Ambient site, home outdoor and home indoor particulate concentrations as proxies of personal exposures

Despite strong longitudinal associations between particle personal exposures and ambient concentrations, previous studies have found considerable inter-personal variability in these associations. Factors contributing to this inter-personal variability are important to identify in order to improve our ability to assess particulate exposures for individuals. This paper examines whether ambient, home outdoor and home indoor particle concentrations can be used as proxies of corresponding personal exposures. We explore the strength of the associations between personal, home indoor, home outdoor and central outdoor monitoring site ("ambient site") concentrations of sulfate, fine particle mass (PM(2.5)) and elemental carbon (EC) by season and subject for 25 individuals living in the Boston, MA, USA area. Ambient sulfate concentrations accounted for approximately 70 to 80% of the variability in personal and indoor sulfate levels. Correlations between ambient and personal sulfate, however, varied by subject (0.1-1.0), with associations between personal and outdoor sulfate concentrations generally mirroring personal-ambient associations (median subject-specific correlations of 0.8 to 0.9). Ambient sulfate concentrations are good indicators of personal exposures for individuals living in the Boston area, even though their levels may differ from actual personal exposures. The strong associations for sulfate indicate that ambient concentrations and housing characteristics are the driving factors determining personal sulfate exposures. Ambient PM(2.5) and EC concentrations were more weakly associated with corresponding personal and indoor levels, as compared to sulfate. For EC and PM(2.5), local traffic, indoor sources and/or personal activities can significantly weaken associations with ambient concentrations. Infiltration was shown to impact the ability of ambient concentrations to reflect exposures with higher exposures to particles from ambient sources during summer. In contrast in the winter, lower infiltration can result in a greater contribution of indoor sources to PM(2.5) and EC exposures. Placing EC monitors closer to participants' homes may reduce exposure error in epidemiological studies of traffic-related particles, but this reduction in exposure error may be greater in winter than summer. It should be noted that approximately 20% of the EC data were below the field limit of detection, making it difficult to determine if the weaker associations with the central site for EC were merely a result of methodological limitations.     

Characterisation of Particulate Matter Sampled during a Study of Children's Personal Exposure to Airborne Particulate Matter in a UK Urban Environment

The personal exposure of children aged 9 – 11 years to particulate matter (PM₁₀ and PM_2.5) was carried out between January and September 1997 in the London Borough of Barnet. Personal sampling along with home, garden and classroom microenvironmental monitoring was completed for all ten children. Each child was monitored for five days during winter, spring and summer. All children completed daily time activity diaries to provide information on any potential activities that could influence their exposure to particulate matter. Each evening a household activity questionnaire was also completed by the parents. Personal Environmental Monitors were used to sample personal exposure to PM₁₀ and PM_2.5. Harvard Impactors were used for the microenvironmental sampling of both size fractions. The children's mean personal exposure concentrations for PM₁₀ during winter, spring and summer were 72, 54 and 35 µg/m³ respectively and for PM_2.5 22, 17 and 18 µg/m³ respectively. In order to determine the potential sources of particulate matter, analysis of the Teflon filters has been undertaken. The physical characteristics of the particles have been identified using Scanning Electron Microscopy. The relationships between personal exposure concentrations and the different microenvironments will be discussed.     

Personal exposures and microenvironmental concentrations of particles and bioaerosols

The aim of this study was to compare the personal exposure to particles and bioaerosols with that measured by stationary samplers in the main microenvironments, i.e., the home and the workplace. A random sample of 81 elementary school teachers was selected from the 823 teachers working for two councils in eastern Finland for the winter time measurement period. Bioaerosol and other particles were collected on filters by button samplers using personal sampling and microenvironmental measurements in homes and workplaces. The 24-hour sampling period was repeated twice for each teacher. Particle mass, absorption coefficient of the filter and the concentration of viable and total microorganisms were analyzed from each filter. In this paper, the study design, quality assurance principles and results of particle and bioaerosol exposure are described. The results show that particle mass concentrations, absorption coefficient and fungi were higher in personal exposure samples than in home and workplace samples. Furthermore, these concentrations were usually lower in the home than in the workplace. Bacterial concentrations were highest in heavily populated workplaces, while the viable fungi concentrations were lowest in workplaces. The fungi and bacteria results showed high variation, which emphasises the importance of quality assurance (duplicates and field blanks) in the microbial field measurements. Our results indicate that personal exposure measurements of bioaerosols in indoor environments are feasible and supplement the information obtained by stationary samplers.     

Air pollution exposure monitoring and estimating. Part I. Integrated air quality monitoring system

This paper presents an integrated exposure monitoring system, based on an expansion of existing air quality monitoring systems using dispersion modelling. The system allows: (1) identifying geographical areas whose inhabitants are most exposed to ambient pollution; (2) identifying how many people in an area are exposed to concentrations of pollution exceeding air quality guidelines; (3) describing the exposure of population subgroups (e.g. children); (4) planning pollution abatement measures and quantifying their effects; (5) establishing risk assessment and management programs, and (6) investigating the short- and long-term effects of both pollutants and pollution sources on public health. The effect of pollution is rarely very large and in order to discover it, exposure estimation must provide data that reflects both spatial and temporal variations. Estimates of pollution exposure are obtained using an integrated approach that combines results of measurements from monitoring programs with dispersion calculations. These values can serve as estimates for individual short-term or long-term exposure. The grouped data allows the expression of ambient pollution concentrations as the spatial distribution of estimates such as the mean or 98th percentile of such compounds as SO2, O3, NO2, PM10 and PM2.5. This integrated approach has been combined into a single software package, AirQUIS.     

Air pollution exposure monitoring and estimation. Part V. Traffic exposure in adults

In Oslo, traffic has been one of the dominating sources of air pollution in the last decade. In one part of the city where most traffic collects, two tunnels were built. A series of before and after studies was carried out in connection with the tunnels in use. Dispersion models were used as a basis for estimating exposure to nitrogen dioxide and particulate matter in two fractions. Exposure estimates were based on the results of the dispersion model providing estimates of outdoor pollutant concentrations on an hourly basis. The estimates represent concentrations in receptor points and in a square kilometre grid. The estimates were used to assess development of air pollution load in the area, compliance with air quality guidelines, and to provide a basis for quantifying exposure-effect relationships in epidemiological studies. After both tunnels were taken in use, the pollution levels in the study area were lower than when the traffic was on the surface (a drop from 50 to 40 micrograms m-3). Compliance with air quality guidelines and other prescribed values has improved, even if high exposures still exist. The most important residential areas are now much less exposed, while areas around tunnel openings can be in periods exposed to high pollutant concentrations. The daily pattern of exposure shows smaller differences between peak and minimum concentrations than prior to the traffic changes. Exposures at home (in the investigation area) were reduced most, while exposures in other locations than at home showed only a small decrease. Highest hourly exposures are encountered in traffic.     

Air pollution exposure monitoring and estimation. Part VI. Ambient exposure of adults in an industrialised region

This paper presents methodology and results of a dynamic individual air pollution exposure model (DINEX) that calculates the hourly exposure for each adult in a panel study. Each of over 260 participants, through the use of a diary, provided information used in the model to calculate his/her personal, individualised exposure. The participants filled out the diary daily, hour by hour, over two, two month periods. The exposure assessment model coupled the diary information and results of an indoor/outdoor measurement program, with the results of dispersion modelling on an hourly basis for an industrial area in Norway. The estimated air pollution concentrations from the dispersion model, based on continuous meteorological measurements, were calibrated with air pollutant concentrations measured continuously.     

A combined analysis to identify airborne PM10 sources

A two step procedure that combines an air dispersion model with a receptor model was used to identify the key sources that contribute to air levels of suspended particulate matter. The contribution to PM(10) concentrations measured at four monitoring sites in San Nicolas, Argentina, of the following sources, a thermal power plant, an integrated steel mill, motor vehicle exhaust fumes, and finally dust from paved and unpaved roads, have been analysed. Moreover, an air dispersion model was used to estimate the contribution of the thermal power plant, emissions of which have been described in depth by means of hourly fuel consumption and specific emission factors. The ratio "apportionment coefficient" was introduced to relate the contribution of this source to the measured 24 h PM(10) concentrations by analysing the frequency of occurrence of connecting winds between the power plant and each monitoring site. In San Nicolas 70% of the PM(10) sampled at three of the four monitoring sites could be attributed to the power plant in those scenarios where winds connected the facility's tall point sources with the sampling locations. The contribution to the measured PM(10) levels of the rest of the sources that are present in the analysed area was confirmed by way of receptor models. For this purpose, the multielemental composition of 41 samples was determined by Wavelength Dispersive X-ray Fluorescence analysis. In order to ascertain the underlying correlations between PM(10) samples and potential sources, Principal Component Analysis was performed on the standard matrix of composition profiles, which comprises the measured PM(10) samples being enlarged with the composition profiles of the potential contributing sources. The diagonalization of the covariance matrix was used as a screening procedure to differentiate the most likely contributing sources from those that were not significant.     

Spatial variability of air pollutants in the city of Taranto, Italy and its potential impact on exposure assessment

Epidemiological studies typically use monitored air pollution data from a single station or as averaged data from several stations to estimate population exposure. In industrialized urban areas, this approach may present critical issues due to the spatial complexities of air pollutants which are emitted by different sources. This study focused on the city of Taranto, which is one of the most highly industrialized cities in southern Italy. Epidemiological studies have revealed several critical situations in this area, in terms of mortality excess and short-term health effects of air pollution. The aims of this paper are to study the variability of air pollutants in the city of Taranto and to interpret the results in relation to the applicability of the data in assessing population exposure. Meteorological and pollution data (SO2, NO2, PM10), measured simultaneously and continuously during the period 2006–2010 in five air quality stations, were analyzed. Relative and absolute spatial concentration variations were investigated by means of statistical indexes. Results show significant differences among stations. The highest correlation between stations was observed for PM10 concentrations, while critical values were found for NO2. The worst values were observed for the SO2 series. The high values of 90th percentile of differences between pairs of monitoring sites for the three pollutants index suggest that mean concentrations differ by large amounts from site to site. The overall analysis supports the hypothesis that various parts of the city are differently affected by the different emission sources, depending on meteorological conditions. In particular, analysis revealed that the influence of the industrial site may be primarily identified with the series of SO2 data which exhibit higher mean concentration values and positive correlations with wind intensity when the monitoring station is downwind from the industrial site. Results suggest evaluating the population exposure to air pollutants in industrialized cities by taking into account the possible zones of influence of different emission sources. More research is needed to identify an indicator, which ought to be a synthesis of several pollutants, and take into account the meteorological variables.     

Source apportionment of personal exposure of fine particulates among school communities in India

Source contribution estimates (SCE) of school community personal Respirable Particulate Matter (RPM) have been investigated. Reported relationships of personal RPM with Ambient-outdoors and indoor RPM levels have given the concept of defining the sources of personal exposure. Ambient-outdoors, indoors, soils and local road- traffic dusts were identified as main routes and principal sources of fine particulates at personal exposure levels. Fifteen subjects (05 from each of three schools) were selected from previous conducted study of interrelationships among classified atmospheric receptors in theses schools located in Bhilai-Durg, District Durg, India. Samples of RPM collected from identified receptors and sources were analyzed for selected chemical constituents and the chemical data has been utilized in preparation of source-receptor profiles. Chemical mass balance (CMB8) model has been used for source apportionment study. Major dominating source is ambient-outdoors in case of school located near to steel plant downwind. Indoors and road-traffic dusts have also played dominating role in case of school located near to National Highways. Indoor ventilation properties have played an important role in source contribution estimates.     

Indoor air pollution levels in public buildings in Thailand and exposure assessment

Levels of pollutants including PM2.5 and PM2.5 composition (black carbon and water soluble ions), SO(2), NO(2), CO, CO(2), and BTEX (benzene, toluene, ethylbenzene, xylene) were monitored for indoor and outdoor air at a university campus and a shopping center, both located in the Northern suburb of Bangkok. Sampling was done during December 2005-February 2006 on both weekdays and weekends. At the university, indoor monitoring was done in two different air conditioned classrooms which shows the I/O ratios for all pollutants to be below 0.5-0.8 during the weekends. However, on weekdays the ratios for CO(2) and most detected BTEX were above 1.0. The concept of classroom occupancy was defined using a function of the student number in a lecture hour and the number of lecture hours per day. Classroom 2, which had a higher occupancy than classroom 1, was characterized by higher concentrations of most pollutants. PM2.5 was an exception and was higher in classroom 1 (37 microg/m(3), weekdays) as compared to classroom 2 (26 microg/m(3), weekdays) which was likely linked to the dust resuspension from the carpeted floor in the former. Monitoring was also done in the shopping mall at three different sites. Indoor pollutants levels and the I/O ratios at the shopping mall were higher than at the university. Levels of all pollutants measured at the car park, except for toluene and CO(2), were the highest. I/O ratios of the pollutants at the mall were above 1.0, which indicates the relatively higher influence of the indoor sources. However, the black carbon content in PM2.5 outdoor is higher than indoor, which suggest the important contribution from outdoor combustion sources such as the traffic. Major sources of outdoor air pollution in the areas were briefly discussed. Exposure modeling was applied using the time activity and measured pollutant concentrations to assess the exposure of different groups of people in the study areas. High exposure to PM2.5, especially for the people working in the mall, should be of health effect concern.     

Indoor and outdoor concentrations of fine particles, particle-bound PAHs and volatile organic compounds in Kaunas, Lithuania

This complex study presents indoor and outdoor levels of air-borne fine particles, particle-bound PAHs and VOCs at two urban locations in the city of Kaunas, Lithuania, and considers possible sources of pollution. Two sampling campaigns were performed in January-February and March-April 2009. The mean outdoor PM(2.5) concentration at Location 1 in winter was 34.5 ± 15.2 μg m(-3) while in spring it was 24.7 ± 12.2 μg m(-3); at Location 2 the corresponding values were 36.7 ± 21.7 and 22.4 ± 19.4 μg m(-3), respectively. In general there was little difference between the PM concentrations at Locations 1 and 2. PM(2.5) concentrations were lower during the spring sampling campaign. These PM concentrations were similar to those in many other European cities; however, the levels of most PAHs analysed were notably higher. The mean sum PAH concentrations at Locations 1 and 2 in the winter campaign were 75.1 ± 32.7 and 32.7 ± 11.8 ng m(-3), respectively. These differences are greater than expected from the difference in traffic intensity at the two sites, suggesting that there is another significant source of PAH emissions at Location 1 in addition to the traffic. The low observed indoor/outdoor (I/O) ratios indicate that PAH emissions at the locations studied arise primarily from outdoor sources. The buildings at both locations have old windows with wooden frames that are fairly permissive in terms of air circulation. VOC concentrations were mostly low and comparable to those reported from Sweden. The mean outdoor concentrations of VOC's were: 0.7 ± 0.2, 3.0 ± 0.8, 0.5 ± 0.2, 3.5 ± 0.3, and 0.2 ± 0.1 μg m(-3), for benzene, toluene, ethylbenzene, sum of m-, p-, o-xylenes, and naphthalene, respectively. Higher concentrations of VOCs were observed during the winter campaign, possibly due to slower dispersion, slower chemical transformations and/or the lengthy "cold start" period required by vehicles in the wintertime. A trajectory analysis showed that air masses coming from Eastern Europe carried significantly higher levels of PM(2.5) compared to masses from other regions, but the PAHs within the PM(2.5) are of local origin. It has been suggested that street dust, widely used for winter sanding activities in Eastern and Central European countries, may act not only as a source of PM, but also as source of particle-bound PAHs. Other potential sources include vehicle exhaust, domestic heating and long-range transport.     

Spatial and temporal distribution of gaseous elemental mercury in Chongqing, China

In order to investigate the spatial and temporal variability of atmospheric mercury (Hg) in Chongqing, China, gaseous elemental mercury (GEM) was measured from August 2006 to September 2007, using Lumex multifunctional mercury analyzer RA-915(+) (Lumex Ltd., Russia). The mean GEM concentration was 6.74 +/- 0.37 ng m(-3) in Chongqing, much higher than the accepted global background values (1.5-2 ng m(-3)). The GEM concentrations were different in different function areas. GEM in transport, industrial and commercial areas were 7.07 +/- 1.04, 7.05 +/- 0.96 and 6.71 +/- 1.10 ng m(-3), respectively, while GEM was 6.14 +/- 1.30 and 4.32 +/- 1.04 in the educational/recreational and nature conservation areas, suggesting that Hg emissions from mobile vehicles and industrial sources (specially coal combustion) were the most important contributors to atmospheric Hg in Chongqing. Mean Hg concentrations also had monthly variations with highest in November (8.24 +/- 0.50 ng m(-3)) and lowest values in August (5.36 +/- 0.70 ng m(-3)). Additionally, the diurnal variation of GEM concentrations was dependent on the local/regional atmospheric conditions. At Jinyun Mountain site (natural conservation area), hourly GEM concentrations had much higher values in daytime than at night. At Power Plant site, however, the hourly GEM concentrations were lower in daytime than at night. GEM concentrations in the air were correlated significantly with meteorological parameters except for barometric pressure.     

Benzene Exposure Assessment at Indoor, Outdoor and Personal Levels. The French Contribution to the Life MACBETH Programme

Many VOC represent hazards to human health through chronic exposure. Recent European and world-wide legislation proposes limit values for ambient concentrations of these compounds. However, very little experimental data exists for true population exposure. In 1996, the European MACBETH initiative set out to measure population exposure to benzene in six European cities. This study details the French contribution to this program. Six campaigns were carried out, each comprising measurements at 100 outdoor sites and the participation of 50 non-smoking volunteers who wore personal samplers and had passive monitors installed in their homes. Iso-concentration maps were drawn for each campaign and the results showed that outdoor concentrations were significantly lower than indoors. Almost 75% of the volunteers were exposed to mean concentrations higher than the limit value of 5µgm³. It is demonstrated that personal exposure levels cannot be deduced simply by combining indoor and outdoor background concentrations. It is also shown that there is need for better knowledge of the contributions to overall exposure of outdoor microenvironments and the authors hope that future European directives will take this into account.     

Intercomparison of five PM10 monitoring devices and the implications for exposure measurement in epidemiological research

Five different instruments for the determination of the mass concentration of PM10 in air were compared side-by-side for up to 33 days in an undisturbed indoor environment: a tripod mounted BGI Inc. PQ100 gravimetric sampler with a US EPA certified Graseby Andersen PM10 inlet; an Airmetrics Minivol static gravimetric sampler; a Casella cyclone gravimetric personal sampler; an Institute of Occupational Medicine gravimetric PM10 personal sampler; and two TSI Inc. Dustrak real-time optical scattering personal samplers. For 24 h sampling of ambient PM10 concentrations around 10 microg m(-3), the estimated measurement uncertainty for the two gravimetric personal samplers was larger (approximately +/- 20%) compared with estimated measurement uncertainty for the PQ100/Graseby Andersen sampler (< +/- 5%). Measurement uncertainty for the Dustraks was lower (approximately +/- 15% on average) but calibration of the optical response against a reference PM10 method is essential since the Dustraks systematically over-read PM10 determined gravimetrically by a factor approximately 2.2. However, once calibrated, the Dustrak devices demonstrated excellent functionality in terms of ease of portability and real-time data acquisition. Estimated measurement uncertainty for PM10 concentrations determined with the Minivol were +/- 5%. The Minivol data correlated well with PQ100/Graseby Andersen data (r= 0.97, n = 18) but were, on average, 23% greater. The reason for the systematic discrepancy could not be traced. Intercomparison experiments such as these are essential for assessing measurement error and revealing systematic bias. Application of two Dustraks demonstrated the spatial and temporal variability of exposure to PM10 in different walking and transport microenvironments in the city of Edinburgh, UK. For example, very large exposures to PM10 were identified for the lower deck of a double-decker tour bus compared with the open upper deck of the same vehicle. The variability observed emphasises the need to determine truly personal exposure profiles of PM10 for quantifying exposure response relationships for epidemiological studies.     

Viable fungi and bacteria in personal exposure samples in relation to microenvironments

Personal exposures to viable fungi and bacteria were compared with the concentrations being assessed by stationary samplers in home and workplace microenvironments. A random sample of 81 elementary school teachers in eastern Finland performed two 24-hour measurement periods in wintertime. Concentrations and prevalences of viable fungi and bacteria on the collection filters were determined by cultivation method. The geometric mean concentration was 3-12 cfu m(-3) for total viable fungi, 0.6-3.7 cfu m(-3) for Penicillium and mainly under 1 cfu m(-3) for other fungi. The samples with higher fungal concentrations also had higher diversity of fungi than samples with lower concentrations. The total number of fungal genera recovered was 39 for personal, 34 for home and 23 for work samples. The variation in concentration of Penicillium explained even 25-95% of the variations of total fungal concentration in personal exposure, home and workplace environments. There was an association between personal exposure and home concentration of viable fungi and between personal exposure and home and work concentrations of viable bacteria. Personal exposure and home concentrations of fungi were higher in rural areas than in urban areas. Our results also indicate that presence of a certain fungus in a microenvironment does not necessarily mean similar findings in personal exposure samples.     

Phthalate levels in Norwegian indoor air related to particle size fraction

Phthalates are found in numerous consumer products, including interior materials like polyvinyl chloride (PVC). Several studies have identified phthalates in indoor air. A recent case-control study demonstrated associations between allergic symptoms in children and the concentration of phthalates in dust collected from their homes. Here we have analyzed the content of selected phthalates in particulate matter (PM): PM(10) and PM(2.5) filter samples collected in 14 different indoor environments. The results showed the presence of the phthalates di-n-butyl phthalate (DBP), butyl benzyl phthalate (BBP), dicyclohexyl phthalate (DCHP) and diethyl hexyl phthalate (DEHP) in the samples. The dominating phthalate in both PM(10) and PM(2.5) samples from all locations was DBP. More than a 10-fold variation in the mean concentration of total phthalates between sampling sites was observed. The highest levels of total phthalates were detected in one children's room, one kindergarten, in two primary schools, and in a computer room. The relative contribution of total phthalates in PM(10) and PM(2.5) was 1.1 +/- 0.3% for both size fractions. The contribution of total phthalates in PM(2.5) to total phthalates in PM(10) ranged from 23-81%, suggesting different sources. Of the phthalates that were analyzed in the PM material, DBP was found to be the major phthalate in rubber from car tyres. However, our analyses indicate that tyre wear was of minor importance for indoor levels of both DBP as well as total phthalates. Overall, these results support the notion that inhalation of indoor PM contributes to the total phthalate exposure.     

Indoor and outdoor formaldehyde concentrations in homes in residential areas in Greater Cairo

Indoor and outdoor measurements of formaldehyde were conducted at seven flats located in residential areas in Greater Cairo, during spring and summer seasons 1999. The mean daytime formaldehyde concentrations in kitchens, bedrooms and living rooms were 89, 100 and 100 ppb, respectively, in the seven flats. Significant positive correlations were found between the concentrations of formaldehyde found in these three rooms. On the other hand, no significant differences were found between the mean formaldehyde concentrations in these three rooms. The maximum mean concentration of formaldehyde (147 ppb) was recorded in a new flat, while the minimum concentration (43 ppb) was observed in an old flat. The maximum hourly and daytime concentrations were 350 and 225 ppb, respectively. Air temperature, relative humidity and the age of the flat are factors affecting the emission and concentration of formaldehyde. The maximum indoor and outdoor formaldehyde concentrations were recorded during the summer season. During the spring, 38% of the samples indicated that the concentration of formaldehyde in the seven flats exceeded 0.1 ppm, the American Society of Heating, Refrigerating, and Air Conditioning Engineers' (ASHRAE) standard; in the summer, this figure increased to 53%.     

Overview of particulate exposures in the US trucking industry

As part of a large epidemiologic study of lung cancer, 55,000 subjects, we have conducted a nation-wide survey of particulate exposures in the US trucking industry. The goal is to differentiate the risks from various types of particulate exposures, such as traffic emissions and general air pollution. We hypothesize that exposures defined by job and work site characteristics can be linked with subjects using their personal job histories. This report covers exposures at 36 randomly chosen large truck freight terminals in the US. Measurements were made of PM2.5, elemental carbon (EC), and organic carbon (OC) upwind of the terminal (background) and in work areas, and by personal samples. Significant differences in exposure intensity, microg m(-3), were found for work locations and jobs relative to background levels (GM[GSD]) at terminal sites: PM2.5 9.8[2.34], EC 0.5[3.24], and OC 5.0[1.76]. Using EC as a marker for diesel particles, work locations varied significantly: office 0.3[3.7], dock area 0.7[2.89] and shop area 1.5[3.52]), as did job titles (non-smokers): clerk 0.1[9.98], dock worker 0.8[2.13], and mechanic 2.0[3.82]. Cigarette smoking contributed substantially to personal exposures, approximately doubling PM2.5 and OC, but having less of an effect on EC. Large differences were seen across the terminal sites due to differences in local regional air pollution levels from traffic and other sources. We conclude that it will be possible to estimate current exposures of the cohort using an exposure assignment matrix based on job title, work location, and terminal site. This distribution overlaps substantially with the general public's exposure to these sources.