Modelling of indoor exposure to nitrogen dioxide in the UK

A dynamic multi-compartment computer model has been developed to describe the physical processes determining indoor pollutant concentrations as a function of outdoor concentrations, indoor emission rates and building characteristics. The model has been parameterised for typical UK homes and workplaces and linked to a time-activity model to calculate exposures for a representative homemaker, schoolchild and office worker, with respect to NO₂. The estimates of population exposures, for selected urban and rural sites, are expressed in terms of annual means and frequency of hours in which air quality standards are exceeded. The annual mean exposures are estimated to fall within the range of 5–21 ppb for homes with no source, and 21–27 ppb for homes with gas cooking, varying across sites and population groups. The contribution of outdoor exposure to annual mean NO₂ exposure varied from 5 to 24%, that of indoor penetration of outdoor air from 17 to 86% and that of gas cooking from 0 to 78%. The frequency of exposure to 1 h mean concentrations above 150 ppb was very low, except for people cooking with gas.     

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.     

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.     

Characterisation of urban inhalation exposures to benzene,formaldehyde and acetaldehyde in the European Union

BACKGROUND, AIM AND SCOPE: All across Europe, people live and work in indoor environments. On average, people spend around 90% of their time indoors (homes, workplaces, cars and public transport means, etc.) and are exposed to a complex mixture of pollutants at concentration levels that are often several times higher than outdoors. These pollutants are emitted by different sources indoors and outdoors and include volatile organic compounds (VOCs), carbonyls (aldehydes and ketones) and other chemical substances often adsorbed on particles. Moreover, legal obligations opposed by legislations, such as the European Union's General Product Safety Directive (GPSD) and Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH), increasingly require detailed understanding of where and how chemical substances are used throughout their life-cycle and require better characterisation of their emissions and exposure. This information is essential to be able to control emissions from sources aiming at a reduction of adverse health effects. Scientifically sound human risk assessment procedures based on qualitative and quantitative human exposure information allows a better characterisation of population exposures to chemical substances. In this context, the current paper compares inhalation exposures to three health-based EU priority substances, i.e. benzene, formaldehyde and acetaldehyde. MATERIALS AND METHODS: Distributions of urban population inhalation exposures, indoor and outdoor concentrations were created on the basis of measured AIRMEX data in 12 European cities and compared to results from existing European population exposure studies published within the scientific literature. By pooling all EU city personal exposure, indoor and outdoor concentration means, representative EU city cumulative frequency distributions were created. Population exposures were modelled with a microenvironment model using the time spent and concentrations in four microenvironments, i.e. indoors at home and at work, outdoors at work and in transit, as input parameters. Pooled EU city inhalation exposures were compared to modelled population exposures. The contributions of these microenvironments to the total daily inhalation exposure of formaldehyde, benzene and acetaldehyde were estimated. Inhalation exposures were compared to the EU annual ambient benzene air quality guideline (5 microg/m3-to be met by 2010) and the recommended (based on the INDEX project) 30-min average formaldehyde limit value (30 microg/m3). RESULTS: Indoor inhalation exposure contributions are much higher compared to the outdoor or in-transit microenvironment contributions, accounting for almost 99% in the case of formaldehyde. The highest in-transit exposure contribution was found for benzene; 29.4% of the total inhalation exposure contribution. Comparing the pooled AIRMEX EU city inhalation exposures with the modelled exposures, benzene, formaldehyde and acetaldehyde exposures are 5.1, 17.3 and 11.8 microg/m3 vs. 5.1, 20.1 and 10.2 microg/m3, respectively. Together with the fact that a dominating fraction of time is spent indoors (>90%), the total inhalation exposure is mostly driven by the time spent indoors. DISCUSSION: The approach used in this paper faced three challenges concerning exposure and time-activity data, comparability and scarce or missing in-transit data inducing careful interpretation of the results. The results obtained by AIRMEX underline that many European urban populations are still exposed to elevated levels of benzene and formaldehyde in the inhaled air. It is still likely that the annual ambient benzene air quality guideline of 5 microg/m3 in the EU and recommended formaldehyde 30-min average limit value of 30 microg/m3 are exceeded by a substantial part of populations living in urban areas. Considering multimedia and multi-pathway exposure to acetaldehyde, the biggest exposure contribution was found to be related to dietary behaviour rather than to inhalation. CONCLUSIONS: In the present study, inhalation exposures of urban populations were assessed on the basis of novel and existing exposure data. The indoor residential microenvironment contributed most to the total daily urban population inhalation exposure. The results presented in this paper suggest that a significant part of the populations living in European cities exceed the annual ambient benzene air quality guideline of 5 microg/m3 in the EU and recommended (INDEX project) formaldehyde 30-min average limit value of 30 microg/m3. RECOMMENDATIONS AND PERSPECTIVES: To reduce exposures and consequent health effects, adequate measures must be taken to diminish emissions from sources such as materials and products that especially emit benzene and formaldehyde in indoor air. In parallel, measures can be taken aiming at reducing the outdoor pollution contribution indoors. Besides emission reduction, mechanisms to effectively monitor and manage the indoor air quality should be established. These mechanisms could be developed by setting up appropriate EU indoor air guidelines.     

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.     

Outdoor/Indoor/Personal ozone exposures of children in Nashville, Tennessee

An ozone (O3) exposure study was conducted in Nashville, TN, using passive O3 samplers to measure six weekly outdoor, indoor, and personal O3 exposure estimates for a group of 10- to 12-yr-old elementary school children. Thirty-six children from two Nashville area communities (Inglewood and Hendersonville) participated in the O3 sampling program, and 99 children provided additional time-activity information by telephone interview. By design, this study coincided with the 1994 Nashville/Middle Tennessee Ozone Study conducted by the Southern Oxidants Study, which provided enhanced continuous ambient O3 monitoring across the Nashville area. Passive sampling estimated weekly average outdoor O3 concentrations from 0.011 to 0.O30 ppm in the urban Inglewood community and from 0.015 to 0.042 ppm in suburban Hendersonville. The maximum 1- and 8-hr ambient concentrations encountered at the Hendersonville continuous monitor exceeded the levels of the 1- and 8-hr metrics for the O3 National Ambient Air Quality Standard. Weekly average personal O3 exposures ranged from 0.0013 to 0.0064 ppm (7-31% of outdoor levels). Personal O3 exposures reflected the proportional amount of time spent in indoor and outdoor environments. Air-conditioned homes displayed very low indoor O3 concentrations, and homes using open windows and fans for ventilation displayed much higher concentrations.     

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.     

Personal exposures to particles and their relationships with personal activities for chronic obstructive pulmonary disease patients living in Boston

An exposure study of 18 subjects with chronic obstructive pulmonary disease (COPD) living in the Boston, MA, area was conducted. The objective was to examine determinants of personal exposures to particulate matter (PM) with aerodynamic diameters of less than 2.5 microm (PM2.5), less than 10 microm (PM10), and between 2.5 and 10 microm (PM2.5-10). In a previous publication, the analyses of the longitudinal individual-specific relationships among indoor, outdoor, and personal levels showed that the relationships varied by subject and by particle size fraction. In the present paper, statistical and physical models were used to examine personal PM2.5, PM10, and PM2.5-10 exposure covariates. Results indicated that time-weighted indoor concentrations were significant predictors of personal PM2.5, PM10, and PM2.5-10 exposures. Also, time-weighted outdoor concentrations, time spent near smokers, and time spent during transportation were important predictors for PM2.5 but not for personal PM2.5-10 exposures. In turn, time spent cleaning contributed to all size-fraction personal exposures, whereas cooking affected only personal PM2.5-10 exposures. The findings showed that the relationship between personal PM2.5 exposures and the corresponding ambient concentrations was influenced by home air exchange rates (or by ventilation status). Because the particle properties or components causing the health effects are unknown, it is not certain to what extent the risk posed by ambient particles can be reduced by controlling any one of these factors.     

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.     

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.     

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.     

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.     

Predicting personal exposure to airborne carbonyls using residential measurements and time/activity data

As a part of the Relationships of Indoor, Outdoor, and Personal Air (RIOPA) study, 48 h integrated residential indoor, outdoor, and personal exposure concentrations of 10 carbonyls were simultaneously measured in 234 homes selected from three US cities using the Passive Aldehydes and Ketones Samplers (PAKS). In this paper, we examine the feasibility of using residential indoor concentrations to predict personal exposures to carbonyls. Based on paired t-tests, the means of indoor concentrations were not different from those of personal exposure concentrations for eight out of the 10 measured carbonyls, indicating indoor carbonyls concentrations, in general, well predicted the central tendency of personal exposure concentrations. In a linear regression model, indoor concentrations explained 47%, 55%, and 65% of personal exposure variance for formaldehyde, acetaldehyde, and hexaldehyde, respectively. The predictability of indoor concentrations on cross-individual variability in personal exposure for the other carbonyls was poorer, explaining<20% of variance for acetone, acrolein, crotonaldehyde, and glyoxal. A factor analysis, coupled with multiple linear regression analyses, was also performed to examine the impact of human activities on personal exposure concentrations. It was found that activities related to driving a vehicle and performing yard work had significant impacts on personal exposures to a few carbonyls.     

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.     

Sources of personal exposure to fine particles in Toronto, Ontario, Canada

Individuals are exposed to particulate matter from both indoor and outdoor sources. The aim of this study was to compare the relative contributions of three sources of personal exposure to fine particles (PM2.5) by using chemical tracers. The study design incorporated repeated 24-hr personal exposure measurements of air pollution from 28 cardiac-compromised residents of Toronto, Ontario, Canada. Each study participant wore the Rupprecht & Patashnick ChemPass Personal Sampling System 1 day a week for a maximum of 10 weeks. During their individual exposure measurement days the subjects reported to have spent an average of 89% of their time indoors. Particle phase elemental carbon, sulfate, and calcium personal exposure data were used in a mixed-effects model as tracers for outdoor PM2.5 from traffic-related combustion, regional, and local crustal materials, respectively. These three sources were found to contribute 13% +/- 10%, 17% +/- 16%, and 7% +/- 6% of PM2.5 exposures. The remaining fraction of the personal PM2.5 is hypothesized to be predominantly related to indoor sources. For comparison, central site outdoor PM2.5 measurements for the same dates as personal measurements were used to construct a receptor model using the same three tracers. In this case, traffic-related combustion, regional, and local crustal materials were found to contribute 19% +/- 17%, 52% +/- 22%, and 10% +/- 7%, respectively. Our results indicate that the three outdoor PM2.5 sources considered are statistically significant contributors to personal exposure to PM2.5. Our results also suggest that among the Toronto subjects, who spent a considerable amount of time indoors, exposure to outdoor PM2.5 includes a greater relative contribution from combustion sources compared with outdoor PM2.5 measurements where regional sources are the dominant contributor.     

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.     

Estimating distributions of long-term particulate matter and manganese exposures for residents of Toronto,Canada

Methylcyclopentadienyl manganese tricarbonyl (MMT), a manganese-based gasoline additive, has been used in Canadian gasoline for about 20 yr. Because MMT potentially increases manganese levels in particulate matter resulting from automotive exhausts, a population-based study conducted in Toronto, Canada assessed the levels of personal manganese exposures. Integrated 3-day particulate matter (PM_2.5) exposure measurements, obtained for 922 participant periods over the course of a year (September 1995–August 1996), were analyzed for several constituent elements, including Mn. The 922 measurements included 542 participants who provided a single 3-day observation plus 190 participants who provided two observations (in two different months). In addition to characterizing the distributions of 3-day average exposures, which can be estimated directly from the data, including the second observation for some participants enabled us to use a model-based approach to estimate the long-term (i.e. annual) exposure distributions for PM_2.5 mass and Mn. The model assumes that individuals’ 3-day average exposure measurements within a given month are lognormally distributed and that the correlation between 3-day log-scale measurements k months apart (after seasonal adjustment) depends only on the lag time, k, and not on the time of year. The approach produces a set of simulated annual exposures from which an annual distribution can be inferred using estimated correlations and monthly means and variances (log scale) as model inputs. The model appeared to perform reasonably well for the overall population distribution of PM_2.5 exposures (mean=28 μg m^-3). For example, the model predicted the 95th percentile of the annual distribution to be 62.9 μg m^-3 while the corresponding percentile estimated for the 3-day data was 86.6 μg m^-3. The assumptions of the model did not appear to hold for the overall population of Mn exposures (mean=13.1 ng m^-3). Since the population included persons who were potentially occupationally exposed to Mn (in non-vehicle-related jobs), we used responses to questionnaire items to form a subgroup consisting of non-occupationally exposed participants (671 participant periods), for which the model assumptions did appear to hold. For that subpopulation (mean=9.2 ng m^-3), the model-predicted 95th percentile of the annual Mn distribution was 16.3-ng m^-3, compared with 21.1 ng m^-3 estimated for the 3-day data.     

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.