Modelling of anaerobic digestion of microalgae biomass: Effect of overloading perturbation

Anaerobic digestion (AD) of microalgae is an intriguing approach for bioenergy production. The scaling-up of AD presents a significant challenge due to the systematic efficiency losses related to process instabilities. To gain a comprehensive understanding of AD behavior, this study assessed a modified version of the anaerobic digestion model No1 (ADM1) + Contois kinetics to represent microalgae AD impacted by overloading. To this end, two new inhibition functions were implemented: inhibition by acetate for acidogenesis/acetogenesis and total volatile fatty acids for hydrolysis. This proposed ADM1 modification (including Contois kinetics) simulated AD behavior during the stable, disturbed and recovery periods, showing that the inhibition functions described in the original ADM1 cannot explain the AD performance under one of the most common perturbations at industrial scale (overloading). The findings underscore the importance of refining the inhibitions present in original ADM1 to better capture and predict the complexities of microalgae AD against overloading.

Modeling key intermediates during anaerobic digestion of lipid rich kitchen waste with an extended ADM1

Quantitative dynamics of the key intermediates, gases and carbohydrates during anaerobic digestion of different lipid rich kitchen waste and lipid rich model kitchen waste were modeled. Six batch reactors loaded with 25 gVS  l- 1 ( ∼ 39  g O 2  l- 1 ) kitchen waste and model kitchen waste during a batch experiment were considered in simulation. Observed dynamics of carbohydrates, volatile organic acids and gases were described by an extended benchmark simulation model no. 2 (BSM2). In this study the extended BSM2 included a more detailed β -oxidation for prediction of caproic acid. Furthermore, the extensions included carbohydrate digestion with an additional intermediate before propionic acid was released. In addition, a novel simplification approach for initial pH estimation was successfully applied. For parameter estimation a Markov Chain Monte Carlo method was used to obtain parameter distributions. With the presented model it was possible even with no calibrated data to predict point of times of intermediates maxima and propionic acid with relative stable concentration over several days for kitchen waste.

Thermally enhanced solid-liquid separation process in food waste biorefinery: modelling the anaerobic digestion of solid residues

The biochemical valorization potential of food waste (FW) could be exploited by extracting decreasing added-value bio-based products and converting the final residues into energy. In this context, multi-purpose and versatile schemes integrating thermal and biochemical conversion processes will play a key role. An upstream thermal pretreatment + solid-liquid separation unit was here proposed to optimize the conversion of the liquid fraction of FW into valuable chemicals through semi-continuous fermentation process, and the conversion of the residual solid fraction into biomethane through anaerobic digestion. The solid residues obtained after thermal pretreatment presented a higher soluble COD fraction, which resulted in higher methane production with respect to the raw residues (0.33 vs. 0.29 Nm3CH4 kg-1VSfed) and higher risk of acidification and failure of methanogenesis when operating at lower HRT (20d). On the contrary, at HRT = 40 d, the pretreatment did not affect the methane conversion rates and both tests evidenced similar methane productions of 0.33 Nm3CH4 kg-1VSfed. In the reactor fed with pretreated residue, the association of hydrogenotrophic methanogens with syntrophic bacteria prevented the acidification of the system. Modelling proved the eligibility of the FW solid residues as substrates for anaerobic digestion, given their small inert fractions that ranged between 0% and 30% of the total COD content.

Analysis of biogas production from sewage sludge combining BMP experimental assays and the ADM1 model

The Anaerobic Digestion Model No. 1 (ADM1) was employed to simulate methane (CH4) production in an anaerobic reactor (AR), and the associated bench-scale biochemical methane potential (BMP) assay, having sewage sludge (SWS) from a municipal wastewater treatment plant (WWTP) as feedstock. The SWS presented the following physical-chemical characteristics: pH (7.4-7.6), alkalinity (2,382 ± 100 mg CaCO3 L-1), tCOD (21,903 ± 1,000 mg L-1), TOC (895 ± 100 mg L-1), TS, TVS, and VSS (2.0%, 1.1%, and 0.8%, respectively). The BMP assay was conducted in six replicates under anaerobic mesophilic conditions (37 ± 0.1°C) for 11 days with a CH4 yield registered of 137.6 ± 6.39 NmL CH4 or 124 ± 6.72 CH4 g-1 VS-1. When the results obtained with the BMP bench-scale reactors were compared to the output generated with computational data by the ADM1 model having as input data the same initial sewage tCOD, similar cumulative CH4 production curves were obtained, indicating the accuracy of the ADM1 model. This approach allowed the characterization of the sludge and estimation of its biogas production potential. The combination of BMP assays, experimental data, and ADM1 model simulations provided a framework for studying anaerobic digestion (AD) processes.

Modeling a propionate-oxidizing syntrophic coculture using thermodynamic principles

A coculture of Syntrophobacter fumaroxidans and Methanospirillum hungatei was modeled using four biokinetic models, which only differed by the functions used to describe the growth yields (dynamic or constant) and the hydrogen inhibition function (noncompetitive or based on thermodynamics). First, a batch experiment was used to train the model and analyze the fitted parameters. Two fitting procedures were followed by minimizing the error on different indicators. Second, a chemostat experiment was used as a test data set to assess the predictive power of the models. Overall, the four models were able to accurately fit the train data set following both fitting procedures. However, some parameters fitted with the ADM1-like model differed significantly from values reported in the literature and were dependent on the fitting procedure. When applied to the test data set it systematically resulted in positive Gibbs free energy changes values for propionate oxidation, in contradiction with the second law of thermodynamics. On the opposite, the parameters fitted with model including both a thermodynamic-based inhibition function and a dynamic computation of growth yields were more consistent with values reported in the literature and repeatable whatever the fitting procedure. The results highlight the potential of implementing thermodynamic-based functions in biokinetic models.

Considering syntrophic acetate oxidation and ionic strength improves the performance of models for food waste anaerobic digestion

Current mechanistic anaerobic digestion (AD) models cannot accurately represent the underlying processes occurring during food waste (FW) AD. This work presents an update of the Anaerobic Digestion Model no. 1 (ADM1) to provide accurate estimations of free ammonia concentrations and related inhibition thresholds, and model syntrophic acetate oxidation as acetate-consuming pathway. A modified Davies equation predicted NH₃ concentrations and pH more accurately, and better estimated associated inhibitory limits. Sensitivity analysis results showed the importance of accurate disintegration kinetics and volumetric mass transfer coefficients, as well as volatile fatty acids (VFAs) and hydrogen uptake rates. In contrast to the default ADM1, the modified ADM1 could represent methane production and VFA profiles simultaneously (particularly relevant for propionate uptake). The modified ADM1 was also able to predict the predominant acetate-consuming and methane-producing microbial clades. Modelling results using data from reactors dosed with granular activated carbon showed that this additive improves hydrogen uptake.

Systematic simplification of the Anaerobic Digestion Model No. 1 (ADM1) - Laboratory experiments and model application

Due to a limited number of available measurements on agricultural biogas plants, established process models, such as the Anaerobic Digestion Model No. 1 (ADM1), are rarely applied in practise. To provide a reliable basis for model-based monitoring and control, different model simplifications of the ADM1 were implemented for process simulation of semi-continuous anaerobic digestion experiments using agricultural substrates (maize silage, sugar beet silage, rye grain and cattle manure) and industrial residues (grain stillage). Individual model structures enable a close depiction of biogas production rates and characteristic intermediates (ammonium nitrogen, propionic and acetic acid) with equal accuracy as the original ADM1. The impact of different objective functions and standard parameter values on parameter estimates of first-order hydrolysis constants and microbial growth rates were evaluated. Due to the small number of required model parameters and suitable system characteristics, simplified model structures show clear advantages for practical application on agricultural biogas plants.

Systematic simplification of the Anaerobic Digestion Model No. 1 (ADM1) - Model development and stoichiometric analysis

Rigorous process models provide a reliable basis for model-based monitoring and control of anaerobic digestion plants. Due to the complex model structure and non-linear system characteristics, the established Anaerobic Digestion Model No. 1 (ADM1) is rarely applied in industrial plant operation. The present investigation proposes a systematic procedure for successive model simplification and presents the description of five model variants of a mass-based ADM1. Individual model structures greatly differ in their number of implemented process phases, characteristic components and required parameters. Simplified model variants combine nutrient degradation and biogas formation based on first-order sum reactions, whereas complex model structures describe individual degradation pathways and intermediates during acido- and acetogenesis. Characteristic features of the derived model structures as well as the stoichiometric methane potentials and microbial biomass yields of the underlying degradation pathways of individual model variations are evaluated and discussed in detail.

Modeling and Simulation of Biogas Production in Full Scale with Time Series Analysis

Future biogas plants must be able to produce biogas according to demand, which requires proactive feeding management. Therefore, the simulation of biogas production depending on the substrate supply is assumed. Most simulation models are based on the complex Anaerobic Digestion Model No. 1 (ADM1). The ADM1 includes a large number of parameters for all biochemical and physicochemical process steps, which have to be carefully adjusted to represent the conditions of a respective full-scale biogas plant. Due to a deficiency of reliable measurement technology and process monitoring, nearly none of these parameters are available for full-scale plants. The present research investigation shows a simulation model, which is based on the principle of time series analysis and uses only historical data of biogas formation and solid substrate supply, without differentiation of individual substrates. The results of an extensive evaluation of the model over 366 simulations with 48-h horizon show a mean absolute percentage error (MAPE) of 14–18%. The evaluation is based on two different digesters and demonstrated that the model is self-learning and automatically adaptable to the respective application, independent of the substrate’s composition.

Diversity and Abundance of Microbial Communities in UASB Reactors during Methane Production from Hydrolyzed Wheat Straw and Lucerne

The use of straw for biofuel production is encouraged by the European Union. A previous study showed the feasibility of producing biomethane in upflow anaerobic sludge blanket (UASB) reactors using hydrolyzed, steam-pretreated wheat straw, before and after dark fermentation with Caldicellulosiruptor saccharolyticus, and lucerne. This study provides information on overall microbial community development in those UASB processes and changes related to acidification. The bacterial and archaeal community in granular samples was analyzed using high-throughput amplicon sequencing. Anaerobic digestion model no. 1 (ADM1) was used to predict the abundance of microbial functional groups. The sequencing results showed decreased richness and diversity in the microbial community, and decreased relative abundance of bacteria in relation to archaea, after process acidification. Canonical correspondence analysis showed significant negative correlations between the concentration of organic acids and three phyla, and positive correlations with seven phyla. Organic loading rate and total COD fed also showed significant correlations with microbial community structure, which changed over time. ADM1 predicted a decrease in acetate degraders after a decrease to pH ≤ 6.5. Acidification had a sustained effect on the microbial community and process performance.

Effects of low pH conditions on decay of methanogenic biomass

Acidic failure is relatively common in anaerobic digesters that receive readily biodegradable food wastes at high loading. Under low pH conditions, the activity of methanogenic biomass decreases resulting in complete failure of the digestion process. In this experimental study, we demonstrated that one of the causes for the digester failure under low pH conditions is due to accelerated decay of methanogenic biomass. When enriched acetate degrading methanogens were exposed to a low pH environment (pH = 5.1 with phosphoric acid) in a batch experiment without external substrate, the specific decay rate was observed to increase as much as 10 times of that at pH 7.0. The specific decay rate for formate degrader was also found to increase under low pH conditions whilst the fermentative microorganisms in the cultures appeared to be tolerant to low pH conditions. A Propidium Mono-Azide-quantitative Polymerase Chain Reaction (PMA-qPCR) analysis revealed that the archaeal biomass dominated by methanogens dropped by 71-79% from the initial concentration after 6 days of the acidic batch experiment whilst the bacterial biomass dominating acidogens decreased by only 25%. The decrease in the number of living cells in the batch experiments at different pH was monitored with time to determine a correlation between decay rate and incubation pH.

Exploitation of the ADM1 in a XXI century wastewater resource recovery facility (WRRF): The case of codigestion and thermal hydrolysis

The aim of this study is to test the capability of the anaerobic digestion model n1 (ADM1) to reproduce data from full-scale digesters operated in a wastewater resource recovery facility (WRRF) where both thermal hydrolysis and codigestion with industrial waste are carried out. Furthermore, the potential uses of the model in a WRRF are also described, with particular relevance for plant engineers/operators. The model capability was calibrated and validated with data from full-scale digesters from the Mapocho-Trebal WRRF (Biofactoría) in Santiago, Chile. A success simulation rate, defined as the percentage of experimental values of a certain variable that lies within the simulation band given by a simulation tolerance established by the user/operator, was established to test the capability of the model as objectively as possible. Regarding the full-scale digester fed with thermally pretreated mixed sludge, success rates of 65% for biogas production and 60-100% for other variables were achieved. Regarding the full-scale digester in codigestion mode, the model had a success rate of approximately 60% for predicting the biogas flow for the whole evaluation period, while for the other variables, values between 70 and 100% were attained. The lowest success rates were observed for the volatile fatty acid (VFA) concentration in the digestate. Despite the lack of available data and the number of assumptions that had to be made, the model was demonstrated to be capable of reproducing the behavior of the full-scale reactors. A proper, up-to-date, calibrated and validated model can aid in the decision-making process in a WRRF, for instance, in determining some unmeasured inlet conditions, in improving the resilience of the process and in managing the incorporation of a new cosubstrate into the plant, among others.

Application of a mathematical model to predict simultaneous reactions in anaerobic plug-flow reactors as a primary treatment for constructed wetlands

Anaerobic digestion technologies offer a set of advantages when they are implemented as a primary treatment phase prior to the use of constructed wetland systems in low cost wastewater facilities. The aim of this study is to describe a model capable of reflecting the complex functioning of anaerobic lagoons, subject to continuous flux in the feed pipe, taking into account that physicochemical properties are subject to a concentration gradient and biochemical ones to simultaneous reactions which depend on each other. Based on both Stokes and advection-diffusion-reaction equations, the proposed model includes twenty-one variables to describe hydraulic, physical, biochemical and physicochemical characteristics that take place in different points of the system and at different moments of time. Drawn up by the International Water Association, the anaerobic digestion model ADM1 is included for the purpose of incorporating the anaerobic processes in the calculation. The finite element method was used to solve the nonlinear, second order partial differential equations of the model. The calculation strategy was designed using a flowchart. Using the open-source FreeFem++ software, a simulation of the mathematical model, in bi-dimensional space, is presented to demonstrate the dynamic behaviour of the proposed model. This yields essential information about the performance of the substrate, cells, and the biochemical reaction products in each of the points within the reactor. Simulations show the potential of this methodology to carry out studies of the behaviour of each of the variables contemplated in the model, as well as comparative studies of the various possible options. In addition, this methodology can be used to help modify the behaviour of the variables based on digester geometry and the boundary values the system is subject to. From the results, it can be concluded that the proposed methodology can be a useful tool for calculating and designing the aforementioned synergistic systems of anaerobic digester plug-flow reactors and constructed wetlands.

Modelling hydrolysis: Simultaneous versus sequential biodegradation of the hydrolysable fractions

Hydrolysis is considered the limiting step during solid waste anaerobic digestion (including co-digestion of sludge and biosolids). Mechanisms of hydrolysis are mechanistically not well understood with detrimental impact on model predictive capability. The common approach to multiple substrates is to consider simultaneous degradation of the substrates. This may not have the capacity to separate the different kinetics. Sequential degradation of substrates is theoretically supported by microbial capacity and the composite nature of substrates (bioaccessibility concept). However, this has not been experimentally assessed. Sequential chemical fractionation has been successfully used to define inputs for an anaerobic digestion model. In this paper, sequential extractions of organic substrates were evaluated in order to compare both models. By removing each fraction (from the most accessible to the least accessible fraction) from three different substrates, anaerobic incubation tests showed that for physically structured substrates, such as activated sludge and wheat straw, sequential approach could better describe experimental results, while this was less important for homogeneous materials such as pulped fruit. Following this, anaerobic incubation tests were performed on five substrates. Cumulative methane production was modelled by the simultaneous and sequential approaches. Results showed that the sequential model could fit the experimental data for all the substrates whereas simultaneous model did not work for some substrates.

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.

Anaerobic co-digestion of food waste and waste activated sludge: ADM1 modelling and microbial analysis to gain insights into the two substrates' synergistic effects

The reasons for the acidification problem affecting Food Waste (FW) anaerobic digestion were explored, combining the outcomes of microbiological data (FISH and CARD-FISH) and process modelling, based on the Anaerobic Digestion Model n°1 (ADM1). Long term semi continuous experiments were carried out, both with sole FW and with Waste Activated Sludge (WAS) as a co-substrate, at varying operational conditions (0.8-2.2 g VS L^-1 d^-1) and FW / WAS ratios. Acidification was observed along FW mono-digestion, making it necessary to buffer the digesters; ADM1 modelling and experimental results suggested that this phenomenon was due to the methanogenic activity decline, most likely related to a deficiency in trace elements. WAS addition, even at proportions as low as 10% of the organic load, settled the acidification issue; this ability was related to the promotion of the methanogenic activity and the consequent enhancement of acetate consumption, rather than to WAS buffering capacity. The ability of the ADM1 to model processes affected by low microbial activity, such as FW mono-digestion, was also assessed. It was observed that the ADM1 was only adequate for digestions with a high activity level for both bacteria and methanogens (FISH/CARD-FISH ratio preferably >0.8) and, under these conditions, the model was able to correctly predict the relative abundance of both microbial populations, extrapolated from FISH analysis.

Modified anaerobic digestion model No.1 (ADM1) for modeling anaerobic digestion process at different ammonium concentrations

Anaerobic digestion (AD) is an established method for sustainable energy production. Anaerobic digestion model No.1 (ADM1) was used to simulate methane production (MP) and volatile fatty acid (VFA) concentrations at different ammonium concentrations. In accordance with the incomplete description of several biochemical reactions and the omission of several reaction processes, ADM1 was modified with the consideration of acetic acid inhibition and valeric acid existence. ADM1_ac (ADM1 added acetic acid inhibition) could obtain better simulation accuracy of MP (goodness-of-fit value = 0.945), and VFA concentrations (goodness-of-fit values > 0.39) were all higher than ADM1_original, but cannot explain the valeric acid production. ADM1_va (ADM1 added valeric acid existence) could achieve better simulation of valeric acid (achieving a breakthrough of zero), nevertheless the accuracy of propionic and butyric acids was poorer than ADM1_ac with differences between experimental and simulation values were 5%-10% lower. With both factors coordinated, MP and VFA concentrations could be simulated accurately by ADM1_ac_va (ADM1 added acetic acid inhibition and valeric acid existence), with the highest goodness-of-fit values (>0.85). The results of a verification experiment with ADM1_ac_va simulation further indicated that acetic acid inhibition and valeric acid as new component were both important in ADM1. PRACTITIONER POINTS: ADM1_ac could simulate MP and acetate, propionate and butyrate concentrations better. ADM1_va could explain the valerate production during AD of glucose. ADM1_ac_va could simulate AD process quite accurately, with the highest goodness-of-fit values (>0.85). Acetate inhibition and valerate existence were both important and should be considered in ADM1.

Modeling long-term performance of full-scale anaerobic expanded granular sludge bed reactor treating confectionery industry wastewater

Production and consumption of confectionery products, such as chocolate, sugar, and cookies, have increased worldwide. Thus, management and treatment of confectionery effluents, as one of the most important agro-industrial wastewaters, become essential. Confectionery industries produce high-strength and highly biodegradable wastewaters that are appropriate for biological treatment prior to discharge. In this study, long-term dynamic performance of a full-scale anaerobic expanded granular sludge bed (EGSB) reactor treating confectionery effluent was simulated by using Anaerobic Digestion Model No. 1 (ADM1). Substrate fractionation was carried out based on the ADM1 state variables, and then, the model was calibrated with 300 days of operation data. The calibrated model could capture the dynamic performance of the anaerobic reactor for a long validation period of 500 days. Although the reactor was operated under highly fluctuating volumetric loading rates (VLR) between 0.2 and 5 kg chemical oxygen demand (COD)/m³ day, the model results indicated medium to high prediction accuracy for effluent COD, methane generation, total volatile fatty acids (VFA), and pH parameters. Mean relative absolute errors for COD, methane flow, VFA, and pH parameter simulations were 22%, 16%, 29%, and 1%, respectively. The study presents the applicability of ADM1 for full-scale reactors treating industrial wastewaters.

On the Effect of Aqueous Ammonia Soaking Pre-Treatment on Continuous Anaerobic Digestion of Digested Swine Manure Fibers

(1) Background: The continuously increasing demand for renewable energy sources renders anaerobic digestion as one of the most promising technologies for renewable energy production. Due to the animal production intensification, manure is being used as the primary feedstock for most biogas plants. Their economical profitable operation, however, relies on increasing the methane yield from the solid fraction of manure, which is not so easily degradable. The solid fraction after anaerobic digestion, the so-called digested fibers, consists mainly of hardly biodegradable material and comes at a lower mass per unit volume of manure compared to the solid fraction before anaerobic digestion. Therefore, investigation on how to increase the biodegradability of digested fibers is very relevant. So far, Aqueous Ammonia Soaking (AAS), has been successfully applied on digested fibers separated from the effluent of a manure-fed, full-scale anaerobic digester to enhance their methane productivity in batch experiments. (2) Methods: In the present study, continuous experiments at a mesophilic (38 °C) CSTR-type anaerobic digester fed with swine manure first and a mixture of manure with AAS-treated digested fibers in the sequel, were performed. Anaerobic Digestion Model 1 (ADM1) previously fitted on manure fed digester was used in order to assess the effect of the addition of AAS-pre-treated digested manure fibers on the kinetics of anaerobic digestion process. (3) Results and Conclusions: The methane yield of AAS-treated digested fibers under continuous operation was 49–68% higher than that calculated in batch experiments in the past. It was found that AAS treatment had a profound effect mainly on the disintegration/hydrolysis rate of particulate carbohydrates. Comparison of the data obtained in the present study with the data obtained with AAS-pre-treated raw manure fibers in the past revealed that hydrolysis kinetics after AAS pre-treatment were similar for both types of biomasses.

Augmenting Biogas Process Modeling by Resolving Intracellular Metabolic Activity

The process of anaerobic digestion in which waste biomass is transformed to methane by complex microbial communities has been modeled for more than 16 years by parametric gray box approaches that simplify process biology and do not resolve intracellular microbial activity. Information on such activity, however, has become available in unprecedented detail by recent experimental advances in metatranscriptomics and metaproteomics. The inclusion of such data could lead to more powerful process models of anaerobic digestion that more faithfully represent the activity of microbial communities. We augmented the Anaerobic Digestion Model No. 1 (ADM1) as the standard kinetic model of anaerobic digestion by coupling it to Flux-Balance-Analysis (FBA) models of methanogenic species. Steady-state results of coupled models are comparable to standard ADM1 simulations if the energy demand for non-growth associated maintenance (NGAM) is chosen adequately. When changing a constant feed of maize silage from continuous to pulsed feeding, the final average methane production remains very similar for both standard and coupled models, while both the initial response of the methanogenic population at the onset of pulsed feeding as well as its dynamics between pulses deviates considerably. In contrast to ADM1, the coupled models deliver predictions of up to 1,000s of intracellular metabolic fluxes per species, describing intracellular metabolic pathway activity in much higher detail. Furthermore, yield coefficients which need to be specified in ADM1 are no longer required as they are implicitly encoded in the topology of the species’ metabolic network. We show the feasibility of augmenting ADM1, an ordinary differential equation-based model for simulating biogas production, by FBA models implementing individual steps of anaerobic digestion. While cellular maintenance is introduced as a new parameter, the total number of parameters is reduced as yield coefficients no longer need to be specified. The coupled models provide detailed predictions on intracellular activity of microbial species which are compatible with experimental data on enzyme synthesis activity or abundance as obtained by metatranscriptomics or metaproteomics. By providing predictions of intracellular fluxes of individual community members, the presented approach advances the simulation of microbial community driven processes and provides a direct link to validation by state-of-the-art experimental techniques.

Competitive dynamics of anaerobes during long-term biological sulfate reduction process in a UASB reactor

To reveal the long-term competitive dynamics of anaerobes in anaerobic bioreactors with sulfate reduction, a comprehensive structured mathematical model was designed for an extension of the Anaerobic Digestion Model No. 1 (ADM1). Sulfate reduction bacteria (SRB) were categorized into acetogenic-likewise SRB (ASRB) and methanogenic-likewise SRB (MSRB). Experimental data from 329 days of continuous operation of a laboratory-scale upflow anaerobic sludge bed (UASB) reactor was used for model calibration and validation. Results show that the model has a good agreement with experimental data and that three stages including the MPA dominant, stalemate and SRB dominant stages were clearly appeared throughout the whole competition period. The model was capable of predicting the long-term dynamic competition of sulfidogens and methanogens for electrons. This could explain a long-term of over 200 days needed for the SRB out-competing the MPA, and support speculation that the SRB could finally out-compete both the AcB and the MPA.

Modeling the fate of organic nitrogen during anaerobic digestion: Development of a bioaccessibility based ADM1

Simulating the fate of nitrogen during anaerobic digestion is required to predict the characteristics of digestates and to improve their exploitation for agricultural uses. The aim of this study was to develop a modified ADM1 model that includes bioaccessibility-based fractionation to accurately simulate the fate of nitrogen during anaerobic digestion. To this end, two complementary approaches were used: (i) changes in the bioaccessibility of protein and non-protein compounds were assessed on eight substrates during anaerobic digestion in batch experiments using the "EPS" fractionation method; (ii) experimental results were used to develop a bio-kinetic model based on anaerobic digestion model n°1. This new model incorporates bioaccessibility-based fractionation in its input state variables. The model was successfully calibrated and model evaluation showed that predicted methane production, ammonium production and changes in protein and non-protein bioaccessibility during anaerobic digestion were accurate.

ADM1 based mathematical model of trace element complexation in anaerobic digestion processes

In this study, a new model based on anaerobic digestion model no.1 (ADM1) approach has been proposed to simulate trace elements (TEs) complexation, precipitation and their effect on the anaerobic batch methane production. TEs complexation reactions with VFAs and EDTA have been incorporated in an extended ADM1 model which considers TE precipitation/dissolution reactions as well as biodegradation processes. The kinetic model tracks the dynamics of 90 state variables which constitute the components of the proposed anaerobic digestion (AD) model. The incorporation of the complexation reactions required the definition of new inorganic components (EDTA species) and new complexation process rates in the ADM1 framework. The charge balance was modified accordingly to consider the effects of the additional components. The new model is able to predict: a) the effect of TE-EDTA/VFA complexation on methane production, and b) the effect of the initial calcium and magnesium concentrations on process performance.

Modified Anaerobic Digestion Model No. 1 for modeling methane production from food waste in batch and semi-continuous anaerobic digestions

A modified Anaerobic Digestion Model No. 1 (ADM1) with optimized kinetic parameters was presented to model methane production in the anaerobic digestion of food waste. Experimental data from batch and semi-continuous fermentations were used to calibrate and verify the model. Modified ADM1 simulation was carried out using AQUASIM 2.0 software. Sensitivity analysis was used to identify and evaluate the most sensitive kinetic parameters during biogas production. The decay constant of microorganisms, the disintegration constant, the hydrolysis constant of carbohydrates, the Monod maximum specific substrate uptake rate, and the half-saturation constants affected biogas production significantly. The optimized values of these parameters were 0.001, 0.16, 3, 1 and 0.23, respectively. Optimization results were validated using batch and semi-continuous experiments. The modified ADM1 well-predicted methane production, with R² values for the validation experiments all above 90%. These results can be used as basic data to simulate methane production in full-scale reactors.

Ammonia Inhibition of Anaerobic Volatile Fatty Acid Degrading Microbial Communities

Ammonia inhibition is an important reason for reactor failures and economic losses in anaerobic digestion. Its impact on acetic acid degradation is well-studied, while its effect on propionic and butyric acid degradation has received little attention and is consequently not considered in the Anaerobic Digestion Model No. 1 (ADM1). To compare ammonia inhibition of the degradation of these three volatile fatty acids (VFAs), we fed a mixture of them as sole carbon source to three continuous stirred tank reactors (CSTRs) and increased ammonium bicarbonate concentrations in the influent from 52 to 277 mM. The use of this synthetic substrate allowed for the determination of degradation efficiencies for the individual acids. While butyric acid degradation was hardly affected by the increase of ammonia concentration, propionic acid degradation turned out to be even more inhibited than acetic acid degradation with degradation efficiencies dropping to 31 and 65% for propionic and acetic acid, respectively. The inhibited reactors acclimatized and approximated pre-disturbance degradation efficiencies toward the end of the experiment, which was accompanied by strong microbial community shifts, as observed by amplicon sequencing of 16S rRNA genes and terminal restriction fragment length polymorphism (T-RFLP) of mcrA genes. The acetoclastic methanogen Methanosaeta was completely replaced by Methanosarcina. The propionic acid degrading genus Syntrophobacter was replaced by yet unknown propionic acid degraders. The butyric acid degrading genus Syntrophomonas and hydrogenotrophic Methanomicrobiaceae were hardly affected. We hypothesized that the ammonia sensitivity of the initially dominating taxa Methanosaeta and Syntrophobacter led to a stronger inhibition of the acetic and propionic acid degradation compared to butyric acid degradation and hydrogenotrophic methanogenesis, which were facilitated by the ammonia tolerant taxa Syntrophomonas and Methanomicrobiaceae. We implemented this hypothesis into a multi-taxa extension of ADM1, which was able to simulate the dynamics of both microbial community composition and VFA concentration in the experiment. It is thus plausible that the effect of ammonia on VFA degradation strongly depends on the ammonia sensitivity of the dominating taxa, for syntrophic propionate degraders as much as for acetoclastic methanogens.

ADM1 based mathematical model of trace element precipitation/dissolution in anaerobic digestion processes

Due to the complex biogeochemistry of trace elements (TEs, e.g. Fe, Ni and Co) in anaerobic digestion processes, their role and fate is poorly understood. Challenging, time consuming and low detection limits of analytical procedures necessitate recruitment of mathematical models. A dynamic mathematical model based on anaerobic digestion model no.1 (ADM1) has been proposed to simulate the effect of TEs. New chemical equilibrium association/dissociation and precipitation/dissolution reactions have been implemented to determine TE bioavailability and their effect on anaerobic digestion. The model considers interactions with inorganic carbonate (HCO₃^- and CO₃^2-), phosphate (PO₄^3-, HPO₄^2-, H₂PO₄^-) and sulfide (HS^- and S^2-). The effect of deficiency, activation, inhibition and toxicity of TEs on the biochemical processes has been modelled based on a dose-response type inhibition function. The new model can predict: the dynamics of TEs (among carbonate, sulfide and phosphate); the starvation of TEs; and the effect of initial sulfur-phosphorus ratio in an in-silico batch anaerobic system.

Modeling of anaerobic digestion of slaughterhouse wastes after thermal treatment using ADM1

According to the European legislation, thermal treatment of category 2 slaughterhouse by-products at 140 °C, 4-5 bar for 20 min is obligatory for their hygienization prior to disposal. This process is known as "rendering". The product of the rendering process is rich in lipids and proteins making it an appropriate feedstock for biogas plants. The mathematical modeling of biogas production from slaughterhouse wastes after the rendering process has been studied adjusting the anaerobic digestion model (ADM1). For this purpose, two mesophilic (38-39 °C) continuous stirred tank reactors (CSTRs) have been operated in parallel under a hydraulic retention time of 21.5 ± 2.14 d, while the organic load was increased from 50 to 149.6 g COD L^-1. Recirculation of the mixed liquor suspended solids (MLSS) took place in one of the CSTRs, resulting in a different solids' concentration in it. The ADM1 was calibrated by estimating key kinetic parameters, such as the maximum specific consumption rate constant and the half-saturation constants of volatile fatty acids and verified. The degradation kinetics of this type of waste seemed to be faster, as a result of its emulsification through rendering, while the coefficient yields of the acidogens were lower than the default values of ADM1. The structure of the model was proven suitable for predicting the response of both bioreactors under small or medium step transitions, but not for abrupt impulse disturbances in the organic loading rate.

Model-based design of a software sensor for real-time diagnosis of the stability conditions in high-rate anaerobic reactors - Full-scale application to Internal Circulation technology

Internal Circulation (IC) anaerobic systems are especially suitable when plant designs that involve both small footprints and high organic loading rates (>25 kg COD m^-3 d^-1) are required. However, given that operating anaerobic processes at high organic loads increases their vulnerability to external disturbances, real-time indicators of the stability conditions become particularly pertinent for IC reactors. This paper addresses the design and full-scale validation of a software sensor that uses only feeding flow-rate and biogas flow-rate measurements to classify the operating conditions of the reactor as "strongly", "moderately" or "weakly" stable. A simulation-based procedure was used to design the software sensor and configure its parameters. Then, the performance of the software sensor was tested under real conditions in a full-scale IC reactor of 1679 m³ installed in a recycled paper mill (RPM).

Intermittent fasting for microbes: how discontinuous feeding increases functional stability in anaerobic digestion

BACKGROUND

Demand-driven biogas production could play an important role for future sustainable energy supply. However, feeding a biogas reactor according to energy demand may lead to organic overloading and, thus, to process failures. To minimize this risk, digesters need to be actively steered towards containing more robust microbial communities. This study focuses on acetogenesis and methanogenesis as crucial process steps for avoiding acidification. We fed lab-scale anaerobic digesters with volatile fatty acids under various feeding regimes and disturbances. The resulting microbial communities were analyzed on DNA and RNA level by terminal restriction fragment length polymorphism of the mcrA gene, 16S rRNA gene amplicon sequencing, and a [2-13C]-acetate assay. A modified Anaerobic Digestion Model 1 (ADM1) that distinguishes between the acetoclastic methanogens Methanosaeta and Methanosarcina was developed and fitted using experimental abiotic and biotic process parameters.

RESULTS

Discontinuous feeding led to more functional resilience than continuous feeding, without loss in process efficiency. This was attributed to a different microbial community composition. Methanosaeta dominated the continuously fed reactors, while its competitor Methanosarcina was washed out. With discontinuous feeding, however, the fluctuating acetic acid concentrations provided niches to grow and co-exist for both organisms as shown by transcription analysis of the mcrA gene. Our model confirmed the higher functional resilience due to the higher abundance of Methanosarcina based on its higher substrate uptake rate and higher resistance to low pH values. Finally, we applied our model to maize silage as a more complex and practically relevant substrate and showed that our model is likely transferable to the complete AD process.

CONCLUSIONS

The composition of the microbial community determined the AD functional resilience against organic overloading in our experiments. In particular, communities with higher share of Methanosarcina showed higher process stability. The share of these microorganisms can be purposefully increased by discontinuous feeding. A model was developed that enables derivation of the necessary feeding regime for a more robust community with higher share of Methanosarcina.

High-solids anaerobic digestion model for homogenized reactors

During high-solids anaerobic digestion (HS-AD) of the organic fraction of municipal solid waste (OFMSW), an important total solid (TS) removal occurs, leading to the modification of the reactor content mass/volume, in contrast to 'wet' anaerobic digestion (AD). Therefore, HS-AD mathematical simulations need to be approached differently than 'wet' AD simulations. This study aimed to develop a modelling tool based on the anaerobic digestion model 1 (ADM1) capable of simulating the TS and the reactor mass/volume dynamics in HS-AD of OFMSW. Four hypotheses were used, including the effects of apparent concentrations at high TS. The model simulated adequately HS-AD of OFMSW in batch and continuous mode, particularly the evolution of TS, reactor mass, ammonia and volatile fatty acids. By adequately simulating the reactor content mass/volume and the TS, the HS-AD model might bring further insight about potentially inhibitory mechanisms (i.e. NH₃ buildup and/or acidification) occurring in HS-AD of OFMSW.

Modelling of an anaerobic plug-flow reactor. Process analysis and evaluation approaches with non-ideal mixing considerations

This study shows the implementation of the Anaerobic Digestion Model (ADM1) in an anaerobic plug-flow reactor (PFR) with two approaches based on the use of consecutive continuous stirred tank reactors (CSTR) connected in serie for considering non-ideal mixing. The two-region (TR) model splits each CSTR into two regions, while the particulate retention (PR) model adds a retention parameter. The models were calibrated and validated based on experimental data from a bench-scale reactor treating cow manure. The PFR conventional model slightly outperformed the non-ideal mixing approaches. However, the PR model showed an increase in biomass retention time treating high solid content substrate. Biogas production was not sensitive to variations of the mixing parameters. The liquid fraction content was better represented by the PR model than the PFR and TR models. The study shows how reactor modelling is useful for monitoring and supervising biogas plants.

Modelling sulfate reduction in anaerobic digestion: Complexity evaluation and parameter calibration

A comparative analysis of five different structures of sulfate reduction (SR) models for anaerobic digestion (AD) was conducted to evaluate their accuracy to provide model developers and users with better information to decide on the optimum degree of complexity. The models evaluated differ in terms of the number/type of sulfate reducing bacterial activities considered based on the electron donors used. A systematic calibration of the evaluated models against a large set of experimental data was also conducted using a very recent parameter calibration method. Results indicate that a simple model incorporating both acetate utilizing and hydrogen utilizing sulfate reducing bacterial activities (the M_AH model) achieves a good balance between performance and complexity in terms of prediction errors against experimental data. All the models evaluated provided acceptable predictions except the model including only hydrogen utilizing sulfate reducing bacterial activity. More complex model structures are recommended only if required in specific experimental cases.

Modelling an industrial anaerobic granular reactor using a multi-scale approach

The objective of this paper is to show the results of an industrial project dealing with modelling of anaerobic digesters. A multi-scale mathematical approach is developed to describe reactor hydrodynamics, granule growth/distribution and microbial competition/inhibition for substrate/space within the biofilm. The main biochemical and physico-chemical processes in the model are based on the Anaerobic Digestion Model No 1 (ADM1) extended with the fate of phosphorus (P), sulfur (S) and ethanol (Et-OH). Wastewater dynamic conditions are reproduced and data frequency increased using the Benchmark Simulation Model No 2 (BSM2) influent generator. All models are tested using two plant data sets corresponding to different operational periods (#D1, #D2). Simulation results reveal that the proposed approach can satisfactorily describe the transformation of organics, nutrients and minerals, the production of methane, carbon dioxide and sulfide and the potential formation of precipitates within the bulk (average deviation between computer simulations and measurements for both #D1, #D2 is around 10%). Model predictions suggest a stratified structure within the granule which is the result of: 1) applied loading rates, 2) mass transfer limitations and 3) specific (bacterial) affinity for substrate. Hence, inerts (X_I) and methanogens (X_ac) are situated in the inner zone, and this fraction lowers as the radius increases favouring the presence of acidogens (X_su,X_aa, X_fa) and acetogens (X_c4,X_pro). Additional simulations show the effects on the overall process performance when operational (pH) and loading (S:COD) conditions are modified. Lastly, the effect of intra-granular precipitation on the overall organic/inorganic distribution is assessed at: 1) different times; and, 2) reactor heights. Finally, the possibilities and opportunities offered by the proposed approach for conducting engineering optimization projects are discussed.

Fast ADM1 implementation for the optimization of feeding strategy using near infrared spectroscopy

Optimization of feeding strategy is an essential issue of anaerobic co-digestion that can be greatly assisted with simulation tools such as the Anaerobic Digestion Model 1. Using this model, a set of parameters, such as the biochemical composition of the waste to be digested, its methane production yield and kinetics, has to be defined for each new substrate. In the recent years, near infrared analyses have been reported as a fast and accurate solution for the estimation of methane production yield and biochemical composition. However, the estimation of methane production kinetics requires time-consuming analysis. Here, a partial least square regression model was developed for a fast and efficient estimation of methane production kinetics using near infrared spectroscopy on 275 bio-waste samples. The development of this characterization reduces the time of analysis from 30 days to a matter of minutes. Then, biochemical composition and methane production yield and kinetics predicted by near infrared spectroscopy were implemented in a modified Anaerobic Digestion Model n°1 in order to simulate the performance of anaerobic digestion processes. This approach was validated using different data sets and was demonstrated to provide a powerful predictive tool for advanced control of anaerobic digestion plants and feeding strategy optimization.

Biomethane potential of food waste: modeling the effects of mild thermal pretreatment and digestion temperature

In order to enhance anaerobic biodegradability of food waste (FW), thermal pretreatment was applied. The effectiveness in terms of biodegradability extent and process rate improvement was investigated. To this aim, Biomethane Potential tests were carried out under mesophilic and thermophilic conditions. The IWA anaerobic digestion Model 1 (ADM1), a powerful tool for modeling the anaerobic digestion (AD) of different substrates, was implemented to predict the methane production. Disintegration constant (k_dis) and maximum acetate uptake rate (km_ac) were identified as the most sensitive parameters and were calibrated over the observed methane production. Pretreatment improvement was more evident in enhancing parameters related to the process rate, such as solubilization extent (+153%) and disintegration constant (+18%), rather than increasing substrate biodegradability. Thermophilic conditions proved to be effective in speeding up the whole AD process, since all the kinetics were significantly improved (disintegration rate increased up to fivefold). Furthermore, it was demonstrated that, after k_dis and km_ac calibration, default thermophilic ADM1 parameters can be suitable to model FW digestion.

Comparison of existing models to simulate anaerobic digestion of lipid-rich waste

Models for anaerobic digestion of lipid-rich waste taking inhibition into account were reviewed and, if necessary, adjusted to the ADM1 model framework in order to compare them. Experimental data from anaerobic digestion of slaughterhouse waste at an organic loading rate (OLR) ranging from 0.3 to 1.9kgVSm^-3d^-1 were used to compare and evaluate models. Experimental data obtained at low OLRs were accurately modeled whatever the model thereby validating the stoichiometric parameters used and influent fractionation. However, at higher OLRs, although inhibition parameters were optimized to reduce differences between experimental and simulated data, no model was able to accurately simulate accumulation of substrates and intermediates, mainly due to the wrong simulation of pH. A simulation using pH based on experimental data showed that acetogenesis and methanogenesis were the most sensitive steps to LCFA inhibition and enabled identification of the inhibition parameters of both steps.

Modified ADM1 for modeling free ammonia inhibition in anaerobic acidogenic fermentation with high-solid sludge

Anaerobic acidogenic fermentation with high-solid sludge is a promising method for volatile fatty acid (VFA) production to realize resource recovery. In this study, to model inhibition by free ammonia in high-solid sludge fermentation, the anaerobic digestion model No. 1 (ADM1) was modified to simulate the VFA generation in batch, semi-continuous and full scale sludge. The ADM1 was operated on the platform AQUASIM 2.0. Three kinds of inhibition forms, e.g., simple inhibition, Monod and non-inhibition forms, were integrated into the ADM1 and tested with the real experimental data for batch and semi-continuous fermentation, respectively. The improved particle swarm optimization technique was used for kinetic parameter estimation using the software MATLAB 7.0. In the modified ADM1, the K_s of acetate is 0.025, the k_m,ac is 12.51, and the K_{I_NH3} is 0.02, respectively. The results showed that the simple inhibition model could simulate the VFA generation accurately while the Monod model was the better inhibition kinetics form in semi-continuous fermentation at pH10.0. Finally, the modified ADM1 could successfully describe the VFA generation and ammonia accumulation in a 30m³ full-scale sludge fermentation reactor, indicating that the developed model can be applicable in high-solid sludge anaerobic fermentation.

Modelling anaerobic digestion in a biogas reactor: ADM1 model development with lactate as an intermediate (Part I)

The Anaerobic Digestion Model No. 1 (ADM1) was extended to include lactate, a crucial metabolic product during sugar fermentation. This study tests the validity of the modified ADM1 model in improving the predictions of a standard biogas reactor. This reactor was prepared in the laboratory with simple organic substrates with an intention to represent an 'average biogas plant'. Kinetic parameters were determined from a lactic acid enriched steady-state reactor. The parameters were adjusted further in order to acquire satisfying simulation results systematically with the batch experiments and then against the standard biogas reactor. Arresting methanogenesis revealed that lactate degradation occurred majorly via acetate followed by propionate, and a non-negligible proportion of butyrate too was found, which were further updated in the model. The modified ADM1 provided a successful correlation with the experimental results for the batch and continuous experiments. We justified that inclusion of lactate in the model resulted in optimized simulation for both biogas and methane content in the standard biogas reactor.

Modeling the performance of an anaerobic baffled reactor with the variation of hydraulic retention time

Anaerobic baffled reactors (ABRs) have been widely used in engineering but very few models have been developed to simulate its performance. Based on the integration of biomass retention and liquid-gas mass transfer of biogas into the biochemical process derived in the International Water Association (IWA) Anaerobic Digestion Model No.1 (ADM1), a mathematical model was developed to predict volatile fatty acids (VFAs), chemical oxygen demand (CODCr) and biogas in a 4-compartment ABR operated with variable hydraulic retention time (HRT). The model was calibrated and validated with the experimental data obtained from the reactor when the HRT decreased from 2.0 to 1.0d by stages. It was found that the predicted VFAs, CODCr and biogas agreed well with the experimental data. Consequently, the developed model was a reliable tool to enhance the understanding among the mechanisms of the anaerobic digestion in ABRs, as well as to reactor's designing and operation.

Modelling anaerobic co-digestion in Benchmark Simulation Model No. 2: Parameter estimation, substrate characterisation and plant-wide integration

Anaerobic co-digestion is an emerging practice at wastewater treatment plants (WWTPs) to improve the energy balance and integrate waste management. Modelling of co-digestion in a plant-wide WWTP model is a powerful tool to assess the impact of co-substrate selection and dose strategy on digester performance and plant-wide effects. A feasible procedure to characterise and fractionate co-substrates COD for the Benchmark Simulation Model No. 2 (BSM2) was developed. This procedure is also applicable for the Anaerobic Digestion Model No. 1 (ADM1). Long chain fatty acid inhibition was included in the ADM1 model to allow for realistic modelling of lipid rich co-substrates. Sensitivity analysis revealed that, apart from the biodegradable fraction of COD, protein and lipid fractions are the most important fractions for methane production and digester stability, with at least two major failure modes identified through principal component analysis (PCA). The model and procedure were tested on bio-methane potential (BMP) tests on three substrates, each rich on carbohydrates, proteins or lipids with good predictive capability in all three cases. This model was then applied to a plant-wide simulation study which confirmed the positive effects of co-digestion on methane production and total operational cost. Simulations also revealed the importance of limiting the protein load to the anaerobic digester to avoid ammonia inhibition in the digester and overloading of the nitrogen removal processes in the water train. In contrast, the digester can treat relatively high loads of lipid rich substrates without prolonged disturbances.

Application of ADM1 for modeling of biogas production from anaerobic digestion of Hydrilla verticillata

The present study focused on the application of anaerobic digestion model no. 1 (ADM1) to simulate biogas production from Hydrilla verticillata. Model simulation was carried out by implementing ADM1 in AQUASIM 2.0 software. Sensitivity analysis was used to select the most sensitive parameters for estimation using the absolute-relative sensitivity function. Among all the kinetic parameters, disintegration constant (kdis), hydrolysis constant of protein (khyd_pr), Monod maximum specific substrate uptake rate (km_aa, km_ac, km_h2) and half-saturation constants (Ks_aa, Ks_ac) affect biogas production significantly, which were optimized by fitting of the model equations to the data obtained from batch experiments. The ADM1 model after parameter estimation was able to well predict the experimental results of daily biogas production and biogas composition. The simulation results of evolution of organic acids, bacteria concentrations and inhibition effects also helped to get insight into the reaction mechanisms.

From pre-treatment toward inter-treatment. Getting some clues from sewage sludge biomethanation

The conventional application of thermal pretreatment of sewage sludge has been to apply it prior to the anaerobic digestion. In this study, the thermal treatment of the digestate was assessed at lab-scale under several temperature and time conditions. Biochemical methane potential (BMP) tests were set up to evaluate the methane production kinetic by using the Gompertz modified and the first order equation. A full-scale digester evaluation was done by using the ADM1 model under different scenarios and by using the parameters drawn from the BMP tests. The best results were obtained at 180°C and 200°C both at 30min where an improvement of 50% in the methane yield in regards to raw digestate. Full-scale simulations show that a scenario with two anaerobic reactors with thermal inter-treatment would improve the methane production by 45% and 20% compared to conventional anaerobic digestion and pretreatments followed by anaerobic digestion, respectively.

Modelling the anaerobic digestion of solid organic waste - Substrate characterisation method for ADM1 using a combined biochemical and kinetic parameter estimation approach

This work proposes a novel and rigorous substrate characterisation methodology to be used with ADM1 to simulate the anaerobic digestion of solid organic waste. The proposed method uses data from both direct substrate analysis and the methane production from laboratory scale anaerobic digestion experiments and involves assessment of four substrate fractionation models. The models partition the organic matter into a mixture of particulate and soluble fractions with the decision on the most suitable model being made on quality of fit between experimental and simulated data and the uncertainty of the calibrated parameters. The method was tested using samples of domestic green and food waste and using experimental data from both short batch tests and longer semi-continuous trials. The results showed that in general an increased fractionation model complexity led to better fit but with increased uncertainty. When using batch test data the most suitable model for green waste included one particulate and one soluble fraction, whereas for food waste two particulate fractions were needed. With richer semi-continuous datasets, the parameter estimation resulted in less uncertainty therefore allowing the description of the substrate with a more complex model. The resulting substrate characterisations and fractionation models obtained from batch test data, for both waste samples, were used to validate the method using semi-continuous experimental data and showed good prediction of methane production, biogas composition, total and volatile solids, ammonia and alkalinity.

Modeling the anaerobic digestion of cane-molasses vinasse: extension of the Anaerobic Digestion Model No. 1 (ADM1) with sulfate reduction for a very high strength and sulfate rich wastewater

This research presents the modeling of the anaerobic digestion of cane-molasses vinasse, hereby extending the Anaerobic Digestion Model No. 1 with sulfate reduction for a very high strength and sulfate rich wastewater. Based on a sensitivity analysis, four parameters of the original ADM1 and all sulfate reduction parameters were calibrated. Although some deviations were observed between model predictions and experimental values, it was shown that sulfates, total aqueous sulfide, free sulfides, methane, carbon dioxide and sulfide in the gas phase, gas flow, propionic and acetic acids, chemical oxygen demand (COD), and pH were accurately predicted during model validation. The model showed high (±10%) to medium (10%-30%) accuracy predictions with a mean absolute relative error ranging from 1% to 26%, and was able to predict failure of methanogenesis and sulfidogenesis when the sulfate loading rate increased. Therefore, the kinetic parameters and the model structure proposed in this work can be considered as valid for the sulfate reduction process in the anaerobic digestion of cane-molasses vinasse when sulfate and organic loading rates range from 0.36 to 1.57 kg [Formula: see text]  m(-3) d(-1) and from 7.66 to 12 kg COD m(-3) d(-1), respectively.

Effects of ionic strength and ion pairing on (plant-wide) modelling of anaerobic digestion

Plant-wide models of wastewater treatment (such as the Benchmark Simulation Model No. 2 or BSM2) are gaining popularity for use in holistic virtual studies of treatment plant control and operations. The objective of this study is to show the influence of ionic strength (as activity corrections) and ion pairing on modelling of anaerobic digestion processes in such plant-wide models of wastewater treatment. Using the BSM2 as a case study with a number of model variants and cationic load scenarios, this paper presents the effects of an improved physico-chemical description on model predictions and overall plant performance indicators, namely effluent quality index (EQI) and operational cost index (OCI). The acid-base equilibria implemented in the Anaerobic Digestion Model No. 1 (ADM1) are modified to account for non-ideal aqueous-phase chemistry. The model corrects for ionic strength via the Davies approach to consider chemical activities instead of molar concentrations. A speciation sub-routine based on a multi-dimensional Newton-Raphson (NR) iteration method is developed to address algebraic interdependencies. The model also includes ion pairs that play an important role in wastewater treatment. The paper describes: 1) how the anaerobic digester performance is affected by physico-chemical corrections; 2) the effect on pH and the anaerobic digestion products (CO2, CH4 and H2); and, 3) how these variations are propagated from the sludge treatment to the water line. Results at high ionic strength demonstrate that corrections to account for non-ideal conditions lead to significant differences in predicted process performance (up to 18% for effluent quality and 7% for operational cost) but that for pH prediction, activity corrections are more important than ion pairing effects. Both are likely to be required when precipitation is to be modelled.

Modified Anaerobic Digestion Model No.1 for dry and semi-dry anaerobic digestion of solid organic waste

The role of total solids (TS) content in anaerobic digestion of selected complex organic matter, e.g. rice straw and food waste, was investigated. A range of TS from wet (4.5%) to dry (23%) was evaluated. A modified version of the Anaerobic Digestion Model No.1 for a complex organic substrate is proposed to take into account the effect of the TS content on anaerobic digestion. A linear function that correlates the kinetic constants of three specific processes (i.e. disintegration, acetate and propionate up-take) was included in the model. Results of biomethanation and volatile fatty acids production tests were used to calibrate the proposed model. Model simulations showed a good agreement between numerical and observed data.

Critical comparison of different model structures for the applied simulation of the anaerobic digestion of agricultural energy crops

Different model structures were compared to simulate the characteristic process variables of the anaerobic digestion of maize, sugar beet and grain silage. Depending on the type and number of the required components, it can be shown that in comparison to the complex Anaerobic Digestion Model No. 1 (ADM1) different simplified model structures can describe the gas production rate, ammonia nitrogen and acetate concentration or pH value equally well. Since the reduction of the predominantly fast kinetics of the methanogenesis, acetogenesis or acidogenesis will only have little effect on the simulation of the specific gas production, it can be proven that the hydrolysis is the rate-limiting step during the uninhibited anaerobic digestion of complex particulate substrates. However, the stoichiometric comparison reveals that the model protein gelatine is not suitable for a representative characterization of agricultural energy crops.

Kinetic modelling of anaerobic hydrolysis of solid wastes, including disintegration processes

A methodology to estimate disintegration and hydrolysis kinetic parameters of solid wastes and validate an ADM1-based anaerobic co-digestion model is presented. Kinetic parameters of the model were calibrated from batch reactor experiments treating individually fruit and vegetable wastes (among other residues) following a new protocol for batch tests. In addition, decoupled disintegration kinetics for readily and slowly biodegradable fractions of solid wastes was considered. Calibrated parameters from batch assays of individual substrates were used to validate the model for a semi-continuous co-digestion operation treating simultaneously 5 fruit and vegetable wastes. The semi-continuous experiment was carried out in a lab-scale CSTR reactor for 15 weeks at organic loading rate ranging between 2.0 and 4.7 gVS/Ld. The model (built in Matlab/Simulink) fit to a large extent the experimental results in both batch and semi-continuous mode and served as a powerful tool to simulate the digestion or co-digestion of solid wastes.

Performance optimization and validation of ADM1 simulations under anaerobic thermophilic conditions

In this study, two experimental sets of data each involving two thermophilic anaerobic digesters treating food waste, were simulated using the Anaerobic Digestion Model No. 1 (ADM1). A sensitivity analysis was conducted, using both data sets of one digester, for parameter optimization based on five measured performance indicators: methane generation, pH, acetate, total COD, ammonia, and an equally weighted combination of the five indicators. The simulation results revealed that while optimization with respect to methane alone, a commonly adopted approach, succeeded in simulating methane experimental results, it predicted other intermediary outputs less accurately. On the other hand, the multi-objective optimization has the advantage of providing better results than methane optimization despite not capturing the intermediary output. The results from the parameter optimization were validated upon their independent application on the data sets of the second digester.

Mathematical modelling of methanogenic reactor start-up: Importance of volatile fatty acids degrading population

Development of balanced community of microorganisms is one of the obligatory for stable anaerobic digestion. Application of mathematical models might be helpful in development of reliable procedures during the process start-up period. Yet, the accuracy of forecast depends on the quality of input and parameters. In this study, the specific anaerobic activity (SAA) tests were applied in order to estimate microbial community structure. Obtained data was applied as input conditions for mathematical model of anaerobic digestion. The initial values of variables describing the amount of acetate and propionate utilizing microorganisms could be calculated on the basis of SAA results. The modelling based on those optimized variables could successfully reproduce the behavior of a real system during the continuous fermentation.