VOC concentrations measured in personal samples and residential indoor,outdoor and workplace microenvironments in EXPOLIS-Helsinki,Finland

Thirty target volatile organic compounds (VOC) were analyzed in personal 48-h exposure samples and residential indoor, residential outdoor and workplace indoor microenvironment samples as a component of EXPOLIS-Helsinki, Finland. Geometric mean residential indoor concentrations were higher than geometric mean residential outdoor concentrations for all target compounds except hexane, which was detected in 40% of residential outdoor samples and 11% of residential indoor samples, respectively. Geometric mean residential indoor concentrations were significantly higher than personal exposure concentrations, which in turn were significantly higher than workplace concentrations for compounds that had strong residential indoor sources (d-limonene, alpha pinene, 3-carene, hexanal, 2-methyl-1-propanol and 1-butanol). 40% of participants in EXPOLIS-Helsinki reported personal exposure to environmental tobacco smoke (ETS). Participants in Helsinki that were exposed to ETS at any time during the 48-h sampling period had significantly higher personal exposures to benzene, toluene, styrene, m,p-xylene, o-xylene, ethylbenzene and trimethylbenzene. Geometric mean ETS-free workplace concentrations were higher than ETS-free personal exposure concentrations for styrene, hexane and cyclohexane. Geometric mean personal exposures of participants not exposed to ETS were approximately equivalent to time weighted ETS-free indoor and workplace concentrations, except for octanal and compounds associated with traffic, which showed higher geometric mean personal exposure concentrations than any microenvironment (o-xylene, ethylbenzene,benzene, undecane, nonane, decane, m,p-xylene, and trimethylbenzene). Considerable differences in personal exposure concentrations and residential levels of compounds with mainly indoor sources suggested differences in product types or the frequency of product use between Helsinki, Germany and the United States.     

Residential Indoor,Outdoor, and Workplace Concentrations of Carbonyl Compounds: Relationships with Personal Exposure Concentrations and Correlation with Sources

Abstract

Personal 48-hr exposures of 15 randomly selected participants as well as microenvironment concentrations in each participant’s residence and workplace were measured for 16 carbonyl compounds during summer–fall 1997 as a part of the Air Pollution Exposure Distributions within Adult Urban Populations in Europe (EXPOLIS) study in Helsinki, Finland. When formaldehyde and acetaldehyde were excluded, geometric mean ambient air concentrations outside each participant’s residence were less than 1 ppb for all target compounds. Geometric mean residential indoor concentrations of carbonyls were systematically higher than geometric mean personal exposures and indoor workplace concentrations. Additionally, residential indoor/outdoor ratios indicated substantial indoor sources for most target compounds. Carbonyls in residential indoor air correlated significantly, suggesting similar mechanisms of entry into indoor environments. Overall, this study demonstrated the important role of non-traffic-related emissions in the personal exposures of participants in Helsinki and that comprehensive apportionment of population risk to air toxics should include exposure concentrations derived from product emissions and chemical formation in indoor air.     

Personal exposure levels and microenvironmental concentrations of formaldehyde and acetaldehyde in the Helsinki metropolitan area, Finland

Personal 48-hr exposures to formaldehyde and acetaldehyde of 15 randomly selected participants were measured during the summer/autumn of 1997 using Sep-Pak DNPH-Silica cartridges as a part of the EXPOLIS study in Helsinki, Finland. In addition to personal exposures, simultaneous measurements of microenvironmental concentrations were conducted at each participant's residence (indoor and outdoor) and workplace. Mean personal exposure levels were 21.4 ppb for formaldehyde and 7.9 ppb for acetaldehyde. Personal exposures were systematically lower than indoor residential concentrations for both compounds, and ambient air concentrations were lower than both indoor residential concentrations and personal exposure levels. Mean workplace concentrations of both compounds were lower than mean indoor residential concentrations. Correlation between personal exposures and indoor residential concentrations was statistically significant for both compounds. This indicated that indoor residential concentrations of formaldehyde and acetaldehyde are a better estimate of personal exposures than are concentrations in ambient air. In addition, a time-weighted exposure model did not improve the estimation of personal exposures above that obtained using indoor residential concentrations as a surrogate for personal exposures. Correlation between formaldehyde and acetaldehyde was statistically significant in outdoor microenvironments, suggesting that both compounds have similar sources and sinks in ambient urban air.     

Residential indoor,outdoor, and workplace concentrations of carbonyl compounds: relationships with personal exposure concentrations and correlation with sources

Personal 48-hr exposures of 15 randomly selected participants as well as microenvironment concentrations in each participant's residence and workplace were measured for 16 carbonyl compounds during summer-fall 1997 as a part of the Air Pollution Exposure Distributions within Adult Urban Populations in Europe (EXPOLIS) study in Helsinki, Finland. When formaldehyde and acetaldehyde were excluded, geometric mean ambient air concentrations outside each participant's residence were less than 1 ppb for all target compounds. Geometric mean residential indoor concentrations of carbonyls were systematically higher than geometric mean personal exposures and indoor workplace concentrations. Additionally, residential indoor/outdoor ratios indicated substantial indoor sources for most target compounds. Carbonyls in residential indoor air correlated significantly, suggesting similar mechanisms of entry into indoor environments. Overall, this study demonstrated the important role of non-traffic-related emissions in the personal exposures of participants in Helsinki and that comprehensive apportionment of population risk to air toxics should include exposure concentrations derived from product emissions and chemical formation in indoor air.     

Behavioral and environmental determinants of personal exposures to PM2.5 in EXPOLIS – Helsinki,Finland

Behavioral and environmental determinants of PM_2.5 personal exposures were analyzed for 201 randomly selected adult participants (25–55 years old) of the EXPOLIS study in Helsinki, Finland. Personal exposure concentrations were higher than respective residential outdoor, residential indoor and workplace indoor concentrations for both smokers and non-smokers. Mean personal exposure concentrations of active smokers (31.0±31.4 μg m⁻³) were almost double those of participants exposed to environmental tobacco smoke (ETS) (16.6±11.8 μg m⁻³) and three times those of participants not exposed to tobacco smoke (9.9±6.2 μg m⁻³). Mean indoor concentrations of PM_2.5 when a member of the household smoked indoors (20.8±23.9 μg m⁻³) were approximately 2.5 times the concentrations of PM_2.5 when no smoking was reported (8.2±5.2 μg m⁻³). Interestingly, however, both mean (8.2 μg m⁻³) and median (6.9 μg m⁻³) residential indoor concentrations for non-ETS exposed participants were lower than residential outdoor concentrations (9.5 and 7.3 μg m⁻³, respectively). In simple linear regression models residential indoor concentrations were the best predictors of personal exposure concentrations. Correlations (r²) between PM_2.5 personal exposure concentrations of all participants, both smoking and non-smoking, and residential indoor, workplace indoor, residential outdoor and ambient fixed site concentrations were 0.53, 0.38, 0.17 and 0.16, respectively. Predictors for personal exposure concentrations of non-ETS exposed participants identified in multiple regression were residential indoor concentrations, workplace concentrations and traffic density in the nearest street from home, which accounted for 77% of the variance. Subsequently, step-wise regression not including residential and workplace indoor concentrations as input (as these are frequently not available), identified ambient PM_2.5 concentration and home location, as predictors of personal exposure, accounting for 47% of the variance. Ambient fixed site PM_2.5 concentrations were closely related to residential outdoor concentrations (r²=0.9, p=0.000) and PM_2.5 personal exposure concentrations were higher in summer than during other seasons. Personal exposure concentrations were significantly (p=0.040) higher for individuals living downtown compared with individuals in suburban family homes. Further analysis will focus on comparisons of determinants between Helsinki and other EXPOLIS centers.     

Benzene exposure in Helsinki,Finland

Personal exposures and microenvironmental concentrations of benzene were measured in the residential indoor, residential outdoor and workplace environments for 201 participants in Helsinki, Finland, as a component of the EXPOLIS-Helsinki study. Median benzene personal exposures were 2.47 (arithmetic standard deviation (ASD)=1.62) μg m⁻³ for non-smokers, 2.89 (ASD=3.26) μg m⁻³ for those exposed to environmental tobacco smoke in any microenvironment and 3.08 (ASD=10.04) μg m⁻³ for active smokers. Median residential indoor benzene concentrations were 3.14 (ASD=1.51) μg m⁻³ and 1.87 (ASD=1.93) μg m⁻³ for environments with and without tobacco smoke, respectively. Median residential outdoor benzene concentrations were 1.51 (ASD=1.11) μg m⁻³ and median workplace benzene concentrations were 3.58 (ASD=1.96) μg m⁻³ and 2.13 (ASD=1.49) μg m⁻³ for environments with and without tobacco smoke, respectively. Multiple step-wise regression identified indoor benzene concentrations as the strongest predictor for personal benzene exposures of those not exposed to tobacco smoke, followed sequentially by time spent in a car, time in the indoor environment, indoor workplace concentrations and time in the home workshop. Relationships between indoor and outdoor microenvironment concentrations and personal exposures showed considerable variation between seasons, due to differences in ventilation patterns of homes in these northern latitudes. Automobile use-related activities were significantly associated with elevated benzene levels in personal and indoor measurements when tobacco smoke was not present, which demonstrates the importance of personal measurements in the assessment of exposure to benzene.     

Impact of Microenvironmental Nitrogen Dioxide Concentrations on Personal Exposures in Australia

ABSTRACT

Indoor and outdoor NO₂ concentrations were measured and compared with simultaneously measured personal exposures of 57 office workers in Brisbane, Australia. House characteristics and activity patterns were used to determine the impacts of these factors on personal exposure. Indoor NO₂ levels and the presence of a gas range in the home were significantly associated with personal exposure. The time-weighted average of personal exposure was estimated using NO₂ measurements in indoor home, indoor workplace, and outdoor home levels. The estimated personal exposures were closely correlated, but they significantly underestimated the measured personal exposures. Multiple regression analysis using other nonmeasured microenvironments indicated the importance of transportation in personal exposure models. The contribution of transportation to the error of prediction of personal exposure was confirmed in the regression analysis using the multinational study database.     

Impact of microenvironmental nitrogen dioxide concentrations on personal exposures in Australia

Indoor and outdoor NO2 concentrations were measured and compared with simultaneously measured personal exposures of 57 office workers in Brisbane, Australia. House characteristics and activity patterns were used to determine the impacts of these factors on personal exposure. Indoor NO2 levels and the presence of a gas range in the home were significantly associated with personal exposure. The time-weighted average of personal exposure was estimated using NO2 measurements in indoor home, indoor workplace, and outdoor home levels. The estimated personal exposures were closely correlated, but they significantly underestimated the measured personal exposures. Multiple regression analysis using other nonmeasured microenvironments indicated the importance of transportation in personal exposure models. The contribution of transportation to the error of prediction of personal exposure was confirmed in the regression analysis using the multinational study database.     

Microenvironmental characteristics important for personal exposures to aldehydes in Sacramento,CA, and Milwaukee,WI

Oxygenated additives in gasoline are designed to decrease the ozone-forming hydrocarbons and total air toxics, yet they can increase the emissions of aldehydes and thus increase human exposure to these toxic compounds. This paper describes a study conducted to characterize targeted aldehydes in microenvironments in Sacramento, CA, and Milwaukee, WI, and to improve our understanding of the impact of the urban environment on human exposure to air toxics. Data were obtained from microenvironmental concentration measurements, integrated, 24-h personal measurements, indoor and outdoor pollutant monitors at the participants' residences, from ambient pollutant monitors at fixed-site locations in each city, and from real-time diaries and questionnaires completed by the technicians and participants. As part of this study, a model to predict personal exposures based on individual time/activity data was developed for comparison to measured concentrations. Predicted concentrations were generally within 25% of the measured concentrations. The microenvironments that people encounter daily provide for widely varying exposures to aldehydes. The activities that occur in those microenvironments can modulate the aldehyde concentrations dramatically, especially for environments such as “indoor at home.” By considering personal activity, location (microenvironment), duration in the microenvironment, and a knowledge of the general concentrations of aldehydes in the various microenvironments, a simple model can do a reasonably good job of predicting the time-averaged personal exposures to aldehydes, even in the absence of monitoring data. Although concentrations of aldehydes measured indoors at the participants' homes tracked well with personal exposure, there were instances where personal exposures and indoor concentrations differed significantly. Key to the ability to predict exposure based on time/activity data is the quality and completeness of the microenvironmental characterizations for the chemicals of interest. Consistent with many earlier studies, personal exposures are difficult to predict using data from regional outdoor monitors.     

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.     

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.     

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.     

Personal exposures to NO2 in the EXPOLIS-study: relation to residential indoor,outdoor and workplace concentrations in Basel,Helsinki and Prague

Personal exposures, residential indoor, outdoor and workplace levels of nitrogen dioxide (NO₂) were measured for 262 urban adult (25–55 years) participants in three EXPOLIS centres (Basel; Switzerland, Helsinki; Finland, and Prague; Czech Republic) using passive samplers for 48-h sampling periods during 1996–1997. The average residential outdoor and indoor NO₂ levels were lowest in Helsinki (24±12 and 18±11 μg m⁻³, respectively), highest in Prague (61±20 and 43±23 μg m⁻³), with Basel in between (36±13 and 27±13 μg m⁻³). Average workplace NO₂ levels, however, were highest in Basel (36±24 μg m⁻³), lowest in Helsinki (27±15 μg m⁻³), with Prague in between (30±18 μg m⁻³). A time-weighted microenvironmental exposure model explained 74% of the personal NO₂ exposure variation in all centres and in average 88% of the exposures. Log-linear regression models, using residential outdoor measurements (fixed site monitoring) combined with residential and work characteristics (i.e. work location, using gas appliances and keeping windows open), explained 48% (37%) of the personal NO₂ exposure variation. Regression models based on ambient fixed site concentrations alone explained only 11–19% of personal NO₂ exposure variation. Thus, ambient fixed site monitoring alone was a poor predictor for personal NO₂ exposure variation, but adding personal questionnaire information can significantly improve the predicting power.     

Evaluation of cumulative PCB exposure estimated by a job exposure matrix versus PCB serum concentrations

Although polychlorinated biphenyls (PCBs) have been banned in many countries for more than three decades, exposures to PCBs continue to be of concern due to their long half-lives and carcinogenic effects. In National Institute for Occupational Safety and Health studies, we are using semiquantitative plant-specific job exposure matrices (JEMs) to estimate historical PCB exposures for workers (n?=?24,865) exposed to PCBs from 1938 to 1978 at three capacitor manufacturing plants. A subcohort of these workers (n?=?410) employed in two of these plants had serum PCB concentrations measured at up to four times between 1976 and 1989. Our objectives were to evaluate the strength of association between an individual worker’s measured serum PCB levels and the same worker’s cumulative exposure estimated through 1977 with the (1) JEM and (2) duration of employment, and to calculate the explained variance the JEM provides for serum PCB levels using (3) simple linear regression. Consistent strong and statistically significant associations were observed between the cumulative exposures estimated with the JEM and serum PCB concentrations for all years. The strength of association between duration of employment and serum PCBs was good for highly chlorinated (Aroclor 1254/HPCB) but not less chlorinated (Aroclor 1242/LPCB) PCBs. In the simple regression models, cumulative occupational exposure estimated using the JEMs explained 14–24 % of the variance of the Aroclor 1242/LPCB and 22–39 % for Aroclor 1254/HPCB serum concentrations. We regard the cumulative exposure estimated with the JEM as a better estimate of PCB body burdens than serum concentrations quantified as Aroclor 1242/LPCB and Aroclor 1254/HPCB.     

Measurements of personal exposure to nitrogen dioxide in four Mexican cities in 1996

Nitrogen dioxide is a ubiquitous pollutant in urban areas. Indoor NO2 concentrations are influenced by penetration of outdoor concentrations and by indoor sources. The objectives of this study were to evaluate personal exposure to NO2, taking into account human time-activity patterns in four Mexican cities. Passive filter badges were used for indoor, outdoor, and personal NO2 measurements over 48 hr and indoor workplace measurements over 16 hr. Volunteers completed a questionnaire on exposure factors and a time-activity diary during the sample period. An unpaired t test, an analysis of variance (ANOVA), and a linear regression were performed to compare differences among cities and mean personal NO2 concentrations involving housing characteristics, as well as to determine which variables predicted the personal NO2 concentration. Sampling periods were in April, May, and June 1996 in Mexico City, Guadalajara, Cuernavaca, and Monterrey. All 122 volunteers in the study were working adults, with a mean age of 34 (SD +/- 7.38); 64% were female, and the majority worked in public offices and universities. The highest NO2 concentrations were found in Mexico City (36 ppb for outdoor, 57 ppb for indoor, and 39 ppb for personal concentration) and the lowest in Monterrey (19 ppb for outdoor, 24 ppb for indoor, and 24 ppb for personal concentration). Significant differences in NO2 concentrations were found among the cities in different microenvironments. During the sampling period, volunteers spent 85% of their time indoors. The highest personal NO2 concentration was found when volunteers kept their windows closed (p = 0.03). In the regression model adjusted by city and gender, the best predictors of personal NO2 concentration were outdoor levels and time spent outdoors (R2 = 0.68). These findings suggest that outdoor NO2 concentrations were an important influence on the personal exposure to NO2, due to the specific characteristics and personal behavior of the people in these Mexican cities.     

Assessing the relationship between personal particulate and gaseous exposures of senior citizens living in Baltimore, MD

We conducted a multi-pollutant exposure study in Baltimore, MD, in which 15 non-smoking older adult subjects (> 64 years old) wore a multi-pollutant sampler for 12 days during the summer of 1998 and the winter of 1999. The sampler measured simultaneous 24-hr integrated personal exposures to PM2.5, PM10, SO4(2-), O3, NO2, SO2, and exhaust-related VOCs. Results of this study showed that longitudinal associations between ambient PM2.5 concentrations and corresponding personal exposures tended to be high in the summer (median Spearman's r = 0.74) and low in the winter (median Spearman's r = 0.25). Indoor ventilation was an important determinant of personal PM2.5 exposures and resulting personal-ambient associations. Associations between personal PM2.5 exposures and corresponding ambient concentrations were strongest for well-ventilated indoor environments and decreased with ventilation. This decrease was attributed to the increasing influence of indoor PM2.5 sources. Evidence for this was provided by SO4(2-) measurements, which can be thought of as a tracer for ambient PM2.5. For SO4(2-), personal-ambient associations were strong even in poorly ventilated indoor environments, suggesting that personal exposures to PM2.5 of ambient origin are strongly associated with corresponding ambient concentrations. The results also indicated that the contribution of indoor PM2.5 sources to personal PM2.5 exposures was lowest when individuals spent the majority of their time in well-ventilated indoor environments. Results also indicate that the potential for confounding by PM2.5 co-pollutants is limited, despite significant correlations among ambient pollutant concentrations. In contrast to ambient concentrations, PM2.5 exposures were not significantly correlated with personal exposures to PM2.5-10, PM2.5 of non-ambient origin, O3, NO2, and SO2. Since a confounder must be associated with the exposure of interest, these results provide evidence that the effects observed in the PM2.5 epidemiologic studies are unlikely to be due to confounding by the PM2.5 co-pollutants measured in this study.     

Determinants of indoor and personal exposure to PM2.5 of indoor and outdoor origin during the RIOPA study

Effects of physical/environmental factors on fine particle (PM_2.5) exposure, outdoor-to-indoor transport and air exchange rate (AER) were examined. The fraction of ambient PM_2.5 found indoors (F_INF) and the fraction to which people are exposed (α) modify personal exposure to ambient PM_2.5. Because F_INF, α, and AER are infrequently measured, some have used air conditioning (AC) as a modifier of ambient PM_2.5 exposure. We found no single variable that was a good predictor of AER. About 50% and 40% of the variation in F_INF and α, respectively, was explained by AER and other activity variables. AER alone explained 36% and 24% of the variations in F_INF and α, respectively. Each other predictor, including Central AC Operation, accounted for less than 4% of the variation. This highlights the importance of AER measurements to predict F_INF and α. Evidence presented suggests that outdoor temperature and home ventilation features affect particle losses as well as AER, and the effects differ.Total personal exposures to PM_2.5 mass/species were reconstructed using personal activity and microenvironmental methods, and compared to direct personal measurement. Outdoor concentration was the dominant predictor of (partial R² = 30–70%) and the largest contributor to (20–90%) indoor and personal exposures for PM_2.5 mass and most species. Several activities had a dramatic impact on personal PM_2.5 mass/species exposures for the few study participants exposed to or engaged in them, including smoking and woodworking. Incorporating personal activities (in addition to outdoor PM_2.5) improved the predictive power of the personal activity model for PM_2.5 mass/species; more detailed information about personal activities and indoor sources is needed for further improvement (especially for Ca, K, OC). Adequate accounting for particle penetration and persistence indoors and for exposure to non-ambient sources could potentially increase the power of epidemiological analyses linking health effects to particulate exposures.     

Indoor particle size distributions in homes with open fires and improved Patsari cook stoves

Particulate pollution has been clearly linked with adverse health impacts from open fire cookstoves, and indoor air concentrations are frequently used as a proxy for exposures in health studies. Implicit are the assumptions that the size distributions for the open fire and improved stove are not significantly different, and that the relationship between indoor concentrations and personal exposures is the same between stoves. To evaluate the impact of these assumptions size distributions of particulate matter in indoor air were measured with the Sioutas cascade impactor in homes using open fires and improved Patsari stoves in a rural Purepecha community in Michoacan, Mexico. On average indoor concentrations of particles less than 0.25 μm were 72% reduced in homes with improved Patsari stoves, reflecting a reduced contribution of this size fraction to PM_2.5 mass concentrations from 68% to 48%. As a result the mass median diameter of indoor PM_2.5 particulate matter was increased by 29% with the Patsari improved stove compared to the open fire (from 0.42 μm to 0.59 μm, respectively). Personal PM_2.5 exposure concentrations for women in homes using open fires were approximately 61% of indoor concentration levels (156 μg m^?3 and 257 μg m^?3 respectively). In contrast personal exposure concentrations were 77% times indoor air concentration levels for women in homes using improved Patsari stoves (78 μg m^?3and 101 μg m^?3 respectively). Thus, if indoor air concentrations are used in health and epidemiologic studies significant bias may result if the shift in size distribution and the change in relationship between indoor air concentrations and personal exposure concentrations are not accounted for between different stove types.