Dynamic modelling of the population distribution in the anaerobic granular biofilm

Author:

Arcand Yves1,Chavarie Claude2,Guiot Serge R.2

Affiliation:

1. Institut de Recherche en Biotechnologie, C.N.R.C., Montréal, H4P 2R2, Canada

2. Dept. de Génie Chimique, école Polytechnique, Montréal, H3C 3A7, Canada

Abstract

Significant downward gradient of glucotrophic (acidogenic) activity was experimentally observed as anaerobic granules were stripped off their surface bacteria. This indicated a clear predominance of fermentative bacteria in the external layer of the granules. This is consistent with the multilayer microstructural model evidenced by scanning electron microscopy (SEM) of cleaved granules. In contrast, acetoclastic activities were evenly distributed along the granule depth even though SEM had shown the core of granules of various sources to be almost exclusively composed of Methanosaeta-like bacteria. A detailed distributed diffusion-reaction mathematical model was developed to predict local substance and biomass concentrations at any depth within the granular biofilm. This intragranular model combines the kinetics of ten substances and eight trophic groups of microorganisms as well as physico-chemical constraints such as ionic dissociation and gas-liquid equilibrium, internal and bulk-surface interfacial diffusion mechanisms. Predicted results of this intragranular kinetic model have shown a drastic downward glucose gradient towards the centre, as a concentration of 10 μM in the bulk liquid boundary layer dropped to almost 0 at a distance less than 100 μm below the surface. In contrast, the model predicted very low to no gradients of acetate. However, the model predicted pH values 1 mm inside the granule to be over one pH unit more alkaline than in the bulk liquid. Hence this significant pH gradient could be the major factor which gives a competitive advantage for Methanosaeta-like population to proliferate in the granule core.

Publisher

IWA Publishing

Subject

Water Science and Technology,Environmental Engineering

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