Bioaccumulation dynamics and modeling in an estuarine invertebrate following aqueous exposure to nanosized and dissolved silver

Farhan R Khan, Superb K Misra, Javier García-Alonso, Brian D Smith, Stanislav Strekopytov, Philip S Rainbow, Samuel N Luoma, Eugenia Valsami-Jones

Research output: Contribution to journalArticlepeer-review

58 Citations (Scopus)


Predicting the environmental impact of engineered nanomaterials (ENMs) is increasingly important owing to the prevalence of emerging nanotechnologies. We derived waterborne uptake and efflux rate constants for the estuarine snail, Peringia ulvae, exposed to dissolved Ag (AgNO(3)) and silver nanoparticles (Ag NPs), using biodynamic modeling. Uptake rates demonstrated that dissolved Ag is twice as bioavailable as Ag in nanoparticle form. Biphasic loss dynamics revealed the faster elimination of Ag from Ag NPs at the start of depuration, but similar slow efflux rate constants. The integration of biodynamic parameters into our model accurately predicted Ag tissue burdens during chronic exposure with 85% of predicted values within a factor of 2 of observed values. Zeta potentials for the Ag NPs were lower in estuarine waters than in waters of less salinity; and uptake rates in P. ulvae were slower than reported for the freshwater snail Lymnaea stagnalis in similar experiments. This suggests aggregation of Ag NPs occurs in estuarine waters and reduces, but does not eliminate, bioavailability of Ag from the Ag NPs. Biodynamic modeling provides an effective methodology to determine bioavailable metal concentrations (originating from metal and metal-oxide nanoparticles) in the environment and may aid future ENM risk assessment.

Original languageEnglish
Pages (from-to)7621-8
Number of pages8
JournalEnvironmental Science & Technology
Issue number14
Publication statusPublished - 17 Jul 2012


  • Animals
  • Environmental Monitoring
  • Hydrodynamics
  • Metal Nanoparticles
  • Models, Biological
  • Particle Size
  • Rivers
  • Seawater
  • Silver
  • Snails
  • Suspensions
  • Time Factors


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