Modeling Population Exposures to Silver Nanoparticles Present in Consumer Products.


Journal Article

Exposures of the general population to manufactured nanoparticles (MNPs) are expected to keep rising due to increasing use of MNPs in common consumer products (PEN 2014). The present study focuses on characterizing ambient and indoor population exposures to silver MNPs (nAg). For situations where detailed, case-specific exposure-related data are not available, as in the present study, a novel tiered modeling system, Prioritization/Ranking of Toxic Exposures with GIS (Geographic Information System) Extension (PRoTEGE), has been developed: it employs a product Life Cycle Analysis (LCA) approach coupled with basic human Life Stage Analysis (LSA) to characterize potential exposures to chemicals of current and emerging concern. The PRoTEGE system has been implemented for ambient and indoor environments, utilizing available MNP production, usage, and properties databases, along with laboratory measurements of potential personal exposures from consumer spray products containing nAg. Modeling of environmental and microenvironmental levels of MNPs employs Probabilistic Material Flow Analysis combined with product LCA to account for releases during manufacturing, transport, usage, disposal, etc. Human exposure and dose characterization further employs screening Microenvironmental Modeling and Intake Fraction methods combined with LSA for potentially exposed populations, to assess differences associated with gender, age, and demographics. Population distributions of intakes, estimated using the PRoTEGE framework, are consistent with published individual-based intake estimates, demonstrating that PRoTEGE is capable of capturing realistic exposure scenarios for the US population. Distributions of intakes are also used to calculate biologically-relevant population distributions of uptakes and target tissue doses through human airway dosimetry modeling that takes into account product MNP size distributions and age-relevant physiological parameters.

Full Text

Duke Authors

Cited Authors

  • Royce, SG; Mukherjee, D; Cai, T; Xu, SS; Alexander, JA; Mi, Z; Calderon, L; Mainelis, G; Lee, K; Lioy, PJ; Tetley, TD; Chung, KF; Zhang, J; Georgopoulos, PG

Published Date

  • November 2014

Published In

Volume / Issue

  • 16 / 11

PubMed ID

  • 25745354

Pubmed Central ID

  • 25745354

Electronic International Standard Serial Number (EISSN)

  • 1572-896X

International Standard Serial Number (ISSN)

  • 1388-0764

Digital Object Identifier (DOI)

  • 10.1007/s11051-014-2724-4


  • eng