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Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm
i n t e r n a t i o n a l j o u r n a l o f h y d r o g e n e n e r g y x x x ( 2 0 1 8 ) 1 e1 2
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Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm Ralph Rolly Gonzales a, Jun Seok Kim b, Sang-Hyoun Kim c,* a
Department of Environmental Engineering, Daegu University, Gyeongbuk 38453, Republic of Korea Department of Chemical Engineering, Kyonggi University, Suwon 16227, Republic of Korea c School of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Republic of Korea b
article info
abstract
Article history:
Pretreatment of the empty fruit brunch (EFB) from oil palm was investigated for H2
Received 21 March 2018
fermentation. The EFB was hydrolyzed at various temperatures, H2SO4 concentrations, and
Received in revised form
reaction times. Subsequently, the acid-hydrolysate underwent enzymatic saccharification
26 July 2018
under various temperature, pH, and enzymatic loading conditions. Response surface
Accepted 6 August 2018
methodology derived the optimum sugar concentration (SC), hydrogen production rate
Available online xxx
(HPR), and hydrogen yield (HY) as 28.30 g L1, 2601.24 mL H2 L1d1, and 275.75 mL H2 g1 total sugar (TS), respectively, at 120 C, 60 min of reaction, and 6 vol% H2SO4, with the
Keywords:
combined severity factor of 1.75. Enzymatic hydrolysis enhanced the SC, HY, and HPR to
Biohydrogen
34.52 g L1, 283.91 mL H2 g1 TS, and 3266.86 mL H2 L1d1, respectively, at 45 C, pH 5.0,
Dilute acid hydrolysis
and 1.17 mg enzyme mL1. Dilute acid hydrolysis would be a viable pretreatment for bio-
Enzyme hydrolysis
hydrogen production from EFB. Subsequent enzymatic hydrolysis can be performed if
Saccharification
enhanced HPR is required.
Lignocellulosic biomass
© 2018 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Response surface methodology
Introduction Lignocellulosic biomass is a cost-effective and environmentfriendly alternative energy source, as compared to fossil fuels which are non-renewable and contribute to greenhouse gas emissions and global warming [1,2]. The use of lignocellulosic biomass for bioenergy generation has the potential to mitigate fossil fuel depletion and reduce dependency on fossil fuels. Furthermore, alternative energy sources significantly reduce greenhouse gas emissions and problems associated with waste management and pollution. This type of biomass
is a typical byproduct of agricultural processes. Thus, abundance and renewability are not limitations for its use as feedstock for the production of biofuels such as biogas, biomethane, syngas, bioethanol, and biodiesel [3]. Hydrogen (H2) is an environmentally-friendly and energyefficient biofuel and has attracted significant interest in recent years [4e6]. Dark H2 fermentation from a variety of biomass sources has been performed using pure microorganism strains or mixed microbial consortiums [7e11]. Optimization of the fermentation process is important for achieving maximum production performance at minimal cost. This entails enhancement of the pretreatment process,
* Corresponding author. School of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Republic of Korea. E-mail address: [email protected] (S.-H. Kim). https://doi.org/10.1016/j.ijhydene.2018.08.022 0360-3199/© 2018 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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during which fermentable monomeric sugars are obtained for subsequent fermentation. Lignocellulosic materials are composed of complex polymeric structures of cellulosic polymers, lignin, and other materials, such as ash and extractives [12e14]. Pretreatment is required to decompose the carbohydrate-lignin linkages, which cause recalcitrant properties in the biomass [15]. Once the complex linkages are broken from the pretreatment, the cellulose and hemicellulose components can be accessed and utilized as feedstock for biofuel production [16,17]. In this particular study, the empty fruit bunch (EFB) of oil palm was chosen as the substrate due to its abundance, cost, and carbohydrate content, which all contributed to its potential as a renewable energy source [18]. Dilute acid hydrolysis is a popular pretreatment method for lignocellulosic biomass [12]. In comparison to concentrated acid hydrolysis, dilute acid hydrolysis is relatively economical and environmentally-friendly. In both acid pretreatment processes, the biomass is subjected to the same thermal and acidic physicochemical conditions to obtain a monomeric sugar-rich solution. Dilute acid hydrolysis is controlled by a number of factors, including hydrolysis temperature, time, dilute acid concentration, and solid/liquid (S/L) ratio. These factors contribute to the combined severity factor (CSF), a parameter that represents the strength or harshness of the hydrolysis process [19]. The CSF can be obtained using Eq. (1) [19]: Th 100 pH CSF ¼ log txe 14:75
(1)
where Th and t are the hydrolysis temperature (in C), and reaction time (in min), respectively. Higher CSF values indicate harsher hydrolysis conditions, which may lead to increased waste production, higher pretreatment costs, and decomposition of the monomeric sugars into byproducts such as 5-hydroxymethylfuraldehyde, furaldehyde, formic acid, and levulinic acid [20e22]. To further decompose the biomass, enzyme saccharification can be performed after dilute acid hydrolysis. Combined hydrolysis represents an efficient method for obtaining fermentable monomeric sugars from lignocellulosic biomass, as demonstrated in previous studies [23,24]. However, this combined pretreatment method is not usually used for dark H2 fermentation studies. Furthermore, optimization of the enzymatic hydrolysis parameters remains an important issue, since no fixed set of pretreatment conditions can be used for all types of lignocellulosic biomass. Based on the biomass used, the following factors may significantly affect the efficiency of enzymatic pretreatment: temperature, pH, and enzyme loading. Response surface methodology (RSM) is used to design experimental procedures, generate models, evaluate the significance of independent variables, and optimize a response influenced by several variables. RSM can determine the optimal process conditions and identify the limit of a response based on the set experimental conditions by developing a model relating a process response to various factors [25,26]. In this method, interactions among the variables and the consequent effects are used for optimization. Furthermore,
the optimal point can be deduced even without experimental data through RSM [27,28]. RSM has been performed previously in a number of H2 fermentation optimization studies [26e35]. However, RSM has not been previously employed for combined dilute acid and enzymatic hydrolysis, thus, it was performed and investigated in this study. Furthermore, a limited number of studies on enzymatic hydrolysis as a pretreatment process for H2 fermentation are available, since this method is mostly used for bioethanol [36] and biomethane [37] production. To the best of the authors' knowledge, there are no previous studies involving statistical tools to optimize the conditions for both dilute acid and enzymatic hydrolysis for lignocellulosic biomass. Furthermore, this study demonstrates a holistic pretreatment and H2 fermentation approach, wherein at the end of the saccharification process, the dilute acid and enzymatic hydrolysates are combined together, prior to use as feed during dark H2 fermentation. This study then aims to bring light to the optimum conditions for sequential dilute acid and enzymatic hydrolysis for lignocellulosic biomass for maximum sugar recovery from the biomass, as well as maximum H2 production and yield during the subsequent fermentation. These are important to be determined for maximum efficiency of the dark fermentative H2 production. In this study, RSM was used to develop a central composite design (CCD) for the determination of optimal operating conditions for dilute acid and enzymatic hydrolysis pretreatments for maximizing monomeric sugar yield and subsequent H2 fermentation. Hydrolysis temperature, H2SO4 concentration, and hydrolysis time were first optimized to increase sugar concentration and H2 production from the dilute acid pretreatment of the EFB of oil palm. Control variables for enzymatic hydrolysis (temperature, pH, and enzyme loading) were then optimized to increase sugar concentration and H2 production.
Experimental Test lignocellulosic biomass EFB pellets obtained from local agricultural sources in Malaysia were used as the test biomass in this study. The EFB composition was measured according to the analytical procedure recommended by the National Renewable Energy Laboratory [38]. Table 1 shows the composition of the biomass on a dry weight basis.
Table 1 e Carbohydrate, lignin, ash, and extractives content in the empty fruit bunch of oil palm. Component Glucan Xylan Arabinan Lignin Ash Extractives
% 38.31 ± 1.01 11.09 ± 0.24 0.13 ± 0.01 9.37 ± 0.03 39.82 ± 2.05 1.43 ± 0.16
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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Inoculum
Response surface methodology
Granular sludge sourced from an up flow anaerobic sludge blanket reactor (UASB) in South Korea was used as the inoculum in this study. The sludge contains a number of H2-producing bacteria strains, mostly Clostridium [39]. The sludge exhibited the following properties: pH 6.8; 12.6 g volatile suspended solids (VSS) L1; and 22.6 g total suspended solids (TSS) L1. The sludge was subjected to a 90 C heat treatment for 30 min [40,41] prior to use such that only anaerobic H2-producing bacteria remained in the sludge.
A full factorial CCD with replicates on the center and axial center points for three factors was used in this study, as shown in Table 2. A total of 20 experimental trials were performed, eight trials for cubic points, six for axial points, and six center point replicates, as shown in Table 2. The individual and synergistic effects of the three variables tested on dilute acid and enzymatic hydrolysis were investigated. The variables were coded according to Eq. (2) [27]: xi ¼
Xi X*i Dxi
(2)
Table 2 e Experimental design for full factorial central composite design. Run
Code Values X1
DILUTE ACID HYDROLYSIS 1 0 2 1 3 0 4 1 5 1 6 1 7 1 8 0 9 1 10 0 11 1 12 1 13 1.68 14 0 15 0 16 1.68 17 0 18 0 19 0 20 0
X4 ENZYMATIC HYDROLYSIS 1 0 2 1 3 0 4 1 5 1 6 1 7 1 8 0 9 1 10 0 11 1 12 1 13 1.68 14 0 15 0 16 1.68 17 0 18 0 19 0 20 0
Real Values
CSF
X2
X3
Temperature ( C)
Time (min)
Acid (vol%)
0 1 0 1 1 1 1 0 1 0 1 1 0 0 0 0 1.68 0 0 1.68
0 1 0 1 1 1 1 0 1 0 1 1 0 1.68 0 0 0 1.68 0 0
100 80 100 80 80 120 120 100 80 100 120 120 133.64 100 100 66.36 100 100 100 100
45 30 45 60 60 30 60 45 30 45 60 30 45 45 45 45 19.77 45 45 70.23
5 4 5 6 4 4 6 5 6 5 4 6 5 6.68 5 5 5 3.32 5 5
1.12 0.15 1.11 0.93 0.41 1.25 2.09 1.22 0.65 1.16 1.51 1.75 2.15 1.47 1.16 0.25 0.85 0.64 1.17 1.34
X5
X6
Temperature ( C)
pH
Enzyme (mg mL¡1)
0 1 0 1 1 1 1 0 1 0 1 1 0 0 0 0 1.68 0 0 1.68
0 1 0 1 1 1 1 0 1 0 1 1 0 1.68 0 0 0 1.68 0 0
45 30 45 30 30 60 60 45 30 45 60 60 70.23 45 45 19.77 45 45 45 45
5 3 5 7 7 3 7 5 3 5 7 3 5 5 5 5 1.64 5 5 8.36
0.75 0.50 0.75 1.00 0.50 0.50 1.00 0.75 1.00 0.75 0.50 1.00 0.75 1.17 0.75 0.75 0.75 0.33 0.75 0.75
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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where Dxi is the step size and xi, Xi, and X are the coded value of the ith variable, uncoded value of the ith variable, and uncoded value of the ith variable at the center point of the investigated area, respectively.
Dilute acid hydrolysis of oil palm EFB The EFB pellets were milled to obtain particles 1e2 mm in size. The temperature (X1), H2SO4 concentration (X2), and hydrolysis time (X3) were the three factors considered in the experimental design, with the following central values: 100 C; 5% H2SO4 (Duksan Pure Chemicals, Korea); and 45 min of reaction time for X1, X2, and X3, respectively. EFB was added into the hydrolysis vessel at a concentration of 10 g L1 [42]. Hydrolysis was performed in an autoclave (SK401, Yamato Scientific Co., Ltd.) at a pressure of 0.9 MPa.
UVeVis Mini 1240, Shimadzu, Japan) at 480 nm. Concentrations of soluble metabolic products (SMPs), or byproducts of the pretreatment and fermentation processes, were determined using an Aminex-87H (Bio-Rad Laboratories, USA) column-equipped HPLC with a UV detector (Waters 2487, USA). A standard procedure was followed to measure the enzyme filter paper activity [47]. Chemical oxygen demand (COD), VSS, and TSS were also measured using standard methods [48]. Gas content was analyzed using a gas chromatography (SRI Instruments, USA) equipped with thermal conductivity detector (TCD) and a 13 mole sieve packed-1.8 m stainless steel column. N2 gas (99% purity) was used as the carrier gas. The temperatures of the column, detector, and injector were maintained at 80 , 90 , and 25 C, respectively.
Assay Enzymatic hydrolysis of the lignocellulosic biomass After determination of the optimal dilute acid hydrolysis conditions, the EFB residue collected after dilute acid hydrolysis was first washed and dried prior to enzymatic hydrolytic saccharification. Thermophilic cellulase (Celluclast 1.5L®, Sigma-Aldrich, Merck, MO, USA) [43] sourced from Trichoderma reesei ATTC 26921, with protein concentration and average activity of 79 mg enzyme mL1 and 65 filter paper unit (FPU)/mL, respectively [44], was used in this study. The saccharification temperature (X4), saccharification pH (X5), and enzyme loading (X6) were the three independent factors whose central values were 45 C, 5, and 0.75 mg enzyme mL1, respectively. The total hydrolysates of EFB obtained from both dilute acid and enzymatic hydrolysis were combined prior to fermentation.
Batch H2 fermentation For H2 fermentation, 100-mL serum bottles were used as batch reactors and 6 mL of the hydrolysate solutions obtained after pretreatment were added to the serum bottle and diluted to 30 mL with distilled water. Subsequently, 5 mL of the anaerobic sludge was added and minerals were supplied to the reactors by adding 5 mL of mineral solution, the concentrations of which were adjusted according to previous studies [13,23,42,45]. The resultant solutions had 40 mL of total working volume and an initial pH of 7.0e7.5, according to a previous study [13]. Anaerobic conditions were obtained when the reactors were purged with N2 gas, after which the reactors were agitated at 150 rpm and 35 C for 72 h. All trials were performed in duplicate.
Analysis An Aminex HPX-87P (Bio-Rad Laboratories, USA) columnequipped high-performance liquid chromatograph (HPLC, Waters 717, Waters, USA) with a refractive index (RI) detector (Waters 410, Waters, USA) was used to determine hydrolysate glucose and xylose concentrations. Total monomeric sugar concentration was analyzed using the phenol-sulfuric acid colorimetric method [46] with an ultravioletevisible (UVevis) spectrophotometer (Shimadzu
The production of H2 was plotted as a function of time, and an adapted Gompertz equation (Eq. (3)) was used to estimate the following parameters: maximum H2 production rate, maximum H2 volume, H2 production, and H2 production yield [49,50]. Eq. (3) can be written as: RH ðl tÞ þ 1 H ¼ P$exp exp P
(3)
where H, P, RH, l, and t are the cumulative H2 volume (mL), H2 production potential (mL), H2 production rate (HPR, mL h1), lag time (h), and time (h), respectively. The volumetric HPR (L H2 L1 h1) and hydrogen yield (HY, mL H2 g biomass1) were calculated from the RH, P, reactor volume, and amount of monomeric sugar substrate. The responses of the independent variables governing the dilute acid and enzymatic hydrolysis were correlated using the following general quadratic equation [32,51]: Y ¼ bo þ
k X i¼1
bi Xi þ
k X
bii X2i þ
X bij Xi Xj
i¼1
(4)
i
where Y, bo, bi, bii, and bij are the response, y-intercept, linear coefficient, quadratic coefficient, and interactive coefficients, respectively. Statistical analysis and modelling were performed using Design-Expert (Stat-Ease, MN, USA).
Results and discussion Dilute acid hydrolysis optimization The dilute acid hydrolysis efficiencies at various temperatures, reaction times, and acid concentrations are listed in Table 3. Regression equations for the sugar concentration (SC, g L1), HPR, and HY are shown in the supplementary section (S. Eqs. 1e3). High regression coefficient values (R2) over 0.94 were obtained, indicating that the regression models represented the experimental data well. The ANOVA results showed that the computed F-values (41.17, 17.18, and 187.11 for SC, HY, and HPR, respectively) are greater than 2.76, or the tabular F-value at the 5% confidence interval. Furthermore, the low P values
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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Table 3 e Sugar concentration, soluble metabolic products production, and hydrogen production from dilute acid hydrolysis of empty fruit bunch of oil palm. Trial Temperature Time Acid CSF Total organic Furaldehyde 5-HMFb Sugar H2 Yield H2 ( C) (min) (vol%) acida (g L1) (g L1) (g L1) concentration (mL H2 g1 Production (g L1) biomass) Rate (mL H2 L1d1) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 a b
100 80 100 80 80 120 120 100 80 100 120 120 133.64 100 100 66.36 100 100 100 100
45 30 45 60 60 30 30 45 30 45 60 60 45 45 45 45 19.77 45 45 70.23
5 4 5 6 4 4 6 5 6 5 4 6 5 6.68 5 5 5 3.32 5 5
1.12 0.15 1.11 0.93 0.41 1.25 2.09 1.22 0.65 1.16 1.51 1.75 2.15 1.47 1.16 0.25 0.85 0.64 1.17 1.34
5.62 4.98 5.07 5.23 4.76 5.61 5.86 4.71 4.93 5.11 5.28 5.63 7.18 5.21 4.56 5.29 4.32 3.77 5.49 6.83
3.53 3.71 4.03 3.64 3.44 4.03 2.25 4.17 2.36 4.97 5.63 8.23 6.82 6.02 5.78 4.24 4.88 2.91 5.15 5.64
1.31 0.84 0.82 0.71 0.58 0.63 1.59 0.79 0.85 0.92 1.01 1.11 1.48 0.99 0.91 0.85 0.56 0.60 0.71 0.93
24.67 20.35 20.63 20.86 19.83 14.38 17.94 26.10 16.55 20.20 17.95 28.30 19.83 25.09 15.30 20.20 18.10 22.35 11.72 21.92
251.63 215.93 218.27 209.45 203.41 155.89 179.70 266.31 166.52 217.04 181.11 275.75 214.33 254.29 175.47 211.81 199.55 231.82 139.55 221.38
2069.24 1464.73 1500.97 1456.38 1344.54 747.23 1074.61 2316.90 918.64 1461.40 1083.64 2601.24 1416.72 2126.71 894.90 1426.19 1203.95 1727.06 545.18 1617.55
The sum of acetate, formate, and propionate species after dilute acid hydrolysis. 5-hydroxymethylfuraldehyde.
(SC: 0.0016; HY: 0.0083; HPR: 0.002) obtained indicate that the regression was statistically significant. Three-dimensional surface plots, which model the synergistic effects of two variables when a third variable is held constant, are shown in Fig. 1. The surface plots show that temperature, reaction time, and dilute acid concentration all exerted significant individual influences on the sugar concentration during the dilute acid hydrolysis, which in turn influenced H2 production. These results further indicate that all three factors influence the combined severity of the dilute acid pretreatment, as shown in Eq. (2). The CSF of each experimental condition was calculated, and the results are listed in Table 2. Increasing the severity factor beyond the optimal range could decrease sugar recovery as excessive degradation of the sugar can occur [52]. Sugar recovery from the biomass, as well as H2 production and yield, can be reduced at harsher conditions, such as higher temperatures and acidity, which correspond to higher CSF values. Park et al. reported that, at CSF values exceeding 2.5, the amount of monomeric sugars decreased while the concentrations of SMPs increased [27]. The SMPs are either organic acids, such as levulinic, formic, and acetic acids, or furan aldehydes, such as furaldehyde and 5-hydroxymethylfuraldehyde (5-HMF), which can be formed during both acid hydrolysis and fermentation as a degradation byproduct of the carbohydrate species. These SMPs, especially the furan aldehydes, can inhibit fermentative H2-producing microorganisms [53]. Thus, these compounds must be removed from the hydrolysate prior to fermentation to avoid inhibitory effects. The severity factors of all dilute acid pretreatment conditions were below 2.5 in this study, within the optimal range of 1.7e2.2, under which maximum sugar concentration can be obtained [54].
Temperature, reaction time, and pH all contributed to the severity of the dilute acid hydrolysis. Therefore, at extreme values of these parameters, partial degradation occurs and the formation of SMPs increased, which was detrimental to the final sugar concentration and subsequent H2 production. The highest SC of 28.30 g L1 was obtained under the following conditions: 120 C, 60 min reaction, and 6 vol % H2SO4, with a CSF of 1.75. In this study, due to the CSF values within acceptable limit, no serious accumulation of inhibitory compounds was observed. Under these optimum conditions, SMPs were only formed in small quantities. However, the SC dropped while the concentrations of the byproducts increased at higher CSF values, despite remaining within the optimum range. Table 3 shows the concentrations of the SMPs after dilute acid hydrolysis. Increased concentrations of SMPs indicate that the monomeric sugars from the biomass were liberated from the complex lignocellulosic structure. However, the severity of the pretreatment caused the sugars to be further degraded. Organic acids and furan compounds are known to be degradation byproduct of polysaccharides during dilute acid hydrolysis; however, among the known organic acids, butyric acid is not among the hydrolysis byproducts. In Table 3 it can be seen that all the runs exhibited low SMP concentrations. Thus, degradation did not occur to a great extent during pretreatment, primarily due to the reasonable CSF values which are all within the optimum range, indicating that the dilute acid hydrolysis conditions performed in this study were not excessively harsh, and it is expected that H2 fermentation would not be greatly affected by these compounds. Hydrogen production using the dilute acid hydrolysates was directly correlated to sugar concentration, such that the optimum values of HPR (2601.24 mL H2 L1d1) and HY
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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Fig. 1 e Three-dimensional surface plots of the quadratic model for sugar concentration (g L¡1), H2 production rate (mL H2 L¡1 d¡1), and H2 yield (mL H2 g biomass¡1) observed after dilute acid hydrolysis of the empty fruit bunch of oil palm.
(275.75 mL H2 g1 biomass) were obtained under the same conditions at which the optimum sugar concentration was achieved. This is because the hydrolysate solutions contained the highest amount of soluble monomeric sugars, and the concentrations of the SMPs were also not high, as shown in Tables 2 and 3, since the operating conditions of the dilute acid pretreatment process resulted to CSF values within the acceptable range for dilute acid hydrolysis of lignocellulosic biomass.
Optimization of enzyme hydrolysis The EFB treated at 120 C and 6 vol% H2SO4 for 60 min was further treated by enzyme hydrolysis at various temperatures, pH values, and enzyme loadings. Table 4 summarizes the effects of the additional enzyme hydrolysis on sugar recovery and subsequent hydrogen production. RSM was implemented to investigate the extent to which each control variable
influenced the efficiency of the enzymatic pretreatment process. Regression equations for SC, HPR, and HY are shown in Eqs. S4eS6. Similar to the RSM analysis of the dilute acid hydrolysis, the ANOVA results showed that the computed F-values (SC: 76.39; HY: 62.25; HPR: 88.73) greatly exceeded the critical value of 2.76. Moreover, the low P values (SC: 0.2422; HY: 0.5376; HPR: 0.3574) indicate that the regression was statistically significant. Furthermore, the high regression coefficients all exceeded 0.98, suggesting that the regression analysis was suitable for reproducing the experimental data. Three-dimensional surface plots of the enzymatic hydrolysis experiments are shown in Fig. 2. Among the three independent variables, the pH and temperature conditions should be strictly controlled close to the optimal conditions due to the biological activity of the enzyme. Large deviations from the optimal conditions would significantly affect the saccharification process. It can be observed from Table 3 and Fig. 2 that
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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Table 4 e Sugar concentration, soluble metabolic products production, and hydrogen production from combined dilute acid and enzymatic hydrolysis of empty fruit bunch of oil palm. Trial Temperature pH Enzyme Total organic Furaldehyde 5-HMFb Sugar H2 Yield H2 Production ( C) (mg mL1) acida (g L1) (g L1) (g L1) concentration (mL H2 g1 Rate (mL H2 L1d1) (g L1) biomass) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 a b c
45 30 45 30 30 60 60 45 30 45 60 60 70.23 45 45 19.77 45 45 45 45
5 3 5 7 7 3 7 5 3 5 7 3 5 5 5 5 1.64 5 5 8.36
0.75 0.50 0.75 1.00 0.50 0.50 1.00 0.75 1.00 0.75 0.50 1.00 0.75 1.17 0.75 0.75 0.75 0.33 0.75 0.75
19.12 8.16 20.24 6.52 8.25 5.12 17.56 19.76 7.33 19.81 18.09 7.81 10.24 21.36 20.17 9.17 3.17 18.04 19.12 5.89
2.21 1.84 2.11 1.96 1.41 1.76 1.84 2.16 2.03 2.09 1.87 1.65 1.83 1.74 2.09 0.81 0.93 1.97 2.23 1.57
0.33 0.21 0.26 0.37 0.18 NDc 0.41 0.25 0.29 0.36 0.17 0.19 ND 0.44 037 ND ND 0.21 0.38 ND
33.46 22.18 23.37 22.81 27.49 20.93 28.02 33.73 21.33 34.16 33.20 20.11 24.52 34.52 30.56 17.29 15.48 21.33 32.77 21.45
278.95 202.16 213.26 214.32 234.92 176.98 241.73 278.30 198.32 271.23 286.98 213.06 231.17 283.91 246.88 183.32 169.53 192.64 274.13 211.19
3111.22 1494.64 1661.30 1629.55 2152.65 1234.73 2257.76 3129.02 1410.06 3088.41 3175.91 1792.66 1889.43 3266.86 2514.88 1056.53 1318.19 1369.67 2994.41 2233.31
Total organic acid (after enzymatic hydrolysis) is the sum of acetate, butyrate, formate, and propionate. 5-hydroxymethylfuraldehyde. Not detected.
temperature and pH are the factors which affect SC the most among the three variables, due to the similar SC values at temperature near 45 C and pH near 5.0. However, it can also be seen that the best experimental run was observed at these temperature and pH and at the highest enzyme loading of 1.17 mg enzyme mL1. Enzyme loading has a direct relationship with sugar concentration, since sugar concentration was observed to increase as enzyme loading increased. The concentrations of the SMPs in the enzymatic hydrolysates were low (Table 4) as the conditions were not harsh enough to degrade monomeric sugars. Based on the experimental design runs, the highest SC of 34.52 g L1 was obtained under the following conditions: 45 C, pH 5.0, and 1.17 mg enzyme mL1. Similar to the results of the dilute acid hydrolysis, the conditions under which the maximum SC value was observed also corresponded to the best H2 production. However, the analysis within the range of the independent variables revealed that only singular values of pH and temperature were suitable for the enzyme, whereas enzyme loading exhibited a linear relationship with SC and H2 production. Maximizing the enzyme loading within the set range of 0.50e1.0 mg enzyme mL1, while maintaining suitable pH and temperature conditions, maximized the amount of monomeric sugars produced, leading to improved H2 fermentation performance. The results of the experimental runs were modelled using the statistical software Design-Expert to obtain the optimal temperature, pH, and enzyme loading for enzymatic saccharification of the EFB of oil palm. At 45 C, pH 5.0, and 1.17 mg enzyme mL1, 34.52 g L1, 283.91 mL H2 g1 TS, and 3266.86 mL H2 L1d1 were the highest values of SC, HY, and HPR, respectively.
Compared to the dilute acid hydrolysis, the subsequent enzyme hydrolysis enhanced the sugar concentration of dilute acid by 20%. The increased content of easily accessible substrates resulted in an enhanced HPR by 22%. Therefore, additional enzymatic hydrolysis results to a better H2 production rate from EFB than just dilute acid hydrolysis.
Overall performance under the optimal conditions During H2 fermentation, the monomeric sugars in the hydrolysate were utilized completely and were exhausted after approximately 60 h, following a lag phase, during which bacterial growth occurs after introduction to the fermentative environment, as shown in Fig. 3a. This was observed in a previous H2 production study with pure sucrose and mixed anaerobic culture as the substrate and inoculum, respectively [31]. During the entire dark fermentation process, no methane production was observed because of the thermal treatment of the sludge, which inhibited methanogen activity while simultaneously enriching H2-producing bacteria [55]. The production of organic acids during the maximum H2 fermentation production is shown in Fig. 3b. Alongside H2, organic acids such as acetate, butyrate, and propionate were also produced as SMPs of the dark fermentation process. These organic acids are commonly observed during fermentation when microorganisms are fed with xylose and glucose. Among them, acetate and butyrate were the major SMPs, suggesting that the main route of H2 production was favored acetate and butyrate [56], which is typical for H2-producing Clostridium [53].
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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Fig. 2 e Three-dimensional surface plots of the quadratic model for sugar concentration (g L¡1), H2 production rate (mL H2 L¡1 d¡1), and H2 yield (mL H2 g biomass¡1) observed after enzymatic saccharification of the empty fruit bunch of oil palm.
Fig. 3 e Organic acid (Fo: formate; Ac: acetate; Pr: propionate; Bu: butyrate; Le: levulinate) formation after H2 fermentation under the optimized conditions for maximum H2 production performance after dilute acid and enzymatic hydrolysis.
Table 5 shows that the peak HY and HPR observed in this study was in the range of previously reported maximum values for H2 production from lignocellulosic biomass. Rice husk underwent the sequential pretreatment and HY and
HPR of 473.91 mL H2 g1 total sugar (TS) and 3340 mL H2 L1 d1, respectively, were obtained [23]. This, however, was not the case in a study involving sequential dilute acid and enzymatic pretreatment of oat straw yielded 113.75 mL H2
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
[61] [13] [60] [45] [13] [58] [42] [45] [23] [59] This study This study 710 mL H2 L d 1824 mL H2 L1 d1 1551 mL H2 L1 d1 2565 mL H2 L1 d1 1629 mL H2 L1 d1 1611 mL H2 L1 d1 2608 mL H2 L1 d1 1510 mL H2 L1 d1 3340 mL H2 L1 d1 1840 mL H2 L1 d1 2061 mL H2 L1 d1 3175 mL H2 L1 d1
1 1
H2 production rate
113.75 mL H2 g TS 165.88 mL H2 g1 TS 278.0 mL H2 g1 TS 191.18 mL H2 g1 TS 179.0 mL H2 g1 TS 44.9 mL H2 g1 TS 251.63 mL H2 g1 TS 275.53 mL H2 g1 TS 473.1 mL H2 g1 TS 178 mL H2 g1 TS 275.75 mL H2 g1 TS 282.17 mL H2 g1 TS
a
5 g TS/L 10 g TS/L 10 g TS/L 20 g TS/L
Anaerobic sludge Anaerobic sludge Anaerobic sludge Anaerobic sludge Anaerobic sludge Mixed culture Anaerobic sludge Anaerobic sludge Anaerobic sludge Anaerobic sludge Anaerobic sludge Anaerobic sludge 5 g TS/L 5 g TS/L 10 g TS/L 10 g TS/L
7.0 7.0, 7.0, 7.0, 7.0, 7.0 7.0, 7.0, 7.0, 7.0, 7.0 7.0 pH pH pH pH pH pH pH pH pH pH pH pH C, C, C, C, C, C, C, C, C, C, C, C,
35 37 35 37 37 35 37 37 37 55 37 37
c
b
a
fruit bunch fruit bunch
Total sugar. Hydrolysate feed was simply obtained from enzymatic hydrolysis. Hydrolysate feed was a mixture of dilute acid and enzymatic hydrolysates.
Batch, Batch, Batch, Batch, Batch, Batch, Batch, Batch, Batch, Batch, Batch, Batch, Oat straw Oil palm empty Oil palm empty Pine tree wood Pine tree wood Poplar leaves Rice husk Rice husk Rice husk Wheat Oil palm empty Oil palm empty
fruit bunch fruit bunch
Sequential dilute acid and enzymatic hydrolysis Dilute acid hydrolysis Dilute acid hydrolysis Dilute acid hydrolysis Dilute acid hydrolysis Dilute acid hydrolysis Dilute acid hydrolysis Dilute acid hydrolysis Sequential dilute acid and enzymatic hydrolysisb Dilute acid hydrolysis Dilute acid hydrolysis Sequential dilute acid and enzymatic hydrolysisc
H2 yield Inoculum
1
H2 Fermentation Conditions Pretreatment Substrate
Table 5 e Dark fermentative H2 production from dilute acid hydrolysis and/or enzyme saccharification-pretreated lignocellulosic biomass in literature.
Reference
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g1 TS at a rate of 710 mL H2 L1 d1 [57]. As earlier mentioned, enzymatic saccharification is not a common pretreatment method prior to H2 fermentation, thus the H2 production in this study will also be compared to previous studies in which the lignocellulosic biomass was subjected to solely dilute acid hydrolysis. Pine tree wood was used as the biomass substrate in two different studies which showed HY values of 179e191 mL H2 g1 TS and HPR values of 1629e2565 mL H2 L1 d1 [13,42]. Cui et al. [58] used poplar leaves as the substrate and HY and HPR of 44.9 mL H2 g1 TS and 3340 mL H2 L1 d1, respectively, were observed. Dilute acid hydrolysates of rice husk were also fed for H2 fermentation and HY of 251e275 mL H2 g1 TS and HPR of 1510e2608 mL H2 L1 d1 were calculated [42,45]. 178 mL H2 g1 TS was yielded at a rate of 1840 mL H2 L1 d1 when dilute acid hydrolysate of wheat was used [59]. The representative biomass chosen in this study, oil palm empty fruit bunch, was also hydrolyzed with dilute acid prior to H2 fermentation in two previous studies. 165.88 mL H2 g1 TS and 1824 mL H2 L1 d1 were the HY and HPR in a study by Gonzales et al. [42], while Chong et al. [60] was able to obtain a higher HY of 278.0 mL H2 g1 TS and but a lower HPR of 1551 mL H2 L1 d1. These results from previous literature show that the HY and HPR from the dilute acid and enzymatic hydrolysate of oil palm empty fruit bunch in this study were significantly better. It may be noticeable that HY only slightly increased even after enzymatic pretreatment. The volumetric HY was significantly higher for the enzymatic hydrolysate; however, dividing that by the TS concentration in the hydrolysate, which was higher than that of the dilute acid hydrolysate, resulted to a supposed slight increase in HY. However, if the HPR values of the dilute acid and enzymatic hydrolysates used as substrates were compared, HPR significantly increased after using enzymatic hydrolysate from 2061 to 3175 mL H2 L1 d1. Dilute-acid hydrolyzed EFB is a promising feedstock for biohydrogen production. Enzymatic hydrolytic saccharification would further enhance the feasibility of EFB by increasing its HPR.
Conclusion CCD was implemented to investigate the influence of two sets of independent variables on sugar concentration and fermentative H2 production during dilute acid and enzymatic pretreatments of EFB, a source of lignocellulosic biomass. Optimization of the conditions for biohydrogen production from EFB was performed using RSM, model building, and regression analysis. The reaction time, reaction temperature, and dilute acid concentration were optimized for dilute acid hydrolysis of empty fruit bunch of oil palm. Furthermore, the saccharification temperature, pH, and enzyme loading were likewise optimized for enzymatic saccharification of the said biomass. The optimum SC, HY, and HPR using dilute acid hydrolysates were 28.30 g L1, 275.75 mL H2 g1 biomass, and 2601.24 mL H2 L1d1, respectively, at 120 C, 60 min reaction, and 6 v/v % H2SO4, with a CSF of 1.75. In this study, due to the CSF values within acceptable limit, no serious accumulation of inhibitory compounds was observed. For enzymatic
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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saccharification, maximum values of 34.52 g L1, 283.91 mL H2 g-1 TS, and 3266.86 mL H2 L1d1, respectively, were the optimal SC, HY, and HPR at 47.63 C, pH of 5.45, and enzyme loading of 1.0 mg enzyme mL1. Optimization of the dilute acid and enzymatic pretreatment processes of lignocellulosic biomass is of great importance in the development of dark H2 fermentation as a sustainable process for renewable energy production. In the future, a larger-scale two-stage: (1) sequential dilute acid and enzymatic pretreatment and (2) dark fermentation system will be developed for practical applications and potential commercialization of the process.
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Acknowledgements The authors acknowledge the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MSIP, No. 2017R1A2A2A07000900).
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Appendix A. Supplementary data Supplementary data related to this article can be found at https://doi.org/10.1016/j.ijhydene.2018.08.022. [15]
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Available online at www.sciencedirect.com
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Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm Ralph Rolly Gonzales a, Jun Seok Kim b, Sang-Hyoun Kim c,* a
Department of Environmental Engineering, Daegu University, Gyeongbuk 38453, Republic of Korea Department of Chemical Engineering, Kyonggi University, Suwon 16227, Republic of Korea c School of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Republic of Korea b
article info
abstract
Article history:
Pretreatment of the empty fruit brunch (EFB) from oil palm was investigated for H2
Received 21 March 2018
fermentation. The EFB was hydrolyzed at various temperatures, H2SO4 concentrations, and
Received in revised form
reaction times. Subsequently, the acid-hydrolysate underwent enzymatic saccharification
26 July 2018
under various temperature, pH, and enzymatic loading conditions. Response surface
Accepted 6 August 2018
methodology derived the optimum sugar concentration (SC), hydrogen production rate
Available online xxx
(HPR), and hydrogen yield (HY) as 28.30 g L1, 2601.24 mL H2 L1d1, and 275.75 mL H2 g1 total sugar (TS), respectively, at 120 C, 60 min of reaction, and 6 vol% H2SO4, with the
Keywords:
combined severity factor of 1.75. Enzymatic hydrolysis enhanced the SC, HY, and HPR to
Biohydrogen
34.52 g L1, 283.91 mL H2 g1 TS, and 3266.86 mL H2 L1d1, respectively, at 45 C, pH 5.0,
Dilute acid hydrolysis
and 1.17 mg enzyme mL1. Dilute acid hydrolysis would be a viable pretreatment for bio-
Enzyme hydrolysis
hydrogen production from EFB. Subsequent enzymatic hydrolysis can be performed if
Saccharification
enhanced HPR is required.
Lignocellulosic biomass
© 2018 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.
Response surface methodology
Introduction Lignocellulosic biomass is a cost-effective and environmentfriendly alternative energy source, as compared to fossil fuels which are non-renewable and contribute to greenhouse gas emissions and global warming [1,2]. The use of lignocellulosic biomass for bioenergy generation has the potential to mitigate fossil fuel depletion and reduce dependency on fossil fuels. Furthermore, alternative energy sources significantly reduce greenhouse gas emissions and problems associated with waste management and pollution. This type of biomass
is a typical byproduct of agricultural processes. Thus, abundance and renewability are not limitations for its use as feedstock for the production of biofuels such as biogas, biomethane, syngas, bioethanol, and biodiesel [3]. Hydrogen (H2) is an environmentally-friendly and energyefficient biofuel and has attracted significant interest in recent years [4e6]. Dark H2 fermentation from a variety of biomass sources has been performed using pure microorganism strains or mixed microbial consortiums [7e11]. Optimization of the fermentation process is important for achieving maximum production performance at minimal cost. This entails enhancement of the pretreatment process,
* Corresponding author. School of Civil and Environmental Engineering, Yonsei University, Seoul 03722, Republic of Korea. E-mail address: [email protected] (S.-H. Kim). https://doi.org/10.1016/j.ijhydene.2018.08.022 0360-3199/© 2018 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved. Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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during which fermentable monomeric sugars are obtained for subsequent fermentation. Lignocellulosic materials are composed of complex polymeric structures of cellulosic polymers, lignin, and other materials, such as ash and extractives [12e14]. Pretreatment is required to decompose the carbohydrate-lignin linkages, which cause recalcitrant properties in the biomass [15]. Once the complex linkages are broken from the pretreatment, the cellulose and hemicellulose components can be accessed and utilized as feedstock for biofuel production [16,17]. In this particular study, the empty fruit bunch (EFB) of oil palm was chosen as the substrate due to its abundance, cost, and carbohydrate content, which all contributed to its potential as a renewable energy source [18]. Dilute acid hydrolysis is a popular pretreatment method for lignocellulosic biomass [12]. In comparison to concentrated acid hydrolysis, dilute acid hydrolysis is relatively economical and environmentally-friendly. In both acid pretreatment processes, the biomass is subjected to the same thermal and acidic physicochemical conditions to obtain a monomeric sugar-rich solution. Dilute acid hydrolysis is controlled by a number of factors, including hydrolysis temperature, time, dilute acid concentration, and solid/liquid (S/L) ratio. These factors contribute to the combined severity factor (CSF), a parameter that represents the strength or harshness of the hydrolysis process [19]. The CSF can be obtained using Eq. (1) [19]: Th 100 pH CSF ¼ log txe 14:75
(1)
where Th and t are the hydrolysis temperature (in C), and reaction time (in min), respectively. Higher CSF values indicate harsher hydrolysis conditions, which may lead to increased waste production, higher pretreatment costs, and decomposition of the monomeric sugars into byproducts such as 5-hydroxymethylfuraldehyde, furaldehyde, formic acid, and levulinic acid [20e22]. To further decompose the biomass, enzyme saccharification can be performed after dilute acid hydrolysis. Combined hydrolysis represents an efficient method for obtaining fermentable monomeric sugars from lignocellulosic biomass, as demonstrated in previous studies [23,24]. However, this combined pretreatment method is not usually used for dark H2 fermentation studies. Furthermore, optimization of the enzymatic hydrolysis parameters remains an important issue, since no fixed set of pretreatment conditions can be used for all types of lignocellulosic biomass. Based on the biomass used, the following factors may significantly affect the efficiency of enzymatic pretreatment: temperature, pH, and enzyme loading. Response surface methodology (RSM) is used to design experimental procedures, generate models, evaluate the significance of independent variables, and optimize a response influenced by several variables. RSM can determine the optimal process conditions and identify the limit of a response based on the set experimental conditions by developing a model relating a process response to various factors [25,26]. In this method, interactions among the variables and the consequent effects are used for optimization. Furthermore,
the optimal point can be deduced even without experimental data through RSM [27,28]. RSM has been performed previously in a number of H2 fermentation optimization studies [26e35]. However, RSM has not been previously employed for combined dilute acid and enzymatic hydrolysis, thus, it was performed and investigated in this study. Furthermore, a limited number of studies on enzymatic hydrolysis as a pretreatment process for H2 fermentation are available, since this method is mostly used for bioethanol [36] and biomethane [37] production. To the best of the authors' knowledge, there are no previous studies involving statistical tools to optimize the conditions for both dilute acid and enzymatic hydrolysis for lignocellulosic biomass. Furthermore, this study demonstrates a holistic pretreatment and H2 fermentation approach, wherein at the end of the saccharification process, the dilute acid and enzymatic hydrolysates are combined together, prior to use as feed during dark H2 fermentation. This study then aims to bring light to the optimum conditions for sequential dilute acid and enzymatic hydrolysis for lignocellulosic biomass for maximum sugar recovery from the biomass, as well as maximum H2 production and yield during the subsequent fermentation. These are important to be determined for maximum efficiency of the dark fermentative H2 production. In this study, RSM was used to develop a central composite design (CCD) for the determination of optimal operating conditions for dilute acid and enzymatic hydrolysis pretreatments for maximizing monomeric sugar yield and subsequent H2 fermentation. Hydrolysis temperature, H2SO4 concentration, and hydrolysis time were first optimized to increase sugar concentration and H2 production from the dilute acid pretreatment of the EFB of oil palm. Control variables for enzymatic hydrolysis (temperature, pH, and enzyme loading) were then optimized to increase sugar concentration and H2 production.
Experimental Test lignocellulosic biomass EFB pellets obtained from local agricultural sources in Malaysia were used as the test biomass in this study. The EFB composition was measured according to the analytical procedure recommended by the National Renewable Energy Laboratory [38]. Table 1 shows the composition of the biomass on a dry weight basis.
Table 1 e Carbohydrate, lignin, ash, and extractives content in the empty fruit bunch of oil palm. Component Glucan Xylan Arabinan Lignin Ash Extractives
% 38.31 ± 1.01 11.09 ± 0.24 0.13 ± 0.01 9.37 ± 0.03 39.82 ± 2.05 1.43 ± 0.16
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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Inoculum
Response surface methodology
Granular sludge sourced from an up flow anaerobic sludge blanket reactor (UASB) in South Korea was used as the inoculum in this study. The sludge contains a number of H2-producing bacteria strains, mostly Clostridium [39]. The sludge exhibited the following properties: pH 6.8; 12.6 g volatile suspended solids (VSS) L1; and 22.6 g total suspended solids (TSS) L1. The sludge was subjected to a 90 C heat treatment for 30 min [40,41] prior to use such that only anaerobic H2-producing bacteria remained in the sludge.
A full factorial CCD with replicates on the center and axial center points for three factors was used in this study, as shown in Table 2. A total of 20 experimental trials were performed, eight trials for cubic points, six for axial points, and six center point replicates, as shown in Table 2. The individual and synergistic effects of the three variables tested on dilute acid and enzymatic hydrolysis were investigated. The variables were coded according to Eq. (2) [27]: xi ¼
Xi X*i Dxi
(2)
Table 2 e Experimental design for full factorial central composite design. Run
Code Values X1
DILUTE ACID HYDROLYSIS 1 0 2 1 3 0 4 1 5 1 6 1 7 1 8 0 9 1 10 0 11 1 12 1 13 1.68 14 0 15 0 16 1.68 17 0 18 0 19 0 20 0
X4 ENZYMATIC HYDROLYSIS 1 0 2 1 3 0 4 1 5 1 6 1 7 1 8 0 9 1 10 0 11 1 12 1 13 1.68 14 0 15 0 16 1.68 17 0 18 0 19 0 20 0
Real Values
CSF
X2
X3
Temperature ( C)
Time (min)
Acid (vol%)
0 1 0 1 1 1 1 0 1 0 1 1 0 0 0 0 1.68 0 0 1.68
0 1 0 1 1 1 1 0 1 0 1 1 0 1.68 0 0 0 1.68 0 0
100 80 100 80 80 120 120 100 80 100 120 120 133.64 100 100 66.36 100 100 100 100
45 30 45 60 60 30 60 45 30 45 60 30 45 45 45 45 19.77 45 45 70.23
5 4 5 6 4 4 6 5 6 5 4 6 5 6.68 5 5 5 3.32 5 5
1.12 0.15 1.11 0.93 0.41 1.25 2.09 1.22 0.65 1.16 1.51 1.75 2.15 1.47 1.16 0.25 0.85 0.64 1.17 1.34
X5
X6
Temperature ( C)
pH
Enzyme (mg mL¡1)
0 1 0 1 1 1 1 0 1 0 1 1 0 0 0 0 1.68 0 0 1.68
0 1 0 1 1 1 1 0 1 0 1 1 0 1.68 0 0 0 1.68 0 0
45 30 45 30 30 60 60 45 30 45 60 60 70.23 45 45 19.77 45 45 45 45
5 3 5 7 7 3 7 5 3 5 7 3 5 5 5 5 1.64 5 5 8.36
0.75 0.50 0.75 1.00 0.50 0.50 1.00 0.75 1.00 0.75 0.50 1.00 0.75 1.17 0.75 0.75 0.75 0.33 0.75 0.75
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where Dxi is the step size and xi, Xi, and X are the coded value of the ith variable, uncoded value of the ith variable, and uncoded value of the ith variable at the center point of the investigated area, respectively.
Dilute acid hydrolysis of oil palm EFB The EFB pellets were milled to obtain particles 1e2 mm in size. The temperature (X1), H2SO4 concentration (X2), and hydrolysis time (X3) were the three factors considered in the experimental design, with the following central values: 100 C; 5% H2SO4 (Duksan Pure Chemicals, Korea); and 45 min of reaction time for X1, X2, and X3, respectively. EFB was added into the hydrolysis vessel at a concentration of 10 g L1 [42]. Hydrolysis was performed in an autoclave (SK401, Yamato Scientific Co., Ltd.) at a pressure of 0.9 MPa.
UVeVis Mini 1240, Shimadzu, Japan) at 480 nm. Concentrations of soluble metabolic products (SMPs), or byproducts of the pretreatment and fermentation processes, were determined using an Aminex-87H (Bio-Rad Laboratories, USA) column-equipped HPLC with a UV detector (Waters 2487, USA). A standard procedure was followed to measure the enzyme filter paper activity [47]. Chemical oxygen demand (COD), VSS, and TSS were also measured using standard methods [48]. Gas content was analyzed using a gas chromatography (SRI Instruments, USA) equipped with thermal conductivity detector (TCD) and a 13 mole sieve packed-1.8 m stainless steel column. N2 gas (99% purity) was used as the carrier gas. The temperatures of the column, detector, and injector were maintained at 80 , 90 , and 25 C, respectively.
Assay Enzymatic hydrolysis of the lignocellulosic biomass After determination of the optimal dilute acid hydrolysis conditions, the EFB residue collected after dilute acid hydrolysis was first washed and dried prior to enzymatic hydrolytic saccharification. Thermophilic cellulase (Celluclast 1.5L®, Sigma-Aldrich, Merck, MO, USA) [43] sourced from Trichoderma reesei ATTC 26921, with protein concentration and average activity of 79 mg enzyme mL1 and 65 filter paper unit (FPU)/mL, respectively [44], was used in this study. The saccharification temperature (X4), saccharification pH (X5), and enzyme loading (X6) were the three independent factors whose central values were 45 C, 5, and 0.75 mg enzyme mL1, respectively. The total hydrolysates of EFB obtained from both dilute acid and enzymatic hydrolysis were combined prior to fermentation.
Batch H2 fermentation For H2 fermentation, 100-mL serum bottles were used as batch reactors and 6 mL of the hydrolysate solutions obtained after pretreatment were added to the serum bottle and diluted to 30 mL with distilled water. Subsequently, 5 mL of the anaerobic sludge was added and minerals were supplied to the reactors by adding 5 mL of mineral solution, the concentrations of which were adjusted according to previous studies [13,23,42,45]. The resultant solutions had 40 mL of total working volume and an initial pH of 7.0e7.5, according to a previous study [13]. Anaerobic conditions were obtained when the reactors were purged with N2 gas, after which the reactors were agitated at 150 rpm and 35 C for 72 h. All trials were performed in duplicate.
Analysis An Aminex HPX-87P (Bio-Rad Laboratories, USA) columnequipped high-performance liquid chromatograph (HPLC, Waters 717, Waters, USA) with a refractive index (RI) detector (Waters 410, Waters, USA) was used to determine hydrolysate glucose and xylose concentrations. Total monomeric sugar concentration was analyzed using the phenol-sulfuric acid colorimetric method [46] with an ultravioletevisible (UVevis) spectrophotometer (Shimadzu
The production of H2 was plotted as a function of time, and an adapted Gompertz equation (Eq. (3)) was used to estimate the following parameters: maximum H2 production rate, maximum H2 volume, H2 production, and H2 production yield [49,50]. Eq. (3) can be written as: RH ðl tÞ þ 1 H ¼ P$exp exp P
(3)
where H, P, RH, l, and t are the cumulative H2 volume (mL), H2 production potential (mL), H2 production rate (HPR, mL h1), lag time (h), and time (h), respectively. The volumetric HPR (L H2 L1 h1) and hydrogen yield (HY, mL H2 g biomass1) were calculated from the RH, P, reactor volume, and amount of monomeric sugar substrate. The responses of the independent variables governing the dilute acid and enzymatic hydrolysis were correlated using the following general quadratic equation [32,51]: Y ¼ bo þ
k X i¼1
bi Xi þ
k X
bii X2i þ
X bij Xi Xj
i¼1
(4)
i
where Y, bo, bi, bii, and bij are the response, y-intercept, linear coefficient, quadratic coefficient, and interactive coefficients, respectively. Statistical analysis and modelling were performed using Design-Expert (Stat-Ease, MN, USA).
Results and discussion Dilute acid hydrolysis optimization The dilute acid hydrolysis efficiencies at various temperatures, reaction times, and acid concentrations are listed in Table 3. Regression equations for the sugar concentration (SC, g L1), HPR, and HY are shown in the supplementary section (S. Eqs. 1e3). High regression coefficient values (R2) over 0.94 were obtained, indicating that the regression models represented the experimental data well. The ANOVA results showed that the computed F-values (41.17, 17.18, and 187.11 for SC, HY, and HPR, respectively) are greater than 2.76, or the tabular F-value at the 5% confidence interval. Furthermore, the low P values
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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Table 3 e Sugar concentration, soluble metabolic products production, and hydrogen production from dilute acid hydrolysis of empty fruit bunch of oil palm. Trial Temperature Time Acid CSF Total organic Furaldehyde 5-HMFb Sugar H2 Yield H2 ( C) (min) (vol%) acida (g L1) (g L1) (g L1) concentration (mL H2 g1 Production (g L1) biomass) Rate (mL H2 L1d1) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 a b
100 80 100 80 80 120 120 100 80 100 120 120 133.64 100 100 66.36 100 100 100 100
45 30 45 60 60 30 30 45 30 45 60 60 45 45 45 45 19.77 45 45 70.23
5 4 5 6 4 4 6 5 6 5 4 6 5 6.68 5 5 5 3.32 5 5
1.12 0.15 1.11 0.93 0.41 1.25 2.09 1.22 0.65 1.16 1.51 1.75 2.15 1.47 1.16 0.25 0.85 0.64 1.17 1.34
5.62 4.98 5.07 5.23 4.76 5.61 5.86 4.71 4.93 5.11 5.28 5.63 7.18 5.21 4.56 5.29 4.32 3.77 5.49 6.83
3.53 3.71 4.03 3.64 3.44 4.03 2.25 4.17 2.36 4.97 5.63 8.23 6.82 6.02 5.78 4.24 4.88 2.91 5.15 5.64
1.31 0.84 0.82 0.71 0.58 0.63 1.59 0.79 0.85 0.92 1.01 1.11 1.48 0.99 0.91 0.85 0.56 0.60 0.71 0.93
24.67 20.35 20.63 20.86 19.83 14.38 17.94 26.10 16.55 20.20 17.95 28.30 19.83 25.09 15.30 20.20 18.10 22.35 11.72 21.92
251.63 215.93 218.27 209.45 203.41 155.89 179.70 266.31 166.52 217.04 181.11 275.75 214.33 254.29 175.47 211.81 199.55 231.82 139.55 221.38
2069.24 1464.73 1500.97 1456.38 1344.54 747.23 1074.61 2316.90 918.64 1461.40 1083.64 2601.24 1416.72 2126.71 894.90 1426.19 1203.95 1727.06 545.18 1617.55
The sum of acetate, formate, and propionate species after dilute acid hydrolysis. 5-hydroxymethylfuraldehyde.
(SC: 0.0016; HY: 0.0083; HPR: 0.002) obtained indicate that the regression was statistically significant. Three-dimensional surface plots, which model the synergistic effects of two variables when a third variable is held constant, are shown in Fig. 1. The surface plots show that temperature, reaction time, and dilute acid concentration all exerted significant individual influences on the sugar concentration during the dilute acid hydrolysis, which in turn influenced H2 production. These results further indicate that all three factors influence the combined severity of the dilute acid pretreatment, as shown in Eq. (2). The CSF of each experimental condition was calculated, and the results are listed in Table 2. Increasing the severity factor beyond the optimal range could decrease sugar recovery as excessive degradation of the sugar can occur [52]. Sugar recovery from the biomass, as well as H2 production and yield, can be reduced at harsher conditions, such as higher temperatures and acidity, which correspond to higher CSF values. Park et al. reported that, at CSF values exceeding 2.5, the amount of monomeric sugars decreased while the concentrations of SMPs increased [27]. The SMPs are either organic acids, such as levulinic, formic, and acetic acids, or furan aldehydes, such as furaldehyde and 5-hydroxymethylfuraldehyde (5-HMF), which can be formed during both acid hydrolysis and fermentation as a degradation byproduct of the carbohydrate species. These SMPs, especially the furan aldehydes, can inhibit fermentative H2-producing microorganisms [53]. Thus, these compounds must be removed from the hydrolysate prior to fermentation to avoid inhibitory effects. The severity factors of all dilute acid pretreatment conditions were below 2.5 in this study, within the optimal range of 1.7e2.2, under which maximum sugar concentration can be obtained [54].
Temperature, reaction time, and pH all contributed to the severity of the dilute acid hydrolysis. Therefore, at extreme values of these parameters, partial degradation occurs and the formation of SMPs increased, which was detrimental to the final sugar concentration and subsequent H2 production. The highest SC of 28.30 g L1 was obtained under the following conditions: 120 C, 60 min reaction, and 6 vol % H2SO4, with a CSF of 1.75. In this study, due to the CSF values within acceptable limit, no serious accumulation of inhibitory compounds was observed. Under these optimum conditions, SMPs were only formed in small quantities. However, the SC dropped while the concentrations of the byproducts increased at higher CSF values, despite remaining within the optimum range. Table 3 shows the concentrations of the SMPs after dilute acid hydrolysis. Increased concentrations of SMPs indicate that the monomeric sugars from the biomass were liberated from the complex lignocellulosic structure. However, the severity of the pretreatment caused the sugars to be further degraded. Organic acids and furan compounds are known to be degradation byproduct of polysaccharides during dilute acid hydrolysis; however, among the known organic acids, butyric acid is not among the hydrolysis byproducts. In Table 3 it can be seen that all the runs exhibited low SMP concentrations. Thus, degradation did not occur to a great extent during pretreatment, primarily due to the reasonable CSF values which are all within the optimum range, indicating that the dilute acid hydrolysis conditions performed in this study were not excessively harsh, and it is expected that H2 fermentation would not be greatly affected by these compounds. Hydrogen production using the dilute acid hydrolysates was directly correlated to sugar concentration, such that the optimum values of HPR (2601.24 mL H2 L1d1) and HY
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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Fig. 1 e Three-dimensional surface plots of the quadratic model for sugar concentration (g L¡1), H2 production rate (mL H2 L¡1 d¡1), and H2 yield (mL H2 g biomass¡1) observed after dilute acid hydrolysis of the empty fruit bunch of oil palm.
(275.75 mL H2 g1 biomass) were obtained under the same conditions at which the optimum sugar concentration was achieved. This is because the hydrolysate solutions contained the highest amount of soluble monomeric sugars, and the concentrations of the SMPs were also not high, as shown in Tables 2 and 3, since the operating conditions of the dilute acid pretreatment process resulted to CSF values within the acceptable range for dilute acid hydrolysis of lignocellulosic biomass.
Optimization of enzyme hydrolysis The EFB treated at 120 C and 6 vol% H2SO4 for 60 min was further treated by enzyme hydrolysis at various temperatures, pH values, and enzyme loadings. Table 4 summarizes the effects of the additional enzyme hydrolysis on sugar recovery and subsequent hydrogen production. RSM was implemented to investigate the extent to which each control variable
influenced the efficiency of the enzymatic pretreatment process. Regression equations for SC, HPR, and HY are shown in Eqs. S4eS6. Similar to the RSM analysis of the dilute acid hydrolysis, the ANOVA results showed that the computed F-values (SC: 76.39; HY: 62.25; HPR: 88.73) greatly exceeded the critical value of 2.76. Moreover, the low P values (SC: 0.2422; HY: 0.5376; HPR: 0.3574) indicate that the regression was statistically significant. Furthermore, the high regression coefficients all exceeded 0.98, suggesting that the regression analysis was suitable for reproducing the experimental data. Three-dimensional surface plots of the enzymatic hydrolysis experiments are shown in Fig. 2. Among the three independent variables, the pH and temperature conditions should be strictly controlled close to the optimal conditions due to the biological activity of the enzyme. Large deviations from the optimal conditions would significantly affect the saccharification process. It can be observed from Table 3 and Fig. 2 that
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Table 4 e Sugar concentration, soluble metabolic products production, and hydrogen production from combined dilute acid and enzymatic hydrolysis of empty fruit bunch of oil palm. Trial Temperature pH Enzyme Total organic Furaldehyde 5-HMFb Sugar H2 Yield H2 Production ( C) (mg mL1) acida (g L1) (g L1) (g L1) concentration (mL H2 g1 Rate (mL H2 L1d1) (g L1) biomass) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 a b c
45 30 45 30 30 60 60 45 30 45 60 60 70.23 45 45 19.77 45 45 45 45
5 3 5 7 7 3 7 5 3 5 7 3 5 5 5 5 1.64 5 5 8.36
0.75 0.50 0.75 1.00 0.50 0.50 1.00 0.75 1.00 0.75 0.50 1.00 0.75 1.17 0.75 0.75 0.75 0.33 0.75 0.75
19.12 8.16 20.24 6.52 8.25 5.12 17.56 19.76 7.33 19.81 18.09 7.81 10.24 21.36 20.17 9.17 3.17 18.04 19.12 5.89
2.21 1.84 2.11 1.96 1.41 1.76 1.84 2.16 2.03 2.09 1.87 1.65 1.83 1.74 2.09 0.81 0.93 1.97 2.23 1.57
0.33 0.21 0.26 0.37 0.18 NDc 0.41 0.25 0.29 0.36 0.17 0.19 ND 0.44 037 ND ND 0.21 0.38 ND
33.46 22.18 23.37 22.81 27.49 20.93 28.02 33.73 21.33 34.16 33.20 20.11 24.52 34.52 30.56 17.29 15.48 21.33 32.77 21.45
278.95 202.16 213.26 214.32 234.92 176.98 241.73 278.30 198.32 271.23 286.98 213.06 231.17 283.91 246.88 183.32 169.53 192.64 274.13 211.19
3111.22 1494.64 1661.30 1629.55 2152.65 1234.73 2257.76 3129.02 1410.06 3088.41 3175.91 1792.66 1889.43 3266.86 2514.88 1056.53 1318.19 1369.67 2994.41 2233.31
Total organic acid (after enzymatic hydrolysis) is the sum of acetate, butyrate, formate, and propionate. 5-hydroxymethylfuraldehyde. Not detected.
temperature and pH are the factors which affect SC the most among the three variables, due to the similar SC values at temperature near 45 C and pH near 5.0. However, it can also be seen that the best experimental run was observed at these temperature and pH and at the highest enzyme loading of 1.17 mg enzyme mL1. Enzyme loading has a direct relationship with sugar concentration, since sugar concentration was observed to increase as enzyme loading increased. The concentrations of the SMPs in the enzymatic hydrolysates were low (Table 4) as the conditions were not harsh enough to degrade monomeric sugars. Based on the experimental design runs, the highest SC of 34.52 g L1 was obtained under the following conditions: 45 C, pH 5.0, and 1.17 mg enzyme mL1. Similar to the results of the dilute acid hydrolysis, the conditions under which the maximum SC value was observed also corresponded to the best H2 production. However, the analysis within the range of the independent variables revealed that only singular values of pH and temperature were suitable for the enzyme, whereas enzyme loading exhibited a linear relationship with SC and H2 production. Maximizing the enzyme loading within the set range of 0.50e1.0 mg enzyme mL1, while maintaining suitable pH and temperature conditions, maximized the amount of monomeric sugars produced, leading to improved H2 fermentation performance. The results of the experimental runs were modelled using the statistical software Design-Expert to obtain the optimal temperature, pH, and enzyme loading for enzymatic saccharification of the EFB of oil palm. At 45 C, pH 5.0, and 1.17 mg enzyme mL1, 34.52 g L1, 283.91 mL H2 g1 TS, and 3266.86 mL H2 L1d1 were the highest values of SC, HY, and HPR, respectively.
Compared to the dilute acid hydrolysis, the subsequent enzyme hydrolysis enhanced the sugar concentration of dilute acid by 20%. The increased content of easily accessible substrates resulted in an enhanced HPR by 22%. Therefore, additional enzymatic hydrolysis results to a better H2 production rate from EFB than just dilute acid hydrolysis.
Overall performance under the optimal conditions During H2 fermentation, the monomeric sugars in the hydrolysate were utilized completely and were exhausted after approximately 60 h, following a lag phase, during which bacterial growth occurs after introduction to the fermentative environment, as shown in Fig. 3a. This was observed in a previous H2 production study with pure sucrose and mixed anaerobic culture as the substrate and inoculum, respectively [31]. During the entire dark fermentation process, no methane production was observed because of the thermal treatment of the sludge, which inhibited methanogen activity while simultaneously enriching H2-producing bacteria [55]. The production of organic acids during the maximum H2 fermentation production is shown in Fig. 3b. Alongside H2, organic acids such as acetate, butyrate, and propionate were also produced as SMPs of the dark fermentation process. These organic acids are commonly observed during fermentation when microorganisms are fed with xylose and glucose. Among them, acetate and butyrate were the major SMPs, suggesting that the main route of H2 production was favored acetate and butyrate [56], which is typical for H2-producing Clostridium [53].
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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Fig. 2 e Three-dimensional surface plots of the quadratic model for sugar concentration (g L¡1), H2 production rate (mL H2 L¡1 d¡1), and H2 yield (mL H2 g biomass¡1) observed after enzymatic saccharification of the empty fruit bunch of oil palm.
Fig. 3 e Organic acid (Fo: formate; Ac: acetate; Pr: propionate; Bu: butyrate; Le: levulinate) formation after H2 fermentation under the optimized conditions for maximum H2 production performance after dilute acid and enzymatic hydrolysis.
Table 5 shows that the peak HY and HPR observed in this study was in the range of previously reported maximum values for H2 production from lignocellulosic biomass. Rice husk underwent the sequential pretreatment and HY and
HPR of 473.91 mL H2 g1 total sugar (TS) and 3340 mL H2 L1 d1, respectively, were obtained [23]. This, however, was not the case in a study involving sequential dilute acid and enzymatic pretreatment of oat straw yielded 113.75 mL H2
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
[61] [13] [60] [45] [13] [58] [42] [45] [23] [59] This study This study 710 mL H2 L d 1824 mL H2 L1 d1 1551 mL H2 L1 d1 2565 mL H2 L1 d1 1629 mL H2 L1 d1 1611 mL H2 L1 d1 2608 mL H2 L1 d1 1510 mL H2 L1 d1 3340 mL H2 L1 d1 1840 mL H2 L1 d1 2061 mL H2 L1 d1 3175 mL H2 L1 d1
1 1
H2 production rate
113.75 mL H2 g TS 165.88 mL H2 g1 TS 278.0 mL H2 g1 TS 191.18 mL H2 g1 TS 179.0 mL H2 g1 TS 44.9 mL H2 g1 TS 251.63 mL H2 g1 TS 275.53 mL H2 g1 TS 473.1 mL H2 g1 TS 178 mL H2 g1 TS 275.75 mL H2 g1 TS 282.17 mL H2 g1 TS
a
5 g TS/L 10 g TS/L 10 g TS/L 20 g TS/L
Anaerobic sludge Anaerobic sludge Anaerobic sludge Anaerobic sludge Anaerobic sludge Mixed culture Anaerobic sludge Anaerobic sludge Anaerobic sludge Anaerobic sludge Anaerobic sludge Anaerobic sludge 5 g TS/L 5 g TS/L 10 g TS/L 10 g TS/L
7.0 7.0, 7.0, 7.0, 7.0, 7.0 7.0, 7.0, 7.0, 7.0, 7.0 7.0 pH pH pH pH pH pH pH pH pH pH pH pH C, C, C, C, C, C, C, C, C, C, C, C,
35 37 35 37 37 35 37 37 37 55 37 37
c
b
a
fruit bunch fruit bunch
Total sugar. Hydrolysate feed was simply obtained from enzymatic hydrolysis. Hydrolysate feed was a mixture of dilute acid and enzymatic hydrolysates.
Batch, Batch, Batch, Batch, Batch, Batch, Batch, Batch, Batch, Batch, Batch, Batch, Oat straw Oil palm empty Oil palm empty Pine tree wood Pine tree wood Poplar leaves Rice husk Rice husk Rice husk Wheat Oil palm empty Oil palm empty
fruit bunch fruit bunch
Sequential dilute acid and enzymatic hydrolysis Dilute acid hydrolysis Dilute acid hydrolysis Dilute acid hydrolysis Dilute acid hydrolysis Dilute acid hydrolysis Dilute acid hydrolysis Dilute acid hydrolysis Sequential dilute acid and enzymatic hydrolysisb Dilute acid hydrolysis Dilute acid hydrolysis Sequential dilute acid and enzymatic hydrolysisc
H2 yield Inoculum
1
H2 Fermentation Conditions Pretreatment Substrate
Table 5 e Dark fermentative H2 production from dilute acid hydrolysis and/or enzyme saccharification-pretreated lignocellulosic biomass in literature.
Reference
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g1 TS at a rate of 710 mL H2 L1 d1 [57]. As earlier mentioned, enzymatic saccharification is not a common pretreatment method prior to H2 fermentation, thus the H2 production in this study will also be compared to previous studies in which the lignocellulosic biomass was subjected to solely dilute acid hydrolysis. Pine tree wood was used as the biomass substrate in two different studies which showed HY values of 179e191 mL H2 g1 TS and HPR values of 1629e2565 mL H2 L1 d1 [13,42]. Cui et al. [58] used poplar leaves as the substrate and HY and HPR of 44.9 mL H2 g1 TS and 3340 mL H2 L1 d1, respectively, were observed. Dilute acid hydrolysates of rice husk were also fed for H2 fermentation and HY of 251e275 mL H2 g1 TS and HPR of 1510e2608 mL H2 L1 d1 were calculated [42,45]. 178 mL H2 g1 TS was yielded at a rate of 1840 mL H2 L1 d1 when dilute acid hydrolysate of wheat was used [59]. The representative biomass chosen in this study, oil palm empty fruit bunch, was also hydrolyzed with dilute acid prior to H2 fermentation in two previous studies. 165.88 mL H2 g1 TS and 1824 mL H2 L1 d1 were the HY and HPR in a study by Gonzales et al. [42], while Chong et al. [60] was able to obtain a higher HY of 278.0 mL H2 g1 TS and but a lower HPR of 1551 mL H2 L1 d1. These results from previous literature show that the HY and HPR from the dilute acid and enzymatic hydrolysate of oil palm empty fruit bunch in this study were significantly better. It may be noticeable that HY only slightly increased even after enzymatic pretreatment. The volumetric HY was significantly higher for the enzymatic hydrolysate; however, dividing that by the TS concentration in the hydrolysate, which was higher than that of the dilute acid hydrolysate, resulted to a supposed slight increase in HY. However, if the HPR values of the dilute acid and enzymatic hydrolysates used as substrates were compared, HPR significantly increased after using enzymatic hydrolysate from 2061 to 3175 mL H2 L1 d1. Dilute-acid hydrolyzed EFB is a promising feedstock for biohydrogen production. Enzymatic hydrolytic saccharification would further enhance the feasibility of EFB by increasing its HPR.
Conclusion CCD was implemented to investigate the influence of two sets of independent variables on sugar concentration and fermentative H2 production during dilute acid and enzymatic pretreatments of EFB, a source of lignocellulosic biomass. Optimization of the conditions for biohydrogen production from EFB was performed using RSM, model building, and regression analysis. The reaction time, reaction temperature, and dilute acid concentration were optimized for dilute acid hydrolysis of empty fruit bunch of oil palm. Furthermore, the saccharification temperature, pH, and enzyme loading were likewise optimized for enzymatic saccharification of the said biomass. The optimum SC, HY, and HPR using dilute acid hydrolysates were 28.30 g L1, 275.75 mL H2 g1 biomass, and 2601.24 mL H2 L1d1, respectively, at 120 C, 60 min reaction, and 6 v/v % H2SO4, with a CSF of 1.75. In this study, due to the CSF values within acceptable limit, no serious accumulation of inhibitory compounds was observed. For enzymatic
Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022
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saccharification, maximum values of 34.52 g L1, 283.91 mL H2 g-1 TS, and 3266.86 mL H2 L1d1, respectively, were the optimal SC, HY, and HPR at 47.63 C, pH of 5.45, and enzyme loading of 1.0 mg enzyme mL1. Optimization of the dilute acid and enzymatic pretreatment processes of lignocellulosic biomass is of great importance in the development of dark H2 fermentation as a sustainable process for renewable energy production. In the future, a larger-scale two-stage: (1) sequential dilute acid and enzymatic pretreatment and (2) dark fermentation system will be developed for practical applications and potential commercialization of the process.
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Acknowledgements The authors acknowledge the National Research Foundation of Korea (NRF) grant funded by the Korea Government (MSIP, No. 2017R1A2A2A07000900).
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Appendix A. Supplementary data Supplementary data related to this article can be found at https://doi.org/10.1016/j.ijhydene.2018.08.022. [15]
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Please cite this article in press as: Gonzales RR, et al., Optimization of dilute acid and enzymatic hydrolysis for dark fermentative hydrogen production from the empty fruit bunch of oil palm, International Journal of Hydrogen Energy (2018), https://doi.org/10.1016/ j.ijhydene.2018.08.022