Development of electrostatic-based bioavailability models for interpreting and predicting differential phytotoxicity and uptake of metal mixtures across different soils.

Metals are ubiquitous and normally co-occur as mixtures in soil, but there remains much to do regarding the development of appropriate models which incorporate mixture interactions and bioavailability to estimate their phytotoxicity and phytoaccumulation. Here, we developed a probability-based electrostatic toxicity model (ETM) and a Langmuir-type electrostatic uptake model (EUM) to predict and normalize toxicity and uptake of zinc-copper mixtures in Hordeum vulgare L. in different soils. For model development, the electrical potential (ψ0) and metal ion activities ({M(2+)}0) at the cell-membrane surface was computed based on plant physiological properties and soil solution chemistry. Single metal toxicity correlated more closely to their corresponding {M(2+)}0 than to ion activities in soil solution or total soil metal concentrations. The ETM explained up to 89% of the variance in mixture toxicity across different soils. Incorporation of ψ0 into the EUM improved the model's ability for predicting metal uptake. Besides, cell-surface H(+) appeared to significantly inhibit copper uptake via competition or other mechanisms, beyond its effect upon ψ0. Our results for the first time demonstrate that electrostatic theory can be used to predict and reconcile mixture toxicity and uptake data in different soils, indicating the potential of electrostatic-based models in risk assessment of multimetal-contaminated soils.