Bedoukian   RussellIPM   RussellIPM   Piezoelectric Micro-Sprayer


Home
Animal Taxa
Plant Taxa
Semiochemicals
Floral Compounds
Semiochemical Detail
Semiochemicals & Taxa
Synthesis
Control
Invasive spp.
References

Abstract

Guide

Alphascents
Pherobio
InsectScience
E-Econex
Counterpart-Semiochemicals
Print
Email to a Friend
Kindly Donate for The Pherobase

« Previous AbstractElectrophysiological responses of olfactory receptor neurons to stimulation with mixtures of individual pheromone components    Next AbstractEffects of PEG-induced osmotic stress on growth and dhurrin levels of forage sorghum »

J Expo Sci Environ Epidemiol


Title:Determining chemical air equivalency using silicone personal monitors
Author(s):O'Connell SG; Anderson KA; Epstein MI;
Address:"MyExposome, Inc., Corvallis, OR, USA. steven.oconnell@myexposome.com. Environmental and Molecular Toxicology Department, Oregon State University, Corvallis, OR, USA. MyExposome, Inc., Corvallis, OR, USA"
Journal Title:J Expo Sci Environ Epidemiol
Year:2022
Volume:20210505
Issue:2
Page Number:268 - 279
DOI: 10.1038/s41370-021-00332-6
ISSN/ISBN:1559-064X (Electronic) 1559-0631 (Print) 1559-0631 (Linking)
Abstract:"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"
Keywords:*Air Pollutants/analysis Environmental Monitoring Humans Silicones *Volatile Organic Compounds/analysis;
Notes:"MedlineO'Connell, Steven G Anderson, Kim A Epstein, Marc I eng Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. 2021/05/07 J Expo Sci Environ Epidemiol. 2022 Mar; 32(2):268-279. doi: 10.1038/s41370-021-00332-6. Epub 2021 May 5"

 
Back to top
 
Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
© 2003-2024 The Pherobase - Extensive Database of Pheromones and Semiochemicals. Ashraf M. El-Sayed.
Page created on 26-12-2024