Article

PM 2.5 of Ambient Origin: Estimates and Exposure Errors Relevant to PM Epidemiology

Department of Environmental Sciences, Rutgers, The State University of New Jersey, Нью-Брансуик, New Jersey, United States
Environmental Science and Technology (Impact Factor: 5.33). 08/2005; 39(14):5105-12. DOI: 10.1021/es048226f
Source: PubMed

ABSTRACT

Epidemiological studies routinely use central-site particulate matter (PM) as a surrogate for exposure to PM of ambient (outdoor) origin. Below we quantify exposure errors that arise from variations in particle infiltration to aid evaluation of the use of this surrogate, rather than actual exposure, in PM epidemiology. Measurements from 114 homes in three cities from the Relationship of Indoor, Outdoor and Personal Air (RIOPA) study were used. Indoor PM2.5 of outdoor origin was calculated as follows: (1) assuming a constant infiltration factor, as would be the case if central-site PM were a "perfect surrogate" for exposure to outdoor particles; (2) including variations in measured air exchange rates across homes; (3) also incorporating home-to-home variations in particle composition, and (4) calculating sample-specific infiltration factors. The final estimates of PM2.5 of outdoor origin take into account variations in building construction, ventilation practices, and particle properties that result in home-to-home and day-to-day variations in particle infiltration. As assumptions became more realistic (from the first, most constrained model to the fourth, least constrained model), the mean concentration of PM2.5 of outdoor origin increased. Perhaps more importantly, the bandwidth of the distribution increased. These results quantify several ways in which the use of central site PM results in underestimates of the ambient PM2.5 exposure distribution bandwidth. The result is larger uncertainties in relative risk factors for PM2.5 than would occur if epidemiological studies used more accurate exposure measures. In certain situations this can lead to bias.

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    • ") (Chen and Zhao, 2011and references therein;Diapouli et al., 2013and references therein). These studies have demonstrated that there is substantial between-and within-home variability in (Ozkaynak et al., 1997;Ott et al., 2000;Meng et al., 2005;Weisel et al., 2005;Polidori et al., 2006;Allen et al., 2012;MacNeil et al., 2012;Hänninen et al., 2013;Kearny et al., 2014), illustrating the difficulty in utilizing measured values of to estimate contributions of ambient PM 2.5 to cumulative indoor intake. In addition, most studies are limited in their geographic and temporal scope and cannot be generalized to a broader population of homes. "
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    ABSTRACT: Exposure to fine particulate matter (PM2.5 ) is a major contributor to the global human disease burden. The indoor environment is of particular importance when considering the health effects associated with PM2.5 exposures because people spend the majority of their time indoors and PM2.5 exposures per unit mass emitted indoors are two to three orders of magnitude larger than exposures to outdoor emissions. Variability in indoor PM2.5 intake fraction (iFin,total ), which is defined as the integrated cumulative intake of PM2.5 per unit of emission, is driven by a combination of building-specific, human-specific, and pollutant-specific factors. Due to a limited availability of data characterizing these factors, however, indoor emissions and intake of PM2.5 are not commonly considered when evaluating the environmental performance of product life cycles. With the aim of addressing this barrier, a literature review was conducted and data characterizing factors influencing iFin,total were compiled. In addition to providing data for the calculation of iFin,total in various indoor environments and for a range geographic regions, this paper discusses remaining limitations to the incorporation of PM2.5 -derived health impacts into life cycle assessments and makes recommendations regarding future research. This article is protected by copyright. All rights reserved.
    No preview · Article · Nov 2015 · Indoor Air
    • "Modeling derived from basic mass balance equation is most frequently used to obtain the static F inf estimates, given that it utilizes data that represent real conditions. For example, gravimetric measurements of PM 2.5 mass concentrations over a given time period were incorporated as input into Random Component Superposition (RCS) model to obtain community-scale F inf estimates in both the RIOPA and EXPOLIS studies (Hanninen et al., 2004, 2013; Meng et al., 2005b). Concerning that the potential large inter-home variability of F inf may lead to PM exposure misclassification and inaccurate health risk estimates (Hystad et al., 2009; Hodas et al., 2012; Zhou et al., 2013), the recursive models that utilize real-time data were applied to yield F inf estimates for single homes (Long et al., 2001; Allen et al., 2003; Bennett and Koutrakis, 2006). "
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    ABSTRACT: Ambient fine particulate matter (PM2.5) pollution is currently a major public health concern in Chinese urban areas. However, assessment of ambient PM2.5 exposure and its health effects is challenging in China because the exposure primarily occurs indoors. There is large inter-home variability of the fraction of ambient PM2.5 that penetrates indoors and remains airborne (Finf), and the factors influencing this variability are unknown. In this study, 24-h real-time indoor and outdoor PM2.5 mass concentrations were concurrently collected for 41 urban residences in the non-heating season. The Finf were estimated with steady-state and dynamic models derived from mass balance considerations. Multivariate statistical analyses were employed to examine the associations between Finf and 78 factors related to building characteristics, motor vehicle traffic, human behavior, meteorology, furnishings, and atmospheric/indoor chemistry. The estimate of Finf over the 24-h monitoring period with the steady-state model was 0.72 ± 0.01; the Finf estimate for single residences, using the dynamic model, were 0.59 ± 0.13 (N = 33). Two predictive models for Finf were constructed with categorical and numerical variables, respectively. The results revealed that building characteristics, traffic, wall and floor coverings, and human behavior had substantial influence on Finf in the non-heating season. The variance contributions of the determinants of traffic, wall and floor coverings, and human behavior were comparable to or even greater than those of the building characteristics.
    No preview · Article · Oct 2015 · Atmospheric Pollution Research
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    • "One possible explanation for this observation is that the use of sulfur as a tracer does not account for changes in PM 2.5 properties that result from indoor– outdoor transport (Meng et al., 2005; Polidori et al., 2006). In particular, sulfur would not reflect losses of volatile or semivolatile components of PM that tend to partition to the gas-phase when entering an indoor environment (Lunden et al., 2003). "
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    ABSTRACT: Unlabelled: Indoor fine particles (FPs) are a combination of ambient particles that have infiltrated indoors, and particles that have been generated indoors from activities such as cooking. The objective of this paper was to estimate the infiltration factor (Finf ) and the ambient/non-ambient components of indoor FPs. To do this, continuous measurements were collected indoors and outdoors for seven consecutive days in 50 non-smoking homes in Halifax, Nova Scotia in both summer and winter using DustTrak (TSI Inc) photometers. Additionally, indoor and outdoor gravimetric measurements were made for each 24-h period in each home, using Harvard impactors (HI). A computerized algorithm was developed to remove (censor) peaks due to indoor sources. The censored indoor/outdoor ratio was then used to estimate daily Finfs and to determine the ambient and non-ambient components of total indoor concentrations. Finf estimates in Halifax (daily summer median = 0.80; daily winter median = 0.55) were higher than have been reported in other parts of Canada. In both winter and summer, the majority of FP was of ambient origin (daily winter median = 59%; daily summer median = 84%). Predictors of the non-ambient component included various cooking variables, combustion sources, relative humidity, and factors influencing ventilation. This work highlights the fact that regional factors can influence the contribution of ambient particles to indoor residential concentrations. Practical implications: Ambient and non-ambient particles have different risk management approaches, composition, and likely toxicity. Therefore, a better understanding of their contribution to the indoor environment is important to manage the health risks associated with fine particles (FPs) effectively. As well, a better understanding of the factors Finf can help improve exposure assessment and contribute to reduced exposure misclassification in epidemiologic studies.
    Full-text · Article · Dec 2013 · Indoor Air
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