Assessment of whole effluent toxicity test variability: Partitioning sources of variability

Citation
Wj. Warren-hicks et al., Assessment of whole effluent toxicity test variability: Partitioning sources of variability, ENV TOX CH, 19(1), 2000, pp. 94-104
Citations number
16
Categorie Soggetti
Environment/Ecology
Journal title
ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY
ISSN journal
07307268 → ACNP
Volume
19
Issue
1
Year of publication
2000
Pages
94 - 104
Database
ISI
SICI code
0730-7268(200001)19:1<94:AOWETT>2.0.ZU;2-X
Abstract
In this article, we quantify the variability of toxicity tests used in whol e effluent toxicity (WET) testing and ambient water testing and demonstrate how knowledge of this variability can be used in the interpretation of com pliance with WET limits in National Pollutant Discharge Elimination System permits. Whole effluent toxicity test endpoint accuracy and precision are i mportant factors in establishing the credibility of test results. Initially , we developed a national data set consisting of raw reference toxicant dat a from freshwater and marine tests. The data set consisted of the most comm only used test species, protocols, and laboratories and included results fr om multiple tests over time within single laboratories. Using a random-effe cts model, we evaluate and estimate the following variance components: betw een-laboratory variability, variability as a function of dilution concentra tion. variability of toxicity tests conducted over time, and random error. A variance components model was used to calculate the relative contribution of each variance component to the total variability in specific test endpo ints. All analyses were conducted separately for specific reference toxican t, test species, and test protocol combinations. We demonstrate how to use the resulting variance estimates to calculate the minimum significant diffe rence expected for specific test species and test protocols and present an application with WET test data. We present an application using actual WET test results and make recommendations for ensuring the quality of the infor mation resulting from future WET testing.