PM2.5 of ambient origin: estimates and exposure errors relevant to PM epidemiology.

Department of Environmental Sciences, Rutgers University, 14 College Farm Road, New Brunswick, New Jersey 08901, USA.
Environmental Science and Technology (Impact Factor: 5.26). 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.

  • [Show abstract] [Hide abstract]
    ABSTRACT: In this study, single-particle characterization of aerosol particles collected at an underground shopping area was performed for the first time. A quantitative single-particle analytical technique, low-Z particle electron probe X-ray microanalysis, was used to characterize a total of 7900 individual particles for eight sets of aerosol samples collected at an underground shopping area in Seoul, Korea. Based on secondary electron images and X-ray spectral data of individual particles, fourteen particle types were identified, in which primary soil-derived particles were the most abundant, followed by carbonaceous, Fe-containing, secondary soil-derived, and secondary sea-salt particles. Carbonaceous particles exist in three types: organic carbon, carbon-rich, and CNO-rich. A significant number of textile particles with chemical composition C, N, and O were encountered in some of the aerosol samples, which were from the textile shops and/or from clothes of passersby. Primary soil-derived particles showed seasonal variation, with peak values in spring samples, reflecting higher air exchange between indoor and outdoor environments in the spring. Secondary soil-derived, secondary sea-salt, and ammonium sulfate particles were frequently encountered in winter samples. Fe-containing particles, contributed from a nearby subway station, were in the range of about 19% relative abundances for all samples. PRACTICAL IMPLICATIONS: In underground shopping areas, particulate matters can be a considerable health hazard to the workers, shoppers, passersby, and shop-keepers as they spend their considerable time in this closed microenvironment. However, no study on the characteristics of indoor aerosols in an underground shopping area has been reported to our knowledge. This work provides detailed information on characteristics of underground shopping area aerosols on a single particle level.
    Indoor Air 02/2011; 21(1):12-24. · 3.30 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Epidemiological studies frequently use central site concentrations as surrogates of exposure to air pollutants. Variability in air pollutant infiltration due to differential air exchange rates (AERs) is potentially a major factor affecting the relationship between central site concentrations and actual exposure, and may thus influence observed health risk estimates. In this analysis, we examined AER as an effect modifier of associations between several urban air pollutants and corresponding emergency department (ED) visits for asthma and wheeze during a 4-year study period (January 1999-December 2002) for a 186 ZIP code area in metro Atlanta. We found positive associations for the interaction between AER and pollution on asthma ED visits for both carbon monoxide (CO) and nitrogen oxides (NOx), indicating significant or near-significant effect modification by AER on the pollutant risk-ratio estimates. In contrast, the interaction term between particulate matter (PM)2.5 and AER on asthma ED visits was negative and significant. However, alternative distributional tertile analyses showed PM2.5 and AER epidemiological model results to be similar to those found for NOx and CO (namely, increasing risk ratios (RRs) with increasing AERs when ambient PM2.5 concentrations were below the highest tertile of their distribution). Despite the fact that ozone (O3) was a strong independent predictor of asthma ED visits in our main analysis, we found no O3-AER effect modification. To our knowledge, our findings for CO, NOx, and PM2.5 are the first to provide an indication of short-term (i.e., daily) effect modification of multiple air pollution-related risk associations with daily changes in AER. Although limited to one outcome category in a single large urban locale, the findings suggest that the use of relatively simple and easy-to-derive AER surrogates may reflect intraurban differences in short-term exposures to pollutants of ambient origin.Journal of Exposure Science and Environmental Epidemiology advance online publication, 19 June 2013; doi:10.1038/jes.2013.32.
    Journal of Exposure Science and Environmental Epidemiology 06/2013; · 3.19 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Both classical and Berkson exposure measurement errors as encountered in environmental epidemiology data can result in biases in fitted exposure-response relationships that are large enough to affect the interpretation and use of the apparent exposure-response shapes in risk assessment applications. A variety of sources of potential measurement error exist in the process of estimating individual exposures to environmental contaminants, and the authors review the evaluation in the literature of the magnitudes and patterns of exposure measurement errors that prevail in actual practice. It is well known among statisticians that random errors in the values of independent variables (such as exposure in exposure-response curves) may tend to bias regression results. For increasing curves, this effect tends to flatten and apparently linearize what is in truth a steeper and perhaps more curvilinear or even threshold-bearing relationship. The degree of bias is tied to the magnitude of the measurement error in the independent variables. It has been shown that the degree of bias known to apply to actual studies is sufficient to produce a false linear result, and that although nonparametric smoothing and other error-mitigating techniques may assist in identifying a threshold, they do not guarantee detection of a threshold. The consequences of this could be great, as it could lead to a misallocation of resources towards regulations that do not offer any benefit to public health.
    Critical Reviews in Toxicology 09/2011; 41(8):651-71. · 6.25 Impact Factor

Full-text (2 Sources)

Available from
Jun 2, 2014