Abstract

This research reports the development of a kinetic model to predict binary mixture degradation and by-product generation in a continuous flow Photocatalytic Oxidation (PCO) reactor. Butyraldehyde and acetone were chosen as a binary VOC mixture to validate the model using experiments conducted with a photocatalyst (TiO2 coated on silica fibers) under various concentration levels (0.1–1 ppm), concentration ratios of target compounds in the mixture (0.5–2), relative humidity levels (17–70%), irradiations (7–23.5 W/m2), and airflow rate (10–30 L/min). Formaldehyde, acetaldehyde, propionaldehyde, butyric acid, propionic acid, and acetic acid were detected as by-products, in which aldehydes had a higher quantity. Carbon balance analysis showed that butyraldehyde and binary mixtures mineralized into carbon dioxide at rates of 19% and 12.8%, respectively. Also, 24% of butyraldehyde and 10% of binary mixture were converted to by-products. Among three proposed scenarios for PCO reaction rate of butyraldehyde, the one including conversion of butyraldehyde directly towards propionaldehyde, acetaldehyde, and formaldehyde, provided the most accurate rate model (R2 = 0.98). Due to its faster reaction rate, butyraldehyde demonstrated a higher degradation efficiency than acetone in the binary mixture. At a constant butyraldehyde concentration, lowering the ratio of butyraldehyde/acetone to 0.5 resulted in the reduction of removal efficiency of butyraldehyde and an increase in concentration of acetaldehyde in air than other by-products. Conversely, enhancing this ratio to 2, led to improved removal efficiency of both butyraldehyde and acetone in the mixture and higher concentration of formaldehyde. Increases in air relative humidity level and velocity resulted in an increase in the outlet concentration of challenge compounds but reduced the formation of all by-products. However, raising the irradiation increased the degradation efficiency of butyraldehyde and binary mixture and, consequently, elevated the formation of by-products. The developed model was capable of properly predicting the concentration of the challenge compounds and their by-products in a binary mixture at different operating conditions.

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