Nanoparticle Surface Affinity as a Predictor of Trophic Transfer.

Published

Journal Article

Nanoscale materials, whether natural, engineered, or incidental, are increasingly acknowledged as important components in large, environmental systems with potential implications for environmental impact and human health. Mathematical models are a useful tool for handling the rapidly increasing complexity and diversity of these materials and their exposure routes. Presented here is a mathematical model of trophic transfer driven by nanomaterial surface affinity for environmental and biological surfaces, developed in tandem with an experimental functional assay for determining these surface affinities. We found that nanoparticle surface affinity is a strong predictor of uptake through predation in a simple food web consisting of the algae Chlorella vulgaris and daphnid Daphnia magna. The mass of nanoparticles internalized by D. magna through consuming nanomaterial-contaminated algae varied linearly with surface-attachment efficiency. Internalized quantities of gold nanoparticles in D. magna ranged from 8.3 to 23.6 ng/mg for nanoparticle preparations with surface-attachment efficiencies ranging from 0.07 to 1. This model, coupled with the functional-assay approach, may provide a useful screening tool for existing materials as well as a predictive model for their development.

Full Text

Duke Authors

Cited Authors

  • Geitner, NK; Marinakos, SM; Guo, C; O'Brien, N; Wiesner, MR

Published Date

  • July 2016

Published In

Volume / Issue

  • 50 / 13

Start / End Page

  • 6663 - 6669

PubMed ID

  • 27249534

Pubmed Central ID

  • 27249534

Electronic International Standard Serial Number (EISSN)

  • 1520-5851

International Standard Serial Number (ISSN)

  • 0013-936X

Digital Object Identifier (DOI)

  • 10.1021/acs.est.6b00056

Language

  • eng