Uncertainty in exposure estimates made by modeling versus monitoring

Nicas, M; Jayjock, M

HERO ID

1060527

Reference Type

Journal Article

Year

2002

Language

English

PMID

12173176

HERO ID 1060527
In Press No
Year 2002
Title Uncertainty in exposure estimates made by modeling versus monitoring
Authors Nicas, M; Jayjock, M
Journal AIHA Journal
Volume 63
Issue 3
Page Numbers 275-283
Abstract To conduct an initial exposure assessment for an airborne toxicant, industrial hygienists usually prefer air monitoring to mathematical modeling, even if only one exposure value is to be measured. This article argues that mathematical modeling may provide a more accurate (less uncertain) exposure estimate than monitoring if only a few air samples are to be collected, if anticipated exposure variability is high, and if information on exposure determinants is not too uncertain. To explore this idea, a hypothetical "true" distribution of 8-hour time-weighted average airborne exposure values, C, is posited based on an NF exposure model. The C distribution is approximately lognormal. Estimation of the mean value, microC (the long-term average exposure level), is considered. Based on simple random sampling of workdays and use of the sample mean C to estimate microC, accuracy (uncertainty) in the estimate is measured by the mean square error, MSE(C). In the alternative, a modeling estimate can be made using estimates of the mean chemical emission rate microG, the mean room dilution supply air rate microQ, and the mean dilution ventilation rate in the NF of the source mu beta. By positing uniform distributions for the estimates microG, microQ, and mu beta, an equation for the modeling mean square error MSE(microC) is presented. It is shown that for a sample size of three or fewer workdays, mathematical modeling rather than air monitoring should provide a more accurate estimate of microC if the anticipated geometric standard deviation for the C distribution exceeds 2.3.
Doi 10.1080/15428110208984714
Pmid 12173176
Wosid WOS:000176252700004
Is Certified Translation No
Dupe Override No
Is Public Yes
Language Text English