Chemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS.
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFOP |
Texto Completo: | http://www.repositorio.ufop.br/handle/123456789/5072 https://doi.org/10.1016/j.microc.2014.06.017 |
Resumo: | Contaminants of emerging concern are organic compounds used in large quantities by the society for various purposes. They have shown biological activity at lowconcentrations,which gives great environmental relevance. The difficulty to detect and quantify contaminants of emerging concern in the environment stimulates the development of appropriate analytical methods. In this work a chemometric approach to positive and negative electrospray ionization (ESI) optimization for the simultaneous determination of contaminants of emerging concern in water samples by liquid chromatography-ion trap-time of flight-high resolution mass spectrometry (LC-IT-TOF-HRMS) was applied. Three types of phase modifiers were used: formic acid, ammonium hydroxide and formic acid/ammonium formate. The effects of operational parameters such as mobile phase modifier concentrations, mobile phase flow rate, heating block temperature and drying gas flow rate were evaluated by the 24− 1 fractional factorial experimental design, resolution IV, in the screening phase and byDoehlert experimental design. Initial factorial experimental design studies indicated that the phasemodifier ammonium hydroxide was more efficient compared to the other evaluated modifiers. It provided higher ion intensities to the majority of analytes. Doehlert experimental design allowed finding a region indicative of the optimum experimental conditions for most analytes. The best experimental condition observedwas 3.5mMammoniumhydroxide concentration; 0.0917 mL/min of mobile phase; 300 °C heating block temperature; and drying gas at 200 kPa. These optimized parameters resulted in decreased detection limits of the method. The optimized method was applied to the evaluation of water samples coming from the Rio Doce basin — Minas Gerais/Brazil utilizing multivariate exploratory techniques such as principal component analysis and Kohonen neural network. In this way, the use of chemometric approach showed to be a promisingway to optimize the simultaneous determination of twentyone contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS using ESI. |
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Rodrigues, Keila Letícia TeixeiraSanson, Ananda LimaQuaresma, Amanda de VasconcelosGomes, Rafaela de PaivaSilva, Gilmare Antônia daAfonso, Robson José de Cássia Franco2015-04-14T17:52:14Z2015-04-14T17:52:14Z2014RODRIGUES, K. L. T. et al. Chemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS. Microchemical Journal, v. 117, p. 242-249, 2014. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0026265X14001209>. Acesso em: 02 fev. 2015.0026-265Xhttp://www.repositorio.ufop.br/handle/123456789/5072https://doi.org/10.1016/j.microc.2014.06.017Contaminants of emerging concern are organic compounds used in large quantities by the society for various purposes. They have shown biological activity at lowconcentrations,which gives great environmental relevance. The difficulty to detect and quantify contaminants of emerging concern in the environment stimulates the development of appropriate analytical methods. In this work a chemometric approach to positive and negative electrospray ionization (ESI) optimization for the simultaneous determination of contaminants of emerging concern in water samples by liquid chromatography-ion trap-time of flight-high resolution mass spectrometry (LC-IT-TOF-HRMS) was applied. Three types of phase modifiers were used: formic acid, ammonium hydroxide and formic acid/ammonium formate. The effects of operational parameters such as mobile phase modifier concentrations, mobile phase flow rate, heating block temperature and drying gas flow rate were evaluated by the 24− 1 fractional factorial experimental design, resolution IV, in the screening phase and byDoehlert experimental design. Initial factorial experimental design studies indicated that the phasemodifier ammonium hydroxide was more efficient compared to the other evaluated modifiers. It provided higher ion intensities to the majority of analytes. Doehlert experimental design allowed finding a region indicative of the optimum experimental conditions for most analytes. The best experimental condition observedwas 3.5mMammoniumhydroxide concentration; 0.0917 mL/min of mobile phase; 300 °C heating block temperature; and drying gas at 200 kPa. These optimized parameters resulted in decreased detection limits of the method. The optimized method was applied to the evaluation of water samples coming from the Rio Doce basin — Minas Gerais/Brazil utilizing multivariate exploratory techniques such as principal component analysis and Kohonen neural network. In this way, the use of chemometric approach showed to be a promisingway to optimize the simultaneous determination of twentyone contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS using ESI.Contaminants of emerging concernMultivariate optimizationDoehlert designKohonen neural networkChemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS.info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleO periódico Microchemical Journal concede permissão para depósito deste artigo no Repositório Institucional da UFOP. Número da licença: 3580760016881.info:eu-repo/semantics/openAccessengreponame:Repositório Institucional da UFOPinstname:Universidade Federal de Ouro Preto (UFOP)instacron:UFOPLICENSElicense.txtlicense.txttext/plain; charset=utf-82636http://www.repositorio.ufop.br/bitstream/123456789/5072/2/license.txtc2ffdd99e58acf69202dff00d361f23aMD52ORIGINALARTIGO_ChemometricApproachOptmize.pdfARTIGO_ChemometricApproachOptmize.pdfapplication/pdf3079748http://www.repositorio.ufop.br/bitstream/123456789/5072/1/ARTIGO_ChemometricApproachOptmize.pdf9b2346692db70feecf2b4829a4ea633aMD51123456789/50722019-07-10 13:03:23.465oai:localhost: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Repositório InstitucionalPUBhttp://www.repositorio.ufop.br/oai/requestrepositorio@ufop.edu.bropendoar:32332019-07-10T17:03:23Repositório Institucional da UFOP - Universidade Federal de Ouro Preto (UFOP)false |
dc.title.pt_BR.fl_str_mv |
Chemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS. |
title |
Chemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS. |
spellingShingle |
Chemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS. Rodrigues, Keila Letícia Teixeira Contaminants of emerging concern Multivariate optimization Doehlert design Kohonen neural network |
title_short |
Chemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS. |
title_full |
Chemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS. |
title_fullStr |
Chemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS. |
title_full_unstemmed |
Chemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS. |
title_sort |
Chemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS. |
author |
Rodrigues, Keila Letícia Teixeira |
author_facet |
Rodrigues, Keila Letícia Teixeira Sanson, Ananda Lima Quaresma, Amanda de Vasconcelos Gomes, Rafaela de Paiva Silva, Gilmare Antônia da Afonso, Robson José de Cássia Franco |
author_role |
author |
author2 |
Sanson, Ananda Lima Quaresma, Amanda de Vasconcelos Gomes, Rafaela de Paiva Silva, Gilmare Antônia da Afonso, Robson José de Cássia Franco |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Rodrigues, Keila Letícia Teixeira Sanson, Ananda Lima Quaresma, Amanda de Vasconcelos Gomes, Rafaela de Paiva Silva, Gilmare Antônia da Afonso, Robson José de Cássia Franco |
dc.subject.por.fl_str_mv |
Contaminants of emerging concern Multivariate optimization Doehlert design Kohonen neural network |
topic |
Contaminants of emerging concern Multivariate optimization Doehlert design Kohonen neural network |
description |
Contaminants of emerging concern are organic compounds used in large quantities by the society for various purposes. They have shown biological activity at lowconcentrations,which gives great environmental relevance. The difficulty to detect and quantify contaminants of emerging concern in the environment stimulates the development of appropriate analytical methods. In this work a chemometric approach to positive and negative electrospray ionization (ESI) optimization for the simultaneous determination of contaminants of emerging concern in water samples by liquid chromatography-ion trap-time of flight-high resolution mass spectrometry (LC-IT-TOF-HRMS) was applied. Three types of phase modifiers were used: formic acid, ammonium hydroxide and formic acid/ammonium formate. The effects of operational parameters such as mobile phase modifier concentrations, mobile phase flow rate, heating block temperature and drying gas flow rate were evaluated by the 24− 1 fractional factorial experimental design, resolution IV, in the screening phase and byDoehlert experimental design. Initial factorial experimental design studies indicated that the phasemodifier ammonium hydroxide was more efficient compared to the other evaluated modifiers. It provided higher ion intensities to the majority of analytes. Doehlert experimental design allowed finding a region indicative of the optimum experimental conditions for most analytes. The best experimental condition observedwas 3.5mMammoniumhydroxide concentration; 0.0917 mL/min of mobile phase; 300 °C heating block temperature; and drying gas at 200 kPa. These optimized parameters resulted in decreased detection limits of the method. The optimized method was applied to the evaluation of water samples coming from the Rio Doce basin — Minas Gerais/Brazil utilizing multivariate exploratory techniques such as principal component analysis and Kohonen neural network. In this way, the use of chemometric approach showed to be a promisingway to optimize the simultaneous determination of twentyone contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS using ESI. |
publishDate |
2014 |
dc.date.issued.fl_str_mv |
2014 |
dc.date.accessioned.fl_str_mv |
2015-04-14T17:52:14Z |
dc.date.available.fl_str_mv |
2015-04-14T17:52:14Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
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article |
status_str |
publishedVersion |
dc.identifier.citation.fl_str_mv |
RODRIGUES, K. L. T. et al. Chemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS. Microchemical Journal, v. 117, p. 242-249, 2014. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0026265X14001209>. Acesso em: 02 fev. 2015. |
dc.identifier.uri.fl_str_mv |
http://www.repositorio.ufop.br/handle/123456789/5072 |
dc.identifier.issn.none.fl_str_mv |
0026-265X |
dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.1016/j.microc.2014.06.017 |
identifier_str_mv |
RODRIGUES, K. L. T. et al. Chemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS. Microchemical Journal, v. 117, p. 242-249, 2014. Disponível em: <http://www.sciencedirect.com/science/article/pii/S0026265X14001209>. Acesso em: 02 fev. 2015. 0026-265X |
url |
http://www.repositorio.ufop.br/handle/123456789/5072 https://doi.org/10.1016/j.microc.2014.06.017 |
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