Mechanistic model for evaluating the performance of suspended growth bioreactors for the off-gas treatment of VOCs

A mechanistic model capable to predict toluene removal in suspended growth bioreactors (SGRs) was proposed and validated. The model predicted with reasonable accuracy both toluene elimination capacities (11% of relative average error) and biomass concentration (6% of relative average error) in a Pseudomonas putida F1 culture growing in a lab-scale chemostat. Unlike previously reported mechanistic models this holistic model was capable to predict process performance under toluene, oxygen or nutrient limiting conditions. Mass transport, Henry law, and biomass yield coefficients were the most significant parameters influencing model predictions as shown by the sensitivity analysis performed. In addition, an innovative vector-based solving approach was proposed, which allowed reducing the complex systems of eight non-linear algebraic equations into a single equation and provided the dimensionless numbers necessary for bioreactor scale-up. Being based in general kinetic and mass transport equations it can be adapted to other processes where mass transport from a gaseous to an aqueous phase is involved.