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TECHNO-ECONOMIC ANALYSIS OF BIOFUELS PRODUCTION
By
NA WU
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2018
© 2018 NA WU
3
To my grandma
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ACKNOWLEDGMENTS
I am grateful to all of those I have had the pleasure to work with: my committee, my
work-mates and my family. First, I would like to thank my committee members who are more
than generous to share their expertise and precious time with me. They set examples of
excellence as researchers, mentors, instructors, and role models. Thanks to Dr. Svoronos with his
countless hours and patience of advising and encouraging throughout the entire process; Dr.
Bucklin, who are always supportive and helpful since I came to the ABE department; Dr. Porter,
whose inspiration lectures gives me valuable guidance to the field of agriculture operations
management; Dr. Philips, who provides me many ideas and insightful advises; Dr. Grogan, to
whom I am so appreciative for her dedication and commitment both in my research and my
development. A special thanks to Dr. Pratap, my committee chair for his extensive personal and
professional guiding and supporting for years. I would like to express the deepest appreciation to
him, who continually and convincingly conveyed the spirit of a researcher and scientist, and
caring for students. Without his guidance and persistent help this dissertation would not have
been possible.
I would like to thank my workmates: Yingxiu, Jack, Yikan, Karl, Samriddhi, for their
help in both my research and life. I would also thank all the stuff in the ABE department as well
as the colleagues who are involved in my graduate studies journey.
I would like to thank my family members: grandparents, parents, aunt, uncle and two
cousins, who provide me emotional support and unconditional love. Most importantly, I wish to
thank my loving and supportive husband, who always backs me up both in work and life.
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TABLE OF CONTENTS
page
ACKNOWLEDGMENTS ...............................................................................................................4
LIST OF TABLES ...........................................................................................................................8
LIST OF FIGURES .........................................................................................................................9
ABSTRACT ...................................................................................................................................11
CHAPTER
1 BACKGROUND AND MOTIVATION ................................................................................14
Market Assessment of Biofuels ..............................................................................................14 Techno-economic Analysis ....................................................................................................17
Benefits of Techno-economic Analysis ...........................................................................18 Different Levels of Techno-economic Analysis at All Pre-commercial Stages ..............19 Steps of Techno-economic Analysis ...............................................................................19
Analysis Tools .................................................................................................................21 ASPEN Plus V8.8 ...................................................................................................................22
Process Simulation ..........................................................................................................22 Economic Analysis ..........................................................................................................22 Research Objectives ........................................................................................................24
2 ANAEROBIC DIGESTION AND PHOSPHATE PRECIPITATION FROM
STILLAGE PRODUCED IN A LIGNOCELLULOSIC ETHANOL PLANT – A
TECHNO-ECONOMIC ANALYSIS USING ASPEN PLUS ...............................................26
Introduction .............................................................................................................................26
Material and Methods .............................................................................................................28 Process Modeling of Lignocellulosic Ethanol Production at Stan Mayfield
Biorefinery ...................................................................................................................28
Thermodynamic Model ...................................................................................................30 Anaerobic digestion ..................................................................................................31 Fertilizer (struvite) precipitation ..............................................................................32
Steam generation ......................................................................................................32 Scenarios Investigated .....................................................................................................32 Economic analysis ...........................................................................................................33
Results and Discussion ...........................................................................................................34
Process Modeling with Electrolytes ................................................................................34 Stillage Characterization .................................................................................................35 Anaerobic Digestion Results ...........................................................................................36 Struvite Precipitation Results ..........................................................................................36 Economics .......................................................................................................................37
Conclusion ..............................................................................................................................39
6
3 TECHNO-ECONOMIC ANALYSIS OF RENEWABLE ENERGY PRODUCTION
THROUGH ANAEROBIC DIGESTION FROM CYANOTHECE SP. BG0011 .................41
Introduction .............................................................................................................................41 Methods ..................................................................................................................................44
Microalgae Cultivation ....................................................................................................44 Anaerobic Digestion ........................................................................................................47 Biogas Purification ..........................................................................................................48
Power Generation from Biogas .......................................................................................50 Results and Discussion ...........................................................................................................51
Microalgae Cultivation Economics .................................................................................51 Studied Cases of Anaerobic Digestion ............................................................................52 Electricity Production Cost ..............................................................................................53
Conclusion and Future Work ..................................................................................................54
4 TECHNO-ECONOMIC ANALYSIS OF EXOPOLYSACCHARIDES PRODUCTION
FROM CYANOTHECE SP. BG0011 ....................................................................................55
Introduction .............................................................................................................................55
Materials and Methods ...........................................................................................................56 Process Description .........................................................................................................57 Economics Assumptions .................................................................................................58
Results and Discussion ...........................................................................................................59 Conclusion ..............................................................................................................................60
5 TECHNO-ECONOMIC ANALYSIS OF BIOBUTANOL PRODUCTION USING A
“HYBRID” CONVERSION APPROACH ............................................................................62
Introduction .............................................................................................................................62 Literature Review of Biobutanol Production Process ............................................................64
Description of Butanol Production Process .....................................................................64 Fraction/pretreatment of lignocellulosic biomass ....................................................65 Detoxification ...........................................................................................................68
Fermentation and reactors ........................................................................................70 Separation of butanol products from the fermentation .............................................74
Information on Biocatalyst Used in the Process ..............................................................77
Metabolic Pathways and Stoichiometry ..........................................................................79 Units of Metabolic Pathways at Acidogenesis .........................................................80
Units of Metabolic Pathways at Solventogenesis ....................................................81 Butyric acid to Butanol Catalytic Process .......................................................................83
Methods ..................................................................................................................................84 Results and Discussion ...........................................................................................................91 Conclusion ..............................................................................................................................93
6 CONCLUSIONS ....................................................................................................................94
APPENDIX
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A ASPEN FLOWSHEET OF THE INTEGRATED PROCESS ...............................................97
B STOICHIOMETRIES.............................................................................................................98
LIST OF REFERENCES .............................................................................................................100
BIOGRAPHICAL SKETCH .......................................................................................................115
8
LIST OF TABLES
Table page
1-1 Summary of operating costs for a continuous fermentation ethanol plant. .......................24
2-1 Simulated chemical characteristics of stillage (82% w/w moisture). ................................36
2-2 Total Capital investment cost in million dollars. ...............................................................37
2-3 Ethanol production cost details. .........................................................................................38
2-4 Detailed yearly labor cost. .................................................................................................39
2-5 Detailed utility usage for the base case. .............................................................................39
3-1 A comparison of open raceway and close bioreactor systems for algal cultivation. .........45
3-2 Technical and economic aspects of the biogas purifying systems in ASPEN. ..................50
3-3 Algae cultivation economics. .............................................................................................51
3-4 Process and economic assessment for purified biogas production through anaerobic
digestion of algae BG001 biomass. ...................................................................................52
3-5 The economics of biogas – electricity and steam system. .................................................53
4-1 Baseline BG0011 growth assumptions. .............................................................................57
4-2 Summary of economic analysis of the proposed process model for EPS production. ......59
4-3 Cost summary - major purchased equipment.....................................................................60
5-1 The status of bio-butanol production in leading biofuel companies. .................................63
5-2 Summary of detoxification method with respect to the inhibitors. ....................................70
5-3 Thermodynamic properties of acetic acid and butyric acid ...............................................85
5-4 Economic summary of butyric acid to butanol catalytic process. .....................................92
5-5 Major unit operation equipment cost and installation cost. ...............................................92
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LIST OF FIGURES
Figure page
1-1 Renewable Fuel Standard Mandate. . ................................................................................15
1-2 Schematic summary of the techno-economic evaluation method. ....................................19
1-3 The Scope of AspenOne engineering. . .............................................................................23
1-4 Summary of capital costs. ..................................................................................................23
2-1 Process flow diagram for the Stan Mayfield biorefinery. ..................................................30
2-2 Process flow diagram of proposed stillage utilization. ......................................................31
2-3 Process design for cases studies. ........................................................................................34
2-4 Mass balance of the Stan Mayfield biorefinery. ................................................................35
3-1 Schematic of biorefinery scenarios. ...................................................................................47
3-2 MEA scrubbing for biogas upgrading................................................................................50
4-1 Flowsheet of processing operations for EPS production from Cyanothece sp.
BG0011. .............................................................................................................................57
5-1 The steps of butanol production from ABE fermentation process ....................................65
5-2 Spatial arrangement of cellulose hemicellulose and lignin in the cell walls of
lignocellulosic biomass. . ...................................................................................................66
5-3 Qualitative comparisons of different pretreatment or fractionation methods. ...................68
5-4 Microbial inhibitors formation during pretreatment and ABE fermentation processes. ...69
5-5 Clostridium acetobutylicum. ..............................................................................................71
5-6 The life cycle of Clostridia. ..............................................................................................71
5-7 Different activities occurred during simultaneous saccharification and fermentation
in batch process. ................................................................................................................73
5-8 Recent continuous fermentation methods for ABE production along with solvent
yield, productivity and total solvents. ................................................................................74
5-9 Alternative butanol recovery process: A. Gas stripping B. Pervaporation C. Liquid-
liquid extraction D. Adsorption. ........................................................................................74
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5-10 Illustration of a pervaporation process. .............................................................................75
5-11 Saccharification of cellulose into glucose molecules. .......................................................78
5-12 Polymeric chemical structure of hemicellulose and targets of hydrolytic enzymes
involved in hemicellulosic polymer degradation. ..............................................................78
5-13 Butanol biosynthesis pathway in C. acetobutylicum. ........................................................79
5-14 Metabolic unit of acetic acid (AA) and lactic acid (LA) production from glucose (G)
by butyric acid bacteria fermentations. ..............................................................................80
5-15 Metabolic unit of butyric acid (BA) production from glucose (G) at acidogenic stage. ...81
5-16 Metabolic unit of acetone (A)/isopropanol (I) production from glucose (G) at
solventogenic stage. ...........................................................................................................82
5-17 Metabolic unit of ethanol (E) production from glucose (G) at solventogenic stage. .........82
5-18 Metabolic unit of butanol (B) production from glucose (G) at solventogenic stage. ........83
5-19 PFD of Scenario 1. .............................................................................................................86
5-20 Azeotropes in Scenario 1 ...................................................................................................87
5-21 PFD for Double effect distillation to obtain ABE as final products. The main
equipments are five columns, Scrubber and a Decanter. ...................................................87
5-22 Vapor-Liquid equilibrium of the mixture of ethanol and water (1 atm). ...........................88
5-23 Vapor-Liquid equilibrium of the mixture of butanol and water (1 atm)............................88
5-24 Ternary diagram for butanol ethanol and water. ................................................................89
5-25 PFD of Scenario 2. .............................................................................................................90
5-26 Azeotropes in Scenario 2. ..................................................................................................90
5-27 PFD of steady state butanol purification in water solutions. .............................................93
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Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
TECHNO-ECONOMIC ANALYSIS OF BIOFUELS PRODUCTION
By
NA WU
May 2018
Chair: Pratap Pullammanappallil
Cochair: Spyros Svoronos
Major: Agricultural and Biological Engineering
Concerns about climate change, energy security and rural development have brought
about a renewed interest in biofuels, especially those for transportation. This research focused on
different biofuels (cellulosic ethanol, cellulosic butanol, and algal biofuels) and their conversion
technologies, regarding to abundance of biomass feedstock, fuel universality and conversion
technology maturity. From biomass to the biofuel product, the conversion processes were
investigated aiming at providing high-yielding, efficient, economical, and clean production of
biofuels.
Given the potential benefits of biofuels, there is still a wide lack of public agreement on
the near term and long term economic viability of biofuels as well as process engineering
performance, due to uncertainties on process scale-up associated with the start-up difficulties of
biorefineries. Techno-economic analysis (TEA) was employed as a tool to provide both
quantitative and qualitative understanding of the impacts that a proposed technology may have
on the financial viability of a conversion strategy, as well as better planning and evaluation of
experimental investigations. The biofuel production process was simulated using different
production approaches (different biomass sources, conversion methods, and recovery options).
12
Possible process improvements such as utilization of wastes for value-added products are
addressed.
In this research, a series of techno-economic studies were conducted on the biologically
based production processes for various biofuels and bioproducts to improve performance of
existing scale-up biorefinery, assess the economic feasibility of new technologies, and creat
conceptual design of biorefineries for diversified products. Firstly, a techno-economic analysis
was performed on an integrated model for lignocellulosic ethanol production with stillage
utilization based on data from the pre-commercial scale pilot plant and laboratory experiments.
Introducing anaerobic digestion and phosphate precipitation of wastes has shown economic and
environmental benefits: the biogas produced has the potential to replace about 68% of the fossil
fuels used for steam generation in the ethanol biorefinery and the phosphorus-rich fertilizer
produced by precipitation further reduced the ethanol production cost to 53.48 cents/L from
54.20 cents/L without waste utilization. The process with stillage treatment was more
economically viable taking the carbon tax into consideration. Secondly, the economic feasibility
of algal biofuels and bioproducts from Cyanothece sp. BG0011 - a marine
microalgae/cyanobacteria species was evaluated. Economics of biomass cultivation and biogas
conversion process as well as biogas purification methods were investigated. It was found that
anaerobic digestion of algal biomass could produce renewable natural gas at a cost of 14.6
$/MMBTU by using high pressure water scrubbing for biogas upgrading. The option using
biogas for electricity production was economically competitive with an electricity production
cost of 13 cents/kwh. The production cost of exopolysaccharides bioproduct from Cyanothece
sp. BG0011, was estimated to be 4.70 $/kg and the cost favorably compares with commercial
polysaccharides. Finally, a novel biobutanol production process - “hybrid conversion”, which
13
converts biomass-derived butyric acid to butanol through a catalytic process, was evaluated for
economic performance using different process design strategies. The butanol cost was estimated
to be 0.87 $/L in the best scenario. This is in comparison to a butanol production cost of 1.00 -
1.80 $/L using the conventional acetone-butanol-ethanol (ABE) fermentation approach.
14
CHAPTER 1
BACKGROUND AND MOTIVATION
Market Assessment of Biofuels
Concerns about climate change, energy security and rural development have brought
about a renewed interest in biofuels, especially liquid biofuels for transportation. Biomass fix
carbon dioxide from the atmosphere, so effective conversion and use of biomass to biofuels
would decrease usage of fossil fuels thereby decreasing net carbon dioxide emissions. One
seventh of total energy consumption is from biomass (a larger portion in developing countries)
and 2.4 billion people (over 1/3 of the population) in the world still rely on biomass for energy.
The development of more efficient and environmentally beneficial uses of biomass for energy
purposes can play a crucial role in rural development including reducing unnecessary agricultural
work, increasing agricultural productivity and increasing income-generating opportunities.
Biomass is also likely to be the only viable option to fossil resources which are used for
transportation fuels and as feedstock for chemicals, compared to the other renewable sources of
energy like solar and wind (Cherubini and Stromman, 2011). As it is still debated whether the
production and use of biofuels increases competition for food, land, and water, more research on
biomass and biofuels adapted to the needs and possibilities of the market and the corresponding
policies is required (Figure 1-1). Research needs to address development of new pathways to
produce biofuels, by limiting potential negative impacts and strengthening its positive impacts. .
To overcome the disadvantages of biofuels, three points need to be considered: First,
identification, cultivation and utilization of biomass feedstock that is abundant does and not
compete with food supply; second, alternative biofuels that have potential to be used efficiently
and widely; third, conversion technologies that provides high-yielding, efficient, and clean
biofuels.
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Figure 1-1. Renewable Fuel Standard Mandate. Source: Energy Independence and Security Act
of 2007 (P.L. 110-140).
First generation feedstocks for biofuels are mainly starch and sugar-based such as corn
grains and sugarcane juice. Corn grains are the primary feedstock for the US bioethanol industry,
but its production has been capped at 15 billion gallons per year due to the effect on feed and
food supplies and prices. Second generation feedstocks are basically lignocellulosic agricultural
residuals such as corn stover, energy crops such as switchgrass, and forestry biomass such as
wood chips. Over one-third of the US’s current petroleum consumption can be sustainably
supplied by forest and agriculture land resources (Perlack, et al. 2005). While the market for
cellulosic ethanol in the US is projected to continue to grow in the coming years as shown in
Figure 1-1, research activities have focused on improving pretreatment methods; developing
cellulose hydrolysis enzymes and ethanol-fermenting organisms; engineering studies on potential
processes; and building demonstration and production facilities. However, given the benefits of
cellulosic biofuels, scaling up of the conversion technology is still an issue to be solved.
Commercial scale production of cellulosic ethanol is emerging these years. Companies such as
Abengoa, Dupont, POET-DSM, and Quad County Corn Processors have put their efforts to
16
produce cellulosic ethanol, but rarely commercial scale plants have the expected productivity and
capacity due to start up issues and mechanical problems. Among those companies, POET has the
most promising process facility due to cost reduction operations such as sharing facilities, and
energy with corn ethanol plants. However, high capital costs require a higher production rate to
break even. Strategies to optimize the processes for conversion of biomass to biofuels still need
further investigation, especially in the field of process engineering.
While ethanol (the first liquid biofuel produced on a large scale) is being studied
intensively by researchers, other biofuels such as butanol have attracted renewed interest for its
superior properties and the advent of new technologies. Butanol overcomes many limitations of
ethanol as a biofuel. First, energy density of ethanol is 34% lower than gasoline; however,
butanol has almost 90% of the energy density of gasoline (Swana et al. 2011), so butanol has a
higher energy content which approaches that of gasoline. Second, the vapor pressure of butanol
(7mm Hg @ 25℃) is much lower than ethanol (55mm Hg @ 25℃); as a result, it will generate
fewer volatile organic compound (VOC) emissions and be safer for handling and use. Third, the
low water solubility of butanol reduces the tendency of microbial-induced corrosion to occur in
pipelines and fuel tanks during its transportation and storage, as well as dispersion in ground
water from spills. Thus, it can be blended into gasoline in conventional pipelines without
corrosion or other water-related issues rather than having to be transported via rail to blending
facilities. Finally, butanol solves the critical problem about a “blend wall” for bio-ethanol, that is,
ethanol can be added to fuel tanks up to a limit of 10% by volume without any deleterious
emissions or performance impacts. Otherwise, engine modifications are required. In comparison,
butanol can be blended at any ratio with gasoline or diesel (Cascone et al. 2008). For the US
biofuels industry, as gasoline consumption is far lower than what was expected due to advances
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in vehicle fuel economy and other economic factors when the Renewable Fuel Standard in 2007
was passed by the Congress, there would be a market imbalance because of the “blend wall”.
The Renewable Fuel Standard (RFS) would require more than necessary ethanol to be blended
into US gasoline. In 2013, Environmental Protection Agency (EPA) revisited ethanol mandate as
gasoline consumption slipped (Tracy, 2013). Accordingly, bio-butanol has been regarded as a
potential surrogate for gasoline (Visioli et al. 2014). Thus, research comparing the production of
biofuels ethanol and butanol may be useful to address motivation and demotivation in
developing each biofuel without all the focus on ethanol.
Algae as a new generation of biofuel feedstock can alleviate the food versus fuel
concerns greatly and be a promising and sustainable resources for energy. Compared to the first
two generations of biofuel feedstock, algae has many advantages: short growth period and high
yield; perform photosynthesis in relatively rough conditions (some species in the sea); and can be
used for treatment of waste water. Algae as a fuel source was studied from 1980 to 1996 with the
support of the US Department of Energy, however, these research studies were terminated due to
financial constraints and low oil price. Recently there is a renewed interest in algae due to
concerns for energy security and environmental problems. Advances in biotechnology, such as
discovery of superior algal species (high yielding, adapted for growth in unfavorable
environment etc.), improved cultivation methods, have made algae a possible cost-effective
resource for bioenergy.
Techno-economic Analysis
Given all the potential benefits of biofuels, there is still a lack of broad public agreement
on the near term and long term economic viability of advanced biofuels as well as process
engineering performance, due to uncertainties on process scale-up associated with the start-up
stages. Techno-economic analysis (TEA) can be an integral tool to direct research during
18
development of specific technology and assist with investment by averting unnecessary
expenditures. It establishes capital and operating cost profile to determine the potential economic
viability of the production process for realizing its commercial viability (Juneja, et al. 2013) and
provides both quantitative and qualitative understanding of the impacts that proposed technology
have on the financial viability of a conversion strategy by combining process modeling and
engineering design with economic evaluation (Wallace, et al. 2011).
Benefits of Techno-economic Analysis
The benefits of techno-economic analysis are manifold: Evaluations of various biofuel
production processes can serve as a basis for technology assessments, long-term corporate
strategies and future investment decisions. Comparing different technologies can underpin the
decisions that are based on system flexibility, energy yield and cost effectiveness. Conceptual
process simulation models will be used in this research as details of large scale productions for
lignocellulosic butanol and ethanol are not readily available. The techno-economic assessment is
better termed techno-financial assessment due to its financial focus (Yimin, 2010) including
project investments, costs, revenues, savings and cash flow analysis. Techno-economic analyses
can be useful in determining which conceptual designs (pretreatment and recovering method,
byproducts allocation, yields etc.) as well as economic parameters (feedstock price, chemicals
cost, inflation rate etc.) have the highest potential for near-, mid-, and long-term success. For the
engineering research, the results of a techno-economic analysis can give a direction toward areas
in which improvements will result in the greatest cost reductions. For stake holders (suppliers of
biomass, investors, government and energy consumers), the results of a techno-economic
analysis contribute to the acceptance, advancement and final realization of the concepts (Dael, et
al. 2013).
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Different Levels of Techno-economic Analysis at All Pre-commercial Stages
Techno-economic analysis could be employed from early stages to advanced stages
before commercial launch. These stages include (1) Preliminary exploration, (2) Detailed
investigation, (3) Development, (4) Validation and (5) Commercial Launch. In each stage, each
new measured system variables (lab/field data, etc.) could be used to update the model built in
previous stages. The stage of analysis is set in the project goals so that in depth analysis would
be conducted. Typically, in early stages, TEA could be made based on simple spreadsheets of
process and simple cash flow analysis. In mid and advanced stages, TEA could employ industry
relevant process simulation and discounted cash flow rate of return analysis.
Steps of Techno-economic Analysis
A visual representation of the structure of the techno-economic model is shown in Figure
1-2. MFD is Material Flow Diagram and CBA is Cost Benefit analysis.
Figure 1-2. Schematic summary of the techno-economic evaluation method. (Dael, et al. 2013).
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The general steps of a techno-economic analysis are as the following: First, a conceptual
process design is built. Alternative approaches to current production process are analyzed, then
the process is engineered based on literature search results. After that, major technical and
economical hurdles such as pretreatment methods, recovery methods are identified. Theoretical
yields based on selected approach are quantified. Finally, decisions are made based on process
and economic projections.
After a conceptual process design is built, a material and energy balances needs to be
calculated as an energy and material flow diagram. This step ensures the process is feasible.
Thermodynamic models are made incorporating the latest R&D results at bench and pilot scales.
Results are obtained including heat and energy requirements, yields and stream composition and
thermodynamics.
Third step is capital and project cost estimates. It requires data from material and energy
balances. In this step, the equipment used in the process needs to be specified. The capital and
operating costs are calculated. A financial analysis including cash flow analysis and rate of
return calculation are performed to identify additional barriers such as oil price, etc.
An environmental analysis is then made based on the energy and carbon balances.
Greenhouse gas emissions, water balances and other critical data are also checked to be supplied
to Life Cycle Analysis (LCA). Based on techno-economic analysis, the total one time and
recurring costs that occur over the life of the project (life cycle costs) may be analyzed.
With all previous analysis, feedback is obtained for continuous process improvement.
The model can then be updated by actual lab/ field data, including addition of new observed
system variables. As the project moves towards the commercialization pathway and the level of
details and testing accumulates, the risk and uncertainty decreases.
21
Due to the uncertain input parameters and assumptions, a sensitivity analysis is used to
determine how the change in the model or its input values affects the outputs and the specific
process uncertainties towards commercialization. It makes comparisons of the magnitude of
effects when changing process (e.g. enzyme loading amount in saccharification step for ethanol
production) and economic parameters (e.g. required rate of return on the minimum selling price)
and uses probability distributions for inputs based on R&D to calculate ranges instead of point
estimates. Focusing on specific sections of a process, the results from the sensitivity analysis can
be used to (i) evaluate the profitability of the energy conversion model (calculating net present
value, unitary production cost etc.) (ii) determine parameters (plant capacity, yields, feedstock
cost, etc.) which have great contributions to the variability of the final results and their effects
(Marvin, 2011).
Analysis Tools
The depth of TEA requires different tool sets for analysis. For example, spreadsheet can
be used for economics, mass balance models and linear programming models. Simulators such
ASPEN PLUS, Chemcad and UniSim Design are useful tools for chemical process simulation
and optimization. Systems dynamics and Monte Carlo method can be used for risk or uncertainty
analysis. Systems dynamic is usually used as an approach for policy analysis and design. The
Monte Carlo method uses computational algorithms that rely on repeated random sampling to
obtain numerical results and can be useful for simulation with uncertainty in inputs and
engineering systems for sensitivity analysis and quantitative probabilistic analysis in process
design. AutoCAD could be used by engineers for computer-aided design and drafting for the
final plant design.
22
ASPEN Plus V8.8
ASPEN Plus is a computer-aided chemical process simulation software. It is a software
widely used in chemical industries and academia. Computer-aided simulations quantitatively
models the process and can quickly test the performance of synthesized process flowsheets and
provide feedback to the process synthesis activities, eventually develop optimum integrated
designs to minimize experimental and scale-up efforts.
Process Simulation
A process model is helpful to predict the behavior of systems (e.g. stream properties,
equipment sizes) using a complete layout of the engineering system including flowsheet,
chemical components, operation conditions and using the underlying physical relationships (e.g.
material and energy balances, thermodynamic properties, reaction kinetics). ASPEN Plus is a
simulation tool to create the process model by taking all the specifications of chemical
components and operating conditions. Process simulation predicts the system behavior by
executing all necessary calculations needed to solve the outcome of the system. After the
simulation with calculations, ASPEN Plus lists the results of stream and data on chemical species
activities.
Economic Analysis
The Activated Economics Workflow in ASPEN Plus is to run simultaneous process cost
evaluation while building a model in the software. It represents a relative feasibility and
conceptual design cost for the studied process. Activated Economics can be exported to other
AspenTech Economic Evaluation products, such as Aspen Process Economic Analyzer, Aspen
Capital Cost Estimator and Aspen In-Plant Cost Estimator, which provide very detailed and
accurate estimates and drill down into the various aspects of a project. The following figure
23
(Figure 1-3) show the scope of Aspen engineering which gives specific information about
economic analysis with regards to each engineering step.
Figure 1-3. The Scope of AspenOne engineering. (AspenTech).
Figure 1-4 shows a general summary of capital costs, which demonstrates the amount of
investment required for building a plant or facility and includes all equipment and labor
associated with installation of the equipment (Brown, 2003).
Figure 1-4. Summary of capital costs.
Operating costs are required to operate the plant after the construction of a plant. A
summary of operation costs is shown in Table 1-1. Here, the working capital includes available
money to cover inventory of raw material finished product storage as well as some other payable
Grassroots capital
Total module cost
Bare module cost
Direct project expenses
Equipments (f. o. b.)
Materials for installation
Direct labor
Total direct
Indirect project expenses
Freight, insurance, taxes
Construction overhead
Engineering expenses
Total indirect
Contingency & fee
Auxiliary facilities
24
accounts, it typically accounts for 10-20% of the fixed capital. The capacity factor shows the
fraction of time the plant operates on an annual base.
Table 1-1. Summary of operating costs for a continuous fermentation ethanol plant. (Brown,
2003).
Fixed capital Working Capital Total Capital
Plant capacity factor Plant capacity
Cost($10^6/yr) Description
Direct
Raw materials
By-product credits
Operation labor
Supervisory labor
Utilities
Maintenance & repairs
Operation supplies
Laboratory charges
Patents and royalties
Direct subtotal
Indirect & General Expenses
overhead
Local taxes
Insurance
General expenses
Indirect subtotal
Annual capital charges
Annual operating cost
Product cost ($/unit
production)
Research Objectives
The purpose of this research is to provide an integrated techno-economic analysis to
enhance the sustainability of biofuel production processes, focusing on the production of bio-
ethanol, bio-butanol, and algal biofuels while developing strategies to optimize the engineering
process. The specific objectives of this research are:
1. To develop an integrated flowsheet for ethanol production from lignocellulosic materials
and validate the model using observed data from the pre-commercial scale Stan Mayfield
Biorefinery Pilot Plant. Scale up the design and determine the impact of introducing
anaerobic digestion of waste streams and nutrient recovery process on the overall mass
and energy balance as well as economic feasibility.
25
2. To develop a process flowsheet and conduct a techno-economic analysis to determine the
economic feasibility of producing biogas from algae, the conversion of biogas to
electrical energy and the upgrading of biogas to renewable natural gas. Laboratory results
from algae cultivation and anaerobic digestion experiments were used as model inputs.
3. To conduct a techno-economic analysis for the production of polysaccharide product
from algae cultivation.
4. To develop an integrated flow sheet for butanol production from lignocellulosic materials
and simulate the process. Two approaches are compared: Conventional ABE
fermentation and butyric acid-to-butanol catalytic process. Different conversion strategies
of butyric acid-to-butanol catalytic process are analyzed for the economic performance.
5. The three different biofuels produced are then compared on a unit energy price.
In all cases above, the process flowsheet was constructed in ASPEN PLUS 8.8. Capital
costs for equipment was obtained from vendors or from literature. If prices from these sources
were not available then costs from ASPEN process economic analyzer were used. Algae
feedstock simulations are conducted using Cyanothece sp. BG0011 as the microorganism. This
cyanobacterium was isolated from a shallow lake in the Florida Keys and in addition to being
native to Florida, it has several advantages as it can be cultivated in salinities ranging from 15-75
psu, produces an extracellular polysaccharide and fixes atmospheric dinitrogen gas (Bailey,
2016).
26
CHAPTER 2
ANAEROBIC DIGESTION AND PHOSPHATE PRECIPITATION FROM STILLAGE
PRODUCED IN A LIGNOCELLULOSIC ETHANOL PLANT – A TECHNO-ECONOMIC
ANALYSIS USING ASPEN PLUS
Introduction
Concerns about climate change, energy security and social-economic development have
brought about a technological and commercial interest in biofuels, especially liquid biofuels for
transportation. Bioethanol is the primary liquid biofuel produced on a large scale in USA.
Currently nearly all the ethanol is produced from corn starch. However, cultivating and using a
food and feed source for fuel production is controversial due to issues such as food security and
prices, and environmental impacts. This has prompted the utilization of more sustainable
feedstocks for ethanol production. Non-food crops (mostly lignocellulosic in nature) and
agricultural residues as feedstock for production of ethanol may alleviate these concerns.
Lignocellulosic biomass (agriculture residues, forestry wastes, food industrial wastes and energy
crops) are the most abundant renewable resources in nature and has the potential of being low
cost and environmentally beneficial.
The economically feasible production of lignocellulosic ethanol on an industrial scale is
limited due to the high cost brought about by low conversion efficiencies, extensive energy
usage, high raw material cost and high cost of consumables like enzymes (Zhao, et al., 2015;
Albarelli, et al. 2014; Frankó, et al. 2016; Valdivia, et al. 2016). Many techno-economic analysis
(TEA) research have been conducted to explore the prospects for commercial production of
lignocellulosic ethanol. TEA studies have been published for range of contexts like different
feedstocks (Franko et al., 2016; Klein-Marcuschamer, et al. 2010; Gnansounou and Dauriat,
2010; Huang, et al. 2009), pretreatment methods (Klein-Marcuschamer, et al. 2011; Silva et al.
2016; Tao, et al. 2011; Yang and Rosentrater, 2015), plant sizes (Gnansounou and Dauriat, 2010;
27
Aden and Foust, 2009; Quintero, et al. 2015; Huang et al. 2009), process parameters such as
ethanol yield, solids loading, enzyme loading and prices (Kadhum, et al. 2017; Gnansounou and
Dauriat, 2010; Aden and Foust, 2009;), and downstream processing including purification and
waste treatment (Kazi, et al. 2010; Rajendran, et al. 2016; Lassmann, et al. 2014). An integrated
biochemical conversion pathway was developed by the United States National Renewable
Energy Laboratory (NREL) by selecting the most promising processes for feedstock handling
and storage, pretreatment, fermentation, ethanol recovery, stillage evaporation, wastewater
treatment, and lignin combustion (Kazi, et al., 2010). Current research and commercial practice
are showing increasing interest in not only reducing ethanol production cost but also minimizing
fossil energy inputs and environmental impacts (Junqueira, et al. 2017; Kadhum, et al. 2017;
Kristianto and Zhu, 2017).
Stillage is the waste stream produced from the distillation units. It is essentially the entire
fermentation liquid remaining after ethanol recovery. Stillage can be considered as a resource
rather than as a waste and various ways of utilizing this has been investigated to generate energy,
and co-products (Barta, et al. 2010; Uellendahl and Ahring, 2010; Baral and Shah, 2017).
Compared to the published stillage treatment methods - direct combustion of the solid fraction
and evaporated liquid fraction (Kazi, et al., 2010; Gubicza, et al., 2016; Aden and Foust, 2009),
anaerobic digestion of stillage is less energy and capital intensive, and environmentally friendly.
Utilization of biogas that is produced from anaerobic digestion of stillage as a fuel has been
found to improve carbon utilization (Uellendahl and Ahring, et al., 2010; Drosg, et al. 2013;
Tian, et al. 2013) by removing the major organic parts (Wilkie, et al., 2000). An integrated
process for ethanol production where biogas is produced as a byproduct was investigated to
optimize the energy input into the process (Cesaro and Belgiorno, 2015). Anaerobic digestion
28
only removes organic carbon. Inorganic components of the stillage stream (like N, P, K and
metals, etc.), as well as refractory compounds could be used as nutrient sources for cropland with
well managed applications. There is no published research that analyzes the technoeconomic
aspects of an integrated process incorporating anaerobic digestion and nutrient recovery as
primary treatment options.
In this research an ASPEN Plus (AspenTech, Cambridge MA) based process flow-
sheeting model was developed for a lignocellulosic ethanol biorefinery. All sections of a
biorefinery including pretreatment, saccharification, fermentation and ethanol recovery were
modeled. The flowsheet was based on a bioethanol production model which was validated using
operating data from the pre-commercial scale Stan Mayfield Biorefinery Pilot Plant of University
of Florida (Gubicza, et al., 2016). An anaerobic digester, a nutrient recovery step and a boiler for
steam generation was integrated into the process. Operating data for anaerobic digester and
nutrient recovery was obtained from laboratory scale experiments. A detailed energy analysis
was performed to evaluate energy consumption in various sections of the biorefinery. The impact
of introducing anaerobic digestion and nutrient recovery on the overall economics and energy
inputs were investigated.
Material and Methods
Process Modeling of Lignocellulosic Ethanol Production at Stan Mayfield Biorefinery
The Stan Mayfield biorefinery (Process flow diagram “PFD” shown in Figure 2-1.) were
processing 2 US tons of dry sugarcane bagasse per day. Sugarcane bagasse contains about 70
percent of total sugars (w/w) with about 2/3 of cellulose and 1/3 of hemicellulose. The bagasse
feedstock is pre-mixed with steam before the pretreatment (hydrolysis) process. Then the
mixture is screw-pressed to the pretreatment tank where steam is used during pretreatment to
maintain the temperature at 185 °C. Phosphoric acid (0.8% w/w) from a 2% solution is added in
29
the pretreatment process. A flash separation at atmospheric pressure is used to release part of the
water and some byproducts between the pretreatment reactor and the saccharification reactor.
The liquefaction (saccharification) occurs at 50 °C with 6 hours of retention (continuous tank).
The pH is kept at 5.0. Enzyme with concentration of 2.5% is used (2.5 mL enzyme solution for
every 100 g of biomass dry weight). The condition of fermentation is 37 °C, pH 6.3, 48 hours
fermentation time. The ethanol purifying process contains the distillation and dehydration.
Distillation is typical stripper column, followed by the rectifier column. The final dehydration
step is carried out by a pervaporation system using membranes instead of the typical molecular
sieves system. The ammonium hydroxide (19%) is used to adjust pH during liquefaction and
fermentation.
In this research, a techno-economic model of a 83 million liters per year bioethanol
biorefinery (Gubicza, et al., 2016) was employed as a basis for development and analysis of
downstream process, using modeling software Aspen Plus V8.8 (Appendix A). This model was
validated by the pilot plant data to prove the feasibility of commercially scale production.
Feedstock compositions, the conversion factors for major reactions in the pretreatment,
liquefaction, and fermentation, as well as ethanol recovery rate were used in this research. Some
modifications are made regarding to the simulation: 1. Build the model based on an electrolytes
environment with specified electrolyte chemistry. 2. Components such as cellobiose,
hemicellulose, corn steep liquor and enzyme are not in the Aspen databank, so they are
simplified by modeling as other chemicals with user specified chemical properties from
literature. Among the components, molecular weight of E.coli, cellobiose are modified as 24.6
and 342, respectively. 3. The high-pressure steam usage is adjusted to maintain the high
30
temperature in the hydrolysis reactor. 4. The reactors (pretreatment, fermentation) are followed
by flash units for gas evacuating (carbon dioxide / water etc.).
Sugarcane bagasse
Steam Steam
Phosphorous acid
Pretreatment tank
Flash
Screw conveyer
Stream splitter
Flash gas 1
Seed propagation tank
Liquefaction tank
Enzyme
Ammonia hyroxide
Heat exchanger
Fermentation tank
Nutrient
pH adjustment tank
Flash
Scrubber
Flash gas 2
Water
Flue gas
Membrane
Ethanol
Stillage 1 Stillage 2
Stripping column
Rectification column
Retentate
Figure 2-1. Process flow diagram for the Stan Mayfield biorefinery.
Thermodynamic Model
The ENRTL-RK (Redlick-Kwong) physical property method has been selected for the
mixed electrolytes system. This method is based on the Unsymmetric Electrolyte NRTL property
model. The Unsymmetric Electrolyte NRTL activity coefficient model (GMENRTLQ) uses
unsymmetric reference state for ions (infinite dilution in aqueous solution). The system employs
binary and pair parameters as well as chemical equilibrium constants from regression of
experimental data included in Aspen Physical Property System databanks.
Proposed Utilization of Stillage
Based on previous simulation and pilot plant data, unconverted sugars, and other organic
chemicals can be used for energy recovery. The processed waste water can be further treated for
removing ammonia and phosphorus as well as producing value added products - fertilizer. The
waste streams for the ethanol plant (stillage and flue gas) are modeled to be sent to an anaerobic
digester for biogas (containing methane) production. The post digestion broth is then treated with
31
chemicals such as magnesium chloride and through aeration to form a fertilizer precipitate
(struvite). In the phosphorous precipitation reactor (PPR), lignin-rich stillage serves as a bedding.
Struvite provides plants N, Mg and P as a valuable fertilizer. Its slow release feature enables it to
be applied at high rates without plant roots damage (Turker and Celen, 2010). The waste water
coming from the biological treatment processes is potentially high in the concentrations of
dissolved P, N and Mg, due to phosphoric acid used in the pretreatment and ammonia used for
pH adjustment process. These P and N could be sources for anaerobic digestion and be recovered
for fertilizer production as well as protect the water resources in consequence. The proposed
utilization of stillage is shown in Figure 2-2.
DecanterStillage
Anaerobic digester
Biogas
PPR
MgCl2
Flash
Lignin-rich stream
Fertilizer and treated water
GasValve
Air blower
Air
Conbustion
Heat exchanger
Water
Pump
Flue gas
High pressure
steam
Ethanol Biorefinery
Flash gas
Liquid stream
Air
Figure 2-2. Process flow diagram of proposed stillage utilization.
Anaerobic digestion
Process description: Methane fermentation stoichiometries (Appendix B) are developed
for 12 components remaining in the wastewater after the ethanol production (Cellulose,
32
Hemicellulose, Ethanol, Glucose, Lactic acid, Succinic acid, Furfural, Acetic acid, Cellobiose,
Xylitol, Xylose, Glycerol, etc.). The general form for the stoichiometry is
𝐶𝑥𝐻𝑦𝑂𝑧 + 𝑏𝑁𝐻3 → 𝑐𝐶𝐻1.8𝑂0.5𝑁0.2 + 𝑑𝐶𝐻4 + 𝑒𝐶𝑂2 + 𝑓𝐻2𝑂 .
Note that a significant amount of lignin exists in the waste stream and it is separated by
the decanter and used as a bedding for phosphorous precipitation. The conversion rate is
assumed to 90% of the 12 reactive components in the waste stream and the microbes E.coli have
the chemical formula CH1.8O0.5N0.2. The anaerobic digestion model given by Aspen Plus have
one source stream and one product stream, so a coupled reactor with flash separator is used to
implement two main product streams: liquid waste and collected biogas.
Fertilizer (struvite) precipitation
Ammonia and phosphorous are recovered thorough struvite precipitation. Aspen
electrolytes database was used to predict electrolyte chemistry (Appendix B). More data could be
obtained by laboratory experiments. The equilibrium constant at the temperature of interest is
obtained from literature (Rahaman, 2009). Struvite precipitation process is further simulated by
MINTEQ. Similar results (struvite production) are obtained compared to Aspen Plus results.
Steam generation
The steam required by the whole process was generated through biogas/natural gas
combustion in a boiler. Biogas/natural gas was the fuel for energy generation, depending on the
scenarios investigated in the following section. The heat produced through combustion was used
to make high pressure steam at a design temperature of 406°F from the water.
Scenarios Investigated
Four Scenarios are investigated as following (Process design shown in Figure 2-3):
33
Base case. Ethanol production + natural gas for steam generation. In this case, bioethanol
production process is simulated and natural gas was combusted in the boiler to produce steam.
No stillage treatment is considered.
Case 1. Ethanol production + biogas (from stillage) and make-up natural gas for steam
generation. In this case, the biogas from anaerobic digestion of the stillage was sent to boiler for
steam generation. In order to meet all the steam requirement for the process, natural gas was also
combusted in the boiler.
Case 2. Ethanol production + biogas (from stillage) for steam generation, no fossil fuel
used for heating. In this case, the ethanol biorefinery was kept at the same scale for ethanol
production except more biomass is pretreated for biogas production. All is steam was produced
from biogas from the anaerobic digester.
Case 3. Ethanol production + biogas (from stillage) for steam generation + struvite
fertilizer precipitation. In this case, the procedure is similar to case 1 except that the post-
fermentation effluent was treated and fertilizer was co-produced.
Economic analysis
Based on the mass and energy balance from process simulations, the economic viability
of the integrated process in different scenarios was assessed. The economic indicators include the
capital cost, operating cost including details such as equipment cost, utility cost etc. The total
capital investment breakdown and ethanol production cost analysis are based on the methods in
literature (Gubicza et al., 2016). The economics of stillage utilize portion was estimated with
vendor quotations (anaerobic digester cost, etc.), Aspen process economic analyzer (utilities,
reactors, etc.) and literature (operating cost, etc.) (Brown, 2003).
34
Figure 2-3. Process design for cases studies.
Results and Discussion
Process Modeling with Electrolytes
The whole simulation is modeled in the electrolyte system, where dissociation and
precipitation are considered to be liquid phase equilibrium reactions and referred as the solution
chemistry. Physical property calculations and phase equilibrium calculations are impacted by
solution chemistry. Electrolyte reactions can be handled in all unit operational models in Aspen
Plus. The non-ideal thermodynamic behavior (caused by the presence of ions) of liquid phase
components can be represented by specialized thermodynamic models and built-in data in the
software to get accurate results. A rigorous treatment of electrolytes is essential in this research
due to the existence of water containing carbon dioxide, ammonia, aqueous acids/bases, and
salts. Based on the electrolyte system built in this model, several points are noted:
35
• Implementing the management of the inorganic compounds that are from the added for
substrates or pH control is essential for the process waste water treatment.
• The simulation results predicted the ammonia usage from a 19% w/w solution:
liquefaction 20.21 kg and fermentation 36.71kg, which fits the pilot plant practical of
added ammonia usage: 1% of the dry weight (18.14kg) during liquefaction and 2%
(38.28kg) during fermentation.
• The pH control is possible throughout the process.
• Distillation and carbon dioxide emissions results are different from the results of non-
electrolytes model with NRTL property method. Electrolyte interactions are to help
predict more accurate vapor-liquid equilibria (Thomas, 2018).
Stillage Characterization
Based on the simulation data, the mass balance of the pilot plant is shown in Figure 2-4.
The stillage composition is shown in Table 2-1. Lignin and cellulose take 33% and 16% dw of
the whole stillage. The cellulosic biorefinery stillage is generally contains about 87.2 wt% water,
3.6 wt%lignin, 1.4 wt% fermentable sugars and 7.8 wt% process chemicals (Baral and Shah,
2017).
Figure 2-4. Mass balance of the Stan Mayfield biorefinery.
36
Table 2-1. Simulated chemical characteristics of stillage (82% w/w moisture).
Chemicals dw % Chemicals dw %
Ethanol 1.3 Z.mobilis 2.5
Glucose 0.13 Glycerol 0.26
Lactic Acid 0.14 Ammonia 0.63
Succinic Acid 0.66 Phosphoric Acid 0
Carbon Dioxide 1.6 Hydronium 0
Furfural 2.9 Ammonium 3.6
Acetic Acid 1 Bicarbonate 11
Cellobiose 0.68 Phosphate Dihydrogen 1.1
CSL 12 Hydroxide 0
Enzyme 3.1 Carbonate 0.011
Xylitol 1.3 Phosphate Hydrogen 0.34
Xylose 0.19 Phosphate 0
Cellulose 16 Hemicellulose 2.2
Lignin 33 Ash 3.3
Anaerobic Digestion Results
The 83 million liters (22 million gallons) per year bioethanol biorefinery has a methane
production 1479.29 kg/hr through simulation, which is 16.5 ml/g stillage (including flash stream
from the pretreatment reactor). This is validated by the lab data analysis of the stillage sample
from Stan Mayfield pilot plant, which is around 14.28 ml/g stillage (Yang, 2017). Both processes
can be implemented as byproducts of ethanol production; specifically, biogas can be used to
supply energy for the whole process, approximately 68.3% of the total steam usage, regarding to
the lab data for stillage treatment of Stan Mayfield biorefinery, approximately.
Struvite Precipitation Results
The struvite-rich fertilizer produced in this process was 9596.47kg/hr, the struvite
concentration is about 7.5% w/w. The phosphorus content was predicted to be 162.67 kg/hr
while lab results showed a value of 163.65 kg/hr (Yang, 2017). High grade struvite may need
recycle stream and long retention time, which results in a high production cost and a relatively
37
small potential market (Sikosana, et al. 2017). Although the fertilizing effect of struvite depends
on the soil type, plant type and climate, the struvite recovery process still benefits from
conservation of limited P resources, safe disposal of nutrient laden waste and cost savings for
upstream production process (Kataki, et al.2016).
Economics
The breakdown of the total capital investment cost is shown in Table 2-2. The capital cost
of ethanol production process includes raw materials handling, pretreatment, Liquefaction and
simultaneously saccharification and fermentation and distillation. Case 2 has the highest capital
cost of ethanol production processes due to more feedstock involved in the pretreatment step. It
also has a higher capital cost of anaerobic digester due to more feed to the anaerobic digester.
The economics of the base case is developed from studies (Gubicza, et al. 2016), while treatment
of the waste stream is in a different approach.
Table 2-2. Total Capital investment cost in million dollars.
Scenario Base case 1 2 3
Ethanol
production
processes
57.97
57.97 60.21 57.97
Anaerobic
digester
- 24.12 32.91
24.12
Struvite PPR
(phosphorous
precipitation
reactor)
- - - 9.17
Heat generation 6.25 6.25 6.25 6.25
Total direct cost 64.22 88.34 99.37 97.51
Total indirect
cost
28.90 39.75 44.72 43.88
Fixed capital
investment
93.12 128.09 144.09 141.39
Working capital 3.26 4.48 5.04 4.95
Total capital
investment
96.38 132.58 149.13 146.34
38
The breakdown of ethanol production cost is listed in Table 2-3. The base case has the
least capital cost due to no waste treatment. Case 2 has the least utility cost since all the required
steam was produced from biomass, which is nearly carbon neutral. Case 3 has promising
economics, even consider the carbon tax. The maintenance and indirect cost are significant costs
due to high fixed capital investment. Table 2-4 shows the detailed labor cost, which is estimated
from tabulations of operator requirements. Table 2-5 gives the detailed utility usage including
cooling water, process water, electricity, and natural gas. Carbon trading price is referred to
California, which is 10$/tonne. In Sweden, the carbon trading price is 168 $/tonne, then the
ethanol production cost would be base case > case 1 > case 2 > case 3.
Table 2-3. Ethanol production cost details. Unit: cents/L of ethanol.
Scenario Base case 1 2 3
Feedstock 14.47 14.47 17.02 14.47
Capital 12.77 17.57 19.76 19.39
Chemicals 7.91 7.91 7.91 8.81
Enzymes 7.38 7.38 7.38 7.38
Utilities (Natural gas price 3/10 $/mmbtu) 5.29/15.58 2.43/6.14 0.90/0.9 2.43/6.14
Labor cost 1.84 2.08 2.08 2.12
Maintenance 2.11 2.9 3.26 3.2
Indirect operational cost (overhead,
insurance etc.) 2.43 3.11 3.36 3.34
Coproducts 0 0 0 7.66
Ethanol production cost 54.20/64.49 57.85/61.56 61.67/61.67 53.48/57.19
Carbon trading price (California/Sweden) 0.7/11.6 0.25/4.2 0 0.25/4.2
Ethanol production cost (w/ carbon credits) 54.90/65.8 58.1/62.05 61.67/61.67 53.73/57.68
39
Table 2-4. Detailed yearly labor cost. Operator
requirements for
various types of
process equipment
Literature
No. of
units
Base case 1 2 3
Wastewater treatment
plants 2 1 0 0.5 0.5 0.5
Compressors 0.2 1 1 1 1 1
Heat exchangers 0.1 3 3 3 3 3
Mixers 0.3 1 1 1 1 1
Reactors 0.5 5 5 5 5 5
Electrostatic precipitators 0.2 0 0 0 0 1
Cooling towers 1 3 3 3 3 3
Electric generating 3 1 0 0 0 0
Evaporators 0.3 1 0 0 0 0
Boiler 1 0 1 1 1 1
Total labor (person/3
shifts) 36 23.1 26.1 26.1 26.7
operating labor cost ($) 2160000 1386000 1566000 1566000 1602000
total labor cost ($) 2376000 1524600 1722600 1722600 1762200
* $ 60000 per employee/year
Table 2-5. Detailed utility usage for the base case. base
case
1
2
3
Name Rate Cost
($/hr)
Rate Cost
($/hr)
Rate Cost
($/hr)
Rate Cost
($/hr)
Electricity (kw) 813.1 63.01 813.06 59.95 844.79 65.47 813.1 63.01
Cooling Water
(m3/hr)
795.33 25.21 795.33 25.21 795.34 25.21 795.34 25.21
Process Water
(kj/hr)
12,098,5
20
2.56 12,098,5
20
2.56 12,098,5
30
2.56 12,098,5
20
2.56
Natral gas
(kmol/min)
2.75 457.69 0.99 164.77 0 0 0.99 164.77
Conclusion
Liquid biofuels derived from lignocellulosic biomass has been in the progress of
commercialization, however, optimization of the process regarding to minimizing energy input,
reducing environmental burdens as well as improving economic performance is still challenging.
This research set out to provide a concept of biorefinery with economic and environmental
benefits by a techno-economic analysis, focusing on the waste utilization and process integration.
It can be concluded that the stillage from lignocellulosic ethanol could be fully utilized for
40
energy and nutrient recovery. The integrated process model shows promising economic and
energetic results. Potential environmental benefits are not discussed. Future work may include
performing integration of bioethanol and stillage utilization processes in a demo-scale plant,
which could be further developed to industrial scale.
41
CHAPTER 3
TECHNO-ECONOMIC ANALYSIS OF RENEWABLE ENERGY PRODUCTION THROUGH
ANAEROBIC DIGESTION FROM CYANOTHECE SP. BG0011
Introduction
The resource depletion and carbon emissions caused by using fossil fuels has increased
interest in alternative fuel sources. One option is the bioenergy, which has been intensively
studied for its potential in environmental and economic benefits. Bioenergy could be derived
from a variety of renewable feedstocks: sugar-based biomass (e.g. corn, sugarcane) and
lignocellulosic biomass (e.g. wheat straw, corn stover, sugarcane bagasse, switchgrass).
However, the sustainability of the feedstock should be evaluated due to risks associated with
farming and conversion processes, for example, risks could be interfering the food chain, causing
eutrophication, reducing biodiversity, quantities insufficiency, and low conversion rate.
Microalgae as a feedstock for biofuels productions dates back to 1940s in Japan due to
the energy shortage in this period. Its superior advantages make it a promising biofuel feedstock
worth further development. Compared to terrestrial plants, microalgae have higher solar energy
yield and biomass productivity. The photosynthetic efficiency of microalgae is 12.6 higher than
those of terrestrial plants (Su, et al. 2017; Dalena, et al. 2017). Less land area is required for its
growth and the land could be non-arable areas. Besides, some species could use low quality
water such as seawater and waste water as well as carbon dioxide emissions and residues from
biofuels production (Ward, et al. 2014). Microalgae has no potential to interfere the food chain
and is characterized by high lipid/starch/protein content with a lack of lignin, which is a well-
suited biomass for different conversion technologies (Zamallioa, et al. 2011; Dunlop et al. 2013;
Moreno-Garcia, et al. 2017). With all the versatilities, microalgae seem to be the only possible
feedstock that have the potential to completely replace fossil fuel (Milano, et al. 2016).
42
Though studies demonstrated most of microalgae the absence of drawbacks associated
with the earlier generation of biofuels, the major challenges for algal biofuels production include
significant utilization of nutrients, high energy inputs for harvesting, dewatering algae biomass
from the culture broth and its downstream conversion to bioenergy (Zamalloa, et al. 2011; Ward,
et al. 2014). One option is biogas production though anaerobic digestion (AD). AD has been
recognized as a mature technology to treat organic waste streams and widely practiced due to its
high energy output to input ratio, environmental benefits, as well as its process simplicity -
compared to bioethanol/biodiesel conversion process (Montingelli, et al. 2015; Jankowska et al.
2017). Besides, no harsh pretreatment is necessary for algal biomass due to the negligible content
of lignin (Montingelli, et al. 2015). In addition, the biogas contains mainly methane which
presents the higher heating value when compared to liquid fuels, such as biodiesel and
bioethanol (Jankowska et al. 2017). The digestate which contains phosphorous and nitrogen
could be recycled as mineral fertilizer (Montingelli, et al. 2015; Jankowska et al. 2017;
Dębowski, et al. 2013). However, economic feasibility and its balance with energetic aspect is
still a main hurdle hampering the development of algae biofuels including biogas (Sialve, et al.
2009; Ribeiro, et al. 2015; Montingelli, et al. 2015; Suganya, et al. 2016).
The biogas production process from microalgae still needs to be improved for its
economic viability. For example, there could be low yield of biogas and the pretreatment to
disrupt the algae cell walls could require high energy inputs as well as the high algae cultivation
cost, so improvements such as pretreatment and process optimization should be based on algae
species and its characteristics (Santos-Ballardo, et al. 2016). The techno-economic analysis
(TEA) is often used as a foundation tool to evaluate the commercial feasibility of algae-based
biofuels (Chew, et al. 2017) and provides direction to experimental research and development.
43
With a number of techno-economic assessment have been completed to evaluate the economic
feasibility of biodiesel derived from microalgae (Hoffman, et al. 2017; Silva, et al. 2013;
Dunlop, et al. 2013; Manganaro and Lawal, 2015). There is a lack of techno-economic analysis
of the anaerobic digestion of microalgae for biogas production, especially full scale production
taking algae characteristics into consideration.
The microalgae in this study is cyanobacterium Cyanothece sp. BG0011 from the Florida
Keys (Phlips et al., 1989). Compared to other algal species, this specie shows unique features.
First, cyanobacterium Cyanothece sp. BG0011 is a saline specie and can be adapt to a wide range
of salinities (10-70psu). Second, it fixes nitrogen in the air, which means it does not require
nitrogen nutrients in the water. Besides, it produces a highly viscous exopolysaccharide (EPS)
which can be converted to a variety of bioproducts. The aim of this paper is to assess the
economic feasibility of biogas production from cyanobacterium Cyanothece sp. BG0011 by a
techno-economic study. The analysis investigated alternative cases to decrease the cost and
energy requirement of cultivation and anaerobic digestion of algae to produce biogas that can be
purified for methane or be further converted to electrical and thermal energy. A comprehensive
TEA is carried out base on experimental data and a set of operational assumptions which could
be plausibly achieve in near term. The model for biomass to biogas conversion through
anaerobic digestion and biogas purification processes were using Aspen Plus V8.8 to obtain
more accurate mass balance and energy requirement results. Discussion focused on preliminary
exploration of the conceptual design of a microalgae cultivation and bioconversion system and
investigation on improvements that could result in the greatest system flexibility, energy yield
and cost reductions.
44
Methods
Microalgae Cultivation
Open raceway ponds and closed photobioreactor for algae productions have been
extensively studied (Jorquera, et al. 2010; Raes, et al. 2014; Narala, et al. 2016). Open raceway
ponds are generally used in large-scale commercial production of algal biomass (Christi, 2016).
Table 3-1 shows a comparison of open raceway and close bioreactor systems for algal
cultivation.
The Lab growth rate of BG0011 cell biomass (dry weight) is 0.1 g/L/day (30 g/m2/day)
and that of EPS biomass 0.12 g/L/day (36 g/m2/day) (Nguyet, 2017). In literature, productivity
in industrial raceway pond is generally lower than in small experimental reactors. Current algae
biomass productivity performance claims to range from 7- 35g/m2/day (Davis, et al. 2016;
Borowitzka and Moheimani, 2013; Pienkos and Darzins, 2009) with corresponding net
photosynthetic efficiencies from under 1% to 4%. Among these studies involving techno-
economic analysis, the baseline productivity is 20 g/m2 /day, the optimistic case is 25-30
g/m2/day, and the conservative case is 15 g/m2 /day. In this research, which use large
commercial ponds, an average daily productivity around 10 g/ m2 with a net photosynthetic
efficiency of under 1% and pond depth of 30cm is assumed. Here, lab BG0011 cell biomass
growth rate is comparable to other algae cell growth rate in lab, however, in the case of BG0011,
it also produces EPS. The mass ratio between EPS : cell biomass = 1.2 : 1. So assume the
commercial algae cell would be produced at a rate of 10 g /m2 /day, then the EPS would be
produced at 1.2 * 10 g/m2/d= 12 g/m2/day. It is assumed that the steady state of algae cell
density is 1 g/L, while EPS is 1.2 g/L, so a total of 2.2 g/L of algal biomass density was used in
this research.
45
Table 3-1. A comparison of open raceway and close bioreactor systems for algal cultivation. Open raceway Close bioreactor
Biomass productivities Low High
Harvesting biomass concentration Low High
Total capital cost (CAPEX) Relatively low High
Total operational cost (OPEX) Relatively low High
Reliability (low contamination Risk, stable yield) Low High
Net energy ratio (Energy ouput/input) >1 >1 in some cases
Area required High Low
Process control Low High
CO2 loss High Low
Water evaporation High Low
Photosynthesis efficiency Low High
Scale up easy Difficult
The scale of algae cultivation in literature value for techno-economic analysis ranges
from 200 - 700 ktonne/year (Norsker, et al., 2011; Jones, et al., 2014; Dutta, et al., 2016;
Hoffman, et al., 2017). Considering that the sugar required for a 20 million gallons/year ethanol
plant is 160 ktonnes/year theoretically and assuming the sugar comes from EPS, then the scale of
this algae cultivation pond is 293 ktonnes/year, which falls into the literature range values. In this
case, with the EPS growth rate of 12 g/m2/day and algal cells of 10 g/m2/day, land area required
is 3500 hectares (4 by 4 miles). The cultivation area is further compared to corn, for the same
production rate (293 ktonnes /year), corn required is 31800 Hectares, almost 10 times of
BG0011. Here, annual yield for corn grain is 7000 kg/ha and sugar content of corn is 72% is
assumed.
The BG0011 cultivation cost is estimated based on vendor quotes, literature, or
engineering estimates. The installed pond capital cost includes civil work, liner, piping,
electrical, other pond costs (such as paddlewheels). In addition, pumps for pumping water from
ponds to refinery/refilling the pond and required land are also significant capital costs. Plastic
lined earthen ponds were chosen for its lower cost compared to concrete ponds. Larger pond
sizes would enable economically viable algal biomass production (Davis, et al. 2016). Here, the
46
installed capital cost was estimated based on “dollars/hectare” of growth ponds for simplicity.
The installed pond cost was set to be 80000 $/ha. Literature value ranges from 46000 $/ha to
more than 150000 $/ha (value adjusted for inflation) due to different liner scenarios (partial or
full) and specific design (e.g. with or without equipment for the dead zones) (Davis, et al. 2016;
Christi, 2016), which was not discussed here. A land cost of 3080 $/acre (USDA, 2017) was used
for low-value land. The operation cost for algae cultivation such as utilities, chemicals, labor,
overheads, maintenance, insurance tax, etc. are estimated using engineering estimates (Brown,
2003). The only fertilizer used for BG 0011 is phosphorus since it is a marine specie which uses
nitrogen in air as a nitrogen source. The phosphorous requirement of BG001 is 8.9 mg/L, so the
annual requirement of phosphorous is 1186.7 tonnes. Here, triple superphosphate (Ca (H2PO4)2
H2O) which contains 24.6 % P was used as phosphorous source with a price of 270 $/tonne. The
requirement of triple superphosphate is 4945 tonne/year.
The fixed capital investment is borrowed at an interest rate of 10% for 20 years. The
plant operates 24 hours a day and 360 days annually. These assumptions are also used in the
following biogas conversion process. The production cost is calculated as the following:
𝑈𝑛𝑖𝑡 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛 𝑐𝑜𝑠𝑡 = (𝐴𝑛𝑛𝑢𝑎𝑙 𝑐𝑎𝑝𝑖𝑡𝑎𝑙 𝑐ℎ𝑎𝑟𝑔𝑒𝑠 + 𝑇𝑜𝑡𝑎𝑙 𝑜𝑝𝑒𝑟𝑎𝑡𝑖𝑛𝑔 𝑐𝑜𝑠𝑡 −
𝐶𝑜𝑝𝑟𝑜𝑑𝑢𝑐𝑡 𝑐𝑟𝑒𝑑𝑖𝑡𝑠) / (𝐴𝑛𝑛𝑢𝑎𝑙 𝑝𝑟𝑜𝑑𝑢𝑐𝑡𝑖𝑜𝑛).
Here, the annual capital charges are calculated as follows:
𝐴𝑛𝑛𝑢𝑎𝑙 𝑐𝑎𝑝𝑖𝑡𝑎𝑙 𝑐ℎ𝑎𝑟𝑔𝑒𝑠 = [𝑇𝑜𝑡𝑎𝑙 𝑐𝑎𝑝𝑖𝑡𝑎𝑙 𝑐𝑜𝑠𝑡 ∗ 𝐼𝑛𝑡𝑒𝑟𝑒𝑠𝑡 𝑟𝑎𝑡𝑒 ∗ (1 +
𝐼𝑛𝑡𝑒𝑟𝑒𝑠𝑡 𝑟𝑎𝑡𝑒)^(𝐿𝑜𝑎𝑛 𝑝𝑒𝑟𝑖𝑜𝑑) ]/[(𝐼𝑛𝑡𝑒𝑟𝑒𝑠𝑡 𝑟𝑎𝑡𝑒)^(𝐿𝑜𝑎𝑛 𝑝𝑒𝑟𝑖𝑜𝑑) − 1].
*Total capital cost= Total fixed cost + Working capital.
*Working capital is 10% of fixed capital.
47
Anaerobic Digestion
The anaerobic digester was designed to treat the cultured algae broth from the pond,
which has 2.2 g/L of algal biomass density. The energy-intensive steps - algae harvesting and
dewatering are avoided in the process which is different from most research (Zamalloa, et al.
2011; Davis, et al. 2011; Hoffman, et al. 2017). Different scenarios are investigated to evaluate
the economic performance. Schematic of biorefinery scenarios are shown in Figure 3-1.
Different anaerobic digester cases were analyzed in an economic and energetic prospective. The
pathway of methane formation is:
𝐵𝐺0011 (𝐶𝑒𝑙𝑙𝑠 𝑎𝑛𝑑 𝐸𝑃𝑆) + 𝑁𝐻3 → 𝐶𝐻1.8𝑂0.5𝑁0.2 + 𝐶𝐻4 + 𝐶𝑂2 + 𝐻2𝑂
Anaerobic Digester ?Cultured algae broth
Algae Pond
Covered anaerobic lagoon
Raw biogas
Mesophilic anaerobic digester
Low-temperature anaerobic digester
Combined heat and power ?
Biogas purification ?
Sludge
Fertilizer
Figure 3-1. Schematic of biorefinery scenarios.
48
Here, the efficiency of the anaerobic digester was assumed to be 0.98, while lab results
shows the same efficiency on the anaerobic digestion of BG0011 cells (Yingxiu, 2017). Further
work involving EPS should be proved in practice.
Case 1. Mesophilic anaerobic digester. In Aspen, the influent of the reactor was 15
ktonne/hr at 2.2g DM/L biomass concentration. The temperature was kept and 37 °C. The capital
cost of anaerobic digester was estimated using vendor quotation. The operating cost was
estimated by Aspen Process Economic Analyzer.
Case 2. Low-temperature anaerobic digester. Anaerobic digestion at low temperatures
(LTAD) is an application to improve the energy balance, in which the temperature (12 °C to 15
°C) is much lower than mesophilic anaerobic digestion (McKeown, et al. 2012; Bialek, et al.
2013; Gunnigle, et al. 2015) LTAD were employed to represents a cost-effective strategy.
However, with the same flowrate and hydraulic retention time (HRT), the digester volume is
larger for LTAD than mesophilic and thermophilic anaerobic digestion. Here, the temperature of
LTAD is set to be 20 °C with a HRT of 50 days.
Case 3. Covered anaerobic lagoon. Covered anaerobic lagoon (CAL) do not require
additional energy for the biogas production because of no aerated, heated, or mixed processes
involved. Besides, it is economical to construct and operate.
The CAL in this research was 6 meters deep and the size of the CAL is 1.5 Hectares
based on literature data (EPA). The cost includes anaerobic lagoon excavation, cut and fill,
lagoon liner, inlet and out structures, lagoon cover, ancillaries, pipework & installation
Contingencies, design, engineering etc. Operating costs including utility usage are minimal.
Biogas Purification
Several biogas purification methods are available such as high-pressure water scrubbing,
membrane, pressure swing, gas permeation and chemical scrubbing. High pressure water
49
scrubbing and chemical scrubbing (using amine solutions - MEA) are two of the most commonly
used processes.
The MEA scrubbing method is to aqueous monoethanolamine (MEA) for acidic gas
removal. The general concentration of amine for acidic gas absorbing are below 30 wt.%. The
amine process has two main steps, the absorption and stripping (Hassan, et al. 2007). The
detailed MEA scrubbing process is shown in Figure 3-2. Similar to MEA scrubbing, high
pressure water scrubbing is to use different solubility of gases in water for biogas upgrading:
feed water to the bottom of scrubber after biogas being pressurized to 10 bar, transfer CO2-rich
water to a flash column (3 bar) to minimize methane loss, and recirculate the CO2-rich water
through a desorption process (Cozma, et al. 2015). The process of biogas produced in previous
research purified in two ways: MEA and high-pressure water scrubbing are simulated by Aspen
Plus to find the appropriate and economic method to be employed in the integrated process. The
technical specification details are shown in Table 3-2. ASPEN models in equilibrium mode for
the absorber and the stripper: difficulties existed in converging the flowsheet. The solution is to
design absorber first, then integrate absorber and stripper simulations, finally, connect recycle
stream to the previous model gradually. This process resulted in a good initial guess input and
the results could be used as initial guesses for subsequent steps. The high-pressure water
scrubbing method is selected in this research based on the comparison. One option to minimize
the cost of methane purification and maximize environmental foot print is to recycle the CO2 for
algal cultivation, which could increase algae production. However, this needs further
investigation.
50
Scrubbing column
Stripping column
CO2 out
Biomethane
Make-up MEA
Make-up water
Regenerated MEA
Raw biogas
Figure 3-2. MEA scrubbing for biogas upgrading.
Table 3-2. Technical and economic aspects of the biogas purifying systems in ASPEN.
Specification MEA High pressure water
scrubbing
Thermodynamic method ELECNRTL PSRK
Scrubbing column RadFrac, 15 stages, pressure:
1.2 bar
RadFrac, 10 stages, pressure:
10 bar
Stripping column RadFrac, 15 stages, pressure:
8 bar
RadFrac, 10 stages, pressure:
1 bar
Make up chemicals Water: 150 kmol/hr
MAE: 750 kmol/hr
Water: 11500 kmol/hr
Solvent recycle rate MEA: 0.99 Water: 0.95
Methane loss 1% 0.3 %
Product methane purity 95 wt% 99.2 wt%
Capacity 948.5 kmol/hr 948.5 kmol/hr
Capital cost (million $) 8.2 12
Operating cost (million
$/year)
20 4.6
Utility cost (million $/year) 17 2
Purification cost ($/kg of
methane)
0.3 0.09
Power Generation from Biogas
While the raw biogas can be purified to obtain biomethane, another option is to use the
raw biogas to produce heat and power. Steam and electricity can be generated by burning the raw
51
biogas through a combined heat and power (CHP) system. For reference, the CHP system uses
General Electric Genbacher JGS 420 which is a 1425 kw generator. The total capital cost is $
1,150,000 (including installation, tax, etc. 2007), which is 807 $/kw. The working capital is 10%
of the total capital. The operating cost includes direct operating cost such as operating labor,
supervised labor, maintenance and repairs, as well as indirect operating cost such as overhead,
taxed, insurances. It is assumed that 40% biogas energy is for electricity, 50% for steam, 10%
loss.
Results and Discussion
Microalgae Cultivation Economics
Table 3-3. Algae cultivation economics.
Parameters Values
Production scale
BG0011 cells production (ktonne/year) 133
BG0011 EPS production (ktonne/year) 160
Total algae biomass production (ktonne/year) 293
Capital cost (including fixed, installed and working capital)
Pond (million $) 308
Land (million $) 26.6
Pump (million $) 7.85
Total capital cost (million $) 342.45
Annual capital charges (million $) 40.22
Operating cost
Chemicals (P fertilizer: Ca (H2PO4)2 H2O) (million $/year) 1.3
Other operating cost (including utilities, maintenance and repairs, labor etc.) (million
$/year)
3.26
Total operating cost (million $/year) 12.26
BG0011 algae biomass production cost ($/tonne) 150
The BG0011 cultivation economics analysis details are shown in Table 3-3. The literature
algae cultivation values range from 150 - 6000 $/tonne, however, the studies vary from
assumptions (production scale, chemical prices, plant life, etc.) to different technical
specification (photobioreactor design, algal species, etc.). Thus, it is difficult to make a direct
52
comparison between different studies. Besides, models built on assumptions that need more
information to understand could make comparisons more complicated (Gubicza, et al. 2016).
Studied Cases of Anaerobic Digestion
Table 3-4. Process and economic assessment for purified biogas production through anaerobic
digestion of algae BG001 biomass.
Item Case 1
(Mesophilic
anaerobic
digester)
Case 2(a) (Low-
temperature
anaerobic
digester)
Case 2(b) (Low-
temperature
anaerobic
digester
Case 3
(Covered
anaerobic
lagoon)
Biogas production
scale (10^6
mmbtu/year)
3.7 3.7 1.85 3.7
The fixed capital
cost of anaerobic
digester (million $)
67.12 102 67.12 7.5
Other capital cost
except anaerobic
digester
16.3 million $ 16.3 million $ 12.3 million $ 16.4 million $
(Including
land: 11400 $)
Annual capital
charges (million
$/year)
9.8 13.9 9.3 2.8
Total raw materials
(algae biomass) cost
(million $/year)
43.8 43.8 43.8 43.8
Other operating
(labor, utility,
indirect, etc.) cost
(million $/year)
25.8 7.1 4.4 7.1
Utility cost (million
$/year)
21 2.3 1.4 2.3
Renewable natural
gas production cost
($/mmbtu)
21.5 19.3 17.6 14.6
The purified biogas production cost details are shown in Table 3-4. Case 2 contains two
scenarios: The size of anaerobic digester in Case 2(a) is two times of that in Case 1. This is
because the hydraulic retention time is longer under lower temperature, the volume of digester
needs be larger to keep the same production scale (the inflow rate). The size of anaerobic
53
digester in Case 2(b) is the same as Case 1, thus Case 2(b) has a lower production scale with the
other conditions as Case 2(a). The main contribution to the production cost of biogas is the
biomass cost. Considering a carbon credit of 10 $/tonne of CO2, the production cost of biogas
only drops 0.5 $/mmbtu, which is not significant. The results are comparable to Zamalloa et al.’s
research (the only paper focusing on the economics of renewable energy through AD, to our best
knowledge): 32.2 - 61.5 $/mmbtu with the algae biomass cost to be 115.4 - 166.4 $/tonne (0.17 -
0.087 euro/kwh with an algae biomass cost of 86 - 124 euro/tonne, 2011). The methane yield
could be obtained accordingly as 0.0124 mmbtu/kg of biomass, which agrees to the experimental
result 0.0125 mmbtu/kg of biomass (Zhang, Y. 2017).
Electricity Production Cost
On an energy potential basis, 40 % of total methane produced per year could support a
50MW power plant. Current residential electricity price is around 12 cents/kwh, while industrial
price is around 7 cents/kwh. As shown in Table 3-5, the electricity production cost from biogas is
0.15 $/kwh.
Table 3-5. The economics of biogas – electricity and steam system.
Item Value
Electricity capacity (million kwh/year) 435
The total capital cost of the CHP system (million $) (including fix capital cost and
10% working capital)
52.4
47.6
Capital charges (million $/year) 6.2
Steam credits (million $/year) 3.7
Raw biogas cost (million $/year) 47.7
Other operating cost (million $/year) 9.5
Electricity production cost ($/kwh) 0.13
Renewable energy technologies are usually more expensive than fossil fuel technologies.
The reasons could be environmental costs associated with fossil fuels that are not paid by the
ratepayers, mechanical difficulty in bioenergy production, start-up issues and so on. European
54
countries such as Germany and UK governments subsidize the production of renewable energy
by introducing feed-in tariffs. These tariffs may be important to make bioenergy industry
profitable.
Conclusion and Future Work
The cultivation of microalgae BG0011 and its economic feasibility as an energy source
through anaerobic digestion has been evaluated through a techno-economic analysis. The main
contribution to the bioenergy cost is the biomass cultivation cost. Improved algal biomass
productivities could be essential for the commercialization of algae-derived bioenergy. For
anaerobic digestion, the best case is a biomethane production cost of 17.1 $/mmbtu using
covered anaerobic lagoon and high-pressure water scrubbing purification, which is cost-effective
way to minimize the energy usage. Algal biofuel economics could be further improved by ways
such as using the solid parts which precipitated at the bottom of anaerobic digester and recycle
the CO2 produced in the whole process for algae cultivation, which closes the “carbon loop”.
The electricity produced from biogas was estimated to have a production cost of 15 cents/kwh.
The cost could be reduced by lower cost of biogas, which is largely depending on the algae
cultivation cost. Future work could involve more experimental data such as pilot plant
demonstration and validation of lab data as well as a sensitivity analysis of economic
performance with different algal biomass density, productivities, production scale and
biorefinery concepts of recycling and co-products production.
55
CHAPTER 4
TECHNO-ECONOMIC ANALYSIS OF EXOPOLYSACCHARIDES PRODUCTION FROM
CYANOTHECE SP. BG0011
Introduction
Microalgae/ Cyanobacteria have been studied and exhibited to be a promising natural
renewable resource of great potential to produce a bulk amount of biomass (Parmer, et al. 2011)
as well as its versatile roles in many applications (Moreno-Garcia, et al. 2017). The
polysaccharides that are present in the cyanobacteria/microalgae not only provide organic carbon
and energy reserves but also play an important part in the exploration of properties and
application for the microalgae. Many microalgae species (notably cyanobacteria) excrete
exopolysaccharides (EPS) to their environment. The EPS are natural polymers with higher
molecular weight and unique molecular structures. The EPS produced by microalgae ranges
from 0.5 g/L to 20 g/L (Delattre et al. 2016). The potential high productivity, compositional and
structural properties promote its possible industrial applications such as pharmaceutical (Arad
and Levy-Ontman, 2010) cosmetics, food, feedstock for biofuels (Simas-Rodrigues, et al. 2015)
and wastewater treatment (Wang, et al. 2016).
There is a growing number of research focusing on the structural data, biological
activities and specific properties of EPS and its potential applications (Rossi and Philippis, 2015;
Chug and Mathur, 2013). However, there are only a small number of EPS have found
commercial applications despite large numbers of chemically characterized polysaccharides
(Sutherland, 2007). The EPS production processes including microbial cultivation, harvesting,
downstream extraction and separation still face many challenges which hurdle the development
of EPS towards its industrialization. These challenges could be low yields, high cost of
production or low product quality (Delattre, et al. 2016). Thus, the conceptual design and
development of integrated production/recovery processes, predicting the yield, energetic and
56
economic performance, would substantially impact on the commercialization of microbial EPS
production (Freitas, et al. 2017): opening the large hydrocolloids and energy market and
competing with those from terrestrial plants aiming at large-scale production for applications that
can benefit humanity.
In this research, Cyanothece sp. BG0011 (Phlips, et al.1989) is the marine species of
interest: it was isolated from a coastal lagoon in the Florida Keys; This cyanobacteria fixes
nitrogen in the air and produces EPS. The EPS shows similar viscosity and shear rate to xanthan
gum. The Cyanothece sp. BG0011 EPS production process was simulated using Aspen Plus
V8.8. In the process simulation, the cultured microbial broth was obtained from an open pond
cultivation system. Following the experimental designed process, the EPS was extracted from the
broth using alcoholic precipitation. The alcohol used for the extraction process was recycled.
Capital and operating cost analysis was conducted and the EPS production cost was estimated.
The economic data is further compared to the production cost of commercial polysaccharides.
Materials and Methods
The Cyanothece sp. BG0011 cultivation process was discussed in previous chapters.
After the step of cultivation of BG0011. The biomass was sent for EPS production. The
processing systems consisted of a series of unit operations. A flowsheet of the process is shown
in Figure 4-1.
57
Filter Refrigeration 01
Refrigeration 02
Recycled ethanol
01Recycled ethanol
02
Distillation column
EPS
Make-up ethanol
Regenerated ethanol
Ethanol 01
Ethanol 02
Cultivated biomass
Centrifuge
BG0011 cells
Supernatant
Figure 4-1. Flowsheet of processing operations for EPS production from Cyanothece sp.
BG0011.
Process Description
BG001 biomass include not only the cells but also the EPS it secreted. The biomass
cultivation is impacted by many factors such as nutrients, pH, temperature which were not
discussed here. In large commercial ponds, an average daily productivity is around 10 g/ m2 with
a net photosynthetic efficiency of under 1%. Assuming the pond depth is 30cm, the steady state
of algae cell density is 1 g/L, while EPS is 1.2 g/L, based on the mass ratio between EPS : cell
biomass = 1.2 : 1. (Nguyet, et al. 2017). The scale of EPS production in this research is 160
ktonnes/year. The key input assumptions are shown in Table 4-1. The selected approach is the
most optimized but one of the more likely options to be feasible.
Table 4-1. Baseline BG0011 growth assumptions.
Item Open pond (values)
Scale (ktonnes EPS /year) 160
Productivity (g/m2/day) 10
Cell density (g/L) 1
EPS yield 1.2 g/g of cells
Operating days/year 360
58
The preconcentration system is largely based on the process developed by Anderson and
Eakin (1985). The culture broth was preconcentrated by a hollow fiber filtration system. Details
of the filter were discussed by Anderson and Eakin (1985). Here, the process reduced the culture
broth volume and reached a maximum total EPD concentration of 20g/L.
After filtration, the volume-reduced culture broth was centrifuged to separate the cells
and EPS portion. The supernatant containing EPS was sent for downstream process and the cells
which is rich in phosphorous and nitrogen could be used for fertilizer as a coproduct.
Extraction processes using alcoholic precipitation was used for EPS production from the
EPS-rich supernatant after centrifuge. The EPS was precipitated by the addition of an alcohol
solvent (ethanol in this case. The precipitation of EPS is impacted by the polarity of ethanol and
the temperature (Delattre, et al. 2016). In this research, ethanol (90% w/w) was used in the
culture broth with a volume ratio of 1:1. The used ethanol is recycled and distilled to the desired
concentration for reuse in the system. The ethanol-broth mixture was refrigerated at 4 C
overnight. Then the EPS precipitate was easily removed from the tank. The precipitation process
was repeated to remove the salts and impurities. For commercial EPS production such as xanthan
gum, the following steps would be drying and milling to the EPS powder. The ethanol
regeneration in the simulation was using rigorous distillation column (RadFrac). Different
recycle rates were considered for the final EPS price.
Economics Assumptions
Both the resulting mass and energy balance outputs from the simulation models and
Aspen Process Economic Analyzer from Aspen Plus were used to evaluate the capital cost
(CAPEX)and operating cost(OPEX). The capital cost of filtrate was estimated based on prior
literature studies (Anderson and Eakin, 1985). All the economic values were adjusted for year
2017. The capital was borrowed at 10% interest rate for 20 years.
59
The operating cost (including raw materials cost, utilities, labor, maintenance, etc.) was
mainly based on Aspen Process Economic Analyzer results. For the materials cost - the cultured
biomass cost was obtained from previous chapter’s studies about BG0011 cultivation cost. A
price of 0.54 $/kg of solvent ethanol was used for the analysis.
Results and Discussion
Throughout the proposed process model, the culture broth was processed to produce 160
ktonne of EPS and 135 ktonne of cells. Results of the economic analysis are shown in Table 4-2.
It has been found that the unit production cost of EPS is sensitive to the ethanol recycle rate.
With an ethanol recycle rate of 95%, the unit production cost of EPS is 6.1 $/kg. The unit cost of
EPS drops to 4.7 $/kg when 99% of ethanol recycled. The large capital cost contains the initial
ethanol input for the precipitation.
The cost summary of major purchased equipment is shown in Table 4-3. The utilities
required in the process are electricity, steam, propane. Utility requirements of the various
equipment operations were calculated and summed by Aspen Process Economic Analyzer.
Additionally, these utilities were used as purchased utilities and the unit costs for each of them
were set based on the default values in the software.
Table 4-2. Summary of economic analysis of the proposed process model for EPS production.
Items value
Total capital cost (million $) 3990
Capital charges (million $) 470
Total operating cost (million $) 480
Utility cost (million $) 214
Ethanol recycle rate 95%
Coproduct credits (million $) 9.5
Unit cost of EPS($/kg) 6.1
Anderson and Eakin (1985) made a cost estimation of 6.93 $/kg, where the EPS
productivities is 20 g/m2/day. The result favorably agrees with the cost estimation in this study
60
based on similar process steps and price adjustment for inflation. The production cost of EPS is
further compared with that of xanthan gum. Bajic, et al. (2017) made a cost estimation of around
4 $/kg of xanthan gum from confectionery industry wastewaters through process model
economics using working capital and operating cost. Lopes, et al. (2015) mentioned that the
production cost of xanthan gum is around 5 $/kg. Although all the production costs are
comparable, the production process are different as well as different assumptions made in the
cost estimation, which make cases more complicated. In this research, the drying and milling
cost was not included in the model, which takes 1 $/kg of final product (Bajic, et al. 2017).
Overall, the biomass productivities play a key role in the commercialization of EPS: the biomass
density in the culture broth have a great impact on the downstream process, energy and materials
consumption, which are the main cost found in this research.
Table 4-3. Cost summary - major purchased equipment.
Section Item Equipment cost (million $) Installed cost (million $)
Concentration Filter 38 22.7
Centrifuge 9.4 14
Precipitation Refrigeration 1.4 1.5
Separator 1 0.04 0.2
Ethanol recovery Heat exchanger 1 0.2 0.4
Distillation column 17 24
Heat exchanger 2 6.5 6.9
Conclusion
A process flowsheet has been developed for the EPS production from Cyanothece sp.
BG0011 using experimental data as well as assumptions for what could be plausibly achieved in
near term. The developed process model for EPS production presents an estimated production
cost of 4.7 $/kg of EPS with 99% ethanol recovered. The EPS production cost is favorably
comparable to xanthan gum, which has the potential to produce EPS commercially that could be
widely used in many application areas. Besides, the environmental benefits could be further
61
studied as the specie’s CO2 fixation through photosynthetic activities. This model can further be
updated with laboratory results for the technology transfer to industry. At the same time,
recognition of the cost extensive sections such as distillation for ethanol recovery from the
developed model could make directions for experimental work to develop more economically
and ecologically efficient EPS production technologies.
62
CHAPTER 5
TECHNO-ECONOMIC ANALYSIS OF BIOBUTANOL PRODUCTION USING A
“HYBRID” CONVERSION APPROACH
Introduction
The traditional fermentation method for butanol production is called Acetone–butanol–
ethanol (ABE) fermentation. ABE fermentation has been carried out industrially throughout the
United States during the first half of last century, but was discontinued in the early1960s due to
the petrochemical industry’s competition (Ezeji et al., 2007). The main problems include high
feedstock cost, product inhibition, low ABE yield, low productivities and inefficient recovery
processes. However, butanol has increasingly attracted researcher’s attention for its various
advantages. Specially, utilizing cost effective cellulosic feedstock has motivated biosynthesis of
butanol in recent era (Kumar et al. 2012). Table 5-1 shows the status of leading biofuel
companies producing bio-butanol.
Economic analysis of ABE fermentation has been performed (Pfromm et al. 2010; Kumar
et al. 2012; Tao et al. 2013; Qureshi et al., 2013) regarding to different feedstocks and process
parameters (fermentor size, plant capacity, production yield, etc.). In these studies, the ABE
fermentation butanol yields are 0.11-0.3 g/g biomass. Many of these studies are in the lab scale
and with additional assumptions. The low yields are due to the low concentration of butanol in
the fermentation broth (12–18 g/l) and a variety of inhibitory chemicals (furfural, HMF, etc.)
generated before and during fermentation. The industrially confirmed yield 0.11 g butanol/g of
corn corresponds to 34 wt% conversion of solvents (Pfromm et al. 2010). Debates existed in
energy yield comparison between ethanol fermentation and ABE fermentation (Wu et al. 2007;
Swana et al. 2011; Tao et al. 2013). Considering the superior features of butanol as well as low
production level of ABE fermentation. A new scheme for “hybrid conversion” process is
promising: using anaerobic bacteria to produce an alternative intermediate - butyric acid, which
63
has a higher titer (more than 60g/l), and then convert butyric acid to butanol through a catalytic
process (more than 98% conversion rate) (Lee et al. 2014).
Table 5-1. The status of bio-butanol production in leading biofuel companies.
Company Product Status Future
Cobalt Technologies n-butanol scale validation finalizing the
commercial facility
Gevo isobutanol Conversion of corn
ethanol plants for
butanol production,
process optimization
More plants for
Cellulosic isobutanol
Eastman n-butanol Producing n-butanol
from petroleum
Commercialization of
the bio-catalysis
technology for
producing butanol
Green biologistics n-butanol Producing n-butanol
from corn cobs and
stalk
Building the plant for
butanol production
from corn
Butamax isobutanol process piloting and
risk mitigation,
beginning of
iobutanol retrofit
project
Commercial
biobutanol production
Butalco GmBH isobutanol Fermenting xylose
into isobutanol by
yeast strain
Develop integrated
production processes
Cathay Industrial
Biotech
n-butanol scaled-up biobutanol
production
Improve productivity
and expand
ZeaChem butanol Indirect production of
butanol from ethanol
-
There is rare research about the comparisons of traditional ABE fermentation and the
butyric acid to butanol catalytic process. The biomass for biofuel production has been studied
intensively, four major domestic lignocelluloses (Switchgrass, Hybrid poplar, Corn stover,
Wheat straw) are representative for their high cellulose content and biomass yield per unit area
(Swana, et al. 2011). Thus, this research will focus on bio-butanol production with
lignocellulosic feedstock. One of the major bottleneck for butyrate production is the difficulty in
separating butyric acid from the fermentation broth. Recovery methods (distillation processes)
64
were discussed to separate butyric acid/butanol from other byproducts, mainly acetic
acid/ethanol. Different biorefinery scenarios (product recovery) were discussed in a perspective
of energy and economic analysis.
Literature Review of Biobutanol Production Process
Description of Butanol Production Process
Two strategies for butanol production from lignocellulosic materials will be discussed in
this research. One is traditional ABE fermentation, the other is butyric acid-to-butanol catalytic
process. For ABE fermentation, Figure 5-1 shows the bioconversion process steps of butanol
from lignocellulosic biomass. The ABE fermentation faces many problems as this four-carbon
alcohol is very toxic to the production microbes. This could cause the low concentration of
microbes in the fermentation broth, low yield of butanol, and high cost of recovery. To overcome
this challenge, Qureshi et al. (2013) pointed out two applied approaches. One is to develop new
strains which are more tolerant to butanol, the other is focused on the recovery process-
simultaneously recovery butanol product to control the toxicities to the microbes. The
simultaneous recovery technique has achived 461g/L ABE totally. One feasible and promising
strategy is to ferment lignocellusic biomass to butyric acid, and then convert butyric acid to
butanol (Ebert, 2008; Dwidar et al., 2012). Butyrate production with this strategy is 3-5 times
more than the current maximum seen of butanol (Dwidar et al., 2012). This process is also called
“hybrid conversion” (Lee et al., 2014) or “indirect fermentation” (Ju, et al. 2010) of butanol
production. The butyric acid production process is similar to butanol production process. The
difference is the selection of fermentation inoculums and specific conditions in each step.
65
Figure 5-1. The steps of butanol production from ABE fermentation process
Fraction/pretreatment of lignocellulosic biomass
The lignocellulosic biomass contains three principal constituents: cellulose,
hemicellulose and lignin (as shown in Figure 5-2.). Lignocellulose is largely found in the cell
walls which have a complex structure where lignin is covalently bonded to hemicellulose. The
structure creates a resistant barrier for hydrolytic enzymes to gain access to the sugar polymers:
cellulose and hemicellulose. Thus, the pretreatment step is to open up that tight structure, remove
the protective layers of either hemicelluloses or lignin and reduce cellulose crystallinity to
increase the accessibility of cellulose.
66
Figure 5-2. Spatial arrangement of cellulose hemicellulose and lignin in the cell walls of
lignocellulosic biomass. (Brandt et al., 2008).
Pretreatment is project to be the most expensive step affecting the production cost of
lignocellulosic ethanol (Yang and Wyman, 2009) and has been intensively studied (Cheng, 2009;
Kumar, et al. 2009; Jurgens et al. 2012). The pretreatments are expected to be an economic way
to improve the formation and the ability for formation of sugars without degrading or loss of
carbohydrate and formation of inhibitive byproducts for the subsequent hydrolysis and
fermentation (Kumar, et al. 2009). The pretreatment methods can be classified as
Physical/mechanical pretreatments, thermal pretreatments, Ammonia fiber explosion (AFEX),
and chemical pretreatments.
Physical pretreatment. It mechanically employs machinery chipping, grinding, or
milling to reduce the size of biomass and the cellulose crystallinity improving easy acid/enzyme
access (Lu, 2011). Small particle size can improve the efficiency of downstream process,
67
however, very small sizes will consume more energy and maybe difficult for downstream
pretreatment. (Talebnia, et al. 2010).
Thermal pretreatment. Steam explosion, liquid hot water treatment and Ammonia fiber
explosion (AFEX) can be classified in this category because all these methods involve high
temperature. Steam explosion employs high temperature steam (up to 160–260 °C) at high
pressure (saturated steam of water at 0.69-4.83 MPa) to treat the lignocellulosic biomass for a
short time (several seconds to minutes) before a sudden release of pressure (to atmospheric
pressure) (Faik, 2013; Lu, 2011). In the process the biomass undergoes an explosive
decompression due to the sudden pressure drop (Lu, 2011). The steam explosion method can
remove more lignin easily (Thirmal and Dahman, 2012) and produce low inhibitors such as
HMF and furfural. Compared to steam explosion pretreatment, liquid hot water pretreatment
cooked the biomass under pressures in the liquid state of water. This method solubilizes the
hemicellulose and lignin so that less monomeric sugars are converted, as well as less inhibitors
but limited amount of lignin is released. These two methods are inefficient in pretreating
lignocellulosics from grass such as switchgrass (Faik, 2013). Ammonia fiber explosion is another
thermal pretreatment method that has similar process with steam explosion. The major difference
is that biomass is exposed to ammonia instead of steam. This method is effective in enhancing
the digestibility of switchgrass (Alizadeh, 2005). However, this method too expensive (ammonia
price and recycling) for commercialization.
Chemical pretreatment. Acidic pretreatment, alkaline pretreatment and organic solvent
pretreatment can be classified in this category. For acidic method, wheat straw (8.6% w/v) was
pretreated by 1% v/v dilute sulphuric acid mixed in distilled water (Qureshi et al. 2008); pH was
adjusted to 5.0 for fermentation. One advantage of acidic pretreatment is that most of
68
hemicellulose was hydrolyzed (Thirmal and Dahman, 2012). Although acidic pretreatments have
good results for cellulose hydrolysis, the process is non-economical due to toxic and corrosive
acid. Alkaline pretreatment includes the use of sodium hydroxide, potassium hydroxide, calcium
hydroxide, ammonia hydroxide, monoethanolamine (MEA), and lime etc. Among all these
alkaline pretreatments, MEA was the best pretreatment to remove lignin (Thirmal and Dahman,
2012). Alkaline pretreatments methods have relatively low energy consumption and long period.
Among all these alkaline pretreatments, lime is cheap and does not require recovery (Jurgens et
al. 2012). However, the precipitation of calcium oxalate in lime pretreatment process is an issue
which causes serious problems in equipment scaling (Zhu et al. 2010; Mats et al. 2012; Xu and
Huang et al. 2014).
Comparisons have been made to summarize the pretreatment methods. Figure 5-3 gives
the advantages and disadvantages of each pretreatment method used for butanol production.
Figure 5-3. Qualitative comparisons of different pretreatment or fractionation methods. (Jurgens
et al., 2012).
Detoxification
Detoxification is to remove the inhibitors generated in the pretreatment process for the
fermentation. During pretreatment and hydrolysis of fiber-rich agricultural biomass, chemicals
such as weak acids (i.e., acetic acid, formic acid), furan derivatives (i.e., hydroxymethyl furfural
69
(HMF) and furfural), salts (i.e., sodium acetate, sodium chloride, and sodium sulfate) and
phenolic compounds (i.e., ferulic acid) are produced (Bara, et al. 2014). They are inhibitors to
specific Clostridium strain(s). Hemicellulose degradation products such ρ-coumaric and ferulic
acids decrease growth and ABE production by C. beijerinckii BA101 significantly. Furfural and
HMF have stimulatory effect on the growth of C. beijerinckii BA101 instead of inhibition to the
microorganism and ABE production (Ezeji, et al. 2007). However, HMF, furfural, acetic acid are
inhibitors using Clostridia acetobutylicum ATCC824 (Sun et al. 2012). In addition, butanol is
itself inhibitory to the most clostridia strains. Figure 5-4 shows the formation of microbial
inhibitors during pretreatment and ABE fermentation processes. Table 5-2 shows the
detoxification methods.
Figure 5-4. Microbial inhibitors formation during pretreatment and ABE fermentation processes.
(Bara, et al. 2014).
70
Table 5-2. Summary of detoxification method with respect to the inhibitors.
Detoxification method Inhibitor
Electrolysis (Qureshi et al. 2008) NaCl
Membrane filtration (Sun et al. 2012) HMF, furfural, acetic acid
Anion exchange resin (Amberlite XAD-4)
(Nilvebrant et al. 2001)
phenolic compounds, furan aldehydes,
and aliphatic acids
Liming (Sklavounos et al. 2011) Sulfate, lignin
Adsorption: activated carbon/ polymeric
adsorbents (Wang et al. 2011)
phenolics
Fermentation and reactors
Butanol-producing microbes include traditional strains and genetically engineered strains.
The naturally butanol producing clostridia include acetobutylicum (Figure 5-5), beijerinckii,
saccaroperbutylacetonicum, saccharoacetobutylicum, aurantibutyricum, pasteurianum,
sporogenes, and tetanomorphum and cadaveris. Among these species, C.acetobutylicum,
C.beijerinckii, C.saccharoacetobutylicum, and C.saccaroperbutylacetonicum are the primary
producers with good butanol production and yields (Lee et al., 2008). Substrate utilization
ability, pH, temperature, and product profiles vary from each other of the species. C.beijerinckii
was the best available specie to produce high composition of butanol, among which the strain C.
beijerinckii P260 and C. beijerinckii BA101 were demonstrated to best strains to produce highest
butanol production in previous studies (Thirmal et al. 2012). Escherichia coli and Saccharomyces
cerevisiae are engineered strains for butanol production. Although some species have achieved
higher butanol production level or more tolerant to butanol, no breakthrough improvement of
butanol production strains have been developed (Qureshi et al., 2013).
71
Figure 5-5. Clostridium acetobutylicum. (Yarris, 2012).
There are two phases in the butanol fementation by clostridia. Figure 5-6 shows the life
cycle of these natural butanol producers-clostridia. During the first phase, which is known as
acidogensis, acids (acetate and butyrate) and carbon dioxide are produced while the microbes has
exponential growth, lowering the pH of the medium. Then, the second phase, which is known as
the solventogensis, starts when the pH reaches a critical point. Acids are reassimilated and
converted to solvents (acetone, butanol and ethanol) (Lee et al., 2008).
Figure 5-6. The life cycle of Clostridia. (Berezina, et al. 2011).
72
For butyric acid production, prime producers are also clostridium strains including C.
butyricum, C. tyrobutyricum, and C. thermalbutyricum. Among these species, C. tyrobutyricum
is most promising for its high productivity and tolerance with butyric acid. The fermentation
process needs to be kept in the acidogensis phase without producing solvents by ways such as a
high ATP concentration.
Batch fermentation. Batch fermentation process (batch reactor) refers to the fermenting
process that all ingredients are filled in one tank of fermentor, starting with the inoculation and
ending with the retrieval of the product with no intermediate steps (Parulekar, 2003). There are
two types of batch process: batch and fed-batch. During the batch run, the former has no addition
or withdraw of materials while the latter has materials to be added. Compared to traditional
batch reactor, fed-batch fermentation (fed-batch reactor) give higher productivity due to adding
highly concentrated substrates into reactor at intervals to maintain a desirable substrate
concentration, however, fed-batch fermentation is feasible only if the reactor is coupled with
product removal stage to avoid butanol toxicity resulting from the addition of high substrate
concentrations (Ezeji et al., 2012). In the research of ABE recovery by pervaporation using
silicalite–silicone composite membrane from fed-batch reactor of Clostridium acetobutylicum,
eight times more solvents were produced in this system, compared to a batch reactor, and in that
integrated fed-batch reactor, the solvent yield was found to be higher (0.34–0.37) than the batch
reactor (0.29–0.30) (Qureshi 2001). The simultaneous saccharification and fermentation has been
analyzed by Qureshi et al. (2008), it is found that simultaneous saccharification and fermentation
achieve higher butanol productivity than separate saccharification and fermentation. The
activities in a simultaneous saccharification and fermentation reactor are illustrated in Figure 5-7.
73
Figure 5-7. Different activities occurred during simultaneous saccharification and fermentation in
batch process. (Thirmal, 2012).
Continuous fermentation. In continuous fermentation, nutrient medium is continuously
added to the bioreactor and an equivalent amount of cell suspension is simultaneously removed
from the system. Continuous fermentations have an advantage of shorter downtime (cleaning,
sanitizing, filling), automatic operation tends to be simpler than in batch fermentations and
usually higher productivity is achieved (Li et al., 2011). However, conducting continuous
fermentation for a longer period increases the chances of microorganism infection and
degeneration. Continuous fermentation could be conducted with free cells (suspended cell
continuous reactor), cell recycling or using immobilized cell fermentation (immobilized reactor).
The continuous fermentation with free cells could not achieve high productivities due to its non-
applicability at high dilution rates (cell wash out). Figure 5-8 shows the advances in continuous
fermentation of butanol with suspended cell, immobilized cells and cell recycling.
74
Figure 5-8. Recent continuous fermentation methods for ABE production along with solvent
yield, productivity and total solvents. (Jurgens et al., 2012).
Separation of butanol products from the fermentation
Until now, all industrial ABE processes are using conventional, energy intensive
distillation (Jurgens, et al. 2012). Distillation is also the only method that separate ABE
completely from the broth. In addition to distillation, there are various alternatives (Figure 5-9).
Energy consumption is an important criterion for those methods.
Figure 5-9. Alternative butanol recovery process: A. Gas stripping B. Pervaporation C. Liquid-
liquid extraction D. Adsorption. (Lu, 2011).
75
Membrane methods. Pervaporation, perstraction, reverse osmosis are recovering
methods involving membrane for separation ABE products. Pervaporation method (Figure 5-10)
is a promising method using a selective non-porous membrane. It does not harm the microbes
and potentially less expensive than distillation. This method has been studied intensively
(Marszałek, et al., 2012; Qureshi, et al., 2001; Thirmal, et al., 2012; Heitmann, et al., 2012). The
membrane with stability, high selectivity, and high flux are desired. Heitmann et al. investigated
the pervaporation performance of supported ionic liquid membranes (SILMs), which shows
advantageous mass transfer properties compared to conventional polymer membranes. The
perstraction method is an extraction process in which the aqueous phase and the solvent are kept
apart by a membrane. Reverse osmosis has been demonstrated the feasibility of being used to
reclaim water from an anaerobic fermentation obtained from the biohydrogen production process
(Diltz et al., 2007). The advantages of membrane method are that it is simple to operate and low
in energy consumption. The drawbacks are that it is not stable and the achievable flux through
the membrane is low.
Figure 5-10. Illustration of a pervaporation process. (Vane, 2008).
76
Gas stripping and flash. In gas stripping, nitrogen or hydrogen, CO2 are introduced
into the fermentation broth and capture all the volatile solvents in the broth and the solvents are
condensed from the gas. Continuous flashing is a method referring to abrupt pressure reduction
(German et al. 2012). The advantage of gas stripping method is that it could utilize the
fermentation gas as the stripping gas and operate at the fermentation temperature with or without
solids removal. The disadvantage is that it has a low selectivity and poor removal efficiency.
Both gas stripping and flash are relatively energy intensive.
Adsorption. Molecules of selective adsorption are put on a solid phase to remove the
components from a fluid phase. This method is promising when used with other methods such as
gas striping (Jurgens, et al. 2012). However, the adsorption materials have low capacity and
relatively low selectivity, which could be expensive (Jurgens, et al., 2012; Kaminski, et al.,
2011). In addition, adsorbent fouling by cells and adsorption of other fermentation components,
such as nutrients, substrates and acids, have been the major concerns of applying adsorption
technology with fermentation to recover alcohols (Vane, 2008).
Liquid-liquid extraction. In this case, fermentation broth is in contact with extractant.
Due to the selectivities difference, alcohols or water are removed from fermentation broth into
the extractant (Ezeji et al., 2004; Vane, 2008). The solvents must meet the following
requirements: 1. Non-toxic to human and environment, as well as the producing organism. 2. The
solvent should be inexpensive, easily available, sterilizable. 3. The fermentation products should
be easily recoverable from the solvent. 4. The solvent should be non-emulsion forming and low
viscosity.
Soybean-derived biodiesel was used as the extractant for the butanol from dilute aqueous
solutions (Adhami et al., 2009). Neither this method requires further process for separating the
77
butanol after the extraction nor is biodiesel toxic to the microbes in the broth. This potential
makes it possible that the production of butanol/biodiesel could be an integrated process
(Adhami et al., 2009). Common solvents’ optimal properties for ABE extraction have also been
studied, and mesitylene could then be identified as novel solvent with excellent solvent
properties for ABE extraction in an external column by means of computer aided molecular
design, so an energy-efficient hybrid extraction-distillation downstream process with the novel
solvent mesitylene has been proposed (Korbinian et. al 2011).
Information on Biocatalyst Used in the Process
Lignocellulose mainly contains lignin, carbohydrate (hemicellulose and cellulose), ash,
protein, and some extractives (Kumar et al., 2009). Hemicellulose and cellulose are sugar
polymers, and can be converted into various pentose and hexose sugar such as xylose, arabinose
and glucose (Lu, 2011).
Cellulose is a very large polymer molecule composed of many hundreds or thousands of
glucose molecules (polysaccharide). The molecular linkages in cellulose form linear chains that
are rigid, highly stable, and resistant to chemical attack. Figure 5-11 shows three types of
enzymes applied to saccharification of cellulose into glucose molecules: endoglucanase,
exoglucanase and glucosidase. Cellulose is the substrate, cellobiose is the intermediate product
and glucose is the final product. Hemicellulose consists of short, highly branched, chains of
sugars. It contains five-carbon sugars pentose (usually D-xylose and L-arabinose), six-carbon
sugars hexoses (D-galactose, D-glucose and D-mannose) and uronic acid. Hemicellulose is
amorphous and relatively easy to hydrolyze to its constituent sugars. When hydrolyzed, the
hemicellulose from hardwoods releases products high in xylose (a five-carbon sugar). The
hemicellulose contained in softwoods, by contrast, yields more six-carbon sugars. Various
78
hydrolytic enzymes degrade hemicellulose (Figure 5-12). For ABE production of butanol, the
enzymes introduced by C. acetobutylicum are shown in Figure 5-13.
Figure 5-11. Saccharification of cellulose into glucose molecules. (Thirmal, et al. 2012).
Figure 5-12. Polymeric chemical structure of hemicellulose and targets of hydrolytic enzymes
involved in hemicellulosic polymer degradation. (Kumar, et al. 2008).
79
Figure 5-13. Butanol biosynthesis pathway in C. acetobutylicum. Circled numbers refer to the
enzymes employed: 1. acetyl-CoA acetyltransferase (thiolase); 2. β-hydroxybutyryl-
CoA dehydrogenase; 3. 3-hydroxybutyryl-CoA dehydratase (crotonase); 4. butyryl-
CoA dehydrogenase; 5. butyraldehyde dehydrogenase; 6. butanol dehydrogenase; 7.
phosphate acetyltransferase; 8. acetate kinase; 9. phosphate butyryltransferase; 10.
butyrate kinase; 11. acetoacetate decarboxylase; 12. CoA-transferase; 13. coenzyme
A (CoA)-acylating; and 14. NAD(P)H alcohol dehydrogenase. (Huang, et al. 2010).
As is shown in Figure 5-13, glucose is firstly metabolized to pyruvate, then acetyl-CoA,
Acetoacetyl-CoA and butyryl-CoA are formed from pyruvate. Butyric acid producing catalysts
include: thiolase, 3-hydroxybutyryl-CoA dehydrogenase and butyryl-CoA dehydrogenase, which
convert acetyl-CoA into butyryl-CoA; phosphotransbutyrylase (phosphate butyryltransferase),
which catlalyzes butyryl-CoA into butyryl phosphate; butyrate kinase, which catalyzes butyryl-
phosphates for the production of butyrate.
Metabolic Pathways and Stoichiometry
The major end products of ABE/IBE (isopropanol butanol ethanol) fermentations are
acetic acid, butyric acid, acetone/ isopropanol, butanol, ethanol, CO2 and H2. Other end product
80
such as lactic acid can be formed in minor amount by some Clostridia on experimental
conditions (Pimpa, 1991).
Units of Metabolic Pathways at Acidogenesis
The two metabolic units in the stage of organic acids formation are shown in Figure 5-14
and Figure 5-15: the unit of acetic and lactic acids formation and the metabolic unit of butyric
acid formation from glucose, respectively.
Figure 5-14. Metabolic unit of acetic acid (AA) and lactic acid (LA) production from glucose (G)
by butyric acid bacteria fermentations. (Pimpa, 1991).
81
Figure 5-15. Metabolic unit of butyric acid (BA) production from glucose (G) at acidogenic
stage. (Pimpa, 1991).
Units of Metabolic Pathways at Solventogenesis
The following (Figure 5-16 to Figure 5-18) show the metabolic pathways respect to
acetone/isopropanol, ethanol, butanol at solventogennesis.
82
Figure 5-16. Metabolic unit of acetone (A)/isopropanol (I) production from glucose (G) at
solventogenic stage. (Pimpa, 1991).
Figure 5-17. Metabolic unit of ethanol (E) production from glucose (G) at solventogenic stage.
(Pimpa, 1991).
83
Figure 5-18. Metabolic unit of butanol (B) production from glucose (G) at solventogenic stage.
(Pimpa, 1991).
Butyric acid to Butanol Catalytic Process
The butyric acid to butanol catalytic process is through the conversion of hydrogenation
of butyric acid in the vapor phase by a stable and selective catalyst. There is very limited
research about the catalysts, especially metal catalysts (Ju et al., 2010; Lee et al., 2014). A
commercial Cu/ZnO/Al2O3 has been investigated for the kinetics in the hydrogenolysis of butyl
butyrate to butanol (Ju et al., 2010). The rate of hydrogenolysis was approximately 0.67 order
with respect to butyl butyrate. Lee et al. (2014) proposed a ZnO-supported Ru-Sn bimetallic
catalysts, which could have more than 98% yield of butanol from biomass-derived butyric acid.
Sjoblom et al. (2016) reviewed current technologies and strategies for the catalytic upgrading of
84
butyric acid. Their research highlighted the importance of supported Ruthenium- and Platinum-
based catalyst and lipase which exhibit important activities and have the potential to make the
biorefinery concepts and process more sustainable. Nilsson et al. (2016) presented a process for
n-butanol production which combines a succinic acid fermentation with subsequent catalytic
process. However, the overall economy for the process are not justified due to the high cost of
succinic acid fermentation.
Methods
The research was focused on the catalytic process for converting butyric acid to butanol
of the “hybrid” conversion process (including butyric acid fermentation). The butyric acid
fermentation process was using results from literature (Sjöblom, et al. 2015). Here, butyric acid
was used as input after fermentation. Since the fermentation broth contains butyric acid and other
coproducts (mainly acetic acid), two scenarios were investigated:
Scenario 1: First catalytically convert the acids (butyric acid and acetic acid) in the
fermentation broth to alcohols, and then separating the alcohols to around 95% mass purity.
Scenario 2: First separate the two acids, and then catalytically convert each of them to
their corresponding alcohol, and finally purify the alcohol to 95% mass purity.
The thermodynamic properties of butyric acid and acetic acid shown in Table 5-3.
Considering a plant capacity of 30 million gallon/year of butanol, assumptions made in this study
are as the following:
• Assume acetic acids and butyric acid could be catalyzed by the same catalyst (ZnO-
supported Ru-Sn bimetallic catalyst).
• Assume the catalyst have the same selectivity (99.9%) and conversion rates (98.6%)on
both acetic acids and butyric acid.
• Assume the concentration of acetic acids and butyric acid have no effect on the catalyst’s
selectivity and conversion rates.
85
• The catalytic process was operated on the same condition: 265 °C and 25 atm
• The concentration of butyric acid and acetic acid in the fermentation are 58.8 g/L and
11.46 g/L, respectively.
• The capital cost is borrowed at an interested rate of 10% for 20 years.
Table 5-3. Thermodynamic properties of acetic acid and butyric acid
Component Formula Molar mass Boiling point
Acetic Acid CH3COOH 60 g/mol 244.6°F
(118.1°C)
Butyric Acid C4H8O2 88 g/mol 326.3°F
(163.5°C)
The catalytic process is through the conversion of hydrogenation of acids in the vapor
phase by a stable and selective catalyst. Metal catalysts such as Cu/ZnO/Al2O3 and ZnO-
supported Ru-Sn bimetallic catalysts could have more than 98% yield of butanol from biomass-
derived butyric acid. The selectivity (Ratio of substrate converted to desired product to total
substrate converted, addressing unwanted reactions) and conversion rates are important criteria
in selecting the catalysts. Here, the main reactions are:
𝐴𝑐𝑒𝑡𝑖𝑐 𝑎𝑐𝑖𝑑 + 2𝐻2 → 𝐸𝑡ℎ𝑎𝑛𝑜𝑙 + 𝑊𝑎𝑡𝑒𝑟
𝐵𝑢𝑡𝑦𝑟𝑖𝑐 𝑎𝑐𝑖𝑑 + 2𝐻2 → 𝐵𝑢𝑡𝑎𝑛𝑜𝑙 + 𝑊𝑎𝑡𝑒𝑟
Then Aspen plus 8.8 was used to simulate the processes of the two scenarios and the
economic performance are evaluated.
Scenario 1: The flowsheet of the process of scenario 1 is shown in Figure 5-19. The feed
broth and hydrogen are introduced into the catalytic reactor R1, where acetic acids and butyric
acid are converted to ethanol and butanol, respectively. The effluent from the reactor goes into a
distillation column (BEERCOL). Here, since there are two azeotropes forms: ethanol and water,
butanol, and water (as analyzed by Aspen show in Figure 5-20). The distillate (S2) contains most
ethanol and butanol as well as a portion of water. The S2 is sent for further distillation SEPDIST,
86
where ethanol and butanol are separated for individual distillation for a 95% mass purity. The
distillation column ETOHD produce the target ethanol and column BTOHD produce the target
butanol. For the butanol purification, a decanter is used for two liquid phase separation for
removing water. Unlike the homogeneous azeotrope found in the ethanol/water system, the n-
butanol/water azeotrope is heterogeneous; thus, two liquid phases occur in the decanter. This
process refers to the double effect distillation (shown in Figure 5-21) to obtain ABE as final
products (Naleli, 2016). Here, the property method chosen is UNIQUAC. Vapor-liquid
equilibrium for ethanol and butanol are shown in Figure 5-22 and Figure 5-23. The ternary
diagram for butanol ethanol and water is shown in Figure 5-24.
H2
BrothReactor(R1)
Distillation column
(BEERCOL)Distillation
column (SEPDIST)
Distillation column (ETOHD)
Distillation column
(BTOHD)
Decanter
Distillate (S2)
Ethanol
Butanol
Water
Water
Distillate (ethanol-rich)
Condensate (butanol-rich)
EXC2
EXC1
Figure 5-19. PFD of Scenario 1.
87
Figure 5-20. Azeotropes in Scenario 1
Figure 5-21. PFD for Double effect distillation to obtain ABE as final products. The main
equipments are five columns, Scrubber and a Decanter. (Naleli, 2016).
88
Figure 5-22. Vapor-Liquid equilibrium of the mixture of ethanol and water (1 atm).
Figure 5-23. Vapor-Liquid equilibrium of the mixture of butanol and water (1 atm).
y-x diagram for ETHANOL/WATER
Liquid/vapor mole fraction, ETHANOL
Vap
or
mo
le f
ract
ion
, ETH
AN
OL
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95 1.000.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
1.0 atm
y-x diagram for BUTANOL/WATER
Liquid mole fraction, BUTANOL
Vap
or
mo
le f
ract
ion
, B
UTA
NO
L
0.00 0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95 1.000.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
0.40
0.45
0.50
0.55
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
1.0 atm
89
Figure 5-24. Ternary diagram for butanol ethanol and water.
Scenario 2: The flowsheet of the process of scenario 1 is shown in Figure 5-25. Different
from scenario 1, the mixture broth of butyric acid and acetic acid is sent to the distillation
column DIST01 for separation. Here, the acetic acid solution AA is obtained at the bottom of the
distillation column, and the azeotrope of butyric acid and water are obtained as distillate, as
analyzed by the azeotrope search report (Figure 5-26) in Aspen. Then the acetic acid and butyric
acid are sent to catalytic process separately. In reactors RAA and RBB, each acid is converted to
its alcohol. The ethanol and butanol solution obtained are sent for purification by distillation.
Then over 95% mass purity alcohols are obtained. The butanol purification process is similar to
scenario 1.
90
Broth
Distillation column(DIST01) acetic acid-rich
stream (AA)
butyric acid-rich stream (BA)
Reactor (RBA)
Reactor (RAA)
Decanter
Butanol
Ethanol
Flue gas
Flue gas
Waste water
Waste water
Distillation column
(PURF02)
Distillation column
(PURF01)EX01
EX02
Figure 5-25. PFD of Scenario 2.
Figure 5-26. Azeotropes in Scenario 2.
91
Results and Discussion
The capital cost and operation cost were obtained by Aspen Process Economic Analyzer
with its built-in evaluation method of sizing based on the mass and energy balance. The
economic analysis summary is shown in Table 5-4. The cost of the main equipment is shown in
Table 5-5. The utilities include electricity, steam, refrigerant and cooling water. The overall
economic performance of scenario 1 is better than scenario 2 regarding to the significant savings
in operating cost. The high capital and operating cost of Scenario 2 is due to the distillation
difficulties in separating butyric acid and acetic acid and huge utility requirement. Here, without
considering the butyric acid fermentation cost, the unit cost for scenario 1 is 0.21 $/L butanol,
while scenario 2 has a unit cost of 0.84 $/L butanol. Thus, the process in which the butyric acid
fermentation broth was catalyzed before products recovery have better economic performance.
Butyric acid fermentation process is similar to bioethanol fermentation process. The major
difference is the microbes for the fermentation. Considering the butyric acid concentration of
58.8 g/L (Sjöblom, et al. 2015), the ethanol fermentation has similar titer. The lignocellulosic
ethanol fermentation process (in previous chapter) was used as a reference for the economic
analysis of butyric acid production cost. The butyric acid production cost is estimated to be 0.71
$/L. To produce 1 kg of butanol, 1.19 kg of butyric acid is required. The butanol production cost
is estimated to be 0.87 $/L in Scenario 1. Due limited studies in the literature about the
production cost of butyric acid, a future work of evaluating the production cost of butyric acid
for the specific fermentation methods is necessary.
Baral and Shah (2016) estimated the butanol production cost from traditional ABE
fermentation to be 1.8 $/L. Qureshi et al. (2013) also presented a technoeconomic analysis of
ABE fermentation with a production cost of 1 $/L. However, different assumptions were made
92
regarding to the plant capacity, biorefinery concepts, recovery methods. It is difficult to make
comparisons in many aspects.
Table 5-4. Economic summary of butyric acid to butanol catalytic process.
Scenario 1 Scenario 2
Total capital cost (million $) 15.5 27.5
Capital charges (million $) 1.8 3.2
Total operating cost (million
$)
21.7 92.7
Total utility cost (million $) 18.3 83.5
Table 5-5. Major unit operation equipment cost and installation cost. Name Equipment Cost (million $) Installed Cost (million $)
Scenario 1 Reactor (R1) 0.27 0.46 Distillation column (SEPDIST) 0.38 0.88 Heat exchanger (EXC1) 0.44 1.05 Heat exchanger (EXC2) 0.08 0.25 Decanter 0.02 0.13 Distillation column (ETOHD) 0.15 0.55 Distillation column (BTOHD) 0.11 0.48 Distillation column (BEERCOL) 1.35 2.75
Scenario 2
Distillation column (DIST01) 8.57 14.97 Heat exchanger (EX01) 0.02 0.09 Heat exchanger (EX02) 0.63 0.99 Decanter 0.02 0.12 Distillation column (PURF01) 0.21 0.66 Distillation column (PURF02) 0.15 0.51 Reactor (RAA) 0.08 0.23 Reactor (RBA) 0.14 0.32
The butanol purification process could be optimized as the following: Butanol-water
system will form two liquid phases once condensed. This is a steady state simulation of
azeotrope mixture of system butanol and water in which case two columns were used with
decanter located in between (Figure 5-27). Decanter separated two liquid phases and returned on
93
aqueous phase and organic (butanol rich) phase to column as reflux stream. Recycles are needed
and not discussed in this study, which could be the future work.
Figure 5-27. PFD of steady state butanol purification in water solutions. (Luyben, 2008).
Conclusion
This research studied different scenarios about the butyric acid to butanol catalytic
process to obtain the final product – butanol. Catalytically convert the acids (butyric acid and
acetic acid) in the fermentation broth to alcohols before separating the alcohols shows promising
economic advantages. With the advantage of a higher titer than ABE fermentation, butyric acid
fermentation still needs techno-economic analysis to investigate whether it achieves a
competitive cost or not. Besides, the waste stream from the whole process is another area for
future studies with the purpose of recovering energy and improving economic performance.
94
CHAPTER 6
CONCLUSIONS
The research presented in this dissertation evaluated the sustainability of biofuels
production from an economic perspective with the integration of environmental considerations to
the production process. Firstly, lingo-cellulosic ethanol production was evaluated through a
techno-economic analysis. An integrated flowsheet for ethanol production from sugarcane
bagasse was developed and the model was validated using data collected from the pre-
commercial scale Stan Mayfield Biorefinery Pilot Plant. The design was scaled up and the
impact of introducing anaerobic digestion of waste streams and nutrient recovery from digested
effluent on the overall mass and energy balance as well as economic feasibility was determined.
The biogas produced by anaerobic digestion has the potential to replace 68.3% of the fossil fuels
used for steam generation in the ethanol production process. The revenue from sale of
phosphorus-rich fertilizer from the phosphate precipitation process further reduced the ethanol
production cost to 53.48 cents/L from 54.20 cents/L without waste utilization. Thus the stillage
from lignocellulosic ethanol production was fully utilized for energy and nutrient recovery.
Biobutanol is an alternative biofuel to bioethanol. Biobutanol has many advantages over
ethanol as a fuel, however, the production of butanol still needs methods to increase yields,
reduce energy inputs and improve economic viability. An integrated flowsheet for butanol
production from lignocellulosic materials was developed and process simulation was conducted.
Two approaches were compared: conventional acetone-butanol-ethanol (ABE) fermentation and
butyric acid fermentation followed by its conversion to butanol using a catalytic process.
Different conversion strategies for butyric acid-to-butanol catalytic process were analyzed for
economic performance. Compared to the conventional production method, butyric acid to
butanol catalytic process shows economic benefits.
95
Algae as a new generation of biomass feedstock overcomes many challenges posed by
terrestrial plants like limited biomass resources, limited arable land, low biomass productivity,
direct or indirect effects on the food price. A process flowsheet was developed and a techno-
economic analysis was conducted to determine the economic feasibility of producing biogas
from algae, the conversion of biogas to electrical energy and the upgrading of biogas to
renewable natural gas. Algae production cost was 149.50 $/tonne. Renewable natural gas
production cost was estimated to be 14.6 $/MMBTU that included using covered anaerobic
lagoon for biogas production and high-pressure water scrubbing for biogas upgrading. The cost
of upgrading biogas was 0.09 $/kg of methane. Electricity production from the biogas was 13
cents/kwh . A techno-economic analysis for the production of polysaccharide product from
algae cultivation was also conducted. The polysaccharides production cost was 4.7 $/kg which
was favorably comparable with market price for xanthan gum. The main hurdle for the
development of algal biofuels’ commercialization was the algae cultivation cost, which could be
expensive due to high capital investment and low yields. Conversion technology such as
anaerobic digestion employed in this research could avoid energy-extensive process such as
algae harvesting and dewatering. On the way to fully explore the application of microalgae, some
bioproducts such as exopolysaccharides could benefit from high market prices if used for
pharmaceutical or cosmetics applications. This could be economically viabile than the case for
making fuels.
The estimated production cost of the selected biofuels was compared and summarized
based on a unit energy value. The ethanol production cost for the best scenario was 2.55
cents/MJ. Renewable natural gas from microalgae has a production cost of 1.38 cents/MJ.
Electricity from biogas produced using the same species as feedstock has an estimated
96
production cost of 3.61 cents/MJ. Though the cost is comparable with residential electricity
price, other biofuels has a lower cost on an energy basis. The estimated butanol production cost
from the hybrid process: butyric acid fermentation and catalytic process, was estimated to be
2.98 cents/MJ. The cost is higher than that of ethanol, but butanol is still promising as a liquid
fuel for transportation due to its various advantages. Compare these costs to the average gasoline
price of 2.4 $/gal in 2017, which corresponds to 1.85 cents/MJ. In summary, it could be
concluded that biofuels are still not economically viable with the current fossil fuel prices, but
some biofuel such as renewable natural gas has the potential to be economic viable on an energy
basis.
Future work may include data validation from pilot plant studies on anaerobic digestion
and phosphate precipitation technology. These could be important not only in the ethanol
production process but also for algal biofuels and butanol. This is an approach to improve the
overall economics and reduce the environmental impacts. Lower algae cultivation costs are
expected to improve the overall economics of the algal biofuels, considering the high costs of
downstream conversion processes. Process optimization is still needed for utilizing the
byproducts such as CO2 for algae growth and waste (e.g. sludge) from the process.
97
APPENDIX A
ASPEN FLOWSHEET OF THE INTEGRATED PROCESS
98
APPENDIX B
STOICHIOMETRIES
Table a. Anaerobic digestion stoichiometry Anaerobic digestion stoichiometry conversion rate
Cellulose + 0.131707 Ammonia + 0.703659 Water → 0.658537 E.coli + 2.65427 Methane +
2.6872 Carbon dioxide
0.9
Hemicellulose + 0.107317 Ammonia + 0.758537 Water → 0.536585 E.coli + 2.21829
Methane + 2.24512 Carbon dioxide
0.9
Ethanol + 0.0373984 Ammonia → 0.186992 E.coli + 1.40183 Methane + 0.411178 Carbon
dioxide + 0.0841443 Water
0.9
Glucose + 0.146341 Ammonia → 0.731707 E.coli + 2.61586 Methane + 2.65244 Carbon
dioxide + 0.329263 Water
0.9
Lactic acid + 0.0731707 Ammonia → 0.365854 E.coli + 1.30793 Methane + 1.32622
Carbon dioxide + 0.164632 Water
0.9
Succinic acid + 0.095935 Ammonia + 0.284146 Water → 0.479675 E.coli + 1.49817
Methane + 2.02215 Carbon dioxide
0.9
Furfural + 0.0780488 Ammonia + 2.82439 Water → 0.390244 E.coli + 2.29512 Methane +
2.31463 Carbon dioxide
0.9
Acetic acid + 0.0487805 Ammonia → 0.243902 E.coli + 0.871952 Methane+ 0.884147
Carbon dioxide + 0.109754 Water
0.9
Cellobiose + 0.278049 Ammonia + 0.37439 Water → 1.39024 E.coli + 5.27012 Methane +
5.33963 Carbon dioxide
0.9
Xylitol + 0.123577 Ammonia → 0.617886 E.coli + 2.42561 Methane + 1.9565 Carbon
dioxide + 0.778047 Water
0.9
Xylose + 0.121951 Ammonia → 0.609756 E.coli + 2.17988 Methane + 2.21037 Carbon
dioxide + 0.274386 Water
0.9
Glycerol + 0.0747967 Ammonia → 0.373984 E.coli + 1.55366 Methane + 1.07236 Carbon
dioxide + 0.668293 Water
0.9
Table b. Electrolytes chemistry Reaction Type Stoichiometry
1 Equilibrium WATER + H2PO4- <--> H3O+ + HPO4--
2 Equilibrium H3PO4 + WATER <--> H3O+ + H2PO4-
3 Equilibrium WATER + HPO4-- <--> H3O+ + PO4---
4 Equilibrium ACETATE + WATER <--> CH3COO- + H3O+
5 Equilibrium HCL + WATER <--> CL- + H3O+
99
6 Equilibrium AMMONIA + HCO3- <--> WATER + NH2COO-
7 Equilibrium AMMONIA + WATER <--> OH- + NH4+
8 Equilibrium WATER + HCO3- <--> CO3-- + H3O+
9 Equilibrium 2 WATER + CO2 <--> HCO3- + H3O+
Equilibrium 2 WATER <--> OH- + H3O+
MGCO3(S) Salt MGCO3(S) <--> CO3-- + MG++
STRUVITE Salt STRUVITE + 2 H3O+ <--> MG++ + H2PO4- + NH4+ + 8 WATER
NAOH Dissociation NAOH --> OH- + NA+
DAP Dissociation DAP --> HPO4-- + 2 NH4+
MGCL2 Dissociation MGCL2 --> MG++ + 2 CL-
100
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BIOGRAPHICAL SKETCH
Na Wu was born in Gansu, China. She received his bachelor’s degree in economics from
Zhejiang University, China. Then, she got her master’s degree in statistics at University of
Florida. She worked as a research and teaching assistant under Dr. Pullammanappallil
supervision and towards her Ph.D in Agriculture operations management. After graduation, she
plans to work in the field of bioprocess simulation and engineering economic analysis.
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