SigmaXL optimisation of oil spill removal from water using orange peels bio-adsorbent / Abdulhalim Musa Abubakar ... [et al.]
Traditional methods for oil spill cleanup, such as chemical dispersants and mechanical recovery, are often expensive and can harm marine ecosystems. If orange peels (OP) prove to be a cost-effective alternative, it could save money for companies and governments involved in oil spill response efforts...
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Universiti Teknologi MARA
2024
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my.uitm.ir.1073082024-12-09T13:15:54Z https://ir.uitm.edu.my/id/eprint/107308/ SigmaXL optimisation of oil spill removal from water using orange peels bio-adsorbent / Abdulhalim Musa Abubakar ... [et al.] mjcet Abubakar, Abdulhalim Musa Diriki, Halleluyah Daniel Umdagas, Lukman Buba Mukwana, Kishan Chand -, Wisdom Chukwuemeke Ulakpa -, Tahiru Saka -, Kamran Khan Bhutto, Afaque Ahmed SB Plant culture Traditional methods for oil spill cleanup, such as chemical dispersants and mechanical recovery, are often expensive and can harm marine ecosystems. If orange peels (OP) prove to be a cost-effective alternative, it could save money for companies and governments involved in oil spill response efforts. Response surface methodology (RSM) optimisation conducted in this study, with dosage ranging from 0.2 – 0.4 g and time from 41 – 50 min, identified OP particles of BSS 100 sieve size as an effective adsorbent for oil spill mop up. Using the basic SigmaXL features in Excel, a design of experiments (DOE) based on central composite design (CCD) indicates that the maximum adsorption capacity of OP is 34.17 g/g. This capacity is characterised by its limonene content, which enhances its sorption ability under optimal conditions of 0.2 g and 50 min. As such, a quadratic model, whose reliability is described by F, p-value, T and mean square (MS) model significance parameters, illustratively satisfy the predicted response variable at R2 = 0.8988. As a result, the residual plots show a uniform distribution of residuals, while the 3D surface and contour plots indicate connection between the input and output variables. SigmaXL not only gives the optimal combinations but allows for further optimum variable predictions outside the boundaries chosen at 95% confidence and prediction intervals. This study also shed light on resource and time management with respect to OP utilisation for oil sorption, which is the sole aim of selecting the two factors analysed to minimise cost. Universiti Teknologi MARA 2024-10 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/107308/1/107308.pdf SigmaXL optimisation of oil spill removal from water using orange peels bio-adsorbent / Abdulhalim Musa Abubakar ... [et al.]. (2024) Malaysian Journal of Chemical Engineering and Technology (MJCET) <https://ir.uitm.edu.my/view/publication/Malaysian_Journal_of_Chemical_Engineering_and_Technology_=28MJCET=29/>, 7 (2): 7. pp. 131-158. ISSN 2682-8588 |
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SB Plant culture Abubakar, Abdulhalim Musa Diriki, Halleluyah Daniel Umdagas, Lukman Buba Mukwana, Kishan Chand -, Wisdom Chukwuemeke Ulakpa -, Tahiru Saka -, Kamran Khan Bhutto, Afaque Ahmed SigmaXL optimisation of oil spill removal from water using orange peels bio-adsorbent / Abdulhalim Musa Abubakar ... [et al.] |
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Traditional methods for oil spill cleanup, such as chemical dispersants and mechanical recovery, are often expensive and can harm marine ecosystems. If orange peels (OP) prove to be a cost-effective alternative, it could save money for companies and governments involved in oil spill response efforts. Response surface methodology (RSM) optimisation conducted in this study, with dosage ranging from 0.2 – 0.4 g and time from 41 – 50 min, identified OP particles of BSS 100 sieve size as an effective adsorbent for oil spill mop up. Using the basic SigmaXL features in Excel, a design of experiments (DOE) based on central composite design (CCD) indicates that the maximum adsorption capacity of OP is 34.17 g/g. This capacity is characterised by its limonene content, which enhances its sorption ability under optimal conditions of 0.2 g and 50 min. As such, a quadratic model, whose reliability is described by F, p-value, T and mean square (MS) model significance parameters, illustratively satisfy the predicted response variable at R2 = 0.8988. As a result, the residual plots show a uniform distribution of residuals, while the 3D surface and contour plots indicate connection between the input and output variables. SigmaXL not only gives the optimal combinations but allows for further optimum variable predictions outside the boundaries chosen at 95% confidence and prediction intervals. This study also shed light on resource and time management with respect to OP utilisation for oil sorption, which is the sole aim of selecting the two factors analysed to minimise cost. |
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Article |
author |
Abubakar, Abdulhalim Musa Diriki, Halleluyah Daniel Umdagas, Lukman Buba Mukwana, Kishan Chand -, Wisdom Chukwuemeke Ulakpa -, Tahiru Saka -, Kamran Khan Bhutto, Afaque Ahmed |
author_facet |
Abubakar, Abdulhalim Musa Diriki, Halleluyah Daniel Umdagas, Lukman Buba Mukwana, Kishan Chand -, Wisdom Chukwuemeke Ulakpa -, Tahiru Saka -, Kamran Khan Bhutto, Afaque Ahmed |
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Abubakar, Abdulhalim Musa |
title |
SigmaXL optimisation of oil spill removal from water using orange peels bio-adsorbent / Abdulhalim Musa Abubakar ... [et al.] |
title_short |
SigmaXL optimisation of oil spill removal from water using orange peels bio-adsorbent / Abdulhalim Musa Abubakar ... [et al.] |
title_full |
SigmaXL optimisation of oil spill removal from water using orange peels bio-adsorbent / Abdulhalim Musa Abubakar ... [et al.] |
title_fullStr |
SigmaXL optimisation of oil spill removal from water using orange peels bio-adsorbent / Abdulhalim Musa Abubakar ... [et al.] |
title_full_unstemmed |
SigmaXL optimisation of oil spill removal from water using orange peels bio-adsorbent / Abdulhalim Musa Abubakar ... [et al.] |
title_sort |
sigmaxl optimisation of oil spill removal from water using orange peels bio-adsorbent / abdulhalim musa abubakar ... [et al.] |
publisher |
Universiti Teknologi MARA |
publishDate |
2024 |
url |
https://ir.uitm.edu.my/id/eprint/107308/1/107308.pdf https://ir.uitm.edu.my/id/eprint/107308/ |
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