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Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor
Bioresource Technology xxx (2014) xxx–xxx
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Short Communication
Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor Gahyun Baek, Jaai Kim, Changsoo Lee ⇑ School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), 50 UNIST-gil, Eonyang-eup, Ulju-gun, Ulsan 689-798, Republic of Korea
h i g h l i g h t s Effects of enhanced IRB activity on anaerobic digestion of WAS were studied. Raised IRB activity by biostimulation/augmentation led to enhanced biomethanation. Acinetobacter- and Spirochaetales-related populations were likely the dominant IRBs.
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Article history: Received 18 April 2014 Received in revised form 15 May 2014 Accepted 16 May 2014 Available online xxxx Keywords: Biomethanation Iron oxyhydroxide Iron-reducing bacteria Microbial community structure Waste activated sludge
a b s t r a c t This study investigated the potential of enhancing the activity of iron-reducing bacteria (IRBs) to increase the biomethanation rate of waste activate sludge (WAS). The effects of biostimulation by ferric oxyhydroxide (Phase 2) and bioaugmentation with an enriched IRB consortium (Phase 3) were examined in a continuous anaerobic reactor treating WAS. Compared to the control operation (Phase 1), significant rises in methane yield (10.8–59.4%) and production rate (24.5–52.9%) were demonstrated by the biostimulation and bioaugmentation treatments. Visible structural changes were observed in bacterial community with the phases while not in archaeal community. Acinetobacter- and Spirochaetales-related populations were likely the major players driving anaerobic iron respiration and thus leading to enhanced biomethanation performance, in Phases 2 and 3, respectively. Our results suggest an interesting new potential for enhancing biomethanation of WAS. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Global primary energy demand today is about 5.8 1011 GJ and is projected to reach 8.7 1011 GJ by 2040 (USEIA, 2013). The rapidly increasing energy demand, along with growing concerns for environmental protection, has fostered the search for alternative energy sources. Production of biogas, composed of CH4 and CO2 mainly, from organic wastes via anaerobic digestion (AD) is a viable option for producing renewable energy. Although gaining growing attention, AD has some limitations attributable to the slow growth rate of anaerobic microbes involved in the methanogenic pathway, for example, longer retention time and lower organic removal rate than aerobic treatment (Ahring, 2003). Such limitations reduce the feasibility of AD and hinder its wider applications in practice. Although many efforts have therefore been directed to improve AD performance, previous works have been confined mostly to changing reactor design and process configura⇑ Corresponding author. Tel.: +82 52 217 2822; fax: +82 52 217 2819. E-mail address: [email protected] (C. Lee).
tion. AD is a series of biological reactions performed by various microbial groups, and therefore its performance basically depends on the harmonized activity of the microbes involved. This suggests that approaches at the microbial community level as well as the process engineering level are necessary for fundamentally improving AD performance. Iron-reducing bacteria (IRBs) are a group of bacteria capable of oxidizing various organic compounds, including refractory compounds such as aromatic hydrocarbons, using ferric iron as electron acceptor under anaerobic conditions (Kim et al., 2014). IRBs play a critical role in iron cycling in both natural and engineered systems, and particular attention has recently been paid to their role in energy-harvesting bioprocesses such as bioelectrochemical cells and AD. The electroactive bacteria in microbial fuel cells (MFCs) are thought to be mostly IRBs, with Geobacter and Shewanella species often being the major populations. These bacteria directly or indirectly transfer electrons released from the oxidation of organic matter to the anode and then to the cathode, generating a flow of electrons between the electrodes, that is, electricity. Although IRBs may not be the major players involved in the
http://dx.doi.org/10.1016/j.biortech.2014.05.052 0960-8524/Ó 2014 Elsevier Ltd. All rights reserved.
Please cite this article in press as: Baek, G., et al. Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor. Bioresour. Technol. (2014), http://dx.doi.org/10.1016/j.biortech.2014.05.052
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G. Baek et al. / Bioresource Technology xxx (2014) xxx–xxx
methanogenic pathway, some previous studies reported interesting observations on their potential function in AD systems. Ivanov et al. (2002) investigated the effect of different iron compounds, i.e., ferric hydroxide, iron-containing clay, and iron ore, on the anaerobic treatment of fat-rich wastewater. The tests amended with ferric iron sources clearly showed enhanced removal rate and biogas yield. Zhang et al. (2010) also observed a positive effect of ferric iron on the methane production from pretreated sewage sludge. Although little biological evidence was given, such enhanced biomethanation performance may be attributed to IRB activity stimulated by ferric iron. A recent study reported that methanogenesis rates from acetate and ethanol were considerably increased by adding ferric oxides in the AD tests using rice paddy soil as the inoculum source (Kato et al., 2012). Interestingly, in that study, it was revealed by 16S rRNA gene analysis that the growth of Geobacter species was stimulated in the cultures supplemented with ferric oxides. These observations may suggest the possibility for enhancing biomethanation through ferric iron addition, yet very limited information is available on this potential particularly for continuous processes. This study therefore aims to examine how process performance and microbial community respond to the addition of ferric oxyhydroxide in a continuous reactor anaerobically treating waste activated sludge (WAS). WAS is one of the largest sources of organic waste and, its treatment is today among the major practical applications of AD. For a comprehensive insight into the underlying phenomena, changes in physicochemical parameters as well as microbial community structure in the reactor were monitored during the biostimulation (i.e., addition of ferric iron source only) and bioaugmentation (i.e., introduction of exogenous IRBs into the reactor) trials over 6 months. To the best of our knowledge, this is one of the first reports that provides evidence for enhanced biomethanation of WAS under iron-reducing conditions.
2. Methods 2.1. Bioreactor operation A continuously stirred tank reactor (CSTR) of a 2-L working volume was anaerobically operated to treat WAS collected from local sewage treatment plant. The reactor was initially inoculated at a 20% rate (v/v) with anaerobic sludge obtained from a full-scale sewage sludge digester. After the batch start-up till biogas production ceased, continuous feeding was started with the feed WAS (regarded as day 0) at 20-day hydraulic retention time (HRT). The reactor was fed on a daily basis and maintained at 35 ± 2 °C with an automatic temperature controller. The pH remained within 7.0–7.4 without adding any buffering reagent throughout the operation period. During over 6 months of continuous operation, the input concentrations of total chemical oxygen demand (COD) and volatile solids (VS) in the feed WAS varied within the ranges of 10.0–10.9 g/L and 6.9–8.1 g/L, respectively. The organic loading rate (OLR) accordingly varied between 0.50 and 0.54 g/Ld in COD and between 0.35 and 0.41 g/Ld in VS. The soluble to total COD ratio was below 2%, indicating that most organics in the feed WAS are in the form of suspended particles. The reactor was fed solely with WAS for the initial 61 days (Phase 1), and ferric oxyhydroxide was added in the feed WAS (final Fe concentration, 20 mM) from day 62 onwards (Phase 2). A microbial culture enriched under iron-reducing conditions was once introduced into the reactor (final volatile suspended solids concentration (VSS), 405 mg/L) on day 122, and the experimental period thereafter was defined as Phase 3 (Fig. 1). The performance of reactor was monitored by periodic sampling (every 2–4 days during the whole
experimental period) and analysis of the effluent and biogas samples. 2.2. Enrichment culture of IRBs An iron-reducing bacterial consortium (ATCC 55339) obtained from the American Type Culture Collection was used as the enrichment source of IRBs. Enrichment was achieved by repeated subcultures as previously described with modifications (Ivanov et al., 2010). The consortium was subcultured weekly by adding 30 mL of anaerobic sludge fluid and 20 mL of distilled water to 20 mL of the preceding culture in a 100-mL gas-tight bottle. Ferric citrate was added as the ferric iron source for the growth of IRBs (final Fe concentration, 16 mM). The subculturing was repeated seven times, the last cycle was scaled-up in a 2-L culture volume to attain sufficient biomass for the bioaugmentation test. The iron-reducing activity was confirmed every cycle by checking the increase in Fe2+ concentration in the culture medium. 2.3. DGGE analysis Genomic DNA was extracted from the reactor samples using an automated nucleic acid extractor (ExiProgen, Bioneer, Daejeon, Korea) according to the manufacturer’s instructions. One milliliter of a sample was pelleted in a 1.5-mL tube at 13,000g for 3 min and washed by repeated centrifuging (13,000g, 1 min), decanting (900 lL), and resuspending (up to 1 mL in distilled water) to eliminate impurities. A 200-lL portion of the suspension was loaded on the extractor with the ExiProgen Bacteria Genomic DNA Kit (Bioneer). The extracted DNA was eluted in 200 lL of elution buffer and stored at –20 °C until use. Archaeal and bacterial 16S rRNA gene fragments for DGGE analysis were prepared by touch-down polymerase chain reaction (PCR) using ARC787F/1059R and BAC338F/805R primer sets, respectively, as previously described (Kim et al., 2013). DGGE electrophoresis was performed using a D-code system (Bio-Rad, Hercules, CA) as previously described with denaturant gradients of 35–65% and 25–60% for the archaeal and bacterial runs, respectively (Kim et al., 2013). The DGGE gels were stained with SYBR Safe dye (Molecular Probe, Eugene, OR) and scanned under blue light for visualization of the banding patterns. A binary matrix was constructed for each gel by scoring the presence or absence of individual DGGE bands as 1 or 0, respectively, using an image-processing software (TotalLab 1D, TotalLab, Newcastle, UK). The similarity between the analyzed microbial community structures was measured by calculating the Dice coefficient of similarity (CS, %) based on the binary matrices in PC-ORD 5.0 (MjM software, Gleneden Beach, OR). Bands of interest were excised from the gels and eluted in 40 lL of sterile water overnight. A 2-lL aliquot of the elution was then reamplified using the same primer sets as for DGGE analysis. The final PCR products were purified, cloned, and sequenced for identification, and the obtained sequence information was analyzed against the GenBank and RDP databases. All nucleotide sequences reported in this paper were deposited in the GenBank database: KJ679856–679873. 2.4. Chemical analyses Solids were analyzed according to the protocols in Standard Methods (APHA-AWWA-WEF., 2005). COD was spectrophotometrically measured using HS-COD-MR kit (HUMAS, Daejon, Korea). Fe2+ and total Fe concentrations were measured using HS-Fe2+ and HS-Fe(T) kits (HUMAS), respectively. Volatile fatty acids (VFAs, C2–C6) were measured using a gas chromatograph (7820A, Agilent, Palo Alto, CA) coupled with a flame ionization detector and an Innowax column (Agilent). Methane content in biogas was
Please cite this article in press as: Baek, G., et al. Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor. Bioresour. Technol. (2014), http://dx.doi.org/10.1016/j.biortech.2014.05.052
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Fig. 1. Effluent COD concentration and methane production rate during the reactor operation.
determined using the same gas chromatograph equipped with a thermal conductivity detector and a ShinCarbon ST column (Restek, Bellefonte, PA). Samples for soluble COD and VFA measurements were prepared by filtering through a 0.45-lm-pore membrane filter. All analyses were performed at least in duplicate.
3. Results and discussion 3.1. Reactor performance The reactor was operated in continuous mode for 184 days, and the performance profiles throughout the trial are shown in Fig. 1. The effluent COD concentration fluctuated between 6.4 and 12.2 g/L during the initial 40-day period (i.e., 2 turnovers). The reactor performance stabilized after 2 months of operation in Phase 1, and the methane content remained between 65.7% and 74.1% thereafter until the end of the experiment. Table 1 summarizes the changes in steady-state performance of the reactor over Phases 1–3. Steady-state data were obtained by analyzing three to five samples collected at different operating times in each phase. The COD and volatile solids (VS) removal rates in Phases 1 and 2 were comparable to those from previous studies on anaerobic WAS treatment (Bolzonella et al., 2012; Feng et al., 2014). However, those were apparently lower in Phase 3, which may reflect an increase in microbial biomass in the reactor due to the bioaugmentation with IRBs (final VSS concentration, 405 mg/L). Microbial
cells are readily measured as COD and VS because their structures are composed of organic compounds. This may raise the residual concentrations of COD and VS (mostly VSS (>96%) in all test phases), leading to decreases in their removal rates. As expected, the concentration of Fe2+, and thus the Fe2+ to total Fe ratio, increased with the implementation of biostimulation in Phase 2 (2.3- and 1.4-fold over Phase 1, respectively) and bioaugmentation in Phase 3 (3.0- and 2.3-fold over Phase 1, respectively). This indicates that IRB activity was effectively enhanced by the addition of ferric oxyhydroxide and further by the augmentation with enriched IRBs from ATCC 55339. Interestingly, likely according to the enhanced IRB activity, methane yield and production rate significantly increased over the test phases (t-test, p < 0.05). The methane production rates in Phases 2 and 3 were greater than in Phase 1 by 24.5% and 52.9%, respectively. Methane yield was also higher in Phases 2 and 3 than in Phase 1 by 10.8% and 59.4%, respectively. These suggest that the enhanced IRB activity likely had a positive effect on biomethanation of WAS in our reactor. In agreement with our observations, a recent study on batch AD of WAS reported a significant increase in methane yield (29.5%) by adding rusty iron scrap containing different types of ferric oxides (Zhang et al., 2014). In that study, the authors suggested that microbial ferric reduction was induced by the iron rust added, and as a consequence, degradation rate of complex organic compounds was enhanced. Such an increase in methane yield without pretreatment of feed sludge or alteration of process configuration suggests an interesting potential for enhancing digestibility and
Table 1 Reactor operating parameters and steady-state performance (average ± standard deviation).
Organic loading rate Residual COD COD removal Residual VS VS removal Methane production rate Methane yield Residual Fe2+ Fe2+/Fe(T) ratioa a
Unit
Phase 1
Phase 2
Phase 3
g COD/L d g VS/L d mg/L % mg/L % mL/L d L/g VSremoved L/g VSadded mg/L %
0.50 0.35 6,608 ± 135 34.0 ± 1.3 4,867 ± 126 29.0 ± 1.8 37.6 ± 8.8 0.37 ± 0.09 0.13 ± 0.03 68.7 ± 6.1 24.1 ± 2.7
0.53 0.40 7,606 ± 88 30.5 ± 0.8 5,733 ± 76 28.3 ± 1.0 46.8 ± 1.2 0.41 ± 0.01 0.14 ± 0.00 161.0 ± 9.8 34.4 ± 2.5
0.54 0.41 8,188 ± 59 24.5 ± 0.5 6,188 ± 63 24.1 ± 0.8 57.5 ± 1.4 0.59 ± 0.02 0.20 ± 0.01 207.3 ± 17.5 54.8 ± 4.5
The concentration ratio of Fe2+ to total iron ion.
Please cite this article in press as: Baek, G., et al. Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor. Bioresour. Technol. (2014), http://dx.doi.org/10.1016/j.biortech.2014.05.052
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biomethanation rate of WAS by direct addition of ferric iron into a sludge digester. 3.2. DGGE profiles and phylogenetic affiliation Archaeal and bacterial community structures in the reactor were analyzed at steady state in each phase based on the DGGE results (Fig. 2). A total of eight archaeal (GA1 to 8) and ten bacterial (GB1 to 10) bands were selected for sequencing, and the phylogenetic affiliation of the retrieved sequences from them is summarized in Table 2. Five archaeal sequences were closely related (P97% sequence similarity) to known methanogen species, and the remaining three were not to any known species. All eight archaeal sequences were, however, affiliated with two methanogenic orders by RDP Classifier at the default confidence threshold of 80%: hydrogenotrophic Methanomicrobiales (GB1 to 4 and 7) and aceticlastic Methanosarcinales (GA5, 6, and 8). GA 1 and 2, observed in Phase 1 only, showed a high similarity of 98.2% to several Methanocorpusculum species. The other three sequences (GA3, 4, and 7) classified to the order Methanomicrobiales were not closely related to known species but to unidentified archaeal clones from anaerobic sludge digesters. GA3, 4, and 7 occurred commonly across all phases while GA1 and 2 detected in Phase 1 disappeared in the later phases. This implies that the Methanocorpusculum-like microbes corresponding to GA1 and 2 were not favored under the iron-reducing conditions in Phase 2 and 3, and the microbes corresponding to GA3, 4, and 7 were likely the main players responsible for hydrogenotrophic methanogenesis in all phases. All Methanosarcinales-related sequences were closely related to Methanosaeta species: GA5 and 6 to M. concilii and GA 8 to M. harundinacea. Methanosaeta species generally dominate the methanogen community in a stable AD process (<1 mM residual acetate) (Ahring, 2003). Given the band intensity, although not robustly quantitative, the Methanosaeta-like microbes, especially that corresponding to GA6, seemed to dominate the methanogen community. This suggests that aceticlastic pathway was likely the major route of methanogenesis in the reactor tested. Eight out of ten bacterial DGGE sequences were closely related to known species across two phyla Firmicutes (GB1, 5, 6, and 8) and Proteobacter (GB3, 4, 9, and 10). The other two sequences poorly related to known species were affiliated with the phyla Bacteroidetes (GB2) and Spirochaetes (GB7). GB1 and 8 showed 100% similar-
ities to a number of Bacillus and Solibacillus (formerly classified as Bacillus) species isolated from soil and sediment samples while GB5 and 6 were closely related to several sulfur-reducing species of the fermentative genus Clostridium frequently found in AD processes (Table 2). WAS is mainly composed of cell biomass and thus rich in protein of which degradation can release sulfur for microbial use. GB3, 4, 9, and 10 were closely related to Acinetobacter, Psychrobacter, Stenotrophomonas, and Rhodobacter species of which relatives often occur in mesophilic AD processes (Krakat et al., 2011; Supaphol et al., 2011; Piterina et al., 2012). Although GB2 and 7 were not assigned to any known genus and classifiable at only the phylum and order levels, respectively (Table 2), both Bacteroidetes and Spirochaetales are commonly found bacterial groups in AD processes (Lee et al., 2009; Krakat et al., 2011; Piterina et al., 2012). 3.3. Changes in microbial community structure No apparent differences in archaeal DGGE banding patterns between the phases of the reactor trial were observed (Fig. 2A), indicating that the archaeal community structure in the reactor was not significantly affected by the biostimulation and bioaugmentation treatments. This was further confirmed by the high similarity among the archaeal community structures (CS, 85.7–94.7%) estimated from the DGGE profiles. Given that most archaea in AD systems are methanogens, this observation could be attributed to the extremely narrow substrate range of methanogens (Kim et al., 2013). In contrast, the bacterial DGGE results showed visibly different banding patterns between the treatment phases (Fig. 2B). Supporting this, the bacterial DGGE profiles shared a fairly low similarity (CS, 51.9–64.5%) among them, indicating that the bacterial community underwent significant structural changes likely by the effect of the biostimulation and bioaugmentation treatments. These observations suggest that the changes in bacterial community structure with the phases had little effect on the formation and evolution of methanogen community structure in the reactor tested. This reflects the less diverse and dynamic nature of archaea as compared to bacteria in AD environments. An intriguing observation in this study is that the band with the highest relative intensity clearly shifted from GB5 to GB3 then to GB7 with the phases of the experimental trial, which greatly affected the bacterial community structure changes (Fig. 2B).
Fig. 2. Archaeal (A) and bacterial (B) 16S rRNA gene DGGE profiles analyzed from steady-state reactor samples in each test phase (sampled time in days in parentheses), waste activated sludge (WAS), and anaerobic seed sludge (AS).
Please cite this article in press as: Baek, G., et al. Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor. Bioresour. Technol. (2014), http://dx.doi.org/10.1016/j.biortech.2014.05.052
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G. Baek et al. / Bioresource Technology xxx (2014) xxx–xxx Table 2 Phylogenetic affiliation of archaeal and bacterial 16S rRNA gene sequences retrieved from DGGE bands. Band Archaea GA1
GA2
GA3 GA4 GA5 GA6 GA7 GA8 Bacteria GB1
GB2 GB3
GB4
GB5
GB6
GB7
GB8
GB9
GB10
a
Closest relative
Accession number
Similarity (%)
Classificationa
Methanocorpusculum aggregans Methanocorpusculum pavum Methanocorpusculum labreanum Methanocorpusculum aggregans Methanocorpusculum pavum Methanocorpusculum labreanum Uncultured archaeal clone MTSArc_E4 Uncultured archaeal clone QEBH2ZB111 Methanosaeta concilii Methanosaeta concilii Uncultured archaeal clone MTSArc_E4 Uncultured archaeal clone QEDF1ZA031 Methanosaeta harundinacea
HG794418 AY260435 NR074173 HG794418 AY260435 NR074173 EU591662 KF198787 CP002565 CP002565 EU591662 KF198685 NR102896
98.2 98.2 98.2 98.2 98.2 98.2 97.4 97.8 97.3 100 98.9 98.9 98.5
Genus Methanocorpusculum
Solibacillus silvestris Bacillus isronensis Bacillus cecembensis Uncultured bacterium clone B58 Uncultured bacterium clone MR3 Acinetobacter haemolyticus Acinetobacter schindleri Acinetobacter johnsonii Acinetobacter baumannii Psychrobacter maritimus Psychrobacter sp. b110-52 Psychrobacter sp. SOD-1303 Clostridium tunisiense Clostridium sp. LAM1030 Clostridium sp. SN_2 H Clostridium thiosulfatireducens Clostridium subterminale Clostridium sulfidigenes Uncultured bacterium clone MADSac69 Uncultured bacterium clone QEEA2CA03 Uncultured bacterium clone FP_C7 Bacillus cecembensis Bacillus isronensis Solibacillus silvestris Stenotrophomonas maltophilia Stenotrophomonas sp. 81 Stenotrophomonas sp. GB6 Rhodobacter sp. MDT1-69-1 Rhodobacter sp. Cr5-50 Pseudorhodobacter sp. MDT1-23-2
KF777397 KF477162 JN819655 AB780945 DQ661705 HE608678 KF193924 EU434432 GU227612 HQ538765 HM468119 JX196611 AY187622 KC967412 JQ271581 JX073561 JF682846 HM163536 AB669259 CU918683 FJ769496 JN819655 KF477162 KF777397 KF973295 KF973291 JX042459 JX949604 GU441680 JX949602
100 100 98.9 100 100 100 100 98.5 98.3 100 100 100 100 100 100 99.8 99.8 99.8 100 100 99.6 100 98.9 98.9 99.6 99.6 99.6 99.8 99.8 99.8
Family Planococcaceae
Genus Methanocorpusculum
Order Methanomicrobiales Order Methanomicrobiales Genus Methanosaeta Genus Methanosaeta Order Methanomicrobiales Genus Methanosaeta
Phylum Bacteroidetes Genus Acinetobacter
Genus Psychrobacter
Genus Clostridium
Genus Clostridium
Order Spirochaetales
Family Planococcaceae
Genus Stenotrophomonas
Family Rhodobacteraceae
The lowest rank assigned by RDP Classifier at a 80% confidence threshold.
Although Acinetobacter species are known to be strictly aerobic, it has been widely observed in different anaerobic or oxygen-limited environments, including soils, sediments, and anaerobic or anoxic processes. Several previous studies suggested that Acinetobacter species are physiologically active and capable of reducing metals as part of their energy metabolism under either aerobic or oxygen-limited conditions (Davelaar, 1993; Zakaria et al., 2007; Shukor et al., 2010). In addition, the Acinetobacter haemolyticus strain (Accession No., HE608678) which GB3 sequence was most closely related to was originally isolated from a biofilm from ferromanganese coatings. These may also explain why GB3, a major band in WAS, was not observed in Phase 1 and emerged as the dominant band with the addition of ferric oxyhydroxide in Phase 2. These suggest that the Acinetobacter-related microbe corresponding to GB3 was likely involved in the reduction of ferric iron through anaerobic respiration of organic substances in Phase 2 (Davelaar, 1993). The dominance shift from GB3 to GB7 in Phase 3 seems to be the effect of bioaugmentation with enriched IRB consortium. The Spirochaetales bacterium corresponding to GB7, detected exclusively in Phase 3, likely originated from the enriched IRB consortium and developed as the dominant iron-reducing population in Phase 3. Supporting this, Spirochaetes species have a demonstrated ability to reduce ferric iron and have been observed
in abundance under iron-reducing conditions with different iron oxides and carbon sources (Lentini et al., 2012). 4. Conclusions IRB activity was successfully enhanced through biostimulation and bioaugmentation in a continuous AD process treating WAS, leading to a positive effect on biomethanation of WAS. A significant increase in both methane yield (10.8–59.4%) and production rate (24.5–52.9%) over the control values in Phase 1 was observed by the effect of ferric oxyhydroxide addition (Phase 2) and IRB augmentation (Phase 3). Visible changes in bacterial community structure were observed with the phases, with Acinetobacter- and Spirochaetales-related bacteria likely being the dominant populations responsible for anaerobic iron respiration, and thus leading to enhanced biomethanation, in Phases 2 and 3, respectively. Acknowledgements This research was supported under the framework of international cooperation program managed by National Research Foundation of Korea (2013K2A1A2054369) and also by the 2014
Please cite this article in press as: Baek, G., et al. Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor. Bioresour. Technol. (2014), http://dx.doi.org/10.1016/j.biortech.2014.05.052
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Research Fund of Ulsan National Institute of Science and Technology (UNIST).
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Please cite this article in press as: Baek, G., et al. Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor. Bioresour. Technol. (2014), http://dx.doi.org/10.1016/j.biortech.2014.05.052
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Bioresource Technology journal homepage: www.elsevier.com/locate/biortech
Short Communication
Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor Gahyun Baek, Jaai Kim, Changsoo Lee ⇑ School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), 50 UNIST-gil, Eonyang-eup, Ulju-gun, Ulsan 689-798, Republic of Korea
h i g h l i g h t s Effects of enhanced IRB activity on anaerobic digestion of WAS were studied. Raised IRB activity by biostimulation/augmentation led to enhanced biomethanation. Acinetobacter- and Spirochaetales-related populations were likely the dominant IRBs.
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Article history: Received 18 April 2014 Received in revised form 15 May 2014 Accepted 16 May 2014 Available online xxxx Keywords: Biomethanation Iron oxyhydroxide Iron-reducing bacteria Microbial community structure Waste activated sludge
a b s t r a c t This study investigated the potential of enhancing the activity of iron-reducing bacteria (IRBs) to increase the biomethanation rate of waste activate sludge (WAS). The effects of biostimulation by ferric oxyhydroxide (Phase 2) and bioaugmentation with an enriched IRB consortium (Phase 3) were examined in a continuous anaerobic reactor treating WAS. Compared to the control operation (Phase 1), significant rises in methane yield (10.8–59.4%) and production rate (24.5–52.9%) were demonstrated by the biostimulation and bioaugmentation treatments. Visible structural changes were observed in bacterial community with the phases while not in archaeal community. Acinetobacter- and Spirochaetales-related populations were likely the major players driving anaerobic iron respiration and thus leading to enhanced biomethanation performance, in Phases 2 and 3, respectively. Our results suggest an interesting new potential for enhancing biomethanation of WAS. Ó 2014 Elsevier Ltd. All rights reserved.
1. Introduction Global primary energy demand today is about 5.8 1011 GJ and is projected to reach 8.7 1011 GJ by 2040 (USEIA, 2013). The rapidly increasing energy demand, along with growing concerns for environmental protection, has fostered the search for alternative energy sources. Production of biogas, composed of CH4 and CO2 mainly, from organic wastes via anaerobic digestion (AD) is a viable option for producing renewable energy. Although gaining growing attention, AD has some limitations attributable to the slow growth rate of anaerobic microbes involved in the methanogenic pathway, for example, longer retention time and lower organic removal rate than aerobic treatment (Ahring, 2003). Such limitations reduce the feasibility of AD and hinder its wider applications in practice. Although many efforts have therefore been directed to improve AD performance, previous works have been confined mostly to changing reactor design and process configura⇑ Corresponding author. Tel.: +82 52 217 2822; fax: +82 52 217 2819. E-mail address: [email protected] (C. Lee).
tion. AD is a series of biological reactions performed by various microbial groups, and therefore its performance basically depends on the harmonized activity of the microbes involved. This suggests that approaches at the microbial community level as well as the process engineering level are necessary for fundamentally improving AD performance. Iron-reducing bacteria (IRBs) are a group of bacteria capable of oxidizing various organic compounds, including refractory compounds such as aromatic hydrocarbons, using ferric iron as electron acceptor under anaerobic conditions (Kim et al., 2014). IRBs play a critical role in iron cycling in both natural and engineered systems, and particular attention has recently been paid to their role in energy-harvesting bioprocesses such as bioelectrochemical cells and AD. The electroactive bacteria in microbial fuel cells (MFCs) are thought to be mostly IRBs, with Geobacter and Shewanella species often being the major populations. These bacteria directly or indirectly transfer electrons released from the oxidation of organic matter to the anode and then to the cathode, generating a flow of electrons between the electrodes, that is, electricity. Although IRBs may not be the major players involved in the
http://dx.doi.org/10.1016/j.biortech.2014.05.052 0960-8524/Ó 2014 Elsevier Ltd. All rights reserved.
Please cite this article in press as: Baek, G., et al. Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor. Bioresour. Technol. (2014), http://dx.doi.org/10.1016/j.biortech.2014.05.052
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methanogenic pathway, some previous studies reported interesting observations on their potential function in AD systems. Ivanov et al. (2002) investigated the effect of different iron compounds, i.e., ferric hydroxide, iron-containing clay, and iron ore, on the anaerobic treatment of fat-rich wastewater. The tests amended with ferric iron sources clearly showed enhanced removal rate and biogas yield. Zhang et al. (2010) also observed a positive effect of ferric iron on the methane production from pretreated sewage sludge. Although little biological evidence was given, such enhanced biomethanation performance may be attributed to IRB activity stimulated by ferric iron. A recent study reported that methanogenesis rates from acetate and ethanol were considerably increased by adding ferric oxides in the AD tests using rice paddy soil as the inoculum source (Kato et al., 2012). Interestingly, in that study, it was revealed by 16S rRNA gene analysis that the growth of Geobacter species was stimulated in the cultures supplemented with ferric oxides. These observations may suggest the possibility for enhancing biomethanation through ferric iron addition, yet very limited information is available on this potential particularly for continuous processes. This study therefore aims to examine how process performance and microbial community respond to the addition of ferric oxyhydroxide in a continuous reactor anaerobically treating waste activated sludge (WAS). WAS is one of the largest sources of organic waste and, its treatment is today among the major practical applications of AD. For a comprehensive insight into the underlying phenomena, changes in physicochemical parameters as well as microbial community structure in the reactor were monitored during the biostimulation (i.e., addition of ferric iron source only) and bioaugmentation (i.e., introduction of exogenous IRBs into the reactor) trials over 6 months. To the best of our knowledge, this is one of the first reports that provides evidence for enhanced biomethanation of WAS under iron-reducing conditions.
2. Methods 2.1. Bioreactor operation A continuously stirred tank reactor (CSTR) of a 2-L working volume was anaerobically operated to treat WAS collected from local sewage treatment plant. The reactor was initially inoculated at a 20% rate (v/v) with anaerobic sludge obtained from a full-scale sewage sludge digester. After the batch start-up till biogas production ceased, continuous feeding was started with the feed WAS (regarded as day 0) at 20-day hydraulic retention time (HRT). The reactor was fed on a daily basis and maintained at 35 ± 2 °C with an automatic temperature controller. The pH remained within 7.0–7.4 without adding any buffering reagent throughout the operation period. During over 6 months of continuous operation, the input concentrations of total chemical oxygen demand (COD) and volatile solids (VS) in the feed WAS varied within the ranges of 10.0–10.9 g/L and 6.9–8.1 g/L, respectively. The organic loading rate (OLR) accordingly varied between 0.50 and 0.54 g/Ld in COD and between 0.35 and 0.41 g/Ld in VS. The soluble to total COD ratio was below 2%, indicating that most organics in the feed WAS are in the form of suspended particles. The reactor was fed solely with WAS for the initial 61 days (Phase 1), and ferric oxyhydroxide was added in the feed WAS (final Fe concentration, 20 mM) from day 62 onwards (Phase 2). A microbial culture enriched under iron-reducing conditions was once introduced into the reactor (final volatile suspended solids concentration (VSS), 405 mg/L) on day 122, and the experimental period thereafter was defined as Phase 3 (Fig. 1). The performance of reactor was monitored by periodic sampling (every 2–4 days during the whole
experimental period) and analysis of the effluent and biogas samples. 2.2. Enrichment culture of IRBs An iron-reducing bacterial consortium (ATCC 55339) obtained from the American Type Culture Collection was used as the enrichment source of IRBs. Enrichment was achieved by repeated subcultures as previously described with modifications (Ivanov et al., 2010). The consortium was subcultured weekly by adding 30 mL of anaerobic sludge fluid and 20 mL of distilled water to 20 mL of the preceding culture in a 100-mL gas-tight bottle. Ferric citrate was added as the ferric iron source for the growth of IRBs (final Fe concentration, 16 mM). The subculturing was repeated seven times, the last cycle was scaled-up in a 2-L culture volume to attain sufficient biomass for the bioaugmentation test. The iron-reducing activity was confirmed every cycle by checking the increase in Fe2+ concentration in the culture medium. 2.3. DGGE analysis Genomic DNA was extracted from the reactor samples using an automated nucleic acid extractor (ExiProgen, Bioneer, Daejeon, Korea) according to the manufacturer’s instructions. One milliliter of a sample was pelleted in a 1.5-mL tube at 13,000g for 3 min and washed by repeated centrifuging (13,000g, 1 min), decanting (900 lL), and resuspending (up to 1 mL in distilled water) to eliminate impurities. A 200-lL portion of the suspension was loaded on the extractor with the ExiProgen Bacteria Genomic DNA Kit (Bioneer). The extracted DNA was eluted in 200 lL of elution buffer and stored at –20 °C until use. Archaeal and bacterial 16S rRNA gene fragments for DGGE analysis were prepared by touch-down polymerase chain reaction (PCR) using ARC787F/1059R and BAC338F/805R primer sets, respectively, as previously described (Kim et al., 2013). DGGE electrophoresis was performed using a D-code system (Bio-Rad, Hercules, CA) as previously described with denaturant gradients of 35–65% and 25–60% for the archaeal and bacterial runs, respectively (Kim et al., 2013). The DGGE gels were stained with SYBR Safe dye (Molecular Probe, Eugene, OR) and scanned under blue light for visualization of the banding patterns. A binary matrix was constructed for each gel by scoring the presence or absence of individual DGGE bands as 1 or 0, respectively, using an image-processing software (TotalLab 1D, TotalLab, Newcastle, UK). The similarity between the analyzed microbial community structures was measured by calculating the Dice coefficient of similarity (CS, %) based on the binary matrices in PC-ORD 5.0 (MjM software, Gleneden Beach, OR). Bands of interest were excised from the gels and eluted in 40 lL of sterile water overnight. A 2-lL aliquot of the elution was then reamplified using the same primer sets as for DGGE analysis. The final PCR products were purified, cloned, and sequenced for identification, and the obtained sequence information was analyzed against the GenBank and RDP databases. All nucleotide sequences reported in this paper were deposited in the GenBank database: KJ679856–679873. 2.4. Chemical analyses Solids were analyzed according to the protocols in Standard Methods (APHA-AWWA-WEF., 2005). COD was spectrophotometrically measured using HS-COD-MR kit (HUMAS, Daejon, Korea). Fe2+ and total Fe concentrations were measured using HS-Fe2+ and HS-Fe(T) kits (HUMAS), respectively. Volatile fatty acids (VFAs, C2–C6) were measured using a gas chromatograph (7820A, Agilent, Palo Alto, CA) coupled with a flame ionization detector and an Innowax column (Agilent). Methane content in biogas was
Please cite this article in press as: Baek, G., et al. Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor. Bioresour. Technol. (2014), http://dx.doi.org/10.1016/j.biortech.2014.05.052
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Fig. 1. Effluent COD concentration and methane production rate during the reactor operation.
determined using the same gas chromatograph equipped with a thermal conductivity detector and a ShinCarbon ST column (Restek, Bellefonte, PA). Samples for soluble COD and VFA measurements were prepared by filtering through a 0.45-lm-pore membrane filter. All analyses were performed at least in duplicate.
3. Results and discussion 3.1. Reactor performance The reactor was operated in continuous mode for 184 days, and the performance profiles throughout the trial are shown in Fig. 1. The effluent COD concentration fluctuated between 6.4 and 12.2 g/L during the initial 40-day period (i.e., 2 turnovers). The reactor performance stabilized after 2 months of operation in Phase 1, and the methane content remained between 65.7% and 74.1% thereafter until the end of the experiment. Table 1 summarizes the changes in steady-state performance of the reactor over Phases 1–3. Steady-state data were obtained by analyzing three to five samples collected at different operating times in each phase. The COD and volatile solids (VS) removal rates in Phases 1 and 2 were comparable to those from previous studies on anaerobic WAS treatment (Bolzonella et al., 2012; Feng et al., 2014). However, those were apparently lower in Phase 3, which may reflect an increase in microbial biomass in the reactor due to the bioaugmentation with IRBs (final VSS concentration, 405 mg/L). Microbial
cells are readily measured as COD and VS because their structures are composed of organic compounds. This may raise the residual concentrations of COD and VS (mostly VSS (>96%) in all test phases), leading to decreases in their removal rates. As expected, the concentration of Fe2+, and thus the Fe2+ to total Fe ratio, increased with the implementation of biostimulation in Phase 2 (2.3- and 1.4-fold over Phase 1, respectively) and bioaugmentation in Phase 3 (3.0- and 2.3-fold over Phase 1, respectively). This indicates that IRB activity was effectively enhanced by the addition of ferric oxyhydroxide and further by the augmentation with enriched IRBs from ATCC 55339. Interestingly, likely according to the enhanced IRB activity, methane yield and production rate significantly increased over the test phases (t-test, p < 0.05). The methane production rates in Phases 2 and 3 were greater than in Phase 1 by 24.5% and 52.9%, respectively. Methane yield was also higher in Phases 2 and 3 than in Phase 1 by 10.8% and 59.4%, respectively. These suggest that the enhanced IRB activity likely had a positive effect on biomethanation of WAS in our reactor. In agreement with our observations, a recent study on batch AD of WAS reported a significant increase in methane yield (29.5%) by adding rusty iron scrap containing different types of ferric oxides (Zhang et al., 2014). In that study, the authors suggested that microbial ferric reduction was induced by the iron rust added, and as a consequence, degradation rate of complex organic compounds was enhanced. Such an increase in methane yield without pretreatment of feed sludge or alteration of process configuration suggests an interesting potential for enhancing digestibility and
Table 1 Reactor operating parameters and steady-state performance (average ± standard deviation).
Organic loading rate Residual COD COD removal Residual VS VS removal Methane production rate Methane yield Residual Fe2+ Fe2+/Fe(T) ratioa a
Unit
Phase 1
Phase 2
Phase 3
g COD/L d g VS/L d mg/L % mg/L % mL/L d L/g VSremoved L/g VSadded mg/L %
0.50 0.35 6,608 ± 135 34.0 ± 1.3 4,867 ± 126 29.0 ± 1.8 37.6 ± 8.8 0.37 ± 0.09 0.13 ± 0.03 68.7 ± 6.1 24.1 ± 2.7
0.53 0.40 7,606 ± 88 30.5 ± 0.8 5,733 ± 76 28.3 ± 1.0 46.8 ± 1.2 0.41 ± 0.01 0.14 ± 0.00 161.0 ± 9.8 34.4 ± 2.5
0.54 0.41 8,188 ± 59 24.5 ± 0.5 6,188 ± 63 24.1 ± 0.8 57.5 ± 1.4 0.59 ± 0.02 0.20 ± 0.01 207.3 ± 17.5 54.8 ± 4.5
The concentration ratio of Fe2+ to total iron ion.
Please cite this article in press as: Baek, G., et al. Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor. Bioresour. Technol. (2014), http://dx.doi.org/10.1016/j.biortech.2014.05.052
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biomethanation rate of WAS by direct addition of ferric iron into a sludge digester. 3.2. DGGE profiles and phylogenetic affiliation Archaeal and bacterial community structures in the reactor were analyzed at steady state in each phase based on the DGGE results (Fig. 2). A total of eight archaeal (GA1 to 8) and ten bacterial (GB1 to 10) bands were selected for sequencing, and the phylogenetic affiliation of the retrieved sequences from them is summarized in Table 2. Five archaeal sequences were closely related (P97% sequence similarity) to known methanogen species, and the remaining three were not to any known species. All eight archaeal sequences were, however, affiliated with two methanogenic orders by RDP Classifier at the default confidence threshold of 80%: hydrogenotrophic Methanomicrobiales (GB1 to 4 and 7) and aceticlastic Methanosarcinales (GA5, 6, and 8). GA 1 and 2, observed in Phase 1 only, showed a high similarity of 98.2% to several Methanocorpusculum species. The other three sequences (GA3, 4, and 7) classified to the order Methanomicrobiales were not closely related to known species but to unidentified archaeal clones from anaerobic sludge digesters. GA3, 4, and 7 occurred commonly across all phases while GA1 and 2 detected in Phase 1 disappeared in the later phases. This implies that the Methanocorpusculum-like microbes corresponding to GA1 and 2 were not favored under the iron-reducing conditions in Phase 2 and 3, and the microbes corresponding to GA3, 4, and 7 were likely the main players responsible for hydrogenotrophic methanogenesis in all phases. All Methanosarcinales-related sequences were closely related to Methanosaeta species: GA5 and 6 to M. concilii and GA 8 to M. harundinacea. Methanosaeta species generally dominate the methanogen community in a stable AD process (<1 mM residual acetate) (Ahring, 2003). Given the band intensity, although not robustly quantitative, the Methanosaeta-like microbes, especially that corresponding to GA6, seemed to dominate the methanogen community. This suggests that aceticlastic pathway was likely the major route of methanogenesis in the reactor tested. Eight out of ten bacterial DGGE sequences were closely related to known species across two phyla Firmicutes (GB1, 5, 6, and 8) and Proteobacter (GB3, 4, 9, and 10). The other two sequences poorly related to known species were affiliated with the phyla Bacteroidetes (GB2) and Spirochaetes (GB7). GB1 and 8 showed 100% similar-
ities to a number of Bacillus and Solibacillus (formerly classified as Bacillus) species isolated from soil and sediment samples while GB5 and 6 were closely related to several sulfur-reducing species of the fermentative genus Clostridium frequently found in AD processes (Table 2). WAS is mainly composed of cell biomass and thus rich in protein of which degradation can release sulfur for microbial use. GB3, 4, 9, and 10 were closely related to Acinetobacter, Psychrobacter, Stenotrophomonas, and Rhodobacter species of which relatives often occur in mesophilic AD processes (Krakat et al., 2011; Supaphol et al., 2011; Piterina et al., 2012). Although GB2 and 7 were not assigned to any known genus and classifiable at only the phylum and order levels, respectively (Table 2), both Bacteroidetes and Spirochaetales are commonly found bacterial groups in AD processes (Lee et al., 2009; Krakat et al., 2011; Piterina et al., 2012). 3.3. Changes in microbial community structure No apparent differences in archaeal DGGE banding patterns between the phases of the reactor trial were observed (Fig. 2A), indicating that the archaeal community structure in the reactor was not significantly affected by the biostimulation and bioaugmentation treatments. This was further confirmed by the high similarity among the archaeal community structures (CS, 85.7–94.7%) estimated from the DGGE profiles. Given that most archaea in AD systems are methanogens, this observation could be attributed to the extremely narrow substrate range of methanogens (Kim et al., 2013). In contrast, the bacterial DGGE results showed visibly different banding patterns between the treatment phases (Fig. 2B). Supporting this, the bacterial DGGE profiles shared a fairly low similarity (CS, 51.9–64.5%) among them, indicating that the bacterial community underwent significant structural changes likely by the effect of the biostimulation and bioaugmentation treatments. These observations suggest that the changes in bacterial community structure with the phases had little effect on the formation and evolution of methanogen community structure in the reactor tested. This reflects the less diverse and dynamic nature of archaea as compared to bacteria in AD environments. An intriguing observation in this study is that the band with the highest relative intensity clearly shifted from GB5 to GB3 then to GB7 with the phases of the experimental trial, which greatly affected the bacterial community structure changes (Fig. 2B).
Fig. 2. Archaeal (A) and bacterial (B) 16S rRNA gene DGGE profiles analyzed from steady-state reactor samples in each test phase (sampled time in days in parentheses), waste activated sludge (WAS), and anaerobic seed sludge (AS).
Please cite this article in press as: Baek, G., et al. Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor. Bioresour. Technol. (2014), http://dx.doi.org/10.1016/j.biortech.2014.05.052
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G. Baek et al. / Bioresource Technology xxx (2014) xxx–xxx Table 2 Phylogenetic affiliation of archaeal and bacterial 16S rRNA gene sequences retrieved from DGGE bands. Band Archaea GA1
GA2
GA3 GA4 GA5 GA6 GA7 GA8 Bacteria GB1
GB2 GB3
GB4
GB5
GB6
GB7
GB8
GB9
GB10
a
Closest relative
Accession number
Similarity (%)
Classificationa
Methanocorpusculum aggregans Methanocorpusculum pavum Methanocorpusculum labreanum Methanocorpusculum aggregans Methanocorpusculum pavum Methanocorpusculum labreanum Uncultured archaeal clone MTSArc_E4 Uncultured archaeal clone QEBH2ZB111 Methanosaeta concilii Methanosaeta concilii Uncultured archaeal clone MTSArc_E4 Uncultured archaeal clone QEDF1ZA031 Methanosaeta harundinacea
HG794418 AY260435 NR074173 HG794418 AY260435 NR074173 EU591662 KF198787 CP002565 CP002565 EU591662 KF198685 NR102896
98.2 98.2 98.2 98.2 98.2 98.2 97.4 97.8 97.3 100 98.9 98.9 98.5
Genus Methanocorpusculum
Solibacillus silvestris Bacillus isronensis Bacillus cecembensis Uncultured bacterium clone B58 Uncultured bacterium clone MR3 Acinetobacter haemolyticus Acinetobacter schindleri Acinetobacter johnsonii Acinetobacter baumannii Psychrobacter maritimus Psychrobacter sp. b110-52 Psychrobacter sp. SOD-1303 Clostridium tunisiense Clostridium sp. LAM1030 Clostridium sp. SN_2 H Clostridium thiosulfatireducens Clostridium subterminale Clostridium sulfidigenes Uncultured bacterium clone MADSac69 Uncultured bacterium clone QEEA2CA03 Uncultured bacterium clone FP_C7 Bacillus cecembensis Bacillus isronensis Solibacillus silvestris Stenotrophomonas maltophilia Stenotrophomonas sp. 81 Stenotrophomonas sp. GB6 Rhodobacter sp. MDT1-69-1 Rhodobacter sp. Cr5-50 Pseudorhodobacter sp. MDT1-23-2
KF777397 KF477162 JN819655 AB780945 DQ661705 HE608678 KF193924 EU434432 GU227612 HQ538765 HM468119 JX196611 AY187622 KC967412 JQ271581 JX073561 JF682846 HM163536 AB669259 CU918683 FJ769496 JN819655 KF477162 KF777397 KF973295 KF973291 JX042459 JX949604 GU441680 JX949602
100 100 98.9 100 100 100 100 98.5 98.3 100 100 100 100 100 100 99.8 99.8 99.8 100 100 99.6 100 98.9 98.9 99.6 99.6 99.6 99.8 99.8 99.8
Family Planococcaceae
Genus Methanocorpusculum
Order Methanomicrobiales Order Methanomicrobiales Genus Methanosaeta Genus Methanosaeta Order Methanomicrobiales Genus Methanosaeta
Phylum Bacteroidetes Genus Acinetobacter
Genus Psychrobacter
Genus Clostridium
Genus Clostridium
Order Spirochaetales
Family Planococcaceae
Genus Stenotrophomonas
Family Rhodobacteraceae
The lowest rank assigned by RDP Classifier at a 80% confidence threshold.
Although Acinetobacter species are known to be strictly aerobic, it has been widely observed in different anaerobic or oxygen-limited environments, including soils, sediments, and anaerobic or anoxic processes. Several previous studies suggested that Acinetobacter species are physiologically active and capable of reducing metals as part of their energy metabolism under either aerobic or oxygen-limited conditions (Davelaar, 1993; Zakaria et al., 2007; Shukor et al., 2010). In addition, the Acinetobacter haemolyticus strain (Accession No., HE608678) which GB3 sequence was most closely related to was originally isolated from a biofilm from ferromanganese coatings. These may also explain why GB3, a major band in WAS, was not observed in Phase 1 and emerged as the dominant band with the addition of ferric oxyhydroxide in Phase 2. These suggest that the Acinetobacter-related microbe corresponding to GB3 was likely involved in the reduction of ferric iron through anaerobic respiration of organic substances in Phase 2 (Davelaar, 1993). The dominance shift from GB3 to GB7 in Phase 3 seems to be the effect of bioaugmentation with enriched IRB consortium. The Spirochaetales bacterium corresponding to GB7, detected exclusively in Phase 3, likely originated from the enriched IRB consortium and developed as the dominant iron-reducing population in Phase 3. Supporting this, Spirochaetes species have a demonstrated ability to reduce ferric iron and have been observed
in abundance under iron-reducing conditions with different iron oxides and carbon sources (Lentini et al., 2012). 4. Conclusions IRB activity was successfully enhanced through biostimulation and bioaugmentation in a continuous AD process treating WAS, leading to a positive effect on biomethanation of WAS. A significant increase in both methane yield (10.8–59.4%) and production rate (24.5–52.9%) over the control values in Phase 1 was observed by the effect of ferric oxyhydroxide addition (Phase 2) and IRB augmentation (Phase 3). Visible changes in bacterial community structure were observed with the phases, with Acinetobacter- and Spirochaetales-related bacteria likely being the dominant populations responsible for anaerobic iron respiration, and thus leading to enhanced biomethanation, in Phases 2 and 3, respectively. Acknowledgements This research was supported under the framework of international cooperation program managed by National Research Foundation of Korea (2013K2A1A2054369) and also by the 2014
Please cite this article in press as: Baek, G., et al. Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor. Bioresour. Technol. (2014), http://dx.doi.org/10.1016/j.biortech.2014.05.052
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Research Fund of Ulsan National Institute of Science and Technology (UNIST).
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Please cite this article in press as: Baek, G., et al. Influence of ferric oxyhydroxide addition on biomethanation of waste activated sludge in a continuous reactor. Bioresour. Technol. (2014), http://dx.doi.org/10.1016/j.biortech.2014.05.052