Effect of narrow feeding regimes on anaerobic digestion performance

Publication Date (Web): October 9, 2018 ... the effect of feeding regimes (FR) on anaerobic digestion performance and microbial community structure of...
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Effect of Narrow Feeding Regimes on Anaerobic Digestion Performance and Microbial Community Structure of Rice Straw in Continuously Stirred Tank Reactors Ruolin Guan,† Hairong Yuan,*,† Akiber Chufo Wachemo,†,‡ Xiujin Li,*,† Xiaoyu Zuo,† Dexun Zou,† Yanping Liu,† and Junyu Gu† Energy Fuels Downloaded from pubs.acs.org by UNIV OF LOUISIANA AT LAFAYETTE on 10/21/18. For personal use only.

†

Centre for Resource and Environmental Research, Beijing University of Chemical Technology, Beijing 100029, People’s Republic of China ‡ Department of Water Supply and Environmental Engineering, Arba Minch University, P.O. Box 21, Arba Minch, Ethiopia ABSTRACT: Demand-oriented conversion of biogas is conducive to meeting the needs of biogas supply and reduces extra costs related to gas storage facilities. In this study, the effect of feeding regimes (FRs) on anaerobic digestion performance and microbial community structure of rice straw were investigated using continuously stirred tank reactors. The result showed that compared to the FRs of every day and every 6 days, the FR of every 3 days achieved the best biomethane yield and substrate conversion rate, which improved by 17.3% and 12.4%, respectively. Additionally, the FR of every 3 days had a significant impact on microbial richness and diversity, and also improved the abundance of dominant archaea Methanosaeta. This indicated that the FR of every 3 days was suitable for the growth rate of Methanosaeta, which resulted in better anaerobic digestion performance. A narrow FR is helpful to meet the demand-oriented conversion of biogas.

1. INTRODUCTION Production of renewable energy from biomass is one of the potential routes to decrease the consumption of fossil fuels and reduce greenhouse gas emissions.1 In China, more than 170 million tons of rice straw (RS) was produced every year, but about 60% of the RS was left untreated annually.2 This could cause environmental pollution and fire disaster due to burning in the open area. Anaerobic digestion (AD) of organic wastes into biogas is a preferred biotechnological way to treat biomass and has long been used as an energy generation method in most Asian countries.3 A continuously stirred tank reactor (CSTR) is one of the popular AD digesters used to treat organic wastes with high solid content.4,5 However, the degradation efficiency and biogas production were commonly lower than those in batch tests.6 This could be due to a “short-circuit” phenomenon, that is, some portion of the raw material is retained in the reactor for a shorter time than the designed retention time.7 Therefore, it is very important to improve the rate of utilization of raw materials for better performance of the CSTR and substance conversion during the process of AD. However, the methods used to improve AD efficiency are often accompanied by cost benefit and energy consumption issues,8 while most of the feeding frequencies in lab experiments and industrial projects are generally fixed at one time per day. Recently, it has been found that the feeding regimes (FRs) would affect biogas production and microbial community in the AD process. Mulat et al.9 compared the effects of three FRs in a CSTR treating a distiller’s dried grains with solubles, which found that the reactors fed after every second day and every day performed better in methane yield than the reactor fed after every 2 h. Piao et al.10 studied a series of laboratory-scale anaerobic reactors under different feeding frequencies (twice a © XXXX American Chemical Society

day, once a day, and every 2 days) using glucose as the raw material. The results showed that frequent feeding promoted more stable digestion performance and the decrease in feeding frequency appeared to cause shifts from acetate-utilizing methanogens to hydrogen-utilizing methanogens. Manser et al.11 researched semicontinuous mesophilic anaerobic digesters with swine waste operating at varying feeding frequencies, which found that the reactor fed weekly had higher average methane yields (0.18 m3 of CH4/kg·VS), specific methanogenic activities (35 mL/day), and fecal indicator bacteria destruction (99.4%) than those fed on a shorter interval. However, most of these studies focused on easily degradable substrates; materials with high percentages of lignocellulose and low biodegradation rates are rarely studied. Zealand et al.12 found that the AD of lignocellulose biomass like RS was also influenced by feeding intervals. However, the variations of microbial community structure and system performance have not been clearly studied in the literature. Flexible biogas production (FBP), which is carried out through changing the feeding intervals and substrate type, has recently received widespread attention.13 Compared to the conventional biogas production, FBP can reduce the economic investment in gas storage because the period that the biogas production is large/small matches with the time when the energy demand is high/low. Additionally, demand-oriented conversion of biogas is conducive to supplying heat and electricity during peak times.14 Therefore, it is important to evaluate the influence of the feed mode on AD biogas production performance and analyze the relationship between Received: August 8, 2018 Revised: September 25, 2018 Published: October 9, 2018 A

DOI: 10.1021/acs.energyfuels.8b02533 Energy Fuels XXXX, XXX, XXX−XXX

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mechanical mixers operated at a speed of 80 rpm for 10 min after every 2 h. The hydraulic retention time (HRT) in this study was 45 days. Phase 1 was the initial setup period (1−30 days); in this stage, each reactor was set up with 65 g of TS·L−1 RS and 30 g (mixed liquid suspended solid, MLSS)·L−1 inoculum, which were fed only once at the initial time during the entire setup period. Then, phase 2 was the semicontinuous mode period (31−165 days); in this stage, three reactors were fed every day. Phase 3 was operated at different FRs (166−255 days); when the reactors were stable in phase 2, the feeding intervals of reactors were changed into every day (R1), every 3 days (R3), and every 6 days (R6), respectively (phase 3). The total amount of feed in R1, R3, and R6 during every 6 days was the same. 2.3. Analytical Methods and Data Analysis. 2.3.1. Biogas Analysis. The biogas components such as CH4, CO2, N2, and H2 were measured using a gas chromatograph (Zhongkehuijie Corp., P-2100, Beijing, China) equipped with a thermal conductivity detector (TCD) and a TDX-01 column. Argon was used as the carrier gas. Daily biogas production (DBP) was recorded using the wet gas meters (LMF-1, Changchun Automobile Filter, China). The amount of produced gas was converted to standard gas using standard pressure and temperature conditions. Daily methane production per volume (DMP-V) was determined from the average DBP, CH4 content, and system working volume. Daily methane production per VS (DMP-VS) was calculated from the average DBP, CH4 content, and VS fed. 2.3.2. Chemical Composition Analysis. Total solid (TS), volatile solid (VS), and total alkalinity concentration (TAC) were determined according to the standard methods.16 The total carbon (TC) and total nitrogen (TN) were analyzed by an elemental analyzer (Vario EL/ micro cube elemental analyzer, Germany). Liquid samples were centrifuged at 10 000 rpm for 10 min at room temperature and filtered with a 0.22 μm membrane filter. Then the concentrations of volatile fatty acids (VFAs) were analyzed using a gas chromatograph (GC-2014, Shimadzu, Japan) equipped with a flame ionization detector (FID) and a DB-WAX123-7032 capillary column. Nitrogen was used as a carrier gas. The operational temperatures of injector, detector, and column were kept at 250 °C, 250 °C, and increased from 100 to 180 °C at a rate of 5 °C/min, respectively. The internal standards to analyze each VFA component were based on the standard calibration curve according to the manufacturer’s protocol. The VFAs yields were calculated as the sum of the measured acetic, propionic, n-butyric, isobutyric, n-valeric, and isovaleric acids. The pH of each digester was detected by a pH meter (Thermo Electron, USA). Digestates from reactors were oven-dried to determine the contents of cellulose, hemicellulose, and lignin, which were measured using a fiber analyzer (A2000I, ANMOM, USA) according to the procedure described by van Soest et al.17 2.3.3. Microbial Community Analysis. The sample for DNA analysis was collected when the CSTR reactor exhibited a stable state,

feed frequency and biogas production so as to achieve low input and high output operation modes. The main objectives of this study were to (1) examine the effect of narrow feeding intervals on CSTR fed with RS, (2) investigate the system stability with semicontinuous feeding in a long-term process, and (3) evaluate whether an alteration of FR could significantly alter the microbial community structures and relative abundance.

2. MATERIALS AND METHODS 2.1. Feedstock and Inoculum. The RS used in this study was collected from Tianjin District, China. The RS was air-dried in an open field and then ground to the size of 20 mesh by a knife mill (YSW-180, Zhengde, China) in a laboratory. The liquid fraction of digestate (LFD) for pretreatment was obtained from an anaerobic reactor where RS was used as feedstock, which has been operated continuously for more than 1 year. Before being fed into reactors, the RS was pretreated with 6% CaO LFD for 3 days and the moisture content was adjusted to 88% based on the dry weight of RS using LFD.15 The inoculum for the AD process was taken from a biogas station in the Shunyi District (Beijing, China), where pig manure was used as feedstock. The characteristics of RS, LFD, and inoculum are listed in Table 1.

Table 1. Characteristics of RS, Inoculum, and LFDa TSb (%) VSb (%) Cc (%) Hc (%) Nc (%) Sc (%) Oc (%) C/N cellulosec (%) hemicellulosec (%) ligninc (%)

RS

inoculum

LFD

93.29 ± 0.09 83.78 ± 0.02 40.59 ± 0.06 5.78 ± 0.03 0.91 ± 0.03 0.11 ± 0.01 39.34 ± 1.59 50.83 35.32 ± 0.56 28.92 ± 0.21 7.88 ± 0.20

11.42 ± 0.17 6.67 ± 0.11 28.36 ± 0.79 4.17 ± 0.11 2.38 ± 0.08 0.66 ± 0.02 − 11.90 − − −

3.93 ± 0.02 2.14 ± 0.01 26.37 ± 0.08 3.54 ± 0.04 2.23 ± 0.06 0.40 ± 0.02 − 11.84 − − −

a Values are means ± SD (n = 3). bContent of fresh matter. cContent of dry matter.

2.2. Reactor Setup and Operations. A CSTR with a total volume of 10 L and a working volume of 8 L was applied for AD. The mixer motor, temperature probe, and biogas outlet were on the top of the reactor, while both the feeding and effluent sites were fit on both sides. Reactor temperature was maintained at 35 ± 1 °C by pumping hot water from an electric heating tank to a water jacket outside the reactor walls. The mix material in the reactor was stirred by

Figure 1. DBP of R1, R3, and R6 at phase 1, phase 2, and phase 3. B

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Figure 2. Methane content of R1, R3, and R6 at phase 1, phase 2, and phase 3.

Table 2. DMP-V, DMP-VS, and Main Component Conversion Rates of Different Feeding Intervals phase

item

2

R1 R3 R6 R1 R3 R6

3

DMP-V (mL·L−1·day−1) 304.0 292.5 301.5 294.6 334.3 294.0

± ± ± ± ± ±

DMP-VS (mL·g−1 of VS·day−1)

29.8 24.6 39.2 10.6 16.4 13.6

234.1 225.2 232.1 226.8 257.4 226.3

± ± ± ± ± ±

23.0 18.9 30.2 15.4 12.6 10.5

cellulose (%) 66.69 67.51 67.74 67.20 70.89 66.79

which was defined as the point where the difference in the production of daily biogas yield was within 5% of average values.9 Microbial DNA was extracted using the FastDNA Spin Kit (MP Biomedicals, USA) according to the manufacturer’s protocols. The final DNA concentration and purification were determined by a NanoDrop 2000 UV−vis spectrophotometer (Thermo Scientific, USA), and DNA quality was checked by 1% agarose gel electrophoresis. The V3−V4 hypervariable region of the bacterial 16S rRNA gene was amplified using primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) by a thermocycler PCR (polymerase chain reaction) system (GeneAmp 9700, ABI, USA). The PCR reactions were conducted using the following program: 95 °C denaturation for 3 min, 27 cycles at 95 °C for 30 s, 55 °C annealing for 30 s, 72 °C elongation for 45 s, and a final extension at 72 °C for 10 min). In the same way the archaeal 16S rRNA gene was amplified by PCR (95 °C for 3 min, followed by 33 cycles at 95 °C for 30 s, 55 °C for 30 s, and 72 °C for 45 s, and a final extension at 72 °C for 10 min) using primers 524F10extF (5′-TGYCAGCCGCCGCGGTAA-3′) and Arch958RmodR (5′-YCCGGCGTTGAVTCCAATT-3′). The PCR reactions were performed in triplicate using 20 μL of a mixture which contained 4 μL of 5×FastPfu Buffer, 2 μL of 2.5 mM dNTPs, 0.8 μL of Forward Primer (5 μM), 0.8 μL of Reverse Primer (5 μM), 0.4 μL of FastPfu Polymerase, 0.2 μL of BSA, and 10 ng of template DNA, and then ddH2O was added to 20 μL. The resulted PCR products were extracted from a 2% agarose gels and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) and quantified using QuantiFluor-ST (Promega, USA) according to the manufacturer’s instructions. The purified amplicons were pooled in equimolar and paired-end sequenced (2 × 250) on an Illumina MiSeq platform (Illumina, San Diego, CA, USA) according to the standard protocols.

± ± ± ± ± ±

0.71 0.47 0.41 0.91 0.90 1.36

hemicellulose (%) 59.39 58.10 59.25 59.23 62.45 59.01

± ± ± ± ± ±

0.68 0.92 0.65 0.53 0.52 0.41

lignin (%) 1.55 2.94 2.73 3.93 4.94 2.79

± ± ± ± ± ±

0.79 1.57 1.08 3.17 1.57 2.03

TS (%) 52.87 55.98 54.14 54.40 58.10 53.67

± ± ± ± ± ±

2.66 1.64 2.16 1.80 1.69 1.10

VS (%) 58.92 59.90 59.41 58.70 63.29 56.33

± ± ± ± ± ±

1.45 1.16 2.43 1.52 1.49 1.11

up phase (phase 1) was common for all reactors, it was not the main focus of this study. In phase 2, three reactors began to be fed every day in three HRTs. During the initial HRT, DBP was unstable, and then it became stable to produce about 4.6−4.7 L·day−1 at the next two HRTs. The methane content of the three reactors was about 51.0%, which was consistent with previous work.18 The biogas production rates of the three reactors varied within 5% of their average values after an operating time to three HRT periods, showing that the three reactors became in the steady state and run synchronically.19 In phase 3, three different FRs were operated. For R3 and R6, DBP and methane content were high on the first day of feeding; however, the biogas production was decreased on the following days of feeding, which was possibly due to the large feed volume of R3 and R6 on the feeding day. Considerable amounts of small molecular weight acids in pretreated RS were directly utilized by methanogens and rapidly converted to methane on the first day after feeding. When the process of AD continued, the readily available soluble compounds in pretreated RS were gradually consumed, resulting in the reduction of DBP and methane content. Besides, the methane content in this study with a narrow range of time margins (every day, every 3 days, and every 6 days) (49.3−60.0%) was higher than that with a wide range of time margin, such as every 14 days (45.4%),12 indicating that more infrequent feeding intervals present negative effects on methane content. This was due to a wide range of time margin fed reactors trended to have greater VFAs accumulation, which could not maintain process stability. 3.2. Biomethane Yield and Substrate Conversion. DMP-V and DMP-VS of the three reactors in phase 2 were 292.5−304.0mL·L−1·day−1 and 225.2−234.1 mL·g−1 of VS· day−1, respectively (p > 0.05) (Table 2). In phase 3, R3 achieved the highest DMP-V and DMP-VS, which were 12.5

3. RESULTS AND DISCUSSION 3.1. Biogas Production and Methane Content. The variations in DBP and methane content for three reactors at different phases are shown in Figures 1 and 2. Since the startC

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Figure 3. VFAs, TAC, and VFAs/TAC of different feeding intervals at phase 2 and phase 3.

the ratio between VFAs and TAC (VFAs/TAC). In this study, these parameters were used to evaluate the reactor stability for each feeding interval. The pH values of three reactors under different feeding intervals were 6.91−7.15 during the entire experimental period, which is believed to be the optimal range (6.8−7.2) for methane bacteria.20 TAC values in the three reactors at phase 2 and phase 3 were all above 2000 mg·L−1, which proved that the AD system maintained the buffer capacity of digestion liquid at an optimum level21 (Figure 3).The production of excess VFAs can inhibit the activity of the methanogens. The recommended value of VFAs for a healthy AD system was less than 790 mg·L−1.22 The ratio of VFAs/TAC is a useful control parameter representing the ratio between intermediate alkalinity by volatile organic acids and alkalinity by the bicarbonates to monitor the risk of acid accumulation in a digester.23 If the ratio of VFAs/TAC is lower than 0.40, the digester is at a stable operating condition.24 From day 30 to day 255 of digestion period, the concentrations of VFAs and the ratios of VFAs/TAC are shown in Figure 3. For both R1 and R3 systems, the concentrations of VFAs in phase 2 and phase 3 were low (below 200 mg·L−1); as a result the VFAs/TAC ratio was lower than 0.05. This showed that AD process was running at continuously stable conditions. On the other hand, in phase 2 of R6, the VFAs concentration was low (below 160 mg·L−1), but a little increase of VFAs and VFAs/TAC in phase 3 was observed, which was 500 mg·L−1 and 0.12, respectively. The reason for higher VFAs accumulation was mainly because of the more infrequent feeding interval; it had been found that the infrequently fed reactors such as once per 21 days would produce significantly more VFAs than other frequently fed reactors, and even an irreversible acidification phenomenon would occur, resulting in the failure of the AD system.12 In this study, the feeding interval in R6 was not too much frequent; the high TAC in the system could still maintain a stable state. In comparison, all three feeding intervals for AD can provide the lignocellulosic AD process a good buffer capacity, though R6 would show slightly high VFAs concentrations. 3.4. Changes in the Microbial Community Structure. 3.4.1. Alpha Diversity Indices of Bacterial and Archaea 16S rRNA Gene Sequences. The activity of members of the microbial community in an anaerobic digester could influence the rate of lignocellulose degradation, which directly affects the process of methane production.25 Therefore, comparison of microbial richness and diversity in different reactors and statistical analysis of bacterial and archaeal communities in

and 17.3% higher than those of R1 and R6 (p < 0.05), respectively. Statistically, there is no significant difference between the DMP-V and DMP-VS of R1 and R6 (p > 0.05). The result in this study was in line with that of Mulat et al.9 which showed the reactor fed after every second day was a better choice in CSTR treating distiller’s dried grains with solubles. Compared with results from other studies, biomethane yields with narrow FRs here were 50.0−76.1% higher than that with a more infrequent feeding interval such as after every 21 days feed rate (148 mL·g−1 of VS·day−1).12 The conversion rates of the main components from the effluents of different FRs are shown at Table 2. In phase 3, the TS and VS reductions for R3 reached 58.10 and 63.29%, respectively, which were 6.8−12.4% higher than those of R1 and R6. The contents of cellulose and hemicellulose were reduced by 67.20 and 59.23% for R1, 70.89 and 62.45% for R3, and 66.79 and 59.01% for R6, respectively. The conversion rate of lignin was 2.79−4.94% for the three runs, indicating that FR had no significant improvement in the degradation of lignin. The cellulose, hemicellulose, and lignin (LCH) achieved a higher conversion rate than Hu’s study,18 when rice straw was employed for biogas production with recirculation of LFD. Because methane is generated from the biological conversion of C-based substances, which is mainly from the LCH of RS in this paper, the higher reductions of TS, VS, and main compositions in R3 during the process of AD correspond to the higher biomethane yield. The biomethane yield obtained and the rate of substrate conversion result showed that R3 achieved better performance of improving the biomethane yield and substrate conversion than R6, which was mainly due to the larger feeding volume in R6. With the same HRT, the RS fed in R6 could not be converted completely (Table 2), which influenced the microbial community structure as discussed in section 3.4. Additionally, R6 and R1 achieved similar efficient conversions of RS to biomethane (p > 0.05), which indicated that too long or too short feeding intervals could not improve the production of methane based on the biomethane yield order: fed every 3 days > fed every day = fed every 6 days. Generally, the reactor fed after every 3 days showed better performance, indicating that the reduction of feeding frequency of RS in the AD process revealed a promising prospect in future AD practical engineering applications. 3.3. System Stability. For the long term of RS AD with different feeding intervals, the stability of the digestion system depends on a number of factors such as pH, VFAs, TAC, and D

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Energy & Fuels Table 3. Alpha Diversity Indices of Bacterial and Archaea 16S rRNA Gene Sequences group

sample

coverage

OTU

Ace

Chao

Shannon

Simpson

bacterial

R1 R3 R6 R1 R3 R6

0.99941 0.99913 0.99870 1.00000 1.00000 0.99996

423 429 383 29 30 31

433 445 413 29 30 33

431 451 414 29 30 32

4.12 4.30 3.21 1.50 2.01 1.66

0.0527 0.0369 0.1760 0.3592 0.1942 0.3221

archaea

during stable process performance26 and have special features to withstand unfavorable environmental conditions because of the spore-forming capability of Firmicutes.29 The abundance of Firmicutes in R1, R3, and R6 was in the range 12.40−17.31%, showing that there was high abundance during system operation, which can explain the system stability during the whole AD process. Meanwhile, a number of other phyla presented in the three reactors might play important roles, although they had low percentages (1.00% in all samples were considered high-rank groups. On the other side, 10 bacterial genera, including VadinBC27_wastewater-sludge_group (23.72 ± 12.51%), Norank_p_WS6 (5.84 ± 1.82%), Norank_f_Synergistaceae (5.16 ± 1.01%), Bacteroides (4.66 ± 1.99%), Norank_f_Draconibacteriaceae (4.36 ± 4.33%), Trichococcus (3.04 ± 0.56%), Georgenia (2.73 ± 1.33%), Norank_f_Porphyromonadaceae (2.50 ± 1.56%), Norank_c_W27 (2.34 ± 2.70%), and Smithella (2.12 ± 1.17%) were relatively dominant. Among all the bacterial genera, the genus VadinBC27_wastewater-sludge_group was the predominant group in three reactors and the relative abundance in R3 (40.59%) was higher than those of R1 (19.89%) and R6 (10.67%). The genus VadinBC27_wastewater-sludge_group, belonging to the phylum Bacteroidetes, class Bacteroidia, order Bacteroidales, family Rikenellaceae, were fermentative acid-producing bacteria and usually play a key role in the degradation of recalcitrant organic material.30 The genera Bacteroides and Norank_c_W27 were two other abundant bacterial groups in R3 (7.28 and 6.14%), which were low in R1 (4.26 and 2.45%) and R6 (0.14 and 0.74%). Bacteroides were reported to be capable of hydrolyzing complex organics such as hemicellulose and xylan; this is because Bacteroides have an important hemicellulolytic activity.31 In addition, some investigated Bacteroides could produce an extracellular multienzyme cellulosome complex to utilize cellulose or cellobiose as carbon sources for efficient degradation of plant cell wall polysaccharides.32 The result showed that the dominant bacterial in the reactor adapted the condition in R3, resulting in higher efficiency of hydrolysis.

each effluent are shown in Table 3. The obtained sequences were quality checked and normalized to approximately 160 000 sequences. The coverage index refers to the coverage of each sample library. The coverage indices of all samples were greater than 99.8%, which indicated that the depth of sequencing had basically covered all species, and the sequencing results of this study represented the real situation of microorganisms in three samples. The bacterial OTU number was higher in R3 than those in R1 and R6, whereas the archaea OTU number in R6 was higher than that in other reactors. Ace and Chao indices were used to estimate the number of OTUs in samples using different calculation methods, which reflected the richness of the community in an anaerobic digester. Though the estimated results (Ace and Chao indices) of three reactors were slightly higher than the observed number of OTUs, the overall trend was similar, which confirmed that the variety of community richness in the study was credible. The alpha diversity indices such as the Shannon and the Simpson indices focused on the community diversity were calculated for each sample. Based on the results, the bacterial Shannon index and the archaea Shannon index in R3 were higher than those in R1 and R6, and the bacterial Simpson index and the archaea Simpson index of each sample in R3 were lower than those in other reactors. The results indicated that too long or too short feeding intervals would inhibit the richness and diversity of the microorganism community in the anaerobic digester. R3 had obvious advantages in microbial richness and diversity compared with R1 and R6, which resulted in a higher degradation rate of RS25 and could improve the ability to overcome process perturbations.26 Besides, the disappearance of some bacterial population suggested the loss of bacterial stratification and the decrease in the evolution of new communities, which was a successful manifestation of the biochemical activities of the AD system.27 3.4.2. Distributions of Bacterial Sequences. To explore the effect of the feed regimes on AD performance, the bacterial community compositions in three feeding intervals were estimated (Figure 4a). Bacteroidetes and Firmicutes were the dominant phyla in all three reactors, containing hydrolytic bacteria as well as acidogenic and fermentative bacteria, which have been reported in both lab-scale and full-scale anaerobic digesters.25,26,28 Among the two dominant phyla, Bacteroidetes showed the highest abundance in three feeding interval reactors, which had been frequently reported for different AD reactors treating agricultural and agro-food residues.28 Bacteroidetes play a vital role in anaerobic degradation, and are important heterotrophs involved in hydrolysis as well as acidification and fermentation.29 The thriving of Bacteroidetes phyla in R3 had a relative abundance of 56.84%, which was higher than that of R1 (41.37%) and R6 (38.33%). This result is directly related to the enhanced biomethane yield, showing that R3 can improve the efficiency of biomasses hydrolysis in the AD process. Firmicutes can dominate carbon metabolism E

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Figure 5. Archaeal sequence distributions at phylum level (a) and genus level (b).

anaerobic conversion of H2 , formate, acetate, methyl compounds, and simple alcohols to methane could be especially facilitated in R3.34 The result was in line with Yuan et al.,35 who reported Euryarchaeota occupied 55.68% of the total archaeal sequences. The dynamic profiles of the archaeal community at the genus level in all reactors are shown in Figure 5b. In the AD system, more than 70% of methane in biogas comes from the cleavage of acetate. However, two common genera are known to use acetate as a substrate for methanogenesis, namely, Methanosarcina and Methanosaeta.36,37 Methanosaeta is one of the main acetate utilizers, which can use acetate at low concentrations such as 5−20 μmol·L−1, while Methanosarcina requires a minimum concentration of about 1 mmol·L−1. The acetic acid concentration in this experiment was at the low range (