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Determining chemical air equivalency using silicone personal monitors
BACKGROUND: Silicone personal samplers are increasingly being used to measure chemical exposures, but many of these studies do not attempt to calculate environmental concentrations. OBJECTIVE: Using measurements of silicone wristband uptake of organic chemicals from atmospheric exposure, create log...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8920887/ https://www.ncbi.nlm.nih.gov/pubmed/33953340 http://dx.doi.org/10.1038/s41370-021-00332-6 |
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author | O’Connell, Steven G. Anderson, Kim A. Epstein, Marc I. |
author_facet | O’Connell, Steven G. Anderson, Kim A. Epstein, Marc I. |
author_sort | O’Connell, Steven G. |
collection | PubMed |
description | BACKGROUND: Silicone personal samplers are increasingly being used to measure chemical exposures, but many of these studies do not attempt to calculate environmental concentrations. OBJECTIVE: Using measurements of silicone wristband uptake of organic chemicals from atmospheric exposure, create log K(sa) and k(e) predictive models based on empirical data to help develop air equivalency calculations for both volatile and semi-volatile organic compounds. METHODS: An atmospheric vapor generator and a custom exposure chamber were used to measure the uptake of organic chemicals into silicone wristbands under simulated indoor conditions. Log K(sa) models were evaluated using repeated k-fold cross-validation. Air equivalency was compared between best-performing models. RESULTS: Log K(sa) and log k(e) estimates calculated from uptake data were used to build predictive models from boiling point (BP) and other parameters (all models: R(2) = 0.70–0.94). The log K(sa) models were combined with published data and refined to create comprehensive and effective predictive models (R(2): 0.95–0.97). Final estimates of air equivalency using novel BP models correlated well over an example dataset (Spearman r = 0.984) across 5-orders of magnitude (<0.05 to >5000 ng/L). SIGNIFICANCE: Data from silicone samplers can be translated into air equivalent concentrations that better characterize environmental concentrations associated with personal exposures and allow direct comparisons to regulatory levels. |
format | Online Article Text |
id | pubmed-8920887 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-89208872022-03-30 Determining chemical air equivalency using silicone personal monitors O’Connell, Steven G. Anderson, Kim A. Epstein, Marc I. J Expo Sci Environ Epidemiol Article BACKGROUND: Silicone personal samplers are increasingly being used to measure chemical exposures, but many of these studies do not attempt to calculate environmental concentrations. OBJECTIVE: Using measurements of silicone wristband uptake of organic chemicals from atmospheric exposure, create log K(sa) and k(e) predictive models based on empirical data to help develop air equivalency calculations for both volatile and semi-volatile organic compounds. METHODS: An atmospheric vapor generator and a custom exposure chamber were used to measure the uptake of organic chemicals into silicone wristbands under simulated indoor conditions. Log K(sa) models were evaluated using repeated k-fold cross-validation. Air equivalency was compared between best-performing models. RESULTS: Log K(sa) and log k(e) estimates calculated from uptake data were used to build predictive models from boiling point (BP) and other parameters (all models: R(2) = 0.70–0.94). The log K(sa) models were combined with published data and refined to create comprehensive and effective predictive models (R(2): 0.95–0.97). Final estimates of air equivalency using novel BP models correlated well over an example dataset (Spearman r = 0.984) across 5-orders of magnitude (<0.05 to >5000 ng/L). SIGNIFICANCE: Data from silicone samplers can be translated into air equivalent concentrations that better characterize environmental concentrations associated with personal exposures and allow direct comparisons to regulatory levels. Nature Publishing Group US 2021-05-05 2022 /pmc/articles/PMC8920887/ /pubmed/33953340 http://dx.doi.org/10.1038/s41370-021-00332-6 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article O’Connell, Steven G. Anderson, Kim A. Epstein, Marc I. Determining chemical air equivalency using silicone personal monitors |
title | Determining chemical air equivalency using silicone personal monitors |
title_full | Determining chemical air equivalency using silicone personal monitors |
title_fullStr | Determining chemical air equivalency using silicone personal monitors |
title_full_unstemmed | Determining chemical air equivalency using silicone personal monitors |
title_short | Determining chemical air equivalency using silicone personal monitors |
title_sort | determining chemical air equivalency using silicone personal monitors |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8920887/ https://www.ncbi.nlm.nih.gov/pubmed/33953340 http://dx.doi.org/10.1038/s41370-021-00332-6 |
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