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Monte Carlo Modeling of Time‐Dependent Exposures Using a Microexposure Event Approach
Author(s) -
Price Paul S.,
Curry Cynthia L.,
Goodrum Philip E.,
Gray Michael N.,
McCrodden Jane I.,
Harrington Natalie W.,
CarlsonLynch Heather,
Keenan Russell E.
Publication year - 1996
Publication title -
risk analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.972
H-Index - 130
eISSN - 1539-6924
pISSN - 0272-4332
DOI - 10.1111/j.1539-6924.1996.tb01468.x
Subject(s) - monte carlo method , term (time) , event (particle physics) , econometrics , statistics , computer science , statistical physics , mathematics , physics , quantum mechanics
Over the last 10 years, a number of researchers have used Monte Carlo analysts to investigate the variation in long‐term average dose rates in exposed populations and the uncertainty in estimates of long‐term average dose rates for specific individuals. In general, these researchers have modeled long‐term exposures using simple dose rate equations which assume that individuals are exposed to a single environmental concentration at a constant rate over a specified exposure duration. This paper presents an alternative approach for modeling long‐term average exposures called microexposure event modeling which addresses a number of shortcomings in traditional dose rate equations. The paper discusses the limitations of the traditional dose rate equation, presents a description of the methodology, and illustrates advantages of the approach with a case study.