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Aerosol Oxidative Potential in the Greater Los Angeles Area: Source Apportionment and Associations with Socioeconomic Position

[Image: see text] Oxidative potential (OP) has been proposed as a possible integrated metric for particles smaller than 2.5 μm in diameter (PM(2.5)) to evaluate adverse health outcomes associated with particulate air pollution exposure. Here, we investigate how OP depends on sources and chemical com...

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Autores principales: Shen, Jiaqi, Taghvaee, Sina, La, Chris, Oroumiyeh, Farzan, Liu, Jonathan, Jerrett, Michael, Weichenthal, Scott, Del Rosario, Irish, Shafer, Martin M., Ritz, Beate, Zhu, Yifang, Paulson, Suzanne E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2022
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9775201/
https://www.ncbi.nlm.nih.gov/pubmed/36472388
http://dx.doi.org/10.1021/acs.est.2c02788
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author Shen, Jiaqi
Taghvaee, Sina
La, Chris
Oroumiyeh, Farzan
Liu, Jonathan
Jerrett, Michael
Weichenthal, Scott
Del Rosario, Irish
Shafer, Martin M.
Ritz, Beate
Zhu, Yifang
Paulson, Suzanne E.
author_facet Shen, Jiaqi
Taghvaee, Sina
La, Chris
Oroumiyeh, Farzan
Liu, Jonathan
Jerrett, Michael
Weichenthal, Scott
Del Rosario, Irish
Shafer, Martin M.
Ritz, Beate
Zhu, Yifang
Paulson, Suzanne E.
author_sort Shen, Jiaqi
collection PubMed
description [Image: see text] Oxidative potential (OP) has been proposed as a possible integrated metric for particles smaller than 2.5 μm in diameter (PM(2.5)) to evaluate adverse health outcomes associated with particulate air pollution exposure. Here, we investigate how OP depends on sources and chemical composition and how OP varies by land use type and neighborhood socioeconomic position in the Los Angeles area. We measured OH formation (OP(OH)), dithiothreitol loss (OP(DTT)), black carbon, and 52 metals and elements for 54 total PM(2.5) samples collected in September 2019 and February 2020. The Positive Matrix Factorization source apportionment model identified four sources contributing to volume-normalized OP(OH): vehicular exhaust, brake and tire wear, soil and road dust, and mixed secondary and marine. Exhaust emissions contributed 42% of OP(OH), followed by 21% from brake and tire wear. Similar results were observed for the OP(DTT) source apportionment. Furthermore, by linking measured PM(2.5) and OP with census tract level socioeconomic and health outcome data provided by CalEnviroScreen, we found that the most disadvantaged neighborhoods were exposed to both the most toxic particles and the highest particle concentrations. OP(OH) exhibited the largest inverse social gradients, followed by OP(DTT) and PM(2.5) mass. Finally, OP(OH) was the metric most strongly correlated with adverse health outcome indicators.
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spelling pubmed-97752012022-12-23 Aerosol Oxidative Potential in the Greater Los Angeles Area: Source Apportionment and Associations with Socioeconomic Position Shen, Jiaqi Taghvaee, Sina La, Chris Oroumiyeh, Farzan Liu, Jonathan Jerrett, Michael Weichenthal, Scott Del Rosario, Irish Shafer, Martin M. Ritz, Beate Zhu, Yifang Paulson, Suzanne E. Environ Sci Technol [Image: see text] Oxidative potential (OP) has been proposed as a possible integrated metric for particles smaller than 2.5 μm in diameter (PM(2.5)) to evaluate adverse health outcomes associated with particulate air pollution exposure. Here, we investigate how OP depends on sources and chemical composition and how OP varies by land use type and neighborhood socioeconomic position in the Los Angeles area. We measured OH formation (OP(OH)), dithiothreitol loss (OP(DTT)), black carbon, and 52 metals and elements for 54 total PM(2.5) samples collected in September 2019 and February 2020. The Positive Matrix Factorization source apportionment model identified four sources contributing to volume-normalized OP(OH): vehicular exhaust, brake and tire wear, soil and road dust, and mixed secondary and marine. Exhaust emissions contributed 42% of OP(OH), followed by 21% from brake and tire wear. Similar results were observed for the OP(DTT) source apportionment. Furthermore, by linking measured PM(2.5) and OP with census tract level socioeconomic and health outcome data provided by CalEnviroScreen, we found that the most disadvantaged neighborhoods were exposed to both the most toxic particles and the highest particle concentrations. OP(OH) exhibited the largest inverse social gradients, followed by OP(DTT) and PM(2.5) mass. Finally, OP(OH) was the metric most strongly correlated with adverse health outcome indicators. American Chemical Society 2022-12-06 2022-12-20 /pmc/articles/PMC9775201/ /pubmed/36472388 http://dx.doi.org/10.1021/acs.est.2c02788 Text en © 2022 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by/4.0/Permits the broadest form of re-use including for commercial purposes, provided that author attribution and integrity are maintained (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Shen, Jiaqi
Taghvaee, Sina
La, Chris
Oroumiyeh, Farzan
Liu, Jonathan
Jerrett, Michael
Weichenthal, Scott
Del Rosario, Irish
Shafer, Martin M.
Ritz, Beate
Zhu, Yifang
Paulson, Suzanne E.
Aerosol Oxidative Potential in the Greater Los Angeles Area: Source Apportionment and Associations with Socioeconomic Position
title Aerosol Oxidative Potential in the Greater Los Angeles Area: Source Apportionment and Associations with Socioeconomic Position
title_full Aerosol Oxidative Potential in the Greater Los Angeles Area: Source Apportionment and Associations with Socioeconomic Position
title_fullStr Aerosol Oxidative Potential in the Greater Los Angeles Area: Source Apportionment and Associations with Socioeconomic Position
title_full_unstemmed Aerosol Oxidative Potential in the Greater Los Angeles Area: Source Apportionment and Associations with Socioeconomic Position
title_short Aerosol Oxidative Potential in the Greater Los Angeles Area: Source Apportionment and Associations with Socioeconomic Position
title_sort aerosol oxidative potential in the greater los angeles area: source apportionment and associations with socioeconomic position
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9775201/
https://www.ncbi.nlm.nih.gov/pubmed/36472388
http://dx.doi.org/10.1021/acs.est.2c02788
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