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Effective Modeling Framework for Quantifying the Potential Impacts of Coexisting Anions on the Toxicity of Arsenate, Selenite, and Vanadate.

Jie JiErkai HeHao QiuWillie J G M PeijnenburgCornelis A M van GestelXinde Cao
Published in: Environmental science & technology (2020)
Hardly any study has focused on the quantitative modeling of the toxicity of anionic metal(loid)s and their mixtures in the presence of potentially competing anions. Here, we designed a univariate experiment (420 treatments) to investigate the influence of various anions (phosphate, sulfate, carbonate, and OH-) on the toxicity of single anionic metal(loid)s (arsenate, selenite, and vanadate) and a full factorial mixture experiment (196 treatments) to examine the interactions and toxicity of As-Se mixtures at 4 phosphate levels. Standard root elongation tests with wheat (Triticum aestivum) were performed. A modeling framework, resembling the biotic ligand model (BLM) for cationic metals, was developed, extended, and applied to explain anion competitions and mixture effects. Carbonate significantly alleviated the toxicity of all three metal(loid)s. The toxicity of As was significantly mitigated by phosphate, while V toxicity was significantly relieved by OH-. The BLM-like model successfully explained more than 93% of the observed variance in toxicity. With the parameters derived from single-metal(loid) exposures, the developed BLM-toxic unit model reached an overall prediction performance of 78% in modeling the toxicity of As-Se mixtures at varying phosphate levels, validating the effectiveness of the model framework. It is concluded that by taking possible anion competitions and interactions into account, the BLM-type approaches can serve as promising tools for the risk assessment of single and mixed metal(loid)s contamination.
Keyphrases
  • ionic liquid
  • oxidative stress
  • risk assessment
  • randomized controlled trial
  • human health
  • oxide nanoparticles
  • systematic review
  • air pollution
  • transcription factor