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}$$K_{w,i}$), adsorption coefficients ($K_i$$K_i$) and overall reaction rates ($k_{\mathit{overall}}$$k_{\mathit{overall}}$) within the Langmuir-Hinshelwood (L-H) model were developed, and used to predict the outlet concentrations of by-products of the proposed reaction pathways for challenging VOCs, including ethanol, 2-propanol, acetone, and methyl ethyl ketone (MEK). Experimental validation using acetone, 2-propanol, and ethanol degradation demonstrated the model’s effectiveness in forecasting by-product generation in UV-PCO processes. Additionally, an evaluation index ($I_i$$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$$I_i$ was estimated for different VOCs under the various relative humidity, revealing that a positive IAQ impact under worst-case conditions (acetone degradation at 70% relative humidity) requires enhanced UV-PCO performance and acetaldehyde removal exceeding 46% to ensure effectiveness ($I_i<1$$I_i<1$). This study provides key insights to enhance the effectiveness and safety of UV-PCO systems in real-world air purification applications.