Assessment and parameter identification of simplified models to describe the kinetics of semi-continuous biomethane production from anaerobic digestion of green and food waste

Raymond O Owhondah, Mark Walker, Lin Ma, Bill Nimmo, Derek B Ingham, Davide Poggio, Mohamed Pourkashanian

Research output: Contribution to journalArticle

6 Citations (Scopus)
1 Downloads (Pure)

Abstract

Biochemical reactions occurring during anaerobic digestion have been modelled using reaction kinetic equations such as first-order, Contois and Monod which are then combined to form mechanistic models. This work considers models which include between one and three biochemical reactions to investigate if the choice of the reaction rate equation, complexity of the model structure as well as the inclusion of inhibition plays a key role in the ability of the model to describe the methane production from the semi-continuous anaerobic digestion of green waste (GW) and food waste (FW). A parameter estimation method was used to investigate the most important phenomena influencing the biogas production process. Experimental data were used to numerically estimate the model parameters and the quality of fit was quantified. Results obtained reveal that the model structure (i.e. number of reactions, inhibition) has a much stronger influence on the quality of fit compared with the choice of kinetic rate equations. In the case of GW there was only a marginal improvement when moving from a one to two reaction model, and none with inclusion of inhibition or three reactions. However, the behaviour of FW digestion was more complex and required either a two or three reaction model with inhibition functions for both ammonia and volatile fatty acids. Parameter values for the best fitting models are given for use by other authors.
Original languageEnglish
Pages (from-to)977-992
Number of pages16
JournalBioprocess and Biosystems Engineering
Volume39
Issue number6
DOIs
Publication statusPublished - 9 Mar 2016

Keywords

  • Anaerobic digestion
  • Modelling
  • Food waste
  • Green waste
  • Parameter estimation
  • Parameter identification

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