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Enzymatic hydrolysis of microalgal cellulose for bioethanol production, modeling and sensitivity analysis
Fuel 228 (2018) 30–38
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Full Length Article
Enzymatic hydrolysis of microalgal cellulose for bioethanol production, modeling and sensitivity analysis
T
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Hanieh Shokrkar, Sirous Ebrahimi , Mehdi Zamani Biotechnology Research Center, Faculty of Chemical Engineering, Sahand University of Technology, Tabriz, Iran
G R A P H I C A L A B S T R A C T
A R T I C LE I N FO
A B S T R A C T
Keywords: Bioethanol Cellulose Enzymatic hydrolysis Kinetic Mixed microalgae Sensitivity analysis
A kinetic model was developed to describe the enzymatic hydrolysis of microalgal cellulose. In the kinetic model, the factors including product inhibition, temperature, and pH were considered. This model combined two reactions for hydrolyzing algal cellulose to cellobiose and glucose and one reaction for cellobiose breakdown to glucose. Results showed that the highest glucose yield (57%) was achieved at microalgal biomass concentration of 50 g/L, pH 5, and temperature of 50 °C. Moreover, the sensitivity analysis was carried out on each kinetic model parameter. This analysis indicated that k′3 and km3 in reaction R3 (cellobiose to glucose) are the most influential parameters during enzymatic hydrolysis of algal cellulose. Finally, the microalgal biomass loading experiment demonstrated that cellulase could be used thrice without compromising on the glucose yield. Fermentation of concentrated sugar medium with Saccharomyces cerevisiae produced ethanol (12.87 g/L) with yield (0.46 g ethanol/g glucose).
1. Introduction
technologies for conversion of other feedstock such as microalgae into biofuel have been considered. Algae grow quickly without need of soil and absorb carbon dioxide from atmosphere for photosynthesis process [6]. In addition, microalgae have short harvesting cycle compared with other feedstocks, which are harvested once or twice a year [4,7,8]. Some studies have reported high levels of carbohydrate accumulation up to 54.3% by microalgae under nitrogen limiting conditions [9,10].
Bioethanol is one of the renewable energy sources that can reduce fossil fuel consumption and environmental pollution [1,2]. Agricultural materials such as starch, corn, rice, wheat, sugar cane, sugar beet, and sweet sorghum are not prospective selections for bioethanol production as the human request for food has yet to be met [3–5]. Lately, process
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Corresponding author. E-mail address: sirous.ebrahimi@epfl.ch (S. Ebrahimi).
https://doi.org/10.1016/j.fuel.2018.04.143 Received 27 April 2017; Received in revised form 28 February 2018; Accepted 25 April 2018 0016-2361/ © 2018 Elsevier Ltd. All rights reserved.
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Table 1 The reaction rates and mass balances. Stage
Rates
Cellulose → Cellobiose
R1 = Cellulose → Glucose
R2 =
E ⎛− a1 ⎞ A1 . e⎝ R.T ⎠ . [ECellulases] . [C] + ⎡ ⎛⎜1 + [G2 ] + [G] ⎞⎟ + [C] ⎤ . ⎡1 + K a2 + [H ] ⎤ ⎢ ⎥ ⎢ k1IG2 k1IG ⎠ K a1 ⎥ [H+] ⎦ ⎣⎝ ⎦ ⎣ E ⎛− a2 ⎞ R.T ⎠ . [ECellulases] . [C] A2 . e⎝ + ⎡ ⎛⎜1 + [G2] + [G] ⎞⎟ + [C]⎤ . ⎡1 + K a2 + [H ] ⎤ ⎢ ⎥ ⎢ k2IG2 k2IG ⎠ K a1 ⎥ [H+] ⎦ ⎣⎝ ⎦ ⎣
Cellobiose → Glucose
E ⎛− a3 ⎞ A3 . e⎝ R.T ⎠ . [ECellulases] . [G2]
R3 = Reaction rate constants
k′i =
Mass Balances
k′1 (h−1) k′2 (h−1) k′3 (h−1)
d[C] dt
Cellobiose:
Glucose:
= −R1−R2
d[G2] dt
d[G] dt
= 1.056R1−R3
= 1.116R2 + 1.053R3
+ ⎡k . ⎛⎜1 + [G] ⎞⎟ + [G ]⎤ . ⎡1 + K a2 + [H ] ⎤ 2⎥ ⎢ ⎢ m3 k3IG ⎠ K a1 ⎥ [H+] ⎝ ⎦ ⎣ ⎦ ⎣
E ⎛− ai ⎞ Ai . e⎝ R.T ⎠ K [H+] + 1 + a2 K a1 [H+]
( i= 1, 2, 3)
2. Materials and methods
Table 2 The estimated values of parameters of the model. Parameter
Cellulose:
Temperature (condition: pH 5)
pH (condition: Temperature 50 °C)
30 °C
40 °C
50 °C
4
5
6
1.12 1.30 1.10
3.18 4.10 3.80
8.76 10.71 8.60
3.56 4.35 3.49
8.76 10.71 8.60
2.73 3.34 2.68
2.1. Microalgae Mixed microalgae (collected from a freshwater located in Oskou, East Azarbayjan, Iran) have been precultured in our previous study [26], and then inoculated into glass photobioreactor with a working volume of 10 L, illuminated with eight white LED lamps with a light intensity of about 260 µmol. m−2. s−1. The aeration rate in the photobioreactor was 8 vvm. The temperature and pH were 25 ± 1 °C and 9, respectively. When the nitrogen source in the photobioreactor medium was depleted, the CO2 was bubbled into the medium with the rate of 0.1 vvm. The medium composition of microalgae was the same as explained in our previous paper [26]. At the end of the cultivation, the algae were harvested from the photobioreactor and then oven dried at 80 °C for 48 h. These dried algae were ground into powder by Planetary Ball Mill and consumed for enzymatic hydrolysis by cellulase.
Carbohydrates in microalgal biomass are chiefly cellulose without lignin. The absence of lignin makes hydrolysis of microalgae easier compared to lignocellulosic materials [11]. Some studies have examined the ethanol production using the pure culture of macroalgae [12–15] and microalgae [16–18]. Cultivation of microalgae in pure culture will increase operating costs because of the need for the sterile condition. Therefore, usage of a mixed microalgal culture dominates these problems [19,20]. Hydrolysis process for carbohydrates extraction from algae can be performed using acids or enzymes. Enzymatic hydrolysis has various advantages compared to acid hydrolysis, including low utility consumption, less corrosion problems, higher glucose yield without sugar-degradation and inhibitory products production. In contrast, the enzymatic hydrolysis increases the cost of producing ethanol [21,22]. Some researchers have investigated carbohydrate extraction from a pure culture of algae [12–18,23]. Besides, Hwang et al. investigated the different pre-treatments of both filamentous and cyclotella algal cells for bioethanol production [24]. To author’s awareness, there is only one research on the kinetics of enzymatic hydrolysis algal cellulose by R. Harun and M. K. Danquah [25] in which the kinetics parameters of hydrolysis was obtained using Michaelis–Menten’s model. However, their study did not consider pH effects on enzyme kinetics and sensitivity analysis of kinetic parameters. In addition, their study investigated the kinetics of enzymatic hydrolysis of a pure culture of algae of Chlorococcum sp. In the present study, the kinetic modeling and sensitivity analysis of enzymatic hydrolysis of microalgal cellulose using cellulase was studied. Furthermore, the microalgae loading strategy was used to obtain a concentrated sugar solution from the enzymatic hydrolysis step, leading to high volumetric bioethanol productivity, the principal factor affecting the cost-effectiveness of full-scale applications. Subsequently, the bioethanol yield of the fermentable sugars derived from enzymatic hydrolysis step was investigated through cultivating Saccharomyces cerevisiae yeast.
2.2. Enzymatic hydrolysis of microalgal cellulose Cellulase from Trichoderma reesei obtained from Novozymes, Denmark was used for enzymatic hydrolysis of algal cellulose. The enzymatic activity of this enzyme was 0.04 U/mg corresponding to 0.054 mg protein/mg. For the enzymatic hydrolysis experiments, the dried algal powder was loaded into citrate buffer with the concentration of 25, 50, 75, and 100 g/L. These samples were autoclaved at 121 °C for 15 min and then mixed with constant cellulase concentration (0.416 mg protein/mL) in a 100 mL-Erlenmeyer flask with 50 mL working volume. The effects of variation of temperature in the range of 30–50 °C and pH in the range of 4–6 on enzymatic hydrolysis were investigated. The Erlenmeyer flasks were incubated in a shaker at 150 rpm for 72 h. The analysis samples were taken at different times during enzymatic hydrolysis of algae. These samples were centrifuged at 4000×g, then the supernatant was taken and cellobiose and glucose concentration were measured.
2.3. Bioethanol production For bioethanol production, S. cerevisiae has been precultured in our previous study [26]. After microalgal biomass loading experiment, pH of the microalgae hydrolysate was adjusted to 6.5 to achieve an appropriate pH range for bioethanol production. Afterwards, 10% V/V of yeast pre-culture cells were added in the fermentation medium, which contained hydrolysates of microalgae. The fermentation experiment was performed anaerobically at 30 °C shaken at 150 rpm for 24 h. 31
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Fig. 1. Effect of pH on concentration of cellobiose, glucose, and glucose yield%; (a), pH 4, (b), pH 5, (c) pH 6; Hydrolysis conditions substrate concentration of 50 g/L and temperature of 50 °C.
2.4. Analytical procedures
Table 3 The estimated values of Ka1 and Ka2. Ka1 (mol/L) Ka2 (mol/L) pK a = −log[Ka]
2.91 × 10−5 4.8 × 10−6
pKa1 pKa2
The biomass concentration of the microalgae culture was measured base on dry weight. Determination of total suspended solids (TSS), Volatile suspended solids amount (VSS) and ash content of microalgae were the same as described in our previous study [26]. Residual concentration of nitrogen was measured using the colorimetric method according to Cataldo, D. et al. [27]. Determination of total carbohydrate of microalgae biomass was performed based on Hedge and Hofreiter method [28]. The cellulose content of microalgal biomass was
4.53 5.31
32
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Fig. 2. Effect of temperature on concentration of cellobiose, glucose, and glucose yield%; (a), 30 °C, (b), 40 °C (c) 50 °C; Hydrolysis conditions substrate concentration of 50 g/L and pH 5.
3. Theory
determined according to Mihranyan et al. method [29]. Determination of lipid and protein contents of microalgae were the same as described in our previous paper [20]. Cellulase concentration (mg protein/mL) was specified as described by Lowry [30]. The concentrations of ethanol, glucose, and cellobiose were analyzed using high-performance liquid chromatography with Aminex HPX-87P column. All experiments were conducted in duplicate. The yield of glucose and ethanol can be represented by the following equations.
Glucose yield % =
Extracted glucose (g) × 100 Total carbohydrate in algae (g)
(1)
Ethanol yield % =
produced ethanol (g) × 100 Extracted glucose from algae (g)
(2)
3.1. Kinetic model The kinetic model assumes that hydrolysis of cellulose occurs in three steps: the cellulose is hydrolyzed to soluble cellobiose, the cellulose is hydrolyzed to glucose, and cellobiose is hydrolyzed to glucose [31]. This model was used to predict concentrations of cellobiose and glucose during enzymatic hydrolysis of microalgal cellulose. Reaction scheme and mass balances for modeling enzymatic hydrolysis are depicted in Table 1. This scheme involved hydrolysis reactions of R1, R3, and R2. In some studies, R2 is ignored [25]. This model has been developed based on end-product inhibition. In these rate equations, k′i (i = 1, 2, 3) are the reaction rate constants (h−1); kiIG (i = 1, 2, 3) and kiIG2 (i = 2, 3) are inhibition constants of glucose and cellobiose on enzyme (g/L), respectively. km3 is cellobiose 33
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Fig. 3. Time course of the sensitivity functions of glucose concentration with respect to model parameters.
and total carbohydrate content of microalgae were 2.05 g/L, 1.56 g/L, 0.43 g/L, respectively. Therefore, the percentage of total carbohydrate was calculated to be about 27% of VSS (or approximately 21% of TSS). In addition, the protein and lipid content of biomass were 0.826 g/L and 0.30 g/L, or approximately 53% and 19% on the basis of VSS, respectively. Furthermore, the percentage of cellulose of microalgae was approximately 60% of total carbohydrate content.
saturation constants (g/L). [C], [G] and [G2] are concentrations of cellulose, glucose, and cellobiose (g/L), respectively. In addition, [ECellulase] is the concentration of cellulase enzyme (mg protein/mL). [H+] is the concentration of hydrogen ions (mol/L). [H+] can be calculated using the equation [H+] = 10-pH. Also, Ka (1, 2) is the acid dissociation constant (mol/L). In Arrhenius equation, Ea is the activation energy (J/mol), A is Arrhenius constant (h−1), R is gas constant, and T is temperature (K). In this study, the AQUASIM software was applied as a tool to model hydrolysis of microalgal cellulose using cellulase. The kinetic model parameters were calculated using the AQUASIM by minimizing the sum of the squares of the weighted deviations ( χ2 ) among measurements and calculated model results [32].
4.2. Calculation of the values of kinetic parameters Microalgae consist of various types of carbohydrates, which are often accumulated in the cell wall. Therefore, disruption of the microalgae cell walls is essential for using it as a carbon source during the fermentation process. In order to determine the kinetic parameters, the effects of microalgae biomass concentration, pH, and temperature on enzymatic hydrolysis of mixed microalgal biomass with constant cellulase concentration for 72 h were investigated. The experimental results were evaluated by solving differential equations using AQUASIM software. Afterwards, the model parameters were estimated by minimizing χ2 between measurements and calculated model results. The estimated parameters are shown in Table 2. The values of km3, kiIG (i = 1, 2, 3) and kiIG2 (i = 2, 3) were the same as reported by Zheng et al. [33]. In order to determine the kinetic parameters (Table 2), in the first stage, the effects of microalgal biomass concentration in the range of 25–100 g/L (pH 5; temperature 50 °C) on sugar production were investigated. The results showed that the increase in the microalgal biomass concentration from 25 to 100 g/L leads to a decrease in enzymatic hydrolysis rate. The highest glucose yield was about 57% after 72 h, while the substrate concentration of 50 g/L was used. When the microalgae biomass concentration was increased from 50 to 100 g/L, the glucose yield decreased from 57% to about 45%. Therefore, microalgae biomass concentration is a significant factor, which can be optimized to obtain the highest glucose yield. When considering both the glucose yield and operating cost, the most appropriate microalgae biomass concentration is 50 g/L. In the second stage, the variation of pH in the range of 4–6 (microalgal biomass concentration 50 g/L; temperature 50 °C) were
3.2. Sensitivity analysis Sensitivity Analysis is an instrument to analyze the effect of various values of a set of parameters on specific dependent variable under certain specific situations. By showing the model behavior responds to change in parameter values, sensitivity analysis is a useful instrument in model evaluation and model building. This analysis lets us understand the effect of different parameters on system behavior and that can be used for identifies a leverage point in the system, a parameter whose specific value can change the behavior of the system significantly. The sensitivity function of the model parameter can be expressed as:
δG,P =
P ∂G . G ∂P
(3)
where G is glucose concentration and P is model parameter (k′1, k′2 , k′3, km3, k1IG, k2IG, k3IG and k1IG2) [32]. 4. Results and discussion 4.1. Microalgal biomass The experimental results showed that algal biomass concentration increased from 0.12 to 1.97 g/L as nitrogen source decreased from 0.12 to 0 g/L after 29 days. At the end of the cultivation (37 days), TSS, VSS 34
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Fig. 4. Effect of kinetic parameter variation on final glucose concentration.
demonstrated that an increase in pH (from 4 to 5) leads to the higher glucose yield of approximately 57%, and then the extent of glucose yield is decreased. The estimated values of Ka1 and Ka2 are presented in Table 3. As seen from the Table 3, the best-fit value for Ka1 and Ka2 were estimated to be 2.91 × 10−5 mol/L and 4.8 × 10−6 mol/L, respectively. Afterwards, pKa1 and pKa2 were calculated to be 4.53 and 5.31, respectively. Enzymes have been reported to have optimum activity within the pH range of pKa1 to pKa2 [34]. Therefore, it can be said that cellulase has optimum activity within the pH range of 4.53–5.31. The similar results were observed R. Harun and M. K. Danquah [25], they achieved maximum glucose yield of approximately 65% in the enzymatic hydrolysis microalgae of Chlorococcum sp using cellulase at pH in the range of 4.5–5.5.
investigated to obtain the pH dependence of the kinetic rates. The comparison between measured and predicted concentration of cellobiose, glucose and glucose yield time-course at different pH are demonstrated in Fig. 1. The activity of the enzyme and binding ability of the enzyme to the substrate are affected by pH variation. The obtained results according to Fig. 1 showed that the hydrolysis at pH 5 resulted in the highest production rate of glucose. Moreover, from the comparison of the values of reaction rate constants obtained for each pH (Table 2), it was observed that the reaction rate constants at pH 5, are higher compared to pH 4 and 6, and higher reaction rate values show faster reaction rates. Basic or acidic conditions could degrade the construction of the enzyme [25]. Therefore, pH of the enzymatic hydrolysis medium has been considered as a major factor to improve the glucose yield. Fig. 1 35
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Fig. 4. (continued)
enzymatic hydrolysis, the glucose yield increased from approximately 21 to 57% with the temperature increasing from 30 to 50 °C. Cellulase has been reported to have optimized activity in the temperature range of 40–50 °C [25,35,36], and our results, which is for the case of microalgal cellulose, corroborate that. From Fig. 2, it is evident that the temperature value of 50 °C gives the highest production rate of glucose. In addition, from the comparison of the values of reaction rate constants under different temperatures (Table 2), it was detected that the reaction rate constants at 50 °C are higher compared to other temperatures (30 °C and 40 °C), and higher reaction rate constants reveal faster hydrolysis of microalgal cellulose. Finally, Figs. 1 and 2 show that the simulation results are in good conformity with the experimental results of enzymatic hydrolysis of microalgal cellulose. Sum of the squares of the weighted deviations ( χ2 )
In the third stage, the variations in sugar production in the enzymatic hydrolysis of microalgae at different temperatures (30, 40, 50 °C) with microalgae biomass concentration of 50 g/L and pH 5 were investigated to obtain the temperature dependence of the kinetic rates. As previously represented in Table 1, the effect of temperature was studied using Arrhenius equation. The A1, A2, and A3 values were 5.46 × 1014 h−1, 1.52 × 1015 h−1 and 7.28 × 1014 h−1, respectively. In addition, the Ea1, Ea2, and Ea3 values were estimated to be 83.70 kJ/ mol, 85.85 kJ/mol, and 83.84 kJ/mol, respectively. The comparison between measured and predicted concentration of cellobiose, glucose and glucose yield time-course at different temperatures are depicted in Fig. 2. It can be observed that the highest glucose yield was about 57% after 72 h, while the temperature of 50 °C was applied. At the end of 36
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demonstrated in Fig. 4. Vertical lines illustrate the values of the nominal kinetic parameter. As shown in Fig. 4(a, b), the increase in reaction rate constants k′1 and k′3 leads to the higher glucose concentration until a critical value, and then the glucose concentration is constant. It can be observed that a 2-fold increase in k′1 (from 2 to 4) results in an increase of 10% in the extent of glucose concentration, whereas the similar change in k′3 (from 2 to 4) results in approximately 20% increase. This observation is in accordance with the Fig. 3(a). In addition, Fig. 4(c) showed that as the value of km3 decreases, final glucose concentration increases. As observed from the final glucose concentration versus k1IG, k2IG, k3IG, and k1IG2 (Fig. 4(d, e, f, g)), if k1IG, k2IG, k3IG, and k1IG2 are increased, the yield of glucose on the hydrolysis of microalgal cellulose increases. Finally, it can be said that nominal values of most of the parameters lie at the optimum value, and change in these parameter values results in a reduction in the extent of glucose concentration. Fig. 5. Time course of glucose consumption and ethanol production by S. cerevisiae from enzymatic hydrolysates of microalgal cellulose.
4.4. Bioethanol production from concentrated sugar medium
has been calculated to be 2.1. As previously mentioned, R. Harun and M. K. Danquah [25] investigated the kinetics of enzymatic hydrolysis of pure culture of microalgae. However, their model did not consider pH effects on enzyme kinetics. Our finding indicates that microalgal biomass concentration, pH, and temperature influence significantly on glucose yield in the enzymatic hydrolysis of algal cellulose. Therefore, it is important to consider these variables in the kinetic model.
Increasing concentration of fermentable sugars in the enzymatic hydrolysis products is one of the significant challenges to boost the economic feasibility of the bioethanol production. Therefore, the microalgae loading strategy was used to obtain a concentrated sugar solution from the enzymatic hydrolysis of microalgal cellulose. The initial algae loading was 100 g/L with enzyme loading equal to 0.416 mg protein/mL at 50 °C and pH 5. After 72 h, the powder algae were attached with a concentration of 50 g/L every 24 h, without the addition of fresh cellulase enzyme. The experimental results demonstrated that cellulase could be used thrice without compromising on the glucose yield. Finally, the glucose concentration reached approximately 28 g/L. This amount is higher than the values reported in the most other papers [18,38,39]. The glucose derived from enzymatic hydrolysis of microalgal cellulose using this experiment, which used as feedstock for S. cerevisiae. The fermentation was carried out anaerobically at 30 °C and 150 rpm for 24 h. Time course of glucose consumption and ethanol production by S. cerevisiae from enzymatic hydrolysates of microalgal cellulose is depicted in Fig. 5. The obtained results demonstrated that yeast could produce 12.87 g/L ethanol from 28 g/L of glucose derived from microalgal cellulose after 24 h. This amount is higher than the values reported in the most other papers [17,18,26]. The ethanol yield was calculated to be 0.46 g/g glucose, which was 92% of the theoretical value.
4.3. Sensitivity analysis Sensitivity Analysis was carried out to explore the effecting kinetic parameters of the enzymatic hydrolysis of microalgal cellulose. The sensitivity indexes with respect to the final glucose concentration in the hydrolysis medium (initial microalgal biomass 50 g/L; pH 5; temperature 50 °C) were computed for each kinetic parameter using AQUASIM. The transformation of the sensitivity indexes with time demonstrates the relative importance of each kinetic parameter in the enzymatic hydrolysis of microalgal cellulose. The dynamics of sensitivity indexes of kinetic parameters are shown in Fig. 3. Fig. 3 (a, b) showed that k′3 and km3 are the most influential parameters during 72 h enzymatic hydrolysis. The enzymatic hydrolysis of cellulose into glucose involves the cooperative action of a mixture of cellulases (endoglucanases, exoglucanases, and β-glucosidases) [37]. k′3, and km3 correspond to the reaction 3 (cellobiose to glucose), which is catalyzed by β-glucosidases. Also, from Fig. 3, it is evident the sensitivity of glucose concentration with respect to the kinetic parameters increases from zero, achieves a maximum value at the different time, and then reduces again to zero. As it can be seen, the dependence of glucose concentration on the parameters k1IG, k2IG, k3IG and k1IG2 is different, whereas the dependence of glucose concentration on the other three parameters k′1, k′3, and km3 leads to a similar shape of the variations in glucose concentration, just with a different magnitude and sign. This means that variations enforced by variations in the parameters k′1 and k′3 can be approximately balanced by suitable variations in the parameter km3. The maximum in the sensitivity function of glucose concentration with respect to k′1 is approximately 0.64 and the minimum in the sensitivity functions of glucose concentration with respect to km3 is about −1.14. This means that, in linear approximation, a variation in k′1 can be compensated for
5. Conclusion In this study, enzymatic hydrolysis of mixed microalgae under varying conditions of microalgal biomass concentration, pH, and temperature with constant cellulase concentration was investigated. The effort has been exerted to evaluate the model to predict kinetic profiles of glucose, cellobiose and cellulose concentration in enzymatic hydrolysis over time. By sensitivity analysis, it was found that k′3 and km3 in the reaction of cellobiose breakdown to glucose are the most influential parameters in the enzymatic hydrolysis of algal cellulose. Moreover, obtaining concentrated fermentable sugar solution from the enzymatic hydrolysis step can lead to the economic feasibility of the bioethanol production. Our findings demonstrated the microalgae loading strategy as a simple, inexpensive, and flexible method to increase sugar concentration in hydrolysis medium. The results demonstrated that cellulase enzyme could be applied thrice without compromising on the glucose yield. In addition, after the microalgae loading experiment, glucose in enzymatic hydrolysates of microalgae was converted into ethanol using S. cerevisiae with the yield values of 0.46 g/g glucose.
( ) 0.64
by a variation in km3 that is a coefficient of 1.14 as magnitude. The negative sign of km3 indicates that the glucose concentration decreases with increasing values of km3. Afterwards, the changing final extents of glucose concentration (g/ L) with respect to the variation in each model parameter are 37
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[1] Mansouri A, Rihani R, Laoufi AN, Özkan M. Production of bioethanol from a mixture of agricultural feedstocks: biofuels characterization. Fuel 2016;185:612. [2] Smuga-Kogut M, Zgórska K, Kogut T, Kukiełka K, Wojdalski J, Kupczyk A, et al. The use of ionic liquid pretreatment of rye straw for bioethanol production. Fuel 2017;191:266. [3] Vassilev SV, Vassileva CG. Composition, properties and challenges of algae biomass for biofuel application: an overview. Fuel 2016;181:1. [4] Ullah K, Ahmad M, Sharma VK, Lu P, Harvey A, Zafar M, et al. Assessing the potential of algal biomass opportunities for bioenergy industry: a review. Fuel 2015;143:414. [5] Fasahati P, Liu JJ. Application of MixAlco® processes for mixed alcohol production from brown algae: economic, energy, and carbon footprint assessments. Fuel Process Technol 2016;144:262. [6] Shokrkar H, Ebrahimi S, Zamani M. Extraction of sugars from mixed microalgae culture using enzymatic hydrolysis: Experimental study and modeling. Chem Eng Commun 2017;204:1246. [7] Song M, Pham HD, Seon J, Woo HC. Marine brown algae: a conundrum answer for sustainable biofuels production. Renew Sust Energy Rev 2015;50:782. [8] Reddy HK, Muppaneni T, Patil PD, Ponnusamy S, Cooke P, Schaub T, et al. Direct conversion of wet algae to crude biodiesel under supercritical ethanol conditions. Fuel 2014;115:720. [9] Yao C, Ai J, Cao X, Xue S, Zhang W. Enhancing starch production of a marine green microalga Tetraselmis subcordiformis through nutrient limitation. Bioresour Technol 2012;118:438. [10] Brányiková I, Maršálková B, Doucha J, Brányik T, Bišová K, Zachleder V, et al. Microalgae—novel highly efficient starch producers. Biotechnol Bioeng 2011;108:766. [11] Ho S-H, Chen C-Y, Chang J-S. Effect of light intensity and nitrogen starvation on CO 2 fixation and lipid/carbohydrate production of an indigenous microalga Scenedesmus obliquus CNW-N. Bioresour Technol 2012;113:244. [12] Wargacki AJ, Leonard E, Win MN, Regitsky DD, Santos CNS, Kim PB, et al. An engineered microbial platform for direct biofuel production from brown macroalgae. Science 2012;335:308. [13] Yazdani P, Zamani A, Karimi K, Taherzadeh MJ. Characterization of Nizimuddinia zanardini macroalgae biomass composition and its potential for biofuel production. Bioresour Technol 2015;176:196. [14] Kumar S, Gupta R, Kumar G, Sahoo D, Kuhad RC. Bioethanol production from Gracilaria verrucosa, a red alga, in a biorefinery approach. Bioresour Technol 2013;135:150. [15] Golberg A, Vitkin E, Linshiz G, Khan SA, Hillson NJ, Yakhini Z, et al. Proposed design of distributed macroalgal biorefineries: thermodynamics, bioconversion technology, and sustainability implications for developing economies. Biofuels Bioprod Biorefin 2014;8:67. [16] Harun R, Danquah MK. Influence of acid pre-treatment on microalgal biomass for bioethanol production. Process Biochem 2011;46:304. [17] Harun R, Danquah MK, Forde GM. Microalgal biomass as a fermentation feedstock for bioethanol production. J Chem Technol Biotechnol 2010;85:199. [18] Ho S-H, Huang S-W, Chen C-Y, Hasunuma T, Kondo A, Chang J-S. Bioethanol production using carbohydrate-rich microalgae biomass as feedstock. Bioresour Technol 2013;135:191.
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Full Length Article
Enzymatic hydrolysis of microalgal cellulose for bioethanol production, modeling and sensitivity analysis
T
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Hanieh Shokrkar, Sirous Ebrahimi , Mehdi Zamani Biotechnology Research Center, Faculty of Chemical Engineering, Sahand University of Technology, Tabriz, Iran
G R A P H I C A L A B S T R A C T
A R T I C LE I N FO
A B S T R A C T
Keywords: Bioethanol Cellulose Enzymatic hydrolysis Kinetic Mixed microalgae Sensitivity analysis
A kinetic model was developed to describe the enzymatic hydrolysis of microalgal cellulose. In the kinetic model, the factors including product inhibition, temperature, and pH were considered. This model combined two reactions for hydrolyzing algal cellulose to cellobiose and glucose and one reaction for cellobiose breakdown to glucose. Results showed that the highest glucose yield (57%) was achieved at microalgal biomass concentration of 50 g/L, pH 5, and temperature of 50 °C. Moreover, the sensitivity analysis was carried out on each kinetic model parameter. This analysis indicated that k′3 and km3 in reaction R3 (cellobiose to glucose) are the most influential parameters during enzymatic hydrolysis of algal cellulose. Finally, the microalgal biomass loading experiment demonstrated that cellulase could be used thrice without compromising on the glucose yield. Fermentation of concentrated sugar medium with Saccharomyces cerevisiae produced ethanol (12.87 g/L) with yield (0.46 g ethanol/g glucose).
1. Introduction
technologies for conversion of other feedstock such as microalgae into biofuel have been considered. Algae grow quickly without need of soil and absorb carbon dioxide from atmosphere for photosynthesis process [6]. In addition, microalgae have short harvesting cycle compared with other feedstocks, which are harvested once or twice a year [4,7,8]. Some studies have reported high levels of carbohydrate accumulation up to 54.3% by microalgae under nitrogen limiting conditions [9,10].
Bioethanol is one of the renewable energy sources that can reduce fossil fuel consumption and environmental pollution [1,2]. Agricultural materials such as starch, corn, rice, wheat, sugar cane, sugar beet, and sweet sorghum are not prospective selections for bioethanol production as the human request for food has yet to be met [3–5]. Lately, process
⁎
Corresponding author. E-mail address: sirous.ebrahimi@epfl.ch (S. Ebrahimi).
https://doi.org/10.1016/j.fuel.2018.04.143 Received 27 April 2017; Received in revised form 28 February 2018; Accepted 25 April 2018 0016-2361/ © 2018 Elsevier Ltd. All rights reserved.
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Table 1 The reaction rates and mass balances. Stage
Rates
Cellulose → Cellobiose
R1 = Cellulose → Glucose
R2 =
E ⎛− a1 ⎞ A1 . e⎝ R.T ⎠ . [ECellulases] . [C] + ⎡ ⎛⎜1 + [G2 ] + [G] ⎞⎟ + [C] ⎤ . ⎡1 + K a2 + [H ] ⎤ ⎢ ⎥ ⎢ k1IG2 k1IG ⎠ K a1 ⎥ [H+] ⎦ ⎣⎝ ⎦ ⎣ E ⎛− a2 ⎞ R.T ⎠ . [ECellulases] . [C] A2 . e⎝ + ⎡ ⎛⎜1 + [G2] + [G] ⎞⎟ + [C]⎤ . ⎡1 + K a2 + [H ] ⎤ ⎢ ⎥ ⎢ k2IG2 k2IG ⎠ K a1 ⎥ [H+] ⎦ ⎣⎝ ⎦ ⎣
Cellobiose → Glucose
E ⎛− a3 ⎞ A3 . e⎝ R.T ⎠ . [ECellulases] . [G2]
R3 = Reaction rate constants
k′i =
Mass Balances
k′1 (h−1) k′2 (h−1) k′3 (h−1)
d[C] dt
Cellobiose:
Glucose:
= −R1−R2
d[G2] dt
d[G] dt
= 1.056R1−R3
= 1.116R2 + 1.053R3
+ ⎡k . ⎛⎜1 + [G] ⎞⎟ + [G ]⎤ . ⎡1 + K a2 + [H ] ⎤ 2⎥ ⎢ ⎢ m3 k3IG ⎠ K a1 ⎥ [H+] ⎝ ⎦ ⎣ ⎦ ⎣
E ⎛− ai ⎞ Ai . e⎝ R.T ⎠ K [H+] + 1 + a2 K a1 [H+]
( i= 1, 2, 3)
2. Materials and methods
Table 2 The estimated values of parameters of the model. Parameter
Cellulose:
Temperature (condition: pH 5)
pH (condition: Temperature 50 °C)
30 °C
40 °C
50 °C
4
5
6
1.12 1.30 1.10
3.18 4.10 3.80
8.76 10.71 8.60
3.56 4.35 3.49
8.76 10.71 8.60
2.73 3.34 2.68
2.1. Microalgae Mixed microalgae (collected from a freshwater located in Oskou, East Azarbayjan, Iran) have been precultured in our previous study [26], and then inoculated into glass photobioreactor with a working volume of 10 L, illuminated with eight white LED lamps with a light intensity of about 260 µmol. m−2. s−1. The aeration rate in the photobioreactor was 8 vvm. The temperature and pH were 25 ± 1 °C and 9, respectively. When the nitrogen source in the photobioreactor medium was depleted, the CO2 was bubbled into the medium with the rate of 0.1 vvm. The medium composition of microalgae was the same as explained in our previous paper [26]. At the end of the cultivation, the algae were harvested from the photobioreactor and then oven dried at 80 °C for 48 h. These dried algae were ground into powder by Planetary Ball Mill and consumed for enzymatic hydrolysis by cellulase.
Carbohydrates in microalgal biomass are chiefly cellulose without lignin. The absence of lignin makes hydrolysis of microalgae easier compared to lignocellulosic materials [11]. Some studies have examined the ethanol production using the pure culture of macroalgae [12–15] and microalgae [16–18]. Cultivation of microalgae in pure culture will increase operating costs because of the need for the sterile condition. Therefore, usage of a mixed microalgal culture dominates these problems [19,20]. Hydrolysis process for carbohydrates extraction from algae can be performed using acids or enzymes. Enzymatic hydrolysis has various advantages compared to acid hydrolysis, including low utility consumption, less corrosion problems, higher glucose yield without sugar-degradation and inhibitory products production. In contrast, the enzymatic hydrolysis increases the cost of producing ethanol [21,22]. Some researchers have investigated carbohydrate extraction from a pure culture of algae [12–18,23]. Besides, Hwang et al. investigated the different pre-treatments of both filamentous and cyclotella algal cells for bioethanol production [24]. To author’s awareness, there is only one research on the kinetics of enzymatic hydrolysis algal cellulose by R. Harun and M. K. Danquah [25] in which the kinetics parameters of hydrolysis was obtained using Michaelis–Menten’s model. However, their study did not consider pH effects on enzyme kinetics and sensitivity analysis of kinetic parameters. In addition, their study investigated the kinetics of enzymatic hydrolysis of a pure culture of algae of Chlorococcum sp. In the present study, the kinetic modeling and sensitivity analysis of enzymatic hydrolysis of microalgal cellulose using cellulase was studied. Furthermore, the microalgae loading strategy was used to obtain a concentrated sugar solution from the enzymatic hydrolysis step, leading to high volumetric bioethanol productivity, the principal factor affecting the cost-effectiveness of full-scale applications. Subsequently, the bioethanol yield of the fermentable sugars derived from enzymatic hydrolysis step was investigated through cultivating Saccharomyces cerevisiae yeast.
2.2. Enzymatic hydrolysis of microalgal cellulose Cellulase from Trichoderma reesei obtained from Novozymes, Denmark was used for enzymatic hydrolysis of algal cellulose. The enzymatic activity of this enzyme was 0.04 U/mg corresponding to 0.054 mg protein/mg. For the enzymatic hydrolysis experiments, the dried algal powder was loaded into citrate buffer with the concentration of 25, 50, 75, and 100 g/L. These samples were autoclaved at 121 °C for 15 min and then mixed with constant cellulase concentration (0.416 mg protein/mL) in a 100 mL-Erlenmeyer flask with 50 mL working volume. The effects of variation of temperature in the range of 30–50 °C and pH in the range of 4–6 on enzymatic hydrolysis were investigated. The Erlenmeyer flasks were incubated in a shaker at 150 rpm for 72 h. The analysis samples were taken at different times during enzymatic hydrolysis of algae. These samples were centrifuged at 4000×g, then the supernatant was taken and cellobiose and glucose concentration were measured.
2.3. Bioethanol production For bioethanol production, S. cerevisiae has been precultured in our previous study [26]. After microalgal biomass loading experiment, pH of the microalgae hydrolysate was adjusted to 6.5 to achieve an appropriate pH range for bioethanol production. Afterwards, 10% V/V of yeast pre-culture cells were added in the fermentation medium, which contained hydrolysates of microalgae. The fermentation experiment was performed anaerobically at 30 °C shaken at 150 rpm for 24 h. 31
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Fig. 1. Effect of pH on concentration of cellobiose, glucose, and glucose yield%; (a), pH 4, (b), pH 5, (c) pH 6; Hydrolysis conditions substrate concentration of 50 g/L and temperature of 50 °C.
2.4. Analytical procedures
Table 3 The estimated values of Ka1 and Ka2. Ka1 (mol/L) Ka2 (mol/L) pK a = −log[Ka]
2.91 × 10−5 4.8 × 10−6
pKa1 pKa2
The biomass concentration of the microalgae culture was measured base on dry weight. Determination of total suspended solids (TSS), Volatile suspended solids amount (VSS) and ash content of microalgae were the same as described in our previous study [26]. Residual concentration of nitrogen was measured using the colorimetric method according to Cataldo, D. et al. [27]. Determination of total carbohydrate of microalgae biomass was performed based on Hedge and Hofreiter method [28]. The cellulose content of microalgal biomass was
4.53 5.31
32
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Fig. 2. Effect of temperature on concentration of cellobiose, glucose, and glucose yield%; (a), 30 °C, (b), 40 °C (c) 50 °C; Hydrolysis conditions substrate concentration of 50 g/L and pH 5.
3. Theory
determined according to Mihranyan et al. method [29]. Determination of lipid and protein contents of microalgae were the same as described in our previous paper [20]. Cellulase concentration (mg protein/mL) was specified as described by Lowry [30]. The concentrations of ethanol, glucose, and cellobiose were analyzed using high-performance liquid chromatography with Aminex HPX-87P column. All experiments were conducted in duplicate. The yield of glucose and ethanol can be represented by the following equations.
Glucose yield % =
Extracted glucose (g) × 100 Total carbohydrate in algae (g)
(1)
Ethanol yield % =
produced ethanol (g) × 100 Extracted glucose from algae (g)
(2)
3.1. Kinetic model The kinetic model assumes that hydrolysis of cellulose occurs in three steps: the cellulose is hydrolyzed to soluble cellobiose, the cellulose is hydrolyzed to glucose, and cellobiose is hydrolyzed to glucose [31]. This model was used to predict concentrations of cellobiose and glucose during enzymatic hydrolysis of microalgal cellulose. Reaction scheme and mass balances for modeling enzymatic hydrolysis are depicted in Table 1. This scheme involved hydrolysis reactions of R1, R3, and R2. In some studies, R2 is ignored [25]. This model has been developed based on end-product inhibition. In these rate equations, k′i (i = 1, 2, 3) are the reaction rate constants (h−1); kiIG (i = 1, 2, 3) and kiIG2 (i = 2, 3) are inhibition constants of glucose and cellobiose on enzyme (g/L), respectively. km3 is cellobiose 33
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Fig. 3. Time course of the sensitivity functions of glucose concentration with respect to model parameters.
and total carbohydrate content of microalgae were 2.05 g/L, 1.56 g/L, 0.43 g/L, respectively. Therefore, the percentage of total carbohydrate was calculated to be about 27% of VSS (or approximately 21% of TSS). In addition, the protein and lipid content of biomass were 0.826 g/L and 0.30 g/L, or approximately 53% and 19% on the basis of VSS, respectively. Furthermore, the percentage of cellulose of microalgae was approximately 60% of total carbohydrate content.
saturation constants (g/L). [C], [G] and [G2] are concentrations of cellulose, glucose, and cellobiose (g/L), respectively. In addition, [ECellulase] is the concentration of cellulase enzyme (mg protein/mL). [H+] is the concentration of hydrogen ions (mol/L). [H+] can be calculated using the equation [H+] = 10-pH. Also, Ka (1, 2) is the acid dissociation constant (mol/L). In Arrhenius equation, Ea is the activation energy (J/mol), A is Arrhenius constant (h−1), R is gas constant, and T is temperature (K). In this study, the AQUASIM software was applied as a tool to model hydrolysis of microalgal cellulose using cellulase. The kinetic model parameters were calculated using the AQUASIM by minimizing the sum of the squares of the weighted deviations ( χ2 ) among measurements and calculated model results [32].
4.2. Calculation of the values of kinetic parameters Microalgae consist of various types of carbohydrates, which are often accumulated in the cell wall. Therefore, disruption of the microalgae cell walls is essential for using it as a carbon source during the fermentation process. In order to determine the kinetic parameters, the effects of microalgae biomass concentration, pH, and temperature on enzymatic hydrolysis of mixed microalgal biomass with constant cellulase concentration for 72 h were investigated. The experimental results were evaluated by solving differential equations using AQUASIM software. Afterwards, the model parameters were estimated by minimizing χ2 between measurements and calculated model results. The estimated parameters are shown in Table 2. The values of km3, kiIG (i = 1, 2, 3) and kiIG2 (i = 2, 3) were the same as reported by Zheng et al. [33]. In order to determine the kinetic parameters (Table 2), in the first stage, the effects of microalgal biomass concentration in the range of 25–100 g/L (pH 5; temperature 50 °C) on sugar production were investigated. The results showed that the increase in the microalgal biomass concentration from 25 to 100 g/L leads to a decrease in enzymatic hydrolysis rate. The highest glucose yield was about 57% after 72 h, while the substrate concentration of 50 g/L was used. When the microalgae biomass concentration was increased from 50 to 100 g/L, the glucose yield decreased from 57% to about 45%. Therefore, microalgae biomass concentration is a significant factor, which can be optimized to obtain the highest glucose yield. When considering both the glucose yield and operating cost, the most appropriate microalgae biomass concentration is 50 g/L. In the second stage, the variation of pH in the range of 4–6 (microalgal biomass concentration 50 g/L; temperature 50 °C) were
3.2. Sensitivity analysis Sensitivity Analysis is an instrument to analyze the effect of various values of a set of parameters on specific dependent variable under certain specific situations. By showing the model behavior responds to change in parameter values, sensitivity analysis is a useful instrument in model evaluation and model building. This analysis lets us understand the effect of different parameters on system behavior and that can be used for identifies a leverage point in the system, a parameter whose specific value can change the behavior of the system significantly. The sensitivity function of the model parameter can be expressed as:
δG,P =
P ∂G . G ∂P
(3)
where G is glucose concentration and P is model parameter (k′1, k′2 , k′3, km3, k1IG, k2IG, k3IG and k1IG2) [32]. 4. Results and discussion 4.1. Microalgal biomass The experimental results showed that algal biomass concentration increased from 0.12 to 1.97 g/L as nitrogen source decreased from 0.12 to 0 g/L after 29 days. At the end of the cultivation (37 days), TSS, VSS 34
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Fig. 4. Effect of kinetic parameter variation on final glucose concentration.
demonstrated that an increase in pH (from 4 to 5) leads to the higher glucose yield of approximately 57%, and then the extent of glucose yield is decreased. The estimated values of Ka1 and Ka2 are presented in Table 3. As seen from the Table 3, the best-fit value for Ka1 and Ka2 were estimated to be 2.91 × 10−5 mol/L and 4.8 × 10−6 mol/L, respectively. Afterwards, pKa1 and pKa2 were calculated to be 4.53 and 5.31, respectively. Enzymes have been reported to have optimum activity within the pH range of pKa1 to pKa2 [34]. Therefore, it can be said that cellulase has optimum activity within the pH range of 4.53–5.31. The similar results were observed R. Harun and M. K. Danquah [25], they achieved maximum glucose yield of approximately 65% in the enzymatic hydrolysis microalgae of Chlorococcum sp using cellulase at pH in the range of 4.5–5.5.
investigated to obtain the pH dependence of the kinetic rates. The comparison between measured and predicted concentration of cellobiose, glucose and glucose yield time-course at different pH are demonstrated in Fig. 1. The activity of the enzyme and binding ability of the enzyme to the substrate are affected by pH variation. The obtained results according to Fig. 1 showed that the hydrolysis at pH 5 resulted in the highest production rate of glucose. Moreover, from the comparison of the values of reaction rate constants obtained for each pH (Table 2), it was observed that the reaction rate constants at pH 5, are higher compared to pH 4 and 6, and higher reaction rate values show faster reaction rates. Basic or acidic conditions could degrade the construction of the enzyme [25]. Therefore, pH of the enzymatic hydrolysis medium has been considered as a major factor to improve the glucose yield. Fig. 1 35
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Fig. 4. (continued)
enzymatic hydrolysis, the glucose yield increased from approximately 21 to 57% with the temperature increasing from 30 to 50 °C. Cellulase has been reported to have optimized activity in the temperature range of 40–50 °C [25,35,36], and our results, which is for the case of microalgal cellulose, corroborate that. From Fig. 2, it is evident that the temperature value of 50 °C gives the highest production rate of glucose. In addition, from the comparison of the values of reaction rate constants under different temperatures (Table 2), it was detected that the reaction rate constants at 50 °C are higher compared to other temperatures (30 °C and 40 °C), and higher reaction rate constants reveal faster hydrolysis of microalgal cellulose. Finally, Figs. 1 and 2 show that the simulation results are in good conformity with the experimental results of enzymatic hydrolysis of microalgal cellulose. Sum of the squares of the weighted deviations ( χ2 )
In the third stage, the variations in sugar production in the enzymatic hydrolysis of microalgae at different temperatures (30, 40, 50 °C) with microalgae biomass concentration of 50 g/L and pH 5 were investigated to obtain the temperature dependence of the kinetic rates. As previously represented in Table 1, the effect of temperature was studied using Arrhenius equation. The A1, A2, and A3 values were 5.46 × 1014 h−1, 1.52 × 1015 h−1 and 7.28 × 1014 h−1, respectively. In addition, the Ea1, Ea2, and Ea3 values were estimated to be 83.70 kJ/ mol, 85.85 kJ/mol, and 83.84 kJ/mol, respectively. The comparison between measured and predicted concentration of cellobiose, glucose and glucose yield time-course at different temperatures are depicted in Fig. 2. It can be observed that the highest glucose yield was about 57% after 72 h, while the temperature of 50 °C was applied. At the end of 36
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demonstrated in Fig. 4. Vertical lines illustrate the values of the nominal kinetic parameter. As shown in Fig. 4(a, b), the increase in reaction rate constants k′1 and k′3 leads to the higher glucose concentration until a critical value, and then the glucose concentration is constant. It can be observed that a 2-fold increase in k′1 (from 2 to 4) results in an increase of 10% in the extent of glucose concentration, whereas the similar change in k′3 (from 2 to 4) results in approximately 20% increase. This observation is in accordance with the Fig. 3(a). In addition, Fig. 4(c) showed that as the value of km3 decreases, final glucose concentration increases. As observed from the final glucose concentration versus k1IG, k2IG, k3IG, and k1IG2 (Fig. 4(d, e, f, g)), if k1IG, k2IG, k3IG, and k1IG2 are increased, the yield of glucose on the hydrolysis of microalgal cellulose increases. Finally, it can be said that nominal values of most of the parameters lie at the optimum value, and change in these parameter values results in a reduction in the extent of glucose concentration. Fig. 5. Time course of glucose consumption and ethanol production by S. cerevisiae from enzymatic hydrolysates of microalgal cellulose.
4.4. Bioethanol production from concentrated sugar medium
has been calculated to be 2.1. As previously mentioned, R. Harun and M. K. Danquah [25] investigated the kinetics of enzymatic hydrolysis of pure culture of microalgae. However, their model did not consider pH effects on enzyme kinetics. Our finding indicates that microalgal biomass concentration, pH, and temperature influence significantly on glucose yield in the enzymatic hydrolysis of algal cellulose. Therefore, it is important to consider these variables in the kinetic model.
Increasing concentration of fermentable sugars in the enzymatic hydrolysis products is one of the significant challenges to boost the economic feasibility of the bioethanol production. Therefore, the microalgae loading strategy was used to obtain a concentrated sugar solution from the enzymatic hydrolysis of microalgal cellulose. The initial algae loading was 100 g/L with enzyme loading equal to 0.416 mg protein/mL at 50 °C and pH 5. After 72 h, the powder algae were attached with a concentration of 50 g/L every 24 h, without the addition of fresh cellulase enzyme. The experimental results demonstrated that cellulase could be used thrice without compromising on the glucose yield. Finally, the glucose concentration reached approximately 28 g/L. This amount is higher than the values reported in the most other papers [18,38,39]. The glucose derived from enzymatic hydrolysis of microalgal cellulose using this experiment, which used as feedstock for S. cerevisiae. The fermentation was carried out anaerobically at 30 °C and 150 rpm for 24 h. Time course of glucose consumption and ethanol production by S. cerevisiae from enzymatic hydrolysates of microalgal cellulose is depicted in Fig. 5. The obtained results demonstrated that yeast could produce 12.87 g/L ethanol from 28 g/L of glucose derived from microalgal cellulose after 24 h. This amount is higher than the values reported in the most other papers [17,18,26]. The ethanol yield was calculated to be 0.46 g/g glucose, which was 92% of the theoretical value.
4.3. Sensitivity analysis Sensitivity Analysis was carried out to explore the effecting kinetic parameters of the enzymatic hydrolysis of microalgal cellulose. The sensitivity indexes with respect to the final glucose concentration in the hydrolysis medium (initial microalgal biomass 50 g/L; pH 5; temperature 50 °C) were computed for each kinetic parameter using AQUASIM. The transformation of the sensitivity indexes with time demonstrates the relative importance of each kinetic parameter in the enzymatic hydrolysis of microalgal cellulose. The dynamics of sensitivity indexes of kinetic parameters are shown in Fig. 3. Fig. 3 (a, b) showed that k′3 and km3 are the most influential parameters during 72 h enzymatic hydrolysis. The enzymatic hydrolysis of cellulose into glucose involves the cooperative action of a mixture of cellulases (endoglucanases, exoglucanases, and β-glucosidases) [37]. k′3, and km3 correspond to the reaction 3 (cellobiose to glucose), which is catalyzed by β-glucosidases. Also, from Fig. 3, it is evident the sensitivity of glucose concentration with respect to the kinetic parameters increases from zero, achieves a maximum value at the different time, and then reduces again to zero. As it can be seen, the dependence of glucose concentration on the parameters k1IG, k2IG, k3IG and k1IG2 is different, whereas the dependence of glucose concentration on the other three parameters k′1, k′3, and km3 leads to a similar shape of the variations in glucose concentration, just with a different magnitude and sign. This means that variations enforced by variations in the parameters k′1 and k′3 can be approximately balanced by suitable variations in the parameter km3. The maximum in the sensitivity function of glucose concentration with respect to k′1 is approximately 0.64 and the minimum in the sensitivity functions of glucose concentration with respect to km3 is about −1.14. This means that, in linear approximation, a variation in k′1 can be compensated for
5. Conclusion In this study, enzymatic hydrolysis of mixed microalgae under varying conditions of microalgal biomass concentration, pH, and temperature with constant cellulase concentration was investigated. The effort has been exerted to evaluate the model to predict kinetic profiles of glucose, cellobiose and cellulose concentration in enzymatic hydrolysis over time. By sensitivity analysis, it was found that k′3 and km3 in the reaction of cellobiose breakdown to glucose are the most influential parameters in the enzymatic hydrolysis of algal cellulose. Moreover, obtaining concentrated fermentable sugar solution from the enzymatic hydrolysis step can lead to the economic feasibility of the bioethanol production. Our findings demonstrated the microalgae loading strategy as a simple, inexpensive, and flexible method to increase sugar concentration in hydrolysis medium. The results demonstrated that cellulase enzyme could be applied thrice without compromising on the glucose yield. In addition, after the microalgae loading experiment, glucose in enzymatic hydrolysates of microalgae was converted into ethanol using S. cerevisiae with the yield values of 0.46 g/g glucose.
( ) 0.64
by a variation in km3 that is a coefficient of 1.14 as magnitude. The negative sign of km3 indicates that the glucose concentration decreases with increasing values of km3. Afterwards, the changing final extents of glucose concentration (g/ L) with respect to the variation in each model parameter are 37
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References
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