Textile Wastewater Treatment in a Spinning Disc Reactor: Improved Performances—Experimental, Modeling and SVM Optimization
The paper presents an experimental study regarding the treatment of a real textile wastewater using the spinning disc (SD) technology, either individually or associated with an advanced Fenton oxidation step. The SD efficiency was investigated by studying the color, suspended solids, or turbidity re...
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2021
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oai:doaj.org-article:45bdb3cdf8eb4fa8b94f32c88bf3a3122021-11-25T18:51:23ZTextile Wastewater Treatment in a Spinning Disc Reactor: Improved Performances—Experimental, Modeling and SVM Optimization10.3390/pr91120032227-9717https://doaj.org/article/45bdb3cdf8eb4fa8b94f32c88bf3a3122021-11-01T00:00:00Zhttps://www.mdpi.com/2227-9717/9/11/2003https://doaj.org/toc/2227-9717The paper presents an experimental study regarding the treatment of a real textile wastewater using the spinning disc (SD) technology, either individually or associated with an advanced Fenton oxidation step. The SD efficiency was investigated by studying the color, suspended solids, or turbidity removals, at distinctive feeding flowrates (10–30 L/h) and disc rotating speeds (100–1500 rpm). The data revealed increasing removal trends and allowed to establish the highest removal values. Based on obtained experimental results, the wastewater treatment efficiency by SD technology was reasonably good and thus, the WW indicators can be improved within relatively short periods of time. Additionally, based on supervised learning algorithms, the study includes treatment modeling for turbidity and color removal, followed by turbidity removal optimization relying on the best learned models. Satisfactory results obtained with the modeling and optimization procedures provide useful predictions for the approached treatment processes. Furthermore, within this study, a Fenton oxidation process was applied to SD technology to minimize the color and solids content. The influence of pH, hydrogen peroxide and ferrous ions concentrations was also investigated in order to establish the highest removal efficiencies. Overall, the SD technology applied in textile effluents treatment proved to be an appropriate and efficient alternative to classical mechanical step applied within the primary treatment step and, when associated with an advanced oxidative process in the secondary step, rendered good improvement, namely of 62.84% and 69.46% for color and respectively, suspended solids removal.Carmen ZahariaFlorin LeonSilvia CurteanuEugenia Teodora Iacob-TudoseMDPI AGarticlediscolorationFenton oxidationSD technologyturbidity reductiontextile effluent treatmentSVM optimizationChemical technologyTP1-1185ChemistryQD1-999ENProcesses, Vol 9, Iss 2003, p 2003 (2021) |
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discoloration Fenton oxidation SD technology turbidity reduction textile effluent treatment SVM optimization Chemical technology TP1-1185 Chemistry QD1-999 |
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discoloration Fenton oxidation SD technology turbidity reduction textile effluent treatment SVM optimization Chemical technology TP1-1185 Chemistry QD1-999 Carmen Zaharia Florin Leon Silvia Curteanu Eugenia Teodora Iacob-Tudose Textile Wastewater Treatment in a Spinning Disc Reactor: Improved Performances—Experimental, Modeling and SVM Optimization |
description |
The paper presents an experimental study regarding the treatment of a real textile wastewater using the spinning disc (SD) technology, either individually or associated with an advanced Fenton oxidation step. The SD efficiency was investigated by studying the color, suspended solids, or turbidity removals, at distinctive feeding flowrates (10–30 L/h) and disc rotating speeds (100–1500 rpm). The data revealed increasing removal trends and allowed to establish the highest removal values. Based on obtained experimental results, the wastewater treatment efficiency by SD technology was reasonably good and thus, the WW indicators can be improved within relatively short periods of time. Additionally, based on supervised learning algorithms, the study includes treatment modeling for turbidity and color removal, followed by turbidity removal optimization relying on the best learned models. Satisfactory results obtained with the modeling and optimization procedures provide useful predictions for the approached treatment processes. Furthermore, within this study, a Fenton oxidation process was applied to SD technology to minimize the color and solids content. The influence of pH, hydrogen peroxide and ferrous ions concentrations was also investigated in order to establish the highest removal efficiencies. Overall, the SD technology applied in textile effluents treatment proved to be an appropriate and efficient alternative to classical mechanical step applied within the primary treatment step and, when associated with an advanced oxidative process in the secondary step, rendered good improvement, namely of 62.84% and 69.46% for color and respectively, suspended solids removal. |
format |
article |
author |
Carmen Zaharia Florin Leon Silvia Curteanu Eugenia Teodora Iacob-Tudose |
author_facet |
Carmen Zaharia Florin Leon Silvia Curteanu Eugenia Teodora Iacob-Tudose |
author_sort |
Carmen Zaharia |
title |
Textile Wastewater Treatment in a Spinning Disc Reactor: Improved Performances—Experimental, Modeling and SVM Optimization |
title_short |
Textile Wastewater Treatment in a Spinning Disc Reactor: Improved Performances—Experimental, Modeling and SVM Optimization |
title_full |
Textile Wastewater Treatment in a Spinning Disc Reactor: Improved Performances—Experimental, Modeling and SVM Optimization |
title_fullStr |
Textile Wastewater Treatment in a Spinning Disc Reactor: Improved Performances—Experimental, Modeling and SVM Optimization |
title_full_unstemmed |
Textile Wastewater Treatment in a Spinning Disc Reactor: Improved Performances—Experimental, Modeling and SVM Optimization |
title_sort |
textile wastewater treatment in a spinning disc reactor: improved performances—experimental, modeling and svm optimization |
publisher |
MDPI AG |
publishDate |
2021 |
url |
https://doaj.org/article/45bdb3cdf8eb4fa8b94f32c88bf3a312 |
work_keys_str_mv |
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