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Acute Toxicity of Ternary Cd–Cu–Ni and Cd–Ni–Zn Mixtures to Daphnia magna: Dominant Metal Pairs Change along a Concentration Gradient

Multiple metals are usually present in surface waters, sometimes leading to toxicity that currently is difficult to predict due to potentially non-additive mixture toxicity. Previous toxicity tests with Daphnia magna exposed to binary mixtures of Ni combined with Cd, Cu, or Zn demonstrated that Ni a...

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Bibliographic Details
Published in:Environmental science & technology 2017-04, Vol.51 (8), p.4471-4481
Main Authors: Traudt, Elizabeth M, Ranville, James F, Meyer, Joseph S
Format: Article
Language:English
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Summary:Multiple metals are usually present in surface waters, sometimes leading to toxicity that currently is difficult to predict due to potentially non-additive mixture toxicity. Previous toxicity tests with Daphnia magna exposed to binary mixtures of Ni combined with Cd, Cu, or Zn demonstrated that Ni and Zn strongly protect against Cd toxicity, but Cu–Ni toxicity is more than additive, and Ni–Zn toxicity is slightly less than additive. To consider multiple metal–metal interactions, we exposed D. magna neonates to Cd, Cu, Ni, or Zn alone and in ternary Cd–Cu–Ni and Cd–Ni–Zn combinations in standard 48 h lethality tests. In these ternary mixtures, two metals were held constant, while the third metal was varied through a series that ranged from nonlethal to lethal concentrations. In Cd–Cu–Ni mixtures, the toxicity was less than additive, additive, or more than additive, depending on the concentration (or ion activity) of the varied metal and the additivity model (concentration-addition or independent-action) used to predict toxicity. In Cd–Ni–Zn mixtures, the toxicity was less than additive or approximately additive, depending on the concentration (or ion activity) of the varied metal but independent of the additivity model. These results demonstrate that complex interactions of potentially competing toxicity-controlling mechanisms can occur in ternary-metal mixtures but might be predicted by mechanistic bioavailability-based toxicity models.
ISSN:0013-936X
1520-5851
DOI:10.1021/acs.est.6b06169