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

To my grandma

3 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.

4 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

5 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

6 A ASPEN FLOWSHEET OF THE INTEGRATED PROCESS ...... 97

B STOICHIOMETRIES...... 98

LIST OF REFERENCES ...... 100

BIOGRAPHICAL SKETCH ...... 115

7 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

8 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

9 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

10 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).

11 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

12 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.

13 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.

14

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

15 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

16 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

17 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).

18 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).

19 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.

20 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.

21 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

22 (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).

Equipments (f. o. b.)

Materials for installation Direct project expenses Direct labor

Total direct

Bare module cost Total module cost Freight, insurance, taxes Grassroots capital Contingency & fee Auxiliary facilities Construction overhead Indirect project expenses Engineering expenses

Total indirect

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

23 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.

24 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).

25 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;

26 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

27 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

28 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

29 temperature in the hydrolysis reactor. 4. The reactors (pretreatment, fermentation) are followed by flash units for gas evacuating (carbon dioxide / water etc.).

Flash gas 1

Enzyme Phosphorous acid Flue gas Water Stream Retentate splitter Ethanol pH adjustment tank Scrubber Membrane Sugarcane Flash gas 2 bagasse Flash Stripping Rectification column column Screw conveyer Liquefaction tank Fermentation Pretreatment tank Flash tank Nutrient

Heat Steam Steam exchanger Seed propagation tank

Stillage 1 Stillage 2 Ammonia hyroxide

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

30 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.

Water

Valve Gas Pump Flue gas

Air Heat exchanger High pressure steam Air blower Biogas

Conbustion

Flash gas

Ethanol Biorefinery Liquid MgCl2 Stillage stream Decanter Flash Anaerobic digester

Air

PPR

Lignin-rich stream Fertilizer and treated water

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,

31 Hemicellulose, Ethanol, Glucose, Lactic acid, Succinic acid, Furfural, Acetic acid, Cellobiose,

Xylitol, Xylose, Glycerol, etc.). The general form for the stoichiometry is

퐶푥퐻푦푂푧 + 푏푁퐻3 → 푐퐶퐻1.8푂0.5푁0.2 + 푑퐶퐻4 + 푒퐶푂2 + 푓퐻2푂 .

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):

32 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).

33

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:

34 • 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.

35

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

36 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 57.97 57.97 60.21 57.97 production processes Anaerobic - 24.12 32.91 24.12 digester Struvite PPR - - - 9.17 (phosphorous precipitation reactor) Heat generation 6.25 6.25 6.25 6.25 Total direct cost 64.22 88.34 99.37 97.51 Total indirect 28.90 39.75 44.72 43.88 cost Fixed capital 93.12 128.09 144.09 141.39 investment Working capital 3.26 4.48 5.04 4.95 Total capital 96.38 132.58 149.13 146.34 investment

37 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

38 Table 2-4. Detailed yearly labor cost. Operator Literature Base case 1 2 3 requirements for No. of various types of units process equipment 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 1 2 3 case Name Rate Cost Rate Cost Rate Cost Rate Cost ($/hr) ($/hr) ($/hr) ($/hr) Electricity (kw) 813.1 63.01 813.06 59.95 844.79 65.47 813.1 63.01 Cooling Water 795.33 25.21 795.33 25.21 795.34 25.21 795.34 25.21 (m3/hr) Process Water 12,098,5 2.56 12,098,5 2.56 12,098,5 2.56 12,098,5 2.56 (kj/hr) 20 20 30 20 Natral gas 2.75 457.69 0.99 164.77 0 0 0.99 164.77 (kmol/min)

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

39 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.

40 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).

41 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.

42 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.

43 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.

44 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

45 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:

푈푛𝑖푡 푝푟표푑푢푐푡𝑖표푛 푐표푠푡 = (퐴푛푛푢푎푙 푐푎푝𝑖푡푎푙 푐ℎ푎푟푔푒푠 + 푇표푡푎푙 표푝푒푟푎푡𝑖푛푔 푐표푠푡 −

퐶표푝푟표푑푢푐푡 푐푟푒푑𝑖푡푠) / (퐴푛푛푢푎푙 푝푟표푑푢푐푡𝑖표푛).

Here, the annual capital charges are calculated as follows:

퐴푛푛푢푎푙 푐푎푝𝑖푡푎푙 푐ℎ푎푟푔푒푠 = [푇표푡푎푙 푐푎푝𝑖푡푎푙 푐표푠푡 ∗ 퐼푛푡푒푟푒푠푡 푟푎푡푒 ∗ (1 +

퐼푛푡푒푟푒푠푡 푟푎푡푒)^(퐿표푎푛 푝푒푟𝑖표푑) ]/[(퐼푛푡푒푟푒푠푡 푟푎푡푒)^(퐿표푎푛 푝푒푟𝑖표푑) − 1].

*Total capital cost= Total fixed cost + Working capital.

*Working capital is 10% of fixed capital.

46 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:

퐵퐺0011 (퐶푒푙푙푠 푎푛푑 퐸푃푆) + 푁퐻3 → 퐶퐻1.8푂0.5푁0.2 + 퐶퐻4 + 퐶푂2 + 퐻2푂

Raw biogas Algae Pond

Biogas purification ?

Cultured algae broth Anaerobic Digester ?

Combined heat and power ?

Mesophilic anaerobic Low-temperature digester anaerobic digester

Covered anaerobic lagoon Fertilizer

Sludge

Figure 3-1. Schematic of biorefinery scenarios.

47 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

48 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.

49 Biomethane

CO2 out

Raw biogas

Stripping column Scrubbing column Make-up MEA

Regenerated MEA

Make-up water

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: RadFrac, 10 stages, pressure: 1.2 bar 10 bar Stripping column RadFrac, 15 stages, pressure: RadFrac, 10 stages, pressure: 8 bar 1 bar Make up chemicals Water: 150 kmol/hr Water: 11500 kmol/hr MAE: 750 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 20 4.6 $/year) Utility cost (million $/year) 17 2 Purification cost ($/kg of 0.3 0.09 methane)

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

50 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 3.26 $/year) 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

51 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 Case 2(a) (Low- Case 2(b) (Low- Case 3 (Mesophilic temperature temperature (Covered anaerobic anaerobic anaerobic anaerobic digester) digester) digester lagoon) Biogas production 3.7 3.7 1.85 3.7 scale (10^6 mmbtu/year) The fixed capital 67.12 102 67.12 7.5 cost of anaerobic digester (million $) Other capital cost 16.3 million $ 16.3 million $ 12.3 million $ 16.4 million $ except anaerobic (Including digester land: 11400 $) Annual capital 9.8 13.9 9.3 2.8 charges (million $/year) Total raw materials 43.8 43.8 43.8 43.8 (algae biomass) cost (million $/year) Other operating 25.8 7.1 4.4 7.1 (labor, utility, indirect, etc.) cost (million $/year) Utility cost (million 21 2.3 1.4 2.3 $/year) Renewable natural 21.5 19.3 17.6 14.6 gas production cost ($/mmbtu)

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

52 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 52.4 10% working capital) 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

53 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.

54 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

55 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.

56 Cultivated biomass Supernatant Filter Refrigeration 01 Centrifuge Ethanol Recycled 01 ethanol Ethanol 02 01 Recycled ethanol BG0011 cells 02 Refrigeration 02

Make-up ethanol

Regenerated ethanol

Distillation column EPS

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

57 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.

58 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

59 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

60 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.

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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

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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 More plants for ethanol plants for Cellulosic isobutanol butanol production, process optimization Eastman n-butanol Producing n-butanol Commercialization of from petroleum the bio-catalysis technology for producing butanol Green biologistics n-butanol Producing n-butanol Building the plant for from corn cobs and butanol production stalk from corn Butamax isobutanol process piloting and Commercial risk mitigation, biobutanol production beginning of iobutanol retrofit project Butalco GmBH isobutanol Fermenting xylose Develop integrated into isobutanol by production processes yeast strain Cathay Industrial n-butanol scaled-up biobutanol Improve productivity Biotech production 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)

63

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.

64

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.

65

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,

66

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

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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

68

(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).

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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) phenolic compounds, furan aldehydes, (Nilvebrant et al. 2001) and aliphatic acids Liming (Sklavounos et al. 2011) Sulfate, lignin Adsorption: activated carbon/ polymeric phenolics adsorbents (Wang et al. 2011)

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).

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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).

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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.

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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.

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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).

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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).

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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

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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

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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).

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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

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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).

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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.

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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).

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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

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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.

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• 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:

퐴푐푒푡𝑖푐 푎푐𝑖푑 + 2퐻2 → 퐸푡ℎ푎푛표푙 + 푊푎푡푒푟

퐵푢푡푦푟𝑖푐 푎푐𝑖푑 + 2퐻2 → 퐵푢푡푎푛표푙 + 푊푎푡푒푟

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,

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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.

Ethanol

Distillate (ethanol-rich)

Distillation column Distillate (ETOHD) (S2)

Distillation EXC2 column (BEERCOL) H2 Distillation column (SEPDIST)

Butanol Condensate Broth Reactor(R1) (butanol-rich) Water

EXC1

Decanter Distillation column (BTOHD) Water

Figure 5-19. PFD of Scenario 1.

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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).

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y-x diagram for ETHANOL/WATER 1.00

0.95 1.0 atm

0.90

0.85

0.80

0.75

0.70

0.65

0.60

0.55

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Vapor mole fraction, ETHANOL fraction, moleVapor 0.35

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0.00 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 1.00 Liquid/vapor mole fraction, ETHANOL

Figure 5-22. Vapor-Liquid equilibrium of the mixture of ethanol and water (1 atm).

y-x diagram for BUTANOL/WATER 1.00

0.95 1.0 atm

0.90

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Vapor mole fraction, BUTANOL fraction, moleVapor 0.35

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0.00 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 1.00 Liquid mole fraction, BUTANOL

Figure 5-23. Vapor-Liquid equilibrium of the mixture of butanol and water (1 atm).

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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.

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Flue gas

Flue gas Distillation column butyric acid-rich (PURF02) stream (BA) Butanol

EX02 Waste water Reactor (RBA) Decanter

Broth Ethanol

Distillation column Distillation (DIST01) acetic acid-rich column stream (AA) EX01 (PURF01)

Reactor (RAA) Waste water

Figure 5-25. PFD of Scenario 2.

Figure 5-26. Azeotropes in Scenario 2.

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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

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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

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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.

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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.

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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

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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.

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APPENDIX A ASPEN FLOWSHEET OF THE INTEGRATED PROCESS

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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 + 0.9 2.6872 Carbon dioxide Hemicellulose + 0.107317 Ammonia + 0.758537 Water → 0.536585 E.coli + 2.21829 0.9 Methane + 2.24512 Carbon dioxide Ethanol + 0.0373984 Ammonia → 0.186992 E.coli + 1.40183 Methane + 0.411178 Carbon 0.9 dioxide + 0.0841443 Water Glucose + 0.146341 Ammonia → 0.731707 E.coli + 2.61586 Methane + 2.65244 Carbon 0.9 dioxide + 0.329263 Water Lactic acid + 0.0731707 Ammonia → 0.365854 E.coli + 1.30793 Methane + 1.32622 0.9 Carbon dioxide + 0.164632 Water Succinic acid + 0.095935 Ammonia + 0.284146 Water → 0.479675 E.coli + 1.49817 0.9 Methane + 2.02215 Carbon dioxide Furfural + 0.0780488 Ammonia + 2.82439 Water → 0.390244 E.coli + 2.29512 Methane + 0.9 2.31463 Carbon dioxide Acetic acid + 0.0487805 Ammonia → 0.243902 E.coli + 0.871952 Methane+ 0.884147 0.9 Carbon dioxide + 0.109754 Water Cellobiose + 0.278049 Ammonia + 0.37439 Water → 1.39024 E.coli + 5.27012 Methane + 0.9 5.33963 Carbon dioxide Xylitol + 0.123577 Ammonia → 0.617886 E.coli + 2.42561 Methane + 1.9565 Carbon 0.9 dioxide + 0.778047 Water Xylose + 0.121951 Ammonia → 0.609756 E.coli + 2.17988 Methane + 2.21037 Carbon 0.9 dioxide + 0.274386 Water Glycerol + 0.0747967 Ammonia → 0.373984 E.coli + 1.55366 Methane + 1.07236 Carbon 0.9 dioxide + 0.668293 Water

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+

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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-

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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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