Lead Human Exposure and Health Risk Assessments for Selected ...

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2.4.4.1 Exposure Assessment
Concentrations of Pb are estimated in ambient media and indoor dust using a
combination of empirical data and modeling projections. The use of empirical data brings with it
uncertainty related to the potential inclusion of background source signals in these measurements
(e.g., house paint contributions to indoor dust and outdoor soil Pb). Conversely, the use of
modeling tools introduces other uncertainties (e.g., model and parameter uncertainties). Both of
these uncertainties are recognized in Section 4.3. Specific approaches used at the three case
study locations are briefly described below.
Characterization of Pb in ambient air relies on (a) dispersion modeling of stack and
fugitive emissions for the primary and secondary Pb smelter case studies and (b) the use of
ambient monitor data for the urban case study. For the urban case study, monitoring data for
U.S. urban areas of more than a million in population were used to identify two current
conditions scenarios, one “typical”, and one higher-end, and to relate alternate NAAQS (of other
forms) to annual average levels needed for blood Pb modeling. A key aspect of the general
urban case study is that ambient air lead levels do not vary spatially within the study area. The
approach is monitor-based rather than source-based as compared to two point source case
studies. This means that we did not explicitly model specific source contributions for the urban
case study (e.g., resuspension of roadside dust, “fresh” industrial emissions) and instead, relied
on empirical data to define ambient air Pb levels for this general case study, with these levels
reflecting contributions from all contributing sources, be they currently active stationary or
mobile sources, resuspension of previously deposited Pb or other.
Characterization of Pb concentrations in outdoor surface soil/dust, resulting from
deposition of air-borne Pb is based on the use of (a) existing site-specific measurements (primary
Pb smelter case study), (b) nationally representative residential soil measurements obtained from
the literature (general urban case )study and (c) fate and transport modeling (secondary Pb
smelter case study). In the case of the primary Pb smelter case study, soil Pb concentration data
were available for a zone close to the facility and statistical extrapolation from the available
empirical data was used to predict soil levels for portions of the study area beyond this zone.
To predict concentrations of ambient Pb in indoor dust, we have relied on a combination
of (a) regression-based models that relate indoor dust to outdoor air Pb and/or outdoor soil Pb
and (b) mechanistic models that predict indoor dust Pb based on key mechanisms (e.g., exchange
of outdoor air with indoor air, deposition rates of Pb to indoor surfaces, house cleaning rates).
For both point source case studies, a combination of regression-based models obtained from the
literature and developed based on site-specific data were used, and a customized hybrid
July 2007 2-30 Draft – Do Not Quote or Cite