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.

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.

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.

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.