Optimized Membrane Fouling Prediction and Mitigation for Improved Water Treatment: a Review

Abstract

This review article presents recent advancements in membrane filtration technologies, particularly focusing on fouling mechanisms affecting reverse osmosis (RO) membranes. It presents a comprehensive analysis of various studies conducted over the past two decades, highlighting the complexities of membrane fouling caused by natural organic matter (NOM), particulate matter, and biofouling. The review also examines innovative modelling approaches to predict fouling behaviour, including the development of the Membrane Fouling Index-Ultrafiltration (MFI-UF) method and the application of advanced characterization techniques such as optical coherence tomography (OCT) and Near-Edge X-ray Absorption Fine Structure (NEXAFS) spectroscopy. Additionally, it discusses the effectiveness of pre-treatment strategies, including coagulation and flocculation in mitigating fouling and enhancing membrane performance. Finally, the integration of artificial intelligence (AI) in predicting fouling behaviour is also highlighted, with emphasis on its potential to optimize operational parameters in membrane systems.