Sociodemographic descriptors of personal exposure to fine particles (PM2.5) in EXPOLIS Helsinki

Demographic and socioeconomic differences between population sub-groups were analyzed, as a component of the EXPOLIS (Air Pollution Exposure Distributions Within Adult Urban Populations in Europe) Helsinki study, to explain variation in personal exposures to fine particles (PM2.5). Two-hundred one individuals were randomly selected among 25--55-year-old inhabitants of Helsinki Metropolitan area. Personal exposure samples and residential indoor, residential outdoor and workplace indoor microenvironment measurements of PM2.5 were collected between October 1996 and December 1997. Variation in PM2.5 personal exposures, between sociodemographic sub-groups, was best described by differences in occupational status, education and age. Lower occupational status, less educated and young participants had greater exposures than upper occupational status, more educated and older participants. Different workplace concentrations explained most of the socioeconomic differences, and personal day and night exposures and concentrations in home (but not workplace or outdoor concentrations) caused the PM2.5 exposure differences between age groups. Men had higher exposures and much larger exposure differences between the sociodemographic groups than women. No gender, socioeconomic or age differences were observed in home outdoor concentrations between groups. Exposure to tobacco smoke did not seem to create new differences between the sociodemographic groups; instead, it amplified the existing differences.     

Exposure to fine particles (PM2.5 and PM1) and black smoke in the general population: personal, indoor, and outdoor levels

Personal exposure to PM(2.5) and PM(1), together with indoor and residential outdoor levels, was measured in the general adult population (30 subjects, 23-51 years of age) of Gothenburg, Sweden. Simultaneously, urban background concentrations of PM(2.5) were monitored with an EPA WINS impactor. The 24-h samples were gravimetrically analyzed for mass concentration and black smoke (BS) using a smokestain reflectometer. Median levels of PM(2.5) were 8.4 microg/m(3) (personal), 8.6 microg/m(3) (indoor), 6.4 microg/m(3) (residential outdoor), and 5.6 microg/m(3) (urban background). Personal exposure to PM(1) was 5.4 microg/m(3), while PM(1) indoor and outdoor levels were 6.2 and 5.2 microg/m(3), respectively. In non-smokers, personal exposure to PM(2.5) was significantly higher than were residential outdoor levels. BS absorption coefficients were fairly similar for all microenvironments (0.4-0.5 10(-5) m(-1)). Personal exposure to particulate matter (PM) and BS was well correlated with indoor levels, and there was an acceptable agreement between personal exposure and urban background concentrations for PM(2.5) and BS(2.5) (r(s)=0.61 and 0.65, respectively). PM(1) made up a considerable amount (70-80%) of PM(2.5) in all microenvironments. Levels of BS were higher outdoors than indoors and higher during the fall compared with spring. The correlations between particle mass and BS for both PM(2.5) vs. BS(2.5) and PM(1) versus BS(1) were weak for all microenvironments including personal exposure. The urban background station provided a good estimate of residential outdoor levels of PM(2.5) and BS(2.5) within the city (r(s)=0.90 and 0.77, respectively). Outdoor levels were considerably affected by long-range transported air pollution, which was not found for personal exposure or indoor levels. The within-individual (day-to-day) variability dominated for personal exposure to both PM(2.5) and BS(2.5) in non-smokers.     

Personal exposure to fine particles in children correlates closely with ambient fine particles

To investigate the validity of ambient fine-particle concentrations as a measure of exposure in epidemiological time-series studies, we established the association between personal and ambient concentrations, within subjects, over time. We conducted repeated measurements of personal and ambient fine-particle concentrations in 13 children who lived in Wageningen, The Netherlands. For each child separately, we related personal exposures to ambient concentrations in a regression analysis. The median Pearson's correlation coefficient was 0.86. Personal fine-particle concentrations were also highly correlated with ambient particulate matter (i.e., < or = 10-microm) concentrations (median Pearson's correlation coefficient = .75). Personal fine-particle concentrations were typically approximately 11 microg/m3 higher than ambient concentrations. We excluded measurements of children who were exposed to environmental tobacco smoke, and the difference was only 5 microg/m3. The findings of high correlations between personal fine-particle concentrations and both ambient fine-particle concentrations and particulate matter (i.e., < or = 10-microm) found in this group of children provide support for investigators to use ambient particulate matter concentrations to measure exposure to fine-particle concentrations in epidemiological time-series studies.     

空气细颗粒物(PM2.5)生物效应指标研究进展

本文阐述了细颗粒物生物效应指标的研究进展。细颗粒物是一种重要的空气污染物 ,它的形态和组成相当复杂 ,不仅含有大量的有机物如B(a)p ,而且含有许多重金属如Pb、Cd、Cr等。这些组分大多数是有毒的 ,其中一些可以引起肺部炎症和哮喘 ,另一些具有遗传毒性的物质可能是潜在的致癌物。细颗粒物可经过呼吸进入肺部 ,并且沉积在肺组织 ,因此它严重危害人类健康。流行病学研究已经显示细颗粒物与疾病发病率和死亡率的上升有关 ,尤其是心脏和肺部疾病。目前认为细颗粒物可能通过氧化、炎症刺激及对遗传物质的作用对机体造成损伤 ,但细颗粒物的致病机制仍不很清楚 ,因此有必要进一步探索其生物效应     

EXPOLIS simulation model: PM2.5 application and comparison with measurements in Helsinki

PM(2.5) exposure distributions of adult Helsinki citizens were simulated using a probabilistic simulation framework. Simulation results were compared to corresponding personal exposure distributions measured in the EXPOLIS study in Helsinki. The simpler models 1 and 2 (with two and three microenvironments, respectively) predict the general outline of the exposure distributions reasonably well. Compared to the observed exposure distribution, the mean is underestimated by less than 3 microg m(-3) (20%) and the standard deviation by 23-35%. In the improved simulation models (3 and 4), the environmental tobacco smoke (ETS)-exposed subjects are excluded, the time-activity models of working and nonworking subpopulations are modeled separately, and the correlations of input concentration and time fraction variables have been accounted for. The output of these models was very close to the observed distributions; the differences in the means were less than 0.1 microg m(-3) and the differences in standard deviation less than 1%. We conclude that when the required input data are available or can be reliably estimated, the target population PM(2.5) exposure distributions can be predicted accurately enough for most practical purposes using this kind of a microenvironment model.     

Personal PM2.5 exposure and markers of oxidative stress in blood

Ambient particulate air pollution assessed as outdoor concentrations of particulate matter less than or equal to 2.5 micro m in diameter (PM(2.5)) in urban background has been associated with cardiovascular diseases at the population level. However, the significance of individual exposure and the involved mechanisms remain uncertain. We measured personal PM(2.5) and carbon black exposure in 50 students four times in 1 year and analyzed blood samples for markers of protein and lipid oxidation, for red blood cell (RBC) and platelet counts, and for concentrations of hemoglobin and fibrinogen. We analyzed protein oxidation in terms of gamma-glutamyl semialdehyde in hemoglobin (HBGGS) and 2-aminoadipic semialdehyde in hemoglobin (HBAAS) and plasma proteins (PLAAS), and lipid peroxidation was measured as malondialdehyde (MDA) in plasma. Median exposures were 16.1 micro g/m(3) for personal PM(2.5) exposure, 9.2 micro g/m(3) for background PM(2.5) concentration, and 8.1 X 10(-6)/m for personal carbon black exposure. Personal carbon black exposure and PLAAS concentration were positively associated (p < 0.01), whereas an association between personal PM(2.5) exposure and PLAAS was only of borderline significance (p = 0.061). A 3.7% increase in MDA concentrations per 10 micro g/m(3) increase in personal PM(2.5) exposure was found for women (p < 0.05), whereas there was no significant relationship for the men. Similarly, positive associations between personal PM(2.5)exposure and both RBC and hemoglobin concentrations were found only in women (p < 0.01). There were no significant relationships between background PM(2.5) concentration and any of the biomarkers. This suggests that exposure to particles in moderate concentrations can induce oxidative stress and increase RBCs in peripheral blood. Personal exposure appears more closely related to these biomarkers potentially related to cardiovascular disease than is ambient PM(2.5) background concentrations.     

A population exposure model for particulate matter: case study results for PM(2.5) in Philadelphia, PA.

A population exposure model for particulate matter (PM), called the Stochastic Human Exposure and Dose Simulation (SHEDS-PM) model, has been developed and applied in a case study of daily PM(2.5) exposures for the population living in Philadelphia, PA. SHEDS-PM is a probabilistic model that estimates the population distribution of total PM exposures by randomly sampling from various input distributions. A mass balance equation is used to calculate indoor PM concentrations for the residential microenvironment from ambient outdoor PM concentrations and physical factor data (e.g., air exchange, penetration, deposition), as well as emission strengths for indoor PM sources (e.g., smoking, cooking). PM concentrations in nonresidential microenvironments are calculated using equations developed from regression analysis of available indoor and outdoor measurement data for vehicles, offices, schools, stores, and restaurants/bars. Additional model inputs include demographic data for the population being modeled and human activity pattern data from EPA's Consolidated Human Activity Database (CHAD). Model outputs include distributions of daily total PM exposures in various microenvironments (indoors, in vehicles, outdoors), and the contribution from PM of ambient origin to daily total PM exposures in these microenvironments. SHEDS-PM has been applied to the population of Philadelphia using spatially and temporally interpolated ambient PM(2.5) measurements from 1992-1993 and 1990 US Census data for each census tract in Philadelphia. The resulting distributions showed substantial variability in daily total PM(2.5) exposures for the population of Philadelphia (median=20 microg/m(3); 90th percentile=59 microg/m(3)). Variability in human activities, and the presence of indoor-residential sources in particular, contributed to the observed variability in total PM(2.5) exposures. The uncertainty in the estimated population distribution for total PM(2.5) exposures was highest at the upper end of the distribution and revealed the importance of including estimates of input uncertainty in population exposure models. The distributions of daily microenvironmental PM(2.5) exposures (exposures due to time spent in various microenvironments) indicated that indoor-residential PM(2.5) exposures (median=13 microg/m(3)) had the greatest influence on total PM(2.5) exposures compared to the other microenvironments. The distribution of daily exposures to PM(2.5) of ambient origin was less variable across the population than the distribution of daily total PM(2.5) exposures (median=7 microg/m(3); 90th percentile=18 microg/m(3)) and similar to the distribution of ambient outdoor PM(2.5) concentrations. This result suggests that human activity patterns did not have as strong an influence on ambient PM(2.5) exposures as was observed for exposure to other PM(2.5) sources. For most of the simulated population, exposure to PM(2.5) of ambient origin contributed a significant percent of the daily total PM(2.5) exposures (median=37.5%), especially for the segment of the population without exposure to environmental tobacco smoke in the residence (median=46.4%). Development of the SHEDS-PM model using the Philadelphia PM(2.5) case study also provided useful insights into the limitations of currently available data for use in population exposure models. In addition, data needs for improving inputs to the SHEDS-PM model, reducing uncertainty and further refinement of the model structure, were identified.     

The two PM(2.5) (fine) and PM(2.5-10) (coarse) fractions: evidence of different biological activity.

Recent studies have shown that an increased concentration of environmental particulate matter (PM(10)) is related to many respiratory diseases. One major issue is whether the toxicity of the particles resides in some particular fraction as defined by chemical composition and size. The overall purpose of this study was to compare the in vitro toxicity of coarse (PM(2.5-10)) and fine (PM(2.5)) particulate matter, collected in an urban area of Rome, in relation to their physicochemical composition as assessed by analytic electron microscopy and atomic absorption spectroscopy. In particular, our aim was to evaluate the importance of particle physicochemical components in the induced toxicity. The in vitro toxicity assays used included human red blood cell hemolysis, cell viability, and nitric oxide (NO) release in the RAW 264.7 macrophage cell line. The hemolytic potential has been widely used as an in vitro toxicity screen and as a useful indicator of oxidative damage to biomembranes. We found that human erythrocytes underwent dose-dependent hemolysis when they were incubated with varying concentrations of fine and coarse particles. The hemolytic potential was greater for the fine particles than for the coarse particles in equal mass concentration. However, when data were expressed in terms of PM surface per volume unit of suspension, the two fractions did not show any significant hemolytic differences. This result suggested that the oxidative stress induced by PM on the cell membranes could be due mainly to the interaction between the particle surfaces and the cell membranes. RAW 264.7 macrophage cells challenged with particles showed decreased viability and an increased release of NO, a key inflammatory mediator, and both effects were not dose dependent in the tested concentration range. The fine particles were the most effective and the differences between the two size fractions in inducing these biological effects remained unchanged when the basis of comparison was changed from weight to surface measures. It seemed therefore that these differences relied on the different physicochemical nature of the particles. The main chemical difference between the two fractions resided in a greater abundance of C-rich particles with S traces in the fine fraction. Therefore, we cautiously suggest a role for these particles in the induction of toxicity.     

Exposure to fine particulate matter (PM2.5) among highway toll station workers in taipei: direct and indirect exposure assessment

In this study, the authors assessed occupational exposure to PM2.5 among 47 highway toll station workers in Taipei, Taiwan. The subjects were monitored for 10 days to assess integrated 8-hr fine particulate matter (PM2.5) breathing zone concentration. Researchers constructed a microenvironment-time-concentration matrix and applied direct and indirect approaches to assess cumulative exposure. Mean PM2.5 concentration for workers in the truck and bus lanes was 308 microg/m3 (SD = 115.5 microg/m3), substantially higher compared with cash-payment car lanes (mean 115, SD = 41.8, p < 0.001) and ticket-payment car lanes (mean 109, SD = 48.7, p < 0.001). Concentration per vehicle in the truck and bus lanes was 6.4 and 3.7 times higher, respectively, than that of ticket- or cash-payment car lanes. Mean cumulative exposure for the 10-day period was 4,900-13,407 microg/m3.hr, with a mean of 8,019 microg/m3.hr (SD = 2,375.3). Indirect and direct concentrations were strongly correlated (r2 = .61, F(1,125); p = 0.000). The results of this study show that personal exposure to PM2.5 can be reliably estimated using indirect approaches.     

大气细颗粒物对实验动物氧化应激及炎症反应研究进展

流行病学研究显示,大气细颗粒物（PM_2.5）可引发人体呼吸系统、心脑血管系统等方面的疾病。为了更详细地了解PM_2.5对人群健康的危害,本文针对PM_2.5在动物实验中氧化应激和炎症反应方面的影响进行了归纳总结,为进一步研究PM_2.5对机体的危害提供理论依据。     

Personal PM(2.5) exposure among wildland firefighters working at prescribed forest burns in southeastern United States

This study investigated occupational exposure to wood and vegetative smoke in a group of 28 forest firefighters at prescribed forest burns in a southeastern U.S. forest during the winters of 2003-2005. During burn activities, 203 individual person-day PM(2.5) and 149 individual person-day CO samples were collected; during non-burn activities, 37 person-day PM(2.5) samples were collected as controls. Time-activity diaries and post-work shift questionnaires were administered to identify factors influencing smoke exposure and to determine how accurately the firefighters' qualitative assessment estimated their personal level of smoke exposure with discrete responses: "none" or "very little," "low," "moderate," "high," and "very high." An average of 6.7 firefighters were monitored per burn, with samples collected on 30 burn days and 7 non-burn days. Size of burn plots ranged from 1-2745 acres (avg = 687.8). Duration of work shift ranged from 6.8-19.4 hr (avg = 10.3 hr) on burn days. Concentration of PM(2.5) ranged from 5.9-2673 μg/m(3) on burn days. Geometric mean PM(2.5) exposure was 280 μg/m(3) (95% CL = 140, 557 μg/m(3), n = 177) for burn day samples, and 16 μg/m(3) (95% CL = 10, 26 μg/m(3), n = 35) on non-burn days. Average measured PM(2.5) differed across levels of the firefighters' categorical self-assessments of exposure (p < 0.0001): none to very little = 120 μg/m(3) (95% CL = 71, 203 μg/m(3)) and high to very high = 664 μg/m(3) (95% CL = 373, 1185 μg/m(3)); p < 0.0001 on burn days). Time-weighted average PM(2.5) and personal CO averaged over the run times of PM(2.5) pumps were correlated (correlation coefficient estimate, r = 0.79; CLs: 0.72, 0.85). Overall occupational exposures to particulate matter were low, but results indicate that exposure could exceed the ACGIH?-recommended threshold limit value of 3 mg/m(3) for respirable particulate matter in a few extreme situations. Self-assessed exposure levels agreed with measured concentrations of PM(2.5). Correlation analysis shows that either PM(2.5) or CO could be used as a surrogate measure of exposure to woodsmoke at prescribed burns.     

Personal exposure of Paris office workers to nitrogen dioxide and fine particles

Aims: (1) To obtain an overall estimate of variability of personal exposure of Paris office workers to fine particles (PM_2.5) and nitrogen dioxide (NO₂), and to quantify their microenvironmental determinants. (2) To examine the role of potential determinants of indoor concentrations.     

Personal exposure to PM(2.5) and urinary hydroxy-PAH levels in bus drivers exposed to traffic exhaust, in Trujillo, Peru

Public transport vehicle drivers, especially in highly polluted or trafficked areas, are exposed to high levels of air pollutants. In this study, we assessed the influence of traffic on levels of hydroxy polycyclic aromatic hydrocarbons (OH-PAHs) in commercial bus drivers in Trujillo, Peru, by measuring the within-shift changes in the urinary whole weight and creatinine-corrected concentrations of the PAH metabolites. We measured personal PM(2.5) as a proxy of exposure to traffic emission. Urine samples were collected daily from two bus drivers and three minivan drivers in Trujillo, pre-, mid-, post-work shift and on days when the drivers were off work (total n = 144). Ten OH-PAH metabolites were measured in the urine samples. Drivers were also monitored for exposure to PM(2.5) (n = 41). Daily work shift (mean = 13.1 ± 1.3 hr) integrated PM(2.5) was measured in the breathing zones of the drivers for an average of 10.5 days per driver. The differences across shift in OH-PAH concentrations were not statistically significant except for urinary 2-hydroxyfluorene (2-FLU) (p = 0.04) and 4-hydroxyphenanthrene (4-PHE)?(p?= 0.01) and creatinine-corrected 4-hydroxyphenanthrene (p = 0.01). Correlation between pairs of hydroxy-PAHs (ρ = 0.50 to 0.93) were highest for mid-shift samples. Concentrations of PM(2.5) (geometric mean = 64 μg/m(3); 95% confidence limits = 52 μg/m(3), 78 μg/m(3)) is similar to those measured in many other studies of traffic exposure. There was significant change across work shift for concentrations of only two of the OH-PAHs (2-FLU and 4-PHE). Results indicate that the drivers may have had limited time for clearance of PAH exposure from the body between work shifts. Comparisons of the concentrations of creatinine-corrected hydroxy-PAH to those reported in other studies indicate that exposure of public transport drivers to PAH could be similar. By following the subjects over multiple days, this study gives an indication of appropriate exposure situations for the use of hydroxy-PAHs and will be beneficial in designing future occupational studies of PAH exposure.     

Estimating effects of ambient PM(2.5) exposure on health using PM(2.5) component measurements and regression calibration

Most air pollution and health studies conducted in recent years have examined how a health outcome is related to pollution concentrations from a fixed outdoor monitor. The pollutant effect estimate in the health model used indicates how ambient pollution concentrations are associated with the health outcome, but not how actual exposure to ambient pollution is related to health. In this article, we propose a method of estimating personal exposures to ambient PM(2.5) (particulate matter less than 2.5 microm in diameter) using sulfate, a component of PM(2.5) that is derived primarily from ambient sources. We demonstrate how to use regression calibration in conjunction with these derived values to estimate the effects of personal ambient PM(2.5) exposure on a continuous health outcome, forced expiratory volume in 1 s (FEV(1)), using repeated measures data. Through simulation, we show that a confidence interval (CI) for the calibrated estimator based on large sample theory methods has an appropriate coverage rate. In an application using data from our health study involving children with moderate to severe asthma, we found that a 10 microg/m3 increase in PM(2.5) was associated with a 2.2% decrease in FEV(1) at a 1-day lag of the pollutant (95% CI: 0.0-4.3% decrease). Regressing FEV(1) directly on ambient PM(2.5) concentrations from a fixed monitor yielded a much weaker estimate of 1.0% (95% CI: 0.0-2.0% decrease). Relatively small amounts of personal monitor data were needed to calibrate the estimate based on fixed outdoor concentrations.     

细颗粒物免疫毒性研究进展

大气中细颗粒物的暴露是多种健康问题的危险因素 ,而免疫系统是细颗粒物毒性作用的靶器官之一 ,细颗粒物对非特异性免疫系统和特异性免疫系统均有一定影响。免疫系统作用有两面性 ,既对颗粒物具有一定的清除能力 ,同时也是机体受损的重要原因。免疫毒性与颗粒物产生的其他生物效应有密切关系。免疫毒性的作用机制可能通过氧化、炎症刺激和神经性炎症反应等有关 ,但具体致病机制仍不清楚 ,有必要从整体上研究颗粒物的毒性及其作用机制。本文从不同角度和不同水平对细颗粒物的免疫毒性进行综述。     

Photometrically measured continuous personal PM(2.5) exposure: levels and correlation to a gravimetric method

There is evidence that hourly variations in exposure to airborne particulate matter (PM) may be associated with adverse health effects. Still there are only few published data on short-term levels of personal exposure to PM in community settings. The objectives of the study were to assess hourly and shorter-term variations in personal PM(2.5) exposure in Helsinki, Finland, and to compare results from portable photometers to simultaneously measured gravimetric concentrations. The effect of relative humidity on the photometric results was also evaluated. Personal PM(2.5) exposures of elderly persons were assessed for 24 h every second week, resulting in 308 successful measurements from 47 different subjects. Large changes in concentrations in minutes after cooking or changing microenvironment were seen. The median of daily 1-h maxima was over twice the median of 24-h averages. There was a strong significant association between the two means, which was not linear. Median (95th percentile) of the photometric 24-h concentrations was 12.1 (37.7) and of the 24-h gravimetric concentrations 9.2 (21.3) microg/m3. The correlation between the photometric and the gravimetric method was quite good (R2=0.86). Participants spent 94.1% of their time indoors or in a vehicle, where relative humidity is usually low and thus not likely to cause significant effects on photometric results. Even outdoors, the relative humidity had only modest effect on concentrations. Photometers are a promising method to explore the health effects of short-term variation in personal PM(2.5) exposure.     

Population sampling in European air pollution exposure study, EXPOLIS: comparisons between the cities and representativeness of the samples

A personal air pollution exposure study, EXPOLIS, was accomplished in six European cities among 25- to 55-year-old citizens. In order to compare the exposure results and different microenvironmental concentrations between the cities it is crucial to know the extent and effects of the population bias that has developed in sampling procedure and the sociodemographic characteristics of each measured population sample. In each participating city a random Base sample of 2000 to 3000 individuals was drawn from the census and a Short Questionnaire (SQ) was mailed to them. Two subsamples of the Respondents of the mailed questionnaire were randomly drawn: Diary sample for 48-h time--microenvironment--activity diary and extensive exposure questionnaires, and Exposure sample for the same plus personal exposure and microenvironmental monitoring. Significant differences existed between the EXPOLIS cities in the population-sampling procedure. Population-sampling bias was evaluated by comparing the Respondents with the total city populations. The share of women and individuals with more than 14 years of education is higher among the Respondents than the overall population except in Athens. Men, younger (25-34 years old) and unmarried individuals were hardest to get to participate in the study at least in Helsinki. The two subsamples differ from Respondents in having more employed and higher- educated individuals. The largest sample bias occurred at the first and easiest step of responding to the mailed Short Screening Questionnaire, and not at the last and most demanding stage of participating in the exposure measurements. Exposure data from some of EXPOLIS cities can only be compared to other cities with caution considering their large population bias or different sample selections. However the selection bias is not necessarily a problem for analyses about predictors of personal exposures or analyses within a city.     

Airborne concentrations of PM(2.5) and diesel exhaust particles on Harlem sidewalks: a community-based pilot study

Residents of the dense urban core neighborhoods of New York City (NYC) have expressed increasing concern about the potential human health impacts of diesel vehicle emissions. We measured concentrations of particulate matter [less than/equal to] 2.5 micro in aerodynamic diameter (PM(2.5)) and diesel exhaust particles (DEP) on sidewalks in Harlem, NYC, and tested whether spatial variations in concentrations were related to local diesel traffic density. Eight-hour (1000-1800 hr) air samples for PM(2.5 )and elemental carbon (EC) were collected for 5 days in July 1996 on sidewalks adjacent to four geographically distinct Harlem intersections. Samples were taken using portable monitors worn by study staff. Simultaneous traffic counts for diesel trucks, buses, cars, and pedestrians were carried out at each intersection on [Greater/equal to] 2 of the 5 sampling days. Eight-hour diesel vehicle counts ranged from 61 to 2,467 across the four sites. Mean concentrations of PM(2.5) exhibited only modest site-to-site variation (37-47 microg/m(3)), reflecting the importance of broader regional sources of PM(2.5). In contrast, EC concentrations varied 4-fold across sites (from 1.5 to 6 microg/m(3)), and were associated with bus and truck counts on adjacent streets and, at one site, with the presence of a bus depot. A high correlation (r = 0.95) was observed between EC concentrations measured analytically and a blackness measurement based on PM(2.5) filter reflectance, suggesting the utility of the latter as a surrogate measure of DEP in future community-based studies. These results show that local diesel sources in Harlem create spatial variations in sidewalk concentrations of DEP. The study also demonstrates the feasibility of a new paradigm for community-based research involving full and active partnership between academic scientists and community-based organizations.     

A Bayesian hierarchical approach for relating PM(2.5) exposure to cardiovascular mortality in North Carolina

Considerable attention has been given to the relationship between levels of fine particulate matter (particulate matter < or = 2.5 microm in aerodynamic diameter; PM(2.5) in the atmosphere and health effects in human populations. Since the U.S. Environmental Protection Agency began widespread monitoring of PM(2.5) levels in 1999, the epidemiologic community has performed numerous observational studies modeling mortality and morbidity responses to PM(2.5) levels using Poisson generalized additive models (GAMs). Although these models are useful for relating ambient PM(2.5) levels to mortality, they cannot directly measure the strength of the effect of exposure to PM(2.5) on mortality. In order to assess this effect, we propose a three-stage Bayesian hierarchical model as an alternative to the classical Poisson GAM. Fitting our model to data collected in seven North Carolina counties from 1999 through 2001, we found that an increase in PM(2.5) exposure is linked to increased risk of cardiovascular mortality in the same day and next 2 days. Specifically, a 10- microg/m3 increase in average PM(2.5) exposure is associated with a 2.5% increase in the relative risk of current-day cardiovascular mortality, a 4.0% increase in the relative risk of cardiovascular mortality the next day, and an 11.4% increase in the relative risk of cardiovascular mortality 2 days later. Because of the small sample size of our study, only the third effect was found to have > 95% posterior probability of being > 0. In addition, we compared the results obtained from our model to those obtained by applying frequentist (or classical, repeated sampling-based) and Bayesian versions of the classical Poisson GAM to our study population.