Personal exposure to mixtures of volatile organic compounds: modeling and further analysis of the RIOPA data.

Emission sources of volatile organic compounds (VOCs*) are numerous and widespread in both indoor and outdoor environments. Concentrations of VOCs indoors typically exceed outdoor levels, and most toxicologic mode of action and represented VOCs associated with hematopoietic, liver, and renal tumors. Estimated lifetime cumulative cancer risks exceeded 10(-3) for about 10% of RIOPA participants. The dependency structures of the VOC mixtures in the RIOPA data set fitted Gumbel (two mixtures) and t copulas (four mixtures). These copula types emphasize dependencies found in the upper and lower tails of a distribution. The copulas reproduced both risk predictions and exposure fractions with a high degree of accuracy and performed better than multivariate lognormal distributions. Specific Aim 3. In an analysis focused on the home environment and the outdoor (close to home) environment, home VOC concentrations dominated personal exposures (66% to 78% of the total exposure, depending on VOC); this was largely the result of the amount of time participants spent at home and the fact that indoor concentrations were much higher than outdoor concentrations for most VOCs. In a different analysis focused on the sources inside the home and outside (but close to the home), it was assumed that 100% of VOCs from outside sources would penetrate the home. Outdoor VOC sources accounted for 5% (d-limonene) to 81% (carbon tetrachloride [CTC]) of the total exposure. Personal exposure and indoor measurements had similar determinants depending on the VOC. Gasoline-related VOCs (e.g., benzene and methyl tert-butyl ether [MTBE]) were associated with city, residences with attached garages, pumping gas, wind speed, and home air exchange rate (AER). Odorant and cleaning-related VOCs (e.g., 1,4-DCB and chloroform) also were associated with city, and a residence\u27s AER, size, and family members showering. Dry-cleaning and industry-related VOCs (e.g., tetrachloroethylene [or perchloroethylene, PERC] and trichloroethylene [TCE]) were associated with city, type of water supply to the home, and visits to the dry cleaner. These and other relationships were significant, they explained from 10% to 40% of the variance in the measurements, and are consistent with known emission sources and those reported in the literature. Outdoor concentrations of VOCs had only two determinants in common: city and wind speed. Overall, personal exposure was dominated by the home setting, although a large fraction of indoor VOC concentrations were due to outdoor sources. City of residence, personal activities, household characteristics, and meteorology were significant determinants. Concentrations in RIOPA were considerably lower than levels in the nationally representative NHANES for all VOCs except MTBE and 1,4-DCB. Differences between RIOPA and NHANES results can be explained by contrasts between the sampling designs and staging in the two studies, and by differences in the demographics, smoking, employment, occupations, and home locations. (ABSTRACT TRUNCATED

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

Part 4. Interaction between air pollution and respiratory viruses: time-series study of daily mortality and hospital admissions in Hong Kong.

BACKGROUND: Populations in Asia are not only at risk of harm to their health through environmental degradation as a result of worsening pollution problems but also constantly threatened by recurring and emerging influenza epidemics and. pandemics. Situated in the area with the world's fastest growing economy and close to hypothetical epicenters of influenza transmission, Hong Kong offers a special opportunity for testing environmental management and public health surveillance in the region. In the Public Health and Air Pollution in Asia (PAPA*) project, the Hong Kong research team assessed the health effects of air pollution and influenza as well as the interaction between them. The team also assessed disparities in the health effects of air pollution between relatively deprived and more affluent areas in Hong Kong. The aim was to provide answers to outstanding research questions relating to the short-term effects of air pollution on mortality and hospital admissions; the health effects of influenza with a view to validating different measures of influenza activity according to virologic data; the confounding effects of influenza on estimates of the health effects of air pollution; the modifying effects of influenza on the health effects of air pollution; and the modifying effects of neighborhood social deprivation on the health effects of air pollution. DATA: Data on mortality and hospital admissions for all natural causes, as well as the subcategories of cardiovascular diseases (CVD) and respiratory diseases (RD), were derived from the Hong Kong Census and Statistics Department and the Hospital Authority. Daily concentrations of nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter with an aerodynamic diameter or = 4% of the annual total number of positive isolates [i.e., twice the expected mean value] in two or more consecutive weeks); and influenza predominance (defined as a period of influenza epidemic when the weekly frequency of RSV was less than 2% for two or more consecutive weeks).link_to_subscribed_fulltex

Part 5. Public health and air pollution in Asia (PAPA): a combined analysis of four studies of air pollution and mortality.

In recent years, Asia has experienced rapid economic growth and a deteriorating environment caused by the increasing use of fossil fuels. Although the deleterious effects of air pollution from fossil-fuel combustion have been demonstrated in many Western nations, few comparable studies have been conducted in Asia. Time-series studies of daily mortality in Asian cities can contribute important new information to the existing body of knowledge about air pollution and health. Not only can these studies verify important health effects of air pollution in local regions in Asia, they can also help determine the relevance of existing air pollution studies to mortality and morbidity for policymaking and environmental controls. In addition, the studies can help identify factors that might modify associations between air pollution and health effects in various populations and environmental conditions. Collaborative multicity studies in Asia-especially when designed, conducted, and analyzed using a common protocol-will provide more robust air pollution effect estimates for the region as well as relevant, supportable estimates of local adverse health effects needed by environmental and public-health policymakers. SPECIFIC OBJECTIVES: The Public Health and Air Pollution in Asia (PAPA*) project, sponsored by the Health Effects Institute, consisted of four studies designed to assess the effects of air pollution on mortality in four large Asian cities, namely Bangkok, in Thailand, and Hong Kong, Shanghai, and Wuhan, in China. In the PAPA project, a Common Protocol was developed based on methods developed and tested in NMMAPS, APHEA, and time-series studies in the literature to help ensure that the four studies could be compared with each other and with previous studies by following an established protocol. The Common Protocol (found at the end of this volume) is a set of prescriptive instructions developed for the studies and used by the investigators in each city. It is flexible enough to allow for adjustments in methods to optimize the fit of health-effects models to each city's data set. It provides the basis for generating reproducible results in each city and for meta-estimates from combined data. By establishing a common methodology, factors that might influence the differences in results from previous studies can more easily be explored. Administrative support was provided to ensure that the highest quality data were used in the analysis. It is anticipated that the PAPA results will contribute to the international scientific discussion of how to conduct and interpret time-series studies of air pollution and will stimulate the development of high-quality routine systems for recording daily deaths and hospital admissions for time-series analysis. Mortality data were retrieved from routine databases with underlying causes of death coded using the World Health Organization (WHO) International Classification of Diseases, 9th revision or 10th revision (ICD-9, ICD-10). Air quality measurements included nitrogen dioxide (NO2), sulfur dioxide (SO2), particulate matter with aerodynamic diameter < or = 10 microm (PM10), and ozone (O3) and were obtained from several fixed-site air monitoring stations that were located throughout the metropolitan areas of the four cities and that met the standards of procedures for quality assurance and quality control carried out by local government units in each city.link_to_subscribed_fulltex