Generalized Richards model of slow sand filtration to remove lead pollutant from polluted waters: study of velocity effect

• Published in: Desalination and water treatment 2024-10, Vol.320, p.100728, Article 100728
• Main Authors: Elhaya, Nassima, EL Fadeli, Sana, Abbassi, Abdelilah, Erraji, El Mahdi, Barkouch, Yassir
• Format: Article
• Language: English
• Subjects: Generalized Richards model; Metallic trace elements; Slow sand filtration; Tensift river Marrakech; Water
• ISSN: 1944-3986
• DOI: 10.1016/j.dwt.2024.100728

In Morocco, numerous regions face water scarcity. To address water shortages in the arid Marrakech region, agricultural reuse of wastewater can be a viable solution, provided that accessible and cost-effective methods, such as slow sand filtration, are employed to reduce pollutant levels. In the vicinity of the Mine Draa Lasfar, wastewater discharged into the Tensift River has led to significant contamination by metallic trace elements, including lead (Pb). This contamination spreads from the water to the soil, plant cover, and living organisms, with severe Pb contamination observed in children, leading to serious neurological diseases. Addressing this critical issue, our study explores the application of slow sand filtration for water treatment. This method is reliable and environmentally friendly, particularly effective at lower water velocities, ensuring optimal contaminant removal. We introduced the Generalized Richards model, a versatile mathematical tool, which outperformed the standard logistic model by providing a more accurate fit to our experimental data. In conclusion, slow sand filtration, when implemented in areas like Mine Draa Lasfar, offers a promising solution for mitigating metallic trace elements contamination in water sources, with the Generalized Richards model enhancing our understanding and optimization of the filtration process. [Display omitted] •Slow Sand Filtration (SSF) Method Proposed to Reduce Metallic Trace Element pollution from Draa Lasfar mine into Morocco’s Tensift River.•Generalized Richards model to understand contaminant behaviour during SSF, offering mathematical Insight.•Comparison shows Generalized Richards model outperforms classical logistic model in predicting contaminant concentrations accurately.