Coagulation/flocculation process for textile mill effluent treatment: experimental and numerical perspectives
This study investigates the feasibility of applying coagulation/flocculation process for real textile wastewater treatment. Batch experiments were performed to detect the optimum performance of four different coagulants; Ferric Sulphate (Fe2(SO4)3), Aluminium Chloride (AlCl3), Aluminium Sulphate (Al...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2021-09-01
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| Series: | International Journal of Sustainable Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/19397038.2020.1842547 |
| _version_ | 1797678287084847104 |
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| author | Ahmed Karam Emad S. Bakhoum Khaled Zaher |
| author_facet | Ahmed Karam Emad S. Bakhoum Khaled Zaher |
| author_sort | Ahmed Karam |
| collection | DOAJ |
| description | This study investigates the feasibility of applying coagulation/flocculation process for real textile wastewater treatment. Batch experiments were performed to detect the optimum performance of four different coagulants; Ferric Sulphate (Fe2(SO4)3), Aluminium Chloride (AlCl3), Aluminium Sulphate (Al2(SO4)3) and Ferric Chloride (FeCl3) at diverse ranges of pH (1–11) on the removal of chemical oxygen demand (COD), total suspended solids (TSS), colour, total nitrogen (TN) and turbidity from real textile wastewater. At pH 9, FeCl3 demonstrated the most effective removal for all studied contaminants. Experiments were conducted to assess the dosage and operating conditions to achieve optimum removal efficiency for all studied contaminants by using FeCl3. The obtained results demonstrated the higher ability of FeCl3 in textile wastewater treatment with optimum conditions; pH 9, 150 rpm in 1 min rapid mixing, 30 rpm in 20 min slow mixing and 30 min settling. Artificial neural network (ANN) model was applied to predict the removal efficiencies of the studied contaminants under different variables using FeCl3 coagulant. ANN model adequately predicted the studied parameters removal efficiencies with a coefficient of determination greater than 90% and has the capability of simulating the coagulation process and predicting removal percentages using the author’s experimental data. |
| first_indexed | 2024-03-11T22:57:31Z |
| format | Article |
| id | doaj.art-5cd396fd2bf643e3951a5b2f6f70a1ec |
| institution | Directory Open Access Journal |
| issn | 1939-7038 1939-7046 |
| language | English |
| last_indexed | 2024-03-11T22:57:31Z |
| publishDate | 2021-09-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | International Journal of Sustainable Engineering |
| spelling | doaj.art-5cd396fd2bf643e3951a5b2f6f70a1ec2023-09-21T15:17:03ZengTaylor & Francis GroupInternational Journal of Sustainable Engineering1939-70381939-70462021-09-0114598399510.1080/19397038.2020.18425471842547Coagulation/flocculation process for textile mill effluent treatment: experimental and numerical perspectivesAhmed Karam0Emad S. Bakhoum1Khaled Zaher2Nile UniversityNile UniversitySanitary and Environmental EngineeringThis study investigates the feasibility of applying coagulation/flocculation process for real textile wastewater treatment. Batch experiments were performed to detect the optimum performance of four different coagulants; Ferric Sulphate (Fe2(SO4)3), Aluminium Chloride (AlCl3), Aluminium Sulphate (Al2(SO4)3) and Ferric Chloride (FeCl3) at diverse ranges of pH (1–11) on the removal of chemical oxygen demand (COD), total suspended solids (TSS), colour, total nitrogen (TN) and turbidity from real textile wastewater. At pH 9, FeCl3 demonstrated the most effective removal for all studied contaminants. Experiments were conducted to assess the dosage and operating conditions to achieve optimum removal efficiency for all studied contaminants by using FeCl3. The obtained results demonstrated the higher ability of FeCl3 in textile wastewater treatment with optimum conditions; pH 9, 150 rpm in 1 min rapid mixing, 30 rpm in 20 min slow mixing and 30 min settling. Artificial neural network (ANN) model was applied to predict the removal efficiencies of the studied contaminants under different variables using FeCl3 coagulant. ANN model adequately predicted the studied parameters removal efficiencies with a coefficient of determination greater than 90% and has the capability of simulating the coagulation process and predicting removal percentages using the author’s experimental data.http://dx.doi.org/10.1080/19397038.2020.1842547real textile wastewaterchemical coagulantscolour removalartificial neural networks |
| spellingShingle | Ahmed Karam Emad S. Bakhoum Khaled Zaher Coagulation/flocculation process for textile mill effluent treatment: experimental and numerical perspectives International Journal of Sustainable Engineering real textile wastewater chemical coagulants colour removal artificial neural networks |
| title | Coagulation/flocculation process for textile mill effluent treatment: experimental and numerical perspectives |
| title_full | Coagulation/flocculation process for textile mill effluent treatment: experimental and numerical perspectives |
| title_fullStr | Coagulation/flocculation process for textile mill effluent treatment: experimental and numerical perspectives |
| title_full_unstemmed | Coagulation/flocculation process for textile mill effluent treatment: experimental and numerical perspectives |
| title_short | Coagulation/flocculation process for textile mill effluent treatment: experimental and numerical perspectives |
| title_sort | coagulation flocculation process for textile mill effluent treatment experimental and numerical perspectives |
| topic | real textile wastewater chemical coagulants colour removal artificial neural networks |
| url | http://dx.doi.org/10.1080/19397038.2020.1842547 |
| work_keys_str_mv | AT ahmedkaram coagulationflocculationprocessfortextilemilleffluenttreatmentexperimentalandnumericalperspectives AT emadsbakhoum coagulationflocculationprocessfortextilemilleffluenttreatmentexperimentalandnumericalperspectives AT khaledzaher coagulationflocculationprocessfortextilemilleffluenttreatmentexperimentalandnumericalperspectives |