Description:
As research toward identifying the specific toxic agents of PM and the mechanisms that lead to health effects proceeds, an understanding of how people are exposed to these compounds and their levels of exposure is needed. 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. To accomplish this objective, the SHEDS (Stochastic Human Exposure and Dose Simulation) model developed previously for estimating population exposures to PM mass (PM10, PM2.5) will be modified and enhanced for application to the various components of PM. The SHEDS-PM model estimates the population distribution of PM exposures by simulating the time series of exposure and dose for individuals that demographically represent the user-defined population of interest. US Census data are used to build the simulation population, and human activity pattern data are assigned to each simulated individual to account for the way people interact with their environment. PM concentrations for the locations people spend time in are estimated based on relationships between ambient and microenvironmental (e.g., indoor, in vehicle) PM concentrations and source strengths obtained from measurement study data. Each simulated individual's exposure and dose profile is determined from the time spent in each location, the PM concentration in that location, and activity-specific inhalation rate while in that location. Daily-averaged exposure and dose for each individual are calculated and combined to provide a distribution of PM exposure and dose for the user-defined population. Statistical methods for incorporating both variability and uncertainty in the model input parameters are utilized to obtain the predicted population distribution of PM exposure and dose, and the uncertainty associated with those predicted distributions. Research activities will focus on enhancing the model and developing new model inputs and algorithms as needed for case study applications. This research effort will provide a population-oriented exposure model for PM constituents that can be linked to other models developed by ORD, including emissions-based atmospheric dispersion models developed by NERL (AMD) and respiratory tract dose models developed by NHEERL. The result will be a scientifically robust exposure modeling system for analyzing the relationship between the sources, ambient air concentrations, and personal exposures and dose for various PM constituents.
Keywords:
PARTICULATE MATTER, EXPOSURE, MODELING,
Project Information:
Progress
:This task began In FY02. Development of Version 2 of the SHEDS-PM model was initiated to allow for prediction of the population distribution of hourly-average total and ambient PM exposures. The model code was modified to calculate total and ambient PM exposures sequentially based on hourly input data, thereby producing a time series of exposures for each individual over a 24-hour period. This modification to the structure of the exposure calculation allowed for intake dose estimates to be incorporated in the SHEDS-PM model. Algorithms for estimating intake dose from hourly-average PM exposures and activity-specific ventilation rates were added to the model code. Extramural resources were used to develop appropriate input parameters for the hourly-average SHEDS-PM model (version 2). In addition to these refinements, the revised MATLAB code was provided to EOHSI under a University Partnership Agreement (cooperative agreement) and was incorporated in a prototype source-to-dose case study for PM2.5 and Ozone in Philadelphia, the results of which were described in a manuscript submitted for publication in FY03.
Development of Version 2 of the Stochastic Human Exposure and Dose Simulation model for particulate matter (SHEDS-PM) was completed in FY03. Significant progress was made toward making the model more flexible and user-friendly through the use of MATLAB software (extramural contract). A graphical user interface (GUI) was developed that allows the user to provide model inputs and select various model run options. The MATLAB platform was also used to create an executable version of the model for use on PCs without any software requirement. A User Guide was developed for the model that provides information on the model structure, navigation of the GUI screens, and descriptions of the input databases and model equations. This research has produced a user-friendly probabilistic exposure and dose model for PM that will allow the Office of Air and Radiation (OAR), EPA Regions and the States to estimate population exposures to PM by applying the model to available ambient PM monitoring data or model output for any US urban/metropolitan area (FY03 APM 19).
Relevance
:Development of the SHEDS-PM model for PM constituents under this task will provide a useful tool for estimating the range in PM exposure and/or dose across a population of interest, and the percentage of estimated exposures that exceed a certain level. Application of the SHEDS-PM model for PM constituents within a modeling system that incorporates air quality dispersion modeling and lung dosimetry modeling will provide EPA the capability to test the impact of changes in PM emissions on human exposures to PM constituents. EPA's Office of Air and Radiation, Regional Offices, and State agencies can use the SHEDS-PM model to estimate population exposures to PM using PM monitoring data or dispersion model output. SHEDS-PM also provides estimates of population exposures to PM of outdoor origin separately from exposures to indoor sources of PM, information critical for understanding personal exposures to PM but not available through monitoring approaches.
Clients
:ORD (NERL, NCEA), OAQPS, OTAQ, Regions, States, Academia (EPA PM Centers)
Project IDs:
ID Code
:12066
Project type
:OMIS