Predicting particulate (PM10) personal exposure distributions using a random component superposition statistical model

This paper presents a new statistical model designed to extend our understanding from prior personal exposure field measurements of urban populations to other cities where ambient monitoring data, but no personal exposure measurements, exist. The model partitions personal exposure into two distinct components: ambient concentration and nonambient concentration. It is assumed the ambient and nonambient concentration components are uncorrelated and add together; therefore, the model is called a random component superposition (RCS) model. The 24-hr ambient outdoor concentration is multiplied by a dimensionless "attenuation factor" between 0 and 1 to account for deposition of particles as the ambient air infiltrates indoors. The RCS model is applied to field PM10 measurement data from three large-scale personal exposure field studies: THEES (Total Human Environmental Exposure Study) in Phillipsburg, NJ; PTEAM (Particle Total Exposure Assessment Methodology) in Riverside, CA; and the Ethyl Corporation study in Toronto, Canada. Because indoor sources and activities (smoking, cooking, cleaning, the personal cloud, etc.) may be similar in similar populations, it was hypothesized that the statistical distribution of nonambient personal exposure is invariant across cities. Using a fixed 24-hr attenuation factor as a first approximation derived from regression analysis for the respondents, the distributions of nonambient PM10 personal exposures were obtained for each city. Although the mean ambient PM10 concentrations in the three cities varied from 27.9 micrograms/m3 in Toronto to 60.9 micrograms/m3 in Phillipsburg to 94.1 micrograms/m3 in Riverside, the mean nonambient components of personal exposures were found to be closer: 52.6 micrograms/m3 in Toronto; 52.4 micrograms/m3 in Phillipsburg; and 59.2 micrograms/m3 in Riverside. The three frequency distributions of the nonambient components of exposure also were similar in shape, giving support to the hypothesis that nonambient concentrations are similar across different cities and populations. These results indicate that, if the ambient concentrations were completely controlled and set to zero in all three cities, the median of the remaining personal exposures to PM10 would range from 32.0 micrograms/m3 (Toronto) to 34.4 micrograms/m3 (Phillipsburg) to 48.8 micrograms/m3 (Riverside). The highest-exposed 30% of the population in the three cities would still be exposed to 24-hr average PM10 concentrations of 47-74 micrograms/m3; the highest 20% would be exposed to concentrations of 56-92 micrograms/m3; the highest 10% to concentrations of 88-131 micrograms/m3; and the highest 5% to 133-175 micrograms/m3, due only to indoor sources and activities. The distribution for the difference between personal exposures and indoor concentrations, or the "personal cloud," also was similar in the three cities, with a mean of 30-35 micrograms/m3, suggesting that the personal cloud accounts for more than half of the nonambient component of PM10 personal exposure in the three cities. Using only the ambient measurements in Toronto, the nonambient data from THEES in Phillipsburg was used to predict the entire personal exposure distribution in Toronto. The PM10 exposure distribution predicted by the model showed reasonable agreement with the PM10 personal exposure distribution measured in Toronto. These initial results suggest that the RCS model may be a powerful tool for predicting personal exposure distributions and statistics in other cities where only ambient particle data are available.     

Estimating Separately Personal Exposure to Ambient and Nonambient Particulate Matter for Epidemiology and Risk Assessment: Why and How

ABSTRACT

This paper discusses the legal and scientific reasons for separating personal exposure to PM into ambient and nonambient components. It then demonstrates by several examples how well-established models and data typically obtained in exposure field studies can be used to estimate both individual and community average exposure to ambient-generated PM (ambient PM outdoors plus ambient PM that has infiltrated indoors), indoor-generated PM, and personal activity PM. Ambient concentrations are not highly correlated with personal exposure to nonambient PM or total PM but are highly correlated with personal exposure to ambient-generated PM. Therefore, ambient concentrations may be used in epidemiology as an appropriate surrogate for personal exposure to ambient-generated PM. Suggestions are offered as to how exposure to ambient-generated PM may be obtained and used in epidemiology and risk assessment.     

Estimating separately personal exposure to ambient and nonambient particulate matter for epidemiology and risk assessment: why and how

This paper discusses the legal and scientific reasons for separating personal exposure to PM into ambient and nonambient components. It then demonstrates by several examples how well-established models and data typically obtained in exposure field studies can be used to estimate both individual and community average exposure to ambient-generated PM (ambient PM outdoors plus ambient PM that has infiltrated indoors), indoor-generated PM, and personal activity PM. Ambient concentrations are not highly correlated with personal exposure to nonambient PM or total PM but are highly correlated with personal exposure to ambient-generated PM. Therefore, ambient concentrations may be used in epidemiology as an appropriate surrogate for personal exposure to ambient-generated PM. Suggestions are offered as to how exposure to ambient-generated PM may be obtained and used in epidemiology and risk assessment.     

Estimated hourly personal exposures to ambient and nonambient particulate matter among sensitive populations in Seattle, Washington

Epidemiological studies of particulate matter (PM) routinely use concentrations measured with stationary outdoor monitors as surrogates for personal exposure. Despite the frequently reported poor correlations between ambient concentrations and total personal exposure, the epidemiologic associations between ambient concentrations and health effects depend on the correlation between ambient concentrations and personal exposure to ambient-generated PM. This paper separates personal PM exposure into ambient and nonambient components and estimates the outdoor contribution to personal PM exposures with continuous light scattering data collected from 38 subjects in Seattle, WA. Across all subjects, the average exposure encountered indoors at home was lower than in all other microenvironments. Cooking and being at school were associated with elevated levels of exposure. Previously published estimates of particle infiltration (Finf) were combined with time-location data to estimate an ambient contribution fraction (alpha, mean = 0.66+/-0.21) for each subject. The mean alpha was significantly lower for subjects monitored during the heating season (0.55+/-0.16) than for those monitored during the nonheating season (0.80+/-0.17). Our modeled alpha estimates agreed well with those estimated with the sulfur-tracer method (slope = 1.08; R2 = 0.67). We modeled exposure to ambient and nonambient PM with both continuous light scattering and 24-hr gravimetric data and found good agreement between the two methods. On average, ambient particles accounted for 48% of total personal exposure (range = 21-80%). The personal activity exposure was highly influenced by time spent away from monitored microenvironments. The median hourly longitudinal correlation between central site concentrations and personal exposures was 0.30. Although both alpha and the nonambient sources influence the personal-central relationship, the latter seems to dominate. Thus, total personal exposure may be poorly predicted by stationary outdoor monitors, particularly among persons whose PM exposure is dominated by nonambient exposures, for example, those living in tightly sealed homes, those who cook, and children.     

Personal carbon monoxide exposure in five European cities and its determinants

Studies involving carbon monoxide (CO) exposure assessment are mainly based on measurements at outdoor fixed sites or in various indoor micro-environments. Few studies have been based on personal exposure measurements. In this paper, we report results on personal measurements of CO in five European cities and we investigate determinants which may influence this personal exposure.Within the multi-centre European EXPOLIS study, personal exposure to CO, measured every minute for 48 h, of 401 randomly selected study participants (mainly non-smokers) was monitored in Athens, Basle, Helsinki, Milan and Prague. Each participant also completed a time-microenvironment-activity diary and an extended questionnaire. In addition, for the same time period, ambient levels of CO from fixed site stations were collected.There are significant differences in both personal exposure and ambient levels within the five cities, ranging from high values in Milan and Athens to low in Helsinki. Ambient levels are a significant correlate and determinant of CO 48-h personal exposure in all cities. From the other determinants studied (time spent in street traffic, time of exposure to ETS and time of exposure to gas burning devices) none was consistently significant for all cities. Change of the ambient CO levels from the 25th to the 75th percentile of its distribution resulted in a 1.5–2 fold increase of 48-h personal exposure. Short time personal exposure was also studied in order to assess the influence of specific sources. Exposure levels were significantly higher when participants were in street traffic and in indoor locations in the presence of smokers.Personal 48-h exposure of non-smokers to CO varies among urban populations depending primarily on the ambient levels. For a CO source to be a significant determinant of the personal 48-h CO exposure, it has to affect the levels of CO in the person's proximity for an adequate length of time. Activities of individuals affect shorter term personal exposure.     

Parameter Evaluation and Model Validation of Ozone Exposure Assessment Using Harvard Southern California Chronic Ozone Exposure Study Data

Abstract

To examine factors influencing long‐term ozone (O₃) exposures by children living in urban communities, the authors analyzed longitudinal data on personal, indoor, and outdoor O₃ concentrations, as well as related housing and other questionnaire information collected in the one‐year‐long Harvard Southern California Chronic Ozone Exposure Study. Of 224 children contained in the original data set, 160 children were found to have longitudinal measurements of O₃ concentrations in at least six months of 12 months of the study period. Data for these children were randomly split into two equal sets: one for model development and the other for model validation. Mixed models with various variance‐covariance structures were developed to evaluate statistically important predictors for chronic personal ozone exposures. Model predictions were then validated against the field measurements using an empirical best‐linear unbiased prediction technique.The results of model fitting showed that the most important predictors for personal ozone exposure include indoor O₃ concentration, central ambient O₃ concentration, outdoor O₃ concentration, season, gender, outdoor time, house fan usage, and the presence of a gas range in the house. Hierarchical models of personal O₃ concentrations indicate the following levels of explanatory power for each of the predictive models: indoor and outdoor O₃ concentrations plus questionnaire variables, central and indoor O₃ concentrations plus questionnaire variables, indoor O₃ concentrations plus questionnaire variables, central O₃ concentrations plus questionnaire variables, and questionnaire data alone on time activity and housing characteristics. These results provide important information on key predictors of chronic human exposures to ambient O₃ for children and offer insights into how to reliably and cost‐effectively predict personal O₃ exposures in the future. Furthermore, the techniques and findings derived from this study also have strong implications for selecting the most reliable and cost‐effective exposure study design and modeling approaches for other ambient pollutants, such as fine particulate matter and selected urban air toxics.     

Designing Optimal Strategies to Attain the New U.S. Particulate Matter Standards: Some Initial Concepts

ABSTRACT

This paper proposes that a fundamental principle for designing optimal strategies to attain new U.S. particulate matter (PM) standards be minimization of community and susceptible group exposure to, and inhaled dosage of, ambient PM. Properly done, such minimization maximizes human health risk reduction. To illustrate implementation of such a principle, an initial prototype model, PM Exposure (PMEX), is described that calculates PM exposure and inhaled dosage as figures-of-merit for control strategy optimization. The model accounts for age-occupation and susceptible group activity patterns, indoor-outdoor concentration differences, and geographical location. Modeling results are presented for a hypothetical example, apportioning inhaled dosage among different classes of sources, under alternative assumptions about the relative potency of different PM species categories. The results, while preliminary, demonstrate that conclusions about source class contribution based on inhaled dosage can be appreciably different than those based on ambient air measurements or emission inventories.     

A procedure for use in estimating human exposure to particulate matter of ambient origin

Modern epidemiology has shown that fluctuations of mortality data are statistically significantly correlated with fluctuations of ambient particulate matter (PM) concentration data. This relation cannot be confounded by exposure to PM of indoor origin because the concentrations of ambient PM are not correlated with concentrations of PM of indoor origin. It has been suggested, given the above understanding, that modern PM exposure measurements and analysis should create separate estimates of exposure to all PM of ambient origin and exposure to all PM of nonambient origin (primarily of indoor origin), and not exposure to total PM. This paper reviews the developments of the form of the general microenvironmental mass balance equation that can be utilized for estimating human exposure to PM of ambient origin and for estimating the portion of total PM exposure that is attributable to nonambient origin PM. The equation is perfectly general and can be applied to conditions of time-varying factors that influence exposure, such as rapidly changing air-exchange rates in a home as doors and windows are opened and closed, and turning on and off air cleaners in a home. It is suggested that this procedure be applied in exposure assessment studies and validated using independent techniques of estimating exposure to PM of ambient origin available in the literature.     

Modeling of Personal Exposures to Ambient Air Toxics in Camden,New Jersey: An Evaluation Study

Abstract

This study presents the Individual Based Exposure Modeling (IBEM) application of MENTOR (Modeling ENvironment for TOtal Risk studies) in a hot spot area, where there are concentrated local sources on the scale of tens to hundreds of meters, and an urban reference area in Camden, NJ, to characterize the ambient concentrations and personal exposures to benzene and toluene from local ambient sources. The emission-based ambient concentrations in the two neighborhoods were first estimated through atmospheric dispersion modeling. Subsequently, the calculated and measured ambient concentrations of benzene and toluene were separately combined with the time-activity diaries completed by the subjects as inputs to MENTOR/IBEM for estimating personal exposures resulting from ambient sources. The modeling results were then compared with the actual personal measurements collected from over 100 individuals in the field study to identify the gaps in modeling personal exposures in a hot spot. The modeled ambient concentrations of benzene and toluene were generally in agreement with the neighborhood measurements within a factor of 2, but were underestimated at the high-end percentiles. The major local contributors to the benzene ambient levels are from mobile sources, whereas mobile and stationary (point and area) sources contribute to the toluene ambient levels in the study area. This finding can be used as guidance for developing better air toxic emission inventories for characterizing, through modeling, the ambient concentrations of air toxics in the study area. The estimated percentage contributions of personal exposures from ambient sources were generally higher in the hot spot area than the urban reference area in Camden, NJ, for benzene and toluene. This finding demonstrates the hot spot characteristics of stronger local ambient source impacts on personal exposures. Non-ambient sources were also found as significant contributors to personal exposures to benzene and toluene for the population studied.     

Assessment of Human Exposure to Ambient Particulate Matter

ABSTRACT

Recent epidemiological studies have consistently shown that the acute mortality effects of high concentrations of ambient particulate matter (PM), documented in historic air pollution episodes, may also be occurring at the low to moderate concentrations of ambient PM found in modern urban areas. In London in December 1952, the unexpected deaths due to PM exposure could be identified and counted as integers by the coroners. In modern times, the PM-related deaths cannot be as readily identified, and they can only be inferred as fractional average daily increases in mortality rates using sophisticated statistical filtering and analyses of the air quality and mortality data. The causality of the relationship between exposure to ambient PM and acute mortality at these lower modern PM concentrations has been questioned because of a perception that there is little significant correlation in time between the ambient PM concentrations and measured personal exposure to PM from all sources (ambient PM plus indoor-generated PM).

This article shows that the critical factor supporting the plausibility of a linear PM mortality relationship is the expected high correlation in time of people's exposure to PM of ambient origin with measured ambient PM concentrations, as used in the epidemiological time series studies. The presence of indoor and personal sources of PM masks this underlying relationship, leading to confusion in the scientific literature about the strong underlying temporal relationship between personal exposure to PM of ambient origin and ambient PM concentration. The authors show that the sources of PM of non-ambient origin operate independently of the ambient PM concentrations, so that the mortality effect of non-ambient PM, if any, must be independent of the effects of the ambient PM exposures.     

Filtration of Radioactive Aerosols By Glass Fibers

Abstract

An ozone (O₃) exposure assessment study was conducted in Toronto, Ontario, Canada during the winter and summer of 1992. A new passive O₃ sampler developed by Harvard was used to measure indoor, outdoor, and personal O₃ concentrations. Measurements were taken weekly and daily during the winter and summer, respectively. Indoor samples were collected at a total of 50 homes and workplaces of study participants. Outdoor O₃ concentrations were measured both at home sites using the passive sampler and at 20 ambient monitoring sites with continuous monitors. Personal O₃ measurements were collected from 123 participants, who also completed detailed time-activity diaries. A total of 2,274 O₃ samples were collected. In addition, weekly air exchange rates of homes were measured.

This study demonstrates the performance of our O₃ sampler for exposure assessment. The data obtained are further used to examine the relationships between personal, indoor (home and workplace), and outdoor O₃ concentrations, and to investigate outdoor and indoor spatial variations in O₃ concentrations. Based on home outdoor and indoor, workplace, and ambient O₃ concentrations measured at the Ontario Ministry of the Environment (MOE) sites, the traditional microenvironmental model predicts 72% of the variability in measured personal exposures. An alternative personal O₃ exposure model based on outdoor measurements and time-activity information is able to predict the mean personal exposures in a large population, with the highest R² value of 0.41.     

Concentrations of mobile source air pollutants in urban microenvironments

Human exposures to criteria and hazardous air pollutants (HAPs) in urban areas vary greatly due to temporal-spatial variations in emissions, changing meteorology, varying proximity to sources, as well as due to building, vehicle, and other environmental characteristics that influence the amounts of ambient pollutants that penetrate or infiltrate into these microenvironments. Consequently, the exposure estimates derived from central-site ambient measurements are uncertain and tend to underestimate actual exposures. The Exposure Classification Project (ECP) was conducted to measure pollutant concentrations for common urban microenvironments (MEs) for use in evaluating the results of regulatory human exposure models. Nearly 500 sets of measurements were made in three Los Angeles County communities during fall 2008, winter 2009, and summer 2009. MEs included in-vehicle, near-road, outdoor, and indoor locations accessible to the general public. Contemporaneous 1- to 15-min average personal breathing zone concentrations of carbon monoxide (CO), carbon dioxide (CO₂), volatile organic compounds (VOCs), nitric oxide (NO), nitrogen oxides (NO_x), particulate matter (<2.5 μm diameter; PM_2.5) mass, ultrafine particle (UFP; <100 nm diameter) number, black carbon (BC), speciated HAPs (e.g., benzene, toluene, ethylbenzene, xylenes [BTEX], 1,3-butadiene), and ozone (O₃) were measured continuously. In-vehicle and inside/outside measurements were made in various passenger vehicle types and in public buildings to estimate penetration or infiltration factors. A large fraction of the observed pollutant concentrations for on-road MEs, especially near diesel trucks, was unrelated to ambient measurements at nearby monitors. Comparisons of ME concentrations estimated using the median ME/ambient ratio versus regression slopes and intercepts indicate that the regression approach may be more accurate for on-road MEs. Ranges in the ME/ambient ratios among ME categories were generally greater than differences among the three communities for the same ME category, suggesting that the ME proximity factors may be more broadly applicable to urban MEs.

Implications:Estimates of population exposure to air pollutants extrapolated from ambient measurements at ambient fixed site monitors or exposure surrogates are prone to uncertainty. This study measured concentrations of mobile source air toxics (MSAT) and related criteria pollutants within in-vehicle, outdoor near-road, and indoor urban MEs to provide multipollutant ME measurements that can be used to calibrate regulatory exposure models.     

Parameter evaluation and model validation of ozone exposure assessment using Harvard Southern California Chronic Ozone Exposure Study data

To examine factors influencing long-term ozone (O3) exposures by children living in urban communities, the authors analyzed longitudinal data on personal, indoor, and outdoor O3 concentrations, as well as related housing and other questionnaire information collected in the one-year-long Harvard Southern California Chronic Ozone Exposure Study. Of 224 children contained in the original data set, 160 children were found to have longitudinal measurements of O3 concentrations in at least six months of 12 months of the study period. Data for these children were randomly split into two equal sets: one for model development and the other for model validation. Mixed models with various variance-covariance structures were developed to evaluate statistically important predictors for chronic personal ozone exposures. Model predictions were then validated against the field measurements using an empirical best-linear unbiased prediction technique. The results of model fitting showed that the most important predictors for personal ozone exposure include indoor O3 concentration, central ambient O3 concentration, outdoor O3 concentration, season, gender, outdoor time, house fan usage, and the presence of a gas range in the house. Hierarchical models of personal O3 concentrations indicate the following levels of explanatory power for each of the predictive models: indoor and outdoor O3 concentrations plus questionnaire variables, central and indoor O3 concentrations plus questionnaire variables, indoor O3 concentrations plus questionnaire variables, central O3 concentrations plus questionnaire variables, and questionnaire data alone on time activity and housing characteristics. These results provide important information on key predictors of chronic human exposures to ambient O3 for children and offer insights into how to reliably and cost-effectively predict personal O3 exposures in the future. Furthermore, the techniques and findings derived from this study also have strong implications for selecting the most reliable and cost-effective exposure study design and modeling approaches for other ambient pollutants, such as fine particulate matter and selected urban air toxics.     

Bayesian hierarchical modeling of personal exposure to particulate matter

In the US EPA's 1998 Baltimore Epidemiology-Exposure Panel Study, a group of 16 residents of a single building retirement community wore personal monitors recording personal fine particulate air pollution concentrations (PM_2.5) for 27 days, while other monitors recorded concurrent apartment, central indoor, outdoor and ambient site PM_2.5 concentrations. Using the Baltimore panel study data, we develop a Bayesian hierarchical model to characterize the relationship between personal exposure and concentrations of PM_2.5 indoors and outdoors. Personal exposure is expressed as a linear combination of time spent in microenvironments and associated microenvironmental concentrations. The model incorporates all available monitoring data and accounts for missing data and sources of uncertainty such as measurement error and individual differences in exposure. We discuss the implications of using personal versus ambient PM_2.5 measurements in characterization of personal exposure to PM_2.5.     

A Statistical Model for FEV1 Response to Arbitrary Dynamic Ozone Exposure Conditions

ABSTRACT

Lung function response to inhaled ozone at ambient air pollution levels is known to be a function of ozone concentration, exposure duration, and minute ventilation. Most data-driven exposure-response models address exposures under static condition (i.e., with a constant ozone concentration and exercise pattern). Such models are simplifications, as both ambient ozone concentrations and normal human activity patterns change with time. The purpose of this study was to develop a dynamic model of response with the advantages of a statistical model (a relatively simple structure with few parameters). A previously proposed mechanistic model for changes in specific airways resistance was adapted to describe the percent change in forced expiratory volume in one second (FEV₁). This model was then reduced using the fit to three existing exposure-response data sets as criterion. The resulting model consists of a single linear differential equation together with an algebraic logistic equation. Under restricted static conditions the model reduces to a logistic model presented earlier by the authors.     

Exposure of Chronic Obstructive Pulmonary Disease Patients to Particulate Matter: Relationships between Personal and Ambient Air Concentrations

ABSTRACT

Most time-series studies of particulate air pollution and acute health outcomes assess exposure of the study population using fixed-site outdoor measurements. To address the issue of exposure misclassification, we evaluate the relationship between ambient particle concentrations and personal exposures of a population expected to be at risk of particle health effects.

Sampling was conducted within the Vancouver metropolitan area during April-September 1998. Sixteen subjects (non-smoking, ages 54-86) with physician-diagnosed chronic obstructive pulmonary disease (COPD) wore personal PM_{2 5} monitors for seven 24-hr periods, randomly spaced approximately 1.5 weeks apart. Time-activity logs and dwelling characteristics data were also obtained for each subject. Daily 24-hr ambient PM₁₀ and PM_2.5 concentrations were measured at five fixed sites spaced throughout the study region. SO₄ ^2-, which is found almost exclusively in the fine particle fraction and which does not have major indoor sources, was measured in all PM_{2 5} samples as an indicator of accumulation mode particu-late matter of ambient origin.     

The 1999 Fresno Particulate Matter Exposure Studies: Comparison of Community,Outdoor, and Residential PM Mass Measurements

ABSTRACT

Two collaborative studies have been conducted by the U.S. Environmental Protection Agency (EPA) National Exposure Research Laboratory (NERL) and National Health and Environmental Effects Research Laboratory to determine personal exposures and physiological responses to par-ticulate matter (PM) of elderly persons living in a retirement facility in Fresno, CA. Measurements of PM and other criteria air pollutants were made inside selected individual residences within the retirement facility and at a central outdoor site on the premises. In addition, personal PM exposure monitoring was conducted for a subset of the participants, and ambient PM monitoring data were available for comparison from the NERL PM research monitoring platform in central Fresno. Both a winter (February 1-28, 1999) and a spring (April 19-May 16, 1999) study were completed so that seasonal effects could be     

Pilot study of personal, indoor and outdoor exposure to benzene, formaldehyde and acetaldehyde

There is a lack of data for health risk assessment of long term personal exposure to certain ubiquitous air pollutants present particularly in urban atmospheres. The relationship between ambient background concentrations and personal exposure is often unknown. A pilot campaign to measure indoor concentrations, outdoor concentrations and personal exposure to benzene, formaldehyde and acetaldehyde was conducted in a medium sized French town. A strong contribution to total personal exposure was observed from indoor sources, especially for formaldehyde and acetaldehyde, suggesting that indoor sources are dominant for these compounds. For benzene, the average personal exposure exceeded a 10 μgm^?3 limit value, although this was not the case for the ambient background concentration. For formaldehyde, the limit level was also exceeded. Observations suggest that true personal exposure cannot be determined directly from measurements pertaining from fixed ambient background monitoring stations. It is hoped that this will be taken into consideration by the bodies responsible for monitoring air pollution and the future European Air Quality Directive.     

Exposure of chronic obstructive pulmonary disease patients to particulate matter: relationships between personal and ambient air concentrations

Mot time-series studies of particulate air pollution and acute health outcomes assess exposure of the study population using fixed-site outdoor measurements. To address the issue of exposure misclassification, we evaluate the relationship between ambient particle concentrations and personal exposures of a population expected to be at risk of particle health effects. Sampling was conducted within the Vancouver metropolitan area during April-September 1998. Sixteen subjects (non-smoking, ages 54-86) with physician-diagnosed chronic obstructive pulmonary disease (COPD) wore personal PM2.5 monitors for seven 24-hr periods, randomly spaced approximately 1.5 weeks apart. Time-activity logs and dwelling characteristics data were also obtained for each subject. Daily 24-hr ambient PM10 and PM2.5 concentrations were measured at five fixed sites spaced throughout the study region. SO4(2-), which is found almost exclusively in the fine particle fraction and which does not have major indoor sources, was measured in all PM2.5 samples as an indicator of accumulation mode particulate matter of ambient origin. The mean personal and ambient PM2.5 concentrations were 18 micrograms/m3 and 11 micrograms/m3, respectively. In analyses relating personal and ambient measurements, ambient concentrations were expressed either as an average of the values obtained from five ambient monitoring sites for each day of personal sampling, or as the concentration obtained at the ambient site closest to each subject's home. The mean personal to ambient concentration ratio of all samples was 1.75 (range = 0.24 to 10.60) for PM2.5, and 0.75 (range = 0.09 to 1.42) for SO4(2-). Regression analyses were conducted for each subject separately and on pooled data. The median correlation (Pearson's r) between personal and average ambient PM2.5 concentrations was 0.48 (range = -0.68 to 0.83). Using SO4(2-) as the exposure metric, the median r between personal and average ambient concentrations was 0.96 (range = 0.66 to 1.0). Use of the closest ambient site did not improve the median correlation of the group for either PM2.5 or SO4(2-). All pooled analyses resulted in lower correlation coefficients than the median correlation coefficient of individual regressions. Personal SO4(2-) was more highly correlated with all ambient measures than PM2.5. Inclusion of time-activity and dwelling characteristics data did not result in a useful predictive regression model for PM2.5 personal exposure, but improved the model fit from simply regressing against ambient concentration (R2 = 0.27). The model for SO4(2-) was predictive (R2 = 0.82), as personal exposures were largely explained by ambient levels. These results indicate a relatively low correlation between personal exposure and ambient PM2.5 that is not improved by assigning exposure to the closest ambient monitor. The correlation between personal exposure and ambient concentration is high, however, when using SO4(2-), an indicator of accumulation mode particulate matter of ambient origin.     

Personal Exposure to Fine Particulate Matter in Elderly Subjects: Relation between Personal,Indoor, and Outdoor Concentrations

ABSTRACT

The time-series correlation between ambient levels, indoor levels, and personal exposure to PM_2.5 was assessed in panels of elderly subjects with cardiovascular disease in Amsterdam, the Netherlands, and Helsinki, Finland. Subjects were followed for 6 months with biweekly clinical visits. Each subject's indoor and personal exposure to PM_2.5 was measured biweekly, during the 24-hr period preceding the clinical visits. Outdoor PM_2.5 concentrations were measured at fixed sites. The absorption coefficients of all PM_2.5 filters were measured as a marker for elemental carbon (EC). Regression analyses were conducted for each subject separately, and the distribution of the individual regression and correlation coefficients was investigated. Personal, indoor, and ambient concentrations were highly correlated within subjects over time. Median Pearson's R between personal and outdoor PM_2.5 was 0.79 in Amsterdam and 0.76 in Helsinki. For absorption, these values were 0.93 and 0.81 for Amsterdam and Helsinki, respectively. The findings of this study provide further support for using fixed-site measurements as a measure of exposure to PM_2.5 in epidemiological time-series studies.