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  • Title: Predicting the combined toxicity of binary metal mixtures (Cu-Ni and Zn-Ni) to wheat.
    Author: Wang X, Luo X, Wang Q, Liu Y, Naidu R.
    Journal: Ecotoxicol Environ Saf; 2020 Dec 01; 205():111334. PubMed ID: 32961486.
    Abstract:
    In order to investigate and model toxicity and interactions between metals in mixtures, inhibition of wheat root elongation in response to additions of single-metals of copper (Cu), zinc (Zn), and nickel (Ni) and of binary mixed-metal combinations of Cu-Ni and Zn-Ni was tested, using water culture experiments under different Mg concentrations and pH values. A biotic ligand model (BLM) of single-metal Cu, Zn, and Ni was established. The results showed that the toxicity of Cu, Zn or Ni in isolation decreased with increasing Mg concentration whereas the effects of pH on Cu, Zn, or Ni toxicity were related not only to free Cu2+, Zn2+, and Ni2+ concentrations, but also to inorganic metal complexes. In binary mixtures, the two metals in the Cu-Ni mixture showed a weakly antagonistic effect, whereas the two metals in the Zn-Ni mixture showed greater antagonism. Using data from single-metal Cu, Zn, and Ni BLMs, combined with the toxicity index and the overall amounts of metal ions bound to the biotic ligands, one simple model was developed. This model consisted of the toxic unit (TUM, no competition included) and two extended BLMs, BLM-TUf (f as a function of TU, including competition between Mg2+ and metal ions) and BLM-fmix (including the competition between Mg2+ and metal ions, as well as between free metal ions). They were then used to predict the joint toxicity of Cu-Ni and Zn-Ni binary mixtures to wheat. Both of the extended BLMs could provide more accurate predictions of toxic effects of Cu-Ni and Zn-Ni than TUM. BLM-fmix performed best for the Zn-Ni binary mixture (r2 = 0.93; root-mean-square error, RMSE = 9.87). On the other hand, for the Cu-Ni mixture, the predictive effect based on BLM-TUf (r2 = 0.93; RMSE = 9.60) was similar to that of BLM-fmix (r2 = 0.93; RMSE = 9.56). The results provide a theoretical basis for the evaluation and remediation of soils contaminated with mixtures of heavy metals.
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