Water reuse for drinking, irrigation, district cooling, process heating/cooling, landscaping, etc. remains pivotal to water security and sustainability. Advanced oxidation processes (AOPs) are at the heart of the industrial wastewater treatment especially for the removal of contaminants of emerging concern. Recent studies conducted to advance AOP technologies for the degradation of industrial wastewater pollutants generally encompass seven areas, namely artificial neural networks (ANNs), sustainability, plasma activation, catalyst structures, AOP-Bioremediation, and membrane-based AOPs. This review presents the advancements in AOPs for oxidation and removal of a wide range of contaminants of emerging concern from water. Detailed discussions and a critical examination of recently published works are presented in this article. Many of the reports have recorded technical progress in the form of: improved energy efficiency through the use of low-energy and renewable energy sources, successful prediction of process performance and process control, improved light capturing capabilities through plasmonic effect, successful integration with biological treatment methods and membrane filtration. In spite of this progress, a number of challenges still persist such as lack of appropriate ANN modeling structures, impractical spatial and temporal scales of investigation (i.e. scales that are too low for real operations), and membrane fouling in membrane-based AOPs. These challenges and the strategies for addressing them are discussed in this article. (C) 2020 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.