Abstract

Environmental characteristics including water quality and sediment properties alter the hazard that metals pose to aquatic systems by governing the speciation and partitioning of metals between water, sediment, and biotic ligands; however, alternate ligands are being introduced into aquatic systems through anthropogenic activity. Microplastics are a ligand on which metals interact through adsorption to the plastic surface. It remains unknown what factors determine the amount of metal bound to microplastic. Using a combination of laboratory experiments and machine learning, we tested a suite of eighteen environmental parameters (inclusive of both water and sediment) to understand how they influence association of cadmium to a representative microplastic, polyethylene. From this, we developed and tested a predictive model that outlines the characteristics that favour the association of cadmium to microplastic. Alkalinity, humification index of dissolved organic matter, and pH (all of which are water quality characteristics) were the three factors determining the proportion of cadmium adsorbed to plastics. These results align with other predictive models, such as the Biotic Ligand Model in demonstrating the governance of metal behaviour by water quality characteristics. To assess the relationship of the amount of cadmium bound to microplastic and cadmium uptake, an exposure was completed in which fathead minnows (Pimephales promelas) were acclimated to environments representing each of the potential outcomes of the model. The uptake of cadmium was not significantly different between groups, indicating that the stress of alterations to water quality may be a confounding factor in determining the exposure risk of microplastics and cadmium.

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