Biofilm growth and the related changes in the physical properties of a porous medium: 3. Dispersivity and model verification

Abstract

In the first part of this paper the change in dispersivity resulting from the growth of a biofilm in a porous medium is derived from an existing model of dispersivity and a cut‐and‐random‐rejoin‐type model of the pore geometry. The change in dispersivity due to a biofilm is also estimated from experimental data. Tracer experiments were conducted in biofilm column reactors and dispersion coefficients estimated by solving the inverse solute transport problem by nonlinear, least squares regression. Due to the presence of the biofilm in the porous media, solute flux into the biofilm is an important transport process and is given special attention. Both the dispersivity model and experimentally estimated dispersivities show order of magnitude increases in dispersivity as a result of significant biofilm growth. In the second part of the paper the models for the biofilm‐affected permeability, porosity, and specific surface derived in a companion paper (Taylor et al., this issue) are verified using data from biofilm column reactors. These models are used to parameterize an equation describing the transport of substrate in the experimental columns. Numerical simulations were performed and compared to observed substrate data. Results show that the models for permeability and porosity can be used to make estimates of these parameters, while the model for specific surface appears to be inadequate.

A dual-porosity theory for solute transport in biofilm-coated porous media

“…Finally, Eqs. (12) and (13) can be simplified and the resulting set of macroscopic equations is the following:…”

“…The assumption that the reactive phenomena do not prevail over the convective and diffusive processes, i.e., Da Ac 6 Pe A and Da Ax 6 Pe A ; is required to overcome this difficulty. These closure fields are used to evaluate the effective parameters of the macroscopic equation, according to the following expressions, which are derived by the injection of the closure assumptions (12) and (13) in the unclosed macroscopic equations (10) and (11). …”

“…Indeed, for the generally accepted orders of magnitude of the pore-scale Péclet number, in the range 0.01-100, and of the Damköhler number, lower than 10, the local-equilibrium model fails (see the comparison with experimental data of [7] or [8]. As an alternative, limitations by diffusion are considered between the microbial and bulk aqueous phase in microcolony models [9,10], while, in biofilm models [11][12][13][14], both external and internal mass transfer limitations are accounted for. These non-equilibrium models differ mainly by the assumption adopted for the geometrical description of the biomass.…”

Development and resistance of a biofilm in a planar fracture during biostimulation, starvation, and varying flow conditions

“…As such, planktonic bacterial density (Batchelor et al 1997;Lehman et al 2001;O'Toole et al 2000), tracer experiments (Hill and Sleep 2002;Taylor and Jaffé 1990), and monitoring of terminal electron accepting conditions, via oxidation-reduction potential (ORP) probes (Appelo and Postma 1993;Bishop and Yu 1999;Kamon et al 2002), have been reported. Again, little information exists on the application of such techniques in fractured media.…”

Bioclogging in porous media: Model development and sensitivity to initial conditions

“…In this section we investigate the impact of this condition on the final results, as well as the 637 additional uncertainty introduced. Also, several experiments reported a medium to large increase in 638 dispersivity together with the reduction in porosity and permeability (Taylor and Jaffé, 1990c growth. We will use numerical experiments to investigate the extent to which such process can con-642 tribute to an increase of dispersivity.…”