Comparison of species sensitivity distribution modeling approaches for environmental risk assessment of nanomaterials - A case study for silver and titanium dioxide representative materials.

Species sensitivity distributions (SSDs) are used in chemical safety assessments to derive predicted-no-effect-concentrations (PNECs) for substances with a sufficient amount of relevant and reliable ecotoxicity data available. For engineered nanomaterials (ENMs), ecotoxicity data are often compromised by poor reproducibility and the lack of nano-specific characterization needed describe an ENM under test exposure conditions. This may influence the outcome of SSD modelling and hence the regulatory decision-making. This study investigates how the outcome of SSD modelling is influenced by: 1) Selecting input data based on the nano-specific "nanoCRED" reliability criteria, 2) Direct SSD modelling avoiding extrapolation of data by including long-term/chronic NOECs only, and 3) Weighting data according to their nano-specific quality, the number of data available for each species, and the trophic level abundance in the ecosystem. Endpoints from freshwater ecotoxicity studies were collected for the representative nanomaterials NM-300 K (silver) and NM-105 (titanium dioxide), evaluated for regulatory reliability and scored according to the level of nano-specific characterization conducted. The compiled datasets are unique in exclusively dealing with representative ENMs showing minimal batch-to-batch variation. The majority of studies were evaluated as regulatory reliable, while the degree of nano-specific characterization varied greatly. The datasets for NM-300 K and NM-105 were used as input to the nano-weighted n-SSWD model, the probabilistic PSSD+, and the conventional SSD Generator by the US EPA. The conventional SSD generally yielded the most conservative, but least precise HC5 values, with 95 % confidence intervals up to 100-fold wider than the other models. The inclusion of regulatory reliable data only, had little effect on the HC5 generated by the conventional SSD and the PSSD+, whereas the n-SSWD estimated different HC5 values based on data segregated according to reliability, especially for NM-105. The n-SSWD weighting of data significantly affected the estimated HC5 values, however in different ways for the sub-datasets of NM-300 K and NM-105. For NM-300 K, the inclusion of NOECs only in the weighted n-SSWD yielded the most conservative HC5 of all datasets and models (a HC5 based on NOECs only could not be estimated for NM-105, due to limited number of data). Overall, the estimated HC5 values of all models are within a relatively limited concentration range of 25-100 ng Ag/L for NM-300 K and 1-15 µgTiO2/L for NM-105.

Systematic Consideration of Parameter Uncertainty and Variability in Probabilistic Species Sensitivity Distributions.

The calculation of a species sensitivity distribution (SSD) is a commonly accepted approach to derive the predicted no-effect concentration (PNEC) of a substance in the context of environmental risk assessment. The SSD approach usually is data demanding and incorporates a large number of ecotoxicological values from different experimental studies. The probabilistic SSD (PSSD) approach is able to fully consider the variability between different exposure conditions and material types, which is of great importance when constructing an SSD for any chemical, especially for nanomaterials. The aim of our work was to further develop the PSSD approach by implementing methods to better consider the uncertainty and variability of the input data. We incorporated probabilistic elements to consider the uncertainty associated with uncertainty factors by using probability distributions instead of single values. The new PSSD method (named "PSSD+") computes 10 000 PSSDs based on a Monte Carlo routine. For each PSSD calculated, the hazardous concentration for 5% of species (HC5 ) was extracted to provide a PNEC distribution based on all data available and their associated uncertainty. The PSSD+ approach also includes the option to consider a species weighting according to a typically constituted biome. We applied this PSSD+ approach to a previously published data set on C nanotubes and Ag nanoparticles. The evaluation of the uncertainty factor distributions and species weighting have shown that the proposed PSSD method is robust with respect to the calculation of the PNEC value. Furthermore, we demonstrated that the PSSD+ can handle both small and more comprehensive data sets because the PNEC distributions are a close representation of the data available. Finally, the sensitivity testing toward data set variations showed that the maximum variation of the mean PNEC was of a factor of about 2, so that the method is relatively insensitive to missing data points as long as the most sensitive species is included. Integr Environ Assess Manag 2020;16:211-222. © 2019 SETAC.

Material-specific properties applied to an environmental risk assessment of engineered nanomaterials - implications on grouping and read-across concepts.

Engineered nanomaterials (ENMs) are intentionally designed in different nano-forms of the same parent material in order to meet application requirements. Different grouping and read-across concepts are proposed to streamline risk assessments by pooling nano-forms in one category. Environmental grouping concepts still are in their infancy and mainly focus on grouping by hazard categories. Complete risk assessments require data on environmental release and exposure not only for ENMs but also for their nano-forms. The key requirement is to identify and to distinguish the production volumes of the ENMs regarding nano-form-specific applications. The aim of our work was to evaluate whether such a grouping is possible with the available data and which influence it has on the environmental risk assessment of ENMs. A functionality-driven approach was applied to match the material-specific property (i.e. crystal form/morphology) with the functions employed in the applications. We demonstrate that for nano-TiO2, carbon nanotubes (CNTs), and nano-Al2O3 the total production volume can be allocated to specific nano-forms based on their functionalities. The differentiated assessments result in a variation of the predicted environmental concentrations for anatase vs. rutile nano-TiO2, single-wall vs. multi-wall CNTs and α- vs. γ-nano-Al2O3 by a factor of 2 to 13. Additionally, the nano-form-specific predicted no-effect concentrations for these ENMs were derived. The risk quotients for all nano-forms indicated no immediate risk in freshwaters. Our results suggest that grouping and read-across concepts should include both a nano-form release potential for estimating the environmental exposure and separately consider the nano-forms in environmental risk assessments.

Risks, Release and Concentrations of Engineered Nanomaterial in the Environment.

For frequently used engineered nanomaterials (ENMs) CeO2-, SiO2-, and Ag, past, current, and future use and environmental release are investigated. Considering an extended period (1950 to 2050), we assess ENMs released through commercial activity as well as found in natural and technical settings. Temporal dynamics, including shifts in release due to ENM product application, stock (delayed use), and subsequent end-of-life product treatment were taken into account. We distinguish predicted concentrations originating in ENM use phase and those originating from end-of-life release. Furthermore, we compare Ag- and CeO2-ENM predictions with existing measurements. The correlations and limitations of the model, and the analytic validity of our approach are discussed in the context of massive use of assumptive model data and high uncertainty on the colloidal material captured by the measurements. Predictions for freshwater CeO2-ENMs range from 1 pg/l (2017) to a few hundred ng/l (2050). Relative to CeO2, the SiO2-ENMs estimates are approximately 1,000 times higher, and those for Ag-ENMs 10 times lower. For most environmental compartments, ENM pose relatively low risk; however, organisms residing near ENM 'point sources' (e.g., production plant outfalls and waste treatment plants), which are not considered in the present work, may be at increased risk.

Influences of use activities and waste management on environmental releases of engineered nanomaterials.

Engineered nanomaterials (ENM) offer enhanced or new functionalities and properties that are used in various products. This also entails potential environmental risks in terms of hazard and exposure. However, hazard and exposure assessment for ENM still suffer from insufficient knowledge particularly for product-related releases and environmental fate and behavior. This study therefore analyzes the multiple impacts of the product use, the properties of the matrix material, and the related waste management system (WMS) on the predicted environmental concentration (PEC) by applying nine prospective life cycle release scenarios based on reasonable assumptions. The products studied here are clothing textiles treated with silver nanoparticles (AgNPs), since they constitute a controversial application. Surprisingly, the results show counter-intuitive increases by a factor of 2.6 in PEC values for the air compartment in minimal AgNP release scenarios. Also, air releases can shift from washing to wearing activity; their associated release points may shift accordingly, potentially altering release hot spots. Additionally, at end-of-life, the fraction of AgNP-residues contained on exported textiles can be increased by 350% when assuming short product lifespans and globalized WMS. It becomes evident that certain combinations of use activities, matrix material characteristics, and WMS can influence the regional PEC by several orders of magnitude. Thus, in the light of the findings and expected ENM market potential, future assessments should consider these aspects to derive precautionary design alternatives and to enable prospective global and regional risk assessments.

Intrinsically green iron oxide nanoparticles? From synthesis via (eco-)toxicology to scenario modelling.

Iron oxide nanoparticles (IONP) are currently being studied as green magnet resonance imaging (MRI) contrast agents. They are also used in huge quantities for environmental remediation and water treatment purposes, although very little is known on the consequences of such applications for organisms and ecosystems. In order to address these questions, we synthesised polyvinylpyrrolidone-coated IONP, characterised the particle dispersion in various media and investigated the consequences of an IONP exposure using an array of biochemical and biological assays. Several theoretical approaches complemented the measurements. In aqueous dispersion IONP had an average hydrodynamic diameter of 25 nm and were stable over six days in most test media, which could also be predicted by stability modelling. The particles were tested in concentrations of up to 100 mg Fe per L. The activity of the enzymes glutathione reductase and acetylcholine esterase was not affected, nor were proliferation, morphology or vitality of mammalian OLN-93 cells although exposure of the cells to 100 mg Fe per L increased the cellular iron content substantially. Only at this concentration, acute toxicity tests with the freshwater flea Daphnia magna revealed slightly, yet insignificantly increased mortality. Two fundamentally different bacterial assays, anaerobic activated sludge bacteria inhibition and a modified sediment contact test with Arthrobacter globiformis, both rendered results contrary to the other assays: at the lowest test concentration (1 mg Fe per L), IONP caused a pronounced inhibition whereas higher concentrations were not effective or even stimulating. Preliminary and prospective risk assessment was exemplified by comparing the application of IONP with gadolinium-based nanoparticles as MRI contrast agents. Predicted environmental concentrations were modelled in two different scenarios, showing that IONP could reduce the environmental exposure of toxic Gd-based particles by more than 50%. Application of the Swiss "Precautionary Matrix for Synthetic Nanomaterials" rendered a low precautionary need for using our IONP as MRI agents and a higher one when using them for remediation or water treatment. Since IONP and (considerably more reactive) zerovalent iron nanoparticles are being used in huge quantities for environmental remediation purposes, it has to be ascertained that these particles pose no risk to either human health or to the environment.