Process modeling toward higher degradation and minimum energy consumption of an electrochemical decontamination of food dye wastewater
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Publication Date: | 2021 |
Other Authors: | , , , , , , , , , , |
Format: | Article |
Language: | eng |
Source: | Repositório Institucional da UNESP |
Download full: | http://dx.doi.org/10.1016/j.eti.2021.101509 http://hdl.handle.net/11449/206152 |
Summary: | This study explores the modeling and optimization of electrochemical influencing parameters on the sunset yellow (SSY) decontamination process by response surface methodology (RSM). Four factors historical data design which include time (X1), pH 03–10 (X2), NaCl concentration 0.02–0.08 M (X3) and current densities 2.5 to 10 mA cm −2 (X4) was employed to correlate the factors with dye removal and electrical energy consumption as responses. Stepwise regression analysis of first order, second order, cubic and quadratic polynomial models were performed to test the model fitness. Higher degradation of SSY at examined array was found to 99.2% with energy consumption of 0.340 kWhm−3 and the operating variables were as follows: time: 48.42 min, pH of 4.15, NaCl concentration of 0.065 M and current density of 2.70 mA cm −2. The model for energy consumption fitted with experimental data demonstrated a higher R2 value of 0.9998, proving the significance of proposed model. The Analysis of variance (ANOVA) with a higher value of R2: 0.9746 adjusted R2: 0.9716, predicted R2: 0.9639 and t-test revealed that second-order polynomial model fitted the experimental results well and have a decent correlation between the observed and predicted data of SSY degrdation. Furthermore, the degradation process followed pseudo first order kinetic under different operating parameters and 53% TOC (total organic carbon) removal as observed as consequence of electrochemical degradation of SSY at optimized conditions. The results revealed that the historical data design response surface methodology is worth statistical tools for accuratley predicting the optimum conditions for electrochemical abatement of food dye sunset yellow. |
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Process modeling toward higher degradation and minimum energy consumption of an electrochemical decontamination of food dye wastewaterElectrochemical oxidationFood dyeHistorical dataModelingRSMWastewaterThis study explores the modeling and optimization of electrochemical influencing parameters on the sunset yellow (SSY) decontamination process by response surface methodology (RSM). Four factors historical data design which include time (X1), pH 03–10 (X2), NaCl concentration 0.02–0.08 M (X3) and current densities 2.5 to 10 mA cm −2 (X4) was employed to correlate the factors with dye removal and electrical energy consumption as responses. Stepwise regression analysis of first order, second order, cubic and quadratic polynomial models were performed to test the model fitness. Higher degradation of SSY at examined array was found to 99.2% with energy consumption of 0.340 kWhm−3 and the operating variables were as follows: time: 48.42 min, pH of 4.15, NaCl concentration of 0.065 M and current density of 2.70 mA cm −2. The model for energy consumption fitted with experimental data demonstrated a higher R2 value of 0.9998, proving the significance of proposed model. The Analysis of variance (ANOVA) with a higher value of R2: 0.9746 adjusted R2: 0.9716, predicted R2: 0.9639 and t-test revealed that second-order polynomial model fitted the experimental results well and have a decent correlation between the observed and predicted data of SSY degrdation. Furthermore, the degradation process followed pseudo first order kinetic under different operating parameters and 53% TOC (total organic carbon) removal as observed as consequence of electrochemical degradation of SSY at optimized conditions. The results revealed that the historical data design response surface methodology is worth statistical tools for accuratley predicting the optimum conditions for electrochemical abatement of food dye sunset yellow.Faculty of Materials and Chemical Engineering GIK Institute of Engineering Sciences and TechnologyFaculdade de Engenharias Arquitetura e Urbanismo e Geografia Universidade Federal de Mato Grosso do Sul Cidade UniversitariaDepartment of Chemistry Islamia College PeshawarSão Paulo State University (UNESP) Institute of Chemistry, Araraquara. 55 Prof. Francisco Degni StSão Paulo State University (UNESP) Institute of Chemistry, Araraquara. 55 Prof. Francisco Degni StGIK Institute of Engineering Sciences and TechnologyUniversidade Federal de Mato Grosso do Sul (UFMS)Islamia College PeshawarUniversidade Estadual Paulista (Unesp)Hussain, SajjadKhan, HammadKhan, NadeemGul, SaimaWahab, FazalKhan, Khurram ImranZeb, Shakeel [UNESP]Khan, Sabir [UNESP]Baddouh, Ali [UNESP]Mehdi, ShozabMaldonado, Ariane FioreseCampos, Marcelo2021-06-25T10:27:26Z2021-06-25T10:27:26Z2021-05-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1016/j.eti.2021.101509Environmental Technology and Innovation, v. 22.2352-1864http://hdl.handle.net/11449/20615210.1016/j.eti.2021.1015092-s2.0-85103692939Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEnvironmental Technology and Innovationinfo:eu-repo/semantics/openAccess2025-05-28T07:44:36Zoai:repositorio.unesp.br:11449/206152Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestrepositoriounesp@unesp.bropendoar:29462025-05-28T07:44:36Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Process modeling toward higher degradation and minimum energy consumption of an electrochemical decontamination of food dye wastewater |
title |
Process modeling toward higher degradation and minimum energy consumption of an electrochemical decontamination of food dye wastewater |
spellingShingle |
Process modeling toward higher degradation and minimum energy consumption of an electrochemical decontamination of food dye wastewater Hussain, Sajjad Electrochemical oxidation Food dye Historical data Modeling RSM Wastewater |
title_short |
Process modeling toward higher degradation and minimum energy consumption of an electrochemical decontamination of food dye wastewater |
title_full |
Process modeling toward higher degradation and minimum energy consumption of an electrochemical decontamination of food dye wastewater |
title_fullStr |
Process modeling toward higher degradation and minimum energy consumption of an electrochemical decontamination of food dye wastewater |
title_full_unstemmed |
Process modeling toward higher degradation and minimum energy consumption of an electrochemical decontamination of food dye wastewater |
title_sort |
Process modeling toward higher degradation and minimum energy consumption of an electrochemical decontamination of food dye wastewater |
author |
Hussain, Sajjad |
author_facet |
Hussain, Sajjad Khan, Hammad Khan, Nadeem Gul, Saima Wahab, Fazal Khan, Khurram Imran Zeb, Shakeel [UNESP] Khan, Sabir [UNESP] Baddouh, Ali [UNESP] Mehdi, Shozab Maldonado, Ariane Fiorese Campos, Marcelo |
author_role |
author |
author2 |
Khan, Hammad Khan, Nadeem Gul, Saima Wahab, Fazal Khan, Khurram Imran Zeb, Shakeel [UNESP] Khan, Sabir [UNESP] Baddouh, Ali [UNESP] Mehdi, Shozab Maldonado, Ariane Fiorese Campos, Marcelo |
author2_role |
author author author author author author author author author author author |
dc.contributor.none.fl_str_mv |
GIK Institute of Engineering Sciences and Technology Universidade Federal de Mato Grosso do Sul (UFMS) Islamia College Peshawar Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Hussain, Sajjad Khan, Hammad Khan, Nadeem Gul, Saima Wahab, Fazal Khan, Khurram Imran Zeb, Shakeel [UNESP] Khan, Sabir [UNESP] Baddouh, Ali [UNESP] Mehdi, Shozab Maldonado, Ariane Fiorese Campos, Marcelo |
dc.subject.por.fl_str_mv |
Electrochemical oxidation Food dye Historical data Modeling RSM Wastewater |
topic |
Electrochemical oxidation Food dye Historical data Modeling RSM Wastewater |
description |
This study explores the modeling and optimization of electrochemical influencing parameters on the sunset yellow (SSY) decontamination process by response surface methodology (RSM). Four factors historical data design which include time (X1), pH 03–10 (X2), NaCl concentration 0.02–0.08 M (X3) and current densities 2.5 to 10 mA cm −2 (X4) was employed to correlate the factors with dye removal and electrical energy consumption as responses. Stepwise regression analysis of first order, second order, cubic and quadratic polynomial models were performed to test the model fitness. Higher degradation of SSY at examined array was found to 99.2% with energy consumption of 0.340 kWhm−3 and the operating variables were as follows: time: 48.42 min, pH of 4.15, NaCl concentration of 0.065 M and current density of 2.70 mA cm −2. The model for energy consumption fitted with experimental data demonstrated a higher R2 value of 0.9998, proving the significance of proposed model. The Analysis of variance (ANOVA) with a higher value of R2: 0.9746 adjusted R2: 0.9716, predicted R2: 0.9639 and t-test revealed that second-order polynomial model fitted the experimental results well and have a decent correlation between the observed and predicted data of SSY degrdation. Furthermore, the degradation process followed pseudo first order kinetic under different operating parameters and 53% TOC (total organic carbon) removal as observed as consequence of electrochemical degradation of SSY at optimized conditions. The results revealed that the historical data design response surface methodology is worth statistical tools for accuratley predicting the optimum conditions for electrochemical abatement of food dye sunset yellow. |
publishDate |
2021 |
dc.date.none.fl_str_mv |
2021-06-25T10:27:26Z 2021-06-25T10:27:26Z 2021-05-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1016/j.eti.2021.101509 Environmental Technology and Innovation, v. 22. 2352-1864 http://hdl.handle.net/11449/206152 10.1016/j.eti.2021.101509 2-s2.0-85103692939 |
url |
http://dx.doi.org/10.1016/j.eti.2021.101509 http://hdl.handle.net/11449/206152 |
identifier_str_mv |
Environmental Technology and Innovation, v. 22. 2352-1864 10.1016/j.eti.2021.101509 2-s2.0-85103692939 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Environmental Technology and Innovation |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
repositoriounesp@unesp.br |
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1834482867851231232 |