Simulating the performance of biogas reactors co-digesting ammonia and/or fatty acid rich substrates

Application of mathematical models as tools and early warning indicators for the prediction of the overall performance of biogas reactors can contribute to the optimization of the anaerobic digestion. The present study aimed to simulate frequently found cases in biogas reactors during which the bioprocess is perturbated by common stressors (i.e., fatty acids and ammonia inhibition). Specifically, the reliability of the Bioconversion Model (BioModel) was evaluated by examining three Case Studies in which the reactors were subjected to different feedstock strategies. Generally, the simulations were well fitting the experimental data associated with methane productivity and pH, while discrepancies were only observed in the prediction of the volatile fatty acids' concentrations. Specifically, it was demonstrated that the default kinetic parameters of the model, which were mainly associated with acetate degradation (Ki,Ac), needed to be adjusted to extract a proper prediction. Overall, the numerical and patterned performance results indicated the accuracy of the BioModel, in terms of its effectiveness in simulating different co-digestion strategies involving the presence of fatty acid or ammonia.

Automated summary

The application of mathematical models as tools and early warning indicators can optimize the anaerobic digestion process in biogas reactors. The Bioconversion Model (BioModel) was evaluated in this study for simulating common perturbation cases caused by fatty acids and ammonia inhibition. The simulations showed good agreement with experimental data on methane productivity and pH, but discrepancies were observed in the prediction of volatile fatty acids' concentrations. Adjustments to the model's kinetic parameters were necessary to improve the prediction accuracy. Overall, the BioModel demonstrated effectiveness in simulating different co-digestion strategies with fatty acid or ammonia presence.