Modeling biofilm and development of rate law expressions for biofilm kinetics

Biofilm processes are gaining significance in the field of wastewater treatment. Biofilm modeling has undergone immense development in the last few decades. The modeling involves developing a mass balance equation for nutrient transport across the biofilm matrix composed of microbes distributed with...

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Bibliographic Details
Main Authors: Deepak Sharma, T.R. Sreekrishnan, Shaikh Ziauddin Ahammad
Format: Article
Language:English
Published: Elsevier 2022-11-01
Series:Chemical Engineering Journal Advances
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S266682112200179X
Description
Summary:Biofilm processes are gaining significance in the field of wastewater treatment. Biofilm modeling has undergone immense development in the last few decades. The modeling involves developing a mass balance equation for nutrient transport across the biofilm matrix composed of microbes distributed within. The diffusion of nutrients within the biofilm matrix and their consumption by microbes govern the biofilm kinetics. For steady-state, the model becomes independent of time. The solution of steady-state Biofilm is used to calculate the mass flux entering the biofilm surface. This flux can be referred to as the biofilm reaction rate. A dimensionless number named 'Biofilm Number'(B) is formulated, which is used to develop the rate law expressions for the flux in terms of a function Ψ(S*), which measures the quality of transport across the biofilm matrix. The Biofilm reaction rate at Monod's half-saturation concentration is calculated, which is superior to the microbial reaction rate in suspended cultures. The Biofilm's effectiveness factor has been developed based on Ψ(S*) and B. The biofilm number gives the knowledge about the nutrient-consuming capacity of the Biofilm. The model presented in this work can be a fundamental tool for designing a typical biofilm-based reactor. The Biofilm model has been validated using the experimental data from the studies by Shukla 2021.
ISSN:2666-8211