Addressing the complexity of water chemistry in environmental fate modeling for engineered nanoparticles

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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Addressing the complexity of water chemistry in environmental fate modeling for engineered nanoparticles. / Sani-Kast, Nicole; Scheringer, Martin; Slomberg, Danielle et al.

in: The Science of The Total Environment, Jahrgang 535, 01.12.2015, S. 150 - 159.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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Sani-Kast N, Scheringer M, Slomberg D, Labille J, Praetorius A, Ollivier P et al. Addressing the complexity of water chemistry in environmental fate modeling for engineered nanoparticles. The Science of The Total Environment. 2015 Dez 1;535:150 - 159. Epub 2015 Jan 27. doi: 10.1016/j.scitotenv.2014.12.025

Bibtex

@article{e8c0392928354d55a07101333babef7f,
title = "Addressing the complexity of water chemistry in environmental fate modeling for engineered nanoparticles",
abstract = "Engineered nanoparticle (ENP) fate models developed to date - aimed at predicting ENP concentration in the aqueous environment - have limited applicability because they employ constant environmental conditions along the modeled system or a highly specific environmental representation; both approaches do not show the effects of spatial and/or temporal variability. To address this conceptual gap, we developed a novel modeling strategy that: 1) incorporates spatial variability in environmental conditions in an existing ENP fate model; and 2) analyzes the effect of a wide range of randomly sampled environmental conditions (representing variations in water chemistry). This approach was employed to investigate the transport of nano-TiO2 in the Lower Rh{\^o}ne River (France) under numerous sets of environmental conditions. The predicted spatial concentration profiles of nano-TiO2 were then grouped according to their similarity by using cluster analysis. The analysis resulted in a small number of clusters representing groups of spatial concentration profiles. All clusters show nano-TiO2 accumulation in the sediment layer, supporting results from previous studies. Analysis of the characteristic features of each cluster demonstrated a strong association between the water conditions in regions close to the ENP emission source and the cluster membership of the corresponding spatial concentration profiles. In particular, water compositions favoring heteroaggregation between the ENPs and suspended particulate matter resulted in clusters of low variability. These conditions are, therefore, reliable predictors of the eventual fate of the modeled ENPs. The conclusions from this study are also valid for ENP fate in other large river systems. Our results, therefore, shift the focus of future modeling and experimental research of ENP environmental fate to the water characteristic in regions near the expected ENP emission sources. Under conditions favoring heteroaggregation in these regions, the fate of the ENPs can be readily predicted.",
keywords = "Chemistry",
author = "Nicole Sani-Kast and Martin Scheringer and Danielle Slomberg and J{\'e}r{\^o}me Labille and Antonia Praetorius and Patrick Ollivier and Konrad Hungerb{\"u}hler",
note = "Copyright {\textcopyright} 2014 Elsevier B.V. All rights reserved.",
year = "2015",
month = dec,
day = "1",
doi = "10.1016/j.scitotenv.2014.12.025",
language = "English",
volume = "535",
pages = "150 -- 159",
journal = "The Science of The Total Environment",
issn = "0048-9697",
publisher = "Elsevier B.V.",

}

RIS

TY - JOUR

T1 - Addressing the complexity of water chemistry in environmental fate modeling for engineered nanoparticles

AU - Sani-Kast, Nicole

AU - Scheringer, Martin

AU - Slomberg, Danielle

AU - Labille, Jérôme

AU - Praetorius, Antonia

AU - Ollivier, Patrick

AU - Hungerbühler, Konrad

N1 - Copyright © 2014 Elsevier B.V. All rights reserved.

PY - 2015/12/1

Y1 - 2015/12/1

N2 - Engineered nanoparticle (ENP) fate models developed to date - aimed at predicting ENP concentration in the aqueous environment - have limited applicability because they employ constant environmental conditions along the modeled system or a highly specific environmental representation; both approaches do not show the effects of spatial and/or temporal variability. To address this conceptual gap, we developed a novel modeling strategy that: 1) incorporates spatial variability in environmental conditions in an existing ENP fate model; and 2) analyzes the effect of a wide range of randomly sampled environmental conditions (representing variations in water chemistry). This approach was employed to investigate the transport of nano-TiO2 in the Lower Rhône River (France) under numerous sets of environmental conditions. The predicted spatial concentration profiles of nano-TiO2 were then grouped according to their similarity by using cluster analysis. The analysis resulted in a small number of clusters representing groups of spatial concentration profiles. All clusters show nano-TiO2 accumulation in the sediment layer, supporting results from previous studies. Analysis of the characteristic features of each cluster demonstrated a strong association between the water conditions in regions close to the ENP emission source and the cluster membership of the corresponding spatial concentration profiles. In particular, water compositions favoring heteroaggregation between the ENPs and suspended particulate matter resulted in clusters of low variability. These conditions are, therefore, reliable predictors of the eventual fate of the modeled ENPs. The conclusions from this study are also valid for ENP fate in other large river systems. Our results, therefore, shift the focus of future modeling and experimental research of ENP environmental fate to the water characteristic in regions near the expected ENP emission sources. Under conditions favoring heteroaggregation in these regions, the fate of the ENPs can be readily predicted.

AB - Engineered nanoparticle (ENP) fate models developed to date - aimed at predicting ENP concentration in the aqueous environment - have limited applicability because they employ constant environmental conditions along the modeled system or a highly specific environmental representation; both approaches do not show the effects of spatial and/or temporal variability. To address this conceptual gap, we developed a novel modeling strategy that: 1) incorporates spatial variability in environmental conditions in an existing ENP fate model; and 2) analyzes the effect of a wide range of randomly sampled environmental conditions (representing variations in water chemistry). This approach was employed to investigate the transport of nano-TiO2 in the Lower Rhône River (France) under numerous sets of environmental conditions. The predicted spatial concentration profiles of nano-TiO2 were then grouped according to their similarity by using cluster analysis. The analysis resulted in a small number of clusters representing groups of spatial concentration profiles. All clusters show nano-TiO2 accumulation in the sediment layer, supporting results from previous studies. Analysis of the characteristic features of each cluster demonstrated a strong association between the water conditions in regions close to the ENP emission source and the cluster membership of the corresponding spatial concentration profiles. In particular, water compositions favoring heteroaggregation between the ENPs and suspended particulate matter resulted in clusters of low variability. These conditions are, therefore, reliable predictors of the eventual fate of the modeled ENPs. The conclusions from this study are also valid for ENP fate in other large river systems. Our results, therefore, shift the focus of future modeling and experimental research of ENP environmental fate to the water characteristic in regions near the expected ENP emission sources. Under conditions favoring heteroaggregation in these regions, the fate of the ENPs can be readily predicted.

KW - Chemistry

U2 - 10.1016/j.scitotenv.2014.12.025

DO - 10.1016/j.scitotenv.2014.12.025

M3 - Journal articles

C2 - 25636351

VL - 535

SP - 150

EP - 159

JO - The Science of The Total Environment

JF - The Science of The Total Environment

SN - 0048-9697

ER -

DOI