Modeling Nanomaterial Environmental Fate in Aquatic Systems

Dale, Amy L.; Casman, Elizabeth A.; Lowry, Gregory V.; Lead, Jamie R.; Viparelli, E.; Baalousha, Mohammed

doi:10.1021/es505076w

Cited by 252 publications

(180 citation statements)

References 53 publications

Supporting

Mentioning

174

Contrasting

Unclassified

Order By: Relevance

“…We consider a daily time step and nonsteady state, to describe [ENM] variability due to seasonal weather, flow-dependent patterns, and release fluctuations. 72 nanoFate considers compartment dimensions and characteristics (e.g., water chemistry, soil properties) and incorporates observed daily hydrometeorological data for precipitation, wind speed, and river flow, which improves the regional specificity of the model. nanoFate accounts for differences in freshwater and coastal w ater ch emistry t hat aff ect E NM p rocesses.…”

Section: ■ Methodsmentioning

confidence: 99%

Assessing the Risk of Engineered Nanomaterials in the Environment: Development and Application of the nanoFate Model

Garner

Suh

Keller

2017

Environ. Sci. Technol.

211

161

View full text Add to dashboard Cite

We developed a dynamic multimedia fate and transport model (nanoFate) to predict the time-dependent accumulation of metallic engineered nanomaterials (ENMs) across environmental media. nanoFate considers a wider range of processes and environmental subcompartments than most previous models and considers ENM releases to compartments (e.g., urban, agriculture) in a manner that reflects their different patterns of use and disposal. As an example, we simulated ten years of release of nano CeO 2 , CuO, TiO 2 , and ZnO in the San Francisco Bay area. Results show that even soluble metal oxide ENMs may accumulate as nanoparticles in the environment in sufficient concentrations to exceed the minimum toxic threshold in freshwater and some soils, though this is more likely with high-production ENMs such as TiO 2 and ZnO. Fluctuations in weather and release scenario may lead to circumstances where predicted ENM concentrations approach acute toxic concentrations. The fate of these ENMs is to mostly remain either aggregated or dissolved in agricultural lands receiving biosolids and in freshwater or marine sediments. Comparison to previous studies indicates the importance of some key model aspects including climatic and temporal variations, how ENMs may be released into the environment, and the effect of compartment composition on predicted concentrations.

show abstract

Section: ■ Methodsmentioning

confidence: 99%

Assessing the Risk of Engineered Nanomaterials in the Environment: Development and Application of the nanoFate Model

Garner

Suh

Keller

2017

Environ. Sci. Technol.

211

161

View full text Add to dashboard Cite

show abstract

“…Among these factors, the role of NOM is one of the most complex [86]. The importance of NOM on the aggregation behavior of nanoparticles has led to many studies.…”

Section: Heteroaggregation and The Role Of Natural Organic Mattermentioning

confidence: 99%

“…Mathematical modeling of heteroaggregation is very important to provide a more fundamental understanding, and allow prediction of the environmental behavior, fate, and transport of NPs [86]. However, there is still a gap between the experimental study and the modeling of heteroaggregation of NPs.…”

Section: Dlvomentioning

confidence: 99%

See 1 more Smart Citation

Heteroaggregation of nanoparticles with biocolloids and geocolloids

Wang

Adeleye

Huang

et al. 2015

Advances in Colloid and Interface Science

164

View full text Add to dashboard Cite

The application of nanoparticles has raised concern over the safety of these materials to human health and the ecosystem. After release into an aquatic environment, nanoparticles are likely to experience heteroaggregation with biocolloids, geocolloids, natural organic matter (NOM) and other types of nanoparticles. Heteroaggregation is of vital importance for determining the fate and transport of nanoparticles in aqueous phase and sediments. In this article, we review the typical cases of heteroaggregation between nanoparticles and biocolloids and/or geocolloids, mechanisms, modeling, and important indicators used to determine heteroaggregation in aqueous phase. The major mechanisms of heteroaggregation include electric force, bridging, hydrogen bonding, and chemical bonding. The modeling of heteroaggregation typically considers DLVO, X-DLVO, and fractal dimension. The major indicators for studying heteroaggregation of nanoparticles include surface charge measurements, size measurements, observation of morphology of particles and aggregates, and heteroaggregation rate determination. In the end, we summarize the research challenges and perspective for the heteroaggregation of nanoparticles, such as the determination of α hetero values and heteroaggregation rates; more accurate analytical methods instead of DLS for heteroaggregation measurements; sensitive analytical techniques to measure low concentrations of nanoparticles in heteroaggregation systems; appropriate characterization of NOM at the molecular level to understand the structures and fractionation of NOM; effects of different types, concentrations, and fractions of NOM on the heteroaggregation of nanoparticles; the quantitative adsorption and desorption of NOM onto the surface of nanoparticles and heteroaggregates; and a better understanding of the fundamental mechanisms and modeling of heteroaggregation in natural water which is a complex system containing NOM, nanoparticles, biocolloids and geocolloids.

show abstract

“…The sedimentation of CNTs in water bodies is driven by the rapid formation of aggregates, with slowly settling natural colloids (Quik et al, 2014(Quik et al, , 2012 and more rapid settling suspended solids (SS) (Velzeboer et al, 2014), leading to the possible accumulation of CNTs in the aquatic sediments. Eventually, aquatic sediments are believed to be an important sink for CNTs and a significant exposure medium for aquatic organisms (Cross et al, 2015;Dale et al, 2015;Klaine et al, 2008;Markus et al, 2015). CNTs exhibit novel properties, e.g.…”

Section: Introductionmentioning

confidence: 99%