A new approach to optimise an annular slurry photoreactor system for the degradation of Congo Red: Statistical analysis and modelling

This study utilised design of experiment, and statistical and modelling tools to understand and optimise photodegradation performance of an annular slurry photoreactor (ASP) system using a newly developed titania impregnated kaolinite photocatalyst (TiO2-K) for the degradation of Congo Red (CR). Using a Taguchi orthogonal array of L9 (3)4, only 9 experiments were required, instead of 81 experiments in a conventional one-factor-at-a-time approach, to optimise the operational factors of TiO2-K loading, pH, aeration rate and CR concentration, and to determine their synergistic factor interactions in the ASP system. The apparent first-order rate constants estimated from the Langmuir–Hinshelwood (L–H) model were assigned as the output responses in the designed array. Analysis of variance showed that the CR concentration appears to be the most significant factor, while pH is the least influential on the photodegradation rate. The response surface model with Box–Cox power iterative procedure was used to model the different output responses and determine the synergistic interactions between the system factors. The optimal operating conditions obtained from numerical simulation were regressed to yield an empirical predictive model for modelling the photoactivity in the ASP system. It is anticipated that this statistical model can be used as an effective design tool for scaling up a photocatalytic process for water treatment.