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

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

Jagannathan Krishnan (Universti Teknologi MARA, Malaysia), Eldon Raj Rene (University of La Coruña,, Spain), Artem A. Lenskiy (University of Ulsan, South Korea) and Tyagarajan Swaminathan (Indian Institute of Technology Madras, India)
DOI: 10.4018/978-1-4666-1833-6.ch015
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Volatile organic compounds (VOCs) belong to a new class of air pollutant that causes significant effect on human health and environment. Photocatalytic oxidation is an innovative, highly efficient, and promising option to decontaminate air polluted with VOCs, at faster elimination rates. This study pertains to the application of artificial neural networks to model the removal dynamics of an annular type photoreactor for gas – phase VOC removal. Relevant literature pertaining to the experimental work has been reported in this chapter. The different steps involved in developing a suitable neural model have been outlined by considering the influence of internal network parameters on the model architecture. Anew, the neural network modeling results were also subjected to sensitivity analysis in order to identify the most influential parameter affecting the VOC removal process in the photoreactor.
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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.

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