Hydrothermal treatment of algal feedstocks

Transcription

1 The University of Toledo The University of Toledo Digital Repository Theses and Dissertations 2013 Hydrothermal treatment of algal feedstocks Joshua C. Wissinger The University of Toledo Follow this and additional works at: Recommended Citation Wissinger, Joshua C., "Hydrothermal treatment of algal feedstocks" (2013). Theses and Dissertations This Thesis is brought to you for free and open access by The University of Toledo Digital Repository. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of The University of Toledo Digital Repository. For more information, please see the repository's About page.

2 A Thesis entitled Hydrothermal Treatment of Algal Feedstocks by Joshua C. Wissinger Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Master of Science Degree in Chemical Engineering Dr. Constance Schall, Committee Chair Dr. Cyndee Gruden, Committee Member Dr. Sridhar Viamajala, Committee Member Dr. Patricia R. Komuniecki, Dean College of Graduate Studies The University of Toledo August 2013

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4 An Abstract of Hydrothermal Treatment of Algal Feedstocks by Joshua C. Wissinger Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Master of Science Degree in Chemical Engineering The University of Toledo August 2013 Global warming, depletion of fossil fuel resources, and foreign oil dependency has placed urgency on the research of alternative fuel sources [1]. This research is focused on the processing of microalgae to a biofuel precursor while utilizing the water content as a valuable biopolymer-rich recycle to growing algal cultures. Mild temperatures for the hydrothermal treatment of the algal feedstock are suggested and supported by experimental results. Some benefits of operating at milder temperatures are the minimization of energy input, biopolymer degradation, toxicity of unwanted byproducts in the aqueous recycle, as well as a high quality oil biofuel precursor of low nitrogen content. Focal points of this research include the characterization of cultured algal feedstocks, various hydrothermal treatment experiments with analyses to quantify changes in resulting product streams, as well as parallel culturing of algae with recycled biopolymer-rich aqueous phase in the media along with standard growth media to determine impact of the recycled stream on growth. A preliminary energy balance and emission estimates were determined to gauge industrial scale feasibility of the hydrothermal treatment proposed. iii

5 Table of Contents Abstract iii Table of Contents... iv List of Tables......vii List of Figures......ix 1. Introduction Background Bioethanol Biodiesel Microalgae Comparison of Microalgal and Terrestrial Plant Feedstocks Research Goals Preliminary Energy Balance of Hydrothermal Processing Introduction Background Process Design Energy Balance Calculations Emissions Algal Growth and Characterization Methods iv

6 3.1 Introduction Background Algal Culturing Material and Methods Algal Compositional Analyses Protein Analysis Carbohydrate Analysis Lipid Analysis Ash Analysis Moisture Analysis Algal Characterization Results Hydrothermal Processing Materials and Methods Introduction Background Reactor Setup and Operation Oil Nitrogen Content FAME Analysis Free Fatty Acid Analysis Amino Acid Analysis Hydrothermal Processing Results Introduction Analysis of Oil Phase Schizochytrium limacinum and Pseudo Algae Comparison of nitrogen content in the oil phase...57 v

7 Oil Nitrogen Content FAME Analysis FA Analysis Oil Phase Result Summary Aqueous Phase Amino Acid Analysis Preliminary Algal Growth Trials with Aqueous Layer Recycle Conclusions and Future Work References.. 87 vi

8 List of Tables 1.1 Comparison of common feedstocks in oil production, land requirements, and percentage of existing cropping area needed in the U.S Comparison of common bioethanol and biodiesel feedstock water footprint, land requirement, energy production and yield of biofuel Determined lipid hydrolysis Arrhenius kinetic parameters used in model prediction of FA production Hydrothermal reactor operating temperatures and pressures used in energy balance calculation obtained from ChemCAD Determined energy inputs and outputs of the proposed hydrothermal treatment process Fatty acid components of oil layer produced from a S. limacinum hydrothermal reactor run with determined mass fractions used in calculation of the overall high heating value based on the weighted fraction Comparison of oil high heating values based on two methods, which use different elemental information in calculations Carbon dioxide pollution estimates based on calculated energy requirements of hydrothermal treatment process. 25 vii

9 4.1 BSA protein amino acid formulas, molecular weights, and weight percentage in BSA used Identifiable amino acids through Phenomenex GC-FID protocol and their retention times Comparing oil nitrogen content of pseudo slurries with different P:L at hydrothermal processing temperatures at 250 and 310 C Summary of author specific feedstock species, biopolymer composition, calculated protein lipid ratios, and loading (% w/v, dry weight basis) Comparison of P:L ratio and oil nitrogen percentage limit from 275 C to 350 C Lipid component retention in hydrothermally treated solid phase Trends in AA concentrations of 30 minute hydrothermally treated aqueous phase samples for both pseudo and S. limacinum Summary of reactor runs used to produce aqueous phases used to recycle to growing cultures for determining impact on growth rates Cultured algae dry weight growth results utilizing aqueous phase recycle from both pseudo and algal slurry hydrothermal treatment reactor runs Summary of hydrothermal treatment phase analyses demonstrating benefits of mild temperature operation over severe conditions viii

10 List of Figures 2-1 Lipid hydrolysis reaction pathway resulting in glycerol and fatty acid products Main steps in mild hydrothermal treatment of algae as a feedstock Diagram detailing the processing stream and equipment involved in the proposed hydrothermal treatment of an algal slurry feedstock Overlaid chromatogram of an S. limacinum oil (red) based FAME sample on a chromatogram of external standards (blue) FAME standard C20:0 calibration curve Compositional results of lab cultured S. limacinum used in this research including lipid, protein, carbohydrate, ash and a small fraction was undetermined Parr Instruments batch reactor setup used in hydrothermal processing experiments of algal slurries Chromatogram of a FA standards overlaid on a S. limacinum hydrothermal treatment oil sample chromatogram Comparison of a BSA standard chromatogram and hydrothermally treated and acidhydrolyzed aqueous layer chromatogram Demonstration of agreement between alga and pseudo slurries in determining trends in oil nitrogen content with 30 minute batch reaction time. 59 ix

11 5-2 Experimental verification of trends in oil layer nitrogen percentage for P:L of 0.9 over a range of reaction durations and temperatures Compilation of hydrothermal processing product oil layer nitrogen percentage over a range of subcritical water temperatures provided by other researcher s results FAME content of the oil phase is shown over a range of temperatures and reaction durations for hydrothermally treated pseudo algae (P:L ratio of 0.9) Comparison of experimental and kinetic model predicted YFA of the pseudo and S. limacinum systems over a range of temperatures and reaction durations Temperature fluctuation seen in a 250 C 60 minute reactor run as a result of introducing burette contents at room temperature into the reactor A comparison of untreated aqueous layer AA chromatogram and that of an acid hydrolyzed releasing the amino acids of the proteins and peptide Tracking of algal growth by OD x

12 Chapter 1 Introduction 1.1 Background The worldwide demand for fossil fuels has increased greatly over the last several decades. Fossil fuels include coal, natural gas, and petroleum. Currently roughly 80% of the world s energy is derived from fossil fuels [1]. These energy sources are considered non-renewable due to the long period of time, millions of years, required for creating these feedstocks from natural geological processes converting prehistoric organisms to carbon rich fossil reserves. An increased demand in fossil fuels is a result of the growth in manufacturing, global economy, household energy, and transportation fuel consumption. The result of this demand and usage is increased carbon and greenhouse gas (GHG) emissions. A carbon cycle is normally in play (distributing between fossil carbon, oceans, atmosphere, and terrestrial biosphere [2]) keeping the atmosphere at consistent levels of carbon. Recently, the carbon output has far outweighed the carbon recovery potential. This imbalance has led to a buildup of carbon dioxide, a product of combustion, in the atmosphere, which has resulted in global warming. 1

13 Nations are starting to implement proactive legislation with respect to energy production as well as transportation emissions [3]. The U.S. has set a goal to develop and support the production and usage of renewable fuel sources and reduce foreign oil dependency [4]. Over the last 3 years America has increased domestic oil production as well as reduced foreign oil dependency consistently [4]. This swing of domestic versus foreign oil production will help with national economic stability, but the continually increasing energy demand is still negatively impacting the environment through increases in greenhouse gas emissions, GHG, (i.e. carbon dioxide). The estimated remaining supply of fossil fuels will last anywhere from 41 to 700 years depending on consumption and accuracy of reserve volume estimates [1]. Biofuels derived from renewable feedstocks have gained much interest in order to reach a goal of minimizing dependency on foreign oil as well as reducing GHG emissions in comparison to petroleum derived transportation fuels [1, 5]. Independence of foreign oil can be achieved through domestic renewable fuel feedstock growth. Two current and near term production processes and renewable feedstocks for bioethanol and biodiesel will be briefly described. The potential of microalgal feedstocks will then be summarized. The focus of the research presented here is in extraction and processing of lipid rich algae for fuel or chemical production. 1.2 Bioethanol Bioethanol has the largest production volume of biofuels globally with worldwide production estimated at 85.2 billion liters in 2012 [5]. It is currently produced from starch-rich (i.e. corn) or sugar-rich (i.e. sugarcane) feedstocks. 2

14 Lignocellulosic biomass can also be used in the production of ethanol from materials such as switchgrass, poplar, and agricultural residues [1]. Some research has suggested production of ethanol has a net energy loss (requiring more fossil fuel energy to produce the fuel than energy available from the fuel) in studies of feedstocks including corn, switchgrass, and woody biomass [6]. This research points out that life cycle analyses which claim energy gains in ethanol production have been proven to omit many sources of energy usage during the production process [6] such as farming equipment, labor, fertilizer, pesticides, etc. Other lignocellulosic biomass life cycle analyses prefer to point out the major areas of concern which require further understanding, modeling, and investigation to increase the viability of this feedstock for [7]. The main area of focus discussed is understanding the pretreatment process mechanistically so that a rational pretreatment process can be modeled for a specific feedstock resulting in efficient processing [7]. These life cycle analyses have been thoroughly investigated, but with such a broad range of feedstock composition, available pretreatment methods, and wide range of parameters in life cycle analyses, a firm conclusion is nearly impossible. Unfavorable processes or feedstocks can be approved due to supply and demand. Research has compared current energy gains over several feedstocks including petroleum, coal, soy oil, and cellulosic crops to name a few [8]. It was determined that gasoline was the most unfavorable energy source at 13.7 $/GJ compared to cellulosic crops at 3.0 $/GJ, corn kernels at 6.6 $/GJ, and soy oil at 13.8 $/GJ [8]. Gasoline derived from petroleum can be sustained through enormous price fluctuations and public willingness to pay. Many alternative fuel producers currently operate with essential government assistance and require secondary products (i.e. animal feed) for profitable 3

15 ethanol fuel production [6]. Ethanol production can be viewed as a viable option needing further investigation and advancement in technology to create an energy and economically positive process. 1.3 Biodiesel Another renewable fuel is biodiesel, which can be produced from vegetable oils, including soybean, palm, rapeseed, and sunflower oils, as well as animal fats [9]. Current biodiesel production in the U.S. primarily utilizes rapeseed and soybean oil as feedstocks [10]. Unfortunately the use of soybean oil has also been determined undesirable due to the fossil fuel requirement for production, which is 27 % above the energy available from the resulting oil product [6]. A larger downfall of terrestrial crops as biofuel feedstocks is the food versus fuel dilemma and limited availability of fertile land for growth [11]. With limited area for growth, both ethanol and crop-based oil production cannot realistically satisfy the overall demand of global transportation fuels [6]. 1.4 Microalgae A source of oils similar to vegetable oils includes microorganisms such as algae, fungi, and bacteria [9]. These single celled organisms are valuable fuel sources due to their biopolymer makeup of protein, lipid, and carbohydrate. Another major advantage of this form of feedstock is the quick and flexible growth platform. An appealing characteristic of these feedstocks is the diversity of growth and media utilization. Microorganisms such as bacteria, fungi, and microalgae can be autotrophic, heterotrophic 4

16 or mixotrophic which gives growth flexibility that can be applied to specific regions of the world depending on the growth environment available. Autotrophic growth would be most applicable in a region of inexpensive or waste carbon dioxide source with sunlight available for photosynthesis [12]. This would create minimal input since sun, carbon dioxide, and water are the main components needed for this growth [12]. Unfortunately, in autotrophic cultivation the available photon flux from sun exposure is essentially inversely proportional to the culture density, which limits growth rate and biomass yields per unit volume [12]. Heterotrophic cultures utilize carbon contained in the media such as glucose or glycerol. This would be a viable option in a region with limited sunlight or limited land capacity since cultures could be stacked as exposure to sunlight is not an issue [12]. Mixotrophic cultures can utilize photosynthesis or media containing carbon material for growth [12]. 1.5 Comparison of Microalgal and Terrestrial Plant Feedstocks Algal microorganisms are beneficial because of their potentially rapid growth rates compared to terrestrial oil producing crops. As seen in both tables below microalgae is a much greater producer of oil and biofuel producer per area of land than any terrestrial producing crop. 5

17 Table 1.1: Comparison of common feedstocks in oil production, land requirements, and percentage of existing cropping area needed in the U.S. Data from reference [13] a For meeting 50 % of all transportation fuel needs in the U.S. b 70 wt % oil in biomass c 30 wt % oil in biomass 6

18 Table 1.2: Comparison of common bioethanol and biodiesel feedstock water footprint, land requirement, energy production and yield of biofuel. Data from reference [14] 1.6 Research Goals The purpose of this research is to assess the feasibility of a hydrothermal pretreatment algal feedstock and production of a nutrient-rich aqueous phase and a low nitrogen content oil phase. An aqueous phase with nutrients could be recycled back to the algal culture, minimizing water and possibly nutrient inputs. The oil phase can serve 7

19 as a precursor for biofuel or chemical production. Several analyses were performed on lab-scale product streams to determine compositional changes as a result of varied batch reactor operating parameters. Aqueous layers have been analyzed to determine nutrient retention (nitrogen and carbon sources) for algal cultures as well as the impact of recycle on growth rates. Oil phases were analyzed for hydrolysis of triacylglycerides (TG) to free fatty acids (FA), fatty acid methyl ester (FAME) content, as well as nitrogen content. A preliminary energy balance for hydrothermal processing has been made, to assist in determination of energy input compared to potential fuel energy value and process feasibility. This energy balance and underlying assumptions are discussed in the second chapter. Chapter three details the culturing and techniques used in characterization of harvested algal feedstocks used in this research. Chapter four begins the discussion of hydrothermal processing. This includes the feedstocks used in experimentation and detailed description of the analyses performed on input and output streams. The findings of the product analyses are summarized and discussed in chapter five. Chapter six summarizes the impacts of hydrothermal treatment aqueous layer recycle on growing cultures. Based on these results, a summary of future work suggestions are discussed in chapter seven. 8

20 Chapter 2 Preliminary Energy Balance of Hydrothermal Processing 2.1 Introduction In this second chapter the process used and modeled in this research is described. Various techniques used to process microalgae are discussed to give an understanding of how the proposed schematic was developed. Determination of process feasibility has been performed through a preliminary energy balance based in part on experimental results. This included energy requirement calculations based on the major steps of the experimental process. Many energy inputs such as those necessary for culturing, process flow management and other common industrial requirements have been neglected for simplicity. Ending the chapter is a calculation of theoretical emissions as a result of our processing scheme. 2.2 Background The proposed treatment and processing of lipid-rich microalgal feedstocks utilizes subcritical water as a reaction medium. Employing subcritical water eliminates the 9

21 energy intensive and expensive water evaporation or drying steps involved in many processing techniques such as pyrolysis. Hydrothermal treatment can be defined as the use of water temperatures between normal boiling and supercritical points, 100⁰C and 374⁰C. Water in this temperature range has a decreased dielectric constant, which begins to approach that of an organic solvent [15]. Mimicking an organic solvent assists in solubility of the hydrophobic fractions of the algae improving disruption and separation of the various biopolymers. With lipid rich algae as the feedstock of focus, the aim of the proposed treatment is to create a separable mixture of lipid and aqueous phases. Conditions are sought to form an oil layer suitable for further biodiesel processing and a nutrient rich aqueous layer enriched in protein and carbohydrate portions of the feedstock suitable for recycling to growing cultures. In a subcritical water reaction environment, biopolymers will participate in hydrolysis reactions. Many of these reactions could produce secondary and unwanted components potentially poisoning growing cultures. Lipids and free fatty acid, FA, are the main components of the produced oil layer. Triacylglyceride, TG, is the common structure of algal lipids as well as soybean oil used in experiments to mimic lipid fractions in pseudo algal mixtures of biopolymers. Hydrolysis of TG to FA, in subcritical water conditions have been modeled [16, 17]. Figure 2-1 below is a general hydrolysis reaction of a triacylglyceride (TG) in water (W) releasing the glycerol (G) backbone and three (FA). 10

22 Figure 2-1: Lipid hydrolysis reaction pathway resulting in glycerol and fatty acid products. Model predictions of TG hydrolysis with subcritical water suggest that lower operating temperature and reaction duration will limit FA production. Production of FA is not necessarily the purpose of the hydrothermal treatment, but is an inevitable result of using a subcritical water system to enhance the separation of lipids from other algal biopolymers. An empirical model of TG hydrolysis suggests the reaction is autocatalytic, [16, 17]. Lipid hydrolysis reaction rates increase with added acid. Since FA is an acid, it is capable of accelerating the hydrolysis of TG. Its production must be minimized if an oil product layer rich in triacylglycerides is desired [16, 17]. The autocatalytic behavior of FA was modeled through the empirical rates equations below [16, 17]. The additional symbols given in these equations include reaction intermediates of diacylglycerides (DG) and monoacylglycerides (MG). Rate constants (k) were determined for the uncatalyzed reactions labeled using the 1 and -1 indicating forward and reverse reactions. Autocatalytic forward and reverse rate constants are labeled with 2 and -2. An Arrhenius relationship (Equation 2-7) was used in regressing the kinetic parameters (Table 2.1) 11

23 from experimental data and rate equations with reaction order assumed to be equivalent to the reaction stoichiometric coefficients [16, 17]. TG k 1 + W DG + k -1 FA (2-1) DG k 1 + W MG + k -1 FA (2-2) MG k 1 + W G + k -1 FA (2-3) TG k 2 + W + FA DG + k -2 2FA (2-4) DG k 2 + W + FA MG + k -2 2FA (2-5) MG k 2 + W + FA G + k -2 2FA (2-6) (2-7) Table 2.1: Determined lipid hydrolysis Arrhenius kinetic parameters used in model prediction of FA production. In order to obtain an oil phase of low nitrogen content as well as minimize unwanted secondary reactions and product formation, mild operating conditions were 12

24 explored in this research. Increasing severity of hydrothermal conditions can produce charring and degradation of contained biopolymers such as proteins and carbohydrate. Degradation reactions can occur at reaction times as low as 15 minutes at 250⁰C [17]. A result of this charring can be the introduction of unwanted secondary reactions and products, which could potentially contaminate the oil or aqueous layers requiring further refining prior to downstream biofuel processing or recycling to cultures. Mild operating conditions are attractive not only from a chemical standpoint, but also an economic one. An energy balance has been performed on a hydrothermal processing scheme for lipid-rich algae for fuel production (Figure 2-2). This energy balance gives an initial indication of whether a process can yield products with more fuel energy than energy input into the process. Higher fuel energy for products compared to process energy inputs suggests that the hydrothermal processing merits further development. Beyond simple determination of energy in versus energy out, a reduction in energy input by operating at milder conditions would be economically beneficial as long as it is also supported from a chemical standpoint. There are many different possible routes to obtain conversion of the microalgae lipids to a biodiesel product. Methods include extraction of the lipid fraction from the algal slurry or processing dried algal powder. Water removed through evaporative heating is very energy intensive [18]. Alternatively, lipids could be separated from water/algal slurry by chemical means such as extraction and phase separation [19]. Mechanical disruption of the cells would also be beneficial for effective solvent extraction, such as bead beating or sonication, but would drive up energy requirements of this separation technique [20]. Extraction methods for alga/water slurries would require 13

25 large volumes of volatile organic solvent when implemented on an industrial scale. In another proposed route of biodiesel production, a one-step transesterification of the lipid is performed on dried algae with methanol and an acid or base catalyst [21]. Water in this case is removed to minimize the competitive hydrolysis reaction. A disadvantage of this approach would be the handling and consumption of catalysts and energy input associated with water removal. 2.3 Process Design The processing scheme investigated in this research includes the culturing of Schizochytrium limacinum, concentration into slurry, hydrothermal treatment of microalgal and pseudo slurries, phase separation, and recycling of the aqueous layer to growing cultures. S. limacinum is a marine fungus, but is referred to as microalgae in this research due to the similar makeup, feedstock applicability, and research between this species and many species of microalgae. 14

26 Figure 2-2: Main steps in mild hydrothermal treatment of algae as a feedstock. 15

27 Figure 2-3: Diagram detailing the processing stream and equipment involved in the proposed hydrothermal treatment of an algal slurry feedstock. 16

28 The schematic above begins with an input stream consisting of water and necessary culture media components detailed in chapter 3. The volume of this growing culture is 33 m 3 (33,000 L or kg), a volume estimated to produce one cubic meter of 10 % (w/v) of algal biomass on a dry weight basis after centrifugation. These values are based on bench-scale results. Lab scale cultures were grown at a volume of 1 L. Post centrifugation, slurries were roughly 0.03 L with ~10 wt % solids [22]. By scaling the lab scale obtained slurry volume of 0.03 L to theoretical process stream volume of 1 m 3 used for calculations, the resulting theoretical culture volume would scale from 1 L (1*10-3 m 3 ) to 33 m 3. The culture is assumed to yield a biomass concentration of 3 kg dry biomass per cubic meter of culture (0.3 % w/v). This dilute culture is concentrated via centrifugation to 10 % (w/v) algal slurry. For every one cubic meter of algal slurry produced, 32 m 3 of water is recycled to the culturing tank. Next the concentrated slurry is pumped to operating pressure determined from steam tables based on the set hydrothermal reactor temperature (Table 2.1). Reactor temperature is reached through pre-heating the reactor feed in the heat recovery exchanger where heat is transferred to the algal slurry from the hydrothermal pretreatment reactor outlet stream. Heat integration is a valuable method of minimizing the energy requirement of a process and is the reasoning behind recovering the heat from the reactor product stream. Assuming a minimum 10⁰C temperature approach in the heat recovery exchanger, further heating is accomplished by the second heat exchanger to reach set reactor operating temperature in the slurry process stream. The reactor produces a stream consisting of both an oil and aqueous layer. The oil layer is rich in lipid and FA and based on the processing 17

29 assumptions would have a volume of roughly 47 L assuming a density of 0.92 kg/l and lipid fraction of the algae at 43 wt %. Major components in the aqueous layer include glycerol, protein, and other carbon materials at a volume of ~950 L. As mentioned previously heat is recovered from the reactor product stream and used to preheat the reactor feed stream. Based on the 10⁰C temperature approach of the heat recovery exchanger, the product stream leaves the exchanger at roughly 35 to 40⁰C. Once cooled, the stream is put through a phase separation vessel, which would utilize solvent extraction in separating the oil from the aqueous layer. The solvent would be evaporated and recovered from the oil layer. The remaining pure oil layer would be taken on for further processing to biofuel or other chemicals. Nutrients contained in the aqueous layer are recycled to the growing cultures to reduce the need for further refining into secondary products, and also to supplement and minimize pure media components. 2.4 Energy Balance Calculations The processing scheme above begins with concentrating the dilute culture from a volume of 33 m 3 to the 1 m 3 concentrated slurry process stream volume. An energy input of 0.9 kwh/m 3 was assumed for the centrifugation of the 33 m 3 process stream volume [23]. This mechanical concentration is a source of energy input accounted for in the energy balance. The pressures associated with water at the reactor operating temperatures were determined through the use of ChemCAD [24], but can also be found in steam tables. These pressures were determined assuming a saturated liquid state would be maintained inside the hydrothermal pretreatment reactor. Energy required to pump the process 18

30 stream to operating pressure is the second contributor to the energy balance input calculations. Energy requirements for the various operating temperatures and pressures were determined using ChemCAD simulations assuming a stream composition of pure water. This is a conservative assumption due to the large fraction of water in the slurry and the high heat capacity of water compared to other components. Assuming the heat capacity of water in calculations will somewhat overestimate actual energy requirements of the process. Four reaction temperatures including 150 C, 200 C, 250 C, and 310 C were examined. The change in operating temperatures impacts the pumping and heat exchanger energy requirements to reach the operating temperature and pressure. Table 2.2: Hydrothermal reactor operating temperatures and pressures used in energy balance calculation obtained from ChemCAD. The need for a second exchanger stems from heat exchanger temperature approach heuristics and incomplete heat recovery. This second exchanger brings the stream to the operating temperature and this is the last energy requirement accounted for in the preliminary energy balance. 19

31 Table 2.3: Determined energy inputs and outputs of the proposed hydrothermal treatment process accounting for processing volumes, oil composition, and recovery efficiencies. The table above summarizes the amount of energy needed to operate the centrifuge, pump, heat exchangers, and summation of these inputs needed in the proposed schematic, Total Energy Usage. The column Energy Produced was calculated based on the 43 kg of oil theoretically produced from the determined processing volume and feedstock lipid content. Based on the theoretical oil weight and known FA profile, an estimate of the oil s energy was calculated and reported as Energy Produced. The Adjusted HHV is based on 40 % of the Energy Produced (HHV) from the lipid fraction, and accounts for incomplete oil recovery seen in lab-scale experiments. The term HHV is discussed below. The centrifuge energy requirement is reported as MJ/m 3 of slurry being processed rather than the kwh unit taken from literature to ensure uniformity. The process streams were assumed to be composed of only water for the energy balance calculations. For a viable process the energy input must be offset by the energy that can be produced through combustion of the fuel product. This fuel energy can be calculated as a high heating value (HHV). The HHV is a measure of the amount of heat released when a defined amount is combusted [25]. The HHV also accounts for the amount of water in the sample by condensing the water vapor contained in the combustion products. The 20

32 lower heating value (LHV) or net heating value (NHV) does not account for the heat needed to vaporize the water, and leaves any water vapor in the combustion products as a vapor [26]. The HHV can be estimated from the FA profile of the oil/fuel with an inaccuracy of ~3 % when compared to other methods [25]. Another method of HHV determination uses the elemental composition of the oil for carbon, hydrogen, nitrogen, oxygen, and sulfur of the oil or fuel [25]. Since the FFA of the algal feedstock was assessed, this profile will be used to estimate HHV. An oil layer obtained from a reactor run using S. limacinum, operated at 250⁰C for 30 minutes was chosen for use in this calculation. The FFA profile of this oil layer can be seen below in Table 2.3. Table 2.4: Fatty acid components of oil layer produced from a S. limacinum hydrothermal reactor run with determined mass fractions used in calculation of the overall high heating value based on the weighted fraction. Six FA standards were used in estimation of the alkyl chain length and concentration of FAs in S. limacinum. These six standards are indicated in Table 2.3 above. For peaks which did not correspond to the retention times of the standards, concentration was estimated by using an average of the FA standard curves of peak retention times larger and smaller than the selected peak. This averaging method was 21

33 also applied to the non-standard peaks for HHV calculations. Seen below are the equations needed to calculate the HHV of an oil sample based on the FA profile. In Equation 2-7 the subscripts x, y and z denote the different elemental composition of each FA. The uppercase X, Y, and Z in the formula denote the mass fraction of carbon, hydrogen and oxygen in the fatty acid [25, 27]. (2-8) (2-9) (2-10) The HHV determined for this S. limacinum FA profile is 39 MJ/kg oil produced (Table 2.3), which is very similar to other determinations of oil sample HHV [27]. With this HHV, the fuel energy from product oil was estimated to complete the energy balance, Energy Produced. Assuming the centrifuged volume of 1 m 3 composed of 10 wt % algae slurry, with an algal lipid content of 43 % on an algal dry weight basis (Chapter 3) the resulting theoretical lipid weight is 43 kg. Based on the HHV, this lipid oil product can provide an energy output of 1680 MJ per 1 m 3 of 10 % slurry or 33 m 3 of culture processed. The temperatures show a net energy gain in the range of 500 MJ/m 3. With a positive energy balance at this point, the hydrothermal treatment merits further experimentation and process development. The higher temperature will be investigated to determine trends and behavior throughout the hydrothermal treatment. A comparison of this energy balance can made to other options of algae processing requiring evaporation of water such as transesterification of dried algal lipids 22

34 or pyrolysis. Only energy input for drying is calculated; input to other equipment energy is neglected. Using a heat capacity of kj/kg C and a temperature increase of 75 C (25 C to 100 C) for the 1 m 3 algal slurry exiting from the centrifuge, an energy consumption of 280 MJ is needed for latent heating. Evaporation of the water is the energy intensive portion. For the 10 % algal slurry of 1 m 3 (~1000 kg), 900 kg of water must be evaporated. Using the latent heat of vaporization of water of 2.26 MJ/kg, equates to a ~2000 MJ energy requirement. This brings the total energy consumption of using an evaporation water removal process to ~2300 MJ/m 3 processed. This energy requirement along with the theoretical fuel energy produced by the lipid fraction of ~1680 MJ/m 3 would create a net loss. This demonstrates the advantage of heat integration utilized in the proposed process. As seen in Table 2.2, an Adjusted HHV is calculated for each of the operating temperatures. As briefly mentioned before, the Energy Produced value assumes all lipid and oil components are recovered and can contribute to HHV and energy content of the product. Attempts to close a mass balance on lipid components have shown losses between 20 to 60%. A loss of 60% is accounted for in the Adjusted HHV column. Solvent extraction was used in lab-scale experiments to recover the oil phase from reactor contents. This processing step can be incorporated into the energy balance through determination of the energy requirement needed to evaporate and recover the solvent. Diethyl ether (DEE) was used in experimentation and has a heat of vaporization value of 27 MJ/kg. Assuming the energy excess of 500 MJ/m 3 of processed slurry, it would take evaporation of roughly 1350 kg DEE/m 3 to negate the positive energy of the process. Lab-scale experiments used 0.5 ml DEE/ ml slurry processed, which scales to 23

35 350 kg/m 3 slurry processed. The energy required to evaporate this sufficient amount of DEE accounts for 130 MJ/m 3 slurry processed, leaving 370 MJ/m 3 slurry processed as the energy gained. These calculations of HHV do not account for the portion of the oil which is not lipid based that would contribute to other approaches of calculation such as carbon, hydrogen, or oxygen content. Ideally biofuel oils have high carbon and hydrogen weight percentages along with low nitrogen and oxygen percentage. One equation can also be used to calculate HHV based on carbon and hydrogen (Equation 2-10) [25]. Using CHN analysis data for the oil used in the previous calculations along with the formula given below, a lower HHV was estimated. The HV (CxHyOz) method assumes a composition based on the algal FA profile. The HV (CxHy) method uses CHN data for carbon and hydrogen weight percentages of the S. limacinum feedstock. (2-11) Table 2.5: Comparison of oil high heating values based on two methods, which use different elemental information in calculations. Depending on the HHV chosen, the energy balance performed on this process will increase or decrease slightly. Another consideration would be the use of pyrolysis and oil production using the entire feedstock. When the CHN data of the S. limacinum feedstock was used to 24

36 calculate the HHV using Equation (2-10), the result was 34 MJ/kg. This could seem beneficial as the entire feedstock would be turned into bio oil, but the excessive temperature and duration used could negate the benefits of additional oil. Another point of interest would be the contents of the resulting water phase and its suitability as a recycle stream to algal cultures without additional purifying. 2.5 Emissions Green engineering implies minimizing pollution and energy consumption from production processes. An estimate can be determined for the amount of carbon dioxide, a greenhouse gas, released from the proposed processing scheme based on the calculated energy consumption. This tool is provided by the EPA [28]. In Table 2.5 below, electricity was assumed for all energy consumption calculated using the SRMW Midwest subregion. Table 2.6: Carbon dioxide pollution estimates based on calculated energy requirements of hydrothermal treatment process. One benefit of using microalgae as a biofuel feedstock is the ability to perform carbon fixation or photosynthesis by using a phototrophic algae strain such as Chlorella vulgaris, which has received much attention in the research community. A study was 25

37 found that claims an algae culture such as C. vulgaris can fix up to kgco 2 /m 3 *h based on culture volume [29]. By using lab scale harvesting data, which results in ~30 ml of 10 wt % slurry from 1 L of culture, we can assume that it takes ~33 m 3 harvested to obtain the 1 m 3 taken through our process. As calculated previously 35 kg CO 2 is released in this process. If CO 2 uptake is at a rate of kgco 2 /m 3 *h, with a culture of 33 m 3, it would only take ~40 h to fix the carbon that has been produced from the process scenario. This is a calculation performed using data from research performed on two separate cultures of algae (S. limacinum and C. vulgaris). The values calculated from the energy balance are based on the lipid content of S. Limacinum. Lipid content of C. vulgaris is similar to when cultured in pursuit of high lipid content [30]. The FA profile may be different between these species, but many oil high heating values have been calculated and are within a small percentage of each other [27]. Culturing time of C. vulgaris is much longer than 27 hours to reach desirable lipid content [31]. These calculations are also based only on the portion of the process presented, but on an industrial scale and actual life cycle analysis would take many energy usages into account and the carbon footprint of this scheme may shift. 26

38 Chapter 3 Algal Growth and Characterization Methods 3.1 Introduction Materials and methods for growing and characterizing the marine microorganism, S. limacinum, are outlined in this chapter. Proximate analysis and assessment of major biopolymer content of this feedstock including proteins, lipids, and carbohydrates. From these analyses a pseudo algal mixture was formulated to preserve limited algal stock used in hydrothermal treatment experiments, as well as providing an easily manipulated material to simulate varying algal compositions, discussed in chapters 4 and Background The marine fungus S. limacinum (American Type Culture Collection (ATTC) MYA 1381) was cultured to provide a lipid-rich feedstock for microalgae hydrothermal treatment experiments. High lipid content and high biomass producing microorganisms are good candidates for biofuel production [21]. Another beneficial factor is the ability of microorganisms to grow heterotrophically on carbon sources such as glycerol, sugars, 27

39 and seed oils [21, 22]. Glycerol is especially beneficial as a feedstock since the market could be saturated with this by-product from biodiesel production [32]. Glycerol, from lipid hydrolysis, is also a component of the aqueous layer that will be recycled to growing cultures. Recent research focuses on S. limacinum for its high lipid content and profile of lipids produced, more specifically its docosahexanoic acid (DHA C22:6) and palmitic acid (C16:0) production [22, 33]. Knowledge of the importance of η-3 fatty acids in the human diet in reducing risk of heart disease, hypertension, type 2 diabetes, rheumatoid arthritis, ulcerative colitis, Crohn s disease and obstructive pulmonary disease has increased attention to culturing of microorganisms producing these specific compounds [22, 32, 34]. 3.3 Algal Culturing Material and Methods Media components for growth of S. limacinum includes sea salt (Instant Ocean, Product # SS15-10), peptone from casein (Sigma Aldrich, Cat. No KG-F), yeast extract (Fisher Scientific, Cat. No. BP ), glycerol (Fisher Scientific, Cat. No. G33500), chloramphenicol (Sigma Aldrich, Cat. No. C G), Chloramphenicaol (Fisher Scientific, Cat. No. BP ), and deionized water (U.S. Filter PURELAB Plus High Purity Water Polishing System). The media component concentrations (excluding chloramphenicol) and a starting culture were provided by Dr. Sridhar Viamajala at the University of Toledo [33]. An aseptic approach was taken when sampling and inoculating new cultures. Workspace and supplies used in the laminar flow hood were cleaned with a 70% solution 28

40 of ethanol and DI water (Decon Labs Inc., Cat. No. 8616). All supplies and glassware were sprayed with the alcohol solution before placing in the laminar flow hood. Culture flasks were held in the flame of a torch for roughly seconds prior to sampling or inoculation. To minimize contamination of the culture, media was autoclaved prior to inoculation (Market Forge Industries Inc. Sterilmatic, Model # ). Growth trials utilizing recycled aqueous layers were performed in 50 ml culture media flasks (Fisher Scientific, Cat. No A). Optical density at 600 nm of the cultures was measured using a spectrophotometer (Shimadzu UV-2401PS, Cat. No ) to monitor changes in biomass density. Serological pipettes were used in transferring and sampling of cultures (Fisher Scientific, Cat. No ). Culture was drawn from smaller volumes of growing culture and expelled into fresh media at an inoculation ratio of ~1:10. One liter of culture was grown in autocalved 2 L baffled flasks (Fisher Scientific, Cat. No E). These flasks were agitated at a controlled temperature using a shaker table (New Brunswick Scientific Class Series C24 Incubator Shaker) at 115 rpm. Cultures were harvested via centrifugation (Thermo Scientific Sorvall RC6+ Centrifuge, Cat. No ). The resulting algal pellet paste was frozen and lyophilized to preserve the biomass (Labconco FreeZone 2.5 Liter Benchtop Freeze Dry System, Model # ). Dried biomass was ground using a mortar and pestle (Fisher Scientific, Coorstek, Cat. No C) and stored as a powder. Cultures of S. limacinum were obtained from Dr. Sridhar Viamajala s research group (University of Toledo, Department of Chemical Engineering) contained in media 29

41 and in a healthy growing state. The media consisted of 10 g/l sea salt, 1 g/l peptone, 1 g/l of yeast extract, 6 g/l of glycerol, and 2.5 mg/l chloramphenicol [33]. Chloramphenicol was not a component in the standard growth media, but was integrated as a means to minimize culture contamination. Normal growth volume consisted of six 2 L culture flasks with half volume of media for a total volume of six liters. Growth of the culture was monitored spectroscopically by optical density measurement (absorbance at 600 nm), OD 600. Growth duration was in the range of five to seven days before harvesting. Cultures were centrifuged at 7500 rpm for 15 minutes, followed by a deionized (DI) water wash to remove residual salts and media components. The volume is centrifuged again and the algal paste placed into a 50 ml centrifuge tubes prior to freezing and lyophilization. The pseudo algae consisted of bovine serum albumin (BSA) protein (Fisher Scientific, Cat. No. AK ), corn starch (Sigma Aldrich, Cat. No. S4126-2KG) and soybean oil (Sigma Aldrich, Cat. No. S7381-1L). 3.4 Algal Compositional Analyses The following procedures were used to determine the proximate biochemical composition of the microalgae. The compositional measurement includes ash fraction, moisture content and the biopolymers of interest including protein, carbohydrates and lipids Protein Analysis 30

42 Protein content of the algae was important in understanding the behavior of the microalgae in the reactor system, potential byproducts of hydrothermal treatment of the algae, as well as ensuring correct mixture of the pseudo algae that is used in this research. The protein fraction was a major component of algae and plays a major role in product formation. Protein content of the algal samples was determined through elemental combustion analysis of nitrogen (Perkin Elmer 2400 Series II CHN Elemental Analyzer). This method analyzes combustion products including carbon, hydrogen, and nitrogen to yield weight percent carbon, hydrogen and nitrogen (CHN). A protein factor of 4.44 was used to relate the elemental percentage of nitrogen to overall protein fraction of the sample [35]. The protein weight fraction was calculated from the nitrogen weight fraction. (3-1) Three to five mg of dried algal samples were weighed in triplicate into tin capsules (Costech Analytical Technologies Inc., Tin capsules 5x9 mm, Part# , Perkin Elmer Corp., Aluminum capsules 2.5 x 7 mm 30 µl, part# ). The samples were analyzed along with a standard, acetanilide (Sigma Aldrich, Cat. No ). Elemental composition of the acetanilide standard is well known and is used to monitor the operation and precision of the instrument throughout the run sequence. Tin capsules containing the samples and standards were folded into balls to ensure no loss of material. Samples were dropped into the combustion chamber one at a time in an excess of oxygen. The result was formation of carbon dioxide, water, and nitric oxide. These products were then sent through a chromatography column with helium as the 31

43 carrier gas. Detection of this stream was accomplished by a thermal conductivity detector Carbohydrate Analysis Carbohydrates in algae and other marine and fresh water microorganisms were present as starch and cellulose with a glucose repeating unit. This monomer unit can be fermented for bioethanol production similar to sugarcane or corn sugars. Quantification of glucose content could be determined by the following National Renewable Energy Laboratory (NREL) analytical procedure Structural Carbohydrate and Lignin Analysis [36]. In brief, the protocol included a two-step concentrated and dilute acid hydrolysis to produce glucose monomers. The acid neutralized samples were then prepared for high performance liquid chromatography (HPLC). Chemicals used in the acid hydrolysis of the sample include 72% sulfuric acid (RICCA, Cat. No. R D) and calcium carbonate (Fisher Scientific, Cat. No. C64-500). This method detected the glucose from both cellulose and starch and can be viewed as a total glucose analysis. Lignin is another polymer that was detectable and quantifiable through the NREL procedure. With respect to algae, only marine red algae have been found to contain lignin [37]. This portion of the procedure was omitted for S. limacinum samples. HPLC Method: The HPLC was composed of the following components; Shimadzu DGU-20A 5 Prominence Degasser, Shimadzu LC-20AD Prominence Liquid Chromatograph, Shimadzu SIL-20AC HC Prominence Auto Sampler, Shimadzu RID-10A Refractive Index Detector, Shimadzu CTO-10AC VP Column Oven, and Shimadzu SCL- 32

44 10A VP System Controller. An Aminex HPX-87P column at 80 C with a mobile phase of deionized water at 0.6 ml/min flowrate was used with refractive index detection. Standards used in quantifying and identifying (by retention time) sugar content include; alpha-d(+)-glucose (Acros Organics, Cat. No. AC ), D(+)-mannose (Acros Organics, Cat. No. AC ), L(+)-arabinose (Acros Organics, Cat. No. AC ), D(+)-cellobiose (Acros Organics, Cat. No. AC ), D-(+)- xylose (Sigma Aldrich, Cat. No. X G) and D-(+)-galactose (Sigma Aldrich, Cat. No. G G). A positive control of known composition (poplar, provided by NREL) was analyzed in parallel with samples Lipid Analysis Fatty acid methyl ester (FAME) analysis was used to determine the algal lipid content and to determine information on the carbon chain length and fraction of each fatty acid in the algal lipids. The overall FAME content of the algae is important in estimation of free fatty acid or biodiesel quality obtainable from algal material. In previous research, a comparison of FAME analysis protocols was conducted [17]. The procedure outlined below, had short preparation time, good accuracy, and small sample size (20 to 100 mg). In this method of FAME analysis [38], lipids are extracted and transesterified in a single step producing fatty acid methyl esters. Samples must be dried or have minimal water content prior to analysis. To assist in lipid release, an ultrasonic Sonic Dismembrator was used (Model 1000, Fisher Scientific). Samples were heated using an aluminum block Dual Thermo 33

45 Bath (AB128, FINEPCR). Post reaction, samples were mechanically separated using an Eppendorf Centrifuge (5810R, Eppendorf) for 10 minutes at 4000 rpm and 25⁰C. The FAME content of each sample was determined using Gas Chromatography (Shimadzu GC-17A) with flame ionization detection (FID), autosampler (AOC-20s), and auto injection (AOC-20i). Computer software (Class VP 7.4) was used to assist in peak area integration of chromatograms. A capillary column was used in the separation of FAMES (FAMEWAX Crossbond Polyethylene Glycol, Restek Cat. No , 30m, 0.25 mm, 0.25 µm df). Chemical reagents used included chloroform (Fisher Scientific, Cat. No. C606SK-4), methanol (Fisher Scientific, Cat. No. A412SK-4) and 96 % sulfuric acid (Acros Organics, Cat. No )Mixtures were reacted and dried in 10 ml Nalgene Teflon line screw top centrifuge tubes (Fisher Scientific, Cat. No C). Separation of phases and centrifugation of samples used 15 ml polypropylene sterile centrifuge tubes (Fisher Scientific, Cat. No ). Prior to GC injection, samples were filtered using 13 mm nylon syringe filters, 0.2 µm (Fisher Brand, Cat. No ). The final GC samples were placed in 2 ml amber screw-thread vials (Restek, Cat. No ), capped with 8 mm screw-thread polypropylene open hole caps (Restek, Cat. No ) and polytetrafluoroethylene/silicone septa (Restek, Cat. No ). Standards used in determination of retention times of chromatogram peaks and development of standard concentration / peak area curves were purchased from Nu-Chek Prep, Inc. The following were chosen to cover the anticipated range of alkyl chain lengths in FAMEs from our algal samples: methyl myristate (C14:0), methyl palmitate (C16:0), methyl stearate (C18:0), methyl oleate (C18:1), methyl linoleate (C18:2), methyl 34

46 linolenate (C18:3), methyl arachidate (C20:0), methyl eicosapentaeoate (C20:5), and methl docosadexaenoate (C22:6). This analysis could be performed on algae as a characterization technique in determining the lipid content or to characterize the portion of oil from hydrolysis reactor runs that can be converted to FAMEs. Dried algae or oil phase samples (~20 mg), were weighed in triplicate in preweighed teflon tubes. Reaction solvents were then added (2.0 ml chloroform, 1.7 ml methanol) and vortexed for one minute. Samples were then sonicated for roughly 30 seconds to further homogenize the reaction slurry. The acid catalyst was then added, 0.3 ml 96 % sulfuric acid, to bring the total mixture volume to four ml. Sample tubes were tightly capped and weighed. Sample tubes were then placed in the aluminum block heater for 90 minutes at 90⁰C. Next 1 ml of DI water was introduced to each sample tube. Samples were then vortexed for 1 minute, transferred to 15 ml centrifuge tubes and placed in a centrifuge operated for 10 minutes at 4000 rpm and 25⁰C. The two liquid phases are a top aqueous layer (with glycerol), and a bottom organic layer containing the FAMEs. The bottom layer was then removed and placed in clean teflon tubes. The water layer was extracted a second time with addition of chloroform, then vortexed, and separated to ensure recovery of FAMEs. Caps containing gas lines and vent holes were then screwed onto the teflon tubes. A light stream of nitrogen was put through the gas line to dry the samples. Once a solid film was formed, samples could be prepared for GC analysis. A third weight measurement was used to estimate the amount of solid in the teflon tube by subtracting empty tube weight taken earlier. The teflon tube with remaining solids was capped and placed on the scale, the scale was tared, 1 ml of hexane 35

47 was added to the tube, capped, and the weight was recorded. This mixture was vortexed for 1-2 minutes depending on the amount of solids and difficulty of dissolving the FAMEs. Samples were filtered with a syringe filter. A range of concentrations of FAME standards, creating a calibration curve of mass fraction versus gas chromatograph peak area. The typical standard mass fractions ranged from 1x10-2 to 1x10-4 in hexane. A stock concentrated standard was prepared for each individual standard, ~100 mg/ml in hexane prepared in a 2 ml GC vial. The concentrated standards were individually weighed into a mixture with hexane and serially diluted. Gas chromatography was used in the determination of FAME retention time and peak area with concentration calculated from standard curves. The identity and retention time of compounds were verified through GC-MS. Specifications for the GC-FID and capillary column used in this research can be found above. The injected sample was detected by the flame ionization detector (FID). The detection appeared as peak intensity per unit time. Ultra high purity helium was used as the carrier gas. The column temperature program began at 195 C and then ramped at a rate of 5 C/min up to 240 C where it is held for 10 minutes. Both detector and injector temperatures were constant at 250 C. Total flow was maintained at 93 ml/min with a split injection of 15:1 and liner velocity of 77 cm/sec. Below is an example with a standard chromatogram overlaid by a S. limacinum oil sample chromatogram. It can be seen that many peaks line up along with the nine FAME standards, while other smaller peaks fall between the standards indicating different chain length or cis and trans variations in the double bonds. 36

48 Figure 3-1: Overlaid chromatogram of an S. limacinum oil (red) based FAME sample on a chromatogram of external standards (blue). The peak areas of the external standards were used to create a calibration curve from which the FAME concentration of experimental samples could be calculated. The retention time for the FAME standards were consistent over all runs and was used estimate alkyl chain length in samples. Nine graphs, one for each standard, were made, displaying the mass fraction and resulting peak area. Linear regression using Excel produced an R 2 value and a best fit linear equation for determining mass fraction of FAME in samples. 37

49 Figure 3-2: FAME standard C20:0 (methyl arachidate) calibration curve displaying the mass fraction of this specific standard in each of the serially diluted standards based off of weight recordings and mass fraction calculations. Concentration of sample peaks which fell in between the retention times of two of the nine standards were estimated by averaging the mass fraction using the standard equation before and after the peak retention time. The FAME content of either algae or oil is presented as a percent FAME determined by dividing the total mass of FAME by the total weight of sample used for the FAME analysis. Samples were usually analyzed in triplicate and therefore an average FAME percent was used the value for oil or algae. FAME content of samples were presented either as weight percent of dry mass or oil Ash Analysis Ash is a term used for the components left after a sample has been burned, and usually consists of metal oxides, minerals, and other inorganic compounds. An NREL 38

50 protocol was used for ash analysis [39]. A single analysis was used to determine the ash content of the microalgae S. limacinum. In brief, porous bottom crucibles (Coorstek Inc., Item # 60531) were cleaned and placed in a muffle furnace (Thermolyne Type 1500 Furnace, Model # F-D1525M) at 575 C for 4 hours to ensure removal of any residual material from previous analyses. The crucibles were then allowed to cool in the presence of desiccant. Weight of the crucibles and samples put into the crucibles was recorded. Crucibles were then placed back into the muffle furnace at 575 C for 24 hours. Once the samples are removed and cooled over desiccant, weight of remaining sample and crucible was recorded and a percent ash could be calculated as seen below. (3-2) (3-3) Moisture Analysis Algal culture harvests were centrifuged in 50 ml tubes in a swinging bucket centrifuge at 4000 rpm (5810R, Eppendorf) to form concentrated algal slurry. Water content of the concentrated slurry was determined gravimetrically. The concentrated slurry was placed into pre-weighed 50 ml centrifuge tubes, then weighed (, frozen, lyophilized, and then weighed ( again to determine the water content (. Based on the determined water concentration in the harvested slurry, the weight of algae in the harvest could also be determined ( ). 39

51 By additional calculation, the water and algae weight percentage of the harvest can also be determined. (3-4) (3-5) (3-6) (3-7) (3-8) 3.5 Algal Characterization Results The composition of lab cultured microalgae S. limacinum was determined through protein, FAME, carbohydrate, and ash analyses described above. 40

52 Figure 3-3: Compositional results of lab cultured S. limacinum used in this research including lipid, protein, carbohydrate, ash and a small fraction was undetermined. With the composition of the cultured algae known, the formulation of pseudo algae was possible. Use of pseudo algae was important in preserving the limited stock of cultures algae as well as the flexibility to mimic similar feedstocks with different compositions. A goal of using a pseudo feedstock was that the mixture behaviorally agrees with the algal feedstock experiments and trends. The pseudo algal system also allows variation of component fractions and testing of in the reactor system and analysis methods. The three main biopolymers of S. limacnium, including protein, lipid, and carbohydrate, were considered when choosing components to compose the pseudo algae. The pseudo system incorporated corn starch, BSA protein, and soybean oil to reflect the major biopolymer portions determined through compositional analyses. 41

53 Chapter 4 Hydrothermal Processing Materials and Methods 4.1 Introduction This chapter describes the lab-scale experimental batch reactor setup for hydrothermal processing along with the analyses used to characterize the resulting product streams. Two feedstocks were used in the processing experiments including S. limacinum and a pseudo algae formulated to mimic biopolymer content of S. limacinum. Preparation of these feedstocks for hydrothermal treatment is discussed. This chapter also walks through the operation of the batch reactor setup. Product stream characterization procedures along with the goal of the analyses are described including oil phase separation, FA and FAME analyses, oil nitrogen content, and aqueous phase analyses. 4.2 Background With the high percentage of water in algal cultures, mechanical concentration of the algae must first take place to minimize the amount of material processed. Drying of the feedstock is a very energy intensive step and can economically negate net energy 42

54 gains of the fuel produced. In subcritical hydrothermal treatment of lipid rich feedstocks, subcritical water can be used as the solvent and catalyst when protonated or deprotonated [40]. Hydrothermal treatment of lipid rich algal feedstocks can result in the creation of two liquid phases, oil and aqueous. This provides an opportunity to recycle water, glycerol, protein, and carbon components in the aqueous phase to growing cultures. The oil phase can provide a lipid rich precursor to biodiesel produced through hydrolysis of lipids to produce FA and G. The biofuel precursor can be sent on for further processing. Benefits of multi-step processing is the ability to monitor and control unwanted side reactions to ensure a high quality nutrient-rich aqueous recycle to the cultures as well as a high quality oil fraction continuing on for biofuel processing. Complete conversion to FA of the oil layer is not necessarily the goal of the initial processing of the feedstock, but rather a result of the processing that can be monitored and used in characterization of the resulting oil phase. With efficient separation after this initial protein and carbon component extraction, water content in the oil phase can be minimized. 4.3 Reactor Setup and Operation Hydrothermal treatment was performed using a Parr Instruments 4560 Series mini reactor, a batch reaction system picture in Figure 4-1. Volume of the reactor used for this research was 100 ml (Parr Instrument Co., Cat. No. 452HC8), with a glass liner (Parr Instrument Co., Cat. No. 762HC7). The reactor was heated with a fitted heating jacket (Parr Instrument Co., Cat. No. A2235HCEB). Slurry mixtures were injected using a 150 ml pressure burette connected to the reactor assembly (Parr instrument Co., Cat. 43

55 No. A2113HC4). Temperature and agitation rate of the reactor setup are maintained via external controller (Parr Instrument Co., Cat. No. 232M). Temperature data throughout the reactor runs can be logged through the CALgraphix computer software (Parr Instrument Co., Cat. No. 450M). Agitation, temperature sensor, and sample injection all occur through the removable reactor head (Parr Instrument Co., Cat. No. 818HC). Figure 4-1: Parr Instruments batch reactor setup used in hydrothermal processing experiments of algal slurries. For both pseudo and algal reactor runs 15 g of DI water was weighed and placed inside the reactor and brought to operating temperature. When the S. limacinum stock was used, ~3 g of the lyophilized algae powder was combined with 15 g of DI water in the pressure bomb prior to reactor injection. The resulting slurry was 9-10 % (w/v) when combined with the preheated water in the reactor. Pseudo slurry components were combined to mimic the algal composition. A mixture of 1.4 g soybean oil, ~1.3 g protein (BSA), and ~0.15 g corn starch, and ~15 g DI water was added to the burette. Final composition of this pseudo slurry in the reactor was equivalent to the 9 % (w/v) S. 44

56 limacinum slurry. Most runs utilized a pseudo algae system to simulate the composition determined for the S. limacinum stock (43 % lipid, 39 % protein, and 5 % carbohydrate). When transferring to the burette there was some loss in material, which was extracted and separated using roughly 5 ml of diethyl ether (DEE). Monitoring of these losses aided in closing of a lipid mass balance. Contents loaded into the burette were injected into the reactor system by pressurizing the cylinder using nitrogen gas to ~100 psi above reactor pressure which was temperature dependent (Table 2.1). Just before the burette contents were injected into the reactor, temperature logging using the Calgraphix software was started. This was meant to capture the large deviation and temperature fluctuation seen when burette contents were injected. Post injection, the burette was separated from the reactor, and any leftover contents were collected and weighed to aid in the lipid mass balance determination. The contents were mixed in the reactor at 300 rpm for the designated duration of the experiment (5, 30, or 60 minutes). Once reaction time had expired, the heating element was removed from the reactor and switched off and cooling of the reactor began. Due to the small volume of this reactor setup, a cooling loop could not fit inside of the reactor. Cooling was accomplished by spraying water on the exterior of the reactor and catching the runoff in a 2 L container. Cooling times were similar to that seen with the larger volume reactor and cooling loop setup (~15 minutes). When room temperature was reached, the excess pressure in the reactor, from burette injection, was released. The reactor contents were placed in a 50 ml centrifuge. This contained the solids, oil, and aqueous phases. This portion of the products was labeled recovered. To obtain the remaining oil stuck to the walls of the reactor, agitator, and other components of the 45

57 reactor, 30 ml DEE was introduced to the reactor. The reactor was then reassembled with the agitation turned on and allowed to operate for ~5 minutes. This second extraction was then collected and labeled retained. The recovered portion was subject to three repetitions of voretexing, centrifugation, and extraction using 5 ml DEE solvent. Extractions were placed in a separate preweighed centrifuge tube and the solvent was evaporated. The retained portion of the oil was placed in a preweighed 50 ml centrifuge tube and the solvent evaporated. To remove small amounts of DEE in the aqueous layer, DEE was evaporated for a much smaller time period than the oil samples to prevent water evaporation which would increase concentration of its contents. All oil samples were refrigerated and aqueous layer samples were placed in a freezer until analyzed. Below are the analyses used in characterizing the aqueous and oil layers obtained from hydrothermal treatment experiments. 4.4 Oil Nitrogen Content Nitrogen content in the oil is an important benchmark when determining quality of oil products because of the additional effort and extended processing that will be needed to recover or remove excess nitrogen in biofuel precursors. Nitrogen content of the oil is indicative of protein breakdown and transfer from the aqueous to oil phase [41]. Oil for biofuel processing, with high nitrogen content, will produce a final product fuel which releases excessive NO x emissions once combusted. By processing the biofuel precursor efficiently, nitrogen content can be minimized which reduces the need for additional refining of the oil, as well as indirectly reduces NO x emissions. 46

58 The oil nitrogen content was determined through CHN analysis described in section Two to five mg of hydrothermally treated oil was weighed into the tin capsules. Results of the CHN gave weight percentages of the three elements. Results are discussed in chapter FAME Analysis Performing the FAME analysis on the reactor oil phase was used to determine the amount of the oil layer produced from the initial lipid fraction. Other biopolymer components such as protein and carbohydrates can contribute to the oil phase, which has been described in previous research [42]. Knowing the portion of oil that was not lipid derived gave an indication of the oil quality and percentage of unwanted contaminants. For example, oil produced with high fractions from protein would contain a higher percentage of nitrogen, which is undesirable for potential side reactions or NO x emissions with further biofuel processing. FAME analysis has been previously described in the feedstock characterization chapter (Section 3.4.3) and was used in the same fashion for oil layer analysis. The results of these analyses are summarized in chapter Free Fatty Acid Analysis Determination of FA is a means of determining the progression of triglyceride hydrolysis through feedstock pretreatment. Analysis of fatty acids in oil samples was completed using a gas chromatography unit (GC-17A) equipped with an auto injection unit (AIC-20i), an auto sampler (AOC- 20s), as well as a flame ionization detector (FID). Class VP software 7.4 was used in 47

59 integration of fatty acid peaks and area determination. A capillary column was used in separation of the fatty acids purchased from Restek (Stabilwax-DA Crossbond Carbowax Polyethylene Glycol, Restek Cat. No , 30 m, 0.53 mm ID, 0.25 µm df). GC samples were prepared in 2 ml amber screw-thread vials (Restek, Cat. No ), capped with 8 mm screw-thread polypropylene open-hole caps (Restek, Cat. No ) which are filled with polytetrafluoroethylene/silicone septa (Restek, Cat. No ). External standards were used in GC analysis to both determine qualitatively and quantitatively the fatty acids, FA, present in the oil. Qualitative analysis is done through retention time comparison between the standard and unknown sample peaks. Quantitative determination of fatty acids is performed by using a calibration curve relating the standard s peak area and known mass fraction. The standards used in FA analysis were purchased from Nu-Check Prep, Inc. The range of standards used in this study includes 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). These standards were chosen based on the known profile of soybean oil used in previous reactor hydrolysis studies. The external standards were used to create a mixture of standards, diluted to cover a range of concentrations expected from the preparation of oil samples. A stock concentrate was made for each standard where 100 mg of the pure standard was combined with 1 ml of chloroform to create a 100 mg/ml solution. The weight of both the pure standard as well as the chloroform was determined to assist in mass fraction calculations of standard mixes prepared for later GC analysis. In preparing the series of standards, 100 µl of each standard was placed into a 2 ml GC vial. Again, the weight of 48

60 each standard was determined and recorded. Caps of the GC vials were replaced in between transfer of standards and weighing to reduce the evaporation of chloroform from the concentrate or current standard sample vial. Following the addition of the standard volumes, a volume of chloroform was added and resulting weight recorded. Once the chloroform portion of the first standard solution was added, an aliquot of this first standard could then be transferred to the next standard GC vial and weight recorded, usually 500 µl. Then an equal amount of chloroform could be added while recording the weight. This procedure of serial diluting the initial sample was carried on until the lower limit concentration or mass fraction of the coverage of standards was reached. Common mass fractions of the five count series of standards used in this research ranged from 5 x10-3 to 2 x A portion of the oil fraction, recovered or retained, was placed into a 2 ml GC vial, usually 35 µl. The weight of the oil fraction is recorded. Then 1 ml of chloroform is added to the sample and weighed so that a mass fraction can be calculated. Gas chromatography was used in the determination of FA concentration. Specifications for the GC-FID and capillary column were discussed above. The prepared samples were placed into the auto sampler tray, which were transferred to the sample rack via robotic arm, and then injected into the GC column using the auto injector. This injected sample was subject to pyrolysis once entering the column, which forms oxidized carbon ions which are detected by the flame ionization detector (FID). The detection is portrayed as peak intensity per unit time based on the measurement of the ions. Ultra high purity helium was used in this setup as the carrier gas. A method to control GC operation was developed through the Class VP 7.4 software. The column temperature 49

61 program began at 40 C and then ramped at a rate of 6 C/min up to 160 C followed by a second ramp of 15 C/min up to 250 C where it was held for 25 minutes. Both detector and injector temperatures are constant at 250 C. Total flow is maintained at 93 ml/min at a split injection of 15:1 and liner velocity of 77 cm/sec. As mentioned previously, the series of determined standard peak areas and their range of mass fractions were used to develop seven calibration curve equations. Once the chromatograms were integrated for the samples, the determined peak areas could be placed in these equations to obtain FA mass fraction in the samples using determined peak areas. These individual mass fractions were then summed over all peak calculations. Peaks which lie between peaks of the standard mixture chromatogram were accounted for by obtaining an average mass fraction by using the equation of the standard before and after peak retention time. Figure 4-2: Chromatogram of a FA standards overlaid on a S. limacinum hydrothermal treatment oil sample chromatogram. 50

62 4.7 Amino Acid Analysis Determination of amino acids (AA) in the reactor aqueous layer provided a measure of the amount of protein in the aqueous phase from either the algae or BSA protein in the slurries. Much of the protein in the aqueous phase is somewhat degraded, but remains in the form of peptides with little to no AA released. Protein samples in the aqueous layer were hydrolyzed in order to release AA detectable by the Phenomenx EZ:faast kit and GC column. Protein hydrolysis used 6N HCl at 100 C for a duration of 24 h [43]. The separation of AA from the hydrolyzed aqueous layer was accomplished through the use of an analysis kit from Phenomenx (Phenomenx EZ:faast GC-FID Protein Hydrolysate Kit, Amino Acid Analysis Kit, Part No. KG0-7176). The aqueous layer from the reactor was analyzed with and without the protein hydrolysis step. The result without protein hydrolysis was a chromatogram that was essentially flat lined suggesting negligible AA present. Acid hydrolysis of the aqueous layer was required for detection of protein, peptides and their AA products. In the acid hydrolysis, a volume of 0.5 ml of the reactor aqueous phase was added to the amber ampoule. The weight of this addition was recorded for later concentration and mass fraction calculations. Next, 0.5 ml of 12N HCl was added to the ampoule while recording the weight of this addition. Finally the ampoule was closed by holding the tip over a flame and twisting the end of the ampoule until an air tight seal was achieved. The ampoules were then placed in the aluminum block heater for 24 hours at 100 C. Once the reaction time had elapsed, the ampoules were broken, the mixture removed, and placed into GC vials for preservation until the Phenomenex procedure was 51

63 started. This Phenomenex kit took the samples through a series of separations and reactions using the included supplies. These included reagents that derivitized both the amino and carboxyl groups. In the final step an organic layer with the derivatized AA was obtained and analyzed through the GC-FID. For an external standard, BSA protein was used due to the well know AA profile and its use in the pseudo algae slurry (Fisher Scientific, Cat. No. AK ). This protein mixture was mixed to produce a ~80 mg BSA/mL protein stock in DI water. This concentrated standard was then serially diluted by taking a volume of 2 ml and adding 2 ml of DI water. This process was continued until 5 standard mixtures were obtained. The BSA standards were also put through the 6N HCl hydrolysis alongside the reactor aqueous layer samples. Once the standards were put through the Phenomenex procedure, they were used as a series of standards similar to other GC standard calibration curve development discussed in FA or FAME sections. The concentration of BSA protein stock was determined by measuring the absorbance at 280 nm using a UV-Vis spectrophotometer [44]. The extinction coefficient used in the calculations is 6.6. The adjustment factor is 10 [44]. (4-1) Standards were diluted usually 1:100 to reach the range between 0 and 1 absorbance. These dilutions were monitored for weight of sample and dilution DI water added to correctly account for the dilutions. Since the amino acid profile of BSA protein is well known, and the concentration has been determined through UV-Vis absorbance 52

64 data, the peaks integrated from the sample FID chromatogram could be correlated to concentration and amino acid weight percent data as seen below. Table 4.1: BSA protein amino acid formulas, molecular weights, and weight percentage in BSA used in chromatogram integration and mass fraction determination of unknown sample analysis. 53

65 Figure 4-3: Comparison of a BSA standard chromatogram and hydrothermally treated and acid-hydrolyzed aqueous layer chromatogram. 54

66 Table 4.2: Identifiable amino acids through Phenomenex GC-FID protocol and their retention times. Gas chromatography was used in the determination of amino acid concentration. A method to control GC operation was developed through the Class VP 7.4 software. The column temperature program begins at 110 C and then ramps at a rate of 15 C/min up to 320 C where it is held for 3 minutes (Zebron ZB-AAA, 10mx 0.25 mm, film composition 50% phenyl 50% dimethyl polysiloxane). The injector temperature is set at 250 C and the detector at 320 C. Total flow is maintained at 44 ml/min at a split injection of 15:1 and liner velocity of 69 cm/sec. Similar to previous mass fraction calculations, the series of determined standard peak areas were used to develop a set of calibration curve equations. Once the 55

67 chromatograms were integrated for the samples, the determined peak areas could be placed in these equations to obtain individual AA mass fractions in the samples using determined peak areas. These individual mass fractions were then summed over all peak calculations. Peaks on a sample chromatogram that fell between two standard peaks retention times were not accounted for in the case of AA analysis. 56

68 Chapter 5 Hydrothermal Processing Results 5.1 Introduction Hydrothermal processing of lipid rich algal feedstocks produces an aqueous and oil phase. The composition of these phases has displayed a dependence on feedstock composition as well as reactor operating conditions [41][40]. The focus of this research is to evaluate these trends in the product streams for S. limacinum and pseudo algal mixtures. In particular, nitrogen composition and FAME content of the oil phase and recycling of the aqueous stream to growing cultures are evaluated under a number of hydrothermal processing conditions. Results of previously described analyses (Chapter 4) on the product phases are discussed in the following sections. 5.2 Analysis of Oil Phase Schizochytrium limacinum and Pseudo Algae Comparison of nitrogen content in the oil phase 57

69 The main purpose of introducing and utilizing a pseudo algae mixture was to preserve the limited amount of S. limacinum stock as well as create slurry that exhibits behavior similar to algae under hydrothermal processing conditions. Nitrogen content of the oil phase recovered after hydrothermal processing was compared for algal and pseudo algal samples. As described in Chapter 4, a pseudo algae system to simulate the composition of the S. limacinum stock (43 % lipid, 39 % protein, and 5 % carbohydrate) was formulated using soy bean oil for the lipid portion, bovine serum albumin (BSA) for the protein portion, and corn starch for the carbohydrate portion. The nitrogen content of recovered oil phases after 30 minutes of hydrothermal treatment was measured and compared for S. limacinum and pseudo algae mixtures for a range of batch reaction temperatures (Figure 5.1). There is good agreement between oil layer nitrogen content of both pseudo and algal slurries between temperatures of 200 to 310 C. The pseudo alga was limited to operating temperatures above 200 C. Below 200 C the mixture would produce an omelet like substance, which increases mass transfer limitations and impedes separation of aqueous and oil phases. The standard deviation of the data points barely or almost overlap. Reasons for deviations between algal and pseudo algal samples include uncertainties in algae analysis and incomplete transfer of bomb contents to the reactor. Taking these uncertainties into consideration, the pseudo alga appears to represent the S. limacinum slurry well with respect to nitrogen content of the oil phase. 58

70 Figure 5-1: Demonstration of agreement between alga and pseudo slurries in determining trends in oil nitrogen content with 30 minute batch reaction time Oil Nitrogen Content As mentioned previously, minimizing oil nitrogen content is important in reducing NO x emissions of a fuel product. For high nitrogen content oils, additional processing and separation would be required to produce a low nitrogen fuel product. The purpose of this research was to assess behavior of algal feedstocks over a range of temperatures and the resulting oil phase nitrogen compositions. Trends observed in data collected from a literature review include oil nitrogen content independent of reaction time length at lower temperatures (below 200⁰C), time dependence between 200 and 275⁰C, and time independence along with a limiting value of nitrogen content beyond 275 to 350⁰C for different feedstock compositions (Figure 5-3). A series of reactor runs, utilizing both algal and pseudo algal slurries was tested over this range of temperatures and durations while monitoring the oil nitrogen percentage. These series of reactor runs 59

71 were performed using S. limacinum and pseudo slurries, both with a protein to lipid ratio (P:L) of 0.9 (See Table 5.2 for reactor run details). Figure 5-2: Experimental verification of trends in oil layer nitrogen percentage for P:L of 0.9 over a range of reaction durations and temperatures using both pseudo algae and S. limacinum slurries. In Figure 5-2 the use of pseudo alga slurry was prohibited at low temperatures due to an omelet like material forming from the BSA protein. To verify the lower end of the envelope the S. limacinum slurry was employed. There was good agreement between pseudo algae and S. limacinum as seen with reactor runs Wissinger-1 and 4 with 30 minute batch times. As expected, the lower temperature runs are very similar in oil nitrogen content. These values are not in as tight of a group as data of Figure 5-3, but considering the scale 60

72 of differences of a fraction of a percentage, are still fairly close and display a relative independence of reaction duration. The second trend verified was the envelope created over the temperatures of 200 to 275⁰C. This can be seen by the dependence of oil nitrogen content between 5 and 60 minutes over the mentioned temperature range. The 30 minute reactor runs were performed to further illustrate the time dependence of oil nitrogen content over the range of temperatures. A similarity between this data and Alba-1 & 2 presented in Figure 5-3 is that beyond 310⁰C, the 5 minute samples contains more nitrogen in the oil than the 60 minute sample. Table 5.1: Comparing oil nitrogen content of pseudo slurries with different P:L at hydrothermal processing temperatures at 250 and 310 C at a reaction duration of 60 minutes. Pseudo slurry protein and lipid weights were adjusted to create different P:L ratios including 3.9, 2.0, and 0.9 to determine the dependence of the oil nitrogen content on feedstock composition. Behavior is as expected with the higher P:L resulting in a higher oil nitrogen content and minimal difference in oil nitrogen content between 250 and 310⁰C (Table 5.1). The P:L composition of the feedstock appears to be a crucial factor in the resulting limiting nitrogen content of the oil phase [41, 45]. As lipid content is increased the nitrogen containing compounds in the oil phase will be essentially diluted in lipid derived oil and results in lower nitrogen content. Also seen in 61

73 Table 5.1 is the non-linear relationship between the P:L and oil nitrogen content. With the P:L doubling for each data set, the limit increases. The nitrogen limit of data sets P:L 3.9, 2.0, and 0.9 was 5.9, 5.3, and 3.0%, respectively. This trend can also be seen over all data presented in Table 5.3. Batch hydrothermal processing results from several researchers are combined in the graph seen below in Figure 5-3 [42, 45-48]. From the data displayed in Figure 5-3 a trend was recognized in oil nitrogen percentage based on both operating conditions as well as feedstock composition. Details of hydrothermal batch reaction time and temperatures and algae feedstock are summarized in Table 5.2. Figure 5-3: Compilation of hydrothermal processing product oil layer nitrogen percentage over a range of subcritical water temperatures provided by other researcher s results demonstrating the dependence on feedstock and operating parameters (Author references in Table 5.2) 62

74 The first trend that can be seen over most data sets is the agreement of oil nitrogen content at lower temperatures regardless of feedstock or reaction duration. This trend is illustrated best in the similarity between data sets Alba-1 and Alba-2 at low reaction temperatures (less than 200 C) which are seemingly independent of the reaction duration difference of 5 and 60 minutes. As the temperature is increased, the resulting nitrogen percentage also increases over the temperature range of 150 C to 250 C for data sets Alba-1, Alba-2, Torri-1, Torri-2, and Brown. When comparing short (5 minute) and long (60 minute) reaction times of Alba-1 and Alba-2 over this temperature range (200 C, 225 C, and 250 C), there is larger difference in oil nitrogen percentage than at the lower temperature. Lower nitrogen percentage is seen with the shorter reaction time and longer duration correlates to higher oil nitrogen content. This envelope development suggests that the oil nitrogen content over this range of temperatures is reaction duration dependent. Beyond 275 C, the oil nitrogen content is again independent of batch reaction time and approaches a limit which appears to be related to the protein:lipid ratio (P:L) Biller-4 has a single point at 350 C with a batch reactor time of 60 minutes. At these elevated temperatures, time does not appear to affect the oil nitrogen percentage. Brown also reacted for 60 minutes at 350 C, but has a low asymptotic value or (limit of the nitrogen content) and a low P:L ratio. This suggests that the reaction duration, at this higher reaction temperature, does not affect the increase or decrease of oil nitrogen content. The P:L ratio was calculated for all algal feedstocks (Table 5.3) and arranged by values of protein lipid ratios to determine a relationship between P:L and the trend in limiting oil nitrogen percentage. It can be seen below that with an increasing P:L there is 63

75 a similar trend in the oil nitrogen content limit reached above 275 C. This is not a linear correlation, but a general trend. Some data does not follow the trend such as Biller-3 and Torri-1. This could be a result of unspecified details in experimentation, temperature fluctuation (experienced in this research and demonstrated later in this review), or inaccuracy of nitrogen determination. 64

76 Table 5.2: Summary of author specific feedstock species, biopolymer composition, calculated protein lipid ratios, and loading (% w/v, dry weight basis) and batch reaction time for oil nitrogen percentage data shown in Figure 5-1. The author Wissinger refers to the research presented in this thesis. *Protein to lipid ratio in feedstock Succession of label denotes increase in reaction duration 65