Electrochemical activation of alum sludge for the adsorption of lead (Pb(II)) and arsenic (As): Mechanistic insights and machine learning (ML) analysis DOI
Hye-Bin Kim, Muhammad Fahad Ehsan, Akram N. Alshawabkeh

et al.

Bioresource Technology, Journal Year: 2025, Volume and Issue: unknown, P. 132563 - 132563

Published: April 1, 2025

Language: Английский

Predicting biomass conversion and COD removal in wastewater treatment by phototrophic bacteria with interpretable machine learning DOI
Pengfei Hou, Shiqi Liu,

Duofei Hu

et al.

Journal of Environmental Management, Journal Year: 2025, Volume and Issue: 375, P. 124282 - 124282

Published: Jan. 24, 2025

Language: Английский

Citations

2
Triggering nanoconfinement effect in advanced oxidation processes (AOPs) for boosted degradation of organic contaminants: A review DOI
Junsuo Li,

Yongshuo Wang,

Ziqian Wang

et al.

Chemical Engineering Journal, Journal Year: 2024, Volume and Issue: 503, P. 158428 - 158428

Published: Dec. 9, 2024

Language: Английский

Citations

9
Recent advancements on elimination of emerging contaminants by homogeneous metal-catalyzed sulfur(Ⅳ) oxidation DOI

Shijie Kuang,

Hongbin Wang,

Youlun Su

et al.

Chemical Engineering Science, Journal Year: 2025, Volume and Issue: unknown, P. 121320 - 121320

Published: Feb. 1, 2025

Language: Английский

Citations

0
Application of Machine Learning Algorithms for the Prediction of Metformin Removal with Hydroxyl Radical-Based Photochemical Oxidation and Optimization of Process Parameters DOI

Narmin Garazade,

Emine Can‐Güven, Fatih Güven

et al.

Journal of Hazardous Materials, Journal Year: 2025, Volume and Issue: 489, P. 137552 - 137552

Published: Feb. 9, 2025

Language: Английский

Citations

0
The Evolving Landscape of Advanced Oxidation Processes in Wastewater Treatment: Challenges and Recent Innovations DOI Open Access

Satyam Satyam,

Sanjukta Patra

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

Citations

0
Enhanced ultrasonic degradation of organic contaminants: Synergistic promotion effects of iron salts and mechanical agitation DOI
Li Zhu, Lijuan Zhang,

Xizi Gao

et al.

Journal of Water Process Engineering, Journal Year: 2025, Volume and Issue: 72, P. 107567 - 107567

Published: April 1, 2025

Language: Английский

Citations

0
Analysis of Ecosystem Service Bundles and Influencing Factors Based on Sofm and Xgboost Models: A Case Study of the Western Dabie Mountains, a Typical Forest Ecosystem in China DOI
Yong Cao,

B. A. C. DON,

Hao Wang

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Electrochemical activation of alum sludge for the adsorption of lead (Pb(II)) and arsenic (As): Mechanistic insights and machine learning (ML) analysis DOI
Hye-Bin Kim, Muhammad Fahad Ehsan, Akram N. Alshawabkeh

et al.

Bioresource Technology, Journal Year: 2025, Volume and Issue: unknown, P. 132563 - 132563

Published: April 1, 2025

Language: Английский

Citations

0