Annals of Occupational Hygiene Advance Access originally published online on December 9, 2004
Annals of Occupational Hygiene 2005 49(2):147-153; doi:10.1093/annhyg/meh072
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
© 2004 British Occupational Hygiene Society Published by Oxford University Press;
Evaluation of an Artificial Intelligence Program for Estimating Occupational Exposures
1 Department of Occupational and Environmental Health, College of Public Health, University of Oklahoma Health Sciences Center, 801 N.E. 13th Street, Oklahoma City, OK 73104, USA; 2 Division of Environmental and Occupational Health Sciences, School of Public Health, University of Illinois at Chicago, 2121 West Taylor Street, Chicago, IL 60612, USA
* Author to whom correspondence should be addressed. Tel: +1 405 271 2070 ext: 46764; fax: +1 405 271 1971; e-mail: margaret-phillips{at}ouhsc.edu
Estimation and Assessment of Substance Exposure (EASE) is an artificial intelligence program developed by UK's Health and Safety Executive to assess exposure. EASE computes estimated airborne concentrations based on a substance's vapor pressure and the types of controls in the work area. Though EASE is intended only to make broad predictions of exposure from occupational environments, some occupational hygienists might attempt to use EASE for individual exposure characterizations. This study investigated whether EASE would accurately predict actual sampling results from a chemical manufacturing process. Personal breathing zone time-weighted average (TWA) monitoring data for two volatile organic chemicals—a common solvent (toluene) and a specialty monomer (chloroprene)—present in this manufacturing process were compared to EASE-generated estimates. EASE-estimated concentrations for specific tasks were weighted by task durations reported in the monitoring record to yield TWA estimates from EASE that could be directly compared to the measured TWA data. Two hundred and six chloroprene and toluene full-shift personal samples were selected from eight areas of this manufacturing process. The Spearman correlation between EASE TWA estimates and measured TWA values was 0.55 for chloroprene and 0.44 for toluene, indicating moderate predictive values for both compounds. For toluene, the interquartile range of EASE estimates at least partially overlapped the interquartile range of the measured data distributions in all process areas. The interquartile range of EASE estimates for chloroprene fell above the interquartile range of the measured data distributions in one process area, partially overlapped the third quartile of the measured data in five process areas and fell within the interquartile range in two process areas. EASE is not a substitute for actual exposure monitoring. However, EASE can be used in conditions that cannot otherwise be sampled and in preliminary exposure assessment if it is recognized that the actual interquartile range could be much wider and/or offset by a factor of 10 or more.
Keywords: EASE • expert system • exposure modeling • measurement data • model evaluation
CiteULike 
Connotea 
Del.icio.us What's this?
This article has been cited by other articles:
|
|
 |
|
  E. Tielemans, D. Noy, J. Schinkel, H. Heussen, D. Van Der Schaaf, J. West, and W. Fransman Stoffenmanager Exposure Model: Development of a Quantitative Algorithm Ann. Hyg., August 1, 2008; 52(6): 443 - 454. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. NORTHAGE EASEing into the Future Ann. Hyg., March 1, 2005; 49(2): 99 - 101. [Full Text] [PDF]
|
|