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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;37:1024-1031. © 2017 SETAC.

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 alpha(hetero). The inherent complexity of heteroaggregation-encompassing at least two different particle populations, various aggregation pathways and several possible attachment efficiencies (alpha 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 alpha. In a second part, experimental approaches to study heteroaggregation and derive alpha 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 alpha reported. For future method development a closer connection between experiments and models is encouraged.

Data sharing and reuse are crucial to enhance scientific progress and maximize return of investments in science. Although attitudes are increasingly favorable, data reuse remains difficult due to lack of infrastructures, standards, and policies. The FAIR (findable, accessible, interoperable, reusable) principles aim to provide recommendations to increase data reuse. Because of the broad interpretation of the FAIR principles, maturity indicators are necessary to determine the FAIRness of a dataset. In this work, we propose a reproducible computational workflow to assess data FAIRness in the life sciences. Our implementation follows principles and guidelines recommended by the maturity indicator authoring group and integrates concepts from the literature. In addition, we propose a FAIR balloon plot to summarize and compare dataset FAIRness. We evaluated the feasibility of our method on three real use cases where researchers looked for six datasets to answer their scientific questions. We retrieved information from repositories (ArrayExpress, Gene Expression Omnibus, eNanoMapper, caNanoLab, NanoCommons and ChEMBL), a registry of repositories, and a searchable resource (Google Dataset Search) via application program interfaces (API) wherever possible. With our analysis, we found that the six datasets met the majority of the criteria defined by the maturity indicators, and we showed areas where improvements can easily be reached. We suggest that use of standard schema for metadata and the presence of specific attributes in registries of repositories could increase FAIRness of datasets.

Riverine transport to the marine environment is an important pathway for microplastic. However, information on fate and transport of nano- and microplastic in freshwater systems is lacking. Here we present scenario studies on the fate and transport of nano-to millimetre sized spherical particles like microbeads (100 nm–10 mm) with a state of the art spatiotemporally resolved hydrological model. The model accounts for advective transport, homo- and heteroaggregation, sedimentation-resuspension, polymer degradation, presence of biofilm and burial. Literature data were used to parameterize the model and additionally the attachment efficiency for heteroaggregation was determined experimentally. The attachment efficiency ranged from 0.004 to 0.2 for 70 nm and 1050 nm polystyrene particles aggregating with kaolin or bentonite clays in natural freshwater. Modeled effects of polymer density (1–1.5 kg/L) and biofilm formation were not large, due to the fact that variations in polymer density are largely overwhelmed by excess mass of suspended solids that form heteroaggregates with microplastic. Particle size had a dramatic effect on the modeled fate and retention of microplastic and on the positioning of the accumulation hot spots in the sediment along the river. Remarkably, retention was lowest (18–25%) for intermediate sized particles of about 5 μm, which implies that the smaller submicron particles as well as larger micro- and millimetre sized plastic are preferentially retained. Our results suggest that river hydrodynamics affect microplastic size distributions with profound implications for emissions to marine systems.

New insights in the environmental exposure to nanomaterials have been gained from simulations with recently developed multimedia fate models: atmospheric concentrations are relatively low, and sedimentation in the water column is dominated by aggregation with natural particles, whereas soils and sediments are identified as environmental sinks. These model simulations however have only been performed for a limited set of nanomaterials. It is not yet clear to what extent the new insights gained from the limited set of evaluated nanomaterials generally apply to all nanomaterials. A sensitivity analysis was therefore performed of the nanomaterial environmental fate model SimpleBox4nano in order to investigate to what extent its model simulations are driven by the physicochemical properties of a nanomaterial. Sensitivity plots are drawn to quantify how the nanomaterial physicochemical properties specific weight, diameter, Hamaker constant, transformation rate constant, and attachment efficiency with natural particles, relate to (i) simulated key environmental fate processes such as deposition, filtration, and attachment and (ii) predicted free, bioavailable and total concentrations in air, water, sediment and soil. The critical transformation rate constant and attachment efficiency, at which these processes become dominant for prediction of the exposure concentrations are derived. Although exposure modelling is only part of a full environmental risk assessment of ENPs, they deliver insightful results for further development of ERA approaches by indicating to what extent ENP physicochemical properties affect predicted environmental exposure.

International audience; 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.

The aim of this paper is to present a new, integrative approach for calculating Fate Factors (FF) for nanomaterials by combining the USEtox2.0 modelling framework with SimpleBox4Nano (SB4N), an advanced environmental fate model for nanomaterials, and to demonstrate its application to life cycle assessment (LCA) by the estimation of characterisation factor (CF) for nano-TiO2 for the impact category of freshwater ecotoxcity. To enable the combination of the USEtox model with SB4N, two principle adaptations were made: (i) the compartments of air and rain were merged, and (ii) the sum of the free, aggregated, and attached species was accounted for in the receiving compartments. Furthermore, a dynamic analysis was conducted to characterize the dynamic behaviour of nanoparticles and to estimate the time at which steady state is actually reached. Our combined USEtox-SB4N approach was then applied to calculate i) the Fate Factor (FF) for unitary emissions of nano-TiO2 to air, freshwater, soil and sediment, and ii) using these, characterisation factors (CF) for nano-TiO2 in the case of the impact category freshwater ecotoxicity. The FF for unitary emissions of nano-TiO2 as free species was calculated. Persistence was found to be highest for emissions to soil (FFs,s = 2.9·105 days), followed by emissions to water (FFw,w = 128 days) and, then for an emissions to air (FFa,a = 3.3 days). The results of the dynamic analysis showed that the soil compartment in fact behaves as a storage compartment. Finally, an update of the freshwater ecotoxicity CF for nano-TiO2 was calculated (CF = 3443 PAF day m3 kg−1), based on the here established FF. The integrative approach presented here for calculating nano-specific FF values serves to reduce the complexity of the S4BN model and make the USEtox modelling framework fit for use with nanomaterials. This approach can be seen as a first step towards a “USEtox4Nano” characterisation model.

There is an increasing need for predictive risk assessment of nanomaterials (NMs) using methods that are rapid, accurate and resource efficient. To fulfill this need, the development and use of Quantitative Property Property Relationships (QPPRs) for estimating the hazard of NMs and NM-related parameters in exposure modelling seems eminent. In this study, we analyze a selection of models used for hazard and/or exposure assessment of NMs. This analysis was done by identifying all the NM-related properties used in these models related to three categories of data: (i) Intrinsic properties specific to the NM, matrix or experimental conditions, (ii) Extrinsic NM properties related to interaction between the intrinsic properties and (iii) Measured hazard or exposure data. This analysis is combined with the current state of QPPR development to recommend further development of QPPRs for predictive risk assessment of NMs. In particular, the use of descriptors related to the interaction between a NM and its surroundings, e.g. the attachment efficiency is proposed. acceptedVersion

The present study investigated how humic substances (HS) modify the aquatic toxicity of silver nanoparticles (AgNPs) as these particles agglomerate in water and interact with HS. An alga species (Raphidocelis subcapitata), a cladoceran species (Chydorus sphaericus), and a freshwater fish larva (Danio rerio), representing organisms of different trophic levels, were exposed to colloids of the polyvinylpyrrolidone-coated AgNPs in the presence and absence of HS. Results show that the presence of HS alleviated the aquatic toxicity of the AgNP colloids to all the organisms in a dose-dependent manner. The particle size distribution of the AgNPs' colloidal particles shifted to lower values due to the presence of HS, implying that the decrease in the toxicity of the AgNP colloids cannot be explained by the variation of agglomeration size. The surface charge of the AgNPs was found to be more negative in the presence of high concentrations of HS, suggesting an electrostatic barrier by which HS might limit interactions between particles and algae cells; indeed, this effect reduced the algae toxicity. Observations on silver ions (Ag(+)) release show that HS inhibit AgNP dissolution, depending on the concentrations of HS. When toxic effects were expressed as a function of each Ag-species, toxicity of the free Ag(+) was found to be much higher than that of the agglomerated particles.

Our understanding of the environmental fate and effects of engineered nanomaterials (ENMs) is in a state of fast transition. Recent scientific developments open new and powerful perspectives to define a framework for the prognostic risk assessment of ENMs in aquatic ecosystems. This requires abandoning the reductionist's approach of mechanistic analysis on particle or cellular scales and calls for engineering solutions that deal with uncertainties by applying assessment factors and probabilistic approaches. An ecological risk assessment (ERA) framework for ENMs is similar to that for other classes of substances, in that it requires clear protection goals based on ecosystem services, evidence-based concepts that link exposure to effects, and a transparent tiered effect assessment. Here, we discuss approaches to assess exposure and effects of ENMs. This includes recent developments in ENP fate modeling that greatly expanded the potential of prognostic exposure assessments. For the effect assessment, we advise a cost-effective screening based on principles of read-across as a conservative first tier. The feasibility of using species sensitivity distributions as a higher tier option is discussed. Controlled model ecosystem field experiments are proposed as a highest experimental tier, and are required for the calibration of the lower tiers. An outlook to unify information from various tiers by experimental work, fate modeling, and effect modeling as cost-effective prognostic tools for the ERA of ENMs is provided.

Sedimentation of engineered nanoparticles (ENPs) has been studied mainly in artificial media and stagnant systems mimicking natural waters. This neglects the role of turbulence and heteroaggregation with sediment. The authors studied the apparent sedimentation rates of selected ENPs (cerium dioxide [CeO2 ], polyvinylpyrrolidone-capped silver [PVP-Ag], and silica-coated silver [SiO2 -Ag]) in agitated sediment-water systems resembling fresh, estuarine, and marine waters. Experiments were designed to mimic low energy and periodically resuspended sediment water systems (14 d), followed by a long-term aging, resuspension, and settling phase (6 months), as would occur in receiving shallow lakes. The ENPs in systems with periodical resuspension of sediment were removed with sedimentation rates between 0.14 m/d and 0.50 m/d. The sedimentation rates did not vary much among ENP type, salinity, and aging time, which is attributed to the capture of ENPs in sediment flocks. The sedimentation rates were 1 to 2 orders of magnitude higher than those reported for aggregation-sedimentation in stagnant systems without suspended sediment. Heteroaggregation rates were estimated and ranged between 0.151 L/mg/d and 0.547 L/mg/d, which is up to 29 times higher than those reported for natural colloids under quiescent settling conditions. The authors conclude that rapid scavenging and sedimentation drives removal of ENPs from the water column.

Parameters and simplified model approaches for describing the fate of engineered nanoparticles (ENPs) are crucial to advance the risk assessment of these materials. Sedimentation behavior of ENPs in natural waters has been shown to follow apparent first order behavior, a ‘black box’ phenomenon that is insufficiently understood and therefore of limited applicability. Here we use a detailed Smoluchowski-Stokes model that accounts for homo- and heteroaggregation and sedimentation of ENPs and natural colloids (NCs), to simulate and interpret experimental ENP aggregation–sedimentation data. The model adequately simulated the observed time and initial concentration dependence of CeO2 settling data, and also predicted the conditions for aggregation rate-limitations of overall removal. Heteroaggregation with natural colloids was identified as the dominating removal process. Finally, the empirical apparent first order model data were calibrated against the mechanistic Smoluchowski-Stokes model simulation data, showing excellent fits for a range of NC initial concentrations. Using first order removal rates thus can be considered a valid and informed approximation when modeling ENP fate in the aquatic environment.

Screening level models for environmental assessment of engineered nanoparticles (ENP) are not generally available. Here we present SimpleBox for Nano (SB4N) as the first model of this type, motivate 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 nano-specific 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, hetero-aggregates 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.

Ecological risk of chemicals is measured by the quotient of predicted no-effect concentrations and predicted exposure concentrations, which are hard to assess for manufactured nanomaterials (NMs). This paper proposes modifications to currently used models, in order to make them suitable for estimating exposure concentrations of NMs in the aquatic environment. We have evaluated the adequacy of the current guidance documents for use with NMs and conclude that nano-specific fate processes, such as sedimentation and dissolution need to be incorporated. We have reviewed the literature on sedimentation and dissolution of NMs in environmentally relevant systems. We deduce that the overall kinetics of water–sediment transport of NMs should be close to first order. The lack of data on dissolution of NMs under environmentally realistic conditions calls for a pragmatic decision on which rates to be used in modeling. We find that first order removal kinetics for dissolution seems adequate. Based on limited data from literature, probable removal rates range from 0 to 10−4 s−1 for sedimentation, and from 0 to 10−5 s−1 for dissolution. Further experimental data at environmentally relevant conditions for sedimentation and dissolution of NMs is needed. Keywords: Nanomaterials, Sedimentation, Dissolution, Exposure assessment, Aquatic environment

Black Carbon (BC) quantification methods are reviewed, including new Rock-Eval 6 data on BC reference materials. BC has been reported to have major impacts on climate, human health and environmental quality. Especially for risk assessment of persistent organic pollutants (POPs) it is important to account for risk reduction caused by BC, as suggested for POP safety assessment in the framework of the new European Community Regulation on Registration, Evaluation, Authorization and Restriction of Chemicals (REACH). Four major classes of BC quantification methods are reviewed including application to BC reference materials. Methods include chemical oxidation, thermal oxidation, molecular marker, optical methods and Rock-Eval analyses. Residual carbon from Rock-Eval 6 analysis correlated well with BC data from 'gentle' methods like optical and molecular marker methods, which capture a major part of the BC continuum including labile fractions (e.g. char). In contrast, the temperature at which 50% of the organic matter was oxidized (T50%) in an oxidation-only Rock-Eval analysis, correlated well with data from chemothermal oxidation (CTO), which captures only refractory BC fractions (e.g. soot). Rock-Eval analysis can further be used for BC characterization through deconvolution of the dominant peaks of the thermogram and appears to be a powerful tool in BC analysis. © 2008 Elsevier B.V. All rights reserved.

The robustness of novel multimedia fate models in environmental exposure estimation of engineered nanoparticles (ENPs) remains unclear, because of uncertainties in the emission, physicochemical properties and natural variability in environmental systems. Here, we evaluate the uncertainty in predicted environmental concentrations (PECs) by using the SimpleBox4nano (SB4N) model. Monte Carlo (MC) simulations were performed on the environmental fate, concentrations and speciation of nano-CeO2, -TiO2 and -ZnO. Realistic distributions of uncertainty and variability were applied for all of SB4N's input and model parameter values. Environmental distribution over air, water, soil and sediment as well as nanomaterial speciation across natural colloid and coarse particles appeared to be similar for nano-CeO2, -TiO2 and -ZnO. ENPs in the atmosphere were effectively removed by deposition. ENPs in the water column were removed through hetero-aggregation–sedimentation with natural particles. ENPs accumulated in soil by attachment to grains. The sources of uncertainty and variability driving variation in PECs, which was identified in Spearman rank analysis, were related to production, emission, compartment volumes, and removal by dissolution or advection and appeared to be similar for the three ENPs. The variation in speciation within environmental compartments was influenced most by the physicochemical properties of the ENP and by model parameters that relate to the compartment of interest.

It is generally acknowledged that fate models for engineered nanoparticles (ENPs) hardly can be validated, given present limitations in analytical methods available for ENPs. Here we report on progress towards validation of the spatially resolved hydrological ENP fate model NanoDUFLOW, by comparing measured and modeled concentrations of < 450 nm Ce, Al, Ti and Zr -based particles for river Dommel (NL), as measured by Asymmetric Flow-Field-Flow Fractionation (AF4) coupled to ICP-MS. NanoDUFLOW simulates advection, aggregation-sedimentation, resuspension, dissolution and burial for singular ENPs, 5 classes of ENP homoaggregates and 25 classes of heteroaggregates, dynamically in space and time, and uses actual hydrological data of the river, 5 tributaries and a waste water treatment plant effluent. Validation for Ce particles was very good, whereas for Al, Ti and Zr particles, reasonable results were obtained. Model output was relatively insensitive to the attachment efficiency parameter, due to fast heteroaggregation. We argue that although the results cannot be taken as formal validation of singular

Site specific exposure assessments for engineered nanoparticles (ENPs) require spatially explicit fate models, which however are not yet available. Here we present an ENP fate model (NanoDUFLOW) that links ENP specific process descriptions to a spatially explicit hydrological model. The link enables the realistic modelling of feedbacks between local flow conditions and ENP fate processes, such as homo- and heteroaggregation, resuspension and sedimentation. Spatially explicit simulations using five size classes of ENPs and five size classes of natural solids showed how ENP sediment contamination ‘hot spots’ and ENP speciation can be predicted as a function of place and time. For the catchment modelled, neglect of spatial heterogeneity caused relatively small differences in ENP retention. However, simplification of the number of size classes to one average class, resulted in up to 3.3 times lower values of retention compared to scenarios that used detailed size distributions. Local concentrations in sediment were underestimated up to 20 fold upon simplification of spatial heterogeneity or particle size distribution. We conclude that spatial heterogeneity should not be neglected when assessing the risks of ENPs.

For twenty-five world lakes and three engineered nanoparticles (ENP), lake retention was calculated using a uniformly mixed lake mass balance model. This follows similar approaches traditionally used in water quality management. Lakes were selected such that lake residence times, depths and areal hydraulic loadings covered the widest possible range among existing lakes. Sedimentation accounted for natural colloid as well as suspended solid settling regimes. An ENP-specific mixed sedimentation regime is proposed. This regime combines ENP sedimentation through slow settling with natural colloids from the water column, with faster settling with suspended solids from a selected part of the water column. Although sedimentation data and hydrodynamic concepts as such were not new, their first time combination for application to ENPs shows in which cases lake retention is important for these particles. In combination with ENP emission data, lake retention translates directly into potential risks of ENPs for lake benthic communities.

Exposure modeling of engineered nanomaterials requires input parameters such as sedimentation rates and heteroaggregation rates. Here, we estimate these rates using quiescent settling experiments under environmentally relevant conditions. We investigated 4 different nanomaterials (C60, CeO2, SiO2-Ag and PVP-Ag) in 6 different water types ranging from a small stream to seawater. In the presence of natural colloids, sedimentation rates ranged from 0.0001 m d(-1) for SiO2-Ag to 0.14 m d(-1) for C60. The apparent rates of heteroaggregation between nanomaterials and natural colloids were estimated using a novel method that separates heteroaggregation from homoaggregation using a simplified Smoluchowski-based aggregation-settling equation applied to data from unfiltered and filtered waters. The heteroaggregation rates ranged between 0.007 and 0.6 L mg(-1) day(-1), with the highest values observed in seawater. We argue that such system specific parameters are key to the development of dedicated water quality models for ENMs.

Estimating the environmental exposure to manufactured nanomaterials is part of risk assessment. Because nanoparticles aggregate with each other (homoaggregation) and with other particles (heteroaggregation), the main route of the removal of most nanoparticles from water is aggregation, followed by sedimentation. The authors used water samples from two rivers in Europe, the Rhine and the Meuse. To distinguish between small (mainly natural organic matter [NOM]) particles and the remainder of the natural colloids present, both filtered and unfiltered river water was used to prepare the particle suspensions. The results show that the removal of nanoparticles from natural river water follows first-order kinetics toward a residual concentration. This was measured in river water with less than 1 mg L(-1) CeO(2) nanoparticles. The authors inferred that the heteroaggregation with or deposition onto the solid fraction of natural colloids was the main mechanism causing sedimentation in relation to homoaggregation. In contrast, the NOM fraction in filtered river water stabilized the residual nanoparticles against further sedimentation for up to 12 d. In 10 mg L(-1) and 100 mg L(-1) CeO(2) nanoparticle suspensions, homoaggregation is likely the main mechanism leading to sedimentation. The proposed model could form the basis for improved exposure assessment for nanomaterials.

The ecological risk assessment of chemicals including nanoparticles is based on the determination of adverse effects on organisms and on the environmental concentrations to which biota are exposed. The aim of this work was to better understand the behavior of nanoparticles in the environment, with the ultimate goal of predicting future exposure concentrations in water. We measured the concentrations and particle size distributions of CeO(2) nanoparticles in algae growth medium and deionized water in the presence of various concentrations and two types of natural organic matter (NOM). The presence of natural organic matter stabilizes the CeO(2) nanoparticles in suspension. In presence of NOM, up to 88% of the initially added CeO(2) nanoparticles remained suspended in deionized water and 41% in algae growth medium after 12d of settling. The adsorbed organic matter decreases the zeta potential from about -15 mV to -55 mV. This reduces aggregation by increased electrostatic repulsion. The particle diameter, pH, electric conductivity and NOM content shows significant correlation with the fraction of CeO(2) nanoparticles remaining in suspension.

Cerium dioxide nanoparticles (CeO2 NPs) are increasingly being used as a catalyst in the automotive industry. Consequently, increasing amounts of CeO2 NPs are expected to enter the environment where their fate in and potential impacts are unknown. In this paper we describe the fate and effects of CeO2 NPs of three different sizes (14, 20, and 29 nm) in aquatic toxicity tests. In each standard test medium (pH 7.4) the CeO2 nanoparticles aggregated (mean aggregate size approximately 400 nm). Four test organisms covering three different trophic levels were investigated, i.e., the unicellular green alga Pseudokirchneriella subcapitata, two crustaceans: Daphnia magna and Thamnocephalus platyurus, and embryos of Danio rerio. No acute toxicity was observed for the two crustaceans and D. rerio embryos, up to test concentrations of 1000, 5000, and 200 mg/L, respectively. In contrast, significant chronic toxicity to P. subcapitata with 10% effect concentrations (EC10s) between 2.6 and 5.4 mg/L was observed. Food shortage resulted in chronic toxicity to D. magna, for wich EC10s ofor = 8.8 andor = 20.0 mg/L were established. Chronic toxicity was found to increase with decreasing nominal particle diameter and the difference in toxicity could be explained by the difference in surface area. Using the data set, PNEC(aquatic)Sor = 0.052 andor = 0.108 mg/L were derived. Further experiments were performed to explain the observed toxicity to the most sensitive organism, i.e., P. subcapitata. Toxicity could not be related to a direct effect of dissolved Ce or CeO2 NP uptake or adsorption, nor to an indirect effect of nutrient depletion (by sorption to NPs) or physical light restriction (through shading by the NPs). However, observed clustering of NPs around algal cells may locally cause a direct or indirect effect.

Surface water used for drinking-water preparation requires continuous monitoring for the presence of toxic compounds. For monitoring of genotoxic compounds fish models have been developed, such as the Eastern mudminnow (Umbra pygmaea L.) because of its clearly visible 22 meta-centric chromosomes. It was demonstrated in the late seventies that Rhine water was able to induce chromosome aberrations and sister chromatid exchange in this fish species. Although in vitro mutagenicity studies of the RIWA (Rhine Water Works, The Netherlands) have shown that the genotoxicity of the river Rhine steadily decreased during the last decades, there is still concern about the presence of some residual mutagenicity. In addition, in most studies the water samples have been tested only in in vitro test systems such as the Salmonella-microsome test. For this reason, and in order to be able to make a comparison with the water quality 27 years ago, a study was performed with the same experimental design as before in order to measure the effect of Rhine water on the induction of SCE in the Eastern mudminnow. As a new test system the single cell gel electrophoresis assay (Comet assay) was performed. Fish were exposed to Rhine water or to groundwater for 3 and 11 days in flow-through aquaria. Fish exposed for 11 days to Rhine water had a significantly higher number of SCE and an increased comet tail-length compared with control fish exposed to groundwater. After exposure for three days to Rhine water there was no difference in SCE and a slightly increased comet tail-length compared with the control. It was concluded that genotoxins are still present in the river Rhine, but that the genotoxic potential has markedly decreased compared with 27 years ago. Furthermore, the Comet assay appears to be a sensitive assay to measure the genotoxic potential of surface waters in fish.

Nanomaterial risk governance requires models to estimate the material flow, fate and transport as well as uptake/bioavailability, hazard and risk in the environment. This study assesses the fit of such available models to different stages during the innovation of nano-enabled products. Through stakeholder consultations, criteria were identified for each innovation stage from idea conception to market launch and monitoring. In total, 38 models were scored against 41 criteria concerning model features, applicability, resource demands and outcome parameters. A scoring scheme was developed to determine how the models fit the criteria of each innovation stage. For each model, the individual criteria scores were added, yielding an overall fit score to each innovation stage. Three criteria were critical to stakeholders and incorporated as multipliers in the scoring scheme; the required time/costs and level of expertise needed to use the model, and for risk assessment models only, the option to compare PEC and PNEC. Regulatory compliance was also identified as critical, but could not be incorporated, as a nanomaterial risk assessment framework has yet to be developed and adopted by legislators. In conclusion, the scoring approach underlined similar scoring profiles across stages within model categories. As most models are research tools designed for use by experts, their score generally increased for later stages where most resources and expertise are committed. In contrast, stakeholders need relatively simple models to identify potential hazards and risk management measures at early product development stages to ensure safe use of nanomaterials without costs and resource needs hindering innovation. acceptedVersion