Systematic optimization approach for the efficient management of the photo-Fenton treatment process

摘要

The photo-Fenton process is a photochemical process that has proved to be highly efficient in degrading new potentially harmful contaminants. Despite of this, scarce attention has been paid to the development of systematic procedures and optimisation strategies to efficiently operate such a process. The present work aims at investigating the effectiveness of a model-based approach in carrying out the dynamic optimisation of the recipe of a photo-Fenton process, performed in fed-batch mode (reactant dosage).This work has addressed and solved multiple optimisation problems, searching for the optimal hydrogen peroxide (H2O2) dosage profile, and Pareto frontiers have been built accordingly in order to point out the interaction between three main process efficiency parameters, such as processing time, total amount of H2O2 used, and Total Organic Carbon (TOC) removal. Such a study allows mapping the best operating conditions and provides a decision-making oriented overview of the process. An economic study has also been carried out with the aim of finding out the optimal H2O2 dosage profile that guarantees the minimum operating cost under a varying set of operational and environmental constraints, such as TOC removal.This work has adopted and properly adapted the model by Cabrera Reina et al. (2012) in order to describe the evolution of the systemunder a flexible reactant dosage. Cabrera Reina et al. (2012) proposed a semi-empirical kinetic model to track paracetamol degradation using the photo-Fenton process and experimentally validated this model for a pollutant load range between 4 and 25 mmol L-1 of TOC (e.g. industrial wastewaters). Dynamic optimisation has been addressed applying a direct simultaneous optimisation method using this extended model. Results have been presented and discussed in regard of optimal H2O2 dosage under both economic and environmental constraints. The model-based optimisation approach has allowed a fast practical recipe adjustment with reduced experimental work. (C) 2018 Published by Elsevier B.V.