Advanced oxidation processes based on photo-Fenton chemistry have gained increasing attention as effective treatment alternatives for the removal of pharmaceutical contaminants from water and wastewater systems. However, large-scale implementation remains constrained by operational requirements, limited mineralization efficiency, and challenges associated with process stability and selectivity. This review provides a critical assessment of recent advances (2022–2025) in conventional photo-Fenton and hybrid systems, including photocatalysis/photo-Fenton and sono-photo-Fenton processes, with emphasis on their performance in water and wastewater treatment applications. The removal of non-steroidal anti-inflammatory drugs, antibiotics, pharmaceutical mixtures, and real wastewater matrices is analyzed considering catalyst configuration, irradiation sources, oxidant utilization, and operating conditions relevant to practical treatment scenarios. Conventional homogeneous Fe2+/H2O2 systems enable rapid contaminant degradation but typically require acidic conditions and show limited mineralization efficiency. In contrast, iron-complexed and heterogeneous catalysts allow operation under near-neutral pH and visible-light irradiation, improving applicability in realistic water treatment systems. Hybrid photocatalysis/photo-Fenton processes enhance treatment efficiency through synergistic generation of reactive oxygen species, while ultrasound-assisted systems further intensify oxidation rates and contaminant removal. Special attention is given to oxidation mechanisms, catalyst stability, transformation products, and toxicity evolution to identify the key factors controlling treatment performance. Finally, current technological limitations, operational challenges, and design considerations for process integration, scale-up, and sustainable implementation in water and wastewater treatment are discussed.
Building similarity graph...
Analyzing shared references across papers
Loading...
Enric Brillas
Juan M. Peralta-Hernández
Water
Universitat de Barcelona
Universidad de Guanajuato
Building similarity graph...
Analyzing shared references across papers
Loading...
Brillas et al. (Mon,) studied this question.
www.synapsesocial.com/papers/69df2c01e4eeef8a2a6b0fca — DOI: https://doi.org/10.3390/w18080920