Regression Method to Estimate Provisional TLV/WEEL-Equivalents for Non-Carcinogens
Public Domain
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2000/08/01
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Description:There is a huge and changing number of chemicals in commerce for which workplace exposure criteria have not been assigned. Assigning an exposure criterion by an expert committee is resource-intensive-not soon available for the large majority of chemicals in current use. In the absence of assigned criteria, we have provided a regression method to estimate a first-screen estimate of a 'TLV/WEEL-equivalent' inhalation time-weighted average exposure criterion for a pure chemical (or chemical group) from a measure of a non-stochastic toxic exposure to elicit a chronic or sub-chronic health effect, known as a lowest observable adverse effect level (LOAEL) or a (highest) no observable adverse effect level (NOAEL). Results are presented for six data sets for which both a threshold limit value (TLV) or workplace environmental exposure level (WEEL) exposure criterion is presently assigned, and a LOAEL or NOAEL measure of toxic health effect was available from the United States Environmental Protection Agency Integrated Risk Information System data base. The results can be applied as a first estimate of exposure to substances for which no TLV or WEEL (TLV/WEEL) exists, and also serve as a mechanism for identifying substances for potential re-evaluation of their exposure limit, based on their relative position about the prediction models. [Description provided by NIOSH]
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ISSN:0003-4878
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Pages in Document:361-374
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Volume:44
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Issue:5
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NIOSHTIC Number:nn:20020858
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Citation:Ann Occup Hyg 2000 Aug; 44(5):361-374
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Contact Point Address:David A. Whaley, Department of Industrial Management Systems Engineering, West Virginia University, P.O. Box 6070, Morgantown, WV 26506, USA
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Email:dwhaley@wvu.edu
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Federal Fiscal Year:2000
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Peer Reviewed:True
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Source Full Name:Annals of Occupational Hygiene
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Main Document Checksum:urn:sha-512:bb1c5543eb38648ed5f4ef6b116930110678b2ab8800189191a49565b942f693a05956dfe04ea1a4f19f0ed0a8c97f4d7fa950de6a8c2cebc772e857244b498e
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