Abstract
Many studies of the photocatalytic oxidation process investigated on the removal efficiency and other variables of the input and output photoreactor. In the laboratory scale, it’s impossible, examination of the removal efficiency details, such as mass and energy transfer with air flow rate. Also, experimental methods request time consumption and money. For this reason, the simulation method can be used. The aim of this study was to prove that the validation of modeling approach in the photocatalytic oxidation process in the removal of toluene from air. Investigation of bed surface morphology, with FESEM, BET and TGA, shows acceptable monotonous of TiO2 nanoparticles on the ss plate. Furthermore, it was observed good adherence of nanoparticles on it. Experimental results on photocatalytic bed surface exhibited in the toluene concentration range of 10–40 ppm and flow rate of 2–5 l/min, with increasing flow and decreasing concentration, removal efficiency increased. The optimum removal point was 59% and 25 g/m3 min for 3.75 ppm and 5.61 l/min. For bed surface performance, the correlation between experimental results and simulation data was obtained 98%. According to the results, the photocatalytic oxidation process performed well for removal of low concentration of toluene from air. In addition, the obtained simulation method eliminated the random factors which can be affected by photocatalytic bed surface and it can show dependence of results based on reality.
Funding source: Qazvin University of Medical Sciences
Award Identifier / Grant number: 14004340 (IR.QUMS.REC.1399.056)
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Research funding: This study is done as a research project with a code of 14004340 (IR.QUMS.REC.1399.056). This work is supported by the Qazvin University of Medical Sciences in all stages. We thank the University for technical assistance in the experimental examination.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/ijcre-2022-0173).
© 2023 Walter de Gruyter GmbH, Berlin/Boston
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