Development of Quantitative Ion Character-Activity Relationship Models to Address the Lack of Toxicological Data for Technology-Critical Elements.

Recent industrial developments have resulted in an increase in the 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 toward freshwater aquatic organisms. In total, 23 metal properties were tested as predictors of acute median effect concentration (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, and rhenium) and platinum group elements (iridium, platinum, palladium, rhodium, and ruthenium) with the few measured values that are available. The 8 "best" QICAR models (adjusted r  > 0.6) used the covalent index as the predictor. For a given metal ion, this composite parameter is a measure of the importance of covalent interactions relative to ionic interactions. Toxicity was reasonably well predicted for most of the TCEs, with values falling within the 95% 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. Environ Toxicol Chem 2021;40:1139-1148. © 2020 SETAC.