Dissipative particle dynamic simulation and experimental assessment of the impacts of humic substances on aqueous aggregation and dispersion of engineered nanoparticles.

Comprehensive experimental quantification and mapping of the aggregation and dispersion state of engineered nanoparticles (NPs) in the presence of humic substances is a great challenge. Dissipative particle dynamic (DPD) simulation was adopted to investigate the aggregation and dispersion mechanisms of NPs in the presence of a humic substance analog. Twelve different types of NPs including 2 metal-based NPs, 7 metal oxide-based NPs, and 3 carbon-based NPs in pure water (pH 3.0) and algae medium (pH 8.0) in the presence of a humic substance analogy were selected for experimental verification of the DPD simulation results. In agreement with results obtained with dynamic light scattering and phase analysis light scattering techniques, the simulations demonstrated that the presence of humic substances reduced the aggregation extent of the NPs. The DPD simulations showed that the stability and dispersity of the NPs increased first, and then decreased with increasing concentrations of humic substances. Moreover, there existed a concentration of humic substances where the NPs became more stable and more dispersed, which was experimentally verified in the case of all the NPs in the pure water and in the algae medium. Furthermore, theory and simulation indicate that both hydrophobic and hydrogen interaction play an important role in controlling the formation of NP aggregates in the presence of humic substances. Electrostatic interaction and steric repulsion are the main mechanisms underlying the effects of humic substances on the aqueous dispersion stability of NPs. Environ Toxicol Chem 2018;9999:1-8. © 2017 SETAC

CSOIL 2020: blootstellingsmodel voor gezondheidsrisico's door bodemvervuiling. Technische beschrijving

This report describes the CSOIL 2020 model, which calculates human exposure to soil contaminants throughout the entire human lifetime. Exposure can occur through, for example, consuming home grown vegetables and inhalation of soil particles during gardening. CSOIL 2020 is the most recent version of the CSOIL model, which was developed in 1995 and revised in 2000. The Government of The Netherlands uses the results of this model to determine soil quality standards. CSOIL 2020 was updated to incorporate recent scientific knowledge and allow functionality under newer IT operating systems. Additionally, the exposure results from CSOIL can now be used in the newest version of the risk toolbox for soil (in Dutch: Risicotoolbox Bodem). The toolbox is used to determine whether soil can safely be (re-)used. New modules are currently under development to allow the toolbox to be used in the Environment and Planning act, which will enter into force on the first of January 2022. Contact with contaminants in soil can be damaging to human health. Information on the extent of human exposure is required to determine the risk to health. CSOIL determines the exposure on the basis of the type of soil use on a location, like 'Residential with garden', the properties of the contaminant, such as solubility, and the local situation.Dit rapport beschrijft de update van het blootstellingsmodel CSOIL 2020. Met dit rekenmodel wordt berekend in welke mate mensen gedurende hun hele leven blootstaan aan bodemvervuiling. Dat kan bijvoorbeeld door groente en fruit uit eigen tuin te eten of gronddeeltjes in te slikken als ze in de tuin werken. Het RIVM heeft dit model, dat in 1995 is ontwikkeld en in 2000 is herzien, nu geactualiseerd. De overheid gebruikt het CSOIL-model om de normen voor de kwaliteit van de bodem te bepalen. Door de update sluit CSOIL 2020 aan op nieuwe ICTbesturingssystemen en wetenschappelijke kennis. Ook kan het model hierdoor aansluiten op de nieuwste versie van de Risicotoolbox Bodem, die de blootstellingsberekeningen van CSOIL gebruikt. Met deze toolbox kan worden bepaald of de grond veilig mag worden (her-)gebruikt. De toolbox wordt op dit moment uitgebreid met andere tools zodat hij voor de Omgevingswet kan worden ingezet. Deze wet treedt, naar verwachting, op 1 januari 2022 in werking. Contact met stoffen uit een vervuilde bodem kan schadelijk zijn voor de gezondheid van mensen. Om te weten hoe groot het risico op gezondheidseffecten is, is informatie nodig over de mate waarin mensen blootstaan aan een stof. Voor de blootstelling kijkt CSOIL 2020 welke functie een bodem op een locatie heeft, zoals wonen of natuur, en naar de eigenschappen van een vervuilende stof. Het samenspel van de functie van een bodem, de stofeigenschappen en de lokale situatie zoals de diepte van de vervuiling bepaalt de blootstelling. Een voorbeeld van een stofeigenschap is hoe makkelijk een stof oplost in water.Ministerie van Infrastructuur en Waterstaa

Multimedia Modeling of Engineered Nanoparticles with SimpleBox4nano: Model Definition and Evaluation

Screening level models for environmental assessment of engineered nanoparticles (ENP) are not generally available. Here, we present SimpleBox4Nano (SB4N) as the first model of this type, assess its validity, and evaluate it by comparisons with a known material flow model. SB4N expresses ENP transport and concentrations in and across air, rain, surface waters, soil, and sediment, accounting for nanospecific processes such as aggregation, attachment, and dissolution. The model solves simultaneous mass balance equations (MBE) using simple matrix algebra. The MBEs link all concentrations and transfer processes using first-order rate constants for all processes known to be relevant for ENPs. The first-order rate constants are obtained from the literature. The output of SB4N is mass concentrations of ENPs as free dispersive species, heteroaggregates with natural colloids, and larger natural particles in each compartment in time and at steady state. Known scenario studies for Switzerland were used to demonstrate the impact of the transport processes included in SB4N on the prediction of environmental concentrations. We argue that SB4N-predicted environmental concentrations are useful as background concentrations in environmental risk assessment

Strategies for determining heteroaggregation attachment efficiencies of engineered nanoparticles in aquatic environments

Heteroaggregation of engineered nanoparticles (ENPs) with suspended particulate matter (SPM) ubiquitous in natural waters often dominates the transport behaviour and overall fate of ENPs in aquatic environments. In order to provide meaningful exposure predictions and support risk assessment for ENPs, environmental fate and transport models require quantitative information about this process, typically in the form of the so-called attachment efficiency for heteroaggregation αhetero. The inherent complexity of heteroaggregation—encompassing at least two different particle populations, various aggregation pathways and several possible attachment efficiencies (α values)—makes its theoretical and experimental determination challenging. In this frontier review we assess the current state of knowledge on heteroaggregation of ENPs with a focus on natural surface waters. A theoretical analysis presents relevant equations, outlines the possible aggregation pathways and highlights different types of α. In a second part, experimental approaches to study heteroaggregation and derive α values are reviewed and three possible strategies are identified: i) monitoring changes in size, ii) monitoring number or mass distribution and iii) studying indirect effects, such as sedimentation. It becomes apparent that the complexity of heteroaggregation creates various challenges and no single best method for its assessment has been developed yet. Nevertheless, many promising strategies have been identified and meaningful data can be derived from carefully designed experiments when accounting for the different concurrent aggregation pathways and clearly stating the type of α reported. For future method development a closer connection between experiments and models is encourage

Considerations for Safe Innovation: The Case of Graphene.

The terms "Safe innovation" and "Safe(r)-by-design" are currently popular in the field of nanotechnology. These terms are used to describe approaches that advocate the consideration of safety aspects already at an early stage of the innovation process of (nano)materials and nanoenabled products. Here, we investigate the possibilities of considering safety aspects during various stages of the innovation process of graphene, outlining what information is already available for assessing potential hazard, exposure, and risks. In addition, we recommend further steps to be taken by various stakeholders to promote the safe production and safe use of graphene

Harmonizing across environmental nanomaterial testing media for increased comparability of nanomaterial datasets

The chemical composition and properties of environmental media determine nanomaterial (NM) transport, fate, biouptake, and organism response. To compare and interpret experimental data, it is essential that sufficient context be provided for describing the physical and chemical characteristics of the setting in which a nanomaterial may be present. While the nanomaterial environmental, health and safety (NanoEHS) field has begun harmonization to allow data comparison and re-use (e.g. using standardized materials, defining a minimum set of required material characterizations), there is limited guidance for standardizing test media. Since most of the NM properties driving environmental behaviour and toxicity are medium-dependent, harmonization of media is critical. A workshop in March 2016 at Duke University identified five categories of test media: aquatic testing media, soil and sediment testing media, biological testing media, engineered systems testing media and product matrix testing media. For each category of test media, a minimum set of medium characteristics to report in all NM tests is recommended. Definitions and detail level of the recommendations for specific standardized media vary across these media categories. This reflects the variation in the maturity of their use as a test medium and associated measurement techniques, variation in utility and relevance of standardizing medium properties, ability to simplify standardizing reporting requirements, and in the availability of established standard reference media. Adoption of these media harmonization recommendations will facilitate the generation of integrated comparable datasets on NM fate and effects. This will in turn allow testing of the predictive utility of functional assay measurements on NMs in relevant media, support investigation of first principles approaches to understand behavioral mechanisms, and support categorization strategies to guide research, commercial development, and policy.publishe