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.

1

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

2

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.

4

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].

5

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.

6

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.

7

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.

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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

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EL

DA

PE

AX

EL

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PE

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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

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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

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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

0.10

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Gasoline SGDAEL SGDAPE SGAXEL SGAXPE SGAXPR SGAHEL SGAHPE SGAHXE SGAHXP

g E

mis

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of

Fu

el

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0.60

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Gasoline HPDAEL HPDAPE HPAXEL HPAXPE HPAHEL HPAHPE HPAHXE HPSEXP

g E

mis

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MJ

of

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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

0.20

0.30

0.40

0.50

0.60

0.70

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

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-1.0

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1.5

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of

En

erg

y /

MJ

of

Fu

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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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103

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.