Wet biowaste digestion: ADM1 model improvement by implementation of known genera and activity of propionate oxidizing bacteria

Co-digestion approach for enhancement of biogas production by mixture of untreated napier grass and industrial hydrolyzed food waste

The co-digestion of untreated Napier grass (NG) and industrial hydrolyzed food waste (FW) was carried out in the batch reactor to investigate the effect of substrate ratios on biogas production performance. Two-stage anaerobic digestion was performed with an initial substrate concentration of 5 g VSadded/L and a Food to Microorganism Ratio (F/M) of 0.84. The 1:1 ratio of the NG and FW showed the optimum performances on biogas production yield with a value of 1,161.33 mL/g VSadded after 60 days of digestion. This was followed by the data on methane yield and concentration were 614.37 mL/g VSadded and 67.29%, respectively. The results were similar to the simulation results using a modified Gompertz model, which had a higher potential methane production and maximum production rate, as well as a shorter lag phase and a coefficient of determination of 0.9945. These findings indicated that the co-digestion of Napier grass and hydrolyzed food waste can enhance biogas production in two-stage anaerobic digestion.

Diverse electron carriers drive syntrophic interactions in an enriched anaerobic acetate-oxidizing consortium

In many anoxic environments, syntrophic acetate oxidation (SAO) is a key pathway mediating the conversion of acetate into methane through obligate cross-feeding interactions between SAO bacteria (SAOB) and methanogenic archaea. The SAO pathway is particularly important in engineered environments such as anaerobic digestion (AD) systems operating at thermophilic temperatures and/or with high ammonia. Despite the widespread importance of SAOB to the stability of the AD process, little is known about their in situ physiologies due to typically low biomass yields and resistance to isolation. Here, we performed a long-term (300-day) continuous enrichment of a thermophilic (55 °C) SAO community from a municipal AD system using acetate as the sole carbon source. Over 80% of the enriched bioreactor metagenome belonged to a three-member consortium, including an acetate-oxidizing bacterium affiliated with DTU068 encoding for carbon dioxide, hydrogen, and formate production, along with two methanogenic archaea affiliated with Methanothermobacter_A. Stable isotope probing was coupled with metaproteogenomics to quantify carbon flux into each community member during acetate conversion and inform metabolic reconstruction and genome-scale modeling. This effort revealed that the two Methanothermobacter_A species differed in their preferred electron donors, with one possessing the ability to grow on formate and the other only consuming hydrogen. A thermodynamic analysis suggested that the presence of the formate-consuming methanogen broadened the environmental conditions where ATP production from SAO was favorable. Collectively, these results highlight how flexibility in electron partitioning during SAO likely governs community structure and fitness through thermodynamic-driven mutualism, shedding valuable insights into the metabolic underpinnings of this key functional group within methanogenic ecosystems.

Modifications to the anaerobic digestion model no. 1 (ADM1) for enhanced understanding and application of the anaerobic treatment processes - A comprehensive review

Anaerobic digestion (AD) is a promising method for the recovery of resources and energy from organic wastes. Correspondingly, AD modelling has also been developed in recent years. The International Water Association (IWA) Anaerobic Digestion Model No. 1 (ADM1) is currently the most commonly used structured AD model. However, as substrates become more complex and our understanding of the AD mechanism grows, both systematic and specific modifications have been applied to the ADM1. Modified models have provided a diverse range of application besides AD processes, such as fermentation and biogas upgrading processes. This paper reviews research on the modification of the ADM1, with a particular focus on processes, kinetics, stoichiometry and parameters, which are the major elements of the model. The paper begins with a brief introduction to the ADM1, followed by a summary of modifications, including extensions to the model structure, modifications to kinetics (including inhibition functions) and stoichiometry, as well as simplifications to the model. The paper also covers kinetic parameter estimation and validation of the model, as well as practical applications of the model to a variety of scenarios. The review highlights the need for improvements in simulating AD and biogas upgrading processes, as well as the lack of full-scale applications to other substrates besides sludge (such as food waste and agricultural waste). Future research directions are suggested for model development based on detailed understanding of the anaerobic treatment mechanisms, and the need to recover of valuable products.

Sustainability for wastewater treatment: bioelectricity generation and emission reduction

This review covers the technological measures of a self-sustainable anaerobic up-flow sludge blanket (UASB) system compared with an aerobic activated sludge process (ASP) for wastewater treatment plants (WWTPs). The ASP requires a huge amount of electricity and chemicals and also results in the emission of carbon. The UASB system, instead, is based on greenhouse gas (GHG) emission reduction and is associated with biogas production for cleaner electricity. WWTPs including the ASP system are not sustainable due to the massive financial power required for clean wastewater. When the ASP system was used, the amount of production was estimated to be 10658.98 tonnes CO₂eq-d^- of carbon dioxide. Whereas it was 239.19 tonnes CO₂eq-d^-1 with the UASB. The UASB system is advantageous over the ASP system as it has a high production of biogas, needs low maintenance, yields a low amount of sludge, and is also a source of electricity that can be used as a power source for the WWTPs. Also, the UASB system produces less biomass, and this helps in reducing costs and maintaining work. Moreover, the aeration tank of the ASP needs 60% of energy distribution; on the other hand, the UASB consumes less energy, approximately 3-11%.

Effect of magnetite particle size on propionate degradation in the propionate-based anaerobic system

The size effect of magnetite (Fe₃O₄) on the degradation of propionate (PA) in the PA-based anaerobic system was investigated. The sequential bench-scale experiments were conducted. Results showed that the effects of different sized magnetite particles on PA degradation varied, and reaction cycles also played a role in substrate removal/degradation. With the increase of reaction cycle, nano-magnetite promoted PA degradation and CH₄ production, which caused faster PA degradation rate (0.997 g/L·d) than the control group (CK) without magnetite (0.834 g/L·d), whereas the groups with micron- and millimeter-sized magnetite had slower PA degradation rates (0.746 and 0.636 g/L·d) than CK group. The particle size or surface characteristics of the magnetite may become the main factor determining the PA degradation rate. Furthermore, the analysis of PA conversion and volatile fatty acids (VFAs) distribution showed the C6-dismutation pathway, which converses PA to butyrate, enhanced by the introduction of magnetite. Microbial community analysis showed that PA was degraded mainly by methyl-malonyl-CoA (MMC) pathway. The relative abundance of Syntrophobacter that catalyze MMC pathway in the group with nano-magnetite were much higher after three reaction cycles at 39 %, as compared to micro-magnetite at 28 %, and millimeter-sized magnetite at 27 %, which contributed to faster degradation of PA. Functional enzyme-encoding genes for the four methanogenesis pathways were identified with reference to KEGG database entries. The methanogenesis pathway using acetate was the most abundant pathway in all groups. The observations have important implications for enhancing the PA removal in PA-inhibited anaerobic digester.

Microbiome Analysis via OTU and ASV-Based Pipelines-A Comparative Interpretation of Ecological Data in WWTP Systems

Linking community composition and ecosystem function via the cultivation-independent analysis of marker genes, e.g., the 16S rRNA gene, is a staple of microbial ecology and dependent disciplines. The certainty of results, independent of the bioinformatic handling, is imperative for any advances made within the field. In this work, thermophilic anaerobic co-digestion experimental data, together with primary and waste-activated sludge prokaryotic community data, were analyzed with two pipelines that apply different principles when dealing with technical, sequencing, and PCR biases. One pipeline (VSEARCH) employs clustering methods, generating individual operational taxonomic units (OTUs), while the other (DADA2) is based on sequencing error correction algorithms and generates exact amplicon sequence variants (ASVs). The outcomes of both pipelines were compared within the framework of ecological-driven data analysis. Both pipelines provided comparable results that would generally allow for the same interpretations. Yet, the two approaches also delivered community compositions that differed between 6.75% and 10.81% between pipelines. Inconsistencies were also observed linked to biologically driven variability in the samples, which affected the two pipelines differently. These pipeline-dependent differences in taxonomic assignment could lead to different conclusions and interfere with any downstream analysis made for such mis- or not-identified species, e.g., network analysis or predictions of their respective ecosystem service.

Mechanisms Driving Microbial Community Composition in Anaerobic Co-Digestion of Waste-Activated Sewage Sludge

Anaerobic co-digestion (Co-AD) is used to increase the effectiveness of anaerobic digestion (AD) using local “wastes”, adding economic and environmental benefits. Since system stability is of existential importance for the operation of wastewater treatment plants, thorough testing of potential co-substrates and their effects on the respective community and system performance is crucial for understanding and utilizing Co-AD to its best capacity. Food waste (FW) and canola lecithin (CL) were tested in mesophilic, lab-scale, semi-continuous reactors over a duration of 120 days with stepwise increased substrate addition. Key performance indicators (biogas, total/volatile solids, fatty acids) were monitored and combined with 16S-rRNA amplicon sequencing to assess the impact of co-substrate addition on reactor performance and microbial community composition (MCC). Additionally, the latter was then compared with natural shifts occurring in the wastewater treatment plant (WWTP, source) at the same time. An almost linear increase in biogas production with both co-substrates at an approximate 1:1 ratio with the organic loading rate (OLR) was observed. The MCCs in both experiments were mostly stable, but also prone to drift over time. The FW experiment MCC more closely resembled the original WWTP community and the observed shifts indicated high levels of functional redundancy. Exclusive to the CL co-substrate, a clear selection for a few operational taxonomic units (OTUs) was observed. There was little evidence for a persistent invasion and establishment of microorganisms from typical primary substrates into the stable resident community of the reactors, which is in line with earlier findings that suggested that the inoculum and history mostly define the MCC. However, external factors may still tip the scales in favor of a few r-strategists (e.g., Prolixibacter) in an environment that otherwise favors K-strategists, which may in fact also be recruited from the primary substrate (Trichococcus). In our study, specialization and diversity loss were also observed in response to the addition of the highly specialized CL, which in turn, may have adverse effects on the system’s stability and reduced resilience and recovery.

Comment on "A compilation and bioenergetic evaluation of syntrophic microbial growth yields in anaerobic digestion" by Patón, M. and Rodríguez, J. [Water Research 162 (2019), 516-517]

Recent efforts have focused on providing a systematic analysis of syntrophic microbial growth yields. These biokinetic parameters are key to developing an accurate mathematical description of the anaerobic digestion process. The agreement between experimentally determined growth yields and those obtained from bioenergetic estimations is therefore of great interest. Considering five important syntrophic groups, including acetoclastic and hydrogenotrophic methanogens, as well as propionate, butyrate and lactate oxidizers, previous findings suggest that measured and estimated growth yields were consistent only for acetoclastic methanogens. A re-analysis revealed that data are also consistent for lactate oxidizers and hydrogenotrophic methanogens, whereas the limited data available for propionate and butyrate oxidizers are unsupportive of firm conclusions. These results highlight pertinent challenges in the analysis of microbial syntrophy and encourage more accurate measurements of syntrophic microbial growth yields in the future.

Interpretable machine learning for predicting biomethane production in industrial-scale anaerobic co-digestion

The objective of this study is to apply machine learning models to accurately predict daily biomethane production in an industrial-scale co-digestion facility. The methodology involved applying elasticnet, random forest, and extreme gradient boosting to input-output data from an industrial-scale anaerobic co-digestion (ACoD) facility. The models were used to predict biomethane for 1-day, 3-day, 5-day, 10-day, 20-day, 30-day, and 40-day time horizons. These models were fit on four years of operational data. The results showed that elastic net (a model with assumptions of linearity) was clearly outperformed by random forest and extreme gradient boosting (XGBoost), which had out-of-sample R²values ranging between 0.80 and 0.88, depending on the time horizon. In addition, feature importance and partial dependence analysis demonstrated the marginal and interaction effects on biomethane of selected biowaste inputs. For instance, food waste co-digested with percolate were shown to have strong positive interaction effects. One implication of this study is that XGBoost and random forest algorithms applied to industrial-scale ACoD data provide dependable prediction results and may be a useful complement for experimental and mechanistic/theoretical models of anaerobic digestion, especially where detailed substrate characterization is difficult. However, these models have limitations, and suggestions for deriving additional value from these methods are proposed.

Dynamic shifts within volatile fatty acid-degrading microbial communities indicate process imbalance in anaerobic digesters

Buildup of volatile fatty acids (VFAs) in anaerobic digesters (ADs) often results in acidification and process failure. Understanding the dynamics of microbial communities involved in VFA degradation under stable and overload conditions may help optimize anaerobic digestion processes. In this study, five triplicate mesophilic completely mixed AD sets were operated at different organic loading rates (OLRs; 1-6 g chemical oxygen demand [COD] L_R^-1day^-1), and changes in the composition and abundance of VFA-degrading microbial communities were monitored using amplicon sequencing and taxon-specific quantitative PCRs, respectively. AD sets operated at OLRs of 1-4 g COD L_R^-1day^-1 were functionally stable throughout the operational period (120 days) whereas process instability (characterized by VFA buildup, pH decline, and decreased methane production rate) occurred in digesters operated at ≥ 5 g COD L_R^-1day^-1. Though microbial taxa involved in propionate (Syntrophobacter and Pelotomaculum) and butyrate (Syntrophomonas) degradation were detected across all ADs, their abundance decreased with increasing OLR. The overload conditions also inhibited the proliferation of the acetoclastic methanogen, Methanosaeta, and caused a microbial community shift to acetate oxidizers (Tepidanaerobacter acetatoxydans) and hydrogenotrophic methanogens (Methanoculleus). This study's results highlight the importance of operating ADs with conditions that promote the maintenance of microbial communities involved in VFA degradation.

Application of IWA Anaerobic Digestion Model No. 1 to simulate butyric acid, propionic acid, mixed acid, and ethanol type fermentative systems using a variable acidogenic stoichiometric approach

IWA Anaerobic Digestion Model No. 1 (ADM1) is the most widely recognised and popular mathematical model for anaerobic digestion processes. However, the application of ADM1 to acidogenic fermentation is limited by its use of constant stoichiometry to describe the formation of products via carbohydrate fermentation. This study presents a modification of ADM1 using a variable acidogenic stoichiometric approach in which the hydrogen partial pressure (p_H2) and pH are used to predict and regulate the acidogenic process. The fermentation of ethanol and its kinetics were introduced into the model structure. Experimental data from mixed acid-type fermentation in a 28.4 L anaerobic baffled reactor (ABR) fed with a sucrose solution with a chemical oxygen demand of 4000 mg L^-1 were used to calibrate the model parameters. Two case studies involving continuous ethanol-type fermentation in an ABR and a continuous stirring tank reactor (CSTR) were used to validate the approach. The modified model achieved good predictions of the experimental data collected from butyric acid, propionic acid, mixed acid, and ethanol-type fermentation in the ABR and CSTR using the standard ADM1 parameter values without any parameter fitting beyond implementation of the variable acidogenic stoichiometry. The p_H2 and pH thresholds in butyric acid, propionic acid, mixed acid, and ethanol-type fermentation could be predicted using this model, which was shown to be a valid mathematical tool for the regulation of fermentation type.

A compilation and bioenergetic evaluation of syntrophic microbial growth yields in anaerobic digestion

A compilation and analysis of experimentally determined microbial growth yields for syntrophic volatile fatty acid (VFA), lactate oxidisers and methanogens in anaerobic digestion (AD) systems is presented. Only studies based on experimental determinations or sound model-to-data fitting that specifically address parameter identifiability, have been considered. The experimentally determined values are compared and discussed with estimations based on bioenergetic correlations. Only for acetoclastic methanogens the experimentally determined microbial yields appear in good consistency with bioenergetic estimations. For syntrophic microbial groups, the experimetal yield values reported appear much higher than those expected from the low amount of metabolic energy available. These large deviations imply either inaccuracy on the microbial biomass quantification methods or that the syntrophic interspecies electron transfer occurs under mechanisms, or hydrogen equivalent intermediate activities, much below those ever observed in methanogenic environments. In addition, the microbial growth yield values most widely adopted in AD model applications (those reported in the IWA Anaerobic Digestion Model No. 1 (ADM1)) are even higher than the experimental determinations from literature. It is therefore proposed that microbial growth yield values should be restricted by the maximum harvestable ATP calculated through a detailed bioenergetic pathway analysis. Model simulations with different parameter configurations for different yield sources (default ADM1, experimentally determined and bioenergetically estimated values) displayed low sensitivity of the simulations with respect to the yield values as long as the maximum specific microbial growth rate (μ_max) remain the same. This suggests that model calibrations could target the accuracy of μ_max maintaining the bioenergetic upper limit for microbial growth yields.

Influence of Pre-Hydrolysis on Sewage Treatment in an Up-Flow Anaerobic Sludge BLANKET (UASB) Reactor: A Review

The up-flow anaerobic sludge blanket (UASB) process has emerged as a promising high-rate anaerobic digestion technology for the treatment of low- to high-strength soluble and complex wastewaters. Sewage, a complex wastewater, contains 30–70% particulate chemical oxygen demand (CODP). These particulate organics degrade at a slower rate than the soluble organics found in sewage. Accumulation of non-degraded suspended solids can lead to a reduction of active biomass in the reactor and hence a deterioration in its performance in terms of acid accumulation and poor biogas production. Hydrolysis of the CODP in sewage prior to UASB reactor will ensure an increased organic loading rate and better UASB performance. While single-stage UASB reactors have been studied extensively, the two-phase full-scale treatment approach (i.e., a hydrolysis unit followed by an UASB reactor) has still not yet been commercialized worldwide. The concept of treating sewage containing particulate organics via a two-phase approach involves first hydrolyzing and acidifying the volatile suspended solids without losing carbon (as methane) in the first reactor and then treating the soluble sewage in the UASB reactor. This work reviews the available literature to outline critical findings related to the treatment of sewage with and without hydrolysis before the UASB reactor.

Effects of endogenous inhibitors on the evolution of antibiotic resistance genes during high solid anaerobic digestion of swine manure

Livestock manure is a reservoir of antibiotic resistance genes (ARGs). The endogenous inhibitors that emerge during high solid anaerobic digestion (HSAD) greatly influence the bioprocess performance and the ARGs. The effect of endogenous inhibitors including volatile fatty acids (VFAs) and free ammonia (FA) on the ARG occurrences during HSAD of swine manure was investigated in this study. The ARG properties during HSAD (8%-14% total solids (TS)) largely differed from the low TS control (4%). The endogenous inhibitors and microbial communities greatly contributed to the three-phase changes in ARGs. The concentrations of VFAs and abundances of Proteobacteria and intI1 were correlated with the changes in ARGs. FA inhibition and VFA accumulation (especially propionate) delayed and restricted the decline of ARGs. The relatively slow rate of changes in ARGs and high ARGs in the end product suggested the high risk of the HSAD digestate for land application.