| Issue |
E3S Web Conf.
Volume 527, 2024
The 4th Edition of Oriental Days for the Environment “Green Lab. Solution for Sustainable Development” (JOE4)
|
|
|---|---|---|
| Article Number | 02010 | |
| Number of page(s) | 10 | |
| Section | Environmental Pollution & Health Risks | |
| DOI | https://doi.org/10.1051/e3sconf/202452702010 | |
| Published online | 24 May 2024 | |
Optimization of micropollutant removal from wastewaters using the PROMETHEE multicriteria decision method
1 Engineering Sciences and Applications Laboratory, National School of Applied Sciences of Al-Hoceima, Abdelmalek Essaâdi University, Tetouan, Morocco
2 Laboratory of Functional Ecology and Environment Engineering, Faculty of Science and Technology of Fez, University of Sidi Mohammed Ben Abdellah, Fez 30500, Morocco
3 Geosciences research team on natural risks, Faculty of Science and Technology of Tangier, Abdelmalek Essaâdi University, Tetouan, Morocco
* Corresponding author: elhammoudani5@gmail.com
This article explores the use of multicriteria decision methods (MCDMs) to identify the optimum treatment for removing micropollutants from wastewater. With the increasing complexity of industrial and urban wastewater, which contains a wide range of micropollutants, it is becoming crucial to develop effective and sustainable treatment strategies. MCDMs provide a framework for evaluating a variety of treatments, considering several criteria, such as efficiency, cost, energy consumption, environmental impact and technical feasibility. This article examines different processing technologies and compares those using MCDM methods such as the preference ranking organization method for enrichment evaluation (PROMETHEE). Using this approach, this study proposes a systematic and objective method for identifying the most appropriate treatment options, facilitating more efficient wastewater management and protection of the aquatic environment.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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