Modeling the photocatalytic degradation of moxifloxacin by means of a stochastic cellular automaton

Fluoroquinolones are a family of synthetic broad-spectrum, antibacterial compounds, with ciprofloxacin and moxifloxacin being two of the most important members. Although very efficient and active, they are incompletely metabolized during human therapy and traditional wastewater treatment plants cannot remove them completely, so that they accumulate in the environment. Research is therefore directed towards novel methods, such as TiO2-assisted photocatalysis, to achieve complete mineralization of organic contaminants. Despite the great potential of photocatalysis and the ongoing research in this field, the reaction mechanism behind photocatalysis is still not completely elucidated and the oxide surfaces of the TiO2 photocatalyst are more complex than anticipated, which hampers the development of a mathematical model for describing photocatalytic degradation. In this paper, a stochastic cellular automata based model is proposed to simulate the mechanism behind photocatalysis. The model is validated and evaluated through sensitivity analysis. Subsequently, it is parameterized using experimental data from a lab-scale batch reactor.

► Cellular automata based model of heterogeneous photocatalysis.
► Stochastic transition function with diffusion and reaction parts.
► Model parameters for adsorption and catalysis most sensitive.
► Model parameterized with experimental data via grid search.