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Predicting the relative toxicity of metal ions using ion characteristics: Microtox® bioluminescence assay
Author(s) -
McCloskey John T.,
Newman Michael C.,
Clark Sue B.
Publication year - 1996
Publication title -
environmental toxicology and chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 171
eISSN - 1552-8618
pISSN - 0730-7268
DOI - 10.1002/etc.5620151011
Subject(s) - chemistry , ion , electronegativity , ionic radius , metal , metal ions in aqueous solution , fluoride , ionic bonding , iodide , analytical chemistry (journal) , inorganic chemistry , environmental chemistry , organic chemistry
Quantitative structure—activity relationships have been used to predict the relative toxicity of organic compounds. Although not as common, ion characteristics have also proven useful for predicting the relative toxicity of metal ions. The purpose of this study was to determine if the relative toxicity of metal ions using the Microtox® bioassay was predictable using ion characteristics. Median effect concentrations (EC50s) were determined for 20 metals in a NaNO 3 medium, which reflected freshwater speciation conditions, using the Microtox bacterial assay. The log of EC50 values was modeled using several ion characteristics, and Akaike's Information Criterion was calculated to determine which ion characteristics provided the best fit. Whether modeling total ion (unspeciated) or free ion (speciated) EC50 values, the one variable which best modeled EC50s was the softness index (σ p , i.e., [coordinate bond energy of the metal fluoride — coordinate bond energy of the metal iodide]/[coordinate bond energy of the metal fluoride]), while a combination of χ 2 m r (χ m = electronegativity, r = Pauling ionic radius) and |log K OH | (absolute value of the log of the first hydrolysis constant, K OH for M n+ + H 2 O → MOH n−1 + H + ) was the best two‐variable model. Other variables, including Δ E 0 and χ 2 m r (one‐variable models) and (Δ N /Δ IP , Δ E 0 ) and (χ 2 m r, Z 2 / r ) (two‐variable models), also gave adequate fits. Modeling with speciated (free ion) versus unspeciated (total ion) EC50 values did not improve fits. Modeling mono‐, di‐, and trivalent metal ions separately improved the models. We conclude that ion characteristics can be used to predict the relative toxicity of metal ions whether in freshwater (NaNO 3 medium) or saltwater (NaCl medium) speciation conditions and that this approach can be applied to metal ions varying widely in both valence and binding tendencies.