A technique for obtaining representative biokinetic parameter values from replicate sets of parameter estimates

The rational design and simulation of biotreatment systems requires sound mathematical models and reliable parameter estimates. Biodegradation kinetics are usually modeled using the Monod or Andrews equation, and model parameters are usually obtained by fitting an observed concentration-time profile to the model. Since the nature of the models and the method of parameter estimation result in correlation between the parameters, the question arose as to how to obtain a single set of Parameters Representing the Average μ-S response (referred to as PRAMUS values) from replicate sets of experimentally derived parameter estimates. The common approach of using the arithmetic mean parameter values was adequate only for data conforming to the Monod model, particularly when the variability among replicate parameter estimates was small. For the Andrews model, nonlinear regression was used to obtain PRAMUS values. The ability of the PRAMUS and mean parameter values to reproduce the average μ-S response and to simulate experimentally observed oxygen uptake was evaluated. On this basis, the use of PRAMUS values is recommended, particularly when dealing with systems modeled by the Andrews equation, with experimental data characterized by a high degree of experimental variability, and/or with process situations where high substrate concentrations are likely to be encountered, e.g. shock loads.