Modelling bioaugmentation: Engineering intervention in anaerobic digestion

Giovanna Lovato, Adam Kovalovszki, Merlin Alvarado-Morales, Arnaud Tristan Arjuna Jéglot, José Alberto Domingues Rodrigues, Irini Angelidaki*

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Bioaugmentation – the addition of specific microorganisms to microbial consortia to obtain specific functions - is a promising method to improve the performance of sub-optimal anaerobic digestion processes and recover methane production. The present study implements for the first time a model with bioaugmentation functionalities, enabling the dynamic microbiological study of augmented anaerobic systems. The model is based on a previous advanced mathematical model focused on ammonia inhibition, which was extended. Three inhibited anaerobic digestion experiments were simulated, where bioaugmentation involved the addition of: (i) hydrogenotrophic methanogenic archaea; (ii) a combination of hydrogenotrophs and syntrophic acetate oxidizing bacteria; and (iii) acetoclastic methanogenic archaea to the inhibited reactors. Methane productivity, pH, and ammonia were correctly predicted by the model, with weighted absolute percentage errors below 10 %. Trends in volatile fatty acids accumulation and consumption showed good agreement between in silico and in vivo data. Simulations revealed that bioaugmentation will result in process improvement when specialized hydrogenotrophs are used: not only do they establish themselves in the inhibited environment, but also help in the recovery of acetoclastic methanogens. Overall, the mathematical approach adopted to describe the bioaugmentation phenomena resulted in a robust computational tool for simulation of general bioaugmentation strategies.
Original languageEnglish
JournalRenewable Energy
Volume175
Pages (from-to)1080-1087
ISSN0960-1481
DOIs
Publication statusPublished - 2021

Keywords

  • Bioaugmentation
  • Inhibition
  • Kinetics
  • Mathematical modelling
  • SAO

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