Recycling fruit peels into :magnetite/carbon adsorbents: A scalable solution for pyrethroid insecticide removal

Bifenthrin (BFN) which is the most stable pyrethroid pesticide was aimed to be removed by the laboratory prepared adsorbents from sweet lime peels. Comparative studies of the activated carbon sweet lime peels (ACSLP) & magnetized nano-composites (MGNC) with that of untreated sweet lime peels...

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Bibliographic Details
Main Authors: Bilal Ashraf, Shafaq Mubarak, Amina Asghar, Abdul Hafeez, Furqan Asif
Format: Article
Language:English
Published: Elsevier 2025-01-01
Series:Desalination and Water Treatment
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Online Access:http://www.sciencedirect.com/science/article/pii/S1944398624203945
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Summary:Bifenthrin (BFN) which is the most stable pyrethroid pesticide was aimed to be removed by the laboratory prepared adsorbents from sweet lime peels. Comparative studies of the activated carbon sweet lime peels (ACSLP) & magnetized nano-composites (MGNC) with that of untreated sweet lime peels (USLP) were carried out to estimate the percentage uptake of BFN by the adsorbents before and after modification. The adsorbents prepared were characterized by SEM, EDX, XRD, FTIR & VSM (Vibrating-sample magnetometer). It is revealed from the characterization that the hydroxyl group present in adsorbents is mainly responsible for adsorption, further, it was seen that an extra peak at 523 cm−1 shows the existence of iron oxide in magnetized peels. SEM-EDX results shows an increase in amounts of iron and oxygen which leads to successful magnetization of peels. Biosorption experiments were conducted by altering various parameters, including adsorbent dosage, initial adsorbate concentration, contact time, temperature, and pH. It was observed that the adsorption capacity ‘q max’ for ACSLP & MGNC increased from 35 to 78 and 83 mg/g respectively for mitigation of BFN. Analysis of the kinetic data indicated that the pseudo-second-order model provides the best fit for the adsorption process studied. Both the Langmuir and Freundlich isotherm models showed high degrees of linear correlation.
ISSN:1944-3986