Modeling reaction kinetics of chlorine dioxide and volatile organic compounds with artificial neural networks

Increasing public concerns over odors and air regulations in non-attainment zones necessitate the remediation of a wide range of volatile organic compounds (VOCs) generated in the poultry-rendering industry. Currently, wet scrubbers using oxidizing chemicals, such as chlorine dioxide (ClO2), are applied to remove VOCs. However, little information is available on the kinetics of chlorine dioxide reaction with rendering air pollutants, which limits wet scrubber design and optimization. Kinetic analysis indicated that chlorine dioxide does not react with aldehydes under typical conditions, while thiols and disulfides rapidly reacted with chlorine dioxide. Moreover, pH can affect their reaction rates significantly. In order to obtain the kinetic data without the study of their complex reaction mechanisms, artificial neural networks (ANNs) were used to model the reactions of chlorine dioxide and VOCs. For the oxidation of single VOC, a standard three-layer back-propagation ANN was developed to predict the reaction rates. For VOC mixtures, a Ward ANN provided the best performance. The final models can be used to predict the initial ClO2 reaction rates with ethanethiol or DMDS for the design and optimization of wet scrubbers.