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1.
Proc Natl Acad Sci U S A ; 114(10): E1756-E1765, 2017 03 07.
Article in English | MEDLINE | ID: mdl-28223482

ABSTRACT

Dissolved organic matter (DOM) strongly influences the properties and fate of engineered nanoparticles (ENPs) in aquatic environments. There is an extensive body of experiments on interactions between DOM and ENPs and also larger particles. [We denote particles on the nano- and micrometer scale as particulate matter (PM).] However, the experimental results are very heterogeneous, and a general mechanistic understanding of DOM-PM interactions is still missing. In this situation, recent reviews have called to expand the range of DOM and ENPs studied. Therefore, our work focuses on the diversity of the DOM and PM types investigated. Because the experimental results reported in the literature are highly disparate and difficult to structure, a new format of organizing, visualizing, and interpreting the results is needed. To this end, we perform a network analysis of 951 experimental results on DOM-PM interactions, which enabled us to analyze and quantify the diversity of the materials investigated. The diversity of the DOM-PM combinations studied has mostly been decreasing over the last 25 y, which is driven by an increasing focus on several frequently investigated materials, such as DOM isolated from fresh water, DOM in whole-water samples, and TiO2 and silver PM. Furthermore, there is an underrepresentation of studies into the effect of particle coating on PM-DOM interactions. Finally, it is of great importance that the properties of DOM used in experiments with PM, in particular the molecular weight and the content of aromatic and aliphatic carbon, are reported more comprehensively and systematically.


Subject(s)
Environmental Monitoring , Nanoparticles/chemistry , Water Pollutants, Chemical/chemistry , Carbon/chemistry , Models, Chemical , Molecular Weight , Nanoparticles/toxicity , Organic Chemicals/chemistry , Organic Chemicals/toxicity , Silver/chemistry , Solubility , Water/chemistry , Water Pollutants, Chemical/toxicity
2.
PLoS One ; 13(5): e0196549, 2018.
Article in English | MEDLINE | ID: mdl-29734351

ABSTRACT

To assess the environmental fate of engineered nanoparticles (ENPs), it is essential to understand their interactions with dissolved organic matter (DOM). The highly complex nature of the interactions between DOM and ENPs and other particulate matter (PM) requires investigating a wide range of material types under different conditions. However, despite repeated calls for an increased diversity of the DOM and PM studied, researchers increasingly focus on certain subsets of DOM and PM. Considering the discrepancy between the calls for more diversity and the research actually carried out, we hypothesize that materials that were studied more often are more visible in the scientific literature and therefore are more likely to be studied again. To investigate the plausibility of this hypothesis, we developed an agent-based model simulating the material choice in the experiments studying the interaction between DOM and PM between 1990 and 2015. The model reproduces the temporal trends in the choice of materials as well as the main properties of a network that displays the DOM and PM types investigated experimentally. The results, which support the hypothesis of a positive reinforcing material choice, help to explain why calls to increase the diversity of the materials studied are repeatedly made and why recent criticism states that the selection of materials is unbalanced.


Subject(s)
Bias , Selection Bias , Computer Simulation , Environmental Monitoring/methods , Humic Substances/analysis , Models, Chemical , Nanoparticles , Organic Chemicals/analysis , Particulate Matter/analysis , Research Design , Solubility , Water Pollutants, Chemical/analysis
3.
Sci Total Environ ; 535: 150-9, 2015 Dec 01.
Article in English | MEDLINE | ID: mdl-25636351

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 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.


Subject(s)
Environmental Monitoring/methods , Environmental Pollutants/analysis , Models, Chemical , Nanoparticles/analysis , France
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