Coupling a Simple and Generic Membrane Fouling Model with Biological Dynamics: Application to the Modeling of an Anaerobic Membrane BioReactor (AnMBR).

A simple model is developed for membrane fouling, taking into account two main fouling phenomena: cake formation, due to attached solids on the membrane surface, and pore clogging, due to retained compounds inside the pores. The model is coupled with a simple anaerobic digestion model for describing the dynamics of an anaerobic membrane bioreactor (AnMBR). In simulations, we investigate its qualitative behavior: it is shown that the model exhibits satisfying properties in terms of a flux decrease due to membrane fouling. Comparing simulation and experimental data, the model is shown to predict quite well the dynamics of an AnMBR. The simulated flux best fits the experimental flux with a correlation coefficient r2=0.968 for the calibration data set and r2=0.938 for the validation data set. General discussions are given on possible control strategies to limit fouling and optimize the flux production. We show in simulations that these strategies allow one to increase the mean production flux to 33 L/(h·m2),whereas without control, it was 18 L/(h·m2).

Biological processes modelling for MBR systems: A review of the state-of-the-art focusing on SMP and EPS.

A mathematical correlation between biomass kinetic and membrane fouling can improve the understanding and spread of Membrane Bioreactor (MBR) technology, especially in solving the membrane fouling issues. On this behalf, this paper, produced by the International Water Association (IWA) Task Group on Membrane modelling and control, reviews the current state-of-the-art regarding the modelling of kinetic processes of biomass, focusing on modelling production and utilization of soluble microbial products (SMP) and extracellular polymeric substances (EPS). The key findings of this work show that the new conceptual approaches focus on the role of different bacterial groups in the formation and degradation of SMP/EPS. Even though several studies have been published regarding SMP modelling, there still needs to be more information due to the highly complicated SMP nature to facilitate the accurate modelling of membrane fouling. The EPS group has seldom been addressed in the literature, probably due to the knowledge deficiency concerning the triggers for production and degradation pathways in MBR systems, which require further efforts. Finally, the successful model applications showed that proper estimation of SMP and EPS by modelling approaches could optimise membrane fouling, which can influence the MBR energy consumption, operating costs, and greenhouse gas emissions.

Consideration of Maintenance in Wine Fermentation Modeling.

We show that a simple model with a maintenance term can satisfactorily reproduce the simulations of several existing models of wine fermentation from the literature, as well as experimental data. The maintenance describes a consumption of the nitrogen that is not entirely converted into biomass. We show also that considering a maintenance term in the model is equivalent to writing a model with a variable yield that can be estimated from data.

Microbial Interactions as Drivers of a Nitrification Process in a Chemostat.

This article deals with the inclusion of microbial ecology measurements such as abundances of operational taxonomic units in bioprocess modelling. The first part presents the mathematical analysis of a model that may be framed within the class of Lotka-Volterra models fitted to experimental data in a chemostat setting where a nitrification process was operated for over 500 days. The limitations and the insights of such an approach are discussed. In the second part, the use of an optimal tracking technique (developed within the framework of control theory) for the integration of data from genetic sequencing in chemostat models is presented. The optimal tracking revisits the data used in the aforementioned chemostat setting. The resulting model is an explanatory model, not a predictive one, it is able to reconstruct the different forms of nitrogen in the reactor by using the abundances of the operational taxonomic units, providing some insights into the growth rate of microbes in a complex community.

Batch Reverse Osmosis Desalination Modeling under a Time-Dependent Pressure Profile.

As world demand for clean water increases, reverse osmosis (RO) desalination has emerged as an attractive solution. Continuous RO is the most used desalination technology today. However, a new generation of configurations, working in unsteady-state feed concentration and pressure, have gained more attention recently, including the batch RO process. Our work presents a mathematical modeling for batch RO that offers the possibility of monitoring all variables of the process, including specific energy consumption, as a function of time and the recovery ratio. Validation is achieved by comparison with data from the experimental set-up and an existing model in the literature. Energetic comparison with continuous RO processes confirms that batch RO can be more energy efficient than can continuous RO, especially at a higher recovery ratio. It used, at recovery, 31% less energy for seawater and 19% less energy for brackish water. Modeling also proves that the batch RO process does not have to function under constant flux to deliver good energetic performance. In fact, under a linear pressure profile, batch RO can still deliver better energetic performance than can a continuous configuration. The parameters analysis shows that salinity, pump and energy recovery devices efficiencies are directly linked to the energy demand. While increasing feed volume has a limited effect after a certain volume due to dilution, it also shows, interestingly, a recovery ratio interval in which feed volume does not affect specific energy consumption.

Integrated membrane bioreactors modelling: A review on new comprehensive modelling framework.

Integrated Membrane Bioreactor (MBR) models, combination of biological and physical models, have been representing powerful tools for the accomplishment of high environmental sustainability. This paper, produced by the International Water Association (IWA) Task Group on Membrane Modelling and Control, reviews the state-of-the-art, identifying gaps for future researches, and proposes a new integrated MBR modelling framework. In particular, the framework aims to guide researchers and managers in pursuing good performances of MBRs in terms of effluent quality, operating costs (such as membrane fouling, energy consumption due to aeration) and mitigation of greenhouse gas emissions.

Bacterial metabolic heterogeneity: from stochastic to deterministic models.

We revisit the modeling of the diauxic growth of a pure microorganism on two distinct sugars which was first described by Monod. Most available models are deterministic and make the assumption that all cells of the microbial ecosystem behave homogeneously with respect to both sugars, all consuming the first one and then switching to the second when the first is exhausted. We propose here a stochastic model which describes what is called "metabolic heterogeneity". It allows to consider small populations as in microfluidics as well as large populations where billions of individuals coexist in the medium in a batch or chemostat. We highlight the link between the stochastic model and the deterministic behavior in real large cultures using a large population approximation. Then the influence of model parameter values on model dynamics is studied, notably with respect to the lag-phase observed in real systems depending on the sugars on which the microorganism grows. It is shown that both metabolic parameters as well as initial conditions play a crucial role on system dynamics.

Insights from Microbial Transition State Theory on Monod's Affinity Constant.

Microbial transition state theory (MTS) offers a theoretically explicit mathematical model for substrate limited microbial growth. By considering a first order approximation of the MTS equation one recovers the well-known Monod's expression for growth, which was regarded as a purely empirical function. The harvest volume of a cell as defined in MTS theory can then be related to the affinity concept, giving a new physical interpretation to it, and a new way to determine its value. Consequences of such a relationship are discussed.

Availability of the Molecular Switch XylR Controls Phenotypic Heterogeneity and Lag Duration during Escherichia coli Adaptation from Glucose to Xylose.

The glucose-xylose metabolic transition is of growing interest as a model to explore cellular adaption since these molecules are the main substrates resulting from the deconstruction of lignocellulosic biomass. Here, we investigated the role of the XylR transcription factor in the length of the lag phases when the bacterium Escherichia coli needs to adapt from glucose- to xylose-based growth. First, a variety of lag times were observed when different strains of E. coli were switched from glucose to xylose. These lag times were shown to be controlled by XylR availability in the cells with no further effect on the growth rate on xylose. XylR titration provoked long lag times demonstrated to result from phenotypic heterogeneity during the switch from glucose to xylose, with a subpopulation unable to resume exponential growth, whereas the other subpopulation grew exponentially on xylose. A stochastic model was then constructed based on the assumption that XylR availability influences the probability of individual cells to switch to xylose growth. The model was used to understand how XylR behaves as a molecular switch determining the bistability set-up. This work shows that the length of lag phases in E. coli is controllable and reinforces the role of stochastic mechanism in cellular adaptation, paving the way for new strategies for the better use of sustainable carbon sources in bioeconomy.IMPORTANCE For decades, it was thought that the lags observed when microorganisms switch from one substrate to another are inherent to the time required to adapt the molecular machinery to the new substrate. Here, the lag duration was found to be the time necessary for a subpopulation of adapted cells to emerge and become the main population. By identifying the molecular mechanism controlling the subpopulation emergence, we were able to extend or reduce the duration of the lags. This work is of special importance since it demonstrates the unexpected complexity of monoclonal populations during growth on mixed substrates and provides novel mechanistic insights with regard to bacterial cellular adaptation.

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.

Assessing practical identifiability during calibration and cross-validation of a structured model for high-solids anaerobic digestion.

High-solids anaerobic digestion (HS-AD) of the organic fraction of municipal solid waste (OFMSW) is operated at a total solid (TS) content ≥ 10% to enhance the waste treatment economy, though it might be associated to free ammonia (NH3) inhibition. This study aimed to calibrate and cross-validate a HS-AD model for homogenized reactors in order to assess the effects of high NH3 levels in HS-AD of OFMSW, but also to evaluate the suitability of the reversible non-competitive inhibition function to reproduce the effect of NH3 on the main acetogenic and methanogenic populations. The practical identifiability of structural/biochemical parameters (i.e. 35) and initial conditions (i.e. 32) was evaluated using batch experiments at different TS and/or inoculum-to-substrate ratios. Variance-based global sensitivity analysis and approximate Bayesian computation were used for parameter optimization. The experimental data in this study permitted to estimate up to 8 biochemical parameters, whereas the rest of parameters and biomass contents were poorly identifiable. The study also showed the relatively high levels of NH3 (i.e. up to 2.3 g N/L) and ionic strength (i.e. up to 0.9 M) when increasing TS in HS-AD of OFMSW. However, the NH3 non-competitive function was unable to capture the acetogenic/methanogenic inhibition. Therefore, the calibration emphasized the need for target-oriented experimental data to enhance the practical identifiability and the predictive capabilities of structured HS-AD models, but also the need for further testing the NH3 inhibition function used in these simulations.

Modeling the anaerobic co-digestion of solid waste: From batch to semi-continuous simulation.

The main purpose of this study was to validate the use of a simple model for forecasting methane production in co-digestion reactors run semi-continuously using substrate data acquired in batch mode. Firstly, seven solid substrates were characterized individually in successive batches to assess their Biochemical Methane Potential (BMP) and kinetic parameters. Afterwards, eight mixtures of two, three or five substrates were processed in semi-continuous mode at an organic loading rate of 1 g VS L-1 d-1. The experimental methane production was always greater than that calculated from the BMP of each substrate. This result suggested that, endogenous activity needs to be taken into consideration in order to predict total methane production accurately. Near equivalence between experimental and modeled methane production was found after integration in the model of the endogenous activity. The results confirmed the possibility for use of substrate batch data (BMP and kinetics) to predict methane production in semi-continuous operations.

A review on anaerobic membrane bioreactors (AnMBRs) focused on modelling and control aspects.

The use of anaerobic membrane bioreactor technology (AnMBR) is rapidly expanding. However, depending on the application, AnMBR design and operation is not fully mature, and needs further research to optimize process efficiency and enhance applicability. This paper reviews state-of-the-art of AnMBR focusing on modelling and control aspects. Quantitative environmental and economic evaluation has demonstrated substantial advantages in application of AnMBR to domestic wastewater treatment, but detailed modelling is less mature. While anaerobic process modelling is generally mature, more work is needed on integrated models which include coupling between membrane performance (including fouling) and the biological process. This should include microbial factors, which are important to generation of specific foulants such as soluble and particulate inert organics. Mature and well-established control tools, including better feedback control strategies are also required for both the process, and for fouling control.

Model assessment of the prevailing fouling mechanisms in a submerged membrane anaerobic reactor treating low-strength wastewater.

Three models (blocking laws, combined and resistance-in-series) were applied to identify the prevailing fouling mechanisms in a submerged membrane in an up-flow anaerobic sludge blanket reactor treating municipal wastewater. Experimental runs were carried out at lab-scale with filtration periods of 4 and 10 min, followed by relaxation periods of one minute with and without nitrogen bubbling. In all conditions excepting one (IF4R), the blocking laws model showed a predominance of cake formation. With the combined model, cake formation coupled with intermediate, standard and complete fouling had the better fits in all conditions, excepting IF4 and IF4R. When sewage was fed, both models pointed at intermediate fouling in the absence of gas bubbling. The resistance-in-series model identified the positive effect of gas bubbling and a post-cake fouling behavior, not shown by the other two models. This modeling approach could be applied for achieving longer filtration runs in submerged UF membranes.

Evaluation of alkalinity spatial distribution in an up-flow fixed bed anaerobic digester.

In this paper, an experimental study upon alkalinity and hydrodynamic behavior in an anaerobic up-flow fixed bed reactor for the treatment of tequila vinasses is presented. Measurements of volatile fatty acids, pH, alkalinity and bicarbonate were obtained at three sampling points in the reactor in the axial axis. Then, the spatial distribution of alkalinity is studied and discussed. Moreover, for further control process purposes, a hydrodynamic model based on the use of two interconnected two-steps reduced AM2 type models is proposed and its parameters are identified using experimental data.

Major changes in the composition of a Southern Ocean bacterial community in response to diatom-derived dissolved organic matter.

In the Southern Ocean, natural iron fertilization in the wake of islands leads to annually occurring spring phytoplankton blooms associated with enhanced heterotrophic activity through the release of labile dissolved organic matter (DOM). The aim of this study was to investigate experimentally how diatom-derived DOM affects the composition of Southern Ocean winter water bacterial communities and to identify the most responsive taxa. A bacterial community collected in the naturally iron-fertilized region off Kerguelen Island (KEOPS2 October-November 2011) was grown onboard in continuous cultures, on winter water alone or amended with diatom-derived DOM supplied at identical DOC concentrations. 454 sequencing of 16S amplicons revealed that the two DOM sources sustained strikingly different bacterial communities, with higher relative abundances of Sulfitobacter, Colwellia and Methylophaga operational taxonomic units (OTUs) and lower relative abundances of Polaribacter, Marinobacter, NAC11-7 and SAR11 OTUs in diatom-DOM compared to winter water conditions. Using a modeling approach, we obtained growth rates for phylogenetically diverse taxa varying between 0.12 and 0.49 d-1 under carbon-limited conditions. Our results identify diatom DOM as a key factor shaping Southern Ocean winter water bacterial communities and suggest a role for niche partitioning and microbial interactions in organic matter utilization.

Co-digestion of solid waste: Towards a simple model to predict methane production.

Modeling methane production is a key issue for solid waste co-digestion. Here, the effect of a step-wise increase in the organic loading rate (OLR) on reactor performance was investigated, and four new models were evaluated to predict methane yields using data acquired in batch mode. Four co-digestion experiments of mixtures of 2 solid substrates were conducted in semi-continuous mode. Experimental methane yields were always higher than the BMP values of mixtures calculated from the BMP of each substrate, highlighting the importance of endogenous production (methane produced from auto-degradation of microbial community and generated solids). The experimental methane productions under increasing OLRs corresponded well to the modeled data using the model with constant endogenous production and kinetics identified at 80% from total batch time. This model provides a simple and useful tool for technical design consultancies and plant operators to optimize the co-digestion and the choice of the OLRs.

A modelling approach to study the fouling of an anaerobic membrane bioreactor for industrial wastewater treatment.

An Anaerobic Membrane BioReactors (AnMBR) model is presented in this paper based on the combination of a simple fouling model and the Anaerobic Model 2b (AM2b) to describe biological and membrane dynamic responses in an AnMBR. In order to enhance the model calibration and validation, Trans-Membrane Pressure (TMP), Total Suspended Solid (TSS), COD, Volatile Fatty Acid (VFA) and methane production were measured. The model shows a satisfactory description of the experimental data with R2≈0.9 for TMP data and R2≈0.99 for biological parameters. This new model is also proposed as a numerical tool to predict the deposit mass composition of suspended solid and Soluble Microbial Products (SMP) on the membrane surface. The effect of SMP deposit on the TMP jump phenomenon is highlighted. This new approach offers interesting perspectives for fouling prediction and the on-line control of an AnMBR process.

Robust assessment of both biochemical methane potential and degradation kinetics of solid residues in successive batches.

The well-known batch assay test is used worldwide to determine the biochemical methane potential (BMP) of solid substrates in a single batch but its use to estimate the degradation kinetics may lead to underestimations. To overcome this problem, a different approach was carried out to characterize simultaneously both BMP of solid substrates and their degradation kinetics in successive batches, i.e. after an acclimation period. In a second step, a simple model was developed based on the methane production curve in batch mode for dividing the organic matter of the substrate into three sub-fractions according to their degradation rates (rapid, moderate and slow). The protocol developed was applied to 50 different substrates and a database was built. This database includes: the overall BMP (mL CH4/g VS) and the degradation kinetics for each substrate, i.e. the global specific organic degradation rate (g VS/g VSS.d) along with the 3 sub-fractions and their specific degradation rates. The comparison with the BMP from the literature did not highlight significant difference with the BMP measured in this study. Furthermore, the degradation rates seem to be specific characteristics for each substrate and no clear correlation was found between the degradation kinetics and the kind of substrates. The information available in the database will be useful for the design and operation of anaerobic digesters: Optimization of the mix of co-substrates, choice of the applied OLR, simulation of methane production and of the rate of substrate degradation.