Anaerobic co-digestion of high-strength organic wastes pretreated by thermal hydrolysis

Accepted Manuscript Anaerobic co-digestion of high-strength organic wastes pretreated by thermal hydrolysis Gyucheol Choi, Jaai Kim, Seungyong Lee, Changsoo Lee PII: DOI: Reference:

S0960-8524(18)30287-6 https://doi.org/10.1016/j.biortech.2018.02.090 BITE 19600

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Bioresource Technology

Received Date: Revised Date: Accepted Date:

30 December 2017 18 February 2018 19 February 2018

Please cite this article as: Choi, G., Kim, J., Lee, S., Lee, C., Anaerobic co-digestion of high-strength organic wastes pretreated by thermal hydrolysis, Bioresource Technology (2018), doi: https://doi.org/10.1016/j.biortech. 2018.02.090

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Anaerobic co-digestion of high-strength organic wastes pretreated by thermal hydrolysis

Gyucheol Choia, Jaai Kima, Seungyong Leeb, Changsoo Leea,*

a

b

School of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan 44919, South Korea R&D Center, POSCO E&C Co. Ltd, 241 Incheon tower-daero, Yeonsu-gu Incheon 22009, Republic of Korea

* Corresponding author. Tel.: +82 52 217 2822; fax: +82 52 217 2819 E-mail address: [email protected]

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ABSTRACT

Thermal hydrolysis (TH) pretreatment was investigated for the anaerobic digestion (AD) of a mixture of high-strength organic wastes (i.e., dewatered human feces, dewatered sewage sludge, and food wastewater) at laboratory scale to simulate a full-scale plant and evaluate its feasibility. The reactors maintained efficient and stable performance at a hydraulic retention time of 20 days, which may be not sufficient for the mesophilic AD of high-suspended-solid wastes, despite the temporal variations in organic load. The addition of FeCl3 was effective in controlling H2S and resulted in significant changes in the microbial community structure, particularly the methanogens. The temporary interruption in feeding or temperature control led to immediate performance deterioration, but it recovered rapidly when normal operations were resumed. The overall results suggest that the AD process coupled with TH pretreatment can provide an efficient, robust, and resilient system to manage high-suspended-solid wastes, supporting the feasibility of its full-scale implementation.

Keywords Anaerobic digestion; Hydrogen sulfide; Microbial community structure; Pretreatment; Thermal hydrolysis

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1. Introduction

Anaerobic digestion (AD) has been considered an attractive option for managing organic wastes as it can recover energy in the form of methane while reducing pollution loads. AD has several other advantages over its aerobic counterpart, including the elimination of aeration costs, less sludge production, and effective pathogen removal (Ward et al., 2008). AD has recently been gaining increasing attention as a renewable energy source owing to growing concerns about energy security and climate change; thus, extensive efforts are being made to facilitate its application in the field. AD is a series of biological reactions involving hydrolysis, acidogenesis, acetogenesis, and methanogenesis. Hydrolysis often forms the rate-limiting step when treating a feedstock of low bioavailability, which can be a major concern in processes treating wastes with a high suspended solids content (Cano et al., 2014). A practical way to mitigate this problem is conditioning the substrate by pretreatment before AD. Various pretreatment methods using thermal, biological, chemical, and mechanical means have been suggested to improve the hydrolysis rate and thus the overall performance. Among the widely used pretreatment methods is thermal hydrolysis (TH), which is a well-proven, effective disintegration technology using high temperature (160–180°C) and pressure (6–8 bar) (Bougrier et al., 2008; Carrère et al., 2010). The application of TH pretreatment coupled with AD for enhanced substrate utilization and methane production has been demonstrated in several previous studies (González-Fernández et al., 2008; del Río et al., 2011). Although its effectiveness has been experimentally verified, it has also been suggested that the extents of substrate solubilization and methane production enhancement are significantly different between

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feedstocks of different chemical compositions (Bougrier et al., 2008; Donoso-Bravo et al., 2011; Qiao et al., 2011; Cano et al., 2014). The effect of such differences in pretreatment efficiency is presumably more complex and difficult to predict when treating different substrates in a mixture for a co-digestion process. TH pretreatment has recently been applied in many full-scale AD plants worldwide, particularly in Europe and China (Qiao et al., 2011; Cano et al., 2014). The first full-scale TH-AD plant in Korea was completed in September 2017 in A city for managing human feces, sewage sludge, and food wastewater generated from the city. Such co-digestion processes can have advantages over mono-digestion because mixing different substrates can help improve process feasibility and stability by, for example, balancing the carbon-to-nitrogen (C/N) ratio, remedying trace-element shortage, improving buffering capacity, and diluting inhibitory compounds (Kim et al., 2013). Human feces and sewage sludge are brought to the TH-AD plant in the form of dewatered cake from different sources, raising concern on low bioavailability and hydrolysis rate. Therefore, the plant needs a pretreatment step. The three waste feeds are mixed into a slurry prior to the TH process, and the pretreated mixture is fed to the AD plant. This study was performed to simulate the full-scale TH-AD process and experimentally investigate the feasibility of the process at the laboratory scale before its completion and start up to collect reference data for process control and monitoring. The TH pretreatment efficiency (i.e., solubilization of substrate) was evaluated in relation to its effects on the utilization and conversion of substrate into methane in two identical reactors during a long-term continuous operation for > 250 d. The reactors were tested under specific conditions simulating start-up, steady operation, sulfide control, and even system faults or maintenance with interrupted feeding and temperature failure.

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Additionally, for deeper insights into the system, changes in the underlying microbial community structures across the experimental phases were analyzed by a combination of molecular and statistical tools.

2. Materials and methods

2.1. Waste collection and TH pretreatment

Dewatered human feces (HFC) and dewatered sewage sludge (SSC) were collected from a sewage treatment plant in A city, Korea. Food wastewater (FWW) was from a food waste recycling facility in the same city. HFC and SSC for experiment were prepared by one-off sampling using a dewatering truck on site and stored refrigerated, while FWW was obtained directly from the source facility on eleven occasions during a 10-month experimental period. The physicochemical characteristics of the wastes are summarized in Table S1. The HFC, SSC, and FWW were mixed in a ratio of 9:60:31 (w/w) in regard to the contribution of each waste to the organic load design for the full-scale plant. The waste mixture was pretreated using a pilot-scale TH unit at the pretreatment conditions set for the full-scale process (160°C and 6 bar for 30 min). The sample load to the TH unit was 1.7 kg per run. The solubilization efficiency by the pretreatment was estimated based on the increase in the soluble fraction of the organic matter. The pretreated mixture was cooled down at ambient temperature and stored refrigerated until use.

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2.2. Bioreactor operation

Two continuously stirred tank reactors (CSTRs) with a 10-L working volume were run anaerobically in continuous mode with daily feeding. Each reactor was initially filled with 9 L of an anaerobic sludge mixture obtained from two AD plants, for treating food wastewater and sewage sludge, respectively, and cow manure from a local farm (mixing ratio, 6.5:74.8:18.7 (v/v)). The anaerobic sludges and cow manure were sieved through a 2.36-mm mesh before use for the inoculum preparation. The substrate for the reactor experiments was prepared by mixing the pretreated waste mixture with synthetic feces reject water and tap water (mixing ratio, 46.7:43.2:10.1 (v/v)) to simulate the addition of feces reject water and process water in the process design for the full-scale plant. Synthetic feces reject water contained the following components (in mM): NaCl, 0.9; NH4Cl, 19.7; KCl, 2.3; MgCl2∙6H2O, 1.3; CaCl2∙2H2O, 1.7; Na2SO4, 0.3; Na2HPO4, 1.1. The reactors were run in fed-batch mode during the start-up period of 1 month by adding the substrate twice to reach a working volume of 10 L. Both the control (PBC) and test (PBT) reactors were then run in continuous mode under the same operating conditions with reduced hydraulic retention time (HRT) from 78 d to 20 d (Phase I). After reaching the steady state in Phase I, the reactors were tested for the effect of FeCl3 addition, at different doses from 50 to 250 mg of FeCl3/L, on the production of H2S (Phase II). Subsequently, in Phase III, the reactors were repeatedly subjected to two system fault scenarios, i.e., (1) maintenance or half failure (feeding at half the normal rate) in PBC and (2) complete TH process failure (no substrate feeding and no temperature control) in PBT. Both reactors were operated at 39 °C, except during Phase III, and without pH control throughout the experiment, with reference to the full-scale plant operating conditions. Further details of the

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reactor operating conditions are provided in Table 1.

2.3. Real-time polymerase chain reaction

The total DNA was extracted from the reactor biomass samples as previously described (Kim et al., 2013). A 1-mL aliquot of the mixed liquor sampled from a reactor was diluted tenfold in distilled water. Biomass was recovered by centrifuging in a 1.5-mL microtube at 13,000g for 3 min and then washed by repeated pelleting, decanting, and resuspension (1 mL) in distilled water. A 200-μL portion of the final resuspension was loaded onto an automated nucleic acid extractor (ExiProgen, Bioneer) following the manufacturer’s instructions. The extracted DNA was recovered in 100 μL of elution buffer and stored at –20°C until use. Real-time polymerase chain reaction (PCR) targeting the 16S rRNA gene was carried out using universal bacterial and archaeal primers/probe sets as previously described (Baek et al., 2017). A reaction mixture (20 L) was prepared using the THUNDERBIRD Probe qPCR mix (TOYOBO): 10 L of the premix, 2 L of the TaqMan probe (final concentration, 200 nM), 1 L of each primer (final concentration, 500 nM), 4 L of PCR-grade water, and 2 L of DNA sample. PCR amplification with fluorescence detection was performed in a QuantStudio 12K Flex system (Life Technologies) in a two-step thermal cycling profile: initial denaturation for 10 min at 95°C followed by 40 cycles of denaturation (15 s at 95°C) and combined annealing and extension (1 min at 60°C). A standard curve was constructed for each primers/probe set as previously described (Kim et al., 2013). The copy concentrations of bacterial and archaeal 16S rRNA genes in an

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unknown sample were determined against the corresponding standard curves. All samples were analyzed in duplicate.

2.4. Next-generation sequencing

The libraries for next-generation sequencing (NGS) were constructed by PCR with universal prokaryotic primers, 515F and 806R (Rognes et al., 2016). Each primer was attached at the 5’ end with an Illumina adapter sequence. PCR was performed in the following thermal cycling program: initial denaturation for 10 min at 94°C, 30 cycles of amplification (30 s at 94°C, 30 s at 55°C, and 30 s at 72°C), and a final extension for 7 min at 72°C. The PCR products were delivered to Macrogen, Inc. (Korea) for NGS analysis on the Illumina MiSeq platform. Reads with poor quality scores (score offset, 33), ambiguous bases, or potential chimeric sequences were discarded. The trimmed reads were aligned and clustered using CD-HIT-OTU (Li et al., 2012), with an operational taxonomic unit (OTU) definition of < 3% sequence difference. The detected OTUs were classified by the RDP classification algorithm (https://rdp.cme.msu.edu). A representative sequence for each OTU was compared against the GenBank database using the BLASTn program. The sequence data generated in this study have been deposited in the NCBI Sequence Read Archive (SRA) under the BioProject accession number PRJNA427759.

2.5. Cluster and correlation analyses

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An archaeal and a bacterial matrix were constructed from the NGS results based on the relative abundance of individual OTUs to the total archaeal or bacterial reads for each library (i.e., each DNA sample). Cluster analysis was performed on the generated matrices using the unweighted pair group method with the arithmetic-means (UPGMA) algorithm. Calculations for UPGMA clustering were carried out based on the Bray–Curtis distance measure using PAST software ver. 3.06. Correlations among OTUs and process parameters of interest were analyzed using the same software. A correlation network was constructed for each reactor based on the Pearson correlation coefficients and pvalues. The correlation network was visualized using Cytoscape ver. 3.4.0 (Shannon et al., 2003). The initial placement of the network nodes was determined by a force-directed layout algorithm.

2.6. Analytical methods

The volumetric production of biogas was measured daily using a wet gas meter (MGC-1, Ritter) and corrected to standard temperature and pressure (0°C and 1 bar, respectively). The composition of biogas (H2, CH4, and CO2) was analyzed using the 7820A gas chromatograph (Agilent) coupled with a thermal conductivity detector and a ShinCarbon ST column (Restek). The H2S content in biogas was determined using the 7890A gas chromatograph (Agilent) equipped with a flame photometric detector and an HP-1 column (Agilent). Chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) were measured using HS-COD-MR kit (HUMAS), HS-TN-H (CA) kit (HUMAS), and HS-TP-H kit (HUMAS), respectively. Volatile fatty acids (VFAs, C2-C7) and ethanol were measured using another 7820A gas

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chromatograph (Agilent) equipped with a flame ionization detector and an HP-Innowax column (Agilent). Samples for measuring soluble COD and VFAs were prepared by filtration through a 0.45-μm pore filter. Solids were measured according to the protocols in Standard Methods (APHA-AWWA-WEF, 2005). The filtered samples for VFA analysis were acidified by formic acid (pH < 2.5) before analysis. Anions and cations were analyzed using two Dionex ICS-1100 ion chromatographs (Thermo Scientific) coupled with an IonPac AS14 column (Thermo Scientific) and an IonPac CS12A column (Thermo Scientific), respectively. Samples for ion analysis were prepared by filtration through a 0.22-μm pore filter. The sample pH was measured using a pH meter (ORION 3-Star, Thermo Scientific). Alkalinity was determined using an ORION total alkalinity test kit (Thermo Scientific). All analyses were performed at least in duplicate, except for pH and alkalinity, which were measured once.

3. Results and discussion

3.1. Pretreatment effects

The solids composition of the waste mixture before and after the pretreatment are shown in Table 2. The total and volatile solid (TS and VS) contents varied between the raw mixture samples: 164.7–208.0 g TS/kg mixture and 130.2–184.0 g VS/kg mixture. This is ascribed to the variations in the characteristics of FWW that was collected from the source facility on each occasion of TH pretreatment (refer to Subsection

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2.1 and Table S1). The TS, VS, TN, TP, and ammonium concentrations decreased by 20–30% after TH, likely due to the dilution effect by steam put into the reaction tank (Table S2). Such a dilution effect has also been observed in a previous study (Dwyer et al., 2008). The proportion of volatile-dissolved solids (VDS) to VS increased significantly after the pretreatment, while the VS/TS ratio did not show remarkable changes. This indicates that the TH pretreatment was effective in disintegrating and solubilizing organic matter suspended in the waste mixture. The substantial variation in the solubilization efficiency (i.e., increase in the VDS/VS ratio) between the pretreatment runs (6.3–511.6%) is noteworthy. Several previous studies have reported that the efficiency of a pretreatment may vary greatly between different types of organic wastes. Bougrier et al. (2008) observed different degrees of solubilization for different sludge samples but could not find any global parameter to explain the results. On the other hand, Qiao et al. (2012) reported that VS content and sludge type significantly affected the solubilization of organic particles. To study the effects of solids composition in more detail, correlations of the concentrations and proportions of solids with solubilization efficiency were calculated (Table 3). The VDS/VS ratio showed a strong and significant positive correlation (Pearson r > 0.90, p < 0.05) with all factors related to the content of the volatile suspended solids (VSS). This result seems reasonable given that the solubilization of suspended organic matter means the disintegration of coarse suspended organic particles (i.e., VSS) into smaller dissolved molecules (i.e., VDS).

3.2. Bioreactor performance

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3.2.1. Phase I: steady-state performance evaluation

After the 1-month start-up period in batch mode, the experimental reactors were operated in continuous mode with reduced HRT in a stepwise manner until it reached the design value of 20 d (from 78 to 39, 26, and 20 d). The start of the continuous operation was set as day 0. The performance profiles of the PBC and PBT over the experimental phases are shown in Fig. 1. Both reactors maintained stable performance during the course of decreasing HRT, and the target HRT was successfully attained in one month. The PBC and PBT were run at a fixed HRT of 20 d for more than four turnovers of the HRT during Phase I. The methane production rate varied with changes in the organic loading rate (OLR) owing to variations in the characteristics of the substrate fed to the reactors (Table S3). This agrees with previous observations that the biogas production rate was significantly affected by changes in the substrate input rate (Illmer and Gstraunthaler, 2009; Wagner et al., 2014). Although the OLR varied between 2.4 and 3.1 g VS/L∙d, the methane yield (i.e., methane production per unit mass of substrate VS fed) was maintained relatively stable, with a fairly constant methane content of approximately 64% in biogas, after three turnovers of the HRT in both reactors. The steady-state methane yield was 0.37 ± 0.03 L/g and 0.36 ± 0.03 L/g VS fed in PBC and PBT, respectively. In addition, VS removal (48–50%), pH (7.4–7.6), and residual VFAs (< 200 mg COD/L) were also at similar stable levels in the experimental reactors. A widely used indicator for evaluating the stability of AD is the VFAs/alkalinity ratio (Callaghan et al., 2002). The ratio remained below 0.02, which is much lower than the critical value for stable operation (< 0.4) in both reactors. These results show that the reactor performance was well replicated between the PBC and PBT in Phase 1, where they were run under the same operating conditions.

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Although easily biodegradable FWW accounted for 31% (w/w) in the raw waste mixture, the VS removal was approximately 50% in both reactors. This could be explained by the contribution of FWW on a VS basis that was only 10%, while SCC (76%) and HFC (14%), which are relatively difficult to degrade, accounted for most of the organic matter in the mixture. The VS removal of approximately 50% appears to indicate a considerable improvement in the anaerobic degradability by the pretreatment, given the high VS contribution and low biodegradability of SCC. The VS removal is often less than 30–40% in the AD of sewage sludge even at an HRT longer than 20 d (Gentile et al., 2014; Cai et al., 2016). In support, the positive effects of the TH pretreatment on the digestibility of sewage sludge have been reported in previous studies. Bougrier et al. (2006) reported a significant increase in both the methane yield and VS removal of waste-activated sludge by approximately 80% by TH at an HRT of 20 d. Perez-Elvira et al. (2010) observed that the biogas yield and VS removal were approximately 40% higher in a digester treating TH-pretreated mixed sludge at a 12-d HRT than in the control treating raw sludge at a 20-d HRT. Although a control experiment was not performed, the efficient and stable performance with consistent methane yield (ca. 0.4 L/g VS fed) and VS removal (ca. 50%) at the 20-d HRT, which is shorter than generally required for a moderate treatment efficiency in a conventional anaerobic CSTR digester (20–30 d), was achieved during Phase I in both the PBC and PBT. Therefore, it implies that the TH pretreatment applied in this study was effective in improving the bioavailability and thus the biomethanation of the waste mixture.

3.2.2. Phase II: H2S control by FeCl3 addition

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H2S in biogas is corrosive and can cause significant damage to boilers, engines, and other installations in AD plants. Therefore, biogas needs to be desulfurized before use according to the application, for example, < 0.1% (v/v) for heaters and < 0.05% (v/v) for engines (Krakat et al., 2011). Given that the H2S content in biogas is typically in the range from several hundred to several thousand ppmv, the desulfurization costs could be significantly reduced by minimizing its content. Adding iron salts, for example, FeCl2 or FeCl3, which removes sulfides by precipitation as FeS or oxidation to S0, is commonly used to control H2S in AD processes (Ge et al., 2012), largely owing to its convenience and effectiveness. In this study, the target H2S content was set to below 250 ppmv at the request of the plant management. At the steady state of Phase I, both reactors showed a H2S content around 1,400 ppmv (Fig. 1b). During Phase II, the PBT was subjected to increased concentrations of FeCl3 for H2S control, while the PBC was operated under the same conditions as in Phase I, without adding FeCl3, for comparison (Table 1). For each FeCl3 dose to test, the target concentration was first attained by adding a certain amount of FeCl3 to the reactor at once, and then the concentration was maintained by adding FeCl3 at the target concentration to the substrate. With the addition of 50 mg FeCl3/L, the H2S content decreased rapidly below 900 ppmv in the PBT. With stepwise increases in the FeCl3 dose by 50 mg/L up to 250 mg/L, the H2S content showed a decreasing trend and reached below 250 ppmv. In addition, the H2S content in the PBC varied widely between 500 ppmv and 3,000 ppmv, which is 2–7 fold greater than that in the PBT. The fluctuations in the H2S content in both reactors may be attributed to the significant variations in substrate characteristics (refer to Subsections 2.1, 2.2, and Table S3). The total COD to VS ratio varied from 1.04 to 1.76, indicating that the chemical composition of substrate varied significantly among sampling occasions. Particularly, although not directly

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comparable, the variations in TN content likely reflect the variation in protein content, which may affect the amount of sulfate available for sulfate-reducing bacteria (SRBs) forming H2S. Given the potential influence of such variations, the H2S control experiment using FeCl3 was performed again in the PBC to confirm its effectiveness, from day 236, after the end of Phase 2 for the PBT. Based on the test results from the PBT, the PBC was initially tested at 100 mg FeCl3/L dose. The H2S content decreased immediately by over 70% and ranged between 200 ppmv and 400 ppmv. At an increased dose of 150 mg FeCl3/L, it was stably maintained below 250 ppmv in the PBC. These results suggest that the FeCl3 addition at 150–250 mg/L can be applied to control the H2S content below 250 ppmv in the full-scale TH-AD plant. H2S removal in an AD process, for example, by adding iron salts as in this study, is often associated with the enhancement of methanogenic activity and thus methane yield (Wang and Banks, 2006; Ge et al., 2012; Park and Novak, 2013). However, no apparent enhancement in the methanogenic performance by FeCl3 addition was observed in both experimental reactors (Fig. 1), possibly because of the relatively low FeCl3 dose applied in this study. As the purpose of the Phase II experiment was to examine whether the H2S content in biogas can be maintained below 250 ppmv by FeCl3 addition, the reactors were not further tested at higher FeCl3 doses.

3.2.3. Phase III: system fault and recovery events

Based on the results of the Phase II experiment, both reactors were run with the addition of 150 mg FeCl3/L during Phase III (Table 1). Among the problems that a TH-AD process will very likely encounter during operation is the faults of the TH units. The full-scale TH-AD

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plant in A city has four TH units in parallel operating by turns for the continuous treatment, and the digester temperature is maintained by the heat from the pretreated substrate without digester heating. Therefore, in cases of failure or maintenance of the TH units, the organic loading as well as the operating temperature, both of which directly affect AD performance, are immediately disturbed. To examine such effects, the PBC and PBT were tested in complete failure and maintenance (or half failure) scenarios, respectively. The PBC was subjected to half the normal feeding rate at the normal operating temperature for 2 and 4 d with an interval for performance recovery between two events. The methane production rate immediately decreased by up to 40% after applying the halved feeding rate, while the methane yield slightly increased, likely due to the effect of prolonged biomass retention by the decrease in feeding rate. The methane productivity was fully restored immediately after the resumption of normal feeding for both the 2- and 4-d perturbations. Meanwhile, the effluent quality remained stable, with very small amounts of residual VFAs (< 50 mg COD/L) and consistent VS removal, during the test periods. The PBT was repeatedly subjected to interrupted feeding and no temperature control for 2, 4, and 7 d, at intervals sufficient for performance recovery. Each event caused an immediate decrease in methane production at the bottom along with a decrease in temperature to room temperature (Fig. 1a). Ahn and Forster (2002) reported that biogas yield remained at 80% of the normal level even when the reactor temperature suddenly decreased to room temperature in mesophilic AD. The almost complete cessation of biogas production immediately after applying the test conditions may be because the available organic substances in the substrate were already almost fully degraded under normal operating conditions. This is supported by the limited amount of readily utilizable organic matter, as reflected in the very low residual

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concentration of VFAs below 30 mg COD/L. Upon resumed feeding and temperature control, the methane yield increased immediately and recovered completely within 5 d regardless of the length of the interruption period. Other process parameters such as VS removal, residual VFAs, and pH were also similar before and after the repeated system fault and recovery events. Overall, the results show that the experimental reactors were highly resilient to all TH unit fault cases simulated. This information can be useful for the management of the full-scale TH-AD plant, particularly when dealing with unintended system faults.

3.3. Microbial community characterization

Real-time PCR targeting the 16S rRNA gene was used to determine the abundance of archaea and bacteria. Both archaeal and bacterial concentrations showed the lowest values in the day-0 sample and increased over time to reach a certain level in the experimental reactors (Fig. 2). After Phase I, archaeal population remained fairly constant at approximately 108 copies/mL, while bacteria were present at approximately two orders of magnitude higher in both reactors. It is noteworthy that the bacterial abundance increased markedly (up to 5.2 fold) between Phases I and II, while archaea did not, in both reactors. Accordingly, the archaea/bacteria ratio decreased significantly in Phase II. This means that the FeCl3 addition may have promoted the growth of bacteria rather than archaea, possibly due to the use of FeCl3 as a source of nutrient or electron acceptor for the growth of certain bacteria, e.g., iron-reducing bacteria (IRBs). For deeper insights into the underlying microbial ecology, 16S rRNA gene-targeted NGS analysis was performed to obtain a total of

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22,514 archaeal and 451,281 bacterial reads. Only one archaeal phylum, Euryarchaeota, and fourteen bacterial phyla were identified (Fig. 3). In all analyzed reactor samples, hydrogenotrophic Methanobacteriales and Methanomicrobiales dominated the archaeal community (82.1– 98.9% of the total archaeal reads). Meanwhile, the strictly aceticlastic Methanosaetaceae was the most abundant aceticlastic methanogen group. These suggest that hydrogenotrophic methanogenesis was likely the dominant pathway for methane production. Firmicutes was the most abundant bacterial phylum at all points of analysis, with Bacteriodetes, Planctomycetes, and Proteobacteria also being the major phyla. Members of these phyla are commonly and abundantly present in AD environments (Lee et al., 2012; Qiao et al., 2013; Shin et al., 2016). A total of 8 archaeal and 461 bacterial OTUs were identified. All archaeal OTUs and the major bacterial OTUs (> 2% relative abundance in at least one bacterial library) are presented in Table 4. Eight archaeal OTUs were all affiliated with methanogens at different hierarchical levels. In both reactors, the archaeal community was dominated by OTUs a1 and a3 assigned to the genus Methanobacterium (> 88% of the total archaeal reads) on day 0 and during Phase I. This may reflect the archaeal community structure in the inoculum biomass. Interestingly, the dominance shifted from Methanobacterium to Methanolinea (OTU a2) with the addition of FeCl3 between Phases I and II in both reactors. The relative abundance of Methanosaeta also increased significantly during Phases II and III (4.1–8.9% of the total archaeal reads) in the experimental reactors. Under Fe3+-rich conditions, iron respiration can become dominant over sulfate respiration as the terminal electronaccepting process because of its higher redox potential (i.e., higher energy yield). The reduction of Fe3+ could be coupled with the oxidation of hydrogen by hydrogen-utilizing IRBs, resulting in a decrease in hydrogen partial pressure (Lovley and Phillips, 1987; Achtnich et al., 1995). This indicates the possibility of a sudden drop in substrate concentration for hydrogenotrophic methanogens by FeCl3 addition in the

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experimental reactors. This may explain the dominance shift between Methanobacterium and Methanolinea with FeCl3 addition given the higher hydrogen affinity of Methanomicrobiales compared to Methanobacteriales (Lovley and Phillips, 1987; Song et al., 2015). The increase in Methanosaeta could be related to the higher susceptibility to toxic ionic agents including H2S and NH3 instead of other methanogens (Demirel and Scherer, 2008). A previous study reported that the sulfate addition resulted in a significant decrease in aceticlastic methanogens, particularly Methanosaeta, in a mesophilic digester (Yang et al., 2015). Among the major bacterial OTUs, Acinetobacter-related OTU b1 increased after adding FeCl3 and accounted for up to 17.3–20.6% of the total bacterial reads during Phases II and III in the experimental reactors. Acinetobacter species are commonly found on electrode biofilms in bioelectrochemical systems and are known to produce an electroactive redox compound similar to pyrroloquinoline quinone (Cai et al., 2016). This suggests that FeCl3 (i.e., Fe3+) may have promoted the growth of the putative electroactive population corresponding to OTU b1. Fe3+ may have also been used as an iron source for growth by the Acinetobacter-related population (Gentile et al., 2014). In contrast, Bacteroidetes-related OTU b3 was the most abundant OTU in Phase I (19.0–21.4% of the total bacterial reads), but substantially diminished after adding FeCl3 in both reactors. Meanwhile, OTU b5, another Bacteroidetes-related OTU, showed an opposite pattern, i.e., increases with FeCl3 addition. Although it is difficult to understand their roles in the reactors because they were classified only at the phylum level, these indicate that the fermentative populations corresponding to OTUs b3 and b5 were affected in negative and positive ways, respectively, by FeCl3. Previous studies reported that the relative abundance of Bacteroidetes decreased or remained low in Fe3+-added or bioelectrochemical processes due to the increase in electroactive bacteria (Ward et al., 2008; Mata-Alvarez et al., 2014). However, Kumaraswamy et al. (2011)

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reported that Bacteroidetes-related bacteria increased after H2S control, implying that the H2S reduction by adding FeCl3 may have had a beneficial effect on the growth of theBacteroidetes species in the experimental reactors. Such contradictory effects can be attributed to the vast metabolic and physiological diversity of the species of the phylum Bacteroidetes. Bacteroidetes remained as a major bacterial phylum with relatively high abundance in both reactors (Fig. 3b). The OTU b2 was classified to the family Planctomycetaceae whose members have often been observed in various anaerobic environments and was suggested to be responsible for the anaerobic oxidation of ammonium (Krakat et al., 2011; Ghylin, 2013). This OTU was therefore possibly involved in the mineralization of ammonium released from the decomposition of substrate, in particular proteinaceous substances. The OTU b4, classified only at the phylum to Firmicutes, had a very low relative abundance (< 0.5% of the total bacterial reads) on day 0, but its proportion increased significantly over the reactor operation, particularly after FeCl3 addition, in both reactors. The increase was more apparent in the PBT. Although uncertain, the corresponding population to this OTU was potentially involved in the fermentation of the substrate. The Ruminococcaceae-related OTU b8 decreased significantly from > 3.0% to < 1.0% after adding FeCl3. Ruminococcaceae species are commonly and abundantly present in the gut and are able to use complex carbohydrates including cellulosic matter for growth (Krause et al., 1999). This indicates that the OTU b8 likely played a role in degrading fibrous substances in the substrate. A recent study reported that this family occurred in high abundance along with SRBs in an acidogenic process treating sulfate-rich ethanol wastewater (Shan et al., 2017). This suggests that the Ruminococcaceae species can grow well under sulfate-reducing environments. The OTU b18, assigned to the family Bacilluaceae 1, was closely related with 97% sequence similarity to a sulfate-reducing species,

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Bacillus persicus (Didari et al., 2013). A steep decrease in the relative abundance of this OTU occurred after FeCl3 addition in both reactors. Bacillus persicus was reported as an acid-producing bacteria, which has the ability to produce H2S. The OTU b21 was assigned to the candidate phylum Atribacteria (formerly OP9 and JS1) whose members have often been identified in organic-rich anaerobic environments and was suggested to produce methanogenic substrates such as acetate and CO2 (Shelton et al., 2016). Interestingly, this OTU showed 99% sequence similarity to an uncultured clone (accession no. AB780939) of Thermodesulfobacteria, a phylum of thermophilic SRBs. The decreases in OTUs b18 and b21 after FeCl3 addition may then be related to the competition between iron respiration and sulfate reduction. Providing a more benign (or less inhibitory) environment for methanogens that compete with SRBs for substrate by sulfide removal may also have affected the decrease in the abundance of the putative sulfate-reducing OTUs. The OTU b9 was affiliated with the genus Petrimonas, which is well known in utilizing S0 as an electron acceptor and frequently found in abundance in iron-reducing microbial communities (Ziganshin et al., 2011; Ye et al., 2016). Sulfide control by FeCl3 addition works by oxidizing S2- to S0 while reducing Fe3+ to Fe2+, which further removes sulfide by FeS precipitation. The increased relative abundance of OTU b9 during Phases II and III could therefore be related to the formation of S 0 from the chemical reaction of FeCl3 and sulfide. OTUs b12 and b13, both of which also exhibited an increasing trend with FeCl3 addition, were assigned to the families Flavobacteriaceae and Synergistaceae, respectively. Flavobacteriaceae is an extraordinarily diverse family comprising of more than 100 genera, and its members play an important role in mineralizing organic matter (Buchan et al., 2014; McBride, 2014). Synergistaceae members ferment amino acids to produce short-chain VFAs, which are in turn utilized by methanogens (Vartoukian et al., 2007). The bacterium corresponding to OTU b13

21

may have contributed to the degradation of proteins in association with proteolytic Bacteroidetes bacteria (e.g., OTU b3 and b5). Synergistaceae has been suggested in a previous study as a core microbial group common to most anaerobic digesters although it was not numerically dominant (Rivière et al., 2009).

3.4. Changes in microbial community structure

The cluster analysis results show that the archaeal community structures before and after the addition of FeCl3 were clustered separately from each other (i.e., day 0 and Phase I versus Phases II and III) regardless of whether they were from the PBC or PBT (Fig. 4). This means that a profound change in the archaeal community structure was induced by FeCl3. In contrast, the bacterial community structures were clustered according to the operation mode. This suggests that altering from batch to continuous mode led to the most significant change in the bacterial community structure, likely due to the washout of slow-growing populations and the addition of fresh substrate. These results are consistent with the general understanding that methanogens are more directly and severely inhibited by H2S and the competition with SRBs on the substrate. It has been reported that the substrate characteristics and hydraulic/organic loading conditions affect bacterial communities more significantly than archaeal communities in anaerobic digesters (Zumstein et al., 2000; Didari et al., 2013; Kim et al., 2013). The less dynamic and less diverse nature of archaeal communities could be related to the narrow substrate spectrum of methanogens given that the archaea present in AD processes are mostly methanogens (Boone and Castenholz, 2001). Although less pronounced than in archaeal

22

communities, a noticeable effect of FeCl3 addition on the development of the bacterial community structure is also shown from the separation of the community profiles analyzed during continuous phases (Phases I–III), largely according to whether FeCl3 was added. These suggest that FeCl3 addition had a strong and significant effect on both the archaeal and bacterial community structures in the experimental reactors. To further study the effect of FeCl3 addition on the microbial community structure, a correlation network among the major OTUs (> 2% relative abundance in at least one bacterial or archaeal library) and the FeCl3 dose was constructed for each reactor (Fig. 5). Insignificant correlations (p > 0.05) were excluded from the networks. The numbers of nodes and edges in the correlation networks for the PBC and PBT were 32 nodes and 177 edges and 37 nodes and 163 edges, respectively. In support of the cluster analysis results, the crucial effect of FeCl3 on the development of the microbial community structure is clearly shown in both correlation networks. FeCl3 was directly correlated with 8 and 7 nodes in the PBC and PBT networks, respectively, and indirectly with all other major OTUs. In both networks, the OTUs were divided into two groups: one positively and one negatively correlated with FeCl3 in a direct or indirect manner. Members of the two co-occurring groups were negatively correlated to each other. Of note is the prevalence of cross-domain correlations between archaeal and bacterial OTUs: 42 out of 169 microbe-microbe edges for PBC, and 37 out of 156 microbe-microbe edges for PBT. This suggests that active and robust interactions between acidogens and methanogens required for effective AD were established in the experimental reactors. It is noteworthy that archaeal and bacterial community structures in each reactor varied little between Phases II and III (Fig. 4). This means that the system faults tested during Phase III did not induce substantial changes in the microbial community structure. Additionally, the total bacterial and archaeal concentrations also remained relatively unchanged over Phases II and III (Fig. 3). These may explain, in part, the

23

high resilience of the experimental reactors to the interrupted feeding and temperature failure imposed. The fault periods (up to 7 d) may not be sufficiently long to lead to significant irreversible changes in the microbial community structure and in the process performance.

Conclusions

This study investigated the feasibility of TH as a pretreatment for the AD of a mixture of HFC, SSC, and FWW. The TH-AD processes, simulating a full-scale plant, maintained stable performance at 20-d HRT for over twelve turnovers of the HRT, despite temporal variations in the substrate characteristics and the OLR. FeCl3 addition (≥ 150 mg/L) proved effective in controlling H2S and induced significant variations in the microbial community structure. The processes were resilient to the simulated system faults, which did not significantly affect the microbial community structures. The overall results support the feasibility of TH-AD system for full-scale implementation.

Acknowledgements

This research was supported by the Korea Institute of Energy Technology Evaluation and Planning (KETEP) through “Human Resources Program in Energy Technology” (No. 20164030201010) funded by the Ministry of Trade, Industry and Energy, Republic of Korea and the

24

Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT and Future Planning (2017R1D1A1B03035489).

References

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31

Figure captions

Fig. 1. Reactor performance profiles during the experimental phases.

Fig. 2. The archaeal and bacterial 16S rRNA gene concentrations, and the archaea/bacteria ratio in the reactors. Samples are labeled with the corresponding reactor name and experimental phases. ‘0’ indicates day 0 (the start of continuous operation).

Fig. 3. Relative distribution of archaeal (a) and bacterial (b) sequences in the 16S rRNA gene libraries for reactor biomass samples. Samples are labeled with the corresponding reactor name and experimental phases. ‘0’ indicates day 0 (the start of continuous operation).

Fig. 4. Cluster dendrograms constructed based on the OTU distribution in the archaeal (a) and bacterial (b) 16S rRNA gene libraries characterized by NGS. Samples are labeled with the corresponding reactor name and experimental phases. ‘0’ indicates day 0 (the start of continuous operation). Bootstrap values higher than 80% (1000 replicates) are shown.

Fig. 5. Correlation network (p < 0.05) among the major populations (> 2% relative OTU abundance in at least one bacterial or archaeal library) and the FeCl3 dose. Green circles, blue squares, and yellow triangle represent archaeal OTUs, bacterial OTUs, and FeCl3, respectively. Node

32

size is proportional to the number of connected edges. Black and red edges represent positive and negative correlations, respectively.

Tables Table 1. Reactor operating conditions during the experimental phases. PBC Phase

Day

HRT (days)

Temperature o

FeCl3 addition (mg/L)

PBT Phase

Day

HRT (days)

Temperature (°C)

FeCl3 addition (mg/L)

I

0–12

78

39

–

13–21 22–30 31–122

39 26 20

39 39 39

– – –

0–12

78

( C) 39

13–21 22–30 31–122

39 26 20

39 39 39

– – – –

II a b c

123–235 236–250 251–262

20 20 20

39 39 39

– 100 150

II a b c d e

123–142 143–165 166–187 188–208 209–235

20 20 20 20 20

39 39 39 39 39

50 100 150 200 250

III

263–264 265–268

40 20

39 39

150 150

III

236–237 238–250

– 20

Uncontrolled 39

– 250

I

a

33

269–272 273–277

a

40 20

39 39

150 150

251–254 255–262 263–269 270–277

Not applicable.

34

– 20 – 20

Uncontrolled 39 Uncontrolled 39

– 250 – 250

Table 2. Solids composition of the waste mixture before and after TH pretreatment. Sampling

TS

VS

VS/TS

VDS/VS

Increase in

(g/kg)

(g/kg)

(%)

(%)

VDS/VS (%)

1

208.7 ± 0.0

184.3 ± 0.0

88.3

–b

2

198.0 ± 5.7

161.1 ± 4.6

81.4

14.3

3

189.6 ± 3.5

154.1 ± 3.4

81.3

16.6

4

186.9 ± 2.7

152.0 ± 3.9

81.4

5.7

5

183.3 ± 1.0

144.3 ± 0.0

78.7

3.5

6

182.2 ± 3.0

144.8 ± 3.3

79.5

14.8

7

187.2 ± 1.1

151.6 ± 1.3

81.0

21.3

8

172.5 ± 2.2

137.4 ± 1.7

79.7

17.6

9

190.1 ± 7.0

158.8 ± 4.3

83.5

14.8

10

197.9 ± 3.6

158.4 ± 1.7

80.0

16.9

11

164.7 ± 3.1

130.2 ± 3.0

79.1

17.3

1

156.2 ± 1.8

129.3 ± 1.8

82.8

18.3

–

2

147.6 ± 2.4

121.1 ± 2.7

82.0

15.2

6.3

3

142.6 ± 0.8

115.4 ± 1.0

80.9

20.2

21.7

4

131.3 ± 0.9

105.7 ± 1.0

80.6

23.6

315.4

5

127.8 ± 1.4

102.6 ± 1.4

80.3

21.4

511.6

6

119.3 ± 0.9

95.0 ± 0.5

79.6

23.6

59.7

7

122.6 ± 1.3

98.6 ± 1.2

80.4

29.2

37.1

8

121.4 ± 0.6

97.5 ± 0.5

80.3

28.2

59.8

9

120.0 ± 0.4

99.1 ± 0.1

82.5

29.3

97.5

10

126.6 ± 0.4

103.3 ± 0.5

81.6

29.5

75.2

11

117.2 ± 1.1

92.5 ± 0.5

78.9

33.3

92.4

a

occasion

Before TH

After TH

a

Eleven sampling occasions of FWW used to prepare the waste mixture.

b

Not determined.

35

Table 3. Correlations of the concentrations and proportions solids with the solubilization efficiency. TS

VS

VS/TS

TSS

TSS/TS

VSS

VSS/TS

VSS/VS

VSS/TSS

Pearson r

0.84

0.87

0.43

0.2

0.96

0.92

0.96

0.99

0.98

p-value

<0.05

<0.05

0.21

0.61

<0.05

<0.05

<0.05

<0.05

<0.05

36

Table 4. Relative abundance and taxonomic affiliation of all archaeal and major bacterial OTUs (>2% relative abundance in at least one library)a. OTU number Archaea a1 a2 a3 a4 a5 a6 a7 a8 Bacteria b1 b2 b3 b4 b5 b6 b7 b8 b9 b10 b11 b12

Sim (%)c

PBCd 0 I

Methanobacterium subterraneum Methanolinea mesophila Methanobacterium ferruginis Methanosaeta concilii Methanobrevibacter boviskoreani Methanothylovorans uponensis Methanosphaerula palustris Methanobacterium palustre

97 95 98 97 86 97 98 99

77.6 91.4 12.8 5.1 5.1 78.6 79.0 50.0 29.4 31.9

Acinetobacter seohaensis Thermostilla marina Mariniphaga sediminis Salinithrix halophila Lentimicrobium saccharophilum Syntrophomonas zehnderi Sedimentibacter hydroxybenzoicus Ercella succinigenes Petrimonas sulfuriphila Lysinibacillus mangiferihumi Tissierella creatinini Spongiimonas flava

99 99 91 88 99 96 95 87 97 99 93 86

0.0 1.8 20.6 5.7 18.8 0.0 10.4 6.4 17.3 16.4

Closest cultivated species

b

f

nd

PBTd IIb IIc III 0 I

IIc IIe III

3.0 67.3 78.1 78.1 0.0 5.5 36.8 61.0 60.2

11.0 4.5 1.9 1.2 0.7 13.7 12.3 1.9 0.9 0.8 2.8 1.1 8.5 8.0 8.9 2.6 2.4 5.2 4.3 4.1 3.1 0.0 5.5 5.5 5.5 1.6 0.6 5.0 3.1 2.7 0.0 0.1 3.9 2.1 1.8 nd

0.2 1.0 1.3 0.3

5.3 nd

nd

nd

nd

3.2 nd

nd

nd

nd

0.3 nd

nd

nd

nd

0.2 nd

nd

nd

nd

0.0 9.1 12.2 12.1 10.9 0.0 8.3 9.6 8.9 9.8 2.2 19.0 4.2 4.1 3.4 2.2 21.4 16.0 5.5 4.3 0.5 3.7 4.8 5.3 4.8 0.5 2.6 6.6 5.6 6.3 2.4 1.1 2.6 4.7 4.4 2.4 1.2 5.4 9.8 11.1 1.5 2.9 3.9 3.2 3.8 2.8 1.2 7.0 3.6 3.5 1.8 5.0 2.0 2.2 1.9 3.3 4.3 4.6 2.7 2.5 4.3 3.4 1.0 0.9 0.9 3.7 4.2 0.4 0.7 0.7 0.1 2.1 3.0 3.6 2.8 0.0 0.8 0.5 2.3 2.3 4.4 1.5 0.5 6.4 3.6 3.1 1.5 0.0 0.1 2.1 0.1 1.6 3.9 1.5 1.6 0.1 2.3 2.1 2.7 2.1 0.0 0.2 2.0 5.1 3.7 0.0 0.6 2.6 3.1 3.3

37

Accession number

Classification

NR028247 NR112799 NR113045 NR102903 NR118565 NR133781 NR074167 NR041713

Methanobacterium Methanoregulaceae Methanobacterium Methanosaeta Euryarchaeota Methanomethylovorans Methanoregulaceae Methanobacterium

NR115299 NR148598 NR137221 NR134171 NR149795 NR044008 NR029146 NR134026 NR042987 NR118146 NR117155 NR114346

Acinetobacter Planctomycetaceae Bacteroidetes Firmicutes Bacteroidetes Syntrophomonas Sedimentibacter Ruminococcaceae Petrimonas Lysinibacillus Clostridiales_Incertae Sedis XI Flavobacteriaceae

e

b13 b14 b15 b16 b17 b18 b19 b20 b21 b22 b23 b24 b25 b26 b27 b28 b29 b30 b31 a b c d e f

Aminivibrio pyruvatiphilus Syntrophomonas bryantii Acinetobacter vivianii Desulfosporosinus meridiei Saccharicrinis carchari Bacillus persicus Saccharicrinis marinus Alcaligenes aquatilis Virgibacillus halotolerans Leptolinea tardivitalis Leptolinea tardivitalis Prolixibacter denitrificans Tissierella creatinophila Tissierella creatinophila Sporosarcina luteola Syntrophaceticus schinkii Aminobacterium colombiense Dechloromonas hortensis Proteiniclasticum ruminis

91 97 99 89 87 98 87 99 86 89 91 90 95 96 99 98 99 99 98

0.6 2.2 3.1 3.5 3.3 0.5 2.0 2.5 2.8 3.3 0.2 2.7 1.5 1.0 1.0 0.3 1.8 3.0 2.9 2.3 0.0 0.6 0.2 5.6 0.6 0.0 0.0 0.8 4.7 nd 0.1 1.2 2.3 2.2 1.9 0.2 0.5 0.5 0.6 1.2 0.4 0.9 2.2 4.1 3.9 0.2 0.6 0.6 0.9 1.4 8.2 7.3 0.2 0.2 0.2 5.8 3.5 1.2 0.1 0.3 0.2 1.7 0.4 0.8 0.9 0.1 0.3 3.5 0.8 0.9 0.1 nd

0.3 0.9 2.1 0.4 nd

0.0 1.0 1.6

3.5 1.1 0.7 0.8 0.8 2.8 1.0 0.4 0.7 0.8 1.3 3.1 0.8 0.9 0.7 0.9 1.8 2.4 0.7 1.0 5.4 0.6 0.4 0.1 0.1 4.8 0.5 0.2 0.3 0.4 3.4 0.1 0.1 0.1 0.1 2.4 0.1 0.2 0.2 0.2 2.9 0.0 nd

nd

nd

4.3 0.0 nd

nd

nd

2.2 0.0 nd

0.0 nd

3.8 0.0 nd

0.0 nd

1.6 0.7 0.2 0.5 1.1 3.0 0.7 0.1 0.1 0.7 2.8 nd

nd

0.0 nd

2.5 nd

0.0 nd

0.0

1.8 0.5 0.1 0.0 0.1 2.4 0.4 0.1 0.1 0.0 2.4 nd

nd

nd

nd

2.8 nd

nd

nd

nd

2.0 nd

nd

nd

nd

1.9 nd

nd

nd

nd

NR113331 NR104881 NR148847 NR074129 NR134164 NR109140 NR137404 NR104977 NR108860 NR040971 NR040971 NR137212 NR037028 NR037028 NR114283 NR116297 NR074624 NR042819 NR115875

Synergistaceae Syntrophomonas Acinetobacter Bacteria Bacteroidetes Bacillaceae 1 Bacteroidetes Alcaligenes Atribacter_genera_incertae_sedis Anaerolineaceae Anaerolineaceae Bacteroidetes Tissierella Tissierella Filibacter Syntrophaceticus Aminobacterium Dechloromonas Proteiniclasticum

Cells with relative abundance values are colored in a heatmap-like fashion: green for archaeal and brick red for bacterial OTUs. Closest cultivated species were determined by BLAST search against the NCBI 16S rRNA sequence database. Sequence similarity. Samples are labeled with the corresponding reactor name and experimental phases. ‘0’ indicates day 0 (the start of continuous operation). The lowest rank classified against the NCBI 16S rRNA sequence database down to the genus level. Not detected at all (zero read). Different from ‘0.0’ which means being detected, but in very low abundance. 38

Highlights  A full-scale TH-AD plant was simulated in two lab-scale reactors run in parallel.  TH pretreatment effectively solubilized a mixture of high-suspended-solids wastes.  The reactors maintained efficient and stable performance at 20-d HRT for 8 months.  FeCl3 addition reduced H2S and greatly affected the microbial community structure.  The reactors were highly resilient to interrupted feeding and temperature failure.

39