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Biogas production and microbial community properties during anaerobic digestion of corn stover at different temperatures
Accepted Manuscript Biogas production and microbial community properties during anaerobic digestion of corn stover at different temperatures ChunMei Liu, Akiber Chufo Wachemo, Huan Tong, SiHui Shi, Liang Zhang, HaiRong Yuan, XiuJin Li PII: DOI: Reference:
S0960-8524(17)32221-6 https://doi.org/10.1016/j.biortech.2017.12.076 BITE 19331
To appear in:
Bioresource Technology
Received Date: Revised Date: Accepted Date:
23 October 2017 21 December 2017 25 December 2017
Please cite this article as: Liu, C., Wachemo, A.C., Tong, H., Shi, S., Zhang, L., Yuan, H., Li, X., Biogas production and microbial community properties during anaerobic digestion of corn stover at different temperatures, Bioresource Technology (2017), doi: https://doi.org/10.1016/j.biortech.2017.12.076
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Biogas production and microbial community properties during anaerobic digestion of corn stover at different temperatures ChunMei Liua, b, Akiber Chufo Wachemoa, c, Huan Tonga, SiHui Shia, Liang Zhanga, HaiRong Yuana, XiuJin Lia* a
Department of Environmental Science and Engineering, Beijing University of Chemical Technology,
15 Beisanhuan East Road, Chaoyang District, Beijing 100029, PR China; b
Beijing Sound Environmental Engineering Company Ltd.
c
Department of Water Supply and Environmental Engineering, Arba Minch University, P.O.Box 21,
Arba Minch, Ethiopia.
Abstract: Temperature has different effects on anaerobic digestion (AD) of various biomasses, which could bring out changes in microbial communities. The relationship between microbial community and methane production at 35°C(R35), 38°C(R38), 41°C(R41), and 44°C(R44) was analyzed during AD of corn stover (CS). The results showed that the daily biogas and methane production from R44 were 16.6%-42.4% and 16.2%-40.6% higher than yields from R35, R38 and R41, respectively. The abundance of Bacteroidetes in R35, R38 and R41 was relatively close (30.70%-39.36%), which was low in R44 (16.00%). The abundance of Firmicutes in R35 was 32.30%, however, Firmicutes was the most dominant phylum at R44 (66.58%). The abundance of Miscellaneous_Crenarchaeotic_Group and Euryarchaeota were 54.63 ± 6.47% and 44.43 ± 6.73% across all digesters. This research demonstrated that among all temperatures studied, 44°C could enhance the conversion efficiency of the substrates to methane and be recommended for better conversion of CS in AD process. Key words: Corn stover; Temperature; Anaerobic digestion; Biogas production; Microbial community 1 Introduction Generation of renewable energy from various sustainable sources like bioorganic materials have gained high interest in recent years. When transforming organic wastes into bio-methane, AD *
Corresponding author. Addresses: 15 Beisanhuan East Road, Chaoyang District, Beijing,100029, P.R. China. Tel/fax.: +86 10 64432281. E-mail addresses: [email protected] or [email protected] (X. Li). 1
plays major role in converting the substrate. AD process is a convenient and environmentally friendly treatment method for strong organic wastes such as agricultural byproducts and food wastes, while producing clean multipurpose energy for the community (Peces et al., 2016). Using corn stover (CS) as a raw material for AD process has tremendous advantages, because the production of CS is one of the most abundant agricultural wastes in China (Li et al., 2017). Additionally, the corn could be cultivated more than once per annum and its stover is rich in carbonaceous compounds. The system stability and process performance of anaerobic reactors mainly depend on many parameters and conditions such as temperature, pH, carbon to nitrogen ratio (C/N) and feedstock to microorganism ratio (F/M) have their own roles in anaerobic digestion process. From these parameters, temperature plays its part in making favorable conditions for various microbial community in reactors (Mao et al., 2015; Pap et al., 2015). Microorganisms in different anaerobic reactors are classified according to the optimum and favorable temperature ranges in which they can grow and develop; these are: psychrophilic (T<20°C), mesophilic (20°C< T <45°C), thermophilic (45°C< T <60 °C) and hyperthermophilic (T >60°C). However, thermophilic (55°C) and mesophilic (35°C) conditions are commonly used temperatures during anaerobic digestion of organic wastes(Kim & Oh, 2011). The operation of AD at mesophilic temperatures is more stable and requires less energy expenditure than thermophilic temperature. Moreover, the advantages of the mesophilic process indicate that there is less probability of ammonia and long chain fatty acids inhibition (Fields, 2001; Hansen et al., 1998). On the other side, the thermophilic anaerobic digestion known by its higher metabolic rates of microorganisms, volatile solids and COD removal, provides more effective pathogen inactivation and yields higher biogas volume compared to mesophilic treatment(Mao et al., 2015; Provenzano et al., 2013). However, several studies have pointed out numerous limitations of the thermophilic process over the mesophilic one including higher sensitivity to operational conditions, decreased stability due to the accumulation of ammonia and volatile fatty acids (propionic acid), lower methane content in biogas and higher net energy input (Bolzonella et al., 2012; Mao et al., 2015). Moreover, the research of temperature mainly focus on the swine manure (Lin et al., 2016b; Xiang-Kun et al., 2014). Therefore, CS digestions were performed at higher temperature ranges of mesophilic condition (38°C, 41°C, 44°C) to get more suitable digestion temperature. 2
Microorganisms are the back bone of anaerobic digestion to convert the feedstock to different components of biogas, so the digester conditions like change in even specific temperature could directly affect the microbial community structure, diversity and activity of specific populations (Gannoun et al., 2016). For example, the importance of hydrogenotrophic methanogenesis increases as temperature shifts from 37°C to 55°C in AD systems, which is based on the observed decrease
of
acetoclastic
Methanosaeta
and
the
increase
of
the
hydrogenotrophic
Methanothermobacter and Methanoculleus. These may result in alternative methanogenic pathways in AD process (Pap et al., 2015; Tian et al., 2015). In contrast to the mesophilic digesters, the microbial communities in the thermophilic digesters were rather similar, mainly consisting of the Firmicutes, Thermotoga and Synergistetes phyla (Zamanzadeh et al., 2016). However, reports which show the variation of microbial community structure and system performance in the reactors with different temperatures at mesophilic condition and its correlation with CS conversion rate have not been clearly studied in literature. The primary objective of this study was to characterize and compare the performance of four anaerobic digesters fed with CS at different temperature conditions using continuously stirred tank reactors (CSTR) experiments. Then the microbial community structures of the four digesters were analyzed to evaluate the temperature-regulated microbial effects on system functioning in AD process based on Illumina MiSeq sequencing analysis method. 2 Materials and methods 2.1 Feedstock and inoculum 2.1.1 Feedstock CS harvested in the Beichen County of Tianjin City and taken from bales stored in sheltered area was used as feedstock in this study. The collected CS was chopped by a paper chopper (PC500, Staida Co., Tianjing, China) and then further ground into the size of 20 meshes by a universal pulverizer (YSW-180, Yanshan Zhengde Co., Beijing, China). 2.1.2 Inoculum
The inoculum used in this experiment was taken from a mesophilic biogas plant using pig manure as the raw material in Shunyi District, Beijing, China. The inoculum 3
was screened by a 1 mm sieve to remove impurities and prevent clogging problems prior to be used as feed. The characteristics of CS and inoculum are shown in Table 1. 2.2 Pretreatment In this study, sodium hydroxide was used as pretreatment reagent. High moisture (wet state) NaOH pretreatment technique was used to pretreat corn stover, which is believed to be a cost-effective and efficient approach for anaerobic digestion process (Luo et al., 2005). Before fed into reactors, the corn stover was pretreated with NaOH solution based on the ratio of dry weight of corn stover : NaOH : H2O=10:0.2:60 (w/w/w) at ambient temperature (20±2°C) for three days(Zheng et al., 2009). 2.3 Anaerobic digestion Lab-scale continuously stirred tank reactors (CSTRs) at various temperature conditions were used to study the anaerobic digestion of CS pretreated by NaOH. To incubate the system, reactors were kept at the selected temperature by water circulating through the surrounding water jacket and the reactor was agitated with a stainless steel stirrer. Four lab-scale CSTRs (R35, R38, R41 and R44) were operated at 35, 38, 41 and 44 °C temperature, respectively. The total volume of each reactor was 10L with the working volume of 8L. Except the difference in temperature conditions, the four reactors were operated under similar operating conditions to set up equivalent starting conditions including the same organic loading rates (OLR, 90g TS· L-1 ) and hydraulic retention time (HRT, 60d). Each reactor was seeded to maintain the inoculum in the digester at 30 g TS· L-1. The added inoculum raised the pH of the alkali treated corn stover to the range of its optimum level for AD (7.2). The steady state was defined to be the point when biogas production rates varied within 10% of their average values between feeding time in one HRT period(Luo et al., 2015). The CS substrate samples were periodically collected from reactors at feeding phase which was used for chemical composition analysis. All tests were performed in triplicate. 2.4 Measurement of biochemical methane potential Biochemical methane potential (BMP) assay was immediately conducted after collecting the effluents from each reactor. The aim of BMP assay was to evaluate the amount of available organic matter remained after AD from every reactor (R35, R38, R41 and R44) irrespective of its 4
temperature differences to analyze the BMP at 35°C uniformly. The specific characteristics of effluent from each reactor are presented in Table 2. BMP assays were carried out using 500 mL reactors with the working volume of 400mL. The amount of inoculum was maintained constant at 10 g TS· L-1 in all reactors where the substrate to inoculum ratio (SIR) was 0.5g TS substrate/g TS inoculum. The BMP tests were conducted using an Automatic Methane Potential System II (Bioprocess Control, Sweden) at 35°C. All tests were performed in triplicate. 2.5 Analysis of the microbial community The microbial communities in each anaerobic digester treating CS at different temperatures were investigated, and the samples were collected from reactors at feeding phase. During this process the functional roles of specific microbial populations were evaluated in relation with methane production in each stages of the AD. 2.5.1 DNA extraction and PCR amplification The sample for DNA extraction was prepared and analyzed based on the method adapted from the manufacturer protocol of FastDNA Spin Kit (MP Biomedicals, U.S.A). The sample (slurry) for DNA analysis was collected when the anaerobic reactors exhibit stable conditions and performance; for example, the difference in the production of daily biogas yield was not more than 5% after feeding time up to the next feeding and continues in the same condition. The V3-V4 region of the bacterial 16S ribosomal RNA gene were amplified by PCR (95°C for 3 min, followed by 27 cycles at 95°C for 30s, 55°C for 30s, and 72°C for 45s and a final extension at 72°C for 10min) using primers 338F (5’- ACTCCTACGGGAGGCAGCAG-3’) and 806R (5’GGACTACHVGGGTWTCTAAT-3’). In the same way the archaeal 16S ribosomal RNA gene were amplified by PCR（95°C for 3min, followed by 33 cycles at 95°C for 30s, 55°C for 30s, and 72°C for 45s and a final extension at 72°C for 10min）using primers 524F_10_ext (5’TGYCAGCCGCCGCGGTAA)-3’) and Arch 958R (5’- YCCGGCGTTGAVTCCAATT-3’). The PCR reactions were performed in triplicate using 20µL mixture which contained 4µL of 5 × FastPfu Buffer, 2µL of 2.5mM dNTPs, 0.8µL of Forward Primer (5µM), 0.8µL of Reverse Primer (5µM), 0.4µL of FastPfu Polymerase, 0.2µL of BSA and 10 ng of template DNA, then add ddH2O 5
to 20µL. 2.5.2 Illumina high-throughput 16S rRNA gene sequencing Amplicons were extracted from 2% agarose gels and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, U.S.) according to the manufacturer’s instructions and quantified using QuantiFluor™ -ST (Promega, U.S.). The purified amplicons were pooled in equimolar and paired-end sequenced (2 × 250) on an Illumina MiSeq platform according to the standard protocols. The raw reads were deposited into the NCBI Sequence Read Archive (SRA) database. 2.6 Analytical methods and data analysis 2.6.1 Biogas analysis The H2, N2, CH4 and CO2 content of biogas were detected using gas chromatograph (SP2100, Beifen, China) with a TDX-01 column, a thermal conductivity detector (TCD) and a calibration curve made of known standard gases (H2 9.99%, N2 5.02%, CH4 49.98%, CO2 35.01%). The operational temperatures at the injection port, column oven, and detector were 150°C, 140°C, and 150°C, respectively. Argon was used as the carrier gas. The amount of daily biogas production was recorded by water displacement method. 2.6.2 Chemical composition analysis The total solid (TS), volatile solid (VS) were determined by the APHA standard methods (Walter, 1998). The pH value was measured using pH meter (CHN868, Thermo Orion, America). TC was analyzed by an elemental analyzer (Vario EL/micro cube elemental analyzer, Germany). TN was determined using the total Kjeldahl nitrogen analyzer (Model KDN-2C, Shanghai). The NH3-N was analyzed by a Kjeldahl analyzer (KT-260, Foss, Suzhou, China). Alkalinity was measured by pH titration method using 0.1M HCl and expressed in g equivalent CaCO3· L-1. The contents of lignin, cellulose, and hemicellulose were determined by fiber analyzer (ANKOM A2000i, ANKOM, USA) according to the procedures proposed by Van Soest et al (1991). 6
The samples for VFAs and ethanol analysis were first centrifuged at 10,000 rpm for 5min, the supernatants were then filtered through a 0.22µm filter, and filtrates were collected in sample vials for analysis. The VFAs yields were calculated as the cumulative sum of the measured acetic (HAc), propionic (HPr), n-butyric (n-HBu), iso-butyric (iso-HBu), n-valeric (n-HVa) and iso-valeric (iso-HVa) acids. The content of each VFA was determined using the gas chromatograph (GC2014, 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 components were based on the standard calibration curve according to manufacturer protocol. 3 Results and discussion 3.1 CSTR experiments 3.1.1 Biogas yield and methane content The process performance of laboratory-scale CSTRs fed with NaOH pretreated CS was analyzed, and the four reactors were operated under identical conditions, except different temperature (35°C, 38°C, 41°C and 44°C). Therefore, the operational parameters of biogas performance were monitored for different temperature conditions during 160 days of digestion period (Fig.1(a, b)). Daily biogas production experienced three-four peaks during starting-up phase (1-40d). At the end of starting-up phase, the total biogas production reached 445.2 L and 451.3 L for R38 and R44, followed by 291.2 L, and 273.0 L for R35 and R41, respectively. Then the daily biogas and methane production tended to be steady from day 41 to 160. Comparatively, R44 resulted the best daily biogas and methane production performance, which were averagely 6.5±0.5 L and 3.4±0.3 L, respectively. The process performances were similar in the R35, R38 and R41, and the average daily biogas and methane production was 4.6-5.6 L and 2.4-2.9 L. As shown in Fig.1(c, d), the average methane and carbon dioxide content of four reactors were almost similar, which were 51.60±0.44 % and 45.45±0.87 %, respectively. When compared with previous studies, which found CH4 content in the biogas during the feeding phase of AD of swine manure was higher at 50 and 55°C (around 60%) than 25 and 35°C (Lin et al., 2016b). In the same way, CH4 content in the biogas increased with temperature from 25°C to 45°C, and was 7
stable at higher temperatures around 60% CH4 content during the feeding phase (Lin et al., 2016a). This indicates that, the methane content of the biogas was mainly affected by the type of substrate, rather than temperature conditions. Table 3 shows that the increment of process efficiency from R35 to R44. The daily methane production based on reactor volume reached 300, 360, 310, 420 mL· L-1·d-1 at 35, 38, 41 and 44°C, respectively. The daily biogas and methane production (based on VS) obtained from R44 were 598 mL· L-1·d-1 and 308 mL· L-1·d-1, respectively, which were 16.6%-42.4% and 16.2%-40.6% higher than yields from R35, R38 and R41, respectively. R44 showed relatively better efficiency in the biogas production performance, indicating a higher capacity of methanogens (in R44) compared to methanogens in R35, R38 and R41. Lin et al found similar results and reported that biogas production is different at specific temperatures from 25°C to 50°C (Lin et al., 2016a).The results stated that temperature affects biogas production, optimal temperature for different substrates could be different and needs to be determined by specific study. 3.1.2 Main component conversions Cellulose, hemicellulose and lignin are the main components of CS, accounting for 74.9% of the total dry matter and providing the main carbon sources for anaerobic microorganisms. However, biogas production is highly affected by the availability and digestibility of cellulose, hemicellulose, and the association of lignin with the carbohydrates. In principle, the production of more biogas is related to the conversion of more substrate resulting the reduction of VS. In this study, cellulose and hemicellulose bioconversion rates were analyzed to investigate the trend of bioconversion. Fig.2 (a, b, c) shows the changes in chemical compositions of the four experimental groups within the feeding time interval of 40 d to160 d. Bioconversion rates of cellulose and hemicellulose varied in all four experimental groups. More specifically, the hemicellulose, cellulose, and lignocellulose bioconversion rates of CS in R44 were 63.4%、62.4% and 61.1%, respectively. The bioconversion rates of hemicellulose for R35、R38 and R41 were 42.8%、47.4% and 55.2%, respectively. The total cellulose bioconversion rates were close to each other in R35 and R41, which were 45.0% and 48.9%, respectively. The conversion rates of total lignocellulose were not statistically significant, which were 45.6% and 49.0% for R35 and R41, respectively, while 55.10% for R38. 8
Changing temperature is a simple and effective method to improve the biodegradability of lignocellulosic material. Optimal increment in temperature can facilitate the hydrolysis of cellulose and hemicellulose into relatively biodegradable components, and break the link between polysaccharide and lignin to make cellulose and hemicellulose more accessible to bacteria. This result further verified that the ability of temperature to improve biodegradability and enhance bioenergy production. Fig.3 (a, b) shows the changes in TS and VS removal rates for the four experimental groups during entire feeding time (40d-160d). TS and VS removal rates represents conversion of CS by anaerobic microorganisms. TS and VS removal rate for the four experimental groups were stable during the feeding phase which showed that there is no obvious fluctuation. However, in feeding phase, TS and VS removal rates of R44 were significantly higher than that of other experimental groups. The average TS and VS removal rate of R44 was 55.1% and 64.2%, respectively. Compared with the experimental groups of R35, R38 and R41, the TS and VS removal rate of R44 increased by 18.3%-30.8% and14.6% to 25.4%, respectively. 3.1.3 System stability When CS used as a sole substrate, AD system has more a probability to lose stability due to possible low buffering capacity. The stability of digestion system depends on a number of factors like pH, volatile fatty acids (VFAs), ammonia nitrogen (AN) and alkalinity. In this study, these parameters were measured to evaluate the reactor stability of NaOH pretreated CS samples in each temperature AD process. The pH values were 7.10-7.22 until the feeding phase for four reactors under different temperatures (Fig.4(a)), which is believed to be optimal for a biogas production process (De et al., 2012). For the digestion period of day 41 to 160, the concentrations of VFAs are shown in Fig.4(b). From R35 to R44, the concentrations of VFAs reached to 109-160 mg· L-1 in the feeding phase. Nevertheless, four reactors maintained low residual VFAs concentration under the different temperature conditions. This shows that the temperature difference in mesophilic condition did not affect the VFAs production, because the VFA production rate by fermentative bacteria and the subsequent production of acetate by acetogenic bacteria were well balanced with the individual VFA consumption rate(Marchaim & Krause, 1993). The concentrations of NH4+–N in four reactors remained in the range of 338-477 mg· L-1 at 9
the feeding phase (Fig.4(c)). Ammonia nitrogen from R44 was 477 mg· L-1, which was higher than the other reactors. The high ammonia nitrogen level at 44°C temperature implies that the protein fraction of CS was better hydrolyzed and fermented in subsequent steps. However, the existence of free ammonia in the reactors did not reach an inhibitory level. The alkalinity concentrations in all reactors were in between 3645-4402 mg CaCO3· L-1 (Fig. 4(d)), which was in the range of favorable conditions for anaerobic microbes. The alkalinity level of the higher temperature reactors was slightly more than that of the lower temperature reactors. 3.2 Evaluation of BMP assays The retention time of BMP analysis depended on the rate of methane production. This could be explained as the experiment stopped when the rate of methane production was undetectable or less than 1% of the total amount. The results of the cumulative methane production from BMP assays are shown in Fig.5. The total duration of the digestion time for effluents varied from 12-35 days. R35 group needed the more digestion time. However, R38, R41 and R44 have finished less than 20 days of AD. It showed that the effluent of R44 can be degraded quickly within short time. As shown in Table 4, the highest cumulative methane production (118 mL) was from the effluent of R35, and the effluent of R44 produced lower cumulative methane yield (25 mL). The methane yields from the three effluent samples (R38, R41 and R44) were lower than that of the effluent from R35, indicating more organic matter was used at higher temperatures. 3.3 Changes in the microbial community structure 3.3.1 Alpha diversity indices of bacterial and archaeal 16S rRNA gene sequences The possible correlations between the function of each microbial group and their performances in different temperature digesters were investigated. Enrichment of certain active microorganisms at specific temperature ranges shows that the sensitivity of anaerobic process within temperature differences which directly affects methane production process (Lin et al., 2016b). Therefore, a comparison of the microbial richness and diversity in the different reactors and statistical analysis of bacterial and archaeal community in each effluent were shown in Table 5. As it can be seen from Table 5, the coverage index was greater than or equal to 99.8% for all samples, this value confirms representativeness. The diversity of bacteria and archaea community were supported by OTUs number. For the 4 samples obtained, the total 16S rRNA gene 10
sequencing gave the range from 382-489 and 18-30 for Bacterial and Archaeal OTUs, respectively which were clearly higher in the R35, R38, and R41 than in the R44 based on chimeras and singletons. Based on the Ace and Chao 1 values (Table 5), bacterial and archaeal richness of each sample was higher in R35, R38 and R41 than in R44. The alpha diversity indexes such as the Shannon and the Simpson index which focuses on the evenness of microbial diversity were calculated for each sample. Based on the results, bacterial shannon index of each sample in the R38 (4.26) and R44 (4.24) were lower than the R35 (4.60) and R41 (4.52), bacterial simpson index of each sample in the R38 (0.0546) and R44 (0.0531) were higher than the R35 (0.0254) and R41 (0.0311). On the other hand, archaea shannon index of each sample in the R35 (1.62) and R41 (1.58) were higher in the R38 (1.85) and R44 (1.87), archaea simpson index of each sample in the R35 (0.2865) and R41 (0.3163) were higher in the R38 (0.2683) and R44 (0.2682). The results indicated that R44 had the lower richness, and higher the bacterial diversity and lower archaea diversity. Various studies also reported that microbial community descriptors such as diversity and evenness indices are directly relating to anaerobic digester functions (Carballa et al., 2011; Fernandez et al., 2000). 3.3.2 The distributions of bacterial sequences In four reactors the dynamic profiles of bacterial phyla varied significantly during the feeding phase (Fig. 6(a)). Bacteroidetes and Firmicutes were the dominant phyla in four reactors. Although the major phyla coexisted in the two communities, their respective abundances were very different. The abundances of Bacteroidetes in R35, R38 and R41 were in the range from 30.70% -39.36%, however, it abundance was low in R44 (16.00%). More specifically, the abundance of Firmicutes in R35 was 32.30%, which was less than the abundance level in R41 (46.67%). As a result, Firmicutes were the most predominant phylum in R44 with maximum proportion of 66.58%. Meanwhile, a number of other phyla presented in each reactor might play important roles, although they had low percentage (>1%), such as proteobacteria, spirochaetae cloacimonetes,
candidate_division_WS6,
tenericutes,
synergistetes,
acteria_unclassified,
acidobacteria, lentisphaerae and so on. Phylum Bacteroidetes and Firmicutes contain hydrolytic bacteria as well as acidogenic and fermentative bacteria which have different functions in anaerobic digestion process(Ariunbaatar et al., 2014). Bacteroidetes are reported as an important member of heterotrophs that involve in 11
organic carbon cycling and proteinaceous substances (Kokkwang et al., 2016; Shi et al., 2015). Moreover, the studies cited that the hydrolysis of biomasses was positively correlated with the percentage of Bacteroidetes (Regueiro et al., 2012). Phylum Firmicutes have special features to tolerate unfavourable environments and can produce methanogenic precursors(Kokkwang et al., 2016). The huge dominance of Firmicutes in both lab-scale and full-scale thermophilic anaerobic digesters has been reported in various literatures (Lee et al., 2016; Pap et al., 2015; Tian et al., 2015). In this study, for the reactors from R35 to R44, Firmicutes’s relative abundance got higher. The ratio of Firmicutes to Bacteroidetes (RFB) in R35, R38 and R41 was 1.05, 0.96 and 1.33, respectively; but the RFB in the R44 was 4.16. (Briones et al., 2014) reported that the RFB could be affected by the types and compositions of substrates fed to the AD systems. In this study, the raw material used in all reactors was CS, so these variations in RFB were due to the temperature differences in the reactors. This result indicated that temperature will affect the microbial community diversity. The findings from various previous metagenomics studies of anaerobes have suggested the correlations between process variables (i.e., environmental variables) and bacteria at the phylum level (Liu et al., 2015; Pap et al., 2015). The genus level in four samples was observed; the result showed that the dynamic profiles of bacterial genus differed significantly in four Reactors (Fig.6(b)). 80.44% of the total bacterial reads were classified into 39 genera, out of these 23 bacterial genera showed relative abundance > 1.0% in all samples which were considered high-rank groups. Among these 23 genera, vadinBC27_wastewater-sludge_group (15.37 ± 11.98%), OPB54_norank (9.14 ± 11.38%), Sedimentibacter (4.70 ±0.03%), Ruminiclostridium (4.68 ± 2.44%), Ruminiclostridium_1 (4.60 ± 1.55%), Bacteroidales_UCG-001_norank (4.34 ± 4.13%), W27_norank (3.70 ±2.52%), Gelria (2.73 ± 5.21%), Bacteroides (2.25 ± 0.94%) and Candidate_division_WS6_norank (2.19 ± 2.64%) were dominant. The genus Subgroup_6_norank (1%) appeared at only 44°C temperature. Therefore, the genus vadinBC27_wastewater-sludge_group was the most abundant bacterial group in the R35, R38 and R41, where its specific abundance was 14.36%, 29.79% and 16.85%, respectively, and only 0.52% in R44. The genus vadinBC27 was first found in vinasses anaerobic digester, where some species in Methanosarcina, Methanobacterium and Thermoplasma also co-existed (Godon et al., 1997). Genus OPB54_norank showed a reverse pattern, as its proportion was the most abundant (25.70%) in the R44 but 0.36%, 3.21%,7.28% in the R35, R38, R41. These 12
results demonstrated that bacterial community shifts occurred in relation to temperature differences, especially the OPB54 bacteria which were previously found in engineered anaerobic systems(Li et al., 2009). The genus Gelria in R44 was the predominant, which accounted for 10.32%. Previous research also supports the significant contribution of Gelria to produce H2, which may then be utilized by HMs in a thermophilic AD system to degrade cellulose and microbial protein(Lü et al., 2014). Thus, Gelria sp. maybe an indicator of process performance in thermophilic AD systems. AT high temperature reactor, the relative abundance of OPB54 and Gelria which belong to the phylum Firmicutes, class Clostridia, order Thermoanaerobacterales, family Thermoanaerobacteraceae get higher. Bacteroides which was reported to be able to degrade cellulose and carbohydrate to cellobiose, glucose, and mannose then to acetate or succinate (Song et al., 2004; Wilson et al., 2008). 3.3.3 The distributions of archaeal sequences The distributions of archaeal sequences at the phylum level from each sample are shown in Fig.6(c). Miscellaneous_Crenarchaeotic_Group and Euryarchaeota were also the most dominant group among the archaeal phylums with an average relative abundance of 54.63 ± 6.47% and 44.43 ± 6.73%, respectively across all digesters. (Lliros et al., 2014) indicated that Miscellaneous_Crenarchaeotic_Group was one of the major archaeal groups in natural wetland ecosystem, and many Archaea are believed to be responsible for many biochemical reactions in the methanogenic phase (Watson-Craik, 1993). The dynamic profiles of the archaeal community at the genus level were significantly different in all reactors (Fig.6(d)). As it can be seen in Fig.6(d), archaeal communities demonstrated a clear dominance of the genus Miscellaneous_ Crenarchaeotic_Group_norank (MCG), which represented 44.95%-58.79% of sequences identified in the all reactors. The genus WCHA1-57_norank was the second abundant genus which contributed 39.45% of the archaeal population in R35, and only 10.93%, 4.39% and 6.32% for R38, R41 and R44, respectively. The abundance of genus Methanosaeta which was not appeared in R44 was dominant in R41; however, the abundance of genus Methanosarcina was low, only 1.70%. The abundance of genus Methanoculleus and Methanomassiliicoccus in R44 were 10.87% and 15.86%, but there were only 2.64%-3.91% and 0.26%-1.29% in R35, R38 and R41. This shows that after adaption to the environment and substrates produced by fermentative microorganisms, the metabolic activity 13
and/or growth rate of Methanoculleus and Methanomassiliicoccus were gradually enhanced. In AD systems, Methanosaeta are known to use acetate as the substrate for methanogenesis, whereas Methanoculleus use CO2 reduction pathway with either H2/CO2, or formateas substrate(Boone et al., 1993). Based on the observed decrease of acetoclastic Methanosaeta and the increase of the hydrogenotrophic Methanoculleus, the importance of hydrogenotrophic methanogenesis increases when temperature increases from 35°C to 44°C, this result in line with the report from (Pap et al., 2015). These observations suggested that when specific microorganisms are suppressed by increasing temperature, their functions might be replaced by other microorganisms with similar roles without major reduction in overall process performance during AD process. Differences in microbial community shifts were considered as an indicator that different microbes may be involved in biogas production. The most important novelty of the data presented in this study is the direct experimental evidence regarding the influence of temperature on the population levels of methanogenic anaerobic microorganisms in the digester. Furthermore, the fact that temperature had similar effects on bacterial and archaeal community structures implies that perturbing temperature could cause critical changes in syntrophic consortia (of bacteria and archaea) that perform methanogenesis. 4. Conclusions CSTR analysis revealed that daily biogas and methane production increased at 44°C. BMP assays at 35 °C showed that the effluent of R44 produced low methane yield, which confirmed more organic matter degraded at 44°C to produce maximum biogas. The most abundant bacterial phylum in four reactors were Firmicutes and Bacteroidetes, but the bacterial community structure was significantly different. Firmicutes dominated in R44, while Bacteroidetes was the dominant phylum in R35. The archaea genus in the four reactors was Miscellaneous_Crenarchaeotic_Group_norank. However, R44 have higher the amount of Methanoculleus and Methanomassiliicoccus while hydrogenotrophic methanogenesis seemed to be the dominant pathway. Acknowledgments: The authors are grateful to the fund supports from National "Twelfth Five-Year" Plan for 14
Science & Technology Support (2014BAC24B01-02), and National "Twelfth Five-Year" Plan for Science & Technology Support(2015BAD21B03).
15
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18
Feeding phase
Starting-up phase
40
10.0
R35
35
R38
R41
R44 7.5
25 20
5.0
15 10
2.5
（ a）
5
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
Digestion time (d)
Feeding phase
Starting-up phase
100
R35
90
R38
R41
R44
Methane content (%)
80 70 60 50 40 30 20
（ b）
10 0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
Digestion time (d) Feeding phase
Starting-up phase
100
R35
90
R38
R41
R44
Carbon dioxide content (%)
80 70 60 50 40 30 20
（ c）
10 0
10
20
30
40
50
60
70
80
90
Digestion time (d)
100
110
120
130
140
150
160
Daily biogas production (L)
Daily biogas production (L)
30
Feeding phase
Starting-up phase
20
5
R38
R41
R44 4
15
3 10 2
5 1
（ d）
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
Digestion time (d)
Fig.1 The performance of four reactors at the OLR of 90 gTS·L-1 for (a) Daily biogas production (L), (b) Methane content (%), (c) Carbon dioxide content (%) and (d) Daily methane production (L)
Daily methane production (L)
Daily methane production (L)
R35
20
R35
18
R38
R41
（ a）
R44
Hemi-celluose contents (%)
16 14 12 10 8 6 4 2 0 40
60
80
100
120
140
160
Time (d) 25
R35
R38
R41
R44 （ b）
Cellulose contents (%)
20
15
10
5
0 40
60
80
100
120
140
160
Time (d) 45
Lignocellulose contents (%)
40 35 30 25 20 15
R35
R38
R41
R44
10
（ c）
5 0 40
50
60
70
80
90
100 110 120 130 140 150 160
Time (d)
Fig.2 The changes of chemical compositions for four reactors at the OLR of 90 gTS·L-1.The error bars show the standard deviations (n=3).
60
R35
R38
R41
R44
TS removal rates (%)
55
50
45
（ a） 40 40
60
80
100
120
140
160
Time (d) 70
R35
R38
R41
R44
VS removal rates (%)
60
50
40
（ b） 30 40
60
80
100
120
140
160
Time (d)
Fig.3 TS and VS removal rate of four reactors at the OLR of 90 gTS·L-1. The error bars show the standard deviations (n=3).
7.6
240
R35
7.4
R38
R41
R44
7.2
7.0
6.8
6.6
R41
R44
120
80
40
（ a）
6.4 40
50
60
70
80
90
0 40
100 110 120 130 140 150 160
（ b） 50
60
70
80
90
100 110 120 130 140 150 160
Digestion time (d)
Digestion time (d) 800
7000
R35
700
R38
R41
R44
600
R35
6000
R38
Alkalinity (mg CaCO3L-1)
Ammonia nitrogen (mgL-1)
R38
160
VFAs (mgL)
pH
R35
200
R41
R44
5000
500
4000
400
3000
300
2000
200
（ c）
100 0 40
50
60
70
80
90
100 110 120 130 140 150 160
（ d）
1000 0 40
50
60
70
80
Digestion time (d)
90
100 110 120 130 140 150 160
Digestion time (d)
Fig.4 pH, VFA, ammonia nitrogen, and alkalinity of different reactors in CSTR experiments. The error
bars show the standard deviations (n=3).
130 120 110
Methane volume (mL)
100 90
R35 R38 R41 R44
80 70 60 50 40 30 20 10 0 0
5
10
15
20
25
30
35
40
Digestion time (d)
Fig.5 The BMP assays of the effluent from R35, R38, R41 and R44
Fig.6 Bacterial and archaeal sequence distributions at phylum (a, c) and genus(b, d) level
Table 1. Characteristics of CS and inoculum used in this study Indexes (Dry matter)
CS
Inoculum
Total Solid (TS, %)
93.21±0.05
10.38±0.04
Volatile Solid (VS, %)
86.38±0.13
5.70±0.12
VS/TS
0.927±0.003
0.549±0.013
Total Carbon（C, %）
43.55±0.23
29.20±0.32
Total Nitrogen（N, %）
0.92±0.06
2.79±0.12
C/N
47.50±4.81
10.49±0.80
Table 2. The characteristics of effluents for different reactors Effluents Indexes R35
R38
R41
R44
Total Solid (%)
4.61±0.06
4.30±0.07
4.16±0.04
4.08±0.04
Volatile Solid (%)
3.36±0.06
3.06±0.09
2.89±0.03
2.83±0.08
Ammonia Nitrogen (mg·L-1)
338±23
375±17
441±18
477±15
Alkalinity (mg CaCO3·L-1)
3645±356
3862±335
4134±400
4402±352
VFAs (mg·L-1)
109±5
123±6
144±9
160±9
Table 3. Daily biogas/methane production (DBP/DMP) per unit feeding VS and per reactor volume DBP-VS Groups
DMP-VS
mL·g-1 VS·d-1
DBP-V
DMP-V
mL·L-1·d-1
R35
420±22
219±11
570±30
300±16
R38
513±8
265±4
700±11
360±6
R41
440±19
225±10
600±26
310±13
R44
598±17
308±9
810±23
420±12
Table 4. Methane yields form BMP assays Effluent
Parameter Cumulative Methane(mL) -1
Methane Yield (mL·g VS)
R35
R38
R41
R44
118±6
56±4
49±4
25±1
41±2
19±1
18±1
11±0.5
Table 5. Alpha diversity indices of the bacterial and archaeal 16S rRNA gene sequences Groups
Samples
Coverage (%)
OTU
Ace
Chao 1
Shannon
Simpson
R35
99.9
460
471
471
4.60
0.0254
R38
99.8
482
511
515
4.26
0.0546
R41
99.9
489
506
515
4.52
0.0311
R44
99.9
382
397
406
4.24
0.0531
R35
1
30
30
30
1.62
0.2865
R38
1
28
28
28
1.85
0.2683
R41
1
24
34
26
1.58
0.3163
R44
1
18
20
19
1.87
0.2682
Bacterial
Archaea
Highlights A mesophilic temperature (44°C) can enhance conversion rate of corn stover to CH4. Biomethane potential assays confirmed that more organic matter degraded in R44. Biogas production rate was highest at 44°C among mesophilic temperatures studied. The abundance of bacterial and archaeal community was varied with temperature.
19
S0960-8524(17)32221-6 https://doi.org/10.1016/j.biortech.2017.12.076 BITE 19331
To appear in:
Bioresource Technology
Received Date: Revised Date: Accepted Date:
23 October 2017 21 December 2017 25 December 2017
Please cite this article as: Liu, C., Wachemo, A.C., Tong, H., Shi, S., Zhang, L., Yuan, H., Li, X., Biogas production and microbial community properties during anaerobic digestion of corn stover at different temperatures, Bioresource Technology (2017), doi: https://doi.org/10.1016/j.biortech.2017.12.076
This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Biogas production and microbial community properties during anaerobic digestion of corn stover at different temperatures ChunMei Liua, b, Akiber Chufo Wachemoa, c, Huan Tonga, SiHui Shia, Liang Zhanga, HaiRong Yuana, XiuJin Lia* a
Department of Environmental Science and Engineering, Beijing University of Chemical Technology,
15 Beisanhuan East Road, Chaoyang District, Beijing 100029, PR China; b
Beijing Sound Environmental Engineering Company Ltd.
c
Department of Water Supply and Environmental Engineering, Arba Minch University, P.O.Box 21,
Arba Minch, Ethiopia.
Abstract: Temperature has different effects on anaerobic digestion (AD) of various biomasses, which could bring out changes in microbial communities. The relationship between microbial community and methane production at 35°C(R35), 38°C(R38), 41°C(R41), and 44°C(R44) was analyzed during AD of corn stover (CS). The results showed that the daily biogas and methane production from R44 were 16.6%-42.4% and 16.2%-40.6% higher than yields from R35, R38 and R41, respectively. The abundance of Bacteroidetes in R35, R38 and R41 was relatively close (30.70%-39.36%), which was low in R44 (16.00%). The abundance of Firmicutes in R35 was 32.30%, however, Firmicutes was the most dominant phylum at R44 (66.58%). The abundance of Miscellaneous_Crenarchaeotic_Group and Euryarchaeota were 54.63 ± 6.47% and 44.43 ± 6.73% across all digesters. This research demonstrated that among all temperatures studied, 44°C could enhance the conversion efficiency of the substrates to methane and be recommended for better conversion of CS in AD process. Key words: Corn stover; Temperature; Anaerobic digestion; Biogas production; Microbial community 1 Introduction Generation of renewable energy from various sustainable sources like bioorganic materials have gained high interest in recent years. When transforming organic wastes into bio-methane, AD *
Corresponding author. Addresses: 15 Beisanhuan East Road, Chaoyang District, Beijing,100029, P.R. China. Tel/fax.: +86 10 64432281. E-mail addresses: [email protected] or [email protected] (X. Li). 1
plays major role in converting the substrate. AD process is a convenient and environmentally friendly treatment method for strong organic wastes such as agricultural byproducts and food wastes, while producing clean multipurpose energy for the community (Peces et al., 2016). Using corn stover (CS) as a raw material for AD process has tremendous advantages, because the production of CS is one of the most abundant agricultural wastes in China (Li et al., 2017). Additionally, the corn could be cultivated more than once per annum and its stover is rich in carbonaceous compounds. The system stability and process performance of anaerobic reactors mainly depend on many parameters and conditions such as temperature, pH, carbon to nitrogen ratio (C/N) and feedstock to microorganism ratio (F/M) have their own roles in anaerobic digestion process. From these parameters, temperature plays its part in making favorable conditions for various microbial community in reactors (Mao et al., 2015; Pap et al., 2015). Microorganisms in different anaerobic reactors are classified according to the optimum and favorable temperature ranges in which they can grow and develop; these are: psychrophilic (T<20°C), mesophilic (20°C< T <45°C), thermophilic (45°C< T <60 °C) and hyperthermophilic (T >60°C). However, thermophilic (55°C) and mesophilic (35°C) conditions are commonly used temperatures during anaerobic digestion of organic wastes(Kim & Oh, 2011). The operation of AD at mesophilic temperatures is more stable and requires less energy expenditure than thermophilic temperature. Moreover, the advantages of the mesophilic process indicate that there is less probability of ammonia and long chain fatty acids inhibition (Fields, 2001; Hansen et al., 1998). On the other side, the thermophilic anaerobic digestion known by its higher metabolic rates of microorganisms, volatile solids and COD removal, provides more effective pathogen inactivation and yields higher biogas volume compared to mesophilic treatment(Mao et al., 2015; Provenzano et al., 2013). However, several studies have pointed out numerous limitations of the thermophilic process over the mesophilic one including higher sensitivity to operational conditions, decreased stability due to the accumulation of ammonia and volatile fatty acids (propionic acid), lower methane content in biogas and higher net energy input (Bolzonella et al., 2012; Mao et al., 2015). Moreover, the research of temperature mainly focus on the swine manure (Lin et al., 2016b; Xiang-Kun et al., 2014). Therefore, CS digestions were performed at higher temperature ranges of mesophilic condition (38°C, 41°C, 44°C) to get more suitable digestion temperature. 2
Microorganisms are the back bone of anaerobic digestion to convert the feedstock to different components of biogas, so the digester conditions like change in even specific temperature could directly affect the microbial community structure, diversity and activity of specific populations (Gannoun et al., 2016). For example, the importance of hydrogenotrophic methanogenesis increases as temperature shifts from 37°C to 55°C in AD systems, which is based on the observed decrease
of
acetoclastic
Methanosaeta
and
the
increase
of
the
hydrogenotrophic
Methanothermobacter and Methanoculleus. These may result in alternative methanogenic pathways in AD process (Pap et al., 2015; Tian et al., 2015). In contrast to the mesophilic digesters, the microbial communities in the thermophilic digesters were rather similar, mainly consisting of the Firmicutes, Thermotoga and Synergistetes phyla (Zamanzadeh et al., 2016). However, reports which show the variation of microbial community structure and system performance in the reactors with different temperatures at mesophilic condition and its correlation with CS conversion rate have not been clearly studied in literature. The primary objective of this study was to characterize and compare the performance of four anaerobic digesters fed with CS at different temperature conditions using continuously stirred tank reactors (CSTR) experiments. Then the microbial community structures of the four digesters were analyzed to evaluate the temperature-regulated microbial effects on system functioning in AD process based on Illumina MiSeq sequencing analysis method. 2 Materials and methods 2.1 Feedstock and inoculum 2.1.1 Feedstock CS harvested in the Beichen County of Tianjin City and taken from bales stored in sheltered area was used as feedstock in this study. The collected CS was chopped by a paper chopper (PC500, Staida Co., Tianjing, China) and then further ground into the size of 20 meshes by a universal pulverizer (YSW-180, Yanshan Zhengde Co., Beijing, China). 2.1.2 Inoculum
The inoculum used in this experiment was taken from a mesophilic biogas plant using pig manure as the raw material in Shunyi District, Beijing, China. The inoculum 3
was screened by a 1 mm sieve to remove impurities and prevent clogging problems prior to be used as feed. The characteristics of CS and inoculum are shown in Table 1. 2.2 Pretreatment In this study, sodium hydroxide was used as pretreatment reagent. High moisture (wet state) NaOH pretreatment technique was used to pretreat corn stover, which is believed to be a cost-effective and efficient approach for anaerobic digestion process (Luo et al., 2005). Before fed into reactors, the corn stover was pretreated with NaOH solution based on the ratio of dry weight of corn stover : NaOH : H2O=10:0.2:60 (w/w/w) at ambient temperature (20±2°C) for three days(Zheng et al., 2009). 2.3 Anaerobic digestion Lab-scale continuously stirred tank reactors (CSTRs) at various temperature conditions were used to study the anaerobic digestion of CS pretreated by NaOH. To incubate the system, reactors were kept at the selected temperature by water circulating through the surrounding water jacket and the reactor was agitated with a stainless steel stirrer. Four lab-scale CSTRs (R35, R38, R41 and R44) were operated at 35, 38, 41 and 44 °C temperature, respectively. The total volume of each reactor was 10L with the working volume of 8L. Except the difference in temperature conditions, the four reactors were operated under similar operating conditions to set up equivalent starting conditions including the same organic loading rates (OLR, 90g TS· L-1 ) and hydraulic retention time (HRT, 60d). Each reactor was seeded to maintain the inoculum in the digester at 30 g TS· L-1. The added inoculum raised the pH of the alkali treated corn stover to the range of its optimum level for AD (7.2). The steady state was defined to be the point when biogas production rates varied within 10% of their average values between feeding time in one HRT period(Luo et al., 2015). The CS substrate samples were periodically collected from reactors at feeding phase which was used for chemical composition analysis. All tests were performed in triplicate. 2.4 Measurement of biochemical methane potential Biochemical methane potential (BMP) assay was immediately conducted after collecting the effluents from each reactor. The aim of BMP assay was to evaluate the amount of available organic matter remained after AD from every reactor (R35, R38, R41 and R44) irrespective of its 4
temperature differences to analyze the BMP at 35°C uniformly. The specific characteristics of effluent from each reactor are presented in Table 2. BMP assays were carried out using 500 mL reactors with the working volume of 400mL. The amount of inoculum was maintained constant at 10 g TS· L-1 in all reactors where the substrate to inoculum ratio (SIR) was 0.5g TS substrate/g TS inoculum. The BMP tests were conducted using an Automatic Methane Potential System II (Bioprocess Control, Sweden) at 35°C. All tests were performed in triplicate. 2.5 Analysis of the microbial community The microbial communities in each anaerobic digester treating CS at different temperatures were investigated, and the samples were collected from reactors at feeding phase. During this process the functional roles of specific microbial populations were evaluated in relation with methane production in each stages of the AD. 2.5.1 DNA extraction and PCR amplification The sample for DNA extraction was prepared and analyzed based on the method adapted from the manufacturer protocol of FastDNA Spin Kit (MP Biomedicals, U.S.A). The sample (slurry) for DNA analysis was collected when the anaerobic reactors exhibit stable conditions and performance; for example, the difference in the production of daily biogas yield was not more than 5% after feeding time up to the next feeding and continues in the same condition. The V3-V4 region of the bacterial 16S ribosomal RNA gene were amplified by PCR (95°C for 3 min, followed by 27 cycles at 95°C for 30s, 55°C for 30s, and 72°C for 45s and a final extension at 72°C for 10min) using primers 338F (5’- ACTCCTACGGGAGGCAGCAG-3’) and 806R (5’GGACTACHVGGGTWTCTAAT-3’). In the same way the archaeal 16S ribosomal RNA gene were amplified by PCR（95°C for 3min, followed by 33 cycles at 95°C for 30s, 55°C for 30s, and 72°C for 45s and a final extension at 72°C for 10min）using primers 524F_10_ext (5’TGYCAGCCGCCGCGGTAA)-3’) and Arch 958R (5’- YCCGGCGTTGAVTCCAATT-3’). The PCR reactions were performed in triplicate using 20µL mixture which contained 4µL of 5 × FastPfu Buffer, 2µL of 2.5mM dNTPs, 0.8µL of Forward Primer (5µM), 0.8µL of Reverse Primer (5µM), 0.4µL of FastPfu Polymerase, 0.2µL of BSA and 10 ng of template DNA, then add ddH2O 5
to 20µL. 2.5.2 Illumina high-throughput 16S rRNA gene sequencing Amplicons were extracted from 2% agarose gels and purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, U.S.) according to the manufacturer’s instructions and quantified using QuantiFluor™ -ST (Promega, U.S.). The purified amplicons were pooled in equimolar and paired-end sequenced (2 × 250) on an Illumina MiSeq platform according to the standard protocols. The raw reads were deposited into the NCBI Sequence Read Archive (SRA) database. 2.6 Analytical methods and data analysis 2.6.1 Biogas analysis The H2, N2, CH4 and CO2 content of biogas were detected using gas chromatograph (SP2100, Beifen, China) with a TDX-01 column, a thermal conductivity detector (TCD) and a calibration curve made of known standard gases (H2 9.99%, N2 5.02%, CH4 49.98%, CO2 35.01%). The operational temperatures at the injection port, column oven, and detector were 150°C, 140°C, and 150°C, respectively. Argon was used as the carrier gas. The amount of daily biogas production was recorded by water displacement method. 2.6.2 Chemical composition analysis The total solid (TS), volatile solid (VS) were determined by the APHA standard methods (Walter, 1998). The pH value was measured using pH meter (CHN868, Thermo Orion, America). TC was analyzed by an elemental analyzer (Vario EL/micro cube elemental analyzer, Germany). TN was determined using the total Kjeldahl nitrogen analyzer (Model KDN-2C, Shanghai). The NH3-N was analyzed by a Kjeldahl analyzer (KT-260, Foss, Suzhou, China). Alkalinity was measured by pH titration method using 0.1M HCl and expressed in g equivalent CaCO3· L-1. The contents of lignin, cellulose, and hemicellulose were determined by fiber analyzer (ANKOM A2000i, ANKOM, USA) according to the procedures proposed by Van Soest et al (1991). 6
The samples for VFAs and ethanol analysis were first centrifuged at 10,000 rpm for 5min, the supernatants were then filtered through a 0.22µm filter, and filtrates were collected in sample vials for analysis. The VFAs yields were calculated as the cumulative sum of the measured acetic (HAc), propionic (HPr), n-butyric (n-HBu), iso-butyric (iso-HBu), n-valeric (n-HVa) and iso-valeric (iso-HVa) acids. The content of each VFA was determined using the gas chromatograph (GC2014, 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 components were based on the standard calibration curve according to manufacturer protocol. 3 Results and discussion 3.1 CSTR experiments 3.1.1 Biogas yield and methane content The process performance of laboratory-scale CSTRs fed with NaOH pretreated CS was analyzed, and the four reactors were operated under identical conditions, except different temperature (35°C, 38°C, 41°C and 44°C). Therefore, the operational parameters of biogas performance were monitored for different temperature conditions during 160 days of digestion period (Fig.1(a, b)). Daily biogas production experienced three-four peaks during starting-up phase (1-40d). At the end of starting-up phase, the total biogas production reached 445.2 L and 451.3 L for R38 and R44, followed by 291.2 L, and 273.0 L for R35 and R41, respectively. Then the daily biogas and methane production tended to be steady from day 41 to 160. Comparatively, R44 resulted the best daily biogas and methane production performance, which were averagely 6.5±0.5 L and 3.4±0.3 L, respectively. The process performances were similar in the R35, R38 and R41, and the average daily biogas and methane production was 4.6-5.6 L and 2.4-2.9 L. As shown in Fig.1(c, d), the average methane and carbon dioxide content of four reactors were almost similar, which were 51.60±0.44 % and 45.45±0.87 %, respectively. When compared with previous studies, which found CH4 content in the biogas during the feeding phase of AD of swine manure was higher at 50 and 55°C (around 60%) than 25 and 35°C (Lin et al., 2016b). In the same way, CH4 content in the biogas increased with temperature from 25°C to 45°C, and was 7
stable at higher temperatures around 60% CH4 content during the feeding phase (Lin et al., 2016a). This indicates that, the methane content of the biogas was mainly affected by the type of substrate, rather than temperature conditions. Table 3 shows that the increment of process efficiency from R35 to R44. The daily methane production based on reactor volume reached 300, 360, 310, 420 mL· L-1·d-1 at 35, 38, 41 and 44°C, respectively. The daily biogas and methane production (based on VS) obtained from R44 were 598 mL· L-1·d-1 and 308 mL· L-1·d-1, respectively, which were 16.6%-42.4% and 16.2%-40.6% higher than yields from R35, R38 and R41, respectively. R44 showed relatively better efficiency in the biogas production performance, indicating a higher capacity of methanogens (in R44) compared to methanogens in R35, R38 and R41. Lin et al found similar results and reported that biogas production is different at specific temperatures from 25°C to 50°C (Lin et al., 2016a).The results stated that temperature affects biogas production, optimal temperature for different substrates could be different and needs to be determined by specific study. 3.1.2 Main component conversions Cellulose, hemicellulose and lignin are the main components of CS, accounting for 74.9% of the total dry matter and providing the main carbon sources for anaerobic microorganisms. However, biogas production is highly affected by the availability and digestibility of cellulose, hemicellulose, and the association of lignin with the carbohydrates. In principle, the production of more biogas is related to the conversion of more substrate resulting the reduction of VS. In this study, cellulose and hemicellulose bioconversion rates were analyzed to investigate the trend of bioconversion. Fig.2 (a, b, c) shows the changes in chemical compositions of the four experimental groups within the feeding time interval of 40 d to160 d. Bioconversion rates of cellulose and hemicellulose varied in all four experimental groups. More specifically, the hemicellulose, cellulose, and lignocellulose bioconversion rates of CS in R44 were 63.4%、62.4% and 61.1%, respectively. The bioconversion rates of hemicellulose for R35、R38 and R41 were 42.8%、47.4% and 55.2%, respectively. The total cellulose bioconversion rates were close to each other in R35 and R41, which were 45.0% and 48.9%, respectively. The conversion rates of total lignocellulose were not statistically significant, which were 45.6% and 49.0% for R35 and R41, respectively, while 55.10% for R38. 8
Changing temperature is a simple and effective method to improve the biodegradability of lignocellulosic material. Optimal increment in temperature can facilitate the hydrolysis of cellulose and hemicellulose into relatively biodegradable components, and break the link between polysaccharide and lignin to make cellulose and hemicellulose more accessible to bacteria. This result further verified that the ability of temperature to improve biodegradability and enhance bioenergy production. Fig.3 (a, b) shows the changes in TS and VS removal rates for the four experimental groups during entire feeding time (40d-160d). TS and VS removal rates represents conversion of CS by anaerobic microorganisms. TS and VS removal rate for the four experimental groups were stable during the feeding phase which showed that there is no obvious fluctuation. However, in feeding phase, TS and VS removal rates of R44 were significantly higher than that of other experimental groups. The average TS and VS removal rate of R44 was 55.1% and 64.2%, respectively. Compared with the experimental groups of R35, R38 and R41, the TS and VS removal rate of R44 increased by 18.3%-30.8% and14.6% to 25.4%, respectively. 3.1.3 System stability When CS used as a sole substrate, AD system has more a probability to lose stability due to possible low buffering capacity. The stability of digestion system depends on a number of factors like pH, volatile fatty acids (VFAs), ammonia nitrogen (AN) and alkalinity. In this study, these parameters were measured to evaluate the reactor stability of NaOH pretreated CS samples in each temperature AD process. The pH values were 7.10-7.22 until the feeding phase for four reactors under different temperatures (Fig.4(a)), which is believed to be optimal for a biogas production process (De et al., 2012). For the digestion period of day 41 to 160, the concentrations of VFAs are shown in Fig.4(b). From R35 to R44, the concentrations of VFAs reached to 109-160 mg· L-1 in the feeding phase. Nevertheless, four reactors maintained low residual VFAs concentration under the different temperature conditions. This shows that the temperature difference in mesophilic condition did not affect the VFAs production, because the VFA production rate by fermentative bacteria and the subsequent production of acetate by acetogenic bacteria were well balanced with the individual VFA consumption rate(Marchaim & Krause, 1993). The concentrations of NH4+–N in four reactors remained in the range of 338-477 mg· L-1 at 9
the feeding phase (Fig.4(c)). Ammonia nitrogen from R44 was 477 mg· L-1, which was higher than the other reactors. The high ammonia nitrogen level at 44°C temperature implies that the protein fraction of CS was better hydrolyzed and fermented in subsequent steps. However, the existence of free ammonia in the reactors did not reach an inhibitory level. The alkalinity concentrations in all reactors were in between 3645-4402 mg CaCO3· L-1 (Fig. 4(d)), which was in the range of favorable conditions for anaerobic microbes. The alkalinity level of the higher temperature reactors was slightly more than that of the lower temperature reactors. 3.2 Evaluation of BMP assays The retention time of BMP analysis depended on the rate of methane production. This could be explained as the experiment stopped when the rate of methane production was undetectable or less than 1% of the total amount. The results of the cumulative methane production from BMP assays are shown in Fig.5. The total duration of the digestion time for effluents varied from 12-35 days. R35 group needed the more digestion time. However, R38, R41 and R44 have finished less than 20 days of AD. It showed that the effluent of R44 can be degraded quickly within short time. As shown in Table 4, the highest cumulative methane production (118 mL) was from the effluent of R35, and the effluent of R44 produced lower cumulative methane yield (25 mL). The methane yields from the three effluent samples (R38, R41 and R44) were lower than that of the effluent from R35, indicating more organic matter was used at higher temperatures. 3.3 Changes in the microbial community structure 3.3.1 Alpha diversity indices of bacterial and archaeal 16S rRNA gene sequences The possible correlations between the function of each microbial group and their performances in different temperature digesters were investigated. Enrichment of certain active microorganisms at specific temperature ranges shows that the sensitivity of anaerobic process within temperature differences which directly affects methane production process (Lin et al., 2016b). Therefore, a comparison of the microbial richness and diversity in the different reactors and statistical analysis of bacterial and archaeal community in each effluent were shown in Table 5. As it can be seen from Table 5, the coverage index was greater than or equal to 99.8% for all samples, this value confirms representativeness. The diversity of bacteria and archaea community were supported by OTUs number. For the 4 samples obtained, the total 16S rRNA gene 10
sequencing gave the range from 382-489 and 18-30 for Bacterial and Archaeal OTUs, respectively which were clearly higher in the R35, R38, and R41 than in the R44 based on chimeras and singletons. Based on the Ace and Chao 1 values (Table 5), bacterial and archaeal richness of each sample was higher in R35, R38 and R41 than in R44. The alpha diversity indexes such as the Shannon and the Simpson index which focuses on the evenness of microbial diversity were calculated for each sample. Based on the results, bacterial shannon index of each sample in the R38 (4.26) and R44 (4.24) were lower than the R35 (4.60) and R41 (4.52), bacterial simpson index of each sample in the R38 (0.0546) and R44 (0.0531) were higher than the R35 (0.0254) and R41 (0.0311). On the other hand, archaea shannon index of each sample in the R35 (1.62) and R41 (1.58) were higher in the R38 (1.85) and R44 (1.87), archaea simpson index of each sample in the R35 (0.2865) and R41 (0.3163) were higher in the R38 (0.2683) and R44 (0.2682). The results indicated that R44 had the lower richness, and higher the bacterial diversity and lower archaea diversity. Various studies also reported that microbial community descriptors such as diversity and evenness indices are directly relating to anaerobic digester functions (Carballa et al., 2011; Fernandez et al., 2000). 3.3.2 The distributions of bacterial sequences In four reactors the dynamic profiles of bacterial phyla varied significantly during the feeding phase (Fig. 6(a)). Bacteroidetes and Firmicutes were the dominant phyla in four reactors. Although the major phyla coexisted in the two communities, their respective abundances were very different. The abundances of Bacteroidetes in R35, R38 and R41 were in the range from 30.70% -39.36%, however, it abundance was low in R44 (16.00%). More specifically, the abundance of Firmicutes in R35 was 32.30%, which was less than the abundance level in R41 (46.67%). As a result, Firmicutes were the most predominant phylum in R44 with maximum proportion of 66.58%. Meanwhile, a number of other phyla presented in each reactor might play important roles, although they had low percentage (>1%), such as proteobacteria, spirochaetae cloacimonetes,
candidate_division_WS6,
tenericutes,
synergistetes,
acteria_unclassified,
acidobacteria, lentisphaerae and so on. Phylum Bacteroidetes and Firmicutes contain hydrolytic bacteria as well as acidogenic and fermentative bacteria which have different functions in anaerobic digestion process(Ariunbaatar et al., 2014). Bacteroidetes are reported as an important member of heterotrophs that involve in 11
organic carbon cycling and proteinaceous substances (Kokkwang et al., 2016; Shi et al., 2015). Moreover, the studies cited that the hydrolysis of biomasses was positively correlated with the percentage of Bacteroidetes (Regueiro et al., 2012). Phylum Firmicutes have special features to tolerate unfavourable environments and can produce methanogenic precursors(Kokkwang et al., 2016). The huge dominance of Firmicutes in both lab-scale and full-scale thermophilic anaerobic digesters has been reported in various literatures (Lee et al., 2016; Pap et al., 2015; Tian et al., 2015). In this study, for the reactors from R35 to R44, Firmicutes’s relative abundance got higher. The ratio of Firmicutes to Bacteroidetes (RFB) in R35, R38 and R41 was 1.05, 0.96 and 1.33, respectively; but the RFB in the R44 was 4.16. (Briones et al., 2014) reported that the RFB could be affected by the types and compositions of substrates fed to the AD systems. In this study, the raw material used in all reactors was CS, so these variations in RFB were due to the temperature differences in the reactors. This result indicated that temperature will affect the microbial community diversity. The findings from various previous metagenomics studies of anaerobes have suggested the correlations between process variables (i.e., environmental variables) and bacteria at the phylum level (Liu et al., 2015; Pap et al., 2015). The genus level in four samples was observed; the result showed that the dynamic profiles of bacterial genus differed significantly in four Reactors (Fig.6(b)). 80.44% of the total bacterial reads were classified into 39 genera, out of these 23 bacterial genera showed relative abundance > 1.0% in all samples which were considered high-rank groups. Among these 23 genera, vadinBC27_wastewater-sludge_group (15.37 ± 11.98%), OPB54_norank (9.14 ± 11.38%), Sedimentibacter (4.70 ±0.03%), Ruminiclostridium (4.68 ± 2.44%), Ruminiclostridium_1 (4.60 ± 1.55%), Bacteroidales_UCG-001_norank (4.34 ± 4.13%), W27_norank (3.70 ±2.52%), Gelria (2.73 ± 5.21%), Bacteroides (2.25 ± 0.94%) and Candidate_division_WS6_norank (2.19 ± 2.64%) were dominant. The genus Subgroup_6_norank (1%) appeared at only 44°C temperature. Therefore, the genus vadinBC27_wastewater-sludge_group was the most abundant bacterial group in the R35, R38 and R41, where its specific abundance was 14.36%, 29.79% and 16.85%, respectively, and only 0.52% in R44. The genus vadinBC27 was first found in vinasses anaerobic digester, where some species in Methanosarcina, Methanobacterium and Thermoplasma also co-existed (Godon et al., 1997). Genus OPB54_norank showed a reverse pattern, as its proportion was the most abundant (25.70%) in the R44 but 0.36%, 3.21%,7.28% in the R35, R38, R41. These 12
results demonstrated that bacterial community shifts occurred in relation to temperature differences, especially the OPB54 bacteria which were previously found in engineered anaerobic systems(Li et al., 2009). The genus Gelria in R44 was the predominant, which accounted for 10.32%. Previous research also supports the significant contribution of Gelria to produce H2, which may then be utilized by HMs in a thermophilic AD system to degrade cellulose and microbial protein(Lü et al., 2014). Thus, Gelria sp. maybe an indicator of process performance in thermophilic AD systems. AT high temperature reactor, the relative abundance of OPB54 and Gelria which belong to the phylum Firmicutes, class Clostridia, order Thermoanaerobacterales, family Thermoanaerobacteraceae get higher. Bacteroides which was reported to be able to degrade cellulose and carbohydrate to cellobiose, glucose, and mannose then to acetate or succinate (Song et al., 2004; Wilson et al., 2008). 3.3.3 The distributions of archaeal sequences The distributions of archaeal sequences at the phylum level from each sample are shown in Fig.6(c). Miscellaneous_Crenarchaeotic_Group and Euryarchaeota were also the most dominant group among the archaeal phylums with an average relative abundance of 54.63 ± 6.47% and 44.43 ± 6.73%, respectively across all digesters. (Lliros et al., 2014) indicated that Miscellaneous_Crenarchaeotic_Group was one of the major archaeal groups in natural wetland ecosystem, and many Archaea are believed to be responsible for many biochemical reactions in the methanogenic phase (Watson-Craik, 1993). The dynamic profiles of the archaeal community at the genus level were significantly different in all reactors (Fig.6(d)). As it can be seen in Fig.6(d), archaeal communities demonstrated a clear dominance of the genus Miscellaneous_ Crenarchaeotic_Group_norank (MCG), which represented 44.95%-58.79% of sequences identified in the all reactors. The genus WCHA1-57_norank was the second abundant genus which contributed 39.45% of the archaeal population in R35, and only 10.93%, 4.39% and 6.32% for R38, R41 and R44, respectively. The abundance of genus Methanosaeta which was not appeared in R44 was dominant in R41; however, the abundance of genus Methanosarcina was low, only 1.70%. The abundance of genus Methanoculleus and Methanomassiliicoccus in R44 were 10.87% and 15.86%, but there were only 2.64%-3.91% and 0.26%-1.29% in R35, R38 and R41. This shows that after adaption to the environment and substrates produced by fermentative microorganisms, the metabolic activity 13
and/or growth rate of Methanoculleus and Methanomassiliicoccus were gradually enhanced. In AD systems, Methanosaeta are known to use acetate as the substrate for methanogenesis, whereas Methanoculleus use CO2 reduction pathway with either H2/CO2, or formateas substrate(Boone et al., 1993). Based on the observed decrease of acetoclastic Methanosaeta and the increase of the hydrogenotrophic Methanoculleus, the importance of hydrogenotrophic methanogenesis increases when temperature increases from 35°C to 44°C, this result in line with the report from (Pap et al., 2015). These observations suggested that when specific microorganisms are suppressed by increasing temperature, their functions might be replaced by other microorganisms with similar roles without major reduction in overall process performance during AD process. Differences in microbial community shifts were considered as an indicator that different microbes may be involved in biogas production. The most important novelty of the data presented in this study is the direct experimental evidence regarding the influence of temperature on the population levels of methanogenic anaerobic microorganisms in the digester. Furthermore, the fact that temperature had similar effects on bacterial and archaeal community structures implies that perturbing temperature could cause critical changes in syntrophic consortia (of bacteria and archaea) that perform methanogenesis. 4. Conclusions CSTR analysis revealed that daily biogas and methane production increased at 44°C. BMP assays at 35 °C showed that the effluent of R44 produced low methane yield, which confirmed more organic matter degraded at 44°C to produce maximum biogas. The most abundant bacterial phylum in four reactors were Firmicutes and Bacteroidetes, but the bacterial community structure was significantly different. Firmicutes dominated in R44, while Bacteroidetes was the dominant phylum in R35. The archaea genus in the four reactors was Miscellaneous_Crenarchaeotic_Group_norank. However, R44 have higher the amount of Methanoculleus and Methanomassiliicoccus while hydrogenotrophic methanogenesis seemed to be the dominant pathway. Acknowledgments: The authors are grateful to the fund supports from National "Twelfth Five-Year" Plan for 14
Science & Technology Support (2014BAC24B01-02), and National "Twelfth Five-Year" Plan for Science & Technology Support(2015BAD21B03).
15
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(31) Song, Y.C., Kwon, S.J., Woo, J.H. 2004. Mesophilic and thermophilic temperature co-phase anaerobic digestion compared with single-stage mesophilic- and thermophilic digestion of sewage sludge. Water Research, 38(7), 1653-62. (32) Tian, Z., Zhang, Y., Li, Y., Chi, Y., Yang, M. 2015. Rapid establishment of thermophilic anaerobic microbial community during the one-step startup of thermophilic anaerobic digestion from a mesophilic digester. Water Research, 69, 9-19. (33) Van Soest, P.J., Robertson, J.B., Lewis, B.A., 1991. Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J. Dairy Sci. 74 (10), 3583–3597. (34) Walter, W.G. 1998. APHA Standard Methods for the Examination of Water and Wastewater. Freshwater Science, 56(3), 387. (35) Watson-Craik, I. 1993. Methanogenesis: Ecology, Physiology, Biochemistry & Genetics. Biochemical Systematics & Ecology, 23(3), 341-341. (36) Wilson, C.A., Murthy, S.M., Fang, Y., Novak, J.T. 2008. The effect of temperature on the performance and stability of thermophilic anaerobic digestion. Water Science & Technology A Journal of the International Association on Water Pollution Research, 57(2), 297. (37) Xiang-Kun, L., Kai-Li, M., Ling-Wei, M., Jie, Z., Ke, W. 2014. Performance and microbial community profiles in an anaerobic reactor treating with simulated PTA wastewater: from mesophilic to thermophilic temperature. Water Research, 61(18), 57-66. (38) Zamanzadeh, M., Hagen, L.H., Svensson, K., Linjordet, R., Horn, S.J. 2016. Anaerobic digestion of food waste - effect of recirculation and temperature on performance and microbiology. Water Research, 96, 246. (39) Zheng, M., Li, X., Li, L., Yang, X., He, Y. 2009. Enhancing anaerobic biogasification of corn stover through wet state NaOH pretreatment. Bioresource Technology, 100(21), 5140.
18
Feeding phase
Starting-up phase
40
10.0
R35
35
R38
R41
R44 7.5
25 20
5.0
15 10
2.5
（ a）
5
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
Digestion time (d)
Feeding phase
Starting-up phase
100
R35
90
R38
R41
R44
Methane content (%)
80 70 60 50 40 30 20
（ b）
10 0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
Digestion time (d) Feeding phase
Starting-up phase
100
R35
90
R38
R41
R44
Carbon dioxide content (%)
80 70 60 50 40 30 20
（ c）
10 0
10
20
30
40
50
60
70
80
90
Digestion time (d)
100
110
120
130
140
150
160
Daily biogas production (L)
Daily biogas production (L)
30
Feeding phase
Starting-up phase
20
5
R38
R41
R44 4
15
3 10 2
5 1
（ d）
0
10
20
30
40
50
60
70
80
90
100
110
120
130
140
150
160
Digestion time (d)
Fig.1 The performance of four reactors at the OLR of 90 gTS·L-1 for (a) Daily biogas production (L), (b) Methane content (%), (c) Carbon dioxide content (%) and (d) Daily methane production (L)
Daily methane production (L)
Daily methane production (L)
R35
20
R35
18
R38
R41
（ a）
R44
Hemi-celluose contents (%)
16 14 12 10 8 6 4 2 0 40
60
80
100
120
140
160
Time (d) 25
R35
R38
R41
R44 （ b）
Cellulose contents (%)
20
15
10
5
0 40
60
80
100
120
140
160
Time (d) 45
Lignocellulose contents (%)
40 35 30 25 20 15
R35
R38
R41
R44
10
（ c）
5 0 40
50
60
70
80
90
100 110 120 130 140 150 160
Time (d)
Fig.2 The changes of chemical compositions for four reactors at the OLR of 90 gTS·L-1.The error bars show the standard deviations (n=3).
60
R35
R38
R41
R44
TS removal rates (%)
55
50
45
（ a） 40 40
60
80
100
120
140
160
Time (d) 70
R35
R38
R41
R44
VS removal rates (%)
60
50
40
（ b） 30 40
60
80
100
120
140
160
Time (d)
Fig.3 TS and VS removal rate of four reactors at the OLR of 90 gTS·L-1. The error bars show the standard deviations (n=3).
7.6
240
R35
7.4
R38
R41
R44
7.2
7.0
6.8
6.6
R41
R44
120
80
40
（ a）
6.4 40
50
60
70
80
90
0 40
100 110 120 130 140 150 160
（ b） 50
60
70
80
90
100 110 120 130 140 150 160
Digestion time (d)
Digestion time (d) 800
7000
R35
700
R38
R41
R44
600
R35
6000
R38
Alkalinity (mg CaCO3L-1)
Ammonia nitrogen (mgL-1)
R38
160
VFAs (mgL)
pH
R35
200
R41
R44
5000
500
4000
400
3000
300
2000
200
（ c）
100 0 40
50
60
70
80
90
100 110 120 130 140 150 160
（ d）
1000 0 40
50
60
70
80
Digestion time (d)
90
100 110 120 130 140 150 160
Digestion time (d)
Fig.4 pH, VFA, ammonia nitrogen, and alkalinity of different reactors in CSTR experiments. The error
bars show the standard deviations (n=3).
130 120 110
Methane volume (mL)
100 90
R35 R38 R41 R44
80 70 60 50 40 30 20 10 0 0
5
10
15
20
25
30
35
40
Digestion time (d)
Fig.5 The BMP assays of the effluent from R35, R38, R41 and R44
Fig.6 Bacterial and archaeal sequence distributions at phylum (a, c) and genus(b, d) level
Table 1. Characteristics of CS and inoculum used in this study Indexes (Dry matter)
CS
Inoculum
Total Solid (TS, %)
93.21±0.05
10.38±0.04
Volatile Solid (VS, %)
86.38±0.13
5.70±0.12
VS/TS
0.927±0.003
0.549±0.013
Total Carbon（C, %）
43.55±0.23
29.20±0.32
Total Nitrogen（N, %）
0.92±0.06
2.79±0.12
C/N
47.50±4.81
10.49±0.80
Table 2. The characteristics of effluents for different reactors Effluents Indexes R35
R38
R41
R44
Total Solid (%)
4.61±0.06
4.30±0.07
4.16±0.04
4.08±0.04
Volatile Solid (%)
3.36±0.06
3.06±0.09
2.89±0.03
2.83±0.08
Ammonia Nitrogen (mg·L-1)
338±23
375±17
441±18
477±15
Alkalinity (mg CaCO3·L-1)
3645±356
3862±335
4134±400
4402±352
VFAs (mg·L-1)
109±5
123±6
144±9
160±9
Table 3. Daily biogas/methane production (DBP/DMP) per unit feeding VS and per reactor volume DBP-VS Groups
DMP-VS
mL·g-1 VS·d-1
DBP-V
DMP-V
mL·L-1·d-1
R35
420±22
219±11
570±30
300±16
R38
513±8
265±4
700±11
360±6
R41
440±19
225±10
600±26
310±13
R44
598±17
308±9
810±23
420±12
Table 4. Methane yields form BMP assays Effluent
Parameter Cumulative Methane(mL) -1
Methane Yield (mL·g VS)
R35
R38
R41
R44
118±6
56±4
49±4
25±1
41±2
19±1
18±1
11±0.5
Table 5. Alpha diversity indices of the bacterial and archaeal 16S rRNA gene sequences Groups
Samples
Coverage (%)
OTU
Ace
Chao 1
Shannon
Simpson
R35
99.9
460
471
471
4.60
0.0254
R38
99.8
482
511
515
4.26
0.0546
R41
99.9
489
506
515
4.52
0.0311
R44
99.9
382
397
406
4.24
0.0531
R35
1
30
30
30
1.62
0.2865
R38
1
28
28
28
1.85
0.2683
R41
1
24
34
26
1.58
0.3163
R44
1
18
20
19
1.87
0.2682
Bacterial
Archaea
Highlights A mesophilic temperature (44°C) can enhance conversion rate of corn stover to CH4. Biomethane potential assays confirmed that more organic matter degraded in R44. Biogas production rate was highest at 44°C among mesophilic temperatures studied. The abundance of bacterial and archaeal community was varied with temperature.
19