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Computational modeling method to estimate secondhand exposure potential from exhalations during e-vapor product use under various real-world scenarios

Potential secondhand exposure of exhaled constituents from e-vapor product (EVP) use is a public health concern. We present a computational modeling method to predict air levels of exhaled constituents from EVP use. We measured select constituent levels in exhaled breath from adult e-vapor product u...

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Autores principales: Edmiston, Jeffery S., Rostami, Ali A., Liang, Qiwei, Miller, Sandra, Sarkar, Mohamadi A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9522680/
https://www.ncbi.nlm.nih.gov/pubmed/36050572
http://dx.doi.org/10.1007/s11739-022-03061-2
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author Edmiston, Jeffery S.
Rostami, Ali A.
Liang, Qiwei
Miller, Sandra
Sarkar, Mohamadi A.
author_facet Edmiston, Jeffery S.
Rostami, Ali A.
Liang, Qiwei
Miller, Sandra
Sarkar, Mohamadi A.
author_sort Edmiston, Jeffery S.
collection PubMed
description Potential secondhand exposure of exhaled constituents from e-vapor product (EVP) use is a public health concern. We present a computational modeling method to predict air levels of exhaled constituents from EVP use. We measured select constituent levels in exhaled breath from adult e-vapor product users, then used a validated computational model to predict constituent levels under three scenarios (car, office, and restaurant) to estimate likely secondhand exposure to non-users. The model was based on physical/thermodynamic interactions between air, vapor, and particulate phase of the aerosol. Input variables included space setting, ventilation rate, total aerosol amount exhaled, and aerosol composition. Exhaled breath samples were analyzed after the use of four different e-liquids in a cartridge-based EVP. Nicotine, propylene glycol, glycerin, menthol, formaldehyde, acetaldehyde, and acrolein levels were measured and reported based on a linear mixed model for analysis of covariance. The ranges of nicotine, propylene glycol, glycerin, and formaldehyde in exhaled breath were 89.44–195.70 µg, 1199.7–3354.5 µg, 5366.8–6484.7 µg, and 0.25–0.34 µg, respectively. Acetaldehyde and acrolein were below detectable limits; thus, no estimated exposure to non-EVP users is reported. The model predicted that nicotine and formaldehyde exposure to non-users was substantially lower during EVPs use compared to cigarettes. The model also predicted that exposure to propylene glycol, glycerin, nicotine and formaldehyde among non-users was below permissible exposure limits. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11739-022-03061-2.
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spelling pubmed-95226802022-10-01 Computational modeling method to estimate secondhand exposure potential from exhalations during e-vapor product use under various real-world scenarios Edmiston, Jeffery S. Rostami, Ali A. Liang, Qiwei Miller, Sandra Sarkar, Mohamadi A. Intern Emerg Med Im - Original Potential secondhand exposure of exhaled constituents from e-vapor product (EVP) use is a public health concern. We present a computational modeling method to predict air levels of exhaled constituents from EVP use. We measured select constituent levels in exhaled breath from adult e-vapor product users, then used a validated computational model to predict constituent levels under three scenarios (car, office, and restaurant) to estimate likely secondhand exposure to non-users. The model was based on physical/thermodynamic interactions between air, vapor, and particulate phase of the aerosol. Input variables included space setting, ventilation rate, total aerosol amount exhaled, and aerosol composition. Exhaled breath samples were analyzed after the use of four different e-liquids in a cartridge-based EVP. Nicotine, propylene glycol, glycerin, menthol, formaldehyde, acetaldehyde, and acrolein levels were measured and reported based on a linear mixed model for analysis of covariance. The ranges of nicotine, propylene glycol, glycerin, and formaldehyde in exhaled breath were 89.44–195.70 µg, 1199.7–3354.5 µg, 5366.8–6484.7 µg, and 0.25–0.34 µg, respectively. Acetaldehyde and acrolein were below detectable limits; thus, no estimated exposure to non-EVP users is reported. The model predicted that nicotine and formaldehyde exposure to non-users was substantially lower during EVPs use compared to cigarettes. The model also predicted that exposure to propylene glycol, glycerin, nicotine and formaldehyde among non-users was below permissible exposure limits. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11739-022-03061-2. Springer International Publishing 2022-09-01 2022 /pmc/articles/PMC9522680/ /pubmed/36050572 http://dx.doi.org/10.1007/s11739-022-03061-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Im - Original
Edmiston, Jeffery S.
Rostami, Ali A.
Liang, Qiwei
Miller, Sandra
Sarkar, Mohamadi A.
Computational modeling method to estimate secondhand exposure potential from exhalations during e-vapor product use under various real-world scenarios
title Computational modeling method to estimate secondhand exposure potential from exhalations during e-vapor product use under various real-world scenarios
title_full Computational modeling method to estimate secondhand exposure potential from exhalations during e-vapor product use under various real-world scenarios
title_fullStr Computational modeling method to estimate secondhand exposure potential from exhalations during e-vapor product use under various real-world scenarios
title_full_unstemmed Computational modeling method to estimate secondhand exposure potential from exhalations during e-vapor product use under various real-world scenarios
title_short Computational modeling method to estimate secondhand exposure potential from exhalations during e-vapor product use under various real-world scenarios
title_sort computational modeling method to estimate secondhand exposure potential from exhalations during e-vapor product use under various real-world scenarios
topic Im - Original
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9522680/
https://www.ncbi.nlm.nih.gov/pubmed/36050572
http://dx.doi.org/10.1007/s11739-022-03061-2
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