Comprehensive probabilistic modelling of environmental emissions of engineered nanomaterials.

By Tian Yin Sun, Fadri Gottschalk, Konrad Hungerbühler, Bernd Nowack. Environmental Pollution, 2014

717 citations recorded by the source corpus.

Subfields: Environmental Chemistry, Materials Chemistry, Pollution

View Paper: https://www.semanticscholar.org/paper/d7d98e73c34832e67c87b5c3a2f5d203289346e4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Chemistry

1. Julian D. Olden
2. Pieter T. J. Johnson
3. D. Dudgeon
4. S. J. Ormerod

In Materials Chemistry

1. G. Metreveli
2. Stephan Wagner
3. Moira S. McKee
4. Ralf Schulz
5. M. Bundschuh
6. J. Filser
7. S. Lüderwald
8. G. Schaumann

In Pollution

1. S. Cooke

Citations in the corpus

• Emerging threats and persistent conservation challenges for freshwater biodiversity (2018, background): “Large quantities are finding their way into fresh waters, but analytical limitations (von der Kammer et al. , 2012) mean that current burden estimates are based primarily on models (Gottschalk, Sun & Nowack, 2013; Sun et al. , 2014; Dale et al. , 2015).”
• Nanoparticles in the environment: where do we come from, where do we go to? (2018, background): “Very recently, more advanced models use probabilistic approaches [49] that consider dynamic input rates, in-use stocks as well as the continuous rise in production volumes [22].”