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In the past decade, governments and development agencies have contributed significantly to society through anaerobic digestion technology (ADT). Anaerobic digestion technology (ADT) has become an important tool in the fight against global poverty and environmental issues, leading to positive change in communities around the world. The technology works as a wet or dry process, depending on its classification. The process is complex and yields multiple benefits, such as creating a natural fertilizer that can be used to help crops grow, as well as generating renewable energy sources. It is common knowledge that many household-sized digesters installed in different areas are one-stage digesters. One-stage digesters do not require a separate pre-treatment stage before the digestion process. This makes them simpler and more cost-effective to install and operate than traditional two-stage digesters. Thus, some drawbacks are associated with these systems since they feed on just one type of feedstock. Many researchers fail to adequately address interactions critical to ADT’s operation, including interactions among growth factors and operating parameters. In a single-stage and one-substrate digester, researchers commonly neglect to study the digester feeding and operational conditions. Anaerobic digestion was the subject of this review, covering research conducted between 2001 and 2022. The study identified a significant drawback associated with mono-digestion and single-stage digestion. The findings illustrate that mono-substrate and single-stage digestion are worthwhile approaches, even though they have their challenges. However, adding a further digestion stage can significantly improve biogas production.

Anaerobic biodigesters play a crucial role in the sustainable development of rural areas, managing waste and generating renewable energy. This review evaluates the development and performance of the fixed dome, floating drum, and tubular biodigesters, viz, shows how design improvements and operational strategies impact their efficiency. The original design of these traditional models was found to be restricted by microbial instability caused by climate fluctuations and operational disturbances. In response, modern designs incorporated specific adaptations, such as thermal control and feedstock optimization. The fixed dome model demonstrated improved durability and performance with solar heating and self-mixing capabilities that increase methane production and volatile solids removal. In contrast, floating drum digesters, which are constantly limited by corrosion and inconsistent yields, have been developed to incorporate plastic protective layers, integrated mixing shafts, and in-situ purification to achieve better methane concentrations and improved system efficiency. Affordable and adaptable tubular digesters with modular expansion capabilities, incorporating trench burial and greenhouse enclosures, have been designed to enhance affordability and mitigate the effects of climate change. The modifications increase methane production, process stability, and energy recovery. Biodigester performance and efficiency are fundamentally driven by design. Accordingly, the future adoption of anaerobic biodigesters will depend on locally adaptable and affordable systems supported by practical maintenance frameworks, as well as community awareness and training. Overall, recent design innovations have enabled a shift from climate-sensitive traditional models toward more durable, efficient, and adaptable digesters capable of stabilizing methane yield under variable operating conditions.

Background Commercial biogas upgrading facilities are expensive and consume energy. Biological biogas upgrading may serve as a low-cost approach because it can be easily integrated with existing facilities at biogas plants. The microbial communities found in anaerobic digesters typically contain hydrogenotrophic methanogens, which can use hydrogen (H2) as a reducing agent for conversion of carbon dioxide (CO2) into methane (CH4). Thus, biological biogas upgrading through the exogenous addition of H2 into biogas digesters for the conversion of CO2 into CH4 can increase CH4 yield and lower CO2 emission. Results The addition of 4 mol of H2 per mol of CO2 was optimal for batch biogas reactors and increased the CH4 content of the biogas from 67 to 94%. The CO2 content of the biogas was reduced from 33 to 3% and the average residual H2 content was 3%. At molar H2:CO2 ratios > 4:1, all CO2 was converted into CH4, but the pH increased above 8 due to depletion of CO2, which negatively influenced the process stability. Additionally, high residual H2 content in these reactors was unfavourable, causing volatile fatty acid accumulation and reduced CH4 yields. The reactor microbial communities shifted in composition over time, which corresponded to changes in the reactor variables. Numerous taxa responded to the H2 inputs, and in particular the hydrogenotrophic methanogen Methanobacterium increased in abundance with addition of H2. In addition, the apparent rapid response of hydrogenotrophic methanogens to intermittent H2 feeding indicates the suitability of biological methanation for variable H2 inputs, aligning well with fluctuations in renewable electricity production that may be used to produce H2. Conclusions Our research demonstrates that the H2:CO2 ratio has a significant effect on reactor performance during in situ biological methanation. Consequently, the H2:CO2 molar ratio should be kept at 4:1 to avoid process instability. A shift toward hydrogenotrophic methanogenesis was indicated by an increase in the abundance of the obligate hydrogenotrophic methanogen Methanobacterium.

Biogas plant operators often face huge challenges in the monitoring, controlling and optimisation of the anaerobic digestion (AD) process, as it is very sensitive to surrounding changes, which often leads to process failure and adversely affects biogas production. Conventional implemented methods and mechanistic models are impractical and find it difficult to model the nonlinear and intricate interactions of the AD process. Thus, the development of machine learning (ML) algorithms has attracted considerable interest in the areas of process optimization, real-time monitoring, perturbation detection and parameter prediction. This paper provides a comprehensive and up-to-date overview of different machine learning algorithms, including artificial neural network (ANN), fuzzy logic (FL), adaptive network-based fuzzy inference system (ANFIS), support vector machine (SVM), genetic algorithm (GA) and particle swarm optimization (PSO) in terms of working mechanism, structure, advantages and disadvantages, as well as their prediction performances in modelling the biogas production. A few recent case studies of their applications and limitations are also critically reviewed and compared, providing useful information and recommendation in the selection and application of different ML algorithms. This review shows that the prediction efficiency of different ML algorithms is greatly impacted by variations in the reactor configurations, operating conditions, influent characteristics, selection of input parameters and network architectures. It is recommended to incorporate mixed liquor volatile suspended solids (MLVSS) concentration of the anaerobic digester (ranging from 16,500 to 46,700 mg/L) as one of the input parameters to improve the prediction efficiency of ML modelling. This review also shows that the combination of different ML algorithms (i.e. hybrid GA-ANN model) could yield better accuracy with higher R 2 (0.9986) than conventional algorithms and could improve the optimization model of AD. Besides, future works could be focused on the incorporation of an integrated digital twin system coupled with ML techniques into the existing Supervisory Control and Data Acquisition (SCADA) system of any biogas plant to detect any operational abnormalities and prevent digester upsets.

Use of anaerobic sludge digester is a common practice around the world for solids digestion and methane generation from municipal sewage sludge. Understanding microbial community structure is vital to get better insight into the anaerobic digestion process and to gain better process control. However, selective analysis of viable microorganisms is limited by DNA-based assays. In this study, propidium monoazide (PMA)-PCR with 16S rRNA gene sequencing analysis was used to distinguish live and dead microorganisms based on cell membrane integrity. Microbial community structures of PMA-treated and PMA-untreated anaerobic digester sludge samples were compared. Quantitative PCR revealed that 5–30% of the rRNA genes were derived from inactive or dead cells in anaerobic sludge digesters. This caused a significant decrease in the numbers of operational taxonomic units and Chao1 and Shannon indices compared with that of the PMA-untreated sludge. Microbial community analysis showed that majority of the viable microbiome consisted of Euryarchaeota, Bacteroidetes, Deltaproteobacteria, Chloroflexi, Firmicutes, WWE1, Spirochaetes, Synergistetes, and Caldiserica. On the other hand, after the PMA treatment, numbers of Alphaproteobacteria and Betaproteobacteria declined. These were considered residual microbial members. The network analysis also revealed a relationship among the OTUs belonging to WWE1 and Bacteroidales. PMA-PCR-based 16S rRNA gene sequencing analysis is an effective tool for uncovering viable microbiome in complex environmental samples.

Presence of carbohydrates hampers protein degradation in anaerobic digesters. To understand this phenomenon, we used proteogenomics to identify the active protein-degraders in the presence of low and high carbohydrates concentrations. Active metabolic pathways of the identified protein-degraders were investigated using proteomics with 13 C-protein substrates (protein stable isotope probing). Results showed that 1) Acinetobacter was the active protein-degraders under both protein-fed and protein-glucose mixture-fed conditions, 2) the relative abundance of Acinetobacter was not affected by the presence of carbohydrates, 3) the incorporation of the 13 C-labelled protein substrate was predominantly observed in outer membrane-bound proteins and porin proteins, which are associated with proteinases or the transportation of amino acids across the cell wall. The Acinetobacter metabolic model and the incubation conditions suggested that glucose and proteins were degraded through anaerobic respiration. The negative impact of carbohydrates on protein biodegradation was attributed to Acinetobacter 's preference for carbohydrates. This work highlights that efficient degradation of protein and carbohydrate mixtures in anaerobic digesters requires a staged or time-phased approach and enrichment of active protein-degraders, offering a new direction for process optimization in anaerobic digestion systems. Key points • Acinetobacter identified for the first time as main anaerobic protein-degrader • Metabolic model revealed protein degradation via anaerobic respiration • Metabolic pathway analysis indicated SO 4 2− or Fe 3+ as terminal electron acceptors

In this pilot-scale study, simultaneous partial nitrification, anammox, and denitrification (SNAD) process was achieved successfully in a moving bed biofilm reactor (MBBR) for treating anaerobic digester liquor of swine wastewater. After 95 days of operation, when the total nitrogen loading rate of SNAD-MBBR process was 1.09 kg TN/m 3 /day, the total nitrogen removal rate could reach 0.87 kg TN/m 3 /day, and the removal efficiencies of ammonium and total nitrogen were 92.0% and 79.7%, respectively. The optimum pH and temperature for SNAD-MBBR process were 8.5 and 35 °C, respectively, and the optimum dissolved oxygen for SNAD1 and SNAD2 were 0.30 and 0.07 mg/L, respectively. The 16S rRNA sequencing suggested that Candidatus Kuenenia, Candidatus Brocadia, Nitrosomonas , and Denitratisoma were the dominant nitrogen removal bacteria. Some of the co-existing bacteria ( Truepera , Limnobacter , and Anaerolineaceae uncultured) promoted ammonium oxidation and guaranteed the growth of the anammox bacteria under adverse environmental conditions. Overall, this study demonstrated that the SNAD-MBBR process would be an energy-saving and cost-effective method for the removal of nitrogen from swine wastewater and provided important process parameters for stable operation of the full-scale SNAD process.

Anaerobic digestion of lipid-rich wastes holds significant potential for enhanced biomethane production, due to the high energy density of lipids. However, to fully harness this potential, a deeper understanding of lipolytic microorganisms is essential, as key microbial players involved in lipid hydrolysis remain largely unidentified. In this study, we employed an integrated approach combining zymography, metaproteomics, and metagenomics to identify the lipolytic microorganisms from anaerobic digester sludge. This activity-based strategy identified a novel lipase distantly related to known lipases. Besides, although this lipase originates from a mesophilic environment, it exhibited unexpected extremophilic-like properties, with maximal activity at 97.5 °C and pH 11. We further reconstructed a metagenome-assembled genome encoding this lipase and demonstrated that it likely represents a novel genus closely related to Candidatus Scatomorpha. Metabolic reconstruction suggested that this bacterium hydrolyzes extracellular lipids and utilizes the resulting hydrolysate, glycerol, to produce lactate and ethanol. Habitat analysis revealed that this bacterium is specifically detected in anaerobic digesters, particularly those processing lipid-rich waste. These findings highlight the pivotal role of this bacterium in anaerobic lipid degradation.

This study evaluated the use of biochar produced from anaerobic digester dairy fiber (ADF) to sequester phosphorus (P) from dairy lagoons. The ADF was collected from a plugged flow digester, air‐dried to <8% water content, and pelletized. Biochar was produced by slow pyrolysis in a barrel retort. The potential of biochar to reduce P in the anaerobic digester effluent (ADE) was assessed in small‐scale filter systems through which the effluent was circulated. Biochar sequestered an average of 381 mg L−1 P from the ADE, and 4 g L−1 ADF was captured as a coating on the biochar. There was an increase of total (1.9 g kg−1), Olsen (763 mg kg−1), and water‐extractable P (914 mg kg−1) bound to the biochar after 15 d of filtration. This accounted for a recovery of 32% of the P in the ADE. The recovered P on the biochar was analyzed using 31P nuclear magnetic resonance for P speciation, which confirmed the recovery of inorganic orthophosphate after liquid extraction of the biochar and the presence of inextractable Ca‐P in the solid state. The inorganic phosphate was sequestered on the biochar through physical and weak chemical bonding. Results indicate that biochar could be a beneficial component to P reduction in the dairy system.

Anaerobic digestion is considered a key technology for the future bio-based economy. The microbial consortium carrying out the anaerobic digestion process is quite complex, and its exact role in terms of “elasticity”, i.e., the ability to rapidly adapt to changing conditions, is still unknown. In this study, the role of the initial microbial community in terms of operational stability and stress tolerance was evaluated during a 175-day experiment. Five different inocula from stable industrial anaerobic digesters were fed a mixture of waste activated sludge and glycerol. Increasing ammonium pulses were applied to evaluate stability and stress tolerance. A different response in terms of start-up and ammonium tolerance was observed among the different inocula. Methanosaetaceae were the dominant acetoclastic methanogens, yet, Methanosarcinaceae increased in abundance at elevated ammonium concentrations. A shift from a Firmicutes to a Proteobacteria dominated bacterial community was observed in failing digesters. Methane production was strongly positively correlated with Methanosaetaceae , but also with Bacteria related to Anaerolinaceae , Clostridiales , and Alphaproteobacteria . Volatile fatty acids were strongly positively correlated with Betaproteobacteria and Bacteroidetes , yet ammonium concentration only with Bacteroidetes . Overall, these results indicate the importance of inoculum selection to ensure stable operation and stress tolerance in anaerobic digestion.