

produce steam required for the process and in the furnaces. The energy demand for conversion of

hybrid poplar to fuels varies for each of the three scenarios, at 1550, 1800, and 1876 MJ of

48

natural gas per tonne of dry biomass for the Baseline FT Scenario, Max Diesel Scenario and Max

Jet Scenario, respectively. An efficiency of 90% conversion of natural gas to steam was used.

The steam demand of the process was calculated from the Aspen Plus simulation. In addition,

biomass is required for the dryer, to reduce the moisture content of the feedstock from 50% to

20% prior to gasification. The estimate of emissions in this drying step is based upon biomass

use for the dryers. The Baseline FT Scenario has the lowest energy consumption among the three

scenarios, this increases in the Max Diesel Scenario because of adding the cracking unit, which

works at high temperature to break down waxes. There are distillation columns after cracking

units in which the hydrocarbons are separated based on their carbon range number and their

boiling point. The first distillation column separates lighter hydrocarbons, mainly naphtha, and it

works at 130 oC, followed by the second column, which works at 270 oC to separate diesel and

residual oil. A significant amount of energy is required for both the (additional) cracking unit and

distillation systems. Moreover, in the Maximum Jet scenario, an isomerization unit is added,

followed by distillation columns to purify the jet fuel and diesel. These units also work at very

high temperature, resulting in a more energy intensive design scenario. These results are used to

calculate the amount of GHG emissions associated with burning natural gas, using GREET

emissions factors.

In addition, the electricity requirement of these scenarios represents the sum of the electricity

used in pumps, turbines and compressors. Based on the Aspen Plus results, the total amount of

electricity required for the Baseline FT Scenario, the Max Diesel Scenario and the Max Jet

Scenario are 0.18, 0.25, and 0.28 MW per dry tonne of biomass, respectively. Table 5-4 lists the

required amount of electricity for these different scenarios.

49

Table 5-4. Natural Gas and Electricity Consumption in the Different Scenarios

Baseline FT

Scenario

Maximum Diesel

Scenario

Maximum Jet Fuel

Scenario

Natural Gas

(MJ/dry tonne of

biomass)

1550 1800 1876

Electricity

(MWh/dry tonne of

biomass)

0.18 0.25 0.28

5.2 Life Cycle Assessment Results

The GHG emissions associated with different stages of the life cycle from poplar farming to the

plant exit gate, are allocated to the different fuel products on an energy basis. The share of GHG

emissions allocated to each product can be calculated from Equation 3-2 in Table 3-1. Table 5-5

indicates the energy fraction of each product.

Table 5-5. Share of GHG Emissions for Each Product Based on Energy Allocation Method

for the Three Scenarios

Product HHV

(MJ/kg )

Density

(kg/m3)

Share of energy content of each product in

total fuel products (%)

Baseline FT

Scenario

Max

Diesel

Scenario

Max Jet Fuel

Scenario

LPG+LG 50 2 25 24 24

Naphtha 48 719 20 27 25

Jet fuel 46 810 2 3 9

Diesel 44 832 12 33 29

Waxy Residue 42 900 41 13 13

50

In both the Maximum Diesel and Maximum Jet Fuel Scenarios, renewable diesel is allocated the

largest share of GHG emissions. Naphtha and LPG+LG also have significant shares of

emissions. However, the smallest portion of emissions is allocated to the renewable jet fuel

product, due to the lower yield of that product.

Based on the energy use of the feedstock production as well as from the Aspen Plus model for

the process, we evaluated the contribution of different stages of the life cycle to life cycle GHG

emissions. In the Maximum Diesel Scenario, the estimated amounts of emissions associated with

different stages of renewable diesel production are presented in Figure 5-2.

Figure 5-2. Greenhouse Gas Emissions Associated with Renewable Diesel for the Different

Life Cycle Stages of Fischer-Tropsch Pathway for the Maximum Diesel Scenario.

51

The GHG emissions associated with the life cycle stages from feedstock preparation to Fischer-

Tropsch diesel are feedstock production, natural gas burning, electricity consumption and fuel

transportation and distribution. The GHG emissions from combusting natural gas in the process,

which also includes upstream emissions associated with production/transportation of the natural

gas, and electricity consumption in the biorefinery are 1.4, and 1.1 g CO2 eq. per MJ of

renewable diesel, respectively. Natural gas and electricity are the two external energy sources

used in the biorefinery. Energy consumption in the biorefinery is the largest contributor to the

GHG emissions of renewable diesel fuel production, accounting for 2.5 g CO2 eq. per MJ of

FTD, or about 57% of total GHG emissions. There are also non CO2 GHG emissions resulting

from burning fuel in the vehicle; these amounts are very small based on GREET [49] model

results. Burning renewable diesel in heavy-duty trucks results in emitting CH4, corresponding to

about 0.5 grams of CO2 eq. per MJ of renewable diesel. In addition, burning renewable diesel in

heavy-duty trucks results in emitting N2O, corresponding to about 0.0003 grams CO2 eq. per MJ

of renewable diesel [49].

The GHG emissions associated with feedstock production include the emissions from harvesting

of hybrid poplar, chipping and transportation of feedstock to the biorefinery. The feedstock

preparation stage also accounts for a considerable share of GHG emissions, accounting for 1.7 g

CO2 eq. per MJ of FTD or 40% of total life cycle GHG emissions.

The life cycle GHG emissions results associated with the Maximum Jet Scenario are illustrated

in Figure 5-3. The feedstock production, feedstock transportation and fuel transportation and

distribution are similar with the renewable diesel production in Maximum Diesel Scenario.

However, the biorefinery stage emits more GHG emissions presenting 2.8 g CO2 eq. per MJ of

FTJ. Moreover, burning renewable jet fuel in an aircraft results in producing CH4, which is about

3.4 e-7 g CO2 eq. per MJ of FTJ. In addition, burning renewable jet fuel in an aircraft results in

producing N2O emission, which is about 6.8 e-7 g CO2 eq. per MJ of FTJ [49].

52

Figure 5-3. Greenhouse Gas Emissions Associated with Renewable Jet Fuel for the

Different Life Cycle Stages of Fischer-Tropsch Pathway for the Maximum Jet Fuel

Scenario

The GHG emissions of renewable diesel are 4.0 g CO2 eq. per MJ of renewable diesel in the

Maximum diesel scenario, which are significantly lower than those of petroleum diesel, which

are estimated to be 85.3 g CO2 eq. per MJ [49]. The main reason is that the carbon used for the

production of renewable diesel is considered biogenic, and is therefore a neutral source of

emissions. Biogenic carbon assumes that CO2 emissions generated during fuel combustion are

sequestered into poplar trees. In the GREET model [49], an energy allocation method has been

used to assign the GHG emissions of oil extraction, hydrotreating and refining to each of the

products (diesel, naphtha and jet fuel) for the petroleum diesel fuel.

GREET [49] includes a hybrid poplar FT jet pathway and other jet fuel pathways, such as hydro-

processed renewable jet (HRJ) production from canola and algae. Table 5-6 presents the GHG

53

emissions results for the renewable diesel and jet fuel produced through each scenario and

compares these results with Fischer-Tropsch pathway from GREET [49].

Table 5-6. Life cycle GHG emissions associated with the three scenarios compared to

petroleum diesel and jet fuel pathway from GREET [49]

Life cycle GHG emissions

gCO2 eq./MJ jet fuel

Life cycle GHG emissions

gCO2 eq./MJ diesel

Baseline FT Scenario 3.3 3.5

Max Diesel Scenario 4.1 4.3

Max Jet Scenario 5.4 5.6

Petroleum Diesel/Jet Fuel 85 88

a Data obtained from GREET 2015 [49]

54

0102030405060708090

Gra

ms

of

CO

2eq

/MJ

of

FT

J

Figure 5-4. Life cycle GHG emissions of different jet fuel production pathways: three

different scenarios in the current study; Fischer-Tropsch jet fuel from biomass which is

hybrid poplar (Biomass-FTJ); Hydroprocessed Renewable jet (HRJ); and petroleum jet

fuel. *Data obtained from GREET [49]

Figure 5-4 illustrates the differences among different scenarios and different pathways. It can be

seen that the life cycle greenhouse gas emission associated with Fischer-Tropsch pathways are

lower compared to hydroprocessed renewable jet fuel from canola and algae. The main reason is

that canola requires more fertilizer inputs compared to poplar and the algae production is a very

energy intensive process compared to other feedstocks.

5.3 Utilizing LPG and its impact on LCA

The light gas and LPG produced from the FTD process can be utilized in the process to generate

the heat and electricity required for the process. Utilization of light gases and LPG will reduce

the GHG emissions associated with natural gas imported for the process, while it will increase

the emissions allocated to diesel and jet fuel under an energy allocation process.

The energy content of LPG is 3000 MJ/dry tonne of biomass, using the higher heating value of

50 MJ/kg of propane. The amount of LPG is sufficient to cover the heating requirements in each

55

of the scenarios (Table 5-3) and it will eliminate the utilization of NG and its associated GHG

emissions. The GHG emissions associated with NG are 1.4 g CO2 eq. per MJ of renewable

diesel, which is equivalent to 35% of total GHG emissions. By utilizing LPG, the total emissions

are reduced by 35%. The remaining portion of the LPG is not sufficient to generate electricity

(1200-1500 MJ/dry tonne of biomass).

5.4 Cost Estimating and Cash Flow Analysis Results

Table 5-7 presents the estimated price for specific process units, including the gasifier, air

separation units, Fischer-Tropsch reactor, reformer, wax cracking, isomerization unit and other

equipment. The installation factor has been applied. It can be seen that both wax cracking and

isomerization units are expensive units, costing $52 MM and $38 MM, respectively.

Table 5-7. Estimated Installed Cost of Units and Equipment for Plant Capacity of 1.4

Million dry tonnes Hybrid Poplar per Year, 2014 USD [47, 58, 59]

Unit Estimated Price ($MM)

Gasifier 55

Air Separation Unit 19

Fischer-Tropsch Reactor 36

Reformer 40

Wax-Cracking 52

Isomerization Unit 38

Equipment

Pumps 0.5

Compressors 44

Columns 9

Heat exchangers 12

Scenario Baseline FT Max Diesel Max Jet

Total Installed Cost (TIC) = Direct Cost 217 270 305

56

The gasifier, wax cracking, and reformer units are the most expensive units, with higher installed

costs, accounting for $55 MM, $53 MM and $41 MM, respectively. Moreover, compressors at

$45 M are the most expensive piece of equipment. Table 5-8 lists indirect costs, including

proratable costs, field expenses, home and office cost, contingency and others.

Table 5-8. Estimated Indirect Cost, Fixed capital cost, and Total Capital Investment (TCI)

for 1.4 Million tonnes dry Poplar, Based on 2014 USD

Assumption $MM

Baseline Max

Diesel

Max Jet

Direct Cost TIC 217 270 308

Proratable Cost 0.1 * TIC 21 27 30

Field Expenses 0.1 * TIC 21 27 30

Home/Office 0.2 *TIC 43 54 61

Contingency 0.1 * TIC 21 27 30

Other Costs 0.1*TIC 21 27 30

Indirect Cost (IC) 130 162 185

Fixed Capital Investment

(FCI)

TIC + IC 347 432 493

Land 0.1 TIC 21 27 30

Working Capital 0.05* FCI 17 21 24

Total Capital Investment

(TCI)

Sum (FCI, Land, Working

Capital)

385 479 548

It can be seen that direct costs and indirect costs account for about 62% and 38% of fixed capital

cost, respectively.

Table 5-9 illustrates the results of cash flow analysis for the Baseline FT, Maximum Diesel and

Maximum Jet Fuel Scenarios. This table represents the results based on a feedstock cost of $40

57

per dry tonne of feedstock. This feedstock price, although low, is a reasonable cost for forest

residues, and represents a “best case” outcome for the financial analysis. The effect of different

ranges of feedstock cost on the levered rate of return on investment is subsequently evaluated.

Each plant has an annual capacity of 1.4 million dry tonnes of biomass. All values are in 2014

USD.

The levered rate of return on investment is calculated for the different scenarios and under the

low and high fuel price scenarios. It is highly dependent on the prices of the fuel products. It can

be seen that for the fuel prices in 2015, this plant would have had a negative rate of return on

investment for the Baseline FT and Maximum Jet Fuel Scenarios. This means that these

scenarios would not have been financially viable. The Maximum Diesel Scenario has a rate of

return of 0.02% – essentially break-even. However, assuming fuel prices from 2008, the levered

rate of return on investment was about 9.0%, 9.4% and 7.8 % for the Base-line FT, Maximum

Diesel and Maximum Jet Scenarios, respectively, due to the much higher prices for fuel products

in 2008.

58

Table 5-9. Cash Flow Analysis Results and Estimated Levered Rates of Return on

Investment for Different Scenarios in 2008 and 2015

Product Low Fuel Price Scenario

($MM/year)

High Fuel Price Scenario ($MM/year)

Baseline

FT

(Annual

Revenue)

Max

Diesel

(Annual

Revenue)

Max Jet

(Annual

Revenue)

Baseline

FT (Annual

Revenue)

Max Diesel

(Annual

Revenue)

Max Jet

(Annual

Revenue)

LPG 10 10 10 56 56 56

Naphtha 31 45 37 76 108 90

Jet fuel 2 3 6 9 16 32

Diesel 10 31 27 37 108 96

Wax 25 8 8 93 31 31

Total

Annual

Revenue

79 98 90 271 319 305

Rate of

Return on

Investment

(%)

-1.1 0.02 -0.2 9.0 9.0 7.8

Table 5-9 indicates that different fuel products have different impacts on total annual revenue.

For example, jet fuel and wax products have a small contribution to total annual revenue;

however, naphtha and diesel have a significant share of the total annual revenue.

59

There are different factors that can affect the rate of return on investment. For example, we

studied the effect of feedstock cost on the levered rate of return on investment based on fuel

product prices in 2008 and 2015.

Figure 5-5 shows that the price of feedstock has a negative effect on the levered rate of return on

investment. Feedstock price is clearly an important parameter. Increasing the feedstock price

from $30 per tonne of dry poplar to $85 per tonne of dry poplar reduces the ROI from 10 to 6

under the 2008 price scenario, and from 0.13 to – 6.8 under the 2015 price scenario. These

results confirm that feedstock price is an important factor impacting the financial viability of a

renewable fuel facility using gasification + FT technology. One means of addressing this issue

would be through a targeted government incentive program, such as the US Biomass Cost

Assistance Program (BCAP), which aims to reduce the cost of feedstock to the biorefinery

through a cost-sharing program.

-8

-6

-4

-2

0

2

4

6

8

10

12

Lev

ered

Rat

e of

Ret

urn

on I

nves

tmen

t %

Poplar Feedstock Price ($/dry tonne)

2015

2008

30 40 50 60 70 80 85

Figure 5-5. Effect of Feedstock Price on Levered Rate of Return on Investment, Assuming

60% equity

60

5.5 Carbon Tax Sensitivity Analysis

The revenue potential of renewable fuels is highly dependent on the petroleum fuel prices and

feedstock price. To reduce the potential market risks associated with renewable jet fuel prices, an

option to include credits for GHG mitigation is considered. The United States Environmental

Protection Agency (EPA) was created for the purpose of protecting the environment, and one of

the EPA’s mandates is to regulate GHG emissions. For example, under the Renewable Fuel

Standard (RFS) in the United States, biofuels that reduce GHG emissions by at least 50% can

qualify for a renewable identification number (RIN), which can be sold by the producer for

added revenue (EPA 2010a). Other jurisdictions, such as California and BC, require obligated

parties to acquire credits based upon the GHG intensity of the fuels that they purchase, and

targeted GHG reductions across the fuel pool. A carbon credit sensitivity analysis has been

studied for two different carbon price scenarios; $30 and $100 per tonne of CO2 equivalent.

Table 5-10 indicates that the carbon credit associated with Fischer-Tropsch renewable jet fuel

production is about 8 cents per liter of renewable jet fuel once the CO2 cost is $30 per tonne of

CO2 equivalent. The carbon credit value increases to 27 cents per liter of renewable jet fuel as

the CO2 cost increases to $100 per tonne of CO2 equivalent.

Table 5-10. Carbon Credit Sensitivity Analysis for Fischer-Tropsch Renewable Jet Fuel

Production

Life Cycle GHG

emissions (g CO2/MJ FTJ)

Carbon Credit

$30/tonne of CO2

equivalent

$100/tonne of CO2

equivalent

Baseline FT 3.3 8.1 cents/L 27 cents/L

Maximum Diesel 4.1 8.0 cents/L 27 cents/L

Maximum Jet Fuel 5.4 7.8 cents/L 26 cents/L

61

A $30/tonne carbon tax would beneficially affect the financial performance of the facility,

although the impact is likely to be small. The difference in fuel prices between the 2008 and

2015 scenarios is about 50 - 60 cents/L, while a $30/tonne carbon tax affects prices by about 8

cents/L. Thus, a carbon tax alone is unlikely to be sufficient to sway an investment decision.

Considering that Canadian jet fuel demand is 4.5 million m3 per year, a facility producing 0.05

million m3 per year of jet fuel (maximum jet scenario) is able to cover only about 1.1% of jet fuel

demand. In order to replace 50% of petroleum jet fuel with renewable jet fuel, about 45 Fischer-

Tropsch facilities are required.

62

6 Conclusions

Although the Fischer-Tropsch process is a developed technology, the potential to produce

renewable jet fuel from hybrid poplar is low. In terms of overall financial metrics, renewable jet

fuel represents the lowest share in total annual revenue; however, diesel has the greatest value

compared to other fuel products.

On the other hand, sustainable feedstock supply is a critical point required to be considered in

renewable jet fuel production. Feedstock is a major contributor to the cost of alternative jet fuels.

Therefore, it needs to be included in supporting policies as well as in the research and

development efforts. In addition, securing a long-term sustainable feedstock supply at

competitive prices is a key asset for an alternative jet fuel project to be financed.

Therefore, building an integrated value chain from the beginning of the project development is

required to secure feedstock supply and feedstock price.

The annual jet fuel demand in Canada is about 4.5 million m3. Considering this number, the

maximum jet fuel scenario, in this study, is able to only cover 0.02 % of Canadian annual jet fuel

demand. To replace 50% of the petroleum jet fuel with renewable jet fuel would require about 45

maximum jet fuel plants, with an annual capacity of 1.4 million tonne of dry biomass.

This study can be continued to investigate the impact of geographical variations in the total GHG

emissions of the Fischer-Tropsch pathway. The geographical variation will impact production of

biomass and the GHG emissions assigned to electricity using in the jet fuel production process.

63

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