Evaluation of parameter estimation methods for ozone disinfection kinetics

Inactivation data with ozone in a CSTR system were analyzed using error-in-variables method (EVM), forced linearization and classical nonlinear regression. Their relative efficiency was compared statistically. The Monte Carlo simulations demonstrated that the EVM produces parameter estimates with the least bias and minimum variance of residuals from the regression. Although used traditionally, the forced linearization would give the biased parameter estimates of kinetics and lead to the potential of misinterpreting the type of inactivation. Requiring the ad hoc assumption of first order decay rate, the classical nonlinear regression is of little use in practice. Fitting the kinetic model to experimental data shows that the behavior of the bacteria and virus inactivation can be well described by predictions from EVM estimates. The resultant coefficient of dilution (n), defined as equation (1) was found to be much higher than one, indicating that the ozone concentration is a dominant factor over the contact time in determining the efficiency of ozone disinfection processes.