Modeling the Photocatalytic Process of Variation in Chemical Oxygen Demand via Stochastic Differential Equations
Adriano F. Siqueira*, Oswaldo L. C. Guimaraes, Helcio J. Izario Filho, Domingos S. Giordani, Ivy dos Santos Oliveira, Henrique Otavio Queiroz de Aquino, Messias Borges Silva
Identifiers and Pagination:Year: 2013
First Page: 1
Last Page: 8
Publisher Id: TOCENGJ-7-1
Article History:Received Date: 17/05/2011
Revision Received Date: 13/07/2012
Acceptance Date: 18/07/2012
Electronic publication date: 5/4/2013
Collection year: 2013
open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Several papers in the literature on Advanced Oxidation Processes (AOPs) confirm the process as a viable alternative for the treatment of a variety of industrial effluents. In many of these works, modeling the variations of Chemical Oxygen Demand (COD) as a function of different experimental conditions was performed by techniques such as Design of Experiments, Artificial Neural Networks and Multivariate Analysis. These techniques require both a large number of parameters and a large quantity of experimental data for a systematic study of the model parameters as a function of experimental conditions. On the other hand, the study of Stochastic Differential Equations (SDE) is presently well developed with several practical applications noted in the literature. This paper presents a new approach in studying the variations of COD in AOPs via SDE. Specifically, two effluents, from the manufacture of paints and textiles were studied by combined treatment of the photo-Fenton process and catalytic ozonization.