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FURTHER REFINEMENTS AND TESTING OF APEX3.0: EPA'S POPULATION EXPOSURE MODEL FOR CRITERIA AND AIR TOXIC INHALATION
Citation:
Richmond, H M., T. Palma, J. Langstaff, T R. McCurdy, G. Glenn, AND L. Smith. FURTHER REFINEMENTS AND TESTING OF APEX3.0: EPA'S POPULATION EXPOSURE MODEL FOR CRITERIA AND AIR TOXIC INHALATION. Presented at International Society of Exposure Analysis, Vancouver, Canada, August 11-15, 2002.
Impact/Purpose:
The two main objectives of this research are (1) to improve and update and (2) to analyze the CHAD database.
For objective 1, we will
* Reconfigure the CHAD program into a completely modularized Oracle database.
* Redesign User Interface for effcient utilization of the program's capability.
* Obtain dates for those surveys that did not provide them to us, so that we can obtain associated meteorological/climatic inputs for the person-days of information without them.
* Revise the upper and lower bound delimiters in the energy expenditure distributions used for activity-specific estimates.
For objective 2, we will
* Evaluate data quality.
* Evaluate trends and activities for various subgroups.
* Identify temporal patterns for longitudinal data.
* Characterize resolution required for output for exposure and dose models.
Description:
The Air Pollutants Exposure Model (APEX(3.0)) is a PC-based model that was derived from the probabilistic NAAQS Exposure Model for carbon monoxide (pNEM/CO). APEX will be one of the tools used to estimate human population exposure for criteria and air toxic pollutants as part of EPA's overall Total Risk Integrated Methodology (TRIM) model framework. The U.S. Environmental Protection Agency (EPA) has made further revisions to APEX over the past year. The model is intended to be applied at the local or urban scale and currently only addresses inhalation exposures. The model simulates the movement of individuals through time and space and their exposure to the given pollutant in indoor, outdoor, and in-vehicle microenvironments. The model has been made flexible so that various pollutants can be analyzed by inputting appropriate pollutant-specific information. The user may choose the number and types of microenvironments to be included, select the time period of interest, use either monitored ambient data or values provided from dispersion or other modeling runs, and use either a mass balance approach or an empirical ratio based approach to estimate indoor or in-vehicle concentrations.
The main exposure program stochastically generates simulated individuals using census-derived probability distributions for the demographic variables. Each such individual is assigned a series of time-activity diaries that are matched on the day type, temperature, age, gender, employment status, and optionally on other variables. The model then estimates the sequence of pollutant exposures for that individual, along with inhaled dose and (for CO only) the sequence of blood carboxyhemoglobin levels. Any number of simulated individuals can be modeled, and collectively they represent a random sample of the study area population. The model output is typically summarized into the number and percentage of person-days of exposure over various concentration cutpoints.
A number of enhancements have been made in this latest version of APEX. These include: (1) allowing for finer geographical units such as census tracts and automatically assigning population to the nearest monitor with a cutoff distance, (2) allowing exposure district specific temperatures to be specified, (3) allowing the user to select the variables that affect each parameter (e.g., the air exchange rate parameter in certain indoor microenvironments may depend on air conditioning status or window position), and (4) enhancing the mass balance algorithms to allow window position or vehicle speed to be considered in determining air exchange rate values. This poster will discuss these enhancements as well as EPA's plans to apply this modeling tool to estimate CO exposures in the Los Angeles urban area and compare the results with pNEM/CO estimates for this same area.
Any opinions, findings, conclusions, or recommendations are those of the authors and do not necessarily reflect the views of the U.S. Environmental Protection Agency or ManTech Environmental Technology, Inc.. This work has been supported by EPA under Contract No. OD-6260-NALX.