Modeling and optimizing electro Fenton process for silica removal to prevent RO membrane fouling in brackish water desalination.

Abstract

Due to high silica concentrations, silica scaling of reverse osmosis (RO) membranes in brackish water desalination poses very serious issues in the cost-effectiveness of desalination processes. The advanced Fenton process (AFP) is one of the most effective water treatment processes. Coagulation of silica on ferric hydroxide and flocculation are the main processes used to remove silica. This process depends on several operating parameters such as hydrogen peroxide and zero-valent metal iron Fe⁰ dosage, initial and equilibrium pH. In this study, we examined the use of Artificial Neural Networks (ANNs) to optimize those parameters using an experimental dataset. For a removal of 71.3%, the optimum operating parameters were: initial pH 2, equilibrium pH 8, iron dosage 15 g/L and hydrogen peroxide 18 mM. We show that the environmentally friendly Fenton process was economically feasible, being able to attain up to 71.2% silica removal with a total cost of $2.09 m^-3 for a typical desilication unit producing 1,000 m³/day.