DEVELOPMENT OF A SUSTAINABLE LIGNOCELLULOSIC BIODIESEL REFINERY By Michael Zanotti A THESIS Submitted to Michigan State University in partial fulfillment of the requirements for the degree of Biosystems Engineering Master of Science 2015 A BSTRACT DEVELOPMENT OF A SUSTAINABLE LIGNOCELLULOSIC BIODIESEL REFINERY By Michael Zanotti A novel co - hydrolysis process, which applies dilute acid pretreatment directly followed by enzymatic saccharification without detoxification and liquid - solid separation between these two steps was implemented to convert lignocellulosic biomass into monomeric sugars. A factorial experiment in a randomized block design was employed to optimize the co - hydrolysis process for several herbaceous crops ( switchgrass, giant reed, and miscanthus) and corn stover, with corn stover showing the greatest overall sugar conversion. Under optimal reaction cond itions, corn stover exhibited a total sugar yield (glucose + xylose) of 0.545 g/g dry biomass at 83.3% of the theoretical yield. The oleaginous fungus Mortierella isabellina was selected and applied to the co - hydrolysate medium to accumulate fungal lipids due to its capability of utilizing both hexose (C6) and pentose (C5) sugars. Mass balance data from the M. isabellina fermentation served as the basis for developing a theoretical biorefinery utilizing fungal lipid for biodiesel production. The unit operat ions identified for the biorefinery are (1) corn stover collection and transportation, (2) pretreatment and enzymatic co - hydrolysis, (3) lignin processing, (4) fungal lipid fermentation, (5) fungal biomass drying, (6) lipid extraction and transesterificati on, (7) anaerobic digestion and aerobic treatment of wastewater, and (8) solar - bio - power generation. Energy life cycle analysis results show the assumed biorefinery system has a net energy output of - 113.79 MJ/kg biodiesel produced. Overall, aerobic fungal lipid fermentation is shown to be the most energy - demanding unit operation, accounting for nearly 50% of all energy inputs, with co - hydrolysis resulting in large water and energy savings. iii ACKNOWLEDGMENTS This thesis work represents the com bined efforts of many individuals whom I would like to express my deepest gratitude. To Dr. Wei Liao for his contributions to c hapters 2 and 3 of this paper , a nd for his enthusiasm, patience, expertise, and support throughout m y g raduate school experi enc e . I am blessed to have had such a wonderful advisor. ir valuable time, effort, and insight to my project while serving on my thesis committee. I would also like to thank Dr. Liu for her contributions t o chapters 2 and 3 of this p aper. Z henhua Ruan, for being a great research partner and friend who made working on the co - hydrolysis project a truly enjoyable experience , and for his cont ributions to chapter 2 of this paper . Fellow laboratory members Steve Archer, Mau ricio Bust aman te, Rui Chen, Christine Isaguirre, Robbie Kra e mer, Zhiguo Liu, Pat Sheridan, Xiaoqing Wang, Tony Zhong, and Yuan Zhong for their combined knowledge, support, and humor. I would also li k e to thank Yuan Zhong and Mauricio Bustamante for th e ir contributions to chapters 2 and 3 of this pape r , respectively. Finally, I would like to thank my family and friends for their loving encouragement during my studies. iv TABLE OF CONTENTS LIST OF TABLES ................................ ................................ ................................ ................................ ....... vi LIST OF FIGURES ................................ ................................ ................................ ................................ .... vii Introduction ................................ ................................ ................................ ................................ ................... 1 1 Literature Rev iew ................................ ................................ ................................ ................................ .. 4 1.1 Lignocellulose ................................ ................................ ................................ ............................... 4 1.2 Pretreatment Methods and Microbial Inhibition Products ................................ ............................ 6 1.3 Enzymes ................................ ................................ ................................ ................................ ........ 9 1.4 Microbial Ferm entation of Lignocellulose Hydrolysate ................................ ............................. 10 1.5 Energy - Neutral Lignocellulosic Biodiesel Production ................................ ............................... 12 1.6 Objective and Hypothesis ................................ ................................ ................................ ........... 13 2 Chapter 2 ................................ ................................ ................................ ................................ ............. 15 2.1 Abstract ................................ ................................ ................................ ................................ ....... 15 2.2 Introduction ................................ ................................ ................................ ................................ . 15 2.3 Material s and Methods ................................ ................................ ................................ ................ 18 2.3.1 Lignocellulosic Biomass ................................ ................................ ................................ ..... 18 2.3.2 Dilute Acid Pretreatment ................................ ................................ ................................ .... 18 2.3.3 Enzymatic Saccharification ................................ ................................ ................................ . 19 2.3.4 Microorganisms and Culture Conditions ................................ ................................ ............ 19 2.4 Mass Balance ................................ ................................ ................................ .............................. 20 2.5 Analytical Methods ................................ ................................ ................................ ..................... 20 2.6 St atistical Analysis ................................ ................................ ................................ ...................... 21 2.7 Results and Discussion ................................ ................................ ................................ ............... 22 2.7.1 Degradation of Carbohydrates into Sugars and Inhibitors ................................ .................. 22 2.7.2 Combined Severity Factor Analysis ................................ ................................ .................... 25 2.7.3 Microbial Lipid Accumulation from Lignocellulosic Hydrolysates ................................ ... 25 2.7.4 Material Balances ................................ ................................ ................................ ................ 26 2.8 Conclusion ................................ ................................ ................................ ................................ .. 27 3 Chapter 3 ................................ ................................ ................................ ................................ ............. 28 3.1 Abstract ................................ ................................ ................................ ................................ ....... 28 3.2 Introduction ................................ ................................ ................................ ................................ . 28 3.3 Methodology ................................ ................................ ................................ ............................... 31 3.3.1 Corn Stover Collection and Transportation ................................ ................................ ........ 33 3.3.2 Corn Stover Pretreatment and Enzymatic Hydrolysis ................................ ......................... 33 3.3.3 Lignin Processing ................................ ................................ ................................ ................ 35 3.3.4 Fungal Lipid Fermentation ................................ ................................ ................................ .. 36 3.3.5 Fungal Biomass Drying ................................ ................................ ................................ ...... 38 3.3.6 Lipid Extraction and Transesterification ................................ ................................ ............. 38 3.3.7 Wastewater Treatment ................................ ................................ ................................ ........ 39 v 3.3.8 Combined Solar and Biological Power Generation ................................ ............................ 40 3.4 Results and Discussion ................................ ................................ ................................ ............... 41 3. 4.1 Corn Stover Collection and Transportation ................................ ................................ ........ 42 3.4.2 Corn Stover Pretreatment ................................ ................................ ................................ .... 43 3.4.3 Lignin Processing ................................ ................................ ................................ ................ 44 3.4.4 Fungal Lipid Fermentation ................................ ................................ ................................ .. 44 3.4.5 Fungal Biomass Drying ................................ ................................ ................................ ...... 45 3.4.6 Lipid Extraction and Transesterification ................................ ................................ ............. 46 3.4.7 Wastewater Treatment ................................ ................................ ................................ ........ 46 3.4.8 Solar - Bio - Power Generation ................................ ................................ ............................... 46 3.5 Conclusion ................................ ................................ ................................ ................................ .. 49 4 Conclusion ................................ ................................ ................................ ................................ .......... 50 APPENDICES ................................ ................................ ................................ ................................ ............ 52 Appendix A: Chapter 2 Tables and Figures ................................ ................................ ............................ 53 Appendix B: Chapter 3 Tables and Figures ................................ ................................ ............................ 63 BIBLIOGRAPHY ................................ ................................ ................................ ................................ ....... 74 vi LIST OF TABLES Table 2 - 1 Lignocellulosic feedstock composition ................................ ................................ ...................... 53 Table 2 - 2 Corn stover pretreatment conditions and results ................................ ................................ ........ 53 Table 2 - 3 Switchgrass pretreatment conditions and results ................................ ................................ ........ 54 Table 2 - 4 Giant reed pretreatment conditions and results ................................ ................................ .......... 55 Table 2 - 5 Miscanthus pretreatment conditions and results ................................ ................................ ......... 56 Table 2 - 6 Mortierella isabellina lipid production on synthetic and lignocellulosic media ......................... 56 Table 3 - 1 Reactor parameters for pretreatment, enzymatic hydrolysis, and aer obic fungal fermentation . 63 Table 3 - 2 Mass balance data for proposed biorefinery ................................ ................................ ............... 64 Table 3 - 3 Energy flow of 1 kg biodiesel production without solar energy input ................................ ....... 66 Table 3 - 4 Sensitivity analysis on energy balance for the lignocellulosic biodiesel production without combined solar bio - power generation ................................ ................................ ................................ ......... 67 Table 3 - 5 Solar and biological power generation ................................ ................................ ....................... 68 Table 3 - 6 Energy balance of a 20 million gallon lignocellulosic biodiesel refinery using solar and biological power generation ................................ ................................ ................................ ........................ 69 vii LIST OF FIGURES Figure 2 - 1 Conventional and co - hydrolysis process of dilute acid pretreatment and enzymatic saccharification operation for microbial lipid production (modified from Struder) ................................ ... 57 Figure 2 - 2 Glucose and xylose production fro m corn stover under different pretreatment conditions ...... 57 Figure 2 - 3 Glucose and xylose production from switchgrass under differen t pretreatment conditions ..... 58 Figure 2 - 4 Glucose and xylose production from giant reed under different pretreatment conditions ........ 58 Figure 2 - 5 Glucose and xylose production from miscanthus under different pretreatment conditions ...... 59 Figure 2 - 6 Combined severity factor effect on the conversion of glucose, xylose, acetic acid, HMF, and furfural from corn stover ................................ ................................ ................................ ............................. 59 Figure 2 - 7 Combined severity factor effect on the conversion of glucose, xylose, acetic acid, HMF, and furfural from switchgrass ................................ ................................ ................................ ............................ 60 Figure 2 - 8 Combined severity factor effect on the conversion of glucose, xylose, acetic acid, HMF, and furfural from giant reed ................................ ................................ ................................ ............................... 60 Figure 2 - 9 Combined severity factor effect on the conversion of glucose, xylose, acetic acid, HMF, and furfural from miscanthus ................................ ................................ ................................ ............................. 61 Figure 2 - 10 Mass balance of microbial lipid accumulation from corn stover, switchgrass, miscanthus, and giant reed co - hydrolysis ................................ ................................ ................................ .............................. 62 Figure 3 - 1 Solar - bio - powered lignocellulosic biodiesel refinery mass (blue lines) and energy (red lines) flows ................................ ................................ ................................ ................................ ............................ 70 Figure 3 - 2 Photovoltaic - biological power generation flow diagram ................................ .......................... 70 Figure 3 - 3 Concentrated solar power (CSP) and biological power generation flow diagram .................... 71 Figure 3 - 4 Mass flow for the production of 1 kg of fungal biodiesel ................................ ......................... 71 Figure 3 - 5 Energy balance without solar - bio - power generation ................................ ................................ . 72 Figure 3 - 6 Energy balance with Photovoltaic - biological power generation ................................ ............... 72 Figure 3 - 7 Energy bala nce with concentrated solar power - biological power generation ........................... 73 1 Introduction Diesel fuels are pivotal components to both advanced and developing economies as they are necessary for the transport of industrial and agricultural goods , and are responsible for the operation of diesel tractors and other agricultural components such as p ump sets (Meher, Sagar, & Naik, 2006) . Economic growth in these economies necessitates an equivalent expansion in the transportation sector dependent on diesel fuel. Worldwide demand for petroleum - based transportation fuels h as increased dramatically over the past decade. Fuel prices have also set record highs in recent years, affecting the cost of many consumer goods which track closely with the price of oil. This increased demand has brought renewed concerns over the sustain ability and environmental impacts posed by these ultimately finite resources. While many alternative sources of energy exist from wind, solar, geothermal, and biomass; biofuels, particularly those produced from abundant and renewable biomass feedstocks, re present a near term solution for alleviating dependence on the petrole um based transportation economy while mitigating environmental impacts (Meher, Sagar, & Naik, 2006) . Biofuels are defined as liquid or gaseous transportation fuels that are principally produced using biomass as a feedstock (Yusuf, Kamarudin, & Yaakub, 2011) . They have the ability to mitigate greenhouse gas (GHG) emissions by r educing the highly oxidized atmospheric carbon (CO 2 ), and storing it as soil organic carbon. Because plant biomass is used as the raw material for biofuel production, the combustion of said fuels theoretically adds no additional CO 2 into the atmosphere sin ce it simply recycles the atmospheric CO 2 embodied in the plant matter (Zhu & Zhuang, 2012) . Biodiesel is a biofuel produced as an alternative to petroleum - based diesel. It is composed of monoalkyl esters of long - chain fatty a cids (fatty acid alkyl esters) produced from renewable oil feedstocks. Biodiesel is most commonly produced through a transesterification reaction in which triaclyglycerides (TAG) (long chain fatty acids bound to a glycerol backbone) found in vegetable oi l or animal fat are reacted with a monohydric aliphatic alcohol (most commonly methanol) in the presence of a catalyst at high temperatures producing biodiesel and glycerol (Van Gerpen, 2005) . The basic theoretical stoichiomet ric equation for the 2 transesterification reaction is such that 1 mole of triglyceride is reacted with 3 moles of methanol to produce 3 moles of fatty acid alkyl ester and 1 mole of glycerol byproduct. While the theoretical ratio of methanol to oil is 3/ 1 , the actual ratio is closer to 6/ 1 in order to give an approximately 98% biodiesel conversion. The transesterification reaction is most commonly catalyzed with sodium hydroxide (NaOH), which allows for the reaction to occur at lower temperatures, thus lowering energy inputs during produc tion. Biodiesel has many properties that make it an attractive alternative to petroleum diesel. It is non - toxic, biodegradable, has a low emissions profile including reduced CO 2 emissions, a superior flash point to petro - diesel, negligible sulfur content , and is produced from a variety of renewable resources such as soybean, sunflower, palm oil, rapeseed, canola, jatropha, and waste oils and animal fats. Additionally, biodiesel blends have increased lubrication properties which reduce long term engine wea r, and it is the only alternative fuel which can run on conventional unmodified compression - ignition (diesel) engines (Demirbas, 2009) . Pure, unblended biodiesel can be directly inputted as engine fuel, or it can be blended in any number of ratios with petroleum diesel. The most common biodiesel blend in the United States is B20, which consists of 20% biodiesel and 80% petroleum diesel. Biodiesel standards exist in many countries in order to ensure quality control of the renewab le fuel as it reaches consumers. Two of the most widely adopted biodiesel standards are the ASTM D6751 in the United States, and the EN 14214 standard in the European Union. Worldwide biodiesel production stood at 431.259 thousand barrels/day in 201 2 , with Europe leading all regions with 170.923 thousand barrels/day, or 40 accounted for 64 thousand barrels/day of biodiesel production in 2012, or 15 % of the (U.S. Energy Information A dministration, 2014) . Rapeseed oil is the major feedstock used in biodiesel production accounting for 48% of all biodiesel produced in 2007 (Moser, 2009) . Other major feedstock oil sources include soybean (22% of biodie sel produced), and palm (11%) oils, with the remaining (19%) inputs spread among a variety of 3 animal fats and other vegetable oil sources (Moser, 2009) . Different oil feedstocks have different TAG chemical compositions, which in turn creates different fatty esters in the final biodiesel product. The composition of the fatty esters dictates the fuel properties of biodiesel. Fatty ester carbon chain lengths vary from C12 to C22 with chain lengths between those extremes predominat ing. As chain length increases the following properties typically increase: melting point, oxidative stability, kinematic viscosity, standard heat of combustion, and cetane number, while lubricity typically decreases. Likewise, as the number of double bond s in the carbon chain increases, the previously mentioned properties typically decrease. Sat urated methyl esters , those with no carbon double bonds, have higher freezing points than unsaturated chains. Feedstocks with high free fatty acid (FFA) content (> 3%) should be avoided as these substances will react with base catalysts such as NaOH, to form soap and water, ultimately retarding the transesterification process and leaving the TAG molecules unreacted. One of the major barriers facing the biodiesel ind ustry is the cost of feedstock acquisition. Feedstock costs account for over 80% of the total expense of biodiesel production (Moser, 2009) , which has led the industry to look for alternative sources of oil. One strain of curr ent research is focused on using lignocellulosic materials as sources of cheap sugars to grow fungal biomass for oil and biodiesel production. The following chapters assess variou s lignocellulosic feedstock sources and pretreatment conditions for their con version into fermentable media for fungal lipid production. A theoretical biodiesel refinery utilizing lignocellulosic pretreatment and fungal lipid fermentation as inputs is discussed , and its unit operations identified. Mass and energy balance data is co llected on the system in order to identify which inputs have the largest impact on the overall system efficiency and sustainability. 4 1 Literature Review 1.1 Lignocellulose Lignocellulosic biomass represents the most abundant source of renewable carbon with ove r 200 billion tons created annually (Chandel & Singh, 2011) . Interest in its use as a feedstock for the production of advanced biofuels has gained momentum in recent years as shown by various government directives. The Renewable Fuels Standard 2 provision in the United States Energy Independence and Security Act of 2007 mandates the production of 36 billion gallons of biofuels by 2022, with 21 billion gallons coming from non - starch sources (i.e. lignocellulosic sources) while cap ping conventional biofuels (i.e. corn starch - based ethanol) at 15 billion gallons (Coyle, 2010) . Support for lignocellulosic fuels is owed not only to its large supply, but also to its ability to mitigate greenhouse gas emissions, avoid competition with food resources, stimulate rural economies, and provide a stable and secure source of energy production (Coyle, 2010) . Many sources of lignocellulose mater ials exist which can be readily converted into microbial biofuel production including municipal solid waste, pulp and paper wastes, forest and agricultural residues, and dedicated woody and herbaceous energy crops (Williams, Inman, A den, & Heath, 2009) . Agricultural residues, primarily corn stover, and herbaceous perennial energy crops have been the focus of much attention due to their positive environmental characteristics. Corn stover consists of the above ground biomass left once the kernels have been harvested, and the total amount produced annually is equal to the total weight of corn harvested. That is to say the corn grain to corn stover ratio is 1/ 1. However, a minimum corn stover amount of 50% must be left in the field t o avoid erosion issues, and research has shown that the upper limit of stover that can be sustainably harvested while avoiding soil organic carbon losses is approximately 30% (Morey, Kaliyan, Tiffany, & Schmidt, 2010) . Compared to their annual counterparts, perennial herbaceous energy crops, once established, do not need reseeding and require lower inputs for water, fertilizer, pesticides, and tillage. Additionally, they can often be grown on uncultivated or marginal lands where their deep root structures act to reduce soil 5 erosion, increase soil fertility, and accumulate greater soil organic carbon than their annual co unterparts, including corn stover. Lignocellulosic materials, despite their source, share similar biochemical characteristics. They are heterogeneous matrices of polysaccharides (cellulose and hemicellulose) and lignin, a phenolic polymer. - 1 , 4 bonds. In dividual cellulose chains are densely packed in micro fibrils consisting of 36 individual cellulose chains forming a tight crystalline structure that is water insoluble and difficult to depolymerize (Mosier, et al., 2005) . Hemicellulose is a branched heteropolymer consisting prima rily of xylose (sometimes glucose) with subunits of galactose, fucose, mannose, glucose, or glucuronic acid substituted in the chain. It often contains side chains with acetate groups. Lignin is a polymer of phenyl propane (C9) which consists of a 6 - carbon phenolic ring with a 3 - carbon side chain. It provides a hydrophobic barrier to water penetration, and also protects plants from degradation by fungi, insects, and microbes. Hemicellulose hydrogen - bonds to cellulose microfibrils forming a complex network o f polysaccharides, providing structure to the plant cell walls (Mosier, et al., 2005) . Lignin fills in the spaces in the cell wall structure adding an additional degree of stability and protection to the polysaccharides. Cellulose and hemicellulose fractions of lignocellulose can p otentially be broken down to their monomeric units and used as substrates for the microbial production of biofuels. While rich in polysaccharides, lignocelluloses have developed mechanisms to pro tect these sugars from degradation. Some key factors believed contributing to the resistant nature of lignocellulose include cellulose crystallinity and insolubility, the presence and abundance of lignin, sheathing of cellulose by hemicellulose, and the he terogeneous composition of the biomass itself (Mosier, et al., 2005) . Though beneficial from an evolutionary standpoint, the natural recalcitrance of lignocellulose nonetheless negatively affects the conversion yield and proces sing costs associated with producing monomeric sugars for second generation biofuels, since expensive chemicals and enzymes must be applied in order to break down the carbohydrate fractions. 6 1.2 Pretreatment Methods and Microbial Inhibition Products The goal o f pretreatment is to disrupt the macromolecular structure of lignocellulose (lignin, cellulose, and hemicellulose) so that hydrolytic enzymes can penetrate and hydrolyze the polysaccharides into individual monomeric units. Effective pretreatment operations maximize the monosugar yield of both pentose and hexose sugars (from hemicellulose and cellulose, respectively) while minimizing the production of chemical by - products harmful to microbial growth. Various pretreatment technologies exist for monosugar extr action, and can be categorized as either physical or chemical in nature (Mosier, et al., 2005) . Physical pretreatment methods include comminution, steam explosion and hydrothermolysis, with steam explosion being the far mo re extensively studied of the three. Steam explosion involves rapidly heating lignocellulosic biomass with high - pressure steam without any added chemicals. Once the target temperature is reached, it is held there for a brief time in order to hydrolyze the hemicellulose fraction, with the process being terminated by an explosive decompression. The high temperature steam releases acetyl groups which are esterified to the hemicellulose chains. These acetyl groups form weak acetic acid which hydrolyzes and solu bilizes the hemicellulose polymers into pentose sugars. Removal of the hemicellulose fraction allows for greater enzyme accessibility to the cellulose for hexose hydrolysis. Physical reduction and increased biomass surface area are considered less importan t with regards to the overall hydrolysis of the cellulose polymers (Brosse, El Hage, Sannigrahi, & Ragauskas, 2010) . Chemical pretreatments involve the addition of dilute acid or alkali to lignocellulose at elevated temperatu res in order to remove either the hemicellul ose or lignin fractions and improve cellulose hydrolysis. Dilute acid pretreatment involves the creation of a weak sulfuric acid (H 2 SO 4 ) solution (1 - 3% weight/weight (w/w) ) and adding lignocellulose at various so lid loadings (5 - 25%), then heating the mixture at high heat (120 - solubilize the hemicellulose portion in the lignocellulose as well as a small amount of lignin, allowing for greater enzymatic access to the cellulose chains. After the initial pretreatment step, the pH of the biomass 7 slurry will be very low and must be neutralized with bases such as NaOH or Ca(OH) 2 in order to stop further degradation of the xylose monomers to inhibitio n products, and to create a pH more conducive to enzymatic hydrolysis (Lee, Iyer, & Torget, 2001) (Lee et al. 1999). Alkali pretreatment methods are performed under lower temperatures and pressures than other pretreatment techniques. Two of the most common pretreatment methods involving alkali chemicals are lime pretreatment and ammonia fiber explosion (AFEX). Lime pretr eatment involves spraying a lime/water solution over the biomass material, and storing it in a pile for a matter of hours to weeks depending on the temperatures involved, with higher temperatures reducing the total treatment time (3 hours ( h ) (Mosier, et al., 2005) . This method solubilizes the lignin from biomass allowing for improved enzymatic access to the remaining polysaccharide fractions. It also removes acetyl and uronic acids on hemicellulose, further increasing enzyme accessibility. AFEX pretreatment is an attractive method for releasing monosugars from herbaceous perennials and agricultural residues, garnering near theoretical yields at low enzyme loadings (< 5 filter paper unit (FPU)) (Mosier, et al., 2005) . This treatment method involves trickling an ammonia solution (5 - 15%) through biomass that is tightly packed in a column reactor at high temperatures (160 - 180°C) and a low veloc ity of 1 mL/cm 2 / min. Residence times are typically around 14 min utes . The aqueous ammonia delignifies the biomass and severs the linkages between lignin and the polysaccharide fractions while solubilizing some hemicellulose as well. Ammonia costs (and reco very) appear to be the limiting factor for this process. However, input costs may be outweighed by the high total sugar yield achieved by this process. No matter the pretreatment process, the resulting hydrolysate (liquid containing the solubilized monos ugars) will contain substances with properties that are inhibitory to the production of biofuels via microbial fermentation. The type and amount of these products is dependent on both the particular biomass being treated, as well as the reaction conditions it is subjected to. These inhibitory products can 8 often be the limiting factor to the viability of microbial biofuel production. The degradation products resulting from chemical pre - treatment of lignocellulosic biomass are divided into the following diffe rent categories: carboxylic acids, furans , phenols, and inorganic salts, with phenols showing the greatest inhibitory effect on fermentation (Pienkos & Zhang, 2009) . Carboxylic acids (primarily acetic acid) are ubiquitous in hemicellulose hydrolysate since that fraction of the biomass (as well as lignin to a smaller degree) is often highly acetylated. They are by - products of acid pretreatment , which release s carboxylic acids from their hemicellulose side chains (Benko, et al., 2007) . Alkali degradation often creates hydroxycarboxylic acids such as glycolic acid and lactic acid. Formic acid is a product of sugar and lignin degradation, while levulinic acid is formed by solely by degrading sugar. Arom atic degradation products form primarily from the breakdown of sugars to furans and phenols formed by the cleavage of solubilized lignin. Furan aldehyde inhibitors are produced from the degradation of monosugars in the hydrolysate. The two most common fura ns include furfural which results from the breakdown of xylose, and hyrodxymethyl furfural (HMF), resulting from glucose degradation. Phenolic compounds result from the breakdown of polyphenolics in lignin. Inorganic salts are created by a variety of meth ods such as their release from both the lignocellulosic biomass itself and the walls of pretreatment vessels and pretreatment chemical reactions (Zhang, French, Hernandez, Alley, & Paraschivescu, 2011) . The manifestations of t he toxic effects vary among the different inhibitors and the different organisms that are subject to them. Low molecular weight (MW) inorganic salts are able to penetrate cell membranes, whereas fermentation inhibitors with high MW influence the expression and activity of sugar and ion transporters in the cell membrane. Acetic acid can penetrate the microorganism cell wall and hinder cellular activity by acidifying the cytoplasm and disrupting the protein gradient across the cell membrane (Takahashi, Takahashi, Carvalhal, & Alterthum, 1999) . Furfural and HMF interfere with glycolysis by disrupting dehydrogenase activity resulting in lower growth rates and yields. Phenolic compounds can pierce cellular membranes resulting in lower growth rates and inhibiting sugar transport 9 (Klinke, Thomsen, & Ahring, 2004) . However, information regarding the specific effects these inhibitors have on oleaginous filamentous fungal lipid accumulation used for biodiesel pr oduction is quite limited and needs further study. 1.3 Enzymes Enzymes are the catalysts for the depolymerization of the lignocellulosic polysaccharides. They have advantages of typically working at low temperatures and are highl y specific reactions. However enzyme costs are typically very high, and the reaction rates can take days. Enzymes specific to glucose and xylose hydrolysis are termed glycoside hydrolases because they catalyze the hydrolysis of the glycoside linkages bet ween monomeric units in the polysaccharides of lignocellulose. Because xylose is typically solubilized into monomeric units during many pretreatment processes, most research focuses on the cellulose enzymes, or those that depolymerize the cellulose chains of biomass. Cellulases must possess the dual ability to both bind a water soluble protein to the insoluble cellulose substrate, as well as depolymerize the highly crystalline structure of the sugar chain. These proteins are categorized as either complexe d or noncomplexed systems. Noncomplexed cellulase enzymes work to degrade cellulose to monomeric glucose units under aerobic conditions. These enzymes include three subclasses: - glucosidase s . Endoglucanases cleave glyco sidic bonds in the amorphous central region of the cellulose molecules creating reducing and non - reducing ends. Exoglucanases release cellobiose (a disaccharide of glucose units) from the outside ends of the cellulose - glucosidase s release glucose from cellobiose and soluble cellodextrins. Typically the endoglucanases and exoglucanases display both cooperatively and synergism, meaning that the combination of those enzymes improves overall hydrolysis yields. The endo - acting enzymes create ne w reducing and non - reducing ends for exo - acting enzymes to work on (Lynd, Weimer, van Zyl, & Pretorius, 2002) . 10 1.4 Microbial Fermentation of Lignocellulose Hydrolysate Because of the growing concerns over using food crops for the p roduction of biofuels, many in the biodiesel industry are now looking to expand production away from rapeseed (canola) and soybean - based biodiesel. Attention has shifted to non - edible oil sources such as those produced from oleaginous microorganisms (those organisms with lipid contents in excess of 20%). Microbial lipids are viewed as a possible alternative for industrial biodiesel production because their triacylglycerol composition is similar to that of vegetable oils (Huang, Zong, Wu, & Liu, 2009) . The major fatty acids present in the lipids produced by oleaginous microorganisms are myristic acid (C14:0), palmitic acid (C16:0), stearic acid (C18:0), oleic acid (C18:1), linoleic acid (C18:2), and linolenic acid (C18:3); all of which can be converted to biodiesel through a transesterification reaction (Chatzifragkou, et al., 2010) . However, the high expense of its gluco se substrate (Hui, Wan, Hai - tao, Xue - jiao, & Yu - hua, 2010) . In order to overcome cost barriers, a less expensive carbon source is desired as well as utilizing microorganisms exhibiting high biomass and lipid yields. Lignocellu losic biomass is of great interest as a sugar substrate source for microbial lipid accumulation due to its abundance and potential to serve as an inexpensive feedstock. Both glucose and xylose can be extracted from such sources, with glucose being the more abundant and easier metabolized of the two (Hu, et al., 2011) . Organisms that can utilize both pentose and hexose sugars for fermentation are thus highly desired in order to increase the efficiency of lipid production from lig nocellulosic materials (Gong, et al., 2012) . In general, lipids are accumulated in oleaginous organisms due to the presence of the ATP - dependent citrate lyase. Under nutrient limited conditions, especially nitrogen limitation with an abundant carbon source (high carbon/ nitrogen ( C/N ) ratio), AMP deaminase is up - regulated eventually leading to the presence of citrate in the cell cytosol. Citrate is cleaved by the ATP - dependent citrate lyase producing acetyl - CoA, which is used in fatty acid biosynthesis. It is by this pathway that oleaginous microorganisms shift their carbon sources away from growth and toward lipid production (Ratledge, 2004) . 11 Though glucose is the more easily assimilated of the two major lignocellulosic carbon sources, studies have investigated oleaginous fungal lipid production using xylose as the sole carbon source as well as using both glucose and xylose simultaneously. Xylo se (80 g/L, C/N ratio of 285) was used as the sole carbon source to cultivate the oleaginous molds Mortierella isabellina ATHUM 2935 and Cunninghamella echinulata ATHUM 4411 resulting in lipid concentrations of 6.1 g/L and 6.7 g/L, respectively at 360 h, h owever, more than 25 g/L of unconsumed xylose remained in the media (Fakas, et al., 2009) . Studies have reported lipid accumulations from xylose of 2.2 g/L for the oleaginous mold Colletotrichum sp.DM06, and 4.3 g/L for Alterna ria sp.DM09 under nitrogen stressed conditions respectively (Dey, Banerjee, & Maiti, 2011) . The oleaginous yeast Trichosporon cutaneum AS 2.571 assimilated glucose and xylose simultaneously, and accumulated intracellular lipid up to 59% ( w/w ) with a lipid coefficient up to 0.17 g lipid /g sugar, upon cultivation on a 2 / 1 glucose/xylose mixture (Hu, et al., 2011) . Additionally, a variety of research has been conducted on oleaginous mold lipid accumulat ion from pretreated lignocellulosic biomass enzymatic hydrolysate. When using a mixture of wheat straw and bran as feedstock with solid culture, 80 mg lipid/g dry solid s cell mass (mg /gds ) was accumulated by the oleaginous mold Microsphaeropsis sp (Peng & Chen, 2008) . For semi - solid culture, 11 g oil/100 g dry sweet sorghum was produced (Economou, Aggelis, Pavlour, & Vayenas, 2011) . Researchers using rice straw and wheat bran under solid cult ure produced 68.2 mg/gds and 60.32 mg/gds lipid using Colletotrichum sp. (DM06) and Alternaria sp. (DM09). The mutant strain Mortierella alpin a (MAI502 - 8) accumulated 27.4 and 10.05 g /L cell mass and lipid respectively from a mixture of glucose and xylose media (5 / 3 w/w ) over 11 days of total culture time (Peng, et al., 2011) . Under varying C/N ratios (35, 44 and 57), lipid accumulated in M . isabellina ATHUM 2935 was 36%, 51.2% and 64.3%, respectively using rice hull hydrolysate (Economou, Aggelis, Pavlour, & Vayenas, 2011) . Ruan demonstrated that M. isabellina grown on un - detoxified corn stover hydrolysate was able to produ ce similar biomass and lipid content when grown on substrate with identical glucose and xylose concentrations and C/N ratios without any added inhibitors (Ruan & Zanotti, 2012) . Additionally it was shown that this oleaginous mo ld was able to utilize acetic acid for fungal growth and lipid accumulation further demonstrating the utility of 12 using molds capable of metabolizing both glucose and xylose in the presence of inhibito ry compounds (Ruan & Zanotti, 20 12) . 1.5 Energy - Neutral Lignocellulosic Biodiesel Production In order for lignocellulosic biodiesel to be considered a viable alternative to petroleum - based fuels it must demonstrate that it can be produced in a sustainable manner. This means that an idea l biorefinery system should have a positive net energy contribution from the feedstock source; otherwise it is no different than a traditionally energy - intensive pulp mill which creates fiber as its primary product and uses residual lignin as a supplementa l power source through combustion (Zhu & Zhuang, 2012) . Evaluating the energy output of a biofuel system requires a detailed evaluation of all mass and energy flows. Energy life cycle analysis (ELCA) is a method for determining the cumulative energy inputs from different sources as well as the total efficiency of the production process (Pradhan, et al., 2011) . Energy balance involves accounting for the amount of energy used during the production and comparing it to the amount contained in the biofuel and other co - products. The results obtained from the energy balance analysis can be expressed as the ratio of energy produced to energy consumed by a production system, otherwise known as the net energy r atio (NER). Increase of NER for biofuel production is key to establishing a sustainable biorefining industry. If the calculated NER is greater than unity, then the biofuel could be utilized to replace all the energy needed in its production, and thus it wo uld be considered infinitely renewable (Pradhan, et al., 2011) . Improving NER can be achieved by supplementation with renewable energy sources, such as solar thermal, wind, geothermal, and biomass. Among these sources, solar t hermal energy, with the advantages of abundance and availability, represents an excellent candidate to be combined with a lignocellulosic refinery to produce biofuels. Several solar thermal conversion technologies have been developed in the past several de cades, such as, flat plate thermal collector, evacuated - tube solar thermal collector, parabolic trough system, power tower system, dish solar system, and Fresnel reflector s (Mills, 2001) . Among these sources, solar energy with the advantages of abundance and availability represents an 13 excellent candidate to be combined with a lignocellulosic refinery to produce biofuels. Many solar technologies have been developed in the past several decades such as silicon wafer PVs, thin - film PV, low - temperature solar thermal systems, and CSP systems (Mills, 2001) (Shukla, Sumathy, Erickson, & Gong, 2013) (Price H. , et al., 2002) (Gre en, 2007) . According to their solar conversion mechanisms, these solar technologies are mainly divided into two categories: PV and CSP. PV uses semiconducting materials to directly covert photons into electrons and generate electricity, while CSP use s heat absorbers or reflective surfaces to collect solar thermal energy for both low temperature (hot water heater) and high temperature (CSP technologies) applications. Integrating such solar technology with lignocellulosic biofuel production could lead t o a sustainable biorefining platform capable of replacing fossil fuel consumption, while maximizing its NER value. 1.6 Objective and Hypothesis While research has established the fact that microbial lipid production from lignocellulosic sources is possible, improvements are still needed. According to Papanikolaou et al., biomass yields of at least 30 g/L with reserve lipid content near 30% are req uired in order to make microbial oil production commercially feasible (Papanikolaou, Komaitis, & Aggelis, 2005) . While lab - scale experiments have come close to reaching such lipid levels, their productivities are often very lo w due to inhibition products present in the fermentation broth, requiring costly detoxification steps to remove. Little is known about the specific type or concentration of inhibitors produced under different pretreatment conditions for various lignocellu losic sources, as well as the individual and synergistic effects those inhibitors may have on oleaginous fungal growth and lipid production. Additionally, an energy neutral production process is also critical to sustain lignocellulosic biodiesel production . Therefore the goal of the study is to develop a sustainable lignocellulosic biodiesel production system that has better biodiesel yield, low water consumption, and a neutral energy balance. The specific objectives of the research include the following: 14 1. Identify a microorganism capable of fermenting substrates derived from lignocellulosic biomass for bio - lipid production, and determine the pretreatment method best - suited for its fermentation. 2. Optimize biomass pretreatment conditions for total sugar yield with regards to the following parameters: chemical concentration, treatment time, temperature, and solid loading. 3. Identify specific inhibition products resulting from the pretreatment of lignocellulosic biomass, as well as conduct fermentation e xperiments in order to determine the microbial growth and lipid production on said lignocellulosic - derived substrates. 4. Perform a broad mass and energy balance, along with a life cycle energy analysis in order to determine a rough estimate of the net e nergy required , as well as the feasibility of commercially scaling up a solar - bio - powered microbial biodiesel production process. 15 2 Chapter 2 2.1 Abstract The herbaceous perennial energy crops miscanthus, giant reed, and switchgrass, along with the annual crop residue corn stover, were evaluated for their bioconversion potential. A co - hydrolysis process, which applied dilute acid pretreatment, directly follo wed by enzymatic saccharification without detoxification and liquid - solid separation between these two steps was implemented to convert lignocellulose into monomeric sugars (glucose and xylose). A factorial experiment in a randomized block design was emplo yed to optimize the co - hydrolysis process. Under the optimal reaction conditions, corn stover exhibited the greatest total sugar yield (glucose + xylose) at 0.545 g/g dry biomass at 83.3% of the theoretical yield, followed by switch grass (0.44 g/g dry biomass, 65.8% of theoretical yield), giant reed (0.355 g /g dry biomass, 64.7% of theoretical yield) and miscanthus (0.349 g /g dry biomass, 58.1% of theoretical yield). The influence of combined severity factor on the susceptibility of pretreated subs trates to enzymatic hydrolysis was clearly discernible, showing that co - hydrolysis is a technically feasible approach to release sugars from lignocellulosic biomass. The oleaginous fungus M . isabellina was selected and applied to the co - hydrolysate mediums to accumulate fungal lipids due to its capability of utilizing both C5 and C6 sugars. Fungal cultivations grown on the co - hydrolysates exhibited comparable cell mass and lipid production to the synthetic medium with pure glucose and xylose. These results show the potential for combining fungal fermentation with a co - hydrolysis pretreatment process for lignocellulosic lipid accumulation , and could enhance the utilization efficiency of lignocellulosic biomass for advanced biofuels production. Keywords: co - hy drolysis, lignocellulosic biomass, oleaginous fungus, lipid accumulation 2.2 Introduction Lignocellu losic biomass represents the mo st abundant natural polymer in the biosphere, and interest in its use as a feedstock for the production of advanced bio fuels has gained momentum in recent years as 16 shown by various government directives. The Renewable Fuels Standard 2 provision in the United States Energy Independence and Security Act of 2007 mandates the production of 36 billion gallons of biofuels by 202 2, with 16 billion gallons coming from lignocellulosic sources while capping conventional biofuels (i.e. corn starch - based ethanol) at 15 billion gallons (Coyle, 2010) . Support for lignocellulosic fuels is owed not only to its large supply, but also its ability to mitigate greenhouse gas emissions, avoid competition with food resources, stimulate rural economies, and provide a stable and secu re source of energy production (Coyle, 2010) . Many sources of lignocellulosic biomass exist, including municipal solid wastes, pulp and paper wastes, forest and agricultural residues, and dedicated woody and herbaceous perennial energy crops. Herbaceous perennial energy crops in particular, have been the focus of much attention due to their positive environmental characteristics. Compared to annual crops, perennials, once established, do not need reseeding, and require lower inputs (i.e., water, fertilizer, pesticide, tillage). Additionally they can often be grown on uncultivated or marginal lands where their deep root systems act to reduce soil erosion, increase soil fertility, and accumulate greater soil organic carbon than their annual counterparts (i.e. corn or canola) (Williams, Inman, A den, & Heath, 2009) . Among the twenty perennial grasses studied by the European Union, the most promising in terms of biofuel production were: miscanthus, giant reed, switchgrass and reed canarygra ss (Lewandowski, Scurlock, Lin dvall, & Christou, 2003) . Miscanthus, giant reed, switchgrass , as well as corn stover will be the primary focus of this investigation. Many studies have been devoted to the pretreatment and enzymatic hydrolysis of the herbaceous perennial en ergy crop switchgrass, however, information about the recalcitrance and bioconversion potential of miscanthus and giant reed is still limited. Wet explosion (Sorensen, Teller, Hilstrom, & Ahring, 2008) , ammonia fiber expansion (Murnen, et al., 2007) , one - step extrusion/NaOH (de Vrije, de Haas, Tan, Keijsers, & Claassen, 2002) , and aqueous - ethanol organosolvent treatments were applied for the bio - conversion of miscanthus t o fermentable sugars (Brosse, El Hage, Sannigrahi, & Ragauskas, 2010) . Dilute acid pretreatment and ethanol - alkaline treatment were carried out for giant reed 17 bioconversion. All such studies employed common methods of biomass p rocessing where, after pretreatment, the solids are separated from the liquid stream, washed to neutralize and detoxify the remaining solids, then subjected to enzymatic hydrolysis in order to extract glucose monomers (Decker, Brune cky, Tucker, Himmel, & Selig, 2009) . Depending on the particular pretreatment method, the discarded liquid stream will often contain a large percentage of the solubilized xylose, and to a lesser extent, glucose monomers and soluble lignin. Since xylos e can compose a large fraction of the lignocellulosic biomass, it is critical from an economic standpoint to retain this fraction in order to improve pretreatment efficiency. Additionally, such a process requires large amounts of water to neutralize and detoxify the so lid biomass, and separation of the solid and liquid streams results in significant turnaround times, and introduces the possibility of contamination (Studer, Brethauer, DeMartini, McKenzie, & Wyman, 2011) . Therefore, developmen t of a novel process (co - hydrolysis), which eliminates liquid - solid separation, detoxification or washing of the pretreated solids, and directly carries out enzymatic hydrolysis after pretreatment would make a significant contribution to the production of advanced biofuels. To date, comprehensive evaluations of co - hydrolysis of lignocellulosic biomass are sparse. A few researchers have studied the effects of higher solids loading for un - detoxified pretreated wheat straw (Georgieva, Hou, Hilstrom, & Ahring, 2008) , the effects of increasing enzyme dosage in comparing washed - solids of wheat straw versus whole - slurry hydrolysis (Felby, Klinke, Olsen, & Thomsen, 2003) , and the combined effects of severity , and enzyme and solid loadings on co - hydro lysis performance of populous (Studer, Brethauer, DeMartini, McKenzie, & Wyman, 2011) . Realizing the potential benefits of co - hydrolysis comes with its own challenges, such as utilizing microbes that are robust enough to withstand elevated levels of toxins specific to each biomass source and pretreatment method, while containing the ability to ferment both hexose and pentose sugars into biofuels. There are few studies on the bioconversion of both the hexose and pentose fractions of herbaceous perennial energy crops like switchgrass, miscanthus, or giant reed. The extreme thermophilic bacterium Thermotoga elfii metabolized undetoxified miscanthus hydrolysate containing glucose and xylose for 18 hydrogen production, while the yeast Scheffersomyces stipitis CBS6054 was able to convert giant reed hydrolysate to ethanol (Scordia D. , Cosentino, Lee, & Jeffries, 2012) . Our previous study found that the oleaginous mold M . isabellina , when grown on corn stover co - hydrolysate, could produce lipid yields comparable to those from synthetic hydrolysate without toxins (Ruan & Zanotti, 2012) . In addi tion, there is still limited information regarding its lipid production from herbaceous perennial energy crops, even though lipid accumulation by M. isabellina from lignocellulosic biomass has been stu died (Economou, Makri, Aggelis, Pavlou, & Vayenas, 2010) . Thus, the aim of this study is to provide a comparative evaluation of M. isabellina lipid accumulation on the co - hydrolysates of four differe nt lignocellulosic feedstocks: switchgrass, giant reed, miscanthus, and corn stover , using a co - hydrolysis process for bioconversion . 2.3 Materials and Methods 2.3.1 Lignocellulosic Biomass Corn stover and switchgrass were collected from the Michigan State University Crop and Soil Science Teaching and Research Field Facility. Miscanthus and giant reed were obtained from Werks Management, LLC (Fishers, IN). Each feedstock was air - dried and ground using a mill (Willey Mill, Standard Model No. 3, Arthur H. Thomas, Philadelphi a, PA) with a 2 mm size screen. All materials were then sieved to make a particle size distribution of less than 30 mesh (< 1.6 mm) but greater than 80 mesh (> 1 mm). The biomass samples were analyzed for cellulose, xylan, and lignin content according to the for determination of structural carbohydrates and lignin in biomass . 2.3.2 Dilute Acid Pretreatment To evaluate the combined glucose and xylose recovery from cellulose and xylan in each biomass sample, dilute acid pretreatment was performed with a fact ori al randomized block design. Dilute acid concentration, pretreatment time, and temperature were the factors investigated. Eighteen treatments with two replicates were applied to each lignocellulosic biomass for a total of thirty - six individual samples per 19 f eedstock. Each sample was treated in a screw cap 125 mL serum bottle and placed in an autoclave (Brinkmann 2540M, Tuttnauer USA Co. Ltd, Hauppauge, NY). Dilute acid pretreatments were carried out at sulfuric acid concentrations of 1%, 2% and 3% (w / w ), resp ectively. Retention times of 1, 2, and 3 h pretreatment, bi omass slurries were titrated to a pH of 4.5 - 5 with 5 mol/L sodium hydroxide. 2.3.3 Enzymatic Saccharification After dilute acid pretreatment and pH adjustment of the biomass slurry, various amounts of 0.1 - 1 citrate buffer (pH 4.8) and an enzyme mi xture consisting of 34.85 mg cellulase (Accellerase 1500®, protein content 69.7 mg/mL , lot number 3016295230; Genencor, Palo Alto, CA) and 4.31 mg xylanase (Accell e rase XY, protein content 43.1 mg/mL , lot number 4900667792; Genencor, Palo Alto, CA) per gra m of initial dry biomass were added to the slurry to achieve a final dry matter concentration of 8% for all pretreated solutions. All of the resulting samples were incubated at 50°C in a shaking incubator at 150 rpm for 72 h . All enzymatic hydrolysis exper iments were carried out in duplicates. After hydrolysis, the samples were removed from the shaker and put on ice to stop the reaction; the hydrolysate was separated by centrifugation at 7025 x g for 5 min utes to obtain a clear sugar solution, which was the n hydrolysa te solutions were stored in a 4 °C refrigerator for further use. 2.3.4 Microorganisms and Culture Conditions Mortierella isabellina ATCC 42613 was o btained from the American Type Culture Collection (Manassas, VA). This strain was first cultured on potato dextrose agar (Sigma - Aldrich, St. Louis, MO) to ater to obtain a spore suspension (stored at 4°C). Seed cultures were grown with 24 g /L potato dextrose broth (Sigma - Aldrich, St. Louis, MO) with 8 g /L yeast extract at 25°C and 180 rpm for 2 days in a rotary shaker (Thermal Scientific, Odessa, Texas) with a spore concentration of 1 - 2×107 spore/mL . The salt 20 medium of submerged batch cultures contained: KH 2 PO 4 (1 g/L ) (Mallinckrodt Bakker), MgCl 2 * 6H 2 O (0. 5 g/L ) (Mallinckrodt Bakker, St. Thomas, US virgin islands), ZnSO 4 * 7H 2 O (0.0014 g/L ) (Sigma - A ldrich), MnSO 4 * H 2 O (0.0016 g/L ) (Sigma - Aldrich), CoCl 2 * 6H 2 O (0.0036 g /L ) (Sigma - Aldrich), and FeSO 4 * 7H 2 O (0.00275 g/L ) (Sigma - Aldrich, St. Louis, MO). 2.74 g/L yea st extract (DOT Scientific Inc. , Burton, MI) was used as the sole nitrogen source. The carbon sources were synthetic sugars (composed of a mixture of glucose and xylose using similar concentrations found in the co - hydrolysates), and lignocellulosic biomass co - hydrolysates. Corn stover and switchgrass co - hydrolysates were diluted to obtain similar sugar concentrations to those found in miscanthus and giant reed co - hydrolysates. The pH of the medium was adjusted to 6.0 ± 0.1 before autoclaving. 250 mL Erlenme yer flasks were filled with 50 mL of growth medium and sterilized at 121°C for 15 min utes . The growth medium was inoculated with a 10% ( volume/volume ( v /v ) ) seed c ulture and cultivated at 25 ± 0.5 °C on a rotary shaker (Thermal Scientific, Odessa, Texas) with an agitation speed of 180 rpm. 2.4 Mass Balance Mass balance analysis was based on the co - hydrolysis and fermentation data. Lipid productivity was calculated by the amount of lipid acc umulated during fermentation divided by the dry weight of initial lignocellulosic biomass per day. 2.5 Analytical Methods The sugar yield from combined dilute acid pretreatment and enzymatic hydrolysis was calculated to evaluate the performance of co - hydrolysis and conduct the mass balance analysis. The sugar yield was determined by the ratio of the measured amount of sugars (glucose and xylose) in co - hydrolysates to the dry weight of initial biomass and also calculated as the percent of theoretical glucose and xylose yields. The combined severity factor (Log CS), which couples reaction conditions of time, te mperature, and acid concentration into a single variable, was used to compare sugar yields. Combined severity is calculated as follows: Log CS = t * exp [(TH - TR)/14.75] pH, where t is reaction time in minutes, TR is 21 the hydrolysis temperature in °C, and TH is the reference temperature of 100°C (Lloyd & Wyman, 2005) ; after pretreatment, the pH measurement was determined by a pH meter ( Fisher Scientific, PA) . Mycelia were collected by filtration and washed twice with distilled water. Cell mass was determined by drying in an oven at 105 ± 1 °C to obtain a consistent weight. Glucose, xylose, acetic acid, formic acid, furfural and HMF in the co - hydrolysates and fermentation broths were determined by High Performance Liquid Chromatography (Shimadzu prominence) equipped with a Bio - rad Aminex HPX - 87H analytical column and a refractive index detector. The mobile phase was 0.005 mol/L sulfuric acid /min . The c olumn temperature was set at 65°C. HPLC standards including glucose (Catalog Number: 49158), xylose (Catalog Number: 9 5729), sodium acetate (Catalog Number: S8750), sodium formate (Catalog Number: 17841), HMF (Catalog Number: 53407), and furfural (Catalog Number: 185914) were purchased from Sigma - Aldrich, St. Louis, MO. Dried mycelia were ground in a mortar and used for l ipid extraction. Total lipid was determined gravimetrically (Ruan & Zanotti, 2012) . 2.6 Statistical Analysis A general linear model using R software (R Version 2.15.0, Vienna, Austria) was applied to the experimental data in order to perform an analysis of variance (ANOVA) and multiple comparisons. - wise type I error rate of 0.05, was adopted to compute honestly significant differences among different feedstocks regarding sugar yield and inhibit or generation. Within each feedstock, the significance of individual factors, as well as the interactions between factors on sugar out at an experimenta l type I error rate of 0.05 to conduct multiple comparisons of both sugar and inhibitor production under different co - hydrolysis conditions. 22 2.7 Results and Discussion 2.7.1 Degradation of Carbohydrates into Sugars and Inhibitors The composition of lignoce llulosic biomass indicated that cellulose was the most abundant fraction in each feedstock ( Table 2 - 1). Corn stover and switchgrass exhibited similar but higher cellulose content (36.3% and 37.4%, respectively) compared to miscanthus (34.2%) and giant reed (29.7%), respectively. The hemicellulose fraction in each feedstock was of a xylan type as indicated by the relatively high amounts of xylose in the polysaccharide. The xylan content for corn stover (22.0%) and switchgrass (22.1%) were equivalent; while m iscanthus (19.0%) and giant reed (19.2%) had comparatively lower levels. In addition, miscanthus and giant reed contained more lignin (22.9% and 22.1%, respectively), compared to switchgrass (20.9%) and corn stover (18.6%). Dilute acid pretreat ment and enzymatic hydrolysis using both the conventional and co - hydrolysis processes were represented in Figure 2 - 1 . Results from the co - hydrolysis process at various pretreatment conditions for the different feedstocks are listed in Tables 2 - 2, 2 - 3, 2 - 4, and 2 - 5 and summarized in Figures 2 - 2, 2 - 3, 2 - 4, 2 - 5, 2 - 6, 2 - 7, 2 - 8, and 2 - 9 , respectively indicated that there were significant (p < 0.0001) mean differences on sugar yields between feedstocks, with the exception of miscan thus and giant reed (p > 0.05). The glucose and xylose yield for corn stover co - hydrolysis was dependent on the main factors of pretreatment temperature and sulfuric acid concentration (p < 0.05), but independent of treatment time (p > 0.05). T here were also significant two - way interactions between time and temperature (p < 0.05), time and sulfuric acid concentration (p < 0.05), and temperature and sulfuric acid concentration (p < 0.05). A pretreatment condition of 130 °C, 2% H 2 SO 4 for 1 h led to the greatest sugar yield of 0.545 g/g dry initial biomass and 83.3% of theoretical glucose and xylose yield for corn stover, producing a total of 52.09 ± 0.13 g/L of fermentable sugars, including 31.1 ± 0.38 g/L glucose and 21.0 ± 0.51 g/L xylose (Table 2 - 2, Figure 2 - 2) . 23 ANOVA analysis indicated that the glucose and xylose yield of switchgrass co - hydrolysis was independent of pretreatment temperature, time and sulfuric acid concentration. The effects of two - factor interactions between time and s ulfuric acid concentration (p < 0.05), as well as temperature and sulfuric acid concentration (p < 0.05) were significant. The treatments of 2% H 2 SO 4 at 130 °C for 2 h had the highest glucose and xylose yields of 0.44 g/g dry initial biomass and 65.8% of th eoretical glucose and xylose yield (Table 2 - 3). It generated 22.8 ± 1.22 g/L glucose and 19.23 ± 0.16 g/L xylose ( Figure 2 - 3 ). The glucose and xylose yield for giant reed co - hydrolysis was shown to be dependent on the main effects of pretreatme nt temperature (p < 0.0001), sulfuric acid concentration (p < 0.05), and pretreatment time (p < 0.05). Two - way interactions of time and sulfuric acid concentration (p < 0.0025), and temperature and time (p < 0.0001)) were also significant. Two different p retreatment conditions (3% H 2 SO 4 at 130 °C for 1 h, and 2% H 2 SO 4 at 130 °C for 1 h) were both shown to have the highest glucose and xylose yield of 0. 355 g/g dry initial biomass at 64.7% of the theoretical glucose and xylose yield ( Table 2 - 4). However, the concentrations of individual sugars from these two pretreatment conditions are significantly different (p < 0.05). The treatment condition of 3% H 2 SO 4 , 130 °C, and 1h generated 18.35 ± 0.67 g/L glucose and 15.56 ± 0.46 g/L xylose, while the treatment condit ion of 2% H 2 SO 4 at 130 °C for 1 h generated 16.71 ± 0.76 g/L glucose and 17.2 ± 0.14 g/L xylose, respectively ( Figure 2 - 4 ). For the miscanthus co - hydrolysis glucose and xylose yield, ANOVA analysis showed that the main pretreatment factors of te mperature (p < 0.0001), time (p < 0.0001), and sulfuric acid concentration (p < 0.05) had significant impacts, while the effects of two - factor interaction terms: temperature and time (p < 0.0001), temperature and sulfuric acid concentration (p < 0.05), and time and sulfuric acid concentration (p < 0.05) as well as the three - factor interaction of temperature, time and sulfuric acid concentration (p < 0.05) were also considered statistically significant. The highest glucose and xylose yield was 0.349 g/g dry initial biomass at 58.1% of the theoretical glucose and xylose yield from the treatment of 2% H 2 SO 4 at 130 °C for 2 h ( Table 2 - 5), corresponding to 17.76 ± 0.94 g/L glucose and 15.55 ± 0.08 g/L xylose, respectively ( Figure 2 - 5 ). 24 Comparison of co - hydrolysis of the four feedstocks demonstrates that combined glucose and xylose yields of miscanthus and giant reed were significantly (p < 0.0001) lower than corn stover and switchgrass. The lower conversion yield was possibly due to those feedstocks having relatively higher lignin contents which likely hindered the enzyme action due to steric actions or absorbing active enzymes during the enzymatic hydrolysis step in the co - hydrolysis process (Liao, et al., 2005) . The co - hydrolysis of corn stover generated the lowest mean concentration of acetic acid (3.92 ± 0.29 g/L ) ( Table 2 - 2), followed by switchgrass (4.04 ± 0. 32 g/L ) (Table 2 - 3), miscanthus (5.12 ± 0.65 g/L ) (Table 2 - 5) and giant reed (5.66 ± 0.86 g /L ) ( Table 2 - and switchgrass had no significant (p > 0.05) differences for acetate generation at the comparison - wise type I error rate of 0.05, while miscanthus and giant reed were significantly diff erent from corn stover and switchgrass (p < 0.0001). Under the best co - hydrolysis conditions of sugar production, the acetic acid concentrations reached 6.43 g/L in miscanthus hydrolysate (Table 2 - 5) and 6.79 or 6.31 g/L for giant reed (Table 2 - 4), respect ively. In contrast, an acetate concentration of 4.08 g/L was obtained from co - hydrolysis of corn stover (Table 2 - 2) and 4.2 g/L from switchgrass, respectively (Table 2 - 3). Furfural and HMF are generated by thermal conversion of pentose and hexose su gars . The experimental results (Table s 2 - 2, 2 - 3, 2 - 4, and 2 - 5) demonstrated that, among the four feedstocks, corn stover hydrolysate exhibited the lowest mean concentrations of furfural (0.54 ± 0.31 g/L ) and HMF (0.0918± 0.018 g/L ), switchgrass hydrolysate had the highest mean furfural concentration (0.77 ± 0.41 g/L ), and giant reed hydrolysate had the highest mean HMF concentration (0.24 ± 0.12 g/L HSD analysis demonstrated that there were significant differences in HMF concentrations between corn stover and giant reed (p < 0.0001), miscanthus and giant reed (p < 0.0001), as well as switchgrass and giant reed (p < 0.0001). However, miscanthus and corn stover (p > 0.05), switchgrass and corn stover (p > 0.05), switchgrass and miscanthus (p > 0.05) were not significantly different in regards to HMF concentrations among the four feedstocks (p > 0.05). 25 2.7.2 Combined Severity Factor Ana lysis The effects of combined severity factor on the co - hydrolysis of the four feedstocks are presented in Figures 2 - 6, 2 - 7, 2 - 8, and 2 - 9 . The concentrations of glucose, xylose, acetate, HMF and furfural were chosen as the responses in order to eval uate the effects of the combined severity factor. The general trend for glucose production in the feedstocks was an initial increase with greater combined severity factor followed by a decrease at higher severity factor levels. Corn stover was an exception to this trend showing no decrease in glucose production even at higher severity levels. It was clear that xylose release was negatively associated with the combined severity factor for all materials due to the degradation of xylose into byproducts, mainly furfural, under harsh conditions. This corresponded well to the fact that furfural generation was positively correlated with the combined severity factor in all samples. Acetic acid likewise showed a positive correlation with combined severity factor, par ticularly for miscanthus and giant reed. However, HMF production appeared to be independent of the combined severity factors for the range being studied. The maximum overall sugar concentrations for corn stover, switchgrass, giant reed and misc anthus were obtained in the combined severity factor ranges of 1.94, 2.14, 1.98 and 2.18 , or 2.25, respectively ( Tables 2 - 2, 2 - 3, 2 - 4, and 2 - 5 ). This indicated that the three herbaceous perennial energy crops required harsher pretreatment conditions compar ed to corn stover. The combined severity analysis effectively allowed for the observation of sugar and inhibitor trends for co - hydrolysis with regards to the dilute acid pretreatment parameters. 2.7.3 Microbial Lipid Accumulation from Lignocellulosic Hydrolysate s The hydrolysates of corn stover, switchgrass, miscanthus and giant reed obtained from the most effective co - hydrolysis conditions were evaluated for their potential uses as carbon sources to cultivate M. isabellina for lipid accumulation. The c ell mass, lipid, and lipid productivity of M. isabellina cultivation, along with sugar concentrations and C/N ratios in the culture medium are shown in Table 2 - 6. 26 The deleterious effects of acetic acid, furfural, and HMF on cell growth and lipid acc umulation of yeasts has been studied (Chen, Zhao, & Xia, 2009) (Hu, Zhao, Zhao, Wu, & Zhao, 2009) (Huang, Wu, Liu, Li, & Zong, 2012) , however, information regarding their effects on oleaginous fungal lipid accumulation is quite limited. The experimental results from this study demonstrated that M. isabellina cultured on the different co - hydrolysates, with the exception of giant reed co - h ydrolysate, exhibited comparable lipid accumulation compared to synthetic hydrolysate (Table 2 - 6). The switchgrass co - hydrolysates accumulated 4.4 ± 0.44 g/L lipid at a culture time of 118 h with initial acetic acid, HMF and furfural concentrations at 3.25 ± 0.088, 0.07 ± 0.002 and 0.97 ± 0.02 g/L , respectively, in the fermentation broth. Miscanthus co - hydrolysate produced 3.71 ± 0. 45 g/L lipid at the same culture time with initial concentrations of acetic acid, HMF and furfural in the fermentation broth of 5.01 ± 0.039, 0.07 ± 0.0009 and 0.92 ± 0.02 g/L , respectively. The corn stover co - hydrolysate produced 3.18 ± 0.02 g/L lipid at 88 h with initial acetic acid, HMF and furfural concentrations of 2.4 ± 0.004, 0.02 ± 0.0004 and 0.19 ± 0.0097 g/L , respectively, in the culture broth. The synthetic hydrolysate produced 3.15 ± 1.13 g/L lipid at 68 h. While giant reed co - hydrolysate generated 3.02 ± 0.31 g/L lipid at 136 h accompanied by initial acetic acid, HMF and furfural concentrations of 6.2 ± 0.07 35, 0.19 ± 0.0004 and 0.51 ± 0.019 g/L in culture media, respectively. Compared to the culture on synthetic hydrolysate, the increased cell mass from co - uch as galactose and arabinose (Chen, Zhao, & Xia, 2009) (Fei, et al., 2011) (Ruan & Zanotti, 2012) found in the co - hydrolysate . Experimental data also indicate that there is a correlation between the period of lag phase and inhibitor concentrations which lead to the difference of lipid productivity among various co - hydrolysates. It was found that the higher acetic acid, HMF and f urfural concentrations in the fermentation broth, such as giant reed, the longer the lag phase and vice versa. 2.7.4 Material Balances Mass balance analysis demonstrated the effects of co - hydrolysates on utilization efficiency of different lignocel lulosic biomass for microbial lipid production (2 - 10). One kg of dry corn stover contains 27 0.363 kg cellulose, 0.22 kg xylan, and 0.186 kg lignin. After co - hydrolysis, 0.33 kg of glucose and 0.20 kg of xylose were obtained resulting in the production of 0.0 628 kg lipid from fungal fermentation (0.0628 g lipid /g corn stover). One kilogram of dry switchgrass contains 0.374 kg cellulose, 0.221 kg xylan and 0.205 kg lignin. Cellulose and xylan were converted to 0.25 kg glucose and 0.20 kg xylose enabling M. isabellina to accumulate 0.0722 kg lipid (0.0722 g lipid/g switchgrass). One kg of dry miscanthus and giant reed were able to produce 0.0499 kg and 0.0421 kg lipid, respectively (0.0499 and 0.04211 g lipid/g biomass). The mass balance analysis demonstrated that the M. isabellina lipid accumulation on co - hydrolysates were superior to other widely studied lipid producing strains such as yeasts grown on similar feedstocks. It has been reported that the oleaginous yeast Trichosporon fermentans grow n on un - detoxified sulfuric acid pretreated rice straw hydrolysate containing glucose (5.1 g/L ), xylose (25.5 g/L ), arabinose (4.6 g/L ), acetic acid (1.4 g/L ), furfural (0.5 g/L ), and HMF (0.08 g/L ) resulted in a lipid yield of 0.017 g lipid/g dry biomass (Huang, Zong, Wu, & Liu, 2009) . The comparison of lipid yield showed filamentous fungi could be a better microbial option to accumulate lipid from lignocellulosic biomass. 2.8 Conclusion This study indicates that the co - hydrolysis process is a technically feasible method to maximize biomass conversion (generate C5 sugars, C6 sugars and acetic acid), and eliminate the need of a large amounts of water for washing and detoxification. The olea ginous fungus M. isabellina ATCC 42613 further demonstrated its unique capacity to not only utilize glucose, xylose and acetic acid in the hydrolysates to accumulate fungal lipids, but also tolerate relatively high concentrations of inhibition products. Th ese results conclude that combining co - hydrolysis of lignocellulosic feedstocks and M. isabellina cultivation for lipid accumulation could be a promising solution for advanced lignocellulosic fuel production. 28 3 Chapter 3 3.1 Abstract Energy balance data is presented for a proposed solar - bio - powered lignocellulosic biodiesel refinery utilizing aerobic filamentous fungal fermentation grown on corn stover co - hydrolysis. The biorefinery assumes eight different unit operations including (1) corn stover collection and transportation, (2) corn stover pretreatment and enzymatic hydrolysis, (3) lignin processing, (4) fungal lipid fermentation, (5) fungal biomass drying, (6) lipid extraction and transesterification, (7) anaerobic digestion and ae robic treatment of wastewater, and (8) solar - bio - power generation. Results demonstrate that aerobic fungal lipid fermentation is the most energy - demanding unit operations, accounting for nearly 49% of the total energy input. Integration of solar - bio - power generation and fungal lipid accumulation is shown to be an effective approach for creating a sustainable lignocellulosic biodiesel production with a positive energy balance. Compared to concentrated solar power (CSP), photovoltaics (PV) technology is more suited to satisfy the energy needs of the lignocellulosic biodiesel production. The PV - bio - powered lignocellulosic biodiesel production has a net energy output of 28.83 MJ/kg biodiesel produced, and a net energy ratio (NER) of 1.11. Keywords : Anaerobic di gestion, Co - hydrolysis Net energy ratio (NER), Energy balance 3.2 Introduction The world economy toda y is virtually petroleum - based, h owever, concerns over its sustainab ility and environmental impact have led to calls for alternative forms of energy production . While many alternative sources of energy exist such as wind, solar, geothermal, and biomass; biofuels represent a near term solution to alleviating dependence on the petroleum based economy while mitigating environmental impacts ( Meher, Sagar, & Naik, 2006) . Biofuels are defined as liquid or gaseous transportation fuels that are principally produced using biomass as a feedstock (Yusuf, Kamarudin, & Yaakub, 2011) . Currently, most biofuels on the market are 29 - canola, or other vegetable oils. First - generation fuels face their own drawbacks. Any increased demand for first - generation fuel crops may result in land use changes on a domestic or international level. If areas containing a significant amount of stored carbon such as forests or peat bogs are converted to agriculture production (which stores comparatively less soil - organic carbon compared to forests and bogs), then a net release of sequestered carbon into the atmosphere may occur, creating a carbon debt that could possibly take the biofuel production system decades to pay off (Mani, Sokhansanj , Tagore, & Turhollow, 2010) . Increased production of first - generation biofuels may also lead to competition with food resources, and possibly lead to shortages and or price increases of feed commodities. One possible solution is the use of lignocellu losic materials as biofuel feedstock, termed second - generation biofuels, which avoid competition with food resources, and may provide greater environmental benefits than first - generation biofuels . Lignocellulosic materials include municipal solid waste, pu lp and paper waste, forest and agricultural residues, and dedicated woody and herbaceous energy crops, and represent the most abundant source of renewable carbon on earth with over 200 billion tons created annually (Chandel & Singh, 2 011) . Current U.S. policy favors the displacement of petroleum - based fuels with lignocellulosic derived sources as seen by the Renewable Fuels 2 Standard in the U.S. Energy and Independence Act of 2007. This law mandates the production of 36 billion gallons of biofuels by 2022, with 21 billion gallons coming from lignocellulosic sources while capping first - generation biofuels at 15 billion gallons (Coyle, 2010) . In order for biofuels to be a viable alter native to petroleu m - based fuels they must demonstrate that they can be produced in a sustainable manner. This means that an ideal biorefinery system should have a positive net energy contribution from the feedstock source; otherwise it is no different than a traditionally e nergy - intensive pulp mill which creates fiber as its primary product and uses residual lignin as a supplemental power source through combustion (Zhu & Zhuang, 2012) . Evaluating the energy output of a biofuel system requires a detailed evaluation of all input and output values. Energy life cycle analysis (ELCA) is a method for determining the cumulative energy inputs from different sources as well as the 30 total efficie ncy of the production process (Pradhan, et al., 2011) . Energy balance methodology involves accounting for the amount of energy used during the production and comparing it to the amount contained in the biofuel. The results obta ined from the energy balance analysis can be expressed as the ratio of energy produced to energy consumed by a production system, otherwise known as the net energy ratio (NER). Increase of NER for biofuel production is key to establishing a sustainable bio refining industry. Renewable energy sources such as solar, wind, geothermal, and biomass could be applied to supplement power to biorefineries and improve their NER. Among these sources, solar energy with the advantages of abundance and availability repres ents an excellent candidate to be combined with a lignocellulosic refinery to produce biofuels. Many solar technologies have been developed in the past several decades such as silicon wafer PVs , thin - film PV, low - temperature solar thermal systems, and CSP systems (Mills, 2001) (Shukla, Sumathy, Erickson, & Gong, 2013) (Price H. , et al., 2002) (Green, 2007) . According to their solar conversio n mechanisms, these solar technologies are mainly divided into two categories: PV and CSP . PV uses semi conducting materials to directly covert phot ons into electrons and generate electricity, while CSP uses heat absorbers or reflective surfaces to collect solar thermal energy for both low temperature ( hot water hea ter) and high temperature ( CSP technologies) applications. Hydrogenated amorphous silicon ( a - Si :H ) thin film PV and parabolic trough power gen eration ( CSP technology ) are selected as the solar power units to be studied for the lignocellulosic biofuel system . Integrating these solar technologies with lignocellulosic biofuel production could lead to a novel biorefining concept that replaces fossil fuel consumption during the process and maximizes NER for next - generation biofuel production. Much of the literature on lignocellulosic biofuels has focused on the ethanol production process, where a pretreatment step is first utilized to disrupt the ma cromolecular structure of the material, and then the solid portion is separated and washed so that hydrolytic enzymes can penetrate and hydrolyze the glucose polymer chain into its monomeric glucose constituents for ethanol fermentation. No general analyse s have been conducted on the production of biodiesel from lignocellulosic feedstocks. Our 31 previous studies developed a new lignocellulosic biodiesel production method to significantly improve process efficiency via removing the solid and liquid separation step after feedstock pretreatment, though the process energy consumption without using other renewable energy is still high, and corresponding energy balance is not favorable for commercial lignocellulosic biodiesel production. Therefore, the goal of thi s chapter is to develop a lignocellulosic biodiesel refining system using the combination of biological and solar technologies to create a neutral energy balance, and thus a sustainable biofuel product. The mass and energy balance was first conducted base d on individual unit operations, and then a system analysis was carried on to conclude an energy neutral lignocellulosic biodiesel refinery. 3.3 Methodology In keeping with LCA principles, two main steps were identified to carry out the analysis. First, we de termined the major unit operations in a lignocellulosic biodiesel refinery capable of producing 20 million gallons of biodiesel a year, including (1) corn stover collection and transportation to the biorefinery, (2) corn stover pretreatment and enzymatic hydrolysis, (3) lignin processing, (4) fungal lipid fermentation, (5) fungal biomass drying, (6) l ipid extraction and transesterification, (7) a naerobic digestion and aerobic tr eatment of wastewater, and (8) solar - bio - power generation. The boundary for the process is shown below Figure 3 - 1, which is described in detail in the following sections. Second, we aimed to conduct an energy inventory in order to calculate the net energy production and thus determine the amount of solar energy input needed to create a sustainable biofuel product. Individual mass inputs to the biorefinery system were converted to common energy units based on their life - cycle energy content (when known), whi ch is defined as the energy needed to produce and transport the final product (Pradhan, et al., 2011) . The energy equivalent for fuel sources combusted for energy production in the refinery were taken to be their low heating va lue (LHV) (Pradhan, et al., 2011) . Based on the mass and energy balance, the net energy analysis (NER) for the system was determined. A sensitivity analysis was likewise conducted in order to identify those factors which could be adjusted in a reasonable manner based on 32 current literature knowledge. A functional unit of 1 kg o f biodiesel produced will serve to quantify the mass and energy products throughout the biorefinery system. Environmental considerations are not explored as this study is focused on the net energy production of a conceptualized stand - alone biorefinery. Fa cility construction, and the production of capital equipment are likewise excluded from the scope of this study, since these impacts are typically considered negligible when weighed against the total amount of product manufactured over their useful lifetim es (International 2010) . S everal co - products were identified during this biorefinery operation including lignin and glycerol. A mass - based system expansion approach is used to account for these co - products. Energy inputs associated with seed cultivation during fermentation were ig nored in this study. Likewise, the electricity usage associated with the downstream recovery and pumping of products was ignored as those technologies vary between plants and the electricity consumed by said processes is likely to be relatively small compa red to upstream processes like fermentation , which can account for approximately 67% of a plants electricity usage (Vogel & Todaro, 1997) . Finally, it should be noted that the when converting electricity consumption to a commo n energy unit, the theoretical conversion factor of 3.61 MJ/kWh was used. This value does not include inefficiencies or transmissio n line losses that are often included in other lifecycle analysis such as Pradhan, which used an energy equivalent of 7.4 MJ/kWh (Pradhan, et al., 2011) . Since fungal - based biodiesel production from lignocellulosic sources is still at the research stage, there are no current operating facilities to serve as a foundation for the analysis. However, many of the unit operations identified are currently used in other industries, and it is reasonable to assume that if and when such a process is developed on an industrial scale it will resemble existing practices as closely as possible (Kim & Parker, 2008) . Thus, much of the data is based on current peer - reviewed resources and industry - derived reports. Thermodynamic calculations were utilized for certain process steps where existing data was deemed incomplete or inadequate, su ch as drying of biomass after fermentation, or the heat energy required for pretreatment reactions. 33 3.3.1 Corn Stover Collection and Transportation The agriculture residue corn stover will be the lignocellulosic feedstock considered as the substrate for fungal - lipid fermentation in this study. It should be made clear that we do not view corn stover to be the only suitable source for fungal - lipid produ ction, rather we consider it as a readily available and attainable resource which can bridge the gap until dedicated energy crop production develops. In our scenario corn stover is treated as an agriculture waste from corn production, and as such, only ene rgies related to its collection, transport, and fertilizer replacement are examined. The energy input of corn stover production is summarized fro m harvesting of the corn stover all the way to its delivery to the biorefinery gate (M orey, Kaliyan, Tiffany, & Schmidt, 2010) . The following values were used in this study: (1) collection/transport to local storage of 196.9 MJ/t on corn stover , (2) local storage inputs of 30.5 MJ/t on corn stover , (3) corn stover compaction for transpo rt of 233.7 MJ/t on corn stover , (4) transport of compacted corn stover to end users 62.4 MJ/t on corn. We also assume that harvesting corn stover likewise removes nutrients which must be replaced by adding additional fertilizer to what is typically applied during regular corn production. The amount of Nitrogen (N), Phosphorus (P), and Potassium (K) fertilizer replacements were 8.8, 0.6, and 7.2 kg/t on dry matter, respectively (Morey, Kaliyan, Tiffany, & Schmidt, 2010) (Sheehan, et al., 2004) . Energy inputs for N, P, and K fertilizer production were 47.7, 13.35, and 8.09 MJ/kg, respectively (Krohn & Fripp, 2012) . 3.3.2 Corn Stover Pretreatment and Enzymatic Hydrolysis Corn stov er received by the biorefinery must undergo both physical and thermochemical treatment steps in order to disrupt the macromolecular structure of lignocellulose (lignin, cellulose, hemicellulose). This allows hydrolytic enzymes to later penetrate and hydrolyze the carbohydrate polymers to their monomeric sugar constit uents, which can readily be metabolized for fungal lipid production. The approximate composition of corn stover is 36.3% (w/w ) cellulose, 22.0% (w/w ) xylan, and 18.6% (w/w ) lignin. Physical treatment is the initial size reduction of the biomass. This proce ss is 34 assumed to be accomplished using a hammer mill, which has energy inputs of approximately 180 MJ/t on of herbaceous biomass (Zhu & Zhuang, 2012) . A novel co - hydrolysis process for lignocellulosic pretreatment and enzymatic saccharification is integrated into this analysis, while co - products are utilized for additional energy production. Co - hydrolysis refers to an initial pretreatment, directly followed by enzymatic saccharification without detoxification and liquid solid se paration between these two steps in order to convert lignocellulose into monomeric sugars (glucose and xylose).The dilute sulfuric acid pretreatment was the thermochemical treatment utilized in this case, where milled corn stover is mixed with water and su lfuric acid, and heated at a particular temperature for a predetermined amount of time. Dilute acid pretreatment is efficient at solubilizing much of the hemicellulose fraction as well as small amounts of the lignin. Our previous study found optimal corn stover pretreatment conditions to be 10% solid loading ( w / w ), 2% acid ( w / w ) at 130°C for 1 h (Ruan Z. , Zanotti, Zhong, Ducey, & Liu, 2013) . Energy consumption to heat the pretreatment slurry to its desired temperature is calcu lated using the following equation. (1) Here E slurry (kJ) is the energy consumption for heating the pretreatment slurry, M slurry is the total mass of the slurry (kg), C p - slurry , is the specific heat capacity of the slurry ( 3.964 kJ/kg / temperature difference between the initial slurry temperature ( 13 °C) and final desired final temperature (130°C) (Kim & Parker, 2008) . Latent heat of vaporization is not factored into the equat ion due to the low reaction temperature and high system pressure. Energy to heat the reaction vessel up to the desired temperature is ignored in this study. The pretreatment step is also assumed to replace any additional sterilization steps since the proce ss occurs at a high enough temperature, time, and at an adequately low pH. After thermochemical pretreatment is complete, the hydrolysate is cooled to 50°C. Regenerative heat exchange is assumed to occur between the hot pretreatment slurry at 130°C and th e incoming water 35 used for the next pretreatment batch . This unit operation has some uncertainty since the 10% solids loading may cause issues with recovering heat in a heat exchanger system which requires further exploration . The total heat recovered is as 80°C. It is assumed that 50% of the recovered heat is used to maintain the enzymatic reaction temperature of 50°C, and other 50% is for preheating the pretreatment slurry. Hydrolytic enzymes are ad ded to the cooled slurry at 50°C in order to cleave the hydrolytic bonds in the remaining cellulose and hemicellulose chains. An enzyme loading of 47 kg protein/ton biomass was used in our previous study resulting in a total sugar yield of 83.3% (Ruan Z. , Zanotti, Zhong, Ducey, & Liu, 2013) . A lignin solubility of 13% at our pretreatment conditions is assumed , which is consistent with past studies (Chen, Zhao, & Xia, 2009) . 3.3.3 Lignin Processing Biomass residues remaining after enzymatic hydrolysis consist primarily of the insoluble lignin fraction at 87% of its original value. Studies show that net system energy can be improved by either combusting the residual lignin for process uses, or refini ng it into value - added products. This study will utilize lignin for combustion due its relatively high low heat ing value (LHV) of 24.4 MJ/kg (Tomani, 2009) . Lignin is typically dewatered to 65% moi sture content before undergoing a drying process to further reduce its moi sture content before combustion . The energy required for lignin drying must consider not only the total lignin mass, but also its water content to account for the heat of vaporization, as shown by the f ollowing equation. (2) Here, E lignin is the total energy to dry the dewatered lignin, M wl is the total mass of wet lignin after dewatering (kg), W is the percent of water in lignin, v is the latent heat of water at 75°C (2321.37 kJ/kg), C p - water is the specific heat capacity of water (4.187 kJ/kg/ °C), C p - lignin is the specific heat capacity of solid lignin (1.1 kJ/kg/ nin temperature (40°C ) and the drying temperature (75°C) (Kim and Parker 2008) (Voitkevich, Kabo, Blokhin, 36 Paulechka, & Shishonok, 2012) . A boiler efficiency (the pe rcentage of feedstock heating value converted to steam) of 80% is assumed (Humbird, et al., 2011) . 3.3.4 Fungal Lipid Fermentation Energy consumption is a major consideration in aerobic fermentation systems. Many components can affect the final power consumption such as agitation, air compression, refrigeration, pasteurization, and downstream processing. Identifying the operating cond itions and unit operations is a key step towards accurately accounting for all energy inputs. Aerobic fungal fermentation for biodiesel production has no current known commercial applications in which to base this analysis on. However, a viable process for producing and extracting gamma - linolenic acid (GLA) from the aerobic culture of the filamentous fungus Mucor circinelloides has been previously implemented and serves as the process basis for the analysis (Cohen & Ratledge, 2010) . The fermentation and downstream processing steps considered in this study include (1) fermentation, (2) pasteurization, (3) filtration /drying, and (4) lipid extraction. Electricity data for the filtration/drying step is ignored in this study. Our pre vious experimental data for the filamentous fungus M . isabellina were used to carry out the mass and energy balance of the fungal - lipid fermentation (Ruan Z. , Zanotti, Zhong, Ducey, & Liu, 2013) . A fungal cell mass concentrati on of 12.84 g cell/L, comprised of 24.82% lipid was reported at 96 h of batch culture. This equates to a lipid yield of 0.0 624 g lipid/g corn stover (Ruan Z. , Zanotti, Zhong, Ducey, & Liu, 2013) . Due to the fact that the M . isabellina fermentation is exothermic, the reaction heat needs to be removed to maintain the desired fermentation temperature of 27°C. The oxygen uptake rate for the fungus is 1.0 mol/kg dry fungal biomass/ h (unpublished data). Since the amount of energy released from consumption of one mol oxygen for aerobic cultures is approximately 460 kJ , the reaction heat generated during the fermentation can be calculated by multiplying oxygen uptake and energy release d per mol oxygen consumption (Doran, 2013) . Heat added due to agitation and the cooling effects of evaporation were ignored in this study. Centrifugal water - cooled chillers are selected to cool the fermentor. The 37 chiller efficiency (defined as kW electric it y needed to remove 12,661 kJ in 1 h) is assumed at 0.6 kW/ton. The electricity demand for cooling the fermenters can then be calculated using heat of the fermentation and chiller efficiency . The fermentors for this process are assumed to contain 100 m 3 o f broth , continuously stirred, with air sparged through the fermentation liquid . The aeration rate is 0.5 m 3 air/m 3 broth/min . The culture time is 96 h . Energy input for the process, largely electricity for agitation and air compression, is calculated as follows (Alves & Vasconcelos, 1996) . (3) Here , P g , P c , and P are agitation power (W), compressed power (W), and total electrical power (W), respectively. The parameters g C are the global efficiencies for agitation and compressor, respectively. Air compressor power is described by the following equations . (4) (5) Here Q is the volumetric air flow rate (m 3 /s) 1 is the coefficient described by equation 5, P 0 is the atmospheric pressure (N/m 2 ), P 1 is the compressor outlet pressure (N/m 2 Agitation power (P g ) is described by equation 6 below. (6) Here N p is the un - 3 ), N is the rotation speed (revolutions/s), P 2 is the pressure at the bottom of the vessel (N/m 2 ), and D is the agitator diameter (m) (Alves & Vasconcelos, 1996) . Assumed values for each parameter are listed in Table 3 - 1. Fungal cells remain metabolically active after substrate consumption, and may begin to consume their oil reserves. As previously detailed, a pasteurization step is necessary to inactivate fungal lipases 38 and phospholipases in order to prevent any unwanted loss in oil content. It has been reported that heating the fermentor to 60°C for approximately 30 minutes prior to harvesting can alleviate these issues. Since fermentation is an exothermic reaction, the cooling process water can simply be shut off, allowing the fermentor to reach the desired temperature without any additional heat ing or cooling input (Cohen & Ratledge , 2010) . Therefore, the energy requirement for pasteurization step is not accounted for in this case. 3.3.5 Fungal Biomass Drying Harvesting the fungal biomass generally includes mechanical dewatering followed by a final thermal drying step. Following mechanical dewatering, the biomass is assumed to have a water content of 80 %. The drying temperature is assumed to be 1 0 5°C, while the incoming biomass temperature is assumed to be 55°C , slightly lower than the broth temperature after pasteurization . Energy to dry the remaining fungal biomass can similarly be calculated using equation 2 with the following changes. M wl is replaced by the total weight of wet fungal mass (M f ), C p - lignin is replaced with specific heat capacity of dry fungal cells (C p - f ), H v is 2066.16 kJ/kg at 1 0 5 0°C. The specific heat capacity for fungal biomass (C p - f ) was calculated based on the composition o f the dry cell mass of M. isabellina shown in equation 7 (Singh & Heldman, 2009) . (7) Here, X is the mass fraction, and the subscripts h, p, f, and a, represent carbohydrate (0.4 8 ), protein (0. 22 ), fat (0. 25 ), and ash content (0.05), respectively. The coefficients represent the specific heat capacity for each mass fraction and are expressed in units of kJ/kg/ °C. 3.3.6 Lipid Extraction and Transesterification Lipid extraction from dried fun gal cells can be modeled using a soybean oil extraction processes without any additional or specialized equipment (Cohen & Ratledge, 2010) . Mass and energy data regarding fungal cell crushing, lipid extraction, crude oil refini ng, and transesterification were collected 39 09 life - cycle analysis study (Pradhan, et al., Energy Life Cycle Assessment of Soybean Biodiesel, 2009) . Consistent with industry - wide practices for soybean biodiesel production, fungal cells will undergo hexane extraction followed by crude oil refining to remove impurities. Refined oil is converted to biodiesel through an acid catalyzed transesterification process. 0.12 kg of glycerol co - product is produced for every 1 kg of biodiesel. Glycerol possesses a relatively large low heating value (LHV) of 1 6 M J/kg and is combusted to produce heat in this study (Emami, Tabil, & Adapa, 2015 ) . 3.3.7 Wastewater T reatment Fermentation effluent after fungal cell harvest is treated by a combined anaerobic digestion, aerobic treatment, and reverse osmosis (RO) process to extract more energy out of the remaining organic matter (OM), reclaim the water, and recycle it back to the process . A naerobic digestion (AD) first utilizes the OM in the effluent to produce methane biogas as an energy by - product, and prepare the effluent with fewer nutrient s for the following aerobic treatment. A continuously stirred mesophilic digester operating at 35°C is assumed to carry out the anaerobic digestion. The fermentation effluent has a chemical oxygen demand (COD) of 35 g/L. The COD reduction of 80% is set for the digestion. Energy usage by the AD system includes electricity for mixing the digestate, as well as heat necessary for raising the waste to the desired temperature. Parasitic electricity cost is assumed to be 2% of the total heat produced by methane com bustion, and parasitic heat demand for heating the reactor will follow equation 1, with C p being that for water (4.18 kJ/kg/ °C 0.25 kg CH 4 /kg COD destroyed (Khanal, 2009) . The effluent waste after anaerobic treatment will have a COD of 7 g/L and will then undergo further aerobic treatment. The required aerobic energy input is calculated based on an energy consumption of 0.317 kWh/m 3 for the effluent with a COD concentration of 500 mg/L (Water Environment Federation, 2009) . A reverse osmosis (RO) and hydrated lime treatment is recommended to be implemented, which could simultaneously produce reclaimed wat er and concentrated NaOH solution for the pretreatment uses, and improve the process efficiency. The reclaimed 40 water from aerobic wastewater treatment process still has 2% Na 2 SO 4 . A reverse osmosis unit with 80% recovery of the feed water can convert 1 kg reclaimed water into 0.8 kg pure water and 0.2 kg brine solution. H ydrated lime is then applied on the brine solution to generate CaSO 4 and 10% NaOH solution. CaSO 4 is settled and removed from the solution. 10% NaOH could be re - used as alkali in the pretre atment. The energy consumption for the RO and lime treatment is 3.35 k W h/m 3 reclaimed water (von Gottberg, Pang, & Talavera, 2012) . 3.3.8 Combined Solar and Biological Power Generation Two solar technologies, PV and CSP , were investigated to be combined with lignin and methane combustion to generate the power to satisfy the energy need s of the system. Since the power generation principles of PV and CSP are different, PV - biological power and CSP - biological power were compared to compare the effects of different solar technologies on the energy balance of the sustainable lignocellulosic biodiesel production system. The PV - biological power generation includes an amorphous silicon (a - Si:H) thin film PV unit and lignin/methane combu stion unit (Figure 3 - 2). The PV module is used solely for electricity generation . The a - Si:H thin film PV is selected because of its low temperature coefficient (0.1% / °C) that allows the PV unit to be operated at a wide range of temperatures without substa ntial power loss (Pathak, Pearce, & Harrison, 2012) . The electricity generated from the PV module is used to power the unit operations in the lignocellulosic biodiesel production. The lignin/ methane combustion unit (boiler ) is dedicated to generate thermal energy for the heat demand of the lignocellulosic biodiesel production. The PV - biological power generation has advantages of direct electricity generation and high utilization efficiencies of electricity and heat. The PV panel s need to be 37 tilted at Meade County, Kansas to obtain maximal solar collection. The average solar radiation available to be extracted by PV is 18 MJ/m 2 /day at Meade County (Marion & Wilcox, 1994) . The electricity conversion efficiency of the thin film PV is 12%. The thermal efficiencies of boilers for lignin/methane combustion are set at 95%. 41 Parabolic trough technology is currently a proven commercial CSP technology on the market today . The para bolic trough solar system is capable of concentrating solar energy to generate steam up to 400°C with a solar thermal efficiency between 30 - 40% (Price H. , et al., 2002) . Therefore, the CSP - bi ological power generation uses par abolic solar trough power technology to be integrate d with lignin/methane combustion to provide power to the lignocellulosic biodiesel production system ( Figure 3 - 3 ). Both parabolic solar trough and lignin/methane combustion technologies generate thermal energy to produce electricity and heat for process uses. The CSP - biological power generation includes parabolic solar trough receiver, boilers, and steam turbine cogeneration. Combining solar thermal energy with lignin/methane combustion has advantages of solving unsteady energy flow issues of solar radiation (using lignin/methane combustion during the period without solar radiation) and alleviating the demand of large solar thermal storage. Meade, KS was again the location for the studied system. The para bolic trough receivers were one - axis tracing parabolic troughs with horizontal north - south axis. The mirror - 305+ polymeric reflector (Price H. , et al., 2002) . The average solar radiation available to be extracted by the parabolic trough receiver is 18 MJ/m 2 /day at Meade County, Kansas (Price H. , et al., 2002) . Solar - radiation - to - steam thermal efficiency (considering radiation an d convection receiver losses, piping and storage thermal losses, and heat - medium to steam thermal losses) is assumed to be 78%. The thermal efficiency of the boilers was set at 95%. The electricity and thermal efficiency of the steam turbine cogeneration a re assumed at 25% and 60%, respectively. 3.4 Results and Discussion Mass and energy data for each unit operation in the biorefinery system are listed below in Tables 3 - 2, and 3 - 3. The net energy production for the entire system is found to be - 113.79 MJ/kg biodiesel produced. This equates to an NER value of 0. 58 . The sensitivity analysis indicates that the lipid yield is the most important parameter to significantly improve the net energy output (reducing a large amount of the energy demand). The sensitivity analysi s indicates that lipid yield is the most important parameter to 42 improve the net energy output (reducing a large amount of the energy demand). The net energy output for the system without combined solar - bio - power generation is changed by 50% respond ing to a 20% change of lipid yield (Table 3 - 4) With combined solar - bio - power generation, the net energy outputs are imp roved to 28.83 and 357.59 MJ/kg biodiesel for the systems with PV - and CSP - bio - power units, respectively; the corresponding NER values ar e changed to 1.11 and 2.32 (Table 3 - 5 ). The detailed interpretation for individual unit operations and integrated system are discussed as follows. 3.4.1 Corn Stover Collection and Transportation Mass balance data in Table 3 - 2 reveals that nitrogen fertilizer re placement is the largest individual input for this operation stage at 0.1 5 kg/kg biodiesel, followed by potassium fertilizer replacement (0.1 2 kg/kg biodiesel), diesel fuel for harvesting stover (0. 10 kg/kg biodiesel), and phosphorus fertilizer replacement (0.01 kg/kg biodiesel), respectively. Total energy consumption for corn stover collection and transportation amounted to 13.23 MJ/kg biodiesel. Paralleling its mass input, nitrogen fertilizer replacement is shown to be the greatest energy consumer at 6.9 7 MJ/kg biodiesel, followed by diesel fuel for harvest ( 5.15 MJ/kg biodiesel), and phosphorus fertilizer replacement ( 0.13 MJ/kg biodiesel ) , respectively. Energy demand s for harvesting and fertilizer rep lacement significantly outweigh those for transportat ion to the biorefinery, indicating that focusing efforts on reducing travel distance to the biorefinery have less of an impact than upstream processes. This is largely owed to the energy - intense production of agricultural chemicals, particularly nitrogen fertilizer. Advances by the fertilizer industry have greatly increased the efficiency of nitrogen production over the last several decades, a nd may continue to play a role, h owever, near - term energy reductions will most likely be achieved through optimizin g fertilizer application rates. This is poses its own issues as there is little agreement in the literature as to the proper nutrient replacement scheme after stover harvest. Petrolia indicates that in a corn - soybean rotation, nitrogen supplementation woul d be unnecessary after stover harvest (Petrolia, 2008) , while Brechbill and Tyner show nitrogen replacement values nearly identical to those assumed in this study (Brechbill & Tyner, 2009) . Sensitiv ity analysis data 43 on fertilizer application rates shown in Table 3 - 4 indicate that slight reductions in nitrogen fertilizer input can lead to significant energy savings. Future work in this area should seek to minimize nutrient inputs while maximizing stov er removal. Ways to address this issue could include researching crop rotation schemes to minimize nitrogen replacement and maximize stover output, or developing dedicated stover harvesters to reduce fuel usage. Due to the high uncertainty with this stage of the biorefinery, continued efforts are needed in order to study the effects of a fully - developed con stover harvesting supply system. 3.4.2 Corn Stover Pretreatment Mass balance data for corn stover pretreatment shows significant inputs for both corn stover (16. 59 kg/kg biodiesel) and water (14 7.67 kg /kg biodiesel) ( Table 3 - 2 ). These two components represent the largest single mass contributors in the entire system. The water input during pretreatment accounts for just over 96% of all water consumption. Though water usage is significant, the co - hydrolysis process actually serves to conserve process water compared to traditional pretreatment methods. This is d ue to the fact that, once pretreatment is complete, the liquid portion of the slurry is retained and further processed. Without co - hydrolysis, water consumption would be double its current value, or 295.34 kg/kg biodiesel. Total energy consumption during this processing stage amounted to 42.68 MJ/kg biodiesel , or roughly 1 6 % of the total energy input. The bulk of this energy is comes from the thermal heat input required to raise the pretreatment slurry to its final temperature. Due to the water conservatio n step during co - hydrolysis, significant energy savings are realized, as any additional water input would likewise require heat energy for sterilization. This means that any reduction in water usage leads to a proportionate drop in energy consumption. Agai n, without co - hydrolysis the thermal energy input would be nearly double its current value, increasing it to 85.26 MJ/kg biodiesel. Thermal energy demand is largely dependent on the reaction temperature , time and solids loading of the pretreatment step s . Therefore, any adjustments to the pretreatment process should focus efforts on increasing solids loading. Adjusting the corn stover solids input from 10% to 12% results in a decrease of the net energy de ficit from - 42.68 to - 34.74 MJ/kg biodiesel, respecti vely. However, it should be noted 44 that at higher solids loadings, additional water must be added in order to match the dilution requirements imposed by the M. isabellina fermentation, thus the energy savings may not be as great as suggested. Though co - hydr olysis comes with certain drawbacks, namely increased toxin concentrations leading to longer fermentation times and lower lipid productivity, it is shown to have great utility in water and energy savings compared to more common methods (Ruan & Zanotti, 2012) . Enzymatic hydrolysis requires a signif icant input of enzymes (0.65 kg protein/kg biodiesel) ( Figure 3 - 4). The en zyme loading (65.2 g protein/kg corn stover) is approximately four times higher than what is reported by other literature studies with similar pretreatment conditions (Zhu & Zhuang, 2012) . Unpublished data from our lab indicates that enzymatic loading can be further dropped by nearly quarter with little loss in saccharification efficiency, thus halving the energy input for this step could be achieved (the result is not used for the mass and energy balance analysis in this study). Reducing enzyme loading, with out sacrificing total sugar yield may require more severe pretreatment conditions in regards to temperature and time, invariably increasing the concentration of compounds toxic to fermentation. 3.4.3 Lignin Processing Utilizing residual lignin as a fuel source is critical to improving the overall energy balance of the biorefinery system. After enzymatic hydrolysis, 3.85 kg lignin rich residue /kg biodiesel rema in s , along with 15.44 kg water/kg biodiesel, which is lost to evaporation (Figure 3 - 4 ) . Lignin residues p rovide approximately 75.30 MJ/kg biodiesel of energy, more than enough to offset the energy demand associated with lignin drying ( 38.98 MJ/kg biodiesel) ( Table 3 - 3 ) . The sensitivity analysis shows that changing drying temperature of the lignin process has a relatively large impact on the net energy output (Table 3 - 4 ). A 20% reduction in the drying temperature leads to a 6.7% sa ving on the net energy output . 3.4.4 Fungal Lipi d Fermentation Aerobic fungal fermentation proved to be by far the largest energy consumer of all unit operations at 132.42 MJ/kg biodiesel ( Table 3 - 3 ), approximately 49% of all energy input. Much of the energy needs associated with this process are due to the electricity consumption required to agitate, aerate 45 and cool the fermentation broth, and as a result of the long fermentation time. Large reductions in energy input are possible with modest adjustments to mixing speed and culture time as shown in the sensitivity analysis (Table 3 - 4 ). When agitation speed and aeration rate are reduced from 90 rpm and 0.5 volume gas flow/volume liquid/minute ( vvm ) to 72 rpm and 0.4 vvm respectively, the energy demand of agitation and aeration is cut from 111.83 to 91.03 MJ/kg biodiesel. If fermentation time is shortened from 96 h to 76.8 h , energy consumption is cut to 107.79 MJ/kg biodiesel. It should be noted that the total kWh calculated for this study based on the assumed parameter values may be on the low side. For i nstance, the calculated air electric power consumption for the air compressor component of fermentation is approximately 10,500 centrifugal air compressor operating at 3 bar g air pressure and supplying 45 m 3 /min (equivalent to the 0.5 vvm used in this study) the total power draw is 260 kW, or nearly 25,000 kWh usage at 96 h of fermentation time (Ingersoll Rand, 2015) . This is an approximately 2.5 t imes greater power draw than assumed in this study, meaning that the already very high electricity usage may be even higher. Decreasing fermentation time is likely best addressed to maximize lipid yields by maximizing lipid productivity. Ruan demonstr ate that once the initial lag phase is overcome in dilute - acid co - hydrolysis, the lipid productivity is similar to that when grown on synthetic sugar substrate (Ruan & Zanotti, 2012) . Aeration rate and agitation speed are both critical parameters as demonstrated in this study. Any proposed large - scale culture should thus strive to decrease agitation and aeration rates by all possible means meanings to reasonable levels while still maintaining sufficient lipid yields. 3.4.5 Fungal Bi omass Drying Once fungal fermentation is complete, a total of 13.67 kg wet biomass/kg biodiesel is produced for harvest. Drying the fungal biomass evaporates 10.94 kg water/ kg biodiesel requiring an energy input of 27.56 MJ/kg biodiesel, in order to reduce the moistur e content to near 0%. Much of this energy input is due to the latent heat of vaporization of water. Decreasing energy consumption for this unit process is likely to come from upstream optimization of the enzymatic hydrolysis or fermentation parameters in 46 o rder to increase biomass yield. The sensitivity analysis also demonstrates that reducing the drying temperature to 84°C can reduce the net energy output by 4.84%. 3.4.6 Lipid Extraction and Transesterification Extraction and downstream processing of fungal oil follows well - established industrial practices from the soybean biodiesel industry including lipid extraction, oil refinement, and transesterification. Microbial lipid extraction converts 2.73 kg of fungal biomass into 1.04 kg of fungal lipid, and is the m ost energy intense step in this unit operation, accounting for 7.64 MJ/kg biodiesel, mainly due to thermal energy requirements. The extraction also requires 2.65 kg of water/kg biodiesel. The final transesterification step producing 1 kg of biodiese l requi res 0.14 MJ , and produces 0.120 kg of glycerol co - product (Figure 3 - 4 ). Combustion of waste glycerol produces enough energy (2.27 MJ/kg) to power t he transesterification process . The whole lipid extraction and transesterification requires 7.78 MJ/kg biodie sel to power the operation ( Table 3 - 3 ). 3.4.7 Wastewater Treatment Applying anaerobic digestion to treat fungal fermentation wastewater significantly improves the overall energy balance of the biodiesel refinery by adding 47.79 MJ/kg biodiesel ( Table 3 - 3 ). The m ethane production of 0.96 kg /kg biodiesel is from the digestion on the fermentation and lipid extraction wastewater ( Figure 3 - 4). After the anaerobic digestion, the AD effluent of 134.82 kg/kg biodiesel is treated by the aerobic treatment process that cons umes 0.154 MJ energy. 132.12 kg reclaimed water from the aerobic treatment is further treated by a combined RO and hydra ted lime treatment. 1.793 MJ/kg biodiesel and 2.44 kg lime/kg biodiesel are used by the treatment to convert the reclaimed water into 10 5.70 kg clean water and 22.46 kg wet CaSO 4 ( Figure 3 - 4 ). 3.4.8 Sola r - Bio - Power Generation The total energy demand for a 20 million gallon per year corn stover biodiesel production is 270.39 MJ/kg biodiesel ( Table 3 - 6 ). The process co - products of lignin, glycerol, and fermentation 47 wastewater are used to generate energy via combustion and anaerobic digestion in order to off - set the energy demand of the production process. The lignin and glycerol combustion (with 95% boi ler thermal efficiency) can generate 71.54 and 2.16 MJ/kg biodiesel of thermal energy, respectively ( Table 3 - 5) The methane from the anaerobic digestion of fermentation effluent can be combusted (with 95% boiler thermal efficiency) and produces 45.40 MJ/kg biodiesel of thermal energy (Table 3 - 5) . The total energy output of the stand - alone lignocellulosic biodiesel production system is 156.60 MJ/kg biodiesel including both biodiesel and thermal energy of lignin/methane/glycerol combustion ( Table 3 - 6 ). The ne t energy output is - 113.79 MJ/kg biodiesel, and the corresponding NER is only 0.58, which means that the energy output from the utilization of these co - products is not enough to cover energy the demand s of biodiesel production ( Table 3 - 6 , Figure 3 - 5). Thus , a renewable energy source, solar energy in this case, is integrated into the onsite power generation system to realize a self - sustaining lignocellulosic biodiesel production. PV and parabolic trough CSP are combined with biological power generation to evaluate their impacts on the energy efficiency of the solar - bio - powered lignocellulosic biodiesel production facility and determine the preferred system configuration. Since the electricity demand of the lignocellulosic biodiesel production is the biggest portion of the overall energy uses usage ( Figure 3 - 5), 147.62 MJ electricity/kg biodiesel is used as the baseline to for the analysis. According to the yearly average solar radiation at Meade KS, the PV - biological power system uses 0.19 m 2 /kg biodiesel th in - film PV panel (12,416,705 m 2 PV panel for a 20 million gallon lignocellulosic biodiesel process) to ge nerate 147.62 MJ electricity/kg biodiesel, and combusts glycerol, lignin and methane to prod uce 119.10 MJ thermal energy/kg biodiesel. The total energy output (including thermal energy from combustion, electricity from PV, and biodiesel energy) is 299.22 MJ/kg. The NER for the process with the PV - biological power generation is 1.11 (Table 3 - 6) , thus making the lignocellulosic biodiesel production an ener gy positive process, and completely sustainable ( Figure 3 - 6 ). In the case of the CSP - biological power generation, solar heat from CSP, lignin, glycerol, and methane are used to generate steam and power a steam co - generator to produce 48 electricity and heat f or the process uses ( Figure 3 - 3) Since the thermal efficiency of the steam co - generator for electricity generation is 25% and boiler efficiency is 95%, the total thermal energy needed from solar heat, lignin, glycerol, and methane to p roduce 147.62 MJ elec tricity/kg biodiesel is 590.48 MJ/kg biodiesel. Subtracting t he thermal energy (119.10 MJ/kg biodiesel) from combustion of lignin, glycerol and methane, the thermal energy needed from solar heat is 471.38 MJ/kg biodiesel ( Figure 3 - 7) which requires an equivalent parabolic trough solar panel area of 0.10 m 2 /kg biodiesel (6,722,000 m 2 parabolic trough solar panel for a 20 million gallon lignocellulosic biodiesel process). Using the CSP - biological power generation, the NER of the studied lignocellulosic biodiesel production is increased to 2.32 (Table 3 - 6) The energy balance analysis demonstrates that an energy positive lignocellulosic biodiesel production can be achieved by integrating biodiesel fermentation technology with solar and bio logical power generation. Considering the total energy output, the CSP - biological power generation uses a smaller solar panel area (0.10 m 2 /kg biodiesel) to generate more energy (627.98 MJ/kg biodiesel) to power the process than the PV - biological power gen eration with corresponding panel area and energy output of 0.19 m 2 /kg biodiesel and 299.22 MJ/kg biodiesel ( Table 3 - 6 ). However, the largest energy demand of the studied lignocellulosic biodiesel production is electricity ( Figure 3 - 5 ), the CSP - biological p ower generation with steam co - generation system has 25% thermal efficiency for electricity generation, which leads to a huge amount of extra heat. The lignocellulosic biodiesel production only uses 25% of this thermal energy, and the remaining 75% of the t hermal energy is not needed by the biodiesel production process. This means that the CSP - biological power generation is not exactly matched with energy demand of the lignocellulosic biodiesel production. In addition, as an on - site power plant unit, the sim ple configuration is an important criterion. CSP - biological power generation consists of solar collector, thermal storage tank, boiler, turbine, generator, and condenser, which is a fairly complicated system (Zhang, Baeyens, Degreve , & Caceres, 2013) . 49 As for the PV - biological power generation, since it directly converts sunlight into electricity, and it avoids the low thermal efficiency issue of heat - to - electricity conversion. Even though the NER for the process combined with the PV - biological power unit (1.11) is lower than the one with the CSP - biological power unit (2.32) (Table 3 - 6 ), the PV - biological power unit has much better energy distribution between electricity and heat than the latter. 100% and 92% of the electricity and heat from the combined PV - biological power unit are used for the biodiesel production process (Table 3 - 6). In addition, the PV - biological power unit has a relatively simple configuration that consists of PV panel, electricity storage, and boiler for s team generation ( Figure 3 - 2) . Therefore, in order to achieve a simple and efficient self - sustaining biodiesel production system, the PV - biological power system is preferred as the power unit to be integrated with the fungal biodiesel production process. 3.5 Conclusion This study has characterized a rudimentary mass and energy balance for a solar - bio - powered lignocellulosic biodiesel refinery. Aerobic fungal fermentation and pretreatment are the largest energy consumers in the refinery, which makes the energy balance unf avorable for lignocellulosic biodiesel pro duction. Co - hydrolysis serves to save both significant amounts of water and energy. Incorporating solar and biological energy production into the process provides a sustainable approach to achieving an energy neutral (or positive) li gnocellulosic biodiesel refinery system . The new concept of solar - bio - powered process can be further extended to other energy - intensive aerobic fermentation processes, so that aerobic biofuel and chemical producti on can be sustainably realized 50 4 Conclusion While petroleum - based fossil fuels play an essential role in the world's economy, their increased consumption and environmental impact have raised concerns. This research, which utilizes filamentous fungal fermentation on lignocellulosic biomass as an alternative scheme for bi odiesel production, represents one possible production substitute for petroleum - based diesel fuel. Chapter 2 focused on the conversion of several different lignocellulosic sources to monomeric sugars, and using a co - hydrolysis process to grow the filamen tous fungus Mortierella isabellina for bio - oil production. The conclusions from this study were: Co - hydrolysis of lignocellulosic biomass with filamentous fungal fermentation can successfully produce bio - oil for use as a feedstock for biodiesel Corn stover exhibited the highest sugar yield of all feedstocks examined in the study at The optimal condtions for corn stover pretreatment were Co - hydrolysis of lignocellulosic Chapter 3 focused on a life cycle energy balance of a proposed lignocellulosic biodiesel biorefinery utilizing filamentous fungal fermentation for lipid production. The conclusions from this study were as follows: Several co - products are produced as a result of the lignocellulosic biodiesel refinery including: lignin remaing from the pretreatm ent and enzymatic hydroslysis of corn stover, fermentation effluent which can be incorporated into an anaerobic digestion scheme , and glycerol produced as a by - product of biodiesel refining . All of these co - proucts can be combusted to help off - set the ener gy inputs to the refinery sytem with lignin combustion providing the greatest total energy output of the co - products . 51 Even with supplemental power produced from co - products , the overall net energy balance is significantly negative (even when ignoring elect ricity usage downstream of fermentation) . The largest single energy input for the entire system is electricity usage for the aerobic fermentation stage, accounting for approximately 50% of all energy input to the system. This number may be even significant ly higher when you consider the fact that no efficiency losses were factored in when converting the kWh of electricity usage to the common energy units of MJ, or the fact that the energy for air compressor usage may be underreported. Sensitivity analysis s hows that lipid yield and productivity as well as the associated fermentation utilities are the most critical factors influencing the overall energy balance for the system and efforts to create a more energy neutral system should focus on these unit operat ions foremost. Incorporating solar PV and CSP technologies can create a positive overall energy balance with CSP requiring a smaller solar panel area to generate more energy compared to the PV. However, t he extra heat energy produced from CSP is difficult to convert to electricity (the largest single input to the biorefinery system). Couple that with the complexity of CSP systems, and it is clear that a more careful analysis between the two technologies is warranted before deciding which to be the better supplement for such a biorefinery. 52 APPENDICES 53 Appendix A : Chapter 2 Tables and Figures Table 2 - 1 Lignocellulosic feedstock composition Cellulose Xylan Lignin Biomass (% w/w) (% w/w) (% w/w) Corn stover 36.3 22 18.6 Switchgrass 37.4 22.1 20.5 Miscanthus 34.2 19 22.9 Giant reed 29.7 19.2 22.1 Table 2 - 2 Corn stover pretreatment conditions and results Dilute acid pretreatment parameters Sugar yields Inhibitory compounds Acid (% w/w) Temp (°C) Time (h) Log CS Glu + Xyl (g/g dry biomass) Glu + Xyl (% of theoretical yield) Acetate (g/L) HMF (mg/L) Furfural (g/L) 1 120 1 1.29 0.455 69.5 3.49 53.05 0.07 2 120 1 1.65 0.503 76.8 3.83 77.57 0.17 3 120 1 1.85 0.51 78 3.88 82.39 0.3 1 120 2 1.57 0.475 72.6 3.53 65.14 0.14 2 120 2 1.9 0.516 78.8 3.94 92.53 0.43 3 120 2 2.1 0.505 77.1 4.01 72.36 0.64 1 120 3 1.97 0.507 77.4 3.66 86.14 0.3 2 120 3 2.22 0.527 80.5 4.21 96.76 0.8 3 120 3 2.35 0.491 75 4.18 93.32 0.91 1 130 1 1.62 0.513 78.4 3.64 89.98 0.25 2 130 1 1.94 0.545 83.3 4.08 109.7 0.63 3 130 1 2.18 0.513 78.5 4.02 98.69 0.59 1 130 2 1.92 0.519 79.4 3.5 114.5 0.3 2 130 2 2.18 0.512 78.3 3.97 110.8 0.7 3 130 2 2.37 0.474 72.4 4.17 107.2 0.97 1 130 3 2.04 0.512 78.2 3.78 99.73 0.33 2 130 3 2.5 0.521 79.6 4.04 102 0.72 3 130 3 1.98 0.507 77.5 4.43 95.29 0.99 Mean / / / 0.506 ± 0.021 77.3 ± 3.2 3.92 ± 0.29 91.8 ± 17.8 0.54 ± 0.31 54 Table 2 - 3 Switchgrass pretreatment conditions and results Dilute acid pretreatment parameters Sugar yields Inhibitory compounds Acid (% w/w) Temp (°C) Time (h) Log CS Glu + Xyl (g/g dry biomass) Glu + Xyl (% of theoretical yield) Acetate (g/L) HMF (mg/L) Furfural (g/L) 1 120 1 1.33 0.388 57.9 3.47 98.54 0.22 2 120 1 1.65 0.421 62.9 3.8 165.8 0.28 3 120 1 1.84 0.428 64 4.02 164.1 0.39 1 120 2 1.57 0.42 62.7 3.78 165.9 0.31 2 120 2 1.93 0.436 65.2 3.81 170.6 0.43 3 120 2 2.09 0.422 63.1 4.08 140.8 0.87 1 120 3 1.89 0.432 64.6 3.91 183.2 0.52 2 120 3 2.22 0.426 63.7 4.13 135.6 1.03 3 120 3 2.32 0.422 63.1 4.5 100.8 1.32 1 130 1 1.85 0.434 64.9 3.67 187.4 0.48 2 130 1 2.04 0.438 65.5 4.05 168.6 0.88 3 130 1 2.18 0.421 62.9 4.11 140.4 0.81 1 130 2 2 0.433 64.7 3.79 191.4 0.57 2 130 2 2.14 0.44 65.8 4.2 146.9 0.96 3 130 2 2.37 0.415 62.1 4.4 136.3 1.17 1 130 3 2.13 0.437 65.3 3.88 198.7 0.56 2 130 3 2.5 0.433 64.7 4.41 155 1.29 3 130 3 2.65 0.399 59.6 4.61 132.8 1.56 Mean / / / 0.425 ± 0.015 63.5 ± 2.05 4.04 ± 0.32 155.4 ± 28.3 0.77 ± 0.41 55 Table 2 - 4 Giant reed pretreatment conditions and results Dilute acid pretreatment parameters Sugar yields Inhibitory compounds Acid (% w/w) Temp (°C) Time (h) Log CS Glu + Xyl (g/g dry biomass) Glu + Xyl (% of theoretical yield) Acetat e (g/L) HMF (mg/L) Furfural (g/L) 1 120 1 1.36 0.262 43.8 4.22 102.8 0.06 2 120 1 1.67 0.305 50.9 4.79 125.8 0.17 3 120 1 1.87 0.311 51.9 4.96 116.8 0.26 1 120 2 1.58 0.303 50.6 4.55 134.6 0.18 2 120 2 1.89 0.319 53.3 4.86 121 0.37 3 120 2 2.08 0.314 52.4 5 86.8 0.62 1 120 3 1.95 0.319 53.2 4.69 109.2 0.32 2 120 3 2.23 0.332 55.3 4.98 73.8 0.76 3 120 3 2.42 0.315 52.6 5.21 66.47 1.06 1 130 1 1.74 0.341 56.9 4.81 155.6 0.37 2 130 1 1.99 0.344 57.3 5.21 85.13 0.96 3 130 1 2.17 0.327 54.5 5.02 68.68 0.91 1 130 2 1.94 0.332 55.5 5.12 201.8 0.37 2 130 2 2.25 0.349 58.1 6.43 174.2 0.89 3 130 2 2.46 0.342 56.9 6.93 114.7 0.88 1 130 3 2.24 0.328 54.8 4.67 126.3 0.41 2 130 3 2.47 0.319 53.3 5.14 74.69 1.11 3 130 3 2.63 0.304 50.6 5.52 72.83 1.49 Mean / / / 0.32 ± 0.02 53.4 ± 3.35 5.12 ± 0.56 111.7 ± 37.7 0.62 ± 0.40 56 Table 2 - 5 Miscanthus pretreatment conditions and results Dilute acid pretreatment parameters Sugar yield Inhibitory compounds Acid (% w/w) Temp (°C) Time (h) Log CS Glu + Xyl (g/g dry biomass) Glu + Xyl (% of theoretical yield) Acetate (g/L) HMF (mg/L) Furfural (g/L) 1 120 1 1.22 0.24 43.8 3.87 270.6 0.04 2 120 1 1.62 0.301 54.8 5.27 352.2 0.18 3 120 1 1.84 0.327 59.6 5.84 307.6 0.31 1 120 2 2 0.32 58.3 6.34 199.5 0.75 2 120 2 1.5 0.267 48.6 4.52 351.1 0.15 3 120 2 1.77 0.314 57.2 5.45 331.4 0.3 1 120 3 1.84 0.313 57.1 5.46 347.2 0.4 2 120 3 2.1 0.334 60.8 6.27 209.9 0.65 3 120 3 2.37 0.328 59.8 6.74 111.1 1.02 1 130 1 1.66 0.327 59.5 5.5 424.3 0.44 2 130 1 1.98 0.355 64.7 6.31 263.1 0.71 3 130 1 2.18 0.355 64.7 6.79 123.5 0.83 1 130 2 2.16 0.339 61.7 4.61 124.2 0.5 2 130 2 2.33 0.336 61.2 4.97 78 0.92 3 130 2 2.52 0.339 61.8 5.19 74.65 0.81 1 130 3 2.04 0.315 57.4 5.47 420.6 0.56 2 130 3 2.39 0.325 59.2 6.25 200 1 3 130 3 2.61 0.302 55 6.98 105 1.01 Mean / / / 0.319 ± 0.028 58.1 ± 5.18 5.66 ± 0.86 238.6 ± 117.2 0.59 ± 0.33 Table 2 - 6 Mortierella isabellina lipid production on synthetic and lignocellulosic media Carbon s ource carbon (mol/mol) Glucose (g/L) Xylose (g/L) Cell mass (X, g/L) Lipid (L, g/L) %Yield L/X (g/g) Lipid productivit y (g/L/d) Synthetic hydrolysate 70.30 ± 4.8 13.66 ± 0.37 14.42 ± 0.78 10.40 ± 0.23 3.15 ± 1.13 30.66 ± 11.77 1.11 ± 0.40 Corn stover hydrolysate 68.90 ± 2.20 15.00 ± 0.04 12.60 ± 0.04 12.84 ± 0.23 3.18 ± 0.02 24.82 ± 0.75 0.87 ± 0.01 Switchgrass hydrolysate 71.50 ± 0.30 13.30 ± 0.10 15.30 ± 0.50 12.55 ± 0.37 4.40 ± 0.44 35.62 ± 3.30 0.90 ± 0.09 Miscanthus hydrolysate 71.00 ± 0.30 13.20 ± 0.10 15.20 ± 0.10 12.28 ± 0.02 3.71 ± 0.45 32.21 ± 3.18 0.76 ± 0.09 Giant reed hydrolysate 68.40 ± 2.6 12.10 ± 0.10 15.10 ± 0.10 13.75 ± 0.87 3.02 ± 0.31 21.18 ± 0.96 0.53 ± 0.05 57 Figure 2 - 1 Conventional and co - hydrolysis process of dilute acid pretreatment and enzymatic saccharification operation for microbial lipid production (modified from Struder) Figure 2 - 2 Glucose and xylose production from corn stover under different pretreatment conditions 58 Figure 2 - 3 Glucose and xylose production from switchgrass under different pretreatment conditions Figure 2 - 4 Glucose and xylose production from giant reed under different pretreatment conditions 59 Figure 2 - 5 Glucose and xylose production from miscanthus under different pretreatment conditions Figure 2 - 6 Combined severity factor effect on the conversion of glucose, xylose, acetic acid, HMF, and furfural from corn stover 60 Figure 2 - 7 Combined severity factor effect on the conversion of glucose, xylose, acetic acid, HMF, and furfural from switchgrass Figure 2 - 8 Combined severity factor effect on the conversio n of glucose, xylose, acetic acid, HMF, and furfural from giant reed 61 Figure 2 - 9 Combined severity factor effect on the conversion of glucose, xylose, acetic acid, HMF, and furfural from miscanthus 62 Figure 2 - 10 Mass balance of microbial lipid accumulation from corn stover, switchgrass, miscanthus, and giant reed co - hydrolysis 63 Appendix B : Chapter 3 Tables and Figures Table 3 - 1 Reactor parameters for pretreatment, enzymatic hydrolysis, and aerobic fungal fermentation Parameter Value Unit Pretreatment reactor N p (power number for marine propeller) 0.35 - D ( a gitator diameter) 1.25 m 1000 kg/m 3 N (rotation speed) 1.5 rotation/s g ( g lobal efficiency for agitation) 0.7 - Hydrolysis reactor N p (power number for marine propeller) 0.35 - D ( a gitator diameter) 1.25 m 1000 kg/m 3 N (rotation speed) 1.5 rotation/s g (Global efficiency for agitation) 0.7 - Fermentor P 0 (atmospheric pressure) 1.0 x 10 5 N/m 2 P 1 ( c ompressor exit pressure) 3.0 x 10 5 N/m 2 P 2 ( p ressure at the bottom of the fermentor) 2.5 x 10 5 N/m 2 N p (power number for marine propeller) 0.35 - D ( a gitator diameter) 1.25 m 1000 kg/m 3 N (rotation speed) 1.5 rotation/s Q (air flow)b 0.83 m 3 /s g ( g lobal efficiency for agitation) 0.7 - c ( g lobal efficiency for compressor) 0.5 - Chiller efficiency 0.6 kW/ton Heat released per mol oxygen consumed during the fungal fermentation 460 kJ/mol O 2 consumed 64 Table 3 - 2 Mass balance data for proposed biorefinery Inventory Input (per kg biodiesel) Output (per kg biodiesel) Stover collection and transport Nitrogen fertilizer 0.146 kg - Phosphorus fertilizer 0.00995 kg - Potassium fertilizer 0.119 kg - Diesel (harvest) 0.0749 kg - Diesel (transport) 0.0200 kg - Corn stover - 16.592 kg Pretreatment and enzymatic hydrolysis Corn stover 16.592 kg - Sulfuric acid 3.320 kg - Alkali 3.320 kg - Water 146.008 kg - Enzyme 0.652 kg - Hydrolysate - 146. 630 kg Hydrolysis residue (wet) - 19. 288 kg Lignin processing Wet hydrolysis residue 19.288 kg - Dry lignin rich residue - 3.858 kg Aerobic fermentation Hydrolysate 146.630 kg - Compressed air (3 bar) 422.294 m 3 - Fungal biomass (wet) - 13. 665 kg Fermentation liquid effluent - 132. 964 kg Fungal drying Wet fungal biomass 13.665 kg - Dry fungal biomass - 2.733 kg Lipid extraction Dry fungal biomass 2.733 kg - Hexane 0.00308 kg - Water 2.652 kg - Fungal lipid - 1.041 kg Fungal biomass residue - 1.692 kg Wastewater - 2.652 kg 65 Table 3 - Transesterification Fungal lipid 1.0413 kg - Methanol 0.0922 kg - Water 0.000 kg - Biodiesel - 1.000 kg Glycerol - 0.120 kg wastewater - 0.156 kg Anaerobic digestion Wastewater (from fermentation and liquid extraction) 135.772 kg - Anaerobic digestion effluent - 134.816 kg Methane - 0.956 kg Aerobic waste treatment Anaerobic digestion effluent 134.816 kg - Reclaimed water - 132.120 kg Reverse osmosis Anaerobic digestion effluent 132.120 kg - Reclaimed water - 105.696 kg Brine water (18.25% Na 2 SO 4 ) - 26.424 kg Lime treatment Brine water (18.25% Na 2 SO 4 ) 26.424 kg - Lime 2.444 kg - NaOH solution (10% w/w) - 6.408 kg Wet CaSO 4 - 22.460 kg 66 Table 3 - 3 Energy flow of 1 kg biodiesel production without solar energy input Unit operations Electricity (MJ/kg biodiesel) Heat (MJ/kg biodiesel) Fossil fuel (MJ/kg biodiesel) Total energy (MJ/kg biodiesel) Energy demand Corn stover collection & transportation - - - 13.23 - 13.23 Pretreatment & enzymatic hydrolysis - 5.23 - 37.45 - - 42.68 Lignin drying - 0.76 - 38.22 - - 38.98 Fungal lipid fermentation - 132.42 - - 132.42 Fungal biomass drying - 0.54 - 27.02 - - 27.56 Lipid extraction & transesterification - 6.61 - 1.17 - - 7.78 Wastewater treatment - 2.06 - 5.68 - - 7.74 Energy product Biodiesel - - 37.5 37.50 Lignin processing (lignin) - 75.3 - 75.30 Glycerol 2.27 2.27 Water treatment (Methane) - 47.79 - 47.79 67 Table 3 - 4 Sensitivity analysis on energy balance for the lignocellulosic biodiesel production without combined solar bio - power generation Key unit operations Parameter Values Corresponding base value (MJ/kg biodiesel) Change on net energy output (%) Base value Sensitivity range Corn stover collection & transportation N fertilizer 0.15 kg/kg biodiesel 0.12 - 0.18 g/kg biodiesel 6.96 ± 1.22 Fossil fuel 0.10 kg/kg biodiesel 0.08 - 0.12 kg/kg biodiesel 5.15 ± 0.91 Pretreatment & enzymatic hydrolysis Solid loading 10% 8 - 12 % 42.68 ± 7.50 Pretreatment temperature 130°C 104 - 156°C 37.45 ± 6.58 Pretreatment time 2 h 1.6 - 2.4 h 37.45 ± 6.58 Hydrolysis time 72 h 57.6 - 86.4 h 2.22 ± 0.39 Lignin process Drying temperature 75°C 60 - 90°C 38.22 ± 6.70 Fungal lipid fermentation Agitation and aeration 90 rpm and 0.5 vvm 72 - 108 rpm and 0.4 - 0.6 vvm 111.83 ± 19.66 Fungal biomass drying Culture time 96 h 76.8 - 115.2 h 132.42 ± 23.27 Drying temperature 105°C 84 - 126°C 27.56 ± 4.84 Entire process Biodiesel yield 0.063 (kg biodiesel/kg corn stover) 0.050 - 0.076 kg biodiesel/kg corn stover 270.39 ± 47.52 68 Table 3 - 5 Solar and biological power generation Energy generation sources Location: Meade, KS PV - biological power Electricity generated by the PV (MJ/m 2 /day) 1.8 Thermal energy from lignin combustion (MJ/kg biodiesel) 71.54 Thermal energy from glycerol combustion (MJ/kg biodiesel) 2.16 Thermal energy from methane combustion (MJ/kg biodiesel) 45.4 CSP - biological power Thermal energy from the parabolic trough collector (MJ/m 2 /day) 14.04 Thermal energy from lignin combustion (MJ/biodiesel) 71.54 Thermal energy from glycerol combustion (MJ/biodiesel) 2.16 Thermal energy from methane combustion (MJ/biodiesel) 45.4 69 Table 3 - 6 Energy balance of a 20 million gallon lignocellulosic biodiesel refinery using solar and biological power generation Without combined solar and biological power generation With combined solar and biological power generation PV CSP Energy demand Process thermal energy demand (MJ/kg biodiesel) - 109.54 - 109.54 - 109.54 Process electricity demand (MJ/kg biodiesel) - 147.62 - 147.62 - 147.62 Process fossil energy demand (MJ/kg biodiesel) - 13.23 - 13.23 - 13.23 Total energy demand (MJ/kg biodiesel) - 270.39 - 270.39 - 270.39 Energy output Biodiesel (MJ/kg biodiesel) 37.5 37.5 37.5 Biological power Thermal energy (MJ/kg biodiesel) 119.1 - - Electricity (MJ/kg biodiesel) - - - Combined solar and biological power generation Thermal energy (MJ/kg biodiesel) - 119.1 442.86 Electricity (MJ/kg biodiesel) - 147.62 147.62 Solar panel area (m2/kg biodiesel) - 0.19 0.1 Total energy output (MJ/kg biodiesel) 156.6 299.22 627.98 Overall energy balance Net electricity output (MJ/kg biodiesel) - 147.62 - 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