Artificial intelligence driven advances in wastewater treatment: Evaluating techniques for sustainability and efficacy in global facilities

Desalination and Water Treatment, Journal Year: 2024, Volume and Issue: 320, P. 100618 - 100618

Published: July 17, 2024

Language: Английский

---

The Evolving Landscape of Advanced Oxidation Processes in Wastewater Treatment: Challenges and Recent Innovations

Processes, Journal Year: 2025, Volume and Issue: 13(4), P. 987 - 987

Published: March 26, 2025

The increasing presence of persistent pollutants in industrial wastewater underscores the shortcomings conventional treatment methods, prompting adoption advanced oxidation processes (AOPs) for sustainable water remediation. This review examines development AOPs, focusing on their ability to produce hydroxyl radicals and reactive oxygen species (ROS) mineralize complex pollutants. Homogeneous systems such as Fenton’s reagent show high degradation efficiency. However, challenges like pH sensitivity, catalyst recovery issues, sludge generation, energy-intensive operations limit scalability. Heterogeneous catalysts, TiO2-based photocatalysts Fe3O4 composites, offer improved adaptability, visible-light activation, recyclability. Emerging innovations ultraviolet light emitting diode (UV-LED)-driven systems, plasma-assisted oxidation, artificial intelligence (AI)-enhanced hybrid reactors demonstrate progress energy efficiency process optimization. Nevertheless, key remain, including secondary byproduct formation, mass transfer constraints, economic feasibility large-scale applications. Integrating AOPs with membrane filtration or biological treatments enhances synergy, while advances materials science computational modeling refine design reaction mechanisms. Addressing barriers use, durability, practical adaptability requires multidisciplinary collaboration. highlights pivotal solutions security amid growing environmental pollution, urging targeted research bridge gaps between laboratory success real-world implementation.

Language: Английский

---

Artificial neural networks applied to photo-Fenton process: An innovative approach to wastewater treatment

Water Science and Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

---

Energy Optimization and AI-Powered Adsorption Technologies for Sustainable Water Treatment

Advances in civil and industrial engineering book series, Journal Year: 2025, Volume and Issue: unknown, P. 159 - 182

Published: Feb. 14, 2025

The integration of energy optimization and AI-powered adsorption technologies holds significant potential for sustainable water treatment. This chapter discusses advanced methods adsorption, amplified by artificial intelligence, in a bid to solve the challenge quality with minimized consumption. Some focus areas include predictive models AI-driven efficiency, real-time monitoring contaminants, adsorbent materials. is an area where machine learning deep techniques enhance treatment systems greater operational less footprint, more scalable. Other novel adsorbents nanomaterials which have been discussed this chapter, discussion on possibility realizing high capacity selectivity. explores AI analytics enhancing global sustainability goals presenting case studies practical frameworks demonstrate feasibility real-world applications.

Language: Английский

---

Water quality index and life cycle assessment of wastewater treatment plant: Feasibility of effluent reuse

Journal of Water Process Engineering, Journal Year: 2025, Volume and Issue: 75, P. 107949 - 107949

Published: May 17, 2025

Language: Английский

---

Hybrid data driven approach based on ANNs-PCA for wastewater treatment plant performance assessment

Cleaner Water, Journal Year: 2024, Volume and Issue: unknown, P. 100058 - 100058

Published: Dec. 1, 2024

Language: Английский

---