Model Development and Validation of Personal Exposure to Volatile Organic Compound Concentrations

Background: Direct measurement of exposure to volatile organic compounds (VOCs) via personal monitoring is the most accurate exposure assessment method available. However, its wide-scale application to evaluating exposures at the population level is prohibitive in terms of both cost and time. Consequently, indirect measurements via a combination of microenvironment concentrations and personal activity diaries represent a potentially useful alternative. Objective: The aim of this study was to optimize a model of personal exposures (PEs) based on microenvironment concentrations and time/activity diaries and to compare modeled with measured exposures in an independent data set. Materials: VOC PEs and a range of microenvironment concentrations were collected with active samplers and sorbent tubes. Data were supplemented with information collected through questionnaires. Seven models were tested to predict PE to VOCs in 75% (n = 370) of the measured PE data set, whereas the other 25% (n = 120) was used for validation purposes. Results: The best model able to predict PE with independence of measurements was based upon stratified microenvironment concentrations, lifestyle factors, and individual-level activities. The proposed model accounts for 40–85% of the variance for individual VOCs and was validated for almost all VOCs, showing normalized mean bias and mean fractional bias below 25% and predicting 60% of the values within a factor of 2. Conclusions: The models proposed identify the most important non-weather-related variables for VOC exposures; highlight the effect of personal activities, use of solvents, and exposure to environmental tobacco smoke on PE levels; and may assist in the development of specific models for other locations.peer-reviewe

Chemical reactivity and long-range transport potential of polycyclic aromatic hydrocarbons – a review

Polycyclic aromatic hydrocarbons (PAHs) are of considerable concern due to their well-recognised toxicity and especially due to the carcinogenic hazard which they present. PAHs are semi-volatile and therefore partition between vapour and condensed phases in the atmosphere and both the vapour and particulate forms undergo chemical reactions. This article briefly reviews the current understanding of vapour-particle partitioning of PAHs and the PAH deposition processes, and in greater detail, their chemical reactions. PAHs are reactive towards a number of atmospheric oxidants, most notably the hydroxyl radical, ozone, the nitrate radical (NO3) and nitrogen dioxide. Rate coefficient data are reviewed for reactions of lower molecular weight PAH vapour with these species as well as for heterogeneous reactions of higher molecular weight compounds. Whereas the data for reactions of the 2-3-ring PAH vapour are quite extensive and generally consistent, such data are mostly lacking for the 4-ring PAHs and the heterogeneous rate data (5 and more rings), which are dependent on the substrate type and reaction conditions, are less comprehensive. The atmospheric reactions of PAH lead to the formation of oxy and nitro derivatives, reviewed here, too. Finally, the capacity of PAHs for long range transport and the results of numerical model studies are described. Research needs are identified

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

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