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Identification of Unknown Substances in Ambient Air (PM(10)), Profiles and Differences between Rural, Urban and Industrial Areas

A fast and automated strategy has been developed for identifying unknown substances in the atmosphere (concretely, in the particulate matter, PM(10)) using LC-HRMS (MS(3)). A total of 15 samples were collected in three different areas (rural, urban and industrial). A sampling flow rate of 30 m(3) h(...

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Autores principales: López, Antonio, Fuentes, Esther, Yusà, Vicent, Ibáñez, María, Coscollà, Clara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9145881/
https://www.ncbi.nlm.nih.gov/pubmed/35622634
http://dx.doi.org/10.3390/toxics10050220
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author López, Antonio
Fuentes, Esther
Yusà, Vicent
Ibáñez, María
Coscollà, Clara
author_facet López, Antonio
Fuentes, Esther
Yusà, Vicent
Ibáñez, María
Coscollà, Clara
author_sort López, Antonio
collection PubMed
description A fast and automated strategy has been developed for identifying unknown substances in the atmosphere (concretely, in the particulate matter, PM(10)) using LC-HRMS (MS(3)). A total of 15 samples were collected in three different areas (rural, urban and industrial). A sampling flow rate of 30 m(3) h(−1) was applied for 24 h, sampling a total volume of around 720 m(3). A total of 49 compounds were tentatively identified using very restrictive criteria regarding exact mass, retention time, isotopic profile and both MS(2) and MS(3) spectra. Pesticides, pharmaceutical active compounds, drugs, plasticizers and metabolites were the most identified compounds. To verify whether the developed methodology was suitable, 11 substances were checked with their analytical standards and all of them were confirmed. Different profiles for industrial, rural and urban areas were examined. The Principal Component Analysis (PCA) model allowed us to separate the obtained data of the three assessed area. When the profiles obtained in the three evaluated areas were compared using a Volcano plot (the rural area was taken as reference), 11 compounds were confirmed as being discriminant: three of them (3-hydroxy-2-methylpyridine, 3-methyladenine and nicotine) were more likely to be found in industrial sites; ten compounds (3-hydroxy-2-methylpyridine, 3-methyladenine, azoxystrobin, cocaine, cotinine, ethoprophos, imidacloprid, metalaxyl-M, nicotine and pyrimethanil) were more probable in the case of urban sites; finally, triisopropanolamine was more likely to be detected in rural locations.
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spelling pubmed-91458812022-05-29 Identification of Unknown Substances in Ambient Air (PM(10)), Profiles and Differences between Rural, Urban and Industrial Areas López, Antonio Fuentes, Esther Yusà, Vicent Ibáñez, María Coscollà, Clara Toxics Article A fast and automated strategy has been developed for identifying unknown substances in the atmosphere (concretely, in the particulate matter, PM(10)) using LC-HRMS (MS(3)). A total of 15 samples were collected in three different areas (rural, urban and industrial). A sampling flow rate of 30 m(3) h(−1) was applied for 24 h, sampling a total volume of around 720 m(3). A total of 49 compounds were tentatively identified using very restrictive criteria regarding exact mass, retention time, isotopic profile and both MS(2) and MS(3) spectra. Pesticides, pharmaceutical active compounds, drugs, plasticizers and metabolites were the most identified compounds. To verify whether the developed methodology was suitable, 11 substances were checked with their analytical standards and all of them were confirmed. Different profiles for industrial, rural and urban areas were examined. The Principal Component Analysis (PCA) model allowed us to separate the obtained data of the three assessed area. When the profiles obtained in the three evaluated areas were compared using a Volcano plot (the rural area was taken as reference), 11 compounds were confirmed as being discriminant: three of them (3-hydroxy-2-methylpyridine, 3-methyladenine and nicotine) were more likely to be found in industrial sites; ten compounds (3-hydroxy-2-methylpyridine, 3-methyladenine, azoxystrobin, cocaine, cotinine, ethoprophos, imidacloprid, metalaxyl-M, nicotine and pyrimethanil) were more probable in the case of urban sites; finally, triisopropanolamine was more likely to be detected in rural locations. MDPI 2022-04-27 /pmc/articles/PMC9145881/ /pubmed/35622634 http://dx.doi.org/10.3390/toxics10050220 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
López, Antonio
Fuentes, Esther
Yusà, Vicent
Ibáñez, María
Coscollà, Clara
Identification of Unknown Substances in Ambient Air (PM(10)), Profiles and Differences between Rural, Urban and Industrial Areas
title Identification of Unknown Substances in Ambient Air (PM(10)), Profiles and Differences between Rural, Urban and Industrial Areas
title_full Identification of Unknown Substances in Ambient Air (PM(10)), Profiles and Differences between Rural, Urban and Industrial Areas
title_fullStr Identification of Unknown Substances in Ambient Air (PM(10)), Profiles and Differences between Rural, Urban and Industrial Areas
title_full_unstemmed Identification of Unknown Substances in Ambient Air (PM(10)), Profiles and Differences between Rural, Urban and Industrial Areas
title_short Identification of Unknown Substances in Ambient Air (PM(10)), Profiles and Differences between Rural, Urban and Industrial Areas
title_sort identification of unknown substances in ambient air (pm(10)), profiles and differences between rural, urban and industrial areas
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9145881/
https://www.ncbi.nlm.nih.gov/pubmed/35622634
http://dx.doi.org/10.3390/toxics10050220
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