Process modeling toward higher degradation and minimum energy consumption of an electrochemical decontamination of food dye wastewater

Bibliographic Details
Main Author: Hussain, Sajjad
Publication Date: 2021
Other Authors: 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
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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spelling 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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