Citation:

Burke, J M. POPULATION-BASED EXPOSURE MODELING FOR AIR POLLUTANTS AT EPA'S NATIONAL EXPOSURE RESEARCH LABORATORY. Presented at EPA Region 1 Air Programs Office, Boston, MA, May 5, 2004.

Impact/Purpose:

The overall objective of this research is to develop, apply, and evaluate a human exposure model for predicting population exposures to the components of particulate matter (PM) identified as potential toxic agents contributing to adverse health effects.

Description:

The US EPA's National Exposure Research Laboratory (NERL) has been developing, applying, and evaluating population-based exposure models to improve our understanding of the variability in personal exposure to air pollutants. Estimates of population variability are needed for EPA to assess what populations are at risk for adverse health outcomes due to air pollutant exposures. Two primary research questions are being addressed: (a) what proportion of the population of interest may be exposed to air pollutant levels where health risks are of concern, and (b) what are the important factors driving the variability in population exposures, and therefore risks. Estimating the uncertainty associated with the findings for these questions is also a key objective of this research.

The Stochastic Human Exposure and Dose Simulation (SHEDS) model has been developed by NERL for addressing these research questions. The SHEDS model is similar in structure to EPA's Hazardous Air Pollutant Exposure Model (HAPEM) used by OAQPS in the National Air Toxics Assessment (NATA). These models estimate population distributions of exposures by simulating the time series of exposure for individuals that demographically represent a user-defined population of interest. US Census demographic data are used to randomly select individuals from the population, and human activity pattern data are randomly assigned to each simulated individual to account for the way people interact with their environment. The differences between these models are primarily in the level of detail and spatial/temporal resolution used in the model calculations. In addition, the SHEDS model utilizes statistical methods for incorporating both variability and uncertainty in the model inputs, and can therefore provide estimates of the uncertainty associated with the model predictions.

The SHEDS model has been applied to particulate matter (PM) and to air toxics using initial case studies that provided information on the impact of different source types (outdoor sources and indoor sources) on exposures for these pollutants, as well as the influence of exposure factors such as the time people spend in various locations (e.g. home, outdoors, in vehicle, workplace, school) and the physical activity level while in those locations. Inhalation exposure to PM2.5 for the population of Philadelphia was investigated using the SHEDS-PM model, and benzene exposure through multiple routes (inhalation, ingestion, dermal) for the Houston population is currently being assessed using the SHEDS-Air Toxics model. Additional PM and air toxics case studies that can address EPA's exposure assessment and risk assessment needs using available data sets would be beneficial for further testing and evaluation of the SHEDS model.

Although this work was reviewed by EPA and approved for publication, it may not necessarily reflect official Agency policy

Record Details: