Modeling of photocatalytic oxidation reactor for methyl ethyl ketone removal from indoor environment: Systematic model development and validation

This paper describes the development of a model for predicting the performance of ultraviolet photocatalytic oxidation (UV-PCO) reactor for the removal of volatile organic compounds (VOCs) from indoor environment. The proposed model performance was validated at two stages. First, it was validated by comparing its performance with the prediction made by other models (inter-model comparison), and with experimental data from two different scales (pilot and bench) of UV-PCO reactors. A good agreement (with R-2 = 0.98) between the developed model prediction and the experimental data was observed. Simulation of light intensity with linear source spherical emission model (LSSE) in bench-scale reactor showed a more uniform distribution than pilot-scale, due to longer distance of the lamp from the media in the benchscale reactor. Beer-Lambert model demonstrated that light absorbed totally with one media, and adding extra media does not improve the PCO removal performance. Furthermore, Langmuir-Hinshelwood (L-H) rate expression by considering competitive effect of water and by-products with target compound was used. Formaldehyde and acetaldehyde were identified as the main by-products of the Methyl Ethyl Ketone (MEK) PCO reaction. A sensitivity analysis was performed to investigate the impact of three dimensionless parameters-Peclet (Pe), Stanton (St), and Damkohler (Da) numbers on the system performance. Simulation results indicated the UV-PCO process is mainly limited by the reaction rate at low removal efficiency. For higher removal efficiency, both the photochemical reaction rate and advective mass transfer have a significant impact on the system performance. The practical validation of the dimensionless model at two different scales of PCO reactor with same operating condition indicated that the proposed dimensionless model analysis can provide useful advice (qualitatively and quantitatively) for scale-up of PCO for the real application.

Automated summary

This paper presented a model for predicting UV-PCO reactor performance in removing VOCs from indoor environment, which was validated through inter-model comparison and experimental data. The study highlighted the impact of light distribution, light absorption, and competitive effects on system performance, providing insights for scale-up of PCO in real application.