Degradation of the pharmaceuticals nimesulide and ibuprofen using photo-Fenton process: toxicity studies, kinetic modeling and use of artificial neural networks
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Eletrônica em Gestão Educação e Tecnologia Ambiental (REGET) |
Texto Completo: | https://periodicos.ufsm.br/reget/article/view/31563 |
Resumo: | The growth of pollution in aquatic environments increases every day, causing compounds like pharmaceuticas to be detected in surface waters. Thus, tecniques such as advanced oxidation processes (AOP) have been used to degrade this compounds. In this work, the efficiency of AOP in the degradation of nimesulide and ibuprofen pharmaceuticals was evaluated through chromatographic analysis as well as organic matter through the levels of chemical oxygen demand (COD) and total organic carbon (TOC). It was verified that the photo-Fenton process presented the bests results, degrading 89.70% of nimesulide and 93.35% of ibuprofen. This same process managed to reduce COD by 91.60% and mineralize 90.04% of the TOC. The kinetic study showed a good linear fit (R2=0.993) for the clustered kinetic model, as well as a good fit to the mathematical model of artificial neural networks (ANNs), with a value of R2=1.000 for the MLP4-4-1 BFGS 4567 model. Finally, the toxicity of the solution after treatment was verified against the seeds of Lactuta sativa, Cichorium endívia, Ocimum basilicum and American Hard grain. It was found that the seeds that received the solution before treatment had a lower germination amount than the ones where the post AOP treatment solution was added. Then, the root growth was evaluated, in which a relative toxic effect was observed. |
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Degradation of the pharmaceuticals nimesulide and ibuprofen using photo-Fenton process: toxicity studies, kinetic modeling and use of artificial neural networksDegradação dos fármacos nimesulida e ibuprofeno empregando processo foto-Fenton: estudos da toxicidade, modelagem cinética e emprego de redes neurais artificiaisIbuprofenNimesulidePhoto-FentonIbuprofenoNimesulidaPhoto-FentonThe growth of pollution in aquatic environments increases every day, causing compounds like pharmaceuticas to be detected in surface waters. Thus, tecniques such as advanced oxidation processes (AOP) have been used to degrade this compounds. In this work, the efficiency of AOP in the degradation of nimesulide and ibuprofen pharmaceuticals was evaluated through chromatographic analysis as well as organic matter through the levels of chemical oxygen demand (COD) and total organic carbon (TOC). It was verified that the photo-Fenton process presented the bests results, degrading 89.70% of nimesulide and 93.35% of ibuprofen. This same process managed to reduce COD by 91.60% and mineralize 90.04% of the TOC. The kinetic study showed a good linear fit (R2=0.993) for the clustered kinetic model, as well as a good fit to the mathematical model of artificial neural networks (ANNs), with a value of R2=1.000 for the MLP4-4-1 BFGS 4567 model. Finally, the toxicity of the solution after treatment was verified against the seeds of Lactuta sativa, Cichorium endívia, Ocimum basilicum and American Hard grain. It was found that the seeds that received the solution before treatment had a lower germination amount than the ones where the post AOP treatment solution was added. Then, the root growth was evaluated, in which a relative toxic effect was observed.O crescimento da poluição de ambientes aquáticos tem aumentado todos os dias, fazendo com que compostos como os fármacos sejam verificados em águas superficiais. Desse modo, técnicas como processos oxidativos avançados (POA) tem sido utilizadas. Neste trabalho a eficiência dos POA na degradação dos fármacos nimesulida e ibuprofeno foi avaliada, através de análises cromatográficas, bem como de matéria orgânica através dos níveis de demanda química de oxigênio (DQO) e carbono orgânico total (COT). Verificou-se que o processo foto-Fenton apresentou os melhores resultados degradando 89,70% do nimesulida e 93,35% do ibuprofeno. Esse mesmo processo conseguiu reduzir em 91,60% a DQO e mineralizar 90,04% do COT. O estudo cinético mostrou bom ajuste linear (R2=0,993) para o modelo cinético agrupado, além de uma boa adequação ao modelo matemático de redes neurais artificiais (RNA), com um valor de R2=1,000 para o modelo MLP4-4-1 BFGS4567. Por fim, verificou-se a toxicidade da solução após tratamento, frente às sementes de Lactuta Sativa, Cichorium endívia, Ocimum basilicum e do grão Americano Hard. Verificou-se que as sementes que receberam a solução antes do tratamento apresentaram uma quantidade menor germinação, do que quando foi adicionada a solução pós-tratamento via POA. Em seguida, avaliou-se o crescimento radicular, no qual foi percebido relativo efeito tóxico.Universidade Federal de Santa Maria2018-08-23info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufsm.br/reget/article/view/3156310.5902/2236117031563Revista Eletrônica em Gestão, Educação e Tecnologia Ambiental; REGET, V. 22, 2018; e3Revista Eletrônica em Gestão, Educação e Tecnologia Ambiental; REGET, V. 22, 2018; e32236-11702236-1170reponame:Revista Eletrônica em Gestão Educação e Tecnologia Ambiental (REGET)instname:Universidade Federal de Santa Maria (UFSM)instacron:UFSMenghttps://periodicos.ufsm.br/reget/article/view/31563/pdfCopyright (c) 2018 Electronic Journal of Management, Education and Environmental Technology (REGET)http://creativecommons.org/licenses/by-nc-sa/4.0info:eu-repo/semantics/openAccessMonteiro, Rubens TelesSantana, Rayany Magali da RochaSilva, Ana Maria Ribeiro Bastos daLucena, Alex Leandro Andrade deZaidan, Léa Elias Mendes CarneiroSilva, Valdinete Lins daNapoleão, Daniella Carla2022-08-09T14:40:14Zoai:ojs.pkp.sfu.ca:article/31563Revistahttps://periodicos.ufsm.br/regetPUBhttps://periodicos.ufsm.br/reget/oaimarcelobdarosa@gmail.com||reget.ufsm@gmail.com2236-11702236-1170opendoar:2022-08-09T14:40:14Revista Eletrônica em Gestão Educação e Tecnologia Ambiental (REGET) - Universidade Federal de Santa Maria (UFSM)false |
dc.title.none.fl_str_mv |
Degradation of the pharmaceuticals nimesulide and ibuprofen using photo-Fenton process: toxicity studies, kinetic modeling and use of artificial neural networks Degradação dos fármacos nimesulida e ibuprofeno empregando processo foto-Fenton: estudos da toxicidade, modelagem cinética e emprego de redes neurais artificiais |
title |
Degradation of the pharmaceuticals nimesulide and ibuprofen using photo-Fenton process: toxicity studies, kinetic modeling and use of artificial neural networks |
spellingShingle |
Degradation of the pharmaceuticals nimesulide and ibuprofen using photo-Fenton process: toxicity studies, kinetic modeling and use of artificial neural networks Monteiro, Rubens Teles Ibuprofen Nimesulide Photo-Fenton Ibuprofeno Nimesulida Photo-Fenton |
title_short |
Degradation of the pharmaceuticals nimesulide and ibuprofen using photo-Fenton process: toxicity studies, kinetic modeling and use of artificial neural networks |
title_full |
Degradation of the pharmaceuticals nimesulide and ibuprofen using photo-Fenton process: toxicity studies, kinetic modeling and use of artificial neural networks |
title_fullStr |
Degradation of the pharmaceuticals nimesulide and ibuprofen using photo-Fenton process: toxicity studies, kinetic modeling and use of artificial neural networks |
title_full_unstemmed |
Degradation of the pharmaceuticals nimesulide and ibuprofen using photo-Fenton process: toxicity studies, kinetic modeling and use of artificial neural networks |
title_sort |
Degradation of the pharmaceuticals nimesulide and ibuprofen using photo-Fenton process: toxicity studies, kinetic modeling and use of artificial neural networks |
author |
Monteiro, Rubens Teles |
author_facet |
Monteiro, Rubens Teles Santana, Rayany Magali da Rocha Silva, Ana Maria Ribeiro Bastos da Lucena, Alex Leandro Andrade de Zaidan, Léa Elias Mendes Carneiro Silva, Valdinete Lins da Napoleão, Daniella Carla |
author_role |
author |
author2 |
Santana, Rayany Magali da Rocha Silva, Ana Maria Ribeiro Bastos da Lucena, Alex Leandro Andrade de Zaidan, Léa Elias Mendes Carneiro Silva, Valdinete Lins da Napoleão, Daniella Carla |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Monteiro, Rubens Teles Santana, Rayany Magali da Rocha Silva, Ana Maria Ribeiro Bastos da Lucena, Alex Leandro Andrade de Zaidan, Léa Elias Mendes Carneiro Silva, Valdinete Lins da Napoleão, Daniella Carla |
dc.subject.por.fl_str_mv |
Ibuprofen Nimesulide Photo-Fenton Ibuprofeno Nimesulida Photo-Fenton |
topic |
Ibuprofen Nimesulide Photo-Fenton Ibuprofeno Nimesulida Photo-Fenton |
description |
The growth of pollution in aquatic environments increases every day, causing compounds like pharmaceuticas to be detected in surface waters. Thus, tecniques such as advanced oxidation processes (AOP) have been used to degrade this compounds. In this work, the efficiency of AOP in the degradation of nimesulide and ibuprofen pharmaceuticals was evaluated through chromatographic analysis as well as organic matter through the levels of chemical oxygen demand (COD) and total organic carbon (TOC). It was verified that the photo-Fenton process presented the bests results, degrading 89.70% of nimesulide and 93.35% of ibuprofen. This same process managed to reduce COD by 91.60% and mineralize 90.04% of the TOC. The kinetic study showed a good linear fit (R2=0.993) for the clustered kinetic model, as well as a good fit to the mathematical model of artificial neural networks (ANNs), with a value of R2=1.000 for the MLP4-4-1 BFGS 4567 model. Finally, the toxicity of the solution after treatment was verified against the seeds of Lactuta sativa, Cichorium endívia, Ocimum basilicum and American Hard grain. It was found that the seeds that received the solution before treatment had a lower germination amount than the ones where the post AOP treatment solution was added. Then, the root growth was evaluated, in which a relative toxic effect was observed. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-08-23 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://periodicos.ufsm.br/reget/article/view/31563 10.5902/2236117031563 |
url |
https://periodicos.ufsm.br/reget/article/view/31563 |
identifier_str_mv |
10.5902/2236117031563 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://periodicos.ufsm.br/reget/article/view/31563/pdf |
dc.rights.driver.fl_str_mv |
Copyright (c) 2018 Electronic Journal of Management, Education and Environmental Technology (REGET) http://creativecommons.org/licenses/by-nc-sa/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2018 Electronic Journal of Management, Education and Environmental Technology (REGET) http://creativecommons.org/licenses/by-nc-sa/4.0 |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
publisher.none.fl_str_mv |
Universidade Federal de Santa Maria |
dc.source.none.fl_str_mv |
Revista Eletrônica em Gestão, Educação e Tecnologia Ambiental; REGET, V. 22, 2018; e3 Revista Eletrônica em Gestão, Educação e Tecnologia Ambiental; REGET, V. 22, 2018; e3 2236-1170 2236-1170 reponame:Revista Eletrônica em Gestão Educação e Tecnologia Ambiental (REGET) instname:Universidade Federal de Santa Maria (UFSM) instacron:UFSM |
instname_str |
Universidade Federal de Santa Maria (UFSM) |
instacron_str |
UFSM |
institution |
UFSM |
reponame_str |
Revista Eletrônica em Gestão Educação e Tecnologia Ambiental (REGET) |
collection |
Revista Eletrônica em Gestão Educação e Tecnologia Ambiental (REGET) |
repository.name.fl_str_mv |
Revista Eletrônica em Gestão Educação e Tecnologia Ambiental (REGET) - Universidade Federal de Santa Maria (UFSM) |
repository.mail.fl_str_mv |
marcelobdarosa@gmail.com||reget.ufsm@gmail.com |
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1799950576950181888 |