Article pubs.acs.org/IECR
Lipid Transformation in Hydrothermal Processing of Whole Algal Cells Michael C. Johnson*,†,§ and Jefferson W. Tester‡ †
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States Department of Chemical and Biomolecular Engineering and Cornell Energy Institute 2160 Snee Hall, Cornell University, Ithaca, New York 14853, United States
‡
S Supporting Information *
ABSTRACT: Hydrothermal processing may provide an attractive alternative for producing biofuels with microalgae. Hydrothermal processing can be used with wet feedstocks without needing energy-intensive drying or solvents for oil recovery as is typical for algae biofuel processes. In this study, microalgae strains Isochrysis sp. and Thalassiosira weissflogii were processed in a hydrothermal batch reactor at temperatures of 250−350 °C and residence times up to 3 h. Triglyceride feedstock hydrolysis in hydrothermal systems was modeled using previously identified methods. Kinetic parameters for triglyceride hydrolysis were fit to literature data. Degradation of unsaturated fatty acids in hydrothermal systems was modeled by adding reaction pathways to the hydrolysis reaction system, and fitting kinetic parameters to the experimental data. The time scale for the degradation indicates that short reaction times (20% drop in value), indicating that specific reactions are occurring that preferentially affect unsaturated fats. However, the actual cause and mechanistic details of this effect was not further probed by Barnebey and Brown or in later reported research. Received: Revised: Accepted: Published: 10988
March 18, 2013 June 29, 2013 July 23, 2013 July 23, 2013 dx.doi.org/10.1021/ie400876w | Ind. Eng. Chem. Res. 2013, 52, 10988−10995
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with conversions of triglyceride to free fatty acids above 80 and 100% at 250 and 280 °C, respectively. Alenezi studied hydrolysis of sunflower oil from 270 to 350 °C in a tubular reactor.21 The resulting free fatty acids were measured by titration. Kinetic parameters were found when a constant induction period was assumed for each temperature. This ignores the physical reality that the induction period was caused by the low solubility of water in triglycerides as earlier suggested by Lascaray. Later studies by Alenzei and co-workers explored pressure effects and longer reaction times.22 Conversion increased to near 90% but subsequently decreased from decomposition above 300 °C and 15 min of residence time. Tavakoli and Yoshida looked at hydrolysis of squid processing wastes to recover free fatty acids at 170−380 °C and 1−40 min reaction time.23 Their research was the first to look at the hydrothermal changes to the lipid profile of a highly unsaturated feedstock similar to fish oils or microalgae. Reactions were performed in a static autoclave (bomb) reactor. Polyunsaturated fatty acids (PUFA), specifically eicosapentaenoic acid (20:5) and docosahexaenoic acid (22:6), were the dominant fatty acids in this feedstock. Results showed that the PUFA concentration increased at 10 min reaction time up to 240 °C, then disappeared at higher temperature, probably due to degradation. Saturated fatty acid content generally increased to the same temperature and then had constant concentration thereafter. In this study, we model the changes that take place in microalgal oils when processed in a hydrothermal environment. Two microalgae strains were reacted in a batch reactor with no head space for 0−3 h at 250−350 °C. A model for triglyceride hydrolysis was found and parameters were fit to literature data. This model was applied to the saturated portion of the algal oils to fit the lipid-specific parameters. The model was then extended to add the degradation of unsaturated fatty acids, and degradation kinetic parameters were fit using the experimental data obtained. This study is focused on the lipid reaction model and parameter fitting; more information is available through other work.24
The most definitive early work on fat splitting was done by Sturzenegger and Sturm in 1951.11 The authors built a sophisticated reactor apparatus that allowed for introduction of large volumes of oils into a pre-heated reactor. The stirred batch reactor kept the contents agitated throughout the reaction, and a sampling device allowed for monitoring during reaction. Peanut oil, coconut oil, and beef tallow were all hydrolyzed at a range of conditions. The pressure was held just above the saturation pressure, at temperatures between 220 and 280 °C. Lascaray proposed that the action of splitting occurs in these dual-phase systems predominately in the oil phase.12 Therefore, the solubility of water in the oil phase is of critical importance. Not much effort was made in modeling the water effect on the reaction until 1988, when Patil and co-workers13 revisited the work of Sturzenegger and Sturm. Patil and co-workers developed a model for the hydrolysis reactions that occur in fats, including the role of water in the reaction. Water solubility in the oil phase was modeled with a linear correlation. To model the chemical reactions, some additional parameters had to be estimated, such as distribution coefficient for glycerol from solubility data. The end result was a fairly accurate representation of the appearance of free fatty acids from oil feeds in hydrothermal systems. This methodology for modeling the kinetics of oil hydrolysis to fatty acids has been scarcely used since. Hydrolysis of renewable oils has been widely studied, likely due to the interest in renewable sources of biologically derived oils for transportation fuels. These reactions have been performed in both batch and continuous systems, mainly without catalysts. Holliday and co-workers noted that above 300 °C, fatty acids began to degrade in a bomb reactor apparatus.14 When King and co-workers switched to a flow reactor with the same feedstock, they noted that the temperature range was between 300 and 340 °C, and no degradation products were observed for reaction times up to 15 min, indicating the head gases may affect the reaction.15 Also, reactant oil was seen moving independently in the reactor from the bulk water flow when immiscible. Complete miscibility of the oil and water was only observed above 340 °C for soybean oil in water. Khuwijitjaru and co-workers explored the hydrolysis of various fatty acid esters at hydrothermal conditions.16 First they reported on the solubility of these products at elevated temperatures17 and then used the solubility data to derive what concentrations to use for hydrolysis reaction kinetic determinations, so that there was no separate oil phase.16 For one set of experiments, several acyl carbon chain lengths were chosen (C8−16), with methyl esters. A second set of experiments used lauryl acid (C12) as the acyl chain with methyl, ethyl, propyl, or butyl as the ester groups, to study the effect of the ester group. Simple first-order kinetics were assumed and kinetic parameters were estimated. Fujii performed hydrolysis of monoglycerides to free fatty acids and glycerol, also beginning with a feed composition at the solubility limit in water.18 Kocsisova observed the appearance of fatty acids in continuous flow reactor operating between 280 and 340 °C at 1:4 and 1:2 oil−water volume ratios.19 He correlated the onset of fatty acids to the disappearance of glycerides over time. Pinto studied the hydrolysis of corn oil at 150−280 °C.20 In these experiments, the reaction was very slow below 250 °C,
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METHOD AND MATERIALS Microalgae were purchased from Reed Mariculture (Campbell, CA). The strains were used as received, at about 18 wt % solids. Samples were sent for analysis to New Jersey Feed Laboratory (Ewing, NJ) for proximate analysis (fat, protein, carbohydrate, and ash content) and fatty acid profile. Reactions were run in a custom-machined, 30 mL HastelloyC reactor, shown in Figure 1. Four ports were tapped into the
Figure 1. Schematic diagram of reactor system. 10989
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100 mg of packing. The protocol for separation followed that of Kaluzny but 0.75 mL of solvent was used. The column was washed with hexane, and then the hydrothermal oil in chloroform was added. Next, a 2:1 chloroform−isopropyl alcohol mixture was added, with the glyceride-containing effluent collected. Then, a 2% acetic acid in ethyl ether reagent was used to elute free fatty acids. Acid number measurement was used to find the total concentration of fatty acids in oil. Ten milliliters of 18:1:1 volume ethanol−methanol−propanol was mixed with 0.25 mL of oil sample and phenolphthalein indicator. Sodium hydroxide was used as the titrant (3.51 mM solution). The standard error for titration values was 1.1%.
reactor, with two used for entrance and exit streams, and the others used for pressure and temperature sensors. Heating was performed by six 125 W Chromalox stick heaters with the temperature controlled by an Omega CN9000A temperature controller. Temperatures were measured with Omega Type-J thermocouples (Omega Engineering, Fairfield, CT). Data were recorded with an MCC USB-TC and MCC software (Measurement Computing Co., Norton, MA). Reactor pressure was monitored with Dynisco μPR690 pressure transducer (Dynisco, Franklin, MA). Ten milliliters of cell solution was injected into the reactor system with a Luer-Lok syringe fitted to a three-way valve. Once the cells were injected, the valve was closed and an Eldex metering pump forced the contents into the reactor (Eldex Laboratories, Napa, CA). Once the reactor reached the set point (approximately 15 min to reach temperature), the pressure was adjusted through use of the exit valve set to 205 bar (3000 psi). This point was considered as the start of the batch reaction residence time. To terminate the reaction, the heaters were turned off and the reactor contents were pumped out of the system where they were quenched using an ice bath. Approximately 200 mL of reaction effluent and reactor wash water was collected from each run. To recover the oil for analysis, the produced organics were extracted twice with 25 mL (2 × 25 mL) of chloroform using a 500 mL separation funnel. To get a cleaner separation, each phase was spun at 6000g for 10 min in 50 mL centrifuge tubes. To determine the weight of oily product produced, 2.0 mL aliquots of the chloroform solution were placed in tin dishes and evaporated. The ratio of solvent-free oil mass to oil and solvent aliquot mass was used as the mass fraction of hydrothermal oil in chloroform. To determine the acyl chain of the lipids, the oil phase was derivatized to fatty acid methyl esters (FAMEs), which can be measured on a gas chromatograph. One milliliter of chloroform solution was evaporated to drive off the solvent. To the solventfree oil was added 4 mL of hexane and then the mixture was placed in a 25 mL Swagelok reactor, followed by 5 mL of acetyl chloride in methanol (1:20 by volume). The reactor was purged with nitrogen to displace oxygen and was placed in a 105 °C oven for 1 h and then quenched. After cooling, the reactor contents were emptied into a 15 mL centrifuge tube and the reactor was rinsed with 2 mL of salt water. The salt water rinse was added to the centrifuge tube, and the tube was capped and shaken. The top hexane layer was withdrawn and analyzed using the following GC−FAME method. The GC−FAME analysis employed a DB-WAX column (PN125-7032, 30m × 0.53 mm × 1.0 μm) from Agilent J&W (Santa Clara, CA). Helium (High Purity, Airgas, Radnor, PA) was used as the carrier gas, with hydrogen (Ultra High Purity), air (Ultra Zero), and nitrogen (High Purity) used for the flame ionization detector (FID). The method used helium at a 4:1 split, with split flow set to 21.2 mL/min. The FID was operated with 450 mL/min air, 40 mL/min hydrogen, and 19.7 mL/min nitrogen. The temperature program started at 130 °C for 3 min, then ramped at 12.5 °C/min to 200 °C and held for 5 min. The injection and FID temperatures were 250 and 350 °C, respectively. A method has been established previously by Kaluzny and co-workers to separate classes of lipids.25 This method was adapted slightly for separation of lipids with solid-phase extraction columns. Pre-packed aminopropyl columns were purchased from Sigma-Aldrich (Discovery DSC-NH2) with
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MODEL RESULTS The overall hydrolysis reaction is broken into three consecutive reactions. In each reaction a water molecule hydrolyzes one ester bond, releasing a free fatty acid. The R group for the fatty acid chain varies from 7 to 23 carbons in length, and is not necessarily identical across the three chains in a triglyceride.
triglycerides (T) + water (W) ↔ diglycerides (D) + fatty acids (F)
(S1)
diglycerides (D) + water (W) ↔ monoglycerides (M) + fatty acids (F)
(S2)
monoglycerides (M) + water (W) ↔ glycerol (G) + fatty acids (F)
(S3)
The first reaction (S1) is assumed rate controlling, and the second and third are sufficiently fast to assume that equilibrium is achieved. The first reaction is reversible, with Arrhenius reaction constants as seen in eqs 1 and 2. Equilibrium is reached at long reaction times, so the equilibrium constant for the first reaction is given by K1, the ratio of the forward and reverse rate constants, shown in eq 3. The equilibrium constant for the second (S2) and third reactions (S3) are given by the ratio of concentrations in the oil of the specified components, given in eqs 4 and 5. The Gibbs free energy, γ, of the reaction is used to give the temperature dependence of the equilibrium constant in eqs 3−5. Note that we assume the Gibbs energy itself to be insensitive to temperature in this approach.
k = α e−E / Rτ
(1)
dT = −k1TW + k 2DF dt
(2)
k1 = e−γ1/ Rτ k2
(3)
K1 = 10990
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Table 1. Fatty Acid Profile (wt %) for Various Feedstock Oils fatty acid
carbon number
tallow
coconut
peanut
sunflower
corn
rapeseed
caprylic capric lauric myristic palmitic palmitoleic stearic oleic linoleic linolenic triglyceride MW(g/mol) density (g/mL) iodine value
8:0 10:0 12:0 14:0 16:0 16:1 18:0 18:1 18:2 18:3
0 0 0 3 27 3 15 48 3 1 857.7 900 54.3
8.3 6.7 47.6 18.2 8.8 0 2.6 6.2 1.6 0 674.9 920 8.5
0 0 0 0 10 1.5 7.7 46.8 33.4 0.6 874.9 914 105.6
0 0 0 0 7 0 4 17 72 0 876 919 145.6
0 0 0 0 14 0 3 36 46 1 871.9 922 118.3
0 0 0 0.1 4.7 0 1.1 68.9 18.6 6.6 879 920 110.4
K2 =
DW = e−γ2 / Rτ MF
(4)
K3 =
MW = e−γ3/ Rτ GF
(5)
eq 9. One more equation is necessary to account for all of the variables, so a balance is written on the acyl chains (free and bound fatty acids) in eq 10, where A/O is the mass ratio of water to oil phases, and m is the equilibrium distribution coefficient for glycerol in the water and oil phase and is assumed to depend on the feedstock. The subscript, 0, denotes initial values corresponding to the feedstock composition. Equations 2−10 can be solved as a differential algebraic equation (DAE) with parameters fit to any unknown variables. Matlab R2010a (Mathworks, Natick, MA) was used to model the DAE system and fit both kinetic and solubility parameters. Parameter estimation was performed by use of a nonlinear parameter fitting function over the DAE system.
The empirical formula for the concentration of water in the oil phase was given by Patil and co-workers and is given in eq 6.13 Water concentration in the oil phase is dependent on the concentration of free fatty acids, F, and triglycerides, T. For free fatty acid dependence, the acid head groups dictate the solubility of water in fatty acids, so the function for ΔF is the same for all feedstocks considered. The values for ΔF were solely a function of temperature in Patil.13 Arrhenius parameters were fit by taking the logarithm of the ΔF values given by Patil and using a least-squares fit of the transformed ΔF. Results of the parameter estimation are given by eq 7. Water solubility in triglycerides depends more on the structure of the acyl chains, which is characterized by the iodine value (IV). The IV was calculated as the mass of iodine that would stoichiometrically react with the double bonds of unsaturated fatty acids in 100 g of an oil sample. Equation 8 was found using the data from Patil and co-workers, where ΔT was estimated by least-squares fit as a linear function of the IV and is proportional to ΔF. The IVs used to correlate ΔT were below those for typical fish oils, so for IV above 110, ΔT was assumed as 1.5 times ΔF. This “ceiling” on iodine value prevents negative Δ T values. Note that this method ignores the other components from the oil phase. In hydrothermal oils, the other liquefied components such as proteins also likely affect solubility of water in the oily phase. W = ΔTT + ΔFF
(6)
ΔF = 40 e−2228/ τ
(7)
ΔF = 9 − 0.0688IV ΔT
(8)
⎛ A ⎞ 0 = ⎜1 + m⎟(G − G0) + (M − M 0) + (D − D0) ⎝ O ⎠ + (T − T0)
(9)
0 = (F − F0) + 1(M − M 0) + 2(D − D0) + 3(T − T0) (10)
Initially, an approximation for the value of m was made for the data from Sturzenegger and Sturm11 for each of the three feeds in that study to put into eq 9. The acid values (total free fatty acid concentration) from Sturzenegger and Sturm11 and the equilibrium coconut monoglyceride concentrations from Patil13 were used along with initial concentrations from those experiments to fit the kinetic parameters in the system of eqs 2−10. These kinetic parameter values and confidence intervals are given in Table 2. With the use of these fitted kinetic Table 2. Fitted Reaction Kinetic Parameters reaction parameters −1
−1
α1 (M min ) E1/R (K) γ1/R (K) γ2/R (K) γ3/R (K)
For this model, an average molecular weight (MW) and IV were calculated from the composition of the acyl chains, which we call the fatty acid profile. The fatty acid profile, given as percent weight of the total lipids, assumed for different oils is shown in Table 1, with the corresponding calculated average MW and IV. Glycerol is soluble in water, and this solubility drives the equilibrium for the system toward free fatty acids. To track the glycerol in the model, a total glycerol balance is used, shown in
value
95% confidence interval
2.0 × 10 6630 −1740 −1020 −110
4
[2.0× 104, 2.0× 104] [6620, 6650] [−12200, 8770] [−3660, 1620] [−990, 780]
parameters, Arrhenius parameters for the glycerol distribution coefficient, m, were fit for each of the data sets from Sturzenegger and Sturm (Table 3). The agreement between estimated acid values and published acid values was generally very good as shown in Figure 2 for the data from Sturzenegger and Sturm.11 Acid value is the mass (in mg) of KOH required to neutralize 1 g of oil. Figure 2 shows 10991
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in eq 11 and 12. The glycerol balance is changed to explicitly include the unsaturated triglycerides as well, and the water solubility is a function of the total concentration of fatty acids and triglycerides. Thus, eqs 13, 14, and 15 replace eqs 9, 10, and 6 in the model.
Table 3. Fitted Arrhenius Parameters for Glycerol Distribution Coefficient (m = α E/RT) for a Variety of Oil Feedstocks α tallow coconut peanut
3.6e-1 1.1e-3 8.6e-6
E/R (K) −2060 −5000 −7190
the experimental data as points, plotted with a line showing the model results under the same conditions. Part (d) of the figure shows the agreement between model prediction and experimental data. At this point, the kinetic model given by eqs 2−10 can be used for hydrolysis of most triglycerides once the feedstock oil is characterized with respect to IV and MW, and an estimate of the distribution coefficient m is known. Once triglycerides are hydrolyzed to free fatty acids, the unsaturated fatty acids are subject to degradation. This additional reaction was added to the model. A simple degradation pathway was assumed, where the free fatty acids that are unsaturated will degrade with first-order kinetics. Because the triglyceride hydrolysis is rate controlling for the formation of free fatty acids from triglycerides, unsaturated fatty acid degradation is the only additional reaction required for the model. The unsaturated units are treated as a separate component from the saturated ones, designated with subscript u. The same overall structure is used for triglyceride hydrolysis to fatty acids, summarized in one reaction (S4). The degradation reaction is shown in S5. Tu + 3W → G + 3Fu
(S4)
Fu → products
(S5)
dTu = −k1TuW dt
(11)
dFu = 3k1TuW − k uFu dt
(12)
⎛ A ⎞ 0 = ⎜1 + m⎟(G − G0) + (M − M 0) + (D − D0) ⎝ O ⎠ + (T − T0) + (Tu − Tu 0)
(13)
0 = (F − F0) + (Fu − Fu 0) + 1(M − M 0) + 2(D − D0)
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+ 3(T − T0) + 3(Tu − Tu 0)
(14)
W = ΔT(T + Tu) + ΔF(F + Fu)
(15)
EXPERIMENTAL RESULTS Two microalgae species were used for experiments: a browntan flagellate from Isochrysis, and a diatom, Thalassiosira weissflogii. Proximate analysis of the algae is given in Table 4, including Bligh−Dyer (chloroform−methanol extracted oil) analysis,26 the total fatty acids from titration, and unsaturated fatty acids from GC−FAME measurement. The kinetic parameters found previously for hydrolysis in Table 2 are used to model the hydrolysis of saturated fats in algal oil. Glycerol distribution coefficient, m, was fit to the saturated algal fat data. Figure 3 shows the measured mass
With these additional reactions, the model must be expanded for two new species, Tu and Fu, by adding two equations shown
Figure 2. Fatty acid evolution as a function of time for (a) tallow, (b) coconut, and (c) peanut oil from Sturzenegger and Sturm.11 Lines represent the model vs the points from data. A comparison of prediction versus measured values is given in (d) with all data points. 10992
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factor of 0.0155 min−1 and E/R of 902 K, with a confidence interval of [−0.0389, 0.0681] and [−1200, 2939], respectively, for these parameters at the 95% confidence level. The large confidence interval stems from the large uncertainty in the GC−FAME and oil yield data. Although this study used a proven method for measuring the fatty acid profile, the data were imprecise and could potentially be improved in future studies with improved method precision and larger sample volumes. Oil yield and GC−FAME data are included in the Supporting Information.
Table 4. Proximate Analysis of Microalgae (as a Percent of Total Weight) component
Isochrysis
protein
T. weissflogii 46.8
42.9 lipids
5.8 10.5
unsaturated (% of lipids)
66.6 34.9
Bligh−Dyer
11.1
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24.3 ash
32.7
DISCUSSION Determining kinetic parameters are an integral step in the translation from laboratory to commercial processes. Although studies have been performed on the transformations of whole algal cells in a hydrothermal environment, nothing resembling kinetic measurements has been reported to date. The methods developed by Patil and co-workers for oil hydrolysis were adapted for several types of oil feedstocks with a single kinetic model.13 The model accurately predicts the results found by Sturzenegger and Sturm.11 Other published data generally agreed with this model as well, including that from Pinto20 and Kocisova19 (see Supporting Information). An exception to the model fit is data from Alenezi21 for sunflower oil, which consists of a feedstock that is 20% diglycerides and 2.5% monoglycerides. The other data sets are all triglycerides initially, so the model defined here is well-suited for triglyceride-rich oil feedstocks. Nonequilibrium hydrolysis would have to be assumed for the second and third reactions (S2 and S3) with corresponding rate parameters for this model to apply to the diglyceride and monoglyceride-rich feeds. Experimental data sets were produced from two whole algal biomass feedstocks (Isochrysis and T. weissflogii) over temperatures ranging from 250 to 350 °C at a pressure of 205 bar. With this model, the saturated oil portion of algal biomass was used to fit the solubility parameter, m. Once solubility parameter was estimated, the expanded kinetic model was used to fit experimental data for unsaturated fatty acid degradation. The time scale for the destruction indicates that shorter reaction times (
