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The Impacts of Xylitol Production from Hemicellulose Residues: Process Design, Life Cycle, and Techno-
Economic Assessment
by
Kelsey Leigh Gerbrandt
A thesis submitted in conformity with the requirements for the degree of Master of Applied Science
Department of Chemical Engineering and Applied Chemistry University of Toronto
© Copyright by Kelsey Gerbrandt 2014
ii
The Impacts of Xylitol Production from Hemicellulose Residues: Process Design, Life Cycle, and Techno-
Economic Assessment
Kelsey Gerbrandt
Masters of Applied Science
Department of Chemical Engineering and Applied Chemistry
University of Toronto
2014
Abstract
Cellulosic ethanol is a promising low-carbon replacement for transportation fuels. The viability
of commercial cellulosic ethanol production is restricted by high process costs. The inclusion of
xylitol as a high-value co-product was investigated as a strategy to offset the high process costs
and provide additional environmental benefits to the production of cellulosic ethanol. Two
pathways for xylitol production are studied: chemical hydrogenation and biological fermentation.
Additional scenarios based on process structure and performance are constructed for both
pathways to assess the assumptions and limitations of the process designs. Results show that
while xylitol hydrogenation can improve the environmental performance of cellulosic ethanol,
fermentation may have the greater potential for improvements, pending the development of
inhibitor tolerant organisms, though results are location dependent. Both hydrogenation and
fermentation have the potential to improve the techno-economic performance of cellulosic
ethanol, though hydrogenation may offer greater improvements in the near-term.
iii
Acknowledgments
I would like to sincerely thank Brad Saville as well as Heather MacLean for their knowledge,
support, and guidance in the production of this thesis. I would also like to thank Mohammad
Pourbafrani, whose knowledge and assistance was invaluable in the creation and fine-tuning of
the process models. The experimental work performed during this thesis would not have been
possible without the generous aid of Tim Sun and Travis Oakes, who analysed my samples and
provided help and advice for many experiments, including several all-nighters. I would also like
to thank Xylitol Canada, for their support and the opportunity they provided to me during my
studies. I would like to further thank Mark Turner for his expertise on financial modelling, and
general support and guidance. Without all your support, this work would not have been possible,
and I am extremely grateful to all those who aided my research. I would like to thank my family
for their love and support and a special thanks to Tyler Schwartz, who has patiently and tirelessly
supported me through my graduate research journey.
iv
Table of Contents
Acknowledgments .......................................................................................................................... iii
Table of Contents ........................................................................................................................... iv
List of Tables ............................................................................................................................... viii
List of Figures ................................................................................................................................ ix
List of Appendices ......................................................................................................................... xi
List of Acronyms .......................................................................................................................... xii
Introduction ................................................................................................................................ 1 1
1.1 Research Objectives ............................................................................................................ 4
1.2 Thesis Outline ..................................................................................................................... 4
1.3 Related publications and presentations to this thesis .......................................................... 5
Literature Review ....................................................................................................................... 6 2
2.1 The Biorefinery ................................................................................................................... 6
2.1.1 First Generation Ethanol ......................................................................................... 7
2.2 Lignocellulosic Biomass ..................................................................................................... 7
2.2.1 Cellulose ................................................................................................................. 9
2.2.2 Hemicellulose ....................................................................................................... 10
2.2.3 Lignin .................................................................................................................... 12
2.2.4 Product Selection .................................................................................................. 14
2.3 Cellulosic Ethanol Production .......................................................................................... 15
2.3.1 Pretreatment .......................................................................................................... 15
2.4 Conventional Xylitol Production ...................................................................................... 20
2.4.1 Acid Pretreatment ................................................................................................. 20
2.4.2 Xylose Purification ............................................................................................... 21
2.4.3 Hydrogenation ....................................................................................................... 22
v
2.4.4 Xylitol Purification ............................................................................................... 23
2.4.5 Limitations ............................................................................................................ 23
2.5 Xylitol Production – Fermentation ................................................................................... 24
2.5.1 Fermentation Metabolic Pathways ........................................................................ 25
2.5.2 Fermentation Conditions and Organism Selection ............................................... 25
2.5.3 Inhibitor Management Strategies .......................................................................... 26
2.5.4 Xylitol Purification from the Fermentation Broth ................................................ 28
2.5.5 Current Fermentation Limitations ......................................................................... 30
2.6 Life Cycle Assessment ...................................................................................................... 31
2.6.1 Co-Product Handling ............................................................................................ 33
2.6.2 Review of Previous Biorefinery LCA Studies ...................................................... 34
Methods .................................................................................................................................... 36 3
3.1 Life Cycle Impact Assessment .......................................................................................... 36
3.1.1 Goal and Context .................................................................................................. 36
3.1.2 System Boundaries and Scope .............................................................................. 36
3.1.3 Co-Product Treatment ........................................................................................... 38
3.1.4 Functional Unit and Impact Category Selection ................................................... 38
3.1.5 Software Used for Process Modeling and Life Cycle Inventory Assessment ...... 39
3.2 Process Modelling ............................................................................................................. 39
3.2.1 Feedstock Production and Delivery ...................................................................... 39
3.2.2 Biorefinery Modelling .......................................................................................... 40
3.2.3 Xylitol Fermentation ............................................................................................. 48
3.2.4 Heat Integration .................................................................................................... 52
3.2.5 Energy Recovery ................................................................................................... 53
3.3 Experimental Work ........................................................................................................... 54
3.3.1 Crystallization ....................................................................................................... 54
vi
3.4 Techno-Economic Considerations .................................................................................... 54
3.4.1 Capital Cost ........................................................................................................... 55
3.4.2 Operating Costs ..................................................................................................... 55
3.4.3 Cash Flow Analysis .............................................................................................. 56
3.5 Sensitivity Analysis .......................................................................................................... 57
3.5.1 Hydrogenation Yield ............................................................................................. 57
3.5.2 Evaporator Technology ......................................................................................... 58
3.5.3 Crystallization Strategy ......................................................................................... 60
3.5.4 Fermentation Inhibitor Tolerance ......................................................................... 61
3.5.5 Techno-Economic Sensitivity ............................................................................... 62
3.5.6 Other Sensitivity Parameters ................................................................................. 63
Results and Discussion ............................................................................................................. 64 4
4.1 Process Modelling and Environmental Results ................................................................ 64
4.1.1 Hydrogenation Pathway ........................................................................................ 64
4.1.2 Fermentation Mass and Energy Balances ............................................................. 79
4.2 Techno-Economic Assessment ......................................................................................... 89
4.2.1 Capital Cost Estimation ........................................................................................ 90
4.2.2 Financial Indicators ............................................................................................... 93
4.2.3 Sensitivity Analysis .............................................................................................. 98
Conclusions, Limitations, and Future Work .......................................................................... 101 5
5.1 Summary ......................................................................................................................... 101
5.2 Implications ..................................................................................................................... 105
5.3 Limitations and Future Work .......................................................................................... 106
References ................................................................................................................................... 108
Appendix A: Stream Tables and Supporting Process Model Information ................................. 123
Appendix B: Experimental Methodology and Results ............................................................... 138
vii
Appendix C: LCA Information and Sample Calculations .......................................................... 147
Appendix D: Financial Modelling Calculations ......................................................................... 154
viii
List of Tables
Table 2-1: Composition of various lignocellulosic materials ......................................................... 8
Table 2-2: Methods of detoxification of hemicellulose hydrolysates [83] ................................... 27
Table 3-1: Hybrid poplar composition (adapted from Kim, 2009[29]) ........................................ 40
Table 3-2: List of values utilized in generating OPEX and TPC .................................................. 56
Table 3-3: Summary of process model scenarios ......................................................................... 63
Table 4-1: Yields utilized in major hydrogenation scenario process stages ................................. 65
Table 4-2: Mass balance for 20, 000 tpy xylitol produced via hydrogenation ............................. 66
Table 4-3: GHG emissions for xylitol hydrogenation process inputs ........................................... 73
Table 4-4: Yields utilized for major xylitol fermentation process stages ..................................... 81
Table 4-5: Fermentation mass balance for Low Tolerance (LT) scenarios and High Tolerance
(HT) scenarios with different evaporation configurations and initial solids loadings .................. 82
Table 4-6: Selected purchased equipment costs ($MM) for major process stages for
hydrogenation and fermentation scenarios ................................................................................... 92
Table 4-7: List of financial assumptions ....................................................................................... 94
Table 4-8: Summary of financial indicators for all scenarios studied .......................................... 95
Table 4-9: Cash flow statement for 10% EC HT TVR Best fermentation scenario ($MM) ........ 96
ix
List of Figures
Figure 2-1: Greenhouse gas emissions for gasoline vs. various sources of corn ethanol (Adapted
from Wang, 2007[6]) .................................................................................................................... 10
Figure 2-2: Sugar platform product options from lignocellulose ................................................. 11
Figure 2-3: Conceptual lignocellulosic biorefinery with xylitol fermentation ............................. 14
Figure 2-4: General life cycle model showing system boundaries, processes, and material and
energy flows .................................................................................................................................. 31
Figure 3-1: Hybrid poplar to ethanol and xylitol block flow diagram including LCA system
boundary ....................................................................................................................................... 37
Figure 3-2: Biorefinery process scenario showing xylitol hydrogenation in conjunction with
cellulosic ethanol and electricity production ................................................................................ 41
Figure 3-3: Block flow diagram of both catalytic hydrogenation (left) and biological
fermentation (right) ....................................................................................................................... 43
Figure 3-4: Xylitol hydrogenation base case (BC) scenario diagram ........................................... 47
Figure 3-5: Low inhibitor (LT) tolerance fermentation block flow diagram ................................ 49
Figure 3-6: Low yield hydrogenation (LYH) scenario block flow diagram ................................. 58
Figure 3-7: Comparison between multiple-effect evaporator (MEE) system, thermal vapour
recompression (TVR) and mechanical vapour recompression (MVR) multiple-evaporator
systems .......................................................................................................................................... 60
Figure 3-8: Two crystallizers in series with no recycle xylitol hydrogenation scenario (2 CR)
block flow diagram ....................................................................................................................... 61
Figure 3-9: High inhibitor tolerance (HT) fermentation scenario block flow diagram ................ 62
x
Figure 4-1: Energy consumption for xylitol hydrogenation pathways (BC: Base Case; LYH: Low
Yield Hydrogenation; 2CR: 2 Crystallizers, No Recycle) ............................................................ 68
Figure 4-2: Turbine process model used to generate electricity (generated in Aspen Plus® with
stream conditions and pressures shown) ....................................................................................... 70
Figure 4-3: LCA results for hydrogenation scenarios ................................................................... 71
Figure 4-4: Contribution of process chemicals to hydrogenation pathway emissions ................. 72
Figure 4-5: Xylitol hydrogenation scenario results utilizing the US Midwest electricity mix ..... 75
Figure 4-6: Isolated evaporation technology scenarios for the xylitol hydrogenation and
purification stage ........................................................................................................................... 77
Figure 4-7: Energy balance for fermentation scenarios ................................................................ 85
Figure 4-8: GHG emissions for xylitol low tolerance (LT) fermentation scenarios ..................... 86
Figure 4-9: GHG emissions associated with chemical inputs into the fermentation scenarios .... 87
Figure 4-10: GHG emissions for xylitol high tolerance (HT) fermentation scenarios ................. 88
Figure 4-11: Summary of best performing scenarios from hydrogenation and fermentation
pathways ....................................................................................................................................... 89
Figure 4-12: Capital cost ranges for all scenarios (Hydrogenation scenarios are shown in red
hatches, fermentation scenarios are displayed in orange) ............................................................. 91
Figure 4-13: Impact of xylitol price on IRR ................................................................................. 98
Figure 4-14: Impacts of changes in CAPEX on IRR .................................................................... 99
xi
List of Appendices
Appendix A: Stream Tables and Supporting Process Model Information
Appendix B: Experimental Methodology and Results
Appendix C: LCA Information and Sample Calculations
Appendix D: Supporting Financial Information
xii
List of Acronyms
AFEX Ammonia Fiber Expansion
ARP Ammonia Recycle Percolation
ATCF After Tax Cash Flow
CAPEX Capital Expenses/Capital Cost
CSL Corn Steep Liquor
DAP Diammonium Phosphate
DS Dry Solids
EBITDA Earnings Before Interest, Taxes, Depreciation, and Amortization
GE General Expenses
GHG Greenhouse Gas
GWP Global Warming Potential
HMF Hydroxymethlyfurfural
HP Hybrid Poplar
HPLC High-Performance Liquid Chromatography
ICIS Independent Chemical Information Services
IPCC Intergovernmental Panel on Climate Change
IRR Internal Rate of Return
ISO International Organization for Standardization
LCA Life Cycle Assessment
LCI Life Cycle Inventory
LCIA Life Cycle Impact Assessment
LHW Liquid Hot Water
MEE Multiple-Effect Evaporation
MVR Multiple-Effect Evaporation with Mechanical Vapour
Recompression
NG Natural Gas
NPV Net Present Value
OPEX Operating Expenses/Operating Costs
ROI Return on Investment
SMB Simulated Moving Bed
SMR Steam Methane Reforming
SLD Straight-Line Depreciation
SS316L Stainless Steel 316L
TPC Total Product Cost
TVR Multiple-Effect Evaporation with Thermal Vapour Recompression
1
Introduction 1
Concerns about the impacts of climate change, resource scarcity and security, and the rapid
growth of world energy markets have led to significant research into alternatives to conventional
fossil fuel products [1]. One area that has been significantly impacted by these issues is the
transportation sector, which relies almost exclusively on energy-dense petroleum fuels to power
its existing infrastructure [2]. There is an incentive to provide alternative fuels that can fit within
the pre-existing transportation grid without needing expensive infrastructure overhauls. It is
unlikely that the future transportation industry will have the ability to rely solely on alternative
fuels such as wind and solar that cannot provide the same energy density as liquid fuels needed
to fuel energy-intensive vehicles such as jets and tankers[3]. Liquid fuels derived from biomass
can potentially displace a segment of fossil fuel use in the transportation sector. Specifically,
ethanol produced from biomass can be blended with gasoline or used as a stand-alone fuel in
automobiles[4]. Similar to gasoline, ethanol can be utilized in the internal combustion engine of
an automobile with minimal modifications required at high ethanol concentrations[4].
Worldwide ethanol production from corn or sugarcane exceeded 89 billion litres in 2013[5].
Ethanol produced from these feedstocks generally has a lower greenhouse gas (GHG) emissions
intensity compared to gasoline[6]. However, as these crops prime agricultural land for their
cultivation, concerns have been raised that they are in competition for soil with food crops and
other activities[6], [7]. In addition, an energy and emissions penalty is associated with these
crops as their cultivation requires fossil fuel inputs[2]. In recent years, alternative biomass
sources that avoid these issues have been explored for ethanol production.
Lignocellulosic materials have attracted significant attention due to their chemical composition
as a feedstock for a variety of biologically derived products, most notably fuels and energy [8].
Lignocellulosic biomass is the most abundant form of renewable carbon in the world and is
found in significant quantities in waste streams from agriculture, forestry, and municipal
systems[9]. Cellulosic ethanol refers to ethanol produced from the cellulose fraction of
lignocellulosic biomass. When cellulosic ethanol produced from a waste stream such as an
agricultural waste, the energy inputs and emissions of crop cultivation are largely avoided as
they are allocated to the main agricultural product and not the lignocellulosic by-product[9]. As a
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result, cellulosic ethanol has been shown to produce significantly less GHG emissions compared
to gasoline or corn and sugarcane ethanol[6].
Despite the environmental success of cellulosic ethanol, concerns exist as cellulosic ethanol has
yet to be largely commercialized due to poor process performance and as a result, elevated
ethanol costs. These technical issues are attributed to factors such as slow enzymatic hydrolysis
kinetics, costly pretreatment, and poor sugar yields[8], [9]. Process improvements may overcome
these technical limitations and decrease the cost of cellulosic ethanol. However, the development
of additional product streams from the other components of lignocellulose may also improve
process economics by providing added sources of revenue to off-set the high ethanol costs and
potentially further improve the environmental performance of cellulosic ethanol.
Lignocellulose is primarily composed of 3 macromolecules: cellulose, hemicellulose, and
lignin[10]. Currently, the production of cellulosic ethanol utilizes nearly all available cellulose,
leaving hemicellulose and lignin as residues, which are commonly burned to generate process
steam and electricity[11]. If hemicellulose and/or lignin can be isolated and transformed into
value-added co-products, they could potentially generate additional revenue, offsetting the high
cost of cellulosic ethanol. There may also be environmental benefits if a co-product displaces a
product conventionally produced from processes that are energy or emissions intensive[12], [13].
Xylitol, a 5-carbon polyol (C5H12O5), is a potential co-product option. Xylitol is commonly used
as a sweetener in products such as gums and toothpastes. It also has anti-cavity properties and is
suitable for diabetic consumption as a sugar substitute[14]. Xylitol is derived from the pentose
sugar xylose, the main monomer of xylan[15]. Xylans comprise between 11-35% of
lignocellulosic biomass, dependent on type and species, which makes xylitol a promising
lignocellulosic co-product option[16].
Conventionally, xylitol is produced from xylose via catalytic hydrogenation[17]. Xylose is
derived from xylan-rich feedstocks such as corn cobs or woodchips. Annual xylitol production
estimated at 130 000 tonnes, with the majority of production occurring in China[14]. Acid
hydrolysis is conventionally used to extract xylose from the biomass[15], [17]. Xylose must be
purified from other contaminant sugars before hydrogenation; a necessary step due to the
challenging separation of xylitol from other polyols formed from contaminant sugars during
hydrogenation such as arabinitol and sorbitol[17],[18]. Generally xylose is purified using a
3
combination of ion exchange chromatography and crystallization. Crystallization is also used to
purify xylitol from contaminants[17]. Crystallization requires highly concentrated solutions;
conventionally concentration is achieved with intensive evaporation[19]. Hydrogenation occurs
at high pressure, temperature, and agitation in the presence of a sponge nickel catalyst[17].
Hydrogenation, evaporation, and crystallization are claimed to be require large energy
inputs[16], [17]. Losses during purification are also reported to lower the overall conversion of
xylans to xylitol to 50-60% [16]. These assertions are used to justify the development of a
biological xylitol pathway, through the fermentation of xylose by microorganisms such as
yeasts[16], [17]. Compared to the non-selective nickel catalyst, fermenting organisms can
selectively consume xylose, indicating that the extensive purification and concentration of xylose
needed before chemical hydrogenation may be unnecessary [17]. As fermentations are generally
carried out at milder conditions, it is claimed that fermentation will reduce process energy-
inputs. A reduction in energy demand could lead to reduced process costs as well as improved
environmental performance. However, as research on xylitol fermentation has been limited to the
lab scale thus far, any potential benefits compared to hydrogenation have yet to be quantified and
these claims are unsubstantiated by any environmental or economic data.
Despite its promise as a potential co-product option, the production of xylitol by any pathway in
conjunction to the cellulosic ethanol process has only been speculative at this point and possible
benefits have yet to be quantified. Life cycle assessment (LCA) is a method used to
quantitatively determine the environmental impacts of process, products or services [12]. LCA is
a commonly used method for assessing biofuels such as cellulosic ethanol [20]–[22]. LCA
methodology can be used to quantify the environmental impacts of xylitol production from
hemicellulose via a chemical hydrogenation process, along with a biological fermentation
process to assess if one pathway has superior environmental performance. To date, few LCA
studies have assessed the environmental impacts of xylitol hydrogenation[13], [23], and those
that have do not involve detailed study of the xylitol pathway. Furthermore, no LCA studies have
been found that investigate the xylitol fermentation pathway.
This work seeks to fill this research gap by conducting detailed LCA studies on the production of
xylitol by both hydrogenation and fermentation. Xylitol production will be situated within a
cellulosic ethanol biorefinery, and will utilize hemicellulose that is conventionally treated as a
4
process residue as a source of xylose. Process residues generated from the xylitol process will be
utilized to generate electricity as a co-product, if applicable.
As the production of co-products such as xylitol is investigated to offset the elevated costs of
cellulosic ethanol, financial analysis of the xylitol pathways will also be conducted. This will aid
in demonstrating whether xylitol can provide an economic benefit to the cellulosic ethanol
process, and if xylitol is a suitable co-product to be produced from hemicellulose residues in this
context. The results of this work are meant to provide an analysis of the feasibility of xylitol as a
co-product from both an environmental and economic perspective.
1.1 Research Objectives
The overall objective of this work is to assess the possible benefits or disadvantages of producing
xylose and xylitol in conjunction to lignocellulosic processes from hemicellulose residues.
1. Evaluate the potential of xylitol as a successful co-product based on factors such as
market demand, availability, processability, time to market, stage of development,
etc.
2. Develop process models from both xylitol hydrogenation and fermentation from
hemicellulose residues rich in xylan in Aspen Plus ®
3. Utilize models to conduct life cycle inventory analysis and techno-economic analysis
to determine the energy usage, environmental impacts, and techno-economic
performance of the processes
4. Determine whether xylitol is a suitable co-product option and offer strategies for
future development into different lignocellulosic processes.
1.2 Thesis Outline
In this thesis the environmental and economic impacts of co-producing xylitol from
hemicellulose residues in a biorefinery are investigated. The layout of the thesis includes a
review of relevant literature, a description of the methodology utilized in the thesis, results and
discussion, and conclusions. Chapter 2 contains the literature review, Chapter 3 discusses thesis
5
methodology, Chapter 4 includes results and a discussion of the results, and Chapter 5 provides a
summary of the thesis, limitations of the work produced, and future considerations.
1.3 Related publications and presentations to this thesis
The following list contains prior presentations and publications related to this thesis:
1. Gerbrandt, K. and Saville, B. “Xylitol production from hemicellulose: process
development and life cycle assessment”, (Poster). 1st Annual FFABNet AGM. Toronto,
Ontario, May 22nd
, 2013.
2. Gerbrandt, K., MacLean, H., and Saville, B. “Xylitol production from hemicellulose:
process development with life cycle and techno-economic assessment”, (Oral
presentation) 63rd
Canadian Chemical Engineering Conference, Fredericton, New
Brunswick, October 21st, 2013.
3. Gerbrandt, K., MacLean, H., and Saville, B. “Case study: Process model for xylitol
production from hemicellulose residues”, (Oral presentation) 2nd
Annual FFABNet
AGM, Kingston, Ontario, May 26th
, 2014.
4. Gerbrandt, K., MacLean, H., and Saville, B. “Xylitol production from hemicellulose
residues: process development with life cycle and techno-economic assessment”, (Oral
presentation) 2nd
Annual BiofuelNet AGM, Ottawa, Ontario, May 28th
, 2014.
5. Gerbrandt, K., MacLean, H., and Saville, B. “Xylitol production from hemicellulose
residues: process development with life cycle and techno-economic assessment”, (Poster)
2nd
Annual BiofuelNet AGM, Ottawa, Ontario, May 28th
, 2014.
6. Gerbrandt, K., Pourbafrani, M., MacLean, H., and Saville, B. “Xylitol from poplar: an
environmental perspective”, (in preparation), 2014
6
Literature Review 2
The concept of producing fuels and chemicals from biomass is not novel, but the performances
of many different pathways have yet to be assessed, particularly at a process and environmental
level. This section provides a summary of lignocellulosic biomass, potential product options, and
an overview of the process pathways that will be investigated to produce xylitol as a co-product
in a cellulosic ethanol biorefinery scenario.
2.1 The Biorefinery
The biorefinery concept is based on the desire to maximize the value and utility of biomass
through the generation of multiple product and/or energy streams from the carbon-rich
feedstock[2]. Similar to a petroleum refinery, the biorefinery would produce a range of products
and energy outputs. Unlike in a petroleum refinery, a renewable, bio-based feedstock is used to
produce the biofuels and bioproducts in the biorefinery; this has the potential to offer significant
benefits, reducing greenhouse gas emissions to mitigate climate change concerns while
conserving non-renewable fossil fuels.
There are several key concepts and goals that have been developed for the biorefinery by
Cherubini[2]. Biomass should be upgraded into fuels and/or value-added products for each major
component, such as the production of ethanol and xylitol from cellulose and hemicellulose,
respectively. Environmental benefits may result from the displacement of a conventional
petroleum product; therefore it is desirable that the biorefinery produce bio-based chemicals and
fuels that can compete with those from the fossil fuel industry. Cellulosic ethanol is a
replacement for gasoline and has been demonstrated to have significantly less GHG
emissions[6]. From a GHG and fossil energy perspective, it is also advantageous for the
biorefinery to be self-sufficient in terms of energy generation. Process residues could be
combusted to produce energy once all reasonable value has been extracted from them. However
if the residue streams are too dilute, alternative measures to extract energy such as anaerobic
digestion to produce biomethane may need to be considered.
7
2.1.1 First Generation Ethanol
Biorefineries that utilize corn or sugarcane feedstocks to produce starch or sugar ethanol as a
main product are well-established worldwide. Globally, bio-ethanol production reached 88.7
billion litres in 2013[5]. Ethanol produced in these facilities is generally blended with gasoline to
produce E10, E22, or E85 fuel, (10, 22, or 85% ethanol by volume, respectively). These blended
fuels are used in light duty flex-fuel vehicles that have been adapted for ethanol combustion[24].
These facilities often produce co-products such as distillers grains and solubles (DGS), which are
utilized as protein-rich animal feed[6], adding additional value to the process that can improve
the financial viability of the biorefinery. The economic performance of first generation ethanol
has been strong: currently, ethanol produced in the US is sold at the refueling stations at lower
price than gasoline, and these biorefineries have been shown to have beneficial financial returns
in the absence of financial incentives[25].
Life cycle assessments have shown that corn ethanol has lower GHG emissions compared to
gasoline except in cases where coal is used to provide process energy to the biorefinery[6].
Despite the environmental benefits, concerns still emerge with the cultivation of energy crops
like corn and sugarcane as they require cultivation on prime agricultural land[2]. This places
energy crops in direct competition for soil with other agricultural products and activities and
adds an energy and emissions penalty to the ethanol produced due to the fossil fuel inputs
required for crop cultivation[6], [7]. These factors in combination with public concern over
issues such as the “food vs. fuel” debate[26], accelerated environmental degradation due to high
intensity cultivation[27], and increased liquid biofuel demand[28] have led to interest in
developing alternative feedstocks for the production of bioethanol and other biofuels.
2.2 Lignocellulosic Biomass
Lignocellulosic biomass, found both in nature and in residue streams from activities such as
agriculture, forestry, and municipal waste treatment, is the most abundant source of biomass on
earth[9], [29]. Common forms of agricultural lignocellulose considered to be candidates as
feedstock for a biorefinery include crop residues such as corn stover and wheat straw and others
that can be grown on marginal land such as hybrid poplar and switchgrass[10]. The impacts of
cultivating crops are associated only with the main product and may be omitted from the
production of the residues as they are conventionally treated as wastes[12]. This leads to reduced
8
energy requirements and emissions for feedstock production when these by-products or residue
streams are utilized as feedstock in a biorefinery, as the residues need only to be collected and
shipped to the biorefinery [9].
Two main processing methods have been proposed for producing value-added chemicals from
lignocellulose: bioconversion processes utilizing the sugars found lignocellulose[30] and thermal
conversion processes such as pyrolysis or gasification that initially break down lignocellulose
into combustion products[10]. Thermal conversion processes reduce the complex lignocellulose
into gases, which are then transformed into products such as methanol and ethanol[2]. The
biorefinery concept benefits from the separation of the major lignocellulose components utilized
in the bioconversion strategy as it allows for the production of diverse products from the multi-
component feedstock. As a result, this work will focus on products produced by bioconversion
techniques and will not include thermal conversion processes, except for the potential to burn
process residues to generate energy.
Lignocellulose is composed of three major macromolecules: cellulose, hemicellulose, and lignin.
The distribution of the different macromolecules varies between species and families of plants
but lignocellulose is generally composed of 40-50% cellulose, 25-30% hemicellulose, and 15-
20% lignin[10], [31]. The composition of different lignocellulosic materials is provided in Table
2-1. The efficacy of producing value-added co-products from hemicellulose and/or lignin is
largely unknown, and has only been recently suggested in literature[2]. This work seeks to
investigate the development of co-products from hemicellulose and lignin in conjunction with
cellulosic ethanol production, and expand upon current knowledge in this area.
Table 2-1: Composition of various lignocellulosic materials
Species Cellulose Hemicellulose Lignin Source
Hybrid Poplar 44 21 29 Kim 2009 [29]
Softwoods 45-50 25-35 35-35
Pan 2005 [32],
Shen 2012[33]
Wheat straw 30 50 20 Saha 2003 [34]
Corn stover 40 25 17 Saha 2003 [34]
Rice straw 35 25 12 Saha 2003 [34]
Sugarcane bagasse 40 24 25 Saha 2003 [34]
Switch grass 45 30 12 Saha 2003 [34]
9
2.2.1 Cellulose
Cellulose has traditionally attracted the most attention due to its use in paper and cardboard
products and more recently due to interest in its glucose composition as a source of fermentable
sugars. In comparison, hemicellulose and lignin have generally been treated as waste products
after their removal from the cellulose fraction[9]. Cellulose is a semi-crystalline polymer
composed of glucose monomers linked via β-(14) glycosidic bonds and is composed of
crystalline and amorphous regions[10],[35]. If the cellulose is hydrolysed, the released glucose
can be used to generate ethanol, but also a wide variety of bioproducts such as succinic acid,
levulinic acid, sorbitol, or other specialty chemicals via fermentation, as displayed in Figure 2-2
[36]. Cellulose-based products are considered to be the main product produced by a biorefinery
because cellulose is the main component of lignocellulose[31]. Cellulosic ethanol is considered
to have the most potential for any product produced from hemicellulose, due to its reduced GHG
footprint compared to gasoline and starch or sugar ethanol, the widespread availability of
lignocellulose, and the increased worldwide consumption of bio-based ethanol[6].
One of the major challenges with the utilization of cellulose is the recalcitrance of lignocellulose.
This is due to the tendency of cellulose chains to associate together via hydrogen bonds, and the
presence of cross-linked covalent bonds that bind cellulose to hemicellulose and lignin[8],[9],
[28],[31]. The recalcitrance of lignocellulose has contributed to increased processing difficulties
such as expensive pretreatment, reduced enzymatic activity during hydrolysis, and lower sugar
yields compared to starch or sugar ethanol processes[8],[9],[37]. Due to these factors, the process
costs to extract glucose from cellulose are higher than those of starch or sucrose, leading to a
price discrepancy between the cost of cellulosic ethanol ($USD 0.57/L) and starch or sugarcane
ethanol ($USD 0.40/L and $USD 0.30/L, respectively)[11].
While the economic performance of cellulosic ethanol lags other fuels, the GHG reductions
achieved by the production of cellulosic ethanol are significant compared to both fossil fuels and
starch or sugar ethanol. Cellulosic ethanol has been shown to reduce GHG emissions by 86%
when compared to gasoline, although this depends significantly upon the process, feedstock, and
co-products[6],[13]. Figure 2-1 displays the GHG intensities of several different first-generation
ethanol pathways located in the US, including different process fuels such as natural gas (NG),
coal, or biomass, compared to gasoline and a cellulosic ethanol pathway.
10
Figure 2-1: Greenhouse gas emissions for gasoline vs. various sources of corn ethanol
(Adapted from Wang, 2007[6])
To obtain the environmental benefits associated with cellulosic ethanol, there is a need for
process improvements that will overcome the price difference between cellulosic and starch or
sugar ethanol. As previously noted, the hemicellulose and lignin fractions of lignocellulose are
typically neglected in cellulosic ethanol processes as residues used only for energy generation,
though some models assume the fermenting organism is able to ferment pentose sugars into
ethanol[11]. While the conversion of hemicellulose monomers into additional ethanol does
improve the ethanol yield, there is the potential to produce high-value product streams from both
hemicellulose and lignin to increase process revenues and allow the feedstock costs to be
allocated across multiple products, thus reducing the higher cellulosic ethanol price[13].
2.2.2 Hemicellulose
Hemicellulose is an amorphous, branched carbohydrate heteropolymer composed of a mixture of
pentose and hexose sugars[35], [38]. The dominate monomer found in hemicellulose is xylose;
however, arabinose, galactose, and mannose are also present[15]. In hardwoods, the most
abundant oligomer is O-acetyl-4-O-methylglucuronoxylan, which composes between 80-90% of
the total hemicellulose[35]. Compared to cellulose, hemicellulose is more readily hydrolysed in
acidic conditions, under high temperature, or in the presence of enzymes[31].
The desire to improve the economic performance of cellulosic ethanol has led to the proposal of
several different pathways to utilize hemicellulose components. One option, displayed in Figure
0
20000
40000
60000
80000
100000
120000
Gasoline Average
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EtOH with
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EtOH with
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11
2-2 is to utilize hemicellulose-derived sugars to generate additional ethanol by pentosan
fermenting organisms, which can improve the yield of cellulosic ethanol processes[11].
Figure 2-2: Sugar platform product options from lignocellulose
Other hemicellulose-based products involve the transformation of xylose into different value-
added products. A harsh pretreatment, especially one that utilizes acid, promotes the degradation
of xylose into furans. Furfural is the main furan produced via the dehydration of pentose sugars
but hydroxymethylfurfural (HMF) is also formed from hexose sugars[28]. The main application
for furfural is primarily in petroleum refineries, where it is used as a solvent in separation
processes[2]. Alternative uses proposed for furfural include its conversion into derivatives such
as the fuel additive methyltetrahydrofuran and tetrahydrofuran, which is used as a solvent or in
the manufacture of a variety of polymers[2], [36]. Tetrahydrofuran is normally produced through
the dehydration of 1,4-butanediol, a petrochemical; thus furan-based products from
hemicellulose can potentially directly replace petroleum based chemicals[39]. Furfural has no
synthetic pathway, making it a unique biochemical with no direct petroleum substitute; as a
result it has not undergone development for wide use as a platform chemical. Consequently,
without additional development and demand, the production of additional furfural could
oversupply an already saturated market, leading to price deflation[36], [40].
A significant concern with the deliberate production of furans is their inhibitory effects on
ethanol fermentation processes[9], [34]. As xylose is the predominant sugar in hemicellulose,
products derived from xylose should be considered. Xylitol, a 5-carbon sugar alcohol (C5H12O5),
can be produced from xylose through catalytic hydrogenation or biological fermentation[36],
12
[41]. Xylitol is predominantly used in the food industry as a sweetener in products such as gums
and jams[14]. Compared to sucrose, xylitol contains approximately 70% of the calories, is
suitable for diabetic consumption, and is reported to be anticariogenic[42], [43]. The feedstock
for commercial xylitol production is typically hemicellulose-rich corn cobs or pulp and paper
waste [14], [43]. Current xylitol production in North America is limited to one facility, with the
majority of production occurring in China. North American demand for xylitol is increasing
annually[14], creating an opportunity to produce additional xylitol from hemicellulose in a
biorefinery.
2.2.3 Lignin
The final major component of lignocellulose, lignin, has a highly amorphous, irregular structure
composed of highly branched phenylpropenyl compounds[44], [45]. The abundance and
methoxylation of the three main monomers of lignin, coumaryl, coniferyl, and sinapyl alcohol,
are species and tissue dependent[44]. Lignin is produced by plants to protect cellulose
macromolecules by preventing enzymatic access to the carbohydrate chains[28]. As a result,
during the production of cellulosic ethanol, it is a priority to remove or restructure lignin in a
pretreatment stage as improperly removed lignin blocks enzymatic access to cellulose and
hemicellulose, resulting in lower oligomer hydrolysis and lower overall process yields[28].
The complex and varied structure of lignin creates a challenge for the production of high-value
chemicals. Doherty states that this complexity and diversity also offers opportunities as lignin
has several promising properties including (1) compatibility with many industrial compounds,
(2) the presence of aromatic rings that improve its mechanical properties, stability, and reactivity,
(3) a variety of functional groups, (4) and promising rheological and viscoelastic properties for it
to be used as a structural material[27]. Lignin is also unique in that it is the largest renewable
source of aromatic compounds[44]. The flavouring agent vanillin historically has been produced
as a by-product of acid sulfate wood pulping process; however, petrochemical feedstocks have
largely replaced lignin[46]. Reaction pathways of lignins to phenolic compounds are not fully
understood at present, largely due to the structural irregularities of lignin and these pathways are
further complicated by the impact of the pretreatment method used on the structure and
composition of lignin molecules[44]. Kleinert describes a one-pot solvolysis conversion method
to produce alkyl phenols and aliphatic hydrocarbons from lignin to avoid the reaction kinetics of
13
individual components. This process, conducted at elevated temperature and pressure and with
hydrogen donating solvents such as tetralin or 9,10-dihydroanthracene, yields a significant range
of products[44]. The large range of products generated in this process mean that the total product
recovery does not exceed 7% of the initial feedstock mixture. This is an example of some of the
challenges faced in producing phenolic compounds from lignins. While there is potential for the
production of high-value chemicals from lignin, this appears to be a long-term opportunity[45].
In many biorefinery and cellulosic ethanol facilities, lignin residues are combusted in a boiler to
generate steam and electricity [11]. The electricity generated by lignin combustion is often in
excess of process demands, which has the potential to improve the environmental performance of
the facility through reduced utility consumption and an electricity co-product GHG emissions
credit[47]. If the lignin and residue streams are dilute and their concentration prior to being fed
to a boiler is uneconomic, anaerobic digestion may be utilized to digest the residues[21], [48].
Anaerobic bacteria break down organic components into methane and other derivatives[49]. The
methane is collected and purified, then fed to the boiler and combusted[21]. The methane
produced from anaerobic digestion can provide partial or complete process energy, with the
potential to produce electricity as a co-product.
Another option for lignin and process residues is to produce pellets for off-site electricity
generation. Lignin and residues are concentrated, if necessary, to between 10-50% moisture
content before they are pelletized[50]. The pellets are subsequently shipped off-site to co-fired
power generation facilities to generate electricity[50], [51]. As the pellets will directly displace
coal in the power stations, they create a large emissions credit[13], though the size of the credit is
also dependent on the GHG intensity of the surrounding electricity generation mixture as coal is
not used to the same extent in all markets[50]. If all process residues are pelletized, the
biorefinery must use grid electricity, thus leading to increased overall utility demands. Pellets
with high cellulose and lignin fractions and low hemicellulose fractions are preferable, due to
improved higher heating values, handling, and storage properties[52]. The composition of the
residues blended with lignin also affects the combustion quality of the pellets; boiler fouling or
handling issues related to particle size are a possibility as the residues may produce smaller
particles than pellets produced from wood chips[53].
14
2.2.4 Product Selection
This study aims to evaluate the environmental and economic impacts of using lignocellulosic
biomass to produce value-added chemicals as co-products to cellulosic ethanol. A near-term
theoretical biorefinery is studied to produce results that are accurate and relevant to the current
development of the bioeconomy. The production of cellulosic ethanol from lignocellulose is
well-studied[6], [54]–[58]; however there is only limited commercial scale production, and the
impacts of producing high value co-products in a cellulosic ethanol facility are not well
understood[2],[16].
Xylitol is selected as the major co-product for this study based on its well-developed commercial
production, North American market potential, and the opportunity to integrate its production into
a biorefinery utilizing hemicellulose residues[14]. The focus of research will be on developing
xylitol production pathways to gain an accurate understanding of the impacts of producing
xylitol as a value-added product and its impact on cellulosic ethanol production.
For the purpose of this study, lignin will be combined with process residues and utilized to
generate steam and electricity for the process, with the potential to produce an electricity co-
product. Figure 2-3 describes the basic scenario for the biorefinery that will be studied in this
work.
Figure 2-3: Conceptual lignocellulosic biorefinery with xylitol fermentation
15
2.3 Cellulosic Ethanol Production
The production of cellulosic ethanol takes place in four process stages: pretreatment, hydrolysis,
fermentation, and distillation[11], [59]. In the first stage, pretreatment, the structure of
lignocellulose is disrupted, enabling enzymatic or chemical access to cellulose molecules in the
subsequent hydrolysis stage. As the molecular structure of cellulose remains largely intact after
pretreatment, hydrolysis is performed with enzymes or chemical agents to release the glucose
monomers from cellulose[11]. A cocktail of cellulases and xylanases including endoglucanases,
cellodextrinases, cellobiohydrolases, and beta-glucosidases are added to the mixture to fully
hydrolyse the cellulose and any residual hemicellulose[60]. After hydrolysis, the glucose is
fermented into ethanol by a fermenting organism, common organisms are yeasts such as
Saccharomyces cerevisiae or Zymomonas mobilis[59]. Post fermentation, the ethanol broth is
purified via distillation. A molecular sieve may also be used to remove remaining water from the
purified ethanol-water mixture[33]. Process residues including lignin, unhydrolysed
polysaccharides, and residual sugars are recovered during the distillation stage and are
commonly directed to a boiler system to be combusted to generate energy for the process. Due to
large residue volume in cellulosic ethanol production, it is common for electricity to be
generated in excess and sold to the grid[6]. Pretreatment will be the main focus of the next
section as cellulosic ethanol and xylitol production will likely share a common pretreatment
pathway, impacting the method of pretreatment and conditions chosen.
2.3.1 Pretreatment
As the feedstock enters the biorefinery in chip, pellet, or powder form, the initial stage in a
lignocellulosic process is a pretreatment process to disrupt lignin and activate cellulose, which
may also solubilize hemicellulose. The digestibility of cellulose is generally enhanced through
the partial removal of hemicellulose and lignin, which increases the accessible surface area and
porosity of cellulose, and by decreasing the crystallinity of cellulose, which promotes the
reactivity of cellulose[47]. As shown in Figure 2-3, xylitol and ethanol production will
potentially share the pretreatment stage; this indicates that the pretreatment process must ensure
low xylose degradation while cellulose is activated for hydrolysis[29]. Several different
pretreatment technologies have been studied for the production of cellulosic ethanol. Yang
suggests that the ideal pretreatment utilizes minimal chemicals, requires limited size reduction of
16
feed material, reduces the formation of inhibitory by-products, and that hemicellulose-based
sugars should be made available for fermentation, in the case where pentose sugars are
fermented into ethanol[28]. The method of pretreatment chosen can affect the properties of the
lignocellulose materials downstream, impacting the effectiveness of hydrolysis, fermentation,
and other conversion processes[10]. Some of the major pretreatment methods developed for
cellulosic ethanol include dilute acid hydrolysis, alkaline pretreatment, steam explosion,
ammonia fiber expansion, and hot water extraction[10], [28].
2.3.1.1 Dilute Acid Hydrolysis
Dilute acid hydrolysis, the most studied form of pretreatment, commonly utilizes sulphuric acid
or sulphur dioxide in conjunction with hot water or steam, although hydrochloric, nitric, and
phosphoric acids have also been considered[10], [28]. Acid hydrolysis selectively attacks the
hemicellulose fraction of lignocellulose, thus increasing the surface area of cellulose available to
enzymes[47]. It is reported that 80-90% of the hemicellulose sugars are solubilized using this
technique[28], but, depending upon the acid concentration, temperature, and residence time,
monomer recovery may be much lower. This method could be promising for a biorefinery that
aims to utilize pentose sugars to produce value-added products such as xylitol, as hemicellulose
is selectively removed by the dilute acid in the initial pretreatment stage. Degradation of sugars
into furan products in acidic conditions is a concern, as acid pretreatment will degrade xylose
and other pentose sugars into furfural[10]. Typical conditions for dilute acid pretreatment
involve acid concentrations between 0.2-2.5% w/w and temperatures between 130-210 °C [10].
Acid treatment does not tend to solubilize a large fraction of lignin, meaning an additional
pretreatment stage may be needed to activate the cellulose or separate it from the remaining
lignin[10], [28]. After acid pretreatment, the soluble and solids fractions must be conditioned
through treatments such as overliming, to neutralize the acids and remove the inhibitory
degradation products formed under acidic conditions[15], [28]. The acidic conditions also
require special process equipment that can withstand the corrosive environment. The
combination of specialized equipment, chemical costs, and the loss of hydrolysed sugars in the
conditioning stage can adversely affect the economics for dilute acid pretreatment at the large
scale, thus limiting its effectiveness[28]. Additionally, there are concerns about the sulfur content
in the hemicellulose fraction, as sulfur has been shown to foul Ni, Pt, and Ru catalysts used in
17
hydrogenation, such as the Raney-Nickel catalyst required for the hydrogenation of xylose into
xylitol.
2.3.1.2 Alkaline Pretreatment
Where dilute acid pretreatment selectively solubilizes hemicellulose, alkaline conditions tend to
solubilize lignin[15]. Basic compounds such as sodium hydroxide or lime most directly affect
lignin via the degradation of glycosidic and ester side chains. The net effect of alkaline
pretreatment is the disruption of the structure of lignin, partial hemicellulose solubilisation, and
swelling and partial decrystallization of cellulose, which activates cellulose for enzymatic
hydrolysis[10]. Sodium hydroxide has received the most study for alkaline pretreatment, and is
commonly used for the mercerization of cotton[61]. Sun reported 60% lignin and 80%
hemicellulose removal for a 144 h treatment at 20 °C with 1.5 % NaOH [10]; however the
relatively high costs of sodium hydroxide combined with longer residence times compared to
other pretreatment types are a barrier to large scale processing. On a raw material basis, the most
cost effective alkaline compound is lime, which is also relatively safe for handling. Lime is
recovered from the solid cellulose fraction through a wash stage with water, which is saturated
with CO2 gas to precipitate lime into calcium carbonate; the precipitate is then heated in a kiln to
regenerate lime[10]. The use of lime is more effective for biomass with a lower lignin
component and is slower than the use of other compounds such as ammonia or sodium
hydroxide, which leads to increased residence times and higher equipment costs[28]. The mild
reaction conditions of alkaline treatment lead to longer treatment times at low temperatures. Low
hemicellulose removal limits the effectiveness of alkaline treatment for a process that will
produce separate hemicellulose and cellulose-derived products as the hemicellulose would need
to be isolated at a later stage in the process.
2.3.1.3 Steam Explosion
In steam explosion, biomass is initially exposed to saturated, high-pressure steam (160-260 C,
0.69-4.83 MPa)[10]. The reaction vessel is suddenly depressurized and as a result, the biomass
decompresses explosively. The sudden pressure change causes the biomass to disintegrate into
fibre or bundles of fibre. While the biomass is initially exposed to high-pressure steam, an
autohydrolysis reaction occurs in the hemicellulose fraction. The dissociation of water at high
temperature and pressure leads to the formation of acids within acetylated components of the
18
biomass[62]. These acids then catalyse hydrolysis reactions within the hemicellulose, leading to
hemicellulose solubilisation, which is halted when the mixture is depressurized[62]. As a result,
both physical size reduction and chemical alteration of lignocellulose takes place during this
pretreatment method[10]. Autohydrolysis is an effective method for the removal of
hemicellulose as it does not require the addition of chemicals such as sulphuric acid, removing
the conditioning phase required in the downstream for pretreatments such as dilute acid
hydrolysis. To improve steam explosion results, the hydrolysis of hemicellulose may be
catalysed with the addition of acid such as sulphuric acid or gaseous SO2[63]. However,
inhibitors to downstream processes such as furfural may be formed in this reaction due to the
degradation of pentose sugars, lowering pentose sugar recoveries and potentially impacting
ethanol fermentation[63]. Steam explosion is a promising method of pretreatment due to low
capital costs due to the low residence times required and minimal environmental impacts due to
low chemical inputs, as well as the high pentose sugar recovery achieved using this technique.
2.3.1.4 Ammonia Fiber Expansion
Ammonia Fibre Expansion (AFEX) is similar to the steam explosion technique, except that
liquid (or gaseous) ammonia is added to biomass before high temperature and pressures are
applied[28]. The typical dosage is stated to be approximately 1-2 kilograms ammonia per
kilogram dry biomass[10]. High recoveries of cellulose and hemicellulose can be obtained by
this technique with hydrolysis conversions of over 90% obtained for certain biomass types.
During this treatment, cellulose is decrystallised, hemicellulose is partially hydrolysed and its
acetyl groups are removed while avoiding the formation of inhibitors, and lignin bonds are
cleaved leading to disruption of the fibre structure of lignocellulose[10], [28]. This improves
accessibility of enzymes to the biomass due to increased surface area, along with wettability,
leading to improved fermentation performance in the downstream[10]. Subsequent fermentation
steps may also be improved as residual ammonia can serve as the nitrogen source[28].
Challenges with AFEX include its limitation to feedstocks with lower lignin content, the
necessity to recover a large percentage of the ammonia to make it cost effective, and the safety
concerns associated with the containment of toxic, volatile ammonia. The incomplete hydrolysis
of hemicellulose is another concern with ammonia-based pretreatment, reducing the yield of
pentose sugars diverted to the xylitol pathway, thus leading to poor process yields and increased
processing requirements.
19
Ammonia recycle percolation (ARP) involves the passage of aqueous ammonia (10-15 wt%)
through biomass packed into a column at 150-170 °C at a typically low fluid velocity[64]. The
treatment mainly affects the lignin present in biomass while leaving cellulose intact; however, a
large amount of xylan may also be removed. Kim proposed a 2-step process to both delignify
biomass and to further fractionate it into lignin, hemicellulose hydrolysate, and cellulose[64].
The first stage involved a hot water treatment to hydrolyse hemicellulose and remove it from the
biomass. The hydrolysed biomass was then exposed to 15 wt% ammonia to remove lignin.
Optimal results of 83% soluble xylan recovery and 75% delignification were obtained for the
following conditions: hot water treatment at 190 °C for 30 min with a flowrate of 5 mL/min and
ARP treatment at 170 °C for 60 min with a flow rate of 5 mL/min of 15 wt% ammonia[64].
However, this technique has not been demonstrated at the large-scale and there may be scale up
concerns that limit its effectiveness.
2.3.1.5 Liquid Hot Water Extraction
Liquid hot water extraction (LHW) utilizes the same autohydrolysis effect described in steam
explosion, where the formation of acids from the acetylated components of biomass from
pressurized, heated water causes solubilisation of the hemicellulose fraction[10],[15],[65]. The
digestibility of the cellulose fraction of lignocellulose is improved by LHW as the hemicellulose
fraction is solubilized into soluble oligomers, while the hydrolysis and degradation of
hemicellulose into pentose sugars and inhibitors can be prevented at low temperatures and
residence times[29]. LHW conditions are commonly between 120-240 °C, under sufficient
pressure to prevent the vaporization of water, with residence times between 3-15 minutes; longer
residence times at high temperature can lead to the degradation of hemicellulose into furans[13],
[15], [58]. One of the major benefits of LHW is that it promotes the selective fractionation of
hemicellulose into a liquid phase hydrolysate without using chemicals or harsh conditions, while
the majority of lignin remains with the cellulose in a solid fraction, simplifying hemicellulose
diversion into the xylitol pathway[15]. However, as the hemicellulose oligomers are not
degraded into monosaccharides, they must be hydrolysed in a separate step in the xylitol
pathway. Additionally, if the mild conditions are not enough to sufficiently disrupt the solid
cellulose and lignin fraction, an additional pretreatment step may be necessary to improve
cellulose digestibility. LHW is chosen as a pretreatment of interest for this process due to its low
chemical demands, mild conditions, and specificity towards hemicellulose solubilisation with
20
low degradation, which enables high xylose recoveries for the xylitol co-product pathway and is
expected to have only mild environmental and economic impacts on the overall process.
2.4 Conventional Xylitol Production
Conventionally, xylitol is produced via the catalytic hydrogenation of xylose derived from corn
cobs or wood-based feedstocks[14], [17]. The majority of xylitol production occurs in China,
where annual production was estimated at 130 000 tonnes in 2011, while the rest is produced in
Europe, Australia, or the US[14]. As the majority of commercial xylitol production is from corn
cobs, this process will be described in detail as follows.
For the production of xylitol from corn cobs, a pretreatment stage is be used to solubilize the
xylose from the solid feedstock. Dilute acid hydrolysis using sulphuric acid is commonly utilized
during pretreatment, similar to the dilute acid method utilized in cellulosic ethanol production for
its specificity towards hemicellulose solubilisation[35], [15], [67]. As the xylitol reaction is
chemical instead of biological, preventing the formation of inhibitors such as furfural is less of a
concern, aside from yield losses, and the xylo-oligomers are hydrolysed directly into
monosaccharides in this step. The xylose then must necessarily be purified from the other
contaminant sugars through chromatography and crystallization stages to yield a nearly pure
xylose solution, due to the non-specific nature of the catalyst used in hydrogenation[17]. During
hydrogenation, the catalyst will act on any sugars present in the solution and transform them into
their respective polyols[18]. As it is difficult to separate xylitol from other polyols formed from
the contaminant sugars such as arabinitol, mannitol, and sorbitol, xylose is purified
upstream[18]. After hydrogenation, the xylitol is purified through a crystallization stage to
remove any remaining contaminants and unconverted xylose[68]. The crystallization stage yields
a pure, colourless, dry xylitol crystal product that is then prepared for distribution from the
biorefinery.
2.4.1 Acid Pretreatment
Dilute acid pretreatment with sulfuric acid is the most commonly used pretreatment method in
commercial xylitol production to selectively solubilize hemicellulose[17], [34]. Other acids such
as hydrochloric and nitric are not normally utilized due to increased corrosion, requiring
specialized process equipment for hydrochloric acid, and concerns about premature degradation
21
of chromatography resins when nitric acid is used[15], [17]. The performance of the pretreatment
is dictated by the concentration of acid, temperature, and the residence time[17]. Generally,
sulphuric acid is added at concentrations between 0.5-5% w/w under elevated temperatures
between 120-160 °C and conditions are maintained for minutes to several hours in laboratory
experiments [15], [35], [42], [67], [69].
The solids loading in this stage has important implications for the economic and environmental
performance of the process; any excess water added will need to be removed in subsequent
energy-intensive concentration stages needed to yield a dry xylitol product. Many experiments
have been performed at low solids loadings, between 10:1 and 8:1 g water/g solids[17], [67] to
produce a dilute xylose extract[35]. Increasing the solids loading can have a negative impact on
the xylose yield however, as sulfuric acid can be neutralized by phosphate, carbonate, or silicate
groups found in plant matter, reducing its efficacy, although this may be overcome by increasing
the acid concentration[17]. The amount of acid utilized can be decreased through elevating the
hydrolysis temperature, which lessens the removal rates of inorganic salts after pretreatment.
However this benefit may be eliminated if higher solids loadings are utilized, and xylose
degradation is a risk at elevated temperatures [17], [35]. The hydrolysis stage yields a liquid
fraction containing xylose, contaminant pentose and hexose sugars such as arabinose, mannose,
and glucose, soluble lignins, acetic acid, phenolics, and other degradation products such as
furfural[11], [21], [67].
2.4.2 Xylose Purification
After hydrolysis, the solution is filtered to recover the solubilized sugar in the liquid fraction[17].
The solid fraction, containing non-solubilized hemicellulose, cellulose, and lignin collected
during this stage can be utilized to generate process energy. Xylose purification is intensive,
requiring multiple chromatographic separation units containing different resin materials to
remove contaminants that have different physical and chemical properties[18]. Prior to
purification, the xylose extract is neutralized and conditioned. The residual acids are generally
neutralized through the addition of calcium hydroxide, sodium hydroxide, or lime and
precipitated as gypsum or salts such as calcium sulfide (CaSO4) [35],[65],[70]. The salts
produced during this stage are then removed and using anionic ion exchange columns[17]. The
22
disposal of the salts produced from the acid hydrolysis stage is costly, with adverse
environmental implications[35],[65].
Activated carbon is utilized to remove colouring bodies within the liquid hydrolysate such as
soluble lignins. Further chromatography using cationic and/or anionic resins may be utilized to
purify xylose from the contaminant sugars[35]. As xylose is the most prevalent sugar in the
solution, it is further purified from the residual contaminating sugars through a crystallization
stage. After colour removal, the purified xylose hydrolysate is concentrated until the xylose
concentration within the solution exceeds supersaturation conditions. This may be done utilizing
a multiple-effect evaporation system to minimize utility demands, with the final concentration
being done within the crystallizer to prevent premature crystal nucleation within the evaporator
equipment[70]. Crystallization yields a pure xylose crystal product, which may be washed to
remove additional impurities, if required[70]. The presence of sugar impurities in the
crystallization stage is known to inhibit the crystallization of xylose, leading to maximum xylose
recoveries of 70-80% in this stage[17].
2.4.3 Hydrogenation
The purified xylose crystals must be dissolved in water to form a solution containing 40-60%
solids in order for catalytic hydrogenation to proceed[71]. The dissolved pure xylose solution is
then added to a hydrogenation reactor, where it is mixed with hydrogen gas and Raney-Nickel
catalyst particles[72]. During hydrogenation, the xylose is chemically reduced to form xylitol, as
displayed in Equation 2-1. The Raney-Nickel catalyst is composed of small particles with an
average particle size of 22.3 μm, which are maintained in suspension via high rates of agitation
during the hydrogenation process[73]. The intense agitation also promotes the diffusion of
hydrogen from the gas phase to the liquid phase where it can interact with the catalyst[73]. The
catalyst will also reduce other pentose and hexose sugars such as arabinose and pentose into
polyols[17], [18]. Despite the non-specificity of the catalyst, it is found to be selective and does
not produce other hydrogenation products from xylose such as arabinitol or xylulose in
significant concentrations[35], [73].
→ (Equation 2-1)
23
Hydrogenation proceeds at high temperature and pressure conditions, typically between 80-
140°C and 40-70 bar[35], [74], [75]. Yields during hydrogenation are between 80-100% after
residence times of 30 minutes to several hours [18], [59], [67], [70].
2.4.4 Xylitol Purification
The xylitol produced during hydrogenation must be purified to remove any unconverted xylose,
colouring agents, or salts that remain present in the syrup. Activated carbon is utilized to remove
colour from the syrup, while ion exchange columns are used to remove the salts[17], [18]. The
decoloured xylitol syrup is then purified from any residual contaminant sugars or polyols via a
secondary crystallization stage. The syrup is concentrated to supersaturation conditions, which
occur at much higher solids loadings due to the increased solubility of xylitol compared to
xylose[77]. The crystallization yields pure xylitol crystals that are separated from the mother
liquor and washed, if necessary, before being dried to yield the final crystalline xylitol
product[17], [77], [78]. Non-crystallized xylitol retained in the mother liquor can be recycled
into the process to improve xylitol recovery[17].
Efforts to improve the crystallization of xylitol have used solvents such as ethanol to reduce the
solubility of xylitol and to improve the precipitation of xylitol crystals[77]. However the addition
and removal of ethanol may be undesirable as it adds additional material and processing stages
that can impact the environmental and economic performance of the process. Other studies have
looked at a variety of temperatures, cooling times, and initial supersaturation values to optimize
xylitol yields[79]. Studies on xylitol crystallization utilize extreme low temperatures from -20 to
-5 °C to decrease the solubility of mixtures containing xylitol at concentrations of 600-800 g/L
and achieve recoveries of 60% at -20 °C[77] or 50% at -6°C[80], or less at higher temperatures
[79]. These low temperatures would require ethylene glycol chillers at a large-scale, potentially
impacting process energy consumption and environmental performance.
2.4.5 Limitations
Several concerns with the conventional xylitol hydrogenation process have been raised in the
literature[47], [74], [69]. Significant water removal is required in this process, dependent on the
solids loading of the initial pretreatment process and the subsequent purification stages required
to produce dry xylitol crystals. Losses during purification are reported to lower the overall
24
conversion of xylans to xylitol to 50-60%, and the overall conversion of the lignocellulosic feed
material to xylitol to 8-15%[16], [42]. The hydrogenation, evaporation, and two separate
crystallization stages of xylose and xylitol require large energy inputs. The purification of xylose
is claimed to account for 80% of the xylitol product costs[17]. However these claims have not
been backed up by any numerical evidence to date, and only minimal information about the
energy demand and environmental impacts of xylitol hydrogenation is available in literature[23].
Available life cycle assessment information on the production of xylitol will be discussed in
section 2.6.2. Limited literature is available on the xylitol hydrogenation process, despite its
commercial production. This has led to challenges in obtaining accurate process data at the large
scale, which can have implications for modelling decisions and also the environmental results.
2.5 Xylitol Production – Fermentation
Concerns over the low yields and energy intensity of xylose purification and xylitol
hydrogenation have led to the study of a fermentation pathway to produce xylitol. Fermenting
organisms, primarily yeasts, are stated to be selective in their consumption and transformation of
xylose to xylitol [17], [34]. This selectivity allows many of the upstream purification stages to
be avoided, as ideally the organisms would directly ferment xylose released during hemicellulose
hydrolysis[81], [82]. Fermentation conditions are also reported to be milder and require lower
energy inputs as ambient temperatures and pressures are utilized and an external supply of
hydrogen is not needed[82]. However it should be noted that the xylitol fermentation pathway
has yet to be implemented a commercial scale.
The fermentation pathway described in literature shares some similarities to the hydrogenation
pathway. The biomass feedstock undergoes a pretreatment step to selectively liberate xylose (or
oligosaccharides) from hemicellulose[15]. In the ideal case, the hemicellulose hydrolysate is
directly fermented; however studies have shown that inhibitors formed during pretreatment are
potent enough to severely impact xylitol production rates and must therefore be removed through
a detoxification stage[83]. It is unlikely that a xylose crystallization stage will be needed in the
fermentation pathway, reducing the upstream energy demands as concentration is deferred to the
downstream[17]. After the fermentation stage, the xylitol must be separated from the
fermentation broth. The broth is expected to contain unconverted xylose and other sugars, trace
amounts of polyols, cells, proteins and other residual hydrolysate components[17], [84]. A
25
combination of chromatography units utilizing different resins, and crystallization stage is
proposed as one method to purify xylitol from the fermentation broth[17].
2.5.1 Fermentation Metabolic Pathways
The fermentation of xylose to xylitol been found in yeasts, such as the Candida guilliermondii
and C. tropicalis species, Debaryomyces hansenii, as well as in fungi such as Aspergillus niger
and the Penicillium family[85], [86]. The first stage of xylitol metabolism in many yeasts and
mycelia fungi is an enzymatic reduction of xylose into xylitol mediated by NADH- or NADPH-
dependent xylose reductase[34], [85]. Xylitol is subsequently either secreted into the
fermentation broth or converted into d-xylulose by NAD- or NADP-dependent xylitol
dehydrogenase[85]. The ability of an organism to further convert xylitol into metabolites has a
strong impact on xylitol accumulation in the fermentation broth and xylitol yield[87]. Under
oxygen limitation, Candida yeasts have been shown to be unable to reoxidize NADH, resulting
in xylitol accumulation due to a redox imbalance between the xylose reductase and xylitol
dehydrogenase enzymes[42],[85],[87]. Complete conversion of xylose to xylitol cannot be
obtained in fermentation, as the cell growth requirements of the fermenting organism must be
met by the metabolic products of xylitol, indicating a balance between metabolic needs and
xylitol production must be struck[85].
2.5.2 Fermentation Conditions and Organism Selection
A large body of literature has been conducted for the fermentation of xylose with different
organisms and feedstocks. The main factors that affect the efficiency and productivity of xylitol
fermentation are organism selection, oxygen availability, medium composition, pH, and
agitation[81]. Barbosa screened a selection of 44 organisms and found that C. guilliermondii and
C. tropicalis strains were able to produce xylitol at the greatest productivity over 48 hours in a
synthetic xylose media enriched with urea and yeast nutrient broth[88]. C. guilliermondii FTI
20037 achieved the highest xylitol yield, at 81% of the maximum theoretical yield of 0.9 g
xylitol/g xylose determined by Barbosa et al.[88]. The use of synthetic fermentation media is
useful in determining the optimal xylitol yield; however, as the fermentation pathway is
proposed to avoid upstream purification of xylose, experimental results utilizing hydrolysates as
the fermentation medium are preferable. Parajo studied the fermentation of Eucalyptus globulus
hydrolysates prepared with dilute acid hydrolysis by D. hansenii and was able to achieve yields
26
up to 0.79 g xylitol/g xylose; however the low productivity (0.033 g/L h) would require extended
residence times to achieve the stated yield[74]. Yields from the utilization of C. guilliermondii
and C. tropicalis cultures on sugarcane bagasse, corn fiber, or straw hydrolysates have been in
the range of 0.36-0.69 g xylitol/g xylose[74], [89]. The lower yield obtained during experiments
with hydrolysates are attributed to the presence of inhibitors in the hydrolysate solutions[74],
[90].
Optimal fermentation temperatures for yeasts are between 28-30 °C, while the optimal pH
generally is between 5.5-6.5[86]. While many nutrients such as phosphate ions may be released
during hydrolysis, in many cases, a nitrogen source must be added to fermentation broths to
improve fermentation yields and productivities[17]. It has been found that the addition of organic
nitrogen sources such as urea, yeast extract, or rice grain is more effective than the addition of
inorganic nitrogen such as ammonium sulfate[16],[86].
2.5.3 Inhibitor Management Strategies
One of the major concerns with the performance of fermentation is the presence of inhibitors
such as furfural and HMF and weak acids such as acetic acid that are released or produced from
hemicellulose during pretreatment[34]. Lignin is also solubilized in this step, releasing phenolic
compounds such as vanillin and syringaldehyde that are toxic to microorganisms[83],[91].
Inhibitors slow cell growth by affecting the permeability of the cell membrane, leading to cell
death or reduced metabolism[83], [90]. To ensure adequate xylitol yields are achieved during
fermentation, different strategies to remove or reduce the impacts of inhibitors have been
explored. Factors that can influence the potency of inhibitors include the intensity of
pretreatment, as harsher conditions will release greater quantities of inhibitors, the solids content
of the fermentation broth, as inhibitors become more concentrated in higher solids environments,
and the initial xylose concentration, as organisms can tolerate higher inhibitor concentrations
when the substrate concentration is elevated[16].
Strategies to mitigate the impacts of inhibitors can be implemented at the microbial strain or
process level[83], [90]. At the microbial level, strain improvement through genetic engineering
or adaption by exposing cultures media containing inhibitors over a series of fermentations has
been explored[41], [90], [92]. Silva found that exposing adapted C. guilliermondii FTI 20037 to
successive fermentations on rice straw hydrolysate improved xylitol yield, xylose consumption,
27
and productivity, although xylitol yields and productivity still remained low at 0.56 g xylitol/g
xylose and 0.42 g/L h[92]. Genetic engineering efforts to improve strains have thus far focussed
on improving utilization of synthetic xylose or xylose and glucose substrates and have not fully
addressed the inhibitor issue thus far[83], [93].
A variety of physical, chemical, and biological strategies may be employed at the process level
to remove or reduce the concentration of inhibitors[94], as is shown in Table 2-2. Additional
processes stages to detoxify the hydrolysate should be avoided to minimize process costs. Liu
states that many remediation methods to remove inhibitors may be too expensive at a process
scale[95]. Selective detoxification methods will be discussed based on their potential as
detoxification methods.
Table 2-2: Methods of detoxification of hemicellulose hydrolysates [83]
Detoxification Method
Physical Chemical Biological
Evaporation
Steam stripping
Membrane filtration
Solvent
extraction/phase
separation
pH adjustment
Overliming
Ion exchange
Activated
carbon
Enzyme treatment
Bioremediation of
inhibitors using fungi
or yeasts
Evaporation can remove volatile inhibitors such as furfural and acetic acid[83], [91].
Concentration of the hydrolysate can be performed under vacuum to lower the boiling point of
the solution while preventing the degradation of xylose and other components into additional
inhibitors[70], [83]. Evaporation has several benefits, including concentration of xylose in
solution, which may improve fermentation performance and overcome the sensitivity of the
organism to the residual inhibitors[16]. Evaporation also reduces the size of process equipment
as volumetric flow rates are reduced by water removal. If the subsequent process stages can be
carried out at higher solids loadings, evaporation is a suitable detoxification adjunct as the xylitol
product must be completely dried and upstream evaporation can aid process water removal.
Anionic ion exchange resins are stated to be effective at removing phenolic, furan aldehyde, and
aliphatic acids, of which most inhibitors are comprised[94], [96], [97]. Chromatography also has
28
the potential to remove the inhibitors prior to fermentation. Nilvebrant determined that an
anionic exchange resin under basic conditions (pH 10) was effective at removing anionic
inhibitors and also uncharged inhibitors through hydrophobic interactions[98]. Maciel de
Mancilha tested the ability of different ion exchange resins to remove furfural, HMF, and acetic
acid from corn stover hydrolysates produced via dilute acid hydrolysis with H2SO4[94]. Results
indicated that while anionic resins were able to remove furfural and HMF, they did not remove
acetic acid in significant quantities and only a commercial resin, Purolite A 103S, was able to
remove all 3 inhibitors[94]. This indicates that one form of ion exchange resin may not be
suitable on its own, as the composition of the commercial resin is unknown. An ion exchange
system could serve a dual purpose of removing both inhibitors along with the contaminant sugars
present in the hydrolysate, aiding in the downstream purification process. If combined with an
evaporation stage to remove volatile furfural and acetic acid, ion exchange could purify the
hydrolysate while detoxifying it for fermentation. As the hydrolysate must be purified and
concentrated at some point in the xylitol process, the location of these stages may not be
important[17].
Other strategies such as bioabatement strategies to convert furans into less toxic derivatives that
do not simultaneously aid in xylitol purification may not be economical to include in a large-
scale process[95]. The removal of glucose by an organism that does not consume xylose is also
beneficial to the fermentation pathway, as the presence of glucose has been shown to be
detrimental to xylitol fermentation and can lead to the growth of microbial contaminants[17].
However, the lack of well-developed yeast or bacteria strains that have the ability to tolerate high
inhibitor loadings indicates that at present, removal of inhibitors is the best strategy to improve
xylitol fermentation kinetics. As more research on inhibitors and their interactions with
fermenting organisms is completed, high tolerance organisms may be developed, removing the
need for hydrolysate conditioning.
2.5.4 Xylitol Purification from the Fermentation Broth
Post-fermentation, the xylitol must be purified and dried to produce a final crystal product.
Compared to the hydrogenation process, the xylitol solution is much less pure, containing a
mixture of contaminants such as non-converted sugars, cells and cell debris, lignin, proteins, and
other components generated during hydrolysis and fermentation[99]. Zhang states that steps must
29
be taken to clarify, decolourize, desalinate, and deodorize the fermentation broth prior to the
separation of xylitol by chromatography and crystallization[17].
Chromatographic methods are suggested as a method to separate xylitol from contaminants
based on their physical and chemical differences. Activated carbon can be utilized to clarify,
decolourize, and deodorize the broth through the absorption of large pigments[17]. However
smaller pigments, salts, and proteins are left behind by this treatment. Ion exchange
chromatography is suggested, similar to the detoxification process, to remove salts and smaller
organic pigment molecules. Anionic resins have been effective at removing inorganic salts and
small lignin molecules, while cationic resins could be utilized to separate xylitol from the
unconverted monosaccharides remaining in the fermentation broth[17].
Membrane filtration is likely a required step immediately after fermentation to recover the
fermenting organism, which may be recycled or discarded, depending on the process design[97].
Proteins, along with large pigment molecules can be removed from the broth via an ultrafiltration
stage, reducing or replacing the need for activated carbon[17]. Membranes may also be utilized
to selectively purify xylitol based on molecular size[84]. Affleck determined that a polysulfone
membrane with a molecular weight cut-off of 10 000 could allow the passage of 82-90% of the
xylitol while retaining 49-54% of the initial proteins; however when this mixture was
crystallized, the xylitol crystals had a purity of only 90.3%[84].
Crystallization is the conventional method for the recovery and purification of xylitol. Martinez
explored the crystallization of xylitol produced by C. tropicalis in water and ethanol-water
mixtures; however an extensive array of 5 different resins was utilized to purify the hydrolysate
prior to fermentation[97]. The removal of impurities before crystallization may not be adequate
to achieve pure xylitol crystals in a single stage[84]; as a result the recovered crystals may be
dissolved in pure water and recrystallized to produce a product purity of over 99%[17], [78].
Xylitol recoveries may be as high as 70-85% in the crystallization stage. Sugar impurities
remaining in the mother liquor may be further separated from the xylitol utilizing calcium cation
exchange resins, to allow the recycle of the mother liquor and improve the xylitol recovery[17].
As the fermentation broth may be quite dilute, concentration forms a large part of the
downstream purification section. Concentration via evaporation will remove volatile
30
contaminants remaining in the broth; however evaporation is energy intensive and can require
large volumes of process steam[17].
It is clear that the diverse nature of contaminants found in the fermentation broth requires
multiple stages of purification to yield a pure xylitol product. A combination of ion exchange
chromatography, membrane filtration, and crystallization appears to be the most effective to
yield a pure, colourless xylitol product. The configuration of the purification system is also
specific to the fermentation broth and the contaminants remaining after detoxification,
concentration, and purification[17].
2.5.5 Current Fermentation Limitations
The avoidance of upstream purification is stated to be one of the major advantages of the
fermentation pathway. However the, inhibitory effects of degradation products and lignin
released during pretreatment have prompted research into purifying the hydrolysate solution
before fermentation. There is interest in metabolic engineering of yeasts to improve
performance; however this method has not been broadly developed to date[86]. The slow
development of inhibitor tolerant organisms, combined with concerns with cell recycle
membrane fouling, creates further uncertainty on the benefits of the fermentation pathway[42].
Without organisms that can tolerate the untreated hydrolysate, the economic and environmental
benefits of the fermentation pathway over the hydrogenation pathway become less clear. While
the xylose crystallization stage does appear to be avoided a fermentation pathway, the need to
remove inhibitors through ion exchange chromatography, filtration, evaporation, or other
methods may mitigate this benefit. Purification of the fermentation broth is also complex, as the
range of contaminants present is much more diverse than in the hydrogenation process, leading
to the use of multiple methods of purification such as chromatography, filtration, and
crystallization.
No information on large-scale xylitol fermentation processes in operation or under development
was found at the time this document was written. The lack of large-scale production may also be
linked to the marginal yield gains fermentation has over hydrogenation, as it has been described
as increasing the xylitol yield from xylan from 50-60% to 70% in literature[100]. The complex
purification process needed to produce xylose crystals in the hydrogenation process is cited as a
major downside to the hydrogenation process. However, study of the fermentation pathway also
31
reveals complex separation strategies are needed to remove inhibitors and to purify xylitol from
the fermentation broth in the downstream. As the potential benefits of fermentation have not
been captured in any environmental studies, the performance of fermentation is unknown and
claims supporting fermentation have yet to be proven. This work attempts to fill this gap by
conducting LCA and financial assessments of the fermentation process to provide information on
its environmental and economic performance.
2.6 Life Cycle Assessment
Life cycle assessment (LCA) will be used in this work to quantify the environmental
performance of different xylitol production pathways within the context of a cellulosic ethanol
biorefinery. LCA is a comprehensive method to determine the environmental impact of a product
or service[12]. The use of LCA as a method of examining the environmental impacts of a biofuel
or bioproduct pathway is well established in literature[2], [6], [24], [56]–[58], [101]. An
advantage of LCA is that instead of focusing on a single aspect of a product or process, the entire
life cycle is investigated from raw material extraction/production to end-of-life options (Figure
2-4). The methodology to conduct an LCA is focussed on 4 general stages: (i) goal scope and
definition, (ii) inventory analysis, (iii) impact assessment, and (iv) interpretation of results. LCA
is an iterative process, where findings from each of the major categories can be used to assess the
initial decisions made in those categories[12]. Standards (ISO 14040, 14044) and have been
released by the International Organization for Standardization that describe LCA methodology.
Figure 2-4: General life cycle model showing system boundaries, processes, and material
and energy flows
The initial phase (i) of an LCA is the goal and scope definition. In this stage, the rationale,
application, methodologies, and system boundaries of the study are described. System
boundaries are defined on a process, geographic, and temporal level and can be limited by the
32
availability and quality of data. The functional unit, which is utilized to normalize all process
material and energy streams, is also chosen. The implementation of the functional unit allows
comparison between different process flows and different studies as all flows in the process
under study are unitized to the functional unit. LCA studies on the production of cellulosic
ethanol have utilized either 1 MJ of ethanol-containing fuel produced or 1 km travelled by an
ethanol-fueled vehicle, among other functional units[54], [57]. The impact categories, used to
present environmental results include resource use global warming potential, land use, and
toxicity, are also selected at this stage. Impact categories are chosen for their relevance to the
process being studied. For example, the study of a biorefinery would typically focus on global
warming potential and resource use to determine performance against a petroleum refinery or
petroleum products.
After the goal and scope of the LCA have been set, the next stage is to generate the life cycle
inventory (LCI) database (ii). A detailed flow chart is produced showing the flows of materials
and energy to and from each major process stage. Data are collected for the energy and material
inputs and outputs for the different process stages. Models are constructed to determine mass and
energy balances for process stages where data is not fully available. It is common for biorefinery
processes to be described by the “black box” approach, where internal process flows are
unknown and only the process inputs and outputs are reported[2]. This approach simplifies
calculations, but is site and process specific and does not identify environmental bottlenecks
within the process. Material and energy flows entering or exiting the system boundary are
normalized against the functional unit.
Once the material and energy balances for the system have been developed in the LCI, the
environmental impacts of flows crossing the system boundary are calculated (iii) in the life cycle
inventory assessment (LCIA). System outputs are translated into the selected impact categories;
for example global warming potential is calculated from the flow of gaseous emissions out of the
system. Greenhouse gas emissions are normalized to the global warming potential (GWP) of
CO2, and are calculated based on individual GWP values for different GHGs, usually CO2, CH4,
and N2O. Energy requirements are generally reported in terms of total, fossil, and petroleum
energy requirements to isolate the non-renewable energy used within the system. In the final
stage of the LCA, results from the LCIA are interpreted and recommendations for decision
33
makers and policy guidance are made, along with the potential for reworking decisions made in
earlier stages.
2.6.1 Co-Product Handling
The production of multiple products from a biorefinery poses a challenge for LCA, as it can
impact how environmental impacts are assessed between the different products as the functional
unit is normally set to a single product flow[12]. The biorefinery investigated in this study
produces ethanol, xylitol, and potentially electricity from process residues, indicating that a
method of co-product handling will need to be selected to assign the appropriate portion of
environmental impacts to each product.
There are two main methods of handling multiple products: allocation through partitioning and
system expansion[12]. Partitioning can be used to allocate environmental impacts between
products based on mass, energy content, market value, etc. [58]. However, determining the mass
allocation fractions of each product can be challenging, especially for products that lack mass,
such as electricity. The energy-content of different products may not be a valid selector when
products are not energy products, such as xylitol. Market-value allocation is limited by
fluctuations in product prices[58]. These issues have led to ISO 14041, stating that allocation
methods should be avoided by increasing the level of model detail or utilizing system
expansion[12]. Increasing the level of model detail can overcome the allocation issue, but is
often hindered by data availability.
System expansion, or displacement, is a method of handling multiple products in which one
product is chosen as the main product, and all environmental impacts are attributed to the
selected product. The other products, known as co-products, are assumed to displace their
conventionally produced equivalents in the market. A co-product credit is then calculated based
on the environmental impacts associated with the displaced conventional product. The energy
and emissions that were avoided by the production of the co-product are then credited against the
main product. While system expansion is the recommended method to handle co-products, Wang
argues that the results may be skewed if co-products compose a significant fraction of the
product output on an energy basis, indicating that main products may be incorrectly labelled if
they compose the minority of the product spread[58].
34
2.6.2 Review of Previous Biorefinery LCA Studies
While many studies have investigated the production of cellulosic ethanol with no co-products or
only an electricity co-product[20], [102], very few have integrated value-added chemicals such
as xylitol into the scope of these studies. Uihlein and Schebek utilized LCA to investigate a
theoretical biorefinery that produces ethanol, xylite (assumed to be xylitol), and lignin from
straw feedstock[23]. The biorefinery based on the Arkenol process, a proprietary biorefinery
configuration, utilizes concentrated hydrochloric acid in the pretreatment stage. Xylitol is
produced by hydrogenation, and is assumed to displace sucrose on a 1:1 mass basis. Results were
compiled based on three impact categories: resources, ecosystem quality, and human health into
a single value using the LCA software EcoIndicator. When compared to conventional products,
the biorefinery products showed a decrease in EcoIndicator-99 points[23]. However, these
results are challenging to compare against other results due to the use of the EcoIndicator
software and the lack of numerical values for GHG emissions, which will be calculated in this
work.
Pourbafrani et al. investigated the production of xylitol as a co-product of cellulosic ethanol
production for a variety of pretreatment methods and residue-based co-products[21]. Xylitol was
also assumed to displace sucrose in a system expansion approach. Pretreatment using
autohydrolysis was utilized for several xylitol production scenarios. The production of xylitol
from hemicellulose residues decreased the ethanol yield, as expected due to the reduction in
fermentable sugars. Scenarios producing xylitol and both pellets and electricity from lignin show
a reduction in the GHG emissions of ethanol compared to gasoline, with the pellet scenario
resulting in negative GHG emissions[21]. While these results are promising, the xylitol pathway
was not modelled in depth. This work seeks to build off of these results by examining the xylitol
pathway in more detail through process modelling and the investigation of both hydrogenation
and fermentation as potential pathways.
Danisco released a study (which has not undergone peer-review) that compares the
environmental impacts of conventional hydrogenation using corn cobs against the Danisco
process, which involves a proprietary wood-based process to acquire xylose from a pulp and
paper plant side-stream[103]. It is unknown whether the Danisco process uses the same
purification and hydrogenation methods as the conventional hydrogenation process, only that the
35
xylose feedstock is different, as it is derived from a side stream of a pulping process. LCA results
are presented for 15 different impact categories including global warming (kg CO2-eq.) and non-
renewable energy (MJ) per 1 000 kg of xylitol. The conventional xylitol hydrogenation process
is stated to incur 38.6 kg CO2-eq. emissions and require 454 MJ of non-renewable energy per 1
000 kg of xylitol[103]. These results present an overall picture of the selected environmental
impacts of xylitol production; however they do not isolate the impacts of individual unit
operations.
As discussed in section 2.4.5, claims have been made by fermentation proponents about the low
yield and high energy requirements for the hydrogenation pathway in support of developing a
biological xylitol pathway. These claims are however, largely unsubstantiated by quantitative
data in literature. Furthermore, despite widespread literature on the fermentation of xylitol, no
life cycle assessment information on this pathway has been found in the literature to date. This
thesis attempts to fill this gap in the literature by producing detailed results on the production of
xylitol from hemicellulose residues by both hydrogenation and fermentation, in the context of the
cellulosic ethanol biorefinery.
36
Methods 3
The focus of this work is to assess the environmental and techno-economic impacts of xylitol
production from hemicellulose residues with life cycle and financial assessment. To determine
detailed impacts for the different pathways, process models are developed to model the process
conversions, inputs, and outputs. The completed models are utilized to construct life cycle
inventory (LCI) databases, which are then utilized as the basis for life cycle assessment. Energy
usage and greenhouse gas emissions are the key metrics focussed on in the LCA; these metrics
are chosen based on convention due to climate change concerns associated with the use of
petroleum fuels and products. Financial assessment including capital and operating cost
estimates will be utilized to determine key financial metrics. These results are used to determine
the net impact of the xylitol pathways on a cellulose-based primary process from both an
environmental and financial perspective.
3.1 Life Cycle Impact Assessment
3.1.1 Goal and Context
The goal of this work is to study two process pathways for xylitol production from xylose,
hydrogenation and fermentation, within the context of a biorefinery operation. The biorefinery is
assumed to ultimately produce cellulosic ethanol as a main product and xylitol as a co-product
from hemicellulose residues separated during the pretreatment stage of the cellulose process.
Lignin and other residues are also treated in an anaerobic digester to produce biomethane, which
replaces natural gas in a co-generation system to produce steam and electricity for the process.
Results from the LCA will be presented in terms of energy requirements and emissions of each
pathway. The results of this work are intended to be utilized to determine if xylitol is an
appropriate co-product to be produced from hemicellulose residues from both an environmental
and economic perspective. Differences between the two pathways will also be quantified to
provide insight on whether one pathway is superior to the other based on environmental factors.
3.1.2 System Boundaries and Scope
The boundaries for the life cycle assessment include both upstream and downstream processes to
generate feedstocks and distribute products, in addition to the main biorefinery (Figure 3-1). The
production and transportation of hybrid poplar feedstock to the biorefinery (well-to-gate) are
37
included in the upstream process. The biorefinery models handle the conversion of the feedstock
into the cellulosic main product and co-products xylitol and electricity. The production of
process chemicals and energy sources both on- and off-site are included as well-to-gate modules
(examples are hydrogen produced on-site from stream methane reforming and off-site production
of other chemicals such as enzymes). Products leaving the biorefinery are tracked depending on
their usage. Cellulosic ethanol is blended with gasoline and distributed to fuelling stations before
it is combusted in a light-duty vehicle. Xylitol and electricity are handled with system expansion
methods. It is assumed that the xylitol will be transported to a distribution centre and its
distribution and consumption is not evaluated. Electricity will be utilized within the biorefinery;
any excess will be transferred to the grid, displacing the regional electricity mixture.
Figure 3-1: Hybrid poplar to ethanol and xylitol block flow diagram including LCA system
boundary
The biorefinery is scaled to the production of 20 000 tonnes of xylitol per year, requiring an
intake of approximately 700 – 2 500 tonnes of hybrid poplar composed of 15-20% xylan per day,
based on process performance variables. The bioconversion process is assumed to be operated
for 24 h per day, 95% of the year and the location of the biorefinery is set in Southern Ontario.
38
3.1.3 Co-Product Treatment
System expansion is utilized for the handling of co-products, as per life cycle assessment
guidelines[12]. Xylitol is assumed to displace sucrose produced from sugar beets or sugarcane,
as the consumption of xylitol in North America is growing as consumers seek alternatives to
traditional sucrose-based products[23], [33]. Biomethane produced from the anaerobic digestion
of process residues will displace natural gas in a boiler to provide process steam and if
applicable, electricity in a co-generation system. The electricity will be utilized within the
process and any excess is assumed to be sold to the grid, displacing the local mixture. Co-
product credit determination is based on the two reference pathways chosen for xylitol (sugar)
and electricity (Ontario grid mix electricity).
3.1.4 Functional Unit and Impact Category Selection
The functional unit is selected based on the goal of isolating the impacts of xylitol production
from hemicellulose residues in a biorefinery. As a result, the functional unit is set as 1 kg xylitol
produced by the biorefinery. The functional unit is not selected based on a cellulosic ethanol
metric such as 1 MJ of E85 fuel as several different xylitol pathways are to be compared against
one another in this work and a xylitol-based functional unit aids the comparison. System
expansion will be utilized to handle the electricity co-product.
Life cycle assessment results are presented in the form of impact categories. Impact categories
can be generalized into three main areas: resource consumption, human health effects, and
ecological consequences[12]. The quantity and quality of available data for the LCA limit the
accuracy and practicality of taking all impact categories into consideration for this study;
therefore, impact categories are chosen which can be directly linked to process model outputs.
Energy consumption and GHG emissions are selected as the major impact categories to be
reported in this work. Energy is tracked in terms of total energy consumption, natural gas
consumption, and petroleum consumption. Energy required in the biorefinery is generally in the
form of steam or electricity, both of which are produced in a co-generation unit attached to a
boiler[11]. The boiler utilizes a combination of biomethane produced from process residues
along with supplemental natural gas if the biomethane provides insufficient energy for the
process. The consumption of energy from sources such as natural gas, as well as chemicals used
in the process, accrues greenhouse gas emissions associated with their production or use. GHG
39
emissions quantified are carbon dioxide, methane, and nitrous oxide (CO2, CH4, and N2O,
respectively). Emissions are reported in terms of a single carbon dioxide equivalence value
calculated based on 100-year global warming potential values for the three gases determined by
the IPCC[104].
3.1.5 Software Used for Process Modeling and Life Cycle Inventory Assessment
The main software used to develop the xylitol process pathways is Aspen Plus ®, a process
modelling software developed by Aspen Tech[105]. Process input conditions and unit operation
functions are entered into the software and an array of results are generated for the process
streams. Aspen Plus ® also includes several built-in software options that are used for utility
minimization and process costing.
Emissions for several of the process stages are primarily taken from GREET 2013[106]. GREET
provides comprehensive emissions models for many bio- and petroleum-based product
pathways, including the production and transport of the hybrid poplar feedstock, as well as the
production of ethanol along all stages of its life cycle. The production of xylitol is not currently
included in GREET, hence the need for the development of process models for its production.
3.2 Process Modelling
3.2.1 Feedstock Production and Delivery
Hybrid poplar, a species of hardwood tree, is chosen as the feedstock for this process due to
several positive attributes such as its relative abundance in North America, short rotation, and the
utilization of marginal land for its cultivation[30], [65], [107], [108]. Hybrid poplar also contains
a relatively high hemicellulose fraction compared to other forms of biomass[15], making it a
viable feedstock option to produce xylan-based products such as xylitol.
Table 3-1 below shows the composition of hybrid poplar; approximately 15% of the dry biomass
is composed of xylan, and 20% is hemicellulose components[29]. However, a disadvantage of
hybrid poplar is that it is more recalcitrant to hydrolysis compared to feedstocks such as corn
stover or switchgrass, requiring more intensive pretreatment conditions to liberate the
polysaccharides from lignin[33].
40
Table 3-1: Hybrid poplar composition (adapted from Kim, 2009[29])
Composition Percentage by dry mass
Glucan 43.8
Xylan 14.9
Other carbohydrates
(galactan, mannan, arabinan) 5.6
Lignin 29.1
Ash 1.1
Extractives 3.6
Acetate 3.6
Total % 101.6
It is assumed that the poplar is chipped at the site of harvest and then transported to the
biorefinery gate via medium- or heavy-duty truck. The transportation distance from the poplar
cultivation site to the biorefinery gate is assumed to be 100 km; GREET 2013 software is utilized
to determine the impacts of feedstock production including emissions and energy usage as well
as direct land use change, nutrient, and pesticide addition. Xylitol is assumed to be produced as a
co-product to cellulosic ethanol in this study. As a result, based on system expansion
methodology, the impacts of feedstock production may be omitted from the xylitol LCA results,
as cellulosic ethanol represents the main product in the biorefinery studied.
3.2.2 Biorefinery Modelling
The biorefinery studied in this work produces a variety of products from hybrid poplar feedstock.
Cellulosic ethanol is chosen to be the main product, produced from glucose derived from
cellulose. Xylitol is produced as a co-product from hemicellulose residues extracted from the
feedstock in pretreatment. Process residues are converted into biomethane and electricity through
an anaerobic digester that feeds into a boiler and co-generation system to create process steam
and electricity. Excess electricity is sold to the local power grid, if applicable. Detailed models
are created for the xylitol pathway using Aspen Plus ® modeling software. Experimental work is
also performed to verify certain stages of the models where literature data are available or
unclear.
41
Figure 3-2: Biorefinery process scenario showing xylitol hydrogenation in conjunction with
cellulosic ethanol and electricity production
3.2.2.1 Pretreatment
The first stage in the biorefinery is to fractionate hemicellulose from the cellulose and lignin
components of biomass. A hot water extraction process is utilized as it selectively removes
hemicellulose while avoiding high rates of xylan degradation[10], [109]. Conditions are between
180-200 °C, with residence times of 5-15 minutes[29]. The percentage of hemicellulose
solubilized is a function of process temperature, residence time, hydraulic load, and recycle rate.
For this process, it is assumed that hot water extraction solubilizes 50-62% of the hemicellulose
in the feedstock[29]. Two fractions are created in the pretreatment stage, a solid fraction
composed mainly of cellulose and lignin that continues on to the cellulosic ethanol process for
additional processing, and a liquid fraction containing mainly xylo-oligosaccharides, organic
acids, and soluble lignin[2], [109]. This liquid fraction enters the xylitol pathway.
3.2.2.2 Cellulosic Ethanol Production
Comprehensive models for the production of cellulosic ethanol have been completed elsewhere,
such as by Humbird et al.[11] and as a result, detailed models are not independently prepared for
this process section. In this work, cellulosic ethanol is produced only from C6 sugars derived
42
from the solid, cellulose fraction remaining after pretreatment. Since fewer sugars are available
for fermentation, the ethanol yield is expected to be lower than that presented in prior models
that assume consumption of C5 and C6 sugars[11], [13]. To compensate for this discrepancy, the
yield of ethanol may be scaled to omit the C5 sugar fermentation. The lower yield is then used to
scale the emissions and energy results to appropriate values for use with the xylitol pathway.
Residues collected during the ethanol recovery section are sent directly to a boiler and processed
independently of xylitol process residues, as the solids loading of ethanol-derived residues is
expected to be significantly greater than that of residues from the xylitol pathway.
3.2.2.3 Xylitol Production
Pretreatment yields a liquid hemicellulose extract containing a mixture of xylo-oligosaccharides,
monomeric sugars, soluble lignin, acetic acid, and degradation products such as furfural[29]. The
xylo-oligomers must first be hydrolysed to release monomeric sugars, which must be further
purified. Xylitol production via hydrogenation requires an extremely pure xylose feed. This is
due to the non-specificity of the Raney-Nickel catalyst[18]. An impure polyol mixture is
challenging to separate due to the similar physical and chemical properties between polyols[18],
[78]. The upstream stages in the xylitol hydrogenation pathway centre on xylose purification to
yield xylose with purity of 99% and above. Similar to hydrogenation, the xylitol fermentation
pathway requires some purification of the hemicellulose extract, dependent on the tolerance of
the fermenting organism to inhibitors and other contaminants found in the extract (Figure 3-3).
3.2.2.4 Enzymatic Hydrolysis
The liquid extract produced during pretreatment is extracted via filtration, then prepared for
enzymatic hydrolysis. The initial xylose purity in the extract is from 30-50%, based upon pilot
trial results from a confidential industry source. Depending on the solids content of the extract, it
may be concentrated immediately after pretreatment or after enzymatic hydrolysis. The extract is
neutralized using sodium hydroxide to pH 4.5-5.5 and cooled to 45-60°C to ensure optimal
enzyme activity. The extract is fed into large, batch stirred tank reactors heated with internal
heating coils. A cocktail of hemicellulase enzymes is fed into the reactors. The enzymatic
hydrolysis proceeds for 48-72 hours, or until 70-90% conversion of the xylans and other
oligosaccharides to xylose and other pentose sugars has occurred. A yield-based reactor (RYield)
is used in Aspen Plus ® to simulate the enzymatic hydrolysis reactor.
43
Figure 3-3: Block flow diagram of both catalytic hydrogenation (left) and biological
fermentation (right)
3.2.2.5 Xylose Purification
Once enzymatic hydrolysis is completed, the hydrolysate is filtered to remove any residual solid
matter. As the hydrolysate is a mixture of sugars, lignin, and other degradation products,
chromatographic separation is needed to purify the xylose. The most common method for
industrial chromatography is to use a simulated moving bed (SMB) chromatography
system[110].
To ensure favourable separation kinetics, the hydrolysate must be concentrated to 15-30% dry
solids (DS) before entering the SMB system. This is achieved with a multiple-effect evaporation
system. A system with 3-5 evaporators is sufficient to remove the water with a favourable steam
economy[70]. The steam economy is improved through the use of a vapour recycle strategy, such
as thermal vapour recompression (TVR), in which the vapour produced from the effects is mixed
with steam to boost its energy content such that it can be recycled back into the system to do
44
more evaporation work. A separation unit is utilized in Aspen Plus ® to simulate a multiple
column SMB unit. The column achieves a xylose recovery between 70-90%, with xylose
purities between 85-90%. The separation unit utilizes water as the mobile phase, and water is
added at a 2:1-8:1 ratio relative to the feed hydrolysate. The majority of lignin is removed, along
with the contaminant sugars; however, the xylose purity remains too low for direct
hydrogenation.
To ensure the xylose is purified above 99%, an additional purification stage is required.
Crystallization selectively precipitates xylose out of the solution. For crystallization to occur, the
solution must be concentrated until the xylose concentration in solution has exceeded
supersaturation levels. The solubility of xylose, tied to crystallization recovery, increases with
temperature; however, care must be taken to maintain the temperature below 60-70°C to prevent
xylose degradation and the formation of colouring bodies. Supersaturation levels that avoid
significant xylose degradation are achieved in solutions with solids contents of 50-60% DS or
higher, at a maximum of 65 °C.
A second multiple-effect falling film evaporator system is required to concentrate the extract to
supersaturation levels. To prevent spontaneous crystallization from occurring in the evaporator,
which would clog the evaporator piping and lead to reduced performance[70], the concentration
is finished in the crystallizer. A vacuum pan crystallizer is utilized to achieve the final
crystallization. Vacuum pressure is applied to the concentrated extract and steam is added to the
pan to finish the concentration. Once the appropriate supersaturation level, (70-80% DS) has
been reached, the solution is seeded with finely ground xylose crystals at approximately 0.5-1%
of the estimated xylose content, by weight. This allows secondary nucleation to occur, which
results in a more uniform size distribution in the crystal product and also reduces the formation
of fines, which are too small to be recovered in the solid-phase post-crystallization[19]. After
seeding, the solution is sent to an agitated cooling crystallizer, where it is slowly cooled over 48-
60 hours to 15-20°C[17]. Cooling rates are determined based on experimental results. As it
cools, more xylose crystals are formed and grow in the solution, leading to the transformation of
the solution into a thick, particle-filled slurry.
After the crystallization has ended, the slurry is transported to a separation system to remove the
uncrystallised liquid, or mother liquor, from the xylose crystals. A batch centrifuge is used for
45
this stage[70]. The mother liquor recovered from this stage is highly concentrated with a solids
content of 50-60% and may be recycled into the SMB or the evaporation system prior to
crystallization, dependent on its xylose purity. Dependent on the feed purity, the xylose crystals
recovered may fail to reach the purity specification of 99%. A washing stage is thus utilized to
remove the contaminants and color from the xylose crystals. A combination of chilled water and
wash liquor recovered from the wash stage is utilized to wash the xylose crystals. The amount of
wash liquid is minimized to prevent excess crystal dissolution, which lowers the xylose yield.
Washing is expected to lead to xylose losses of 10-30%. The washing stage is combined with
centrifugal separation, leading to an exit xylose crystal purity specification of 99% and a solids
content of 88-92%. If the xylose crystals are further processed off-site, at this stage they are dried
in a spray-dryer and packaged for transportation. In the case of this biorefinery design however,
the production of xylitol is on-site, and the drying stage is omitted for this design. The xylose
crystals are now ready for hydrogenation into xylitol. Process models for the purification of
xylose, from the hemicellulose extract after pretreatment are adapted from Aspen Plus ® models
previously completed within the research group.
3.2.2.6 Xylitol Hydrogenation
The xylose purification process yields purified 90% DS xylose crystals. In order for
hydrogenation to proceed, an aqueous solution of xylose is required at 40-60% DS[71], [75]. The
first stage in the hydrogenation process is to re-dissolve the xylose crystals in process water. The
water is preheated to 60°C and agitated to speed dissolving. Hydrogenation occurs at high
temperature (100-150°C) [17], [111], pressure (50-100 bar)[17], and agitation (300-400 rpm)[75]
to ensure favourable reaction kinetics. To reach the ideal reaction conditions, the solution is first
pressurized from 1 to 70 bar utilizing a series of 3 pumps[112]. The pressurized solution is then
heated to 130°C using a series of heat exchangers. Figure 3-4 displays a block flow diagram of
the xylitol hydrogenation base case (BC) model developed in Aspen Plus®.
Once at reaction conditions, the solution is fed into the batch hydrogenation reactor. The reactor
is an agitated pressure vessel capable of handling the extreme reaction conditions. Granular
Raney-nickel catalyst is added as a slurry to the reactor at 1-5% w/w [113] and is kept in
suspension through agitation from the mixer. Hydrogen gas is sparged into the reactor through a
gas distributor to ensure hydrogen gas bubbles are formed at small enough sizes to overcome
46
mass transfer limitations. The high agitation rate (400 rpm) also enables faster diffusion of the
hydrogen gas from the gas phase into the liquid phase, where it can interact with xylose and the
catalyst. Gas is collected at the top of the reactor, where it exits and flows to a hydrogen recovery
column. The column is modelled as a 2-phase flash column in Aspen Plus ® and operates at high
pressure and low temperature to ensure separation of hydrogen gas from entrained water vapour.
The hydrogen gas is then re-pressurized in a compressor and recycled back into the reactor[114].
It is assumed that 10% of the gas is lost in this recycle process.
The reaction is allowed to proceed for 2 hours, at which point the reaction rate has slowed to the
point where continuing the reaction will yield minimal additional xylitol[113]. Two reaction
yields are proposed for study in this model: a low yield situation and a high yield situation.
Based on literature, the reaction may stall at approximately 80% conversion of xylose to
xylitol[73], or it may proceed to near completion or completion (95-100% conversion) [75], [76],
[78]. The high yield scenario is used as the default for modelling; however, the low yield
scenario is considered as a “worst-case” outcome in a sensitivity analysis. The formation of other
reaction products from xylose such as xylulose and arabinitol is assumed to be negligible, and
omitted from the model[73]. Contaminant sugars remaining in the xylose mixture, glucose and
arabinose are converted to their respective polyols, sorbitol and arabinitol, using the same
fractional conversion as for xylose.
As the solution exits the reactor, it passes through a filter, where the catalyst is recovered for
recycling back into the reactor. Catalyst deactivation is expected to occur; as a result, fresh
catalyst will periodically need to be added to the catalyst stream [111].
47
Figure 3-4: Xylitol hydrogenation base case (BC) scenario diagram
3.2.2.7 Xylitol Purification
Xylitol now must be purified from any remaining contaminants to yield a high purity final
product. This is done through an additional crystallization stage. Due to the increased solubility
of xylitol-water solutions compared to xylose-water solutions, higher solids concentrations must
be reached to obtain an acceptable crystallization yield. Experimental work and literature are
used to determine the optimal solids content of the solution, between 80-90% DS[78]. The
solution is concentrated using a 2-stage multiple effect evaporator system. The final
concentration is done in a vacuum pan evaporator to prevent spontaneous nucleation in the
evaporators, which would lead to clogged equipment and processing difficulties. Experimental
trials reveal that xylitol does not degrade as readily at elevated temperatures as xylose, and
therefore, a higher temperature is used in the evaporators, from 80-100 °C.
After the final concentration occurs under vacuum in the crystallizer, the solution is seeded with
finely ground xylitol crystals. Similar to the xylose crystallization, seeding regulates the crystal
size and growth, leading to a more homogenous product. The crystallizing slurry is moved to a
cooling crystallizer, where it is slowly cooled over 36-60 hours under slow agitation,
approximately 20-50 rpm, to a final temperature of 20°C. The cooled slurry is moved to a
centrifuge, where the liquid mother liquor is separated from the crystals and recycled back to the
48
evaporators. The mother liquor is expected to have a high purity based on the intensive xylose
purification upstream yielding 99% pure xylose and a hydrogenation reaction that proceeds to
near completion. A purge is added to the mother liquor recycle, but the high purity enables the
purge fraction to be low, less than 5%.
The crystals are moved to a fluid bed dryer for polishing before final packaging (Figure 3-4).
The crystals move through the fluid bed dryer on a conveyor belt and hot air is passed through
the belt to vaporize the residual water trapped between the crystals[115]. As the dried crystals
exit the fluid dryer, they are allowed to fall by gravity into the packaging system, which prepares
the crystals for transport by placing them in bulk shipping sacks. As the xylitol will be shipped to
a distribution centre for processing into various food products, individual consumer packaging
and product formulation is not conducted at the biorefinery and is omitted from the model. The
packaging system on-site is assumed to have a negligible contribution to overall process
emissions and energy requirements.
3.2.3 Xylitol Fermentation
One of the key differences between the hydrogenation and fermentation pathways is that
fermentation has not been commercialized to date and has largely been restricted to study at the
laboratory scale. This is a challenge for accurate modelling, as many of the scale-up factors have
yet to be determined and it is unknown what differences in yield and process conditions exist
between the laboratory and the process scale. As a result, where possible, the xylitol
fermentation process stages are kept similar to the hydrogenation stages, as more is known on a
larger scale about these processes. For example, enzymatic hydrolysis is the same for both
fermentation and hydrogenation, as opposed to utilizing a CBP scenario for the fermentation, as
more information is available on the separate hydrolysis stage, which is assumed to lead to
greater accuracy in results. The hydrolysis reaction proceeds at 50°C for 48-72 hours with the
same blend of hemicellulase enzymes added to the stirred tank reactor. Figure 3-3 demonstrates
the major process details for the fermentation pathway, including the common enzymatic
hydrolysis stage. The detoxification stages are also assumed to utilize the same chromatographic
separation technology as in the xylose purification stages of hydrogenation, as a purer xylose
will contain less fermentation inhibitors, including furfural and lignin-derived aldehydes[90]. A
49
block flow diagram for a fermentation scenario using inhibitor intolerant yeast is shown in
Figure 3-5.
Figure 3-5: Low inhibitor (LT) tolerance fermentation block flow diagram
3.2.3.1 Detoxification
The pre-treatment process is expected to release fermentation inhibitors such as lignin
derivatives and furfural and 5-hydroxymethylfurfural from the degradation of pentose and
hexose sugars [74], [91], [92]. Soluble lignins released during hot water extraction such as
syringaldehyde and vanillin may be more toxic to the fermenting organism than the pentose
sugar degradation products [91]. The tolerance of the organism to these inhibitors dictates the
scale of detoxification that must be performed on the extract prior to fermentation. Experimental
results have shown that most yeast species, such as Candida guilliermondii are very sensitive to
inhibitors[92], [116].
The method for removing inhibitors chosen for this work is ion-exchange chromatographic
separation. Similar to the xylose purification process utilized in the hydrogenation process, an
SMB system is utilized for an industrial scale process[110]. Ion exchange chromatography has
50
been shown during pilot trials to be effective at removing soluble lignins, the most toxic
inhibitors, from the xylose fraction. To aid in comparison to the hydrogenation process, the SMB
column is operated at the same conditions and is assumed to have the same recoveries as in the
hydrogenation process. Depending upon organism tolerance to inhibitors, a second SMB unit
may be required to ensure lignin and degradation product concentrations are low enough to allow
favourable fermentation rates. The extract exits the SMB system at approximately 8-15% total
solids[110].
3.2.3.2 Organism Selection and Fermentation
Literature suggests that certain species of yeasts are the most effective at fermenting xylose into
xylitol. Candida guilliermondii FTI 20037 is selected as the fermenting organism for this work
due to the large volume of literature that has been produced for this organism[83], [88], [90],
[92]. C. guilliermondii has a theoretical xylitol yield of 0.9 mole xylitol per mole xylose
consumed[88]; however, a range of literature values have been reported due to factors such as
inhibition[117]. As a result, it is assumed that after purification, xylitol fermentation proceeds to
90% of the theoretical yield, or 0.81 mole xylitol produced per mole xylose consumed.
Fermentation conditions are selected based on literature values. Prior to fermentation, the extract
is neutralized using NaOH[74]. Diammonium phosphate (DAP) is added to the fermentation
broth as a source of nitrogen for the fermenting organism and corn steep liquor (CSL) is added as
an additional N-source as well as to provide trace nutrients[11]. Fermentation is carried out at
30°C in a batch reactor [85], [92]. The reactor is aerated through a gas sparger and agitation is
utilized to maintain appropriate dissolved oxygen levels for cell growth[118]. The duration of the
fermentation is 48-96 hours or until the xylose has been depleted [117].
Fermentation comprises several different reactions including product formation, biomass
accumulation, and several accessory side metabolic reactions that produce ethanol, glycerol, and
lactic acid. The product reaction (Equation 3-1) is determined using the method of half-reactions,
while the other reactions involving biomass are derived from the NREL cellulosic ethanol
fermentation model[11]. These reactions are described in equations 3-1 to 3-5:
(Equation 3-1)
(Equation 3-2)
51
(Equation 3-3)
(Equation 3-4)
(Equation 3-5)
The components for protein and yeast are derived from the NREL cellulosic ethanol
model and the same properties for each component are utilized in Aspen Plus®. Similar to the
NREL model, diammonium phosphate (DAP) and corn steep liquor are used to provide nitrogen
to the fermenting yeast[11]. Xylose fractional conversions for each of the reactions are assumed
to be as follows for all scenarios: the main reaction (Eq. 3-1) is 81%, the biomass accumulation
reaction (Eq. 3-2) is 9%, ethanol formation (Eq. 3-3) is 9%, and the glycerol and lactic acid
reactions (Eq. 3-4 and 3-5) are both 0.5%, leading to complete xylose utilization.
3.2.3.3 Xylitol Purification
One of the significant differences between xylitol hydrogenation and fermentation is the extent
of upstream xylose purification. Dependent on organism tolerance to inhibitors, a less pure
xylose feed can be sent to the bioreactor, compared to the 99% purity xylose crystals required
prior to hydrogenation. The lower purity specification means that crystallization is avoided in the
fermentation process, leading to reduced evaporation demands in the upstream process as the
fermentation broth is dilute at approximately 5-15% DS[110]. To produce the final xylitol crystal
product, the fermentation broth must be purified, concentrated, and crystallized with a final
crystal polishing and drying stage[17].
After exiting the fermentor, the xylitol broth is first filtered to remove the yeast cells, which can
be collected and recycled, if desired. The filtered broth is a mixture of xylitol, unconsumed
sugars, proteins, and residual lignins[116]. Chromatographic separation with a monovalent
cation resin is utilized to separate xylitol from the contaminants. As fermentation is selective,
xylitol is the only polyol present in the broth and the difficulties in separating polyols are
avoided[18]. A combination of ion exchange chromatography and activated carbon is utilized to
remove impurities and to decolourize the broth, which contains many colouring bodies in the
form of soluble lignins.
52
The purified, decoloured broth is then concentrated for the final crystallization step. A multiple-
effect evaporator system is used to bring the solution from 5-15% DS to 80-90% DS.
Evaporation occurs under vacuum, with temperatures in the effects ranging between 70-90°C to
prevent colour formation from any residual impurities. Similar to the hydrogenation pathway, the
final concentration is performed in a vacuum pan crystallizer to prevent spontaneous
crystallization from occurring in the falling-film evaporator system. Crystallization is initiated
through seeding with fine xylitol crystals once supersaturation conditions have been
achieved[70]. The crystallizing mixture is moved to a cooling crystallizer, where the mixture is
agitated and slowly cooled over 48-60 hours.
The crystallized slurry is then separated into crystals and mother liquor by centrifugation. As the
crystals move through the centrifuge, they may be washed with a combination of cooled water
and the collected mother liquor wash liquor combination, dependent on crystal colour. The
washing removes residual impurities and colouring agents, leaving a purified colourless xylitol
crystal product. The crystals are passed into a fluid bed dryer, where they are dried and deposited
into bulk-packaging for transport. The mother liquor and wash liquor are recycled back into the
process to enhance the xylitol recovery. Dependent on mother liquor purity, the recycle may be
directed into a column for additional purification before the recycle.
3.2.4 Heat Integration
To improve the energy consumption of the process models, heat integration is utilized to reduce
utility demand by matching hot and cold streams for heat exchange within the process. The
energy analyser function is utilized within Aspen Plus ®, along with manual calculations for
stream matching and heat exchanger utilization. An interior network of heat exchangers is added
to the process to minimize utility demand. Where stream matching is not possible, utilities are
used to heat and cool the process streams.
3.2.4.1 Utility Estimations
Utilities are needed to provide heating and cooling for process streams and also to provide
electrical work for certain process equipment such as pumps. Low pressure steam at 150°C and
4.5 bar is utilized to heat process streams and for the evaporator systems. High pressure steam is
generated at 60 bar in a boiler and is passed through a combined cycle turbine, which produces
53
electricity for the process. Low pressure steam exits the turbine and is used within the process.
Cooling water is available at 30°C and is produced from a cooling tower using air cooling. For
process streams that need to be cooled below 30°C, chilled water at 4.4 °C is utilized. The water
is chilled in an ammonia chiller, which utilizes electricity to power its internal equipment.
3.2.5 Energy Recovery
Due to the dilute nature of process residue streams, which contain between 5-10% organic solids,
anaerobic digestion is utilized to recover additional value from the residue. Residues are digested
to produce biomethane. It is assumed that the composition of organic waste in the residues is
equivalent to waste produced from a dairy facility. Based on this assumption, it is further
assumed that biomethane will be produced at a ratio of 0.487 m3 per kilogram of dry residue
digested. It is assumed 3.1% of the biomethane produced escapes as fugitive emissions[21]. The
biomethane is fed into a boiler, assumed to operate at 90% thermal efficiency, and combusted to
generate high pressure steam. This steam is fed through a series of turbines to produce
electricity, it is assumed that the turbines operate at 72% efficiency, and the conversion of
turbine work to electricity occurs at 85% efficiency. Low pressure steam at 4.5 bar is extracted
from the turbine system and utilized within the process. Any excess electricity produced by the
system is sold to the local electricity grid.
To obtain accurate, reasonable results in Aspen Plus®, the physical property method must be
changed for each process block and stream. The xylitol pathways are generally modelled using
the ELECNRTL method, due to the diverse composition of liquid and solid streams in the
process as well as the presence of electrolyte species in solution, such as in the neutralization
stage[105]. Vapour components are assumed to be ideal, however, when the STEAM-TA
property method, which utilizes steam table values for water vapour properties was utilized,
turbines were found to require work to expand the high-pressure steam. As this result does not
make physical sense, the property method was changed to SYSOP0, similar to the property
method utilized by NREL for turbines in a cellulosic ethanol process model[8]. The SYSOP0
property method assumes ideal behaviour for both vapour and liquid phases, according to
Raoult’s law and omits heat of mixing and the Poynting correction from all calculations[105].
54
3.3 Experimental Work
Experimental work was done on xylose and xylitol purification to verify the process models, as
literature data were not widely available for these process stages. Crystallization was the primary
focus of experimental work; however, some work with activated carbon and activated carbon
resin mixtures was investigated to remove colour from the hemicellulose extract at various
purification stages.
3.3.1 Crystallization
Crystallization experiments were performed with mixtures of both xylose and xylitol. Full
experimental procedures may be found in Appendix B. Crystallization experiments utilized
different initial solids concentrations, cooling rates, and substrate purities to determine the effects
of these factors on xylose and/or xylitol recovery. A stirred, jacketed, temperature controlled 4 L
glass reactor was used for the majority of all experiments, although several were performed in
shake flasks and 20 L reactors during the concentration stages.
The impacts of crystal washing were also studied using crystallized xylose recovered by vacuum
filtration. Chilled water and water-ethanol mixtures were applied to the crystals through a
sprayer apparatus in order to remove impurities and colouring agents that remained in the crystal
fraction after filtration. For all experiments, samples of the liquor and recovered crystals were
collected and analysed using high-performance liquid chromatography (HPLC), to determine
recoveries and purities. Full results for crystallization and washing experiments are found in
Appendix B. Results from these experiments are utilized for the design/modelling of the
crystallization stages, including xylitol and xylose recoveries, crystal purities, crystal moisture
content, and washing crystal recoveries.
3.4 Techno-Economic Considerations
Financial modelling is utilized to determine the net financial impact of xylitol production on a
primary cellulosic process. As the xylitol process is co-located with cellulosic ethanol in a
biorefinery, the equipment costs and operating costs are assessed to determine the full impact of
xylitol production on the entire biorefinery. Techno-economic results are presented in terms of
2011 US dollars.
55
3.4.1 Capital Cost
To determine the capital costs of the xylitol pathway, the equipment costs for all process units
are estimated. Equipment is sized based on process flows and residence times, yielding a size
factor than can be utilized in equipment sizing correlations. The Aspen Process Economic
Analyser within Aspen Plus ® is utilized to determine costs of process units based on their
individual size factors. Units that are not fully specified in Aspen Plus ® are assessed using
correlations. Vendor data, if available, are considered to be superior to software costing
estimations and are utilized where available. Scaling is utilized to correct capital cost estimates
for equipment with size factors or material outside beyond the range of the software estimate.
Differences in size factors are corrected using the cost-capacity equation:
(Equation 3-1)
Where C represents the equipment cost, and Q represents the size factor. The majority of process
equipment, with the exception of the utility equipment, is composed of stainless steel 316L (SS
316L); differences in material are corrected with a material factor. It is assumed that the material
factor to switch from carbon steel (CS) to SS 316L is 2.1[119]
3.4.2 Operating Costs
The costs related to operation of the xylitol pathway are assessed to determine a total product
cost (TPC) for the xylitol produced. Operating costs (OPEX) are determined by calculating the
flow and cost of raw materials and energy into the process. Required raw materials include
enzymes, sodium hydroxide, hydrogen, and the hybrid poplar feedstock among others and
material flows are taken directly from the process models. Utility costs are also calculated
directly from modelling results. Pricing information for raw materials and utilities is taken from
sources such as ICIS[120] and local utility pricing information. Other operating costs, such
personnel wages, are estimated. Fixed costs, such as insurance, maintenance costs, and others are
also estimated as a percentage of the total capital or operating costs. The following table the
values used to calculate the operating costs and total product cost.
56
Table 3-2: List of values utilized in generating OPEX and TPC
Chemicals Cost Unit Source
Enzymes $4.70 $/kg Hong et al. [121]
50% w/w NaOH $0.69 $/kg ICIS [120]
DAP $0.25 $/kg ICIS [122]
CSL $0.18 $/kg Sengupta and Pike [123]
Hydrogen $1.50 $/kg Dillich et al. [124]
Utilities
Steam 0 $/kg Seider et al. [125]
Cooling Water 0.02 $/m3 Seider et al. [126]
Chilled Water 4 $/GJ Seider et al. [126]
Electricity 0.06 $/kWh Seider et al. [126]
Labour
Operators 70,000
$/person-
year
Seider et al. [126]
Maintenance 2% of CAPEX $/yr Lau [119]
Consumables 1% of CAPEX $/yr Lau [119]
Laboratory 1% of CAPEX $/yr Lau [119]
OPEX
Chemicals +
Utilities + Labour $/kg
General Expenses (GE)
Insurance 0.5% of CAPEX $/yr Lau [119]
Administration, R&D,
Distribution 10% of TPC $/yr
Lau [119]
Depreciation SLD $/yr
Interest Loan interest $/yr
Total Product Cost OPEX + GE $/kg
Calculation of the TPC gives a rough indication of of a “break-even” cost for xylitol. If this price
is in-line with or below current market prices, then there is a benefit to producing xylitol using
this method. If not, the xylitol product will cost the biorefinery more money to produce than to
sell, which will lead to losses if there are no other pricing incentives in place to mitigate a
discrepency.
3.4.3 Cash Flow Analysis
A cash flow table allows the calculation of financial metrics such as the internal rate of return
(IRR), net present value (NPV), and return on investment (ROI). To construct the cash flow
table, straight line depreciation is utilized for the depreciation of plant capital cost. A 20-year
lifespan of the facility is assumed. For each operating year, the operating costs and product
revenues are used to calculate the EBITDA (earnings before interest, taxes, depreciation and
57
amortization). Depreciation and any applicable interest on debt, dependent on how the project in
financed, is then subtracted from the EBITDA, and the relevant taxes owed are removed, leading
the net profit (or loss). Profits or losses are carried forward to the next year, and the same
calculations are repeated.
Once the cash flow has been completed for the lifespan of the xylitol plant, financial metrics are
calculated based on annual net income. The IRR and NPV are calculated utilizing built-in Excel
functions. An interest rate of 15% is utilized to calculate NPV values, as this typically represents
a minimally acceptable rate of return for investment. The ROI is calculated by dividing the
average cash flow by the fixed capital investment. These metrics can determine if the project is
financially viable and can be utilized for different scenarios or pathways to determine if there is
an optimal processing method to produce xylitol.
3.5 Sensitivity Analysis
Many assumptions are made in the construction of process models and in drawing the system
boundaries for life cycle assessment. These assumptions may have significant impacts on overall
process results. To capture the impact of these assumptions, a variety of scenarios are created for
each pathway. Different parameters assumed within the process are altered, and their impact on
the environmental (and financial) results is measured. The sub-sections below describe key
parameters that are considered.
3.5.1 Hydrogenation Yield
Literature values present different yields for the hydrogenation reactor. The low-yield scenario
(LYH), selected as 80% conversion of xylose to xylitol, is studied as a worst-case scenario to
reveal the impact of a low xylitol yield on the overall process. In the low-yield scenario, the
xylitol purity is reduced, and therefore, modifications must be made in the xylitol purification
stage to produce a high purity final product (Figure 3-6). The xylitol purification strategy is
guided by a patent by Melaja[78]. After concentration and crystallization, the xylitol crystals still
contain impurities, reducing crystal purity to approximately 95%. To increase the purity, the
crystals are re-dissolved in pure heated water to 85% DS, then sent into a secondary cooling
crystallizer for additional crystallization. After this step, the crystals are centrifuged and dried,
yielding crystals with 99% purity. Due to the two crystallization stages, a larger fraction of
58
xylitol is lost to the mother liquors, which would otherwise reduce the xylitol recovery across
this stage and for the overall process. To improve xylitol recovery, the mother liquor from the
secondary crystallizer is directly recycled into the pre-crystallization evaporator system, while
the mother liquor from the initial crude crystallization is purified in a column. The column is
able to selectively purify xylose from xylose, given their different physical and chemical
properties, and is estimated to recover 90% of the xylitol[78]. As water is used as the mobile
phase in the column, the purified mother liquor must be concentrated significantly before it is
recrystallized; the mother liquor is thus added back into the evaporator system where water is
removed, albeit with a greater steam/energy demand.
Figure 3-6: Low yield hydrogenation (LYH) scenario block flow diagram
3.5.2 Evaporator Technology
Stream concentration plays a large role in the utility demands of the biorefinery, especially as a
dilute feed produced from hot water extraction must be transformed into a dried final product.
Concentration is typically performed using multiple-effect evaporators[70], [127]. In a multiple-
effect evaporator (MEE), steam is condensed within the calandria of the first effect, causing the
feed to partially vaporize. The vapour produced from the feed is passed onto the next effect,
where it is condensed to provide the heat needed to remove additional water from the feed. This
59
continues for a total of three to five stages in most industrial evaporators[70] until low-pressure
and temperature water vapour exits the final effect. This depleted vapour lacks the energy
content to do additional work, and is condensed and fed back to the boiler that supplies steam to
the MEE system.
Techniques have been developed to optimize the use of steam in the MEE system through the
recycle and reuse of the water vapour that exits each effect. The first is thermal vapour
recompression (TVR). The TVR system utilizes a steam-jet booster to combine steam and
exhausted water vapour to improve the heat value of the vapour[70]. Process steam is first sent
into the steam-jet booster, where it passes through a thin nozzle, simultaneously increasing in
velocity and decreasing in pressure. The low pressure, high velocity steam draws a fraction of
the water vapour exiting the last effect into the steam-jet booster where it is compressed as it
exits the booster to increased temperature and pressure[128]. The revitalized vapour is then sent
to the first effect to drive evaporation. The use of the steam-jet booster can lead to major
reductions in steam demand for the MEE system[129]. The layout of a TVR system is displayed
in Figure 3-7.
An alternative method of vapour re-use can be obtained if the vapour is recompressed
mechanically via a compressor, instead of with steam. This method, known as mechanical
vapour recompression (MVR), completely removes the need for steam from the evaporator
system. As is displayed in Figure 3-7, vapour exiting each effect is directed to a compressor,
with only a fraction being diverted to a condenser that follows the last effect. The compressor
utilizes electricity to pressurize the vapour, increasing both vapour pressure and temperature. The
vapour passes through a cooler after compression to ensure it maintains appropriate temperatures
within each effect that do not cause sugar degradation. The vapour is split after it is cooled and
returned to the effects, where it is condensed to drive the evaporation. The most distinct feature
of MVR is the elimination of steam demand, which is useful for processes that face steam
constraints or elevated steam and/or boiler fuel costs. However the effectiveness of MVR is tied
into the local grid electricity emissions and price, as the electricity demand of MVR is higher
than MEE or TVR[17].
An additional method of concentration is reverse osmosis or nanofiltration. Contrary to
evaporator systems, reverse osmosis utilizes a pressure differential to selectively remove water
60
through a porous membrane[129]. While a promising option, the study of RO is not included in
this work and the scope is limited to studying differences only in evaporator systems.
For the hydrogenation pathway models, two-stage MVR and TVR modules are created within
Aspen Plus ® to capture the impacts of their utilization on steam and electricity demand for the
concentration of xylitol solutions after hydrogenation. Three to five stage evaporator systems are
utilized for the evaporation in the fermentation process, dependent on evaporation demand, as
well as for the upstream concentration in the hydrogenation process. A comparison of the TVR
and MVR modules aids in capturing the cost and environmental impacts of the evaporator design
in the context of an Ontario biorefinery.
Figure 3-7: Comparison between multiple-effect evaporator (MEE) system, thermal vapour
recompression (TVR) and mechanical vapour recompression (MVR) multiple-evaporator
systems
3.5.3 Crystallization Strategy
An additional strategy not included in the high-yield baseline pathway for xylitol hydrogenation
is the use of multiple crystallizers instead of a single crystallizer and a recycle loop (Figure 3-8).
In this scenario, the first crystallization remains the same as in the initial scenario, and the
crystals are separated from the mother liquor via centrifugation. However, instead of recycling
the mother liquor, it is concentrated in a vacuum pan crystallizer to supersaturation conditions
61
and is re-crystallized to yield additional xylitol. The xylitol produced in the second crystallizer is
expected to be of a lower grade than what is produced from the first crystallizer[70]. This xylitol
may be packaged and sold for a lower price than the higher grade xylitol, or it can be washed and
included with the higher grade crystals. The mother liquor produced from the second crystallizer
is treated as waste and directed to residue collection for conversion into process energy. A
summary of all hydrogenation scenarios is provided in Table 3-3.
Figure 3-8: Two crystallizers in series with no recycle xylitol hydrogenation scenario (2
CR) block flow diagram
3.5.4 Fermentation Inhibitor Tolerance
A major factor in the performance of the fermentation pathway is the tolerance of the fermenting
organism to inhibitors present in the hemicellulose extract. The baseline process model assumes
a low tolerance to inhibitors, in-line with literature findings. However, it may be reasonable to
expect an improvement in organism inhibitor tolerance through genetic engineering or selection.
As a result, a high-tolerance scenario is investigated where no purification of the hydrolysate is
required after enzymatic hydrolysis, leading to the omission of the upstream chromatographic
separation units (Figure 3-9). This is representative of a best case scenario for the fermentation
pathway, and will aid in determining if the fermentation pathway has any expected advantage
62
over the conventional chemical hydrogenation pathway. A summary of all fermentation
scenarios is provided in Table 3-3.
Figure 3-9: High inhibitor tolerance (HT) fermentation scenario block flow diagram
3.5.5 Techno-Economic Sensitivity
Sensitivity of the financial performance to a variety of parameters is also assessed:
1. Xylitol Product Price
Range: $3/kg, $3.5/kg, $4/kg, $4.5/kg $5/kg, $5.5/kg
2. Debt-to-Equity Ratio
Range: 40%:60%, 50%:50%, 60%:40%
3. Loan Rate
Range: 6%, 8%, 10%
4. Capital Cost
Range: -25%, 0%, +25%
63
The sensitivity analysis can identify critical process parameters that impact financial
performance. This can gauge the robustness of the xylitol plant, and forecast how it will perform
under different economic conditions.
3.5.6 Other Sensitivity Parameters
The yields of major process stages, such as the hot water pretreatment process, enzymatic
hydrolysis, and chromatographic separation are also investigated to determine their impacts on
overall process yields and emissions.
Table 3-3: Summary of process model scenarios
Pathway Case Abbreviation Evaporation
Scenario
Methods
Section
Hydrogenation
Base case
BC
MEE 3.2.2.6
TVR 3.5.2
MVR 3.5.2
Low yield hydrogenation LYH MEE 3.5.1
Two crystallizers, no recycle 2CR MEE 3.5.3
Fermentation
Low tolerance
LT
MEE 3.2.3
TVR 3.5.2
High Tolerance
HT
MEE 3.5.4
TVR 3.5.2
64
Results and Discussion 4
The process, environmental, and economic results for the production of xylitol from
hemicellulose are presented for xylitol hydrogenation, fermentation, and different process
scenarios. The process modelling and environmental results for the hydrogenation and
fermentation pathways, including the performance of different scenarios for each pathway, are
discussed individually. A combined financial analysis for selected pathways scenarios is
discussed following the pathway-specific modelling and life cycle results.
Due to the broad scope of results presented, results will be presented in the following order: (i)
mass and energy balance results obtained from process modelling and experimental work, (ii) an
investigation of the impacts of the different scenario results, (iii) life cycle results for the
scenarios, and finally (iv) combined financial results. Electricity is considered as a co-product in
cases where process residues are able to generate energy in excess of process needs.
4.1 Process Modelling and Environmental Results
Process models prepared in the Aspen Plus software are used to generate mass and energy
balances for both the hydrogenation and fermentation pathways, including different process
scenarios explored. The models begin with hemicellulose hydrolysate produced during
pretreatment as this is the point at which the hemicellulose residues exit the cellulosic ethanol
process and enter the xylitol process. A dry xylitol crystal of minimum 98.5% purity is produced
from the models in all scenarios. Process residues are dilute and transformed into biomethane via
anaerobic digestion. Biomethane is utilized within a boiler system to generate process energy.
Utilities are calculated in the models to assess steam and electricity demand.
4.1.1 Hydrogenation Pathway
The hydrogenation process model is generated from a combination of three separate modules:
enzymatic hydrolysis, xylose purification, and xylitol hydrogenation. The overall process is run
as a batch-continuous process, with some stages such as enzymatic hydrolysis and hydrogenation
occurring in batch, and others such as chromatographic separation and crystallization occurring
continuously or in a combination of batch and continuous operations. The enzymatic hydrolysis
and xylose purification modules utilized in this work were adapted from modules previously
completed in the research group. The xylitol hydrogenation model commences with the
65
crystallized, purified xylose produced from the enzymatic hydrolysis and xylose purification
modules. The initial hemicellulose extract is composed of 10% dry solids. Several different
scenarios for the xylitol hydrogenation process, beginning downstream of xylose purification, are
developed to study the impacts of different process parameters on overall process yield and
performance. It is assumed that the hydrogenation facility will operate 24 hours a day at a 95%
yearly operation factor, or 347 days, leaving time for annual shut down and maintenance.
Confidentiality agreements with industrial partners prevent the presentation of explicit results for
the hydrogenation pathways. To overcome these limitations, results are presented as a range
between “worst” case and “best” case scenarios, with the calculated results falling within this
range. Performance for the best case and worst case scenarios is determined for each major
process section; a summary of the performance assumptions made for each case may be found in
Table 4-1. Yields are derived from both literature and experimental work. The yields for the
xylitol hydrogenation and recovery section are taken directly from Aspen Plus® models
developed in this work.
Table 4-1: Yields utilized in major hydrogenation scenario process stages
Base Case
(BC)
Low Yield
Hydrogenation (LYH)
Two-Stage
Crystallization (2CR)
Worst Best Worst Best Worst Best
Hybrid Poplar
Hemicellulose Fraction 15% 21% 15% 21% 15% 21%
Autohydrolysis Xylan
Yield 62% 70% 62% 70% 62% 70%
Enzymatic Hydrolysis
Xylan Conversion 70% 90% 70% 90% 70% 90%
Xylose Purification
Recovery 35% 72% 35% 72% 35% 72%
Xylitol Hydrogenation and
Recovery 90% 90% 60% 80% 70% 90%
Crystallization experiments conducted in the laboratory were utilized to estimate yields and
recoveries for both xylose and xylitol crystallization. A lack of available literature on
crystallization at mild process conditions led to the development of several experimental trials.
Single-stage crystallization was able to recover 40% to 60% of the available xylose in the form
of 90-99% purity crystals from solutions with an initial purity of 60-80%, and 40% to 50%
xylitol could be recovered in the form of 92-99.9% purity crystals from solutions with an initial
purity of 90-100%. One major limitation with the experimental results is that they were
66
conducted at the lab scale, and recoveries and purities may not scale directly to a large scale
process. The impacts of recycling mother liquor were also not directly captured in the
experimental work. However, testing the crystallization of lower purity feeds can be
representative of the second stage of crystallization using liquor from the first stage of
crystallization, Thus, the overall recovery, including liquor recycle or a second stage of
crystallization, is expected to be significantly greater than the single pass yields listed above, and
a recovery of 70% was assumed for crystallization performance in the models. Results from
crystallization experiments may be found in Appendix B. Table 4-2 contains mass balance
results for products entering and leaving the xylitol biorefinery. Only a portion of the hybrid
poplar is diverted into the xylitol pathway, as only the hemicellulose and lignin components of
poplar that are solubilized become feedstock for the xylitol pathway. Results are shown in for the
base case, which has been modelled as described in Section 3.2.2, as well as for several different
scenarios, which are described in Section 3.5.
Table 4-2: Mass balance for 20, 000 tpy xylitol produced via hydrogenation
Base Case (BC)
Low Yield
Hydrogenation (LYH)
2 Stage
Crystallization (2CR)
Inputs Unit Worst Best Worst Best Worst Best
Hybrid
Poplar
103
tonne/yr 887 217 1880 308 1140 217
Enzyme tonne/yr 762 288 1160 330 1000 295
NaOH tonne/yr 6860 3340 10480 3820 9030 3410
Hydrogen tonne/yr 296 296 364 273 314 244
Yield kg/tonne 22.6 92.1 15.0 65.0 17.5 92.1
Outputs
Xylitol tonne/yr 20000 20000 20000 20000 20000 20000
Electricity GWh/yr 22.0 10.7 5.88 1.91 26.9 10.2
Digestate 10
3
tonne/yr 100 48.8 140 45.2 109 41.3
Overall yields for conversion of the hybrid poplar feed to xylitol are between 2.3-9.2%,
comparable to ranges presented in literature[16], [42]. The base case (BC) has the highest yield
performance of the three pathways as the high purity of the xylose into the hydrogenation
pathway and the high conversion of xylose achieved in hydrogenation enables a high recycle rate
in the xylitol recovery stage (98%), leading to minimal product loss. Raney-Nickel catalyst,
along with the chromatography resin, are not included in the mass balance as it is assumed to
have a long life span, and thus, has a negligible input flow compared to other input flows.
67
Significant yield losses in the hydrogenation stage are observed for the low yield hydrogenation
(LYH) and 2-stage series crystallization (2CR) scenarios, increasing the consumption of
feedstock and chemicals in the upstream processes for both cases, since the objective is to
maintain 20,000 tpy of xylitol production. In the LYH scenario, hydrogenation proceeds at 80%
xylose conversion, resulting in an impure feed to the crystallization recovery stage. To produce
high-purity xylitol (99.1% purity), the material initially undergoes crude crystallization. The
crude crystals are then re-dissolved and crystallized in a second crystallization unit. The mother
liquor produced from the crude crystallizer is purified in a chromatographic column to separate
xylitol from xylose, and is recycled to the pre-crystallization evaporation system. This is in
contrast to the base case (BC), which produces sufficiently pure xylitol such that a
chromatography system is not required. The need for a chromatographic separation unit in the
LYH scenario increases the evaporation demand, removing the additional water that must be
used as the mobile phase in the SMB columns. This increases the energy demand in the process,
which is reflected in the lower electricity production seen for the LYH case compared to the
other cases.
The two crystallizer scenario (2CR) utilizes two crystallizers in series to purify xylitol after
hydrogenation. The concentrated xylitol solution is crystallized to produce “A” grade xylitol
crystals, with a purity of 99.8%. The mother liquor is then passed to a second vacuum pan
crystallizer, where it is re-concentrated and crystallized to produce “B” grade xylitol, with a
purity of 99.4%. The xylitol streams may be combined into a bulk product stream, or separated if
there is a price incentive for the higher purity xylitol.
The xylitol process yields may be improved for all scenarios by selecting an alternative
feedstock, such as corn cobs or other agricultural residues. Hybrid poplar was selected due to its
importance as a cellulosic ethanol feedstock, however the prevalence of corn cultivation in North
America means corn based feedstocks are potential alternatives. Corn based feedstocks have
higher hemicellulose and lower cellulose contents than hybrid poplar (refer to Table 2-1). This
implies that the xylitol yield from these feedstocks will likely be increased, while the cellulosic
ethanol yield is reduced, which may impact the environmental results.
68
4.1.1.1 Energy Use
The combustion of biomethane produced from process residues eliminates the need for an
external boiler energy source such as natural gas or biomass. Fossil-derived energy is required to
transport the xylitol to a distribution centre, and to produce the hydrogen utilized within the
process. Hydrogen is produced from natural gas via a small-scale on-site steam methane
reforming facility. As xylitol is to be produced as a co-product of cellulosic ethanol, the energy
required to produce and transport the feedstock can be completely allocated to cellulosic ethanol
production, as this research follows a system expansion approach for handling co-products.
Petroleum is required to transport the xylitol product by truck to a distribution facility. It is
assumed that the facility is located 800 km from the biorefinery and that the average truck
payload is 30,420 kg[130]. Electricity production from biomethane is in excess of process
requirements for all hydrogenation scenarios. A summary of the energy demand for the
hydrogenation scenarios is presented in Figure 4-1.
Due to the production of biomethane from process residues, as well as the allocation of all
feedstock energy requirements to the main cellulosic ethanol product, energy demand for the
hydrogenation process is primarily dictated by hydrogen demand. In the base case (BC), xylose
flows entering the hydrogenation stage are equal, as the performance of hydrogenation and
xylitol recovery, 0.9 kg purified xylitol/kg xylitol, is the same for both the best and worst case.
Due to this, process energy use values are the same for both the best and worst cases in the BC
scenario.
Figure 4-1: Energy consumption for xylitol hydrogenation pathways (BC: Base Case;
LYH: Low Yield Hydrogenation; 2CR: 2 Crystallizers, No Recycle)
-5
-4
-3
-2
-1
0
1
2
3
Worst Best Worst Best Worst Best
BC LYH 2CR
MJ
/kg
xy
lito
l
Electricity Credit
Coal
Petroleum
Natural Gas
Total Energy Usage
69
The reduced yield and more intensive xylitol purification required in the LYH scenario cause this
pathway to have the highest net energy demand of all the cases studied. The electricity produced
from biomethane is largely consumed within the LYH process due to the higher extent of water
removal that must occur to yield the target 20 ktonne/yr xylitol product. As the 2CR pathway
does not involve a recycle loop or additional chromatographic purification, a lower energy
demand is expected, dependent on crystallization recoveries and the energy required for
additional cooling in the second crystallizer. The worst case scenarios for both the BC and 2CR
stages generate more process residues compared to the best case scenarios. Yield losses imply
that 410% more HP feedstock is required in the BC worst case scenario, and 525% more
feedstock is required in the 2CR worst case scenario compared to their respective best case
scenarios. The additional process residues generated by the additional feedstock lead to greater
production of methane compared to the higher yield cases. The increased electricity output
causes the BC and 2CR pessimistic cases to require less net energy than the optimistic cases,
despite having poorer xylitol yields and a much greater demand for feedstock.
4.1.1.1.1 Anaerobic Digestion and Electricity Production
For models in which biomethane production from anaerobic digestion of residues exceeds
process thermal energy demands, an electricity generation system is developed. A turbine system
is used to produce electricity from the combustion of biomethane. A series of turbines is utilized
to extract work from high pressure steam generated at 60 bar the boiler. The amount of high
pressure steam entering the turbine system is a function of the biomethane produced by
anaerobic digestion. It is assumed that the boiler has a thermal efficiency of 90% and that the
biomethane has a higher heating value equivalent to natural gas. A compression ratio of 0.5 is
used in each turbine until the pressure reaches 4.5 bar, the steam pressure used in the process unit
operations. Figure 4-2 displays the Aspen Plus turbine model used to calculate process electricity
generation.
The work produced by the turbines is summed and multiplied by an efficiency of 85% to
calculate the electricity production in a generator. Electricity generation results for all scenarios
yield electricity at 15-18% of the boiler heat duty, which may be a conservative value as 20-25%
electricity recovery is expected for a similar system. As a result, the electricity co-product values
may be slightly underestimated in the energy, GHG, and economic results.
70
Figure 4-2: Turbine process model used to generate electricity (generated in Aspen Plus®
with stream conditions and pressures shown)
The extent of the anaerobic digestion of residues is based on the assumption that organic
components found in the residue streams including carbohydrates, organic acids, and soluble
lignin components are digestible. This assumption may impact biomethane production, as
phenolics found in soluble lignin components may inhibit digestion, leading to lower rates of
biomethane production. The waste stream fed to the anaerobic digestion unit is composed of 55-
60% carbohydrates, xylitol, and other organic components (glycerol, ethanol, lactic acid, etc.)
and 40-45% soluble lignin, though slight variation exists between xylitol pathways. If the soluble
lignin cannot be partially or fully digested, there will be significant reductions in the biomethane
produced via anaerobic digestion, likely leading to elevated GHG emissions for all xylitol
pathways as the electricity co-product will likely be reduced or eliminated.
4.1.1.2 Greenhouse Gas Emissions Results
As xylitol is a co-product in this analysis, the production of hybrid poplar feedstock is
completely allocated to the cellulosic ethanol main product, based on system expansion
methodology. Emissions for the production and transport of the feedstock are thus not included
in the xylitol results. Figure 4-3 displays GHG results for the different hydrogenation scenarios
for both the best and worst case performance cases. The production of biomethane is expected to
lead to fugitive biomethane emissions. Fugitive biomethane is assumed to be produced at 3.1%
of the total biomethane production.
71
As xylitol is assumed to displace sucrose, a displacement credit based on the GHG intensity of
sucrose production can be applied. The GHG emissions from the production of sucrose are
dependent on feedstock and location. Renouf reports the GHG emissions of sucrose from
Australian sugarcane to be 120 g CO2-eq/kg sucrose, including a displacement credit from the
production of electricity from bagasse, while US corn based sucrose and UK sugar beet sucrose
have GHG values of 950 and 580 g CO2-eq/kg sucrose, respectively [131]. Seabra reported GHG
emissions of 234 g CO2-eq/kg sucrose for a Brazilian facility producing sugar and ethanol from
sugarcane[132]. Emissions values obtained from the LCA software SimaPro for the production
of sucrose from sugar beets in the European Union show net emissions of 841 g CO2-eq/kg
sucrose (Refer to: Appendix C). As Canadian sucrose is primarily produced from sugar beets and
sugarcane, the approximate the sucrose credit obtained for an Ontario-based biorefinery is
expected to fall within the range of values presented for sugarcane and sugar beet production
(134-841 g CO2-eq/kg) [133].
Figure 4-3: LCA results for hydrogenation scenarios
From Figure 4-3, it can be seen that for all cases, process performance determines whether the
emissions for xylitol production will exceed the upper end of the sugar displacement credit
range. As the sucrose GHG emissions credit would be subtracted from the net xylitol GHG
-500
0
500
1000
1500
2000
2500
Worst Best Worst Best Worst Best
BC LYH 2CR
g C
O2
-eq
/kg
xylit
ol
Product Transport Biomethane Emissions Chemicals Electricity Credit Net
72
emissions, this indicates that the worst performing xylitol hydrogenation scenarios would
increase overall GHG emissions for a cellulosic ethanol process and would negatively impact its
environmental performance for a biorefinery situated in Ontario, while the best performing
scenarios may offer an overall reduction in GHG emissions, dependent on the value of the
sucrose credit. The predominant contribution to net process emissions comes from chemicals
used within the process. Table 4-3 summarizes the GHG emissions associated with the major
chemical inputs utilized in the xylitol hydrogenation pathway. The emissions value for hydrogen
is significant due to the high volume of natural gas used as both the feedstock and process fuel in
SMR (3.6-4.2 kg NG/kg H2)[134], [135]. Hong et al. demonstrated that the production of
enzymes is more GHG intensive compared to previous estimates[121]. The worst case scenarios
have much greater throughputs at the earlier process stages to overcome yield losses, leading to
increased enzyme and sodium hydroxide demand for each unit of xylitol, as shown in Figure 4-4.
Yield differences in the hydrogenation stage have smaller impacts on hydrogen demand as
purified xylose flows into the hydrogenation stage are several orders of magnitude smaller than
in the early stages of xylose purification, leading to smaller variations in hydrogen demand (and
associated GHG emissions) compared to enzyme and sodium hydroxide demand.
Figure 4-4: Contribution of process chemicals to hydrogenation pathway emissions
The high emissions associated with enzyme production indicate that the choice of the
combination of hot water extraction and enzymatic hydrolysis as the pretreatment method is
another contributor to the process emissions. While the treatment was chosen for its mild process
0
100
200
300
400
500
600
700
800
900
1000
WORST BEST WORST BEST WORST BEST
BC LYH 2CR
g C
O2-e
q/k
g x
yli
tol
Enzyme
NaOH
Hydrogen
73
conditions, and low degree of xylose degradation, the environmental benefits are mitigated by
the significant enzyme demand and the GHG intensity of enzyme production. An alternative
pretreatment method, such as dilute acid pretreatment, which simultaneously solubilizes xylans
and degrades them into xylose, may reduce chemical emissions as it avoids the use of enzymes.
Sulfuric acid is commonly utilized in conventional xylitol production at solution concentrations
of 0.5-4% w/w[16], [17]. The emissions value for the production of sulfuric acid has been
estimated at 14.8 g CO2-eq/kg H2SO4[106]. This is considerably smaller than the GHG value for
enzymes. Emissions for the use of sulfuric acid would be an estimated 25-105 g CO2-eq/kg
xylitol for the best and worst base case scenarios, respectively for the addition of sulfuric acid at
2%w/w to a flow of hybrid poplar at 11% solids. The use of an acid may, however, also increase
the amount sodium hydroxide required to neutralize the solution, as a lower pH would be
expected in the pretreatment stage that produces the C5-rich extract. Residual sulfur and
inhibitors from use of sulfuric acid may also affect downstream separation and reduce yields,
which would ultimately increase emissions. Nonetheless, given that emissions associated with
enzyme addition are as high as 930 g CO2-eq/kg xylitol in the LYH worst case scenario,
significant improvements in process environmental performance might be achieved using dilute
acid pretreatment instead, although this could add other environmental and financial burdens.
Anticipated improvements to enzyme performance could also significantly reduce the
contribution of this factor to overall process emissions.
Table 4-3: GHG emissions for xylitol hydrogenation process inputs
Chemical Emissions Unit Source
Hydrogen 16.3 kg CO2/kg H2 GREET 2013[106]
Enzymes 16.0 kg CO2/kg protein Hong 2013[121]
Sodium Hydroxide 1.45 kg CO2/kg NaOH Hong 2013[121]
The production of biomethane completely mitigates emissions associated with process thermal
and electrical energy demands for all scenarios, and leads to the generation of an electricity co-
product credit. Electricity generation is dependent on the amount of process residues captured
from process waste streams. Despite having a poorer performance in the production of xylitol,
process scenarios with lower yields generate larger volumes of process residues, resulting in the
generation of larger amounts of electricity. This is seen in the lower performance cases for all
hydrogenation scenarios, as the magnitude of the electricity credit is greater than that obtained
74
for the higher performing cases (Figure 4-3). Despite having the lowest xylitol yields, the
electricity credit for the LYH scenario is reduced due to the more intensive xylitol separation
process, which requires more energy. The addition of a chromatography column leads to
increased evaporation demand, negating the benefit of additional electricity produced from
biomethane. The LYH scenario is the worst performing scenario out of all hydrogenation cases
looked at, and represents a worst case scenario for hydrogenation as an industrial hydrogenation
reactor is expected to achieve xylose conversions of at least 80%. Differences in GHG emissions
between the BC and 2CR scenarios are less apparent than in the LYH scenario. The 2CR
scenario utilizes 2 xylitol crystallizers in series instead of a single crystallizer with a recycle
loop, and has a slightly lower yield than the BC scenario, leading to slightly greater GHG
emissions for this scenario compared to the BC. The BC scenario has the best environmental
performance compared to the LYH and 2CR scenarios, and will be used as the main basis for
comparison against fermentation pathways.
The best hydrogenation results calculated in this work, corresponding to the BC best case
scenario (627 g CO2-eq/kg xylitol, or 627 kg CO2-eq/tonne xylitol) far exceed the emissions
value of 3.59 kg CO2-eq/tonne xylitol and 38.6 kg CO2-eq/tonne xylitol reported by Danisco for
the pulp and paper process and the conventional process, respectively[103]. It is unknown what
methods of allocation and crediting were utilized to obtain the emissions results presented by
Danisco. For example, emissions resulting from the consumption of hydrogen alone (240 kg
CO2-eq/tonne xylitol) far exceed the total emissions values reported by Danisco, and therefore, it
is apparent that significant (but undefined) credits were applied. Another factor is that the initial
concentration of the hemicellulose extract used in their analysis is unknown; a more concentrated
initial feed will have lower energy demand, leading to a greater electricity co-product credit.
Furthermore, the Danisco analysis may not have accounted for emissions associated with
enzymes, an important metric that has only recently been recognized. It is known that acid
hydrolysis was utilized in the conventional process analysed, and GHG emissions from the use
of enzymes were avoided in this scenario. As described earlier, using a dilute acid such as
sulfuric acid during pretreatment can reduce GHG emissions if it can hydrolyse xylan and avoid
the use of enzymes, while minimizing other adverse impacts such as yield losses and demand for
neutralizing agents. However, the discrepancy between the current results and those presented by
Danisco cannot be attributed to enzyme emissions alone.
75
All scenarios yield excess electricity, which displaces local grid electricity and results in a GHG
credit for the equivalent emissions of the displaced electricity. Electricity emissions are
calculated on a regional basis using the GREET software. As the plant is situated in Ontario,
excess electricity replaces the Ontario grid mixture. The Ontario grid is composed of a mixture
of nuclear, hydroelectric, natural gas, and renewable electricity sources[136]. As a result, the
GHG emissions associated with grid electricity (226 g CO2-eq/kWh)[106], [136] are smaller than
those for other regional electricity mixes that use GHG intensive fuels such as coal. If the plant
were located in another region, such as the US Midwest where electricity generation is
predominantly fueled by coal, the GHG credit for electricity emissions would increase to 720 g
CO2-eq/kWh[106]. The impacts of the electricity source and plant location are shown in Figure
4-5.
Figure 4-5: Xylitol hydrogenation scenario results utilizing the US Midwest electricity mix
The impact of the grid intensity and larger electricity credit mainly affects the worst case
scenarios, where the larger credit value reduces net GHG emissions significantly compared to
when the Ontario electricity mixture credit is utilized. The BC and 2CR scenarios have net
emissions ranges of 363-616 and 351-819 g CO2-eq/kg xylitol, respectively; these ranges fit
within the range sucrose displacement credits, indicating that these pathways could offer
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2500
Worst Best Worst Best Worst Best
BC LYH 2CR
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Product Transport Biomethane Emissions Chemicals Electricity Credit Net
76
environmental benefits to the cellulosic ethanol main product. These results indicate that location
has a significant impact on process environmental performance, due to regional variations in the
generation of grid electricity. Improving conversions within the process can reduce chemical
demands, leading to reduced GHG emissions; however, these improvements may fail to have as
large an impact as plant location and electricity mix.
The calculation of the Ontario grid electricity GHG intensity is based on an average intensity
taken for all electricity sources. However, the electricity produced from the biorefinery may not
displace the base load electricity produced from hydro or nuclear sources, and instead may
displace the only incremental supply, which is primarily produced from sources such as natural
gas. If this is the case, the Ontario electricity co-product credit can be calculated based on the
incremental supply that is displaced. As natural gas has higher GHG emissions relative to hydro
or nuclear[137], the credit would be greater than the one currently used in the co-product credit
calculations. This indicates that the emissions results presented for all scenarios in Ontario are
conservative estimates, and greater GHG reductions may be expected to be obtained for all cases.
Another factor that impacts overall GHG results is the allocation of emissions associated with
feedstock production and transport to the cellulosic ethanol main process, as xylitol is intended
to be a cellulosic ethanol co-product. This was also done to isolate the xylitol pathway and
improve comparisons between different xylitol pathways. Feedstock production and
transportation emissions were calculated in GREET 2013 [106], to estimate the impact of this
assumption, and were found to contribute between 200 – 660 g CO2-eq/kg xylitol, between the
best and worst scenarios for the BC scenario. Mass allocation was utilized to allocate the
emissions associated with the feedstock to the xylitol process, based on the mass fraction of
feedstock that enters the xylitol pathway after the pretreatment stage. This indicates that
feedstock production can significantly impact the overall GHG emissions of the xylitol pathway.
4.1.1.2.1 Evaporator Technology Emissions Results
The dry xylitol crystals must be produced from a dilute, 5-10% solids initial solution, and
therefore, evaporation drives process energy demand. Reducing process energy demand can
potentially lead to increased electricity export to the local grid, increasing the co-product credit
and reducing overall GHG emissions. Different evaporator technologies are investigated to
determine their impact on evaporation system performance for the BC and LYH scenarios. As
77
the models for xylose purification already have complex TVR systems and heat integration built-
in, they were not additionally modified. To simplify the comparison, only the final evaporation
stage in the hydrogenation process is studied. In this stage, the hydrogenated xylitol solution
exits the reactor at 60% dry solids, and must be concentrated to 90% dry solids prior to
crystallization. As the volume of water to be removed is low, relative to a more dilute initial
solution, a 2-stage evaporator system is studied for all cases. All scenarios are evaluated using
the same evaporator temperature conditions. Thermal (TVR) and mechanical (MVR) vapour
scenarios are created in a separate Aspen Plus ® module and integrated with hydrogenation
model results to yield total thermal and electrical energy results. Thermal and electrical energy
demands for the xylitol hydrogenation and purification stage for each evaporation scenario are
displayed in Figure 4-6. To isolate the impacts of the evaporation technology, scenarios do not
include the production of electricity from process residues; instead it is assumed that natural gas
is utilized to fire the boiler and the Ontario grid mix is used for all electricity demand. Emissions
for natural gas are sourced from GREET 2013[106]. It is assumed that natural gas is converted
into process steam at 90% efficiency in the boiler with zero internal electricity generation.
Figure 4-6: Isolated evaporation technology scenarios for the xylitol hydrogenation and
purification stage
The mechanism of TVR involves recycling vapour produced from each effect by mixing it with
process steam, such that it can provide energy to the evaporator effects, and it is thus expected to
0
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MEE TVR MVR MEE TVR MVR
BC LYH
g C
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lito
l
Steam Generation Electricity Total
78
reduce steam demand. Reduced steam demand reduces thermal energy demand and may lower
electricity and cooling water demand as the condenser on the final effect utilizes cooling water to
condense the effluent process vapour. This is seen in Figure 4-6, as the TVR scenario has both
lowered thermal and electrical emissions compared to the initial MEE scenario for both BC and
LYH. By contrast, MVR eliminates steam demand from the evaporation system through
complete vapour recycle. A compressor is utilized in MVR systems to increase vapour
temperature and pressure prior to recycle. MVR systems are expected to lower thermal energy
demand, but increase electricity demand. As expected, this occurs for both the BC and LYH
scenario in Figure 4-6. In this analysis, both TVR and MVR show emissions reductions for the
base case, while only TVR improves emissions in LYH. As the LYH scenario involves a higher
evaporation load due to the use of a chromatography column in the xylitol purification stage,
emissions are higher for all evaporation scenarios compared to the base case. The high volume of
vapour recycle necessary to concentrate the xylitol solution to the desired solids content in the
LYH scenario leads to a significantly larger compressor duty value compared to the BC scenario.
Due to this, the MVR scenario does not improve the GHG emissions compared to the MEE
system. The LYH scenario is more representative of the evaporation stages that must be done at
lower solids concentrations. As TVR was shown to have the lowest emissions of the evaporator
scenarios, TVR will be used in the fermentation scenarios. TVR is also chosen for the
fermentation scenarios, to remain consistent with the xylose purification model, which utilizes
TVR systems to concentrate the xylose solution.
From the results, it is clear that some form of vapour recycle should be used to lower steam
demand, improve environmental results, and potentially improve process economics. Whether
TVR or MVR is utilized in an evaporator system is dependent on several factors. Results are
shown using the Ontario grid electricity mixture and natural gas as energy sources. The use of a
different electricity mixture, such as the US Midwest mix, could significantly alter the
performance/value of the MVR system as the use of coal to generate electricity greatly increases
its associated emissions. The choice of boiler fuel can also have an impact on thermal energy
emissions; for example, a biomass based boiler fuel is expected to have fewer emissions than a
natural gas fuel. Outside restrictions, such as limitations on available process steam, can also
drive the decision between TVR and MVR. Steam limited process facilities are more likely to
choose an MVR system, as it requires no steam, unlike both TVR and a conventional MEE.
79
Reverse osmosis (RO) is another technology option that can be utilized to concentrate process
streams. Conventionally used in desalination and other water treatment applications, RO has
recently risen in popularity as a concentration technology[138]. Reverse osmosis utilizes
pressure gradients to selectively remove water across a membrane, eliminating energy intensive
evaporation entirely. Reverse osmosis does not require steam, only electricity to power the
pumps that pressurize the solution. Jevons and Awe reported that RO requires more electrical
energy than TVR, but less than an MVR system[129]. Based on results shown in Figure 4-6, RO
could offer emissions reductions compared to MVR scenarios, dependent on thermal and
electrical energy sources. However reverse osmosis is limited to concentrating process streams to
a maximum of 25-30% dry solids, and cannot be utilized in this scenario as the initial
concentration is 60% dry solids[129]. Using RO for concentration means that volatile
contaminants will not be removed during an RO process, unlike during evaporation. This does
not necessarily impact the hydrogenation process, but can have an impact on biological processes
as the volatile component furfural is a potent microbial inhibitor.
Xylitol hydrogenation emissions are driven by the intensive production of process chemicals, as
well as the significant energy demand to produce a dry product. Fermentation does not utilize
hydrogen; however, many of the same issues related to enzyme use and concentration are still
present. A comparison of results for different fermentation scenarios is provided and compared
against the hydrogenation scenarios in the following section.
4.1.2 Fermentation Mass and Energy Balances
Fermentation models are generated with Aspen Plus® software based on the methodology
described in section 3.2.3. Two different processing scenarios are explored for the fermentation
pathway. Mass balance results for both scenarios are displayed in Table 4-5. The first assumes
the fermenting organism has a very low tolerance to inhibitors found in the hemicellulose
extract, specifically furfural, HMF, and lignin/phenolics. This is consistent with the current
performance of Candida yeasts in hemicellulose extracts as described in the literature. Inhibitors
are removed by 2 stages of chromatographic purification prior to fermentation to ensure inhibitor
concentrations are below 2 g/L, as recommended by Wang [91]. Chromatographic separation
recoveries are specified based on chromatograms previously generated in the laboratory for
similar feedstocks and conditions. Furfural is more volatile than HMF or lignin and is mostly
80
removed during the evaporation stages prior to chromatographic purification. As
chromatographic separation is optimal at 20-30% dry solids and produces extract at 5-15% dry
solids, the hemicellulose extract must be concentrated before and after each chromatographic
separation stage. Post-fermentation, the broth is purified utilizing a chromatographic column as
described by Melaja to separate xylitol from the other broth components and residual sugars[78].
The second scenario investigated is a theoretical high tolerance scenario, where the organism is
assumed to be completely tolerant to the presence of inhibitors in the fermentation broth, such
that the hemicellulose extract can be directly fermented after enzymatic hydrolysis. This scenario
is a theoretical best case scenario, as the organism that can ferment xylose into xylitol while
withstanding elevated inhibitor concentrations has not been developed, at present. To
compensate for the fact that purification is not performed upstream, the post-fermentation broth
in the high tolerance scenario is purified through a multiple column chromatographic separation
system. A series of resins, including an anionic resin, a cationic resin, and activated carbon are
utilized to selectively purify xylitol. The performance of the column system is calculated to have
a net xylitol recovery between 60% - 77%, which is consistent with the limited literature
available on the purification of xylitol from fermentation broths[17], [94].
As confidentiality requirements with an industrial partner must be respected, the results for both
high and low tolerance scenarios are presented as a range between the expected best and worst
cases determined for the performance of each major process stage. Unit operations upstream of
fermentation, such as enzymatic hydrolysis and chromatographic purification will be presented
in terms of ranges, while fermentation and downstream purification stages will largely be
maintained for all scenarios. This is done to improve comparisons between the low and high
tolerance scenarios, as well as to be consistent with the methodology followed in the
hydrogenation process. Yield values for each stage for both low and high tolerance fermentation
scenarios are presented in Table 4-4. Fermentation for both scenarios is initiated in a seed
fermenter, which receives 10% of the feed flow into the fermentation stage. It is assumed that the
fermentation reactions that occur in the seed fermenter are identical to those in the main
fermenter.
81
Table 4-4: Yields utilized for major xylitol fermentation process stages
Low Tolerance
High Tolerance
Worst Best Worst Best
Hybrid Poplar Hemicellulose Fraction 15% 21% 15% 21%
Autohydrolysis Xylan Yield 62% 70% 62% 70%
Enzymatic Hydrolysis Xylan
Conversion 70% 90% 70% 90%
Detoxification Xylose Recovery 49% 81% 100% 100%
Xylitol Fermentation Yield 81% 81% 81% 81%
Xylitol Purification 86% 86% 60% 77%
Xylitol Crystallization 92% 92% 92% 92%
As the process is heavily dependent on concentration, scenarios utilizing TVR systems with
different configurations and numbers of effects are also studied for both low and high tolerance
scenarios. TVR systems are chosen based on the results of the LYH hydrogenation evaporator
analysis, which showed the largest reduction in GHG results from evaporation came from a TVR
system, and that the results were amplified for the more dilute solution concentrated in the LYH
scenario compared to the BC scenario.
Table 4-5 displays major inputs and outputs for all fermentation scenarios considered. The two
main scenarios, high inhibitor tolerance (HT) and low inhibitor tolerance (LT) are compared for
different initial solids loadings and different evaporator technology strategies. The solids loading
and evaporator technology do not impact process yields, and instead only alter process energy
demand. For the initial concentration stage, the 5% initial solids hemicellulose extract case
utilizes a 5-stage multiple effect evaporator system with two TVR units to re-energize process
vapour. The 10% initial solids hemicellulose extract cases utilize a 4-stage multiple effect
evaporator system for the first concentration stage, with a single TVR unit. All other evaporation
stages are conducted using 3-stage multiple effect evaporators with or without TVR units,
depending on the scenario.
82
Table 4-5: Fermentation mass balance for Low Tolerance (LT) scenarios and High Tolerance (HT) scenarios with different
evaporation configurations and initial solids loadings
Low Tolerance High Tolerance
5% EC1 – TVR
2 10% EC
1 – MEE
2 10% EC
1 – TVR
2 5% EC
1 – TVR
2 10% EC
1 – MEE
2 10% EC
1 – TVR
2
Inputs Unit Worst Best Worst Best Worst Best Worst Best Worst Best Worst Best
Hybrid Poplar 103 tonne/yr 967 299 969 299 969 299 629 249 629 249 629 249
Enzyme tonne protein/yr 641 321 645 307 645 307 418 256 418 256 418 256
NaOH tonne/yr 4010 1910 4030 1920 4030 1920 2620 1600 2620 1600 2620 1600
DAP tonne/yr 166 79.6 167 79.6 167 79.6 109 66.4 109 66.4 109 66.4
CSL tonne/yr 2240 1070 2250 1070 2250 1070 1740 1060 1740 1060 1740 1060
Yield kg/tonne HP 20.7 66.9 20.6 66.9 20.6 66.9 31.8 80.3 31.8 80.3 31.8 80.3
Outputs
Xylitol tonne/yr 20000 20000 20000 20000 20000 20000 20000 20000 20000 20000 20000 20000
Electricity GWh/yr 42.1 0.121 42.0 0.00 93.5 26.9 0 0 9.39 2.82 40.6 18.9
Digestate 103 tonne/yr 129 54.1 133 56.8 136 56.8 79.2 43.7 80.1 44.2 80.1 44.2
1. EC denotes the concentration of the hemicellulose extract entering the pathway. 5% EC indicates a 5% initial solids loading, while 10% EC indicates a
10% initial solids loading. 2. MEE denotes a standard multiple effect evaporator, while TVR implies a multiple effect evaporator with thermal vapor recycle
83
From Table 4-5, it can be seen that overall process yields are higher for the HT scenario
compared to the LT scenario. This is due to the reduction in xylose losses during the
detoxification stages. Based on the yields shown in Table 4-4, the LT scenarios lose between 19-
51% of the available xylose during chromatographic purification, which is necessary to remove
inhibitors and allow fermentation to proceed at the desired rate and yield. Despite these yield
loses, the overall xylitol yield for the LT scenario is reduced by 17-50% compared to the HT
scenario. This may be explained by the need for extensive chromatographic purification in both
scenarios, as a purified xylitol product is required for all cases. The LT scenario utilizes intensive
chromatographic purification in the upstream to reduce the impact of inhibitors on the
fermentation. As a result, the post-fermentation broth has fewer contaminants and requires a less
intensive chromatographic xylitol purification stage compared to the HT scenario. The HT
scenario defers all purification to the post-fermentation downstream, where a more intensive set
of chromatography units must be utilized to separate xylitol from both lignocellulosic
contaminants and microbial products formed during fermentation, leading to greater xylitol
losses in this stage than for the LT scenario.
Overall yields for both the HT and LT scenarios are comparable to the ranges found for the
xylitol hydrogenation scenarios described in Table 4-2; however, it should be noted that the
ranges in the hydrogenation scenarios include more variability in process performance than the
fermentation scenarios, where the performance of fermentation and xylitol crystallization are
unchanged for all cases. Despite the intensive xylose purification required in the hydrogenation
scenario, including an additional crystallization stage, the near 100% xylose conversion achieved
in hydrogenation allows a greater xylitol yield for all hydrogenation scenarios except for the low-
yield LYH scenario, which has a lower yield than both the HT and LT scenarios. This indicates
that one of the benefits of hydrogenation is the high xylitol conversion that can be achieved by
an inorganic catalyst which, unlike a microorganism, does not need to divert xylose into other
metabolic pathways to generate biomass and other fermentation products. An equivalent
biological catalyst, such as the xylose reductase enzyme, could be used in isolation to improve
xylose conversion results[139]; however, considering the GHG intensity of producing the
enzymes required for cellulosic ethanol, the production of xylose reductase could completely
negate the lowered GHG emissions associated with the fermentation pathway.
84
The scenario analysis indicates that both pathways are hindered by low xylan content in the
hemicellulose extract. The dilute nature of the hemicellulose extract feed amplifies the impact of
yield losses, leading to much greater process volumes upstream of the pathway, and greater
feedstock demand to produce an equivalent amount of xylitol. This is demonstrated in the
variability of overall yields shown for both hydrogenation and fermentation, where overall
process yields can be as low as 1.5% hybrid poplar to xylitol.
4.1.2.1 Energy Balance Results
Similar to the hydrogenation scenarios, the combustion of biomethane produced from process
residues alleviates the need for an external boiler fuel. In nearly all scenarios, the combustion of
biomethane is able to generate process steam and electricity in excess of what is required,
leading to the return of excess electricity to the electrical grid. As the fermentation pathway does
not require hydrogen, an SMR facility is not required on-site and the fossil energy associated
with the production of hydrogen is avoided. As a result, fossil energy is only needed to transport
the xylitol to a distribution facility in diesel-powered trucks. The same assumptions are made in
the hydrogenation scenarios for the transportation distance and truck payload.
Energy balance results for the fermentation pathway scenarios are shown in Figure 4-7. As
minimal external energy is required, most cases have a negative energy balance, due to the
export of electricity to the local grid. In general, the LT scenario contributes more electricity to
the grid due to the lower xylitol yield, which results in greater methane and electricity production
on a per kilogram xylitol basis. In particular, the worst case scenarios are shown to have greater
electricity credits due to the excess production of process residues resulting from the lower
xylitol recoveries and conversions. The lower residue production in the HT scenario results in a
higher net energy balance compared the LT scenario for all evaporation scenarios. With less
residue production, there is less organic material available for anaerobic digestion, reducing the
amount of steam that can be produced from biomethane. Consequently, despite having a higher
xylitol yield and a lower evaporation demand due to the reduction in chromatographic
purification stages, the HT scenarios produce less electricity and generally have higher net
energy usage values than the LT scenarios.
85
Figure 4-7: Energy balance for fermentation scenarios
The impacts of thermal vapour recompression are investigated in two different scenarios for both
the LT and HT process models. The inclusion of a TVR system has a dramatic effect on the
results for the 10% EC LT and HT scenarios. The TVR system reduces steam and cooling water
demand by as much as 66%, increasing the excess electricity produced, and leading to a greater
electricity credit, which lowers the overall energy usage. The benefits of including a TVR system
are demonstrated by comparing the 5% EC TVR scenarios for both HT and LT against the 10%
EC MEE scenarios. The first concentration stage must concentrate the extract from the initial
solids percentage to 30% solids prior to chromatographic purification. In the HT 5% EC TVR
Worst Case scenario, to produce a 30% solids extract stream, 296 000 kg/hr of water must be
removed by evaporation in the first evaporation stage. By contrast, only 103 000 kg/hr of water
must be removed in the HT 10% EC Worst Case scenario. Despite the large difference in water
removal, the two scenarios have an equivalent energy balance due to the TVR systems utilized in
the 5% EC case. The use of TVR improves the steam economy of each concentration stage,
reducing the steam and energy demand in all cases where it is utilized.
4.1.2.2 Fermentation Pathway Greenhouse Gas Emissions
Similar to the hydrogenation pathway, emissions resulting from the production of the hybrid
poplar feedstock are completely allocated to the main cellulosic ethanol product and are not
included with the xylitol results. Anaerobic digestion is again utilized, with fugitive emissions
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Low Tolerance High Tolerance
MJ/
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ylit
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Electricity Credit
Electricity
Coal
Petroleum
Natural Gas
Total Energy Usage
86
estimated at 3.1% of the total biomethane volume produced. Results for the low tolerance (LT)
fermentation scenarios are displayed in Figure 4-8 for a conventional multiple-effect evaporator
(MEE) and for a system with a TVR, and corresponding results for the high tolerance (HT)
scenarios are shown in Figure 4-10.
Figure 4-8: GHG emissions for xylitol low tolerance (LT) fermentation scenarios
Compared to the hydrogenation scenarios, the LT fermentation process generates less GHG
emissions in general (Refer to Figure 4-3). The 10% EC LT TVR fermentation pathway has the
lowest net GHG emissions, even obtaining a net negative GHG emissions value for the worst
case, due to the large electricity credit. Based on the net emissions results, this pathway would
reduce the emissions of the cellulosic ethanol main product once the sucrose displacement credit
is applied for both the best and worst case scenarios. Due to the large volume of process residues
produced in the worst case LT scenarios, large electricity co-product credits are achieved for all
worst case scenarios. These results indicate that the amount of process residues and the resultant
electricity produced by each scenario are major contributors to the overall environmental
performance, and a higher xylitol process yield does not necessarily result in improved
environmental performance. As was shown in the hydrogenation scenario, locating the plant in a
geographic location that has a more GHG intensive electricity supply would enhance the
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5% EC TVR 10% EC MEE 10% EC TVR
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Electricity Credit Electricity ChemicalsBiomethane Emissions Product Transport Net
87
electricity credit generated in each scenario, further skewing the environmental results in favour
of the worst case scenarios.
Compared to the hydrogenation pathway, chemical GHG emissions are reduced by eliminating
the hydrogen demand. The nutrients required during fermentation, DAP and CSL, are not
associated with GHG intensive production to the same extent as hydrogen gas. This is reflected
in Figure 4-9, which shows that NaOH and enzyme emissions far exceed the DAP and CSL
emissions for all cases. It can thus be concluded that GHG emissions for xylitol production are
driven by the both chemical demand and the electricity credit generated from transforming
process residues into electricity.
Figure 4-9: GHG emissions associated with chemical inputs into the fermentation scenarios
Despite the overall improved xylitol yield and fewer evaporation stages due to reduced
chromatographic separation states, the HT scenarios do not have significantly reduced net GHG
emissions compared to the LT scenarios (Figure 4-10). This is attributed to the dominant effect
of the electricity credit. Even though the HT scenarios have reduced chemical emissions than the
LT scenarios, the higher yields contribute to a lower residue production, reducing the net
electricity co-product credit. The 10% EC HT TVR case has the lowest net emissions range
(130-150 g CO2-eq/kg xylitol) of the HT scenarios. This is within the sucrose displacement
credit range, indicating that this pathway will have a beneficial impact on the overall cellulosic
0
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200
300
400
500
600
Worst Best Worst Best Worst Best Worst Best Worst Best Worst Best
5% EC -
TVR
10% EC -
MEE
10% EC -
TVR
5% EC -
TVR
10% EC -
MEE
10% EC -
TVR
LT HT
g C
O2
-eq
/kg
xy
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l
NaOH
Enzyme
DAP
CSL
88
ethanol emissions. When compared to the much greater chemical demand of the hydrogenation
pathway, the reduced chemical demand has a large impact on the results. These results indicate
that the fermentation pathway has the potential to significantly improve the environmental
impact of xylitol production compared to the conventional hydrogenation process. However, it
should be noted that tolerance to inhibitors has not been developed to the extent assumed in this
model, and a scenario closer to the LT model would likely represent near term environmental
performance. The role of the electricity credit also has a large impact on net GHG emissions. For
the 10% EC TVR scenario, the worst case scenario has slightly lower emissions than the best
case scenario due to the large electricity credit generated, which compensates for higher
emissions tied to increased chemical demand.
Figure 4-10: GHG emissions for xylitol high tolerance (HT) fermentation scenarios
Similar to the LT scenario, the addition of two TVR units to the 5-stage evaporation system in
the 5% initial extract concentration (EC) scenario improves emissions results to the level
obtained with 10% initial solids and no TVR unit, despite the much larger volume of water that
must be removed in the 5% EC case. These results may be further improved through the usage of
an RO system. As the upper concentration limit of an RO system is approximately 30% dry
-1000
-500
0
500
1000
Worst Best Worst Best Worst Best
5% EC TVR 10% EC MEE 10% EC TVR
Electricity Credit Electricity Chemicals
Biomethane Emissions Product Transport Net
89
solids, this would be an ideal case for the initial concentration stage, which brings the
fermentation broth up to 30% solids prior to chromatographic separation.
In general, the fermentation pathways offer potential reductions in GHG intensity and energy
consumption compared to the hydrogenation pathway (Figure 4-11). Much of this is attributed to
the difference in process chemical requirements, as the production of hydrogen from natural gas
is more GHG intensive than emissions associated with the production of the fermentation
nutrition additives DAP and CSL. However, location also plays an important role in the
performance of these pathways, due to the impact of the electricity grid mixture on the impact of
the electricity credit generated.
Figure 4-11: Summary of best performing scenarios from hydrogenation and fermentation
pathways
4.2 Techno-Economic Assessment
While the LCA results may favour the fermentation pathway over hydrogenation, financial
performance is also a key factor in process selection. In conjunction with the 3 hydrogenation
scenarios discussed, 3 fermentation scenarios are also investigated (5% EC LT TVR, 10% EC
-1500
-1000
-500
0
500
1000
1500
2000
Worst Best Worst Best Worst Best
BC 10% EC LT TVR 10% EC HT TVR
Hydrogenation Fermentation
g C
O2
-eq
/kg
xy
lito
l
Product Transport Biomethane Emissions Chemicals Electricity Credit Net
90
LT TVR, and 10% EC HT TVR). All 3 fermentation scenarios utilize TVR systems, due to the
superior performance of the TVR systems in terms of steam demand and GHG intensity. By
comparison, the selected fermentation cases represent best case scenarios; models that do not
utilize TVR systems will have larger evaporators and greater utility demands, leading to
increased process costs and greater process emissions, and were thus excluded from further
study. All models are scaled to a set xylitol production rate of 20 000 tonnes per year.
4.2.1 Capital Cost Estimation
Summary sheets containing individual capital costs for selected models may be found in
Appendix D. Analogous to the LCA results, financial results are presented in terms of best and
worst cases for all scenarios considered. Costing spreadsheets were developed for the best case
scenarios, then scaled for the worst case scenarios based on process flow rate differences; the
seven-tenths rule was again used for all scaling calculations. Hydrogenation scenarios were only
modelled for the process downstream of xylose purification. Based on shared purification
strategies between the low tolerance fermentation model and the xylose purification model, it is
reasonable to assume that the xylose purification in the hydrogenation models is equivalent to
that for the low tolerance fermentation model up to the xylose crystallization stage. Xylose
purification costs in the hydrogenation scenario are therefore determined by scaling the
chromatographic purification stage in the LT fermentation model based on feedstock flow rates.
Additional costs for the xylose crystallization stage are added separately to the hydrogenation
scenarios.
The Aspen Process Economic Analyser software generates purchased equipment cost values. To
convert the purchased equipment cost to a total capital cost value, a Lang Factor of 2 is utilized;
this factor is expected to include the cost of the construction of buildings, wiring, and other
construction factors. As the Lang Factor method can only provide a rough estimate of total plant
costs, and to account for other factors that may have been omitted from the equipment estimate, a
contingency factor of 20% of the purchased equipment cost is added to the total capital cost
value to provide a conservative capital cost estimate. Total capital cost (CAPEX) values,
including the Lang factor and contingency, are presented in Figure 4-12. Within the
hydrogenation pathway scenarios, it can be seen that the base case (BC) has a lower CAPEX
than the scenarios with 2 crystallizers or a low yield hydrogenation.
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Figure 4-12: Capital cost ranges for all scenarios (Hydrogenation scenarios are shown in
red hatches, fermentation scenarios are displayed in orange)
The hydrogenation scenarios were chosen to investigate differences within a small subset of the
overall hydrogenation process, beginning after the xylose purification stage. As the xylitol
hydrogenation process only composes a fraction of the overall process, the differences in
CAPEX between the 3 scenarios are small, especially in the best case scenario, as the majority of
capital costs are associated with the upstream xylose purification. The differences between the
worst case scenarios are amplified due to yield losses, leading to greater variation in CAPEX
because purchased equipment costs were scaled based on process flows. This is shown in the
wide range of CAPEX scenarios across the hydrogenation scenarios (Figure 4-12). CAPEX
values are presented in 2011 US dollars. The wide range of CAPEX values between the best and
worst cases in the hydrogenation process indicates that yield has a strong impact on total capital
costs, as the yield differences between the best/worst hydrogenation cases are more exaggerated
than the fermentation cases. This difference in yield ranges is a function of the process
performance parameters that were selected for the best/worst cases, as displayed in Table 4-1 and
Table 4-4.
To provide a more detailed understanding of the impact of the different hydrogenation scenarios
on CAPEX, the purchased equipment (PE) costs for the major process scenarios can be isolated,
excluding utility units and anaerobic digestion. A breakdown of the purchased costs of
equipment (PE) in major process stages for both pathways is displayed in Table 4-6. For the
hydrogenation pathway, additional chromatography and crystallization units required to purify
xylitol cause the LYH PE to be higher than the BC and 2CR cases. However, despite the addition
$0 $100 $200 $300 $400 $500 $600 $700
5% EC LT TVR
10% EC LT TVR
10% EC HT TVR
BC
LYH
2CR
Capital Cost ($MM)
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of an additional crystallizer stage in the 2CR system, there is only a small difference in cost
compared to the BC scenario, as the cost of one additional crystallizer is approximately $1MM.
The hydrogenation process scenarios incur the majority of equipment costs in the xylose
purification stage. Similar to the overall CAPEX results, yield differences lead to wide variation
between the best case and worst case PE values.
Table 4-6: Selected purchased equipment costs ($MM) for major process stages for
hydrogenation and fermentation scenarios
Purchased Equipment Cost ($MM)
Hydrogenation Stage BC LYH 2CR
Enzymatic Hydrolysis
and Xylose Purification $65 - $170 $65 - $230 $65 - $200
Xylitol Production and
Purification $6.3 - $12 $8.7 - $22 $6.8 - $20
Fermentation Stage 5% EC LT TVR 10% EC LT TVR 10% EC HT TVR
Enzymatic Hydrolysis $13 - $35 $8.8 - $18 $8.8 - $13
Detoxification $61 - $79 $43 - $66 $0.19 - $0.32
Fermentation $8.0 - $8.6 $8.0 - $8.7 $22 - $35
Xylitol Purification $13-$13 $12 - $13 $22 - $30
Xylitol Crystallization $6.1-$6.1 $6.2 - $6.2 $6.0 - $6.6
When the fermentation scenarios are considered, it can be seen that there is a different PE cost in
the initial stages of the 5% EC LT TVR scenario and the 10% EC LT TVR scenario, despite both
models utilizing the same process conversions. This can be attributed to elevated process
volumes in the initial stages of the model, up to the first concentration stage and the higher
hydraulic load that must be handled by the equipment, leading to larger equipment. The best
performing scenario of all is the high tolerance fermentation scenario (10% EC HT TVR).
Compared to the hydrogenation scenarios and the low tolerance fermentation scenarios, the 10%
EC HT TVR scenario requires fewer purification stages, leading to the omission of 2
chromatography and evaporation stages from this scenario, which contribute strongly to the
elevated CAPEX values for the LT scenarios. The reduction in process equipment reduces the
CAPEX for the HT TVR scenario. Given that the hemicellulose extract is directly fermented
after enzymatic hydrolysis, HT fermentation proceeds at lower solids content, 10%, than the 14%
solids mixture fermented in the low tolerance scenarios. Enzymatic hydrolysis is the first process
stage in all pathway scenarios; as a result, this unit handles the largest flow rates in the process,
prior to any concentration stages. To manage the high process volumes, each scenario is assumed
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to utilize multiple tanks with a liquid volume of 4 000 m3
each. Similar to the enzymatic
hydrolysis stage, the fermentation stage is assumed to occur in multiple agitated, half-pipe
jacketed, SS316L fermenters, each with a liquid volume of 3 000 m3 over a 72 hour fermentation
cycle time, including filling, emptying and cleaning. The difference in solids loading, combined
with the presence of impurities, requires a much larger fermentation reactor, and as a result, the
purchased cost of the main fermenters is $21 MM-$35MM for the 10% HT TVR scenario, but
only $8 MM-$9MM for the 10% LT TVR scenario. Despite the improved performance of the
high tolerance scenario, the range of CAPEX values still overlaps with the range for the
hydrogenation scenarios.
Another significant contributor to the total CAPEX for all scenarios is the anaerobic digestion
unit required to produce biomethane from process residues. Anaerobic digester units are
calculated to contribute between $30MM to $80 MM to the total installed equipment cost. The
dilute nature of the process residues, between 5-10% DS, indicates that the digester must handle
significant residue volumes between 700 000 to 4 000 000 Mg per year, leading to the high
equipment costs.
4.2.2 Financial Indicators
To further understand process financial performance, a cash flow statement was developed for
each design scenario considered in the economic assessment. It is assumed that construction of
the plant will begin 1 year prior to operation of the facility, and that during the first operating
year, the plant will only operate at 50% capacity. Default assumptions used in the financial
analysis for all scenarios are displayed in Table 4-7. A summary of values used to determine the
OPEX is found in Table 3-2. As process steam is generated internally, and not purchased from an
external source, it is assumed to have no explicit costs. An annual interest payment is calculated
using the PMT function in Excel. Property tax is assumed to be associated with the main
cellulosic ethanol plant, since we assume the plants are co-located and is not included in this
estimate.
Full OPEX and TPC statements can be found in Appendix D for selected scenarios. TPC values
for both hydrogenation and fermentation scenarios are displayed in Table 4-8. In general, major
contributors to TPC values include capital related expenses such as depreciation and interest,
which compromise approximately 60% of the TPC in all cases. As steam is produced internally,
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operating costs such as chemical and utility costs only contribute 10% of the TPC, with other
costs such as maintenance and laboratory work that are calculated based on CAPEX comprising
the residual 30% of the TPC.
Table 4-7: List of financial assumptions
Operating Factor 0.95
Operating Year 347 d
Plant Life 20 yr
Xylitol Produced 20000 tonne/yr
Equity 40%
Debt 60%
Loan Rate 8%
Loan Period 10 yr
Tax Rate 25%
Xylitol Price $4.50/kg
Electricity Price 5.72 ȼ/kWh
The best case hydrogenation scenarios generate TPC values less than the xylitol product price of
$4.50 per kg; however, all worst case scenarios have TPC values that exceed the xylitol product
price of $4.50/kg, indicating that the profitability of the hydrogenation pathway is strongly
linked to process performance. Similar results are found for both low tolerance fermentation
cases. It should be noted that while the best case TPC values for the LT cases are greater than the
TPC for the hydrogenation cases, the range of LT TPC values fit completely within the range of
TPC values of the hydrogenation BC pathway. As a result, it is difficult to determine whether the
BC scenario will outperform the 10% EC LT scenario without a more accurate estimation of
process performance. The 10% EC HT TVR scenario has the best TPC performance of all
scenarios, as all TPC values ($2.03/kg - $2.75/kg) are well below the xylitol product price. The
likelihood of a pathway to perform closer to the best case scenario cannot be determined from
the information available in this study, as more detailed process information at a pilot or
industrial scale would be required. However, it does set a valuable research/development target
for organizations aiming to develop a fermentation-based pathway.
95
Table 4-8: Summary of financial indicators for all scenarios studied
Total Product Cost ($/kg) IRR ROI NPV (15%) ($MM)
Hydrogenation Worst Best Worst Best Worst Best Worst Best
BC $5.18 $2.30 20% 56% 10% 29% $67.0 $253
LYH $7.03 $2.38 13% 54% 6.7% 28% -$34.0 $244
2CR $6.38 $2.32 16% 56% 8.1% 29% $12.0 $252
Total Product Cost ($/kg) IRR ROI NPV (15%) ($MM)
Fermentation Worst Best Worst Best Worst Best Worst Best
5% LT TVR $4.62 $3.15 24 % 38% 12% 19% $111 $198
10% LT TVR $4.02 $2.62 32% 48% 16% 24% $172 $237
10% HT TVR $2.74 $1.95 46% 65% 23% 34% $229 $277
While the TPC gives a rough indication of whether the process will produce positive revenue, the
internal rate of return (IRR) gives a better estimate of the viability of a process. The IRR is
calculated from the cash flow statements prepared for each scenario, and results are displayed in
Table 4-8. Cash flow statements may be found in Appendix D for selected scenarios; an example
cash flow statement for the 10% EC HT TVR best scenario is shown Table 4-9. A minimum IRR
value of 15% is a common metric to determine the viability of a project. The IRR values
calculated indicate that all fermentation and hydrogenation scenarios can satisfy this criterion
over the entire range of process yields and conditions, whereas the LYH hydrogenation pathway
can only achieve an IRR of 15% or above for select process conditions. This indicates that the
LYH scenario carries a greater risk for losing money if it cannot perform close to the best case
yield parameters. The higher the IRR, the more attractive the project becomes to an investor.
This indicates that while the best case scenario for the 5% EC LT TVR case exceeds the 15%
IRR threshold, it is less likely to be developed because the IRR is only 38%, much less than the
IRR for the other scenarios, which all exceed IRR values of 48% for the best case scenarios.
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Table 4-9: Cash flow statement for 10% EC HT TVR Best fermentation scenario ($MM)
The net present value (NPV) provides a litmus test of the profitability, as positive NPV values
indicate that the project will perform acceptably, while negative values indicate that the project
should be rejected. NPV values are calculated based on a 15% discount rate, to remain consistent
with the threshold value for IRR performance. Results for NPV calculations for all scenarios are
shown in Table 4-8. Despite the wide range presented for the hydrogenation scenarios, results
indicate that projects will perform acceptably, except for the worst case LYH scenario. The NPV
results for the fermentation 10% HT and 10% LT cases indicate that these projects may be viable
across all performance conditions studied. Another method of evaluating a project is to consider
the return on investment (ROI). ROI results are shown in Table 4-8 for all scenarios. The results
for the ROI values follow a similar trend to the IRR results. It can be seen that scenarios with
favourable IRR values will also have relatively higher ROI values compared to scenarios with
lower IRR values.
Feedstock costs were not included in these results, as they are assumed to be associated with the
main cellulosic ethanol process, and the hemicellulose residues are considered a waste stream.
The cost of waste treatment is omitted from the xylitol results, aside from the cost of anaerobic
digestion and costs are assumed to be associated with the main process. Costs for the xylitol
Year CAPEX Revenue OPEX EBITDA SLD Interest Gross Profit Taxes Net Profit ATCF
0 -$175.0 $104.8 $0.00 -$69.9 $0.00 $0.00 $0.00 $0.00 -$69.9 -$69.9
1 $0.0 $46.1 $5.40 $40.8 $8.70 -$8.40 $23.6 $5.90 $17.7 $26.5
2 $0.0 $92.3 $10.7 $81.5 $8.70 -$7.80 $65.0 $16.2 $48.7 $57.5
3 $0.0 $92.3 $10.7 $81.5 $8.70 -$7.20 $65.6 $16.4 $49.2 $57.9
4 $0.0 $92.3 $10.7 $81.5 $8.70 -$6.50 $66.3 $16.6 $49.7 $58.4
5 $0.0 $92.3 $10.7 $81.5 $8.70 -$5.80 $67.0 $16.8 $50.3 $59.0
6 $0.0 $92.3 $10.7 $81.5 $8.70 -$5.00 $67.8 $16.9 $50.8 $59.6
7 $0.0 $92.3 $10.7 $81.5 $8.70 -$4.10 $68.6 $17.2 $51.5 $60.2
8 $0.0 $92.3 $10.7 $81.5 $8.70 -$3.20 $69.6 $17.4 $52.2 $60.9
9 $0.0 $92.3 $10.7 $81.5 $8.70 -$2.20 $70.6 $17.6 $52.9 $61.7
10 $0.0 $92.3 $10.7 $81.5 $8.70 -$1.20 $71.6 $17.9 $53.7 $62.5
11 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
12 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
13 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
14 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
15 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
16 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
17 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
18 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
19 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
20 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
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process are thus improved via co-location with the cellulosic ethanol process, as there are
opportunities to share utilities, waste water treatment, and others.
Overall, while the economic results for the LT fermentation pathways are comparable to
hydrogenation, falling within the best/worst case ranges described for the hydrogenation
scenarios, there does not appear to be a large incentive to move away from the hydrogenation
technology that has already been proven and commercialized on the large scale. However, due
to the large range in values for each hydrogenation scenario, there is risk that poor process
performance could lead to relatively weaker economic performance. The HT fermentation
pathway does appear to offer an economic improvement over the hydrogenation BC pathway,
although there is overlap between the two ranges. However, this pathway was deliberately
selected to represent a theoretical best case scenario, which has not been achieved in any real
world setting at present. This indicates that inhibitor tolerance is a major objective for organism
development for bio-product applications, and can determine whether a biologically based
process could be superior to a conventional process using hydrogenation catalysts.
Financial results would likely be improved for all scenarios if the anaerobic digestion unit was
removed, as anaerobic digestion accounts for 15-20% of the total CAPEX and the revenue
provided by the sale of electricity to the grid is only $0.03-$0.12 per kg xylitol. Eliminating
anaerobic digestion would require the purchase of a boiler fuel and electricity to meet process
energy demand, which would impact operating costs. However, this would have the greatest
impact on the environmental results, as the environmental benefit of producing xylitol is largely
dependent on the significant electricity GHG credit generated in many scenarios. Without the
electricity credit, it is likely that all scenarios, both hydrogenation and fermentation, would
produce GHG emissions above the emissions value for sucrose, and would increase the net GHG
emissions intensity of the cellulosic ethanol main product. As one of the main benefits of
producing cellulosic ethanol is its superior environmental performance compared to other
biofuels or petroleum fuels; removing the anaerobic digester would greatly increase the GHG
intensity of xylitol production, such that cellulosic ethanol with xylitol production could become
less favorable scenario from an environmental standpoint. Despite the negative impact on the
financial performance of the xylitol pathway, the anaerobic digester is an essential component of
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its environmental performance, and its removal should only be contemplated with a full
assessment of all risks and benefits.
4.2.3 Sensitivity Analysis
Two pathways, the hydrogenation BC and fermentation 10% LT TVR scenarios are chosen for
further analysis through a study of the sensitivity of IRR, NPV, and ROI values to changes in
several different economic parameters. Analysis is carried out for variations in xylitol product
price, debt-to-equity ratio, loan rate, and capital cost. Results are shown for all cases in Appendix
D. Results indicate that xylitol product price has a significant impact on the IRR, NPV, and ROI
values for both scenarios. To highlight the impacts on IRR, Figure 4-13 shows changes in IRR
against changes in xylitol price.
Figure 4-13: Impact of xylitol price on IRR
It can be seen that changes in IRR are relatively stable and linear for both hydrogenation cases
(Hyd-Best and Hyd-Worst) and both fermentation cases (Fmt-Best and Fmt-Worst). Similar to
previous results, the range of IRR values for the fermentation case fits completely within the
range of values for the hydrogenation case. From Figure 4-13, it can be seen that changes in the
xylitol product price impact the IRR significantly, as a -33% change in product price can reduce
the IRR by as much as 20%, absolute basis, while a 22% increase can increase the IRR by 7-
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14%, absolute. By contrast, the Debt-to-Equity ratio and loan rate do not significantly alter the
financial indicators, indicating that these assumptions do not significantly impact process
financial performance. An increase in xylitol price raises the IRR values for the worst case
scenarios, indicating that the risk of losing money is reduced for both the hydrogenation and
fermentation case. The opposite is true for a decrease in xylitol price, indicating that all scenarios
are sensitive to variations in the market price for xylitol.
Collectively, the sensitivity analyses also demonstrate that process performance is a far greater
driver of financial performance than most of the parameters considered here. For example,
changing the capital cost by 25% changes the IRR by 5 – 10%, depending upon the scenario,
whereas moving from a low performance “worst case” to a high performance “best case” can
impact the IRR by a much greater amount, often 30 to 40% on an absolute basis.
Significant impacts on financial performance are also seen for changes in CAPEX, as highlighted
in Figure 4-14. As the CAPEX values utilized for all scenarios are conservative estimates, this
indicates that the true financial performance may be significantly different from what is
presented. A more detailed investigation may refine the CAPEX values, reducing uncertainty in
the results.
Figure 4-14: Impacts of changes in CAPEX on IRR
Overall, the sensitivity analysis reveals that financial performance of a xylitol plant is sensitive
to changes in xylitol price and CAPEX, while other factors involving project financing such as
the debt-to-equity ratio and loan interest rate are not as vital. Despite these sensitivity factors,
process performance will still likely be the deciding factor to determine which xylitol pathway,
0%
25%
50%
75%
-30% -20% -10% 0% 10% 20% 30%
%∆
IRR
%∆CAPEX
Hyd-Worst
Hyd-Best
Fmt-Worst
Fmt-Best
Breakeven
100
hydrogenation or fermentation, has the superior economic performance. This can make it
challenging to objectively state that one pathway performs better than the other from an
economic perspective. One major consideration, however, is that while the hydrogenation
pathway is well established and can likely be expected to perform closer to the best case
performance values, the fermentation pathway has not been developed above the laboratory
scale. This lack of development for the fermentation pathway indicates that there may be
additional costs required for the fermentation pathway that cannot be determined without further
study. Despite having improved environmental performance, the fermentation pathway in its
current state does not offer a large incentive to move away from the conventional hydrogenation
pathway based on economic factors. Results have shown that this can be mitigated by improving
the ability of a fermenting organism to tolerate inhibitors, such as in the HT fermentation
scenario, which does offer significant improvements in economic (and environmental)
performance.
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Conclusions, Limitations, and Future Work 5
5.1 Summary
This thesis investigated the environmental and economic impacts of producing xylitol by either
chemical hydrogenation or biological fermentation in the context of a cellulosic biorefinery. This
was achieved through the construction detailed process models investigating 3 hydrogenation
scenarios and 2 fermentation scenarios that were further, differentiated by process design and
operating parameters. Models were further modified to include different evaporation
technologies and to include variations in process performance for key process stages. A summary
of the process models created is displayed below.
Hydrogenation:
Base Case (BC), Low Yield Hydrogenation (LYH), and 2 Crystallizers in series (2CR)
Base case evaporator technology scenarios:
Multiple-effect evaporation (MEE), 2-stage MEE with thermal vapour recompression (TVR),
and 2-stage MEE with mechanical vapour recompression (MVR)
Fermentation:
Low Inhibitor Tolerance (LT) and High Inhibitor Tolerance (HT)
Fermentation evaporator technology scenarios: 3 to 5-stage multiple-effect evaporation (MEE), 3
to 5-stage MEE with thermal vapour recompression (TVR)
Hydrogenation models utilized a 10% DS hemicellulose extract, while the fermentation models
utilized either a 5% DS or 10% DS hemicellulose extract. Biomethane produced from process
residues was evaluated as a fuel to produce process steam and electricity for all scenarios.
Electricity was produced as a co-product for several scenarios and was returned to the local
electrical grid to generate a GHG emissions credit based on system expansion methodology and
an additional revenue source.
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The models were constructed using Aspen Plus ® process modelling software to generate mass
and energy balances for each scenario, which were used to determine chemical inputs, outputs,
and utility demands. GREET software was then used to calculate the GHG emissions for each
scenario based on the mass and energy balance results. Process yields ranged between 15-92 kg
xylitol per tonne of hybrid poplar feedstock entering the biorefinery for the hydrogenation
pathway and 21-80 kg per tonne hybrid poplar for the fermentation pathway. As expected, the
highest yields were achieved for scenarios assuming best case performance in the major process
stages, though the low overall yields obtained for the worst case performance scenarios led to
large variation in the yield results and subsequent LCA and economic results. Small variation is
seen in yield results between the BC and 2CR hydrogenation scenarios, indicating that omitting a
recycle in lieu of several crystallizers in series is an appropriate xylitol recovery strategy. The
LYH scenario has the poorest performance of the hydrogenation scenarios, representing a worst
case as hydrogenation yield is expected to far exceed the 80% conversion assumed in this
scenario. The HT fermentation case achieved the best xylitol yields for the fermentation
pathway. As the HT fermenting yeast was assumed to be completely inhibitor tolerant, extensive
xylose purification was avoided, minimizing yield losses. Despite lacking extensive upstream
purification, the HT fermentation scenario still has a lower overall yield than the BC
hydrogenation scenario for the best case performance scenarios. In a fermentation pathway, the
use of a biological organism requires the internal utilization of an energy source (xylose) to meet
the metabolic requirements of the organism, leading to unavoidable yield losses as a fraction of
the xylose is transformed into biomass instead xylitol. This indicates that despite optimal process
performance, the metabolic requirements of an organism lead to poorer xylitol conversion than a
chemical hydrogenation, which can achieve xylose conversions of near 100% as the metal
catalyst does not consume xylose to sustain itself.
Energy balance results are strongly impacted by excess electricity generated from biomethane,
leading to negative energy balance results for the hydrogenation BC and 2CR scenarios. The
LYH scenario utilized a more intensive xylitol purification strategy; as a result more electricity is
utilized internally, leading to less electricity export and a net positive energy balance. Similar to
the hydrogenation scenarios, the fermentation scenarios generally produced net negative energy
balances due to the significant electricity credit. Hydrogen production is avoided in the
fermentation scenario, eliminating the requirement for natural gas. Electricity generation is
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determined to be an inverse function of process yield, as lower yields contribute to the generation
of greater volumes of process residues, leading to larger volumes of biomethane fed to the boiler
on a kilogram xylitol basis. This is observed in the difference in electricity generation between
the best and worst performance cases for all scenarios.
When GHG results are compared for the hydrogenation scenarios, it is seen that the ability of all
cases to produce xylitol with emissions below the sucrose displacement credit for a biorefinery
located in Ontario is strongly impacted by process performance. This indicates that the xylitol
hydrogenation pathway would increase the emissions associated with cellulosic ethanol for poor
performing cases, leading to decreased environmental performance, and would likely decrease
the overall emissions for optimal performing cases. When the location of the biorefinery was
changed to an area that has a more GHG intensive electricity grid mixture, net GHG emissions
were reduced due to an increased electricity credit value, showing the importance of location
when handling an electricity credit. The GHG intensity of the hydrogenation pathway is driven
by chemical requirements, as enzymes, sodium hydroxide, and hydrogen gas produced via SMR
all contribute significantly to the overall emissions. This indicates that the environmental
performance of the xylitol pathway is determined by two main factors: chemical requirements
and the generation of an electricity credit from process residues. This trend is also seen in the
fermentation results. The replacement of hydrogen gas with the less GHG intensive nutrients
(DAP and CSL) reduces the chemical emissions in the fermentation pathway such that overall
emissions fall within the sucrose displacement range for all scenarios considered. The electricity
co-product credit has a significant impact on the net GHG emissions of the fermentation
pathways, specifically the worst performing cases as the greater process residues allow greater
electricity production. This leads to the result in certain cases, such as the 10% EC LT TVR
scenario, where the worst performing case has a lower net GHG intensity than the best
performing case, despite a 50% reduction in xylitol yield. These results indicate that,
paradoxically, there is a trade-off to be made between process performance and environmental
performance due to the relationship between process residues and the magnitude of the
electricity credit.
Analysis of different evaporation technologies in the hydrogenation BC scenario indicated that
the use of TVR reduced GHG emissions significantly compared to MEE systems that lacked
104
vapour recompression, and lead to greater GHG reductions than an MVR system. As a result,
TVR systems were utilized in the fermentation scenario, leading to emissions reductions of 75%
to 130% in the 10% EC LT TVR scenario and 57% to 75% in the 10% EC HT TVR scenario
compared to their equivalent MEE-only scenarios.
Financial analysis was performed on selected hydrogenation (BC, LYH, and 2CR) and
fermentation (5% EC LT TVR, 10% EC LT TVR, and 10% EC HT TVR) scenarios. Capital cost
values ranged greatly between the best and worst performance cases for all hydrogenation
scenarios. This is likely due to the wide variation in yield between the best and worst
performance cases, as the best case yield varies between 400-500% of the worst case yield. The
poor yields in the worst case scenarios lead to elevated process volumes that are compounded in
the upstream sections of the process, leading to greater equipment sizes. Due to these wide
ranges, there is significant overlap in the CAPEX ranges across the hydrogenation (BC: $200
MM - $460 MM) and fermentation scenarios (10% EC LT TVR: $240 MM - $360 MM). These
ranges persist in results for financial indicators such as the IRR (BC: 20%-56%, 10% EC LT
TVR: 32%-48%) and TPC (BC: $2.30-$5.18, 10% EC LT TVR: $2.62-$4.02). The significant
overlap prevents an objective evaluation of whether the hydrogenation BC scenario performs
better than the 10% EC LT TVR or 10% EC HT TVR scenarios as there is no clear winner.
Despite the variability, it does appear that in many cases that both hydrogenation and
fermentation can add value to the biorefinery, and provide an offset to the high cellulosic ethanol
cost. These results indicate that process performance will be the driver in relative economic
performance. As the hydrogenation process has been commercialized, it may be reasonable to
expect the risk of poor performance to be reduced, as xylitol hydrogenation facilities in operation
would not have likely been constructed and operated if they were not financially feasible, though
it should be noted that these facilities utilize a different feedstock and pretreatment method,
which impacts economic performance. By contrast, the lack of large-scale development of the
fermentation pathways indicates that significant risk may exist in assuming the performances
calculated will hold true at a commercial scale. The 10% HT TVR fermentation pathway
outperforms the hydrogenation scenarios based on an environmental level and has the best
financial performance of all scenarios, though there is overlap with the hydrogenation scenarios
for all financial parameters evaluated. This indicates that there is potential for a fermentation
scenario to outperform the conventional hydrogenation of xylitol on both an environmental and
105
economic basis. However, the HT scenario deliberately assumes that the fermenting organism,
whether it is C. guilliermondii or a different microorganism, is completely tolerant to inhibitors.
This inhibitor tolerance level is not reflected in current literature for xylitol fermenting
organisms and represents a future scenario that may not be achieved without significant research.
A sensitivity analysis of different financial parameters was performed for the hydrogenation BC
and fermentation 10% EC LT TVR scenarios. Results indicated that CAPEX and xylitol product
price have significant impacts on plant performance, while other parameters such as loan interest
rate and debt-to-equity ratio are less important.
5.2 Implications
Overall, results indicate trade-offs exist between environmental performance and process
performance, as the electricity co-product credit generated from excess electricity production is
closely tied to the production of process residues, which are increased for less efficient
processes. It can be concluded that for a biorefinery located in Ontario, the xylitol hydrogenation
pathway modelled in this work may improve the environmental performance of cellulosic
ethanol, based on process performance. A biorefinery located in the US Midwest may see
improved environmental results for hydrogenation, as this area has a more GHG intensive
electricity mix and a greater resultant electricity co-product credit. The fermentations scenarios
produce overall fewer GHG emissions than the hydrogenation scenarios, with the best results
showing net negative GHG emissions for the 10% EC LT TVR worst case. The GHG emissions
are similar for the high and low tolerance scenarios, highlighting the relationship between
process performance and environmental performance. While the hydrogenation scenarios have a
greater GHG intensity than the fermentation scenarios, high performance processes can perform
better on an economic level, and may provide a greater price offset for cellulosic ethanol, though
this is tied closely to process performance. The broad ranges found the results between the best
and worst performance cases for the hydrogenation scenario are a significant limitation of this
work, as they prevent the ability to draw definite conclusions about the performance of the
hydrogenation pathways over the fermentation pathways. This is especially present in the
economic analysis, where strong overlap exists for the capital costs and financial indicators such
as the IRR.
106
It is clear from the results, that process performance is one of the main drivers of the success or
failure of xylitol production. Future improvements in enzyme production, enzyme activity, and
chromatographic separation could have significant impacts on the performance of the different
xylitol pathways. Improving conversions within the process can reduce chemical demands,
leading to reduced GHG emissions; however these improvements may fail to have as large an
impact as plant location and electricity mix.
In general, there does not appear to be a significant enough improvement in environmental and
economic results between the conventional hydrogenation process and the current xylitol
fermentation process that uses inhibitor intolerant organisms to justify the switch from a proven
conventional pathway and one that has not been tested above the laboratory scale. A xylitol
fermentation scenario with high inhibitor tolerance has the potential to improve the main
cellulosic ethanol product both environmentally and economically; however, as this theoretical
pathway has yet to be developed, the results can only offer an incentive to develop inhibitor
tolerant organisms for the production of value-added bioproducts from lignocellulosic
feedstocks.
These results may be extrapolated to other theoretical bioprocesses that could potentially produce
high-value products that would compete with conventional petroleum pathways. In general, the
bio-based pathways are new, unproven technologies and must display significant incentives over
the established technologies to justify the risk that is associated with new production methods.
Results from this work indicate that the ability of an organism to tolerate inhibitors can be the
difference between a process that does not offer significant improvements over a conventional
process, and a process that has the potential to outcompete it. The development of organisms that
are capable of withstanding the mixture of inhibitors found in lignocellulosic based feed streams
should not be ignored in future research.
5.3 Limitations and Future Work
The results presented in this work represent theoretical biorefinery pathways that have not been
developed at the large scale. The theoretical nature of this work may lead to inaccurate results as
necessary performance factors and process strategies may have been inadvertently omitted from
the process models. Performance-based scenarios were utilized to overcome confidentiality
107
agreements. While this provided information on how the xylitol pathways would perform for
different process performance values, it also obscured the results, specifically for the
hydrogenation economic analysis, such that drawing definitive conclusions about individual
pathway performance became infeasible. Process stages such as autohydrolysis and enzymatic
hydrolysis are still under development, and it is likely that their performance will improve over
time as process conditions such as hydraulic loadings, temperature, residence time, and enzyme
activity are optimized. As a result, it is likely that results presented in this work tend to be
conservative towards the worst case performance results, and may not accurately represent the
true state of these technologies.
Environmental impact categories were restricted to GHG emissions and pathway energy demand.
Other environmental factors such as direct or indirect land use changes, ozone depletion, human
or eco-toxicity, and others were not considered and could have on impact on how the
environmental performance of the xylitol pathways is assessed. The work also only considered a
limited selection of economic indicators, and economic results are only expected to present a
rough indicator of the true financial performance of the pathways studied. Additionally, this
work considered only one co-product option from the solubilized lignin and other process
residues, anaerobic digestion to product an electricity co-product. Other product options from
lignin, such as lignin pellets or plastics were not considered. No feedstocks other than hybrid
poplar were investigated; the inclusion of more diverse sources of biomass could influence
process yields and results. The utilities and residue handling processes associated with the xylitol
pathways were also separated from the cellulosic ethanol process, and the impacts of co-location
were not fully explored in this work, which could have an impact on process results, energy
consumption, and economic performance. A technological aspect overlooked in this work was
the emerging use of membranes to concentrate process streams. Processes such as reverse
osmosis could have a considerable impact on process energy intensity and as a result, its
environmental and economic performance. Membranes are an interesting concept for both
concentration and xylitol separation, and should be further investigated to develop a more in-
depth understanding of the role of concentration technology on process performance. Future
work could also include an assessment of other pretreatment technologies, such as dilute-acid
hydrolysis, to gain more understanding of the role of pretreatment on xylitol process
performance.
108
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Appendix A: Stream Tables and Supporting Process Model Information
This appendix presents a summary of the stream tables generated by the process models.
Modelling results are shown for the best performance scenarios for the hydrogenation and
fermentation scenarios. Selected stream tables are displayed for the hydrogenation base case
scenario, fermentation 10% extract concentration low tolerance TVR scenario, and fermentation
10% extract concentration high tolerance TVR scenario.
124
Figure A-1: Hydrogenation Base Case (BC) block flow diagram with stream numbers
Table A-1: Hydrogenation Base Case (BC) stream table
Stream BC-01 BC-02 BC-03
BC-
04 BC-05 BC-06 BC-07 BC-08 BC-09
BC-
10 BC-11 BC-12 BC-13 BC-14 BC-15
BC-
16 BC-17
BC-
18
Temperature C 25.0 60.0 130.0 130.0 100.0 129.1 51.4 4.0 81.8 150.0 70.2 62.0 20.0 20.0 20.0 20.0 20.0 88.0
Pressure bar 1 1 70.35 70 1.65 47 70 47 1.3 4.5 2 1 1.3 1.3 1.3 1.3 1.3 1
Vapor Frac 0 0 0 1 0 1 1 0 0 1 0 0 0 0 0 0 0 0
Solid Frac 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
Mole Flow
kmol/hr 26.44 79.63 106.07 42.00 103.45 27.35 25.99 1.36 122.79 38.00 48.63 74.16 48.63 28.90 19.34 0.39 16.00 12.90
Mass Flow kg/hr
2614.6
3
1434.5
1
4049.1
4 84.67 4034.39 77.05 52.47 24.58 5590.62
684.5
0
4254.5
9 1336.03 4254.59
2666.6
0
1556.2
3 31.76
2434.1
9
232.4
1
Volume Flow
cum/hr 2.05 1.46 3.70 20.80 2.85 19.85 10.42 0.02 3.76
290.2
4 2.36 1.36 2.28 1.36 0.91 0.02 1.13 0.24
Mass Flow kg/hr
ARABINOSE 12.14 0.00 12.14 0.00 0.18
2.43E-
12 0.00 0.00 1.85 0.00 1.85
1.54E-
11 1.85 0.15 1.67 0.03 0.15 0.00
XYLITOL 0.00 0.00 0.00 0.00 2422.75
9.98E-
05
5.04E-
18
9.98E-
05 3431.66 0.00
3431.6
6 0.00 3431.66
2402.1
6
1008.9
1 20.59
2402.1
6 0.00
WATER 184.80 1434.5 1619.3 0.00 1572.24 24.67 0.09 24.58 1758.58 684.5 422.56 1336.03 422.56 232.41 186.35 3.80 0.00 232.4
125
1 1 0 1
HYDROGEN 0.00 0.00 0.00 84.67
9.76E-
10 52.38 52.38
1.50E-
07
9.76E-
10 0.00 0.00
9.76E-
10 0.00 0.00 0.00 0.00 0.00 0.00
XYLOSE
2415.0
0 0.00
2415.0
0 0.00 24.39
3.26E-
10
2.07E-
28
3.26E-
10 247.82 0.00 247.81
2.06E-
09
2.48E+0
2 19.82 223.42 4.56 19.82 0.00
GLUCOSE 2.69 0.00 2.69 0.00 0.04032
2.01E-
10
8.22E-
26
2.01E-
10 0.41 0.00 0.41
1.47E-
09
4.10E-
01 0.03 0.37 0.01 0.03 0.00
ACETIC ACID 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
LIGNIN 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
SORBITOL 0.00 0.00 0.00 0.00 2.68
2.91E-
11
1.11E-
31
2.91E-
11 27.20 0.00 27.20
4.51E-
11
2.72E+0
1 2.18 24.52 0.50 2.18 0.00
ARABITOL 0.00 0.00 0.00 0.00 12.12
4.99E-
07
2.52E-
20
4.99E-
07 123.10 0.00 123.10 0.00
1.23E+0
2 9.85 110.99 2.27 9.85 0.00
126
Figure A-2: Fermentation 10% EC Low Tolerance (LT) best case block flow diagram with stream numbers
127
Table A-2: Fermentation 10% EC Low Tolerance (LT) best case stream table LT-01 to LT-17
LT-01 LT-02 LT-03 LT-04 LT-05 LT-06 LT-07 LT-08 LT-09 LT-10 LT-11 LT-12 LT-13 LT-14 LT-15 LT-16 LT-17
PH 3.03 15.62 5.01 5.01 6.63 5.33 5.53 3.46 3.16 6.51 10.35 3.11 3.30 3.50
Temperature C 50.01 56.30 50.00 50.13 50.13 85.00 50.13 65.00 150.00 76.25 60.02 60.00 60.02 65.00 150.00 74.22 60.01
Pressure bar 2.00 1.00 1.00 10.00 10.00 9.30 10.00 0.24 4.50 0.41 1.00 1.00 1.00 0.24 4.50 0.39 1.00
Mass VFrac 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00 1.00 0.00 0.00 0.00 0.00 1.00 0.00 0.00
Mass Flow kg/hr
132079.
75 644.15
132723.
90
131437.
51
1286.3
9
131375.
10 62.41
47157.
21
9087.0
0
93305.8
5
49385.
20
130455.
00
128227.
01
22533.
49
2650.0
0
29501.
71
40833.
25
Volume Flow
cum/hr 131.48 0.48 133.15 131.82 1.29 133.97 0.23 46.65
3852.8
7
366266.
54 48.95 132.69 130.19 21.72
1123.5
9 30.18 40.45
Density kg/cum 1004.54
1351.2
9 996.82 997.13 996.29 980.65
275.2
1
1010.8
6 2.36 969.25
1008.9
8 983.19 984.94
1037.3
8 2.36 975.02
1009.5
4
Mass Flow kg/hr
GLUCOSE 0.00 0.00 901.60 901.60 0.00 901.60 0.00 901.60 0.00 0.00 631.12 0.00 270.48 631.12 0.00 0.00 441.78
CELLULOSE 901.60 0.00 90.16 88.36 1.80 88.36 0.00 88.36 0.00 0.00 1.77 0.00 86.59 1.77 0.00 0.00 0.04
XYLOSE 257.60 0.00 5526.67 5526.67 0.00 5526.67 0.00
5526.6
7 0.00 0.00
4974.0
0 0.00 552.67
4974.0
0 0.00 0.00
4476.6
0
XYLAN 5152.00 0.00 515.20 504.90 10.30 504.90 0.00 504.90 0.00 0.00 10.10 0.00 494.80 10.10 0.00 0.00 0.20
XYLITOL 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
LIGNIN 4379.20 0.00 4379.20 4291.62 87.58 4291.62 0.00
4291.6
2 0.00 0.00 85.83 0.00 4205.78 85.83 0.00 0.00 1.72
ENZYME 0.00 36.83 36.83 36.83 0.00 36.83 0.00 36.83 0.00 0.00 0.00 0.00 36.83 0.00 0.00 0.00 0.00
HMF 29.44 0.00 29.44 29.44 0.00 29.44 0.00 29.43 0.00 0.01 26.49 0.00 2.94 26.48 0.00 0.01 23.83
ARABINOSE 0.00 0.00 526.91 526.91 0.00 526.91 0.00 526.91 0.00 0.00 105.38 0.00 421.53 105.38 0.00 0.00 21.08
GALACTOSE 0.00 0.00 515.20 515.20 0.00 515.20 0.00 515.20 0.00 0.00 412.16 0.00 103.04 412.16 0.00 0.00 329.73
MANNOSE 0.00 0.00 515.20 515.20 0.00 515.20 0.00 515.20 0.00 0.00 412.16 0.00 103.04 412.16 0.00 0.00 329.73
ARABINAN 515.20 0.00 51.52 50.49 1.03 50.49 0.00 50.49 0.00 0.00 1.01 0.00 49.48 1.01 0.00 0.00 0.02
MANNAN 515.20 0.00 51.52 50.49 1.03 50.49 0.00 50.49 0.00 0.00 1.01 0.00 49.48 1.01 0.00 0.00 0.02
GALACTAN 515.20 0.00 51.52 50.49 1.03 50.49 0.00 50.49 0.00 0.00 1.01 0.00 49.48 1.01 0.00 0.00 0.02
H2O
118871.
82 377.32
118360.
45
117176.
84
1183.6
0
117176.
84 0.00
33268.
50
9087.0
0
92996.3
1
42568.
11
130455.
00
121155.
39
15787.
45
2650.0
0
29430.
66
35181.
57
FURFURAL 147.20 0.00 147.20 147.20 0.00 147.20 0.00 1.59 0.00 145.61 1.43 0.00 0.16 0.05 0.00 1.38 0.05
128
CO2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
O2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
LACID 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
AACID 644.00 0.00 644.00 644.00 0.00 644.00 0.00 480.07 0.00 163.93 153.62 0.00 326.45 83.96 0.00 69.66 26.87
GLYCEROL 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
YEAST 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
DAP 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
NAOH 0.00 230.00 230.00 230.00 0.00 230.00 0.00 230.00 0.00 0.00 0.00 0.00 230.00 0.00 0.00 0.00 0.00
CA 39.47 0.00 39.47 39.47 0.00 0.00 39.47 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
K 47.46 0.00 47.46 47.46 0.00 47.46 0.00 47.46 0.00 0.00 0.00 0.00 47.46 0.00 0.00 0.00 0.00
S 39.73 0.00 39.73 39.73 0.00 39.73 0.00 39.73 0.00 0.00 0.00 0.00 39.73 0.00 0.00 0.00 0.00
MG 11.67 0.00 11.67 11.67 0.00 0.00 11.67 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
FE 8.24 0.00 8.24 8.24 0.00 0.00 8.24 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
NA 1.69 0.00 1.69 1.69 0.00 1.69 0.00 1.69 0.00 0.00 0.00 0.00 1.69 0.00 0.00 0.00 0.00
AL 3.02 0.00 3.02 3.02 0.00 0.00 3.02 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
PROTEIN 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
ETHANOL 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
129
Table A-3: Fermentation 10% EC Low Tolerance (LT) best case stream table LT-18 to LT-34
LT-18 LT-19 LT-20 LT-21 LT-22 LT-23 LT-24 LT-25 LT-26 LT-27 LT-28 LT-29 LT-30 LT-31 LT-32 LT-33 LT-34
PH 6.51 3.38 3.39 3.39 6.97 6.97 3.37 3.37 3.39 3.27 3.43 3.63 3.98 6.51 3.70 4.08
Temperature C 60.00 60.01 30.00 30.00 30.00 30.00 30.00 30.00 30.12 30.12 65.00 150.00 73.45 60.01 60.00 60.01 83.10
Pressure bar 1.00 1.00 1.00 1.00 1.00 1.00 1.20 1.20 10.00 10.00 0.24 4.50 0.40 1.00 1.00 1.00 0.80
Mass VFrac 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.00 1.00 0.00 0.00 0.00 0.00 0.00
Mass Flow kg/hr
63095.0
0
44795.2
4
4083.3
2
36749.9
2 14.47 130.21
4033.8
1
40338.1
2
39153.8
6
1184.2
6
15024.1
0
2425.0
0
26554.7
6
18722.8
5
42056.0
0
38357.2
5
19626.5
9
Volume Flow
cum/hr 64.17 45.39 3.99 35.93 0.01 0.12 3.87 38.66 37.59 3.41 13.52
1028.1
9 27.21 17.51 42.78 38.75 18.34
Density kg/cum 983.19 986.87
1022.7
3 1022.73
1121.3
8
1121.3
8
1043.3
2 1043.32 1041.49 347.74 1111.58 2.36 972.57 1069.41 983.19 989.78 1069.89
Mass Flow kg/hr
GLUCOSE 0.00 189.34 44.18 397.60 0.00 0.00 44.18 441.78 432.95 8.84 432.95 0.00 0.00 47.62 0.00 385.32 106.30
CELLULOSE 0.00 1.73 0.00 0.03 0.00 0.00 0.00 0.04 0.03 0.00 0.03 0.00 0.00 0.00 0.00 0.03 0.01
XYLOSE 0.00 497.40 447.66 4028.94 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
XYLAN 0.00 9.90 0.02 0.18 0.00 0.00 0.02 0.20 0.20 0.00 0.20 0.00 0.00 0.02 0.00 0.18 0.05
XYLITOL 0.00 0.00 0.00 0.00 0.00 0.00 334.07 3340.73 3273.92 66.81 3273.92 0.00 0.00 2815.57 0.00 458.35 3433.62
LIGNIN 0.00 84.12 0.17 1.54 0.00 0.00 0.17 1.72 1.68 0.03 1.68 0.00 0.00 0.19 0.00 1.50 0.45
ENZYME 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
HMF 0.00 2.65 2.38 21.45 0.00 0.00 2.38 23.83 23.36 0.48 23.35 0.00 0.01 2.57 0.00 20.78 5.72
ARABINOSE 0.00 84.31 2.11 18.97 0.00 0.00 2.11 21.08 20.65 0.42 20.65 0.00 0.00 2.27 0.00 18.38 5.07
GALACTOSE 0.00 82.43 32.97 296.75 0.00 0.00 32.97 329.73 323.13 6.59 323.13 0.00 0.00 35.54 0.00 287.59 79.34
MANNOSE 0.00 82.43 32.97 296.75 0.00 0.00 32.97 329.73 323.13 6.59 323.13 0.00 0.00 35.54 0.00 287.59 79.34
ARABINAN 0.00 0.99 0.00 0.02 0.00 0.00 0.00 0.02 0.02 0.00 0.02 0.00 0.00 0.00 0.00 0.02 0.01
MANNAN 0.00 0.99 0.00 0.02 0.00 0.00 0.00 0.02 0.02 0.00 0.02 0.00 0.00 0.00 0.00 0.02 0.01
GALACTAN 0.00 0.99 0.00 0.02 0.00 0.00 0.00 0.02 0.02 0.00 0.02 0.00 0.00 0.00 0.00 0.02 0.01
H2O
63095.0
0
43700.8
7
3518.1
6
31663.4
1 6.73 60.61
3513.3
7
35133.7
3
34431.0
5 702.67
10515.5
9
2425.0
0
26340.4
6
15771.4
8
42056.0
0
36800.1
1
15889.2
9
FURFURAL 0.00 0.01 0.00 0.04 0.00 0.00 0.00 0.05 0.04 0.00 0.00 0.00 0.04 0.00 0.00 0.00 0.00
CO2 0.00 0.00 0.00 0.00 0.00 0.00 5.25 52.49 0.00 52.49 0.00 0.00 0.00 0.00 0.00 0.00 0.00
O2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00
130
LACID 0.00 0.00 0.00 0.00 3.37 30.30 5.61 56.05 54.93 1.12 54.80 0.00 0.14 6.03 0.00 48.77 14.61
AACID 0.00 57.09 2.69 24.18 0.00 0.00 2.69 26.86 26.33 0.54 12.70 0.00 13.62 1.40 0.00 11.31 1.46
GLYCEROL 0.00 0.00 0.00 0.00 0.00 0.00 2.29 22.88 22.43 0.46 22.42 0.00 0.00 2.47 0.00 19.96 6.16
YEAST 0.00 0.00 0.00 0.00 0.00 0.00 33.23 332.25 6.65 325.61 6.65 0.00 0.00 0.73 0.00 5.91 1.83
DAP 0.00 0.00 0.00 0.00 1.00 9.00 0.47 4.68 4.59 0.09 4.59 0.00 0.00 0.50 0.00 4.09 1.26
NAOH 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
CA 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
K 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
S 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
MG 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
FE 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
NA 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
AL 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
PROTEIN 0.00 0.00 0.00 0.00 3.37 30.30 1.47 14.75 7.37 7.37 7.37 0.00 0.00 0.81 0.00 6.56 1.97
ETHANOL 0.00 0.00 0.00 0.00 0.00 20.55 205.47 201.36 4.11 0.87 0.00 200.49 0.10 0.00 0.78 0.10
131
Table A-3: Fermentation 10% EC Low Tolerance (LT) best case stream table LT-35 to LT-43
LT-35 LT-36 LT-37 LT-38 LT-39 LT-40 LT-41 LT-42 LT-43
PH 4.10 4.06 3.92 7.43 3.69 3.69
Temperature C 70.00 150.00 73.95 20.00 20.00 20.00 20.00 20.00 105.00
Pressure bar 0.16 4.50 1.00 0.16 0.16 0.16 0.16 0.16 1.21
Mass VFrac 0.00 1.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00
Mass Flow kg/hr 4171.86 2117.00 17571.71 4171.86 2665.63 903.74 602.49 2425.64 239.99
Volume Flow
cum/hr 2.38 897.60 17.97 2.30 1.37 0.57 0.38 1.12 344.61
Density kg/cum 1750.33 2.36 974.83 1809.93 1952.73 1598.98 1598.98 2156.75 0.70
Mass Flow kg/hr
GLUCOSE 106.30 0.00 0.00 106.30 8.50 58.68 39.12 8.50 0.00
CELLULOSE 0.01 0.00 0.00 0.01 0.00 0.01 0.00 0.00 0.00
XYLOSE 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
XYLAN 0.05 0.00 0.00 0.05 0.00 0.03 0.02 0.00 0.00
XYLITOL 3433.62 0.00 0.00 3433.62 2403.53 618.05 412.03 2403.53 0.00
LIGNIN 0.45 0.00 0.00 0.45 0.01 0.26 0.18 0.01 0.00
ENZYME 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
HMF 5.70 0.00 0.01 5.70 0.46 3.15 2.10 0.46 0.00
ARABINOSE 5.07 0.00 0.00 5.07 0.41 2.80 1.87 0.41 0.00
GALACTOSE 79.34 0.00 0.00 79.34 6.35 43.80 29.20 6.35 0.00
MANNOSE 79.34 0.00 0.00 79.34 6.35 43.80 29.20 6.35 0.00
ARABINAN 0.01 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00
MANNAN 0.01 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00
GALACTAN 0.01 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00
H2O 436.34 2117.00 17569.93 436.34 239.99 117.81 78.54 0.00 239.99
FURFURAL 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
CO2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
O2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
132
LACID 14.30 0.00 0.31 14.30 0.00 8.58 5.72 0.00 0.00
AACID 0.10 0.00 1.36 0.10 0.00 0.06 0.04 0.00 0.00
GLYCEROL 6.16 0.00 0.00 6.16 0.00 3.69 2.46 0.00 0.00
YEAST 1.83 0.00 0.00 1.83 0.00 1.10 0.73 0.00 0.00
DAP 1.26 0.00 0.00 1.26 0.00 0.76 0.50 0.00 0.00
NAOH 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
CA 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
K 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
S 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
MG 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
FE 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
NA 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
AL 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
PROTEIN 1.97 0.00 0.00 1.97 0.04 1.16 0.77 0.04 0.00
ETHANOL 0.00 0.00 0.10 0.00 0.00 0.00 0.00 0.00 0.00
133
Figure A-3: Fermentation 10% EC High Tolerance (HT) best case block flow diagram with stream numbers
134
Table A-4: Fermentation 10% EC High Tolerance (HT) best case stream table HT-01 to HT-16
Stream HT-01 HT-02 HT-03 HT-04 HT-05 HT-06 HT-07 HT-08 HT-09 HT-10 HT-11 HT-12 HT-13 HT-14 HT-15 HT-16
PH 3.03 15.62 5.01 5.01 6.63 5.01 4.88 4.88 6.97 6.97 4.85 4.85 2.96 9.13 2.96
Temperature C 50.00 56.30 50.00 50.13 50.13 50.13 50.13 30.00 30.00 30.00 30.00 30.00 30.00 30.11 30.11 65.00
Pressure bar 1.00 1.00 1.00 10.00 10.00 10.00 10.00 10.00 10.00 1.00 1.00 1.20 1.20 10.00 10.00 0.24
Mass VFrac 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
Mass Flow kg/hr 110258 537.77 110796 109722 1074 109670 52.10 10967 98703 16.78 118.88 10927 109241 104036 5206 25244
Volume Flow cum/hr 109.76 0.40 111.15 110.04 1.08 109.70 0.19 10.89 97.98 0.01 0.11 10.76 107.62 102.69 4.55 23.94
Density kg/cum 1004.51 1351 996.82 997.13 996.29 999.70 275.21 1007.43 1007.43 1123.69 1122.13 1015.09 1015.06 1013.13 1143.07 1054.44
Mass Flow kg/hr
GLUCOSE 0.00 0.00 752.64 752.64 0.00 752.64 0.00 75.26 677.37 0.00 0.00 75.26 752.64 737.58 15.05 737.58
CELLULOSE 752.64 0.00 75.26 73.76 1.51 73.76 0.00 7.38 66.38 0.00 0.00 7.38 73.76 1.48 72.28 1.48
XYLOSE 215.04 0.00 4613.57 4613.57 0.00 4613.57 0.00 461.36 4152.21 0.00 0.00 0.00 0.00 0.00 0.00 0.00
XYLAN 4300.80 0.00 430.08 421.48 8.60 421.48 0.00 42.15 379.33 0.00 0.00 42.15 421.48 8.43 413.05 8.43
XYLITOL 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 344.29 3442.94 3374.08 68.86 3374.08
LIGNIN 3655.68 0.00 3655.68 3582.57 73.11 3582.57 0.00 358.26 3224.31 0.00 0.00 358.26 3582.57 1791.28 1791.28 1791.28
ENZYME 0.00 30.77 30.77 30.77 0.00 30.77 0.00 3.08 27.69 0.00 0.00 3.08 30.77 0.31 30.46 0.31
HMF 24.58 0.00 24.58 24.58 0.00 24.58 0.00 2.46 22.12 0.00 0.00 2.46 24.58 24.08 0.49 24.07
ARABINOSE 0.00 0.00 439.85 439.85 0.00 439.85 0.00 43.99 395.87 0.00 0.00 43.99 439.85 431.06 8.80 431.06
GALACTOSE 0.00 0.00 430.08 430.08 0.00 430.08 0.00 43.01 387.07 0.00 0.00 43.01 430.08 421.48 8.60 421.48
MANNOSE 0.00 0.00 430.08 430.08 0.00 430.08 0.00 43.01 387.07 0.00 0.00 43.01 430.08 421.48 8.60 421.48
ARABINAN 430.08 0.00 43.01 42.15 0.86 42.15 0.00 4.21 37.93 0.00 0.00 4.21 42.15 0.84 41.30 0.84
MANNAN 430.08 0.00 43.01 42.15 0.86 42.15 0.00 4.21 37.93 0.00 0.00 4.21 42.15 0.84 41.30 0.84
GALACTAN 430.08 0.00 43.01 42.15 0.86 42.15 0.00 4.21 37.93 0.00 0.00 4.21 42.15 0.84 41.30 0.84
H2O 99232.13 315.00 98805.26 97817.21 988.05 97817.21 0.00 9781.72 88035.49 7.98 55.90 9777.97 97763.75 95808.47 1955.27 17689.18
FURFURAL 122.88 0.00 122.88 122.88 0.00 122.88 0.00 12.29 110.59 0.00 0.00 12.28 122.83 120.37 2.46 0.50
CO2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 14.77 147.63 0.00 147.63 0.00
O2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.04 0.00 0.04 0.00
135
LACID 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.00 27.90 6.31 54.97 53.87 1.10 53.68
AACID 537.60 0.00 537.60 537.60 0.00 537.60 0.00 53.76 483.84 0.00 0.00 53.76 537.59 526.83 10.75 182.11
GLYCEROL 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 2.36 23.58 23.11 0.47 23.11
YEAST 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 34.24 342.42 0.00 342.42 0.00
DAP 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.80 7.18 0.25 2.50 2.45 0.05 2.45
NAOH 0.00 192.00 192.00 192.00 0.00 192.00 0.00 19.20 172.80 0.00 0.00 19.20 192.00 0.00 192.00 0.00
CA 32.95 0.00 32.95 32.95 0.00 0.00 32.95 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
K 39.62 0.00 39.62 39.62 0.00 39.62 0.00 3.96 35.66 0.00 0.00 3.96 39.62 38.83 0.79 38.83
S 33.17 0.00 33.17 33.17 0.00 33.17 0.00 3.32 29.85 0.00 0.00 3.32 33.17 32.50 0.66 32.50
MG 9.74 0.00 9.74 9.74 0.00 0.00 9.74 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
FE 6.88 0.00 6.88 6.88 0.00 0.00 6.88 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
NA 1.41 0.00 1.41 1.41 0.00 1.41 0.00 0.14 1.27 0.00 0.00 0.14 1.41 1.38 0.03 1.38
AL 2.52 0.00 2.52 2.52 0.00 0.00 2.52 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
PROTEIN 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 4.00 27.90 2.05 12.40 6.20 6.20 6.20
ETHANOL 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 21.22 212.16 207.92 4.24 0.12
136
Table A-5: Fermentation 10% EC High Tolerance (HT) best case stream table HT-17 to HT-31
Stream HT-17 HT-18 HT-19 HT-20 HT-21 HT-22 HT-23 HT-24 HT-25 HT-26 HT-27 HT-28 HT-29 HT-30 HT-31
PH 3.19 3.91 6.51 3.24 4.01 4.04 3.98 3.86 4.31 3.65 3.65
Temperature C 150.00 74.25 60.01 60.00 60.01 82.53 70.00 150.00 73.84 20.00 20.00 20.00 20.00 20.00 105.00
Pressure bar 4.50 0.40 1.00 1.00 1.00 1.00 0.15 4.50 0.42 1.00 1.00 1.00 1.00 1.00 1.21
Mass VFrac 1.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00
Mass Flow kg/hr 8535.00 87326.90 19241.70 70688.00 76690.13 20519.40 4263.03 1800.00 18056.41 4263.03 2665.91 1277.69 319.42 2431.94 233.97
Volume Flow cum/hr 3618.82 89.39 18.15 71.90 77.65 19.26 2.48 763.20 18.47 2.40 1.37 0.83 0.21 1.13 335.96
Density kg/cum 2.36 974.32 1060.14 983.19 987.61 1065.25 1717.50 2.36 974.85 1773.95 1952.91 1532.30 1532.30 2150.76 0.70
Mass Flow kg/hr
GLUCOSE 0.00 0.00 24.34 0.00 713.24 92.20 92.20 0.00 0.00 92.20 7.38 67.86 16.96 7.38 0.00
CELLULOSE 0.00 0.00 0.02 0.00 1.46 0.08 0.08 0.00 0.00 0.08 0.00 0.06 0.01 0.00 0.00
XYLOSE 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
XYLAN 0.00 0.00 0.09 0.00 8.34 0.43 0.43 0.00 0.00 0.43 0.01 0.34 0.08 0.01 0.00
XYLITOL 0.00 0.00 2611.54 0.00 762.54 3436.24 3436.24 0.00 0.00 3436.24 2405.36 824.70 206.17 2405.36 0.00
LIGNIN 0.00 0.00 19.70 0.00 1771.58 91.22 91.22 0.00 0.00 91.22 1.82 71.52 17.88 1.82 0.00
ENZYME 0.00 0.00 0.00 0.00 0.30 0.06 0.07 0.00 0.00 0.07 0.00 0.05 0.01 0.00 0.00
HMF 0.00 0.01 2.38 0.00 21.69 8.96 8.94 0.00 0.02 8.94 0.72 6.58 1.64 0.72 0.00
ARABINOSE 0.00 0.00 4.74 0.00 426.31 17.96 17.96 0.00 0.00 17.96 1.44 13.22 3.30 1.44 0.00
GALACTOSE 0.00 0.00 23.18 0.00 398.30 87.81 87.81 0.00 0.00 87.81 7.02 64.63 16.16 7.02 0.00
MANNOSE 0.00 0.00 23.18 0.00 398.30 87.81 87.81 0.00 0.00 87.81 7.02 64.63 16.16 7.02 0.00
ARABINAN 0.00 0.00 0.01 0.00 0.83 0.04 0.04 0.00 0.00 0.04 0.00 0.03 0.01 0.00 0.00
MANNAN 0.00 0.00 0.01 0.00 0.83 0.04 0.04 0.00 0.00 0.04 0.00 0.03 0.01 0.00 0.00
GALACTAN 0.00 0.00 0.01 0.00 0.83 0.04 0.04 0.00 0.00 0.04 0.00 0.03 0.01 0.00 0.00
H2O 8535.00 86654.30 16526.53 70688.00 71850.64 16679.68 425.40 1800.00 18054.31 425.40 233.97 153.14 38.29 0.00 233.97
FURFURAL 0.00 119.87 0.05 0.00 0.45 0.05 0.00 0.00 0.05 0.00 0.00 0.00 0.00 0.00 0.00
CO2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
137
O2 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
LACID 0.00 0.19 0.59 0.00 53.09 2.11 2.06 0.00 0.05 2.06 0.16 1.51 0.38 0.16 0.00
AACID 0.00 344.72 2.00 0.00 180.11 2.10 0.13 0.00 1.97 0.13 0.01 0.10 0.02 0.01 0.00
GLYCEROL 0.00 0.00 1.78 0.00 21.33 6.73 6.72 0.00 0.01 6.72 0.54 4.95 1.24 0.54 0.00
YEAST 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
DAP 0.00 0.00 0.01 0.00 2.44 0.02 0.02 0.00 0.00 0.02 0.00 0.02 0.00 0.00 0.00
NAOH 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
CA 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
K 0.00 0.00 0.78 0.00 38.05 2.94 2.94 0.00 0.00 2.94 0.24 2.16 0.54 0.24 0.00
S 0.00 0.00 0.65 0.00 31.85 2.46 2.46 0.00 0.00 2.46 0.20 1.81 0.45 0.20 0.00
MG 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
FE 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
NA 0.00 0.00 0.03 0.00 1.35 0.10 0.10 0.00 0.00 0.10 0.01 0.08 0.02 0.01 0.00
AL 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
PROTEIN 0.00 0.00 0.07 0.00 6.13 0.32 0.32 0.00 0.00 0.32 0.01 0.25 0.06 0.01 0.00
ETHANOL 0.00 207.80 0.01 0.00 0.11 0.01 0.00 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.00
138
Appendix B: Experimental Methodology and Results
Experimental work was performed to collect information on the behaviour of both xylose and
xylitol solutions during crystallization. A summary of the procedures utilized and results
obtained is provided in this appendix. Sample experimental procedures are included for several
different experiments, including xylose crystallization and crystal washing, and xylitol
crystallization. Experiments are primarily performed using purified hemicellulose extract for
xylose crystallizations and primarily synthetic solutions for xylitol crystallization scenarios.
139
Protocol and Results: Xylose Crystallization with Water Wash Step
Xylose can be removed from a solution via a solid-liquid separation process such as
crystallization. Hemicellulose hydrolysate is concentrated at elevated to increase sugar
concentration to create supersaturation conditions. The temperature is then slowly lowered and
the solution is seeded with xylose crystals to promote crystallization. The crystal slurry is then
filtered to remove the liquid fraction and washed 3 times with cold water to remove
contaminants in the solid fraction.
Experimental Procedure:
Crystallization
1) Hydrolysate solution is concentrated in a 4 L jacketed reactor vessel. The temperature is set
to 50 ºC, but was increased to 74 ºC to prevent premature crystal formation before the
crystallization procedure was carried out. Approximately 8-9 L of hydrolysate is
concentrated to a final volume of 1040 mL (before crystallization) and a dry matter content
of ~75 %. The concentration step may take several days to complete.
2) The concentrated crystal slurry solution is seeded with xylose crystals to promote crystal
formation. Xylose crystals are added at approximately 1% of the xylose content of the crystal
slurry. It is assumed that xylose composes 90% of the dry matter.
3) The temperature is reduced over ~5 hours to room temperature (20 ºC). Mixing speed is also
reduced from 50 rpm to a final speed of 5 rpm (Note: Subsequent crystallizations utilized a
set mixing speed of 50 rpm during crystallization).
140
Figure B-1: Crystal slurry before and after crystallization, Xylose-1 (photo on left is at t = 0 hr,
photo on right is at t = 5 hr)
4) The crystal slurry is transferred to a contained and refrigerated overnight at ~ 4ºC; some
slurry losses occurred during the transfer.
Observations:
- As the crystallization progressed, the slurry became lighter in colour, crystals were visible
moving in the slurry from agitation
Filtration:
1) The crystal slurry is transferred to a vacuum filter apparatus (~ 25 cm diameter, see photo).
Vacuum pressure is applied for ~ 30 minutes over the filter to remove the liquid fraction.
2) The solid fraction remaining on the filter is washed with 250 mL of water using a squirt
bottle. The water is kept in an ice bath until use to maintain a cold temperature to suppress
sugar dissolution.
3) Samples are taken of the solid fraction and liquid fraction for HPLC analysis.
4) The filtrate is removed and measured. The solid fraction (including the filter apparatus) is
weighed to determine solid weight.
5) The wash step is repeated using another 250 mL of chilled water. Weighing and sampling
steps are repeated.
6) A third wash stage is completed after the solid fraction is removed from the filter apparatus
and weight. Chilled water equal to half the mass of the solid fraction is used for the third and
final wash (~68 mL H2O was used for this trial).
7) The solid fraction is dried in a 45 ºC oven for approximately 2 hours to remove residual
moisture.
Filtration Results:
141
Figure B-2: Solid fraction containing sugars during filtration and wash stages (From left to right:
no wash, after 1st wash, after 2
nd wash, after final wash) (Xylose-1)
Figure B-3: Liquid filtrate samples (From left to right: no wash, after 1st wash, after 2
nd wash,
after final wash) (Xylose-1)
Sugar losses are calculated relative to the sugar recovered after initial filtration before any wash
stages had occurred.
Table B-1: Sugar yields for different wash stages for Xylose-1 trial
Wash Water
(mL)
Sugar (g) Filtrate
(g)
Solid Sample
Removed (g)
Total Slurry
Weight (g)
Total sugar loss
from washing
(%)
Xylose
crystal
Purity
(%)a
No wash 0 429.6 547.15 1.52 976.75 0.0% 93.0
Wash 1 250 244.72 421.28 1.52 666 43.4% 96.4
Wash 2 250 135.46 333.55 1.52 469.01 69.2% 99.9%
Wash 3 68 95.9 100.53 - 196.43 78.7% 99.9%
a Purity is based on carbohydrate concentration, determined via HPLC, and does not take lignin into account
Observations:
- During the first attempt at filtration, a different filter apparatus was used. The slurry went
directly through the filter and no separation occurred. Slurry was lost to the pump, the filter
paper, and the flask used to hold filtrate in this stage.
- The sugar losses might be partially explained by the type of bottle used to do the washing. It
produced a thin stream of water that appeared to fully saturate the sugar crystals in certain
areas, causing them to dissolve and pass through the filter. A finer spray of water (such as
from a spray bottle) could possibly reduce sugar losses.
142
Sample Xylitol Crystallization Protocol (March 17, 2014)
Goal: Attempt to quantify the performance of xylitol crystallization at lower purities and dry
matter content.
Rationale: A high-yield hydrogenation reactor will give a high xylitol yield with minimal
impurities, however low crystallization yields limit the amount of xylitol that can be recovered
without a recycle loop. It is desirable to increase the amount of xylitol captured through
additional crystallizers, but the lower limit of crystallization due to a diluted/impure feed is
unknown.
Test conditions: 2 different solids contents (50% and 60%) all with Xyla™ xylitol at 95% purity
(5% of total solids are xylose, 95% xylitol).
Protocol: (Same protocol to be followed for both the 50% and 60% trials)
1) All components are weighed and the masses recorded (See table 1)
2) Crystals and water added to reactor.
3) Reactor temperature is increased to 65-70 °C, agitation set to 125-150 rpm. Ensure
minimal crystals are trapped on agitator above the liquid line.
4) Reactor is left at elevated temperature and agitation until all crystals have dissolved and
the solution becomes clear.
5) Once the crystals have dissolved, a sample is taken and its mass recorded. The sample is
analysed for dry matter content, then immediately diluted by 50% in pure water and set
aside for HPLC measurement.
6) Agitation is reduced to 50 rpm and the temperature is lowered to 10 °C. Cooling should
occur at -15 °C/hr, if crystals spontaneously form at any point during the process the
temperature and time at which this occurs should be recorded.
7) Once the mixture reaches 10 °C, it is seeded with xylitol crystals (from an earlier trial,
either XC-1 or fresh Xyla crystals) at 1% of the total solids content.
8) The reactor is maintained at 10 °C for 8 hours, or overnight.
9) The slurry is then separated via filtration using the vacuum pump.
143
10) Weights, DS% and HPLC measurements are taken for both the crystals and the filtrate
recovered. The crystal sample is diluted 1:5 in water, and the filtrate sample is diluted 1:1
in water.
11) Any recovered crystals are dried in the oven at ~37 °C. The mother liquor is collected
and stored at room temperature.
Summary of required information:
a. Initial weights of xylitol, xylose, and water added to the reactor
b. Weights of slurry removed from reactor, crystal, and filtrate recovered by
filtration
c. HPLC (xylitol and sugars), DS%, and weights of the initial, crystal, and filtrate
samples.
d. Times and reactor conditions for when crystals dissolved, seeding, crystallization
start (if crystallization occurs)
Table B-2: Initial component masses added to reactor
Mass of Components – 50% DS Calculated (g) Actual added (g)
Xylitol (Xyla bag) 475 500.01
Xylose 25 26.33
Water 500 526.5
Total 1000 1052.83
Seeding (XC-1 or Xyla) 4.75 5.00, 5.01
Mass of Components – 60% DS Calculated (g) Actual added (g)
Xylitol (Xyla bag) 570 600
Xylose 30 31.59
Water 400 421.2
Total 1000 1052.79
Seeding (XC-1 or Xyla) 5.70 6.02
Table B-3: Crystallization Conditions – 50% solids
Date/Time Reactor Temp
(°C)
Agitation
(rpm)
Suggested event
timeline
Comment
March 5 12PM 69C 125 Crystal Addition
Due to splashing in the reactor
the volume of material was
increased slightly to cover the
agitator blades better - partially
successful.
March 5 1:15PM 69C 125 Crystals fully
dissolved. *Sample
taken*
All crystals dissolved. Sample
taken @ 1:25PM, Temperature
reduction began @ 1:30PM
March 5 3:45PM 41C 50 Temperature reaches
40 °C
No splashing at 50RPM
March 5 5:55PM 27C 50 Temperature reaches
144
25 °C
March 5 7:30PM 10C 50 Temperature reaches
10 °C
No crystal formation
March 5 &:30PM 10C 50 Seeding
Crystals added (g):
Seeded with Xyla, seed crystals
rest at bottom of the reactor.
March 6 10:30AM 10C 50 Crystallization Occurs:
Y/N
NO
March 6, 11:30AM 10C 50 End of Crystallization:
Crystals present: Y/N
No crystals, original seed
crystals dissolved. Reseeded.
March 6 2:30PM 10C 50 End of trial Second batch of seed crystals
did not dissolve, no crystal
formation - ended trial.
Table B-4: Crystallization Conditions – 60% solids
Date/Time Reactor Temp
(°C)
Agitation
(rpm)
Suggested event
timeline
Comment
March 5, 12PM 69C 125 Crystal Addition
Increased volume to match
50% solids trial - this trial
DID NOT have issues with
material splashing in the
reactor.
March 5 12:45PM 69C 125 Crystals fully
dissolved. *Sample
taken*
Crystals dissolved, sample
taken.
March 5 3:45PM 41C 50 Temperature reaches
40 °C
March 5 5:55PM 27C 50 Temperature reaches
25 °C
March 5 7:30PM 10C 50 Temperature reaches
10 °C
March 5 7:30PM 10C 50 Seeding
Crystals added
Seed crystals did not
dissolve, but did disperse
through the liquid material.
March 6 10:30AM 10C 50 Crystallization Occurs:
Y/N
Yes, poorly
March 6 11:30AM 10C 50 End of Crystallization:
Crystals present: Y/N
Yes
March 5 8PM 10C 50 Seed crystals mostly
dissolved.
Table B-5: Crystal Separation – 50% and 60% solids
50% Solids 60% solids
Filter apparatus + filter paper weight 762.54 Filter apparatus + filter paper weight 754.49
145
(g) (g)
Filtrate flask weight (g) 1760.88 Filtrate flask weight (g) 1760.88
Slurry Recovered from reactor (g) 993.26 Slurry Recovered from reactor (g) 997.21
Begin filtration: (time) 2:45PM Begin filtration: (time) 11:35AM
End filtration: (time) 2:55PM End filtration: (time) 11:55AM
Crystals + filter recovered (g) 770.1 Crystals + filter recovered (g) 860.97
Filtrate +flask recovered (g) 2754.74 Filtrate +flask recovered (g) 2650.79
Table B-6: Sample summary 50% solids
Sample Mass Collected (g) DM% Dry Matter
sample (g)
Dilution: water
added (g)
Dilution: sample
added (g)
Initial 5.6 49.38 1.67 2 2
Crystal N/A N/A N/A N/A N/A
Filtrate 4.97 48.35 1.07 2 2
Table B-7: Sample summary 60% solids
Sample Mass Collected (g) DM% Dry Matter
sample (g)
Dilution: water
added (g)
Dilution: sample
added (g)
Initial 5.58 60.44 1.41 2 2
Crystal 3.28 99.65 3.28 12 3
Filtrate 9.7 54.3 1.64 2 2
146
Summary of xylose and xylitol crystallization experiments
Table B-8: Summary of xylose crystallization experimental results
Trial Initial Temp
(°C)
Final Temp
(°C)
Crystallizatio
n time (hr)
Initial Slurry
Carbohydrate Purity
Crystals Recovered
(g)
Filtrat
e (g)
Crystal
Purity
Filtrate
Purity
Xylose
Recovery
Initial
DM %
Crysta
l DM
Filtrat
e DM
Mixing Speed
(rpm)
Xylose 1 74 20 5 95.6% 429.6 547.1
5 99.6% 93.0% 59.2%* - - - 50 to 5
Xylose 2 62 20 45 90.9% 484.62 535.8
8 99.1% 85.8% 63.6%* - - - 25 to 10
Xylose 3 62 20 75 91.2% 461.11 508.2
2 98.7% 83.5% 58.5%* 79.87% - - 25
Xylose 4 - decolourized
extract 65 20 52 97.5% 694.04
702.5
1 98.0% 95.0% 47.3% 74.41%
93.21
% - 50
Xylose 5 60.5 20 24 88.3% 891.14 1337.
29 91.5% 85.0% 51.2% 71.45%
89.57
%
60.35
% 50
Xylose 6 - decolourized
extract 55 18 16 88.3% 648.54
973.8
1 92.1% 85.3% 52.1% 69.21%
87.82
%
57.98
% 50
Xylose 7 - Synthetic
xylose glucose solution 65 20 40.5 93.7% 511.55
406.3
6 98.0% 86.0% 63.4% 78.15%
96.06
%
59.50
% 50
Flask Trials
Xylose-Glucose 1 60 27 2 94.5% 34.8 49.23 97.4% 91.4% 52.2% 70% 91.22
% 62.97
%
Xylose - Arabinose 1 60 27 2 94.7% 27.27 57.75 98.7% 92.5% 42.0% 70% 95.87
%
66.64
%
* - Approximate
Table B-9: Summary of xylitol crystallization experimental results
Initial
Temp
(°C)
Final
Temp
(°C)
Crystalliza
tion time
(hr)
Initial
Slurry
Purity
Crystals
Recovered (g)
Filtrate
(g)
Crystal
Purity
Filtrate
Purity
Xylitol
Recovery
Initial
DM|
Crystal
DM
Filtrate
DM
Mixing
Speed
(rpm)
Xylitol 1 (XC-1) - Pure Xyla xylitol 58 20 29 100%* 689.27 1345.03 100%* 99.4% 43.7% 68.85% 97.14% 57.38% 50
Xylitol 2 (XC-2)- xylitol and xylose mixed with filtrate from XC-1 57 20 24 94.2% 596.06 1236.2 98.8% 91.5% 44.8% 70.93% 98.30% 60.30% 50
Xylitol 3 (XC-3)- XC-2 filtrate +
xylose/xylitol 59 20 24 89.3% 360.43 1095.58 98.3% 85.2% 36.8% 70.90% 98.25 61.63% 50
Xylitol 60% DS Initial 69 20 24 94.7% 106.48 889.91 99.7% 93.8% 18.9% 60.44% 99.65% 54.3% 50
Xylitol 50% DS Initial 69 20 26 94.7% 7.56 993.86 - 94.7% 0% 49.38% - 48.35% 50
147
Appendix C: LCA Information and Sample Calculations
C.1 – Electricity Co-product Credit Determination
System expansion methodology is selected for the handling of the electricity co-product
generated in certain xylitol scenarios. The use of system expansion requires the determination of
a displacement credit for the product that is to be displaced in the market, which is assumed to be
local grid electricity in this study. As the biorefinery is assumed to be located in Ontario, the
emissions associated with displacement of the Ontario electrical grid are determined by inputting
the fuel source distribution of the mixture into GREET 2013[106]. Table C-1 displays a detailed
breakdown of the Ontario electrical grid contract capacity mix.
Table C-1: Breakdown of Total Ontario electricity grid contract capacity as of December 31,
2013[136]
Fuel Source Percentage in Grid
Bio-energy 0.70%
Solar PV 6.39%
Wind 15.59%
Non-Hydroelectric - Sub-total (MW) 22.68%
Hydroelectric 10.92%
Renewables - Sub-total (MW) 33.60%
Natural Gas and Other Fuel Sources 0.00%
Combined Heat and Power (CHP) 2.60%
Simple Cycle and Combined Cycle (SC/CC) 44.98%
Energy from Waste (EFW) 0.02%
Natural Gas and Other - Sub-total (MW) 47.59%
Nuclear
Bruce A 18.81%
Nuclear Sub-total (MW) 18.81%
Total Contract Capacity (MW) 100.01%
To determine the emissions credit of the Ontario electricity mix, GREET 2013 is utilized. Table
C-2 displays the actual input values utilized within GREET 2013 to generate the emissions
values. As the US Midwest was investigated as an alternate biorefinery location, the emissions
associated with the regional electrical grid were also calculated. The US Midwest electricity mix
is included in GREET 2013; the distribution of fuel sources for this mix is also displayed in
Table C-2.
148
Table C-2: Electricity grid mixtures values used in GREET 2013 for different geographic
locations[106]
Ontario Grid Mixture
December 2013
US Midwest
MRO Mixture
Fuel Grid Fraction Grid Fraction
Residual oil 0.00% 0.3%
Natural gas 47.59% 3.3%
Coal 0.00% 65.5%
Nuclear power 18.81% 15.1%
Biomass 0.70% 0.3%
Others 32.89% 15.7%
Emissions results from GREET 2013 for the two regions are shown in Table C-3. These values
are for a stationary power plant, and neglect transmission losses, as losses within the
transmission system will occur independently of the electricity fuel source. A net electricity
credit is determined by calculating the carbon dioxide equivalent value from the emissions of
CO2, N2O, and CH4. Electricity generation from the biorefinery is expected to directly replace
grid electricity, and therefore is assumed to have a displacement ratio (R) of 1. Global warming
potential (GWP) 100-year values, determined based on the warming potentials of different
gaseous emissions are used to convert individual emissions to the carbon dioxide equivalent
value. The electricity credit is determined as follows:
Electricity Credit = GHGeq.*R = (ECO2*GWPCO2 + ECH4*GWPCH4 + EN2O*GWPN2O)*R
Where E represents individual gas emissions in grams per kilowatt-hour. GWP-100 year values
for the gases studied are: CO2 = 1, CH4 = 24, N2O = 298, based on 2007 IPCC values[140].
Table C-3: Electricity emissions for different generation mixtures (Source: GREET 2013 [106])
Stationary Use:
Ontario Mix Dec 2013
Stationary Use:
MRO Mix
Emissions (g/kWh) Total Total
VOC 0.009 0.017
CO 0.135 0.142
NOx 0.130 1.030
PM10 0.027 0.108
PM2.5 0.021 0.085
SOx 0.017 2.355
CH4 0.008 0.009
149
N2O 0.001 0.012
CO2 226 716
CO2-eq
(g CO2-eq/kWh) 226 720
C.2 – Sucrose displacement credit
To supplement the values found for sucrose production in the literature, the LCA software
SimaPro 8.0[141] was utilized to calculate the net GHG emissions for the production of sucrose
(sugar) from sugar beets. Data are taken from the European Union, specifically Denmark, to
generate the emissions values[142].
Table C-4: Sucrose GHG emissions summary (Source: SimaPro 8.0 [141])
Substance
Total of all
compartments
Remaining
substances
Carbon
dioxide
Dinitrogen
monoxide Methane
Compartment
Air Air Air
Unit kg CO2 eq kg CO2 eq
kg CO2
eq kg CO2 eq
kg CO2
eq
Total 0.8409 0.0008 0.7649 0.0361 0.0391
Sugar x x x x x
Sugar beet, from farm 0.4100 0.0001 0.1598 0.2400 0.0101
Truck 28t 0.1140 0.0004 0.1059 0.0032 0.0045
Water (tap) 0.0004 0.0000 0.0004 0.0000 0.0000
Heat (sugar ind.) 0.6053 0.0004 0.5724 0.0022 0.0304
Electricity (natural gas) 0.0150 0.0000 0.0148 0.0000 0.0002
Animal feed (molasses) -0.1147 0.0000 -0.0334 -0.0790 -0.0023
Animal feed (feed pills, sugar
prod.) -0.1892 0.0000 -0.0551 -0.1303 -0.0038
Unspecified x x x x x
Wastewater treatment, BOD 4.17E-06 3.55E-10 4.10E-06 9.12E-09 6.15E-08
Wastewater treatment N 7.07E-05 6.01E-09 6.95E-05 1.54E-07 1.04E-06
C.3 – Product transportation emissions and energy consumption
Xylitol is transported to a distribution centre, where the life cycle boundary ends, by diesel-
fueled truck. The transportation distance is assumed to be 800 km and only the emissions
associated with the trip from the biorefinery to the distribution centre are included, as it is
assumed that the trucks will not make the return trip empty. The average truck payload is
calculated to be 30 420 kg, based on available data[130]. Emissions values are calculated using
150
results from GREET 2013 for a compression-ignition direct injection (CIDI) vehicle using
conventional or low sulfur diesel. A summary of emissions is presented in Table C-4. Net
emissions are calculated based on the GWP values of CO2, N2O, and CH4 as previously
described. GREET results are also utilized to calculate the energy consumption of this life cycle
stage.
Table C-5: Energy and emissions results for a CIDI Vehicle: Conventional and LS Diesel
(Source: GREET 2013 [106])
Item Feedstock Fuel
Vehicle
Operation Total
Energy (MJ/km)
Total Energy 0.185 0.418 2.62 3.22
Fossil Fuels 0.176 0.411 2.62 3.21
Coal 0.037 0.027 0.000 0.065
Natural Gas 0.097 0.213 0.000 0.310
Petroleum 0.042 0.171 2.62 2.83
Emissions (g/km)
CO2 (w/ C in
VOC & CO) 15 31 196 243
CH4 0.238 0.054 0.000 0.292
N2O 0.000 0.001 0.000 0.001
C.4 – Hydrogen production via steam methane reforming
It is assumed that hydrogen gas is produced by a small-scale steam methane reforming (SMR)
unit located on-site, using natural gas as both a feedstock and fuel source. Emissions values for
the SMR are taken from GREET 2013 for a central plant using NG to produce gaseous
hydrogen. Energy and emissions values are shown in Table C-5. It is assumed that the central
plant accurately represents the facility located at the biorefinery. The SMR facility is not
independently modelled. The Ontario electricity grid mix is utilized within GREET to determine
fuel sources and resultant emissions. Based on literature, SMR produces 0.24-0.27 kg H2 per kg
NG[134], [135].
Table C-6: Energy and emissions associated with hydrogen production via SMR (Source:
GREET 2013 [106])
Central Plants: NG or FG to Gaseous Hydrogen
Feedstock (MJ/GJ H2) Fuel(MJ/GJ H2)
151
Total energy 78.0 666
Fossil fuels 77.2 579
Coal 0.00 0.00
Natural gas 73.1 576.3
Petroleum 4.08 2.42
Emissions Feedstock (g/GJ H2) Feedstock (g/GJ H2)
VOC 6.01 5.92
CO 9.62 23.8
NOx 23.82 46.25
PM10 0.42 13.02
PM2.5 0.38 12.74
SOx 10.24 6.22
CH4 144.8 83.5
N2O 0.32 0.51
CO2 4873 89189
CO2 (w/ C in VOC
& CO) 4907 89245
GHGs 8621 91485
C.5 – Fermentation Nutrient Emissions
Corn steep liquor (CSL) and diammonium phosphate (DAP) are utilized in the fermentation
models as nitrogen and trace nutrient sources. Emissions are calculated for CSL based on results
from the US LCI database[143] and are displayed in Table C-6.
Table C-7: Emissions for Corn Steep Liquor (Source: U.S. LCI Database[143])
To Nature corn steep liquor, RNA, [kg]
Number Name Location Infra Mean value Unit
air/unspecified
23 Aldehydes, unspecified UNSPECFIED No 6.11E-09 kg
11 Ammonia UNSPECFIED No 1.20E-04 kg
37 Antimony
No 5.63E-12 kg
12 Arsenic UNSPECFIED No 1.29E-10 kg
2 Barium
No 4.39E-12 kg
35 Benzene
No 2.91E-08 kg
42 Cadmium UNSPECFIED No 1.05E-11 kg
58 Carbon dioxide, fossil No 0.006861 kg
27 Carbon monoxide, fossil No 2.05E-05 kg
49 Chromium UNSPECFIED No 5.22E-10 kg
152
13 Cobalt
No 1.28E-11 kg
15 Copper
No 1.73E-12 kg
50 Dinitrogen monoxide UNSPECFIED No 6.21E-06 kg
36 Fluoride UNSPECFIED No 1.12E-07 kg
5 Formaldehyde UNSPECFIED No 1.73E-09 kg
51 Hydrocarbons, unspecified UNSPECFIED No 7.64E-06 kg
32 Hydrogen chloride UNSPECFIED No 1.21E-07 kg
39 Hydrogen fluoride UNSPECFIED No 1.87E-08 kg
41 Hydrogen sulfide UNSPECFIED No 3.57E-09 kg
53 Lead UNSPECFIED No 2.60E-10 kg
56 Magnesium UNSPECFIED No 8.70E-10 kg
55 Manganese
No 3.22E-10 kg
17 Mercury
No 9.64E-12 kg
33 Methane, fossil UNSPECFIED No 1.06E-05 kg
19 Molybdenum UNSPECFIED No 7.28E-13 kg
8 Nickel UNSPECFIED No 5.33E-10 kg
7 Nitrogen oxides UNSPECFIED No 2.99E-05 kg
59
Organic substances,
unspecified UNSPECFIED No 4.98E-06 kg
16 Particulates UNSPECFIED No 2.03E-04 kg
24 Sulfur dioxide UNSPECFIED No 0.0082154 kg
22 Toluene UNSPECFIED No 2.75E-11 kg
46 Vanadium UNSPECFIED No 1.30E-11 kg
25 Xylene UNSPECFIED No 1.10E-12 kg
40 Zinc UNSPECFIED No 2.33E-11 kg
final-waste-flow/unspecified
57 Waste, industrial UNSPECFIED No 5.80E-07 kg
38 Waste, unspecified UNSPECFIED No 4.20E-04 kg
water/unspecified
47 Acids, unspecified No 6.02E-08 kg
60 Ammonia UNSPECFIED No 8.33E-08 kg
10
BOD5, Biological Oxygen
Demand UNSPECFIED No 1.54E-06 kg
31 Chloride UNSPECFIED No 7.22E-06 kg
1
COD, Chemical Oxygen
Demand UNSPECFIED No 6.20E-06 kg
4 Fluoride UNSPECFIED No 1.58E-09 kg
18 Hydrocarbons, unspecified UNSPECFIED No 1.65E-09 kg
26 Iron UNSPECFIED No 3.15E-12 kg
30 Metallic ions, unspecified UNSPECFIED No 1.30E-08 kg
14 Nitrate UNSPECFIED No 5.34E-04 kg
0 Oils, unspecified No 1.64E-07 kg
45 Phenol UNSPECFIED No 5.35E-09 kg
21 Salts, unspecified UNSPECFIED No 1.41E-06 kg
54 Sodium, ion UNSPECFIED No 9.30E-06 kg
153
43 Sulfate UNSPECFIED No 3.45E-10 kg
29
Suspended substances,
unspecified UNSPECFIED No 1.32E-06 kg
6 Waste water/m3 No 8.25E-09 m3
To determine the emissions of DAP, SimaPro 8.0 is utilized[141]. A summary of the emissions
determined in SimaPro is presented in Table C-7. For brevity, only the results associated with
CO2, N2O, and CH4 are presented.
Table C-8: Emissions for diammonium phosphate (DAP) (Source: SimaPro 8.0[141])
Species Source
Emissions
(kg/kg DAP)
Carbon dioxide biogenic high. pop. 0.022844
Carbon dioxide biogenic low. pop. 0.0013074
Carbon dioxide biogenic 0.0007638
Carbon dioxide fossil high pop. 2.1616
Carbon dioxide fossil low pop. 0.32037
Carbon dioxide fossil stratosphere + tropo 1.485E-06
Carbon dioxide fossil 0.1511
Carbon dioxide land transformation low. pop. 3.214E-05
Dinitrogen monoxide high. pop. 2.765E-05
Dinitrogen monoxide low. pop. 5.525E-06
Dinitrogen monoxide stratosphere + tropo 0
Dinitrogen monoxide
6.415E-06
Methane fossil high. pop. 8.717E-05
Methane fossil low. pop. 0.005805
Methane fossil stratosphere + tropo 0
Methane fossil 8.446E-06
154
Appendix D: Financial Modelling Calculations
Capital cost summary sheets, operating cost and total product cost summary sheets, and cash
flow statements are provided in this section. To reduce appendix length, only selected scenarios
are presented. Results are shown for the hydrogenation best case (best and worst performance),
fermentation 10% extract concentration low tolerance TVR (best and worst performance), and
fermentation 10% extract concentration high tolerance TVR (best and worst performance) cases.
155
Table D-1: Sensitivity results for variations in xylitol price on IRR and ROI
IRR Hydrogenation:
BC
Fermentation:
LT 10% TVR ROI
Hydrogenation:
BC
Fermentation:
LT 10% TVR
Product
Price ($/kg) Worst Best Worst Best Worst Worst Best Worst Best
3 10% 36% 19% 30% 5.44% 0.4% 13% 4.2% 10%
3.5 14% 43% 23% 36% 7.05% 2.1% 16% 6.2% 13%
4 17% 50% 28% 42% 8.66% 3.7% 20% 8.3% 16%
4.5 20.14% 56.3% 31.9% 47.5% 10.20% 4.9% 24% 10% 19%
5 24% 63% 36% 53% 11.88% 6.9% 28% 12% 22%
5.5 27% 70% 40% 59% 13.49% 8.5% 31% 14% 25%
Table D-2: Sensitivity results for variations in Debt-to-Equity ratio on IRR and ROI
IRR
Hydrogenation:
BC
Fermentation:
LT 10% TVR
ROI
Hydrogenation:
BC
Fermentation:
LT 10% TVR
D:E Worst Best Worst Best D:E Worst Best Worst Best
40:60 15% 41% 23% 35% 40:60 11% 30% 16% 25%
50:50 17% 47% 27% 40% 50:50 10% 29% 16% 24%
60:40 20% 56% 32% 48% 60:40 10% 29% 16% 24%
156
Table D-3: Sensitivity results for variations in loan rate on IRR and ROI
IRR
Hydrogenation:
BC
Fermentation:
LT 10% TVR
ROI
Hydrogenation:
BC
Fermentation:
LT 10% TVR
Rate Worst Best Worst Best Rate Worst Best Worst Best
6% 22% 58% 33% 49% 6% 11% 29% 16% 25%
8% 20% 56% 32% 48% 8% 10% 29% 16% 24%
10% 19% 55% 30% 46% 10% 10% 29% 16% 24%
Table D-4: Sensitivity results for variations in CAPEX on IRR and ROI
IRR
Hydrogenation:
BC
Fermentation:
LT 10% TVR ROI
Hydrogenation:
BC
Fermentation:
LT 10% TVR
CAPEX Worst Best Worst Best
Interest Worst Best Worst Best
75% CAPEX 27% 73% 42% 62%
75% CAPEX 14% 39% 21% 32%
100% CAPEX 20% 56% 32% 48%
100% CAPEX 10% 29% 16% 24%
125% CAPEX 16% 46% 26% 39%
125% CAPEX 8.2% 23% 13% 19%
157
Table D - 5: Hydrogenation Base Case (BC) Equipment List – Best Case
Component
Name Component Type Description Material
Material
factor
Size
Factor
Actual Size
factor Unit
Equipment
Cost
Scale
Factor Scaled Cost
Feed scale
factor Scaled Best
COND2HEX
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 76.24 76.24 m2 $30,800 1.00 $30,800 0.88 $27,000
CRYS1HEX
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 19.57 19.57 m2 $17,700 1.00 $17,700 0.88 $15,500
CRYS2HEX
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 41.64 41.64 m2 $24,900 1.00 $24,900 0.88 $21,800
DRYCNHEX
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 30.88 9.74 m2 $20,900 0.45 $9,315 0.88 $8,200
HINTHEX
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 4.38 4.38 m2 $17,200 1.00 $17,200 0.88 $15,100
PRHEAHEX DHE TEMA EXCH
Fixed tube, float head, u-tube exchanger SS316 L 1 3.50 3.50 m2 $11,200 1.00 $11,200 0.88 $9,800
PRXNHEX
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 8.84 8.84 m2 $21,600 1.00 $21,600 0.88 $18,900
EVAP1
EE STAND
VERT
Standard vertical tube
evaporator SS316 L 1 142.00 10.31 L/min $1,700,000 0.16 $271,126 0.88 $237,200
EVAP2
EE STAND
VERT
Standard vertical tube
evaporator SS316 L 1 142.00 70.91 L/min $1,700,000 0.62 $1,045,541 0.88 $914,900
BOILER_COM
B
ESTBSTM
BOILER Field erected boiler unit CS 1
35292.4
0 62000.00 kg/hr $614,200 1.48 $911,186 0.88 $797,300
COOLINGTO
WER
ECTWCOOLIN
G
Cooling tower, less pumps,
field assembly GALV 1 65.00 472.80 L/s $97,300 4.01 $390,252 0.88 $341,500
CHILLER
ERU
MECHANICAL
Mechanical compress,
refrigeration unit CS 1 488.00 500.00 kW $276,300 1.02 $281,039 0.88 $245,900
MPUMP1
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 0.41 0.41 L/s $11,300 1.00 $11,300 0.88 $9,900
MPUMP2
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 1.03 1.03 L/s $12,700 1.00 $12,700 0.88 $11,100
MPUMP3
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 0.81 0.81 L/s $12,300 1.00 $12,300 0.88 $10,800
MPUMP4 EP DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 0.66 0.66 L/s $12,000 1.00 $12,000 0.88 $10,500
MPUMP5 EP DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 0.44 0.44 L/s $11,400 1.00 $11,400 0.88 $10,000
PUMP1
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 0.98 0.98 L/s $12,700 1.00 $12,700 0.88 $11,100
PUMP2
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 0.98 0.98 L/s $12,700 1.00 $12,700 0.88 $11,100
PUMP3
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 0.98 0.98 L/s $12,700 1.00 $12,700 0.88 $11,100
H2RC1
DGC RECIP
MOTR Reciprocating compressor CS 1 13.13 13.13 m3/hr $349,200 1.00 $349,200 0.88 $305,600
158
REACTMIX DAT REACTOR
Agitated tank, enclosed,
jacketed SS316 L 1 11.57 11.57 m3/hr $721,300 1.00 $721,300 0.88 $631,200
VACCRYST
ECRYBATCH
VAC Batch Vacuum Crystallizer SS304L 1 25.80 25.80 m3 $692,900 1.00 $692,900 0.88 $606,300
COOLCRYST ECRYOSLO Oslo growth type crystallizer CS 2.1 4.25 4.25
tonne/
hr $609,300 2.10 $1,279,530 0.88 $1,119,600
DRYER ED SPRAY
Continuous spray drying
system CS 2.1 320.00 232.41 kg/hr $293,800 1.68 $493,219 0.88 $431,600
#1#CENTRIFU
GE
ECT BATCH
AUTO
Auto batch filtering
centrifuge SS316 L 1 1520.00 1520.00 mm $188,200 1.00 $188,200 0.88 $164,700
BFWMP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.36 0.36 L/s $6,100 1.00 $6,100 0.88 $5,300
BFWP2 DCP ANSI Standard ANSI single stage pump 316 SF 1 0.06 0.06 L/s $6,100 1.00 $6,100 0.88 $5,300
BWFP3 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.05 0.05 L/s $6,100 1.00 $6,100 0.88 $5,300
BWFP4 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.21 0.21 L/s $6,100 1.00 $6,100 0.88 $5,300
BWFP5 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.05 0.05 L/s $6,100 1.00 $6,100 0.88 $5,300
CHWP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 1.67 1.67 L/s $6,200 1.00 $6,200 0.88 $5,400
COND1P DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.18 0.18 L/s $6,100 1.00 $6,100 0.88 $5,300
COND2P DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.20 0.20 L/s $6,100 1.00 $6,100 0.88 $5,300
COND3P DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.07 0.07 L/s $6,100 1.00 $6,100 0.88 $5,300
CWP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 11.56 11.56 L/s $7,900 1.00 $7,900 0.88 $6,900
CWP2 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 3.58 3.58 L/s $6,300 1.00 $6,300 0.88 $5,500
CWP3 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 1.88 1.88 L/s $6,200 1.00 $6,200 0.88 $5,400
BFWM1 VT CYLINDER Vertical process vessel SS316 1 0.11 0.11 m3 $5,400 1.00 $5,400 0.88 $4,700
CONDM1 VT CYLINDER Vertical process vessel SS316 1 0.13 0.13 m3 $5,600 1.00 $5,600 0.88 $4,900
COOLERM1 VT CYLINDER Vertical process vessel SS316 1 5.10 5.10 m3 $37,100 1.00 $37,100 0.88 $32,500
EVAPMIX VT CYLINDER Vertical process vessel SS316 1 0.31 0.31 m3 $17,500 1.00 $17,500 0.88 $15,300
MIXER AT CYLINDER Agitated tank, enclosed SS316 1 1.76 1.76 m3 $65,000 1.00 $65,000 0.88 $56,900
FILTER - RA NI F LEAF WET Pressure-leaf wet filter SS316 L 1 4.70 4.70 m2 $41,300 1 $41,300 0.88 $36,100
NaOH Storage TANK
VT PLAST TANK PLAST TANK FRP 1 20.00 20.00 m3 $25,300 1.00 $25,300 0.88 $22,100
Enzyme
Storage Tank VT STORAGE
Vertical storage vessel, flat
bottom SS316 1 10.00 10.00 m3 $27,200 1.00 $27,200 0.88 $23,800
H2 Gas Storage VT STORAGE
Low pressure gas storage
vessel A285C 1 5.00 5.00 m3 $18,000 1.00 $18,000 0.88 $15,800
159
Anaerobic
Digestion VT STORAGE
1
129566
8.46 1295668.46
tonne/
yr
$41,608,05
6 1.00 $41,608,056 1.00
$41,600,00
0
Xylose Cryst1
ECRYBATCH
VAC Batch Vacuum Crystallizer SS304L 1 25.80 358.71 m3 $692,900 6.31 $4,373,743 0.88 $3,850,000
Xylose Cryst2 ECRYOSLO Oslo growth type crystallizer CS 2.1 3.08 10.36
tonne/
hr $494,000 4.91 $2,425,214 0.88 $2,130,000
UPSTREAM XYLOSE
PURIFICATION
1
29955.1
5 26105.99
$64,512,76
2
0.90821
3815 $58,591,381 1
$58,590,00
0
Table D - 6: Hydrogenation Base Case OPEX and TPC Calculation List – Best Case
Chemicals Flow Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg xylitol)
Enzymes 35.1 kg/hr 4.7 $/kg $165 $1,370,000 $0.07
NaOH 407 kg/hr 0.69 $/kg $281 $2,340,000 $0.12
Hydrogen 36.0 kg/hr 1.5 $/kg $54.0 $449,000 $0.02
Utilities Flow Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg)
Steam 49,600 kg/hr 0 $/kg $0.00 $0.00 $0.00
Cooling Water 1,702,000 kg/hr 0.02 $/m3 $34.0 $283,000 $0.01
Chilled Water 500 kWh 4 $/GJ $7.20 $59,900 $0.00
Electricity 0
0.06 $/kWh $0.00 $0.00 $0.00
Labour
Operators 15 # employees $70,000 $/year $126 $1,050,000 $0.05
Maintenance
2% CAPEX $3,940,000 $/year $475 $3,950,000 $0.19
Consumables
1% CAPEX $1,970,000 $/year $237 $1,970,000 $0.10
Laboratory
1% CAPEX $1,970,000 $/year $237 $1,970,000 $0.10
OPEX
$1,620 $13,400,000 $0.66
SLD
20 yr $9,870,000 $/year $1,190 $9,870,000 $0.49
Property Tax 0
$0.00 $/year $0.00 $0.00 $0.00
Insurance
0.5% FCI $987,000 $/year $119 $987,000 $0.05
Interest
$17,700,000 $/year $2,120 $17,700,000 $0.87
FC Total
$3,430 $28,500,000 $1.41
Administration,
marketing, distribution 10% TPC
$504 $4,200,000 $0.21
TPC
$5,550 $46,100,000 $2.28
160
Products Flow Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg xylitol)
Xylitol 2430 kg/hr 4.5 $/kg $11,000 $91,200,000 $4.50
Electricity 1300 kWh 5.72 c/kWh $74.0 $617,000 $0.03
Revenue
$11,000 $91,800,000 $4.53
Table D - 7: Hydrogenation BC Cash Flow Statement - Best Case ($MM)
Year Capital Cost Revenue Operating Costs EBITDA Depreciation Interest GP Taxes Net Profit ATCF
0 -$198 $119 $0.0 -$79.0 $0.0 $0.0 $0.0 $0.0 -$79.0 -$79.0
1 $0.0 $45.9 $6.7 $39.2 $9.9 -$9.5 $19.8 $5.0 $14.9 $24.8
2 $0.0 $91.8 $13.5 $78.3 $9.9 -$8.8 $59.6 $14.9 $44.7 $54.6
3 $0.0 $91.8 $13.5 $78.3 $9.9 -$8.1 $60.3 $15.1 $45.2 $55.1
4 $0.0 $91.8 $13.5 $78.3 $9.9 -$7.4 $61.1 $15.3 $45.8 $55.7
5 $0.0 $91.8 $13.5 $78.3 $9.9 -$6.5 $61.9 $15.5 $46.4 $56.3
6 $0.0 $91.8 $13.5 $78.3 $9.9 -$5.6 $62.8 $15.7 $47.1 $57.0
7 $0.0 $91.8 $13.5 $78.3 $9.9 -$4.7 $63.8 $15.9 $47.8 $57.7
8 $0.0 $91.8 $13.5 $78.3 $9.9 -$3.6 $64.8 $16.2 $48.6 $58.5
9 $0.0 $91.8 $13.5 $78.3 $9.9 -$2.5 $65.9 $16.5 $49.4 $59.3
10 $0.0 $91.8 $13.5 $78.3 $9.9 -$1.3 $67.1 $16.8 $50.4 $60.3
11 $0.0 $91.8 $13.5 $78.3 $9.9 $0.0 $68.4 $17.1 $51.3 $61.2
12 $0.0 $91.8 $13.5 $78.3 $9.9 $0.0 $68.4 $17.1 $51.3 $61.2
13 $0.0 $91.8 $13.5 $78.3 $9.9 $0.0 $68.4 $17.1 $51.3 $61.2
14 $0.0 $91.8 $13.5 $78.3 $9.9 $0.0 $68.4 $17.1 $51.3 $61.2
15 $0.0 $91.8 $13.5 $78.3 $9.9 $0.0 $68.4 $17.1 $51.3 $61.2
16 $0.0 $91.8 $13.5 $78.3 $9.9 $0.0 $68.4 $17.1 $51.3 $61.2
17 $0.0 $91.8 $13.5 $78.3 $9.9 $0.0 $68.4 $17.1 $51.3 $61.2
18 $0.0 $91.8 $13.5 $78.3 $9.9 $0.0 $68.4 $17.1 $51.3 $61.2
19 $0.0 $91.8 $13.5 $78.3 $9.9 $0.0 $68.4 $17.1 $51.3 $61.2
20 $0.0 $91.8 $13.5 $78.3 $9.9 $0.0 $68.4 $17.1 $51.3 $61.2
161
Table D - 8: Hydrogenation Base Case (BC) Equipment List – Worst Case
Component Name Component Type Description
Mate
rial
Material
size factor
Size
Factor
Actual Size
factor Unit
Equipmen
t Cost
Scale
Factor
Scaled Cost
AVG
Feed scale
factor
Scaled
Worst
COND2HEX DHE TEMA EXCH Fixed tube, float head, u-tube exchanger
SS316 L 1 76.24 76.2413 m2 $30,800 1.00 $30,800 1.73 $53,200
CRYS1HEX DHE TEMA EXCH
Fixed tube, float head, u-
tube exchanger
SS31
6 L 1 19.57 19.5684 m2 $17,700 1.00 $17,700 1.73 $30,600
CRYS2HEX DHE TEMA EXCH
Fixed tube, float head, u-
tube exchanger
SS31
6 L 1 41.64 41.637 m2 $24,900 1.00 $24,900 1.73 $43,000
DRYCNHEX DHE TEMA EXCH
Fixed tube, float head, u-
tube exchanger
SS31
6 L 1 30.88 9.73604 m2 $20,900 0.45 $9,315 1.73 $16,100
HINTHEX DHE TEMA EXCH
Fixed tube, float head, u-
tube exchanger
SS31
6 L 1 4.38 4.3834 m2 $17,200 1.00 $17,200 1.73 $29,700
PRHEAHEX DHE TEMA EXCH
Fixed tube, float head, u-
tube exchanger
SS31
6 L 1 3.50409 3.50409 m2 $11,200 1.00 $11,200 1.73 $19,400
PRXNHEX DHE TEMA EXCH
Fixed tube, float head, u-
tube exchanger
SS31
6 L 1 8.84246 8.84246 m2 $21,600 1.00 $21,600 1.73 $37,300
evap1 EE STAND VERT
Standard vertical tube
evaporator
SS31
6 L 1 142.00
10.3114726
5
L/mi
n
$1,700,00
0 0.16 $271,126 1.73
$468,70
0
EVAP2 EE STAND VERT
Standard vertical tube
evaporator
SS31
6 L 1 142.00
70.9097523
3
L/mi
n
$1,700,00
0 0.62 $1,045,541 1.73
$1,807,4
00
BOILER_COMB ESTBSTM BOILER Field erected boiler unit CS 1 35292.4 62000 kg/hr $614,200 1.48 $911,186 1.73
$1,575,2
00
COOLINGTOWER ECTWCOOLING Cooling tower, less pumps, field assembly
GALV 1 65.00 472.796621 L/s $97,300 4.01 $390,252 1.73
$674,600
CHILLER ERU MECHANICAL
Mechanical compress, refrigeration unit CS 1 488.00 500 kW $276,300 1.02 $281,039 1.73
$485,800
MPUMP1 EP DIAPHRAGM Diaphragm pump, TFE type
SS31
6 L 1 0.41 0.41 L/s $11,300 1.00 $11,300 1.73 $19,500
MPUMP2 EP DIAPHRAGM Diaphragm pump, TFE type
SS31
6 L 1 1.03 1.03 L/s $12,700 1.00 $12,700 1.73 $22,000
MPUMP3 EP DIAPHRAGM Diaphragm pump, TFE type
SS31
6 L 1 0.81 0.81 L/s $12,300 1.00 $12,300 1.73 $21,300
MPUMP4 EP DIAPHRAGM Diaphragm pump, TFE type
SS31
6 L 1 0.66 0.66 L/s $12,000 1.00 $12,000 1.73 $20,700
MPUMP5 EP DIAPHRAGM Diaphragm pump, TFE type
SS31
6 L 1 0.44 0.44 L/s $11,400 1.00 $11,400 1.73 $19,700
PUMP1 EP DIAPHRAGM Diaphragm pump, TFE type
SS31
6 L 1 0.98 0.98 L/s $12,700 1.00 $12,700 1.73 $22,000
PUMP2 EP DIAPHRAGM Diaphragm pump, TFE type
SS31
6 L 1 0.98 0.98 L/s $12,700 1.00 $12,700 1.73 $22,000
PUMP3 EP DIAPHRAGM Diaphragm pump, TFE type
SS31
6 L 1 0.98 0.98 L/s $12,700 1.00 $12,700 1.73 $22,000
H2RC1 DGC RECIP MOTR Reciprocating compressor CS 1 13.13 13.13
m3/h
r $349,200 1.00 $349,200 1.73
$603,70
0
REACTMIX DAT REACTOR Agitated tank, enclosed, jacketed
SS316 L 1 11.57 11.57
m3/hr $721,300 1.00 $721,300 1.73
$1,246,900
VACCRYST ECRYBATCH VAC Batch Vacuum Crystallizer
SS30
4L 1 25.80 25.80 m3 $692,900 1.00 $692,900 1.73
$1,197,8
00
COOLCRYST ECRYOSLO Oslo growth type CS 2.1 4.25 4.25 tonn $609,300 2.10 $1,279,530 1.73 $2,211,9
162
crystallizer e/hr 00
DRYER ED SPRAY Continuous spray drying system CS 2.1 320.00 232.406446 kg/hr $293,800 1.68 $493,219 1.73
$852,600
#1#CENTRIFUGE
ECT BATCH
AUTO
Auto batch filtering
centrifuge
SS31
6 L 1
1,520.0
0 1,520.00 mm $188,200 1.00 $188,200 1.73
$325,30
0
BFWMP1 DCP ANSI
Standard ANSI single stage
pump
316
SF 1
0.36246
1111
0.36246111
1 L/s $6,100 1.00 $6,100 1.73 $10,500
BFWP2 DCP ANSI
Standard ANSI single stage
pump
316
SF 1
0.06014
25 0.0601425 L/s $6,100 1.00 $6,100 1.73 $10,500
BWFP3 DCP ANSI
Standard ANSI single stage
pump
316
SF 1
0.04908
1111
0.04908111
1 L/s $6,100 1.00 $6,100 1.73 $10,500
BWFP4 DCP ANSI
Standard ANSI single stage
pump
316
SF 1
0.20636
3611
0.20636361
1 L/s $6,100 1.00 $6,100 1.73 $10,500
BWFP5 DCP ANSI
Standard ANSI single stage
pump
316
SF 1
0.04687
2222
0.04687222
2 L/s $6,100 1.00 $6,100 1.73 $10,500
CHWP1 DCP ANSI
Standard ANSI single stage
pump
316
SF 1
1.66786
9444
1.66786944
4 L/s $6,200 1.00 $6,200 1.73 $10,700
COND1P DCP ANSI
Standard ANSI single stage
pump
316
SF 1
0.17578
0833
0.17578083
3 L/s $6,100 1.00 $6,100 1.73 $10,500
COND2P DCP ANSI
Standard ANSI single stage
pump
316
SF 1
0.20205
5278
0.20205527
8 L/s $6,100 1.00 $6,100 1.73 $10,500
COND3P DCP ANSI Standard ANSI single stage pump
316 SF 1
0.0667975 0.0667975 L/s $6,100 1.00 $6,100 1.73 $10,500
CWP1 DCP ANSI Standard ANSI single stage pump
316 SF 1 11.563 11.563 L/s $7,900 1.00 $7,900 1.73 $13,700
CWP2 DCP ANSI
Standard ANSI single stage
pump
316
SF 1 3.576 3.576 L/s $6,300 1.00 $6,300 1.73 $10,900
CWP3 DCP ANSI
Standard ANSI single stage
pump
316
SF 1
1.87538
6111
1.87538611
1 L/s $6,200 1.00 $6,200 1.73 $10,700
BFWM1 VT CYLINDER Vertical process vessel
SS31
6 1
0.10873821
8 m3 $5,400 1.00 $5,400 1.73 $9,300
CONDM1 VT CYLINDER Vertical process vessel
SS31
6 1
0.13332896
9 m3 $5,600 1.00 $5,600 1.73 $9,700
COOLERM1 VT CYLINDER Vertical process vessel
SS31
6 1
5.10426935
8 m3 $37,100 1.00 $37,100 1.73 $64,100
EVAPMIX VT CYLINDER Vertical process vessel
SS31
6 1
0.31332873
8 m3 $17,500 1.00 $17,500 1.73 $30,300
MIXER AT MIXER Agitated tank, enclosed
SS31
6 1
1.76138215 m3 $65,000 1.00 $65,000 1.73
$112,40
0
FILTER - RA NI F LEAF WET Pressure-leaf wet filter
SS31
6 L 1 4.7
m2 $41,300 1 $41,300 1.73 $71,400
NaOH Storage
TANK VT PLAST TANK PLAST TANK FRP 1
20 m3 $25,300 1.00 $25,300 1.73 $43,700
Enzyme Storage Tank VT STORAGE
Vertical storage vessel, flat bottom
SS316 1
10 m3 $27,200 1.00 $27,200 1.73 $47,000
H2 Gas Storage VT STORAGE
Low pressure gas storage
vessel
A285
C 1
5 m3 $18,000 1.00 $18,000 1.73 $31,100
Anaerobic Digestion
1
266537
5.114
2665375.11
4
tonn
e/yr
$62,339,3
32 1.00
$62,339,33
2 1.00
$62,339,
300
Xylose Cryst1 ECRYBATCH VAC Batch Vacuum Crystallizer
SS30
4L 1 25.80
358.705378
9 m3 $692,900 6.31 $4,373,743 1.73
$7,560,8
00
163
Xylose Cryst2 ECRYOSLO
Oslo growth type
crystallizer CS 2.1
3.08039
221
10.3625998
4
tonn
e/hr $494,000 4.91 $2,425,214 1.73
$4,192,4
00
UPSTREAM XYLOSE PURIFICATION
29955.1
4755 106541.316 kg/hr
$64,512,7
62
2.43070
7021
$156,811,6
23 1
$156,81
0,000
Table D - 9: Hydrogenation Base Case OPEX and TPC Calculation List – Worst Case
Chemicals Flow Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg xylitol)
Enzymes 92.8 kg/hr 4.7 $/kg $ 436 $ 3,630,000 $ 0.18
NaOH 835 kg/hr 0.692 $/kg $ 578 $ 4,810,000 $ 0.24
Hydrogen 36.0 kg/hr 1.5 $/kg $54.0 $ 449,000 $ 0.02
Utilities Flow Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg)
Steam 107,000 kg/hr 0 $/kg $ - $ - $ -
Cooling Water 2,940,000 kg/hr 0.02 $/m3 $ 58.9 $ 490,000 $ 0.02
Chilled Water 500 kWh 4 $/GJ $ 7.20 $59,900 $ 0.00
Labour
Operators 15 employee $ 70,000 $/year $ 126 $1,050,000 $ 0.05
Maintenance 1 2% CAPEX $9,210,000 $/year $ 1,110 $ 9,210,000 $ 0.45
Consumables 1 1% CAPEX $4,600,000 $/year $553 $4,600,000 $ 0.23
Laboratory 1 1% CAPEX $4,600,000 $/year $ 553.30 $4,600,000 $ 0.23
OPEX
$ 3,470 $ 28,900,000 $ 1.43
SLD 1 20 year $23,000,000 $/yr $ 2,770 $ 23,000,000 $ 1.14
Property Tax 0
0 $/yr $ - $ - $ -
Insurance 1 0.5% FCI $2,300,000 $/yr $ 277 $2,300,000 $ 0.11
Interest
$41,200,000 $/yr $ 4,947.44 $41,200,000 $ 2.03
FC Total
$ 7,990 $ 66,500,000 $ 3.28
Administration,
marketing, distribution 10% TPC
$ 1,150 $9,540,000 $ 0.47
TPC
$ 12,600 $105,000,000 $ 5.18
Products Flow Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg xylitol)
Xylitol 2430 kg/hr 4.5 $/kg $ 10,953.86 $ 91,200,000 $ 4.50
Electricity 2680 kWh 5.72 c/kWh $ 153 $1,270,000 $ 0.06
164
Revenue
$ 11,100 $92,400,000 $ 4.56
Table D - 10: Hydrogenation BC Cash Flow Statement - Worst Case ($MM)
Year Capital Cost Revenue Operating Costs EBITDA Depreciation Interest GP Taxes Net Profit ATCF
0 -$460.0 $276.3 $0.0 -$184.2 $0.0 $0.0 $0.0 $0.0 -$184.2 -$184.2
1 $0.0 $46.2 $14.5 $31.8 $23.0 -$22.1 -$13.4 $0.0 -$13.4 $9.7
2 $0.0 $92.4 $28.9 $63.5 $23.0 -$20.6 $19.9 $5.0 $14.9 $38.0
3 $0.0 $92.4 $28.9 $63.5 $23.0 -$18.9 $21.6 $5.4 $16.2 $39.2
4 $0.0 $92.4 $28.9 $63.5 $23.0 -$17.1 $23.4 $5.8 $17.5 $40.5
5 $0.0 $92.4 $28.9 $63.5 $23.0 -$15.2 $25.3 $6.3 $19.0 $42.0
6 $0.0 $92.4 $28.9 $63.5 $23.0 -$13.2 $27.4 $6.8 $20.5 $43.5
7 $0.0 $92.4 $28.9 $63.5 $23.0 -$10.9 $29.6 $7.4 $22.2 $45.2
8 $0.0 $92.4 $28.9 $63.5 $23.0 -$8.5 $32.0 $8.0 $24.0 $47.0
9 $0.0 $92.4 $28.9 $63.5 $23.0 -$5.9 $34.6 $8.7 $26.0 $49.0
10 $0.0 $92.4 $28.9 $63.5 $23.0 -$3.0 $37.5 $9.4 $28.1 $51.1
11 $0.0 $92.4 $28.9 $63.5 $23.0 $0.0 $40.5 $10.1 $30.4 $53.4
12 $0.0 $92.4 $28.9 $63.5 $23.0 $0.0 $40.5 $10.1 $30.4 $53.4
13 $0.0 $92.4 $28.9 $63.5 $23.0 $0.0 $40.5 $10.1 $30.4 $53.4
14 $0.0 $92.4 $28.9 $63.5 $23.0 $0.0 $40.5 $10.1 $30.4 $53.4
15 $0.0 $92.4 $28.9 $63.5 $23.0 $0.0 $40.5 $10.1 $30.4 $53.4
16 $0.0 $92.4 $28.9 $63.5 $23.0 $0.0 $40.5 $10.1 $30.4 $53.4
17 $0.0 $92.4 $28.9 $63.5 $23.0 $0.0 $40.5 $10.1 $30.4 $53.4
18 $0.0 $92.4 $28.9 $63.5 $23.0 $0.0 $40.5 $10.1 $30.4 $53.4
19 $0.0 $92.4 $28.9 $63.5 $23.0 $0.0 $40.5 $10.1 $30.4 $53.4
20 $0.0 $92.4 $28.9 $63.5 $23.0 $0.0 $40.5 $10.1 $30.4 $53.4
165
Table D - 11: Fermentation 10% EC LT TVR Equipment List – Best Case
Component Name Component Type Description Material
Material
size factor Size Factor
Actual Size
factor Unit
Equipment
Cost
Scale
Factor
Units
Required Scaled Cost
BOILER ESTBSTM BOILER Field erected boiler unit CS 1 69387.76 69387.76 kg/hr $1,038,500 1.00 1.00 $1,038,500
CHILLER
ERU
MECHANICAL
Mechanical compress
refrigerator unit CS 1 499.26 499.26 kW $281,700 1.00 1.00 $281,700
COOLER
ECTWCOOLIN
G
Cooling tower, less pumps,
field assembly GALV 1 335.09 335.09 L/s $198,400 1.00 1.00 $198,400
DRYER ED SPRAY
Continuous spray drying
system CS 2.1 320.00 239.99 kg/hr $293,800 1.72 1.00 $504,400
CRYST1
ECRYBATCH
VAC Batch Vacuum Crystallizer SS304L 1 25.80 35.13 m3 $692,900 1.24 1.00 $860,100
CRYST2 ECRYOSLO Oslo growth type crystallizer CS 2.1 4171.86 4171.86 kg/hr $599,600 2.10 1.00 $1,259,200
HEX-CL3
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 19.89 19.89 m2 $17,700 1.00 1.00 $17,700
HEX-CL4
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 3.21 3.21 m2 $11,100 1.00 1.00 $11,100
HEX-DC1
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 2.53 2.53 m2 $11,100 1.00 1.00 $11,100
HEX-INT2
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 101.48 101.48 m2 $49,600 1.00 1.00 $49,600
HEX-MPH3
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 22.33 22.33 m2 $20,900 1.00 1.00 $20,900
HEX-MPH4
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 12.88 12.88 m2 $16,600 1.00 1.00 $16,600
HEX-SMB1
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 52.93 52.93 m2 $26,200 1.00 1.00 $26,200
HEX-SMB3 DHE TEMA EXCH
Fixed tube, float head, u-tube exchanger SS316 L 1 24.28 24.28 m2 $19,800 1.00 1.00 $19,800
HEX1-MP1
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 50.62 50.62 m2 $31,300 1.00 1.00 $31,300
HEX2MPU1
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 89.27 89.27 m2 $44,700 1.00 1.00 $44,700
HEX4-MP2
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 20.70 20.70 m2 $14,700 1.00 1.00 $14,700
HEX5-CL2
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 4.41 4.41 m2 $12,800 1.00 1.00 $12,800
SMB2PREH
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 125.84 125.84 m2 $46,500 1.00 1.00 $46,500
HEX-C1CE
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 284.89 284.89 m2 $99,300 1.00 1.00 $99,300
HEX-C2C2
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 99.68 99.68 m2 $37,700 1.00 1.00 $37,700
HEX-C3CC
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 89.02 89.02 m2 $36,700 1.00 1.00 $36,700
HEX-C4CC
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 87.61 87.61 m2 $36,600 1.00 1.00 $36,600
166
CENTRIFUGE
ECT BATCH
BOTM Auto batch filtering centrifuge SS316 L 1 1520.00 1520.00 mm $188,200 1.00 1.00 $188,200
FILTR1 EF LEAF WET Pressure-leaf wet filter SS316 L 1 4.70 4.7 m2 $41,300 1.00 1.00 $41,300
FILTR2 EF LEAF WET Pressure-leaf wet filter SS316 L 1 4.70 4.7 m3 $27,500 1.00 1.00 $27,500
SOFTENING DTW PACKED Packed tower SS316L 1 2.40 2.4 m $147,600 1.00 1.00 $147,600
BFWP1 DCP ANSI Standard ANSI single stage pump 316 SF 1 6.15 2.34 L/s $7,200 0.51 1.00 $3,700
BFWP2 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 5.43 2.74 L/s $6,500 0.62 1.00 $4,000
BFWP3 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 2.27 2.28 L/s $6,200 1.00 1.00 $6,200
BFWP4 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.81 0.80 L/s $6,200 0.99 1.00 $6,100
BFWP5 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.70 0.73 L/s $6,100 1.03 1.00 $6,300
BFWP6 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.64 0.64 L/s $6,100 1.00 1.00 $6,100
BFWP7 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.73 0.75 L/s $6,100 1.01 1.00 $6,200
BFWP8 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.08 0.09 L/s $6,100 1.04 1.00 $6,300
BFWP9 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.29 0.64 L/s $6,100 1.74 1.00 $10,600
C2CON1P1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 2.43 2.42 L/s $6,200 1.00 1.00 $6,200
C2CON2P1 DCP ANSI Standard ANSI single stage pump 316 SF 1 2.58 2.57 L/s $6,200 1.00 1.00 $6,200
C2CON3P1 DCP ANSI Standard ANSI single stage pump 316 SF 1 2.67 2.67 L/s $6,200 1.00 1.00 $6,200
C2CONP2 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 2.19 2.31 L/s $6,200 1.04 1.00 $6,400
C3CONP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 2.10 2.21 L/s $6,200 1.04 1.00 $6,400
C3CONP3 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 2.26 2.37 L/s $6,200 1.03 1.00 $6,400
C4CONP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 1.76 1.43 L/s $6,200 0.87 1.00 $5,400
C4CONP2 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 1.81 1.48 L/s $6,200 0.87 1.00 $5,400
C34CONP3 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 1.82 1.49 L/s $6,200 0.87 1.00 $5,400
CHWP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 1.61 1.79 L/s $6,200 1.08 1.00 $6,700
CHWP2 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 9.36 9.48 L/s $7,600 1.01 1.00 $7,700
CON1AP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 14.77 5.70 L/s $8,200 0.51 1.00 $4,200
CON1BP1 DCP ANSI Standard ANSI single stage pump 316 SF 1 15.31 5.91 L/s $8,200 0.51 1.00 $4,200
167
CON1CP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 15.97 6.07 L/s $8,300 0.51 1.00 $4,200
CON1DP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 16.09 6.28 L/s $8,300 0.52 1.00 $4,300
CWP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 354.46 171.34 L/s $18,800 0.60 1.00 $11,300
CWP2 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 57.63 59.63 L/s $12,600 1.02 1.00 $12,900
CWP3 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 2.42 2.48 L/s $6,200 1.02 1.00 $6,300
CWP5 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 51.43 53.08 L/s $12,200 1.02 1.00 $12,500
CWP6 DCP ANSI Standard ANSI single stage pump 316 SF 1 1.83 1.80 L/s $6,200 0.99 1.00 $6,100
CWP7 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 41.27 41.32 L/s $11,100 1.00 1.00 $11,100
CWP8 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 1.79 1.80 L/s $6,200 1.01 1.00 $6,200
CWP9 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 3.45 3.63 L/s $6,300 1.04 1.00 $6,500
PPUMP1
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 37.50 33.88 L/s $49,400 0.93 1.00 $46,000
PPUMP2
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 37.50 35.67 L/s $49,400 0.97 1.00 $47,700
PSMB1
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 11.46 11.68 L/s $22,100 1.01 1.00 $22,400
PSMB2
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 5.86 5.99 L/s $16,200 1.02 1.00 $16,400
PSMB3
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 3.81 3.74 L/s $15,100 0.99 1.00 $14,900
PUMPF
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 10.40 10.68 L/s $21,000 1.02 1.00 $21,400
EH REACTOR DAT MIXER
Agitated tank, enclosed,
jacketed SS316 L 1 4000 4000 m3 $4,361,200 1.00 2.00 $8,722,400
FERMENTER DAT REACTOR Agitated tank, enclosed, jacketed SS316 L 1 3,000.00 3,000.00 m3 $6,292,700 1.00 1.00 $6,292,700
SEED
FERMENTER DAT REACTOR
Agitated tank, enclosed,
jacketed SS316 L 1 185.58 185.58 m3 $1,618,700 1.00 1.00 $1,618,700
BFWCM1
DVT
CYLINDER Vertical process vessel SS316 1 3.30 3.30 m3 $33,300 1.00 1.00 $33,300
BFWCM2
DVT
CYLINDER Vertical process vessel SS316 1 3.17 3.17 m3 $28,800 1.00 1.00 $28,800
CCONM1
DVT
CYLINDER Vertical process vessel SS316 1 3.64 3.64 m3 $33,900 1.00 1.00 $33,900
CHMIX
DVT
CYLINDER Vertical process vessel SS316 1 3.38 3.38 m3 $33,400 1.00 1.00 $33,400
CWTM1
DVT
CYLINDER Vertical process vessel SS316 1 100.53 100.53 m3 $178,700 1.00 1.00 $178,700
DCONM1
DVT
CYLINDER Vertical process vessel SS316 1 9.25 9.25 m3 $50,000 1.00 1.00 $50,000
WASTEM1
DVT
CYLINDER Vertical process vessel SS316 1 18.13 18.13 m3 $64,500 1.00 1.00 $64,500
168
EVAP4M DAT MIXER
Agitated tank, enclosed,
jacketed SS316 L 1 6.11 6.11 m3 $105,400 1.00 1.00 $105,400
NaOH STORAGE
TOTE
EVT PLAST
TANK PLAST TANK FRP 1 7.30 7.30 m3 $14,600 1.00 1.00 $14,600
Enzyme Storage
Tank DVT STORAGE
Vertical storage vessel, flat
bottom SS316 1 3.69 3.69 m3 $18,900 1.00 1.00 $18,900
DAP Storage DVT STORAGE
Vertical storage vessel, flat
bottom SS316 1 0.22 0.22 m3 $9,000 1.00 1.00 $9,000
CSL Storage DVT STORAGE
Vertical storage vessel, flat
bottom SS316 1 2.99 2.99 m3 $17,300 1.00 1.00 $17,300
Turbine1
EEG TURBO
GEN Electrical Turbo-generator CS 1 2249.45 2249.45 kW $1,272,200 1.00 1.00 $1,272,200
Turbine2 EEG TURBO GEN Electrical Turbo-generator CS 1 2003.63 2003.63 kW $1,143,000 1.00 1.00 $1,143,000
Turbine3
EEG TURBO
GEN Electrical Turbo-generator CS 1 1781.65 1781.65 kW $1,026,800 1.00 1.00 $1,026,800
Turbine4
EEG TURBO
GEN Electrical Turbo-generator CS 1 1200.17 1200.17 kW $723,400 1.00 1.00 $723,400
Turbine5
EEG TURBO
GEN Electrical Turbo-generator CS 1 1026.87 1026.87 kW $632,600 1.00 1.00 $632,600
VP_Cryst1
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef1
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef2
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef3
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef4
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef5
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC2Ef1
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC2Ef2 EVP WATER SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC2Ef3
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC3Ef1
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC3Ef2
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC3Ef3
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC4Ef1
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC4Ef2
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC4Ef3
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
CONC1EF1
Falling film evap SS316L 1 142 526 L/min $1,700,000 2.50 1.00 $4,251,200
169
CONC1EF2
Falling film evap SS316L 1 142 536 L/min $1,700,000 2.54 1.00 $4,310,400
CONC1EF3
Falling film evap SS316L 1 142 169 L/min $1,700,000 1.13 1.00 $1,919,400
CONC1EF4
Falling film evap SS316L 1 142 181 L/min $1,700,000 1.19 1.00 $2,018,500
TVR1 EEJ SINGLE STG Steam-jet booster SS316L 1 190 586
CEPCI
1976 - 2011 $12,000 2.20 1.00 $26,400
CONC2EF1
Falling film evap SS316L 1 142 182 L/min $1,700,000 1.19 1.00 $2,021,800
CONC2EF2
Falling film evap SS316L 1 142 190 L/min $1,700,000 1.23 1.00 $2,086,200
CONC2EF3
Falling film evap SS316L 1 142 63 L/min $1,700,000 0.57 1.00 $962,700
TVR2
Steam-jet booster SS316L 1 190 586
CEPCI
1976 -
2011 $12,000 2.20 1.00 $26,400
CONC3EF1
Falling film evap SS316L 1 142 167 L/min $1,700,000 1.12 1.00 $1,905,000
CONC3EF2
Falling film evap SS316L 1 142 173 L/min $1,700,000 1.15 1.00 $1,949,300
CONC3EF3
Falling film evap SS316L 1 142 56 L/min $1,700,000 0.52 1.00 $887,700
TVR3
Steam-jet booster SS316L 1 190 586
CEPCI
1976 -
2011 $12,000 2.20 1.00 $26,400
CONC4EF1
Falling film evap SS316L 1 142 136 L/min $1,700,000 0.97 1.00 $1,648,200
CONC4EF2
Falling film evap SS316L 1 142 138 L/min $1,700,000 0.98 1.00 $1,670,100
CONC4EF3
Falling film evap SS316L 1 142 64 L/min $1,700,000 0.57 1.00 $974,300
TVR4
Steam-jet booster SS316L 1 190 586
CEPCI
1976 -
2011 $12,000 2.20 1.00 $26,400
SMB1
Chromatography Unit SS316L 1 29601 177719 kg/hr $4,400,000 3.51 1.00 $15,429,500
SMB2
Chromatography Unit SS316L 1 29601 85629 kg/hr $4,400,000 2.10 1.00 $9,254,900
SMB3
Chromatography Unit
1 29601 57080 kg/hr $4,400,000 1.58 1.00 $6,967,500
ANAEROBIC DIGESTION
1 1770005 1770005 tonne/yr $49,558,061 1.00 1.00 $49,558,100
Table D - 12: Fermentation 10% EC LT TVR OPEX and TPC Calculation List – Best Case
Chemicals Flow (kg/hr) Unit Cost ($/unit) Unit Cost ($/hr) Annualized
$/kg
xylitol
Enzymes 37.3 kg/hr 4.7 $/kg $175 $1,460,000 $0.07
NaOH 234 kg/hr 0.692 $/kg $162 $1,350,000 $0.07
170
DAP 9.68 kg/hr 0.254 $/kg $2.46 $20,400 $0.00
CSL 130 kg/hr 0.177 $/kg $23.0 $192,000 $0.01
Utilities Flow (kg/hr) Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg)
Steam 69,400 kg/hr 0 $/kg $ - $0 $0.00
Cooling Water 1,210,000 kg/hr 0.02 $/m3 $24.13 $201,000 $0.01
Chilled Water 499 kWh 4 $/GJ $7.19 $59,800 $0.00
Labour
Operators 15 employees $70,000 $/year $126 $1,050,000 $0.05
Maintenance 2% CAPEX $4,780,000 $/year $575 $4,780,000 $0.24
Consumables 1% CAPEX $2,390,000 $/year $287 $2,390,000 $0.12
Laboratory 1% CAPEX $2,390,000 $/year $287 $2,390,000 $0.12
OPEX $1,647 $13,700,000 $0.68
SLD 20 year $12,000,000 $/year $1,437 $12,000,000 $0.59
Property Tax $0 $/year $0 $0 $0.00
Insurance 0.5% FCI $1,200,000 $/year $144 $1,200,000 $0.06
Interest/Financing $21,400,000 $/year $2,570 $21,400,000 $1.06
FC Total $4,150 $34,500,000 $1.71
Administration, distribution,
and marketing ~10% TPC $580 $4,830,000 $0.24
TPC $6,380 $53,100,000 $2.62
Products Flow Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg)
Xylitol 2430 kg/hr 4.5 $/kg $11,000 $91,200,000 $4.50
Electricity 3270 kWh 5.72 c/kWh $187 $1,556,000 $0.08
Revenue $11,100 $92,700,000 $4.58
171
Table D - 13: Fermentation 10% EC LT TVR Cash Flow Statement – Best Case ($MM)
Year Capital Cost Revenue Operating Costs EBITDA Depreciation Interest GP Taxes Net Profit ATCF
0 -$239.0 $143.5 $0.0 -$95.7 $0.0 $0.0 $0.0 $0.0 -$95.7 -$95.7
1 $0.0 $46.4 $6.9 $39.5 $12.0 -$11.5 $16.1 $4.0 $12.0 $24.0
2 $0.0 $92.7 $13.7 $79.0 $12.0 -$10.7 $56.4 $14.1 $42.3 $54.2
3 $0.0 $92.7 $13.7 $79.0 $12.0 -$9.8 $57.2 $14.3 $42.9 $54.9
4 $0.0 $92.7 $13.7 $79.0 $12.0 -$8.9 $58.1 $14.5 $43.6 $55.6
5 $0.0 $92.7 $13.7 $79.0 $12.0 -$7.9 $59.1 $14.8 $44.4 $56.3
6 $0.0 $92.7 $13.7 $79.0 $12.0 -$6.8 $60.2 $15.1 $45.2 $57.1
7 $0.0 $92.7 $13.7 $79.0 $12.0 -$5.7 $61.4 $15.3 $46.0 $58.0
8 $0.0 $92.7 $13.7 $79.0 $12.0 -$4.4 $62.6 $15.7 $47.0 $58.9
9 $0.0 $92.7 $13.7 $79.0 $12.0 -$3.1 $64.0 $16.0 $48.0 $60.0
10 $0.0 $92.7 $13.7 $79.0 $12.0 -$1.6 $65.5 $16.4 $49.1 $61.1
11 $0.0 $92.7 $13.7 $79.0 $12.0 $0.0 $67.0 $16.8 $50.3 $62.2
12 $0.0 $92.7 $13.7 $79.0 $12.0 $0.0 $67.0 $16.8 $50.3 $62.2
13 $0.0 $92.7 $13.7 $79.0 $12.0 $0.0 $67.0 $16.8 $50.3 $62.2
14 $0.0 $92.7 $13.7 $79.0 $12.0 $0.0 $67.0 $16.8 $50.3 $62.2
15 $0.0 $92.7 $13.7 $79.0 $12.0 $0.0 $67.0 $16.8 $50.3 $62.2
16 $0.0 $92.7 $13.7 $79.0 $12.0 $0.0 $67.0 $16.8 $50.3 $62.2
17 $0.0 $92.7 $13.7 $79.0 $12.0 $0.0 $67.0 $16.8 $50.3 $62.2
18 $0.0 $92.7 $13.7 $79.0 $12.0 $0.0 $67.0 $16.8 $50.3 $62.2
19 $0.0 $92.7 $13.7 $79.0 $12.0 $0.0 $67.0 $16.8 $50.3 $62.2
20 $0.0 $92.7 $13.7 $79.0 $12.0 $0.0 $67.0 $16.8 $50.3 $62.2
172
Table D - 14: Fermentation 10% EC LT TVR Equipment List – Worst Case
Component
Name
Component
Type Description Material
Mate
rial facto
r
Size
Factor
Actual Size
factor
Worst Size
Factor Unit
Equipment
Cost
Scale
Factor
Units
Required Worst Cost
BOILER
ESTBSTM
BOILER Field erected boiler unit CS 1 69387 69387.76 167346.94 kg/hr $1,038,500 1.00 1.00 $1,923,300
CHILLER
ERU
MECHANICA
L
Mechanical compress
refrigerator unit CS 1 499.26 499.26 551.91 kW $281,700 1.00 1.00 $302,200
COOLER
ECTWCOOLIN
G
Cooling tower, less
pumps, field assembly GALV 1 335.09 335.09 556.76 L/s $198,400 1.00 1.00 $283,100
DRYER ED SPRAY
Continuous spray drying
system CS 2.1 320.00 239.99 239.99 kg/hr $293,800 1.72 1.00 $504,400
CRYST1
ECRYBATCH
VAC
Batch Vacuum
Crystallizer SS304L 1 25.80 35.13 37.95 m3 $692,900 1.24 1.00 $907,800
CRYST2 ECRYOSLO
Oslo growth type
crystallizer CS 2.1 4171 4171 4364 kg/hr $599,600 2.10 1.00 $1,299,600
HEX-CL3 DHE TEMA EXCH
Fixed tube, float head, u-tube exchanger SS316 L 1 19.89 19.89 22.32 m2 $17,700 1.00 1.00 $19,200
HEX-CL4
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 3.21 3.21 3.72 m2 $11,100 1.00 1.00 $12,300
HEX-DC1
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 2.53 2.53 2.53 m2 $11,100 1.00 1.00 $11,100
HEX-INT2
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 101.48 101.48 113.90 m2 $49,600 1.00 1.00 $53,800
HEX-MPH3
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 22.33 22.33 25.21 m2 $20,900 1.00 1.00 $22,800
HEX-MPH4
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 12.88 12.88 14.95 m2 $16,600 1.00 1.00 $18,400
HEX-SMB1
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 52.93 52.93 108.43 m2 $26,200 1.00 1.00 $43,300
HEX-SMB3
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 24.28 24.28 28.54 m2 $19,800 1.00 1.00 $22,200
HEX1-MP1
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 50.62 50.62 51.46 m2 $31,300 1.00 1.00 $31,700
HEX2MPU1
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 89.27 89.27 191.28 m2 $44,700 1.00 1.00 $76,200
HEX4-MP2
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 20.70 20.70 28.02 m2 $14,700 1.00 1.00 $18,200
HEX5-CL2 DHE TEMA EXCH
Fixed tube, float head, u-tube exchanger SS316 L 1 4.41 4.41 6.14 m2 $12,800 1.00 1.00 $16,100
SMB2PREH
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 125.84 125.84 167.27 m2 $46,500 1.00 1.00 $56,700
HEX-C1CE
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 284.89 284.89 601.34 m2 $99,300 1.00 1.00 $167,500
HEX-C2C2
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 99.68 99.68 141.69 m2 $37,700 1.00 1.00 $48,200
HEX-C3CC
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 89.02 89.02 99.77 m2 $36,700 1.00 1.00 $39,700
173
HEX-C4CC
DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 87.61 87.61 211.31 m2 $36,600 1.00 1.00 $67,800
CENTRIFUGE
ECT BATCH
BOTM
Auto batch filtering
centrifuge SS316 L 1 1520 1520 1520 mm $188,200 1.00 1.00 $188,200
FILTR1 EF LEAF WET Pressure-leaf wet filter SS316 L 1 4.70 4.70 7.755 m2 $41,300 1.00 1.00 $58,600
FILTR2 EF LEAF WET Pressure-leaf wet filter SS316 L 1 4.70 4.70 7.755 m3 $27,500 1.00 1.00 $39,000
SOFTENING DTW PACKED Packed tower SS316L 1 2.40 2.40 3.96 m $147,600 1.00 1.00 $209,600
BFWP1 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 6.15 2.34 3.86 L/s $7,200 0.51 1.00 $5,200
BFWP2 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 5.43 2.74 4.52 L/s $6,500 0.62 1.00 $5,700
BFWP3 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 2.27 2.28 3.77 L/s $6,200 1.00 1.00 $8,800
BFWP4 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 0.81 0.80 1.32 L/s $6,200 0.99 1.00 $8,700
BFWP5 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 0.70 0.73 1.21 L/s $6,100 1.03 1.00 $8,900
BFWP6 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 0.64 0.64 1.05 L/s $6,100 1.00 1.00 $8,700
BFWP7 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 0.73 0.75 1.23 L/s $6,100 1.01 1.00 $8,800
BFWP8 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 0.08 0.09 0.14 L/s $6,100 1.04 1.00 $9,000
BFWP9 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 0.29 0.64 1.06 L/s $6,100 1.74 1.00 $15,000
C2CON1P1 DCP ANSI Standard ANSI single stage pump 316 SF 1 2.43 2.42 3.99 L/s $6,200 1.00 1.00 $8,800
C2CON2P1 DCP ANSI Standard ANSI single stage pump 316 SF 1 2.58 2.57 4.23 L/s $6,200 1.00 1.00 $8,800
C2CON3P1 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 2.67 2.67 4.40 L/s $6,200 1.00 1.00 $8,800
C2CONP2 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 2.19 2.31 3.80 L/s $6,200 1.04 1.00 $9,100
C3CONP1 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 2.10 2.21 3.65 L/s $6,200 1.04 1.00 $9,100
C3CONP3 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 2.26 2.37 3.92 L/s $6,200 1.03 1.00 $9,100
C4CONP1 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 1.76 1.43 2.37 L/s $6,200 0.87 1.00 $7,600
C4CONP2 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 1.81 1.48 2.44 L/s $6,200 0.87 1.00 $7,600
C34CONP3 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 1.82 1.49 2.46 L/s $6,200 0.87 1.00 $7,700
CHWP1 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 1.61 1.79 2.95 L/s $6,200 1.08 1.00 $9,500
CHWP2 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 9.36 9.48 15.64 L/s $7,600 1.01 1.00 $10,900
CON1AP1 DCP ANSI Standard ANSI single stage pump 316 SF 1 14.77 5.70 9.41 L/s $8,200 0.51 1.00 $6,000
174
CON1BP1 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 15.31 5.91 9.75 L/s $8,200 0.51 1.00 $6,000
CON1CP1 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 15.97 6.07 10.02 L/s $8,300 0.51 1.00 $6,000
CON1DP1 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 16.09 6.28 10.36 L/s $8,300 0.52 1.00 $6,100
CWP1 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 354.46 171.34 282.71 L/s $18,800 0.60 1.00 $16,000
CWP2 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 57.63 59.63 98.38 L/s $12,600 1.02 1.00 $18,300
CWP3 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 2.42 2.48 4.09 L/s $6,200 1.02 1.00 $9,000
CWP5 DCP ANSI Standard ANSI single stage pump 316 SF 1 51.43 53.08 87.59 L/s $12,200 1.02 1.00 $17,700
CWP6 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 1.83 1.80 2.97 L/s $6,200 0.99 1.00 $8,700
CWP7 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 41.27 41.32 68.19 L/s $11,100 1.00 1.00 $15,800
CWP8 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 1.79 1.80 2.97 L/s $6,200 1.01 1.00 $8,900
CWP9 DCP ANSI
Standard ANSI single
stage pump 316 SF 1 3.45 3.63 5.98 L/s $6,300 1.04 1.00 $9,300
PPUMP1
EP
DIAPHRAGM
Diaphragm pump, TFE
type SS316 L 1 37.50 33.88 55.90 L/s $49,400 0.93 1.00 $65,300
PPUMP2
EP
DIAPHRAGM
Diaphragm pump, TFE
type SS316 L 1 37.50 35.67 58.86 L/s $49,400 0.97 1.00 $67,700
PSMB1
EP
DIAPHRAGM
Diaphragm pump, TFE
type SS316 L 1 11.46 11.68 19.28 L/s $22,100 1.01 1.00 $31,800
PSMB2
EP
DIAPHRAGM
Diaphragm pump, TFE
type SS316 L 1 5.86 5.99 9.89 L/s $16,200 1.02 1.00 $23,300
PSMB3
EP
DIAPHRAGM
Diaphragm pump, TFE
type SS316 L 1 3.81 3.74 6.17 L/s $15,100 0.99 1.00 $21,200
PUMPF
EP
DIAPHRAGM
Diaphragm pump, TFE
type SS316 L 1 10.40 10.68 17.61 L/s $21,000 1.02 1.00 $30,400
EH REACTOR DAT MIXER Agitated tank, enclosed, jacketed SS316 L 1 4000 4000 4000 m3 $4,361,200 1.00 4.00 $17,444,800
FERMENTER
DAT
REACTOR
Agitated tank, enclosed,
jacketed SS316 L 1 3000 3,000 3,000.00 m3 $6,292,700 1.00 1.00 $6,292,700
SEED
FERMENTER
DAT
REACTOR
Agitated tank, enclosed,
jacketed SS316 L 1 185.58 185.58 315.52 m3 $1,618,700 1.00 1.00 $2,347,000
BFWCM1
DVT
CYLINDER Vertical process vessel SS316 1 3.30 3.30 6.57 m3 $33,300 1.00 1.00 $53,900
BFWCM2
DVT
CYLINDER Vertical process vessel SS316 1 3.17 3.17 5.81 m3 $28,800 1.00 1.00 $44,000
CCONM1
DVT
CYLINDER Vertical process vessel SS316 1 3.64 3.64 4.74 m3 $33,900 1.00 1.00 $40,800
CHMIX
DVT
CYLINDER Vertical process vessel SS316 1 3.38 3.38 3.73 m3 $33,400 1.00 1.00 $35,800
CWTM1
DVT
CYLINDER Vertical process vessel SS316 1 100.53 100.53 167.03 m3 $178,700 1.00 1.00 $255,000
DCONM1
DVT
CYLINDER Vertical process vessel SS316 1 9.25 9.25 17.64 m3 $50,000 1.00 1.00 $78,500
175
WASTEM1
DVT
CYLINDER Vertical process vessel SS316 1 18.13 18.13 35.26 m3 $64,500 1.00 1.00 $102,800
EVAP4M DAT MIXER
Agitated tank, enclosed,
jacketed SS316 L 1 6.11 6.11 7.13 m3 $105,400 1.00 1.00 $117,400
NaOH
STORAGE
TOTE
EVT PLAST
TANK PLAST TANK FRP 1 7.30 7.30 15.30 m3 $14,600 1.00 1.00 $24,500
Enzyme Storage
Tank
DVT
STORAGE
Vertical storage vessel,
flat bottom SS316 1 3.69 3.69 9.30 m3 $18,900 1.00 1.00 $36,100
DAP Storage
DVT
STORAGE
Vertical storage vessel,
flat bottom SS316 1 0.22 0.22 0.48 m3 $9,000 1.00 1.00 $15,700
CSL Storage DVT STORAGE
Vertical storage vessel, flat bottom SS316 1 2.99 2.99 6.77 m3 $17,300 1.00 1.00 $30,700
Turbine1
EEG TURBO
GEN
Electrical Turbo-
generator CS 1
2249.4
5 2249.45 5425.14 kW $1,272,200 1.00 1.00 $2,356,100
Turbine2
EEG TURBO
GEN
Electrical Turbo-
generator CS 1
2003.6
3 2003.63 4832.29 kW $1,143,000 1.00 1.00 $2,116,800
Turbine3
EEG TURBO
GEN
Electrical Turbo-
generator CS 1
1781.6
5 1781.65 4296.92 kW $1,026,800 1.00 1.00 $1,901,600
Turbine4
EEG TURBO
GEN
Electrical Turbo-
generator CS 1
1200.1
7 1200.17 2894.53 kW $723,400 1.00 1.00 $1,339,700
Turbine5
EEG TURBO
GEN
Electrical Turbo-
generator CS 1
1026.8
7 1026.87 3214.29 kW $632,600 1.00 1.00 $1,406,100
VP_Cryst1
EVP WATER
SEAL
Water-sealed vacuum
pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef1
EVP WATER
SEAL
Water-sealed vacuum
pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef2
EVP WATER
SEAL
Water-sealed vacuum
pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef3
EVP WATER
SEAL
Water-sealed vacuum
pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef4 EVP WATER SEAL
Water-sealed vacuum pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef5 EVP WATER SEAL
Water-sealed vacuum pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC2Ef1
EVP WATER
SEAL
Water-sealed vacuum
pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC2Ef2
EVP WATER
SEAL
Water-sealed vacuum
pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC2Ef3
EVP WATER
SEAL
Water-sealed vacuum
pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC3Ef1
EVP WATER
SEAL
Water-sealed vacuum
pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC3Ef2
EVP WATER
SEAL
Water-sealed vacuum
pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC3Ef3
EVP WATER
SEAL
Water-sealed vacuum
pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC4Ef1
EVP WATER
SEAL
Water-sealed vacuum
pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC4Ef2
EVP WATER
SEAL
Water-sealed vacuum
pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
176
VP_CONC4Ef3
EVP WATER
SEAL
Water-sealed vacuum
pump SS316L 1 55.00 55 55 m3/h $24,500 1.00 1.00 $24,500
CONC1EF1
Falling film evap SS316L 1 142.00 525.96 1114 L/min $1,700,000 2.50 1.00 $7,189,000
CONC1EF2
Falling film evap SS316L 1 142.00 536.45 1136 L/min $1,700,000 2.54 1.00 $7,287,300
CONC1EF3
Falling film evap SS316L 1 142.00 168.89 357 L/min $1,700,000 1.13 1.00 $3,242,800
CONC1EF4
Falling film evap SS316L 1 142.00 181.48 383 L/min $1,700,000 1.19 1.00 $3,406,500
TVR1 EEJ SINGLE STG Steam-jet booster SS316L 1 190.00 585.70 586
CEPCI
1976 - 2011 $12,000 2.20 1.00 $26,400
CONC2EF1
Falling film evap SS316L 1 142.00 181.91 259 L/min $1,700,000 1.19 1.00 $2,587,300
CONC2EF2
Falling film evap SS316L 1 142.00 190.24 270 L/min $1,700,000 1.23 1.00 $2,668,400
CONC2EF3
Falling film evap SS316L 1 142.00 63.02 89 L/min $1,700,000 0.57 1.00 $1,229,300
TVR2
Steam-jet booster SS316L 1 190.00 585.70 586
CEPCI
1976 -
2011 $12,000 2.20 1.00 $26,400
CONC3EF1
Falling film evap SS316L 1 142.00 167.09 186 L/min $1,700,000 1.12 1.00 $2,056,000
CONC3EF2
Falling film evap SS316L 1 142.00 172.66 193 L/min $1,700,000 1.15 1.00 $2,106,600
CONC3EF3
Falling film evap SS316L 1 142.00 56.13 63 L/min $1,700,000 0.52 1.00 $961,700
TVR3
Steam-jet booster SS316L 1 190.00 585.70 586
CEPCI
1976 -
2011 $12,000 2.20 1.00 $26,400
CONC4EF1
Falling film evap SS316L 1 142.00 135.86 130 L/min $1,700,000 0.97 1.00 $1,596,800
CONC4EF2
Falling film evap SS316L 1 142.00 138.44 133 L/min $1,700,000 0.98 1.00 $1,621,400
CONC4EF3
Falling film evap SS316L 1 142.00 64.11 41 L/min $1,700,000 0.57 1.00 $714,800
TVR4
Steam-jet booster SS316L 1 190.00 585.70 586
CEPCI 1976 -
2011 $12,000 2.20 1.00 $26,400
SMB1
Chromatography Unit SS316L 1
29601.
00 177718.53 362714 kg/hr $4,400,000 3.51 1.00 $25,423,400
SMB2
Chromatography Unit SS316L 1
29601.
00 85628.51 119350 kg/hr $4,400,000 2.10 1.00 $11,676,500
SMB3
Chromatography Unit
1
29601.
00 57080.12 67094 kg/hr $4,400,000 1.58 1.00 $7,802,200
ANAEROBIC DIGESTION
1
348036
1.01 3480361.01 3480361
tonnes/y
r $72,394,407 1.00 1.00 $72,394,400
177
Table D - 15: Fermentation 10% EC LT TVR OPEX and TPC Calculation List – Worst Case
Chemicals Flow (kg/hr) Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg
xylitol)
Enzymes 78.5 kg/hr 4.7 $/kg $369 $3,070,000 $0.15
NaOH 490 kg/hr 0.692 $/kg $340 $2,830,000 $0.14
DAP 20.41 kg/hr 0.254 $/kg $5.16 $43,000 $0.00
CSL 273.8 kg/hr 0.177 $/kg $48.4 $403,000 $0.02
Utilities Flow Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg)
Steam 167,000 kg/hr 0 $/kg $ - $0 $0.00
Cooling Water 2,000,000 kg/hr 0.02 $/m3 $40.09 $334,000 $0.02
Chilled Water 552 kWh 4 $/GJ $7.95 $66,100 $0.00
Operators 15 employees $70,000 $/year $126 $1,050,000 $0.05
Maintenance 2% CAPEX $6,950,000 $/year $835 $6,950,000 $0.34
Consumables 1% CAPEX $3,480,000 $/year $418 $3,480,000 $0.17
Laboratory 1% CAPEX $3,480,000 $/year $418 $3,480,000 $0.17
OPEX $2,560 $21,300,000 $1.05
SLD 20 year $17,400,000 $/year $2,088 $17,400,000 $0.86
Property Tax $0 $/year $0 $0 $0.00
Insurance 0.5% FCI $1,740,000 $/year $209 $1,740,000 $0.09
Interest/Financing $31,100,000 $/year $3,730 $31,100,000 $1.53
FC Total $6,030 $50,200,000 $2.48
Administration,
distribution, and marketing ~10% TPC $859 $7,150,000 $0.35
TPC $9,450 $78,600,000 $3.88
Products Flow Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg)
Xylitol 2,430 kg/hr 4.5 $/kg $11,000 $92,000,000 $4.50
Electricity 11,400 kWh/hr 5.72 c/kWh $651 $5,42,000 $0.27
Revenue $11,600 $96,600,000 $4.77
178
Table D - 16: Fermentation 10% EC LT TVR Cash Flow Statement – Worst Case ($MM)
Year Capital Cost Revenue Operating Costs EBITDA Depreciation Interest GP Taxes Net Profit ATCF
0 -$348.0 $208.5 $0.0 -$139.0 $0.0 $0.0 $0.0 $0.0 -$139.0 -$139.0
1 $0.0 $48.3 $10.6 $37.6 $17.4 -$16.7 $3.6 $0.9 $2.7 $20.1
2 $0.0 $96.6 $21.3 $75.3 $17.4 -$15.5 $42.4 $10.6 $31.8 $49.2
3 $0.0 $96.6 $21.3 $75.3 $17.4 -$14.3 $43.6 $10.9 $32.7 $50.1
4 $0.0 $96.6 $21.3 $75.3 $17.4 -$12.9 $45.0 $11.2 $33.7 $51.1
5 $0.0 $96.6 $21.3 $75.3 $17.4 -$11.5 $46.4 $11.6 $34.8 $52.2
6 $0.0 $96.6 $21.3 $75.3 $17.4 -$9.9 $48.0 $12.0 $36.0 $53.4
7 $0.0 $96.6 $21.3 $75.3 $17.4 -$8.2 $49.7 $12.4 $37.3 $54.6
8 $0.0 $96.6 $21.3 $75.3 $17.4 -$6.4 $51.5 $12.9 $38.6 $56.0
9 $0.0 $96.6 $21.3 $75.3 $17.4 -$4.4 $53.5 $13.4 $40.1 $57.5
10 $0.0 $96.6 $21.3 $75.3 $17.4 -$2.3 $55.6 $13.9 $41.7 $59.1
11 $0.0 $96.6 $21.3 $75.3 $17.4 $0.0 $57.9 $14.5 $43.4 $60.8
12 $0.0 $96.6 $21.3 $75.3 $17.4 $0.0 $57.9 $14.5 $43.4 $60.8
13 $0.0 $96.6 $21.3 $75.3 $17.4 $0.0 $57.9 $14.5 $43.4 $60.8
14 $0.0 $96.6 $21.3 $75.3 $17.4 $0.0 $57.9 $14.5 $43.4 $60.8
15 $0.0 $96.6 $21.3 $75.3 $17.4 $0.0 $57.9 $14.5 $43.4 $60.8
16 $0.0 $96.6 $21.3 $75.3 $17.4 $0.0 $57.9 $14.5 $43.4 $60.8
17 $0.0 $96.6 $21.3 $75.3 $17.4 $0.0 $57.9 $14.5 $43.4 $60.8
18 $0.0 $96.6 $21.3 $75.3 $17.4 $0.0 $57.9 $14.5 $43.4 $60.8
19 $0.0 $96.6 $21.3 $75.3 $17.4 $0.0 $57.9 $14.5 $43.4 $60.8
20 $0.0 $96.6 $21.3 $75.3 $17.4 $0.0 $57.9 $14.5 $43.4 $60.8
179
Table D - 17: Fermentation 10% EC HT TVR Equipment List – Best Case
Component Name Component Type Description Material
Material
factor
Size
Factor
Actual Size
factor Unit Equipment Cost
Scale
Factor
Units
Required Scaled Cost
BOILER
ESTBSTM
BOILER Field erected boiler unit CS 1 48571.43 48571.43 kg/hr $758,000 1.00 1.00 $758,000
CHILLER
ERU
MECHANICAL
Mechanical compress
refrigerator unit CS 1 1750.00 1831.16 kW $828,500 1.03 1.00 $855,200
COOLER ECTWCOOLING
Cooling tower, less pumps,
field assembly GALV 1 196.99 196.99 L/s $145,000 1.00 1.00 $145,000
DRYER ED SPRAY
Continuous spray drying
system CS 2.1 320.00 234.02 kg/hr $293,800 1.69 1.00 $495,600
CRYST1
ECRYBATCH
VAC Batch Vacuum Crystallizer SS304L 1 25.80 36.61 m3 $692,900 1.28 1.00 $885,300
CRYST2 ECRYOSLO Oslo growth type crystallizer CS 2.1 4263.13 4263.13 kg/hr $610,100 2.10 1.00 $1,281,200
HEX-CL3
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 74.49 74.49 m2 $30,600 1.00 1.00 $30,600
HEX-CL4
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 5.24 5.24 m2 $13,000 1.00 1.00 $13,000
HEX-DC1 DHE TEMA EXCH
Fixed tube, float head, u-tube exchanger SS316 L 1 2.47 2.47 m2 $11,000 1.00 1.00 $11,000
HEX-INT1
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 47.71 47.71 m2 $30,600 1.00 1.00 $30,600
HEX-MPH3
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 79.45 79.45 m2 $37,300 1.00 1.00 $37,300
HEX-MPH4
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 13.89 13.89 m2 $15,800 1.00 1.00 $15,800
HEX-SMB3
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 28.68 28.68 m2 $20,100 1.00 1.00 $20,100
HEX-C1CE
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 256.85 256.85 m2 $91,500 1.00 1.00 $91,500
HEX-C2CC
DHE TEMA
EXCH
Fixed tube, float head, u-tube
exchanger SS316 L 1 72.39 72.39 m2 $30,400 1.00 1.00 $30,400
CENTRIFUGE
ECT BATCH
BOTM Auto batch filtering centrifuge SS316 L 1 1520.00 1520.00 mm $188,200 1.00 1.00 $188,200
FILTR1 EF LEAF WET Pressure-leaf wet filter SS316 L 1 4.70 4.70 m2 $41,300 1.00 1.00 $41,300
FILTR2 EF LEAF WET Pressure-leaf wet filter SS316 L 1 4.70 4.70 m3 $27,500 1.00 1.00 $27,500
SOFTENING DTW PACKED Packed tower SS316L 1 2.40 2.40 m $147,600 1.00 1.00 $147,600
BFWP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 2.57 2.57 L/s $6,200 1.00 1.00 $6,200
BFWP2 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 2.86 2.86 L/s $6,200 1.00 1.00 $6,200
BFWP3 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.54 0.54 L/s $6,100 1.00 1.00 $6,100
180
BFWP4 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 1.24 1.24 L/s $6,200 1.00 1.00 $6,200
BFWP5 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 0.09 0.09 L/s $6,100 1.00 1.00 $6,100
BFWP6 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 2.44 2.44 L/s $6,200 1.00 1.00 $6,200
BFWP7 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 4.75 4.75 L/s $6,400 1.00 1.00 $6,400
C1CONP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 8.22 8.22 L/s $7,500 1.00 1.00 $7,500
C1CONP2 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 8.33 8.33 L/s $7,500 1.00 1.00 $7,500
C1CONP3 DCP ANSI Standard ANSI single stage pump 316 SF 1 2.59 2.59 L/s $6,200 1.00 1.00 $6,200
C1CONP2 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 2.72 2.72 L/s $6,200 1.00 1.00 $6,200
CHWP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 1.63 1.63 L/s $6,200 1.00 1.00 $6,200
CHWP2 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 39.58 39.58 L/s $10,900 1.00 1.00 $10,900
C2CONP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 2.26 2.26 L/s $6,200 1.00 1.00 $6,200
C2CONP2 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 2.31 2.31 L/s $6,200 1.00 1.00 $6,200
C2CONP3 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 1.07 1.07 L/s $6,200 1.00 1.00 $6,200
CWP1 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 125.00 153.74 L/s $18,800 1.16 1.00 $21,700
CWP2 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 35.64 35.64 L/s $10,300 1.00 1.00 $10,300
CWP3 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 2.94 2.94 L/s $6,200 1.00 1.00 $6,200
CWP4 DCP ANSI
Standard ANSI single stage
pump 316 SF 1 1.81 1.81 L/s $6,200 1.00 1.00 $6,200
CWP5 DCP ANSI Standard ANSI single stage pump 316 SF 1 3.54 3.54 L/s $6,300 1.00 1.00 $6,300
PPUMP1
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 28.28 28.28 L/s $39,200 1.00 1.00 $39,200
PPUMP2
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 29.79 29.79 L/s $40,900 1.00 1.00 $40,900
PSMB3
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 6.16 6.16 L/s $16,600 1.00 1.00 $16,600
PUMPF
EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 28.76 28.76 L/s $39,700 1.00 1.00 $39,700
EH REACTOR DAT MIXER
Agitated tank, enclosed,
jacketed SS316 L 1 4000.00 4000.00 m3 $4,361,200 1.00 2.00 $8,722,400
FERMENTER DAT REACTOR
Agitated tank, enclosed,
jacketed SS316 L 1 3000.00 3000.00 m3 $6,292,700 1.00 3.00 $18,878,100
SEED
FERMENTER DAT REACTOR
Agitated tank, enclosed,
jacketed SS316 L 1 516.66 774.98 m3 $1,970,300 1.33 1.00 $2,617,000
BFWCM1 DVT CYLINDER Vertical process vessel SS316 1 2.19 2.19 m3 $30,700 1.00 1.00 $30,700
181
BFWCM2 DVT CYLINDER Vertical process vessel SS316 1 2.15 2.15 m3 $30,600 1.00 1.00 $30,600
CCONM1 DVT CYLINDER Vertical process vessel SS316 1 1.41 1.41 m3 $24,200 1.00 1.00 $24,200
CHMIX DVT CYLINDER Vertical process vessel SS316 1 12.37 12.37 m3 $53,100 1.00 1.00 $53,100
CWTM1 DVT CYLINDER Vertical process vessel SS316 1 59.30 59.30 m3 $138,100 1.00 1.00 $138,100
DCONM1 DVT CYLINDER Vertical process vessel SS316 1 6.73 6.73 m3 $40,300 1.00 1.00 $40,300
WASTEM1 DVT CYLINDER Vertical process vessel SS316 1 7.01 7.01 m3 $40,700 1.00 1.00 $40,700
EVAP2M DAT MIXER
Agitated tank, enclosed,
jacketed SS316 L 1 6.42 6.42 m3 $106,900 1.00 1.00 $106,900
NaOH STORAGE
TOTE
EVT PLAST
TANK PLAST TANK FRP 1 6.09 6.09 m3 $13,300 1.00 1.00 $13,300
Enzyme Storage
Tank DVT STORAGE
Vertical storage vessel, flat
bottom SS316 1 3.69 3.69 m3 $18,900 1.00 1.00 $18,900
DAP Storage DVT STORAGE
Vertical storage vessel, flat
bottom SS316 1 0.19 0.19 m3 $9,000 1.00 1.00 $9,000
CSL Storage DVT STORAGE
Vertical storage vessel, flat
bottom SS316 1 3.06 3.06 m3 $17,400 1.00 1.00 $17,400
Turbine1
EEG TURBO
GEN Electrical Turbo-generator CS 1 1574.61 1574.61 kW $918,700 1.00 1.00 $918,700
Turbine2 EEG TURBO GEN Electrical Turbo-generator CS 1 1402.54 1402.54 kW $828,900 1.00 1.00 $828,900
Turbine3
EEG TURBO
GEN Electrical Turbo-generator CS 1 1247.15 1247.15 kW $747,900 1.00 1.00 $747,900
Turbine4
EEG TURBO
GEN Electrical Turbo-generator CS 1 840.12 840.12 kW $534,300 1.00 1.00 $534,300
Turbine5
EEG TURBO
GEN Electrical Turbo-generator CS 1 800.00 795.28 kW $513,000 1.00 1.00 $510,900
VP_Cryst1
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef1
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef2
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef3
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef4
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC2Ef1
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC2Ef2
EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
VP_CONC2Ef3 EVP WATER SEAL Water-sealed vacuum pump SS316L 1 55 55 m3/h $24,500 1.00 1.00 $24,500
CONC1EF1
Falling film evap
142 493 L/min $1,700,000 2.39 1.00 $4,063,700
CONC1EF2
Falling film evap
142 500 L/min $1,700,000 2.41 1.00 $4,103,700
CONC1EF3
Falling film evap
142 155 L/min $1,700,000 1.07 1.00 $1,810,900
182
CONC1EF4
Falling film evap
142 163 L/min $1,700,000 1.10 1.00 $1,874,700
TVR1
EEJ SINGLE
STG Steam-jet booster SS316L
190 586
CEPCI 1976
- 2011 $12,000 2.20 1.00 $26,400
CONC2EF1
Falling film evap
142 136 L/min $1,700,000 0.97 1.00 $1,648,200
CONC2EF2
Falling film evap
142 138 L/min $1,700,000 0.98 1.00 $1,670,100
CONC2EF3
Falling film evap
142 64 L/min $1,700,000 0.57 1.00 $974,300
TVR2
Steam-jet booster
190 586
CEPCI 1976
- 2011 $12,000 2.20 1.00 $26,400
SMB3
Chromatography Unit
29601 95933 kg/hr $4,400,000 2.28 1.00 $10,021,100
ANAEROBIC DIGESTION
1 694480 694480 tonne/yr $29,334,238 1.00 1.00 $29,334,200
Table D - 18: Fermentation 10% EC HT TVR OPEX and TPC Calculation List – Best Case
Chemicals Flow (kg/hr) Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg xylitol)
Enzymes 31 kg/hr 4.7 $/kg $146 $1,220,000 $0.06
NaOH 195 kg/hr 0.692 $/kg $135 $1,120,000 $0.06
DAP 8.08 kg/hr 0.254 $/kg $2.05 $17,100 $0.00
CSL 129 kg/hr 0.177 $/kg $22.8 $190,000 $0.01
Utilities Flow (kg/hr) Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg)
Steam 48,600 kg/hr 0 $/kg $ - $0 $0.00
Cooling Water 709,000 kg/hr 0.02 $/m3 $14.2 $118,000 $0.01
Chilled Water 1,830 kWh 4 $/GJ $26.4 $219,000 $0.01
Labour
Operators 15 employees $70,000 $/year $126 $1,050,000 $0.05
Maintenance 2% CAPEX $3,490,000 $/year $420 $3,490,000 $0.17
Consumables 1% CAPEX $1,750,000 $/year $210 $1,750,000 $0.09
Laboratory 1% CAPEX $1,750,000 $/year $210 $1,750,000 $0.09
OPEX $1,290 $10,700,000 $0.53
SLD 20 year $8,740,000 $/year $1,050 $8,740,000 $0.43
Property Tax $0 $/year $0 $0 $0.00
183
Insurance 0.5% FCI $874,000 $/year $105 $874,000 $0.04
Interest/Financing $15,600,000 $/year $1,880 $15,600,000 $0.77
FC Total $3,030 $25,200,000 $1.25
Administration, distribution, and
marketing
~10% TPC $432 $3,600,000 $0.18
TPC $4,760 $39,600,000 $1.95
Products Flow Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg)
Xylitol 2,430 kg/hr 4.5 $/kg $11,000 $91,200,000 $4.50
Electricity 2,300 kWh 5.72 c/kWh $132 $1,100,000 $0.05
Revenue $11,100 $92,300,000 $4.55
Table D - 19: Fermentation 10% EC HT TVR Cash Flow Statement – Best Case ($MM)
Year CAPEX Revenue OPEX EBITDA SLD Interest Gross Profit Taxes Net Profit ATCF
0 -$175.0 $104.8 $0.00 -$69.9 $0.00 $0.00 $0.00 $0.00 -$69.9 -$69.9
1 $0.0 $46.1 $5.40 $40.8 $8.70 -$8.40 $23.6 $5.90 $17.7 $26.5
2 $0.0 $92.3 $10.7 $81.5 $8.70 -$7.80 $65.0 $16.2 $48.7 $57.5
3 $0.0 $92.3 $10.7 $81.5 $8.70 -$7.20 $65.6 $16.4 $49.2 $57.9
4 $0.0 $92.3 $10.7 $81.5 $8.70 -$6.50 $66.3 $16.6 $49.7 $58.4
5 $0.0 $92.3 $10.7 $81.5 $8.70 -$5.80 $67.0 $16.8 $50.3 $59.0
6 $0.0 $92.3 $10.7 $81.5 $8.70 -$5.00 $67.8 $16.9 $50.8 $59.6
7 $0.0 $92.3 $10.7 $81.5 $8.70 -$4.10 $68.6 $17.2 $51.5 $60.2
8 $0.0 $92.3 $10.7 $81.5 $8.70 -$3.20 $69.6 $17.4 $52.2 $60.9
9 $0.0 $92.3 $10.7 $81.5 $8.70 -$2.20 $70.6 $17.6 $52.9 $61.7
10 $0.0 $92.3 $10.7 $81.5 $8.70 -$1.20 $71.6 $17.9 $53.7 $62.5
11 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
12 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
13 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
14 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
184
15 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
16 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
17 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
18 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
19 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
20 $0.0 $92.3 $10.7 $81.5 $8.70 $0.00 $72.8 $18.2 $54.6 $63.3
Table D -20: Fermentation 10% EC HT TVR Equipment List – Worst Case
Component
Name
Component
Type Description Material
Material
factor
Size
Factor
Actual Size
factor
Worst Size
Factor Unit
Equipment
Cost
Scale
Factor
Units
Required Worst Cost
BOILER ESTBSTM BOILER
Field erected boiler unit CS 1 48571.43
48571.43 88776.51 kg/hr $758,000 1.00 1.00 $1,156,100
CHILLER
ERU
MECHANICA
L
Mechanical compress
refrigerator unit CS 1 1750.00 1831.16 2950.66 kW $828,500 1.03 1.00 $1,194,300
COOLER ECTWCOOLI
NG
Cooling tower, less pumps,
field assembly GALV 1 196.99 196.99 304.18 L/s $145,000 1.00 1.00 $196,500
DRYER ED SPRAY Continuous spray drying
system CS 2.1 320.00 234.02 243.65 kg/hr $293,800 1.69 1.00 $509,800
CRYST1 ECRYBATCH
VAC Batch Vacuum Crystallizer SS304L 1 25.80 36.61 37.06 m3 $692,900 1.28 1.00 $892,900
CRYST2 ECRYOSLO Oslo growth type crystallizer CS 2.1 4263.13 4263.13 4291.34 kg/hr $610,100 2.10 1.00 $1,287,100
HEX-CL3 DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 74.49 74.49 121.97 m2 $30,600 1.00 1.00 $43,200
HEX-CL4 DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 5.24 5.24 7.17 m2 $13,000 1.00 1.00 $16,200
HEX-DC1 DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 2.47 2.47 2.57 m2 $11,000 1.00 1.00 $11,300
HEX-INT1 DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 47.71 47.71 78.07 m2 $30,600 1.00 1.00 $43,200
HEX-MPH3 DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 79.45 79.45 129.70 m2 $37,300 1.00 1.00 $52,600
HEX-MPH4 DHE TEMA EXCH
Fixed tube, float head, u-tube exchanger
SS316 L 1 13.89 13.89 14.18 m2 $15,800 1.00 1.00 $16,000
HEX-SMB3 DHE TEMA EXCH
Fixed tube, float head, u-tube exchanger
SS316 L 1 28.68 28.68 39.45 m2 $20,100 1.00 1.00 $25,100
HEX-C1CE DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 256.85 256.85 431.46 m2 $91,500 1.00 1.00 $131,600
HEX-C2CC DHE TEMA
EXCH
Fixed tube, float head, u-
tube exchanger SS316 L 1 72.39 72.39 192.41 m2 $30,400 1.00 1.00 $60,300
185
CENTRIFUGE ECT BATCH
BOTM
Auto batch filtering
centrifuge SS316 L 1 1520.00 1520.00 1520.00 mm $188,200 1.00 1.00 $188,200
FILTR1 EF LEAF
WET Pressure-leaf wet filter SS316 L 1 4.70 4.70 10.00 m2 $41,300 1.00 1.00 $70,100
FILTR2 EF LEAF
WET Pressure-leaf wet filter SS316 L 1 4.70 4.70 10.00 m3 $27,500 1.00 1.00 $46,700
SOFTENING DTW
PACKED Packed tower SS316L 1 2.40 2.40 5.11 m $147,600 1.00 1.00 $250,500
BFWP1 DCP ANSI Standard ANSI single stage
pump 316 SF 1 2.57 2.57 5.48 L/s $6,200 1.00 1.00 $10,500
BFWP2 DCP ANSI Standard ANSI single stage
pump 316 SF 1 2.86 2.86 6.10 L/s $6,200 1.00 1.00 $10,500
BFWP3 DCP ANSI Standard ANSI single stage pump
316 SF 1 0.54 0.54 1.16 L/s $6,100 1.00 1.00 $10,400
BFWP4 DCP ANSI Standard ANSI single stage
pump 316 SF 1 1.24 1.24 2.63 L/s $6,200 1.00 1.00 $10,500
BFWP5 DCP ANSI Standard ANSI single stage
pump 316 SF 1 0.09 0.09 0.18 L/s $6,100 1.00 1.00 $10,400
BFWP6 DCP ANSI Standard ANSI single stage
pump 316 SF 1 2.44 2.44 5.19 L/s $6,200 1.00 1.00 $10,500
BFWP7 DCP ANSI Standard ANSI single stage
pump 316 SF 1 4.75 4.75 10.11 L/s $6,400 1.00 1.00 $10,900
C1CONP1 DCP ANSI Standard ANSI single stage
pump 316 SF 1 8.22 8.22 17.49 L/s $7,500 1.00 1.00 $12,700
C1CONP2 DCP ANSI Standard ANSI single stage
pump 316 SF 1 8.33 8.33 17.74 L/s $7,500 1.00 1.00 $12,700
C1CONP3 DCP ANSI Standard ANSI single stage
pump 316 SF 1 2.59 2.59 5.51 L/s $6,200 1.00 1.00 $10,500
C1CONP2 DCP ANSI Standard ANSI single stage
pump 316 SF 1 2.72 2.72 5.79 L/s $6,200 1.00 1.00 $10,500
CHWP1 DCP ANSI Standard ANSI single stage
pump 316 SF 1 1.63 1.63 3.48 L/s $6,200 1.00 1.00 $10,500
CHWP2 DCP ANSI Standard ANSI single stage
pump 316 SF 1 39.58 39.58 84.26 L/s $10,900 1.00 1.00 $18,500
C2CONP1 DCP ANSI Standard ANSI single stage pump
316 SF 1 2.26 2.26 4.82 L/s $6,200 1.00 1.00 $10,500
C2CONP2 DCP ANSI Standard ANSI single stage
pump 316 SF 1 2.31 2.31 4.91 L/s $6,200 1.00 1.00 $10,500
C2CONP3 DCP ANSI Standard ANSI single stage
pump 316 SF 1 1.07 1.07 2.27 L/s $6,200 1.00 1.00 $10,500
CWP1 DCP ANSI Standard ANSI single stage
pump 316 SF 1 125.00 153.74 327.25 L/s $18,800 1.16 1.00 $36,900
CWP2 DCP ANSI Standard ANSI single stage
pump 316 SF 1 35.64 35.64 75.85 L/s $10,300 1.00 1.00 $17,500
CWP3 DCP ANSI Standard ANSI single stage
pump 316 SF 1 2.94 2.94 6.26 L/s $6,200 1.00 1.00 $10,500
CWP4 DCP ANSI Standard ANSI single stage
pump 316 SF 1 1.81 1.81 3.86 L/s $6,200 1.00 1.00 $10,500
CWP5 DCP ANSI Standard ANSI single stage
pump 316 SF 1 3.54 3.54 7.53 L/s $6,300 1.00 1.00 $10,700
PPUMP1 EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 28.28 28.28 60.20 L/s $39,200 1.00 1.00 $66,500
186
PPUMP2 EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 29.79 29.79 63.40 L/s $40,900 1.00 1.00 $69,400
PSMB3 EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 6.16 6.16 13.11 L/s $16,600 1.00 1.00 $28,200
PUMPF EP
DIAPHRAGM Diaphragm pump, TFE type SS316 L 1 28.76 28.76 61.22 L/s $39,700 1.00 1.00 $67,400
EH REACTOR DAT MIXER Agitated tank, enclosed,
jacketed SS316 L 1 4000.00 4000.00 4000.00 m3 $4,361,200 1.00 3.00 $13,083,600
FERMENTER DAT
REACTOR
Agitated tank, enclosed,
jacketed SS316 L 1 3000.00 3000.00 3000.00 m3 $6,292,700 1.00 5.00 $31,463,500
SEED
FERMENTER
DAT
REACTOR
Agitated tank, enclosed,
jacketed SS316 L 1 516.66 516.66 1269.12 m3 $1,970,300 1.00 1.00 $3,696,100
BFWCM1 DVT CYLINDER
Vertical process vessel SS316 1 2.19 2.19 3.42 m3 $30,700 1.00 1.00 $42,000
BFWCM2 DVT
CYLINDER Vertical process vessel SS316 1 2.15 2.15 3.39 m3 $30,600 1.00 1.00 $42,000
CCONM1 DVT
CYLINDER Vertical process vessel SS316 1 1.41 1.41 1.44 m3 $24,200 1.00 1.00 $24,600
CHMIX DVT
CYLINDER Vertical process vessel SS316 1 12.37 12.37 19.95 m3 $53,100 1.00 1.00 $74,200
CWTM1 DVT
CYLINDER Vertical process vessel SS316 1 59.30 59.30 91.25 m3 $138,100 1.00 1.00 $186,700
DCONM1 DVT
CYLINDER Vertical process vessel SS316 1 6.73 6.73 11.42 m3 $40,300 1.00 1.00 $58,400
WASTEM1 DVT
CYLINDER Vertical process vessel SS316 1 7.01 7.01 10.42 m3 $40,700 1.00 1.00 $53,700
EVAP2M DAT MIXER Agitated tank, enclosed,
jacketed SS316 L 1 6.42 6.42 6.60 m3 $106,900 1.00 1.00 $109,000
NaOH
STORAGE
TOTE
EVT PLAST
TANK PLAST TANK FRP 1 6.09 6.09 10.00 m3 $13,300 1.00 1.00 $18,800
Enzyme Storage Tank
DVT STORAGE
Vertical storage vessel, flat bottom
SS316 1 3.69 3.69 6.04 m3 $18,900 1.00 1.00 $26,700
DAP Storage DVT STORAGE
Vertical storage vessel, flat bottom
SS316 1 0.19 0.19 0.31 m3 $9,000 1.00 1.00 $12,700
CSL Storage DVT
STORAGE
Vertical storage vessel, flat
bottom SS316 1 3.06 3.06 5.01 m3 $17,400 1.00 1.00 $24,600
Turbine1 EEG TURBO
GEN Electrical Turbo-generator CS 1 1574.61 1574.61 2877.97 kW $918,700 1.00 1.00 $1,401,200
Turbine2 EEG TURBO
GEN Electrical Turbo-generator CS 1 1402.54 1402.54 2563.47 kW $828,900 1.00 1.00 $1,264,300
Turbine3 EEG TURBO
GEN Electrical Turbo-generator CS 1 1247.15 1247.15 2279.46 kW $747,900 1.00 1.00 $1,140,700
Turbine4 EEG TURBO
GEN Electrical Turbo-generator CS 1 840.12 840.12 1535.52 kW $534,300 1.00 1.00 $814,900
Turbine5 EEG TURBO
GEN Electrical Turbo-generator CS 1 800.00 795.28 1593.33 kW $513,000 1.00 1.00 $830,900
VP_Cryst1 EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 55.00 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef1 EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 55.00 m3/h $24,500 1.00 1.00 $24,500
187
VP_CONC1Ef2 EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 55.00 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef3 EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 55.00 m3/h $24,500 1.00 1.00 $24,500
VP_CONC1Ef4 EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 55.00 m3/h $24,500 1.00 1.00 $24,500
VP_CONC2Ef1 EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 55.00 m3/h $24,500 1.00 1.00 $24,500
VP_CONC2Ef2 EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 55.00 m3/h $24,500 1.00 1.00 $24,500
VP_CONC2Ef3 EVP WATER
SEAL Water-sealed vacuum pump SS316L 1 55 55 55.00 m3/h $24,500 1.00 1.00 $24,500
CONC1EF1
Falling film evap SS316L 1 142 493 840.32 L/min $1,700,000 2.39 1.00 $5,901,500
CONC1EF2
Falling film evap SS316L 1 142 500 851.36 L/min $1,700,000 2.41 1.00 $5,955,600
CONC1EF3
Falling film evap SS316L 1 142 155 263.47 L/min $1,700,000 1.07 1.00 $2,620,400
CONC1EF4
Falling film evap SS316L 1 142 163 274.73 L/min $1,700,000 1.10 1.00 $2,698,200
TVR1 EEJ SINGLE
STG Steam-jet booster SS316L 1 190 586 585.70
CEPCI
1976 -
2011
$12,000 2.20 1.00 $26,400
CONC2EF1
Falling film evap SS316L 1 142 136 118.02 L/min $1,700,000 0.97 1.00 $1,493,500
CONC2EF2
Falling film evap SS316L 1 142 138 120.74 L/min $1,700,000 0.98 1.00 $1,517,500
CONC2EF3
Falling film evap SS316L 1 142 64 37.57 L/min $1,700,000 0.57 1.00 $670,300
TVR2
Steam-jet booster SS316L 1 190 586 585.70 CEPCI 1976 -
2011
$12,000 2.20 1.00 $26,400
SMB3
Chromatography Unit SS316L 1 29601 95933 131965.80 kg/hr $4,400,000 2.28 1.00 $12,527,400
ANAEROBIC DIGESTION
1 104063
5 1040635 1040635.06 tonne/yr $36,797,675 1 1.00 $36,797,700
Table D - 21: Fermentation 10% EC HT TVR OPEX and TPC Calculation List – Worst Case
Chemicals
Flow (kg/hr) Unit Cost ($/unit) Unit Cost ($/hr) Annualized
Cost ($/kg
xylitol)
Enzymes 50.9 kg/hr 4.7 $/kg $239 $1,990,000 $ 0.10
NaOH 319 kg/hr 0.692 $/kg $221 $1,840,00 $ 0.09
DAP 13.2 kg/hr 0.254 $/kg $3.35 $27,900 $ 0.00
CSL 212 kg/hr 0.177 $/kg $37.5 $312,000 $ 0.02
Utilities Flow (kg/hr) Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg)
Steam 88,800 kg/hr 0 $/kg $ - $0 $ -
188
Cooling Water 882,000 kg/hr 0.02 $/m3 $17.7 $147,000 $ 0.01
Chilled Water 2,300 kWh 4 $/GJ $33.2 $276,000 $ 0.01
Labour
Operators 15 employees $70,000 $/year $126 $1,050,000 $ 0.05
Maintenance 2% CAPEX $4,900,000 $/year $589 $4,900,000 $ 0.24
Consumables 1% CAPEX $2,450,000 $/year $295 $2,450,000 $ 0.12
Laboratory 1% CAPEX $2,450,000 $/year $295 $2,450,000 $ 0.12
OPEX $1,820 $15,100,000 $ 0.75
SLD 20 year $12,300,000 $/year $1,470 $12,300,000 $ 0.61
Property Tax $0 $/year $0 $0 $ -
Insurance 0.5% FCI $1,230,000 $/year $147 $1,230,000 $ 0.06
Interest/Financing $22,000,000 $/year $2,630 $22,000,000 $ 1.08
FC Total $4,250 $35,400,000 $ 1.75
General Expenses 10% TPC $607 $5,050,000 $ 0.25
TPC $6,680 $55,600,000 $ 2.74
Products Flow Unit Cost ($/unit) Unit Cost ($/hr) Annualized Cost ($/kg)
Xylitol 2,430 kg/hr 4.5 $/kg $11,000 $91,200,000 $ 4.50
Electricity 3,465 kWh/hr 5.72 c/kWh $198 $1,650,000 $ 0.08
Revenue $11,200 $92,800,000 $ 4.58
Table D - 22: Fermentation 10% EC HT TVR Cash Flow Statement – Worst Case ($MM)
Year Capital Cost Revenue Operating Costs EBITDA Depreciation Interest GP Taxes Net Profit ATCF
0 -$245.0 $147.1 $0.0 -$98.0 $0.0 $0.0 $0.0 $0.0 -$98.0 -$98.0
1 $0.0 $46.4 $7.6 $38.8 $12.3 -$11.8 $14.8 $3.7 $11.1 $23.4
2 $0.0 $92.8 $15.1 $77.7 $12.3 -$11.0 $54.5 $13.6 $40.8 $53.1
3 $0.0 $92.8 $15.1 $77.7 $12.3 -$10.1 $55.3 $13.8 $41.5 $53.8
4 $0.0 $92.8 $15.1 $77.7 $12.3 -$9.1 $56.3 $14.1 $42.2 $54.5
5 $0.0 $92.8 $15.1 $77.7 $12.3 -$8.1 $57.3 $14.3 $43.0 $55.2
189
6 $0.0 $92.8 $15.1 $77.7 $12.3 -$7.0 $58.4 $14.6 $43.8 $56.1
7 $0.0 $92.8 $15.1 $77.7 $12.3 -$5.8 $59.6 $14.9 $44.7 $57.0
8 $0.0 $92.8 $15.1 $77.7 $12.3 -$4.5 $60.9 $15.2 $45.7 $57.9
9 $0.0 $92.8 $15.1 $77.7 $12.3 -$3.1 $62.3 $15.6 $46.7 $59.0
10 $0.0 $92.8 $15.1 $77.7 $12.3 -$1.6 $63.8 $15.9 $47.8 $60.1
11 $0.0 $92.8 $15.1 $77.7 $12.3 $0.0 $65.4 $16.4 $49.1 $61.3
12 $0.0 $92.8 $15.1 $77.7 $12.3 $0.0 $65.4 $16.4 $49.1 $61.3
13 $0.0 $92.8 $15.1 $77.7 $12.3 $0.0 $65.4 $16.4 $49.1 $61.3
14 $0.0 $92.8 $15.1 $77.7 $12.3 $0.0 $65.4 $16.4 $49.1 $61.3
15 $0.0 $92.8 $15.1 $77.7 $12.3 $0.0 $65.4 $16.4 $49.1 $61.3
16 $0.0 $92.8 $15.1 $77.7 $12.3 $0.0 $65.4 $16.4 $49.1 $61.3
17 $0.0 $92.8 $15.1 $77.7 $12.3 $0.0 $65.4 $16.4 $49.1 $61.3
18 $0.0 $92.8 $15.1 $77.7 $12.3 $0.0 $65.4 $16.4 $49.1 $61.3
19 $0.0 $92.8 $15.1 $77.7 $12.3 $0.0 $65.4 $16.4 $49.1 $61.3
20 $0.0 $92.8 $15.1 $77.7 $12.3 $0.0 $65.4 $16.4 $49.1 $61.3
190