Palm Oil Mill Effluent Treatment Through Combined Process Adsorption and Membrane Filtration
The growth in palm oil production also leads to an Increase in the production of palm oil mill effluent (POME). Nowadays, POME was treated using an open lagoon but this method is ineffectiveness in complying with the standards for water disposal. Therefore, efficient and cohesive treatment system is...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Sriwijaya University, Graduate Program
2016-08-01
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| Series: | Sriwijaya Journal of Environment |
| Subjects: | |
| Online Access: | http://ojs.pps.unsri.ac.id/index.php/ppsunsri/article/view/17/11 |
| _version_ | 1797969451367268352 |
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| author | Muhammad Said Siti Rozaimakh Sheikh Abdullah Abdul Wahab Mohammad |
| author_facet | Muhammad Said Siti Rozaimakh Sheikh Abdullah Abdul Wahab Mohammad |
| author_sort | Muhammad Said |
| collection | DOAJ |
| description | The growth in palm oil production also leads to an Increase in the production of palm oil mill effluent (POME). Nowadays, POME was treated using an open lagoon but this method is ineffectiveness in complying with the standards for water disposal. Therefore, efficient and cohesive treatment system is highly desired to ensure the final discharge of the treated water meets the effluent discharge standards. Initially, the POME was treated through adsorption, followed by UF membranes roomates were intended to reduce COD, TSS and turbidity up to 88%, 99%, and 98%, while the final treatment of RO membranes can reduce BOD, COD and color up to 92%, 98% and 99%. To determine the optimum condition of the RO membrane, response surface methodology (RSM) was used. The results showed there was correlation between all key variables. POME concentration, trans-membrane pressure, pH and time would give significant effects in reducing the parameters in POME treatment with the optimum condition of 15.77% for POME concentration, 3.73 for pH, 0.5 bar trans-membrane pressure and 5 hours for filtration time. To predict COD removal, the results were analyzed by applying the artificial neural network (ANN) to derive a mathematical model. |
| first_indexed | 2024-04-11T03:02:26Z |
| format | Article |
| id | doaj.art-0ae6cdd4979a4a32b75340eee760bcba |
| institution | Directory Open Access Journal |
| issn | 2527-4961 2527-3809 |
| language | English |
| last_indexed | 2024-04-11T03:02:26Z |
| publishDate | 2016-08-01 |
| publisher | Sriwijaya University, Graduate Program |
| record_format | Article |
| series | Sriwijaya Journal of Environment |
| spelling | doaj.art-0ae6cdd4979a4a32b75340eee760bcba2023-01-02T13:45:50ZengSriwijaya University, Graduate ProgramSriwijaya Journal of Environment2527-49612527-38092016-08-0112364110.22135/sje.2016.1.2.36-41Palm Oil Mill Effluent Treatment Through Combined Process Adsorption and Membrane FiltrationMuhammad SaidSiti Rozaimakh Sheikh AbdullahAbdul Wahab MohammadThe growth in palm oil production also leads to an Increase in the production of palm oil mill effluent (POME). Nowadays, POME was treated using an open lagoon but this method is ineffectiveness in complying with the standards for water disposal. Therefore, efficient and cohesive treatment system is highly desired to ensure the final discharge of the treated water meets the effluent discharge standards. Initially, the POME was treated through adsorption, followed by UF membranes roomates were intended to reduce COD, TSS and turbidity up to 88%, 99%, and 98%, while the final treatment of RO membranes can reduce BOD, COD and color up to 92%, 98% and 99%. To determine the optimum condition of the RO membrane, response surface methodology (RSM) was used. The results showed there was correlation between all key variables. POME concentration, trans-membrane pressure, pH and time would give significant effects in reducing the parameters in POME treatment with the optimum condition of 15.77% for POME concentration, 3.73 for pH, 0.5 bar trans-membrane pressure and 5 hours for filtration time. To predict COD removal, the results were analyzed by applying the artificial neural network (ANN) to derive a mathematical model.http://ojs.pps.unsri.ac.id/index.php/ppsunsri/article/view/17/11POMEAdsorptionMembrane filtrationCODRSMANN |
| spellingShingle | Muhammad Said Siti Rozaimakh Sheikh Abdullah Abdul Wahab Mohammad Palm Oil Mill Effluent Treatment Through Combined Process Adsorption and Membrane Filtration Sriwijaya Journal of Environment POME Adsorption Membrane filtration COD RSM ANN |
| title | Palm Oil Mill Effluent Treatment Through Combined Process Adsorption and Membrane Filtration |
| title_full | Palm Oil Mill Effluent Treatment Through Combined Process Adsorption and Membrane Filtration |
| title_fullStr | Palm Oil Mill Effluent Treatment Through Combined Process Adsorption and Membrane Filtration |
| title_full_unstemmed | Palm Oil Mill Effluent Treatment Through Combined Process Adsorption and Membrane Filtration |
| title_short | Palm Oil Mill Effluent Treatment Through Combined Process Adsorption and Membrane Filtration |
| title_sort | palm oil mill effluent treatment through combined process adsorption and membrane filtration |
| topic | POME Adsorption Membrane filtration COD RSM ANN |
| url | http://ojs.pps.unsri.ac.id/index.php/ppsunsri/article/view/17/11 |
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