Issue 2, 2018

Emission and fate modelling framework for engineered nanoparticles in urban aquatic systems at high spatial and temporal resolution

Abstract

Trends in global urbanization and technology development have raised concerns about the associated increase in emissions to the environment, including novel contaminants such as engineered nanoparticles (ENPs). The assessment of these emissions in urban systems requires modelling approaches that integrate the complexity of urban environments as well as the high spatial and temporal variability of contaminant emissions. ENPs are emitted to urban surface waters through a variety of point and diffuse sources, with these emissions being driven by weather, usage patterns and population density. While the potential environmental and health impacts of ENPs are still not fully understood, understanding the spatial and temporal distribution of ENPs at the local scale will help to inform risk assessment. In this paper, we propose a novel modelling approach for estimating the exposure of ENPs in surface waters of urban systems. An integrative modelling framework combining an emission and a fate model for ENPs with high spatial and temporal resolution is presented and strategies for data gathering and the handling of knowledge gaps are discussed. Our framework is capable of identifying local emission hot spots and predicting exposure across a city, while generating information on the final speciation of the emitted ENPs (nano form, aggregates and other transformation products) within the studied environmental compartments over time.

Graphical abstract: Emission and fate modelling framework for engineered nanoparticles in urban aquatic systems at high spatial and temporal resolution

Article information

Article type
Paper
Submitted
13 Sep 2017
Accepted
01 Jan 2018
First published
03 Jan 2018
This article is Open Access
Creative Commons BY license

Environ. Sci.: Nano, 2018,5, 533-543

Emission and fate modelling framework for engineered nanoparticles in urban aquatic systems at high spatial and temporal resolution

P. Domercq, A. Praetorius and A. B. A. Boxall, Environ. Sci.: Nano, 2018, 5, 533 DOI: 10.1039/C7EN00846E

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