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Development of QICAR Models to Address the Lack of Toxicological Data for Technology-Critical Elements.

Abstract：

:recent industrial developments have resulted in an increase in use of so-called technology-critical elements (TCEs), for which the potential impacts on aquatic biota remain to be evaluated. In the present study, quantitative ion character activity relationships (QICARs) have been developed to relate intrinsic metal properties to their toxicity towards freshwater aquatic organisms. In total, 23 metal properties were tested as predictors of acute ec50 values for 12 data-rich metals, for algae, daphnids and fish (with and without species distinction). Simple and multiple linear regressions were developed using the toxicological data expressed as a function of the total dissolved metal concentrations. The best regressions were then tested by comparing the predicted ec50 values for the tces (germanium, indium, gold, rhenium and platinum group elements - pges - which include iridium, platinum, palladium, rhodium, and ruthenium) with the few measured values that are available. The eight 'best' QICAR models (adjusted r2 > 0.6) used χm2 r as the predictor. For a given metal ion, this composite parameter, also known as the covalent index, is a measure of the importance of covalent interactions relative to ionic interactions. The toxicity of the tces was reasonably well predicted for most of the TCEs, with values falling within the 95 percent prediction intervals for the regressions of the measured versus predicted ec50 values. Exceptions included au(i) (all test organisms), au(iii) (algae and fish), pt(ii) (algae, daphnids), ru(iii) (daphnids) and rh(iii) (daphnids, fish). We conclude that qicars show potential as a screening tool to review toxicity data and flag 'outliers', which might need further scrutiny, and as an interpolating or extrapolating tool to predict TCE toxicity. This article is protected by copyright. All rights reserved.

journal_name

Environ Toxicol Chem

journal_title

Environmental toxicology and chemistry

authors

Le Faucheur S,Mertens J,Van Genderen E,Boullemant A,Fortin C,Campbell PGC

doi

10.1002/etc.4960

subject

Has Abstract

pub_date

2020-12-14 00:00:00

eissn

0730-7268

issn

1552-8618

pub_type

杂志文章

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Development of QICAR Models to Address the Lack of Toxicological Data for Technology-Critical Elements.