Effects of microbial inoculum optimization on biomethane production from paper mill solid residues
Marília Bixilia-Sanchez, Welington Luiz Araújo
TL;DR
This study shows that optimizing microbial inoculum and adding nutrients can greatly increase biomethane production from paper mill waste.
Contribution
The study demonstrates that acclimatized inoculum and chicken manure supplementation significantly enhance biomethane yield from cellulose residues.
Findings
Bioreactors with chicken manure and acclimatized inoculum produced up to four times more biomethane.
Methanosarcina and Methanobacterium became dominant archaeal genera in supplemented bioreactors.
Supplemented bioreactors showed increased abundance of specific bacterial and fungal genera.
Abstract
The conversion of residual biomass can significantly enhance renewable energy production and reduce greenhouse gas emissions. According to the Brazilian Tree Industry (IBÁ), Brazil produced approximately 23.5 million tons of cellulose and 11 million tons of paper, generating about 0.4 tons of residues for every ton of cellulose produced. This study utilizes a laboratory-scale batch anaerobic reactor to evaluate the effects of microbial inoculum acclimatization and nutritional supplementation on the conversion of cellulose residues into biomethane. Bioreactors that were supplemented with chicken manure and acclimatized inoculum (Batch 04) produced up to four times more biomethane compared to those without supplementation and those using non-acclimatized inoculum. Molybdenum supplementation had no effect on gas production. In Batch 04, the archaeal genera Methanobrevibacter and…
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Figure 5- —Universidade De São Paulo
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TopicsAnaerobic Digestion and Biogas Production · Landfill Environmental Impact Studies · Biofuel production and bioconversion
Introduction
The microbiological conversion of residual biomass may make a significant contribution to a sustainable and flexible program for production of renewable energy. According to the Brazilian Tree Industry [1], Brazil produced approximately 23.5 and 11 million tons of cellulose and paper, respectively, especially exporting short fiber cellulose. In this perspective, considering that 0,4 tons of residues are generated per 1 tons of produced cellulose the quantity of residues that are disposable in landfills increases soil pollution. Although several studies have investigated potential disposal methods for this waste, such as incineration, land application, incorporation into cement, polymer composites, and ceramic products, one of the most used options is landfill disposal [2, 3]. However, these organic wastes can be converted into energy, such as bioethanol and biomethane [4, 5], reducing the environmental impact and contributing to a more sustainable paper production, achieving sustainable development goals. Harnessing innovative solutions to manage waste using anaerobic digestion (AD) could expand biofuel production and cut down our dependence on fossil fuels for energy.
A potentially valuable solution for sustainable energy production is the conversion of primary sludge into methane [6]. Some advantages of using primary sludge from paper production for this process include low cost and a significant amount of cellulose readily available for conversion. Through a cascading series of steps, including hydrolysis, acidogenesis, acetogenesis, and methanogenesis, a consortium of bacteria and archaea converts organic matter into biogas (50–80% methane) [5], reducing the organic load of the waste and its polluting potential. Numerous laboratory-scale studies have shown that, contrary to common perception, most different effluents from paper and pulp mills are also, to some extent, treatable anaerobically. Even for hard-to-digest effluents, COD removal rates vary between 15 and 90%, depending on the extent of dilution prior to anaerobic treatment and the experimental environment applied. Co-digestion, containing diverse substrates, can balance and reduce toxicity and may lead to a more robust microbial community, which must be adapted to the substrate to buffer the capacity of AD system [7]. Moreover, the microbial community has the capability to acclimate to adverse conditions. Recent study has addressed that the higher energy recovers from lignocellulosic residues depend on the acclimatized inoculum [7]. In addition, the anaerobic treatment of wastewater containing high levels of inhibitors or toxins should begin with an acclimation/adaptation period that can last from a few weeks to several months [6] and therefore, the AD performance is influenced by the structure of the microbial community [8].
The potential for methane production from waste depends on the concentration of the three main organic components: proteins, lipids, and carbohydrates, and substrate characterization is necessary to predict methane production. Although there is an appropriate methodology to determine methane production potential, most approaches used thus far rely on experimental studies concerning the behavior of different feedstocks with varying properties of raw waste [1]. Co-digestion of organic materials can generally improve the balance of various factors in the mixture, including macro and micronutrients, C:N ratio, pH, inhibitors, toxic compounds, biodegradable organic matter, and total solids [1], which affect the establishment of the microbial community structure and function and in turn the biogas and biomethane yield in anaerobic digestion system [2].
The rationale for conducting this study was to establish, in vitro, the synergy between microbial community adaptation, nutritional supplementation, and biomethane production to improve the utilization of cellulose-rich residues from the paper and cellulose industry. To achieve this goal, the following objectives were accomplished: I) Development of an efficient microbial consortium for generating biogas rich in CH₄; II) Assessment of microbial community diversity and richness (including bacteria and fungi) during the development of an effective batch anaerobic digestion system; III) Establishment of physical, chemical, and microbiological parameters as indicators of process efficiency; IV) Formulation of a pilot-scale strategy for biogas production. The hypothesis underlying this study posits that nutritional supplementation, combined with community adaptation, can provide valuable insights for establishing a pilot-scale process for biogas production with high methane content.
Materials and methods
Substrate and primary inoculum experiments
The waste used in this study, referred to as Dewatered Primary Sludge (DPS), was provided by Suzano Company and consists of degraded cellulose (40–60%), calcium carbonate (40–60%), and kaolin (1–2%). After being deposited in the company’s wastewater treatment plant (WWTP), the sludge was drained until it reached a total solids content of 30–50%. The inoculum for this study was harvested from the anaerobic digester at the Mogi das Cruzes WWTP in São Paulo, Brazil, under mesophilic conditions (33 °C). To evaluate the effectiveness of the conventional inoculum on the methane potential of cellulose residues, 10-day batch studies were conducted in 300 mL reactors made from borosilicate flasks. The experiment included six treatments that utilized varying inoculum concentrations and sugarcane vinasse supplementation (see Table 1).Table 1. Composition of the reactors for conventional inoculum evaluationTreatments DPS (g)Vinasse (mL)Inoculum (mL)TS (%)IETR155.71-40 (13.33%)6.5IETR247.14-80 (26.66%)5.5IETR345.005040 (13.33%)5.3IETR442.86-100 (33.33%)5.0IETR536.435080 (26.66%)4.3IETR632.1450100 (33.33%)3.7^^ The volume was 300 mL with water. Legend: DPS: Dewatered Primary Sludge; TS: Total Solids of the inoculum
Since inoculum from the wastewater treatment plant (WWTP) was unable to produce significant cumulative biomethane, it was necessary to adapt the microbial community to the dewatered primary sludge (DPS). For this acclimatization, a mixture was prepared with 10% v/v WWTP sludge, 20% w/v DPS, 20 g of peptone, 0.371 mM nickel (Ni), and 0.454 mM cobalt (Co) in a final volume of 1 L. This mixture was incubated anaerobically at 28 °C for 15 days. After this incubation period, 200 mL of the adapted microbial community was added back to a fresh mixture of DPS, peptone, Ni, and Co at the same concentrations and incubated under the same conditions. This process was repeated once more, totaling three cycles, before using the adapted microbial community for biogas production.
Batch anaerobic digestion
The objective of this study was to evaluate the impact of inoculum and nutritional supplementation on the methane potential of cellulose residues. For this, three batches of Anaerobic Digestion (AD) were conducted in borosilicate flasks, sealed with silicone stoppers and equipped with hoses to prevent gas leakage or exchange with the external environment. This setup, termed the Apparatus II system (Mariotte Flask), was based on the methodology described by Aquino et al. [9]. The composition of each anaerobic digestion batch is detailed in Table 2.Table 2. Composition and experimental design for laboratory scale evaluation of the inoculum and nutritional supplementation for biogas productionTreatmentsComponentsDPS (kg)Vinasse (L)Peptone (Kg)CM (kg)DI (%)Ni (mM)Co (mM)Mo (mM)Volume (L)B01TR10.34-------1.7B01TR20.34-0.1--0.2180.267-1.7B01TR30.32---6.0---1.7B01TR40.32-0.1-6.00.2180.267-1.7B01TR50.30---12.0---1.7B01TR60.30-0.1-12.00.2180.267-1.7B02TR10.30---10.0---1.9B02TR20.240.6--10.0---1.9B02TR30.240.60.1-5.0---1.9B03TR10.19----0.7420.908-1.0B03TR20.19--0.05-0.7420.908-1.0B03TR30.19--0.05-0.7420.9080.2191.0B03TR40.17---10.00.7420.908-1.0B03TR50.17--0.0510.00.7420.908-1.0B03TR60.17--0.0510.00.7420.9080.2191.0B03TR70.15---20.00.7420.908-1.0B03TR80.15--0.0520.00.7420.908-1.0B03TR90.15--0.0520.00.7420.9080.2191.0DPS: Dewatered Primary Sludge; Peptone: contains 20% total N; CM: Chicken Manure; DI: Inoculum; Nickel: (Ni(NO3)2.6H2O); Cobalt: (CoCl2.6H2O); Molybdenum: (Na2MoO4)
In these experiments, the Developed Inoculum (ID) was used in conjunction with the substrate (DPS) to assess biogas production. Batch 01 (B01) focused on evaluating the effect of microbial load. Treatments were implemented using inoculum concentrations of 6% (B01TR3 and B01TR4), 12% (B01TR5 and B01TR6), and a control without inoculum (B01TR1 and B01TR2). Additionally, the influence of nutrients (peptone as a nitrogen source) and micronutrients (nickel (Ni) and cobalt (Co)) was assessed, maintaining a final volume of 1,700 mL (as shown in Table 2). The treatments were incubated in a water bath at 37 °C for 9 days to facilitate biomethane production. Batch 02 (B02) examined the effects of vinasse as a potassium (K) and phosphorus (P) source (B02TR2 and B02TR3), the presence of peptone (as a nitrogen source) (B02TR3), and the absence of both vinasse and peptone (B02TR1) on biogas production. This batch was prepared with a total volume of 1,900 mL (refer to Table 2), using 10 or 5% of inoculum and incubated at 37 °C for 7 days. Batch 03 (B03) evaluated different inoculum concentrations (0%, 10%, and 20%) along with supplementation of chicken manure (CM).
Micronutrient supplementation included nickel, cobalt, and molybdenum (Mo) in total volume of 1,000 mL (see Table 2). The treatments were maintained at 37 °C for 8 days to promote biomethane production. In Batch 04 (B04), the treatments B03TR7, B03TR8, and B03TR9 (see Table 2) were repeated using 20% inoculum, with anaerobic digestion (AD) maintained for 15 days at 37 °C. The microbial communities developed in these three B03 treatments served as the inoculum for Batch 04.
Biomethane production and chemical analysis
The direct measurement of the volume of methane produced during biogas production was conducted as described by Aquino et al. [9] using the Apparatus II system (Mariotte Bottle). This system allows for the measurement of biogas generation through volumetric assessment, using a 0.5 M NaOH solution as a displacement medium. The end of the assessment is established when there is a significant reduction in the displacement of the 0.5 M NaOH solution, indicating that biogas is no longer being produced. Biochemical and Chemical Oxygen Demand (BOD and COD), Total Organic Carbon (TOC), and Total Organic Nitrogen (TON) were quantified, according to Standard Methods for the Examination of Water and Wastewater—23rd Edition. Further, the Carbon:Nitrogen (C:N) ratio was calculated. The concentration of micronutrient, such as Iron (Fe), Manganese (Mn), Copper (Cu), Zinc (Zn), and Boron (B) were carried out in Agronomic Institute of Campinas (IAC, Campinas, SP, Brazil).
Microbial community analysis
To assess variations in the diversity and richness of the microbial community during anaerobic digestion (AD), genomic DNA was extracted from 0.25 g samples collected from dewatered primary sludge (DPS), adapted inoculum, and from batches 03 and 04, and the samples were evaluated by sequencing. This was accomplished using the NucleoSpin® Soil Kit (Macherey–Nagel) according to the manufacturer’s instructions. The extracted DNA was then utilized for the partial amplification of the V3-V4 variable region of the 16S rDNA gene (bacteria and Archaea) with primers Bakt_341F (5’-CCT ACG GGN GGC WGC AG-3’) and Bakt_805R (5’-GAC TAC HVG GGT ATC TAA TCC-3’) and the ITS-1 region of rRNA (fungi) with primers ITS1F: 3’-CTT GGT CAT TTA GAG GAA GTA A-5’ and ITS2: 3’-GCTGCGTTCTTCATCGATGC-5’.
The resulting amplicons were prepared for library construction using the TrueSeq DNA PCR Free LT sample preparation kit (Illumina, CA, USA) and sequenced by DSMA (Sustainable Development and Environmental Monitoring) using the Illumina MiSeq sequencing platform (Illumina, CA, USA). Raw sequencing data (fastq datasets) were processed to ensure quality control, removing PCR artifacts and low-quality reads (Q value < 30%) using the Mothur v.1.48.1 pipeline [10]. The reads were then grouped into Operational Taxonomic Units (OTUs), with taxonomic assignments made through comparisons with the Silva 138 database [11]. The relative abundance of the microbial community was expressed as the average number of reads from biological replicates of the samples.
Community clustering analysis among the various samples was performed using classical clustering methods, specifically UPGMA (Unweighted Pair Group Method with Arithmetic Mean), with 1000 bootstrap replicates, as well as Principal Coordinates Analysis (PCA), applying the Bray–Curtis similarity index. Species accumulation curves were calculated using the rarefaction method, while richness estimates were obtained with the Chao 1 and ACE (Abundance-based Coverage Estimator) indices. Diversity indices, including Shannon–Wiener and Simpson, were calculated using PAST 4.17 software [12].
Results
Anaerobic digestion, biogas production, and chemical analyses
The results indicated that, regardless of inoculum concentration, vinasse supplementation, and total solids (Table 1), the cumulative biomethane production measured daily during the anaerobic digestion (AD) of dewatered primary sludge (DPS) with wastewater treatment plant (WWTP) sludge as inoculum resulted in low biogas production and only a limited reduction in chemical oxygen demand (COD). Consequently, we developed an acclimatized inoculum specifically for this substrate, as described in the Materials and Methods section, which was used in subsequent batches.
The Chemical Oxygen Demand (COD) of the Dewatered Primary Sludge (DPS) ranged from 1.28 to 17.26 g/L, while the Total Solids (TS) content varied between 31.23% and 37.53%. Within each batch, TS levels ranged from 5 to 9%. The cumulative biomethane production curves for batches 1 to 3 are presented in Fig. 1 (A-C). In Batch 01, the negative controls B01TR1 and B01TR2, which did not include inoculum (refer to Table 2), produced biomethane amounts of 0.335 L and 0.830 L, respectively (Fig. 1A). Over a 9-day period, significant differences in daily cumulative biomethane production were observed among the treatments. The most significant factor was the inoculum concentration; cumulative biomethane production in B01TR5 was 2.5 times higher than in B01TR3 (Fig. 1A), with inoculum volumes of 0.2 (~ 12%) and 0.1 L (~ 6%) (Table 2), respectively. Additionally, this B01TR5 treatment presented 22.1% of COD reduction (Table 3). Supplementation with Nickel (Ni) and Cobalt (Co) positively affected biomethane production when low inoculum concentrations were used.Fig. 1. Cumulative biomethane production was evaluated across three batches to assess the effects of inoculum and nutritional supplementation. A) Batch 01; B) Batch 02 and C) Batch 03. The conditions described for each batch are described in Table 2Table 3. Summary of Anaerobic Digestion Across Three Batches (B01, B02, and B03)TreatmentsTS (%)COD_i_ (g)COD_r_ (%)BME (L)BMO (L)Efficiency (%)B01TR17.019.704.807.940.3354.22%B01TR27.019.7012.007.940.83010.45%B01TR37.218.528.307.460.5357.17%B01TR47.218.5215.007.460.96512.93%B01TR57.417.3022.106.971.33019.08%B01TR67.417.3016.306.970.98014.06%B02TR16.615.6030.006.291.65526.32%B02TR25.512.508.005.040.4408.73%B02TR34.912.508.205.040.4508.93%B03TR16.714.059.105.660.3506.18%B03TR28.414.0531.205.661.20021.19%B03TR38.414.0523.405.660.94016.60%B03TR47.014.0550.005.661.93034.09%B03TR58.714.0556.205.662.40042.39%B03TR68.714.0568.705.662.37041.86%B03TR77.314.0571.405.662.18038.50%B03TR89.014.0586.205.662.61046.10%B03TR99.014.0584.705.662.57045.39%This table presents the following parameters: the percentage of total solids (TS), initial chemical oxygen demand (CODi), percentage of COD removal (CODr), estimated (BME) and observed (BMO) maximum CH₄ production at 37 °C, and the efficiency expressed as the yield percentage in relation to both estimated and observed values
In Batch 02, the conditions from B01TR5 (Batch 01) served as a guide for the next experiment. The inoculum concentration was reduced to approximately 10% and included supplementation with vinasse and/or peptone as sources of carbon and nitrogen. In this batch, the cumulative CH₄ production for the treatment B02TR1 was 1,655 L, while the treatments with vinasse supplementation produced up to 0.450 L over 7 days, regardless of the inclusion of peptone as a nitrogen source (see Table 2 and Fig. 1B). The COD conversion efficiency was 30% for treatment B02TR1 and reached up to 8% for treatments B02TR2 and B02TR3 (Table 3).
In Batch B03, variations in the inoculum amount (0%, 10%, and 20%), supplementation with chicken manure (CM), and micronutrients (Nickel, Cobalt, and Molybdenum) were evaluated. Cumulative biomethane production ranged from 0.350 L (B03TR1) to 2.610 L (B03TR8) (Fig. 1C). Overall, Molybdenum supplementation reduced biomethane production. In contrast, a synergistic effect was observed between higher inoculum concentrations and CM, with cumulative biomethane production increasing by at least 10% when the inoculum concentration increased from 10 to 20%. Additionally, CM supplementation resulted in a 20% increase in biomethane production. In this Batch 03, COD removal ranged from 9.1% (B03TR1) to 86.20% (B03TR8). The inoculum concentration was the most critical factor in reducing COD, with up to a 28% greater reduction observed with 20% inoculum compared to 10%. Conversely, CM supplementation was associated with up to a 10% increase in COD reduction compared to treatments without CM (Table 3).
In Batch 04, the conditions used for treatments B03TR7, B03TR8, and B03TR9 were repeated, with anaerobic digestion (AD) maintained for 15 days (360 h). The cumulative biomethane curves for these treatments are shown in Fig. 2. The production pattern showed three distinct phases: an initial phase (up to 144 h) with high production, a second phase (144–240 h) with reduced production, and a third phase (240–360 h) with minimal to no biomethane production. Supplementation with chicken manure (CM) resulted in at least a 43% increase in biomethane yield, whereas molybdenum was associated with a reduction in biomethane production.Fig. 2. Cumulative biomethane in anaerobic digestion of DPS with chicken manure (B04TR2 and B04TR3) and Molybdenum (B04TR3) supplementation
Given that COD removal in these treatments exceeded 80% (Table 3), we conclude that optimal conditions for digesting dewatered primary sludge (DPS) include 20% adapted inoculum and 5% CM supplementation. It is advisable to evaluate the necessity of Nickel (Ni) and Cobalt (Co) supplementation on a case-by-case basis, while supplementation with molybdenum and vinasse may not be required.
Analysis of the microbial community during anaerobic digestions
To examine shifts in the microbial community during anaerobic digestion, samples from the initial inoculum and treatments used in Batches 03 (B03) and 04 (B04) were collected for 16S rRNA gene sequencing (bacteria and archaea) and ITS sequencing (fungi). Figures 3, 4 and 5 present the evolution of archaeal, bacterial, and fungal communities at the genus level (with abundance greater than 1%) across the evaluated Batches.Fig. 3. Relative abundance of archaeal communities in the inoculum (ID) and anaerobic digestion across different treatments in Batch 03 (A) and Batch 04 (B), presented at the genus level (dominant genera with greater than 1% abundance)Fig. 4. Relative abundance of bacterial communities in the inoculum (ID) and anaerobic digestion across different treatments in Batch 03 (A) and Batch 04 (B), presented at the genus level (dominant genera with greater than 1% abundance)Fig. 5. Relative abundance of Fungal communities in the inoculum (ID) and anaerobic digestion across different treatments in Batch 03 (A) and Batch 04 (B), presented at the genus level (dominant genera with greater than 1% abundance)
The structure of microbial communities in B03 and B04 was assessed by analyzing operational taxonomic unit (OTU) diversity, including metrics such as OTU richness, Simpson's D, Shannon diversity, evenness, equitability, and Chao-1. These metrics were used to evaluate changes in microbial alpha diversity under different anaerobic digestion conditions (Table 4). Notable differences linked to the batch treatments were observed in the diversity of archaeal, bacterial, and fungal communities. In Batch 04, the richness (Chao-1) and diversity (measured by Simpson's D and Shannon index) of the microbial communities were significantly reduced compared to Batch 03. Furthermore, a higher dominance was noted in Batch 04 (Table 4), indicating that certain microbial species were selected preferentially in this batch.Table 4. Diversity (OTU richness, Simpson_1-D, Shannon_H, Evenness, Equitability_J and Chao-1) of archaeal, bacterial and fungal communities in bioreactor for anaerobic digestion of DPS under different conditionsB03IDB03TR1B03TR2B03TR3B03TR4B03TR5B03TR6B03TR7B04IDB04TR1B04TR2B04TR3Dominance_DBacteria0,0260,0230,0210,0210,0220,0160,0180,1270,1340,0530,0670,061Archaea0,0800,0860,0750,0700,0870,0800,3770,1580,7540,6110,6370,776Fungi0,0920,1140,0530,0280,1520,0360,1060,7920,3070,3810,0870,176Simpson_1-DBacteria0,9740,9770,9790,9790,9780,9840,9820,8730,8660,9470,9330,939Archaea0,9200,9140,9250,9300,9130,9200,6230,8420,2460,3890,3630,224Fungi0,9080,8860,9470,9720,8480,9640,8940,2080,6940,6190,9130,824Shannon_HBacteria4,7584,8774,9135,0404,9425,2175,0343,2132,9053,9463,6833,713Archaea2,8892,7862,9562,8972,7492,8221,5312,4580,4390,6850,6350,393Fungi3,5453,3133,6814,2452,7574,1033,3280,7922,1281,7703,0092,236EvennessBacteria0,1320,1470,1570,1710,1550,2040,1820,0390,0540,1050,0870,090Archaea0,6200,6480,6630,7250,6250,6470,2720,4500,5170,1980,3770,370Fungi0,1240,1030,1470,2290,0600,1930,1110,0130,0590,0400,1470,077Equitability_JBacteria0,7020,7180,7260,7410,7260,7670,7470,4970,4990,6360,6010,606Archaea0,8580,8650,8780,9000,8540,8660,5410,7550,4000,2970,3950,284Fungi0,6290,5930,6580,7420,4960,7140,6020,1540,4290,3560,6110,466Chao-1Bacteria1039,01002,01004,01018,01026,01032,0960,6828,0526,3631,0630,5684,2Archaea34,23032,46030,99026,49036,93028,49022,23042,4003,00010,0005,0004,000Fungi365,500299,200329,000368,700312,000361,000251,500244,900172,100191,500170,500151,100
Archaeal communities
The relative abundance of archaeal genera (greater than 1%) is illustrated in Fig. 3A. In Batch 03, microbial communities were not evaluated for treatments B03TR8 and B03TR9. Among the other treatments, the most abundant archaeal genera included Methanosarcina*, Methanobrevibacter, Bathyarchaeia_ge, Methanobacterium, *Odinarchaeia_ge, and Methanococcoides. Notably, the uncultured Methanomethylophilaceae (order Methanomassiliicoccales) was the most prominent in treatment B03TR6, comprising over 58% of the archaeal community, even though it remained undetected in at least six treatments within Batch 03 (see Fig. 3A and Table 4). The relative abundance of Methanosarcina exhibited distinct trends between the two batches. It was below the detection level in B03ID and treatments B03TR1 to B03TR5, registering at 0.44% and 13.21% in B03TR6 and B03TR7, respectively. However, its abundance increased to over 74% in Batch 04. The hydrogenotrophic genus Methanobacterium showed a range of 5.71% to 34.59% in Batch 03 and 12.64% to 23.41% in Batch 04 (Fig. 3; Table 4).
In contrast, there was a notable decrease in the abundance of the archaeal genus Methanobrevibacter, a strictly anaerobic hydrogenotrophic archaeon, which ranged from 6.19% to 19.88% in Batch 03 and decreased to 0% in Batch 04. Similarly, the abundance of Methanococcoides, a methylotrophic methanogenic archaeon, ranged from 1.77% to 19.52% in Batch 03 and decreased below to 0.27% in Batch 04.
Bacterial communities
The relative bacterial abundance at the genus level reveals that treatments B03TR1 through B03TR5 exhibited a community structure closely resembling that of the inoculum B03ID (Fig. 4A). In contrast, treatments B03TR6 and B03TR7 displayed an increased abundance of Sphaerochaetae*, Ethanoligenes, Erysipelothrix, *Sulfurospirillum, and Candidatus_Falkowbacteria_ge, along with a decreased abundance of Faecalibacterium. Additionally, Parabacteroides and Bacteroides, which have hydrolytic capabilities and can assimilate complex carbohydrates, were dominant in all treatments of Batch 03 (Fig. 4A).
In Batch 04, which achieved the highest cumulative biomethane production during the experiment, the richness and diversity of the bacterial community were lower in comparison to that observed in B03TR1 to B03TR5 and comparable to B03TR7 (Table 4), which served as the inoculum for the Batch 04 treatments. The bacterial communities in Batch 04 included significant abundances of Aerosphaera*, Bacteroides, Candidatus_Falkowbacteria_ge, Erysipelothrix, *Ethanoligenes, Parabacteroides, Sphaerochaetae, and Sulfurospirillum. In average Bacteroidetes was abundant in Batches 03 and 04, but considering each treatment, in treatment B03TR7, which was selected for the Batch 04 the abundance of this genus was 31.2%, while its abundance in the other treatments was below 10.3%.
The addition of chicken manure (CM) resulted in an increased abundance of Candidatus_Falkowbacteria_ge in treatments B04TR2 and B04TR3 (Fig. 4B and Table 2). The minor genus Cellulomonas was only detected in B03TR6 (0.03%) in Batch 03, but it was present in all treatments of Batch 04, with abundances ranging from 0.01% to 0.11%. Meanwhile, Cellulosimicrobium was absent in B03TR1 to B03TR5, yet it was identified in all Batch 04 treatments with levels between 0.02% and 0.04% (Supplementary Material Fig. S1), indicating its enrichment under these conditions. Additionally, several genera showed significant enrichment in Batch 04 compared to Batch 03, including Aerosphaera (increasing from 0 in B03 to 3.5 in B04), Ethanoligens (from 1.29 in B03 to 6.17 in B04), Parabacteroides (from 1.72 in B03 to 4.33 in B04), and Proteiniphilum (from 1.06 in B03 to 2.95 in B04).
Fungal communities
The fungal community structure at the genus level displayed notable differences between Batch 03 (B03) and Batch 04 (B04), while remaining relatively consistent across the treatments within each batch. In Batch 03, the dominant genera were as follows: Mortierella (7.17%), Fusarium (5.52%), Pisolithus (5.35%), Gibellula (4.11%), Cryptococcus (3.74%), Penicillium (3.06%), Pyronema (2.95%), and Porpomyces (2.28%). In contrast, the abundance of these genera significantly declined in Batch 04; specifically, Mortierella, Fusarium, Pisolithus*, *Pyronema, and Porpomyces were undetectable in B04. Cryptococcus and Penicillium were recorded at low levels of 0.36% and 0.66%, respectively.
In Batch 04, certain genera experienced substantial enrichment. The relative abundance of Pseudoeurotium surged from 0.01% in B03 to 20.31% in B04. Similarly*, *Arachnomyces increased from 0.02% to 13.17%, Issatchenkia from 0% to 10.76%, Malassezia from 0.23% to 8.72%, Corallocytostroma from 0.02% to 7.69%, and Hamigera from 0.04% to 4.20%. Additionally, Candida exhibited dominance in the B03 treatment (B03TR7), accounting for 88.95% of the community, but its prevalence dropped significantly to below 0.75% in most other treatments. This shift highlights the dynamic changes in fungal community composition between the two batches.
Discussion
The need to reduce industrial waste has led to the exploration of alternatives for managing byproducts. Substrates rich in organic matter can be used for energy generation, including biogas production. However, selecting the optimal management strategy requires consideration of substrate type and composition, as certain compounds may hinder microbial metabolism and reduce methane production. Biomethane can be sourced from both liquid and solid waste, as well as dedicated biomass. In the European Union, data from 2011 showed that biogas were generated from agricultural substrates (66.5%), landfills (23.6%), and sewage sludge (9.9%) [10].
The inclusion of micronutrients such as iron (Fe), cobalt (Co), and nickel (Ni) in biodigesters is linked to increased biogas production [13]. Essential metalloenzymes for methanogenesis depend on these micronutrients during anaerobic digestion [14, 15]. While trace metal supplementation can enhance anaerobic digestion efficiency, excessive concentrations may inhibit methanogenesis [14, 16].
Kang and Ahn [13] identified optimal ranges for Fe, Co, and Ni, revealing that combinations of Fe + Co or Fe + Co + Ni were more effective than Fe alone. In mesophilic digesters, ideal concentrations were Co: 0.33 mg/L, Ni: 0.43 mg/L, and Fe: 5.35 mg/L; in thermophilic digesters, they were Co: 1.41 mg/L, Ni: 3.84 mg/L, and Fe: 200 mg/L. Excess trace metals were noted to decrease biogas production. In this study, mesophilic reactors used Ni (21.7 or 43.5 mg/L) and Co (26.7 or 53.5 mg/L) at concentrations significantly higher—up to 11 and 37 times, respectively—than previously reported, and both metals enhanced biogas production. Molybdenum did not impact biodigestion, suggesting adequate levels may already be present in the substrate.
Nickel, despite being toxic, is essential for many microorganisms, supporting cellulolytic and methanogenic activity. Concentrations below 0.8 mg/L or above 100 mg/L can inhibit biogas production, while approximately 20 mg/L is optimal for methane-rich biogas [17]. Nickel is in high demand among microorganisms, including protozoa, bacteria, and archaea involved in anaerobic processes [16, 18]. Iron concentrations around 1.0 mg/L enhance enzyme activity, such as cellulase, correlating with increased biogas production; deficiencies in iron are linked to reduced efficiency [19, 20]. Although molybdenum and other elements are recognized as important for biogas production [21, 22], its addition did not enhance significantly biogas production in our laboratory-scale study. In this study, the COD removal in treatments for Batch 04 exceeded 80% (Table 3), indicating that optimal conditions for digesting dewatered primary sludge (DPS) include 20% adapted inoculum and 5% chicken manure (CM) supplementation. The need for Nickel (Ni) and Cobalt (Co) supplementation should be evaluated on a case-by-case basis. Additionally, supplementation with molybdenum and vinasse may not be necessary, while inoculum acclimatization significantly enhances biomethane production.
In anaerobic biodigesters, bacteria, archaea, and fungi interact synergistically. Bacteria and fungi cooperate to degrade organic matter, producing hydrogen and acetate, which methanogenic archaea then convert to biogas. Bacteroidota and Bacillota are the most abundant bacterial phyla in digesters fed with animal manure [23], consistent with findings from this study. Conversely, solid waste-fed digesters primarily host Bacteroidota, Pseudomonadota, and Bacillota [24], indicating that substrate composition influences bacterial community structure. Bacteroidota are effective at fermenting carbohydrates and producing byproducts like propionate, acetate, hydrogen, and carbon dioxide, while Clostridiales excel at degrading plant cellulose and fatty acids [13]. Both bacterial groups were present across all samples in this study.
The efficiency of anaerobic digesters producing biomethane depends on the composition and diversity of microbial communities essential for degrading complex substrates. This diversity is influenced by the microenvironment where microbial succession occurs. To optimize performance, it is crucial to start with an inoculum of known origin to facilitate adaptation to the new substrate [14, 25]. Previous studies have shown that digestate from liquid anaerobic digestion can effectively serve as an inoculum for solid anaerobic digestion [26].
In this study, the use of conventional inoculum from a wastewater treatment plant (WWTP) did not produce biogas from dewatered primary sludge. Rani and Dhoble [7] highlight the importance of inoculum acclimatization and aging in anaerobic digestion. Our findings indicate that acclimatization significantly influenced the final microbiome during digestion,specifically, it reduced both diversity and richness while increasing dominance, suggesting that certain microbial groups became predominant under these conditions.
The archaeal genus Methanobrevibacter, a strictly anaerobic hydrogenotrophic archaeon, was present at up to 19.88% in some samples from Batch 03 but was not detected in Batch 04. Similarly, the abundance of Methanococcoides, a methylotrophic methanogenic archaeon, ranged from 1.77% to 19.52% in Batch 03 and decreased below to 0.27% in Batch 04. In contrast, the genera Methanosarcina and Methanobacterium dominated Batch 04, together accounting for nearly 98% of the entire archaeal community.
Methanosarcina spp. represent a group of methanogenic archaea capable of utilizing various small organic substrates to produce methane [27]. According to Yun et al. [28], methylotrophic methanogens such as Methanosarcina spp. can contribute up to 70% of methane production in anaerobic digestion. The genus Methanobacterium, known for its role in interspecies electron transfer via hydrogen, may also directly accept electrons from Fe(0) or cathodes [6]. In a separate study utilizing accumulated fermentable sugars from biosaccharified corn as a substrate for anaerobic digestion, it was suggested that Methanobacterium significantly contributed to high methane yields [29].
In our laboratory-scale study, Batch 04 exhibited higher biomethane production, with a notable dominance of Methanosarcina and Methanobacterium, indicating a synergistic relationship between these two populations during biomethane production. Members of these archaeal genera utilize acetate, hydrogen, and carbon dioxide to generate methane at various stages of digestion [30, 31]. The order Methanosarcinales is particularly predominant in worldwide anaerobic biodigesters [20, 27], comprising up to 85% of the archaeal community in the acclimatized inoculum used in Batch 04, which produced a significantly larger amount of biomethane.
Bacteria such as Sphaerochaeta*, Candidatus Cloacimonas, *Dysgonomonas, and Saccharofermentans play vital roles in organic matter degradation. For example, Candidatus Cloacimonas, a Spirochaete, oxidizes propionate into carbon dioxide and acetate under low hydrogen pressure [18]. Acholeplasma produces fatty acids that serve as substrates for methane production [32], while Syntrophomonas metabolizes fatty acids in synergy with hydrogen-utilizing bacteria [33]. Dysgonomonas assists in lignin decomposition into biogas during the digestion of heat-treated residues, but it is present in low abundance due to the lack of lignin in the residual material [34].
The bacterium Proteiniphilum, which converts organic acids into acetic acid, was found in nearly all treatments except for batch B03, highlighting its role in the initial stages of methane production [35]. Syntrophic bacteria like Tissierella and Clostridium play roles in degrading organic polymers to yield methane [13], while Acinetobacter and Spirochaetales perform anaerobic iron respiration and produce intermediates used by methanogenic archaea [36]. At the start of digestion, facultative anaerobic bacteria break down carbohydrates, lipids, and proteins into sugars, amino acids, and fatty acids. Bacillus and Lactobacillus convert these products into acids and alcohols, which are then transformed into hydrogen, carbon dioxide, and acetic acid by various bacteria [3, 37]. This hydrogen and acetic acid are ultimately utilized by methanogenic archaea to produce methane.
The Ascomycota phylum is notably abundant in the analyzed digesters, encompassing genera like Hanseniaspora and Aspergillus that are essential for food waste fermentation and the promotion of methanogenic microorganisms [38]. Microbial assessments of the substrates revealed optimal conditions for anaerobic digestion and biogas production. Supplementation with nitrogen, nickel, and cobalt enhances biomethane output, with optimal concentrations identified as 43.55 mg/L for nickel and 53.51 mg/L for cobalt. Additionally, a carbon-to-nitrogen ratio of around 9 was found to be ideal, providing a foundation for large-scale testing.
In biomethane production from nitrogen-poor residues, such as degraded cellulose from the paper industry evaluated in this study, it is essential to supplement these materials with nutrients like nitrogen and minerals [39–42]. Additionally, acclimatizing the inoculum to utilize these residues during anaerobic digestion appears to be a critical step in enhancing the potential for generating renewable energy from such pollutants.
Many studies have investigated the impact of nutrient supplementation and inoculum acclimatization on the anaerobic digestion of lignocellulosic residues [39–43]. However, they often overlook the influence of these factors on the diversity and structure of the adapted microbiome. In our laboratory-scale evaluation involving three batches, we identified the optimal conditions for digesting residues from the paper mill industry. Our findings demonstrate that acclimatized inoculum offers superior performance and greater process stability. This inoculum exhibited lower richness and diversity, but higher dominance, suggesting that the process favored the development of an adapted microbial community that likely functions synergistically to enhance biomethane production. While our study showed that supplementation with molybdenum and vinasse as an additional carbon source did not significantly impact cumulative biomethane production, the addition of chicken manure and an increased concentration of acclimatized inoculum resulted in a substantial boost in biomethane output. The knowledge contributed from this study can aid in the implementation of pilot-scale management and utilization of biomass, as well as increase the potential for recovering energy from cellulose-rich residues.
Supplementary Information
Below is the link to the electronic supplementary material.Supplementary file1 (CSV 196 KB)
The reference list from the paper itself. Each links out to its DOI / PubMed record.
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