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

Predicting environmental concentrations of nanomaterials for exposure assessment - a review

There have been major advances in the science to predict the likely environmental concentrations of nanomaterials, which is a key component of exposure and subsequent risk assessment. Considerable progress has been since the first Material Flow Analyses (MFAs) in 2008, which were based on very limited information, to more refined current tools that take into account engineered nanoparticle (ENP) size distribution, form, dynamic release, and better-informed release factors. These MFAs provide input for all environmental fate models (EFMs), that generate estimates of particle flows and concentrations in various environmental compartments. While MFA models provide valuable information on the magnitude of ENP release, they do not account for fate processes, such as homo- and heteroaggregation, transformations, dissolution, or corona formation. EFMs account for these processes in differing degrees. EFMs can be divided into multimedia compartment models (e.g., atmosphere, waterbodies and their sediments, soils in various landuses), of which there are currently a handful with varying degrees of complexity and process representation, and spatially-resolved watershed models which focus on the water and sediment compartments. Multimedia models have particular applications for considering predicted environmental concentrations (PECs) in particular regions, or for developing generic "fate factors" (i.e., overall persistence in a given compartment) for life-cycle assessment. Watershed models can track transport and eventual fate of emissions into a flowing river, from multiple sources along the waterway course, providing spatially and temporally resolved PECs. Both types of EFMs can be run with either continuous sources of emissions and environmental conditions, or with dynamic emissions (e.g., temporally varying for example as a new nanomaterial is introduced to the market, or with seasonal applications), to better understand the situations that may lead to peak PECs that are more likely to result in exceedance of a toxicological threshold. In addition, bioaccumulation models have been developed to predict the internal concentrations that may accumulate in exposed organisms, based on the PECs from EFMs. The main challenge for MFA and EFMs is a full validation against observed data. To date there have been no field studies that can provide the kind of dataset(s) needed for a true validation of the PECs. While EFMs have been evaluated against a few observations in a small number of locations, with results that indicate they are in the right order of magnitude, there is a great need for field data. Another major challenge is the input data for the MFAs, which depend on market data to estimate the production of ENPs. The current information has major gaps and large uncertainties. There is also a lack of robust analytical techniques for quantifying ENP properties in complex matrices; machine learning may be able to fill this gap. Nevertheless, there has been major progress in the tools for generating PECs. With the emergence of nano- and microplastics as a leading environmental concern, some EFMs have been adapted to these materials. However, caution is needed, since most nano- and microplastics are not engineered, therefore their characteristics are difficult to generalize, and there are new fate and transport processes to consider.

Prospective Dynamic and Probabilistic Material Flow Analysis of Graphene-Based Materials in Europe from 2004 to 2030

As industrial demand for graphene-based materials (GBMs) grows, more attention falls on potential environmental risks. The present article describes a first assessment of the environmental releases of GBMs using dynamic probabilistic material flow analysis. The model considered all current or expected uses of GBMs from 2004 to 2030, during which time there have already been significant changes in how the graphene mass produced is distributed to different product categories. Although the volume of GBM production is expected to grow exponentially in the coming years, outflow from the consumption of products containing GBMs shows only a slightly positive trend due to their long lifetimes and the large in-use stock of some applications (e.g., GBM composites used in wind turbine blades). From consumption and end-of-life phase GBM mass flows in 2030, estimates suggest that more than 50% will be incinerated and oxidized in waste plants, 16% will be landfilled, 12% will be exported out of Europe, and 1.4% of the annual production will flow to the environment. Predicted release concentrations for 2030 are 1.4 ng/L in surface water and 20 μg/kg in sludge-treated soil. This study's results could be used for prospective environmental risk assessments and as input for environmental fate models.

Impacts of a novel controlled-release TiO2-coated (nano-) formulation of carbendazim and its constituents on freshwater macroinvertebrate communities

Recently, the delivery of pesticides through novel controlled-release (nano-)formulations has been proposed intending to reduce (incidental) pesticide translocation to non-target sites. Concerns have however been raised with regards to the potentially enhanced toxicity of controlled-release (nano-)formulations to non-target organisms and ecosystems. We evaluated long-term (i.e. 1 and 3 month-) impacts of a novel controlled-release pesticide formulation (nano-TiO₂-coated carbendazim) and its individual and combined constituents (i.e. nano-sized TiO₂ and carbendazim) on naturally established freshwater macroinvertebrate communities. In doing so, we simultaneously assessed impacts of nano-sized TiO₂ (nTiO₂), currently one of the most used and emitted engineered nanomaterials world-wide. We determined ecological impacts on diversity (i.e. β-diversity), structure (i.e. rank abundance parameters), and functional composition (i.e. feeding guilds & trophic groups) of communities and underlying effects at lower organizational levels (i.e. population dynamics of individual taxa). Freshwater macroinvertebrate communities were negligibly impacted by nTiO₂ at environmentally realistic concentrations. The controlled-release (nano-)formulation significantly delayed release of carbendazim to the water column. Nevertheless, conventional- (i.e. un-coated-) and nTiO₂-coated carbendazim induced a similar set of adverse impacts at all investigated levels of ecological organization and time points. Our findings show fundamental restructuring of the taxonomic- and functional composition of macroinvertebrate communities as a result of low-level pesticide exposure, and thereby highlight the need for mitigating measures to reduce pesticide-induced stress on freshwater ecosystems.

Correlation analysis of single- and multigenerational endpoints in Daphnia magna toxicity tests: A case-study using TiO2 nanoparticles

Multigenerational toxicity tests provide more sensitive measures of population-level effects than conventional single-generation tests. Particularly for stressors which exhibit slow uptake rates (e.g. nanomaterials), multigenerational tests may also provide a more realistic representation of natural exposure scenarios. To date, the inherently high costs and labor intensity have however limited the use of multigenerational toxicity tests and thereby their incorporation in environmental risk assessment. The aim of the present study was therefore to determine to what extent short(er) term endpoints which are conventionally measured in Daphnia magna toxicity tests hold predictive capacity towards reproduction measured over longer timescales, including multiple generations. To assess this, a case-study was performed in which effects of TiO₂ nanoparticles (0, 0.02, 0.2, 2 and 5 mg L^-1) on D. magna life-history traits were assessed over five generations. Additionally, it was determined whether offspring derived from exposed parents exhibited sustained adverse effects when rearing them in clean (non-exposed) media after each generation of exposure. The present study showed that although various life-history traits correlate with the total reproductive output in the same- and subsequent generation under non-exposed conditions, these correlations were decoupled in presence of exposure to nTiO₂. In addition, it was found that nTiO₂ can induce adverse effects on population relevant endpoints at concentrations 1-2 orders of magnitude lower than previously found (i.e. 0.02 mg L^-1), and close to the range of concentrations occurring in natural freshwater ecosystems.

Nanosafety: An Evolving Concept to Bring the Safest Possible Nanomaterials to Society and Environment

The use of nanomaterials has been increasing in recent times, and they are widely used in industries such as cosmetics, drugs, food, water treatment, and agriculture. The rapid development of new nanomaterials demands a set of approaches to evaluate the potential toxicity and risks related to them. In this regard, nanosafety has been using and adapting already existing methods (toxicological approach), but the unique characteristics of nanomaterials demand new approaches (nanotoxicology) to fully understand the potential toxicity, immunotoxicity, and (epi)genotoxicity. In addition, new technologies, such as organs-on-chips and sophisticated sensors, are under development and/or adaptation. All the information generated is used to develop new in silico approaches trying to predict the potential effects of newly developed materials. The overall evaluation of nanomaterials from their production to their final disposal chain is completed using the life cycle assessment (LCA), which is becoming an important element of nanosafety considering sustainability and environmental impact. In this review, we give an overview of all these elements of nanosafety.

Collection of Controlled Nanosafety Data—The CoCoN-Database, a Tool to Assess Nanomaterial Hazard

Hazard assessment is the first step in nanomaterial risk assessment. The overall number of studies on the biological effects of nanomaterials or innovative materials is steadily increasing and is above 40,000. Several databases have been established to make the amount of data manageable, but these are often highly specialized or can be used only by experts. This paper describes a new database which uses an already existing data collection of about 35,000 publications. The collection from the first phase between the years 2000 and 2013 contains about 11,000 articles and this number has been reduced by specific selection criteria. The resulting publications have been evaluated for their quality regarding the toxicological content and the experimental data have been extracted. In addition to material properties, the most important value to be extracted is the no-observed-adverse-effect-level (NOAEL) for in vivo and the no-observed-effect-concentration (NOEC) for in vitro studies. The correlation of the NOAEL/NOEC values with the nanomaterial properties and the investigated endpoints has been tested in projects such as the OECD-AOP project, where the available data for inflammatory responses have been analysed. In addition, special attention was paid to titanium dioxide particles and this example is used to show with searches for in vitro and in vivo experiments on possible lung toxicity what a typical result of a database query can look like. In this review, an emerging database is described that contains valuable information for nanomaterial hazard estimation and should aid in the progress of nanosafety research.

Recent Advancements in the Nanomaterial Application in Concrete and Its Ecological Impact

At present, nanotechnology is a significant research area in different countries, owing to its immense ability along with its economic impact. Nanotechnology is the scientific study, development, manufacturing, and processing of structures and materials on a nanoscale level. It has tremendous application in different industries such as construction. This study discusses the various progressive uses of nanomaterials in concrete, as well as their related health risks and environmental impacts. Nanomaterials such as nanosilica, nano-TiO₂, carbon nanotubes (CNTs), ferric oxides, polycarboxylates, and nanocellulose have the capability to increase the durability of buildings by improving their mechanical and thermal properties. This could cause an indirect reduction in energy usage and total expenses in the concrete industry. However, due to the uncertainties and irregularities in size, shape, and chemical compositions, some nanosized materials might have harmful effects on the environment and human health. Acknowledgement of the possible beneficial impacts and inadvertent dangers of these nanosized materials to the environment will be extremely important when pursuing progress in the upcoming years. This research paper is expected to bring proper attention to the probable effects of construction waste, together with the importance of proper regulations, on the final disposal of the construction waste.

Form-Specific and Probabilistic Environmental Risk Assessment of 3 Engineered Nanomaterials (Nano-Ag, Nano-TiO2 , and Nano-ZnO) in European Freshwaters

The release of engineered nanomaterials (ENMs) to the environment necessitates an assessment of their environmental risks. The currently available environmental risk assessments (ERA) for ENMs are based on an analysis of the total flows of a specific ENM to the environment and on ecotoxicity studies performed with pristine ENMs. It is known that ENMs undergo transformation during product use and release and in technical systems such as wastewater treatment. The aim of the present study was therefore to perform an ERA of 3 ENMs (nano-Ag, nano-TiO2 , and nano-ZnO) based on a form-specific release model and a form-specific analysis of ecotoxicological data. Predicted environmental concentration values were derived using a form-specific material flow model. Species sensitivity distributions were used to derive predicted-no-effect concentrations (PNECs) for the pristine ENMs and for dissolved and transformed Ag and ZnO. For all ENMs, the matrix-embedded form was included in the assessment. A probabilistic assessment was applied, yielding final probability distributions for the risk characterization ratio (RCR). For nano-Ag, the form-specific assessment resulted in a decrease of the mean RCR from 0.061 for the approach neglecting the different release forms to 0.034 because of the much lower PNEC of transformed Ag. Likewise, for nano-ZnO, the form-specific approach reduced the mean RCR from 1.2 to 0.86. For nano-TiO2 , the form-specific assessment did not change the mean RCR of 0.026. This analysis shows that a form-specific approach can have an influence on the assessment of the environmental risks of ENMs and that, given the availability of form-specific release models, an updated ERA for ENMs can be performed. Environ Toxicol Chem 2021;40:2629-2639. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Integrated dynamic probabilistic material flow analysis of engineered materials in all European countries

Uncertainties remain regarding the potential environmental risks of engineered nanomaterials, reflecting missing information on both the exposure and the hazard sides. Probabilistic material flow analysis (PMFA) is a useful exposure assessment tool that maps the flows of a substance through its lifecycle towards the environment, taking into account the uncertainties associated with the input data. In the last years, several refinements have been made to the original PMFA method, increasing its complexity with respect to systems dynamics, fate during recycling and reprocessing and forms of release. In this work, an integrated dynamic probabilistic material flow analysis (IDPMFA) was developed that combines all separate advancements of the method in one overarching software code. The new method was used to assess the forms in which nano-Ag, nano-TiO₂ and nano-ZnO are released into air, soils and surface water. Each European country (EU28, Norway and Switzerland) was studied from the year 2000 to the year 2020. The present model includes new assessments of the forms in which nano-ZnO is released into the environment and of the flows out of reprocessing (last step of recycling) of nano-Ag, nano-TiO₂ and nano-ZnO towards both technical and environmental compartments. The forms of ZnO released to different compartments vary greatly with different proportions between pristine, dissolved, matrix-embedded and transformed forms. The same applies for the forms of the other ENMs released after reprocessing, where different processes result in very different distributions between the various forms. The country-specific assessment showed that it is mainly the different solid waste treatment schemes that influence the distribution to final environmental sinks. Overall, the results of IDPMFA show the great importance of considering the full life cycle of nanoproducts including the different stages of recycling, the differences between countries, and the forms of the released materials. The results from the integrated model will provide useful input information for environmental fate models and for environmental risk assessments.

Size-Specific, Dynamic, Probabilistic Material Flow Analysis of Titanium Dioxide Releases into the Environment

Most of the existing exposure models for engineered nanomaterials (ENMs) do not consider particle size, crystalline forms, and coating materials that all may influence the material's fate, transport, and toxicity. Our work aimed to incorporate particle size distributions into a material flow analysis (MFA) to develop a size-specific, dynamic, probabilistic MFA model (ss-DPMFA). Using titanium dioxide (TiO₂) as a first case study, we aimed to determine the contribution of conventional TiO₂ pigments to the total amount of nanoscale TiO₂ released into the environment. Besides providing information on mass flows, the new model used particle size distributions and crystalline forms to describe the stocks and flows of TiO₂. The most striking modeling result to emerge was that before TiO₂ ENMs came onto the market as such in 2000, 22,400 tons of nanosized (<100 nm) TiO₂ particles had already been released into the environment, originating from conventional TiO₂ pigments. Even in 2016, 50% of the nanosized TiO₂ particles released into wastewater came from the nanosized fraction of TiO₂ particles in pigments. Quantitative data on the particle size distribution of TiO₂ particles released into the environment can be used as input for environmental fate models. Our new ss-DPMFA model's additional insights about crystalline forms and coatings could pave the way for advanced size- and form-specific hazard and risk assessments for other nanomaterials in ecological systems.

Environmental Risk Assessment of Nanomaterials in the Light of New Obligations Under the REACH Regulation: Which Challenges Remain and How to Approach Them?

Within the European regulation on the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH, EC No 1907/2006) specific provisions for nanomaterials were included, which have become effective on 1 January 2020. Although knowledge on the peculiarities of testing and assessing fate and effects of nanomaterials in the environment strongly increased in the last years, uncertainties about how to perform a reliable and robust environmental risk assessment for nanomaterials still remain. These uncertainties are of special relevance in a regulatory context, challenging both industry and regulators. The present paper presents current challenges in regulatory hazard and exposure assessment under REACH, as well as classification of nanomaterials, and makes proposals to address them. Still, the nanospecific considerations made here are expected to also be valid for environmental risk assessment approaches in other regulations of chemical safety. Inter alia, these proposals include a way forward to account for exposure concentrations in aquatic toxicity test systems, a discussion of how to account for availability of dissolving nanomaterials in aquatic test systems, and a pragmatic proposal to deduce effect data for soil organisms. Furthermore, it specifies how to potentially deal with nanoforms under the European regulation on Classification, Labelling and Packaging of substances and mixtures (CLP) and outlines the needs for proper exposure assessments of nanomaterials from a regulatory perspective. Integr Environ Assess Manag 2020;16:706-717. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Development of Deep Learning Models for Predicting the Effects of Exposure to Engineered Nanomaterials on Daphnia magna

This study presents the results of applying deep learning methodologies within the ecotoxicology field, with the objective of training predictive models that can support hazard assessment and eventually the design of safer engineered nanomaterials (ENMs). A workflow applying two different deep learning architectures on microscopic images of Daphnia magna is proposed that can automatically detect possible malformations, such as effects on the length of the tail, and the overall size, and uncommon lipid concentrations and lipid deposit shapes, which are due to direct or parental exposure to ENMs. Next, classification models assign specific objects (heart, abdomen/claw) to classes that depend on lipid densities and compare the results with controls. The models are statistically validated in terms of their prediction accuracy on external D. magna images and illustrate that deep learning technologies can be useful in the nanoinformatics field, because they can automate time-consuming manual procedures, accelerate the investigation of adverse effects of ENMs, and facilitate the process of designing safer nanostructures. It may even be possible in the future to predict impacts on subsequent generations from images of parental exposure, reducing the time and cost involved in long-term reproductive toxicity assays over multiple generations.

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.

Crystalline phase-dependent toxicity of aluminum oxide nanoparticles toward Daphnia magna and ecological risk assessment

Aluminum oxide nanoparticles (Al₂O₃ NPs) can be found in different crystalline phases, and with the emergence of nanotechnology there has been a rapid increase in the demand for Al₂O₃ NPs in different engineering areas and for consumer products. However, a careful evaluation of the potential environmental and human health risks is required to assess the implications of the release of Al₂O₃ NPs into the environment. Thus, the objective of this study was to investigate the toxicity of two crystalline phases of Al₂O₃ NPs, alpha (α-Al₂O₃ NPs) and eta (η-Al₂O₃ NPs), toward Daphnia magna and evaluate the risk to the aquatic ecology of Al₂O₃ NPs with different crystalline phases, based on a probabilistic approach. Different techniques were used for the characterization of the Al₂O₃ NPs. The toxicity toward Daphnia magna was assessed based on multiple toxicological endpoints, and the probabilistic species sensitivity distribution (PSSD) was used to estimate the risk of Al₂O₃ NPs to the aquatic ecology. The results obtained verify the toxic potential of the NPs toward D. magna even in sublethal concentrations, with a more pronounced effect being observed for η-Al₂O₃ NPs. The toxicity is associated with an increase in the reactive oxygen species (ROS) content and deregulation of antioxidant enzymatic/non-enzymatic enzymes (CAT, SOD and GSH). In addition, changes in MDA levels were observed, indicating that D. magna was under oxidative stress. The most prominent chronic toxic effects were observed in the organisms exposed to η-Al₂O₃ NPs, since the lowest LOEC was 3.12 mg/L for all parameters, while for α-Al₂O₃ NPs the lowest LOEC was 6.25 mg/L for longevity, growth and reproduction. However, the risk assessment results indicate that, based on a probabilistic approach, Al₂O₃ NPs (alpha, gamma, delta, eta and theta) only a very limited risk to organisms in surface waters.

Hepatotoxicity and the role of the gut-liver axis in rats after oral administration of titanium dioxide nanoparticles

Background

Due to its excellent physicochemical properties and wide applications in consumer goods, titanium dioxide nanoparticles (TiO₂ NPs) have been increasingly exposed to the environment and the public. However, the health effects of oral exposure of TiO₂ NPs are still controversial. This study aimed to illustrate the hepatotoxicity induced by TiO₂ NPs and the underlying mechanisms. Rats were administered with TiO₂ NPs (29 nm) orally at exposure doses of 0, 2, 10, 50 mg/kg daily for 90 days. Changes in the gut microbiota and hepatic metabolomics were analyzed to explore the role of the gut-liver axis in the hepatotoxicity induced by TiO₂ NPs.

Results

TiO₂ NPs caused slight hepatotoxicity, including clear mitochondrial swelling, after subchronic oral exposure at 50 mg/kg. Liver metabolomics analysis showed that 29 metabolites and two metabolic pathways changed significantly in exposed rats. Glutamate, glutamine, and glutathione were the key metabolites leading the generation of energy-related metabolic disorders and imbalance of oxidation/antioxidation. 16S rDNA sequencing analysis showed that the diversity of gut microbiota in rats increased in a dose-dependent manner. The abundance of Lactobacillus_reuteri increased and the abundance of Romboutsia decreased significantly in feces of TiO₂ NPs-exposed rats, leading to changes of metabolic function of gut microbiota. Lipopolysaccharides (LPS) produced by gut microbiota increased significantly, which may be a key factor in the subsequent liver effects.

Conclusions

TiO₂ NPs could induce slight hepatotoxicity at dose of 50 mg/kg after long-term oral exposure. The indirect pathway of the gut-liver axis, linking liver metabolism and gut microbiota, played an important role in the underlying mechanisms.