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Application of esterified sago bark for removal of oil from palm oil mill effluent

Removal of emulsified oil in palm oil mill effluent (POME) is a challenge to palm oil industries. The aim of the present study was to develop a hydrophobic oil sorbent by incorporating fatty acid derivatives, namely stearic acid, on sago bark (SB) network via esterification process. The effect of es...

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Main Author: Wahi, Rafeah
Format: Thesis
Language:English
Published: 2014
Online Access:http://psasir.upm.edu.my/id/eprint/64859/1/FK%202014%20171IR.pdf
http://psasir.upm.edu.my/id/eprint/64859/
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description Removal of emulsified oil in palm oil mill effluent (POME) is a challenge to palm oil industries. The aim of the present study was to develop a hydrophobic oil sorbent by incorporating fatty acid derivatives, namely stearic acid, on sago bark (SB) network via esterification process. The effect of esterification parameters such as the SB to stearic acid (SA) ratio (SB:SA), the amount of catalyst and the refluxing time on the oil removal efficiency of ESB and the optimization study were conducted via surface response methodology (RSM). The oil removal efficiency of SB and ESB in POME was also studied at different adsorption conditions in batch experiments. Artificial neural network (ANN) modelling was applied to model the column oil adsorption process. Chemical modification of SB has been successfully carried out via esterification with SA to afford ESB, the oil sorbent of high hydrophobicity and high oil removal efficiency. The esterification has successfully increased the hydrophobicity of SB by 42.2% and the oil removal efficiency in POME by 50.2%. The ESB produced at the optimum operating condition of SB:SA 1:1, 15% catalyst, and 8 h refluxing time gave the highest oil removal efficiency in POME (95.52%). The two most dominant influencing factors for ESB preparation were SB:SA and refluxing time. The batch oil adsorption study showed that the ESB exhibits better oil removal efficiency compared to SB in all studied conditions, namely adsorbent dosage, contact time, temperature and pH. Overall, the oil removal efficiency of both SB and ESB increased with increasing sorbent dosage and contact time. On the other hand, the oil removal efficiency of both SB and ESB decreased with the increasing temperature. Acidic pH was favorable pH condition for high oil removal efficiency. Overall, results showed a good correlation (R2 > 9.5) between experimental data and the intra-particle diffusion model for both SB and ESB. Results also showed that adsorption of oil in POME using SB was best described by Freundlich isotherm (R2=0.998), indicating heterolayer adsorption of oil on SB. The adsorption of oil in POME using ESB was better represented using Langmuir isotherm (R2=0.992), indicating a monolayer adsorption of oil onto the ESB surface. It is also evident from the study that ESB afforded good oil removal efficiency in deep bed filtration system. The ANN data showed that SB and ESB were found to remove oil from POME up to 59.12% and 89.79%, respectively in column system. The data means that after deep bed filtration of typical POME with initial oil concentration of 4000 mg/l using ESB, the treated POME is estimated to have 409 mg/l oil and grease content. ANN model was found to fit well with the experimental data with R2 > 0.95 for both training and testing data of SB and ESB. ANN study also indicated that all studied parameters are effective parameters in the sequence of temperature (30.09%) > pH (26.8%) > bed height (26.73% > flow rate (16.38%). The result revealed that the Thomas model and Yoon & Nelson model did not represented the experimental data very well. On the other hand, the column oil adsorption from POME using ESB can be excellently described by the intraparticle diffusion model. A multi-linearity plot of intra-particle diffusion model indicated the occurrence of three stages of adsorption during the experiment. Good oil removal efficiency and environmental friendliness make ESB a viable choice for use as bed material of a deep bed filter system for emulsified oil removal from POME. The importance of these research findings to advance the emulsified oil removal technology will hopefully find good use in the oil processing industry. The findings of this research will provide new insights to the emulsified oil removal technology.
format Thesis
author Wahi, Rafeah
spellingShingle Wahi, Rafeah
Application of esterified sago bark for removal of oil from palm oil mill effluent
author_facet Wahi, Rafeah
author_sort Wahi, Rafeah
title Application of esterified sago bark for removal of oil from palm oil mill effluent
title_short Application of esterified sago bark for removal of oil from palm oil mill effluent
title_full Application of esterified sago bark for removal of oil from palm oil mill effluent
title_fullStr Application of esterified sago bark for removal of oil from palm oil mill effluent
title_full_unstemmed Application of esterified sago bark for removal of oil from palm oil mill effluent
title_sort application of esterified sago bark for removal of oil from palm oil mill effluent
publishDate 2014
url http://psasir.upm.edu.my/id/eprint/64859/1/FK%202014%20171IR.pdf
http://psasir.upm.edu.my/id/eprint/64859/
_version_ 1643838147166994432
spelling my.upm.eprints.648592018-07-31T06:18:10Z http://psasir.upm.edu.my/id/eprint/64859/ Application of esterified sago bark for removal of oil from palm oil mill effluent Wahi, Rafeah Removal of emulsified oil in palm oil mill effluent (POME) is a challenge to palm oil industries. The aim of the present study was to develop a hydrophobic oil sorbent by incorporating fatty acid derivatives, namely stearic acid, on sago bark (SB) network via esterification process. The effect of esterification parameters such as the SB to stearic acid (SA) ratio (SB:SA), the amount of catalyst and the refluxing time on the oil removal efficiency of ESB and the optimization study were conducted via surface response methodology (RSM). The oil removal efficiency of SB and ESB in POME was also studied at different adsorption conditions in batch experiments. Artificial neural network (ANN) modelling was applied to model the column oil adsorption process. Chemical modification of SB has been successfully carried out via esterification with SA to afford ESB, the oil sorbent of high hydrophobicity and high oil removal efficiency. The esterification has successfully increased the hydrophobicity of SB by 42.2% and the oil removal efficiency in POME by 50.2%. The ESB produced at the optimum operating condition of SB:SA 1:1, 15% catalyst, and 8 h refluxing time gave the highest oil removal efficiency in POME (95.52%). The two most dominant influencing factors for ESB preparation were SB:SA and refluxing time. The batch oil adsorption study showed that the ESB exhibits better oil removal efficiency compared to SB in all studied conditions, namely adsorbent dosage, contact time, temperature and pH. Overall, the oil removal efficiency of both SB and ESB increased with increasing sorbent dosage and contact time. On the other hand, the oil removal efficiency of both SB and ESB decreased with the increasing temperature. Acidic pH was favorable pH condition for high oil removal efficiency. Overall, results showed a good correlation (R2 > 9.5) between experimental data and the intra-particle diffusion model for both SB and ESB. Results also showed that adsorption of oil in POME using SB was best described by Freundlich isotherm (R2=0.998), indicating heterolayer adsorption of oil on SB. The adsorption of oil in POME using ESB was better represented using Langmuir isotherm (R2=0.992), indicating a monolayer adsorption of oil onto the ESB surface. It is also evident from the study that ESB afforded good oil removal efficiency in deep bed filtration system. The ANN data showed that SB and ESB were found to remove oil from POME up to 59.12% and 89.79%, respectively in column system. The data means that after deep bed filtration of typical POME with initial oil concentration of 4000 mg/l using ESB, the treated POME is estimated to have 409 mg/l oil and grease content. ANN model was found to fit well with the experimental data with R2 > 0.95 for both training and testing data of SB and ESB. ANN study also indicated that all studied parameters are effective parameters in the sequence of temperature (30.09%) > pH (26.8%) > bed height (26.73% > flow rate (16.38%). The result revealed that the Thomas model and Yoon & Nelson model did not represented the experimental data very well. On the other hand, the column oil adsorption from POME using ESB can be excellently described by the intraparticle diffusion model. A multi-linearity plot of intra-particle diffusion model indicated the occurrence of three stages of adsorption during the experiment. Good oil removal efficiency and environmental friendliness make ESB a viable choice for use as bed material of a deep bed filter system for emulsified oil removal from POME. The importance of these research findings to advance the emulsified oil removal technology will hopefully find good use in the oil processing industry. The findings of this research will provide new insights to the emulsified oil removal technology. 2014-11 Thesis NonPeerReviewed text en http://psasir.upm.edu.my/id/eprint/64859/1/FK%202014%20171IR.pdf Wahi, Rafeah (2014) Application of esterified sago bark for removal of oil from palm oil mill effluent. PhD thesis, Universiti Putra Malaysia.
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