Literature DB >> 19999825

Measurement and modeling of exposure to selected air toxics for health effects studies and verification by biomarkers.

Roy M Harrison1, Juana Maria Delgado-Saborit, Stephen J Baker, Noel Aquilina, Claire Meddings, Stuart Harrad, Ian Matthews, Sotiris Vardoulakis, H Ross Anderson.   

Abstract

The overall aim of our investigation was to quantify the magnitude and range of individual personal exposures to a variety of air toxics and to develop models for exposure prediction on the basis of time-activity diaries. The specific research goals were (1) to use personal monitoring of non-smokers at a range of residential locations and exposures to non-traffic sources to assess daily exposures to a range of air toxics, especially volatile organic compounds (VOCs) including 1,3-butadiene and particulate polycyclic aromatic hydrocarbons (PAHs); (2) to determine microenvironmental concentrations of the same air toxics, taking account of spatial and temporal variations and hot spots; (3) to optimize a model of personal exposure using microenvironmental concentration data and time-activity diaries and to compare modeled exposures with exposures independently estimated from personal monitoring data; (4) to determine the relationships of urinary biomarkers with the environmental exposures to the corresponding air toxic. Personal exposure measurements were made using an actively pumped personal sampler enclosed in a briefcase. Five 24-hour integrated personal samples were collected from 100 volunteers with a range of exposure patterns for analysis of VOCs and 1,3-butadiene concentrations of ambient air. One 24-hour integrated PAH personal exposure sample was collected by each subject concurrently with 24 hours of the personal sampling for VOCs. During the period when personal exposures were being measured, workplace and home concentrations of the same air toxics were being measured simultaneously, as were seasonal levels in other microenvironments that the subjects visit during their daily activities, including street microenvironments, transport microenvironments, indoor environments, and other home environments. Information about subjects' lifestyles and daily activities were recorded by means of questionnaires and activity diaries. VOCs were collected in tubes packed with the adsorbent resins Tenax GR and Carbotrap, and separate tubes for the collection of 1,3-butadiene were packed with Carbopack B and Carbosieve S-III. After sampling, the tubes were analyzed by means of a thermal desorber interfaced with a gas chromatograph-mass spectrometer (GC-MS). Particle-phase PAHs collected onto a quartz-fiber filter were extracted with solvent, purified, and concentrated before being analyzed with a GC-MS. Urinary biomarkers were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS-MS). Both the environmental concentrations and personal exposure concentrations measured in this study are lower than those in the majority of earlier published work, which is consistent with the reported application of abatement measures to the control of air toxics emissions. The environmental concentration data clearly demonstrate the influence of traffic sources and meteorologic conditions leading to higher air toxics concentrations in the winter and during peak-traffic hours. The seasonal effect was also observed in indoor environments, where indoor sources add to the effects of the previously identified outdoor sources. The variability of personal exposure concentrations of VOCs and PAHs mainly reflects the range of activities the subjects engaged in during the five-day period of sampling. A number of generic factors have been identified to influence personal exposure concentrations to VOCs, such as the presence of an integral garage (attached to the home), exposure to environmental tobacco smoke (ETS), use of solvents, and commuting. In the case of the medium- and high-molecular-weight PAHs, traffic and ETS are important contributions to personal exposure. Personal exposure concentrations generally exceed home indoor concentrations, which in turn exceed outdoor concentrations. The home microenvironment is the dominant individual contributor to personal exposure. However, for those subjects with particularly high personal exposures, activities within the home and exposure to ETS play a major role in determining exposure. Correlation analysis and principal components analysis (PCA) have been performed to identify groups of compounds that share common sources, common chemistry, or common transport or meteorologic patterns. We used these methods to identify four main factors determining the makeup of personal exposures: fossil fuel combustion, use of solvents, ETS exposure, and use of consumer products. Concurrent with sampling of the selected air toxics, a total of 500 urine samples were collected, one for each of the 100 subjects on the day after each of the five days on which the briefcases were carried for personal exposure data collection. From the 500 samples, 100 were selected to be analyzed for PAHs and ETS-related urinary biomarkers. Results showed that urinary biomarkers of ETS exposure correlated strongly with the gas-phase markers of ETS and 1,3-butadiene. The urinary ETS biomarkers also correlated strongly with high-molecular-weight PAHs in the personal exposure samples. Five different approaches have been taken to model personal exposure to VOCs and PAHs, using 75% of the measured personal exposure data set to develop the models and 25% as an independent check on the model performance. The best personal exposure model, based on measured microenvironmental concentrations and lifestyle factors, is able to account for about 50% of the variance in measured personal exposure to benzene and a higher proportion of the variance for some other compounds (e.g., 75% of the variance in 3-ethenylpyridine exposure). In the case of the PAHs, the best model for benzo[a]pyrene is able to account for about 35% of the variance among exposures, with a similar result for the rest of the PAH compounds. The models developed were validated by the independent data set for almost all the VOC compounds. The models developed for PAHs explain some of the variance in the independent data set and are good indicators of the sources affecting PAH concentrations but could not be validated statistically, with the exception of the model for pyrene. A proposal for categorizing personal exposures as low or high is also presented, according to exposure thresholds. For both VOCs and PAHs, low exposures are correctly classified for the concentrations predicted by the proposed models, but higher exposures were less successfully classified.

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Year:  2009        PMID: 19999825

Source DB:  PubMed          Journal:  Res Rep Health Eff Inst        ISSN: 1041-5505


  14 in total

1.  Association between cancer risk and polycyclic aromatic hydrocarbons' exposure in the ambient air of Ahvaz, southwest of Iran.

Authors:  Gholamreza Goudarzi; Sahar Geravandi; Nadali Alavi; Esmaeil Idani; Shokrolah Salmanzadeh; Ahmad Reza Yari; Farkhondeh Jamshidi; Mohammad Javad Mohammadi; Akbar Ranjbarzadeh; Farzaneh Aslanpour Alamdari; Fatemeh Darabi; Alireza Rohban
Journal:  Int J Biometeorol       Date:  2018-06-29       Impact factor: 3.787

2.  Environmental and biological monitoring of exposures to PAHs and ETS in the general population.

Authors:  Noel J Aquilina; Juana Mari Delgado-Saborit; Claire Meddings; Stephen Baker; Roy M Harrison; Peyton Jacob; Margaret Wilson; Lisa Yu; Minjiang Duan; Neal L Benowitz
Journal:  Environ Int       Date:  2010-06-29       Impact factor: 9.621

3.  Health risk assessment on human exposed to heavy metals in the ambient air PM10 in Ahvaz, southwest Iran.

Authors:  Gholamreza Goudarzi; Nadali Alavi; Sahar Geravandi; Esmaeil Idani; Hamid Reza Adeli Behrooz; Ali Akbar Babaei; Farzaneh Aslanpour Alamdari; Sina Dobaradaran; Majid Farhadi; Mohammad Javad Mohammadi
Journal:  Int J Biometeorol       Date:  2018-02-20       Impact factor: 3.787

4.  Estimation of chronic personal exposure to airborne polycyclic aromatic hydrocarbons.

Authors:  Hyunok Choi; Michael Zdeb; Frederica Perera; John Spengler
Journal:  Sci Total Environ       Date:  2015-05-14       Impact factor: 7.963

5.  Neighborhood socioeconomic status modifies the association between individual smoking status and PAH-DNA adduct levels in prostate tissue.

Authors:  Andrew Rundle; Catherine Richards; Christine Neslund-Dudas; Deliang Tang; Benjamin A Rybicki
Journal:  Environ Mol Mutagen       Date:  2012-03-29       Impact factor: 3.216

Review 6.  Genetic and epigenetic influences associated with intrauterine growth restriction due to in utero tobacco exposure.

Authors:  Melissa Suter; Adi Abramovici; Kjersti Aagaard-Tillery
Journal:  Pediatr Endocrinol Rev       Date:  2010-12

Review 7.  A review of PAH exposure from the combustion of biomass fuel and their less surveyed effect on the blood parameters.

Authors:  Atif Kamal; Alessandra Cincinelli; Tania Martellini; Riffat Naseem Malik
Journal:  Environ Sci Pollut Res Int       Date:  2014-11-21       Impact factor: 4.223

8.  Modeling personal particle-bound polycyclic aromatic hydrocarbon (pb-pah) exposure in human subjects in Southern California.

Authors:  Jun Wu; Thomas Tjoa; Lianfa Li; Guillermo Jaimes; Ralph J Delfino
Journal:  Environ Health       Date:  2012-07-11       Impact factor: 5.984

9.  Predictors of blood volatile organic compound levels in Gulf coast residents.

Authors:  Emily J Werder; Kaitlyn B Gam; Lawrence S Engel; Richard K Kwok; Christine C Ekenga; Matthew D Curry; David M Chambers; Aaron Blair; Aubrey K Miller; Linda S Birnbaum; Dale P Sandler
Journal:  J Expo Sci Environ Epidemiol       Date:  2017-12-29       Impact factor: 5.563

10.  Model development and validation of personal exposure to volatile organic compound concentrations.

Authors:  Juana Mari Delgado-Saborit; Noel J Aquilina; Claire Meddings; Stephen Baker; Roy M Harrison
Journal:  Environ Health Perspect       Date:  2009-06-23       Impact factor: 9.031

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