Application of response surface methodology (RSM) for optimization of color removal from POME by granular activated carbon
Color is one of the major remaining contami- nants in the palm oil mill effluent (POME) following the conventional treatment of POME. The removal of color from POME using adsorption on activated carbon was investigated. The adsorption experimental design was performed using the standard response surf...
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iium-382552014-09-12T09:17:17Z http://irep.iium.edu.my/38255/ Application of response surface methodology (RSM) for optimization of color removal from POME by granular activated carbon Al-Khatib, Ma An Fahmi Rashid Mamun, Abdullah Al Akbar, Iqrah TD169 Environmental protection TD172 Environmental pollution TD194 Environmental effects of industries and plants TP155 Chemical engineering Color is one of the major remaining contami- nants in the palm oil mill effluent (POME) following the conventional treatment of POME. The removal of color from POME using adsorption on activated carbon was investigated. The adsorption experimental design was performed using the standard response surface method (RSM) design that is central composite design to determine the optimum process variables for color removal by using the Design-Expert software (version 7.0. Stat-Ease, trial version). Besides obtaining optimum values, RSM also has the advantage of studying the interaction between various experimental parameters compared to one-factor-at-a-time. The equilibrium experimental data were analyzed by Langmuir and Freundlich isotherms. The statistical ana- lysis showed that the quadratic model as well as the model terms was significant. The model had very low probability value (0.0003). The R2 for the model was 0.9184 and the adjusted R2 was 0.8380. The validation of the model showed experimental value and predicted value of 0.124 and 0.106, respectively. The optimum conditions suggested by the model for the process variable were 87.9 min, 4.05 and 7.86 g, for time, pH and granular activated carbon dose, respectively. The maximum removal obtained at these conditions was 89.95 %. The adsorption isotherm data were fitted well to the Langmuir isotherm compared to Freundlich isotherm with R2 value of 0.850 for the former and 0.273 for the later. Center for Environmental and Energy Research and Studies 2014 Article PeerReviewed application/pdf en http://irep.iium.edu.my/38255/1/Application_of_%28RSM%29_for_optimization_of_color_removal_by_AC.pdf Al-Khatib, Ma An Fahmi Rashid and Mamun, Abdullah Al and Akbar, Iqrah (2014) Application of response surface methodology (RSM) for optimization of color removal from POME by granular activated carbon. International Journal of Environmental Science and Technology , xx (xx). pp. 1-8. ISSN 1735-1472 (P), 1735-2630 (O) (In Press) http://link.springer.com/article/10.1007%2Fs13762-014-0504-4 10.1007/s13762-014-0504-4 |
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TD169 Environmental protection TD172 Environmental pollution TD194 Environmental effects of industries and plants TP155 Chemical engineering |
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TD169 Environmental protection TD172 Environmental pollution TD194 Environmental effects of industries and plants TP155 Chemical engineering Al-Khatib, Ma An Fahmi Rashid Mamun, Abdullah Al Akbar, Iqrah Application of response surface methodology (RSM) for optimization of color removal from POME by granular activated carbon |
description |
Color is one of the major remaining contami- nants in the palm oil mill effluent (POME) following the conventional treatment of POME. The removal of color from POME using adsorption on activated carbon was investigated. The adsorption experimental design was performed using the standard response surface method (RSM) design that is central composite design to determine the optimum process variables for color removal by using the Design-Expert software (version 7.0. Stat-Ease, trial version). Besides obtaining optimum values, RSM also has the advantage of studying the interaction between various experimental parameters compared to one-factor-at-a-time. The equilibrium experimental data were analyzed by Langmuir and Freundlich isotherms. The statistical ana- lysis showed that the quadratic model as well as the model terms was significant. The model had very low probability value (0.0003). The R2 for the model was 0.9184 and the adjusted R2 was 0.8380. The validation of the model showed experimental value and predicted value of 0.124 and 0.106, respectively. The optimum conditions suggested by the model for the process variable were 87.9 min, 4.05 and 7.86 g, for time, pH and granular activated carbon dose, respectively. The maximum removal obtained at these conditions was 89.95 %. The adsorption isotherm data were fitted well to the Langmuir isotherm compared to Freundlich isotherm with R2 value of 0.850 for the former and 0.273 for the later.
|
format |
Article |
author |
Al-Khatib, Ma An Fahmi Rashid Mamun, Abdullah Al Akbar, Iqrah |
author_facet |
Al-Khatib, Ma An Fahmi Rashid Mamun, Abdullah Al Akbar, Iqrah |
author_sort |
Al-Khatib, Ma An Fahmi Rashid |
title |
Application of response surface methodology (RSM) for optimization of color removal from POME by granular activated carbon |
title_short |
Application of response surface methodology (RSM) for optimization of color removal from POME by granular activated carbon |
title_full |
Application of response surface methodology (RSM) for optimization of color removal from POME by granular activated carbon |
title_fullStr |
Application of response surface methodology (RSM) for optimization of color removal from POME by granular activated carbon |
title_full_unstemmed |
Application of response surface methodology (RSM) for optimization of color removal from POME by granular activated carbon |
title_sort |
application of response surface methodology (rsm) for optimization of color removal from pome by granular activated carbon |
publisher |
Center for Environmental and Energy Research and Studies |
publishDate |
2014 |
url |
http://irep.iium.edu.my/38255/ http://irep.iium.edu.my/38255/ http://irep.iium.edu.my/38255/ http://irep.iium.edu.my/38255/1/Application_of_%28RSM%29_for_optimization_of_color_removal_by_AC.pdf |
first_indexed |
2023-09-18T20:54:56Z |
last_indexed |
2023-09-18T20:54:56Z |
_version_ |
1777410241409843200 |