Predictive Modeling of Air Purification Efficiency in Nano-TiO2-Modified Photocatalytic Cementitious Composites Using High-Resolution EDS Mapping and Mercury Intrusion Porosimetry

This study investigates the relationship between surface properties and microstructural characteristics of photocatalytic composites and their impact on air purification efficiency. High-resolution energy-dispersive X-ray spectroscopy (EDS) mapping and mercury intrusion porosimetry (MIP) were employed to analyze photocatalyst distribution and pore structure quantitatively. The findings demonstrated a strong correlation between TiO2 coverage on the photoactive surface and NO removal rates and between pore structure characteristics and NO2 generation rates. Two predictive models were developed to link NOx removal rates with photocatalytic cementitious mortars’ surface and structural properties. A stepwise regression approach produced a second-degree polynomial model with an adjusted R2 of 0.98 and a Mean Absolute Percentage Error (MAPE) of 8.34%, indicating high predictive accuracy. The results underscore the critical role of uniform photocatalyst distribution and optimized pore structure in enhancing NOx removal efficiency while promoting the generation of desirable products (NO3−) and minimizing the formation of undesirable byproducts (NO2).