Nanoparticle scattering characterization and mechanistic modelling of UV-TiO2 photocatalytic reactor using computational fluid dynamics

A computational fluid dynamic (CFD) model was developed to describe the process performance of a semi-batch annular TiO2-UV photoreactor in an Eulerian framework. The model accounted for the optical behaviour of titanium dioxide (TiO2) suspensions, the flow distribution and the oxalic acid degradation in the reactor. The scattering component of the optical model, explicitly included in the CFD simulations using a TiO2-specific scattering phase function integrated in the radiative transfer equation, was calibrated using an optical goniometer by comparing simulated scattering light profiles against irradiance measurements collected for various TiO2 concentrations and UV wavelengths and subsequently solved by the discrete ordinate (DO) radiation model. Several scattering phase functions were tested against the goniometric measurements confirming that the Henyey-Greenstein (HG) equation was the most appropriate angular distribution function at 254 and 355 nm, irrespective of the TiO2 concentration. Using the calibrated HG function, a new approach for quantifying the absolute values of absorption and scattering coefficients in TiO2 suspensions was proposed. It consists of iteratively solving, using the DO model, the radiative transfer equation for various combinations of absorption and scattering coefficients until the error between observed and predicted angular irradiance measurements is minimized. The accuracy of the optical parameters was verified with independent CFD simulations carried out for an annular photoreactor and already available in the literature. Predicted and simulated irradiance and oxalic acid degradation data were found to be in excellent agreement, confirming the considerable potential of the integrated modelling approach presented in this paper for the design, optimization and scale-up of photocatalytic technologies for water and wastewater treatment applications.