Dynamic validation of online applied and surrogate-based models for tertiary ozonation on pilot-scale

Abstract New robust correlation models for ozonation, based on UVA 254 and fluorescence surrogate parameters and developed considering kinetic information, have been applied at pilot-scale. This model framework is validated with the aim for operators to control the ozone dose for the removal of trace organic contaminants (TrOCs) in effluents from full-scale municipal wastewater treatment plants. The inflected correlation model between ΔTrOCs and the surrogates predicts the removal of TrOCs (based on statistical evidence) solely using the 2nd order reaction rate constant with ozone ( k O3 ) and in a more adequate manner than similar single correlation models. This allows the use of this new model for current and future TrOCs under investigation which is highly interesting when imposed discharge limits might include more and other TrOCs in future. The use of UVA 254 might be preferable at the current timing for online monitoring of TrOC abatement as the model showed a good predictive power (based on statistical evidence and visual confirmation). Reliable online sensors are more widespread (and commercially) available compared to fluorescence sensors which are still under development, with the exception of a few examples. Nevertheless, the data processing of the fluorescence signals, isolating the different intensities associated with moieties reacting similarly to ozone might even increase the predictive power, given the lower degree of interference (i.e. less scattering).