Evaluation of novel NaOH/activated carbon/zeolite biocomposite as an efficient adsorbent for oilfield produced water treatment
This study investigates the efficiency of a sodium hydroxide-modified biocomposite, synthesized from zeolite and activated carbon derived from coconut shells, for the removal of hydrocarbon from produced water. The adsorption process was optimized using Response Surface Methodology (RSM) and Artific...
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Elsevier
2025-01-01
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Series: | South African Journal of Chemical Engineering |
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Online Access: | http://www.sciencedirect.com/science/article/pii/S1026918524001458 |
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author | Eghe Amenze Oyedoh Onyedikachi Praise Igbokwe |
author_facet | Eghe Amenze Oyedoh Onyedikachi Praise Igbokwe |
author_sort | Eghe Amenze Oyedoh |
collection | DOAJ |
description | This study investigates the efficiency of a sodium hydroxide-modified biocomposite, synthesized from zeolite and activated carbon derived from coconut shells, for the removal of hydrocarbon from produced water. The adsorption process was optimized using Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) integrated with genetic algorithms. The results indicated a hydrocarbon removal efficiency of 99.86 % with RSM and 99.99 % with ANN under optimal conditions. The ANN model demonstrated superior predictive accuracy (R² = 0.9984, MSE = 0.4004, RMSE = 0.6328) compared to RSM (R² = 0.9976, MSE = 0.5635, RMSE = 0.7507). Characterization techniques, including Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD), Brunauer–Emmet–Teller (BET) analysis, and Energy Dispersive X-ray Spectroscopy (EDX), confirmed the successful integration of zeolite onto activated carbon and the presence of active functional groups favorable for hydrocarbon adsorption. The Redlich-Peterson model was identified as the best fit for the experimental data, highlighting the biocomposite's potential as an effective adsorbent for treating produced water. These findings show the promising application of NaOH-modified AC-ZE biocomposites in achieving sustainable development goals. |
format | Article |
id | doaj-art-f66dacd0b9854b18aab2ae8c5612004d |
institution | Kabale University |
issn | 1026-9185 |
language | English |
publishDate | 2025-01-01 |
publisher | Elsevier |
record_format | Article |
series | South African Journal of Chemical Engineering |
spelling | doaj-art-f66dacd0b9854b18aab2ae8c5612004d2025-01-19T06:24:20ZengElsevierSouth African Journal of Chemical Engineering1026-91852025-01-0151302314Evaluation of novel NaOH/activated carbon/zeolite biocomposite as an efficient adsorbent for oilfield produced water treatmentEghe Amenze Oyedoh0Onyedikachi Praise Igbokwe1Department of Chemical Engineering, University of Benin, Benin City, NigeriaCorresponding author at: University of Benin, Nigeria.; Department of Chemical Engineering, University of Benin, Benin City, NigeriaThis study investigates the efficiency of a sodium hydroxide-modified biocomposite, synthesized from zeolite and activated carbon derived from coconut shells, for the removal of hydrocarbon from produced water. The adsorption process was optimized using Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) integrated with genetic algorithms. The results indicated a hydrocarbon removal efficiency of 99.86 % with RSM and 99.99 % with ANN under optimal conditions. The ANN model demonstrated superior predictive accuracy (R² = 0.9984, MSE = 0.4004, RMSE = 0.6328) compared to RSM (R² = 0.9976, MSE = 0.5635, RMSE = 0.7507). Characterization techniques, including Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), X-ray Diffraction (XRD), Brunauer–Emmet–Teller (BET) analysis, and Energy Dispersive X-ray Spectroscopy (EDX), confirmed the successful integration of zeolite onto activated carbon and the presence of active functional groups favorable for hydrocarbon adsorption. The Redlich-Peterson model was identified as the best fit for the experimental data, highlighting the biocomposite's potential as an effective adsorbent for treating produced water. These findings show the promising application of NaOH-modified AC-ZE biocomposites in achieving sustainable development goals.http://www.sciencedirect.com/science/article/pii/S1026918524001458AdsorptionWastewater treatmentArtificial neural networkResponse surface methodologyOil removalCoconut shell |
spellingShingle | Eghe Amenze Oyedoh Onyedikachi Praise Igbokwe Evaluation of novel NaOH/activated carbon/zeolite biocomposite as an efficient adsorbent for oilfield produced water treatment South African Journal of Chemical Engineering Adsorption Wastewater treatment Artificial neural network Response surface methodology Oil removal Coconut shell |
title | Evaluation of novel NaOH/activated carbon/zeolite biocomposite as an efficient adsorbent for oilfield produced water treatment |
title_full | Evaluation of novel NaOH/activated carbon/zeolite biocomposite as an efficient adsorbent for oilfield produced water treatment |
title_fullStr | Evaluation of novel NaOH/activated carbon/zeolite biocomposite as an efficient adsorbent for oilfield produced water treatment |
title_full_unstemmed | Evaluation of novel NaOH/activated carbon/zeolite biocomposite as an efficient adsorbent for oilfield produced water treatment |
title_short | Evaluation of novel NaOH/activated carbon/zeolite biocomposite as an efficient adsorbent for oilfield produced water treatment |
title_sort | evaluation of novel naoh activated carbon zeolite biocomposite as an efficient adsorbent for oilfield produced water treatment |
topic | Adsorption Wastewater treatment Artificial neural network Response surface methodology Oil removal Coconut shell |
url | http://www.sciencedirect.com/science/article/pii/S1026918524001458 |
work_keys_str_mv | AT egheamenzeoyedoh evaluationofnovelnaohactivatedcarbonzeolitebiocompositeasanefficientadsorbentforoilfieldproducedwatertreatment AT onyedikachipraiseigbokwe evaluationofnovelnaohactivatedcarbonzeolitebiocompositeasanefficientadsorbentforoilfieldproducedwatertreatment |