Development of an Intelligent Neural Model to Predict and Analyze the VOC Removal Pattern in a Photocatalytic Reactor

Photoreactor For Voc Removal And Working Mechanism

Among the different techniques, chemical and – or biological, used for the removal of gas – phase VOCs, photocatalytic oxidation process can be considered as ‘’an innovative and promising technology to completely oxidize high concentrations of VOCs to harmless end – products such as H₂O and CO₂, at ambient temperatures’’. Titanium dioxide (TiO₂) irradiating with UV or near UV light, results in the formation of ‘electron – hole pairs’ on the catalyst surface. These electrons and holes interact with the adsorbed species producing highly reactive hydroxyl radicals, which in turn initiate redox reactions to decompose VOCs. In some cases, it has been proved that the activity of TiO₂ could be greatly enhanced by modifying the catalyst properties. Zuo et al. (2006) gave sufficient information on the benefits of modifying a photocatalyst, as; (i) inhibiting electron–hole recombination by increasing the charge separation, (ii) increasing the wavelength response range, and (iii) changing the selectivity or yield of a particular product.

According to Wang and Ray (2000), the application of photo oxidation technique for gas – phase VOC removal is more appealing due to the following reasons: (i) lower UV absorption by air than water; (ii) higher mobility of dissociated species which prevents the reverse process of recombination of the radicals; (iii) higher UV –absorbance of the organics in the gas – phase compared to that in the liquid phase, (iv) presence of excess oxygen in the gas – phase promotes oxidation by producing reactive species such as ozone, and (v) the absence of scavengers such as bicarbonate and carbonate ions.