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Evaluation of the lead removal capacity by the adsorption process of Corbula trigona shell powder: modeling and optimization through reponse surface methodology
This study is based on the evaluation of the adsorption process using Corbula trigona shell powder to remove lead from aqueous solution in a batch mode. Different analytical techniques, including X-ray diffraction, Fourier transform infrared spectroscopy, and EDS-coupled scanning electron microscopy...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Royal Society of Chemistry
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10088489/ https://www.ncbi.nlm.nih.gov/pubmed/37057272 http://dx.doi.org/10.1039/d3ra00562c |
Sumario: | This study is based on the evaluation of the adsorption process using Corbula trigona shell powder to remove lead from aqueous solution in a batch mode. Different analytical techniques, including X-ray diffraction, Fourier transform infrared spectroscopy, and EDS-coupled scanning electron microscopy, were used to characterize the shell powder before and after lead treatment. Regarding the pollutant removal, a Plackett–Burman design (PBD) was first used to determine the influencing factors from the following experimental domain: solution pH (3–9), adsorbent mass (0.1–0.5 g), contact time (40 –240 min), initial pollutant concentration (10 –60 mg L(−1)), and adsorbent size (100 –200 μm). The respective contributions of the various factors listed above are 31.7%, 30.51%, 25.17%, 12.44%, and 0.18%. As a result, solution pH, adsorbent mass, contact time, and initial pollutant concentration were selected to optimize the lead removal process using the composite central plan. The optimal lead removal conditions were 99.028% by setting the solution pH to 4.5, initial lead concentration to 47 mg L(−1), contact time to 125 min, and adsorbent mass to 0.2 g. In addition, it was found that the composite central plan could be a reliable statistical tool to model and determine the optimal conditions. |
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