Prediction of by-product generation in gaseous ultraviolet photocatalytic oxidation processes

By-product generation poses a significant challenge in ultraviolet photocatalytic oxidation (UV-PCO) processes for removing gaseous volatile organic compounds (VOCs). It must be carefully addressed when evaluating and optimizing UV-PCO-based air purifiers. This study establishes a comprehensive modeling framework to predict and mitigate by-product generation in UV-PCO systems, bridging a critical research gap. Regression models for water adsorption coefficients (K_w,i), adsorption coefficients (K_i) and overall reaction rates (k_overall) within the Langmuir-Hinshelwood (L-H) model were developed, and used to predict the outlet concentrations of by-products of the proposed reaction pathways for challenging VOCs, including ethanol, 2-propanol, acetone, and methyl ethyl ketone. Experimental validation using acetone, 2-propanol, and ethanol degradation demonstrated the model's effectiveness in forecasting by-product generation in UV-PCO processes. Additionally, an evaluation index (I_i) was introduced to quantify the system's impact on indoor air quality (IAQ), incorporating 8-hour occupational exposure limits for toxic by-products. I_i was estimated for different VOCs under the various relative humidity, revealing that a positive IAQ impact under worst-case conditions (acetone degradation at 70 % relative humidity) requires enhanced UV-PCO performance and acetaldehyde removal exceeding 46 % to ensure effectiveness (I_i<1). This study provides key insights to enhance the effectiveness and safety of UV-PCO systems in real-world air purification applications.