Post on 20-Sep-2020
Life Cycle Modelling of Multi-Product Lignocellulosic Ethanol Systems
by
Timothy Shen
A thesis submitted in conformity with the requirements for the degree of Masters of Applied Science
Graduate Department of Chemical Engineering and Applied Chemistry University of Toronto
© Copyright by Timothy Shen 2012
ii
Life Cycle Modelling of Multi-Product Lignocellulosic Ethanol
Systems
Timothy Shen
Masters of Applied Science
Graduate Department of Chemical Engineering and Applied Chemistry University of Toronto
2012
Abstract
Life cycle assessment is an important tool to evaluate the impact of 2nd generation
lignocellulosic ethanol, and its potential greenhouse gas (GHG) emissions benefits relative to
gasoline. The choice of feedstock, process technology, and co-products may affect GHG
emissions and energy metrics. Co-products may improve both the financial and environmental
performance of the biorefinery. 26 well-to-wheel models of future lignocellulose-to-ethanol
pathways were constructed, considering corn stover, switchgrass, and poplar feedstocks, three
pre-treatment technologies, four co-product options, and the use of ethanol in a light-duty
vehicle. Model results showed that all pathways with lignin pellet co-production had
significantly lower net GHG emissions relative to gasoline and corresponding pathways
producing only electricity. Pathways co-producing xylitol had at least 66% greater GHG
emission reductions relative to pathways co-producing only lignin pellets. All
feedstock/pretreatment/co-product combinations led to GHG reductions of at least 60%,
meeting the threshold stipulated under the Energy Independence and Security Act.
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Acknowledgments
I wish to express my sincere gratitude and thanks to Professors Bradley A. Saville and Heather L.
MacLean for all their guidance, advice, knowledge and patience leading up to the creation of this thesis.
They have both been an endless source of inspiration and support in this field of study. I would also like
to thank Jon McKechnie for his boundless enthusiasm and assistance in life cycle calculations and
Mohammad Pour Bafrani for his expert and friendly advice in lignocellulosic ethanol pre-treatment,
distillation and technology. Additionally I would like to extend a special thanks to Daniel Liao and
Mascoma Canada Inc. for providing detailed and necessary information on autohydrolysis pretreatment
and modelling and Mark Laser for providing vital model information on ammonia fibre expansion
pretreatment. Without their combined assistance, this work would not have been possible. Finally I
would like to thank my parents for their tireless support of my goals.
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Table of Contents
ABSTRACT ..................................................................................................................................................... ii
ACKNOWLEDGEMENTS ............................................................................................................................... iii
LIST OF TABLES ........................................................................................................................................... vii
LIST OF FIGURES ........................................................................................................................................ viii
LIST OF ABBREVIATIONS ................................................................................ Error! Bookmark not defined.
1. INTRODUCTION ........................................................................................................................................1
1.1 Research objectives ............................................................................................................................5
1.2 Thesis Outline .....................................................................................................................................6
1.3 Related publications and presentations to this thesis .......................................................................6
2. LITERATURE REVIEW ................................................................................................................................7
2.1 Life Cycle Assessment ........................................................................................................................7
2.1.1 Co-Product Allocation .............................................................................................................. 12
2.2 Lignocellulosic Structure and Components ..................................................................................... 13
2.3 Lignocellulose to Ethanol Conversion Technology .......................................................................... 15
2.3.1 Pretreatment Technology ........................................................................................................ 16
2.3.2 Enzymatic Hydrolysis Technology ............................................................................................ 21
2.3.3 Ethanol Fermentation .............................................................................................................. 23
2.3.4 Ethanol Recovery ..................................................................................................................... 25
2.4 Ethanol Co-Products ........................................................................................................................ 25
2.4.1 Electricity Generation ............................................................................................................... 26
2.4.2 Lignin Pellets ............................................................................................................................ 27
2.4.3 Protein ...................................................................................................................................... 27
2.4.4 Xylitol ........................................................................................................................................ 28
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2.5 Review of Well-to-Wheel Analyses of Lignocellulosic Ethanol ....................................................... 28
3. METHODS .............................................................................................................................................. 31
3.1 Well-to-Wheel Model Scope, Development and Data Sources ...................................................... 31
3.2 Life Cycle Metrics and Functional Unit ............................................................................................ 35
3.3 Feedstock Production...................................................................................................................... 35
3.4 Lignocellulosic Biomass Conversion to Ethanol Modelling ............................................................. 37
3.4.1 Pretreatment Modelling........................................................................................................... 40
3.4.2 Enzymatic Hydrolysis & Fermentation ..................................................................................... 43
3.4.3 Ethanol Recovery and Blending ............................................................................................... 45
3.4.4 Waste Residue Processing, Boiler and Wastewater Treatment .............................................. 47
3.5 Co-Product Production Modelling .................................................................................................. 48
3.6 Co-Product Allocation ..................................................................................................................... 51
3.7 Ethanol Fuel, Distribution (gate to pump) and Model Vehicle ....................................................... 52
4. RESULTS AND DISCUSSION .................................................................................................................... 53
4.1 Single Feedstock Pathways Comparison ......................................................................................... 53
4.1.1 Ethanol and Co-Product Outputs ............................................................................................. 54
4.1.2 Energy Use Results ................................................................................................................... 56
4.1.3 Greenhouse Gas EmissionsResults ........................................................................................... 63
4.2 Comparisons Between Feedstocks ................................................................................................. 65
4.2.1 Pretreatment Monomer Yields ................................................................................................ 66
4.2.2 Ethanol Plant Stage Outputs .................................................................................................... 67
4.2.3 Energy Considerations.............................................................................................................. 69
4.2.4 Greenhouse Gas Emissions Considerations ............................................................................. 73
4.3 Non-Greenhouse Gas Emissions ..................................................................................................... 77
4.4 Water Use ....................................................................................................................................... 80
4.5 Ethanol Plant Waste ........................................................................................................................ 81
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4.6 Low Ethanol Yield Scenarios ............................................................................................................ 83
4.6.1 Fossil Energy ............................................................................................................................. 83
4.6.2 Greenhouse Gas Emissions ...................................................................................................... 85
5. CONCLUSIONS ....................................................................................................................................... 87
5.1 Summary ......................................................................................................................................... 87
5.2 Implications ..................................................................................................................................... 92
5.3 Limitations and Future Work .......................................................................................................... 94
6. BIBLIOGRAPHY ....................................................................................................................................... 96
APPENDICES ............................................................................................................................................ 103
Appendix A Life Cycle Model Design Calculationsぐぐぐぐぐ..........ぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐくヱヰヶ
Appendix B Life Cycle Results Data Tablesぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐぐ..ぐぐぐぐくヱヴヵ
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List of Tables
Table 2.1 Composition of Common Lignocellulosic Materials .................................................................. 15
Table 2.2 World Demand (1987) for Various Products Derivable from Lignocellulose Fermentation ..... 26
Table 3.1 Lignocellulosic Biomass to Ethanol Pathway Designations and Characteristics ....................... 34
Table 3.2 Feedstock Composition ............................................................................................................. 37
Table 3.3 Pretreatment Conditions for Ethanol Conversion Models by Feedstock ................................. 39
Table 3.4 Enzymatic Hydrolysis & Fermentation Conditions by Pretreatment ........................................ 44
Table 4.1 Annual Production of Ethanol and Co-Products by Pathway .................................................... 55
Table 4.2 Sugar Monomer Yield for Pretreatment and Enzymatic Hydrolysis Steps by Pathway Typea .. 56
Table 4.3 Ethanol Fermentation Yields from Monomeric Sugars by Pathway Type ................................ 56
Table 4.4 Co-product Energy and Emissions Credits Generated per Unit of Co-Product ......................... 62
Table 4.5 Combined Sugar Monomer Yield for Pretreatment and Enzymatic Hydrolysis Steps by
Feedstock and Pre-treatment Type Used ................................................................................................. 66
Table 4.6 Ethanol Plant Stage Outputs for all Conversion Pathways and all Feedstocks ......................... 68
Table 4.7 Life Cycle Fossil Energy Use for Agricultural Activities by Feedstock ........................................ 72
Table 4.8 Composition of Gypsum Waste Stream from Dilute Acid Hydrolysis Pathways by Feedstock 82
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List of Figures
Figure 1.1 Generic Biochemical and Thermochemical Biomass-to-Ethanol Conversion Processes ............2
Figure 2.1 International Organization for Standardization Life Cycle Assessment Framework ..................8
Figure 2.2 Generalized Life Cycle Inventory ............................................................................................. 10
Figure 2.3 Generalized Lignocellulosic Ethanol Life Cycle ........................................................................ 10
Figure 2.4 Well-to-Gate Life Cycle Inventory for Cellulosic Ethanol ......................................................... 11
Figure 2.5 Chemical Structure of Cellulose ............................................................................................... 13
Figure 2.6 Chemical Structure of Hemicellulose ....................................................................................... 13
Figure 2.7 Portion of the Chemical Structure of Lignin ............................................................................ 14
Figure 2.8 Block Diagram of a Typical Lignocellulose-to-Ethanol Conversion Scheme ............................ 16
Figure 2.9 Effect of Pretreatment on Lignocellulose ................................................................................ 17
Figure 2.10 Mechanism for Enzymatic Hydrolysis of Cellulose by Cellulase ............................................ 22
Figure 2.11 Xylanase Specificity ................................................................................................................ 23
Figure 2.12 Different Enzymatic Hydrolysis and Fermentation Strategies ............................................... 24
Figure 3.1 Lignocellulose to Ethanol and Reference System Block Diagrams .......................................... 32
Figure 3.2 Simplified Ethanol Plant Schema utilizing Dilute Acid, AFEX and Autohydrolysis Pretreatment
Processes ................................................................................................................................................... 39
Figure 3.3 Block Diagram of Dilute Acid Hydrolysis Pretreatment and Detoxification Steps ................... 41
Figure 3.4 Block Diagram of Ammonia Fibre Expansion Pretreatment and Ammonia Recovery Steps ... 42
Figure 3.5 Block Diagram of Autohydrolysis Pretreatment ...................................................................... 43
Figure 3.6 Block Flow Diagram of Autohydrolysis Pathway Ethanol Recovery Scheme ........................... 46
Figure 3.7 Block Flow Diagram of Ethanol Recovery Scheme ................................................................... 48
Figure 3.8 Block Diagram of Pelletization Module .................................................................................... 49
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Figure 3.9 Block Diagram of Xylitol Production Model ............................................................................. 50
Figure 4.1a Well-to-wheel Energy Use of Gasoline and Corn Stover-to-E85 Pathways ........................... 58
Figure 4.1b Well-to-wheel Petroleum Energy Use of Gasoline and Corn Stover-to-E85 Pathways ......... 60
Figure 4.2 Breakdown of Well-to-Pump Fossil Energy Use by Activity for Ethanol Pathways ................. 61
Figure 4.3 Well-to-Wheel GHG Emissions of Gasoline and Corn Stover-to-E85 Pathways ...................... 65
Figure 4.4 WTW Fossil Energy Use for each Pathway by Feedstock and Conversion Technology ........... 70
Figure 4.5 Net Well-to-Wheel Methane Emissions by Conversion Pathway and Feedstock ................... 73
Figure 4.6 Net Well-to-Wheel Nitrous Oxide Emissions by Conversion Pathway and Feedstock ............ 73
Figure 4.7 Well-to-wheel Greenhouse Gas Emissions by Conversion Pathway and Feedstock ............... 76
Figure 4.8 Net Well-to-Wheel Non-Greenhouse Gas Emissions by Pathway ........................................... 79
Figure 4.9 Ethanol Plant Stage Water Requirement for all Conversion Pathways and Feedstocks ......... 80
Figure 4.10 Well-to-Wheel Fossil Energy Use for High and Low Ethanol Yield Scenarios using Corn Stover
Feedstock by Conversion Pathway ........................................................................................................... 84
Figure 4.11 WTW Greenhouse Gas Emissions for High and Low Yield Scenarios using Corn Stover
Feedstock by Conversion Pathway ........................................................................................................... 86
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List of Abbreviations/Glossary
DOE US Department of Energy
USDA US Department of Agriculture
EISA Energy Independence and Security Act of 2007
NREL National Renewable Energy Laboratory
GREET Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation Model
LCA Life Cycle Assessment
LCI Life Cycle Inventory Analysis
LCIA Life Cycle Impact Assessment
SB Sugar Beet
CS Corn Stover
SG Switchgrass
HP Hybrid Poplar
DA Dilute Acid Hydrolysis
AFEX Ammonia Fibre Expansion
AH Autohydrolysis
EL Electricity Co-production
PE Lignin Pellet Co-production
PR Protein and Electricity Co-Production (Simultaneous Co-Production)
XE Xylitol and Electricity Co-Production (Simultaneous Co-Production)
XP Xylitol and Lignin Pellet Co-Production (Simultaneous Co-Production)
GHG Greenhouse Gas
HMF Hydromethoxyfurfural
NMVOC Non-Methane Volatile Organic Compound (same as VOC in this thesis)
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RFG Reformulated Gasoline
E85 Ethanol Fuel (85vol% Ethanol, 15vol% gasoline)
WTP Well-to-Pump
PTW Pump-to-Wheel
WTW Well-to-Wheel
CBP Consolidated BioProcessing
System Expansion Method of avoiding co-product allocation, in which the scope of a life cycle
system is expanded to encompass the life cycle of an established product(s) that is/are displaced by a
co-product(s) produced by the main life cycle.
System Sub-Division Method of avoiding co-product allocation by dividing the unit process to be
allocated into two or more sub-processes and collecting the input and output data related to
these sub-processes (sub-divisions).
Allocation Method Method involving the partitioning of life cycle impacts to multiple products
from a single life cycle stage on the basis of a metric such as energy content, mass, or market value.
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1. Introduction
Interest in alternatives to fossil fuels for the transportation sector has motivated research,
development and deployment of biofuels. In particular, ethanol produced from lignocellulosic
feedstocks has seen increasing attention as a light-duty vehicle fuel, giving rise to a large number of
production pathways that have been examined in technological reviews [1,2]. In 2012, the US
Environmental Protection Agency (EPA) is looking to produce between 1.3-48.8 million litres of
cellulosic biofuels, with the majority likely coming from ethanol production[3]. Canadian regulations
have also been implementedwith a required 5% and 2% (by volume) renewable fuels content in
gasoline and diesel [4]. With the adoption of ethanol blending targets, there is increasing pressure to
produce ethanol from renewable sources.
Starch-to-ethanol processes using corn and wheat are the dominant production methods for ethanol in
the United States and Canada to date. However, there are food versus fuel concerns and these
feedstocks are less abundant than lignocellulosic feedstocks. Ultimately, lignocellulosic biomass will be
required to further expand the bioethanol industry. Mabee et al.[5] stated that lignocellulosic biomass
from agricultural and forest residues alone had the potential to satisfy approximately 14% and 5% of
Canadian and US annual transport fuel demand, respectively. While there are mature technologies that
produce ethanol from corn and sugarcane, ethanol from lignocellulosic feedstocks remains on the
verge of commercialization. Due to lignocellulosic ethanolげゲ ヴWノ;デキ┗W キミa;ミI┞が デエWヴW キゲ ミラデ ┞Wデ ;
dominant conversion process as the technology continues to develop.
Lignocellulosic material is characterized as a biomass feedstock consisting of cellulose, hemicellulose
and lignin. Lignocellulosic feedstocks include agricultural crops and residues, forests biomass and
portions of municipal waste. Due to the prevalence of corn and wheat production, it is likely that the
first lignocellulosic ethanol plants will use agricultural residues such as corn stover and wheat straw as
feedstock [5]. Wood and forest residues remain another popular source of lignocellulosic material with
large supplies in Canada and the U.S., particularly in British Columbia, Quebec, Georgia, Oregon, North
Carolina and Alabama. Mabee et al. [5] estimated that between 0.2 and 1.6% of US 2010 gasoline
demand can be satisfied by ethanol produced from US forests while between 2 and 8.4% of Canadian
gasoline demand can be satisfied by Canadian forests. Decades of funding by the US Department of
Energy (DOE) for woody and herbaceous energy crop research has produced species such as hybrid
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poplar and switchgrass. These species demonstrate advantageous characteristics such as fast growth
and high yields on marginal cropland. Switchgrass in particular has been identified by the DOE as a
model lignocellulosic energy crop [7].
To date, lignocellulosic conversion methods presented in the literature mainly fall into two categories:
Biochemical and thermochemical, which are able to convert a wide variety of biomass to ethanol and a
number of co-products (e.g., electricity, fuel pellets, chemicals). As summarized in Figure 1.1, both
categories of conversion methods involve breaking down lignocellulosic feedstocks to simpler
intermediates to produce ethanol; however biochemical methods generally use a living organism to
convert the intermediates (fermentation), while thermochemical methods use catalytic synthesis.
Intermediates for biochemical methods often involve five and six carbon sugars that are the product of
hydrolysis of the original lignocelllulosic material. The intermediate in thermochemical methods is
generally a syngas formed from subjecting the feedstock to extreme temperatures [7]. The focus of this
thesis is on biochemical methods, and thus further description and analysis will only involve
biochemical conversion.
Figure 1.1 Generic Biochemical and Thermochemical Biomass-to-Ethanol Conversion Processes
The majority of established ethanol production methods are based on biochemical conversion, and
have been well characterized in the literature [2,8]. Biochemical based ethanol production generally
involves several common steps: pretreatment, hydrolysis, fermentation and fractionation to produce
an anhydrous ethanol that is compatible with commercial specifications [9]. In general, the
3
pretreatment step is used to disrupt the structure of the lignocellulose to make it susceptible to
hydrolysis. In many cases, pretreatment technologies are able to hydrolyze a portion of the
hemicellulose fraction of the lignocellulose as well. After pretreatment, a dedicated hydrolysis step
breaks the pretreated fibres into individual hexose and pentose sugars that are fermented to ethanol
using a strain of yeast (Saccharomyces cerevisiae) or other suitable microorganism. The ethanol-
coミデ;キミキミェ さHWWヴざ ヮヴラS┌IWS aヴラマ aWヴマWミデ;デキラミ キゲ デエWミ aヴ;Iデキラミ;デWS デラ ヴWIラ┗Wヴ デエW Wデエ;ミラノ ;デ エキェエ
purity. A wide number of feedstock options exist, as well as options for each of the steps in the
conversion process. To be economically viable, many ethanol production pathways are expected to
involve co-product production following a biorefinery concept [10]. Biorefinery concepts in the
literature have included bio-based plastics, isolated lignins, lactic and acetic acid, protein, hydrogen,
and electricity as products [10,11,12]. The co-production of value-added products with lignocellulosic
ethanol is an emerging opportunity, due to the wide variety of possible products and their potential
environmental and economic benefits.There are differing views as to whether liquid transportation
fuels or electricity generation or bioproducts or all of the aforementioned should be the focus for the
use of biomass feedstock. FitzPatrick et al. [10] noted that the use of biomass for energy and fuel
production is limited by the availability of biomass, while the use of biomass for chemical production is
limited by market demand. According to Smith et al. [13] in 2007, 3% of US petroleum was used to
produce chemical products, while over 70% was used by the transportation sector, amounting to
US$375 billion and US$385 billion markets, respectively . The similarity of the market values led
FitzPatrick et al. [10] to state that there is a potentially substantial economic gain for bio-based
chemicals and intermediates due to their high value-added, while using only a fraction of the available
biomass. However, due to its high volumetric demand and wide variety of uses, the DOE (US
DWヮ;ヴデマWミデ ラa EミWヴェ┞ぶ ゲデキノノ ノキゲデゲ Wデエ;ミラノ a┌Wノ ;ゲ ; デラヮ さゲ┌ヮWヴIラママラSキデ┞ざ aラヴ ノキェミラIWノノ┌ノラゲキI aWWSゲデラIニ
use [12].
Life Cycle Assessment (LCA) is a method to quantify the environmental impacts of products, processes
and projects. Several guidelines for LCA have been published by the International Organization for
Standardization [14,15,16]. LCA has seen widespread use in biofuels literature and a considerable
number of studies have examined lignocellulosic ethanol [17]. In-depth lignocellulosic ethanol-related
LCA research has been published in the literature by Sheehan et al. [18], Luo et al. [19], Spatari et al.
[20], Cherubini et al. [21] and McKechnie et al. [22], among others.
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Despite the available life cycle studies on lignocellulosic ethanol, only a limited set consider multiple co-
products and/or conversion technologies and only a subset of these investigate them in terms of
energy and environmental impacts (eg. [20,23,17]). Studies have concluded that co-products can have
a considerable effect on overall life cycle performance [20,24,25]. However, investigation of a wide
range of co-products in lignocellulosic ethanol LCAs is still not a well explored area of study, although
they play potentially large economic and environmental roles [9]. The majority of studies have treated
Wデエ;ミラノ ヮヴラS┌Iデキラミ ;ゲ ; さHノ;Iニ Hラ┝ざ ヮヴラIWゲゲが マ;ニキミェ キデ キマヮラゲゲキHノW デラ デエラヴラ┌ェエノ┞ W┝;マキミW ヮヴラIWゲゲWゲ
based on different conversion and co-product options [26]. Most studies have focused on a single
conversion pathway and co-product and comparison of studies with different technologies remains
difficult due to greatly differing life cycle frameworks involved [20].
The research in this thesis aims to address some of the above stated gaps in LCAs. Within this thesis, an
LCA framework has been constructed for a number of biomass-to-ethanol scenarios in order to study
the energetic and environmental consequences of different co-production strategies on the
lignocellulosic ethanol process. These analyses involve utilizing three feedstocks (corn stover,
switchgrass, hybrid poplar) in combination with three biochemical lignocellulosic ethanol conversion
processes differentiated by pretreatment (dilute acid hydrolysis, ammonia fibre expansion and
autohydrolysis), each producing up to four different co-products (electricity, protein, lignin pellets,
xylitol). Comprehensive process models have been developed to analyze the ethanol plant life cycle
stage of each combination. We examine a total of twenty three different well-to-wheels (the term for
life cycle studies of transportation fuels and their use in vehicles) pathways for the production of
ethanol from lignocellulosic feedstocks, focusing on quantification of energy and environmental
マWデヴキIゲく Tエキゲ デエWゲキゲげ ラHテWIデキ┗W キゲ キミ-part to reconcile the differences in the literature by employing a
consistent model development strategy and lifecycle framework in order to create and benchmark
various ethanol production schemes employing different co-product strategies. Co-products explored
in this thesis are briefly described as follows:
Electricity: Electricity cogeneration is common in cellulosic biomass-to-ethanol strategies. Combustion
of non-ethanol producing components of lignocellulosic biomass is a method of mitigating plant energy
costs and generating additional revenue [8].
Lignin Pellets: Recently, there has been growing interest in co-firing biomass pellets and coal in power
plants [25]. While this strategy is not a new concept, co-producing fuel pellets from ethanol plant lignin
may offer an opportunity to lessen environmental impacts of coal-based electricity generation [22].
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Xylitol: Xylitol co-production from lignocellulosic xylose is a relatively new concept when paired with
lignocellulosic ethanol production. Xylitol offers an economic advantage alongside the environmental
benefits of lignocellulosic ethanol and has not been investigated in prior literature using life cycle
methodology.
Protein Concentrate: Protein extraction from leaves has been under investigation for several decades
and has established theory that can be applied to ethanol producing concepts [27]. Co-production of
protein offers a potential economic advantage for lignocellulosic ethanol.
Published LCAs on non-energy based co-products such as xylitol and protein concentrate remain sparse
or non-existent while work on lignin pellets has only been investigated in one prior study (within our
research group). A critical goal of this work is to aid in expanding the understanding of several
emerging co-products linked with ethanol production in a life cycle context.
1.1 Research objectives
The overall objective of this research is to evaluate and compare the life cycle energetic and
environmental performance of a set of lignocellulosic ethanol pathways that produce one or more co-
products, as well as the performance of a reference reformulated gasoline pathway. Sub-objectives of
the thesis are as follows:
1. Evaluate the fuel/vehicle pathways in terms of energy (total, fossil, petroleum) and (selected
greenhouse gas and air pollutant emissions, water use, liquid and solid waste) metrics.
2. Identify tradeoffs and quantify the effects of producing co-products on their respective overall
processes, as well as compare them against each other.
3. Discuss, examine and benchmark the ethanol conversion processes modelled against those in
literature and industry.
4. Make recommendations for future cellulosic ethanol policy with regards to selection of co-
product strategies as well as selection of technology and feedstock combinations.
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1.2 Thesis Outline
This thesis evaluates lignocellulosic ethanol in a technological, energy and environmental context. The
structure of this thesis begins with a literature review, followed by methodology, results and discussion,
and conclusions. Chapter 2 focuses on literature and prior work related to the scope of this thesis.
Chapter 3 describes the methodology used to model the pathways within the thesis. Chapter 4
presents and discusses the results of modelling these pathways. Lastly, Chapter 5 summarizes
conclusions, speculates on implications and discusses future work.
1.3 Related publications and presentations to this thesis
The following is a list of prior presentations and publications related to portions of this thesis in the
past:
Shen, T., Saville, Bくが M;IノW;ミが Hく Lくが さLキaW C┞IノW AゲゲWゲゲマWミデ ラa LキェミラIWノノ┌ノラゲキI Eデエ;ミラノ ;ミS Cラ-Product
“┞ゲデWマゲ ふゲヮW;ニWヴぶざが ヱst Annual BEEM Research Meeting, Toronto, Ontario, Nov 18-19th, 2010.
“エWミが Tくが “;┗キノノWが Bくが M;IノW;ミが Hく Lくが さEnergetic and Environmental Impacts of Co-Products on
Lignocellulosic Ethanol (poster)ざ 2nd Annual BEEM Research Meeting, Toronto, Ontario, Oct 5th, 2011.
Shen, T., Saville, B., Macleanが Hく Lくが さLキaW C┞IノW Aミ;ノ┞ゲキゲ ラa LキェミラIWノノ┌ノラゲキI Eデエ;ミラノ キミ RWェ;ヴSゲ デラ M┌ノデキヮノW
Co-PヴラS┌Iデ “┞ゲデWマゲざが ふキミ ヮヴWヮ;ヴation), 2012.
My co-supervisors Bradley Saville and Heather L. Maclean are the co-authors for all my prior oral
presentations and posters, and any forthcoming publications based on the data from this work. They
are additionally the reviewers of this thesis.
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2. Literature Review
This chapter reviews information related to the field of lignocellulosic ethanol and published life cycle
studies. The first section discusses life cycle assessment (LCA) methodology. The second section
examines cellulosic ethanol technology and associated co-products. The third identifies prior life cycle
studies done on lignocellulosic feedstocks, ethanol conversion technologies and co-products relevant to
this thesis.
2.1 Life Cycle Assessment
Life cycle assessment is a technique for assessing the potential environmental impacts associated with
a product, process or service. Historically LCA has been applied to biofuels as an input into the
decision-making process, directing research, government policy and industry efforts. The majority of
LCAs of biofuels have been performed using process-based LCA (eg. [18,19,20,21]). Material and
WミWヴェ┞ H;ノ;ミIWゲ ;ヴW ゲ┞ゲデWマ;デキI;ノノ┞ H┌キノデ ;ヴラ┌ミS W;Iエ ゲデ;ェW キミ ; Hキラa┌Wノげゲ ヮヴラS┌Iデキラミ ;ミS WミS-use in
order to determine the inputs and outputs [14]. In terms of this thesis, a process-based LCA approach
has been utilized. As defined in ISO 14040 [28] and illustrated in Figure 2.1, life cycle assessment
generally consists of four main phases: (i) Goal scope and definition, (ii) life cycle inventory (LCI)
analysis, (iii) life cycle impact assessment (LCIA) and (iv) interpretation.
8
Figure 2.1 International Organization for Standardization Life Cycle Assessment Framework [29]
LCA is an iterative process and previous phases are revised based on the findings of the interpretation.
In phase (i), the purpose and boundaries of an LCA are determined, and a functional unit identified.
The functional unit must be defined in order to normalize life cycle results against a main product-
related metric. The scope generally encompasses all stages of the product or service in question from
キデゲ さIヴ;SノWざ デラ さェヴ;┗Wざく WエキノW キデ マ;┞ HW SWゲキヴ;HノW デラ エ;┗e as large a scope as possible (such as
encompassing the extraction of materials for agricultural equipment), the scope is more often limited
by the availability of reliable data and/or the impact of some processes being too minor to include.
Proper scope definition involves defining the boundaries of the LCA spatially and temporally. For
lignocellulosic ethanol LCAs, functional units vary from MJ of ethanol produced during the ethanol life
cycle to kilometers driven by an ethanol-fueled vehicle. Phase (ii), the LCI, involves systematically
modelling and determining the inputs and outputs associated with each of the life cycle stages from a
ヮヴラS┌Iデ ラヴ ゲWヴ┗キIWげゲ IヴW;デキラミ デラ WミS-use. A generalized diagram of life cycle stages within an LCI is
shown in Figure 2.2. In the context of cellulosic ethanol, the inputs would involve activities such as
9
fertilizer, diesel and gasoline use during the feedstock production stage as well as addition of required
chemicals during the ethanol conversion plant (biorefinery) stage. Examples of outputs would include
emissions of greenhouse gases from all the stages. LCIs of ethanol have primarily focused on
greenhouse gas (GHG) and air pollutant emissions as well as fossil and petroleum energy use [29].
Phase (iii), the LCIA, assesses the impacts (e.g., global warming potential, acidification potential, ozone
depletion) resulting from the LCI (ii). The final stage in traditional LCA provides recommendations and
conclusions based on the results of the LCI and/or LCIA. Depending on the conclusions reached,
previous stages may be re-worked or re-evaluated.
Tools for LCA have been developed and used in the past. Since LCAs require data extending back to
primary fuel production (such as natural gas and coal), LCA modelling software containing data from a
wide range of industries has been developed to aid researchers. Among publicly available LCA tools are
software such as the Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation Model
(GREET) by Argonne National Laboratory [30] and GHGenius by Natural Resources Canada [31].
Commercial life cycle modeling tools such as GaBi [32] and SimaPro [33] also exist. These tools typically
maintain inventories of energy and emissions data related to primary and alternative fuel sources,
material and product manufacturing processes, agricultural processes, etc. Although the sources of
data and tools involved vary widely, LCA is useful in informing the development of new technologies. In
addition to LCA tools, some studies in literature (eg. [19,20,34]) involving chemical plants have also
used simulation software such as Aspen Plus [35] to build models of various plant operations (as these
plants often employ new technology not in practical use). Inputs and output material and energy flows
predicted by the plant models are then included as information for the chemical plant life cycle stage in
the overall study.
Figure 2.3 shows the basic stages involved in an ethanol life cycle. The life cycle begins with biomass
production (agriculture crop production, forest residue collection, etc.), follows to ethanol production,
ethanol blending (with gasoline) and distribution at a refuelling station, and finally, the combustion of
the fuel in a light-duty vehicle. Transportation of products between the stages is also included within
the life cycle. Significant focus in the thesis is placed on the modelling of the lignocellulosic ethanol
production stage and its associated LCI aspects.
10
Figure 2.2 Generalized Life Cycle Inventory
Often in lignocellulosic ethanol LCA, the ethanol production stage of the life cycle is modelled as a
さHノ;Iニ Hラ┝ざが キミ ┘エキIエ キミヮ┌デゲ ;ミS ラ┌デヮ┌デゲ ;ヴW ヮヴキマ;ヴキノ┞ H;ゲWS ラミ H;ゲキI WミWヴェ┞ ;ミS Wマキゲゲキラミゲ a;Iデラヴゲく Iミ
this thesis, the ethanol production stage is modelled in detail to better predict the effects of process
changes in ethanol production on the overall life cycle.
Figure 2.3 illustrates the generalized life cycle of lignocellulosic ethanol. Lignocellulosic ethanol life
cycles can be broken down into smaller categories typically derived from terminology used in
ヮWデヴラノW┌マ ノキaW I┞IノW ゲデ┌SキWゲく TエWゲW ゲデ;ェWゲ ;ヴW さ┘Wノノ-to-ェ;デWざ ふWTGぶが さ┘Wノノ-to-デ;ミニざ ふWTTぶ ;ミS さデ;ミニ-to-
┘エWWノざ ふTTWぶく WTG WミIラマヮ;ゲゲWゲ Hキラマ;ゲゲ ヮヴラS┌Iデキラミ ふラヴ IラノノWIデキラミぶ ;ミS デエW デヴ;ミゲヮラヴデ ラa デエ;デ Hキラマ;ゲゲ
to the ethanol plant gate. WTT covers biomass production through to the actual delivery of the
ヴWゲ┌ノデキミェ Wデエ;ミラノ a┌Wノ ヮヴラS┌IWS デラ ; ┗WエキIノWげゲ fuel tank. TTW indicates the combustion of the ethanol
fuel in the vehicle itself (energy from the fuel tank to the vehicle wheel). All the cellulosic ethanol
ゲデ;ェWゲ デラェWデエWヴ ;ヴW ヴWaWヴヴWS デラ IラノノWIデキ┗Wノ┞ ;ゲ さ┘Wノノ-to-┘エWWノざ ふWTWぶく These terms are used to refer to
groups of ethanol life cycle stages throughout this thesis.
Figure 2.3 Generalized Lignocellulosic Ethanol Life Cycle
11
Figure 2.4 illustrates some of the inputs and outputs relevant to the biomass production and ethanol
production life cycle stages. Biomass production generally involves either the collection of
lignocellulosic residues or cultivation of a biomass source. The thesis focuses on agricultural
feedstocks. Agricultural crop production uses fuels such as diesel to power agricultural machinery
(tractors, tillers, harvesters, etc.) as well to produce chemicals such as fertilizers, herbicides and
pesticides. Outputs from the agricultural stage include N2O emissions from fertilizer use, and CO2
emissions from diesel combustion. Non-gaseous emissions such as pesticide and herbicide leaching
into local water sources and organic waste are also possible. Energy inputs to the stage are generally
calculated based on the amounts of diesel, gasoline, and/or electricity required to operate agricultural
machinery and trucks for transportation as well as energy inputs required to produce agricultural
chemicals. N2O emissions associated with agricultural production are generally found to be
considerable contributors to the life cycles of many crops [36]. Inputs associated with ethanol
production generally include chemicals to hydrolyze lignocellulose (e.g., acids and enzymes) in addition
to required process electricity and heating, which vary depending on the design and technology being
used. Outputs can involve a wide range of air emissions as well as treated water discharge to sewer
systems and solid waste delivery to landfills. Transportation between the biomass production stage
and the ethanol production stage also has inputs and outputs that can be quantified. Determining the
magnitudes of these inputs and outputs is necessary to create a LCI for lignocellulosic ethanol.
Figure 2.4 Well-to-Gate Life Cycle Inventory for Cellulosic Ethanol
12
2.1.1 Co-Product Allocation
In addition to ethanol, the ethanol production life cycle stage in Figure 2.3 may produce one or more
co-products. Co-products present a challenge in LCA because it is difficult to determine exactly what
share of inputs and outputs are associated with the production of the co-products. Thus, several
methods of dealing with co-products are documented in ISO 14040 [15]. The standard recommends the
methods of system subdivision or system expansion [28]. According to ISO 14041 [14], allocation
should be avoided, where possible, by dividing the unit process to be allocated into two or more
subprocesses (system subdivision) or expanding the product system to include the additional functions
related to co-products (system expansion).
When applied to ethanol, the subdivision method involves subdividing the ethanol production stage
into smaller stages for the primary product (ethanol) and co-product, respectively. This method is not
often used due to the difficulty in acquiring data for the individual sub-divisions between the primary
product and co-ヮヴラS┌Iデく TエW ゲ┞ゲデWマ W┝ヮ;ミゲキラミ マWデエラS ラヴ さSキゲヮノ;IWマWミデざ マWデエラS キミ┗ラノ┗Wゲ ;デデヴキH┌デキミェ
the impacts from the ethanol production stage entirely to the ethanol product, rather than to any of
the co-products. Impacts from the co-product(s) are then determined and attributed as a credit to the
life cycle impact of ethanol. The credit the co-product provides is determined by assuming the co-
product displaces an established product already in the market. The impacts of the displaced product
are treated as a credit to the ethanol life cycle because it is assumed to be replaced (based on a
displacement ratio) by the co-product. In the case of system expansion, results have the potential to be
さdistorteSざ when the amount of co-products on an energy basis is larger than the primary product or
when there is not an actual market for the product or a market large enough to accommodate the
quantity of the co-product. Nonetheless, the system expansion method has been selected by the US
Environmental Protection Agency [37] as their co-product method of choice. If an allocation method is
utilized (rather than system subdivision or expansion), methods documented in ISO 14040 [15] include;
energy, mass and market value bases (see [15] for further details on allocation methods).
Huo et al. [38] investigated displacement (system expansion), energy, market value and hybrid
displacement-energy and displacement-market value methods for a variety of biofuel based systems.
They observed that energy and market value allocation methods generally produced less optimistic
results compared to methods using displacement allocation and advocated a hybrid approach (with an
appropriate allocation method applied to each co-product).
13
2.2 Lignocellulosic Structure and Components
Lignocellulosic biomass is comprised of three main components: cellulose, hemicellulose, and lignin.
Cellulose is a linear long chain polysaccharide made up of D-glucose units linked by ß-glycosidic linkages
(Figure 2.5). It is a structural component of plant cell walls and typically makes up the majority of
lignocellulosic matter. Hemicellulose is a highly branched, long chain polymer made of xylan, arabinan,
galactan, and mannan polysaccharides along with acetate units in its sidechains (Figure 2.6). In contrast
to cellulose, hemicellulose polysaccharides can be decomposed into both pentose sugars (xylose and
arabinose), and hexose sugars (galactose and mannose) [8]. Hemicellulose is present alongside
cellulose in plant cell wall material.
Figure 2.5 Chemical Structure of Cellulose
Figure 2.6 Chemical Structure of Hemicellulose
14
Lignin is a complex cross-linked aromatic polymer made up of a wide range of complex compounds and
generally serves as a binder in plant structures (Figure 2.7). It has no precise structure and has a
composition that varies depending on plant species. There is considerable potential to extract groups
of chemicals such as phenols from lignin; however, it is often used as a fuel source because it
commonly possesses highly recalcitrant linkages between compounds that are difficult to fractionate
[39]. Lignin can exist in amorphous and crystalline forms and differences in lignin composition can
cause major differences in pretreatment effectiveness. For crop residues, herbaceous plants, and
hardwoods, lignin is made of guaiacyl and syringyl units, while in softwoods it is made mainly of
guaiacyl units. This difference has traditionally made it difficult to process softwoods compared to
other types of feedstock and has led to conversion methods such as organosolv being preferential for
softwood processing [40].
Figure 2.7 Portion of the Chemical Structure of Lignin [41]
15
As seen in Table 2.1, the specific composition and structure of lignocellulose varies widely, but within
agricultural residues (corn stover, wheat straw, etc.) and herbaceous crops (switchgrass, Miscanthus,
etc.) the three components of lignocellulose tend to be found in similar proportions. Cellulose and
lignin are typically larger fractions in woody materials compared to other sources of lignocellulose [39].
Crop residues, herbaceous crops and hardwoods all have larger fractions of cellulose and xylan
compared to other sugar yielding components. As such, these components have become the focus for
conversion to ethanol. In contrast, softwoods contain a larger fraction of mannan than xylan, and thus
many softwood-to-ethanol processes have become distinct in trying to convert mannan rather than
xylan [40].
Table 2.1 Composition of Common Lignocellulosic Materials [42]
Lignocellulosic Material Cellulose (%) Hemicellulose (%) Lignin (%)
Hardwood stems 40-55 24-40 18-25
Softwood stems 45-50 25-35 25-35
Wheat straw 30 50 15
Rice straw 32.1 24 18
Primary wastewater solids 8-15 NA 24-29
Fresh bagasse 33.4 30 18.9
Solid cattle manure 1.6-4.7 1.4-3.3 2.7-5.7
Coastal Bermuda grass 25 35.7 6.4
Switch grass 45 31.4 12.0
Grasses (average values for grasses) 25-40 25-50 10-30
2.3 Lignocellulose to Ethanol Conversion Technology
Lignocellulose conversion to anhydrous ethanol is typically done in four stages: pretreatment,
hydrolysis, fermentation and ethanol recovery (Figure 2.8). The pretreatment stage is mainly used to
disrupt the structure of lignocellulose in order to make it vulnerable to hydrolysis by enzymes or other
hydrolyzing agents. In addition, pretreatments may also be able to partially separate the lignin from
the rest of the lignocellulose and partially hydrolyze the hemicellulose to oligomers or monomers.
Cellulose normally remains unhydrolyzed during pretreatment.
16
Figure 2.8 Block Diagram of a Typical Lignocellulose-to-Ethanol Conversion Scheme
Once pretreated, the lignocellulosic material then moves to a hydrolysis step where it is subjected to a
catalyst to convert polysaccharides to sugar monomers. Historically, dilute or concentrated acids have
been used as catalysts, but the recent focus has turned to mixtures of enzymes as the catalyst, due to
better environmental performance, reduced corrosion, and their effectiveness and specificity in
hydrolyzing cellulose as well as hemicellulose. Modern production techniques have greatly lowered the
cost of enzymes and decreased the hydrolysis time. However, enzymatic hydrolysis still remains
ineffective on un-pretreated lignocellulosic residues, as the cellulose is well protected within a matrix of
lignin and hemicellulose [40]. Following hydrolysis is a fermentation step where the resulting
monomeric sugars are converted to ethanol by an ethanol fermenting organism. The resulting ethanol
aWヴマWミデ;デキラミ さHヴラデエざ キゲ デエWミ デ┞ヮキI;ノノ┞ SキゲデキノノWS in a two step process, and the remaining water is
removed using molecular sieve technology. Residual solids に primarily lignin, unconverted sugars,
oligomers and polysaccharide components are normally sent to a combustor to generate renewable
heat and power for the eth;ミラノ a;Iキノキデ┞く B┞ ┌ゲキミェ デエWゲW さ┘;ゲデWざ ヮヴラS┌Iデゲ ;ゲ a┌Wノが lignocellulosic ethanol
plants are often able to satisfy all of the thermal energy demands of the process, while becoming net
electricity producers.
2.3.1 Pretreatment Technology
The main aim of pretreatment is to alter the structure of lignocellulose, improving accessibility and
reactivity of the cellulose, while partially separating it from lignin and hemicellulose. As illustrated in
Figure 2.9, by weakening the bonds between cellulose, lignin and hemicellulose, as well as removing
(some of) the latter two components, cellulose can be preferentially exposed to enzymatic attack,
resulting in improved hydrolysis yields. An effective pretreatment also minimizes the generation of
17
inhibitors that affect the hydrolytic enzymes or ethanol producing organisms during fermentation, and
avoids degradation of hemicellulose-derived sugars. Other important factors during pretreatment are
energy use, water use, chemical use, the cost of feedstock size reduction, and recovery of residues [43].
Each of these factors can influence process yields, chemical demand and energy demand, all of which
may impact LCA outcomes.
Figure 2.9 Effect of Pretreatment on Lignocellulose
A large number of pretreatment technologies have been developed for lignocellulosic ethanol. These
include hot water pretreatment, dilute acid hydrolysis, organosolv, steam explosion and ammonia fibre
expansion, lime pretreatment and ammonia percolation among others. Of the pretreatments listed,
dilute acid hydrolysis, steam explosion, and ammonia fibre expansion are among the most promising
pretreatments in active development for lignocellulosic ethanol. Steam explosion is one of the most
highly investigated pretreatment process in literature, and as of 2011, Mascoma Inc. has assembled
plants at pilot scale in Canada and the US [40,44]. Likewise, sulfuric acid hydrolysis has received
considerable attention and has been the most extensively studied in terms of acid hydrolysis
pretreatments [18,19]. In 2004, the first lignocellulosic ethanol demonstration plant was opened by
Iogen Corp. and utilized batch steam explosion combined with dilute sulfuric acid hydrolysis as a means
of pretreatment [45]く さOヮデキマ;ノざ ヮヴWデヴW;デマWミデ IラミSキデキラミゲ aラヴ Iラヴミ ゲデラ┗Wヴが ゲ┘キデIエェヴ;ゲゲ ;ミS エ┞HヴキS
poplar feedstocks were published as part of the Biomass Refining Consortium for Applied Fundamentals
and Innovation project (CAFI) in 2005 [46], 2011 [47]and 2009 [48] respectively, and serve as the basis
for pretreatment conditions used in this thesis.
18
During pretreatment, most or all of the hemicellulose is hydrolysed to monomers and oligomers. Most
pretreatments such as dilute acid hydrolysis also hydrolyze a minor portion of cellulose (glucan) to
monomers and oligomers, depending upon severity, although cellulose normally remains resistant to
hydrolysis. Chemical formulae for major reactions that occur during the majority of pretreatment
processes are listed below:
(Glucan)n + n H2O n Glucose (C6H12O6) Equation 2.1
(Glucan)n + n H2O n Glucose Oligomer (C6H12O6)m Equation 2.2
(Mannan)n + n H2O n Mannose (C6H12O6) Equation 2.3
(Mannan)n + n H2O n Mannose Oligomer (C6H12O6)m Equation 2.4
(Galactose)n + n H2O n Galactose (C6H12O6) Equation 2.5
(Galactose)n + n H2O n Galactose Oligomer (C6H12O6)m Equation 2.6
(Xylan)n + n H2O n Xylose (C5H10O5) Equation 2.7
(Xylan)n + n H2O n Xylose Oligomer (C5H10O5)m Equation 2.8
(Arabanose)n + n H2O n Arabinose (C5H10O5) Equation 2.9
(Arabinose)n + n H2O n Arabinose Oligomer (C5H10O5)m Equation 2.10
Acetate Acetic Acid (C2H4O2) Equation 2.11
(Lignin)n n Soluble Lignin Equation 2.12
Some pretreatment processes are able to solubilize a significant portion of lignin as well, thus
separating it from the lignocellulosic structure and improving downstream enzymatic hydrolysis of
cellulose. Acetate present in hemicellulose side chains is hydrolyzed to acetic acid in most
pretreatments. The formation of acetic acid reduces the pH of the pretreatment mixture and further
aids in the hydrolysis of hemicellulose.
Other components within the lignocellulosic matrix mainly consist of extractives and inorganic
components (ash). Extractives consist of water soluble or lipophilic compounds that are extractible
using standard methods. These compounds include acetone, free fatty acids, resin acids, ethyl ether,
19
ethyl acetates, polyphenols, and higher alcohols among others[49]. The extractives portion listed in
lignocellulosic biomass proximate analyses found in literature may vary based on the extraction solvent
used, but generally pertain to a combination of water-extracted and ethanol-extracted residues as
stated by the National Renewable Energy Laboratory[50].
2.3.1.1 Dilute Acid Hydrolysis
Among pretreatment options, dilute acid is likely the most commonly studied method. Among acids,
use of sulfuric acid is the most widely used, although hydrolysis using other types of acids such as nitric,
hydrochloric or phosphoric is also used [43]. Acid hydrolysis involves subjecting lignocellulosic biomass
to an acid which partially or completely hydrolyzes the bonds within and between the polymeric
components within biomass. It can generally be conducted under two sets of conditions: High acid
concentration and low temperature conditions or low acid concentration and high temperature
conditions. Research on low concentration (dilute, 0.2-2%) acid conditions has become more popular
due to the toxicity and corrosivity of high acid concentrations, leading to increased rates of sugar
degradation and difficulty in detoxifying the pretreated material prior to subsequent fermentation, and
increased cost for corrosion-resistant materials. Typical temperatures used for this pretreatment are
between 121-ヲヲヰΔC [51]. Dilute acid hydrolysis pretreatment remains an attractive method due to its
ability to hydrolyze pretreated lignocellulose, which reduces downstream enzyme costs. Dilute acid
hydrolysis is able to partially or completely hydrolyze the hemicellulose fraction in biomass feedstocks
to monomers (80-100% conversion). However, depending on the severity of the acid pretreatment,
sugar degradation to fermentation inhibitors such as furfural and hydromethoxyfurfural (HMF) may
occur, via the following reactions [52].
(Glucan)n n HMF + 2n H2O Equation 2.13
(Xylan)n n Furfural + 2n H2O Equation 2.14
Due to the formation of degradation products and the addition of acid, solid residues from dilute acid
pretreatment generally require a washing and detoxification step prior to enzymatic hydrolysis and
fermentation. The detoxification step often involves overliming, in which the acid is neutralized at
~50oC by lime, raising the pH of the pre-treated slurry to 10. The resulting gypsum is recovered, and the
20
pH of the slurry is then subsequently re-adjusted to ~5.0, suitable for hydrolysis or fermentation.
Overliming has been shown to substantially reduce the concentration of HMF and furans, and improve
fermentation yields [53], but increases process capital and operating costs, water demand and energy
demand.
2.3.1.2 Ammonia Fibre Expansion (AFEX)
Ammonia fibre expansion (AFEX) is a developing technology that has been reported to be effective at
disrupting the structure of lignocellulosic feedstocks while causing minimal degradation to sugars and
protein within the feedstock (unlike a dilute acid process) [23]. The AFEX pretreatment subjects the
feedstock to liquid ammonia at high pressure followed by an explosive decompression when the
pressure is released [52]. After exiting the reactor, the gaseous ammonia is recovered in a column
using superheated steam, condensed and recycled to the pretreatment step. Recycling ammonia in the
liquid phase is integral to keeping the process economically viable due to ammonia demand typically
being in the range of 1-2 kg NH3 デラ ニェ Sヴ┞ Hキラマ;ゲゲく Cラママラミ IラミSキデキラミゲ キミ┗ラノ┗W デWマヮWヴ;デ┌ヴWゲ ラa ΓヰΔC
or higher and moisture contents of 80% (w/w dry biomass) or more [51]. In contrast to other
pretreatments, AFEX pretreatment does not normally hydrolyze a significant amount of the
hemicellulose, although the reactivity of cellulose can still be significantly enhanced. Some of the
hemicellulose fraction may be solubilised, mainly in oligomeric form. As such, AFEX is dependent on
subsequent enzymatic hydrolysis to coverts oligomers into monomers for fermentation. AFEX is been
ニミラ┘ミ ;ゲ ; さSヴ┞-to-Sヴ┞ざ ヮヴラIWゲゲ キミ デエ;デ ; ゲラノキS aWWSゲデラIニ ふデ┞ヮキI;ノノ┞ бヴヰХ solids) feedstock enters and
leaves the pretreatment reactor [48]. Another advantage of AFEX is that the residual ammonia within
pretreated residues can act as a nitrogen source during fermentation [54]. Unlike dilute acid hydrolysis,
AFEX pretreated residues generally do not require a washing or detoxification step prior to
fermentation. This is mainly due to the lower operating temperature during AFEX pretreatment,
coupled with the absence of acid, which otherwise acts as a catalyst to enhance the degradation of
sugars into furfural and HMF (equations 2.13 and 2.14 above).
21
2.3.1.3 Autohydrolysis
TエW デWヴマ さ;┌デラエ┞Sヴラノ┞ゲキゲざ ヴWaWヴゲ デラ デエW a;Iデ デエ;デ デエW エ┞Sヴolysis during pretreatment is catalyzed by
acids already in the feedstock (such as acetic acid) [55]. Autohydrolysis (steam explosion) pretreatment
has proven effective on a variety of hardwoods and agricultural residues such as corn stover [56].
Success in treating softwoods by autohydrolysis was also found in a study by Wayman et al. [57],
although even better conversions were obtained when SO2 was used to catalyze the pretreatment.
Although autohydrolysis is able to significantly depolymerize cellulose and solubilize 80-100% of
hemicellulose, it is often paired with acid catalysis (or SO2) in order to enhance hydrolysis [58]. In its
さヮ┌ヴWざ aラヴマが ;┌デラエ┞Sヴラノ┞ゲキゲ ヮヴWデヴW;デマWミデ ラミノ┞ ヴWケ┌キヴWゲ エキェエ ヮヴWssure superheated steam, followed by
a rapid depressurization causing an explosive expansion of the fiber [43]. Depending upon the
pretreatment conditions, autohydrolysis can hydrolyze a considerable portion of the hemicellulose to
monomers, although very little cellulose is solubilised. The process avoids the use of additional
chemicals and the resulting subsequent detoxification step, unlike the dilute acid pretreatment process.
Conditions for performing autohydrolysis typically involve temperatures between 160-ヲヶヰΔC ;ミS
pressures of 0.69 to 4.83 MPa [51]. It was reported by Lloyd et al. [58] that hemicellulose to monomer
yields during autohydrolysis were marginally lower than those found when employing acid for
pretreatment of corn stover. Cleavage of bonds between lignin and other components (cellulose and
hemicellulose) is significant, improving cellulose accessibility and reactivity. Mascoma Canada Inc. has
developed a proprietary continuous autohydrolysis process, which is used as the basis for
autohydrolysis pretreatment used in this work.
2.3.2 Enzymatic Hydrolysis Technology
Enzymatic hydrolysis has become a common method for hydrolysis of cellulose and hemicellulose,
supplanting acid hydrolysis processes used in the early to mid 20th century. Enzymatic hydrolysis has a
high specificity for celluloses and other polysaccharides, with no formation of degradation products,
taking place at mild conditions (pH 4.8 に 5.2, 45-ヵヰΔCぶ ┘エキノW ;┗ラキSキミェ Iラヴヴラゲキラミ ヮヴラHノWマゲ I;┌ゲWS H┞
acids. Hydrolysis of untreated lignocellulose is generally ineffective, and thus pretreatment is required.
Current enzymatic hydrolysis processes can convert >80% of the available glucan to glucose, with
22
newer enzymes able to achieve 85-95% hydrolysis under high solids [8,51]. However, modern
enzymatic hydrolysis still remains a bottleneck in lignocellulosic ethanol production due the high cost of
enzymes and long hydrolysis times spanning several days. However, efforts to develop enzymes over
the last decade have managed to reduce enzyme costs by 20-30 times [8]. This reduction has allowed
pretreatments that do not completely hydrolyze hemicellulose to become more economically viable, in
spite of higher enzyme loadings. Cellulases have been isolated from a mutant strain of fungi
Trichoderma reesei, which has long been recognized as productive source of cellulases useful for
breaking down cellulose (equation 2.15).
Glucan Cellulase Glucose (C6H12O6) Equation 2.15
Cellulases have been characterized in literature as a group of enzymes that work synergistically to break
down cellulose. Three subgroups of Wミ┣┞マWゲ ふWミSラェノ┌I;ミ;ゲWゲが IWノノラHキラエ┞Sヴラノ;ゲWゲ ;ミS é-glucosidases)
are used to hydrolyze cellulose, as illustrated in Figure 2.10 [51].
Figure 2.10 Mechanism for Enzymatic Hydrolysis of Cellulose by Cellulase
CWノノ┌ノ;ゲW さIラIニデ;キノゲざ エ;┗W ;ノゲラ HWWミ ラHゲWヴ┗WS デラ エ;┗W ゲラマW ┝┞ノ;ミ エ┞Sヴラノ┞ゲキゲ ;Iデキ┗キデ┞が ;ノデエラ┌ェh often
cellulase is supplemented with xylanase, which has higher specificity for xylan polysaccharides (Figure
2.11). Since xylan is the second most abundant polysaccharide in common lignocellulosic feedstocks
aside from softwoods, increased hydrolysis of xylan has become necessary to achieve sufficient ethanol
yields. Commercial enzyme formulations tend to have different levels of key enzyme components,
leading to different hydrolysis rates and conversions of key components in pretreated feedstocks.
23
Figure 2.11 Xylanase Specificity
2.3.3 Ethanol Fermentation
Historically, ethanol fermentation using yeast (Saccharomyces cerevisiae) has been able to convert
>90% of glucose into ethanol. Common ethanologens able to ferment glucose to ethanol include
Saccharomyces cerevisiae, Escherichia coli, and Zymomonas mobilis. While glucose fermentation is
already well developed in the beer, wine, and sugar/starch-ethanol industries, hydrolysis of
lignocellulosic materials usually produce a mixture of both five and six carbon sugars; fermenting these
さミラミ-ェノ┌IラゲWざ ゲ┌ェ;ヴゲ ヮヴWゲWミデゲ ; IラミゲキSWヴ;HノW Iエ;ノノWミェWく O┗Wヴ;ノノ ヴW;ctions for five and six carbon sugars
are as follows:
C6H12O6 nEthanologe2C2OH6 + 2CO2 Equation 2.16
3C5H10O5 nEthanologe 5C2OH6 + 5CO2 Equation 2.17
Fermentation of pentose sugars to ethanol has required genetic modification of existing strains. All
three of the previously mentioned strains have been genetically engineered to ferment pentoses (in
particular xylose) at varying rates. Among promising strains are Saccharomyces cerevisiae 424A(LNH-
ST), Escherichia coli KO11 and Zymomonas mobilis AX101. A 2010 study by Lau et al. [54] reported that
all strains were able to ferment glucose and xylose simultaneously at a metabolic ethanol yield of 82-
88% in 48 hours. Strain AX101 was the most effective at fermenting both sugars. Metabolic yield when
fermenting glucose alone was 85.0-93.2% and for xylose alone was 84.9-89.8%. AX101 and 424A(LNH-
ST) achieved the highest yields when solely fermenting glucose and xylose respectively.
24
Large scale fermentation is usually performed by separate seed and production fermentation batch
trains, where several trains are operated in parallel, for continual operation. Different strategies of
approaching enzymatic hydrolysis and fermentation have been developed and are illustrated in Figure
2.12.
Figure 2.12 Different Enzymatic Hydrolysis and Fermentation Strategies
Traditional methods separate the enzymatic hydrolysis and fermentation processes into different unit
operations in an overall technique known as Separate Hydrolysis and Fermentation (SHF). The
advantage of SHF is that both enzymatic hydrolysis and fermentation can be run at optimal conditions;
however a disadvantage is that enzymes during hydrolysis are inhibited by the production of monomers
[51], which would otherwise be removed during fermentation. In contrast to SHF, enzymatic
hydrolysis and ethanol fermentation can be combined to create a strategy known as Simultaneous
Saccharification and Fermentation (SSF), where, fermentation of sugar monomers to ethanol alleviates
enzyme inhibition and provides a driving force for enzymes to hydrolyze polysaccharides. With recent
successes in genetic engineering, SSF can be modified to Simultaneous Saccharification and Co-
Fermentation (SSCF), in which SSF is performed with both hexose and pentose fermentation. A third
strategy still in experimental development is Consolidated Bioprocessing (CBP), in which an organism is
engineered to produce the enzymes needed to hydrolyze the pretreated material and to ferment the
resulting sugar monomers to ethanol [8]. Although CBP is still in development, it has been employed in
さa┌デ┌ヴWざ ゲIWミ;ヴキラゲ キミ ゲラマW ゲデ┌SキWゲ [23].
ETHANOL BROTH
Consolidated Bioprocessing
FermentationEnzymatic
Hydrolysis
Simultaneous Saccharification &
Fermentation
PRETREATED
BIOMASS
PRETREATED
BIOMASS
ENZYMES
Separate Hydrolysis and Fermentation
25
2.3.4 Ethanol Recovery
Ethanol recovery from fermentation broth is a well documented process that has been previously
employed in the alcohol and sugar/starch ethanol industries. Ethanol recovery generally involves a two
column distillation, in which the first column isolates an ethanol-water mixture from fermentation
ゲラノキSゲが ┘エキノW デエW ゲWIラミS ふ; さヴWIデキaキI;デキラミざ Iラノ┌マミぶ Sキゲデキノノゲ Wデエ;ミラノ aヴラマ ┘;デWヴく Eデエ;ミラノ エ;ゲ ; ┘Wノノ ニミラ┘ミ
positive azeotrope with water at 95.63 wt% ethanol and 4.37 wt% water, and cannot be distilled
further usually conventional distillation. In lignocellulosic ethanol production, the ethanol water
mixture is normally distilled to approximately 92.5 wt% ethanol and then purified to 99.9 wt% ethanol
using molecular sieve technology [8]. Distillation is commonly the largest and most energy intensive
unit operation in the entire ethanol plant, and thus the rectification column reflux condenser is often
integrated with another unit operation that requires heating. In a 2002 process model by the National
Renewable Energy Laboratory [34], the rectification condenser is integrated with a multiple effect
evaporator system elsewhere in the plant. A more recent distillation strategy by Lohrasbi et al. [59]
employed a three column configuration, in which the ethanol broth was split into two streams
proceeding to two ethanol strippers run at different vacuum pressures. The stripped ethanol was
combined from the two columns and distilled in a third conventional rectification column as normal.
The three column configuration allowed for integration of the rectification condenser with one of the
lower pressure ethanol strippers, and subsequent integration of the condenser of that steam stripper
with the remaining stripper. Ethanol leaving rectification is denatured (often with gasoline) by
approximately 2 to 5% of its volume to meet regional ethanol fuel specifications and optionally blended
with gasoline to various levels (based on percent volume) depending on ethanol fuel blending targets.
Flexible-fuel vehicles are generally able to use a fuel blend of up to 85vol% ethanol 15vol% gasoline
(E85 fuel). Actual ethanol content in ethanol fuel blends may contain less than 85vol% ethanol due to
the addition of the denaturant, or to meet seasonal fuel specifications.
2.4 Ethanol Co-Products
Due to the numerous organic compounds present within lignocellulosic biomass, production of a wide
range of co-products is possible. Historically, electricity generation was the most common ethanol co-
product due to its simplicity to generate, and readily available technology solutions [8].
26
The majority of organic chemicals worldwide (>75%) are produced from five chemicals: Ethylene,
propylene, benzene, toluene and xylene. All of these chemicals are derived from petroleum as their
main production source. Thus, co-producing value-added chemicals in addition to ethanol could
potentially eliminate a portion of the petroleum dependence of organic chemical producers [42].
Worldwide demand for several organic chemicals able to be derived from lignocellulosic substrates is
listed in Table 2.2. Although data are from year 1987, it is likely that demand for these products has
grown in the last 30 years (especially ethanol) in light of recent efforts to reduce petroleum use in
major countries.
Table 2.2 World Demand (1987) for Various Products Derivable from Lignocellulose Fermentation [42]
Products World Demand (10³ Tonnes)
Ethanol 16 000
Acetone 1659
Butanol 1400
Glycerol 414
Acetic acid 2539
Citric acid 300
Fumaric acid 60
2.4.1 Electricity Generation
Electricity generation from biomass in an ethanol facility is often assumed to occur using a Rankine
cycle combustor turbogenerator combination. The biomass is delivered through a feedstock chute into
a combustion chamber where it is combusted with excess oxygen. the temperature in the combustor is
マ;キミデ;キミWS ;デ бΒヰヰΔC キミ ラヴSWヴ デラ マキミキマキ┣W デエW aラヴマ;デキラミ ラa Sキラ┝キミゲ ;ミS a┌ヴ;ミゲ [34]. Flue gases leaving
the combustor heat a series of heat exchanger tubes, which generate steam that is fed to a condensing
turbine system to generate electricity. Biomass primary energy is converted to electricity at an average
efficiency of approximately 32% [30].
27
2.4.2 Lignin Pellets
Lignin pellets are similar to wood pellets, as lignin makes up the second largest component in wood. In
ethanol production (refer to Figure 2.8) the majority of waste residues sent to the electricity generation
unit consist of lignin. By redirecting waste residues away from the electricity generation unit and
towards a pelletization unit, biomass residues can be pelletized and, for example, shipped offsite for
use in co-firing with coal in coal generating stations. McKechnie et al. [22] reported that this approach
was able to reduce overall GHG emissions from ethanol production, and slightly reduce fossil energy
use. Pelletization technology is readily available and normally consists of a biomass grinding step,
followed by feedstock drying below 10% moisture before entering a pellet press system. In an ethanol
production scheme, energy and capital requirements are reduced as the grinding step is not required
[60].
2.4.3 Protein
Plant-based protein has been reported as a possible partial substitute for animal protein [27]. In an
ethanol production setting, protein can be extracted using an alkaline solution in an extraction column
or vessel before pretreatment [61]. Filtration systems such as ultrafiltration and diafiltration are
normally required to recover soluble extracted protein as well as keep downstream processes sterile (a
requirement if the protein is to be used for human consumption). In order to dry the extracted protein,
a spray dryer with a low protein residence time needs to be employed, in order to minimize possible
protein degradation. Post biomass pretreatment extraction of protein may also be possible depending
on pretreatment severity. Pretreatments using acids and/or elevated temperatures with prolonged
residence times may damage protein. AFEX pretreatment in particular is reported to take place at mild
conditions に low enough to prevent damage to lignocellulosic protein [61]. In addition, AFEX also has a
synergistic effect with protein extraction technology in general due to ammonia use in pretreatment
(allowing for ammonia recycling schemes). Protein has potential as a value-added product similar to
soy protein and soy meal used for animal feed [27,61].
28
2.4.4 Xylitol
Xylitol is an artificial sweetener with a sweetness equivalent to sucrose on a g/g basis. Xylitol can be
produced through biological (fermentation) or synthetic (hydrogenation) methods. Due to the fact that
xylose and other pentose sugars are more difficult to ferment than glucose in ethanol production
settings, production of xylitol from xylose is an attractive option. Xylose can be separated from glucose
via chromatography post enzymatic hydrolysis, and fermented to xylitol using the yeast strain Pichia
stipitis [62]. Separated xylose can also be converted to xylitol using hydrogenation, where xylose and
hydrogen are reacted at elevated temperatures. The general hydrogenation reaction is:
Xylose (C5H10O5 + H2) Ni-AlXylitol (C5H12O5) Equation 2.18
Hydrogenation is currently the preferred method for xylitol production and requires a catalyst such as
aluminium-nickel. Xylitol is a value-added product that has potentially substantial economic value. An
ethanol process currently under development by Mascoma Canada Inc. proposes to co-produce xylitol
[44].
2.5 Review of Well-to-Wheel Analyses of Lignocellulosic Ethanol
Over the last decade, there have been a large number of life cycle studies of lignocellulosic ethanol with
associated co-products. This review focuses on prior lignocellulosic ethanol techno-economic and LCA
studies involving multiple co-products. A secondary focus will be on prior work utilizing similar
feedstock (corn stover, switchgrass, and hybrid poplar) and pretreatment technology (dilute acid
hydrolysis, AFEX, and autohydrolysis) combinations to those in this thesis.
Sheehan et al. [18] and Luo et al. [19] both examined ethanol produced from corn stover using a dilute
acid process with electricity co-production based on a model developed by the National Renewable
Energy Laboratory (NREL). Both studies reported significant reductions (minimum 200%) in life cycle
fossil energy use relative to corn ethanol. Wu et al.[24] and Bai et al. [63] examined switchgrass to
ethanol using an AFEX ethanol conversion pathway with electricity co-production and reported similar
results (65% GHG emissions reductions compared with gasoline per vehicle kilometre driven), despite
utilizing different co-product allocation methods (system expansion vs. economic allocation). Laser et
29
al. [23] and Spatari et al. [20] investigated ethanol production from both corn stover and switchgrass in
combination with both dilute acid and AFEX conversion methods using modified NREL models. Spatari
et al. [20] investigated the model uncertainty of these conversion processes using Monte Carlo analysis,
while Laser et al. [23] investigated multiple AFEX process configurations and some additional co-
products (hydrogen, Fischer-Tropsch liquids, and protein). Both studies reported GHG reductions for
the ethanol vehicles relative to those of gasoline reference vehicles of at least 90%. Spatari et al. also
reported that in general AFEX processes had higher GHG emissions than a similar dilute acid hydrolysis
process due to the potential for higher electricity co-product credits to be generated in the former case.
There are a few other life cycle studies that have examined multiple co-products. Uihlein et al. [64]
examined ethanol from hydrochloric acid-treated wheat straw, with electricity, isolated lignin and
xylitol as potential co-products. The study reported results (under the Eco-Indicator system) in terms of
human health, resource and eco-system quality, which showed positive impacts for ethanol fuel (E85)
pathways compared to a reference gasoline pathway in all categories except carcinogens. Cherubini et
al. [21] studied ethanol production from corn stover and wheat straw (both abundant lignocellulosic
residues in the US) using an autohydrolysis pretreatment, with electricity and lignin-derived phenols as
co-products. The results showed that both corn stover and wheat straw-to-ethanol strategies had 54%
and 49% lower life cycle GHG emissions per kilotonne of fuel input (e.g., corn stover or crude oil),
respectively, than their fossil fuel counterparts (gasoline, petroleum derived phenols, natural gas
sourced electricity). Only aggregated results from a single model were presented, and thus it was not
possible to isolate the individual effects of the multiple co-products involved. Wang et al. [65]
evaluated various co-product allocation methods and co-product scenarios; however the co-products
were associated with the production of several different fuels and not exclusively ethanol. Only one co-
product (electricity) was produced in association with lignocellulosic ethanol. The only ethanol
pathway included involved a switchgrass fed dilute acid conversion process in which only one co-
product (electricity) was produced, resulting in an 89% GHG emissions reduction relative to gasoline.
Wang et al. further studied three co-product allocation methods (displacement/system expansion,
energy allocation, market allocation), which all produced similar results, in contrast with Luo et al. [19]
who studied similar allocation methods but reported GHG reductions differing by over 100% (absolute
basis). Overall however, the displacement/system expansion co-product allocation method was
generally seen as producing the largest reductions in both studies. Zondervan et al. [66] investigated
the optimal configuration of an ethanol plant co-producing acetone, butanol and succinic acid through
mathematical modelling. Among pretreatment options, both dilute acid and AFEX were considered in
30
addition to ammonia recycle pretreatment (ARP), controlled pH pretreatment and lime pretreatment.
The authors found that dilute acid pretreatment resulted in the highest ethanol yields in every case.
However, energy use and GHG emissions were not reported.
31
3. Methods
Life cycle assessment is the primary framework used in this thesis. Life cycle inventories (LCI) of a large
set of lignocellulose-to-ethanol pathways with different conversion technologies and co-production
schemes were developed. Selection of investigated pathways involved combining ethanol conversion
schemes with one or more technologically feasible co-product strategies, while using one of three
selected feedstocks. The ethanol and co-products produced by each pathway are compared with
respect to energy use and emissions relative to selected current industry equivalents. The thesis
focuses on these metrics due to concerns regarding fossil and petroleum energy use, climate change
and air pollutant emissions. Water use and liquid and solid waste emissions from the ethanol
conversion plant stage were also quantified. Detailed modeling of the lignocellulose-to-ethanol
conversion stage is completed within the thesis.
3.1 Well-to-Wheel Model Scope, Development and Data Sources
The boundary of the ethanol pathways includes activities associated with corn stover, switchgrass or
hybrid poplar production and transportation to a biorefinery (well-to-gate), conversion of these
feedstocks to ethanol in a plant facility (gate-to-gate), blending of the ethanol and its distribution to
refuelling stations (gate-to-pump) and finally combustion of the ethanol in a light-duty vehicle (pump-
to-wheel) (Figure 3.1). Well-to-gate modules for energy and material inputs into the life cycle stages
are included (e.g., recovery and processing of petroleum, generation of regional electricity, production
of process chemicals), but are not shown in Figure 3.1 due to the large number of inputs involved.
Energy use and emissions associated with capital and equipment within each of the stages are not
included. Co-products are dealt with through system expansion. The life cycle stages for relevant
reference systems are also shown in Figure 3.1. The reference systems employ traditional methods to
produce products assumed to be displaced by the ethanol or co-products. The displaced products
include gasoline (reformulated), average US Midwest grid electricity mix, electricity derived from coal,
and soy-meal.
32
Figure 3.1 Lignocellulose to Ethanol and Reference System Block Diagrams
Note that competing pathways are denoted by the same letter.
Two main software tools were used to create models of each pathway involved; the Greenhouse
Gases, Regulated Emissions, and Energy Use in Transportation model (GREET 1.8d.1) developed by
Argonne National Laboratory [30], and ASPEN Plus [35]. GREET was used mainly as a data source for
agricultural, primary energy, transportation and vehicle parameters external to the corn stover-to-
ethanol plant process models while ASPEN Plus was used to calculate mass and energy balances for the
corn stover-to-ethanol conversion processes. Two additional tools: GHGenius 4a [31] and SimaPro [33]
were also used as data sources for co-product life cycle information. Modifications were made to
ASPEN models provided by NREL [34] (dilute acid pretreatment), Laser et al. [23] (AFEX pretreatment)
and Mascoma Canada Inc. (autohydrolysis pretreatment, enzymatic hydrolysis and fermentation, xylitol
production), which were used to model the gate-to-gate stage of the corn stover-to-ethanol pathways
(model change details are provided in Appendix A7). GREET 1.8d.1 includes a lignocellulosic ethanol
Iラミ┗Wヴゲキラミ ヮヴラIWゲゲ H;ゲWS ラミ NRELげゲ Sキノ┌デW ;IキS ヮヴラIWゲゲき エラ┘W┗Wヴ, this was not utilized as we had access
to the more detailed ASPEN model from NREL. Life cycle inventory data for process chemicals related
to the dilute acid and AFEX conversion processes were obtained from Spatari et al. [67].
33
Table 3.1 lists the 26 pathways modeled in this work. All pathways use one feedstock (corn stover,
switchgrass or hybrid poplar), one pretreatment technology (dilute acid hydrolysis, ammonia fibre
expansion or autohydrolysis) and produce up to two co-products from a set of four possible co-
products (electricity, lignin pellets, protein concentrate, xylitol). The primary product of all ethanol
plant pathways is E85 fuel (actual blend is 81 vol% ethanol due to addition of a denaturant) with the
assumption that the fuel is ultimately used in an E85 flexible fuel light-duty vehicle. The plant capacity
is common to all pathways and has been scaled to 2000 Mg/day dry biomass. All pathways were
ultimately compared with a reference pathway involving reformulated gasoline (RFG) utilized in a
conventional light-duty internal combustion engine vehicle.
34
Table 3.1 Lignocellulosic Biomass to Ethanol Pathway Designations and Characteristics
Pathway
Namea
Feedstockb Conversion
Technologyc
Co-Product(s)
CSDAEL CS DA + SHCF Electricity (EL)
SGDAEL SG DA + SHCF Electricity (EL)
HPDAEL HP DA + SHCF Electricity (EL)
CSDAPE CS DA + SHCF Lignin Pellets (PE)
SGDAPE SG DA + SHCF Lignin Pellets (PE)
HPDAPE HP DA + SHCF Lignin Pellets (PE)
CSAXEL CS AFEX + SHCF Electricity (EL )
SGAXEL SG AFEX + SHCF Electricity (EL )
HPAXEL HP AFEX + SHCF Electricity (EL )
CSAXPE CS AFEX + SHCF Lignin Pellets (PE)
SGAXPE SG AFEX + SHCF Lignin Pellets (PE)
HPAXPE HP AFEX + SHCF Lignin Pellets (PE)
CSAXPR CS AFEX + SHCF Electricity, Protein concentrate (PR)
SGAXPR SG AFEX + SHCF Electricity, Protein concentrate (PR)
CSAHEL CS AH + SHF (Sep C6/C5)d Electricity (EL)
SGAHEL SG AH + SHF (Sep C6/C5) Electricity (EL)
HPAHEL HP AH + SHF (Sep C6/C5) Electricity (EL)
CSAHPE CS AH + SHF (Sep C6/C5) Lignin Pellets (PE)
SGAHPE SG AH + SHF (Sep C6/C5) Lignin Pellets (PE)
HPAHPE HP AH + SHF (Sep C6/C5) Lignin Pellets (PE)
CSAHXE CS AH + SHF (C6 only) Electricity, Xylitol (XE)
SGAHXE SG AH + SHF (C6 only) Electricity, Xylitol (XE)
HPAHXE HP AH + SHF (C6 only) Electricity, Xylitol (XE)
CSAHXP CS AH + SHF (C6 only) Lignin Pellets, Xylitol (XP)
SGAHXP SG AH + SHF (C6 only) Lignin Pellets, Xylitol (XP)
HPAHXP HP AH + SHF (C6 only) Lignin Pellets, Xylitol (XP)
RFG N/A N/A N/A aNote that although each pathway has two letters to refer to the pretreatment being used in it (e.g., DA, AX, AH),
no distinction in pathway naming convention is made for non-pretreatment technologies used that may be
different between pathways with the same prWデヴW;デマWミデ ふヴWaWヴ デラ デエW さIラミ┗Wヴゲキラミ デWIエミラノラェ┞ざ Iラノ┌マミ aラヴ デエWゲW differences).
bCS = Corn stover, SG = Switchgrass, HP = Hybrid poplar.
cDA = dilute acid pretreatment, AFEX =
ammonia fibre expansion pretreatment, AH = Autohydrolysis pretreatment, SHCF = separate hydrolysis and co-
fermentation, SHF = separate hydrolysis and fermentation, Sep C6/C5 = C6 and C5 sugars fermented separately,
C6 only = Only C6 sugars fermented. dPathways with AH designation use a proprietary enzymatic hydrolysis
system from Mascoma (refer to Section 3.4.2). They also contain a modified distillation strategy from other
pathway types not using AH pretreatment (refer to Section 3.4.3).
35
3.2 Life Cycle Metrics and Functional Unit
Energy use is quantified in terms of total, fossil and petroleum energy requirements. Total energy use
includes fossil (coal, natural gas, petroleum), renewable (biomass, solar, hydro, geothermal, wind) and
other (nuclear, biogenic waste, pumped storage, etc.) energy sources and remains an effective measure
of comparison in terms of the energy efficiency of a process. Fossil energy use includes coal, natural
gas and petroleum and is of interest because reduction of fossil fuel dependence is one of the primary
reasons for using biomass. Petroleum energy is quantified separately as the scarcity of readily
extractible crude oil is becoming a concern worldwide and the use of ethanol fuel is seen as a partial
solution [9]. Emissions quantified include volatile organic compounds (VOC), carbon monoxide (CO),
nitrogen oxides (NOx), sulfur oxides (SOx), particulate matter (PM10 and PM2.5) and greenhouse gases
(CO2, CH4, N2O). The GHGs are also reported in carbon dioxide equivalents based on the IPCC [69] 100-
year global warming potentials (CO2 に 1, CH4 = 25, N2O = 298).The functional unit is 1 MJ of E85
produced and used in a light-duty vehicle.
3.3 Feedstock Production
Feedstocks selected for evaluation in this research include an agricultural residue (corn stover), an
herbaceous energy crop (switchgrass) and a short-rotation forestry feedstock (hybrid poplar). The
assumed compositions for these feedstocks as used in this thesis are listed in Table 3.2.
Corn stover: Corn stover is an agricultural residue in abundance in the US Midwest [9] that has large
biofuel potential and has been the subject of many life cycle studies (e.g. [18,70].). The corn stover
composition in this work is consistent with that used by Aden et al. [24] and Sheehan et al. [42]. During
corn harvesting, the stalks and leafy plant matter external to the corn grain is termed corn stover and
can be collected for biofuel use. Normally, the residue is left on the field to return nutrients to the soil
and prevent release of soil carbon. NREL [71] estimated that 30-50% of the residue can be removed for
ethanol production without seriously impacting soil regeneration, erosion and soil organic carbon (SOC)
release rates. A 48% removal rate is assumed in this thesis, as recommended by Willhelm et al. [72]. It
should be noted however, that despite previous recommendations corn stover removal rate is still
highly debated due to insufficient data and sustainable practice can vary on a field specific basis. The
36
feedstock transport distance for corn stover was determined by obtaining the maximum feedstock
collection radius using the method employed by NREL [35] (refer to calculation in Appendix Appendix A,
;ゲ デエW Wデエ;ミラノ ヮノ;ミデゲ ┌ゲWS キミ デエキゲ ┘ラヴニ ;ヴW ノラI;デWS キミ ; ゲキマキノ;ヴ ヴWェキラミ ふNRELげゲ ヮノ;ミデ ┘;ゲ ;ゲゲ┌マWS デラ HW
in Iowa, a Midwestern state). An average collection radius of approximately 40 km is assumed.
Switchgrass: Switchgrass is an herbaceous crop that can be grown in regions of the United States and
Southern Canada. Switchgrass is available in several varieties with diverse compositions; however, the
relative composition of various components within these varieties is not substantially different [48].
Dacotah switchgrass was used in this work due to key source data based on this variety [48].
Switchgrass has been used in work mostly pertaining to AFEX pretreatment [23], although it is stated to
have similar susceptibility to pretreatments as crop residues [8].
Hybid poplar: A fast growing hardwood known for its high cellulose content, hybrid poplar is abundant
throughout British Columbia, South Dakota and Wyoming, among others [72]. Hybrid poplar as a
hardwood is significantly more recalcitrant than corn stover or switchgrass, and thus harsher
pretreatment conditions are normally needed to hydrolyze its structure. It was assumed that hybrid
poplar has zero protein content, which is characteristic of hardwoods. This feedstock was included in
this work due to its importance as a lignocellulosic feedstock to the Canadian ethanol industry, as well
as its generally advantageous characteristics (fast growing, high cellulose content) [73].
37
Table 3.2 Feedstock Composition
Componenta
Corn Stover Switchgrass Hybrid Poplar
Percentage (Dry wt. Basis) Percentage (Dry wt. Basis) Percentage (Dry wt. Basis)
Extractives 4.68 10.51 4.47
Cellulose 37.4 33.14 41.51
Xylan 21.07 21.79 14.22
Galactan 1.94 1.06 0.87
Arabinan 2.92 2.72 0.88
Mannan 1.56 0.35 1.9
Lignin 17.99 19.08 26.06
Acetate 2.93 2.4 3.6
Protein 3.1 3.61 0
Ash 5.23 5.19 1.74
Soluble Solids 1.18 0.15 4.75
Total 100 100 100
Moisture % 15 25 50
HHV (MJ/Mg) 17452 18782 19606
Corn stover composition was obtained from [34] while compositions for switchgrass and hybrid poplar
┘WヴW ラHデ;キミWS aヴラマ ;ミ ;┗Wヴ;ェW ラa Iラマヮラゲキデキラミゲ aヴラマ デエW U“ DWヮ;ヴデマWミデ ラa EミWヴェ┞げゲ Hキラマ;ゲゲ S;デ;H;ゲW
[74] . Feedstock transport distance was combined with data from GREET 1.6d.1 to determine overall
life cycle impacts. All feedstock were assumed to be transported to their associated ethanol plants by
truck. Direct land use change impacts, fertilizer, insecticide and herbicide addition, as well as energy
needed in farming were determined from GREET 1.8.d.1 (refer to Appendix A2 for actual factors).
3.4 Lignocellulosic Biomass Conversion to Ethanol Modelling
The dilute acid, ammonia fibre expansion (AFEX) and autohydrolysis processes were selected due to
their compatibility with co-products, and data availability. Detailed modelling studies on dilute acid and
AFEX pathways have been conducted by NREL and a joint effort between Michigan State University and
Dartmouth College, respectively [23,34,75], while base design work on autohydrolysis pathways was
performed by Mascoma Canada Inc. Among chemical pretreatment methods, dilute acid hydrolysis
pretreatment is one of the most exhaustively researched methods, and remains one of the few
operated pretreatment technologies at larger scales [76].
38
Illustrated in Figure 3.2 is a simplified block flow diagram for producing ethanol from corn stover for the
dilute acid (DA), ammonia fibre expansion (AFEX) and autohydrolysis (AH) pretreatment strategies.
Activities illustrated in blue boxes indicate base steps to produce ethanol. Electricity is considered to
be a base co-product of ethanol production. Activities in white boxes indicate process modifications to
produce co-products examined in this paper (lignin pellets, protein meal, xylitol). We use the
デWヴマキミラノラェ┞ さDA ヮ;デエ┘;┞ゲざが さAFEX ヮ;デエ┘;┞ゲざ ;ミS さAH ヮ;デエ┘;┞ゲざ デラ ヴWaWヴ デラ デエW pretreatment step
used in each the ethanol production process (refer to Table 3.3 for operating conditions). Beyond the
pretreatment step, the majority of the subsequent process steps (e.g., hydrolysis, fermentation,
distillation and dehydration) are common to all three pretreatment processes. It should be noted that
the overliming step is unique to the DA plant scheme, and is a consequence of dilute acid pretreatment,
while separate five (C5) and six (C6) carbon fermentation is employed in the AH plant scheme. The
autohydrolysis plant scheme is unique in that it is based on a realistic plant design from Mascoma
Canada, and provides a real world comparison to the largely theoretical DA and AFEX designs.
39
Figure 3.2 Simplified Ethanol Plant Schema utilizing Dilute Acid, AFEX and Autohydrolysis Pretreatment Processes
Table 3.3 Pretreatment Conditions for Ethanol Conversion Models by Feedstock
Feedstock Corn Stover Switchgrass Hybrid Poplar
Pretreatment DA AFEX AH DA AFEX AH DA AFEX AH
Temperature ヱヶヰΔC ΓヰΔC ヲヰヵΔC ヱヴヰΔC ヱヴヰΔC ヲヰヵΔC ヱΓヰΔC ヱΒヰΔC ヲヰヵΔC
Pressure 1.2 MPa 1.9 MPa 1.75 MPa 1.2 MPa 1.9 MPa 1.75 atm 1.2 MPa 1.9 MPa 1.75 MPa
Solids Loadinga 30 wt% 38 wt% 50 wt% 30 wt% 22 wt% 50 wt% 30 wt% 19 wt% 50 wt%
Moistureb 186% 60% 94% 231% 200% 94% 229% 233% 94%
Chemical
Loadingc
0.49wt%
H2SO4
1:1
NH3:DBMd
- 1.0wt%
H2SO4
1.5:1
NH3:DBM
- 2.0wt%
H2SO4
2:1
NH3:DBM
-
Residence Time 5 min 5 min 8 min 40 min 30 min 8 min 1.1 min 10 min 8 min
DA = Dilute acid hydrolysis, AFEX = Ammonia fibre expansion, AH = Autohydrolysis awt% is in wet basis.
bPercent indicates g H2O/g dry biomass.
cChemical and loading are pretreatment specific.
dDBM denotes dry biomass.
40
3.4.1 Pretreatment Modelling
Pretreatment model parameters for all feedstocks are listed in Table 3.3. Sugar yields were sourced
from experimental data from the Biomass Refining Consortium for Applied Fundamentals and
Innovation project (CAFI) [46,47,48,58] in combination with publicly available data [77] and previously
mentioned base models, in order to determine model parameters for pretreatment, enzymatic
hydrolysis and fermentation steps.
3.4.1.1 Dilute Acid Hydrolysis (DA)
Dilute acid conditions employed in this work were based on conditions in Wyman et al. [46], as well as
デエラゲW キミ NRELげゲ H;ゲW ヲヰヰヲ-2007 model [34], as shown in Figure 3.3. The exact pretreatment conditions
employed are shown in Table 3.3. Sulfuric acid from 0.49-2wt% is added to a wet feedstock at a
consistency of 30-38% solids during pretreatment at 140-ヱΓヰΔCく TエW ヴW;Iデラヴ キゲ Hヴラ┌ェエデ ┌ヮ デラ
temperature using 1.3 MPa steam, as in [34]. After the appropriate residence time, the pretreatment
mixture is flashed and the pretreated material undergoes a solid-liquid washing and separation step.
TエW ノキケ┌キS aヴ;Iデキラミ キゲ ゲWミデ デラ ;ミ ラ┗Wヴノキマキミェ ゲデWヮ ┘エWヴW デエW ヮH キゲ ヴ;キゲWS デラ ヱヰ ;デ ヵヰΔC キミ ラヴSWヴ デo detoxify
the pretreated material for hydrolysis and fermentation. The pretreated feedstock is blended with
process water to create a 20% solids slurry prior to enzymatic hydrolysis. Pretreatment severity is
generally highest for hybrid poplar feedstock due to the different fiber sizes and multiple cellulose
layers present, coupled with a greater fraction of lignin present.
41
Figure 3.3 Block Diagram of Dilute Acid Hydrolysis Pretreatment and Detoxification Steps
3.4.1.2 Ammonia Fibre Expansion (AFEX)
Table 3.3 summarizes key AFEX pretreatment model parameters used in this work and Figure 3.4
illustrates AFEX pretreatment and subsequent NH3 recovery steps. The model uses a liquid ammonia
to biomass ratio ranging from 1:1 to 2:1 and a g H2O/g dry biomass ratio ranging from 0.6 to 2.3. The
pretreatment reactor is operated from 90-ヱΒヰΔC SWヮWミSキミェ ラミ aWWSゲデラIニく TエW ヴW;Iデラヴ キゲ Hヴラ┌ェエデ ┌ヮ デラ
temperature by indirect heating using low pressure steam (0.45 MPa). In the switchgrass and hybrid
poplar feedstock cases where a higher temperature is required, direct injection of superheated steam
(1.3 MPa) is also used. Following the pretreatment, the ammonia is recovered in a column with 10
theoretical stages using superheated steam (0.45 MPa), condensed using a combination of water
quenching and indirect cooling, and recycled to the pretreatment reactor as in Laser et al. [75]. High
purity NH3 (99.6%) is recovered for re-use in pretreatment. The pretreated material exits the bottom
of the ammonia recovery column, and is diluted to 20% solids before enzymatic hydrolysis and
fermentation.
42
Figure 3.4 Block Diagram of Ammonia Fibre Expansion Pretreatment and Ammonia Recovery Steps
3.4.1.3 Autohydrolysis (AH)
Biomass feedstock is delivered to a pretreatment conveyor where it is diluted to the required solid
consistency (50%) using water (no dilution is required for hybrid poplar feedstock due to high initial
moisture content). The pretreatment conveyor moves the diluted feed to a holding vessel equipped
with a feed screw, which controls the movement of biomass into the pretreatment reactor. The
reactor is brought up to temperature and pressure by direct injection of superheated low pressure
steam at 1.74 MPa. After approximately 5 to 8 min, the pressure in the reactor is then released in a
two stage flash to 0.4 and 0.2 MPa, respectively, as in Figure 3.5. Overhead steam is collected and used
for heat integration in other areas of the plant while the pretreated material moves on to enzymatic
hydrolysis. M;ゲIラマ; C;ミ;S;げゲ ;┌デラエ┞Sヴラノ┞ゲキゲ ヮヴWデヴW;デマWミデ IラミSキデキラミゲ ;ミS ヮラノ┞ゲ;IIエ;ヴキSW
conversions were originally based on the use of hybrid poplar. These conditions correspond to 205ΔC ;デ
50% solids. It should be noted that the same conditions are used for all feedstocks as CAFI data [58]
only investigated uncatalyzed steam explosion (autohydrolysis) for corn stover feedstock at similar
conditions. Given these conditions, polysaccharide conversions were modified to match data reported
in Wyman et al. [58] for corn stover. In contrast, no easily obtainable data on switchgrass
autohydrolysis was found in literature. As SO2 catalyzed steam explosion data was available for
switchgrass and hybrid poplar [46,47,48], polysaccharide conversions were obtained by modifying
switchgrass SO2 explosion conversions to represent the same pretreatment without SO2. This
modification was based on the ratio between polysaccharide conversions reported for hybrid poplar
with and without SO2 from Mascoma and CAFI data [46,47,48], respectively. This amounts to a 2.5%
43
and 23% increased conversion of cellulose and hemicellulose to monomers, respectively, when
switchgrass feedstock is being used in autohydrolysis compared to hybrid poplar with the same
pretreatment.
Figure 3.5 Block Diagram of Autohydrolysis Pretreatment
3.4.2 Enzymatic Hydrolysis & Fermentation
In all pathways, hydrolysis and fermentation steps following pretreatment were modelled using SHF
(separate hydrolysis and fermentation) to better match source data, although better ethanol yields and
process economics may be achieved using SSF (simultaneous saccharification and fermentation).
Hydrolysis and fermentation conditions are summarized in Table 3.4. Enzymatic hydrolysis parameters
for DA and AFEX pathways were sourced from the CAFI data, and the same hydrolysis conditions
applied to all feedstocks [46,47,48]. Autohydrolysis enzymatic hydrolysis parameters were sourced
from a process from Mascoma Canada Inc. Enzymatic hydrolysis parameters and conversions were
assumed to be the same for all feedstocks in the case of autohydrolysis due to Mascoma employing a
proprietary design.
44
Table 3.4 Enzymatic Hydrolysis & Fermentation Conditions by Pretreatment
Dilute Acid AFEX Autohydrolysis
Enzymatic Hydrolysis
Temperature ヵヰΔC ヵヰΔC ヵヰΔCEnzyme Loading 30 mg/g glucan
a30 mg/g glucan 7.5 kg/kg DBM
b
Solids Loadingc
20 wt% 20 wt% 25 wt%
Residence Time 3 days 3 days 4 days
Fermentation
Organism Z. Mobilis Z. Mobilis S. Cerevisiaed
, Z. Mobilis
Temperature ンヲΔC ンヲΔC 31, 32e
Pressure 0.1 MPa 0.1 MPa 0.1 MPaavalue refers to mg total enzyme protein/g glucan (Speczyme CP & Novozyme 188, refer to [46,47,48] for enzyme
details). bkg enzyme solution (proprietary)/kg dry biomass.
bwt% is on wet basis.
cFermentation of C6 and C5
sugars were completed separately. Second listed organism was used for separate C5 fermentation. dFirst value
indicates temperature for C6 fermentation, second value indicates temperature for separate C5 fermentation.
For DA and AFEX pathways, enzymatic hydrolysis was performed using 30 mg total enzyme protein /g
cellulose ;SSキデキラミ ;デ ヵヰΔC ;ミS ヲヰХ ゲラノキSゲ ノラ;Sキミェく Fラヴ ;┌デラエ┞Sヴラノ┞ゲキゲ ヮ;デエ┘;┞ゲが Wミ┣┞マ;デキI エ┞Sヴラノ┞ゲキs
takes place in 3 stages where enzyme addition is added in the first stage followed by an inhibitor
removal step between the 1st and 2nd stages. More enzymes are added in the 2nd stage after the isolated
biomass is re-slurried. Control of pH is also used in all stages by adding NaOH to neutralize acetic acid
(although this is mainly done in the 1st stage, with little addition in remaining stages). This enzymatic
hydrolysis strategy removes inhibitors (as well as soluble monomers) such as furfural and HMF between
stages to enhance hydrolysis and further minimizes enzyme inhibition by acetic acid. It was assumed
that all polysaccharides were hydrolyzable during enzymatic hydrolysis in all pathways, and that all
hemicellulosic sugars were hydrolyzable with similar effectiveness to xylose. Refer to Appendix A6 for
reactions and conversions used.
C6 and C5 sugars were co-fermented in DA and AFEX pathways but separately in autohydrolysis
pathways (if xylose was not being used to create xylitol co-product). It was assumed that all C6 and C5
monomers were fermentable (normally only glucose and xylose are fermented) in all pathways, and
that all hemicellulosic monomers were able to be fermented with similar effectiveness to xylose.
Similarly, in AH pathways where separate C6 and C5 fermentation was used, C6 monomers were
45
assumed to be fermented with similar effectiveness to glucose. Oligomers were assumed to be
unfermentable. DA and AFEX pathways utilized simultaneous anaerobic fermentation of C6 and C5
マラミラマWヴゲ ┌ゲキミェ ヴWIラマHキミ;ミデ )く MラHキノキゲ ;デ ンヲΔCが ;ゲ SWゲIヴキHWS H┞ NREL キミ [34]. AH pathways originally
designed by Mascoma Canada Inc. employ SHF to facilitate the production of xylose, followed by
separation using ion exchange and chromatographic separation before fermentation. Only C6 sugars
were fermented using a proprietary strain of Saccharomyces cerevisiae, while the remaining xylose was
used to produce xylitol. For the purpose of this thesis, the base model was modified in order to
facilitate C5 fermentation in AH pathways where xylitol co-production is not implemented. C5
aWヴマWミデ;デキラミ キゲ ヮWヴaラヴマWS ┌ゲキミェ )く MラHキノキゲ ;デ ンヲΔC キミ デエW ;HゲWミIW ラa ェノ┌IラゲWが ┌ゲキミェ ヮ;ヴ;マWデWヴゲ SWヴキ┗WS
from NREL [77].
3.4.3 Ethanol Recovery and Blending
For DA and AFEX pathways, the separation of ethanol from beer produced during fermentation is
handled in the same method as the NREL 2002 model [34], to facilitate comparison. This consists of a
beer distillation + rectification column, followed by dehydration using a molecular sieve to recover
99.5% pure ethanol. The rectification condenser is integrated with a multiple effect evaporator system
to reduce overall plant heating load; details can be found in [34]. For the autohydrolysis pathway,
modifications were made for a two column distillation and rectification setup where the rectification
column condenser was modified to be integrated with the beer column reboiler instead (Figure 3.6).
These modifications were only made to the AH pathway because distillation designs originally from
Mascoma Canada Inc. were only partially complete. The beer column is operated in a vacuum at 0.3
;デマ キミ ラヴSWヴ デラ ノラ┘Wヴ ヴWHラキノWヴ デWマヮWヴ;デ┌ヴW デラ ヶΒΔCく TエW ヴWIデキaキI;デキラミ Iラノ┌マミ キゲ IラヴヴWゲヮラミSキミェノ┞
ラヮWヴ;デWS ;デ ヲくン ;デマが ;ノノラ┘キミェ キデゲ IラミSWミゲWヴ デラ ラヮWヴ;デW ;デ ΑヴΔCく Tエキゲ IヴW;デWゲ ; ヶΔC デWマヮWヴ;デ┌ヴW
difference, facilitating heat transfer between the two units. Beer distillation and rectification columns
with 11 and 18 theoretical stages, respectively, at 50% efficiency are used. The direction of heat flow is
indicated by the red line in Figure 3.6. For all pathways, any overhead vapors containing ethanol, e.g.,
from process vents, are collected and sent to an ethanol scrubber and recovered at 99.5% efficiency.
46
Figure 3.6 Block Flow Diagram of Autohydrolysis Pathway Ethanol Recovery Scheme
Complete ethanol dehydration is accomplished via a molecular sieve system. The molecular sieve
system is implemented identically in all pathways, as shown in Figure 3.6. The molecular sieve system
is sourced from a proprietary system being used by NREL, and is described in detail in [34]. Two
molecular sieve columns are used in which the incoming ethanol vapor (92.5 wt%) is passed through
one column where water is removed, while the other column is being regenerated by passing a high
デWマヮWヴ;デ┌ヴW Wデエ;ミラノ ゲノキヮゲデヴW;マ デエヴラ┌ェエが ヴWマラ┗キミェ ┘;デWヴく TエW Wデエ;ミラノ ゲノキヮゲデヴW;マ ふデエW さヴWェWミWヴ;ミデざぶ キゲ
then sent back to the rectification column. Together, the two molecular sieve columns form a
continuous ethanol dehydration process able to purify ethanol to approximately 99.94 wt% ethanol. As
a final step to produce E85 fuel, reformulated gasoline is blended with the dehydrated ethanol as a
denaturant (4.75 vol% of resulting mixture), and then further added until an E85 blend is achieved
(note that due to the addition of the denaturant, actual ethanol vol% in final E85 fuel is 81 vol%).
Ethanol denaturing and blending is a common step to all pathways and is handled in the same manner
as presented in Figure 3.6. It should be noted that all vented gases containing ethanol (such as from
fermentation) were sent to a scrubber column with four theoretical stages, where water was used to
scrub ethanol out of the vapor phase. Scrubbed ethanol is then blended with the fermentation broth
on its way to the beer column.
47
3.4.4 Waste Residue Processing, Boiler and Wastewater Treatment
Steam and electricity generation (if the pathway co-generates electricity as a co-product) for all
pathways is handled via a Rankine boiler and turbogenerator system (CHP, combined heat and power
system) as described by NREL [34] (refer to Appendix A7 for details). The only exception to this is when
the pathway in question does not produce an electricity co-product (e.g., lignin pellet producing
pathways). In this case, turbines are removed, steam header pressure is reduced (1.3 MPa for DA and
AFEX ヮ;デエ┘;┞ゲが ヱくΑヴ MP; aラヴ AH ヮ;デエ┘;┞ゲぶ ;ミS ゲデW;マ キゲ ラミノ┞ ゲ┌ヮWヴエW;デWS H┞ ヱヰΔCく Wキデエ デエWゲW
modifications, a Rankine boiler producing only steam for heating purposes was created for scenarios
that do not include electricity generation. In general, steam and electricity are used to supply plant
operations while excess electricity is assumed to be sold to the local (Midwest) grid. The AFEX and AH
models received included only partially completed and/or unique boiler systems. Thus, for consistency,
NRELげゲ HラキノWヴ デ┌ヴHラェWミWヴ;デラヴ ゲ┞ゲデWマ ふ┌ゲWS キミ デエWキヴ ヲヰヰヲ マラSWノ [34]) was integrated into all AFEX and
AH model pathways. A consistent waste management process was used for all pathways, with NRELげゲ
2002 model wastewater treatment system integrated into all models. In this system, dilute waste
streams are sent to an anaerobic digestor, followed by an aerobic digestor to lower chemical oxygen
demand before solids are removed in a clarifier. These solids are dried in a belt press, then delivered to
combustion. Biogas generated from anaerobic digestion is used for combustion, while water leaving
the belt press is recycled.
The recovery strategy for lignin and soluble biomass residues was identical in DA and AFEX designs,
with some differences in AH designs. In DA and AFEX processes, lignin-rich residues are separated from
ethanol during beer distillation and are recovered in the bottoms stream as seen in Figure 3.7. Water is
removed from the residues using a three-stage multiple effect evaporator system; the bottoms from
the first stage are sent to a solid-liquid separation step (pneumapress) where lignin is recovered and
sent to combustion. The remaining liquids are returned to the second stage of the evaporator.
Overhead evaporated liquid (water) from all stages of the evaporator is condensed and recycled while
the dried soluble biomass residues from the bottom of evaporator stages 2 and 3 are collected and sent
デラ IラマH┌ゲデキラミく F┌ヴデエWヴ SWデ;キノゲ ラミ デエW ┘;ゲデW マ;ミ;ェWマWミデ ゲ┞ゲデWマ I;ミ HW aラ┌ミS キミ NRELげゲ ヲヰヰヲ マラSWノ
[34] and Appendix A7. In AH models, lignin is removed by a filter press directly after enzymatic
hydrolysis, facilitating a clear liquid fermentation and distillation. Without the need to recover lignin in
48
downstream leftover residue streams, evaporation is removed in favour of sending these streams
directly to wastewater treatment.
Figure 3.7 Block Flow Diagram of Ethanol Recovery Scheme
3.5 Co-Product Production Modelling
Co-product and pretreatment combinations were mainly selected due to their compatibility. Electricity
and lignin pellet co-product production were investigated for the three pretreatment strategies, while
protein concentrate co-production was only investigated for AFEX pretreatment. This was due to the
likelihood that dilute acid pretreatment would degrade proteins while the milder conditions of AFEX
would be able to preserve them [23]. Autohydrolysis pretreatment conditions may also be able to
preserve protein; but alkaline conditions are required for protein extraction, basically creating the
conditions used in AFEX. Thus, protein extraction was not considered as an independent option for
autohydrolysis pretreatment pathways. Similarly, xylitol was only investigated in AH pathways, where
xylose was separated from glucose using proprietary Mascoma Canada Inc. technology. As electricity is
the most common co-product included in lignocellulosic ethanol models [8], it was included in all of the
pathways. Due to this, pathways with a sole electricity co-product are considered base case pathways.
49
Electricity generation has already been discussed in Section 3.4.4. Descriptions of modifications to the
base models to produce non-electricity co-products are provided below.
Lignin Pelletization: Fuel pellet production is an alternate co-product option for dealing with ethanol
plant lignin and other biomass residues [25]. This thesis explores the option of either completely
diverting lignin to electricity co-generation or to fuel pellet production for subsequent offsite
combustion, although the author acknowledges that combinations of both methods can be used.
To produce lignin pellets, biomass residue waste streams were directed to a pelletization module
shown in Figure 3.8. This module was based on information from Thek et al. [60], employing a
superheated steam dryer followed by a pelletizing unit (ring die), a vertical pellet air cooler and a
sieving unit. Lignin pellets were dried below 15 wt% moisture (wet basis), and overhead vapors were
condensed and sent to wastewater treatment. Total operating electricity requirements for the entire
module was estimated from Thek et al. [60] (based on power quotes for individual units) to be
Figure 3.8 Block Diagram of Pelletization Module
Pelletization of biomass residues is advantageous as the residues do not require grinding prior to
entering the pellet press, as would normally be required in pelletization operations [60]. With the
complete use of biomass-derived lignin and residues for pelletization, for W;Iエ さヮWノノWデキ┣;デキラミざ ヮ;デエ┘;┞が
natural gas was used to supply energy to produce steam for plant needs. Plant electricity requirements
were satisfied through electricity sourced from the local power grid.
Protein Meal Isolation: The protein extraction module used in the protein concentrate co-production
pathway has the same design as that in Laser et al. [23]. Corn stover feedstock is contacted with a basic
50
solution of ammonium hydroxide (pH 10) in an W┝デヴ;Iデキラミ Iラノ┌マミ ;デ ヴヰΔCく TエW W┝デヴ;Iデ マラ┗Wゲ ラミ デラ ;ミ
┌ノデヴ;aキノデヴ;デキラミ ┌ミキデ デラ ヴWIラ┗Wヴ デエW Iヴ┌SW ヮヴラデWキミが ┘エキIエ キゲ デエWミ SヴキWS キミ ; ゲヮヴ;┞ Sヴ┞Wヴ ┌ゲキミェ ヱΒヰΔC ;キヴ ;デ ;
low residence time to prevent damage, yielding a final protein co-product. The remaining feedstock
exits the extraction column and is subjected to AFEX pretreatment as previously described in (Section
3.4.1.2). Pre-treated material leaving the pretreatment reactor is then sent to another extraction
column using ammonium hydroxide, with the extract portion once again being dried in a spray dryer at
similar conditions yielding a second protein co-product. Further details can be found in [23]. A notable
departure from the original model is that NH3 recovery in AFEX pathways with protein co-production
has been modified to use an NH3 stripper with 15 stages at 0.2 MPa, and overhead NH3 condensation
has been partially integrated with distillation preheating. NH3 is recycled to both the protein extraction
and AFEX pretreatment ┌ミキデゲ ;ゲ ミWWSWSく PヴラS┌IWS ヮヴラデWキミ キゲ ヴWaWヴヴWS デラ ;ゲ さヮヴラデWキミ IラミIWミデヴ;デWざ S┌W
to the isolated protein being only 81-85 wt% pure.
Xylitol Production: Detailed design data for xylitol production from xylose using the AH pathway was
sourced from Mascoma Canada Inc. C5 sugars are recovered exclusively for xylitol production, and
ethanol is produced from C6 alone. With only C6 fermentation, C5 sugars exit the bottoms of the beer
distillation column, and are then separated prior to xylitol production (Figure 3.9).
Figure 3.9 Block Diagram of Xylitol Production Model
The filtration system consists of a microfilter followed by a reverse osmosis system remove solids and
other impurities, which are sent to wastewater treatment. The xylose-rich stream is then concentrated
51
to ~50% solids using a three-stage multiple effect evaporator, then enters a simulated moving bed
chromatography system where xylose is separated from other components. The xylose-rich stream
moves on to a second multiple effect evaporation, concentrating the xylose stream to 60% solids. The
concentrated xylose then enters a hydrogenation reactor, producing xylitol by using a proprietary
aluminum-ミキIニWノ I;デ;ノ┞ゲデ ふヱヰヲくヵΔCが ンくΒ MP;ぶく TエW Iヴ┌SW ┝┞ノキデラノ キゲ デエWミ ヮ┌ヴキaキWS ┌ゲキミェ ;ミラデエWr
chromatography column followed by a third multiple effect evaporation step (wiped film evaporators
to avoid damage to the xylitol) to concentrate xylitol to 40% solids. The xylitol concentrate then enters
a final crystallization process to produce a final xylitol product at 99.9wt% purity. Exact details on the
xylitol process are largely proprietary.
3.6 Co-Product Allocation
In past LCAs, utilization of different co-product allocation methods has been shown to substantially
impact results [38,65]. The system expansion method (displacement) has been selected for this thesis
as discussed in Section 2.1.1. The products assumed to be displaced by the co-products are as follows:
Co-produced electricity displaces electricity produced by the average US Midwest grid mix
Lignin pellets displace coal in 20wt% biomass co-fired burners, based on work by McKechnie et al.
[25] and information from GREET 1.8d [30].
Biomass-derived protein concentrate displaces soy meal produced in the US
Xylitol replaces sugar derived from sugar beet produced in the province of Alberta, Canada.
The impacts from displacement of the local grid electricity depend on the regional electricity grid mix.
The average US Midwest electricity grid mix is dominated by coal (51.6%) and natural gas (33.5%), with
small amounts of biomass (5.8%) and renewables (9.1%) [78]. The Midwest electricity grid mix was
obtained from California GREET [78]. Fuel cycle energy and emissions associated with generation of
this grid mix were obtained from GREET 1.8d.1 (refer to Appendix A3 for actual co-product credit
parameters and calculation methods). As lignin pellets were assumed to displace coal in biomass co-
fired electricity generating stations, data were sourced from GREET 1.8d.1 and from previous work by
McKechnie et al. [25]. Impacts due to soymeal were calculated based on GREET 1.8d.1 parameters for
soymeal production from soybean. Chiesa et al. [79] reported that protein from AFEX pre-treated corn
52
stover and switchgrass were potentially suitable substitutes for food grade protein. As mentioned in
Section 3.5, the purity of the protein concentrate produced in this study is below 85 wt% - the US
Department of Agriculture (USDA) minimum standard for use in poultry products [80]. Thus, a
conservative approach has been adopted whereby soy meal is displaced rather than food-grade protein
for human consumption. For the xylitol credit calculation, life cycle information for the displacement of
sugar beet derived sugar was sourced from GHGenius [31], which used a combination of UK sugar beet
agricultural practices (e.g. agricultural chemical requirements) combined with sugar beet yields and
local conditions associated with Alberta sugar beet agriculture. The resulting information was assumed
to represent North American sugar beet agriculture in general, as sugar beet information for North
America does not otherwise exist in publically available literature.
3.7 Ethanol Fuel, Distribution (gate to pump) and Model Vehicle
This thesis examines E85 fuel and its use in a light-duty vehicle as the final stage in its life cycle. The
ethanol is produced in an anhydrous form (99.94% pure) before blending with a denaturant and RFG.
E85 fuel was selected because it is the highest ethanol blend that can be utilized in light-duty vehicles in
the U.S. and Canada, and it has been analyzed in prior studies (to facilitate easier comparison of
results). The default gasoline and E85 flexible fuel vehicles in GREET 1.8d.1 [30] are examined for RFG
and E85 pathways (fuel economy for flexible fuel vehicle is 9.48 L gasoline equivalent/100km, see
Appendix A4 for more detail), respectively for the projected year of 2015.
53
4. Results and Discussion
Due to the large number of pathways involved, results are first discussed in terms of the effect of
technological and co-product differences for the same feedstocks, followed by a discussion of the effect
of using different feedstocks. Descriptive acronyms are used to identify each pathway (e.g., CSDAEL, CS
= corn stover, DA = dilute acid, EL = electricity co-product) when discussing results due to the number of
pathways. Refer to Table 3.1 for a full description of acronyms for each pathway. Pathways that only
ヮヴラS┌IW WノWIデヴキIキデ┞ ふDAELが AXELが AHELが AHXEぶ ;ヴW ヴWaWヴヴWS デラ ;ゲ さH;ゲWざ ヮ;デエ┘;┞ゲ デエヴラ┌ェエラ┌デ デエW
section in order to provide a basis of comparison against other pathways using different conversion
technology schemes. In addition, it should be noted that all other pathways employing different co-
ヮヴラS┌Iデゲ ;ヴW マラSキaキI;デキラミゲ ラa デエWゲW さH;ゲWざ ヮ;デエ┘;┞ゲが テ┌ゲデキa┞キミェ デエWキヴ SWゲキェミ;デキラミく Refer to Appendix B
for disaggregated results data tables.
The co-product credits throughout the results are generally negative values that normally lower energy
requirements and emissions for pathways. Co-product credits are subtracted because they are the
result of a co-product eliminating the energy and emissions from a competing process. In some cases
(especially when dealing with emissions), co-product credits cause a pathway to have net life cycle
energy or emissions below zero. This would indicate that the pathway is able to reduce all of its own
energy and/or emissions in addition to eliminating energy and/or emissions outside of the actual main
pathway. This does not in actuality indicate that a pathway has zero energy use and/or emissions;
however it does indicate that it has eliminated an amount of energy or emissions at least equal to the
amount of energy used (or emissions generated) in the baseline process, once co-products are also
taken into account.
4.1 Single Feedstock Pathways Comparison
The results in this section are shown for the corn stover feedstock only. Results are quantified in terms
of energy use and greenhouse gas (GHG) emissions. Other metrics such as water use are discussed in
the section where multiple/different feedstocks are compared (Section 4.2).
54
4.1.1 Ethanol and Co-Product Outputs
Table 4.1 presents ethanol and co-product volumes, energy content produced from corn stover via
each of the pathways, and ethanol plant yields. The different conversion technologies produce
different amounts of anhydrous ethanol, due to differences in C6/C5 sugar conversion and diversion of
xylose to co-products. Pathways with pellets as co-products did not affect overall ethanol yield, as
pellets simply provide an alternative to dealing with lignin residues. The only co-product that
considerably affected ethanol production was xylitol, as C5 sugars are diverted to hydrogenation rather
than fermentation. With respect to base pathways (electricity co-production only), DA pathways
produced the most ethanol (19% and 18% more than the AFEX and AH pathways, respectively) while
ethanol production was similar for AFEX and AH. AH pathways with xylitol production produced the
least ethanol (140 x 106 L/yr). These production rates correspond to ethanol yields of 374, 301, 308 and
200 L per dry Mg of corn stover input for DA, AFEX, AHEL and AHXE pathways, respectively.
Although the AHEL pathway had low sugar monomer yields (refer to Table 4.2), it is still able to produce
essentially the same amount of ethanol as AFEX pathways. This was partially due to low C5 sugar
monomer yields for AFEX pathways and the higher ethanol yields for AH pathways during fermentation.
Both DA and AH pretreatments are able to hydrolyze corn stover hemicellulose to monomers, while
AFEX is only able to hydrolyze hemicellulose to oligomers, which were assumed to be unfermentable.
Low monomer yields in pretreatment can typically be overcome by higher enzyme loadings in
enzymatic hydrolysis, but this was not done in the DA and AFEX pathways to ensure consistency with
the enzymatic hydrolysis conditions employed in the source data [46]. Table 4.3 summarizes metabolic
and productive ethanol yields for monomers entering fermentation for each pathway. All pathways
except AHXE employ Zymomonas mobilis to ferment C5 and C6 sugars, and display >90% metabolic
yield. AH pathways provided the highest metabolic yield and productivity due to separate C6 and C5
fermentation, resulting in higher selectivity for each sugar type as xylose fermentation is improved in
the absence of glucose [81].
In AH pathways producing xylitol as a co-product, ethanol production was reduced by 35% relative to
pathways producing electricity, due to diversion of C5 sugars to hydrogenation rather than
fermentation. These pathways produced 0.77 kg xylitol/kg isolated xylose at 96% purity. Yields of lignin
pellets were inversely correlated with ethanol plant yield when comparing similar pathways with similar
designs (AXPE produces 4% more lignin pellet energy than DAPE). Lignin co-product yields are also
55
highly dependent on how lignin residues are processed. Drying residues and sending them to
pelletization produced more pellets than re-routing the same residues to wastewater treatment
without drying, where the soluble component fraction would be digested to produce biogas (which is
subsequently combusted for plant heating). The pellet co-production rate for the AHPE pathway was
13% lower than for the AXPE pathway on an energy basis, despite similar ethanol production due to
more residues digested into biogas. Pellet co-product yields were similar between AHPE and AHXP
pathways (although ethanol plant yields were considerably different), mainly because use of xylose,
whether for xylitol or ethanol, has limited effect on the energy content of the residues. Like lignin
pellet output, total electricity output from each pathway is also generally dependent on plant ethanol
yield, but net electricity output is also influenced by plant electricity requirements. The plant electricity
ヴWケ┌キヴWマWミデ ヴWS┌IWゲ デエW ミWデ さゲ;ノW;HノWざ WノWIデヴキIキデ┞ H┞ ンΑ-56%. The largest amount of net electricity
(218 GWh/yr) was produced by the AXEL pathways, while the smallest amount was produced by the
AHXE pathway (151 GWh/yr).
Table 4.1 Annual Production of Ethanol and Co-Products by Pathway
Product Unit DAEL DAPE AXEL AXPE AXPR AHEL AHPE AHXE AHXP
E100 106 L/yr 273 273 220 220 220 225 225 146 146
E85a 106 L/yr 339 339 273 273 273 184 184 283 283
E100 Yield L/Mgb 374 374 301 301 301 200 200 308 308
Electricity GWhc 181
218
53 186
151
Lignin Pellets TJ/yrd
5711
5965
5258
5241
Xylitol 103 Mg/yr
111 111
Protein
Concentrate 103 Mg/yr
25
DAEL = DA + Electricity, DAPE = DA + Pellets, AXEL = AFEX + Electricity, AXPE = AFEX + Pellets, AXPR = AFEX +
protein & electricity, AHEL = AH + Electricity, AHPE = AH + Pellets, AHXE = AH + Xylitol & Electricity, AHXP = AH +
Xylitol & Pellets. aE85 fuel has been both denatured and blended with gasoline.
bYield is presented in units of L of E100 per Mg of dry corn stover.
cValues refer to net saleable electricity produced by the ethanol plant, after subtracting plant electricity use.
dLower heating value used to determine primary energy content of lignin pellets.
56
Table 4.2 Sugar Monomer Yield for Pretreatment and Enzymatic Hydrolysis Steps by Pathway Typea
Pathway
Typeb
Pretreatment
Monomer Yield (%)
Enzymatic Hydrolysis
Sugar Yield (%) Overall Yield (%)
C6 C5 C6 C5 C6 C5
DA 12.8 82.6 91.1 57.8 91.0 88.2
AFEX 0.0 0.0 95.1 77.7 91.0 38.8
AH 8.1 42.8 86.3 78.5 87.2 82.1 aMonomer yields are based on maximum available sugars released in each category.
bPathway type refers the pre-treatment designations described in Table 3.1. The yields displayed apply to all
pathways with the same designation.
Table 4.3 Ethanol Fermentation Yields from Monomeric Sugars by Pathway Type
Pathway Type Metabolic (%)a Productive (%)b
DA 91.0 88.7
AFEX 92.1 90.6
AH 95.3 (92.1)d 95.1 (90.3)
AH + Xylitolc 91.1 90.9 aMetabolic yield refers to produced ethanol/theoretical ethanol potential from consumed sugars (refer to
Appendix A5 for yield calculation methods). bProductive yield refers to produced ethanol/theoretical ethanol potential of all fermentative sugars available.
cRefers to the autohydrolysis pathway type with xylitol co-production (see Table 3.1).
dNumber outside the parentheses indicates yield for C6 only, parentheses indicates yield from C5 fermentation
only.
4.1.2 Energy Use Results
Well-to-wheel (WTW) energy use for all pathways is summarized in Figure 4.1. Results are presented in
disaggregated form (energy requirement and associated co-product credit) and net WTW energy use is
indicated by a diamond symbol.
4.1.2.1 Total Energy Use
WTW total energy use includes energy from both renewable (e.g., solar, wind, hydro) and non-
renewable (e.g., coal, petroleum, nuclear) sources used for ethanol and co-product production (this
includes energy in the corn stover itself). Significant differences in total energy use (Figure 4.1) are only
a function of upstream ethanol plant activities because all results are a function of the volume of
ethanol fuel produced. Since the functional unit of this analysis is MJ of ethanol (E85) fuel produced,
and downstream activities (combustion of fuel in the vehicle) represent only the release of energy from
57
the fuel produced, their values are the same in every pathway. Total energy use is generally useful for
comparing energy efficiency among processes. All ethanol pathways have at least a 42% greater net
total energy use compared to the gasoline reference pathway. This is in line with prior studies (e.g.
[38,65]) and emphasizes the generally high efficiency of gasoline production from crude oil.
Comparing pathway types, total energy use for AH pathwaysis higher than for DA and AFEX pathways
producing similar co-products (21% increase when comparing DAEL to AHEL). Although DA and AFEX
pathways required the use of hydrocarbon-intensive (from a life cycle perspective) chemicals such as
sulfuric acid and ammonia during pretreatment, AH pathways required a greater enzyme loading in
addition to the use of a base (NaOH), which offset this disadvantage. Furthermore, AH pathway
ethanol plants used a larger amount of energy derived from corn stover for plant heating and electricity
requirements, due to lower ethanol yields compared to DA plants. Total energy use between DA and
AFEX pathways differed by 10%, at most.
Ethanol plant pathways with higher ethanol yields require less total energy per MJ of ethanol. As
ethanol is the primary product, corn stover-derived energy used for electricity/steam appears intotal
energy use. Only a fraction of the stover energy is transferred to the electricity/steam (32% when
considering primary energy to electricity). In pathways with higher ethanol yields, less stover energy is
used for electricity/steam, and more is released in combustion of the ethanol in a model vehicle. Due
to normalization of total energy results per MJ of E85 produced, the loss in E85 energy associated with
fuel combustion in a vehicle is not included, while a 32% reduction in stover energy associated with
electricity generation is. Pathways with lignin pellets as co-products had the largest total energy use,
due to considerable energy required to dry and pelletize lignin residues. Furthermore, lignin pellet
scenarios had a low co-product credit, because the renewable energy in the pellet itself does not
generate credits against total energy use. This is due to the nature of the lignin pellet co-product in
conjunction with total energy accounting. The lignin pellet itself must be combusted in order to
produce useful energy in the same way as coal (the product it is displacing). Since the total energy
IヴWSキデ キミIノ┌SWゲ ;ミ┞ ヴWミW┘;HノW WミWヴェ┞ さ┌ゲWSざが デエW ヴWミW┘;HノW WミWヴェ┞ キミ デエW ヮWノノWデ キデゲWノa マ┌ゲデ HW
subtracted from the total energy displaced when useful energy from coal is eliminated (largely
counteracting the fossil energy released in coal combustion, which is similar in magnitude, see
Appendix A3 for details). This would not be the case when considering fossil energy use only, because
this renewable energy is not subtracted from the fossil credit. The AHXP pathway had the highest net
total energy use, due to considerable energy required to isolate, dry and hydrogenate xylose residues
58
to xylitol, in addition to energy required to dry and pelletize lignin residues. AFEX pathways with
protein as a co-product only needed a 9% increase in net total energy to create a value-added product,
compared to the net energy with AFEX and electricity as a co-product (AXEL). In contrast, to produce a
xylitol co-product via autohydrolysis (AHXE), a 22% increase in net total energy is required compared to
AHEL. This 22% increase in energy is accompanied by a 35% reduction in ethanol yield, which both
offset potential financial gains from xylitol production. While the lower ethanol plant yield in AHXE
lowers the total energy for distillation compared to AHEL (14% reduction in plant heating), this is
counterbalanced by a 56% increase in plant heating for evaporation and hydrogenation during xylitol
production.
Figure 4.1a Well-to-wheel Energy Use of Gasoline and Corn Stover-to-E85 Pathways
DAEL = DA + Electricity, DAPE = DA + Pellets, AXEL = AFEX + Electricity, AXPE = AFEX + Pellets, AXPR = AFEX +
protein & electricity, AHEL = AH + Electricity, AHPE = AH + Pellets, AHXE = AH + Xylitol & Electricity, AHXP = AH +
Xylitol & Pellets. 1Total energy use includes fossil, renewable and other energy.
2Co-ヮヴラS┌Iデ IヴWSキデ ヴWaWヴゲ デラ デエW WミWヴェ┞ Wノキマキミ;デWS H┞ ; ヮ;デエ┘;┞げゲ Iラ-product that displaces a competing product
in industry. Refer to Section 3.6. 3NWデ ヴWaWヴゲ デラ デエW ゲ┌マ ラa ; ヮ;デエ┘;┞げゲ ヴWケ┌キヴWS WミWヴェ┞ ;ミS キデゲ Iラ-product credit. 4F┌Wノ ヴWaWヴゲ デラ WキデエWヴ ェ;ゲラノキミW ラヴ EΒヵ ヮヴラS┌IWS S┌ヴキミェ W;Iエ ヮ;デエ┘;┞げゲ ノキaW I┞IノWく Aノノ ヮ;デエ┘;┞ゲ ラデエWヴ デエ;ミ ェ;ゲラノキミW produce E85.
Ga
solin
e
DA
EL
DA
PE
AX
EL
AX
PE
AX
PR
AH
EL
AH
PE
AH
XE
AH
XP
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
MJ
of
En
erg
y /
MJ
of
EtO
H P
rod
uce
d4
Total¹ Fossil Petroleum Co-Product Credit² Net³
59
4.1.2.2 Fossil Energy Use
Fossil energy use only includes energy from non-renewable sources. Differences between the various
pathways are again due solely to ethanol plant activities, for the same reasons as described above. All
ethanol pathways require more total energy when compared to the reference gasoline pathway.
However, a large portion of WTW total energy is renewable (biomass-based), and thus, fossil energy
use is much lower for ethanol pathways compared to the gasoline pathway. All ethanol pathways have
at least a net 47% reduction in fossil energy use relative to the gasoline reference pathway. The AXEL
pathway has the largest reduction in fossil energy use, at approximately 80% relative to gasoline. This
is mainly due to the fact that the majority of the energy in the ethanol produced is actually renewable
energy from corn stover. This is partially offset by blending of ethanol with gasoline to result in E85
fuel.
Pathways with electricity as a co-product have a substantial difference between total and fossil energy
use, while pathways producing lignin pellets have a lower difference. This can be attributed to the
following. All ethanol pathways co-producing electricity were energy self-sufficient due to the
combustion of stover residues, thus these pathways rely mainly on renewable energy. In contrast,
pathways co-producing lignin pellets rely on combustion of biomass residues outside the actual ethanol
plant (relying completely on the generated credit to stay competitive with on-site electricity
generation) and import fossil sourced energy. The credit from lignin pellets is nearly completely fossil
fuel based (due to the assumed displacement of coal), and thus, the largest fossil energy credit is
generated via pathways with lignin pellets as the co-product. Value-added co-products typically require
;SSキデキラミ;ノ WミWヴェ┞ さキミ┗WゲデマWミデざが ;ゲ キミ デエW I;ゲW ラa ヮヴラデWキミ ;ミS ┝┞ノキデラノ ふAXPR ;ミS AHXEぶく Hラ┘W┗Wヴが キデ I;ミ
be observed that the AHXE pathway still has 14% less fossil energy use than the AHEL pathway which
solely produces electricity, despite a higher plant energy demand. This outcome arises from the fossil
energy credit from displacement of sugar beet-derived sugar by xylitol, which is large enough to
overcome the additional energy requirement for xylitol production compared to a process with
electricity co-generation. In addition, lower ethanol production in the pathways co-producing xylitol
reduced the distillation energy demand, while the amount of electricity produced from residues in the
AHXE pathway was only 19% lower than for the AHEL pathway, because xylose is only a small fraction
of the energy contained in residues allocated to electricity co-generation.
60
Net petroleum energy use in each pathway has been reduced by at least 67% compared to gasoline as
illustrated in Figure 4.1b. Petroleum energy in each ethanol pathway was mainly attributable to energy
for feedstock and product transport, and petroleum energy in the gasoline blended with ethanol to
produce E85. In general, petroleum energy is relatively constant throughout the various ethanol
production pathways.
Figure 4.1b Well-to-wheel Petroleum Energy Use of Gasoline and Corn Stover-to-E85 Pathways
1NWデ ヴWaWヴゲ デラ デエW ゲ┌マ ラa ; ヮ;デエ┘;┞げゲ ヴWケ┌キヴWS WミWヴェ┞ ;ミS キデゲ Iラ-product credit.
A breakdown of well-to-pump (WTP) fossil energy use by life cycle activity is shown in Figure 4.2. In all
pathways generating electricity as a co-product (including cases co-producing another value-added
product), gasoline used in blending is one of the largest contributors to fossil energy use (34-53% of
total WTP fossil energy). Most of the remainder of the energy in these pathways is generated from
renewable sources, as a consequence of the ethanol plant producing energy from biomass and using a
combined heat and power (CHP) system. Plant heating and electricity only contribute significantly to
WTP fossil energy use in pathways producing lignin pellets. In these scenarios, none of the residual
-0.2
0
0.2
0.4
0.6
0.8
1
1.2
Gasoline DAEL DAPE AXEL AXPE AXPR AHEL AHPE AHXE AHXP
MJ
of
Pe
tro
leu
m E
ne
rgy
/ M
J o
f F
ue
l P
rod
uce
d
Petroleum Energy Requirement Co-Product Credit Net¹
61
lignin from corn stover is sent to CHP, and natural gas is used instead, which accounts for a large
fraction of the total fossil energy. Pathways producing lignin pellets must also purchase electricity from
the grid, 85% of which is derived from fossil energy as the Midwestern U.S. grid is assumed in the study.
Ethanol plant heating and electricity requirements constitute 66-74% of the fossil energy use in lignin
pellet pathways.
Figure 4.2 Breakdown of Well-to-Pump Fossil Energy Use by Activity for Ethanol Pathways
DAEL = DA + Electricity, DAPE = DA + Pellets, AXEL = AFEX + Electricity, AXPE = AFEX + Pellets, AXPR = AFEX +
protein & electricity, AHEL = AH + Electricity, AHPE = AH + Pellets, AHXE = AH + Xylitol & Electricity, AHXP = AH +
Xylitol & Pellets. RFG blending = blending of reformulated gasoline to produce E85
Table 4.4 summarizes the total, fossil and petroleum energy credits obtained for each unit of co-
product, and also shows the corresponding GHG emissions credit. The largest overall credit per unit of
co-product comes from xylitol, which generates total energy, fossil energy and GHG credits of 3.2
MJ/kg, 3.0 MJ/kg and 0.5 kg CO2eq/kg, respectively. The fossil energy credit obtained from protein
concentrate is 2.5 MJ per kg produced, 18% lower than that for xylitol. Protein concentrate has a lower
credit because soybean meal requires less energy to produce than beet sugar, and protein concentrate
is extracted early in the soy oil production process. The majority of the energy credit for biomass-
derived protein results from eliminating energy inputs related to soybean agricultural and crushing
activities. The energy credit from protein concentrate in AXPR is small, accounting for a reduction of
only 2% of WTP fossil energy in AXPR compared to the credit from other co-products (e.g., 18%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
DAEL DAPE AXEL AXPE AXPR AHEL AHPE AHXE AHXP
Sh
are
of
To
tal
WT
P F
oss
il E
ne
rgy
Agriculture Plant Heating/Electricity Plant Chemicals RFG Blending Transportation
62
reduction from xylitol in AHXE), due to the inherently low protein content of corn stover (approximately
5% dry basis). In the AXPR pathway, at the current plant capacity (2000 dry Mg/day), only 2260 kg/hr
of protein concentrate is produced, while net electricity generation is on the order of 25 MW for the
same ethanol process technology producing solely heat and electricity.
The credit for lignin pellets in Table 4.4 is on a primary energy basis. When compared on a secondary1
energy basis (accounting for the 32% efficiency for conversion of pellets into electricity), electricity
actually has a lower fossil energy credit than lignin pellets at 2.4 MJ/MJ vs. 3.0 MJ/MJ. Despite this, net
fossil energy consumption is still marginally greater for pathways producing lignin pellets. It is likely
that a switch to a more efficient and larger scale lignin pelletization unit than the one currently in this
study (see base case, Thek et al. [60]) would allow this pathway to match or exceed the net fossil
energy performance of an equivalent pathway solely generating electricity. Lignin pellets generate
larger fossil and GHG credits than electricity because they are assumed to displace coal, while
electricity sourced from the grid displaces a mix of fuels that is less GHG intensive.
Table 4.4 Co-product Energy and Emissions Credits Generated per Unit of Co-Producta
Co-Product Unit MJ TE/Unitb MJ FE/Unitc MJ PEd/Unit kg CO2eq/Unit
Protein
Concentrate kg 2.5 2.4 1.6 0.3
Xylitol kg 3.2 3.0 0.3 0.5
Pellet MJ LHV 0.0e 1.0 0.0 0.1
Electricity MJ Electricity 2.7 2.4 0.0 0.2 aDisplacement method is used in all calculations.
bMJ TE/Unit refers to MJ of total energy demand per unit.
cMJ FE/Unit refers to MJ of fossil energy demand per unit.
dMJ PE/Unit refers to MJ of petroleum energy demand per unit.
eCredit is insignificant so it has been rounded to zero. All zero values in this table are a result of this.
1Secondary energy refers to potential electricity produced by the lignin pellet (32% conversion assumed) to make
it comparable to the energy contained in electricity, which is already on a secondary energy basis.
63
4.1.3 Greenhouse Gas Emissions Results
Biofuels typically have been reported to have lower WTW GHG emissions than fossil fuels in part
because the feedstock is commonly assumed to be さI;ヴHラミ ミW┌デヴ;ノざ. Under this assumption, biomass-
based CO2 emissions resulting from the combustion of the feedstock and/or ethanol are assumed to be
balanced by carbon sequestration in biomass re-growth, and therefore, do not increase atmospheric
GHGs. Based on this, WTW GHG emissions for all ethanol pathways are much lower than those of the
gasoline reference pathway (Figure 4.3), similar to the trend seen with fossil energy use. Net GHG
emissions are reduced by at least 60% across all pathways. As the US Energy Independence and
Security Act of 2007 (EISA) [82] mandates at least a 60% reduction in GHG emissions for cellulosic
ethanol pathways compared with gasoline, all pathways in this work are thus acceptable routes of
production, provided that they meet the yield and process energy thresholds developed in the ASPEN
models. The AHXP and AXPE pathways have the lowest GHG emissions, due to the large GHG credit
received for lignin pellets. The GHG emissions credit in all pathways producing lignin pellets is, on
average, approximately 3.5 times larger than that for the corresponding pathways with electricity as
the co-product. As previously mentioned, this arises because lignin pellets are assumed to displace coal
where as the electricity co-product displaces grid electricity. The AXPR pathway has considerably
higher GHG emissions compared to the other AFEX pathways. This is due to a smaller co-product credit
for biomass protein, because its counterpart, soy meal, is derived from soybeans and thus already has
significant renewable content. In addition, soybeans require less nitrogen based fertilizer due to their
ability to fix nitrogen, reducing the potential to displace associated N2O emissions.
Examining xylitol co-production, it should be noted that AHXE demonstrates the largest GHG reductions
(relative to gasoline) among cases with electricity as a co-product (83%), and AHXP demonstrates the
largest reductions among cases with pellets as a co-product (140%). This would indicate that at the
current scale, producing both xylitol and electricity has a greater GHG benefit than the standard
process co-producing electricity alone, while creating a value-added product that may have financial
benefits as well. This may be partially explained by the fact that at lower ethanol yields, potential co-
ヮヴラS┌Iデ GHG IヴWSキデゲ aラヴ さWミWヴェ┞ H;ゲWSざ Iラ-products (electricity and lignin pellets) generally become
larger, while the downstream GHG emissions from ethanol are reduced. The co-product credit in the
DAEL pathway reduces 43% of total WTW GHG emissions, while the co-product credits in the AXEL and
AHEL pathways (lower ethanol yield) account for 62% and 47% of the total. At lower ethanol yields,
64
more residues are available for electricity and lignin co-products. As illustrated by these results, in all
pathways, the co-product credit has a substantial effect on GHG emissions performance.
Overall, the GHG reductions calculated in the current work for the baseline pathways (electricity
generation as sole co-product) are generally more conservative than those reported in the literature,
taking into account differences in feedstock and other key assumptions. The GHG reduction for the
DAEL pathway relative to gasoline (74%) is lower than the range reported by Wang et al. [59], who
reported reductions of 83-89% for a switchgrass-fed dilute acid conversion pathway with electricity co-
production. Some of the difference may be attributed to differences in plant modelling, and to the
lower lignin content in corn stover vs. switchgrass, resulting in more lignin for electricity co-production.
Luo et al. [19] studied corn stover using dilute acid conversion, and reported a GHG reduction of 81%,
which is also slightly greater than our DAEL result. Life cycle GHG reductions via the AXEL pathway
relative to gasoline (82%) are also somewhat lower than the values reported by Laser et al. [23], who
reported a 88-90% reduction for similar AXEL systems. However, Laser et al. [23] used consolidated
bioprocessing (CBP) (assuming a higher yield and fewer process units), a futuristic single column
distillation architecture utilizing energy saving features, and a switchgrass feed. Cherubini et al. [21]
reported only a 54% GHG reduction relative to gasoline for a corn stover autohydrolysis conversion
pathway producing ethanol, biogas and lignin phenols, which is lower than the 72-83% range reported
herein for autohydrolysis models that do not produce lignin pellets. A major difference in the work of
Cherubini et al. [21] is their assumption that corn stover removal leads to changes in soil organic
carbon, which accounts for almost 50% of their reported emissions. The GHG reductions presented in
the current study for all pathways with lignin pellet co-products are similar to those previously
documented by our research group (McKechnie et al. [22]) for similar scenarios (autohydrolysis, hybrid
poplar). In particular, both McKechnie et al. [22] and this thesis have a common result: The co-product
credit for pathways co-producing lignin pellets is approximately four times greater than the credit for
analogous pathways co-producing electricity. Also, the same co-product credit ratio is used (0.1 kg
CO2eq/MJ pellet, independently calculated). GHG emissions associated with for xylitol co-production
via the Mascoma autohydrolysis process have not been previously quantified in literature. It should be
noted that PTW (pump-to-wheel) activities typically represent at least 45% of pathway total energy use
and GHG emissions. This would indicate that some of the largest gains in energy reduction lie in
improving vehicle efficiency.
65
Figure 4.3 Well-to-Wheel GHG Emissions of Gasoline and Corn Stover-to-E85 Pathways
DAEL = DA + Electricity, DAPE = DA + Pellets, AXEL = AFEX + Electricity, AXPE = AFEX + Pellets, AXPR = AFEX +
protein & electricity, AHEL = AH + Electricity, AHPE = AH + Pellets, AHXE = AH + Xylitol & Electricity, AHXP = AH +
Xylitol & Pellets. 1Pump-to-wheel emissions are those associated with combustion of fuel during vehicle operation.
2Well-to-pump emissions.
3Net refers to the WTW emissions with the co-product emissions credit included in each pathway.
4Fuel produced refers to either gasoline or E8ヵ ヮヴラS┌IWS S┌ヴキミェ W;Iエ ヮ;デエ┘;┞げゲ ノキaW I┞IノWく Aノノ ヮ;デエ┘;┞ゲ ラデエWヴ
than gasoline produce E85.
4.2 Comparisons Between Feedstocks
This section compares results from switchgrass, hybrid poplar and corn stover with common processing
pathways. Energy use and GHG emissions results were quite different between feedstocks. The choice
of feedstock affected the agricultural stage, where different agricultural inputs and farming practices
were required. It also impacted the ethanol plant stage, where different pretreatment conditions and
sugar monomer yields affected ethanol yield. Differences in moisture content between feedstocks
additionally affected the water balance in the ethanol plant stage of each pathway.
-0.15
-0.10
-0.05
0.00
0.05
0.10
0.15
Gasoline DAEL DAPE AXEL AXPE AXPR AHEL AHPE AHXE AHXP
kg
CO
2e
q /
MJ
of
Fu
el
Pro
du
ced
4
PTW¹ WTP² Co-Product Credit Net³
66
4.2.1 Pretreatment Monomer Yields
Sugar monomer yields for each feedstock, pre-treatment and enzymatic hydrolysis combination are
presented in Table 4.5.
Table 4.5 Combined Sugar Monomer Yield for Pretreatment and Enzymatic Hydrolysis Steps by
Feedstock and Pre-treatment Type Useda
Feedstock
Pathway/Process Type
Dilute Acid Hydrolysis
Ammonia Fibre
Expansion (AFEX) Autohydrolysis
C6 C5 C6 C5 C6 C5
Corn Stover 91.0% 88.2% 91.0% 38.8% 87.2% 82.1%
Switchgrass 76.1% 77.0% 77.4% 42.2% 90.2% 90.1%
Hybrid Poplar 82.7% 59.2% 49.7% 21.7% 88.0% 85.3% aMonomer yields are based on maximum possible sugars able to be released in each category.
Autohydrolysis pre-treatment monomer yields for hybrid poplar were based on data from Mascoma
Canada Inc., while yields for other feedstocks were based on data from reports pertaining to the
Biomass Refining Consortium for Applied Fundamentals and Innovation project (CAFI, [46,47,48]). Corn
stover showed the highest (and most consistent) total sugar monomer yields in the dilute acid and AFEX
pretreatments, while hybrid poplar was among the lowest and most variable due to its recalcitrant
nature. In contrast, for the autohydrolysis case (uncatalyzed steam explosion), switchgrass had the
highest monomer yields (approximately 90% for both C6 and C5) while corn stover had lowest yields
(87% for C6, 82.1% for C5). Although CAFI experiments did not include autohydrolysis pretreatment of
hybrid poplar, they did present sugar monomer results for hybrid poplar SO2 catalyzed steam explosion.
CAFI data for SO2 explosion with hybrid poplar were similar to Mascoma Canada polysaccharide
conversions (e.g., approximately 45% hydrolysis of xylan to xylose in both cases) despite the fact that
the addition of SO2 normally improves hydrolysis. The above observations only pertain to
hemicellulose hydrolysis, as cellulose is relatively unhydrolyzed during pre-treatment for all feedstocks.
Sugar monomer yield trends from pre-treatment follow the pattern of corn stover > hybrid poplar >
switchgrass for dilute acid hydrolysis, corn stover > switchgrass > hybrid poplar for AFEX and
switchgrass > hybrid poplar > corn stover for autohydrolysis based on CAFI data [46,47,48] and previous
extrapolation (refer to Section 3.4.1.3). Although hybrid poplar was not consistently the lowest in
overall monomer yield, it did consistently require the harshest pre-treatment conditions (refer to Table
67
3.3) to achieve these yields. Of note is the fact that AFEX pre-treatment was unfavourable for hybrid
poplar (49.7% conversion of glucan) hydrolysis based on CAFI and NREL data [47,77], and that AFEX pre-
treatment in general was slightly less favourable for hydrolysis of hemicellulose to C5 sugars due to the
total reliance on enzymatic hydrolysis for hydrolysis of oligomers to monomers.
4.2.2 Ethanol Plant Stage Outputs
Outputs from the ethanol plant stage for all feedstocks and pathways are summarized in Table 4.6.
Ethanol production rates generally reflect the combined yields from pre-treatment and enzymatic
hydrolysis, as previously presented in Table 4.5; fermentation was identical across all feedstocks
sharing the same conversion pathway. However, autohydrolysis pathways with different feedstocks led
to different trends. The effect of composition on ethanol yield is apparent; the highest ethanol
production in autohydrolysis scenarios is obtained with corn stover, despite the fact that it has the
lowest monomer yield after hydrolysis of the three feedstocks (87.2% C6, 82.1% C5). Although corn
stover has a lower cellulose content than hybrid poplar, it has a higher overall sugar content. The
ethanol production in the corn stover scenario (CSAHEL) exceeds that of the hybrid poplar scenario
(225 x 106L/yr vs. 209 x 106L/yr) because the 10% higher total carbohydrate content2 in corn stover
compensates for the lower pretreatment fractional yield of sugar monomer from corn stover processed
via autohydrolysis. Average fractional monomer yield across all feedstocks when using AH
pretreatment had a lower standard deviation than other pretreatments (1.5 standard deviation for AH
vs. 7.5 and 21 for DA and AFEX respectively). In contrast, autohydrolysis pathways producing xylitol
(AHXE, AHXP) produced the most ethanol when hybrid poplar was used as the feedstock (158 x 106
L/yr). This reversal is due to the removal of xylose from ethanol production. By removing xylose (the
second largest sugar component fraction in CS and SG feedstocks, third largest in HP), the cellulose
content becomes a dominant factor in overall ethanol production. Among the three feedstocks used
for xylitol and ethanol production, hybrid poplar leads to the greatest ethanol production, with 8% and
28% greater C6 content than corn stover and switchgrass respectively. However, its xylitol production is
32% less than that from corn stover, because of the higher C5 content in corn stover.
2 Potential sugars refer to the conversion of polysaccharide containing components such as cellulose, xylan,
mannan, etc. to their potential sugar equivalents when completely hydrolyzed to monomers.
e.g., Potential Glucose = (Mass of Cellulose)/(Molecular Weight of Cellulose) x (Molecular Weight of Glucose).
68
Table 4.6 Ethanol Plant Stage Outputs for all Conversion Pathways and all Feedstocks
Dilute Acid Hydrolysis (DA)
Product Unit/yr CSDAEL SGDAEL HPDAEL CSDAPE SGDAPE HPDAPE
Ethanol (E100) 106 L 273 211 215 273 211 214
Electricity GWha 181 329 361
Lignin Pellets TJb 5711 7720 8248
Ammonia Fibre Expansion (AX)
Product Unit/yr CSAXEL SGAXEL HPAXEL CSAXPE SGAXPE HPAXPE CSAXPR SGAXPR
Ethanol (E100) 106 L 220 174 119 220 174 119 220 174
Electricity GWha 218 245 280
53 137
Lignin Pellets TJb
5965 7294 9519
Protein Concentrate 103 Mg 25 29
Autohydrolysis (AH)
Product Unit/yr CSAHEL SGAHEL HPAHEL CSAHPE SGAHPE HPAHPE
Ethanol (E100) 106 L 225 217 209 225 217 209
Electricity GWha 214 187 271
Lignin Pellets TJb 5276 5006 6478
Product Unit/yr CSAHXE SGAHXE HPAHXE CSAHXP SGAHXP HPAHXP
Ethanol (E100) 106 L 146 128 158 146 128 158
Electricity GWha 151 121 244
Lignin Pellets TJb
5258 4766 6468
Xylitol 103 Mg 111 123 75 111 123 75
aValues refer to net electricity produced by the ethanol plant after subtraction of its own electricity use.
bLower heating value used to determine energy content of lignin pellets.
CS = corn stover; SG = Switchgrass; HP = Hybrid Poplar; EL = Electricity; PE = Pellets; PR = Protein; XP = Xylitol and Pellets
69
For all pathways and conversion technologies, hybrid poplar generates the largest pellet energy value
per year (6468-9519 TJ/yr) due to its higher lignin content compared to other feedstocks. The general
trend for feedstock use and lignin pellet energy content is hybrid poplar > switchgrass > corn stover for
dilute acid hydrolysis and AFEX pathways. For autohydrolysis pathways, corn stover generates 5-10%
more pellet energy than switchgrass, but still has 23% less pellet energy than hybrid poplar. The pellet
energy content is affected by the quantity of residuals (thus impacted by ethanol yields - see Table 4.5),
and is also affected by the energy value of components in the residuals. Residues from switchgrass
contain a larger amount of extractives, which are inherently low in energy value (7.2x106 J/kg) relative
to other components such as lignin, cellulose and xylan present in residues. Generally speaking, LHVs of
unconverted sugars and unhydrolyzed polysaccharides are at least 2.2 times greater than the LHV of
extractives.
AHXP cases using switchgrass generate 11% more xylitol than corn stover. While corn stover may
possess a larger absolute amount of carbohydrates, the difference in sugars is chiefly attributed to C6
sugars which are only used for ethanol production. Switchgrass additionally has 3% more xylan than
corn stover (absolute basis), thus leading to more available xylose, and more xylitol production.
4.2.3 Energy Considerations
Different feedstocks have a considerable effect on WTW fossil energy use within the various pathways
studied, as illustrated in Figure 4.4.
70
Figure 4.4 WTW Fossil Energy Use for each Pathway by Feedstock and Conversion Technology
DAEL = DA + Electricity, DAPE = DA + Pellets, AXEL = AFEX + Electricity, AXPE = AFEX + Pellets, AXPR = AFEX +
protein & electricity, AHEL = AH + Electricity, AHPE = AH + Pellets, AHXE = AH + Xylitol & Electricity, AHXP = AH +
Xylitol & Pellets. 1NWデ ヴWaWヴゲ デラ デエW ゲ┌マ ラa ; ヮ;デエ┘;┞げゲ ヴWケ┌キヴWS WミWヴェ┞ ;ミS キデゲ Iラ-product credit. 2Fuel produced refers to E85 in ethanol pathways and RFG (reformulated gasoline) in gasoline pathway.
The same general trends appear between pathways of the same type, as discussed previously in Section
4.1.2. Ethanol plant activities are the main distinguishing factor between the various pathways, in
addition to different agricultural activities for each feedstock. The highest net fossil energy use is seen
in the AHXP pathway using switchgrass, where there is only a 28% reduction in fossil energy use relative
to gasoline. In this pathway, fossil energy is used for electrical and thermal energy in the plant, while
xylose is diverted to xylitol and lignin is converted to pellets.
The least fossil energy use is seen in the AXEL pathway using hybrid poplar, which displays a 110%
reduction. Pathways producing lower amounts of ethanol are generally capable of obtaining >100%
fossil energy reduction due to the fact that producing less ethanol would reduce the energy
requirements of the ethanol life cycle and generate greater amounts of co-products reliant on energy
contained in unused feedstock material (e.g. electricity). The net fossil energy becomes negative due to
the fact that the co-product generated is able to displace a greater amount of energy than the energy
Ga
solin
e
DA
EL
DA
PE
AX
EL
AX
PE
AX
PR
AH
EL
AH
PE
AH
XE
AH
XP
-3.0
-2.0
-1.0
0.0
1.0
2.0
3.0
MJ
of
Fo
ssil
En
erg
y /
MJ
of
Fu
el
Pro
du
ced
2
Corn Stover Switchgrass Hybrid Poplar Co-Product Credit Net¹
71
required to produce ethanol, in addition to the energy in the ethanol itself. In the case of HPAXEL, the
amount of fossil energy displaced is the primary energy of all the fossil fuels used to generate an
equivalent amount of electricity compared to that generated by hybrid poplar residues in addition to all
the energy required to extract, refine and transport those fossil fuels. Local grid electricity is generated
from many sources and also suffers from inefficiency compared to electricity from just one source (in
the case of electricity co-generation from biomass residues). Thus, the amount of fossil energy that can
be displaced is potentially even larger.
For DA and AFEX pathways, net fossil energy use was the greatest for corn stover and the lowest for
hybrid poplar. For autohydrolysis pathways, hybrid poplar has the least net life cycle fossil energy use,
while switchgrass led to the largest net fossil energy use among the three feedstocks, due the lower
heating value of residues used in biomass combustion. Net fossil energy reductions relative to gasoline
for autohydrolysis pathways were approximately 26% greater when using hybrid poplar than
switchgrass on average. The quantity and lignin content of the ethanol plant residues has a major
influence on the yield of electricity or lignin pellets, and thus, the feedstock with the largest lignin
content typically generated the largest co-product credit. Low hydrolysis and fermentation yields also
increased the magnitude of the co-product credit. These conditions also led to the lowest fossil energy
use overall, as the residues are a renewable source of energy, thereby displacing fossil fuels. Less
energy is required for direct combustion of lignocellulosic feedstocks than for transformation of
biomass into ethanol, although the economic value of ethanol and overall demand for liquid
transportation fuels dictates that this transformation has value, in spite of the higher energy demand.
In pathways using hybrid poplar, the fossil energy credit reduces the fossil energy requirement by 99%
(on average) when using dilute acid hydrolysis or AFEX pretreatments. The average reduction is only
78% when considering autohydrolysis pathways. Other feedstocks have lower co-product credits
relative to their actual energy requirements; co-product credits for corn stover and switchgrass amount
to 47% and 70% of their fossil energy demand in DA and AFEX cases, and 61% and 56%, respectively, in
AH cases. This would indicate that less of the energy in hybrid poplar is converted into the main
ethanol product, and more is allocated to co-products, for which it receives substantial co-product
credits. This is a natural outcome of a feedstock with a higher lignin content. Higher co-product credits
are indicative of less energy being transferred to the primary product when only energy based co-
products (electricity, lignin pellets) are generated. This is not necessarily true however, when non-
energy replacing co-products are generated (e.g., protein, xylitol). In these cases such as AHXE and
AHXP, a low amount of feedstock energy can potentially be used to displace a large amount of energy
72
and thus generate a large co-product credit. This is because these co-products can be compared to
products in industry on a non-WミWヴェ┞ H;ゲキゲ ゲ┌Iエ ;ゲ さゲ┘WWデミWゲゲざ ラヴ マ;ゲゲく TエWラヴWデキI;ノノ┞, the best case
scenario for energy use would be if ethanol production is minimized and the co-product displaces an
energy-intensive industry equivalent. This is at least partially true for xylitol in this work, as its co-
production substantially lowers ethanol yields (as previously mentioned in section 4.1.1), and displaces
a large amount of energy. This is untrue however, of protein concentrate, which replaces an industry
equivalent product (soy meal) that has a low fossil energy demand, and does not affect ethanol yield.
Although the main differences in net fossil energy use shown in Figure 4.4 occur from ethanol plant
activities, notable differences in the agricultural activities common to each pathway arise when
comparing different feedstocks. As the agricultural activities in each pathway were identical for
pathways using the same feedstock, the aggregated energy results for each feedstock are summarized
in Table 4.7.
Table 4.7 Life Cycle Fossil Energy Use for Agricultural Activities by Feedstock
Agricultural Activity Fossil Energy Use (MJ / Mg Output)
Corn Stover Switchgrass Hybrid Poplar
Fertilizers1 348 573 44
Pesticides 0 9 8
Farm equipment
operation and Other2 316 327 348 1Feedstock energy use associated with fertilizers refers to energy used in producing, transporting and applying the
fertilizer to produce the feedstock. In the case of corn stover (agricultural residue), this only encompasses
additional fertilizer needed to make up for lost nutrients when corn stover is removed from the land for use in
ethanol production. Pesticide use for stover was zero due to the fact that pesticide use during the actual
cultivation of corn (and stover) was allocated completely to corn in GREET 1.8d.1 [30]. 2Includes fossil energy (primarily diesel fuel) required to operate farm machinery required to till, grow and
harvest/collect the feedstock among other agricultural activities. Only includes harvesting/collection activities for
corn stover.
Switchgrass has the highest agricultural fossil energy use (37% higher than corn stover, 127% higher
than hybrid poplar), the lowest absolute amount of potential sugars (8% lower than corn stover, 0.1%
lower than hybrid poplar), and the lowest cellulose content (approximately 4% and 8% lower than corn
stover and hybrid poplar, respectively).
73
4.2.4 Greenhouse Gas Emissions Considerations
The type of feedstocks and process pathways had a significant effect on GHG emissions profiles due to
the different compositions of the feedstocks and differences in their ease of processing. WTW GHG
emissions are disaggregated in this section to show CH4 and N2O emissions, as presented in Figure 4.5
and Figure 4.6, respectively.
Figure 4.5 Net Well-to-Wheel Methane Emissions by Conversion Pathway and Feedstock
Figure 4.6 Net Well-to-Wheel Nitrous Oxide Emissions by Conversion Pathway and Feedstock
-0.10
-0.05
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
Gasoline DAEL DAPE AXEL AXPE AXPR AHEL AHPE AHXE AHXP
g C
H4 /
MJ
Eth
an
ol
Fu
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Pro
du
ced
Corn Stover Switchgrass Hybrid Poplar
0.00
0.01
0.02
0.03
0.04
0.05
0.06
0.07
Gasoline DAEL DAPE AXEL AXPE AXPR AHEL AHPE AHXE AHXP
g N
2O
/ M
J E
tha
no
l F
ue
l P
rod
uce
d Corn Stover Switchgrass Hybrid Poplar
74
Compared to the gasoline reference pathway, WTW CH4 emissions for the E85 pathways are lower for
non-lignin pellet producing pathways and higher for lignin pellet co-producing pathways. For the
majority of pathways utilization of switchgrass led to the highest methane emissions (up to 219%
increase relative to gasoline) while utilization of hybrid poplar had the lowest emissions (a 134%
reduction relative to gasoline).
Pathways producing lignin pellets had at least 61% greater CH4 emissions per MJ of fuel produced,
when compared to gasoline. In contrast, pathways with electricity as a co-product (alone or
simultaneously with another co-product) reduced CH4 emissions by at least 52% relative to gasoline.
This can be partially explained by the fact that co-produced lignin pellets are ultimately combusted to
produce electricity while displacing coal, which is also combusted (refer to lignin pellet co-product
credit calculation in Appendix A3). CH4 emissions credits from displacing coal were mitigated by CH4
emissions released from actual lignin pellet combustion. While the carbon neutrality assumption
associated with biomass related emissions applies to CO2 emissions, it does not apply to other GHGs,
and thus, CH4 emissions from pellet combustion were not reduced by this. The use of natural gas for
plant heating in pathways producing lignin pellets (other pathways were self-sufficient in plant heating
and electricity) also increased CH4 emissions compared to pathways using solid biomass residues to
supply the energy for the ethanol plant.
Compared to the gasoline reference pathway, WTW N2O emissions for the E85 pathways are generally
substantially larger when switchgrass feedstock is used. Switchgrass had the highest N2O emissions (at
least 713% increase relative to gasoline) while corn stover had the lowest emissions for the majority of
pathways (at most a 79% decrease in emissions relative to gasoline). Hybrid poplar still remained
competitive to corn stover in pathways producing only electricity. Pathways producing lignin pellets
generally had higher N2O emissions than pathways producing electricity.
High N2O emissions from switchgrass feedstock arises from higher nitrogen/fertilizer inputs during
feedstock production, and to a lesser extent, the release of nitrogen when biomass residues are
burned. For all pathways, N2O release (due to nitrification and denitrification effects associated with
nitrogen-based fertilizer use) contributes between 18-90% of WTW N2O emissions, depending on the
feedstock used. In particular, use of switchgrass results in extremely large N2O emissions due to the
high amount of nitrogen fertilizer used relative to other feedstocks (2.4 times larger requirement than
corn stover, 15 times larger than hybrid poplar). Although hybrid poplar uses less nitrogen-based
fertilizer than corn stover during its production, in pathways where xylitol is a co-product, its net N2O
75
emissions exceed those from pathways using corn stover, because stover can produce less xylitol and
create a larger N2O emissions credit from emissions displaced during sugar beet production (0.3 g N2O
displaced per kg xylitol).
Similar to CH4 emissions, the greater N2O emissions during lignin pellet co-production can be partially
explained by the fact that is released to the atmosphere compared to when combusting coal (the
product it displaces), because of the nitrogen in the biomass and its lower energy density (coal is of the
bituminous variety). An N2O penalty is actually returned per unit of pellet LHV (0.009 g N2O / MJ pellet)
instead of a credit, due to N2O emissions from pellet combustion being greater than those from coal
combustion. It should be noted that although the relative difference between WTW N2O emissions
from gasoline pathways and ethanol pathways appears large, the absolute difference is much smaller
than those seen in WTW CH4 emissions.
Greenhouse gas emissions (GHGs) for pathways employing multiple feedstocks are summarized in
Figure 4.7. Life cycle net GHG trends generally mirror those seen for life cycle fossil energy use, as
discussed in Section 4.2.3.
76
Figure 4.7 Well-to-wheel Greenhouse Gas Emissions by Conversion Pathway and Feedstock
DAEL = DA + Electricity, DAPE = DA + Pellets, AXEL = AFEX + Electricity, AXPE = AFEX + Pellets, AXPR = AFEX +
protein & electricity, AHEL = AH + Electricity, AHPE = AH + Pellets, AHXE = AH + Xylitol & Electricity, AHXP = AH +
Xylitol & Pellets. 1Net refers to the sum of a pathway`s GHG emissions and its associated co-product credit.
2Fuel produced refers to E85 in ethanol pathways and RFG (reformulated gasoline) in gasoline pathway.
Compared to the gasoline reference pathway, all E85 pathways reduce WTW GHG emissions by
between 60% (CSAXPR) to 288% (HPAXPE). Except for AXPR pathways and pathways producing
electricity using corn stover and switchgrass, WTW emissions are generally negative due to the
influence of co-product credits. Use of hybrid poplar resulted in the lowest net GHG emissions of any
pathway. All pathways and all feedstocks generated GHG emissions reductions greater than the 60%
threshold stipulated for cellulosic biofuels under the EISA mandate [82].
Corn stover leads to the smallest net GHG reductions for the DA and AFEX pathways, at 60% (AXPR) and
121% (AXPE). For the autohydrolysis pathway, switchgrass generates reductions of 70% (AHEL) and
134% (AHXP) relative to gasoline. Use of hybrid poplar led to the largest reductions of any pathway,
ranging from 103% (AHEL) to 288% (AXPE). In addition generating a large co-product credit, the
effectiveness of hybrid poplar in reducing GHGs can also be attributed to a larger direct land use
Ga
solin
e
DA
EL
DA
PE
AX
EL
AX
PE
AX
PR
AH
EL
AH
PE
AH
XE
AH
XP
-0.3
-0.25
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
kg
CO
2e
q /
MJ
of
Fu
el
Pro
du
ced
2
Corn Stover Switchgrass Hybrid Poplar Co-Product Credit Net¹
77
change credit than the other feedstocks (124,010 gCO2/Mg dry hybrid poplar vs. 53,462 gCO2/Mg dry
switchgrass and 0 gCO2/Mg dry corn stover).
A notable observation is that the AHXP pathway had the greatest GHG reductions relative to gasoline
(approximately 100% greater than the next highest pathway AXPE) when considering corn stover, but
only the second highest in reduction in GHG emissions when using hybrid poplar. This can be
attributed to the fact that although use of hybrid poplar generally resulted in a higher co-product credit
across all pathways (and thus lower emissions), AFEX pre-treatment was especially ineffective in
hydrolyzing hybrid poplar, compared to the other pretreatments. While this led to the lowest ethanol
production rates of any pathway at 119 x 106 L/yr, it also produced the most co-product as only 30% of
the energy in the hybrid poplar was used to create ethanol. While the overall decrease in GHG
Wマキゲゲキラミゲ キゲ ェWミWヴ;ノノ┞ ; ヮラゲキデキ┗W WaaWIデ ふノキニWノ┞ S┌W デラ デエW a;Iデ デエ;デ デエW さWミWヴェ┞ざ Iラ-products themselves
are a more efficient use of energy and a more environmental option overall compared to the primary
product), less than 50% of the feedstock energy being present in the primary product is likely
impractical.
4.3 Non-Greenhouse Gas Emissions
Figure 4.8 summarizes the net WTW emissions of non-GHG compounds. Carbon monoxide is the largest
emission produced by every life cycle pathway, followed by NOx and non-methane volatile organic
compounds (NMVOCs). Emissions are generally higher for pathways producing lignin pellets and lower
for pathways producing electricity, similar to trends seen in Section 4.2.4. Pathways producing lignin
pellets also led to particulate matter and SOx emissions reductions greater than 100% relative to
gasoline.
The range of CO emissions among all pathways is 0.78-0.95 g CO/MJ E85 produced, which is similar to
the reference gasoline pathway (0.91 g CO/MJ gasoline produced). The majority of CO emissions can
be attributed to incomplete combustion of the E85 fuel in the vehicle life cycle stage. Across all
pathways, the amount of net CO released to the atmosphere is approximately 11 times larger during
the PTW (pump-to-wheel) stage compared to its corresponding WTP stage. CO typically contributes to
the formation of smog and ground level ozone; improvement in the efficiency of internal combustion
engines would reduce these emissions. The next largest net emissions among the various pathways are
from NOx and non-methane volatile organic compounds. Combustion of biomass is known for
78
generating greater NOx and NMVOC emissions due to the greater diversity of compounds involved,
generally higher nitrogen content and lower energy density than fossil fuels. Compared to the
reference gasoline pathway, all pathways had at least 124% and 38% greater net NOx and NMVOC
emissions, respectively. The pathways with the lowest net NOx emissions were the ones employing DA,
while AFEX and Autohydrolysis were among the highest (557% and 555% increases relative to gasoline
for both SGAXPE and SGAHPE, respectively). In DA cases, lower NOz emissions are attributed to
removal of nitrogen containing components by overliming, leading to solid waste removal (gypsum),
combined with the lower amount of waste residues combusted (due to higher ethanol yields). Higher
ethanol yields affect NOx emissions because these emissions are scaled from the lower heating value of
the fuel being combusted, according to the U.S. Environmental Protection Agency (EPA) emissions
factors used in GREET 1.8d [30]. Net life cycle NOx emissions were greater (at least an 18% increase)
when switching from an electricity co-generating pathway to a lignin pellet co-product pathway. This
was due to the fact that displacing coal actually imposes a life cycle NOx penalty, rather than a credit of
0.02 g NOx per MJ of E85 produced, because biomass has a higher NOx emission rate than coal during
combustion (however it is acknowledged that more sophisticated NOx control systems than those
employed by EPA emissions factors may be able to largely mitigate biomass NOx). A penalty of 0.04 g
CO per MJ of E85 produced also exists for similar reasons. Thus, an emissions tradeoff exists when
producing lignin pellets, which offer a reduction in GHG emissions at the cost of an increase in the
emissions of species such as NOx and CO. Considering SOx emissions, DA cases produced the largest net
emissions per MJ of fuel produced (highest: SGDAEL, 980% higher than gasoline reference) due to the
use of sulfuric acid.
Among different feedstocks, switchgrass had the highest SOx and NOx emissions in the majority of
pathways. This is likely due to the high protein content and the high extractives content (both nitrogen
containing species) in switchgrass. Hybrid poplar as used in the HPAXPE case achieved the lowest net
emissions of particulate matter and SOx, mainly due to a large lignin pellet credit. Differences in all
emissions when employing xylitol co-production vs. solely generating electricity were not substantial.
The largest difference was in net NMVOC emissions which increased by 10% on average in pathways
producing xylitol.
79
Figure 4.8 Net Well-to-Wheel Non-Greenhouse Gas Emissions by Pathway
-0.40
0.10
0.60
1.10
Gasoline CSDAEL CSDAPE CSAXEL CSAXPE CSAXPR CSAHEL CSAHPE CSAHXE CSAHXP
g E
mis
sio
n /
MJ
of
Fu
el
NMVOC CO NOx PM10 PM2.5 SOx
-0.40
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1.10
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g E
mis
sio
n /
MJ
of
Fu
el
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g E
mis
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n /
MJ
of
Fu
el
80
4.4 Water Use
As previously stated in Section 2.3.1, water is consumed in lignocellulose hydrolysis reactions, but may
also be lost due to cooling tower losses. Thus, a typical ethanol plant co-producing electricity would
consume water in order to maintain operation. Water requirements for the ethanol plant stage of all
pathways are presented in Figure 4.9 for all feedstocks, on a per MJ of ethanol fuel (E100 due to only
the ethanol plant stage being examined) produced basis.
Figure 4.9 Ethanol Plant Stage Water Requirement for all Conversion Pathways and Feedstocks
Due to the nature of biomass, feedstocks generally reach the ethanol plant stage with a high water
content, and consequently, feedstocks with higher initial moisture will theoretically lower the water
requirement of the ethanol plant. Hybrid poplar has the largest advantage in that it typically has
approximately 50% moisture content when entering the ethanol plant. As illustrated in Figure 4.9
however, the actual configuration of the plant has an appreciable effect on the final water use, mainly
due to differences in pre-treatment conditions. Although hybrid poplar has the lowest water use in DA
and AH pathways (11-50% lower relative to using corn stover for DA), it had 91-99% higher water use
than corn stover when used in AFEX pathways. The extra water use in AFEX pathways for switchgrass
and hybrid poplar relative to corn stover is tied to the much higher water to biomass ratios (60% water
to dry corn stover vs >200% water to dry biomass for switchgrass and hybrid poplar, refer to Table 3.3)
0.00
0.10
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0.30
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DAEL DAPE AXEL AXPE AXPR AHEL AHPE AHXE AHXP
L H
2O
/ M
J o
f E
10
0 F
ue
l
Corn Stover Switchgrass Hybrid Poplar
81
required for these feedstocks in AFEX pre-treatment to achieve the listed sugar monomer yields (a clear
disadvantage). Although switchgrass has a higher moisture content than corn stover (25% vs. 15%,
respectively), use of switchgrass resulted in consistently higher water requirements than corn stover for
the DA and autohydrolysis conversion pathways (6% higher water requirements than when using corn
stover on average). The lower ethanol production from switchgrass was the main contributor to this
increase in water use. The general increase in water use for xylitol co-producing pathways vs. non-
xylitol co-producing pathways employing autohydrolysis is due to the substantial increase from
chromatographic separation to isolate xylose and xylitol (using water as a solvent). In contrast,
pathways co-producing lignin pellets saw a general decrease in water use of 20-44% vs. base pathways
(electricity co-generation only) of the same type for corn stover and switchgrass feedstocks. Even less
water was required 30 to 68% less than base pathways for lignin pellet co-production pathways
using hybrid poplar, due to the considerably higher water content of poplar. Pathways producing lignin
pellet include extraction and recycling of the water recovered during pellet drying operations. Pathways
co-producing protein concentrate required slightly more water than their corresponding base
conversion pathways (AXEL), due to water required for the protein extraction columns, ultrafiltration,
diafiltration and filter press unit operations. The difference in water use between AXPR and AXEL
pathways was only 3-6%, due to recycling of water evaporated from spray dryers used dry the protein
concentrate.
4.5 Ethanol Plant Waste
Ethanol plants generated little solid waste, regardless of conversion technology or feedstock with the
exception of the DA pathways. In DA and AFEX pathways, feedstock washing was performed prior to
pretreatment of the lignocellulosic material to remove dirt and other impurities. However,
components such as dirt were not explicitly modelled, and thus this waste stream was only represented
as wash water to wastewater treatment. In AH pathways, fiber cleaning by air-density separation and
screening leads to losses of fines and dirt entrained in the air stream leaving cyclones or retained on
fiber screens. These oversized and undersized fibers were sent to combustion (or pelletization) instead
of solid waste handling. Thus, the main solid waste resulting from all modelled ethanol plants is
attributed to gypsum removal in DA pathways and ash removal in all pathways except those co-
producing lignin pellets.
82
Gypsum waste streams from DA pathways are summarized in Table 4.8. Different co-product strategies
did not affect gypsum waste streams, as gypsum is removed in an upstream operation directly after
overliming. However, the composition of the waste stream still varies by feedstock. Sugar-containing
components are also lost in the gypsum stream; however, losses only represent approximately 0.5% of
the theoretical ethanol maximum from each feedstock. For corn stover, switchgrass and hybrid poplar
feedstocks, approximately 0.05 kg/kg DBM3, 0.07 kg/kg DBM and 0.1 kg/kg DBM of gypsum is sent to
solid waste disposal, respectively. More gypsum waste occurred in the various feedstocks mainly due
to differences in sulfuric acid loading (HP>SG>CS) followed by differences in acetate content (hybrid
poplar having the highest content). Higher actetate content and sulfuric acid loading caused decreases
in pH. Composition of the gypsum waste differed substantially according to differences in composition
and pretreatment hydrolysis of monomers. Increased water content and decreased ash content was
due to hybrid poplar having the highest initial moisture and lowest ash content respectively. Similar
reasoning can be applied to the increase in lignin when using hybrid poplar relative to other feedstocks.
Table 4.8 Composition of Gypsum Waste Stream from Dilute Acid Hydrolysis Pathways by Feedstock
Component Pathway (kg/hr @ 2000 Mg DBM
a / day)
Corn Stover Switchgrass Hybrid Poplar
Gypsum 3872 5627 8426
Polysaccharides 160 158 167
Lignin 74 79 113
Monomers 76. 83 138
Water 895 1279 1925
Ash 22 22 7
Other 53 90 111
Total 5151.74 7338.05 10886.63 aValues in table are in kg/hr and refer to the amounts generated from a constant input of 2000 Mg of dry biomass
feedstock per day (default plant capacity). DBM refers to dry biomass.
Gypsum not collected in filter press operations after overliming will ultimately be collected in the
bottoms of the plant combustor, along with ash and other un-combusted materials. In scenarios
generating lignin pellets, uncaptured gypsum ends up in the pellets, where it lowers the heating value
of the pellets by <0.01% MJ/kg. On average, approximately 98% of the ash originally present in the
feedstock is emitted from the combustor as ash and flyash, along with other un-combusted material
such as lignin.
3 DBM refers to dry biomass
83
4.6 Low Ethanol Yield Scenarios
High and low overall ethanol yields from pre-treatment, enzymatic hydrolysis and fermentation
combinations have historically been used for sensitivity analyses in life cycle studies (including
uncertainty in actual ethanol plant design decisions). Ethanol yield from fermentation has a significant
impact on plant energy use, emissions and economics [8], and is therefore appropriate for sensitivity
analysis. High and low yield scenarios have been used in this study in a manner similar to in [22]. The
high yield scenario corresponds to the default scenario presented thus far, and represents a condition
whereby all C6 (glucose, mannose, galactose) and C5 (xylose, arabinose) sugars have been fermented
with the same effectiveness as glucose and xylose. The low yield scenario in this thesis corresponds to
a condition where only glucose is fermentable. The effect of yield was only examined for corn stover; it
was assumed that trends/impacts from yield changes with corn stover would likewise apply to other
feedstocks. The results from the C6-only low yield scenario with corn stover are presented in the
following subsections, and compared to results from the high yield scenario (in which all available C6
and C5 sugars are fermented) presented thus far.
4.6.1 Fossil Energy
Fossil energy use is summarized for high and low yield scenarios in Figure 4.10. As noted previously,
fossil energy (and total energy) use is influenced by a combination of factors, including energy demand
for the ethanol process itself, energy demand for co-products, and the amount of energy generated
internally from combustion of residues. A lower ethanol yield may drive up ethanol process energy
demands, but will also generate more residues, which can be used to generate process energy or other
co-products that can displace energy-intensive products.
Ethanol distillation is the largest single energy draw for any pathway studied in this work. Ethanol yields
affect distillation energy because lower ethanol titers in fermentation require more distillation energy
to remove water and generate the purified ethanol product.
The second largest energy demand is for evaporation, either for drying of leftover fermentation
residues before combustion or pelletization, or for concentration of co-products, e.g., as part of
chromatographic separation processes in pathways to convert xylose into xylitol.
84
Figure 4.10 Well-to-Wheel Fossil Energy Use for High and Low Ethanol Yield Scenarios using Corn Stover
Feedstock by Conversion Pathway
DAEL = DA + Electricity, DAPE = DA + Pellets, AXEL = AFEX + Electricity, AXPE = AFEX + Pellets, AXPR = AFEX +
protein & electricity, AHEL = AH + Electricity, AHPE = AH + Pellets, AHXE = AH + Xylitol & Electricity, AHXP = AH +
Xylitol & Pellets. 1High yield scenario refers to scenario where all sugars (C6 and C5) are fermented to ethanol in each pathway.
2Low yield scenario refers to scenario where only glucose is fermentable.
3NWデ WミWヴェ┞ ヴWaWヴゲ デラ デエW ゲ┌マ ラa ; ヮ;デエ┘;┞げゲ ヴWケ┌キヴWS WミWヴェ┞ ;ミS キデゲ Iラ-product credit.
Aノノ さノラ┘ ┞キWノSざ ヮ;デエ┘;┞ゲ ノWS デラ ; ヶヴХ ;┗Wヴ;ェW SWIヴW;ゲW キミ ミWデ aラゲゲキノ WミWヴェ┞ ┌ゲW Iラマヮ;ヴWS デラ
corresponding pathways with a high ethanol yield. This decrease was mainly the result of a
substantially greater co-product credit (approximately 100% average increase). Lower ethanol yields
considerably increase the amount of residues diverted to co-product streams. In general, high yield
scenario pathways with higher ethanol production rates led to the greatest decreases in net fossil
energy when the low yield scenario was applied, due to greater potential quantities of additional co-
product generated when the yield was reduced.
When comparing high yield scenarios vs. low yield scenarios, base cases producing electricity saw a
small change in actual non-net fossil energy requirements (13% higher on average) due to the fact that
Ga
solin
e
DA
EL
DA
PE
AX
EL
AX
PE
AX
PR
AH
EL
AH
PE
AH
XE
AH
XP
-2.0
-1.5
-1.0
-0.5
0.0
0.5
1.0
1.5
2.0
2.5
MJ
of
En
erg
y /
MJ
of
Fu
el
Pro
du
ced
Co-Product Credit High Yield¹ Low Yield² Net³
85
energy required in distillation and evaporation of leftover residues only slightly increased (6% and 10%
higher respectively for DAEL). However, the majority of pathways with lignin pellet co-production saw
greater increases in fossil energy requirements due to the much larger amount of energy required to
dry residues to the 15% pellet moisture specification. In the case of the low yield DAPE pathway, 66%
more pellet drying energy was required, commensurate with the greater quantity of pellets generated.
A yield reduction had the smallest impact on net fossil energy for the xylitol pathways, because these
scenarios already focus on C6 fermentation, even in the high yield cases. The net fossil energy impact
was 4% for the AHXE and 7% for the AHXP pathway. Yield had the greatest impact on the AHEL
pathway, with a 143% decrease in fossil energy in the low yield scenario compared to the baseline high
yield scenario. This is due to the large co-product credit from the additional electricity generated from
fermentation residues.
4.6.2 Greenhouse Gas Emissions
As illustrated in Figure 4.11, trends for GHG emissions in the high and low yield scenarios are similar to
those observed for fossil energy. When comparing the absolute emissions of the low yield scenario
relative to the high yield one, GHG emissions generally decrease. DA and AH pathways producing
either electricity or pellets show the largest decreases in GHG emissions. The low yield DAPE scenario
has a 14-fold decrease in net GHG emissions relative to the high yield scenario, because dilute acid
pretreatment has the largest yield of C5-derived ethanol among the pre-treatment. This C5-derived
production is lost in the low-yield scenario, and with only glucose fermentation, C5 sugars are directed
to co-product generation. Pellet co-product pathways magnify the effect because of the larger kg CO2eq
credit for pellets compared to electricity (Table 4.4). There is little difference in GHG emissions from
the low yield and high yield pathways with xylitol as a co-product, because neither scenario ferments
C5 sugars. Similarly, the production of protein concentrate in the AXPR pathway is unaffected by
changes in fermentation, and thus, the 21% difference between the high and low yield scenarios is due
to additional electricity co-ェWミWヴ;デWS キミ デエW ノラ┘ ┞キWノS I;ゲWく O┗Wヴ;ノノが さミラミ-WミWヴェ┞ざ Iラ-products such as
xylitol and protein concentrate are relatively unaffected by changes in ethanol yield. McKechnie et al.
[22] observed a similar reduction in net GHG emissions when the ethanol yield was reduced.
86
Figure 4.11 WTW Greenhouse Gas Emissions for High and Low Yield Scenarios using Corn Stover
Feedstock by Conversion Pathway
DAEL = DA + Electricity, DAPE = DA + Pellets, AXEL = AFEX + Electricity, AXPE = AFEX + Pellets, AXPR = AFEX +
protein & electricity, AHEL = AH + Electricity, AHPE = AH + Pellets, AHXE = AH + Xylitol & Electricity, AHXP = AH +
Xylitol & Pellets. 1High yield scenario refers to scenario where all sugars (C6 and C5) are fermented to ethanol in each pathway.
2Low yield scenario refers to scenario where only glucose is fermentable.
3NWデ ヴWaWヴゲ デラ デエW ゲ┌マ ラa ; ヮ;デエ┘;┞げゲ ヴWケ┌キヴWS GHG Wマキゲゲキラミゲ ;ミS キデゲ Iラ-product credit.
Ga
solin
e
DA
EL
DA
PE
AX
EL
AX
PE
AX
PR
AH
EL
AH
PE
AH
XE
AH
XP
-0.2
-0.15
-0.1
-0.05
0
0.05
0.1
0.15
kg
CO
2e
q /
MJ
of
EtO
H P
rod
uce
d
Co-Product Credit High Yield¹ Low Yield² Net³
87
5. Conclusions
5.1 Summary
This thesis involved the construction and analysis of 26 well-to-wheel pathways for future US midwest
lignocellulosic lignocellulose-to-ethanol systems. Three different feedstocks and pretreatment
technologies were considered:
CS - corn stover, SG - switchgrass, HP - hybrid poplar
DA - dilute acid, AFEX - ammonia fibre expansion and AH - autohydrolysis.
Four different co-product options were also considered: electricity, lignin pellets, protein concentrate,
and xylitol. The ethanol was blended with gasoline and used as E85 in a flexible fuel E85 internal
combustion engine light-duty vehicle.
Aspen Plus models from the National Renewable Energy Laboratory, Dartmouth College and Mascoma
Canada Inc. were modified to create in-depth process models of each of the biorefineries involved,
using publicly available and proprietary data. GREET 1.8d.1 [30] was also used to model factors
external to the ethanol plant for the year 2015. The system expansion method was used to treat co-
product emissions and energy use, assuming Midwest U.S. electricity, coal, soybean meal and sugar
beet-derived sugar as displaced products. The various ethanol pre-treatment technologies and their
associated co-products led to different ethanol yields (163-374 L/ dry Mg feedstock). In most process
pathways, corn stover led to the greatest ethanol yields. In the process involving autohydrolysis with
xylitol as a co-product, hybrid poplar led to the highest ethanol yield, but corn stover led to the greatest
xylitol yield, due to its higher C5 content. Otherwise, the lowest ethanol yields (163 L/ dry Mg) were
generally obtained with hybrid poplar, which proved more resistant to the majority of pretreatments
(most notably ammonia fibre expansion, AFEX) than other feedstocks.
When comparing conversion technologies and co-production strategies for a single feedstock (corn
stover), WTW results predicted that all pathways would be able to reduce fossil energy use by at least
47% and greenhouse gas (GHG) emissions by at least 60% when compared to a gasoline reference
pathway. The 60% reduction in GHG emissions is the minimum standard for cellulosic biofuels
mandated by the US 2007 Energy Independence and Security Act (EISA) [82]. Thus, under the
conditions and yields modeled, all ethanol pathways would meet the EISA standard. The corn stover
88
pathway co-producing protein and electricity reduced GHG emissions by 60%, and therefore would be
likely to fall afoul of the EISA specification if process energy demands were greater or yields were
reduced. Ethanol production accompanied by production of lignin pellets via the dilute acid, AFEX and
autohydrolysis pre-treatment pathways predicts, respectively, GHG reductions of 105, 121 and 107%
relative to the gasoline reference pathway. Ethanol production with xylitol and lignin pellet co-products
led to the greatest GHG emissions reduction (140% relative to gasoline), while producing electricity as
the co-product had the lowest net fossil energy use (80% less than gasoline pathway), because the
ethanol plant does not require outside sources of electrical or thermal energy. Ethanol production with
xylitol and electricity as co-products also had a high fossil energy reduction, 77% reduction compared to
gasoline. Considerable WTW GHG reductions were also observed (72-140%) for pathways with xylitol as
a co-product. Xylitol co-ヮヴラS┌Iデキラミ ゲIWミ;ヴキラゲ ;ヴW ;HノW デラ デ;ニW ;S┗;ミデ;ェW ラa ┝┞ノキデラノげゲ ノ;ヴェW aラゲゲキノ WミWヴェ┞
use credit and GHG credit while leading to only a 19% reduction in co-generated electricity when
compared to pathways without xylitol co-production. However, co-production of xylitol reduced the
ethanol yield by 35% compared to similar cases not producing xylitol. An economic analysis is needed
to further verify the value of this trade-off.
Energy and GHG credits per unit of co-product were calculated independently of the pathways studied,
based on the life cycle of each co-product. Lignin pellets (on a secondary energy basis4) have larger
fossil energy and GHG emissions credits than electricity. on a MJ of co-product produced basis (fossil
energy: 2.95 vs. 2.43; GHG emissions: 0.30 vs. 0.22). This is due to assumptions regarding the fuels
displaced (coal in the pellet cases and the average Midwest grid mix in electricity cases) and their
associated carbon intensities. Xylitol had larger fossil energy and GHG credits than protein
concentrate (2.95 MJ/kg and 0.51 kg CO2eq/kg respectively), because sugar from sugar beets is more
WミWヴェ┞ キミデWミゲキ┗W デラ マ;ミ┌a;Iデ┌ヴW デエ;ミ ゲラ┞ マW;ノく Iミ ェWミWヴ;ノが ヮヴラS┌Iキミェ さミラミ-WミWヴェ┞ざ Iラ-products such
as xylitol and protein concentrate led to a higher net total energy demand for their overall pathways
compared to co-producing only electricity.
Based on the data available, corn stover was generally the most hydrolysable feedstock, with most
pretreatments well adapted to producing high monomer yields (>85% C6 monomer yield for all
pretreatments and between 21.7 to 90.1% C5 monomer yield) ). Overall plant ethanol yields were
CS>HP> SG for dilute acid, CS>SG>HP for AFEX, and CS>SG>HP for autohydrolysis. Feedstock
4 Secondary energy refers to potential electricity produced by the lignin pellet (32% conversion assumed) to make
it comparable to the energy contained in electricity, which is already on a secondary energy basis.
89
composition had ; ノ;ヴェW キマヮ;Iデ ラミ ┞キWノSゲき Iラヴミ ゲデラ┗Wヴげゲ エキェエWヴ I;ヴHラエ┞Sヴ;デW IラミデWミデ ェWミWヴ;ノノ┞ a;┗ラヴWS
its conversion into ethanol or other carbohydrate derived co-products such as xylitol. In AH pathways
co-producing xylitol, hybrid poplar (HP) generated the greatest ethanol yield, followed by corn stover
and switchgrass. The greater C6 content of poplar enhanced ethanol production, while the greater C5
content of stover enhanced xylitol production. Directing C5/xylose to xylitol reduced ethanol yields by
35%, 41% and 24% for corn stover, switchgrass and hybrid poplar respectively. Pathways using hybrid
poplar produced the most electricity and lignin pellets, regardless of conversion technology, due to a
higher lignin content in hybrid poplar. Electricity yields using poplar were 42% and 54% more on
average than for CS and SG respectively, while lignin pellet yields were, on average, 26% and 37%
greater than for CS and SG respectively. Conversely, hybrid poplar produced the least amount of
xylitol, due to its lower C5 sugar content.
Among the feedstock, process and co-product combinations considered, switchgrass processed using
autohydrolysis generating xylitol and lignin pellets had only a 28% fossil energy reduction relative to
gasoline. In contrast, the greatest reduction in fossil energy use was achieved with hybrid poplar
processing using AFEX, with electricity as a co-product (110% relative to gasoline). For the dilute acid
and AFEX pathways, net fossil energy use was generally greatest for corn stover and lowest for hybrid
poplar. Net fossil energy reduction relative to gasoline was approximately 35% greater for hybrid
poplar relative to CS on average in DA and AFEX pathways. Switchgrass generally had the greatest fossil
energy use in AH pathways; the fossil energy reduction from poplar was 26% greater on average than
for switchgrass in AH pathways. The majority of the fossil energy reduction attributed to the use of
hybrid poplar is from increased production of co-products, which mitigate net fossil energy use through
credits. Different feedstocks also led to substantial differences in fossil energy use during feedstock
production (agriculture and/or collection). Switchgrass production required 37% more fossil energy
than corn stover production and 127% more fossil energy than hybrid poplar production, while yielding
the lowest amount of total carbohydrate and the lowest cellulose content.
Methane emissions are reduced by at least 52% relative to gasoline for any pathway producing
electricity (alone or simultaneously with another co-product). In contrast, any pathway producing
lignin pellets increases CH4 emissions by at least 61% relative to gasoline. N2O emissions are increased
by at least 713% for switchgrass feedstock, with corn stover and hybrid poplar feedstocks seeing
average increases of 125% and 187% respectively relative to gasoline. This is due to the fact that the
agricultural stage for any biomass feedstock used is a substantial source of N2O release (contributing
90
between 18-90% of N2O release for a given pathway). Switchgrass agriculture is a larger source of N2O
release than the other two feedstocks due to higher fertilizer use (2.4 times more than CS, 15 times
more than HP). In particular, pathways co-producing lignin pellets are notable for having an N2O
release penalty instead of credit returned per unit of lignin pellets produced (0.009 g N2O / MJ5 pellet),
because displaced coal has lower N2O emissions than the biomass-derived pellets. The xylitol co-
product is able to displace a large amount of N2O emissions generated from sugar beet production (0.3
gN2O / kg xylitol).
The largest net GHG reduction is obtained with hybrid poplar processed by autohydrolysis, with lignin
as a co-product. Under these conditions, a 287% reduction in GHG emissions relative to gasoline is
projected, because of the large amount of co-product and its large co-product credit relative to coal.
Among the DA and AFEX pathways, corn stover generally had the smallest net GHG reductions relative
to gasoline when (60% for AXPR, 121% for AXPE), while for the AH pathways, switchgrass had the
smallest reductions for (70% for AHEL and 134% AHXP). All pathway/feedstock/process combinations
had GHG reductions of at least 60%, and thus, all should satisfy EISA cellulosic biofuel mandates.
Among non-greenhouse gas emissions, CO was the largest species produced (0.78-0.95 g CO/MJ E85
produced) at a rate similar to the gasoline reference pathway (0.91 g CO/MJ gasoline produced). The
majority of CO emissions (>70%) for all pathways was from activities during the fuel combustion stage,
where CO is emitted from vehicle engines. NOx and NMVOC emissions were generally larger in every
pathway relative to the gasoline reference (at least 124% and 38% higher, respectively), due to the
diversity of compounds present in lignocellulose and its higher nitrogen content compared to
petroleum and other fossil fuels). Like with N2O emissions, pathways co-producing lignin pellets
suffered both a CO and NOx penalty (0.02 g NOx/MJ pellet and 0.04 g CO/MJ pellet respectively) instead
of a credit, as the emissions from burning biomass (lignin pellets) were generally larger than those from
an equivalent amount of displaced coal.
Ethanol plant water use was generally lower for hybrid poplar feedstock due to its high water content
(50wt%) compared the other two feedstocks, except in pathways where AFEX pretreatment was used.
Water use trends were not entirely feedstock dependent as pretreatment water requirements differed
depending on feedstock. AFEX in particular required a water loading of greater than 2:1 kg water to kg
dry feedstock for hybrid poplar due to its recalcitrant nature. Use of hybrid poplar in AFEX pathways
5 Energy value is in primary energy (e.g., MJ based on lower heating value of the pellet).
91
resulted in a 91-99% greater water requirement than using corn stover. Water requirements for
switchgrass were likewise larger in AFEX pathways, also resulting in larger water requirements relative
to corn stover. Plant pathways with lignin pellet co-production had considerably lower water use than
counterpart pathways solely producing electricity, due to the fact that all residues going to
pelletization needed to be dried to below 15% moisture, and thus, the majority of the water was
recovered.
Ethanol plant solid waste was from two main sources, gypsum removal in DA pathways and ash and
other uncombusted material from combustion in all pathways that did not produce lignin pellets.
Approximately 0.05 kg/kg dry biomass, 0.07 kg/kg DBM and 0.1 kg/kg DBM of gypsum is sent to solid
waste disposal for corn stover, switchgrass and hybrid poplar feedstocks respectively. Other
components in the gypsum waste streams include minor amounts of monomers and polysaccharides.
98% of initial feedstock ash in each electricity producing pathway was captured in the boiler bottoms
and flyash following combustion of leftover residues; these residue streams also included small
amounts of uncombusted lignin and cellulose.
A low ethanol yield scenario with corn stover was compared to the defa┌ノデ さエキェエざ ┞キWノS ゲIWミ;ヴキラく TエW
low yield scenario was based upon fermentation of glucose only. The lower ethanol yield led to a
general decrease in net fossil energy across all pathways, because the lower ethanol yield was
accompanied by a greater co-product yield, which displaced fossil energy Pathways producing only
electricity saw a small increase (13%) in non-net fossil energy requirements; however, pathways co-
producing lignin pellets saw a much larger increase in ethanol plant fossil energy requirements (e.g.
66% drying energy increase in DAPE). Pathways with xylitol as a co-product saw very little change in
net fossil energy (4% and 7% decrease in AHXE and AHXP pathways), because, even in the high yield
scenario, only C6 sugars were fermented, with the majority being glucose. The pathway with the
lowest net fossil energy requirement is AHPE (107% lower than gasoline reference).
The low yield scenario also led to greater net GHG reductions, and lower net GHG emissions overall.
The reduction is GHG emissions is likewise a result of increased co-product generation and resulting
credits. The largest change compared to the high yield scenario is in the DAPE pathway, where the low
yield scenario has only one-fourteenth of the GHG emissions that the high yield scenario displays. DA
pathways in general had large decreases in GHG emissions because this particular pretreatment had
the largest hydrolysis of C5 sugars, and thus the highest yield of ethanol from C5 sugars; these
components were directed to co-products in the low yield scenario. Pathways with lignin pellet co-
92
products saw greater reductions in GHG emissions than pathways producing other co-products,
because lignin pellets have the largest co-product credit per unit of co-product. There was little
difference in GHG emissions between high and low yield scenarios for xylitol co-production pathways.
Likewise, yield had little effect on GHG emissions from the protein co-production pathway (AXPR)
because protein co-production is unaffected by changes in fermentation.
Overall, the results show that biorefineries employing any of the strategies studied are viable options to
reduce GHG emissions, particularly considering EISA mandates. Furthermore, the choice of co-products
may have considerable impact on energy use and GHG emissions performance. If GHG emissions
reduction is the primary objective, processes accompanied by pellet production, assuming coal is
displaced, have the greatest benefit, albeit with a lower fossil energy reduction than analogous
pathways solely producing electricity. Overall, given that all pathways can satisfy GHG emissions
reduction requirements stipulated under EISA, choices regarding co-products can be made based on
market, economic, geographical, political and other factors not within the scope of this study.
5.2 Implications
O┗Wヴ;ノノが ;ノノ ヮ;デエ┘;┞ゲ ゲデ┌SキWS ヴWヮヴWゲWミデ ;ミ さEI“A-;IIWヮデ;HノWざ マW;ミゲ デラ ヮヴラS┌IW Wデエ;ミラノ ;ゲ ;
ノキェミラIIWノノ┌ノラゲキI Hキラa┌Wノく TエW さマラゲデ ;デデヴ;Iデキ┗Wざ ヮ;デエ┘;┞ ;マラミェ デエラゲW キミ デエキゲ デエWゲキゲ ┘キノノ ┌ノデキマ;デWノ┞
depend on which parameters are of interest, considering economic (which products are to be
maximized), geographical (which feedstocks are available) and political (government regulations
regarding biofuels) factors.
In the interest of maximizing ethanol yield, a corn stover fed pathway employing dilute acid
pretreatment conversion technology with lignin pellet co-production is the best solution, providing
both the highest ethanol yield and the lowest GHG emissions among corn stover pathways. In the
interest of maximizing GHG reductions and minimizing fossil energy use, a hybrid poplar feedstock
combined with AFEX pretreatment and lignin pellet co-production is the most attractive pathway
among those studied. Due to the nature of waste/leftover products used for electricity or lignin pellets
in every scenario, the most notable tradeoff appears to be that with a lower ethanol yield, more co-
product can be produced, which reduces fossil energy demands and GHG emissions, despite the
93
normalization to the amount of ethanol produced. Although pathways with a lower ethanol yield have
the lowest fossil energy requirements and lowest GHG emissions, they also rely heavily on co-product
credits for environmental benefits. Heavy reliance on co-product credits creates risk associated with
changes in the type/use of displaced products in the regional market. In particular, lignin pellet co-
production is only environmentally beneficial (in terms of GHG reductions) over electricity generation
because of its ability to replace coal. In areas with electricity grids that have a low reliance on coal, the
cleaner fuels will mitigate the GHG advantage of lignin pellets as a co-product. Furthermore, the
regional market demand for the pellets may be reduced in areas with greater renewables in the grid
mix. Pathways with electricity as the sole co-product also have the lowest total energy use of any
pathway, although they do not have the lowest net fossil energy use or greatest GHG reduction. A
notable middle ground between ethanol yield and environmental performance are the pathways co-
producing xylitol. Although these pathways sacrifice approximately 24-35% ethanol yield, they are able
to produce an added-value co-product while generating one of the largest GHG reductions. Pathways
involving autohydrolysis of hybrid poplar with xylitol as a co-product produce 24% less ethanol, but
have the lowest GHG emissions and non-GHG emissions (NOx, SOx, NMVOC, etc.) of all the feedstocks
studied for xylitol production.
Among the feedstocks studied, hybrid poplar has the lowest direct land use change and has low
fertilizer requirements. Among the co-products considered in this thesis, protein concentrate was the
least advantageous co-product from an environmental standpoint (highest net fossil energy use,
highest net GHG emissions, lowest energy and GHG credit per unit). If, however, the protein displaced
was food-grade, it is likely that the environmental and economic benefits would be more competitive
with the other co-products.
Although lignocellulosic ethanol generally reduces GHG emissions, it is subject to increased NOx
emissions compared to gasoline production; some of these NOx emissions may increase eutrophication
potential due to run-off. DA pathways generate much higher SOx emissions relative to other pathways,
increasing acidification potential and posing potential challenges with fuel sulfur content. Finally, it
should be noted that PTW (pump-to-wheel) activities, although not the focus of this thesis, typically
represent at least 45% of pathway energy use and GHG emissions. Although advances in biomass-to-
ethanol conversion and lignocellulosic feedstock production technologies will no doubt aid the
development of lignocellulosic ethanol as an environmental fuel, advances in vehicle efficiency remain
ラミW ラa デエW マラゲデ キマヮラヴデ;ミデ a;Iデラヴゲ キミ Wデエ;ミラノげゲ a┌デ┌ヴWく
94
5.3 Limitations and Future Work
It is important to recognize the limitations of the current work. It is critical to note that while this thesis
is region specific to the US Midwest, the data used represent a generalization of regional conditions
rather than the actual conditions in a specific area. The majority of data collected pertain directly to
the United States and North America, and may not be generalizable to other continents such as Europe
or Asia. Likewise, generalized designs of theoretical ethanol conversion plants were used as a means to
gauge possible ethanol production strategies in the near-future. In the case of dilute acid, AFEX and
autohydrolysis pretreatment conversion pathways, the technology is still undergoing refinement,
where parameters such as temperature, chemical loading, enzyme loading, etc. are still being
optimized. This is especially true for AFEX, where the majority of knowledge on polysaccharide-to-
monomer conversions exists at lab scale rather than pilot scale. Pretreatment, enzymatic hydrolysis
and fermentation techniques pertaining to lignocellulosic ethanol are in a state of flux and will remain
so beyond the target year of this thesis (2015). Co-product specific production modules will likely
change as well. Lignocellulosic protein and xylitol co-production are still new concepts not widely
considered, and better methods to integrate them into each pretreatment pathway may exist in the
future. In regards to co-products, this study only compares a limited subset of co-products in a limited
number of combinations with the various feedstocks and pretreatment technologies previously
described. Other emerging products from lignocellulosics such as generating plastics and high purity
lignins are popular options not explored in this work. Investigation into co-product combinations not
within the scope of this work such as extraction of protein from autohydrolysis pretreated residues
could serve as a basis for future work. In addition to considering a limited set of co-products, this thesis
has also considered a limited set of metrics that only pertain to the environment. It has not dealt with
factors relating to political, geopolitical, and (most of all) economic issues. Even within the
environmental metrics studied, this work can only be considered a partial investigation of the
environmental profile of lignocellulosic ethanol. Several pollutants such as the emission of black carbon
were not quantified. Also, no actual characterization of the environmental results was undertaken as
seen in typical life cycle assessments (although this was purposely not done, as characterization often
presents aggregated environmental results that are difficult to disaggregate). Finally, this work has not
considered co-location with any other facilities that could potentially aid or otherwise affect the
95
energetic, environmental or economic performance of the existing plant pathways. Of all the
previously mentioned limitations, the one most appropriate for future investigation would likely be the
exploration of pathway economics, which would complement the environmental information already at
hand. Aside from environmental concerns, economics remains the primary dictator of lignocellulosic
ethanol pathway viability in the present day, as well as the principal motivation behind the production
of co-products in general.
96
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APPENDICES
104
Appendix A Life Cycle Model Design Calculations
A1 Transport
Feedstock Transport Distance
The plant location for this study was selected as the US Midwest. Previous National Renewable Energy
Laboratory (NREL) modelling has also placed their plant in the same region (Iowa) [35]. Although the
US Midwest is not the optimal choice regarding feedstocks such as hybrid poplar and Dakota
switchgrass, assumptions were made in order to unify local conditions. Due to the US Midwest being in
the center of the US cornbelt, the same calculation as that used by NREL [35] was used to calculate corn
stover transport. This calculated distance was also used for the other two feedstocks. Transport
distance is calculated as follows: Area = collection area of plant (acres)
Dfeedstock = Feedstock Demand (MT/yr) = 730000 Mg/yr (based on 2000 Mg/day) demand)
Yfeedstock = Mg of feedstock harvested per acre per year = 2 Mg/acre/yr for corn stover [35]
Favailacres = Fraction of farm land containing feedstock from which it can be collected (farmers are willing
to provide feedstock) = 0.1 (assumption is 10% for corn stover [35])
Fcropland = Fraction of surrounding land containing feedstock = 0.75 [35])
Area = Dfeedstock/(Yfeedstock x Favailacres x Fcropland) = 973333.3 Acres
*Assume area is circular around the plant:
Rmax = Maximum radius of collection = SQRT(Area x 4046.86 m2/acre / ) = 35418 m = 79.2 km
Ravg = Rmax / 2 = 39.6 km
Average transport radius for lignocellulosic feedstock to the ethanol plant is assumed rather than the
maximum distance. Further transport steps are illustrated in Figure A.1. E85 fuel is transported from
the ethanol plant stage using an assumed 40% split of transport by rail (1287 km), 40% by barge (837
km) and 20% by truck (129 km). Transport distances for these additional steps are based on US
national average transport data from GREET 1.8d [31].
105
Figure A.1 Transport Diagram for Lignocellulosic Ethanol Fuel Life Cycle
Aggregated transport factors from GREET 1.8d are presented in Table A.1. These factors represent the
energy required and the emissions involved with each stage of feedstock and ethanol transport.
Table A.1 Aggregated GREET 1.8d [30] Transport Energy and Emissions Factors
Energy Biomass to Plant
(MJ/dry Mg BM1)
Ethanol to Bulk Terminal
(J/MJ E85)
Bulk to Distributors
(J/MJ E85)
Total energy 70 14850 3173
Fossil energy 65 14817 3165
Coal 1 185 46
Natural gas 5 959 243
Petroleum 59 13673 2875
Emissions Biomass to Plant
(g/dry Mg BM)
Ethanol to Bulk Terminal
(g/GJ E85)
Bulk to Distributors
(g/GJ E85)
VOC 1 0.5 0.04
CO 1 2 0.1
NOx 4 11 0.2
PM10 0.5 0.4 0.02
PM2.5 0.3 0.3 0.01
SOx 2 2 0.1
CH4 6 1 0.3
N2O 0.1 0.03 0.01
CO2 4946 1157 240 1BM refers to lignocellulosic biomass feedstock
106
A2 Feedstock Agriculture
Agricultural production for all three feedstocks (corn stover, switchgrass, hybrid poplar) was based on
GREET 1.8d simulation [30], which involved estimation of fertilizer and pesticide use for each feedstock,
direct land use change, and energy associated with feedstock cultivation. In the case of corn stover,
addition of fertilizer associated with replacement of nutrients lost from stover removal was also
included. 48% of corn stover removal was assumed. In each feedstock case, energy used during actual
cultivation was assumed to be entirely from diesel used in agricultural machinery (tractors, tillers,
harvesters). Total energy and emissions from feedstock agriculture were calculated using aggregated
factors from GREET 1.8d simulation presented below for each feedstock. Total energy and emissions
were the sum of values associated with fertilizer and pesticide manufacture and feedstock cultivation
(including carbon sequestration and nitrification and denitrification effects) for each feedstock.
Agricultural energy use and emissions for each stage were calculated as:
Eaginputs = sum of energy (MJ) or emissions (g CO2, NOx, etc.) from production and use of chemicals
required in feedstock production
Ecultivation = sum of energy (MJ) or emissions (g CO2, NOx, etc.) from use of diesel in agricultural activities
ENOnd = net NO emission (g NO) from nitrification and denitrification (only for calculating NOx emissions)
EN2Ond = net N2O emission (g N2O) from nitrification and denitrification (only for calculating N2O
emissions)
Eluc = emissions (gCO2) associated with direct land use change (feedstock specific, may be a positive or
negative value)
Eag = energy (MJ) or emissions (g CO2, NOx, etc.) from agricultural activities overall
Eag = Eaginputs + Ecultivation + ENOnd + EN2Ond + Eluc
All variables above except Eag were calculated from aggregated GREET 1.8d factors specific to each
feedstock (Table A.2-Table A.10) based on the amount of feedstock required (2000 Mg/day plant
capacity). Note that a portion of the agricultural chemical requirements (e.g. fertilizer, herbicides) for
corn agriculture was not allocated to corn stover requirements. Instead, corn stover agricultural
chemical requirements deal only with the replacement of lost nutrients from the soil from the removal
of stover. Corn stover also has a zero direct land use change factor compared to other feedstocks such
as switchgrass and hybrid poplar. This is due to the assumption that stover is an agricultural residue
107
and its collection requires no major changes in corn agriculture and land use. Switchgrass and hybrid
poplar incur negative land use change values (credits to overall emissions) due to the fact that only the
above ground portion of these feedstocks is harvested while their extensive root structures are left
behind (representing a net accumulation of carbon from atmospheric CO2 into the soil).
Corn Stover
Table A.2 Aggregated GREET1.8d Factors for Corn Stover Agricultural Chemical Requirements
Agricultural Chemical g/dry Mg CS1
Nitrogen from Fertilizer 4954
P2O5 1800
K2O 9200 1CS refers to corn stover feedstock
Table A.3 Aggregated GREET1.8d Energy and Emissions Factors for Corn Stover Agricultural Chemicals1
Energy Nitrogen2
MJ/dry Mg CS3
P2O5
MJ/dry Mg CS
K2O
MJ/dry Mg CS
Total energy 243 26 87
Fossil fuels 240 25 82
Coal 15 5 29
Natural gas 216 13 30
Petroleum 9 7 22
Emissions Nitrogen
g/dry Mg CS
P2O5
g/dry Mg CS
K2O
g/dry Mg CS
VOC 30 1 1
CO 28 2 3
NOx 14 11 14
PM10 5 3 6
PM2.5 3 2 2
SOx 8 114 11
CH4 15 3 10
N2O 8 0.04 0.1
CO2 13890 1845 6478
g/dry Mg CS
*NO4 69
*N2O
5 15 1
Energy and emissions from fertilizers and other agricultural chemicals represent the emissions associated with
production, delivery and application of the chemicals to the soil, not emissions post application (such as N2O
emissions from nitrification/denitrification). 2Refers to nitrogen from fertilizer.
3CS refers to corn stover.
4NO emissions are from nitrification and denitrification as a result of fertilizer application.
5N2O emissions are from nitrification and denitrification as a result of fertilizer application.
108
Table A.4 Aggregated GREET 1.8d Factors for Corn Stover Cultivation and Collection
Farming Energy Use MJ/dry Mg CS
Total energy 317
Fossil fuels 317
Coal 5
Natural gas 24
Petroleum 288
Emissions from Farming g/dry Mg CS
VOC 14
CO 61
NOx 127
PM10 12
PM2.5 10
SOx 6
CH4 27
N2O 0.3
CO2 23889 1CS refers to corn stover feedstock.
Switchgrass
Table A.5 Aggregated GREET1.8d Factors for Switchgrass Agricultural Chemical Requirements
Agricultural Chemicals g/dry Mg SG1
Nitrogen from Fertilizer 11723
P2O5 157
K2O 249
Herbicide 31 1SG refers to switchgrass feedstock.
109
Table A.6 Aggregated GREET1.8d Energy and Emissions Factors for Switchgrass Agricultural Chemicals1
Energy Nitrogen2
MJ/dry Mg SG3
P2O5
MJ/dry Mg SG
K2O
MJ/dry Mg SG
Herbicide
MJ/dry Mg SG
Total energy 575 2 2 9
Fossil fuels 568 2 2 9
Coal 35 0.5 0.8 2
Natural gas 512 1 0.8 3
Petroleum 21 0.6 0.6 4
Emissions Nitrogen
g/dry Mg SG
P2O5
g/dry Mg SG
K2O
g/dry Mg SG
Herbicide
g/dry Mg SG
VOC 71 0.05 0.03 0.1
CO 66 0.2 0.1 0.3
NOx 33 0.9 0.4 0.9
PM10 11 0.3 0.2 0.5
PM2.5 6 0.2 0.1 0.2
SOx 19 10 0.3 0.9
CH4 35 0.3 0.3 1
N2O 19 0.003 0.004 0.01
CO2 32866 160 175 665
g/dry Mg SG
*NO4 163
*N2O
5 244 1
Energy and emissions from fertilizers and other agricultural chemicals represent the emissions associated with
production, delivery and application of the chemicals to the soil, not emissions post application (such as N2O
emissions from nitrification/denitrification). 2Refers to nitrogen from fertilizer.
3SG refers to switchgrass.
4NO emissions are from nitrification and denitrification as a result of fertilizer application.
5N2O emissions are from nitrification and denitrification as a result of fertilizer application.
110
Table A.7 Aggregated GREET 1.8d Factors for Switchgrass Cultivation and Collection
Farming Energy Use MJ/dry Mg SG1
Total energy 333
Fossil fuels 327
Coal 34
Natural gas 39
Petroleum 254
Emissions from Farming g/dry Mg SG
VOC 13
CO 55
NOx 116
PM10 15
PM2.5 10
SOx 12
CH4 31
N2O 0.4
CO2 25193
CO2 from Land use change -53462 1SG refers to switchgrass feedstock.
Hybrid Poplar
Table A.8 Aggregated GREET1.8d Factors for Hybrid Poplar Agricultural Chemical Requirements
Agricultural Chemical g/dry Mg HP1
Nitrogen from Fertlizer 782
P2O5 208
K2O 365
Herbicide 26
Insecticide 2 1HP refers to lignocellulosic biomass feedstock
111
Table A.9 Aggregated GREET1.8d Energy and Emissions Factors for Hybrid Poplar Agricultural
Chemicals1
Energy Nitrogen2
MJ/dry Mg HP3
P2O5
MJ/dry Mg HP
K2O
MJ/dry Mg HP
Herbicide
MJ/dry Mg HP
Insecticide
MJ/dry Mg HP
Total energy 38 3 3 8 0.8
Fossil fuels 38 3 3 7 0.7
Coal 2 0.6 1 2 0.2
Natural gas 34 2 1 2 0.2
Petroleum 1 0.8 0.9 3 0.3
Emissions Nitrogen
g/dry Mg HP
P2O5
g/dry Mg HP
K2O
g/dry Mg HP
Herbicide
g/dry Mg HP
Insecticide
g/dry Mg HP
VOC 5 0.07 0.04 0.06 0.01
CO 4 0.2 0.1 0.2 0.03
NOx 2 1 0.6 0.8 0.08
PM10 0.8 0.4 0.2 0.4 0.04
PM2.5 0.4 0.3 0.09 0.2 0.02
SOx 1 13 0.4 0.7 0.04
CH4 2 0.4 0.4 0.9 0.09
N2O 1 0.005 0.01 0.01 0.001
CO2 2191 214 257 570 56
g/dry Mg HP
*NO4 11
*N2O
5 16 1
Energy and emissions from fertilizers and other agricultural chemicals represent the emissions associated with
production, delivery and application of the chemicals to the soil, not emissions post application (such as N2O
emissions from nitrification/denitrification). 2Refers to nitrogen from fertilizer.
3HP refers to hybrid poplar.
4NO emissions are from nitrification and denitrification as a result of fertilizer application.
5N2O emissions are from nitrification and denitrification as a result of fertilizer application.
112
Table A.10 Aggregated GREET 1.8d Factors for Hybrid Poplar Cultivation and Collection
Farming Energy Use MJ/dry Mg HP1
Total energy 353
Fossil fuels 348
Coal 30
Natural gas 38
Petroleum 279
Emissions from Farming g/dry Mg HP
VOC 14
CO 60
NOx 127
PM10 16
PM2.5 11
SOx 11
CH4 32
N2O 0.4
CO2 26666
CO2 from Land use change -124010 1HP refers to hybrid poplar feedstock.
A3 Co-Product Credit Calculation
Traditionally, it has proven difficult to allocate energy and emissions between products of a life cycle
producing multiple products. System expansion is a method that involves expanding the boundaries of
a life cycle to encompass products that are displaced by co-products in the main life cycle. In order to
avoid allocation, it involves attributing the impacts of the production of ethanol entirely to the ethanol
product, although there may be secondary co-products involved. The impact of these co-products is
determined by displacing a competing product in industry. Thus, life cycles of these competing
ヮヴラS┌Iデゲ マ┌ゲデ ;ノゲラ HW ;Iケ┌キヴWS ふ;ミSっラヴ さIラミゲデヴ┌IデWSざぶが キミ ;SSキデキラミ デラ デエW マ;キミ ノキaW I┞IノWく TエW Sキゲヮノ;IWS
energy is subtracted from the energy attributed to ethanol as a credit.
Each co-product typically has a displacement ratio at which it effectively replaces an established
industry product. Displacement ratio is usually valued along a key parameter relating to the co-product
at hand. In terms of co-products that are mainly valued for their energy content, they are normally
equated on an energy basis with their industry equivalent (however, adjustments for energy conversion
efficiency will affect the displacement ratio when using a solid fuel).
113
Electricity
Co-product credits for electricity were calculated based on the displacement of the US Midwest
electricity grid mix. The electricity grid mix was sourced from California GREET 1.8b used by models
within the California Low Carbon Fuel Standard (LCFS) [77].
Table A.11 US Midwestern Electricity Grid Mix
Fuel Percentage
in Grid (%)
Residual oil 0
Natural gas 33.5
Coal 51.6
Nuclear power 0
Biomass 5.8
Others 9.1
Net electricity generated from all ethanol plant pathways was assumed to displace an energy
equivalent amount of electricity in the local electricity grid. Life cycle information pertaining to
upstream energy and emissions associated with displacing the individual fuels that were used to
generate local grid electricity was available in GREET 1.8d. Transmission losses (typically 8% over 1000
km) of net electricity over the grid were not considered part of the calculation, due to the fact that the
same transmission losses were present in electricity derived from the sources already comprising the
local grid. The electricity co-product credit for both energy and emissions is calculated as follows:
Eupstream = Sum of energy (MJ) or emissions (gCO2, NOx, etc.) from upstream fuel manufacture (e.g.,
extraction and refining of coal).
Edownstream = Sum of energy (MJ) or emissions (gCO2, NOx, etc.) from downstream conversion of fuels to
electricity (e.g., combustion of fuel to generate electricity in a Rankine cycle). In the case of energy
credits, energy キミ a┌Wノ キデゲWノa キゲ ;ノゲラ キミIノ┌SWS SWヮWミSキミェ ラミ a┌Wノ デ┞ヮW ふヴWミW┘;HノW WミWヴェ┞ キゲミげデ キミIノ┌SWS キミ
fossil fuel energy credit, for instance.).
R = Displacement ratio = 1
Ecredit = Energy (MJ) or emissions (gCO2, NOx, etc.) credit = R x (Eupstream + Edownstream)
114
An aggregated GREET 1.8d factor for energy and emissions is presented in Table A.12 for electricity as a
whole from all of the grid fuels involved to determine Eupstream and Edownstream values.
Table A.12 Aggregated GREET 1.8d Factor for Energy and Emissions from Generation of Regional US
Midwestern Electricity Grid
Energy Upstream Fuel
Production (J/MJ)
Conversion of Fuels
to Electricity (J/MJ)
Total energy 1.0x105 2.6 x106
Fossil fuels 1.0x105 2.3 x106
Coal 7.2x103 1.5x106
Natural gas 5.7x104 8.2x105
Petroleum 3.5x104 0
Emissions Upstream Fuel
Production (g/GJ)
Conversion of Fuels
to Electricity (g/GJ)
VOC 15 4
CO 11 60
NOx 34 167
PM10 243 14
PM2.5 61 8
SOx 19 327
CH4 308 5
N2O 0.1 5
CO2 7.3x103 2.0x105
Lignin Pellets
Lignin pellets were selected to displace coal in co-fired burners for electricity generation. Although the
primary energy value of lignin pellets could be equated to that of coal to derive an energy equivalent
mass of coal displaced, it is more useful to compare the two fuels on an equivalent amount of potential
electricity generated. Thus, the displacement ratio in this thesis is defined as the ratio of coal primary
energy to pellet primary energy needed to generate an equivalent amount of electricity. The electricity
generation efficiency (primary energy to electricity) between the two fuels varies by approximately 2%
(32.2% for lignin pellets at 15% co-fire vs. 34.4% for 100% coal) based on GREET 1.8d data [30]. Dividing
the two energy conversion values results in a coal to biomass primary energy displacement ratio of
approximately 94%. The lignin pellet energy credit was calculated as:
Eupstream = Sum of energy (MJ) used in coal extraction and refining for use in electricity generation.
115
Edownstream = Sum of energy (MJ) used in electricity generation from coal (includes primary energy in coal)
Ecredit = Energy credit (MJ, only applies to non-biomass energy)
R = primary energy displacement ratio (coal/pellet) = 0.94
Ecredit = R x (Eupstream + Edownstream)
Eupstream and Edownstream values are derived from aggregated GREET 1.8d factors, and the primary energy
of lignin pellets produced in each lignin pellet co-producing pathway. The formula for Ecredit above only
applies to non-renewable energy. The credit for total energy (which includes biomass energy) is
calculated by the formula: Ecredit = R x (Eupstream + Edownstream) に Epellet where Epellet = Primary energy in pellet.
Emissions credit calculation for lignin pellets is similar, however it includes emissions from pellet
combustion:
Eupstream = Sum of emissions (gCO2, NOx, etc.) used in coal extraction and refining for use in electricity
generation.
Edownstream = Sum of emissions (gCO2, NOx, etc.) used in electricity generation from coal (includes primary
energy in coal)
Epellet = Emissions (gCO2, NOx, etc.) from combustion of lignin pellet.
Ecredit = Emissions credit (gCO2, NOx, etc.).
R = primary energy displacement ratio (coal/pellet) = 0.94
Ecredit = R x (Eupstream + Edownstream) - Epellet
It should be noted that the emissions credit is on a per species basis, although the formula is the same.
Due to the assumption of さI;ヴHラミ ミW┌デヴ;ノキデ┞ざ, Epellet , when considering CO2 emissions in the lignin
pellet, is zero. Lignin pellet emissions factors were based on the assumption of using biomass pellet
emissions factors from the US Environmental Protection Agency (present in GREET 1.8d) [30].
116
Table A.13 Aggregated GREET 1.8d Energy and Emissions Factors for Upstream Coal Production
Energy J/MJ Electricity at Power Plant Outlet1
Total energy 56549
Fossil fuels 55104
Coal 9903
Natural gas 7593
Petroleum 37608
Emissions g/GJ Electricity at Plant Outlet
VOC 21
CO 6
NOx 26
PM10 470
PM2.5 117
SOx 20
CH4 330
N2O 0
CO2 4353 1Refers to electricity generated from coal leaving downstream power plant to the local grid.
Table A.14 Aggregated GREET 1.8d Energy and Emissions Factors for Downstream Coal-to-Electricity
Activities
Energy J/MJ Electricity at Power Plant Outlet1
Total energy 2924502
Fossil fuels 2924502
Coal 2924502
Natural gas 0
Petroleum 0
Emissions g/GJ Electricity at Power Plant Outlet
VOC 15
CO 11
NOx 34
PM10 243
PM2.5 61
SOx 19
CH4 308
N2O 0.1
CO2 7312 1Refers to electricity generated from coal leaving downstream power plant to the local grid.
117
Table A.15 Aggregated GREET 1.8d Emissions Factors for Lignin Pellet Emissions
Emissions g/GJ Electricity at Power Plant Outlet1
VOC 16
CO 225
NOx 322
PM10 37
PM2.5 19
SOx 89
CH4 11
N2O 32
CO2 0 1Refers to electricity generated from coal leaving downstream power plant to the local grid.
Xylitol
Xylitol co-product credits were based on the displacement of sugar (white) from sugar beet. Life cycle
stages for this displaced sugar involve sugar beet agriculture, and sugar manufacturing from raw beets.
Data for sugar beet agriculture were based on sugar beets from GHGenius [31], which in turn based
sugar beet agriculture on production in the province of Alberta at an average yield of 50 tonnes of
sugar beet per 10 km2. Fertilizer and other agricultural chemical requirements, however, were based
on sugarbeet agriculture in the UK from Mortimer et al. [82]. Sugar production from sugar beet was
based on data from SimaPro [33]. SimaPro sugar production data from sugar beet are based on
European plant architecture from Switzerland (although sugar plant designs using sugar beet feedstock
are largely the same). Individual processes in sugar production from sugar beet involve sugar beet
washing and size reduction, sugar extraction using hot water (70C), separation of beet pulp from the
resulting solution, purification of the solution using CaCO3, two stage evaporation, and finally,
centrifugation of the resulting sugar crystal-molasses mixture to isolate the crystals. The displacement
ratio was 1:1 for sugar to xylitol on a mass basis due to 1 ェ ┝┞ノキデラノ エ;┗キミェ デエW ゲ;マW さゲ┘WWデミWゲゲざ ;ゲ ヱ g of
sugar. Overall calculation for the sugar from sugar beet pathway is as follows:
Eag = Energy (MJ) or emissions (gCO2, NOx, etc.) from sugar beet agriculture.
Etransport = Energy (MJ) or emissions (gCO2, NOx, etc.) associated with transport of sugar beet to sugar
manufacturing facility.
Eheating = Energy (MJ) or emissions (gCO2, NOx, etc.) associated with sugar plant heating.
118
Eelec = Energy (MJ) or emissions (gCO2, NOx, etc.) associated with sugar plant electricity requirements.
Esugarprod = Energy (MJ) or emissions (gCO2, NOx, etc.) associated with sugar manufacture = Eheating + Eelec
R = displacement ratio = 1
Ecredit = Energy (MJ) or emissions (gCO2, NOx, etc.) credit for sugar beet = R x (Eag + Etransport + Esugarprod)
Eag was obtained through similar means as described in Appendix A2. Agricultural factors (obtained
from GHGenius sugar beet agricultural factors) are listed below based on the amount of sugar beet
required.
Sugar Beet Agriculture
Table A.16 Aggregated Factors for Sugar Beet Agricultural Chemical Requirements
Agricultural Chemical g/dry Mg SB1
Nitrogen from Fertilizer 1902
P2O5 687
K2O 1874
Herbicide 21339
Insecticide 68 1SB refers to sugar beet
119
Table A.17 Aggregated Energy and Emissions Factors for Sugar Beet Agricultural Chemicals1
Energy Nitrogen2
kJ/g req.
P2O5
kJ/g req.
K2O
kJ/g req.
CaCO3
kJ/g req.
Herbicide
kJ/g req.
Insecticide
kJ/g req.
Total energy 49 15 9 9 290 346
Fossil fuels 48 14 9 8 280 333
Coal 3 3 3 3 58 72
Natural gas 44 7 3 3 91 109
Petroleum 2 4 2 2 130 153
Emissions Nitrogen
g/kg req.
P2O5
g/kg req.
K2O
g/kg req.
CaCO3
g/kg req.
Herbicide
g/kg req.
Insecticide
g/kg req.
VOC 6 0.3 0.1 0.1 2 3
CO 6 1 0.4 0.3 9 13
NOx 3 6 2 0.7 30 37
PM10 1 2 0.7 0.6 16 18
PM2.5 0.5 1 0.2 0.2 7 9
SOx 2 64 1 0.8 28 20
CH4 3 2 1 1 32 39
N2O 2 0.02 0.01 0.01 0.3 0.4
CO2 2472 1025 704 645 21541 25322
g/dry Mg SB3
*NO4 26
*N2O
5 40
1
Energy and emissions from fertilizers and other agricultural chemicals represent the emissions associated with
production, delivery and application of the fertilizer to the soil, not emissions post application (such as N2O
emissions from nitrification/denitrification). 2Refers to the amount of nitrogen from fertilizer.
3SB refers to dry sugar beet.
4NO emissions from nitrification and denitrification as a result of nitrogen fertilizer application.
5N2O from nitrification and denitrification as a result of fertilizer application.
120
Table A.18 Aggregated Energy and Emissions Factors for Sugar Beet Cultivation
Diesel Use in Sugar
Beet Agriculture1
MJ Diesel/Mg SB2
149
Energy Use from Diesel
Production and Use J/MJ Diesel
Total energy 193757
Fossil fuels 190618
Coal 17476
Natural gas 91439
Petroleum 81703
Emissions from Diesel
Production and Use g/GJ Diesel
VOC 8
CO 12
NOx 40
PM10 6
PM2.5 3
SOx 21
CH4 103
N2O 0.258720327
CO2 16224.80012
g/Mg SB
CO2 from Land use
change 16857.435
1Assumption is that energy use and emissions from actual cultivation is only diesel based with the exception of
direct land use change, which is also included.
2SB refers to sugar beet.
121
Table A.19 Aggregated Energy and Emissions Factors for Sugar Beet Cultivation1
Energy MJ/dry Mg Sugar Beet
Total energy 25.12
Fossil energy 25.06
Coal 0.34
Natural gas 1.91
Petroleum 22.81
Emissions g/dry Mg Sugar Beet
VOC 0.28
CO 0.54
NOx 1.72
PM10 0.17
PM2.5 0.10
SOx 0.62
CH4 2.18
N2O 0.05
CO2 1900.45 1Sugar beet transport distance between production site and sugar manufacturing facility was estimated to be 10
km based on SimaPro transport data using 100% truck (tractor trailer) transport (58.5 kg鋲km, 5.85 kg sugar beet
req. to make 1 kg sugar) [33]. Transport associated with shipping sugar to suppliers was not included in sugar
from sugar beet life cycle due to being a common element with co-produced xylitol.
122
Sugar to Sugar Beet Production
Table A.20 Aggregated Energy and Emissions Factors for Sugar Plant Heating from Natural Gas
Plant Heating MJ/kg Sugar
Natural Gas Req. 2
Energy Use from Production
and Use of Natural Gas J/MJ
Total energy 73291
Fossil fuels 72853
Coal 2455
Natural Gas 66221
Petroleum 4177
Emissions g/GJ NG req.1
VOC 5
CO 7
NOx 19
PM10 0.8
PM2.5 0.5
SOx 11
CH4 186
N2O 0.09
CO2 5028 1NG refers to natural gas.
123
Table A.21 Aggregated Energy and Emissions Factors for Required Sugar Plant Electricity from Local
Grid1
Required Plant
Electricity
kWh/kg Sugar
0.19
Energy Use Electricity Upstream Fuel
Production (J/MJ Electricity Req.)
Fuel Conversion to Electricity
(J/MJ Electricity Req.)
Total energy 1.1 x 105 2.8 x 106
Fossil fuels 1.1 x 105 2.5 x 106
Coal 8.4 x 103 1.6 x 106
Natural gas 6.3 x 104 8.9 x 105
Petroleum 3.8 x 104 0
Emissions g/GJ Electricity Req. g/GJ Electricity Req.
VOC 17 5
CO 12 65
NOx 37 182
PM10 265 15
PM2.5 66 8
SOx 21 356
CH4 334 6
N2O 0.2 5
CO2 8029 218773 1US Midwest electrical grid was used.
Protein Concentrate
Co-product credits associated with protein concentrate were dealt with by displacing soy meal. The soy
meal life cycle pathway was already present in GREET 1.8d. The soy meal life cycle consisted of
soybean agriculture to produce soybeans, which were subjected to hexane extraction to remove oil.
The remaining material after soy oil extraction is soy meal (typically containing 50% of the protein in
soybean). The displacement ratio of protein concentrate and soy meal was 1:1 on a mass basis. The
displacement ratio was selected due to the fact that it is difficult to compare the effect of both
products on actual ruminant nutrition. Amino acid composition on the actual protein concentrate co-
produced was not available. Energy and emissions credits were based on the aggregated GREET 1.8d
net life cycle energy and emissions factors in Table A.22.
124
Table A.22 Aggregated GREET 1.8d Energy and Emissions Factors for Protein Concentrate Credit
Energy MJ/kg Protein Concentrate
Total energy 2
Fossil fuels 2
Coal 0.2
Natural Gas 0.6
Petroleum 2
Emissions g/kg Protein Concentrate
VOC 0.1
CO 0.5
NOx 1
PM10 0.1
PM2.5 0.07
SOx 0.7
CH4 0.3
N2O 0.3
CO2 177
A4 Downstream Vehicle Activities
Pump-to-wheel (PTW) energy in this thesis refers to the energy released (primary energy content)
during the combustion of a fuel (RFG or E85) in a light duty model vehicle. Both the baseline gasoline
and flexible fuel model vehicles in GREET 1.8d [30] had identical fuel economy on a gasoline equivalent
basis (9.48 L gasoline equivalents / 100 km), which was used to calculate the distance travelled from
the volume of ethanol produced in each pathway. Emissions associated with PTW activities were
calculated based on flexible fuel vehicle emissions from GREET 1.8d [30].
125
Table A.23 Aggregated GREET 1.8d Emissions Factors for E85 Fuel Combustion in a Flexible Fuel Vehicle
Emissions g/km
VOC: exhaust 10.7
VOC: evaporation 5.4
CO 392
NOx 7.7
PM10: exhaust 0.9
PM10: brake and tire wear 2.3
PM2.5: exhaust 0.8
PM2.5: brake and tire wear 0.8
SOx 0.2
CH4 1.2
N2O 1.3
CO2 38382
A5 Yield Calculations
Maximum Theoretical Ethanol from C6 and C5 Sugars
Max ethanol from sugars:
Me = mass of ethanol
Ye = 0.511 g ethanol / g sugar (both hexose and pentose sugars have same max ethanol yield)
Em = max theoretical ethanol = Me x Ye
Metabolic Yield
Sc = mass of sugars consumed by fermentation to produce ethanol
Ye = 0.511 g ethanol / g sugar (both hexose and pentose sugars have same max ethanol yield)
E = mass of ethanol produced
Ecmax = maximum theoretical mass of ethanol from consumed sugars = Sc x Ye
Ym = metabolic yield = E / Ecmax
Productive Yield
Stotal = mass of total sugars entering fermentation
126
Ye = 0.511 g ethanol / g sugar (both hexose and pentose sugars have same max ethanol yield)
E = mass of ethanol produced
Emax = maximum amount of ethanol from all sugars entering fermentation = Stotal x Ye
Yp = productive yield = E / Emax
Overall Plant Ethanol Yield
Ep = rate of ethanol production (mass / time)
Fm = plant feedstock capacity (mass / time)
Ypy = Ep / Fm
Plant Feedstock Energy Conversion Efficiency (Electricity Co-production Only)
Ee = Energy content in produced ethanol (MJ)
Eelec = Energy value of net electricity (MJ)
Ef = Energy content in feedstock (MJ primary energy)
Ye = (Ee + Eelec) / Ef
Note this formula can be used for lignin pellets in place of electricity; however, the value will not be
comparable to when electricity is used due to the fact that the energy value of lignin pellets is on a
primary basis while electricity is on a secondary basis (after losses during power generation). In order
for the two values to be comparable, the lignin pellet primary energy must be converted to a secondary
basis (to electricity through combustion at a 32% efficiency). For co-products other than electricity and
lignin pellets that are not conventional fuels, Eelec is effectively zero.
127
A6 Pretreatment and Ethanol Reaction Conversion Data Tables
Data tables for fractional conversions for pretreatment and ethanol conversion reactions are listed in
this section.
Table A.24 Reaction Summary for Corn Stover Dilute Acid (CSDA) Pathways
Pretreatment Saccharification Fermentation
Reaction fc(%)1 Reaction fc (%) Reaction fc (%)
Cellulose to Oligomer 0 Cellulose to Oligomer 4 Glucose to Ethanol 95
Cellulose to Cellobiose 0.7 Cellulose to Cellobiose 1.2 Glucose to Zymonomas 2
Cellulose to Glucose 6.26 Cellulose to Glucose 91.12 Glucose to Glycerol 0.4
Cellulose to HMF 0.3 Cellobiose to Glucose 100 Glucose to Succinic Acid 0.6
Xylan to Oligomer 2.71 Xylan to Xylose 57.78 Glucose to Acetic Acid 1.5
Xylan to Xylose 82.62 Arabinan to Arabinose 57.78 Glucose to Lactic Acid 0.2
Xylan to Furfural 5 Galactan to Galactose 57.78 Xylose to Ethanol 85
Xylan to Tar 0 Mannan to Mannose 57.78 Xylose to Zymomonas 1.9
Mannan to Oligomer 2.71
Xylose to Glycerol 0.3
Mannan to Mannose 82.62
Xylose to Xylitol 4.6
Mannan to HMF 5
Xylose to Succinic Acid 0.9
Galactan to Oligomer 2.71
Xylose to Acetic Acid 1.4
Galactan to Galactose 82.62
Xylose to Lactic Acid 0.2
Galactan to HMF 5
Arabinose to Ethanol 85
Arabinan to Oligomer 2.71
Arabinose to Zymomonas 1.9
Arabinan to Arabinose 82.62
Arabinose to Glycerol 0.3
Arabinan to Furfural 5
Arabinose to Succinic Acid 1.5
Arabinan to Tar 0
Arabinose to Acetic Acid 1.4
Acetate to Oligomer 0
Arabinose to Lactic Acid 0.2
Acetate to Acetic Acid 100
Galactose to Ethanol 85
Furfural to Tar 100
Galactose to Zymomonas 1.9
HMF to Tar 100
Galactose to Glycerol 0.3
Lignin to Soluble Lignin 5
Galactose to Succinic Acid 1.5
Galactose to Acetic Acid 1.4
Galactose to Lactic Acid 0.2
Mannose to Ethanol 0.85
Mannose to Zymomonas 1.9
Mannose to Glycerol 0.3
Mannose to Succinic Acid 1.5
Mannose to Acetic Acid 1.4
Mannose to Lactic Acid 0.2 1fc refers to fractional conversion percentage for the associated reaction.
128
Table A.25 Reaction Summary for Switchgrass Dilute Acid (SGDA) Pathways
Pretreatment Saccharification Fermentation
Reaction fc (%)1 Reaction fc (%) Reaction fc (%)
Cellulose to Oligomer 0.92 Cellulose to Oligomer 4 Glucose to Ethanol 95
Cellulose to Cellobiose 0.7 Cellulose to Cellobiose 1.2 Glucose to Zymonomas 2
Cellulose to Glucose 6.27 Cellulose to Glucose 75.02 Glucose to Glycerol 0.4
Cellulose to HMF 0 Cellobiose to Glucose 100 Glucose to Succinic Acid 0.6
Xylan to Oligomer 4.9 Xylan to Xylose 34.47 Glucose to Acetic Acid 1.5
Xylan to Xylose 70.06 Arabinan to Arabinose 34.47 Glucose to Lactic Acid 0.2
Xylan to Furfural 5 Galactan to Galactose 34.47 Xylose to Ethanol 85
Xylan to Tar 0 Mannan to Mannose 34.47 Xylose to Zymomonas 1.9
Mannan to Oligomer 4.9
Xylose to Glycerol 0.3
Mannan to Mannose 70.06
Xylose to Xylitol 4.6
Mannan to HMF 5
Xylose to Succinic Acid 0.9
Galactan to Oligomer 4.9
Xylose to Acetic Acid 1.4
Galactan to Galactose 70.06
Xylose to Lactic Acid 0.2
Galactan to HMF 5
Arabinose to Ethanol 85
Arabinan to Oligomer 4.9
Arabinose to Zymomonas 1.9
Arabinan to Arabinose 70.06
Arabinose to Glycerol 0.3
Arabinan to Furfural 5
Arabinose to Succinic Acid 1.5
Arabinan to Tar 0
Arabinose to Acetic Acid 1.4
Acetate to Oligomer 0
Arabinose to Lactic Acid 0.2
Acetate to Acetic Acid 100
Galactose to Ethanol 85
Furfural to Tar 100
Galactose to Zymomonas 1.9
HMF to Tar 100
Galactose to Glycerol 0.3
Lignin to Soluble Lignin 5
Galactose to Succinic Acid 1.5
Galactose to Acetic Acid 1.4
Galactose to Lactic Acid 0.2
Mannose to Ethanol 0.85
Mannose to Zymomonas 1.9
Mannose to Glycerol 0.3
Mannose to Succinic Acid 1.5
Mannose to Acetic Acid 1.4
Mannose to Lactic Acid 0.2 1fc refers to fractional conversion percentage for the associated reaction.
129
Table A.26 Reaction Summary for Hybrid Poplar Dilute Acid (HPDA) Pathways
Pretreatment Saccharification Fermentation
Reaction fc (%)1 Reaction fc (%) Reaction fc (%)
Cellulose to Oligomer 0 Cellulose to Oligomer 4 Glucose to Ethanol 95
Cellulose to Cellobiose 0.7 Cellulose to Cellobiose 1.2 Glucose to Zymonomas 2
Cellulose to Glucose 23.17 Cellulose to Glucose 79.04 Glucose to Glycerol 0.4
Cellulose to HMF 0 Cellobiose to Glucose 100 Glucose to Succinic Acid 0.6
Xylan to Oligomer 0 Xylan to Xylose 16.29 Glucose to Acetic Acid 1.5
Xylan to Xylose 52.21 Arabinan to Arabinose 16.29 Glucose to Lactic Acid 0.2
Xylan to Furfural 5 Galactan to Galactose 16.29 Xylose to Ethanol 85
Xylan to Tar 0 Mannan to Mannose 16.29 Xylose to Zymomonas 1.9
Mannan to Oligomer 0
Xylose to Glycerol 0.3
Mannan to Mannose 52.21
Xylose to Xylitol 4.6
Mannan to HMF 5
Xylose to Succinic Acid 0.9
Galactan to Oligomer 0
Xylose to Acetic Acid 1.4
Galactan to Galactose 52.21
Xylose to Lactic Acid 0.2
Galactan to HMF 5
Arabinose to Ethanol 85
Arabinan to Oligomer 0
Arabinose to Zymomonas 1.9
Arabinan to Arabinose 52.21
Arabinose to Glycerol 0.3
Arabinan to Furfural 5
Arabinose to Succinic Acid 1.5
Arabinan to Tar 0
Arabinose to Acetic Acid 1.4
Acetate to Oligomer 0
Arabinose to Lactic Acid 0.2
Acetate to Acetic Acid 100
Galactose to Ethanol 85
Furfural to Tar 100
Galactose to Zymomonas 1.9
HMF to Tar 100
Galactose to Glycerol 0.3
Lignin to Soluble Lignin 5
Galactose to Succinic Acid 1.5
Galactose to Acetic Acid 1.4
Galactose to Lactic Acid 0.2
Mannose to Ethanol 0.85
Mannose to Zymomonas 1.9
Mannose to Glycerol 0.3
Mannose to Succinic Acid 1.5
Mannose to Acetic Acid 1.4
Mannose to Lactic Acid 0.2 1fc refers to fractional conversion percentage for the associated reaction.
130
Table A.27 Reaction Summary for Corn Stover AFEX (CSAX) Pathways
Pretreatment Saccharification Fermentation
Reaction fc (%)1 Reaction fc (%) Reaction fc (%)
Lignin to Soluble Lignin 33 Cellulose to Oligomer 0 Glucose to Ethanol 95
Xylan to Oligomer 50 Cellulose to Cellobiose 0 Glucose to Zymonomas 2
Arabinan to Oligomer 50 Cellulose to Glucose 95.9 Glucose to Glycerol 0.4
Galactan to Oligomer 50 Cellobiose to Glucose 100 Glucose to Succinic Acid 0.6
Mannan to Oligomer 50 Xylan to Xylose 77.7 Glucose to Acetic Acid 1.5
Acetate to Ammonium
Acetate 100 Arabinan to Arabinose 77.7 Glucose to Lactic Acid 0.2
Galactan to Galactose 77.7 Xylose to Ethanol 85
Mannan to Mannose 77.7 Xylose to Zymomonas 1.9
Xylose to Glycerol 0.3
Xylose to Xylitol 4.6
Xylose to Succinic Acid 0.6
Xylose to Acetic Acid 1.4
Xylose to Lactic Acid 0.2
Arabinose to Ethanol 85
Arabinose to Zymomonas 1.9
Arabinose to Glycerol 0.3
Arabinose to Succinic Acid 1.5
Arabinose to Acetic Acid 1.4
Arabinose to Lactic Acid 0.2
Galactose to Ethanol 85
Galactose to Zymomonas 1.9
Galactose to Glycerol 0.3
Galactose to Succinic Acid 1.5
Galactose to Acetic Acid 1.4
Galactose to Lactic Acid 0.2
Mannose to Ethanol 0.85
Mannose to Zymomonas 1.9
Mannose to Glycerol 0.3
Mannose to Succinic Acid 1.5
Mannose to Acetic Acid 1.4
Mannose to Lactic Acid 0.2 1fc refers to fractional conversion percentage for the associated reaction.
131
Table A.28 Reaction Summary for Switchgrass AFEX (SGAX) Pathways
Pretreatment Saccharification Fermentation
Reaction fc (%)1 Reaction fc (%) Reaction fc (%)
Lignin to Soluble Lignin 33 Cellulose to Oligomer 0 Glucose to Ethanol 95
Xylan to Oligomer 50 Cellulose to Cellobiose 0 Glucose to Zymonomas 2
Arabinan to Oligomer 50 Cellulose to Glucose 78.87 Glucose to Glycerol 0.4
Galactan to Oligomer 50 Cellobiose to Glucose 100 Glucose to Succinic Acid 0.6
Mannan to Oligomer 50 Xylan to Xylose 84.38 Glucose to Acetic Acid 1.5
Acetate to Ammonium
Acetate 100 Arabinan to Arabinose 84.38 Glucose to Lactic Acid 0.2
Galactan to Galactose 84.38 Xylose to Ethanol 85
Mannan to Mannose 84.38 Xylose to Zymomonas 1.9
Xylose to Glycerol 0.3
Xylose to Xylitol 4.6
Xylose to Succinic Acid 0.6
Xylose to Acetic Acid 1.4
Xylose to Lactic Acid 0.2
Arabinose to Ethanol 85
Arabinose to Zymomonas 1.9
Arabinose to Glycerol 0.3
Arabinose to Succinic Acid 1.5
Arabinose to Acetic Acid 1.4
Arabinose to Lactic Acid 0.2
Galactose to Ethanol 85
Galactose to Zymomonas 1.9
Galactose to Glycerol 0.3
Galactose to Succinic Acid 1.5
Galactose to Acetic Acid 1.4
Galactose to Lactic Acid 0.2
Mannose to Ethanol 0.85
Mannose to Zymomonas 1.9
Mannose to Glycerol 0.3
Mannose to Succinic Acid 1.5
Mannose to Acetic Acid 1.4
Mannose to Lactic Acid 0.2 1fc refers to fractional conversion percentage for the associated reaction.
132
Table A.29 Reaction Summary for Hybrid Poplar AFEX (HPAX) Pathways
Pretreatment Saccharification Fermentation
Reaction fc (%)1 Reaction fc (%) Reaction fc (%)
Lignin to Soluble Lignin 33 Cellulose to Oligomer 0 Glucose to Ethanol 95
Xylan to Oligomer 50 Cellulose to Cellobiose 0 Glucose to Zymonomas 2
Arabinan to Oligomer 50 Cellulose to Glucose 51.58 Glucose to Glycerol 0.4
Galactan to Oligomer 50 Cellobiose to Glucose 100 Glucose to Succinic Acid 0.6
Mannan to Oligomer 50 Xylan to Xylose 43.46 Glucose to Acetic Acid 1.5
Acetate to Ammonium
Acetate 100 Arabinan to Arabinose 43.46 Glucose to Lactic Acid 0.2
Galactan to Galactose 43.46 Xylose to Ethanol 85
Mannan to Mannose 43.46 Xylose to Zymomonas 1.9
Xylose to Glycerol 0.3
Xylose to Xylitol 4.6
Xylose to Succinic Acid 0.6
Xylose to Acetic Acid 1.4
Xylose to Lactic Acid 0.2
Arabinose to Ethanol 85
Arabinose to Zymomonas 1.9
Arabinose to Glycerol 0.3
Arabinose to Succinic Acid 1.5
Arabinose to Acetic Acid 1.4
Arabinose to Lactic Acid 0.2
Galactose to Ethanol 85
Galactose to Zymomonas 1.9
Galactose to Glycerol 0.3
Galactose to Succinic Acid 1.5
Galactose to Acetic Acid 1.4
Galactose to Lactic Acid 0.2
Mannose to Ethanol 0.85
Mannose to Zymomonas 1.9
Mannose to Glycerol 0.3
Mannose to Succinic Acid 1.5
Mannose to Acetic Acid 1.4
Mannose to Lactic Acid 0.2 1fc refers to fractional conversion percentage for the associated reaction.
133
Table A.30 Reaction Summary for Corn Stover Autohydrolysis (CSAH) Pathways
Pretreatment Saccharification Fermentation
Reaction fc (%)1 Reaction fc (%) Reaction fc (%)
Cellulose to Oligomer 0 Stage 1 (2 Tanks)2
C6 Fermentation (4 tanks)
4
Cellulose to Cellobiose 0 Cellulose to Glucose 41 Glucose to Ethanol 95
Cellulose to Glucose 4.86 Xylan to Xylose 42.7 Glucose to Yeast 2
Cellulose to HMF 0 Arabinan to Arabinose 0 Glucose to Glycerol 0.4
Xylan to Oligomer 0 Galactan to Galactose 0 Glucose to Succinic Acid 0.6
Xylan to Xylose 43.05 Mannan to Mannose 0 Glucose to Acetic Acid 1.5
Xylan to Furfural 13.2 Acetate to Acetic Acid 63 Glucose to Lactic Acid 0.2
Xylan to Tar 0
Galactose to Ethanol 95
Mannan to Oligomer 0 Stages 2 & 3 (5 tanks)3
Galactose to Yeast 2
Mannan to Mannose 43.05 Cellulose to Glucose 23.5 Galactose to Glycerol 0.4
Mannan to HMF 5 Xylan to Xylose 21.88 Galactose to Succinic Acid 0.6
Galactan to Oligomer 0 Arabinan to Arabinose 0 Galactose to Acetic Acid 1.5
Galactan to Galactose 43.05 Galactan to Galactose 0 Galactose to Lactic Acid 0.2
Galactan to HMF 5 Mannan to Mannose 0 Mannose to Ethanol 95
Arabinan to Oligomer 0 Acetate to Acetic Acid 33 Mannose to Yeast 2
Arabinan to Arabinose 43.05
Mannose to Glycerol 0.4
Arabinan to Furfural 5
Mannose to Succinic Acid 0.6
Arabinan to Tar 0
Mannose to Acetic Acid 1.5
Acetate to Oligomer 0
Mannose to Lactic Acid 0.2
Cellulose to Oligomer 0
C5 Fermentation5
Xylose to Ethanol 90
Xylose to Zymomonas 1.9
Xylose to Glycerol 0.3
Xylose to Xylitol 3.6
Xylose to Succinic Acid 0.6
Xylose to Acetic Acid 1.4
Xylose to Lactic Acid 0.2
Arabinose to Ethanol 90
Arabinose to Zymomonas 1.9
Arabinose to Glycerol 0.3
Arabinose to Succinic Acid 0.6
Arabinose to Acetic Acid 1.4
Arabinose to Lactic Acid 0.2
1fc refers to fractional conversion percentage for the associated reaction.
2Stage 1 of enzymatic hydrolysis in AH
pathways consists of two tanks in series, in which the same reactions and conversions listed take place in each. 3Stages 2 and 3 of enzymatic hydrolysis in AH pathways consists of 5 tanks total connected in series, the same
reactions and conversions listed take place in each of the 5 tanks. 4C6 fermentation takes place in 4 tanks in
parallel fermentation, each tank contains the reactions and conversions listed. 5C5 fermentation takes place
separately from C6 fermentation in AH pathways without xylitol co-production. C5 fermentation does not take
place in pathways with xylitol co-production.
134
Table A.31 Reaction Summary for Switchgrass Autohydrolysis (SGAH) Pathways
Pretreatment Saccharification Fermentation
Reaction fc (%)1 Reaction fc (%) Reaction fc (%)
Cellulose to Oligomer 0 Stage 1 (2 Tanks)2
C6 Fermentation (4 tanks)
4
Cellulose to Cellobiose 0 Cellulose to Glucose 41 Glucose to Ethanol 95
Cellulose to Glucose 2.5 Xylan to Xylose 42.7 Glucose to Yeast 2
Cellulose to HMF 0 Arabinan to Arabinose 0 Glucose to Glycerol 0.4
Xylan to Oligomer 0 Galactan to Galactose 0 Glucose to Succinic Acid 0.6
Xylan to Xylose 68 Mannan to Mannose 0 Glucose to Acetic Acid 1.5
Xylan to Furfural 13.2 Acetate to Acetic Acid 63 Glucose to Lactic Acid 0.2
Xylan to Tar 0
Galactose to Ethanol 95
Mannan to Oligomer 0 Stages 2 & 3 (5 tanks)3
Galactose to Yeast 2
Mannan to Mannose 68 Cellulose to Glucose 23.5 Galactose to Glycerol 0.4
Mannan to HMF 5 Xylan to Xylose 21.88 Galactose to Succinic Acid 0.6
Galactan to Oligomer 0 Arabinan to Arabinose 0 Galactose to Acetic Acid 1.5
Galactan to Galactose 68 Galactan to Galactose 0 Galactose to Lactic Acid 0.2
Galactan to HMF 5 Mannan to Mannose 0 Mannose to Ethanol 95
Arabinan to Oligomer 0 Acetate to Acetic Acid 33 Mannose to Yeast 2
Arabinan to Arabinose 68
Mannose to Glycerol 0.4
Arabinan to Furfural 5
Mannose to Succinic Acid 0.6
Arabinan to Tar 0
Mannose to Acetic Acid 1.5
Acetate to Oligomer 0
Mannose to Lactic Acid 0.2
Cellulose to Oligomer 60
C5 Fermentation5
Xylose to Ethanol 90
Xylose to Zymomonas 1.9
Xylose to Glycerol 0.3
Xylose to Xylitol 3.6
Xylose to Succinic Acid 0.6
Xylose to Acetic Acid 1.4
Xylose to Lactic Acid 0.2
Arabinose to Ethanol 90
Arabinose to Zymomonas 1.9
Arabinose to Glycerol 0.3
Arabinose to Succinic Acid 0.6
Arabinose to Acetic Acid 1.4
Arabinose to Lactic Acid 0.2
1fc refers to fractional conversion percentage for the associated reaction.
2Stage 1 of enzymatic hydrolysis in AH
pathways consists of two tanks in series, in which the same reactions and conversions listed take place in each. 3Stages 2 and 3 of enzymatic hydrolysis in AH pathways consists of 5 tanks total connected in series, the same
reactions and conversions listed take place in each of the 5 tanks. 4C6 fermentation takes place in 4 tanks in
parallel fermentation, each tank contains the reactions and conversions listed. 5C5 fermentation takes place
separately from C6 fermentation in AH pathways without xylitol co-production. C5 fermentation does not take
place in pathways with xylitol co-production.
135
Table A.32 Reaction Summary for Hybrid Poplar Autohydrolysis (HPAH) Pathways
Pretreatment Saccharification Fermentation
Reaction fc (%)1 Reaction fc (%) Reaction fc (%)
Cellulose to Oligomer 0 Stage 1 (2 Tanks)2
C6 Fermentation (4 tanks)4
Cellulose to Cellobiose 0 Cellulose to Glucose 41 Glucose to Ethanol 95
Cellulose to Glucose 0 Xylan to Xylose 42.7 Glucose to Yeast 2
Cellulose to HMF 0 Arabinan to Arabinose 0 Glucose to Glycerol 0.4
Xylan to Oligomer 0 Galactan to Galactose 0 Glucose to Succinic Acid 0.6
Xylan to Xylose 45 Mannan to Mannose 0 Glucose to Acetic Acid 1.5
Xylan to Furfural 13.2 Acetate to Acetic Acid 63 Glucose to Lactic Acid 0.2
Xylan to Tar 0
Galactose to Ethanol 95
Mannan to Oligomer 0 Stages 2 & 3 (5 tanks)3
Galactose to Yeast 2
Mannan to Mannose 45 Cellulose to Glucose 23.5 Galactose to Glycerol 0.4
Mannan to HMF 5 Xylan to Xylose 21.88 Galactose to Succinic Acid 0.6
Galactan to Oligomer 0 Arabinan to Arabinose 0 Galactose to Acetic Acid 1.5
Galactan to Galactose 45 Galactan to Galactose 0 Galactose to Lactic Acid 0.2
Galactan to HMF 5 Mannan to Mannose 0 Mannose to Ethanol 95
Arabinan to Oligomer 0 Acetate to Acetic Acid 33 Mannose to Yeast 2
Arabinan to Arabinose 45
Mannose to Glycerol 0.4
Arabinan to Furfural 5
Mannose to Succinic Acid 0.6
Arabinan to Tar 0
Mannose to Acetic Acid 1.5
Acetate to Oligomer 0
Mannose to Lactic Acid 0.2
Cellulose to Oligomer 60
C5 Fermentation5
Xylose to Ethanol 90
Xylose to Zymomonas 1.9
Xylose to Glycerol 0.3
Xylose to Xylitol 3.6
Xylose to Succinic Acid 0.6
Xylose to Acetic Acid 1.4
Xylose to Lactic Acid 0.2
Arabinose to Ethanol 90
Arabinose to Zymomonas 1.9
Arabinose to Glycerol 0.3
Arabinose to Succinic Acid 0.6
Arabinose to Acetic Acid 1.4
Arabinose to Lactic Acid 0.2
1fc refers to fractional conversion percentage for the associated reaction.
2Stage 1 of enzymatic hydrolysis in AH
pathways consists of two tanks in series, in which the same reactions and conversions listed take place in each. 3Stages 2 and 3 of enzymatic hydrolysis in AH pathways consists of 5 tanks total connected in series, the same
reactions and conversions listed take place in each of the 5 tanks. 4C6 fermentation takes place in 4 tanks in
parallel fermentation, each tank contains the reactions and conversions listed. 5C5 fermentation takes place
separately from C6 fermentation in AH pathways without xylitol co-production. C5 fermentation does not take
place in pathways with xylitol co-production.
136
A7 Base Model Changes
Three Aspen Plus models were used as base マラSWノゲ キミ デエキゲ ゲデ┌S┞ aラヴ マラSキaキI;デキラミく NRELげゲ ヲヰヰヲ Iラヴミ
stover dilute acid hydrolysis model (DA base design) [34] was publically available at their website
(http://www.nrel.gov/extranet/biorefinery/aspen models), 2009 AFEX (AFEX base design) models used
in Laser et al. [23,74] were provided by Mark Laser from Dartmouth College and a 2011 autohydrolysis
model (AH base design, proprietary) was received from affiliates at Mascoma Canada Inc. The in-depth
design of DA and AFEX models is not described explicitly in this thesis due to their rigorous description
at the aforementioned sources. In contrast, Mascomaげゲ in-depth design work outside of what is
already described in Section 3.4 is proprietary. Major base model changes are listed in Table A.33.
137
Table A.33 Major Changes to Base Models
Plant
Area/Activity DA (NREL 2002 Model) [34] AFEX (Laser et al. Model) [74] AH (Mascoma Model)
Biomass
Feedstock
Adapted feed composition
to corn stover, switchgrass
and hybrid poplar.
Adapted feed composition to
corn stover, switchgrass and
hybrid poplar.
Adapted feed composition
to corn stover, switchgrass
and hybrid poplar.
Rerouted rejected residues
from size screening to
combustion.
Pretreatment Temperature and sugar
monomer yields changed to
match CAFI experimental
data [46,47,48,58].
Temperature, NH3:Biomass,
H2O:Biomass and sugar
monomer yields changed to
match CAFI experimental data
[46,47,48,58], ammonia
recovery system integrated
with ethanol distillation pre-
heating.
Sugar monomer yields
changed to match CAFI
experimental data
[46,47,48,58]. Modified
single stage flash of
pretreatment steam to two
stage flash (0.4 and 0.2
MPa respectively).
Enzymatic
Hydrolysis
Temperature and sugar
yields changed to match
CAFI experimental data
[46,47,48,58].
Temperature and sugar
monomer yields changed to
match experimental CAFI data
[46,47,48,58].
-
Fermentation Changed temperature and
conditions to match NREL
2010 model [76].
Changed consolidated
bioprocessing to same
fermentation strategy as
NREL 2010 [76].
Adapted fermentation to
ferment all C6 sugars in
addition to glucose. Added
separate C5 fermentation
for non-xylitol co-producing
pathways as in NREL 2010
[76].
Ethanol
Recovery
No change Changed one column
distillation (IHOSR) to two
column ethanol distillation
system as in NREL 2002 [34].
Redesigned distillation to a
two column beer distillation
and rectification scheme.
Condenser of rectification
column is integrated with
beer distillation reboiler.
Residue
Processing
No change Lignin and residues in beer
column bottoms now routed
through evaporator before
combustor instead of directly
to wastewater treatment.
Added waste water
treatment from NREL 2002
[24]. Routed leftover
residues to wastewater
treatment.
Combustor &
Power
Generation
No change
(exception is made for lignin
pellet co-producing
pathways, where electricity
generation was removed)
Reintegrated Rankine
combustor-turbine system
from NREL 2002 [34].
Integrated Rankine
combustor-turbine system
from NREL 2002 [34].
Other Added gasoline blending for
E85 production.
Added gasoline blending for
E85 production.
Added gasoline blending for
E85 production.
138
NRELげゲ ヲヰヰヲ マラSWノ ┘;ゲ ┌ゲWS ;ゲ デエW H;ゲW SWゲキェミ I;ゲW キミ デエキゲ ゲデ┌S┞ ;ミS ┘;ゲ ノWaデ ノ;ヴェWノ┞ ┌ミIエ;ミェWSく Aノノ
models originally followed a standard ethanol producing strategy of pre-treatment fermentation
distillation dehydration final ethanol.
Waste Management
Residues in all models were sent ultimately to combustion; however, differences in residue processing
steps before combustion produced considerably different results. Originally, AFEX models directed
the majority of residues to wastewater treatment, producing a large amount of biogas. This produced
different results when comparing the pelletization of residues in AFEX models to other models, as any
biogas was assumed to immediately be used onsite (resulting in lower energy available in the pellet
product, as this energy was captured in biogas instead). AH models as received were not complete and
did not feature a method to deal with waste residues. Residue processing steps were ultimately
modified to the following: AFEX cases were modified to be dealt with using same strategy as in NREL
2002 [34] already employed in DA. AH cases, which contained no lignin in downstream leftover
residues routed these residues directly to wastewater treatment due to >85% water content in most
streams and combined water content of >95% when the residue streams were combined. Residue
processing followed the general method of multiple effect evaporation + lignin removal by
pneumapress to 60% solids solid residues being delivered to combustor liquid residues delivered
to wastewater treatment remaining wastewater treatment solids dried using a filter press and
delivered to combustor. A costing analysis by NREL of the two options indicated that evaporation was a
more cost effective option [34]. Our own analysis, however (after modeling the AFEX models with the
evaporator option), indicated that sending the residues through wastewater treatment had the
advantage of lower energy demand for the plant overall. For this study, we unified the architecture of
the two models by sending soluble residues through multiple effect evaporation in both cases (higher
energy demand overall), to reflect a conservative approach. Justification and exact details for residue
processing can be found in NREL 2002 documentation [34].
139
Figure A.2 Waste Management System Diagram for All Ethanol Plant Pathway Types
1Stream is only present in lignin pellet co-production pathways.
2Stream is only present in autohydrolysis (AH) pathways with no xylitol co-production.
3Stream is only present in AH pathways with xylitol co-production.
4Stream is only present in AH pathways.
5Entire section is not present in AH pathways.
Pretreatment
Pretreatment conditions were modified to match CAFI experimental data [46,47,48,58] depending on
feedstock. Conversions of initial glucan, and hemicellulose during pretreatment and enzymatic
hydrolysis for the dilute acid model were also modified to match sugar yields from the CAFI project, as
described in section 3.4.1.
Fermentation
Fermentation conditions for DA and AFEX models were modified to be nearly identical; however,
residual ammonia from pre-treatment in the AFEX model was also used to supplement fermentation
requirements for nitrogen. Both models were then further modified to use separate hydrolysis and
fermentation (SHF) in order to use the modified sugar yields from the CAFI project. The AH model
differed from the DA and AFEX cases in that it used a proprietary fermentation method in which a
proprietary yeast was employed and was already operating at SHF. Original AFEX models used
consolidated bioprocessing conditions (where one organism is used to both hydrolyse the feedstock by
producing its own enzymes and fermenting it to ethanol). This was reverted to the NREL 2002 [34]
140
method to maintain greater similarity and due to the fact that CBP has not been realized at high
ethanol yields and short fermentation times [83].
Ethanol Recovery
Distillation and dehydration in all models used a two column + molecular sieve approach. Distillation in
DA and AFEX models were once again modified to be identical, while the proprietary AH model was
modified to distillation improve heat integration, which had already been previously optimized in DA
and AFEX models. The AFEX model from Laser et al. [23,74] originally did not contain a two column +
molecular sieve approach and instead used an energy saving measure in the form of IHOSR
(Intermediate Heat Pumps and Optimal Sidestream Return) distillation. This was removed in order to
ensure comparable downstream operations. The rectification condenser in DA and AFEX models were
integrated with the multiple effect evaporator unit used in these models to dry leftover biomass
residues (in conjunction with separating lignin in a filter press). In the AH model, the rectification
condenser was integrated with the beer distillation reboiler, using a similar strategy as Lohrasbi et al.
[59] and as described in section 3.4.3. The necessary temperature difference between the rectification
and beer distillation columns was achieved by running the beer column in vacuum while increasing the
pressure of the rectification column.
Boiler Modification
Each pathway uses one of two boiler systems. Electricity co-production is used in all pathways except
those producing lignin pellets. The default NREL boiler-turbogenerator system was used, as in Figure
A.3. Steam header pressure is approximately 8.7 MPa, and steam is delivered to the process at high
pressure (1.3 MPa for DA and AFEX, 1.74 MPa for AH), medium pressure (0.44 MPa for DA and AFEX,
1.1 MPa for AH) and low pressure (0.17 MPa for DA and AFEX, not required in AH) variations.
141
Figure A.3 NREL Boiler-Turbogenerator System
Note that boiler heat integration (economizers, combustion air preheater, etc.) is not illustrated.
Pathways producing lignin pellets do not generate electricity. Thus, removal of the turbine from the
Rankine system in Figure A.3 is required and illustrated in Figure A.4. High degrees of superheat
(>200C) and steam pressures (>18 atm) were not required in the absence of a turbine power
generation system. Thus, steam header pressure was lowered to 1.3 MPa for DA and AFEX pathways
and 1.74 MPa for AH pathways with 10C superheat (superheated steam is required in DA and AH
pretreatment as well as residue drying for pelletization). Flue gas and ash streams leaving both the
original and modified boiler systems represent main sources of plant emissions and solid waste (in
addition to gypsum for DA pathways).
142
Figure A.4 Modified NREL Boiler System Note that boiler heat integration (economizers, combustion air preheater, etc.) is not illustrated.
143
Appendix B Life Cycle Results Data Tables
Listed in this section are aggregated life cycle results data tables for all energy and emissions across all
pathways. Values for individual catagories are generally listed on a /hr basis in accordance with the
default ethanol plant capacity 2000 dry Mg of lignocellulosic feedstock per day used in every pathway.
Total values were normalized to a /MJ E85 basis by dividing the total WTW value of the appropriate
category (e.g., kg CO2/hr) by the energy value of the produced E85 in the associated pathway (see Table
4.6). Values were normalized to a /100km basis by dividing the total WTW value of the appropriate
category (e.g., kg CO2/hr) by the number of 100 km units potentially travelled by a model vehicle given
the volume of ethanol produced by the associated pathway. Pathway designations have been re-listed
below in Table B.1 for convenience (see Section 3.1 for more detail).
144
Table B.1 Lignocellulosic Biomass to Ethanol Pathway Designations and Characteristics
Pathway
Name
Feedstock Conversion
Technology
Co-Product(s)
CSDAEL CS DA + SHCF Electricity (EL)
SGDAEL SG DA + SHCF Electricity (EL)
HPDAEL HP DA + SHCF Electricity (EL)
CSDAPE CS DA + SHCF Lignin Pellets (PE)
SGDAPE SG DA + SHCF Lignin Pellets (PE)
HPDAPE HP DA + SHCF Lignin Pellets (PE)
CSAXEL CS AFEX + SHCF Electricity (EL )
SGAXEL SG AFEX + SHCF Electricity (EL )
HPAXEL HP AFEX + SHCF Electricity (EL )
CSAXPE CS AFEX + SHCF Lignin Pellets (PE)
SGAXPE SG AFEX + SHCF Lignin Pellets (PE)
HPAXPE HP AFEX + SHCF Lignin Pellets (PE)
CSAXPR CS AFEX + SHCF Electricity, Protein concentrate (PR)
SGAXPR SG AFEX + SHCF Electricity, Protein concentrate (PR)
CSAHEL CS AH + SHF (Sep C6/C5)d Electricity (EL)
SGAHEL SG AH + SHF (Sep C6/C5) Electricity (EL)
HPAHEL HP AH + SHF (Sep C6/C5) Electricity (EL)
CSAHPE CS AH + SHF (Sep C6/C5) Lignin Pellets (PE)
SGAHPE SG AH + SHF (Sep C6/C5) Lignin Pellets (PE)
HPAHPE HP AH + SHF (Sep C6/C5) Lignin Pellets (PE)
CSAHXE CS AH + SHF (C6 only) Electricity, Xylitol (XE)
SGAHXE SG AH + SHF (C6 only) Electricity, Xylitol (XE)
HPAHXE HP AH + SHF (C6 only) Electricity, Xylitol (XE)
CSAHXP CS AH + SHF (C6 only) Lignin Pellets, Xylitol (XP)
SGAHXP SG AH + SHF (C6 only) Lignin Pellets, Xylitol (XP)
HPAHXP HP AH + SHF (C6 only) Lignin Pellets, Xylitol (XP)
RFG N/A N/A N/A
145
Table B.2 Life Cycle Energy Use and Emissions Results Data Table for CSDAEL Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/hr
Agriculture 56153.4 55345.1 27160.5 3841.8 1.9 4.7 4535.9 3.8 7.8 19.6 2.2 1.4 11.6
Ethanol Plant
Plant Emissions 94686.0 0.0 3.3 94768.3 37.1 43.3 61.9 52.3 3.6 77.1
Plant Chemicals 37660.8 37660.8 8626.9 3853.3 0.0 0.0 3853.3 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 593342.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 159823.1 130008.7 59802.8 11003.0 1.5 14.8 11834.0 20.3 5.8 15.5 4.5 2.0 10.7
Transportation 21541.5 21124.4 19376.5 1631.1 0.0 1.8 1688.7 0.5 2.2 10.2 0.4 0.3 1.8
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-200656.1 -180411.4 -2617.0 -15505.2 -0.3 -23.3 -16190.0 -1.5 -5.2 -14.9 -19.1 -5.1 -25.8
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -94686.0 0.0 0.0 -94686.0 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 667865.0 63727.5 112349.7 4824.1 3.2 1.3 5804.3 60.1 53.9 92.2 40.2 2.2 75.5
Vehicle (PTW)c 872530.7 213204.7 213204.7 14781.2 2.2 1.9 15474.9 25.9 630.7 12.5 5.2 2.7 0.3
Total (WTW)d 1540395.7 276932.3 325554.4 19605.3 5.3 3.2 21279.2 86.1 684.5 104.7 45.3 4.9 75.8
WTW (/MJ E85)e 1.8 0.3 0.4 0.02 0.00001 0.000004 0.02 0.0001 0.0008 0.0001 0.00005 0.00001 0.00009
WTW (/100km)f 530.0 95.3 112.0 6.7 0.002 0.001 7.3 0.03 0.24 0.04 0.02 0.002 0.03
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
146
Table B.3 Life Cycle Energy Use and Emissions Results Data Table for SGDAEL Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/hr
Agriculture 76805.1 75723.2 23387.5 466.4 22.0 5.6 7155.0 7.0 10.1 26.2 2.3 1.4 3.5
Ethanol Plant
Plant Emissions 109742.5 0.0 2.6 109806.3 30.9 53.8 76.9 52.0 4.4 201.1
Plant Chemicals 37566.1 37566.1 11403.6 4036.1 0.0 0.0 4036.1 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 737446.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 123202.6 100219.6 46100.1 8481.9 1.2 11.4 9122.5 15.6 4.4 12.0 3.5 1.6 8.3
Transportation 17938.2 17529.4 16068.1 1351.8 0.0 1.5 1399.6 0.4 1.8 7.9 0.3 0.3 1.5
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-364686.3 -327892.1 -4756.2 -28180.2 -0.6 -42.3 -29424.7 -2.7 -9.5 -27.1 -34.8 -9.3 -46.8
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -109742.5 0.0 0.0 -109742.5 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 628272.3 -96853.8 92203.1 -13844.0 22.6 -21.2 -7647.7 51.2 60.6 95.9 23.3 -1.6 167.5
Vehicle (PTW)c 672606.6 164381.3 164381.3 11396.4 1.7 1.5 11931.1 20.0 486.2 9.6 4.0 2.1 0.2
Total (WTW)d 1300878.9 67527.5 256584.4 -2447.6 24.2 -19.7 4283.4 71.2 546.8 105.5 27.3 0.4 167.7
WTW (/MJ E85)e 1.9 0.1 0.4 -0.004 0.00004 -0.000029 0.01 0.0001 0.0008 0.0002 0.00004 0.000001 0.00025
WTW (/100km)f 580.6 30.1 114.5 -1.1 0.011 -0.009 1.9 0.03 0.24 0.05 0.01 0.000 0.07
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
147
Table B.4 Life Cycle Energy Use and Emissions Results Data Table for HPDAEL Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 33858.4 33320.0 23833.6 -7838.1 1.5 3.0 -7315.9 1.6 5.4 11.9 1.5 1.0 2.2
Ethanol Plant
Plant Emissions 115213.0 0.0 3.4 115296.7 31.8 62.8 89.7 17.8 5.2 205.1
Plant Chemicals 49479.5 49479.5 16794.3 5427.5 0.0 0.0 5427.5 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 860272.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 125791.3 102325.4 47068.7 8660.1 1.2 11.6 9314.2 16.0 4.5 12.2 3.5 1.6 8.5
Transportation 18192.9 17783.5 16301.9 1371.6 0.0 1.6 1420.0 0.4 1.8 8.1 0.3 0.3 1.5
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-399655.1 -359332.8 -5212.3 -30882.3 -0.7 -46.3 -32246.2 -2.9 -10.5 -29.7 -38.1 -10.2 -51.3
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -115213.0 0.0 0.0 -115213.0 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 687939.6 -156424.4 98786.3 -23261.3 2.1 -26.8 -23316.7 46.8 64.1 92.1 -15.0 -2.2 165.9
Vehicle (PTW)c 686739.2 167826.8 167826.8 11635.2 1.7 1.5 12181.2 20.4 496.4 9.8 4.1 2.1 0.2
Total (WTW)d 1374678.8 11402.4 266613.0 -11626.0 3.8 -25.3 -11135.4 67.2 560.5 102.0 -10.9 -0.1 166.2
WTW (/MJ E85)e 2.0 0.02 0.4 -0.017 0.00001 -0.00004 -0.02 0.0001 0.0008 0.0001 -0.00002 -0.0000001 0.0002
WTW (/100km)f 600.9 5.0 116.5 -5.1 0.002 -0.011 -4.9 0.03 0.24 0.04 0.00 0.000 0.07
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
148
Table B.5 Life Cycle Energy Use and Emissions Results Data Table for CSDAPE Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 56153.4 55345.1 27160.5 3841.8 1.9 4.7 4535.9 3.8 7.8 19.6 2.2 1.4 11.6
Ethanol Plant
Plant Emissions 50047.7 0.0 96.1 52450.9 140.8 7.4 24.0 0.0 0.0 0.0
Plant Chemicals 46152.3 46152.3 8696.5 4253.5 0.0 0.0 4253.5 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 460235.6 416838.6 1535.4 1848.2 0.0 68.4 3567.8 2.0 2.7 7.1 0.3 0.2 4.0
Electricity 182469.5 164059.7 2379.8 14099.9 0.3 21.1 14722.4 1.3 4.8 13.6 17.4 4.6 23.4
Gasoline 159822.9 130008.6 59802.7 11003.0 1.5 14.8 11834.0 20.3 5.8 15.5 4.5 2.0 10.7
Transportation 21541.5 21124.4 19376.5 1631.1 0.0 1.8 1688.7 0.5 2.2 10.2 0.4 0.3 1.8
Lignin Pellet Credit
-6612.8 -619461.1 -3111.6 -63549.0 6.1 -67.1 -63394.4 -1.3 35.6 16.1 -94.8 -22.6 -116.1
Net Electricity Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -50047.7 0.0 0.0 -50047.7 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 919762.3 214067.4 115839.7 -26871.5 10.0 139.8 -20388.7 167.4 66.3 106.1 -70.1 -14.0 -64.5
Vehicle (PTW)c 872529.9 213201.8 213201.8 14781.0 2.2 1.9 15474.7 25.9 630.7 12.5 5.2 2.7 0.3
Total (WTW)d 1792292.2 427269.1 329041.5 -12090.5 12.2 141.7 -4914.1 193.3 696.9 118.6 -64.9 -11.3 -64.2
WTW (/MJ E85)e 2.1 0.5 0.4 -0.01 0.00001 0.0002 -0.01 0.0002 0.0008 0.0001 -0.00007 -0.00001 -0.00007
WTW (/100km)f 616.6 147.0 113.2 -4.2 0.004 0.049 -1.7 0.07 0.24 0.04 -0.02 -0.004 -0.02
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
149
Table B.6 Life Cycle Energy Use and Emissions Results Data Table for SGDAPE Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 76805.1 75723.2 23387.5 466.4 22.0 5.6 7155.0 7.0 10.1 26.2 2.3 1.4 3.5
Ethanol Plant
Plant Emissions 43409.8 0.0 91.8 45704.8 131.8 7.1 22.9 0.0 0.0 0.0
Plant Chemicals 49392.5 49392.5 11795.1 4797.1 0.0 0.0 4797.1 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 481879.2 446509.6 1644.6 1979.8 0.0 73.3 3821.8 2.2 2.9 7.6 0.3 0.2 4.3
Electricity 194768.3 175117.6 2540.2 15050.2 0.3 22.6 15714.7 1.4 5.1 14.5 18.6 5.0 25.0
Gasoline 123200.5 100217.9 46099.3 8481.7 1.2 11.4 9122.3 15.6 4.4 12.0 3.5 1.6 8.3
Transportation 17938.0 17529.2 16067.9 1351.8 0.0 1.5 1399.6 0.4 1.8 7.9 0.3 0.3 1.5
Lignin Pellet Credit
-8939.7 -837434.5 -4206.5 -85910.4 8.3 -90.7 -85701.3 -1.8 48.1 21.8 -128.2 -30.5 -157.0
Net Electricity Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -43409.8 0.0 0.0 -43409.8 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 935043.9 27055.6 97328.1 -53783.3 31.9 115.4 -41395.8 156.6 79.5 112.9 -103.2 -22.2 -114.4
Vehicle (PTW)c 672595.2 164378.8 164378.8 11396.2 1.7 1.5 11931.0 20.0 486.2 9.6 4.0 2.1 0.2
Total (WTW)d 1607639.1 191434.4 261706.9 -42387.1 33.6 116.9 -29464.9 176.6 565.6 122.5 -99.2 -20.1 -114.2
WTW (/MJ E85)e 2.4 0.3 0.4 -0.063 0.00005 0.0002 -0.04 0.0003 0.0008 0.0002 -0.0002 -0.00003 -0.0002
WTW (/100km)f 717.5 85.4 116.8 -18.9 0.015 0.052 -13.2 0.08 0.25 0.05 -0.04 -0.009 -0.05
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
150
Table B.7 Life Cycle Energy Use and Emissions Results Data Table for HPDAPE Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 33858.4 33320.0 23833.6 -7838.1 1.5 3.0 -7315.9 1.6 5.4 11.9 1.5 1.0 2.2
Ethanol Plant
Plant Emissions 42114.2 0.0 86.0 44264.7 141.2 6.6 21.3 0.0 0.0 0.0
Plant Chemicals 61722.7 61722.7 17195.5 6212.1 0.0 0.0 6212.1 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 448862.5 410316.3 1511.3 1819.3 0.0 67.3 3512.0 2.0 2.7 7.0 0.3 0.2 3.9
Electricity 201084.5 180796.5 2622.6 15538.3 0.3 23.3 16224.3 1.5 5.3 15.0 19.2 5.1 25.8
Gasoline 124946.2 101638.0 46752.5 8601.9 1.2 11.5 9251.6 15.8 4.5 12.1 3.5 1.6 8.4
Transportation 18109.7 17700.6 16225.6 1365.1 0.0 1.5 1413.4 0.4 1.8 8.1 0.3 0.3 1.5
Lignin Pellet Credit
-9550.8 -894679.5 -4494.0 -91783.0 8.9 -96.9 -91559.7 -1.9 51.4 23.3 -136.9 -32.6 -167.7
Net Electricity Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -42114.2 0.0 0.0 -42114.2 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 879033.2 -89185.4 103647.0 -66084.3 12.0 95.8 -60111.7 160.6 77.6 98.6 -112.2 -24.5 -125.8
Vehicle (PTW)c 682125.7 166701.3 166701.3 11557.2 1.7 1.5 12099.5 20.3 493.0 9.7 4.0 2.1 0.2
Total (WTW)d 1561158.9 77515.9 270348.3 -54527.1 13.7 97.3 -48012.2 180.8 570.7 108.4 -108.1 -22.4 -125.6
WTW (/MJ E85)e 2.3 0.1 0.4 -0.08 0.00002 0.0001 -0.07 0.0003 0.0008 0.0002 -0.0002 -0.00003 -0.0002
WTW (/100km)f 687.0 34.1 119.0 -24.0 0.006 0.043 -21.1 0.08 0.25 0.05 -0.05 -0.010 -0.06
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
151
Table B.8 Life Cycle Energy Use and Emissions Results Data Table for CSAXEL Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 56153.4 55345.1 27160.5 3841.8 1.9 4.7 4535.9 3.8 7.8 19.6 2.2 1.4 11.6
Ethanol Plant
Plant Emissions 98993.1 0.0 17.2 99422.1 43.1 46.3 66.4 52.3 3.8 34.5
Plant Chemicals 40545.6 40545.6 1793.1 2955.9 0.0 0.0 2955.9 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 634764.4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 128697.7 104689.6 48156.2 8860.2 1.2 11.9 9529.4 16.3 4.6 12.5 3.6 1.6 8.7
Transportation 18478.9 18068.9 16564.5 1393.8 0.0 1.6 1443.0 0.4 1.8 8.3 0.3 0.3 1.5
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-241275.1 -216932.2 -3146.7 -18643.9 -0.4 -28.0 -19467.3 -1.8 -6.3 -17.9 -23.0 -6.1 -31.0
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -98993.1 0.0 0.0 -98993.1 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 637364.8 1717.0 90527.6 -1592.3 2.8 7.3 -574.1 61.9 54.3 88.8 35.4 1.0 25.3
Vehicle (PTW)c 702606.3 171639.4 171639.4 11899.4 1.7 1.5 12458.0 20.9 507.9 10.0 4.2 2.2 0.2
Total (WTW)d 1339971.1 173356.4 262167.0 10307.2 4.5 8.9 11884.0 82.7 562.1 98.8 39.5 3.1 25.5
WTW (/MJ E85)e 1.9 0.3 0.4 0.02 0.00001 0.00001 0.02 0.0001 0.0008 0.0001 0.00006 0.000005 0.00004
WTW (/100km)f 572.5 74.1 112.0 4.4 0.002 0.004 5.1 0.04 0.24 0.04 0.02 0.001 0.01
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
152
Table B.9 Life Cycle Energy Use and Emissions Results Data Table for SGAXEL Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 76805.1 75723.2 23387.5 466.4 22.0 5.6 7155.0 7.0 10.1 26.2 2.3 1.4 3.5
Ethanol Plant
Plant Emissions 110183.9 0.0 22.0 110733.9 36.8 58.8 84.3 51.9 4.8 110.0
Plant Chemicals 37238.1 37238.1 1680.3 2743.9 0.0 0.0 2743.9 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 805124.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 101679.4 82711.5 38046.5 7000.1 1.0 9.4 7528.8 12.9 3.7 9.9 2.9 1.3 6.8
Transportation 15820.4 15416.5 14123.6 1187.7 0.0 1.3 1229.7 0.3 1.5 6.6 0.3 0.2 1.2
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-272048.7 -244601.0 -3548.1 -21021.9 -0.5 -31.5 -21950.3 -2.0 -7.1 -20.2 -25.9 -6.9 -34.9
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -110183.9 0.0 0.0 -110183.9 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 764618.7 -33511.7 73689.9 -9623.8 22.5 6.8 -2742.8 55.0 66.9 106.8 31.4 0.8 86.6
Vehicle (PTW)c 555103.8 135605.7 135605.7 9401.3 1.4 1.2 9842.6 16.5 401.2 7.9 3.3 1.7 0.2
Total (WTW)d 1319722.5 102094.0 209295.6 -222.5 23.9 8.1 7099.8 71.5 468.1 114.7 34.7 2.5 86.8
WTW (/MJ E85)e 2.4 0.2 0.4 -0.0004 0.00004 0.00002 0.01 0.0001 0.0008 0.0002 0.00006 0.000005 0.0002
WTW (/100km)f 713.7 55.2 113.2 -0.1 0.013 0.004 3.8 0.04 0.25 0.06 0.02 0.001 0.05
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
153
Table B.10 Life Cycle Energy Use and Emissions Results Data Table for HPAXEL Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 33858.4 33320.0 23833.6 -7838.1 1.5 3.0 -7315.9 1.6 5.4 11.9 1.5 1.0 2.2
Ethanol Plant
Plant Emissions 128237.8 0.0 14.7 128606.3 47.2 76.6 109.6 17.4 6.3 56.1
Plant Chemicals 45030.6 45030.6 1939.9 3245.2 0.0 0.0 3245.2 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 1050281.7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 69816.6 56792.6 26124.1 4806.5 0.7 6.5 5169.5 8.9 2.5 6.8 2.0 0.9 4.7
Transportation 12685.2 12288.6 11245.0 944.7 0.0 1.1 978.1 0.3 1.0 4.7 0.2 0.2 0.9
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-310138.3 -278847.6 -4044.8 -23965.2 -0.5 -35.9 -25023.5 -2.3 -8.1 -23.1 -29.6 -7.9 -39.8
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -128237.8 0.0 0.0 -128237.8 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 901534.2 -131415.9 59097.7 -22806.9 1.7 -10.7 -22578.1 55.6 77.5 109.8 -8.6 0.4 24.1
Vehicle (PTW)c 381153.7 93179.7 93179.7 6460.1 0.9 0.8 6763.1 11.3 275.5 5.4 2.3 1.2 0.1
Total (WTW)d 1282687.8 -38236.2 152277.4 -16346.8 2.6 -9.8 -15814.9 66.9 353.0 115.2 -6.3 1.6 24.2
WTW (/MJ E85)e 3.4 -0.1 0.4 -0.04 0.00001 -0.00003 -0.04 0.0002 0.0009 0.0003 -0.00002 0.000004 0.00006
WTW (/100km)f 1010.2 -30.1 119.9 -12.9 0.002 -0.008 -12.5 0.05 0.28 0.09 0.00 0.001 0.02
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
154
Table B.11 Life Cycle Energy Use and Emissions Results Data Table for CSAXPE Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 56153.4 55345.1 27160.5 3841.8 1.9 4.7 4535.9 3.8 7.8 19.6 2.2 1.4 11.6
Ethanol Plant
Plant Emissions 46465.8 0.0 98.0 48915.3 24.5 47.7 68.3 0.0 0.0 0.0
Plant Chemicals 42144.5 42144.5 1846.2 3058.8 0.0 0.0 3058.8 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 523964.4 450412.3 1659.0 1997.1 0.0 73.9 3855.2 2.2 2.9 7.7 0.3 0.2 4.3
Electricity 188167.6 169182.9 2454.1 14540.2 0.3 21.8 15182.1 1.4 4.9 14.0 17.9 4.8 24.2
Gasoline 128699.2 104690.8 48156.8 8860.3 1.2 11.9 9529.5 16.3 4.6 12.5 3.6 1.6 8.7
Transportation 18479.0 18069.0 16564.7 1393.8 0.0 1.6 1443.0 0.4 1.8 8.3 0.3 0.3 1.5
Lignin Pellet Credit
-6907.6 -647074.2 -3250.3 -66381.8 6.4 -70.1 -66220.2 -1.4 37.2 16.9 -99.0 -23.6 -121.3
Net Electricity Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -46465.8 0.0 0.0 -46465.8 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 950700.5 192770.4 94590.9 -32689.8 10.0 141.7 -26166.2 47.2 107.0 147.2 -74.7 -15.3 -71.1
Vehicle (PTW)c 702614.3 171641.5 171641.5 11899.6 1.7 1.5 12458.2 20.9 507.9 10.0 4.2 2.2 0.2
Total (WTW)d 1653314.9 364412.0 266232.4 -20790.2 11.7 143.3 -13708.0 68.1 614.9 157.3 -70.5 -13.2 -70.9
WTW (/MJ E85)e 2.4 0.5 0.4 -0.03 0.00002 0.0002 -0.02 0.0001 0.0009 0.0002 -0.0001 -0.00002 -0.0001
WTW (/100km)f 706.4 155.7 113.7 -8.9 0.005 0.061 -5.9 0.03 0.26 0.07 -0.03 -0.006 -0.03
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
155
Table B.12 Life Cycle Energy Use and Emissions Results Data Table for SGAXPE Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 76805.1 75723.2 23387.5 466.4 22.0 5.6 7155.0 7.0 10.1 26.2 2.3 1.4 3.5
Ethanol Plant
Plant Emissions 49720.6 0.0 124.7 52838.8 21.9 59.2 84.8 0.0 0.0 0.0
Plant Chemicals 38656.2 38656.2 1727.4 2835.2 0.0 0.0 2835.2 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 609065.7 519912.1 1915.0 2305.3 0.0 85.3 4450.0 2.5 3.4 8.9 0.4 0.2 5.0
Electricity 200389.6 180171.7 2613.5 15484.6 0.3 23.2 16168.3 1.5 5.2 14.9 19.1 5.1 25.7
Gasoline 101679.1 82711.2 38046.4 7000.1 1.0 9.4 7528.8 12.9 3.7 9.9 2.9 1.3 6.8
Transportation 15820.3 15416.5 14123.6 1187.7 0.0 1.3 1229.7 0.3 1.5 6.6 0.3 0.2 1.2
Lignin Pellet Credit
-8446.4 -791226.3 -3974.4 -81170.0 7.9 -85.7 -80972.5 -1.7 45.5 20.6 -121.1 -28.9 -148.3
Net Electricity Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -49720.6 0.0 0.0 -49720.6 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 1033969.6 121364.8 77839.0 -51890.7 31.2 163.9 -38487.2 44.4 128.5 171.9 -96.2 -20.6 -106.0
Vehicle (PTW)c 555102.0 135605.3 135605.3 9401.3 1.4 1.2 9842.6 16.5 401.2 7.9 3.3 1.7 0.2
Total (WTW)d 1589071.6 256970.0 213444.3 -42489.5 32.6 165.1 -28644.6 60.9 529.7 179.9 -92.9 -18.9 -105.8
WTW (/MJ E85)e 2.9 0.5 0.4 -0.08 0.00006 0.0003 -0.05 0.0001 0.001 0.0003 -0.0002 -0.00003 -0.0002
WTW (/100km)f 859.4 139.0 115.4 -23.0 0.02 0.09 -15.5 0.03 0.3 0.1 -0.05 -0.01 -0.06
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
156
Table B.13 Life Cycle Energy Use and Emissions Results Data Table for HPAXPE Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 33858.4 33320.0 23833.6 -7838.1 1.5 3.0 -7315.9 1.6 5.4 11.9 1.5 1.0 2.2
Ethanol Plant
Plant Emissions 52348.0 0.0 154.3 56206.3 18.0 3.9 5.6 0.0 0.0 0.0
Plant Chemicals 45742.4 45742.4 1963.3 3291.1 0.0 0.0 3291.1 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 689824.0 636404.5 2344.1 2821.8 0.0 104.4 5447.1 3.1 4.1 10.9 0.4 0.3 6.1
Electricity 258003.9 231973.2 3364.9 19936.6 0.4 29.9 20816.8 1.9 6.7 19.2 24.6 6.6 33.1
Gasoline 69805.9 56783.9 26120.0 4805.8 0.7 6.5 5168.8 8.9 2.5 6.8 2.0 0.9 4.7
Transportation 12684.1 12287.5 11244.0 944.6 0.0 1.1 978.1 0.3 1.0 4.7 0.2 0.2 0.9
Lignin Pellet Credit
-11022.1 -1032505.4 -5186.4 -105922.2 10.2 -111.9 -105664.5 -2.2 59.3 26.9 -158.0 -37.6 -193.5
Net Electricity Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -52348.0 0.0 0.0 -52348.0 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 1098896.6 -15993.9 63683.7 -81960.5 12.9 187.3 -73420.3 31.4 83.1 85.9 -129.4 -28.8 -146.5
Vehicle (PTW)c 381095.2 93165.7 93165.7 6459.1 0.9 0.8 6762.1 11.3 275.5 5.4 2.3 1.2 0.1
Total (WTW)d 1479991.8 77171.8 156849.3 -75501.4 13.9 188.2 -66658.2 42.7 358.5 91.3 -127.1 -27.6 -146.4
WTW (/MJ E85)e 3.9 0.2 0.4 -0.2 0.00004 0.0005 -0.2 0.0001 0.0009 0.0002 -0.0003 -0.00007 -0.0004
WTW (/100km)f 1165.8 60.8 123.6 -59.5 0.01 0.1 -52.5 0.03 0.3 0.07 -0.1 -0.02 -0.1
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
157
Table B.14 Life Cycle Energy Use and Emissions Results Data Table for CSAXPR Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 56153.4 55345.1 27160.5 3841.8 1.9 4.7 4535.9 3.8 7.8 19.6 2.2 1.4 11.6
Ethanol Plant
Plant Emissions 95155.2 0.0 15.7 95547.4 43.4 42.1 60.2 52.3 3.5 21.0
Plant Chemicals 42752.6 42752.6 1866.8 3097.8 0.0 0.0 3097.8 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 576399.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 128722.9 104710.1 48165.7 8861.9 1.2 11.9 9531.2 16.3 4.6 12.5 3.6 1.6 8.7
Transportation 18481.4 18071.3 16566.8 1393.9 0.0 1.6 1443.2 0.4 1.8 8.3 0.3 0.3 1.5
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-58434.5 -52538.9 -762.1 -4515.4 -0.1 -6.8 -4714.8 -0.4 -1.5 -4.3 -5.6 -1.5 -7.5
Protein or Xylitol Credit
-5555.8 -5435.9 -3512.5 -400.5 -0.6 -0.6 -582.7 -0.3 -1.0 -2.2 -0.3 -0.2 -1.5
Biomass Credit -95155.2 0.0 0.0 -95155.2 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 758519.5 162904.2 89485.2 12279.6 2.6 26.5 13702.9 63.3 53.8 94.0 52.5 5.1 33.8
Vehicle (PTW)c 702744.0 171731.3 171731.3 11905.9 1.7 1.5 12464.6 20.9 508.0 10.0 4.2 2.2 0.2
Total (WTW)d 1461263.6 334635.6 261216.5 24185.5 4.3 28.0 26167.5 84.1 561.8 104.1 56.7 7.3 34.0
WTW (/MJ E85)e 2.1 0.5 0.4 0.03 0.00001 0.00004 0.04 0.0001 0.0008 0.0001 0.00008 0.00001 0.00005
WTW (/100km)f 624.2 142.9 111.6 10.3 0.002 0.01 11.2 0.04 0.2 0.04 0.02 0.003 0.01
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
158
Table B.15 Life Cycle Energy Use and Emissions Results Data Table for SGAXPR Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 76805.1 75723.2 23387.5 466.4 22.0 5.6 7155.0 7.0 10.1 26.2 2.3 1.4 3.5
Ethanol Plant
Plant Emissions 105798.5 0.0 17.3 106230.7 36.7 52.4 75.0 51.9 4.3 93.2
Plant Chemicals 38869.2 38869.2 1736.5 2848.3 0.0 0.0 2848.3 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 717953.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 101750.6 82769.4 38073.2 7005.0 1.0 9.4 7534.1 12.9 3.7 9.9 2.9 1.3 6.8
Transportation 15827.4 15423.5 14130.0 1188.2 0.0 1.3 1230.2 0.3 1.5 6.6 0.3 0.2 1.2
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-151871.4 -136548.7 -1980.7 -11735.5 -0.3 -17.6 -12253.8 -1.1 -4.0 -11.3 -14.5 -3.9 -19.5
Protein or Xylitol Credit
-6496.5 -6356.4 -4107.3 -468.3 -0.7 -0.7 -681.4 -0.3 -1.2 -2.5 -0.3 -0.2 -1.7
Biomass Credit -105798.5 0.0 0.0 -105798.5 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 792837.9 69880.3 71239.2 -695.9 22.1 15.4 6264.7 55.5 62.5 103.9 42.5 3.2 83.5
Vehicle (PTW)c 555492.8 135773.0 135773.0 9413.0 1.4 1.2 9854.7 16.5 401.5 7.9 3.3 1.7 0.2
Total (WTW)d 1348330.8 205653.3 207012.3 8717.2 23.4 16.6 16119.4 72.0 464.0 111.8 45.8 4.9 83.7
WTW (/MJ E85)e 2.4 0.4 0.4 0.02 0.00004 0.00003 0.03 0.0001 0.0008 0.0002 0.00008 0.000009 0.0002
WTW (/100km)f 728.7 111.1 111.9 4.7 0.01 0.009 8.7 0.04 0.3 0.06 0.02 0.003 0.05
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
159
Table B.16 Life Cycle Energy Use and Emissions Results Data Table for CSAHEL Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 56153.4 55345.1 27160.5 3841.8 1.9 4.7 4535.9 3.8 7.8 19.6 2.2 1.4 11.6
Ethanol Plant
Plant Emissions 97734.3 0.0 35.1 98610.5 5.5 51.7 76.3 52.3 4.3 49.6
Plant Chemicals 67841.8 67841.8 4553.4 6150.7 0.0 0.0 6150.7 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 708880.9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 131678.4 107114.3 49271.6 9065.4 1.3 12.2 9750.1 16.7 4.8 12.8 3.7 1.7 8.9
Transportation 18772.2 18361.5 16833.8 1416.5 0.0 1.6 1466.5 0.4 1.9 8.5 0.3 0.3 1.5
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-237732.6 -213747.1 -3100.5 -18370.2 -0.4 -27.5 -19181.5 -1.7 -6.2 -17.7 -22.7 -6.0 -30.5
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -97734.3 0.0 0.0 -97734.3 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 745593.9 34915.5 94718.7 2104.1 2.8 25.9 3598.0 24.6 59.9 99.4 35.8 1.6 41.0
Vehicle (PTW)c 718879.0 175655.8 175655.8 12178.0 1.8 1.6 12749.5 21.3 519.6 10.3 4.3 2.2 0.3
Total (WTW)d 1464472.9 210571.3 270374.5 14282.1 4.6 27.5 16347.5 46.0 579.6 109.7 40.1 3.8 41.3
WTW (/MJ E85)e 2.0 0.3 0.4 0.02 0.00001 0.00004 0.02 0.0001 0.0008 0.0002 0.00006 0.000005 0.00006
WTW (/100km)f 611.5 87.9 112.9 6.0 0.002 0.01 6.8 0.02 0.2 0.05 0.02 0.002 0.02
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
160
Table B.17 Life Cycle Energy Use and Emissions Results Data Table for SGAHEL Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 76805.1 75723.2 23387.5 466.4 22.0 5.6 7155.0 7.0 10.1 26.2 2.3 1.4 3.5
Ethanol Plant
Plant Emissions 94130.4 0.0 34.0 94979.4 5.2 49.1 73.9 51.9 4.0 44.1
Plant Chemicals 56696.7 56696.7 3786.1 5134.9 0.0 0.0 5134.9 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 673240.5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 127017.3 103322.7 47527.5 8744.5 1.2 11.7 9405.0 16.1 4.6 12.3 3.6 1.6 8.5
Transportation 18313.5 17903.9 16412.7 1380.9 0.0 1.6 1429.7 0.4 1.8 8.2 0.3 0.3 1.5
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-207839.0 -186869.6 -2710.6 -16060.2 -0.4 -24.1 -16769.5 -1.5 -5.4 -15.5 -19.8 -5.3 -26.7
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -94130.4 0.0 0.0 -94130.4 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 744234.1 66777.0 88403.1 -333.5 22.9 28.8 7204.1 27.2 60.2 105.2 38.3 2.0 31.0
Vehicle (PTW)c 693432.6 169438.1 169438.1 11746.9 1.7 1.5 12298.2 20.6 501.2 9.9 4.1 2.1 0.2
Total (WTW)d 1437666.7 236215.0 257841.2 11413.4 24.6 30.3 19502.3 47.8 561.4 115.1 42.4 4.1 31.2
WTW (/MJ E85)e 2.1 0.3 0.4 0.02 0.00004 0.00004 0.03 0.0001 0.0008 0.0002 0.00006 0.000006 0.00005
WTW (/100km)f 622.4 102.3 111.6 4.9 0.01 0.01 8.4 0.02 0.2 0.05 0.02 0.002 0.01
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
161
Table B.18 Life Cycle Energy Use and Emissions Results Data Table for HPAHEL Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 33858.4 33320.0 23833.6 -7838.1 1.5 3.0 -7315.9 1.6 5.4 11.9 1.5 1.0 2.2
Ethanol Plant
Plant Emissions 109802.4 0.0 25.8 110447.9 5.7 58.0 84.3 17.6 4.8 49.5
Plant Chemicals 73948.6 73948.6 4940.0 6705.9 0.0 0.0 6705.9 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 795394.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 122449.7 99607.2 45818.4 8430.0 1.2 11.3 9066.8 15.5 4.4 11.9 3.4 1.5 8.2
Transportation 17864.1 17455.5 16000.1 1346.1 0.0 1.5 1393.7 0.4 1.7 7.9 0.3 0.3 1.4
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-300731.0 -270389.5 -3922.1 -23238.2 -0.5 -34.8 -24264.5 -2.2 -7.9 -22.4 -28.7 -7.6 -38.6
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -109802.4 0.0 0.0 -109802.4 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 742784.0 -46058.1 86669.9 -14594.3 2.2 6.8 -13768.7 21.0 61.8 93.6 -5.9 -0.1 22.8
Vehicle (PTW)c 668496.5 163344.8 163344.8 11324.5 1.7 1.5 11855.9 19.8 483.2 9.5 4.0 2.0 0.2
Total (WTW)d 1411280.5 117286.7 250014.7 -3269.9 3.9 8.3 -1912.7 40.8 545.0 103.1 -1.9 2.0 23.1
WTW (/MJ E85)e 2.1 0.2 0.4 -0.005 0.00001 0.00001 -0.003 0.0001 0.0008 0.0002 -0.000003 0.000003 0.00003
WTW (/100km)f 633.7 52.7 112.3 -1.5 0.002 0.004 -0.9 0.02 0.24 0.05 -0.001 0.001 0.01
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
162
Table B.19 Life Cycle Energy Use and Emissions Results Data Table for CSAHPE Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 56153.4 55345.1 27160.5 3841.8 1.9 4.7 4535.9 3.8 7.8 19.6 2.2 1.4 11.6
Ethanol Plant
Plant Emissions 47473.3 0.0 96.5 49884.8 18.7 74.2 107.2 0.0 0.0 0.4
Plant Chemicals 68308.6 68308.6 4570.2 6182.2 0.0 0.0 6182.2 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 470968.2 328787.6 1211.0 1457.8 0.0 54.0 2814.2 1.6 2.1 5.6 0.2 0.1 3.1
Electricity 171487.8 154186.0 2236.6 13251.3 0.3 19.9 13836.3 1.3 4.5 12.8 16.4 4.4 22.0
Gasoline 131680.7 107116.1 49272.4 9065.6 1.3 12.2 9750.3 16.7 4.8 12.8 3.7 1.7 8.9
Transportation 18772.4 18361.7 16834.0 1416.5 0.0 1.6 1466.5 0.4 1.9 8.5 0.3 0.3 1.5
Lignin Pellet Credit
-6109.7 -572327.2 -2874.8 -58713.6 5.7 -62.0 -58570.8 -1.2 32.9 14.9 -87.6 -20.9 -107.3
Net Electricity Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -47473.3 0.0 0.0 -47473.3 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 911261.4 159778.0 98409.8 -23498.5 9.3 126.7 -17573.8 41.2 128.1 181.3 -64.8 -13.0 -59.8
Vehicle (PTW)c 718891.3 175658.8 175658.8 12178.2 1.8 1.6 12749.7 21.3 519.6 10.3 4.3 2.2 0.3
Total (WTW)d 1630152.7 335436.8 274068.7 -11320.3 11.0 128.3 -4824.1 62.6 647.8 191.5 -60.6 -10.8 -59.5
WTW (/MJ E85)e 2.3 0.5 0.4 -0.02 0.00002 0.0002 -0.007 0.0001 0.0009 0.0003 -0.00008 -0.00002 -0.00008
WTW (/100km)f 680.7 140.1 114.4 -4.7 0.005 0.05 -2.0 0.03 0.3 0.08 -0.03 -0.005 -0.02
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
163
Table B.20 Life Cycle Energy Use and Emissions Results Data Table for SGAHPE Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 76805.1 75723.2 23387.5 466.4 22.0 5.6 7155.0 7.0 10.1 26.2 2.3 1.4 3.5
Ethanol Plant
Plant Emissions 46478.0 0.0 95.7 48871.0 15.1 71.7 104.3 0.0 0.0 0.6
Plant Chemicals 57081.2 57081.2 3799.8 5160.8 0.0 0.0 5160.8 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 467117.3 330391.5 1216.9 1464.9 0.0 54.2 2827.9 1.6 2.1 5.6 0.2 0.1 3.2
Electricity 180048.8 161883.2 2348.2 13912.8 0.3 20.9 14527.1 1.3 4.7 13.4 17.2 4.6 23.1
Gasoline 127013.2 103319.4 47525.9 8744.2 1.2 11.7 9404.7 16.1 4.6 12.3 3.6 1.6 8.5
Transportation 18313.1 17903.5 16412.3 1380.9 0.0 1.6 1429.7 0.4 1.8 8.2 0.3 0.3 1.5
Lignin Pellet Credit
-5796.6 -542998.6 -2727.5 -55704.9 5.4 -58.8 -55569.4 -1.1 31.2 14.1 -83.1 -19.8 -101.8
Net Electricity Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -46478.0 0.0 0.0 -46478.0 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 920582.2 203303.4 91963.2 -24574.8 29.0 130.9 -12671.2 40.4 126.2 184.3 -59.5 -11.8 -61.4
Vehicle (PTW)c 693410.2 169432.6 169432.6 11746.5 1.7 1.5 12297.8 20.6 501.2 9.9 4.1 2.1 0.2
Total (WTW)d 1613992.4 372736.0 261395.8 -12828.3 30.7 132.4 -373.4 61.0 627.5 194.2 -55.4 -9.7 -61.2
WTW (/MJ E85)e 2.3 0.5 0.4 -0.02 0.00004 0.0002 -0.001 0.0001 0.0009 0.0003 -0.000080 -0.00001 -0.00009
WTW (/100km)f 698.7 161.4 113.2 -5.6 0.01 0.06 -0.2 0.03 0.3 0.08 -0.02 -0.004 -0.03
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
164
Table B.21 Life Cycle Energy Use and Emissions Results Data Table for HPAHPE Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 33858.4 33320.0 23833.6 -7838.1 1.5 3.0 -7315.9 1.6 5.4 11.9 1.5 1.0 2.2
Ethanol Plant
Plant Emissions 43721.7 0.0 91.0 45996.2 21.3 81.9 117.7 0.0 0.0 0.2
Plant Chemicals 74578.6 74578.6 4962.8 6748.6 0.0 0.0 6748.6 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 446125.1 349103.0 1285.9 1547.9 0.0 57.3 2988.1 1.7 2.3 6.0 0.2 0.1 3.3
Electricity 179887.9 161738.5 2346.1 13900.4 0.3 20.8 14514.1 1.3 4.7 13.4 17.2 4.6 23.1
Gasoline 122459.0 99614.7 45821.8 8430.7 1.2 11.3 9067.4 15.5 4.4 11.9 3.4 1.5 8.2
Transportation 17865.0 17456.4 16000.9 1346.2 0.0 1.5 1393.7 0.4 1.7 7.9 0.3 0.3 1.4
Lignin Pellet Credit
-7501.8 -702737.5 -3529.9 -72092.1 7.0 -76.1 -71916.7 -1.5 40.4 18.3 -107.5 -25.6 -131.7
Net Electricity Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Protein or Xylitol Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Biomass Credit -43721.7 0.0 0.0 -43721.7 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 867272.1 33073.6 90721.2 -47956.5 10.0 108.8 -42246.2 40.3 140.8 187.0 -84.9 -18.1 -93.2
Vehicle (PTW)c 668546.9 163357.1 163357.1 11325.3 1.7 1.5 11856.8 19.9 483.2 9.5 4.0 2.0 0.2
Total (WTW)d 1535818.9 196430.8 254078.3 -36631.2 11.7 110.3 -30389.4 60.2 624.1 196.5 -81.0 -16.1 -93.0
WTW (/MJ E85)e 2.3 0.3 0.4 -0.05 0.00002 0.0002 -0.05 0.0001 0.0009 0.0003 -0.0001 -0.00002 -0.0001
WTW (/100km)f 689.6 88.2 114.1 -16.4 0.005 0.05 -13.6 0.03 0.3 0.09 -0.04 -0.007 -0.04
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
165
Table B.22 Life Cycle Energy Use and Emissions Results Data Table for CSAHXE Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 56153.4 55345.1 27160.5 3841.8 1.9 4.7 4535.9 3.8 7.8 19.6 2.2 1.4 11.6
Ethanol Plant
Plant Emissions 89801.0 0.0 35.2 90681.7 5.5 49.1 72.4 52.3 4.0 49.7
Plant Chemicals 67841.8 67841.8 4553.4 6150.7 0.0 0.0 6150.7 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 673437.6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 85608.8 69638.8 32033.2 5893.7 0.8 7.9 6338.9 10.9 3.1 8.3 2.4 1.1 5.8
Transportation 14239.1 13838.9 12671.7 1065.1 0.0 1.2 1102.8 0.3 1.3 5.6 0.2 0.2 1.1
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-166965.7 -150120.1 -2177.6 -12901.9 -0.3 -19.3 -13471.6 -1.2 -4.4 -12.4 -15.9 -4.2 -21.4
Protein or Xylitol Credit
-40240.1 -37436.9 -3832.7 -5286.1 -3.2 -10.9 -6525.5 -0.1 -0.1 -0.4 -0.1 0.0 -0.2
Biomass Credit -89801.0 0.0 0.0 -89801.0 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 690074.9 19107.4 70408.5 -1236.6 -0.7 18.7 -988.1 19.1 56.8 93.1 41.1 2.4 46.4
Vehicle (PTW)c 467368.7 114199.5 114199.5 7917.3 1.2 1.0 8288.9 13.9 337.8 6.7 2.8 1.4 0.2
Total (WTW)d 1157443.6 133307.0 184608.0 6680.7 0.4 19.8 7300.7 33.0 394.6 99.8 43.9 3.9 46.6
WTW (/MJ E85)e 2.5 0.3 0.4 0.01 0.000001 0.00004 0.02 0.0001 0.0008 0.0002 0.00009 0.000008 0.0001
WTW (/100km)f 743.4 85.6 118.6 4.3 0.0003 0.01 4.7 0.02 0.3 0.06 0.03 0.002 0.03
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
166
Table B.23 Life Cycle Energy Use and Emissions Results Data Table for SGAHXE Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 76805.1 75723.2 23387.5 466.4 22.0 5.6 7155.0 7.0 10.1 26.2 2.3 1.4 3.5
Ethanol Plant
Plant Emissions 85212.1 0.0 34.1 86065.6 5.2 46.3 69.6 51.9 3.8 44.3
Plant Chemicals 56696.7 56696.7 3786.1 5134.9 0.0 0.0 5134.9 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 634809.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 74818.2 60861.2 27995.6 5150.9 0.7 6.9 5539.9 9.5 2.7 7.3 2.1 0.9 5.0
Transportation 13177.3 12779.6 11696.9 982.8 0.0 1.1 1017.6 0.3 1.1 5.0 0.2 0.2 0.9
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-134074.3 -120547.2 -1748.6 -10360.3 -0.2 -15.5 -10817.8 -1.0 -3.5 -10.0 -12.8 -3.4 -17.2
Protein or Xylitol Credit
-44636.8 -41527.3 -4249.5 -5864.4 -3.6 -12.1 -7239.5 -0.1 -0.1 -0.5 -0.1 0.0 -0.3
Biomass Credit -85212.1 0.0 0.0 -85212.1 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 677595.4 43986.3 60868.0 -4489.7 18.9 20.1 1643.7 20.9 56.6 97.6 43.6 2.9 36.3
Vehicle (PTW)c 408459.2 99804.9 99804.9 6919.3 1.0 0.9 7244.1 12.1 295.2 5.8 2.4 1.3 0.1
Total (WTW)d 1086054.6 143791.2 160672.9 2429.7 19.9 21.0 8887.7 33.0 351.8 103.4 46.1 4.1 36.5
Total (/MJ E85)e 2.7 0.4 0.4 0.006 0.00005 0.00005 0.02 0.0001 0.0009 0.0003 0.0001 0.00001 0.00009
Total (/100km)f 798.2 105.7 118.1 1.8 0.01 0.02 6.5 0.02 0.3 0.08 0.03 0.003 0.03
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
167
Table B.24 Life Cycle Energy Use and Emissions Results Data Table for HPAHXE Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 33858.4 33320.0 23833.6 -7838.1 1.5 3.0 -7315.9 1.6 5.4 11.9 1.5 1.0 2.2
Ethanol Plant
Plant Emissions 106414.1 0.0 30.9 107187.3 5.7 57.8 83.8 17.6 4.8 50.2
Plant Chemicals 73948.6 73948.6 4940.0 6705.9 0.0 0.0 6705.9 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Electricity 792053.2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Gasoline 92632.5 75352.2 34661.3 6377.3 0.9 8.6 6858.9 11.7 3.3 9.0 2.6 1.2 6.2
Transportation 14930.2 14528.4 13306.3 1118.7 0.0 1.3 1158.3 0.3 1.3 6.1 0.2 0.2 1.1
Lignin Pellet Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Net Electricity Credit
-270734.4 -243419.3 -3530.9 -20920.3 -0.5 -31.4 -21844.2 -2.0 -7.1 -20.1 -25.8 -6.9 -34.8
Protein or Xylitol Credit
-27207.0 -25312.3 -2597.4 -3571.7 -2.2 -7.4 -4409.2 -0.1 -0.1 -0.3 0.0 0.0 -0.2
Biomass Credit -106414.1 0.0 0.0 -106414.1 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 709481.5 -71582.3 70612.9 -18128.3 -0.2 5.0 -18073.1 17.3 60.7 90.3 -4.0 0.2 24.9
Vehicle (PTW)c 505713.5 123569.2 123569.2 8566.9 1.3 1.1 8968.9 15.0 365.5 7.2 3.0 1.5 0.2
Total (WTW)d 1215195.0 51986.8 194182.0 -9561.4 1.0 6.1 -9104.1 32.3 426.3 97.5 -1.0 1.7 25.0
Total (/MJ E85)e 2.4 0.1 0.4 -0.02 0.000002 0.00001 -0.02 0.0001 0.0008 0.0002 -0.000002 0.000003 0.00005
Total (/100km)f 721.3 30.9 115.3 -5.7 0.0006 0.004 -5.4 0.02 0.3 0.06 -0.001 0.001 0.01
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
168
Table B.25 Life Cycle Energy Use and Emissions Results Data Table for CSAHXP Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 56153.4 55345.1 27160.5 3841.8 1.9 4.7 4535.9 3.8 7.8 19.6 2.2 1.4 11.6
Ethanol Plant
Plant Emissions 45516.1 0.0 115.0 48390.4 18.1 38.5 56.1 0.0 0.0 0.1
Plant Chemicals 68281.9 68281.9 4568.0 6179.0 0.0 0.0 6179.0 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 552936.3 383852.9 1413.9 1702.0 0.0 63.0 3285.5 1.9 2.5 6.6 0.3 0.2 3.7
Electricity 175196.7 157520.6 2284.9 13537.9 0.3 20.3 14135.6 1.3 4.6 13.0 16.7 4.5 22.5
Gasoline 85609.7 69639.5 32033.5 5893.8 0.8 7.9 6338.9 10.9 3.1 8.3 2.4 1.1 5.8
Transportation 14239.2 13839.0 12671.8 1065.1 0.0 1.2 1102.8 0.3 1.3 5.6 0.2 0.2 1.1
Lignin Pellet Credit
-6088.7 -570366.9 -2865.0 -58512.5 5.7 -61.8 -58370.2 -1.2 32.8 14.9 -87.3 -20.8 -106.9
Net Electricity Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Protein or Xylitol Credit
-40240.1 -37436.9 -3832.7 -5286.1 -3.2 -10.9 -6525.5 -0.1 -0.1 -0.4 -0.1 0.0 -0.2
Biomass Credit -45516.1 0.0 0.0 -45516.1 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 906088.2 140675.1 73434.9 -31579.0 5.5 139.3 -26443.7 34.9 90.4 123.6 -65.6 -13.5 -62.6
Vehicle (PTW)c 467373.5 114200.8 114200.8 7917.4 1.2 1.0 8289.0 13.9 337.8 6.7 2.8 1.4 0.2
Total (WTW)d 1373461.7 254875.9 187635.7 -23661.7 6.7 140.3 -18154.7 48.8 428.2 130.3 -62.8 -12.1 -62.4
Total (/MJ E85)e 2.9 0.6 0.4 -0.05 0.00001 0.0003 -0.04 0.0001 0.0009 0.0003 -0.0001 -0.00003 -0.0001
Total (/100km)f 882.2 163.7 120.5 -15.2 0.004 0.09 -11.7 0.03 0.3 0.08 -0.04 -0.008 -0.04
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
169
Table B.26 Life Cycle Energy Use and Emissions Results Data Table for SGAHXP Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 76805.1 75723.2 23387.5 466.4 22.0 5.6 7155.0 7.0 10.1 26.2 2.3 1.4 3.5
Ethanol Plant
Plant Emissions 43227.7 0.0 112.5 46039.7 14.6 37.6 55.6 0.0 0.0 0.1
Plant Chemicals 57065.0 57065.0 3798.3 5158.6 0.0 0.0 5158.6 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 538894.4 370487.5 1364.6 1642.7 0.0 60.8 3171.1 1.8 2.4 6.3 0.3 0.2 3.5
Electricity 183566.9 165046.4 2394.1 14184.7 0.3 21.3 14810.9 1.3 4.8 13.7 17.5 4.7 23.6
Gasoline 74819.0 60861.8 27995.9 5150.9 0.7 6.9 5540.0 9.5 2.7 7.3 2.1 0.9 5.0
Transportation 13177.4 12779.6 11697.0 982.8 0.0 1.1 1017.6 0.3 1.1 5.0 0.2 0.2 0.9
Lignin Pellet Credit
-5519.4 -517033.9 -2597.1 -53041.2 5.1 -56.0 -52912.2 -1.1 29.7 13.5 -79.1 -18.9 -96.9
Net Electricity Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Protein or Xylitol Credit
-44636.8 -41527.3 -4249.5 -5864.4 -3.6 -12.1 -7239.5 -0.1 -0.1 -0.5 -0.1 0.0 -0.3
Biomass Credit -43227.7 0.0 0.0 -43227.7 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 894171.6 183402.5 63790.8 -31319.5 24.6 140.1 -20486.4 33.3 88.3 127.0 -56.8 -11.6 -60.5
Vehicle (PTW)c 408463.7 99806.2 99806.2 6919.4 1.0 0.9 7244.2 12.1 295.2 5.8 2.4 1.3 0.1
Total (WTW)d 1302635.3 283208.7 163597.0 -24400.1 25.6 141.0 -13242.3 45.4 383.5 132.9 -54.4 -10.3 -60.4
Total (/MJ E85)e 3.2 0.7 0.4 -0.06 0.00006 0.0003 -0.03 0.0001 0.0009 0.0003 -0.0001 -0.00003 -0.0002
Total (/100km)f 957.3 208.1 120.2 -17.9 0.02 0.1 -9.7 0.03 0.3 0.1 -0.04 -0.008 -0.04
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.
170
Table B.27 Life Cycle Energy Use and Emissions Results Data Table for HPAHXP Pathway
Life Cycle Stage Total
(MJ/hr) Fossil (MJ/hr)
Petro (MJ/hr)a
kgCO2
/hr kgN2O
/hr kgCH4
/hr kgCO2eq
/hr kgVOC
/hr kgCO/hr
kgNOx
/hr kgPM10
/hr kgPM2.5
/hr kgSOx/h
r
Agriculture 33858.4 33320.0 23833.6 -7838.1 1.5 3.0 -7315.9 1.6 5.4 11.9 1.5 1.0 2.2
Ethanol Plant
Plant Emissions 44450.9 0.0 110.9 47222.2 21.0 37.3 53.9 0.0 0.0 0.0
Plant Chemicals 74525.6 74525.6 4959.2 6743.0 0.0 0.0 6743.0 0.0 0.0 0.0 0.0 0.0 0.0
Natural Gas 538549.8 423948.9 1561.5 1879.8 0.0 69.6 3628.7 2.1 2.8 7.2 0.3 0.2 4.0
Electricity 185079.0 166405.9 2413.8 14301.5 0.3 21.4 14932.9 1.4 4.8 13.8 17.6 4.7 23.8
Gasoline 92633.7 75353.2 34661.8 6377.4 0.9 8.6 6859.0 11.7 3.3 9.0 2.6 1.2 6.2
Transportation 14930.3 14528.5 13306.4 1118.7 0.0 1.3 1158.3 0.3 1.3 6.1 0.2 0.2 1.1
Lignin Pellet Credit
-7489.6 -701595.4 -3524.2 -71975.0 7.0 -76.0 -71799.8 -1.5 40.3 18.3 -107.4 -25.6 -131.5
Net Electricity Credit
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0
Protein or Xylitol Credit
-27207.0 -25312.3 -2597.4 -3571.7 -2.2 -7.4 -4409.2 -0.1 -0.1 -0.3 0.0 0.0 -0.2
Biomass Credit -44450.9 0.0 0.0 -44450.9 0.0 0.0 0.0 0.0 0.0 0.0
Total (WTP)b 904880.3 61174.5 74614.7 -52964.4 7.5 131.3 -47431.8 36.5 95.2 119.8 -85.2 -18.4 -94.2
Vehicle (PTW)c 505720.3 123570.9 123570.9 8567.0 1.3 1.1 8969.1 15.0 365.5 7.2 3.0 1.5 0.2
Total (WTW)d 1410600.6 184745.4 198185.6 -44397.5 8.8 132.4 -38462.8 51.6 460.8 127.1 -82.2 -16.8 -94.0
Total (/MJ E85)e 2.8 0.4 0.4 -0.09 0.00002 0.0003 -0.08 0.0001 0.0009 0.0003 -0.0002 -0.00003 -0.0002
Total (/100km)f 837.3 109.7 117.6 -26.4 0.005 0.08 -22.8 0.03 0.3 0.08 -0.05 -0.01 -0.06
aPetro refers to petroleum energy use.
bHorizontal category refers to the total of the MJ/hr or kg emission/hr values above this row (well-to-pump).
cHorizontal category refers to the MJ/hr or kg emission/hr associated with E85 fuel use (pump-to-wheel in a model vehicle (see Appendix A4).
dHorizontal category refers to the sum of WTP and PTW MJ/hr or kg emission/hr values (well-to-wheel).
eHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by the primary energy content of the E85 produced in this pathway.
Units are consequently in MJ/MJ E85 produced or kg emission/MJ E85 produced. fHorizontal category refers to total WTW MJ/hr or kg emission/hr values normalized by 100km units of distance travelled in a model vehicle from use of the
E85 produced in this pathway. Units are consequently in MJ/100km travelled or kg emission/100km travelled.