Variability of environmental exposures to volatile organic compounds

Land-Use Regression Modeling to Estimate NO2 and VOC Concentrations in Pohang City, South Korea

Land-use regression (LUR) has emerged as a promising technique for air pollution modeling to obtain the spatial distribution of air pollutants for epidemiological studies. LUR uses traffic, geographic, and monitoring data to develop regression models and then predict the concentration of air pollutants in the same area. To identify the spatial distribution of nitrogen dioxide (NO2), benzene, toluene, and m-p-xylene, we developed LUR models in Pohang City, one of the largest industrialized areas in Korea. Passive samplings were conducted during two 2-week integrated sampling periods in September 2010 and March 2011, at 50 sampling locations. For LUR model development, predictor variables were calculated based on land use, road lengths, point sources, satellite remote sensing, and population density. The averaged mean concentrations of NO2, benzene, toluene, and m-p-xylene were 28.4 µg/m3, 2.40 µg/m3, 15.36 µg/m3, and 0.21 µg/m3, respectively. In terms of model-based R2 values, the model for NO2 included four independent variables, showing R2 = 0.65. While the benzene and m-p-xylene models showed the same R2 values (0.43), toluene showed a lower R2 value (0.35). We estimated long-term concentrations of NO2 and VOCs at 167,057 addresses in Pohang. Our study could hold particular promise in an epidemiological setting having significant health effects associated with small area variations and encourage the extended study using LUR modeling in Asia.

Frequency of use of household products containing VOCs and indoor atmospheric concentrations in homes

Volatile organic compounds (VOCs) are a key class of atmospheric emission released from highly complex petrochemical, transport and solvent sources both outdoors and indoors. This study established the concentrations and speciation of VOCs in 60 homes (204 individuals, 360 × 72 h samples, 40 species) in summer and winter, along with outdoor controls. Self-reported daily statistics were collected in each home on the use of cleaning, household and personal care products, all of which are known to release VOCs. Frequency of product use varied widely: deodorants: 2.9 uses home per day; sealant-mastics 0.02 uses home per day. The total concentration of VOCs indoors (range C2-C10) was highly variable between homes e.g. range 16.6-8150 μg m-3 in winter. Indoor concentrations of VOCs exceeded outdoor for 84% of households studied in summer and 100% of homes in winter. The most abundant VOCs found indoors in this study were n-butane (wintertime range: 1.5-4630 μg m-3), likely released as aerosol propellant, ethanol, acetone and propane. The cumulative use VOC-containing products over multiday timescales by occupants provided little predictive power to infer 72 hour averaged indoor concentrations. However, there was weak covariance between the cumulative usage of certain products and individual VOCs. From a domestic emissions perspective, reducing the use of hydrocarbon-based aerosol propellants indoors would likely have the largest impact.

The Fort Collins commuter study: Variability in personal exposure to air pollutants by microenvironment

This study investigated the role of microenvironment on personal exposures to black carbon (BC), fine particulate mass (PM2.5 ), carbon monoxide (CO), and particle number concentration (PNC) among adult residents of Fort Collins, Colorado, USA. Forty-four participants carried a backpack containing personal monitoring instruments for eight nonconsecutive 24-hour periods. Exposures were apportioned into five microenvironments: Home, Work, Transit, Eateries, and Other. Personal exposures exhibited wide heterogeneity that was dominated by within-person variability (both day-to-day and between microenvironment variability). Linear mixed-effects models were used to compare mean personal exposures in each microenvironment, while accounting for possible within-person correlation. Mean personal exposures during Transit and at Eateries tended to be higher than exposures at Home, where participants spent the majority of their time. Compared to Home, mean exposures to BC in Transit were, on average, 129% [95% confidence interval: 101% 162%] higher and exposures to PNC were 180% [101% 289%] higher in Eateries.

Determinants of personal exposure to some carcinogenic substances and nitrogen dioxide among the general population in five Swedish cities

Environmental levels of airborne carcinogenic and related substances are comparatively better known than individual exposure and its determinants. We report on a personal monitoring program involving five Swedish urban populations. The aim of the program was to investigate personal exposure to benzene, 1,3-butadiene, formaldehyde, and nitrogen dioxide (NO2). The measurements were performed among 40 inhabitants during seven consecutive days, in one urban area each year, during 2000-2008. The estimated population exposure levels were 1.95 μg/m(3) for benzene, 0.56 μg/m(3) for 1,3-butadiene, 19.4 μg/m(3) for formaldehyde, and 14.1 μg/m(3) for NO2. Statistical analysis using a mixed-effects model revealed that time spent in traffic and time outdoors contributed to benzene and 1,3- butadiene exposure. For benzene, refueling a car was an additional determinant influencing the exposure level. Smoking or environmental tobacco smoke were significant determinants of exposure to NO2, benzene, and 1,3-butadiene. Those with a gas stove had higher NO2 exposure. Living in a single-family house increased the exposure to formaldehyde significantly. In a variance component model, the between-subject variance dominated for 1,3-butadiene and formaldehyde, whereas the between-city variance dominated for NO2. For benzene, the between-subject and between-cities variances were similar.

Addressing extrema and censoring in pollutant and exposure data using mixture of normal distributions

BACKGROUND

Volatile organic compounds (VOC), which include many hazardous chemicals, have been used extensively in personal, commercial and industrial products. Due to the variation in source emissions, differences in the settings and environmental conditions where exposures occur, and measurement issues, distributions of VOC concentrations can have multiple modes, heavy tails, and significant portions of data below the method detection limit (MDL). These issues challenge standard parametric distribution models needed to estimate the exposures, even after log-transformation of the data.

METHODS

This paper considers mixture of distributions that can be directly applied to concentration and exposure data. Two types of mixture distributions are considered: the traditional finite mixture of normal distributions, and a semi-parametric Dirichlet process mixture (DPM) of normal distributions. Both methods are implemented for a sample data set obtained from the Relationship between Indoor, Outdoor and Personal Air (RIOPA) study. Performance is assessed based on goodness-of-fit criteria that compare the closeness of the density estimates with the empirical density based on data. The goodness-of-fit for the proposed density estimation methods are evaluated by a comprehensive simulation study.

RESULTS

The finite mixture of normals and DPM of normals have superior performance when compared to the single normal distribution fitted to log-transformed exposure data. The advantages of using these mixture distributions are more pronounced when exposure data have heavy tails or a large fraction of data below the MDL. Distributions from the DPM provided slightly better fits than the finite mixture of normals. Additionally, the DPM method avoids certain convergence issues associated with the finite mixture of normals, and adaptively selects the number of components.

CONCLUSIONS

Compared to the finite mixture of normals, DPM of normals has advantages by characterizing uncertainty around the number of components, and by providing a formal assessment of uncertainty for all model parameters through the posterior distribution. The method adapts to a spectrum of departures from standard model assumptions and provides robust estimates of the exposure density even under censoring due to MDL.

Health and household air pollution from solid fuel use: the need for improved exposure assessment

BACKGROUND

Nearly 3 billion people worldwide rely on solid fuel combustion to meet basic household energy needs. The resulting exposure to air pollution causes an estimated 4.5% of the global burden of disease. Large variability and a lack of resources for research and development have resulted in highly uncertain exposure estimates.

OBJECTIVE

We sought to identify research priorities for exposure assessment that will more accurately and precisely define exposure-response relationships of household air pollution necessary to inform future cleaner-burning cookstove dissemination programs.

DATA SOURCES

As part of an international workshop in May 2011, an expert group characterized the state of the science and developed recommendations for exposure assessment of household air pollution.

SYNTHESIS

The following priority research areas were identified to explain variability and reduce uncertainty of household air pollution exposure measurements: improved characterization of spatial and temporal variability for studies examining both short- and long-term health effects; development and validation of measurement technology and approaches to conduct complex exposure assessments in resource-limited settings with a large range of pollutant concentrations; and development and validation of biomarkers for estimating dose. Addressing these priority research areas, which will inherently require an increased allocation of resources for cookstove research, will lead to better characterization of exposure-response relationships.

CONCLUSIONS

Although the type and extent of exposure assessment will necessarily depend on the goal and design of the cookstove study, without improved understanding of exposure-response relationships, the level of air pollution reduction necessary to meet the health targets of cookstove interventions will remain uncertain.

Indoor tetrachloroethylene levels and determinants in Paris dwellings

There is growing public health concern about indoor air quality. Tetrachloroethylene (PERC), a chlorinated volatile organic compound widely used as a solvent in dry cleaning facilities, can be a residential indoor air pollutant. As part of an environmental investigation included in the PARIS (Pollution and asthma Risk: an Infant Study) birth cohort, this study firstly aimed to document domestic PERC levels, and then to identify the factors influencing these levels using standardized questionnaires about housing characteristics and living conditions. Air samples were collected in the child's bedroom over one week using passive devices when infants were 1, 6, 9, and 12 months. PERC was identified and quantified by gas chromatography/mass spectrometry. PERC annual domestic level was calculated by averaging seasonal levels. PERC was omnipresent indoors, annual levels ranged from 0.6 to 124.2 μg/m3. Multivariate linear and logistic regression models showed that proximity to dry cleaning facilities, do-it-yourself activities (e.g.: photographic development, silverware), presence of air vents, and building construction date (<1945) were responsible for higher domestic levels of PERC. This study, conducted in an urban context, provides helpful information on PERC contamination in dwellings, and identifies parameters influencing this contamination.

Extreme value analyses of VOC exposures and risks: A comparison of RIOPA and NHANES datasets

Extreme value theory, which characterizes the behavior of tails of distributions, is potentially well-suited to model exposures and risks of pollutants. In this application, it emphasizes the highest exposures, particularly those that may be high enough to present acute or chronic health risks. The present study examines extreme value distributions of exposures and risks to volatile organic compounds (VOCs). Exposures of 15 different VOCs were measured in the Relationship between Indoor, Outdoor and Personal Air (RIOPA) study, and ten of the same VOCs were measured in the nationally representative National Health and Nutrition Examination Survey (NHANES). Both studies used similar sampling methods and study periods. Using the highest 5 and 10% of measurements, generalized extreme value (GEV), Gumbel and lognormal distributions were fit to each VOC in these two large studies. Health risks were estimated for individual VOCs and three VOC mixtures. Simulated data that matched the three types of distributions were generated and compared to observations to evaluate goodness-of-fit. The tail behavior of exposures, which clearly neither fit normal nor lognormal distributions for most VOCs in RIOPA, was usually best fit by the 3-parameter GEV distribution, and often by the 2-parameter Gumbel distribution. In contrast, lognormal distributions significantly underestimated both the level and likelihood of extrema. Among the RIOPA VOCs, 1,4-dichlorobenzene (1,4-DCB) caused the greatest risks, e.g., for the top 10% extrema, all individuals had risk levels above 10-4, and 13% of them exceeded 10-2. NHANES had considerably higher concentrations of all VOCs with two exceptions, methyl tertiary-butyl ether and 1,4-DCB. Differences between these studies can be explained by sampling design, staging, sample demographics, smoking and occupation. This analysis shows that extreme value distributions can represent peak exposures of VOCs, which clearly are neither normally nor lognormally distributed. These exposures have the greatest health significance, and require accurate modeling.

Variability of indoor and outdoor VOC measurements: an analysis using variance components

This study examines concentrations of volatile organic compounds (VOCs) measured inside and outside of 162 residences in southeast Michigan, U.S.A. Nested analyses apportioned four sources of variation: city, residence, season, and measurement uncertainty. Indoor measurements were dominated by seasonal and residence effects, accounting for 50 and 31%, respectively, of the total variance. Contributions from measurement uncertainty (<20%) and city effects (<10%) were small. For outdoor measurements, season, city and measurement variation accounted for 43, 29 and 27% of variance, respectively, while residence location had negligible impact (<2%). These results show that, to obtain representative estimates of indoor concentrations, measurements in multiple seasons are required. In contrast, outdoor VOC concentrations can use multi-seasonal measurements at centralized locations. Error models showed that uncertainties at low concentrations might obscure effects of other factors. Variance component analyses can be used to interpret existing measurements, design effective exposure studies, and determine whether the instrumentation and protocols are satisfactory.

New approach for particulate exposure monitoring: determination of inhaled particulate mass by 24 h real-time personal exposure monitoring

The objectives of this study were to measure particulate pollution (PM(10), PM(2.5), and PM(1.0)) continuously (24 h/day for 7 day) using real-time exposure monitoring and to estimate total inhalation mass using breathing rate and time-activity. Breathing rates were calculated from measured heart rates. Participants were asked to record a time-activity diary every 15 min. Five microenvironments were defined based on the time-activity diary: home, workplace/school, other indoor, outdoor, and transportation. The average masses of inhaled PM(10) were 530, 316, and 280 μg/day for two office workers, a housewife, and three students, respectively; those of PM(2.5) were 316, 279, and 210 μg/day; and those of PM(1.0) were 251, 264, and 187 μg/day, respectively. We found that home and office/school microenvironments were the main contributors of PM(10), PM(2.5), and PM(1.0) inhaled mass during weekdays and weekends because dwelling time was a determinant factor for inhaled mass. Considering microenvironmental concentration, breathing rate, and dwelling time in each microenvironment, indoor home microenvironments were the largest source of particulate inhalation, followed in order by workplace, transportation, other indoor, and outdoor microenvironments. 34.6% and 69.6% of PM(10) inhalation mass were accumulated in home microenvironments during weekdays and weekends, respectively. The inhaled mass of particulate <1.0 μm (PM(1.0)) in size occupied largest, followed in order by particulate 10-2.5 μm (coarse particle) and 2.5-1.0 μm in size for all occupations.

Trends of VOC exposures among a nationally representative sample: Analysis of the NHANES 1988 through 2004 data sets

Exposures to volatile organic compounds (VOCs) are ubiquitous due to emissions from personal, commercial and industrial products, but quantitative and representative information regarding long term exposure trends is lacking. This study characterizes trends from1988 to 2004 for the 15 VOCs measured in blood in five cohorts of the National Health and Nutrition Examination Survey (NHANES), a large and representative sample of U.S. adults. Trends were evaluated at various percentiles using linear quantile regression (QR) models, which were adjusted for solvent-related occupations and cotinine levels. Most VOCs showed decreasing trends at all quantiles, e.g., median exposures declined by 2.5 (m, p-xylene) to 6.4 (tetrachloroethene) percent per year over the 15 year period. Trends varied by VOC and quantile, and were grouped into three patterns: similar decreases at all quantiles (including benzene, toluene); most rapid decreases at upper quantiles (ethylbenzene, m, p-xylene, o-xylene, styrene, chloroform, tetrachloroethene); and fastest declines at central quantiles (1,4-dichlorobenzene). These patterns reflect changes in exposure sources, e.g., upper-percentile exposures may result mostly from occupational exposure, while lower percentile exposures arise from general environmental sources. Both VOC emissions aggregated at the national level and VOC concentrations measured in ambient air also have declined substantially over the study period and are supportive of the exposure trends, although the NHANES data suggest the importance of indoor sources and personal activities on VOC exposures. While piecewise QR models suggest that exposures of several VOCs decreased little or any during the 1990's, followed by more rapid decreases from 1999 to 2004, questions are raised concerning the reliability of VOC data in several of the NHANES cohorts and its applicability as an exposure indicator, as demonstrated by the modest correlation between VOC levels in blood and personal air collected in the 1999/2000 cohort. Despite some limitations, the NHANES data provides a unique, long term and direct measurement of VOC exposures and trends.

Variability of environmental exposure to fine particles, black smoke, and trace elements among a Swedish population

Mixed-effects models were used to estimate within-person and between-person variance components, and some determinants of environmental exposure to particulate matter (PM(2.5)), black smoke (BS) and trace elements (Cl, K, Ca, Ti, Fe, Ni, Cu, Zn, and Pb) for personal measurements from 30 adult subjects in Gothenburg, Sweden. The within-person variance component dominated the total variability for all investigated compounds except for PM(2.5) and Zn (in which the variance components were about equal). Expressed as fold ranges containing 95% of the underlying distributions, the within-person variance component ranged between 5-fold and 39-fold (median: sixfold), whereas the between-person variance component was always <sixfold (median: threefold). The relatively large within-person variance components can lead to attenuation bias in exposure-response relationships and point to the importance of obtaining repeated samples of PM exposure from study subjects in epidemiological investigations of urban air pollution. On the basis of the variance components estimated for the various particulate species, between 3 and 39 repeated measurements per subject would be required to limit attenuation bias to 20%. Significant determinants for personal exposure levels were urban background air concentrations (PM(2.5), BS, Cl, Zn, and Pb), cigarette smoking (PM(2.5), BS, K, and Ti), season (PM(2.5), Fe, and Pb), and the time spent outdoors or in traffic (Fe).

Socioeconomic and personal behavioral factors affecting children's exposure to VOCs in urban areas in Korea

Volatile organic compounds (VOCs) are known to cause adverse health effects. We investigated the relationships between children's VOC exposure and socioeconomic and human activity factors with passive personal samplers, questionnaires, and time-activity diaries (TAD). Statistical analyses were conducted using SAS 9.1, and the results were organized using SigmaPlot 8.0 software. Chemicals such as benzene, toluene, 2-butanone, ethylbenzene, xylene, chloroform, n-hexane, heptane, and some kinds of decanes, which are known to adversely affect public health, were identified in measured samples. These were mainly emitted from outdoor sources (e.g., vehicular traffic) or indoor sources (e.g., household activities such as cooking and cleaning) or both. We concluded that region was the most important socioeconomic factor affecting children's VOC exposure, and the significant compounds were n-hexane (p = 0.006), 1,1,1-trichloroethane (p = 0.001), benzene (p = 0.003), toluene (p = 0.002), ethylbenzene (p = 0.020), m-, p-xylene (p = 0.014), dodecane (p = 0.003), and hexadecane (p = 0.001). Parental education, year of home construction and type of housing were also slightly correlated with personal VOC exposure. Only the concentration of o-xylene (p = 0.027) was significantly affected by the parental education, and the concentrations of benzene (p = 0.030) and 2-butanone (p = 0.049) by the type of housing. Also, tridecane (p = 0.049) and n-hexane (p = 0.033) were significantly associated with the year of home construction. When household activities such as cooking were performed indoors, children's VOC concentrations tended to be higher, especially for n-hexane, chloroform, heptane, toluene (p < 0.05), 1,1,1-trichloroethane, benzene, dodecane, and hexadecane (p < 0.01). However, smoking had a significant effect for only dodecane, and cleaning had no impact on any VOC concentrations. Considering both socioeconomic and personal behavioral factors simultaneously, socioeconomic factors such as region had a greater effect on children's VOC exposures than indoor activities. From this study, we can suggest that socioeconomic factors as well as environmental factors should be considered when formulating environmental policy to protect children's health.

Role of exhaled breath biomarkers in environmental health science

As a discipline of public health, environmental health science is the study of the linkage from environmental pollution sources to eventual adverse health outcome. This progression may be divided into two components, (1) "exposure assessment," which deals with the source terms, environmental transport, human exposure routes, and internal dose, and (2) "health effects," which deals with metabolism, cell damage, DNA changes, pathology, and onset of disease. The primary goal of understanding the linkage from source to health outcome is to provide the most effective and efficient environmental intervention methods to reduce health risk to the population. Biomarker measurements address an individual response to a common external environmental stressor. Biomarkers are substances within an individual and are subdivided into chemical markers, exogenous metabolites, endogenous response chemicals, and complex adducts (e.g., proteins, DNA). Standard biomarker measurements are performed in blood, urine, or other biological media such as adipose tissue and lavage fluid. In general, sample collection is invasive, requires medical personnel and a controlled environment, and generates infectious waste. Exploiting exhaled breath as an alternative or supplement to established biomarker measurements is attractive primarily because it allows a simpler collection procedure in the field for numerous individuals. Furthermore, because breath is a gas-phase matrix, volatile biomarkers become more readily accessible to analysis. This article describes successful environmental health applications of exhaled breath and proposes future research directions from the perspective of U.S. Environmental Protection Agency (EPA) human exposure research.

Relative performance of different exposure modeling approaches for sulfur dioxide concentrations in the air in rural western Canada

Background

The main objective of this paper is to compare different methods for predicting the levels of SO₂ air pollution in oil and gas producing area of rural western Canada. Month-long average air quality measurements were collected over a two-year period (2001–2002) at multiple locations, with some side-by-side measurements, and repeated time-series at selected locations.

Methods

We explored how accurately location-specific mean concentrations of SO₂ can be predicted for 2002 at 666 locations with multiple measurements. Means of repeated measurements on the 666 locations in 2002 were used as the alloyed gold standard (AGS). First, we considered two approaches: one that uses one measurement from each location of interest; and the other that uses context data on proximity of monitoring sites to putative sources of emission in 2002. Second, we imagined that all of the previous year's (2001's) data were also available to exposure assessors: 9,464 measurements and their context (month, proximity to sources). Exposure prediction approaches we explored with the 2001 data included regression modeling using either mixed or fixed effects models. Third, we used Bayesian methods to combine single measurements from locations in 2002 (not used to calculate AGS) with different priors.

Results

The regression method that included both fixed and random effects for prediction (Best Linear Unbiased Predictor) had the best agreement with the AGS (Pearson correlation 0.77) and the smallest mean squared error (MSE: 0.03). The second best method in terms of correlation with AGS (0.74) and MSE (0.09) was the Bayesian method that uses normal mixture prior derived from predictions of the 2001 mixed effects applied in the 2002 context.

Conclusion

It is likely that either collecting some measurements from the desired locations and time periods or predictions of a reasonable empirical mixed effects model perhaps is sufficient in most epidemiological applications. The method to be used in any specific investigation will depend on how much uncertainty can be tolerated in exposure assessment and how closely available data matches circumstances for which estimates/predictions are required.

Relationships between levels of volatile organic compounds in air and blood from the general population

The relationships between levels of volatile organic compounds (VOCs) in blood and air have not been well characterized in the general population where exposure concentrations are generally at parts per billion levels. This study investigates relationships between the levels of nine VOCs, namely, benzene, chloroform, 1,4-dichlorobenzene, ethylbenzene, methyl tert-butyl ether (MTBE), tetrachloroethene, toluene, and m-/p- and o-xylene, in blood and air from a stratified random sample of the general US population. We used data collected from 354 participants, including 89 smokers and 265 nonsmokers, aged 20-59 years, who provided samples of blood and air in the National Health and Nutrition Examination Survey (NHANES) 1999-2000. Demographic and physiological characteristics were obtained from self-reported information; smoking status was determined from levels of serum cotinine. Multiple linear regression models were used to investigate the relationships between VOC levels in air and blood, while adjusting for effects of smoking and demographic factors. Although levels of VOCs in blood were positively correlated with the corresponding air levels, the strength of association (R(2)) varied from 0.02 (ethylbenzene) to 0.68 (1,4-DCB). Also the blood-air relationships of benzene, toluene, ethylbenzene, and the xylenes (BTEX) were influenced by smoking, exposure-smoking interactions, and by gender, age, and BMI, whereas those of the other VOCs were not. Interestingly, the particular exposure-smoking interaction for benzene was different from those for toluene, ethylbenzene, and the xylenes. Whereas smokers retained more benzene in their blood at increasing exposure levels, they retained less toluene, ethylbenzene, and xylenes at increasing exposure levels. Investigators should consider interaction effects of exposure levels and smoking when exploring the blood-air relationships of the BTEX compounds in the general population.

ATSDR evaluation of potential for human exposure to benzene

As part of its mandate, the Agency for Toxic Substances and Disease Registry (ATSDR) prepares toxicological profiles on hazardous chemicals found at Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) National Priorities List (NPL) sites that have the greatest public health impact. These profiles comprehensively summarize toxicological and environmental information. This article constitutes the release of portions of the toxicological profile for benzene. The primary purpose of this article is to provide interested individuals with environmental information on benzene that includes production data, environmental fate, potential for human exposure, analytical methods, and a listing of regulations and advisories.

Organic air pollutants inside and outside residences in Shimizu, Japan: levels, sources and risks

Concentrations of 38 organic air pollutants including aromatic hydrocarbons (AHCs), carbonyl compounds (CCs), volatile organic halogenated compounds (VOHCs), and organophosphorus compounds (OPCs) were measured in indoor and outdoor air in an industrial city, Shimizu, Shizuoka Prefecture, Japan. Levels of pollutants tended to be higher indoors than outdoors in both summer and winter except for benzene, carbon tetrachloride, trichloroethylene, tetrachloroethylene, and dichlorvos (DDVP). This trend was especially pronounced for CCs such as formaldehyde and acetaldehyde. For the organic air pollutants, the concentrations of AHCs and VOHCs substantially increased in winter, but not those of CCs and OPCs; the trends were similar for both indoors and outdoors. We investigated possible indoor sources of pollutants statistically. Multiple regression analysis of corresponding indoor and outdoor concentrations and the responses to our questionnaire showed that indoor concentrations of certain AHCs were significantly affected by their outdoor concentrations and cigarette smoking. For formaldehyde, indoor concentrations were significantly affected by house age and the presence of carpet or pets. For p-dichlorobenzene (pDCB), the concentrations in bedroom trended to be higher than those in other indoors and outdoors, suggested that mothballs for clothes present in bedrooms are the principal indoor source of pDCB. We compared indoor and outdoor pollutant concentrations to acceptable risk limits for 11 organic air pollutants. In indoors without smoking samples, the geometric mean concentrations of benzene, formaldehyde, acetaldehyde, carbon tetrachloride, pDCB, and DDVP exceeded the equivalent concentration representing the upper bound of one-in-one-hundred-thousand (1x10(-5)) excess risk over a lifetime of exposure.

Using urinary biomarkers to elucidate dose-related patterns of human benzene metabolism

Although the toxicity of benzene has been linked to its metabolism, the dose-related production of metabolites is not well understood in humans, particularly at low levels of exposure. We investigated unmetabolized benzene in urine (UBz) and all major urinary metabolites [phenol (PH), E,E-muconic acid (MA), hydroquinone (HQ) and catechol (CA)] as well as the minor metabolite, S-phenylmercapturic acid (SPMA), in 250 benzene-exposed workers and 139 control workers in Tianjin, China. Median levels of benzene exposure were approximately 1.2 p.p.m. for exposed workers (interquartile range: 0.53-3.34 p.p.m.) and 0.004 p.p.m. for control workers (interquartile range: 0.002-0.007 p.p.m.). (Exposures of control workers to benzene were predicted from levels of benzene in their urine.) Metabolite production was investigated among groups of 30 workers aggregated by their benzene exposures. We found that the urine concentration of each metabolite was consistently elevated when the group's median benzene exposure was at or above the following air concentrations: 0.2 p.p.m. for MA and SPMA, 0.5 p.p.m. for PH and HQ, and 2 p.p.m. for CA. Dose-related production of the four major metabolites and total metabolites (micromol/l/p.p.m. benzene) declined between 2.5 and 26-fold as group median benzene exposures increased between 0.027 and 15.4 p.p.m. Reductions in metabolite production were most pronounced for CA and PH<1 p.p.m., indicating that metabolism favored production of the toxic metabolites, HQ and MA, at low exposures.

Air samples versus biomarkers for epidemiology

BACKGROUND

It has been speculated on theoretical grounds that biomarkers are superior surrogates for chemical exposures to air samples in epidemiology studies.

METHODS AND RESULTS

Biomarkers were classified according to their position in the exposure-disease continuum-that is, parent compound, reactive intermediate, stable metabolite, macromolecular adduct, or measure of cellular damage. Because airborne exposures and these different biomarkers are time series that vary within and between persons in a population, they are all prone to measurement error effects when used as surrogates for true chemical exposures. It was shown that the attenuation bias in the estimated slope characterising a log exposure-log disease relation should decrease as the within- to between-person variance ratio of a given set of air or biomarker measurements decreases. To gauge the magnitudes of these variance ratios, a database of 12,077 repeated observations was constructed from 127 datasets, including air and biological measurements from either occupational or environmental settings. The within- and between-person variance components (in log scale, after controlling for fixed effects of time) and the corresponding variance ratios for each set of air and biomarker measurements were estimated. It was shown that estimated variance ratios of biomarkers decreased in the order short term (residence time < or =2 days) > intermediate term (2 days < residence time < or =2 months) > long term biomarkers (residence time >2 months). Overall, biomarkers had smaller variance ratios than air measurements, particularly in environmental settings. This suggests that a typical biomarker would provide a less biasing surrogate for exposure than would a typical air measurement.

CONCLUSION

Epidemiologists are encouraged to consider the magnitudes of variance ratios, along with other factors related to practicality and cost, in choosing among candidate surrogate measures of exposure.

Cost/variance optimization for human exposure assessment studies

The National Human Exposure Assessment Survey (NHEXAS) field study in EPA Region V (one of three NHEXAS field studies) provides extensive exposure data on a representative sample of 249 residents of the Great Lakes states. Concentration data were obtained for both metals and volatile organic compounds (VOCs) from multiple environmental media and from human biomarkers. A variance model for the logarithms of concentration measurements is used to define intraclass correlations between observations within primary sampling units (PSUs) (nominally counties) and within secondary sampling units (SSUs) (nominally Census blocks). A model for the total cost of the study is developed in terms of fixed costs and variable costs per PSU, SSU, and participant. Intraclass correlations are estimated for media and analytes with sufficient sample sizes. We demonstrate how the intraclass correlations and variable cost components can be used to determine the sample allocation that minimizes cost while achieving pre-specified precision constraints for future studies that monitor environmental concentrations and human exposures for metals and VOCs.

Protein adducts as biomarkers of human benzene metabolism

We used cysteinyl adducts of serum albumin (Alb) to investigate the production of two reactive benzene metabolites, namely, benzene oxide (BO) and 1,4-benzoquinone (1,4-BQ) in workers exposed to benzene. Adducts were measured in 160 benzene-exposed workers who did not use respiratory protection (based upon individual geometric mean benzene exposure levels: median=5.27 ppm, interquartile range=2.14-13.4 ppm, range=0.074-328 ppm) and 101 local controls, from populations in Shanghai and Tianjin, China. After isolation of Alb, these adducts (designated as BO-Alb and 1,4-BQ-Alb) were cleaved from the protein with methanesulfonic acid and trifluoroacetic anhydride and measured by gas chromatography-mass spectrometry. Although BO-Alb and 1,4-BQ-Alb were measured in all subjects, levels of both adducts were 2.4-fold greater (median value) in exposed subjects than in controls (interquartile-fold range=1.63-4.05 for BO-Alb and 1.64-3.69 for 1,4-BQ-Alb). Log-log plots of the individual adduct levels versus exposure were quasi-linear with straight-line slopes of about 0.3 for both BO-Alb and 1,4-BQ-Alb. Since these log-space slopes were significantly less than one, we infer that adduct production was nonlinear, i.e., less-than proportional to benzene exposure, over the indicated range. This behavior points to saturation of CYP2E1 as a critical metabolic consequence of high exposure to benzene in humans. Thus, the biologically effective dose of BO and 1,4-BQ should be proportionally greater in persons exposed to low rather than high levels of benzene.