Optimization of adsorption conditions using response surface methodology for glyphosate removal from river water matrices by granular activated carbon
Granular activated carbon (GAC) was investigated as an effective adsorbent for the adsorption of glyphosate herbicide from the river water matrix. Six physiochemical factors were screened using a Plackett-Burman fractional factorial design to identify the most important variables in the glyphosate a...
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Faculty of Science and Natural Resources
2023
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my.ums.eprints.392342024-07-26T01:20:12Z https://eprints.ums.edu.my/id/eprint/39234/ Optimization of adsorption conditions using response surface methodology for glyphosate removal from river water matrices by granular activated carbon Hartinie Marbawi Mohd Yunus Abd. Shukor Jualang Azlan Gansau Ahmad Razi Othman Mohd Izuan Efendi Halmi Nur Adeela Yasid Q1-390 Science (General) TP200-248 Chemicals: Manufacture, use, etc. Granular activated carbon (GAC) was investigated as an effective adsorbent for the adsorption of glyphosate herbicide from the river water matrix. Six physiochemical factors were screened using a Plackett-Burman fractional factorial design to identify the most important variables in the glyphosate adsorption process.Subsequently, the synergistic effects between the four independent variables studied including the pH of glyphosate solution (4.0 –8.0), adsorbent dose (0.1–0.5 g.L⁻¹), initial glyphosate concentration (30 –150 mg L⁻¹) and agitation speed (0-100 rpm) on the glyphosate removal efficiency (%) were statistically optimized according to the Box-Behnken approach. Quadratic model was considered to be the best fit with a maximum R2 value of 0.9650 and provides an ideal relationship between the variables and response. An analysis of variance (ANOVA) further confirms the validity of the suggested model. The optimal factors for 95.11 ± 0.77% glyphosate removal were predicted to be a pH solution of 4.00, glyphosate initial concentration of 48.47 mg.L⁻¹ , 0.1g.L⁻¹ GAC and without agitation. The findings showed that the Box-Behnken-based optimization using response surface methodology is a helpful tool for determining the best adsorption conditions and the method can also be customised for glyphosate treatment in natural water or actual wastewater. Faculty of Science and Natural Resources 2023 Proceedings PeerReviewed text en https://eprints.ums.edu.my/id/eprint/39234/1/ABSTRACT.pdf text en https://eprints.ums.edu.my/id/eprint/39234/2/FULL%20TEXT.pdf Hartinie Marbawi and Mohd Yunus Abd. Shukor and Jualang Azlan Gansau and Ahmad Razi Othman and Mohd Izuan Efendi Halmi and Nur Adeela Yasid (2023) Optimization of adsorption conditions using response surface methodology for glyphosate removal from river water matrices by granular activated carbon. https://www.ums.edu.my/fssa/index.php/research/conference-publication |
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Q1-390 Science (General) TP200-248 Chemicals: Manufacture, use, etc. Hartinie Marbawi Mohd Yunus Abd. Shukor Jualang Azlan Gansau Ahmad Razi Othman Mohd Izuan Efendi Halmi Nur Adeela Yasid Optimization of adsorption conditions using response surface methodology for glyphosate removal from river water matrices by granular activated carbon |
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Granular activated carbon (GAC) was investigated as an effective adsorbent for the adsorption of glyphosate herbicide from the river water matrix. Six physiochemical factors were screened using a Plackett-Burman fractional factorial design to identify the most important variables in the glyphosate adsorption process.Subsequently, the synergistic effects between the four independent variables studied including the pH of glyphosate solution (4.0 –8.0), adsorbent dose (0.1–0.5 g.L⁻¹), initial glyphosate concentration (30 –150 mg L⁻¹) and agitation speed (0-100 rpm) on the glyphosate removal efficiency (%) were statistically optimized according to the Box-Behnken approach. Quadratic model was considered to be the best fit with a maximum R2 value of 0.9650 and provides an ideal relationship between the variables and response. An analysis of variance (ANOVA) further confirms the validity of the suggested model. The optimal factors for 95.11 ± 0.77% glyphosate removal were predicted to be a pH solution of 4.00, glyphosate initial concentration of 48.47 mg.L⁻¹ , 0.1g.L⁻¹ GAC and without agitation. The findings showed that the Box-Behnken-based optimization using response surface methodology is a helpful tool for determining the best adsorption conditions and the method can also be customised for glyphosate treatment in natural water or actual wastewater. |
format |
Proceedings |
author |
Hartinie Marbawi Mohd Yunus Abd. Shukor Jualang Azlan Gansau Ahmad Razi Othman Mohd Izuan Efendi Halmi Nur Adeela Yasid |
author_facet |
Hartinie Marbawi Mohd Yunus Abd. Shukor Jualang Azlan Gansau Ahmad Razi Othman Mohd Izuan Efendi Halmi Nur Adeela Yasid |
author_sort |
Hartinie Marbawi |
title |
Optimization of adsorption conditions using response surface methodology for glyphosate removal from river water matrices by granular activated carbon |
title_short |
Optimization of adsorption conditions using response surface methodology for glyphosate removal from river water matrices by granular activated carbon |
title_full |
Optimization of adsorption conditions using response surface methodology for glyphosate removal from river water matrices by granular activated carbon |
title_fullStr |
Optimization of adsorption conditions using response surface methodology for glyphosate removal from river water matrices by granular activated carbon |
title_full_unstemmed |
Optimization of adsorption conditions using response surface methodology for glyphosate removal from river water matrices by granular activated carbon |
title_sort |
optimization of adsorption conditions using response surface methodology for glyphosate removal from river water matrices by granular activated carbon |
publisher |
Faculty of Science and Natural Resources |
publishDate |
2023 |
url |
https://eprints.ums.edu.my/id/eprint/39234/1/ABSTRACT.pdf https://eprints.ums.edu.my/id/eprint/39234/2/FULL%20TEXT.pdf https://eprints.ums.edu.my/id/eprint/39234/ https://www.ums.edu.my/fssa/index.php/research/conference-publication |
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