API PUBL 4617-1995

$25.35

A Monte Carlo Approach to Generating Equivalent Ventilation Rates in Population Exposure Assessments

Published By	Publication Date	Number of Pages
API	1995	163

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Description

A number of researchers have developed computer-based models for simulating the exposure of human populations to air pollution. The probabilistic version of the National Ambient Air Quality Standards Exposure Model (pNEM) is typical of these models in that it characterizes each exposure by time period and pollutant concentration. Unlike most other exposure models, pNEM also characterizes each exposure by a measure of respiration, the equivalent ventilation rate (EVR). EVR is defined as ventilation rate divided by body surface area. In the current version of pNEM, EVR is determined by an algorithm that randomly selects values from Iognormal distributions that are specific to age and breathing rate category. A research team directed by Jack Hackney and William Linn conducted four studies in Los Angeles which used time/activity diaries and heart rate monitors to obtain ventilation rate data representative of typical daily activities. IT Air Quality Services acquired the four Hackney/Linn databases and converted each into a file of EVR values, one EVR value for each diary event. Researchers analyzed these files and developed a series of algorithms for generating EVR values that are superior to those used in the current pNEM methodology. Each algorithm uses Monte Carlo (probabilistic) techniques to produce EVR values that vary according to age, gender, activity, breathing rate category (slow, medium, or fast), microenvironment, time of day, activity duration, and other variables present in the input time/activity data files. The algorithms were tested by applying them to representative time/activity databases that contained a measured EVR value for each diary record. In each test, analysts compared the distribution of generated EVR values with the corresponding distribution of measured EVR values. Results of these tests suggest that the algorithms produce realistic EVR distributions.

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