You are here:
Evaluating the All-Ages Lead Model Using SiteSpecific Data: Approaches and Challenges
Citation:
McLanahan, E., L. Wilder, K. Scruton, K. Bradham, AND R. Worley. Evaluating the All-Ages Lead Model Using SiteSpecific Data: Approaches and Challenges. 2015 SOT Conference, New Orleans, New Orleans, LA, March 13 - 17, 2016.
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA mission to protect human health and the environment. HEASD research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Description:
Lead (Pb) exposure continues to be a problem in the United States. Even after years of progress in reducing environmental levels, CDC estimates at least 500,000 U.S. children ages 1-5 years have blood Pb levels (BLL) above the CDC reference level of 5 µg/dL. Childhood Pb exposure is associated with neurological consequences and public health professionals continue to work to reduce Pb exposures. To better understand the relationship between exposure and BLL, the USEPA has developed a beta version of the All-Ages Lead Model (AALM). Compared to the Integrated Exposure Uptake Biokinetics (IEUBK) Model for lead in children, the AALM provides greater flexibility to describe Pb exposures (acute or chronic, constant or intermittent) for any age. At this time, the AALM has the capability to predict exposure in each of the following media: dust/soil, water, air, food, and other. As part of an interagency test group, we evaluated the ability of the AALM beta v4.2 (Leggett version) to predict BLLs for children that were exposed to Pb in their environment near the John T. Lewis and Bros Lead Smelter Superfund site. The model predicted that fourteen children met our inclusion criteria that spent less than 20 hours a week away from the home (e.g., no daycare or school) and had paired BLL and environmental sampling data (i.e., Pb in soil, window sill dust, front door dust, floor dust, and drinking water). The model can predict average BLLs, but it remains difficult to predict individual level BLLs due to a number of uncertainties associated with characterizing lead exposures.
