Seaweeds as a major source of dietary microplastics exposure in East Asia

Microplastics (MPs) occurrence in marine ecosystems is well known, but their accumulation in seaweeds and subsequent human exposure remain understudied. This research quantifies MPs presence in two commonly consumed seaweeds, kelp (Saccharina japonica) and nori (Pyropia yezoensis), in East Asia, revealing widespread contamination dominated by microfibers (<500 μm). Based on dietary patterns, human uptake through seaweed consumption was estimated and quantified. Notably, Chinese people consume an estimated 17,034 MPs/person/year through seaweed consumption, representing 13.1% of their total annual MPs intake. This seaweeds-derived exposure surpasses all other dietary sources, contributing up to 45.5% of overall MPs intake. The highest intake was in South Korea, followed by North Korea, China, and Japan. This research identifies seaweeds as a major, previously overlooked route of dietary MPs exposure. These findings are crucial for comprehensive risk assessments of seaweed consumption and the development of mitigation strategies, particularly for populations in East Asian countries.

Emerging contaminants: A One Health perspective

Environmental pollution is escalating due to rapid global development that often prioritizes human needs over planetary health. Despite global efforts to mitigate legacy pollutants, the continuous introduction of new substances remains a major threat to both people and the planet. In response, global initiatives are focusing on risk assessment and regulation of emerging contaminants, as demonstrated by the ongoing efforts to establish the UN's Intergovernmental Science-Policy Panel on Chemicals, Waste, and Pollution Prevention. This review identifies the sources and impacts of emerging contaminants on planetary health, emphasizing the importance of adopting a One Health approach. Strategies for monitoring and addressing these pollutants are discussed, underscoring the need for robust and socially equitable environmental policies at both regional and international levels. Urgent actions are needed to transition toward sustainable pollution management practices to safeguard our planet for future generations.

Comparing the impact of microplastics derived from a biodegradable and a conventional plastic mulch on plant performance

Agricultural lands have been identified as plastic sinks. One source is plastic mulches, which are a source of micro- and nano-sized plastics in agricultural soils. Because of their persistence, there is now a push towards developing biodegradable plastics, which are designed to undergo (partial) breakdown after entering the environment. Yet, limited research has investigated the impacts of both conventional and biodegradable plastics on distinct plants. Moreover, comparisons among studies are difficult due to differences in experimental design. This study directly compares the effects of artificially weathered conventional polyethylene (PE) and starch-based biodegradable polybutylene adipate terephthalate (PBAT) on four food crops, including two monocots (barley, Hordeum vulgare, and wheat, Triticum aestivum L.) and two dicots (carrot, Daucus carota, and lettuce, Lactuca sativa L.). We investigated the effects of environmentally relevant low, medium, and high (0.01 %, 0.1 %, 1 % w/w) concentrations of PE and starch-PBAT blend on seed germination (acute toxicity), and subsequently on plant growth and chlorophyll through a pot-plant experiment (chronic toxicity). Germination of all species was not affected by both plastics. However, root length was reduced for lettuce and wheat seedlings. No other effects were recorded on monocots. We observed a reduction in shoot length and bud wet weight of carrot seedlings for the highest concentration of PE and starch-PBAT blend. Chronic exposure resulted in a significant decrease in shoot biomass of barley and lettuce. Additionally, a positive increase in the number of leaves of lettuce was observed for both plastics. Chlorophyll content was increased in lettuce when exposed to PE and starch-PBAT blend. Overall, adverse effects in dicots were more abundant than in monocots. Importantly, we found that the biodegradable plastic caused more commonly adverse effects on plants compared to conventional plastic, which was confirmed by a mini-review of studies directly comparing the impact of conventional and biodegradable microplastics.

Ototoxicity of polystyrene nanoplastics in mice, HEI-OC1 cells and zebrafish

Polystyrene nanoplastics are a novel class of pollutants. They are easily absorbed by living organisms, and their potential toxicity has raised concerns. However, the impact of polystyrene nanoplastics on auditory organs remains unknown. Here, our results showed that polystyrene nanoplastics entered the cochlea of mice, HEI-OC1 cells, and lateral line hair cells of zebrafish, causing cellular injury and increasing apoptosis. Additionally, we found that exposure to polystyrene nanoplastics resulted in a significant elevation in the auditory brainstem response thresholds, a loss of auditory sensory hair cells, stereocilia degeneration and a decrease in expression of Claudin-5 and Occludin proteins at the blood-lymphatic barrier in mice. We also observed a significant decrease in the acoustic alarm response of zebrafish after exposure to polystyrene nanoplastics. Mechanistic analysis revealed that polystyrene nanoplastics induced up-regulation of the Nrf2/HO-1 pathway, increased levels of malondialdehyde, and decreased superoxide dismutase and catalase levels in cochlea and HEI-OC1 cells. Furthermore, we observed that the expression of ferroptosis-related indicators GPX4 and SLC7A11 decreased as well as increased expression of ACLS4 in cochlea and HEI-OC1 cells. This study also revealed that polystyrene nanoplastics exposure led to increased expression of the inflammatory factors TNF-α, IL-1β and COX2 in cochlea and HEI-OC1 cells. Further research found that the cell apoptosis, ferroptosis and inflammatory reactions induced by polystyrene nanoplastics in HEI-OC1 cells was reversed through the pretreatment with N-acetylcysteine, a reactive oxygen species inhibitor. Overall, our study first discovered and systematically revealed the ototoxicity of polystyrene nanoplastics and its underlying mechanism.

Using Machine Learning to Predict Adverse Effects of Metallic Nanomaterials to Various Aquatic Organisms

The wide production and use of metallic nanomaterials (MNMs) leads to increased emissions into the aquatic environments and induces high potential risks. Experimentally evaluating the (eco)toxicity of MNMs is time-consuming and expensive due to the multiple environmental factors, the complexity of material properties, and the species diversity. Machine learning (ML) models provide an option to deal with heterogeneous data sets and complex relationships. The present study established an in silico model based on a machine learning properties-environmental conditions-multi species-toxicity prediction model (ML-PEMST) that can be applied to predict the toxicity of different MNMs toward multiple aquatic species. Feature importance and interaction analysis based on the random forest method indicated that exposure duration, illumination, primary size, and hydrodynamic diameter were the main factors affecting the ecotoxicity of MNMs to a variety of aquatic organisms. Illumination was demonstrated to have the most interaction with the other features. Moreover, incorporating additional detailed information on the ecological traits of the test species will allow us to further optimize and improve the predictive performance of the model. This study provides a new approach for ecotoxicity predictions for organisms in the aquatic environment and will help us to further explore exposure pathways and the risk assessment of MNMs.

Exposure protocol for ecotoxicity testing of microplastics and nanoplastics

Despite the increasing concern about the harmful effects of micro- and nanoplastics (MNPs), there are no harmonized guidelines or protocols yet available for MNP ecotoxicity testing. Current ecotoxicity studies often use commercial spherical particles as models for MNPs, but in nature, MNPs occur in variable shapes, sizes and chemical compositions. Moreover, protocols developed for chemicals that dissolve or form stable dispersions are currently used for assessing the ecotoxicity of MNPs. Plastic particles, however, do not dissolve and also show dynamic behavior in the exposure medium, depending on, for example, MNP physicochemical properties and the medium's conditions such as pH and ionic strength. Here we describe an exposure protocol that considers the particle-specific properties of MNPs and their dynamic behavior in exposure systems. Procedure 1 describes the top-down production of more realistic MNPs as representative of MNPs in nature and particle characterization (e.g., using thermal extraction desorption-gas chromatography/mass spectrometry). Then, we describe exposure system development for short- and long-term toxicity tests for soil (Procedure 2) and aquatic (Procedure 3) organisms. Procedures 2 and 3 explain how to modify existing ecotoxicity guidelines for chemicals to target testing MNPs in selected exposure systems. We show some examples that were used to develop the protocol to test, for example, MNP toxicity in marine rotifers, freshwater mussels, daphnids and earthworms. The present protocol takes between 24 h and 2 months, depending on the test of interest and can be applied by students, academics, environmental risk assessors and industries.

Expanding the applicability domain of QSPRs for predicting water solubility and vapor pressure of PFAS

This work aimed to verify whether it is possible to extend the applicability domain (AD) of existing QSPR (Quantitative Structure-Property Relationship) models by employing a strategy involving additional quantum-chemical calculations. We selected two published QSPR models: for water solubility, logSW, and vapor pressure, logVP of PFAS as case studies. We aimed to enlarge set of compounds used to build the model by applying factorial planning to plan the augmentation of the set of these compounds based on their structural features (descriptors). Next, we used the COSMO-RS model to calculate the logSW and logVP for selected chemicals. This allowed filling gaps in the experimental data for further training QSPR models. We improved the published models by significantly extending number of compounds for which theoretical predictions are reliable (i.e., extending the AD). Additionally, we performed external validation that had not been carried out in original models. To test effectiveness of the AD extension, we screened 4519 PFAS from NORMAN Database. The number of compounds outside the domain was reduced comparing the original model for both properties. Our work shows that combining physics-based methods with data-driven models can significantly improve the performance of predictions of phys-chem properties relevant for the chemical risk assessment.

Species-dependent responses of crop plants to polystyrene microplastics

Only recently there has been a strong focus on the impacts of microplastics on terrestrial crop plants. This study aims to examine and compare the effects of microplastics on two monocotyledonous (barley, Hordeum vulgare and wheat, Triticum aestivum), and two dicotyledonous (carrot, Daucus carota and lettuce, Lactuca sativa) plant species through two complimentary experiments. First, we investigated the effects of low, medium, and high (103, 105, 107 particles per mL) concentrations of 500 nm polystyrene microplastics (PS-MPs) on seed germination and early development. We found species-dependent effects on the early development, with microplastics only significantly affecting lettuce and carrot. When acutely exposed during germination, PS-MPs significantly delayed the germination of lettuce by 24%, as well as promoted the shoot growth of carrot by 71% and decreased its biomass by 26%. No effect was recorded on monocot species. Secondly, we performed a chronic (21 d) hydroponic experiment on lettuce and wheat. We observed that PS-MPs significantly reduced the shoot growth of lettuce by up to 35% and increased its biomass by up to 64%, while no record was reported on wheat. In addition, stress level indicators and defence mechanisms were significantly up-regulated in both lettuce and wheat seedlings. Overall, this study shows that PS-MPs affect plant development: impacts were recorded on both germination and growth for dicots, and responses identified by biochemical markers of stress were increased in both lettuce and wheat. This highlights species-dependent effects as the four crops were grown under identical conditions to allow direct comparison. For future research, our study emphasizes the need to focus on crop specific effects, while also working towards knowledge of plastic-induced impacts at environmentally relevant conditions.

What is the ecotoxicity of a given chemical for a given aquatic species? Predicting interactions between species and chemicals using recommender system techniques

Ecotoxicological safety assessment of chemicals requires toxicity data on multiple species, despite the general desire of minimizing animal testing. Predictive models, specifically machine learning (ML) methods, are one of the tools capable of solving this apparent contradiction as they allow to generalize toxicity patterns across chemicals and species. However, despite the availability of large public toxicity datasets, the data is highly sparse, complicating model development. The aim of this study is to provide insights into how ML can predict toxicity using a large but sparse dataset. We developed models to predict LC50-values, based on experimental LC50-data covering 2431 organic chemicals and 1506 aquatic species from the ECOTOX-database. Several well-known ML techniques were evaluated and a new ML model was developed, inspired by recommender systems. This new model involves a simple linear model that learns low-rank interactions between species and chemicals using factorization machines. We evaluated the predictive performances of the developed models based on two validation settings: 1) predicting unseen chemical-species pairs, and 2) predicting unseen chemicals. The results of this study show that ML models can accurately predict LC50-values in both validation settings. Moreover, we show that the novel factorization machine approach can match well-tuned, complex, ML approaches.

Comparative physiological and metabolomics analyses using Ag⎯NPs and HAS31 (PGPR) to alleviate Cr stress in barley (Hordeum vulgare L.)

In the current industrial scenario, chromium (Cr) as a metal is of great importance but poses a major threat to the ecosystem because of its toxicity, but fewer studies have been conducted on its effects and alleviation strategies by using nanoparticles (NPs) and plant growth promoting rhizobacteria (PGPR). Taking into consideration the positive effects of silver⎯nanoparticles (Ag⎯NPs) and (HAS31) rhizobacteria in reducing Cr toxicity in plants, the present study was conducted. A pot experiment was conducted to determine the effects of single and/or combined application of different levels [0 (no Ag⎯NPS), 15 and 30 mM] of Ag⎯NPs and HAS31 [0 (no HAS31), 50 g and 100 g] on Cr accumulation, morpho-physiological and antioxidative defense attributes of barley (Hordeum vulgare L.) exposed to severe Cr stress [0 (without Cr stress), 50 and 100 μM)]. Results from the present study showed that the increasing levels of Cr in the soil significantly (P < 0.05) decreased plant growth and biomass, photosynthetic pigments, gas exchange attributes, sugars, and nutritional contents from the roots and shoots of the plants. In contrast, increasing levels of Cr in the soil significantly (P < 0.05) increased oxidative stress indicators in term of malondialdehyde, hydrogen peroxide, and electrolyte leakage, and also increased organic acid exudation patter in the roots of H. vulgare. Although, the activities of enzymatic antioxidants and the response of their gene expressions in the roots and shoots of the plants and non-enzymatic such as phenolic, flavonoid, ascorbic acid, and anthocyanin contents were increased by increasing the Cr concentration in the soil. The negative impacts of Cr injury were reduced by the application of PGPR (HAS31) and Ag⎯NPs, which increased plant growth and biomass, improved photosynthetic apparatus, antioxidant enzymes, and mineral uptake, as well as diminished the exudation of organic acids and oxidative stress indicators in roots of H. vulgare by decreasing Cr toxicity. Research findings, therefore, suggest that the application of PGPR (HAS31) and Ag⎯NPs can ameliorate Cr toxicity in H. vulgare, resulting in improved plant growth and composition under metal stress, as depicted by balanced exudation of organic acids.

Evaluating the spatial and temporal distribution of emerging contaminants in the Pearl River Basin for regulating purposes

Little information is available on how the types, concentrations, and distribution of chemicals have evolved over the years. The objective of the present study is therefore to review the spatial and temporal distribution profile of emerging contaminants with limited toxicology data in the pearl river basin over the years to build up the emerging contaminants database in this region for risk assessment and regulatory purposes. The result revealed that seven groups of emerging contaminants were abundant in this region, and many emerging contaminants had been detected at much higher concentrations before 2011. Specifically, antibiotics, phenolic compounds, and acidic pharmaceuticals were the most abundant emerging contaminants detected in the aquatic compartment, while phenolic compounds were of the most profound concern in soil. Flame retardants and plastics were the most frequently studied chemicals in organisms. The abundance of the field concentrations and frequencies varied considerably over the years, and currently available data can hardly be used for regulation purposes. It is suggested that watershed management should establish a regular monitoring scheme and comprehensive database to monitor the distribution of emerging contaminants considering the highly condensed population in this region. The priority monitoring list should be formed in consideration of historical abundance, potential toxic effects of emerging contaminants as well as the distribution of heavily polluting industries in the region.

Nano- and microplastics commonly cause adverse impacts on plants at environmentally relevant levels: A systematic review

Over the last years there has been significant research on the presence and effects of plastics in terrestrial systems. Here we summarize current research findings on the effects of nano- and microplastics (NMPs) on terrestrial plants, with the aim to determine patterns of response and sensitive endpoints. We conducted a systematic review (based on 78 studies) on the effects of NMPs on germination, plant growth and biochemical biomarkers. This review highlights that the majority of studies to date have used pristine polystyrene or polyethylene particles, either in a hydroponic or pot-plant setup. Based on these studies we found that effects on plants are widespread. We noted similar responses between and within monocots and dicots to NMPs, except for consistent lower germination seen in dicots exposed to NMPs. During early development, germination and root growth are more strongly affected compared to shoot growth. NMPs induced similar adverse growth effects on plant biomass and length in the most tested plant species (lettuce, wheat, corn, and rice) irrespective of the polymer type and size used. Moreover, biomarker responses were consistent across species; chlorophyll levels were commonly negatively affected, while stress indicators (e.g., ROS or free radicals) and stress respondents (e.g., antioxidant enzymes) were consistently upregulated. In addition, effects were commonly observed at environmentally relevant levels. These findings provide clear evidence that NMPs have wide-ranging impacts on plant performance. However, as most studies have been conducted under highly controlled conditions and with pristine plastics, there is an urgent need to test under more environmentally realistic conditions to ensure the lab-based studies can be extrapolated to the field.

Grouping MWCNTs based on their similar potential to cause pulmonary hazard after inhalation: a case-study

BACKGROUND

The EU-project GRACIOUS developed an Integrated Approach to Testing and Assessment (IATA) to support grouping high aspect ratio nanomaterials (HARNs) presenting a similar inhalation hazard. Application of grouping reduces the need to assess toxicity on a case-by-case basis and supports read-across of hazard data from substances that have the data required for risk assessment (source) to those that lack such data (target). The HARN IATA, based on the fibre paradigm for pathogenic fibres, facilitates structured data gathering to propose groups of similar HARN and to support read-across by prompting users to address relevant questions regarding HARN morphology, biopersistence and inflammatory potential. The IATA is structured in tiers, allowing grouping decisions to be made using simple in vitro or in silico methods in Tier1 progressing to in vivo approaches at the highest Tier3. Here we present a case-study testing the applicability of GRACIOUS IATA to form an evidence-based group of multiwalled carbon nanotubes (MWCNT) posing a similar predicted fibre-hazard, to support read-across and reduce the burden of toxicity testing.

RESULTS

The case-study uses data on 15 different MWCNT, obtained from the published literature. By following the IATA, a group of 2 MWCNT was identified (NRCWE006 and NM-401) based on a high degree of similarity. A pairwise similarity assessment was subsequently conducted between the grouped MWCNT to evaluate the potential to conduct read-across and fill data gaps required for regulatory hazard assessment. The similarity assessment, based on expert judgement of Tier 1 assay results, predicts both MWCNT are likely to cause a similar acute in vivo hazard. This result supports the possibility for read-across of sub-chronic and chronic hazard endpoint data for lung fibrosis and carcinogenicity between the 2 grouped MWCNT. The implications of accepting the similarity assessment based on expert judgement of the MWCNT group are considered to stimulate future discussion on the level of similarity between group members considered sufficient to allow regulatory acceptance of a read-across argument.

CONCLUSION

This proof-of-concept case-study demonstrates how a grouping hypothesis and IATA may be used to support a nuanced and evidence-based grouping of 'similar' MWCNT and the subsequent interpolation of data between group members to streamline the hazard assessment process.

Development of a Quasi-Quantitative Structure-Activity Relationship Model for Prediction of the Immobilization Response of Daphnia magna Exposed to Metal-Based Nanomaterials

The conventional Hill equation model is suitable to fit dose-response data obtained from performing (eco)toxicity assays. Models based on quasi-quantitative structure-activity relationships (QSARs) to estimate the Hill coefficient ( n H ) ${n}_{{\rm{H}}})$ were developed with the aim of predicting the response of the invertebrate species Daphnia magna to exposure to metal-based nanomaterials. Descriptors representing the pristine properties of nanoparticles and media conditions were coded to a quasi-simplified molecular input line entry system and correlated to experimentally derived values of n H ${n}_{{\rm{H}}}$ . Monte Carlo optimization was used to model the set of n H ${n}_{{\rm{H}}}$  values, and the model was trained on the basis of reported dose-response relationships of 60 data sets (n = 367 individual response observations) of 11 metal-based nanomaterials as obtained from 20 literature reports. The model simulates the training data well, with only 2.3% deviation between experimental and modeled response data. The technique was employed to predict the dose-response relationships of 15 additional data sets (n = 72 individual observations) not included in model development of seven metal-based nanomaterials from 10 literature reports, with an average error of 3.5%. Combining the model output with either the median effective concentration value or any other known effect level as obtained from experimental data allows the prediction of full dose-response curves of D. magna immobilization. This model is an accurate screening tool that allows the determination of the shape and slope of dose-response curves, thereby greatly reducing experimental effort in case of novel advanced metal-based nanomaterials or the prediction of responses in altered exposure media. This screening model is compliant with the 3Rs (replacement, reduction, and refinement) principle, which is embraced by the scientific and regulatory communities dealing with nano-safety. Environ Toxicol Chem 2022;41:1439-1450. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Improved science-based transformation pathways for the development of safe and sustainable plastics

Projected plastic production volumes are rising, as is societal and political attention to plastic pollution and possible health impacts. In line with ambitions for climate mitigation and the circular economy, various national and international policies and action plans address the reduction of impacts of plastics. Quantitative scenario analyses show that even if current ambitious targets to reduce plastics are achieved, plastics will remain a source of millions of tons of environmental pollution annually. To achieve a sustainable transformation of the global plastics economy, 'extraordinary effort' and 'coordinated global action' beyond current ambitions are needed. While mapping knowledge gaps for the effects of micro and nano plastics (MNP) is crucial, mapping alone is not enough to achieve the needed transition. In this communication, we propose a scope for the exploration of societal transformation pathways to safe and sustainable plastics. To see which efforts are needed globally we need to advance in the following three areas: (i) embedding risk assessment methodologies in wider cost-benefit and life cycle analyses; (ii) using safe-and-sustainable design strategies that include alternative solutions and look at multiple life cycles, and (iii) reflecting on the societal transformation pathways with stakeholders by using co-created quantitative models. We believe that these practices are crucial in the coming decade to realise the extraordinary effort of defining safe and sustainable plastics.

Refinement of the selection of physicochemical properties for grouping and read-across of nanoforms

Before placing a new nanoform (NF) on the market, its potential adverse effects must be evaluated. This may e.g. be done via hazard and risk assessment. Grouping and read-across of NFs is a possible strategy to reduce resource consumption, maximising the use of existing data for assessment of NFs. The GRACIOUS project provides a framework in which possible grouping and read-across for NFs is mainly based on an evaluation of their similarity. The impact of NFs on human health and the environment depends strongly on the concentration of the NF and its physicochemical properties, such as chemical composition, size distribution, shape, etc. Hence, knowledge of the most relevant physicochemical properties is essential information for comparing similarity. The presented work aims to refine existing proposals for sets of descriptors (descriptor array) that are needed to describe distinct NFs of a material to identify the most relevant ones for grouping and read-across. The selection criteria for refining this descriptor array are explained and demonstrated. Relevant protocols and methods are proposed for each physicochemical property. The required and achievable measurement accuracies of the refined descriptor array are reviewed, as this information is necessary for similarity assessment of NFs based on individual physicochemical properties.

Ordered weighted average based grouping of nanomaterials with Arsinh and dose response similarity models

In the context of the EU GRACIOUS project, we propose a novel procedure for similarity assessment and grouping of nanomaterials. This methodology is based on the (1) Arsinh transformation function for scalar properties, (2) full curve shape comparison by application of a modified Kolmogorov-Smirnov metric for bivariate properties, (3) Ordered Weighted Average (OWA) aggregation-based grouping distance, and (4) hierarchical clustering. The approach allows for grouping of nanomaterials that is not affected by the dataset, so that group membership will not change when new candidates are included in the set of assessed materials. To facilitate the application of the proposed methodology, a software script was developed by using the R programming language which is currently under migration to a web tool. The presented approach was tested against a dataset, derived from literature review, related to immobilization of Daphnia magna and reporting information on several nanomaterials and properties.

Bayesian based similarity assessment of nanomaterials to inform grouping

Nanoforms can be manufactured in plenty of variants by differing their physicochemical properties and toxicokinetic behaviour which can affect their hazard potential. To avoid testing of each single nanomaterial and nanoform variation and subsequently save resources, grouping and read-across strategies are used to estimate groups of substances, based on carefully selected evidence, that could potentially have similar human health and environmental hazard impact. A novel computational similarity method is presented aiming to compare dose-response curves and identify sets of similar nanoforms. The suggested method estimates the statistical model that best fits the data by leveraging pairwise Bayes Factor analysis to compare pairs of curves and evaluate whether each of the nanoforms is sufficiently similar to all other nanoforms. Pairwise comparisons to benchmark materials are used to define threshold similarity values and set the criteria for identifying groups of nanoforms with comparatively similar toxicity. Applications to use case data are shown to demonstrate that the method can support grouping hypotheses linked to a certain hazard endpoint and route of exposure.

How can we justify grouping of nanoforms for hazard assessment? Concepts and tools to quantify similarity

The risk of each nanoform (NF) of the same substance cannot be assumed to be the same, as they may vary in their physicochemical characteristics, exposure and hazard. However, neither can we justify a need for more animal testing and resources to test every NF individually. To reduce the need to test all NFs, (regulatory) information requirements may be fulfilled by grouping approaches. For such grouping to be acceptable, it is important to demonstrate similarities in physicochemical properties, toxicokinetic behaviour, and (eco)toxicological behaviour. The GRACIOUS Framework supports the grouping of NFs, by identifying suitable grouping hypotheses that describe the key similarities between different NFs. The Framework then supports the user to gather the evidence required to test these hypotheses and to subsequently assess the similarity of the NFs within the proposed group. The evidence needed to support a hypothesis is gathered by an Integrated Approach to Testing and Assessment (IATA), designed as decision trees constructed of decision nodes. Each decision node asks the questions and provides the methods needed to obtain the most relevant information. This White paper outlines existing and novel methods to assess similarity of the data generated for each decision node, either via a pairwise analysis conducted property-by-property, or by assessing multiple decision nodes simultaneously via a multidimensional analysis. For the pairwise comparison conducted property-by-property we included in this White paper: The x-fold, Bayesian and Arsinh-OWA distance algorithms performed comparably in the scoring of similarity between NF pairs. The Euclidean distance was also useful, but only with proper data transformation. The x-fold method does not standardize data, and thus produces skewed histograms, but has the advantage that it can be implemented without programming knowhow. A range of multidimensional evaluations, using for example dendrogram clustering approaches, were also investigated. Multidimensional distance metrics were demonstrated to be difficult to use in a regulatory context, but from a scientific perspective were found to offer unexpected insights into the overall similarity of very different materials. In conclusion, for regulatory purposes, a property-by-property evaluation of the data matrix is recommended to substantiate grouping, while the multidimensional approaches are considered to be tools of discovery rather than regulatory methods.

Mitigation of the effect of drought on growth and yield of pomegranates by foliar spraying of different sizes of selenium nanoparticles

BACKGROUND

Drought is a very important environmental stressor, which has negative effects on the growth of trees, decreasing their yield. The role of different-sized selenium nanoparticles (Se-NPs) in the mitigation of environmental stresses such as drought in crops has not yet been investigated.

RESULTS

Trees treated with Se-NPs displayed higher levels of photosynthetic pigments, a better nutrient status, better physical parameters (especially fruit cracking) and chemical parameters, a higher phenolic content, and higher concentrations of osmolytes, antioxidant enzymes, and abscisic acid than untreated trees under drought stress. Foliar spraying of 10 and 50 nm Se-NPs alleviated many of the deleterious effects of drought in pomegranate leaves and fruits and this was achieved by reducing stress-induced lipid peroxidation and H₂ O₂ content by enhancing the activity of antioxidant enzymes. Furthermore, the 10 nm Se-NPs treatment produced more noticeable effects than the treatment with 50 nm Se-NPs.

CONCLUSION

Results confirm the positive effects of nanoparticle spraying, especially the role of 10 nm Se-NPs in the management of negative effects of drought not only for pomegranates but potentially also for other crops. © 2021 Society of Chemical Industry.

Identification of emerging safety and sustainability issues of advanced materials: Proposal for a systematic approach

The EU Chemicals Strategy for Sustainability is a first step to achieve the Green Deal ambition for a toxic-free environment, and ensure that chemicals are produced and used in a way that maximises their contribution to society while avoiding harm to our planet and to future generations. Advanced materials are predicted to play a pivotal role in achieving this ambition and the underlying sustainability goals, and considerable efforts are invested in designing new classes of materials. Examples of such materials are metamaterials, artificially architectured materials designed to have material properties beyond those of the individual ingredient materials, or active materials at the boundary between materials and devices (e.g., new biomedical soft materials). Such innovative advanced materials raise concern about possible future safety and sustainability issues and would benefit from appropriate risk governance that promotes innovation, while pushing for safety and sustainability. To balance these aspects, a methodology is proposed for the early-stage identification of emerging safety and sustainability issues of advanced materials. As exemplified by two case studies, the methodology aims to be of use for innovators, risk assessors, and regulators. Extension of the methodology is highlighted, as well as implementation in broader initiatives like the EU's industrial policy approach.

Compositional and functional responses of bacterial community to titanium dioxide nanoparticles varied with soil heterogeneity and exposure duration

Titanium dioxide nanoparticles (TiO₂ NPs) are widely used as nano-agrochemicals. In this study we investigated the influence of soil heterogeneity on bacterial communities exposed to TiO₂ NPs over time. Clay and sandy soils with low- and high-organic matter contents were exposed to environmentally relevant concentration of TiO₂ NPs (1 mg/kg) and soil bacterial communities were sampled after short-term (15 days) and long-term exposure (60 days). After short-term TiO₂ NPs exposure, significant effects regarding the enzyme activity, bacterial community structure and composition, and community functioning were observed in the clay soils with high organic matter (clay-HOM) but not in other soil groups. Response alterations were observed to taxa belonging to Acidobacteria and Verrucomicrobia, and functional pathways related to carbohydrates degradation. These results indicated that soil heterogeneity play more important roles in shaping the bacterial community in soil with low clay fraction and less organic matter, while TiO₂ NPs selection was the main driver in inducing the compositional and functional impacts on the soil bacterial community in the presence of clay soil with high organic matter content. As exposure time increased, the bacterial community recovered after a long-term exposure of 60 days, suggesting that the bacterial evolution and adaptation could overcome the TiO₂ NPs selection after long-term exposure. Our results highlighted the importance of soil heterogeneity including clay fraction and organic matter and exposure duration in assessing the impact of nanoparticle on soil bacterial activity, community and function. By comprehensively evaluating the risks of nanoparticles on soil ecosystem and explicitly and explicitly include spatial and temporal variations, the benefit of nano-agrochemical products has the potential to be promoted in future applications.

Understanding Dissolution Rates via Continuous Flow Systems with Physiologically Relevant Metal Ion Saturation in Lysosome

Dissolution rates of nanomaterials can be decisive for acute in vivo toxicity (via the released ions) and for biopersistence (of the remaining particles). Continuous flow systems (CFSs) can screen for both aspects, but operational parameters need to be adjusted to the specific physiological compartment, including local metal ion saturation. CFSs have two adjustable parameters: the volume flow-rate and the initial particle loading. Here we explore the pulmonary lysosomal dissolution of nanomaterials containing the metals Al, Ba, Zn, Cu over a wide range of volume flow-rates in a single experiment. We identify the ratio of particle surface area (SA) per volume flow-rate (SA/V) as critical parameter that superimposes all dissolution rates of the same material. Three complementary benchmark materials—ZnO (quick dissolution), TiO₂ (very slow dissolution), and BaSO₄ (partial dissolution)—consistently identify the SA/V range of 0.01 to 0.03 h/cm as predictive for lysosomal pulmonary biodissolution. We then apply the identified method to compare against non-nanoforms of the same substances and test aluminosilicates. For BaSO₄ and TiO₂, we find high similarity of the dissolution rates of their respective nanoform and non-nanoform, governed by the local ion solubility limit at relevant SA/V ranges. For aluminosilicates, we find high similarity of the dissolution rates of two Kaolin nanoforms but significant dissimilarity against Bentonite despite the similar composition.

Development of Empirical Bioavailability Models for Metals

Recently, there has been renewed interest in the development and use of empirical models to predict metal bioavailability and derive protective values for aquatic life. However, there is considerable variability in the conceptual and statistical approaches with which these models have been developed. In the present study, we review case studies of empirical bioavailability model development, evaluating and making recommendations on key issues, including species selection, identifying toxicity-modifying factors (TMFs) and the appropriate environmental range of these factors, use of existing toxicity data sets and experimental design for developing new data sets, statistical considerations in deriving species-specific and pooled bioavailability models, and normalization of species sensitivity distributions using these models. We recommend that TMFs be identified from a combination of available chemical speciation and toxicity data and statistical evaluations of their relationships to toxicity. Experimental designs for new toxicity data must be sufficiently robust to detect nonlinear responses to TMFs and should encompass a large fraction (e.g., 90%) of the TMF range. Model development should involve a rigorous use of both visual plotting and statistical techniques to evaluate data fit. When data allow, we recommend using a simple linear model structure and developing pooled models rather than retaining multiple taxa-specific models. We conclude that empirical bioavailability models often have similar predictive capabilities compared to mechanistic models and can provide a relatively simple, transparent tool for predicting the effects of TMFs on metal bioavailability to achieve desired environmental management goals. Environ Toxicol Chem 2019;39:85-100. © 2019 SETAC.

Toward harmonizing ecotoxicity characterization in life cycle impact assessment

Ecosystem quality is an important area of protection in life cycle impact assessment (LCIA). Chemical pollution has adverse impacts on ecosystems on a global scale. To improve methods for assessing ecosystem impacts, the Life Cycle Initiative hosted by the United Nations Environment Programme established a task force to evaluate the state-of-the-science in modeling chemical exposure of organisms and the resulting ecotoxicological effects for use in LCIA. The outcome of the task force work will be global guidance and harmonization by recommending changes to the existing practice of exposure and effect modeling in ecotoxicity characterization. These changes will reflect the current science and ensure the stability of recommended practice. Recommendations must work within the needs of LCIA in terms of 1) operating on information from any inventory reporting chemical emissions with limited spatiotemporal information, 2) applying best estimates rather than conservative assumptions to ensure unbiased comparison with results for other impact categories, and 3) yielding results that are additive across substances and life cycle stages and that will allow a quantitative expression of damage to the exposed ecosystem. We describe the current framework and discuss research questions identified in a roadmap. Primary research questions relate to the approach toward ecotoxicological effect assessment, the need to clarify the method's scope and interpretation of its results, the need to consider additional environmental compartments and impact pathways, and the relevance of effect metrics other than the currently applied geometric mean of toxicity effect data across species. Because they often dominate ecotoxicity results in LCIA, we give metals a special focus, including consideration of their possible essentiality and changes in environmental bioavailability. We conclude with a summary of key questions along with preliminary recommendations to address them as well as open questions that require additional research efforts. Environ Toxicol Chem 2018;37:2955-2971. © 2018 SETAC.

Modelling the toxicity of a large set of metal and metal oxide nanoparticles using the OCHEM platform

Inorganic nanomaterials have become one of the new areas of modern knowledge and technology and have already found an increasing number of applications. However, some nanoparticles show toxicity to living organisms, and can potentially have a negative influence on environmental ecosystems. While toxicity can be determined experimentally, such studies are time consuming and costly. Computational toxicology can provide an alternative approach and there is a need to develop methods to reliably assess Quantitative Structure-Property Relationships for nanomaterials (nano-QSPRs). Importantly, development of such models requires careful collection and curation of data. This article overviews freely available nano-QSPR models, which were developed using the Online Chemical Modeling Environment (OCHEM). Multiple data on toxicity of nanoparticles to different living organisms were collected from the literature and uploaded in the OCHEM database. The main characteristics of nanoparticles such as chemical composition of nanoparticles, average particle size, shape, surface charge and information about the biological test species were used as descriptors for developing QSPR models. QSPR methodologies used Random Forests (WEKA-RF), k-Nearest Neighbors and Associative Neural Networks. The predictive ability of the models was tested through cross-validation, giving cross-validated coefficients q² = 0.58-0.80 for regression models and balanced accuracies of 65-88% for classification models. These results matched the predictions for the test sets used to develop the models. The proposed nano-QSPR models and uploaded data are freely available online at http://ochem.eu/article/103451 and can be used for estimation of toxicity of new and emerging nanoparticles at the early stages of nanomaterial development.

Current Knowledge on the Use of Computational Toxicology in Hazard Assessment of Metallic Engineered Nanomaterials

As listed by the European Chemicals Agency, the three elements in evaluating the hazards of engineered nanomaterials (ENMs) include the integration and evaluation of toxicity data, categorization and labeling of ENMs, and derivation of hazard threshold levels for human health and the environment. Assessing the hazards of ENMs solely based on laboratory tests is time-consuming, resource intensive, and constrained by ethical considerations. The adoption of computational toxicology into this task has recently become a priority. Alternative approaches such as (quantitative) structure-activity relationships ((Q)SAR) and read-across are of significant help in predicting nanotoxicity and filling data gaps, and in classifying the hazards of ENMs to individual species. Thereupon, the species sensitivity distribution (SSD) approach is able to serve the establishment of ENM hazard thresholds sufficiently protecting the ecosystem. This article critically reviews the current knowledge on the development of in silico models in predicting and classifying the hazard of metallic ENMs, and the development of SSDs for metallic ENMs. Further discussion includes the significance of well-curated experimental datasets and the interpretation of toxicity mechanisms of metallic ENMs based on reported models. An outlook is also given on future directions of research in this frontier.

The way forward for risk assessment of nanomaterials in solid media

There is an urgent need for sufficient knowledge to allow reliable assessment of the risks associated with engineered nanomaterials (ENPs). Significant advances in basic understanding of nano safety have been made, but there is still no clear systematic basis for risk-related research, and major uncertainties remain in the absence of uniform procedures. The following papers provide the guidance on how to proceed within the area of fate and hazard assessment, and how this links into grouping, testing and risk assessment of nanomaterials. This guidance is coupled with an industrial view on the most important research areas for nanomaterials.

Fate assessment of engineered nanoparticles in solids dominated media - Current insights and the way forward

Exposure assessment of engineered nanoparticles (ENPs) in soil and sediment is severely hampered by a lack of understanding of the underlying processes and of the impact of matrix constituents on the fate of ENPs in natural systems, including porewater properties like pH, ionic strength, and presence of naturally occurring (nano)particles. Additional issues such as lack of proper methods for in-situ assessment of ENP speciation, ENP ageing, and agglomeration state, hinder proper exposure assessment. Let alone that the lack does not allow for development of predictive methods for endpoints like transformation and agglomeration potential. This paper discusses current approaches for fate assessment of ENPs in solids dominated media and addresses the most prominent knowledge gaps and how these may be addressed. It is concluded that the key issue to be dealt with, are the attachment and deposition processes that are characteristic for ENPs as opposed to equilibrium-driven partitioning processes of non-particulate organic and inorganic contaminants.

Frameworks and tools for risk assessment of manufactured nanomaterials

Commercialization of nanotechnologies entails a regulatory requirement for understanding their environmental, health and safety (EHS) risks. Today we face challenges to assess these risks, which emerge from uncertainties around the interactions of manufactured nanomaterials (MNs) with humans and the environment. In order to reduce these uncertainties, it is necessary to generate sound scientific data on hazard and exposure by means of relevant frameworks and tools. The development of such approaches to facilitate the risk assessment (RA) of MNs has become a dynamic area of research. The aim of this paper was to review and critically analyse these approaches against a set of relevant criteria. The analysis concluded that none of the reviewed frameworks were able to fulfill all evaluation criteria. Many of the existing modelling tools are designed to provide screening-level assessments rather than to support regulatory RA and risk management. Nevertheless, there is a tendency towards developing more quantitative, higher-tier models, capable of incorporating uncertainty into their analyses. There is also a trend towards developing validated experimental protocols for material identification and hazard testing, reproducible across laboratories. These tools could enable a shift from a costly case-by-case RA of MNs towards a targeted, flexible and efficient process, based on grouping and read-across strategies and compliant with the 3R (Replacement, Reduction, Refinement) principles. In order to facilitate this process, it is important to transform the current efforts on developing databases and computational models into creating an integrated data and tools infrastructure to support the risk assessment and management of MNs.

Regulatory ecotoxicity testing of nanomaterials - proposed modifications of OECD test guidelines based on laboratory experience with silver and titanium dioxide nanoparticles

Regulatory ecotoxicity testing of chemicals is of societal importance and a large effort is undertaken at the OECD to ensure that OECD test guidelines (TGs) for nanomaterials (NMs) are available. Significant progress to support the adaptation of selected TGs to NMs was achieved in the context of the project MARINA ( http://www.marina-fp7.eu/ ) funded within the 7th European Framework Program. Eight OECD TGs were adapted based on the testing of at least one ion-releasing NM (Ag) and two inert NMs (TiO₂). With the materials applied, two main variants of NMs (ion releasing vs. inert NMs) were addressed. As the modifications of the test guidelines refer to general test topics (e.g. test duration or measuring principle), we assume that the described approaches and modifications will be suitable for the testing of further NMs with other chemical compositions. Firm proposals for modification of protocols with scientific justification(s) are presented for the following tests: growth inhibition using the green algae Raphidocelis subcapitata (formerly: Pseudokirchneriella subcapitata; TG 201), acute toxicity with the crustacean Daphnia magna (TG 202), development toxicity with the fish Danio rerio (TG 210), reproduction of the sediment-living worm Lumbriculus variegatus (TG 225), activity of soil microflora (TGs 216, 217), and reproduction of the invertebrates (Enchytraeus crypticus, Eisenia fetida, TGs 220, 222). Additionally, test descriptions for two further test systems (root elongation of plants in hydroponic culture; test on fish cells) are presented. Ecotoxicological data obtained with the modified test guidelines for TiO₂ NMs and Ag NM and detailed method descriptions are available.

Bioaccumulation of Polybrominated Diphenyl Ethers by Tubifex Tubifex

The selective uptake of polybrominated diphenyl ethers (PBDEs) by oligochaetes makes it possible to assess the bioaccumulation of individual congeners in commercial mixtures. Twenty-one congeners from three BDE commercial mixtures (TBDE-71, TBDE-79 and TBDE-83R) and as individual congeners (BDE-77, BDE-126, BDE-198 and BDE-204) were tested on Tubifex tubifex in accordance with the OECD TG 315 "Bioaccumulation in Sediment-Dwelling Benthic Oligochaetes". All the congeners that were spiked in the sediment were detected at the end of the uptake phase and at the end of the experiment. The bioaccumulation factor (BAF), the kinetic bioaccumulation factor (BAFK) and the biotasediment accumulation factor (BSAF) were calculated, and indicate a high bioaccumulation potential for tri- to hexa-BDEs and a lower bioaccumulation potential for hepta- to deca-BDEs. The penta-homologues BDE-99 and BDE-100 showed the highest BSAFs of 4.84 and 5.85 (BAFs of 7.34 and 9.01), while the nona- and deca-BDEs exhibit bioaccumulation in up to one-order-lower concentrations. The change in the bioaccumulation potential between the group of trito hexa-BDEs and hepta- to deca-BDEs correlated with the generally accepted molecular-mass threshold for the molecular transition through biological membranes (700 g/mol).

How should the completeness and quality of curated nanomaterial data be evaluated?

Nanotechnology is of increasing significance. Curation of nanomaterial data into electronic databases offers opportunities to better understand and predict nanomaterials' behaviour. This supports innovation in, and regulation of, nanotechnology. It is commonly understood that curated data need to be sufficiently complete and of sufficient quality to serve their intended purpose. However, assessing data completeness and quality is non-trivial in general and is arguably especially difficult in the nanoscience area, given its highly multidisciplinary nature. The current article, part of the Nanomaterial Data Curation Initiative series, addresses how to assess the completeness and quality of (curated) nanomaterial data. In order to address this key challenge, a variety of related issues are discussed: the meaning and importance of data completeness and quality, existing approaches to their assessment and the key challenges associated with evaluating the completeness and quality of curated nanomaterial data. Considerations which are specific to the nanoscience area and lessons which can be learned from other relevant scientific disciplines are considered. Hence, the scope of this discussion ranges from physicochemical characterisation requirements for nanomaterials and interference of nanomaterials with nanotoxicology assays to broader issues such as minimum information checklists, toxicology data quality schemes and computational approaches that facilitate evaluation of the completeness and quality of (curated) data. This discussion is informed by a literature review and a survey of key nanomaterial data curation stakeholders. Finally, drawing upon this discussion, recommendations are presented concerning the central question: how should the completeness and quality of curated nanomaterial data be evaluated?

Incorporating availability/bioavailability in risk assessment and decision making of polluted sites, using Germany as an example

Nearly all publications dealing with availability or bioavailability of soil pollutants start with the following statement: the determination of total pollutant content will lead to an over-estimation of risk. However, an assessment of contaminated sites should be based on the determination of mobile fractions of pollutants, and the fractions with potential for mobilisation that threaten groundwater and surface water, and the actual and potential fractions available for uptake by plants, soil microflora and soil organisms. After reviewing the literature for method proposals concerning the determination of available/bioavailable fractions of contaminants with respect to leaching, plants, microorganisms (biodegradation) and soil organisms, we propose a testing and assessment scheme for contaminated sites. The proposal includes (i) already accepted and used methods, (ii) methods which are under standardisation, and (iii) methods for which development has just started in order to promote urgently needed research.

Possibilities of implementation of bioavailability methods for organic contaminants in the Dutch Soil Quality Assessment Framework

In the Netherlands, risk assessment of contaminated soils is based on determining the total contaminant concentration. If this measured soil concentration exceeds the Soil Quality Standards (SQS) a higher tier risk evaluation must be performed. Experiences from the field have given rise to the perception that performing risk evaluations based on (measured) total concentrations may lead to an inaccurate assessment of the actual risks. Assuming that only the bioavailable fraction is capable of exerting adverse effects in the soil ecosystem, it is suggested, that by taking bioavailability into account in a (higher tier) risk evaluation, a more effect-based risk assessment can be performed. Bioavailability has been a subject of research for several decades. However up to now bioavailability has not been implemented in the Dutch Soil Quality Assessment Framework. First actions were taken in the Netherlands to determine whether the concept of bioavailability could be implemented in the risk assessment of contaminated soils and to find out how bioavailability can become part of the Dutch Soil Quality Assessment Framework. These actions have led to a concrete proposal for implementation of bioavailability methods in the risk assessment of organic contaminants in soils. This paper focuses on the chemical prediction of bioavailability for ecological risk assessment of contaminated soils.

Perspectives for integrating human and environmental risk assessment and synergies with socio-economic analysis

For more than a decade, the integration of human and environmental risk assessment (RA) has become an attractive vision. At the same time, existing European regulations of chemical substances such as REACH (EC Regulation No. 1907/2006), the Plant Protection Products Regulation (EC regulation 1107/2009) and Biocide Regulation (EC Regulation 528/2012) continue to ask for sector-specific RAs, each of which have their individual information requirements regarding exposure and hazard data, and also use different methodologies for the ultimate risk quantification. In response to this difference between the vision for integration and the current scientific and regulatory practice, the present paper outlines five medium-term opportunities for integrating human and environmental RA, followed by detailed discussions of the associated major components and their state of the art. Current hazard assessment approaches are analyzed in terms of data availability and quality, and covering non-test tools, the integrated testing strategy (ITS) approach, the adverse outcome pathway (AOP) concept, methods for assessing uncertainty, and the issue of explicitly treating mixture toxicity. With respect to exposure, opportunities for integrating exposure assessment are discussed, taking into account the uncertainty, standardization and validation of exposure modeling as well as the availability of exposure data. A further focus is on ways to complement RA by a socio-economic assessment (SEA) in order to better inform about risk management options. In this way, the present analysis, developed as part of the EU FP7 project HEROIC, may contribute to paving the way for integrating, where useful and possible, human and environmental RA in a manner suitable for its coupling with SEA.

Experimental Assessment of the Environmental Fate and Effects of Triazoles and Benzotriazole

The environmental fate and effects of triazoles and benzotriazoles are of concern within the context of chemical regulation. As part of an intelligent testing strategy, experimental tests were performed on endpoints that are relevant for risk assessment. The experimental tests included the assessment of ecotoxicity to an alga, a daphnid and zebrafish embryos, and the assessment of ready biodegradability. Triazole and benzotriazole compounds were selected for testing, based on existing toxicity data for vertebrate and invertebrate species, as well as on the principal component analysis of molecular descriptors aimed at selecting the minimum number of test compounds in order to maximise the chemical domain spanned for both compound classes. The experimental results show that variation in the toxicities of triazoles and benzotriazole across species was relatively minor; in general, the largest factor was approximately 20. The study conducted indicated that triazoles are not readily biodegradable.

Natural colloids are the dominant factor in the sedimentation of nanoparticles

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.