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Environ Pollut. 2014 Feb;185:69-76. doi: 10.1016/j.envpol.2013.10.004. Epub 2013 Nov 9.

Comprehensive probabilistic modelling of environmental emissions of engineered nanomaterials.

Author information

1
Empa - Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, CH-9014 St. Gallen, Switzerland; Institute for Chemical and Bioengineering, ETH Zürich, CH-8093 Zürich, Switzerland.
2
Empa - Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, CH-9014 St. Gallen, Switzerland; ETSS, CH-7558 Strada, Switzerland.
3
Institute for Chemical and Bioengineering, ETH Zürich, CH-8093 Zürich, Switzerland.
4
Empa - Swiss Federal Laboratories for Materials Science and Technology, Technology and Society Laboratory, Lerchenfeldstrasse 5, CH-9014 St. Gallen, Switzerland. Electronic address: nowack@empa.ch.

Abstract

Concerns about the environmental risks of engineered nanomaterials (ENM) are growing, however, currently very little is known about their concentrations in the environment. Here, we calculate the concentrations of five ENM (nano-TiO2, nano-ZnO, nano-Ag, CNT and fullerenes) in environmental and technical compartments using probabilistic material-flow modelling. We apply the newest data on ENM production volumes, their allocation to and subsequent release from different product categories, and their flows into and within those compartments. Further, we compare newly predicted ENM concentrations to estimates from 2009 and to corresponding measured concentrations of their conventional materials, e.g. TiO2, Zn and Ag. We show that the production volume and the compounds' inertness are crucial factors determining final concentrations. ENM production estimates are generally higher than a few years ago. In most cases, the environmental concentrations of corresponding conventional materials are between one and seven orders of magnitude higher than those for ENM.

KEYWORDS:

Engineered nanomaterials (ENM); Environmental concentrations; Material flow modelling; Probability distributions; Production estimates

PMID:
24220022
DOI:
10.1016/j.envpol.2013.10.004
[Indexed for MEDLINE]

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