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USE OF REAL-TIME LIGHT SCATTERING DATA TO ESTIMATE THE CONTRIBUTION OF INFILTRATED AND INDOOR-GENERATED PARTICLES TO INDOOR AIR
Citation:
Allen, R., T. Larson, L. Sheppard, L A. Wallace, AND L. S. Liu. USE OF REAL-TIME LIGHT SCATTERING DATA TO ESTIMATE THE CONTRIBUTION OF INFILTRATED AND INDOOR-GENERATED PARTICLES TO INDOOR AIR. ENVIRONMENTAL SCIENCE & TECHNOLOGY 37(16):3484-3492, (2003).
Impact/Purpose:
The primary study objectives are:
1.To quantify personal exposures and indoor air concentrations for PM/gases for potentially sensitive individuals (cross sectional, inter- and intrapersonal).
2.To describe (magnitude and variability) the relationships between personal exposure, and indoor, outdoor and ambient air concentrations for PM/gases for different sensitive cohorts. These cohorts represent subjects of opportunity and relationships established will not be used to extrapolate to the general population.
3.To examine the inter- and intrapersonal variability in the relationship between personal exposures, and indoor, outdoor, and ambient air concentrations for PM/gases for sensitive individuals.
4.To identify and model the factors that contribute to the inter- and intrapersonal variability in the relationships between personal exposures and indoor, outdoor, and ambient air concentrations for PM/gases.
5.To determine the contribution of ambient concentrations to indoor air/personal exposures for PM/gases.
6.To examine the effects of air shed (location, season), population demographics, and residential setting (apartment vs stand-alone homes) on the relationship between personal exposure and indoor, outdoor, and ambient air concentrations for PM/gases.
Description:
The contribution of outdoor particulate matter (PM) to residential indoor concentrations is currently not well understood. Most importantly, separating indoor PM into indoor- and outdoor-generated components will greatly enhance our knowledge of the outdoor contribution to total indoor and personal PM exposures. This paper examines continuous light scattering data at 44 residences in Seattle, WA. A newly adapted recursive model was used to model outdoor-originated PM entering indoor environments. Non-linear regression was used to predict particle penetration (P, 0.94 +/- 0.10), air exchange rate (a, 0.54 +/- 0.60 hr-1), particle decay rate (k, 0.20 +/- 0.16 hr-1), and particle infiltration (Finf, 0.65 +/- 0.21) for each of the 44 residences. All of these parameters showed seasonal differences. The Finf estimates agree well with those estimated from the sulfur-tracer method (R2=0.78). The Finf estimates also showed robust and expected behavior when compared against known influencing factors. Among our study residences, outdoor-generated particles accounted for an average of 79 +/- 17% of the indoor PM concentration, with a range of 40 to 100% at individual residences. Although estimates of P, a, and k for individual residences may be unstable due to the limited capability of the non-linear model to simultaneously solve three unknowns, the recursive model provides a useful technique for estimating P and k in situations where air exchange rate can be measured.
The United States Environmental Protection Agency through its Office of Research and Development partially funded and collaborated in the research described here under assistance agreement number CR827177 to the University of Washington. It has been subjected to Agency review and approved for publication.