Bioresource Technology 159 (2014) 365–372

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Bioresource Technology

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Application of a novel enzymatic pretreatment using crude hydrolyticextracellular enzyme solution to microalgal biomass for darkfermentative hydrogen production

http://dx.doi.org/10.1016/j.biortech.2014.02.1290960-8524/� 2014 Elsevier Ltd. All rights reserved.

⇑ Corresponding author. Tel.: +82 2 958 6859; fax: +82 2 958 6854.E-mail address: kw512@kist.re.kr (K.-W. Jung).

Yeo-Myeong Yun a, Dong-Hoon Kim b, You-Kwan Oh c, Hang-Sik Shin a, Kyung-Won Jung d,⇑a Department of Civil and Environmental Engineering, KAIST, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Koreab Waste Energy Research Center, Korea Institute of Energy Research, 102 Gajeong-ro, Yuseong-gu, Daejeon 305-343, Republic of Koreac Bioenergy Center, Korea Institute of Energy Research, 102 Gajeong-ro, Yuseong-gu, Daejeon 305-343, Republic of Koread Center for Water Resources Cycle Research, Korea Institute of Science and Technology, P.O. Box 131, Cheongryang, Seoul 130-650, Republic of Korea

h i g h l i g h t s

� A novel enzymatic pretreatment of microalgal biomass using CHEES.� CHEES has a dual role as the hydrolysis enhancer and the co-subsrate supplier.� Lactate and acetate in CHEES acted as co-substrate for DFHP.� The accumulated butyrate in CHEES was not affected.

a r t i c l e i n f o

Article history:Received 9 December 2013Received in revised form 27 February 2014Accepted 28 February 2014Available online 12 March 2014

Keywords:Chlorella vulgarisFood wasteCrude hydrolytic extracellular enzymesolutionCo-substrate

a b s t r a c t

In this study, a novel enzymatic pretreatment of Chlorella vulgaris for dark fermentative hydrogen produc-tion (DFHP) was performed using crude hydrolytic extracellular enzyme solution (CHEES) extracted fromthe H2 fermented effluent of food waste. It was found that the enzyme extracted at 52 h had the highesthydrolysis efficiency of microalgal biomass, resulting in the highest H2 yield of 43.1 mL H2/g dry cellweight along with shorter lag periods. Even though a high amount of VFAs was accumulated in CHEES,especially butyrate, the fermentative bacteria on the DFHP was not affected from product inhibition. Italso appears that the presence of organic acids, especially lactate and acetate, contained in the CHEESfacilitated enhancement of H2 production acted as a co-substrate. Therefore, all of the experimentalresults suggest that the enhancement of DFHP performance caused by CHEES has a dual role as the hydro-lysis enhancer and the co-substrate supplier.

� 2014 Elsevier Ltd. All rights reserved.

1. Introduction

Due to political, economic, and environmental issues that haverisen over the past several decades, biofuels have been in the spot-light as an economically viable and environmentally clean energy.During the past decade, hydrogen (H2) has garnered huge interestas a promising alternative energy carrier among various alternativeenergy sources. This is due to its tremendous potential as a cleanand renewable energy currency. Among various H2 generation pro-cesses, dark fermentative H2 production (DFHP), a term referring tobiological hydrogen production, from renewable biomass has beenone of the focal points in this research field due to its valuable

inherent ability to produce energy simultaneously with waste deg-radation (Jung et al., 2011a).

Among the various affecting factors for DFHP, the selection offeedstock is the most rudimentary progress for determiningwhether successful H2 production or not. Up to date, varioustypes of renewable biomass have been considerably employedas feedstock for DFHP such as agricultural crops and wastebiomass, referring to first- and second- generation biomass,respectively, due to their large potential for reduction of environ-mental issues (IEA, 2010; Singh et al., 2010). On the other hand,recently, the third-generation biomass, micro- and macro algae,has been paid most attention as a technologically viable futureenergy source due to it can overcome the major drawbacks ofthe previous generation biomass regarding land availability andcarbon debt (Joseph et al., 2008; Jung et al., 2011b). Microalgal

Table 1Characteristics of microalgal biomass and food waste.

Items Units C. vulgaris Food waste

Carbohydrate Nutritional componentsof cell (g/100 g)

38.8Protein 49.6Lipid 0.7Ash 9.0Etc. 1.9

TCOD g COD/L 145.1 ± 15.2SCOD g COD/L 52.7 ± 3.4TS g/L 171.5 ± 5.2VS g/L 123.7 ± 10.1Carbohydrate g COD/L 85.6 ± 9.8TN g N/L 4.1 ± 2.5TKN g N/L 2.9 ± 0.2Ammonia mg NH4-N/L 340 ± 17.2pH - 5.2 ± 0.1

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biomass can be converted into a number of different biofuels, e.g.into biodiesel, bioethanol, or biogas (hydrogen and methane)(Singh et al., 2010; Yang et al., 2011). However, most researchhas been one sided on biodiesel production from the lipid extrac-tion of microalgal biomass. According to the reports, even thoughthe main composition of the cell wall of Chlorella vulgaris, one ofthe most popular microalgal biomass, depends on the species orcondition of cultivation, the major accumulated constituent ofmicroalgal biomass is starch and it makes algae become a verypotential feedstock source for biological processes to produce bio-fuels. For a more sustainable development of third-generationbiofuels, researching DFHP is also important (Blumreisingeret al., 1983; Yun et al., 2012).

Taking into consideration the abovementioned issues, the con-siderable efforts to improve DFHP have focused on pretreating thesubstrate over the last three decades by using chemical (mostlyacid/base), thermal, microwave, hydrodynamic cavitation, andultrasonication (pretreatment or combined pretreatment) (Carlssonet al., 2012; Cheng et al., 2011; Pilli et al., 2011; Wu et al., 2012).Even though the effective hydrolysis performance can be antici-pated via physical and chemical pretreatment technique, theirstrong activation also can lead to form inhibitory materials underthe severe conditions of pretreatment (Datar et al., 2007; Junget al., 2011b) such as furfural and hydroxylmethylfurfural. On theother hand, the enzymatic hydrolysis, often referred to as biologicalpretreatment, has been suggested as a more environmentally- andeconomically-friendly perspective to release easily fermentablesugars from a biomass due to the low energy requirement, no corro-sion issues, less byproduct production, and a higher yield undermild environmental conditions, since the first application of micro-bial enzymes in the food industry in the early 1960s (Balat et al.,2008). Up to now, a large number of commercial enzymes (e.g. per-oxidase, oxidoreductase, cellulase, protease, and amylase.) from avariety of different sources have been reported to play an importantrole in an array of waste treatment applications and fermentationindustry (Nguyen et al., 2010; Sangave and Pandit, 2006). However,due to the high cost, the application of commercial enzymes forhydrolysis makes the entire DFHP process become a non-cost-effective process. In addition, the enzyme generally reacts to onlythe specific target material and it needs optimum environmentalconditions (Choi et al., 2010). For instance, the optimal activeconditions of amylase, the hydrolytic enzyme of starch, are similarto the DFHP condition, where there is a pH of 5.5–7.0 and tempera-ture of 30–55 �C (Pandya et al., 2005). Ideally, when using the starchenriched microalgal biomass as feedstock for DFHP, if the enzymecan be extracted from the H2 fermented effluent by using biomassas feedstock, there would be no need to consider the above limitingissues and it can be directly applied to the DFHP process becausethe extracted enzyme was produced from the same operationalconditions as DFHP.

In light of the above research background, a novel enzymaticpretreatment of microalgal biomass on DFHP was performed byusing a crude hydrolytic extracellular enzyme solution (CHEES)extracted from the H2 fermented effluent. To minimize the effectof seeding sludge during the CHEES production on further proce-dures, including hydrolysis and DFHP, and to maximize the eco-nomic and environment values, the DFHP of food waste wasconducted without the addition of external inoculum to produceCHEES as described in previous work (Kim et al., 2009). The re-duced sugar concentration was monitored for the evaluation ofhydrolysis and the optimal sampling time of CHEES from the H2

fermenter. To ascertain the effect of CHEES on DFHP, severalbatch tests were carried out. To the best of the authors’ knowl-edge, this is the first report regarding a novel enzymatic pretreat-ment of microalgal biomass optimized for DFHP. Lastly, the H2

fermented effluent using CHEES was continuously treated using

anaerobic sequencing batch reactor (ASBR) for methane (CH4)production.

2. Methods

2.1. Inoculum and feedstock preparation

The source of the anaerobic mixed culture was collected froman anaerobic digester at a local wastewater treatment plant(Daejeon, Korea). The pH, alkalinity, and volatile suspended solid(VSS) concentration of the sludge were 7.6, 2.83 g CaCO3/L, and5.5 g/L, respectively. The sludge was heat-treated at 90 �C for20 min and then cooled to room temperature in an attempt toharvest only spore-forming anaerobic bacteria such as Clostridiumsp. (Jung et al., 2010).

C. vulgaris, freshwater microalgal biomass, was used as feed-stock for this DFHP experiment, and it was stored at 4 �C to pre-serve its characteristics. The total chemical oxygen demand(COD) concentration of C. vulgaris was 1.37 g COD/g dry cell weight(dcw). In order to produce CHEES via DFHP from food waste, foodwaste was collected from a KAIST cafeteria and was shredded by agrinder to be smaller than 5 mm in diameter. The characteristics ofC. vulgaris and food waste used in this experiment are shown inTable 1.

2.2. Batch fermentation

In batch test I, the H2 fermentation of food waste without theaddition of inoculum was conducted to produce CHEES, as de-scribed in previous work (Kim et al., 2009). In detail, prior to theaddition to the reactor, food waste was boiled at 90 �C for20 min. A certain amount of food waste and tap water were addedinto the batch fermenter to the carbohydrate concentration of 30 gcarbo. COD/L in order to reach a working volume of 2.0 L (total vol-ume = 3.5 L). N2 gas was purged in order to provide an anaerobiccondition. By using a pH sensor and pH controller, the initial pHwas adjusted at 7.0 ± 0.1, and the operational pH during fermenta-tion was maintained at higher than 5.5 ± 0.2 by adding 3 N of KOH.

During H2 fermentation (batch test I), the mixed liquors weredirectly taken from sampling ports in the reactor at determinedtime intervals from 10 h to 52 h of operation time. In order toobtain the supernatant (enriched enzyme solution), the centrifuga-tion at 7000 rpm for 10 min was applied, and then all sampleswere immediately filtered through a 0.45 lm GF/C paper (What-man, USA) to enrich CHEES.

Batch test II was performed to check the pretreatment efficiencyof CHEES. Every enriched CHEES at different sampling times wasadded to the 7.61 g dcw microalgal biomass in order to make itbe 100 mL and easier to prepare the substrate concentration of

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76.1 g dcw/L for future batch tests, which were optimized in aprevious study (Yun et al., 2012). In order to define the optimumenzyme extraction point, changes in reducing the sugar concentra-tion were monitored at 2 h intervals.

Batch test III was conducted using the enzymatic pretreatedmicroalgal biomass in the batch test II as feedstock for DFHP. A to-tal volume of 250 mL serum bottles (working volume = 100 mL)was seeded with the heat-pretreated sludge equivalent to 30% ofthe working volume, and filled with a specified amount of microal-gal biomass with CHEES and tap water. There was no addition of anexternal nutrient. The substrate concentration was fixed at76 g dcw/L, and the initial pH was adjusted at 7.4 by adding 3 Nof KOH. The pH was not controlled during fermentation.

All batch tests were conducted in a temperature controlledroom of 35 �C ± 1, and the mixing rate was 150 rpm. Batch testswere carried out in triplicate and average values were determinedfor each set.

2.3. CH4 production: ASBR system

For the CH4 production, an ASBR system (working volume 3.0 L;380 mm high by 135 mm ID) was applied. One cycle period for theASBR was 24 h: 18 h reaction time, 5 h settling time, and 1 h fillingand decanting. The OLR was controlled by HRT (30–12 d or1.0–2.5 g COD/L/d) and substrate concentration (30–50 g COD/Lor 2.0–3.34 g COD/L/d). The solid retention time (SRT) has beencalculated as the ratio of the mass of VSS within the reactor tothe mass of VSS in the effluents removed from the ASBR (Luoet al., 2013). As a result, the calculated SRT at each HRT conditionswere 27.7, 22.5, 19.3, 16.9, and 9.2 d at HRT of 30, 25, 20, 15, and12 d, respectively. The seed sludge was taken from anaerobicdigestion. Reactor was installed in a temperature controlled roomat 35 �C ± 1.

2.4. H2 fermentation analysis

The measured biogas production was adjusted to the standardconditions of temperature (0 �C) and pressure (760 mmHg) (STP).To describe the H2 production, a cumulative H2 production curvewas described by the modified Gompertz Eq. (1) (Chen et al., 2006).

HðtÞ ¼ P � exp � expR0 � e

Pðk� tÞ þ 1

� �� �ð1Þ

where H(t) = cumulative H2 production (L) at cultivation time t (h);P = ultimate H2 production (L); R0 = H2 production rate (L/L/h);k = lag phase (h); and e = exp(1) = 2.71828.

H2 production was calculated from the headspace measure-ments of gas composition and the total volume of biogas producedat each time interval using the mass balance Eq. (2).

VH2 ;i ¼ VH2 ;i�1 þ VWCH2 ;i þ VG;iCH2 ;i � VG;i�1CH2 ;i�1 ð2Þ

where VH2 ;i and VH2 ;i�1 are the volumes of cumulative hydrogen(mL) calculated after the ith and the previous measurement; VW

is the total gas volume measured by the water displacementmethod (mL); CH2 ;i is the concentration of H2 gas in the total gasmeasured by the water displacement method (%); VG,i and VG,i � 1

are the volumes of gas in the headspace of the bottle for the ithand previous measurement (mL); CH2 ;i and CH2 ;i�1 are the percentH2 in the headspace of the bottle for the ith and the previous mea-surement (Argun et al., 2008).

2.5. Analytical method

To determine the H2 content in the biogas, a gas chromatogra-phy (GC, Cow Mac series 580, Gow-Mac Instrument Co., USA)

equipped with a thermal conductivity detector and a1.8 m � 3.2 mm stainless-steel column packed with molecularsieve 5 A was employed with N2 as a carrier gas. The contents ofCH4, N2, and CO2 were measured using a GC of the same modelnoted previously with a 1.8 m � 3.2 mm stainless-steel columnpacked with porapak Q (80/100 mesh) using helium as a carriergas. The concentrations of organic acids (VFAs, C2–C6) and lacticacid were measured by a high-performance liquid chromatography(HPLC) (Finnigan Spectra SYSTEM LC, Thermo Electron Co.) usingan ultraviolet (210 nm) detector (UV1000, Thermo Electron) andan 100 � 7.8 mm Fast Acid Analysis column (Bio-Rad Lab.) with0.005 M H2SO4 as a mobile phase at a flow rate of 0.6 mL/min.The COD and pH of the samples were measured according to Stan-dard Methods (APHA, 1998). The chemical components of microal-gae biomass were analyzed by the Korea Food Research Instituteaccording to the Korean Food Standards Codex (2009) and the Kjel-dahl method (Jones and Woods, 1986; Merill and Watt, 1973;Schakel et al., 1996). The concentration of reducing sugar was mea-sured by a 3,5-dinitrosalicylic acid (DNS) method (Miller, 1959).Microalgal biomass observation was conducted via digital micros-copy (Axioscpoe, Zeiss) and use of a digital camera (Axiocam MRm,Zeiss).

2.6. Microbial analysis

To identify the microbial communities in batch test I and III, theDNA samples were taken from each batch fermenter and then itwas extracted using an Ultraclean Soil DNA Kit (Cat # 12800-50;Mo Bio Laboratory Inc., USA). The 16S rDNA fragments were storedat �20 �C before being amplified by polymerase chain reaction(PCR). The region corresponding to positions 357F and 518R inthe 16S rDNA of Escherichia coli was PCR-amplified using theforward primer EUB357f (50-CCTACGGGAGGCAGCAG-30) with aGC clamp (50-CGCCCG CCGCGCCCCGCGCCCGGCCCGCCGCCCCCGCCCC-30) at the 50 end to stabilize the melting behavior of theDNA fragments and the reverse primer UNIV518r (50-ATTACCGCGGCTGCTGG-30). PCR amplification was conducted in anautomated thermal cycler (MWG-Bio TECH, Germany) using thefollowing protocol: initial denaturation for 4 min at 94 �C, anneal-ing for 40 s at 55 �C, extension for 1 min at 72 �C, followed by a fi-nal extension for 8 min at 72 �C. PCR mixtures had a final volume of50 ll of 10 � PCR buffer, 0.8 mM MgSO4, 0.5 mM of each primer,0.1 mM dNTP, 25 pg template, and 1 U polymerase. PCR productswere electrophoresed on 2% (wt./vol) agarose gel in 1 � TAE for30 min for 50 V, and then checked with ethidium bromide stainingto confirm the amplification. Denaturing gradient gel electrophore-sis (DGGE) was carried out using a Dcode Universal MutationDetection System (BioRad, USA) in accordance with the manufac-turer’s instruments. PCR products were electrophoresed in 1 � TAEbuffer for 480 min at 70 V and 60 �C on a polyacrylamide gel (7.5%)containing a linear gradient ranging from 40% to 60% denaturant.After electrophoresis, the polyacrylamide gel was stained withethidium bromide for 30 min, and then visualized on a UV transil-luminator. Most bands were excised from the DGGE polyacryl-amide gel for 16S rDNA sequencing. DNA was eluted from theexcised bands by immersion in 20 ll of Tris EDTA buffer (pH 8.0)for one day, and then PCR-amplified with the forward primerEUB357f without a GC clamp and the reverse primer UNIV518r.After PCR amplification, PCR products were purified using a Multi-screen Vacuum Manifold (MILLIPORE com., USA). All strands of thepurified PCR products were sequenced with primers EUB357f by anABIPRISM Big Terminator Cycle Sequencing Kit (Applied Biosys-tems, USA) in accordance with the manufacturer’s instructions.Search of the GenBank database was conducted using the BLASTprogram.

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3. Results and discussion

3.1. Batch test I: DFHP from food waste without external inoculumaddition

The objective of batch test I was to obtain CHEES during DFHPfrom food waste without the addition of an external inoculum.Fig. 1 shows the time frame of cumulative H2 production fromthe food waste. During the entire H2 fermentation (tests were donethree times), CH4 was not detected and the curves were well fittedby the modified Gompertz equation with a high R2 value of 0.99.Although there was no addition of inoculum, the fermentation be-gan in about 10 h of operation and it was completed within 52 h.Finally, the H2 yield of 181.3 mL H2/g hexoseadded, or 1.6 mol H2/mol hexoseconsumed was obtained, as shown in Table 1, which wassimilar with previous research (Kim et al., 2009). In terms of organ-ic acid production, DFHP could be accomplished by acetate andbutyrate production with propionate and lactate, which are knownto be byproducts that are not related to H2 fermentation (Hawkeset al., 2002). As provided in Table 1, acetate and butyrate were themain VFA components with a carbohydrate removal rate of92.0 ± 0.6% (data not shown). These results indicated that the DFHPof food waste without the addition of an external inoculum wassuccessfully reproduced in this study.

Fig. 2. DGGE profiles of the 16S rDNA gene fragment after batch test I and III.

3.2. Batch test II: Extraction of a CHEES from H2 fermeter

According to the report, the various extracellular enzymes couldbe produced by H2-producing bacteria from a substrate (carbohy-drate), mainly Clostridium sp., including amylase, cellulase, lipase,and protease (HPA, 2008). In order to detect dominant microorgan-isms, a mixed sample was taken from the batch fermenter and thebacterial diversity was monitored by polymerase chain reaction–denaturing gradient gel electrophoresis (PCR–DGGE). From theDGGE profile (Fig. 2), a total of 10 bands were detected, where eachband represents one microbial species. The results of 16S rDNA se-quences shown in Table 3 reveal that 8 matched well with H2-proudcing bacteria, showing a high similarity level of about 97%.Clostridium butyricum (band #2), Clostridium saccharobutylicum(band #3), and Clostridium acetobutyricum (band 9) were knownto be producers of amylase and cellulase. Even though there wasno knowing how much of them exist in the fermenter, this meansthat the crude enzyme from the DFHP of food waste could be

Fig. 1. Cumulative H2 production of food waste without external inoculum addition (Relegend, the reader is referred to the web version of this article.)

applied as an enzymatic pretreatment material to improve thehydrolysis of microalgal biomass with an economic and viableprocess.

However, among Clostridium sp., Clostridium perfringens (band#7) and Clostridium sporogenes (band #12) were also detected,which are well-known phospholipase and protease producers fromfeedstock (HPA, 2008). This means that, unlike the application of acommercial specific enzyme, the most considerable factor in this

d line: sampling time). (For interpretation of the references to colour in this figure

Table 3Closet match of DGGE fragments determined by their 16S rDNA and isolated microorganisms.

Sample Band Closet match Accession number Length (bp) Similarity (%)

Batch test I 1 Lactobacillus delbrueckii HQ293115 149 992 Clostridium butyricum AJ458421 145 973 Clostridium saccharobutylicum NR_036951 156 994 Clostridium baratii JN048942 166 995 Clostridium botulinum FR773526 156 956 Lactobacillus fermentum EU931242 147 997 Clostridium perfringens L77965 150 938 Clostridium acetobutyricum DQ831124 172 969 Clostridium sp. TERIGK12 EF605259 169 98

10 Eubacterium pyruvativorans AJ310135 168 9011 Clostridium peptidivorans AF156796 166 9812 Clostridium sporogenes JN048943 150 96

Batch test III 10 Clostridium saccharobutylicum NR_036951 139 9720 Clostridium acetobutylicum DQ831124 166 9630 Eubacterium pyruvativorans AJ310135 152 9040 Clostridium diolois NR_025542 150 9850 Clostridium beijerinckii AJ458421 172 9760 Not matched – – –70 Clostridium sp. AY827856 170 95

Table 4Average gas and liquid phase parameters in batch fermentation of microalgal biomass with CHEES.

Time (h) H2 yield (mL H2/g dcw) k (h) Rm (mL H2/L/h) Reducing sugar removal (%) Organic acids production (%) Total organic acids (mg COD/L)

HLaa HAca HPra HBua EtOHa

Control 30.3 9.9 20.6 90.6 0 33 6 54 7 11.959 ± 8010 31.6 8.7 21.7 91.3 3 34 5 53 5 12.110 ± 9030 37.0 6.9 16.8 92.9 3 29 2 59 7 19.410 ± 23040 39.7 5.6 18.8 90.2 4 28 3 60 5 21.521 ± 10052 43.1 4.8 21.8 93.0 5 26 2 61 6 23.512 ± 12052b 30.6 9.6 21.1 91.1 0 39 5 54 2 12.234 ± 65

a HLa = Lactate; HAc = acetate; HPr = propionate; HBu = butyrate; EtOH = ethanol.b Addition of boiled CHEES.

Table 2Average gas and liquid phase parameters in batch fermentation of food waste without inoculum addition.

Time (h) H2 yield (mL H2/g hexoseadded) k (h) Rm (mL H2/L/h) Organic acids production (%) Total organic acids (mg COD/L)

HLaa HAca HPra HBua EtOHa

10 9.6 – – 3 36 – 57 4 969 ± 2320 118.6 – – 8 34 – 52 6 11,344 ± 10230 169.3 – – 13 33 3 44 7 15,851 ± 11340 176.7 – – 13 32 2 45 8 16,920 ± 12252 181.3 10.4 1,075 15 30 2 45 8 18,540 ± 115

a HLa = Lactate; HAc = acetate; HPr = propionate; HBu = butyrate; EtOH = ethanol.

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study is the existence of protease when using a crude enzyme solu-tion because this can degrade and destroy other enzymes (Satoshiet al., 1986). In addition, enzyme concentration is also the decisivefactor for enzymatic hydrolysis efficiency, and thus, for these rea-sons, the optimal sampling time during DFHP was performed at10 (starting point), 20, 30, 40, and 52 h (finishing point). Fig. 3shows the time frame of reducing sugar concentration that origi-nated from C. vulgaris using various collected CHEES, and conse-quently, the highest improvement of hydrolysis efficiency wasobserved at over 5200 mg/L after 8 h of reaction time (over 560%increased), where the CHEES of 52 h (control = 920 mg/L). Eventhough the total enzyme concentration was not monitored becauseit was hard to analyze the conjugated enzyme, it can be indirectlyassumed that the higher concentration of enzymes derived fromthe higher microbial population than the initial fermentation per-iod leads to the enhancement of hydrolysis efficiency. In addition,as is illustrated clearly in Fig. 4, microalgal biomass cell wall was

disrupted by CHEES of 52 h after 8 h of reaction time. Therefore,these results clearly indicate that the CHEES derived here fromthe DFHP of food waste is a potent material for the alternativeenzymatic pretreatment of microalgal biomass, as well as theenhancement of H2 production performance. This is discussed fur-ther in the next chapter.

3.3. Batch test III: DFHP of microalgal biomass with CHEES

In order to feasibly enhance H2 productivity, several batch testswere conducted using the extracted CHEES at different times fromthe H2 fermenter. Moreover, unusually, CHEES was directly addedto the batch fermenter in this study, and then fermentation beganbecause the hydrolysis reaction of CHEES and the lag period of thebatch test (control: raw C. vulgaris as feedstock) were similarlywithin 10 h, as shown in Fig. 5 and Table 4, respectively. As a result,the highest H2 yield was 43.1 mL H2/g dcw and the highest H2

Fig. 3. Change of hydrolysis rate using different collected CHEES from batch fermenter (Control: mixing with DI water and C. vulgaris).

Fig. 4. Electro-microscopic images of microalgal cell: (a) microalgal biomass without CHEES; (b) microalgal biomass with CHEES.

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production rate was 21.8 mL H2/L/h. The lag period was approxi-mately halved compared to the control test. These results coin-cided with the hydrolysis rates observed in different extractedCHEES samples, and they suggest that a higher enzyme activitycould result in a more complete hydrolysis of C. vulgaris, which fur-ther leads to higher H2 productivity. Additionally, in order to knowthe reason for enhancing the hydrolysis and DFHP caused by thesole enzyme activity, or whether those microorganisms externallyinjected cannot be sifted out during the extraction process, anadditional batch test was conducted using boiled CHEES at 90 �Cfor 20 min. As presented in Table 4, the H2 fermentation perfor-mances were similar with the control test, which might have re-sulted from the destruction of enzymes. In other words, it couldbe concluded that the enhancement of hydrolysis and DFHP perfor-mance was caused by only CHEES, not microorganisms, because itis well known that Clostridium sp. could make spores when envi-ronments are not suitable for them, but the germination can occurafter a while in a favorable condition.

Interestingly, the concentration of butyrate was significantly in-creased after fermentation compared to the control test, while theconcentration of acetate was decreased. Moreover, the lactate con-centration of CHEES was 2630 ± 120 mg COD/L (Table 2), but it wasdecreased to 1170 ± 50 mg COD/L after DFHP (Table 4). Accordingto the reports, the DFHP efficiency is lower when metabolic flowsto the lactate rather than acetate and butyrate, while lactate canbe oxidized to butyrate by C. acetobutylicum (also detected in this

study, as shown in Fig. 2 and Table 3) coupled with acetate reduc-tion to become energetically feasible (Agler et al., 2010; Juanget al., 2011; Kim et al., 2012) via Eq. (3), resulting in 1.5 mol buty-rate production.

Acetateþ 2 Lactate! 1:5 ButyrateþH2 þ CO2 ð3Þ

Furthermore, in comparison to the H2 productivity in previousstudies, the H2 yield obtained in this study was higher than acid(37.0 mL H2/g dcw), ultrasonication (36.5 mL H2/g dcw), and com-bined (acid + ultrasonication, 42.1 mL H2/g dcw) pretreatmentswith a low energy requirement for pretreatment (Yun et al.,2013). Therefore, all of the experimental results suggest that theenhancement of DFHP performance caused by CHEES has a dualrole as a hydrolysis enhancer and a co-substrate supplier.

3.4. Continuous test: CH4 production from H2 fermented effluent

To maximize bioenergy recovery, ASBR system was operated asa second-stage fermentation system for CH4 production from H2

fermented effluent during 234 days, and CH4 content was around65–73% during whole operation period. Fig. 6 shows the dailyvariations of CH4 yield and CH4 production rate and the averagereactor performance at various operational conditions was ar-ranged in Table 5. The overall COD removal efficiency indicatesthat the H2 fermented effluent of this study is a favorable feedstockfor CH4 production. At the first 35 days, the reactor was operated at

Fig. 5. Cumulative H2 production of C. vulgaris using extracted CHEES at different time (Control: mixing with DI water and C. vulgaris).

Fig. 6. Daily CH4 production from the H2 fermented effluent at different HRTs and substrate concentration.

Table 5Average CH4 production performance at various operational conditions.

Conditions CH4 yield (mL CH4/g COD) CH4 production rate (mL CH4/L/d) COD removal (%) VS reduction (%)

HRT (day) OLR (g COD/L/d)

30 1.0 81.8 ± 6.9 – 90 6425 1.2 108.6 ± 3.8 130.4 ± 6.5 90 6520 1.5 173.9 ± 7.3 261.2 ± 8.4 93 7515 2.0 230.6 ± 3.5 461.3 ± 4.8 92 6412 2.5 – – 50 52

15 2.0 229.6 ± 5.2 462.5 ± 7.5 93 742.67 315.9 ± 4.8 592.4 ± 10.1 91 713.34 330.2 ± 8.6 436.3 ± 9.0 82 53

Y.-M. Yun et al. / Bioresource Technology 159 (2014) 365–372 371

a HRT of 30 days (OLR = 1.0 gCOD/L/d) as a start-up period, andsubsequently, the HRT condition was gradually decreased to12 days (OLR = 2.5 g COD/L/d), when stable biogas productivitywas obtained over 15 days in each condition. As the OLR increased

up to 2.0 g COD/L/d (HRT 15 days), both CH4 yield and productionrate increased simultaneously, resulting in the highest CH4 yieldand its production rate of 230.6 ± 3.5 mL CH4/g COD and461.3 ± 4.8 mL CH4/L/d with 90% COD removal (64% VS reduction),

372 Y.-M. Yun et al. / Bioresource Technology 159 (2014) 365–372

respectively. However, the both decrease of COD removal and VSreduction of around 50% lead to failure of reactor performance ata HRT of 12 days. Hence, the HRT was increased to 15 days, andthen, the reactor recovered rapidly after 14 days. After optimizingHRT condition, the OLR was gradually increased up to 3.34 g COD/L/d by increasing substrate concentration from 30 g COD/L to50 g COD/L. Even though the maximum CH4 yield of 330.2 ±8.6 mL CH4/g COD was obtained at 3.34 g COD/L/d, the OLR of2.67 g COD/L/d was optimal for maximizing the CH4 productionrate (592.4 ± 10.1 mL CH4/L/d), and thus, the latter condition wasselected as optimal condition for CH4 production because produc-tion rate is more important factor in real field in economic point ofview. Based on the experimental results of H2 and CH4 production,the bioenergy recovery efficiency of the whole system were evalu-ated using the H2 yield of batch test I, III, and the highest CH4 yields(Jung et al., 2012). It was found that 56.7% biogas conversion (6.2%of the influent COD (batch test I), 1.6% of the influent COD (batchtest III), and 48.9% of the influent COD (CH4 production) wasachieved in this system; however, further additional treatmentsuch as fertilization or dry digestion on the sediment derived fromcentrifugation (about 35% of influent COD) should be required toobtain more bioenergy and to achieve zero-waste emission system.

4. Conclusion

A novel enzymatic pretreatment of microalgal biomass on DFHPwas performed by using CHEES derived from the H2 fermenter. Itwas found that the CHEES extracted at 52 h had the highest hydro-lysis efficiency of microalgal biomass, resulting in the highest H2

yield of 43.1 mL H2/g dcw along with shorter lag periods. In addi-tion, it appears that the presence of lactate and acetate containedin the CHEES facilitated the enhancement of H2 production bychanges in the metabolic pathway. These results suggest that theCHEES is a potent material for the alternative enzymatic pretreat-ment of microalgal biomass for DFHP.

Acknowledgements

This work was supported by Grants from the Eco-STAR ProjectProgram of the ministry of Korean Environmental Technology(EW21-07-11) and the National Research Foundation of Korea(NRF) Grant funded by the Korea government Ministry of Educa-tion, Science and Technology (MEST) (NRF-2012M1A2A2026587).

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