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Front Bioeng Biotechnol. 2019 May 8;7:93. doi: 10.3389/fbioe.2019.00093. eCollection 2019.

Identification of the Methanogenesis Inhibition Mechanism Using Comparative Analysis of Mathematical Models.

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1
Department of Water Management, Delft University of Technology, Delft, Netherlands.

Abstract

The application of cationic polymers to enhance membrane fluxes in anaerobic membrane bioreactors has been proposed by several authors. However, literature shows contradictory results on the influence of those chemicals on the biological activity. In this research, we studied the effect of a cationic polymer on the production of methane from acetate by acetoclastic methanogens. We assessed the effect of polymer concentration on the accumulated methane production (AMP) and the specific methanogenic activity (SMA) in batch tests. Batch tests results showed lower SMA values at higher concentrations of polymer and no effect on the final AMP. Different inhibition models were calibrated and compared to find the best fit and to hypothesize the prevailing inhibition mechanisms. The assessed inhibition models were: competitive (M1a), non-competitive (M2a), un-competitive (M3a), biocide-linear (M4a), and biocide-exponential (M5a). The parameters in the model related to the polymer characteristics were adjusted to fit the experimental data. M2a and M3a were the only models that fitted both experimental SMA and AMP. Although M1a and M4a adequately fitted the experimental SMA, M1a simulations slightly deviated from the experimental AMP, and M4a considerably underpredicted the AMP at concentrations of polymer above 0.23 gCOD L-1. M5a did not adequately fit either experimental SMA and AMP results. We compared models a (M1a to M5a), which consider the inhibition by the concentration of polymer in the bulk liquid, with models b (M1b to M5b) considering the inhibition being caused by the total concentration of polymer in the reactor. Results showed that the difference between a and b models' simulations were negligible for all kinetic models considered (M1, M2, M3, M4, and M5). Therefore, the models that better predicted the experimental data were the non-competitive (M2a and M2b) and un-competitive (M3a and M3b) inhibition models, which are biostatic inhibition models. Consequently, the decreased methanogenic activity caused by polymer additions is presumably a reversible process.

KEYWORDS:

Monte Carlo (MC); anaerobic membrane bioreactor (AnMBR); cationic polymer; flux enhancers; langmuir isotherm; methanogenesis inhibition; modeling; specific methanogenic activity (SMA)

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