Application of biopolymer in turbidity removal and sludge settling behaviour of travertine-processing wastewater: Performance optimization using response surface methodology (RSM)
A flocculation process was performed to treat travertine-processing effluents with a high concentration of suspended solids using an eco-friendly biopolymer. The experiments were conducted through a standard jar test procedure to optimize the process parameters for sludge volume index (SVI) and turb...
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| Veröffentlicht in: | Water S. A. 2023-01, Vol.49 (1), p.19-25 |
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| creator | Tas, Ebru Ugwu, Emmanuel Ikechukwu Sabah, Eyup Arsoy, Zeyni |
| description | A flocculation process was performed to treat travertine-processing effluents with a high concentration of suspended solids using an eco-friendly biopolymer. The experiments were conducted through a standard jar test procedure to optimize the process parameters for sludge volume index (SVI) and turbidity removal. The effects of mixing time, suspension pH, and polymer dosage on treatment efficiency were investigated using central composite design, a standard technique in response surface methodology. The constructed response model was tested using the analysis of variance (ANOVA). Using the Design-Expert tool, the coefficients of regression models were computed. The Fischer value (F-value) was used to evaluate the significance and validity of the predicted model, while the coefficient of determination (R2) was applied to estimate the model significance by comparing the predicted data with the measured data. The optimized parameters obtained were polymer dose of 276.20 mg/L, suspension pH of 8.60, and mixing time of 4.20 min. The optimal SVI and turbidity values obtained were 1.36 mL/g and 2.99 NTU, respectively. Additionally, R2 values for SVI and turbidity were determined as 0.9337 and 0.8654, respectively. Also, the difference between adjusted R2 values and predicted R2 was less than 0.2. Validation tests showed that the response surface methodology is an effective method for optimizing the flocculation mechanism. |
| doi_str_mv | 10.17159/wsa/2023.v49.i1.3952 |
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| fullrecord | <record><control><sourceid>gale_proqu</sourceid><recordid>TN_cdi_proquest_journals_2777084936</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A737979200</galeid><sourcerecordid>A737979200</sourcerecordid><originalsourceid>FETCH-LOGICAL-c431t-a4f7cc82738b57c4e85ce8091cca666aa8e9ceade56399b71a0d9a21951bc4653</originalsourceid><addsrcrecordid>eNpNkU1r3DAQhk1poCHJTygIemkPdiTZsqzeltCPQEpDP85iLI83CrbkSvIum7-VP1httoeig8TwzDuMnqJ4y2jFJBPqeh_hmlNeV7tGVZZVtRL8VXHOOtaWUgn6-r_3m-IqxkdKKWeN4EqeF8-bZZmsgWS9I34kvfWLnw4zBmIdSWvo7WDTgQSc_Q4mAm4gcVqHLZKIKU3WbUmPD7Czfg3HgBRghyFZh-USvMEYj8geYsI9JAwfyT2G0YcZnEHil2Rn-3Qav76gAePiXcz5axghMzOmBz_4yW8P5P2Pn98-XBZnI0wRr_7dF8Xvz59-3Xwt775_ub3Z3JWmqVkqoRmlMR2XddcLaRrshMGOKmYMtG0L0KEyCAOKtlaqlwzooIAzJVhvmlbUF8W7U25e5M-KMenHvKTLIzWXUtKuUXWbqepEbWFCbd3o8xeYfAacrfEOR5vrG1lLJRWnNDeIU4MJPsaAo16CnSEcNKP6xanOTvXRqc5OtWX66LT-C1X5nEc</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2777084936</pqid></control><display><type>article</type><title>Application of biopolymer in turbidity removal and sludge settling behaviour of travertine-processing wastewater: Performance optimization using response surface methodology (RSM)</title><source>DOAJ Directory of Open Access Journals</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>African Journals Online (Open Access)</source><source>Sabinet African Journals Open Access Collection</source><source>Free Full-Text Journals in Chemistry</source><creator>Tas, Ebru ; Ugwu, Emmanuel Ikechukwu ; Sabah, Eyup ; Arsoy, Zeyni</creator><creatorcontrib>Tas, Ebru ; Ugwu, Emmanuel Ikechukwu ; Sabah, Eyup ; Arsoy, Zeyni</creatorcontrib><description>A flocculation process was performed to treat travertine-processing effluents with a high concentration of suspended solids using an eco-friendly biopolymer. The experiments were conducted through a standard jar test procedure to optimize the process parameters for sludge volume index (SVI) and turbidity removal. The effects of mixing time, suspension pH, and polymer dosage on treatment efficiency were investigated using central composite design, a standard technique in response surface methodology. The constructed response model was tested using the analysis of variance (ANOVA). Using the Design-Expert tool, the coefficients of regression models were computed. The Fischer value (F-value) was used to evaluate the significance and validity of the predicted model, while the coefficient of determination (R2) was applied to estimate the model significance by comparing the predicted data with the measured data. The optimized parameters obtained were polymer dose of 276.20 mg/L, suspension pH of 8.60, and mixing time of 4.20 min. The optimal SVI and turbidity values obtained were 1.36 mL/g and 2.99 NTU, respectively. Additionally, R2 values for SVI and turbidity were determined as 0.9337 and 0.8654, respectively. Also, the difference between adjusted R2 values and predicted R2 was less than 0.2. Validation tests showed that the response surface methodology is an effective method for optimizing the flocculation mechanism.</description><identifier>ISSN: 1816-7950</identifier><identifier>ISSN: 0378-4738</identifier><identifier>EISSN: 1816-7950</identifier><identifier>DOI: 10.17159/wsa/2023.v49.i1.3952</identifier><language>eng</language><publisher>Gezina: Water Research Commission</publisher><subject>Biopolymers ; Caustic soda ; Coefficients ; Design ; Design standards ; Effluents ; Flocculation ; Hydrochloric acid ; Jar tests ; Methods ; Model testing ; Optimization ; Parameters ; Polymers ; Process parameters ; Regression analysis ; Regression models ; Removal ; Response surface methodology ; Settling behavior ; Settling behaviour ; Sludge ; Sludge settling ; Sludge volume index ; Solid suspensions ; Stone ; Suspended particulate matter ; Suspended solids ; Travertine ; Turbidity ; Variance analysis ; Wastewater ; Wastewater treatment ; Water treatment</subject><ispartof>Water S. A., 2023-01, Vol.49 (1), p.19-25</ispartof><rights>COPYRIGHT 2023 Water Research Commission</rights><rights>2023. This work is published under http://www.wrc.org.za/water-sa/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,861,27905,27906</link.rule.ids></links><search><creatorcontrib>Tas, Ebru</creatorcontrib><creatorcontrib>Ugwu, Emmanuel Ikechukwu</creatorcontrib><creatorcontrib>Sabah, Eyup</creatorcontrib><creatorcontrib>Arsoy, Zeyni</creatorcontrib><title>Application of biopolymer in turbidity removal and sludge settling behaviour of travertine-processing wastewater: Performance optimization using response surface methodology (RSM)</title><title>Water S. A.</title><description>A flocculation process was performed to treat travertine-processing effluents with a high concentration of suspended solids using an eco-friendly biopolymer. The experiments were conducted through a standard jar test procedure to optimize the process parameters for sludge volume index (SVI) and turbidity removal. The effects of mixing time, suspension pH, and polymer dosage on treatment efficiency were investigated using central composite design, a standard technique in response surface methodology. The constructed response model was tested using the analysis of variance (ANOVA). Using the Design-Expert tool, the coefficients of regression models were computed. The Fischer value (F-value) was used to evaluate the significance and validity of the predicted model, while the coefficient of determination (R2) was applied to estimate the model significance by comparing the predicted data with the measured data. The optimized parameters obtained were polymer dose of 276.20 mg/L, suspension pH of 8.60, and mixing time of 4.20 min. The optimal SVI and turbidity values obtained were 1.36 mL/g and 2.99 NTU, respectively. Additionally, R2 values for SVI and turbidity were determined as 0.9337 and 0.8654, respectively. Also, the difference between adjusted R2 values and predicted R2 was less than 0.2. Validation tests showed that the response surface methodology is an effective method for optimizing the flocculation mechanism.</description><subject>Biopolymers</subject><subject>Caustic soda</subject><subject>Coefficients</subject><subject>Design</subject><subject>Design standards</subject><subject>Effluents</subject><subject>Flocculation</subject><subject>Hydrochloric acid</subject><subject>Jar tests</subject><subject>Methods</subject><subject>Model testing</subject><subject>Optimization</subject><subject>Parameters</subject><subject>Polymers</subject><subject>Process parameters</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Removal</subject><subject>Response surface methodology</subject><subject>Settling behavior</subject><subject>Settling behaviour</subject><subject>Sludge</subject><subject>Sludge settling</subject><subject>Sludge volume index</subject><subject>Solid suspensions</subject><subject>Stone</subject><subject>Suspended particulate matter</subject><subject>Suspended solids</subject><subject>Travertine</subject><subject>Turbidity</subject><subject>Variance analysis</subject><subject>Wastewater</subject><subject>Wastewater treatment</subject><subject>Water treatment</subject><issn>1816-7950</issn><issn>0378-4738</issn><issn>1816-7950</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNpNkU1r3DAQhk1poCHJTygIemkPdiTZsqzeltCPQEpDP85iLI83CrbkSvIum7-VP1httoeig8TwzDuMnqJ4y2jFJBPqeh_hmlNeV7tGVZZVtRL8VXHOOtaWUgn6-r_3m-IqxkdKKWeN4EqeF8-bZZmsgWS9I34kvfWLnw4zBmIdSWvo7WDTgQSc_Q4mAm4gcVqHLZKIKU3WbUmPD7Czfg3HgBRghyFZh-USvMEYj8geYsI9JAwfyT2G0YcZnEHil2Rn-3Qav76gAePiXcz5axghMzOmBz_4yW8P5P2Pn98-XBZnI0wRr_7dF8Xvz59-3Xwt775_ub3Z3JWmqVkqoRmlMR2XddcLaRrshMGOKmYMtG0L0KEyCAOKtlaqlwzooIAzJVhvmlbUF8W7U25e5M-KMenHvKTLIzWXUtKuUXWbqepEbWFCbd3o8xeYfAacrfEOR5vrG1lLJRWnNDeIU4MJPsaAo16CnSEcNKP6xanOTvXRqc5OtWX66LT-C1X5nEc</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Tas, Ebru</creator><creator>Ugwu, Emmanuel Ikechukwu</creator><creator>Sabah, Eyup</creator><creator>Arsoy, Zeyni</creator><general>Water Research Commission</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QH</scope><scope>7ST</scope><scope>7T7</scope><scope>7UA</scope><scope>7XB</scope><scope>88I</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H97</scope><scope>HCIFZ</scope><scope>L.G</scope><scope>L6V</scope><scope>LK8</scope><scope>M2O</scope><scope>M2P</scope><scope>M7P</scope><scope>M7S</scope><scope>MBDVC</scope><scope>P64</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>SOI</scope></search><sort><creationdate>20230101</creationdate><title>Application of biopolymer in turbidity removal and sludge settling behaviour of travertine-processing wastewater: Performance optimization using response surface methodology (RSM)</title><author>Tas, Ebru ; Ugwu, Emmanuel Ikechukwu ; Sabah, Eyup ; Arsoy, Zeyni</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c431t-a4f7cc82738b57c4e85ce8091cca666aa8e9ceade56399b71a0d9a21951bc4653</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Biopolymers</topic><topic>Caustic soda</topic><topic>Coefficients</topic><topic>Design</topic><topic>Design standards</topic><topic>Effluents</topic><topic>Flocculation</topic><topic>Hydrochloric acid</topic><topic>Jar tests</topic><topic>Methods</topic><topic>Model testing</topic><topic>Optimization</topic><topic>Parameters</topic><topic>Polymers</topic><topic>Process parameters</topic><topic>Regression analysis</topic><topic>Regression models</topic><topic>Removal</topic><topic>Response surface methodology</topic><topic>Settling behavior</topic><topic>Settling behaviour</topic><topic>Sludge</topic><topic>Sludge settling</topic><topic>Sludge volume index</topic><topic>Solid suspensions</topic><topic>Stone</topic><topic>Suspended particulate matter</topic><topic>Suspended solids</topic><topic>Travertine</topic><topic>Turbidity</topic><topic>Variance analysis</topic><topic>Wastewater</topic><topic>Wastewater treatment</topic><topic>Water treatment</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tas, Ebru</creatorcontrib><creatorcontrib>Ugwu, Emmanuel Ikechukwu</creatorcontrib><creatorcontrib>Sabah, Eyup</creatorcontrib><creatorcontrib>Arsoy, Zeyni</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Science Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Middle East & Africa Database</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 3: Aquatic Pollution & Environmental Quality</collection><collection>SciTech Premium Collection</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Engineering Collection</collection><collection>ProQuest Biological Science Collection</collection><collection>Research Library</collection><collection>Science Database</collection><collection>Biological Science Database</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Environment Abstracts</collection><jtitle>Water S. A.</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tas, Ebru</au><au>Ugwu, Emmanuel Ikechukwu</au><au>Sabah, Eyup</au><au>Arsoy, Zeyni</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of biopolymer in turbidity removal and sludge settling behaviour of travertine-processing wastewater: Performance optimization using response surface methodology (RSM)</atitle><jtitle>Water S. A.</jtitle><date>2023-01-01</date><risdate>2023</risdate><volume>49</volume><issue>1</issue><spage>19</spage><epage>25</epage><pages>19-25</pages><issn>1816-7950</issn><issn>0378-4738</issn><eissn>1816-7950</eissn><abstract>A flocculation process was performed to treat travertine-processing effluents with a high concentration of suspended solids using an eco-friendly biopolymer. The experiments were conducted through a standard jar test procedure to optimize the process parameters for sludge volume index (SVI) and turbidity removal. The effects of mixing time, suspension pH, and polymer dosage on treatment efficiency were investigated using central composite design, a standard technique in response surface methodology. The constructed response model was tested using the analysis of variance (ANOVA). Using the Design-Expert tool, the coefficients of regression models were computed. The Fischer value (F-value) was used to evaluate the significance and validity of the predicted model, while the coefficient of determination (R2) was applied to estimate the model significance by comparing the predicted data with the measured data. The optimized parameters obtained were polymer dose of 276.20 mg/L, suspension pH of 8.60, and mixing time of 4.20 min. The optimal SVI and turbidity values obtained were 1.36 mL/g and 2.99 NTU, respectively. Additionally, R2 values for SVI and turbidity were determined as 0.9337 and 0.8654, respectively. Also, the difference between adjusted R2 values and predicted R2 was less than 0.2. Validation tests showed that the response surface methodology is an effective method for optimizing the flocculation mechanism.</abstract><cop>Gezina</cop><pub>Water Research Commission</pub><doi>10.17159/wsa/2023.v49.i1.3952</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Biopolymers Caustic soda Coefficients Design Design standards Effluents Flocculation Hydrochloric acid Jar tests Methods Model testing Optimization Parameters Polymers Process parameters Regression analysis Regression models Removal Response surface methodology Settling behavior Settling behaviour Sludge Sludge settling Sludge volume index Solid suspensions Stone Suspended particulate matter Suspended solids Travertine Turbidity Variance analysis Wastewater Wastewater treatment Water treatment |
| title | Application of biopolymer in turbidity removal and sludge settling behaviour of travertine-processing wastewater: Performance optimization using response surface methodology (RSM) |
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