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

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

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

A novel approach for the fractionation of organic components and microbial degraders in ADM1 and model validation based on the methanogenic potential

The anaerobic digestion model No 1 (ADM1), with fixed fractions of the substrate components, is currently used to simulate methane production during the anaerobic digestion (AD) of waste activated sludge (WAS). However, the goodness-of-fit for the simulation is not ideal due to the different characteristics of WAS from different regions. In this study, a novel methodology based on a modern instrumental analysis and 16S rRNA gene sequence analysis for the fractionation of organic components and microbial degraders in the WAS is investigated to modify the fractions of the components in the ADM1. The combination of Fourier transform infrared (FTIR), X-ray photoelectron spectroscopy (XPS), and nuclear magnetic resonance (NMR) analyses were used to achieve a rapid and accurate fractionation of the primary organic matters in the WAS that was verified using both the sequential extraction method and the excitation-emission matrix (EEM). The protein, carbohydrate, and lipid contents in the four different sludge samples measured using the above combined instrumental analyses were 25.0 - 50.0%, 2.0 - 10.0%, and 0.9 - 2.3%. The microbial diversity based on 16S rRNA gene sequence analysis was utilized to re-set the initial fractions of the microbial degraders in the ADM1. A batch experiment was utilized to further calibrate the kinetic parameters in the ADM1. Based on the above optimization of the stoichiometric and kinetic parameters, the ADM1 with full parameter modification for WAS (ADM1-FPM) simulated the methane production of the WAS very well with a Theil's inequality coefficient (TIC) of 0.049, which was increased by 89.8% than that of the default ADM1 fit. The proposed approach, with its rapid and reliable performance, demonstrated a strong application potential for the fractionation of organic solid waste and the modification of ADM1, which contributed to a better simulation of methane production during the AD of organic solid wastes.

Microbial Community Successional Changes in a Full-Scale Mesophilic Anaerobic Digester from the Start-Up to the Steady-State Conditions

Anaerobic digestion is a widely used technology for sewage sludge stabilization and biogas production. Although the structure and composition of the microbial communities responsible for the process in full-scale anaerobic digesters have been investigated, little is known about the microbial successional dynamics during the start-up phase and the response to variations occurring in such systems under real operating conditions. In this study, bacterial and archaeal population dynamics of a full-scale mesophilic digester treating activated sludge were investigated for the first time from the start-up, performed without adding external inoculum, to steady-state operation. High-throughput 16S rRNA gene sequencing was used to describe the microbiome evolution. The large majority of the reads were affiliated to fermentative bacteria. Bacteroidetes increased over time, reaching 22% of the total sequences. Furthermore, Methanosaeta represented the most abundant methanogenic component. The specific quantitative data generated by real-time PCR indicated an enrichment of bacteria and methanogens once the steady state was reached. The analysis allowed evaluation of the microbial components more susceptible to the shift from aerobic to anaerobic conditions and estimation of the microbial components growing or declining in the system. Additionally, activated sludge was investigated to evaluate the microbial core selected by the WWTP operative conditions.

History and Evolution of Modeling in Biotechnology: Modeling & Simulation, Application and Hardware Performance

Biological systems are typically composed of highly interconnected subunits and possess an inherent complexity that make monitoring, control and optimization of a bioprocess a challenging task. Today a toolset of modeling techniques can provide guidance in understanding complexity and in meeting those challenges. Over the last four decades, computational performance increased exponentially. This increase in hardware capacity allowed ever more detailed and computationally intensive models approaching a "one-to-one" representation of the biological reality. Fueled by governmental guidelines like the PAT initiative of the FDA, novel soft sensors and techniques were developed in the past to ensure product quality and provide data in real time. The estimation of current process state and prediction of future process course eventually enabled dynamic process control. In this review, past, present and envisioned future of models in biotechnology are compared and discussed with regard to application in process monitoring, control and optimization. In addition, hardware requirements and availability to fit the needs of increasingly more complex models are summarized. The major techniques and diverse approaches of modeling in industrial biotechnology are compared, and current as well as future trends and perspectives are outlined.

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.

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.

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.

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 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.