Multimedia modeling of engineered nanoparticles with SimpleBox4nano: model definition and evaluation

Next Generation Risk Assessment approaches for advanced nanomaterials: Current status and future perspectives

This manuscript discusses the challenges of applying New Approach Methodologies (NAMs) for safe by design and regulatory risk assessment of advanced nanomaterials (AdNMs). The authors propose a framework for Next Generation Risk Assessment of AdNMs involving NAMs that is aligned to the conventional risk assessment paradigm. This framework is exposure-driven, endpoint-specific, makes best use of pre-existing information, and can be implemented in tiers of increasing specificity and complexity of the adopted NAMs. The tiered structure of the approach, which effectively combines the use of existing data with targeted testing will allow safety to be assessed cost-effectively and as far as possible with even more limited use of vertebrates. The regulatory readiness of state-of-the-art emerging NAMs is assessed in terms of Transparency, Reliability, Accessibility, Applicability, Relevance and Completeness, and their appropriateness for AdNMs is discussed in relation to each step of the risk assessment paradigm along with providing perspectives for future developments in the respective scientific and regulatory areas.

Applications of mathematical modelling for assessing microplastic transport and fate in water environments: a comparative review

Microplastics in the environment are considered complex pollutants as they are chemical and corrosive-resistant, non-biodegradable and ubiquitous. These microplastics may act as vectors for the dissemination of other pollutants and the transmission of microorganisms into the water environment. The currently available literature reviews focus on analysing the occurrence, environmental effects and methods of microplastic detection, however lacking a wide-scale systematic review and classification of the mathematical microplastic modelling applications. Thus, the current review provides a global overview of the modelling methodologies used for microplastic transport and fate in water environments. This review consolidates, classifies and analyses the methods, model inputs and results of 61 microplastic modelling studies in the last decade (2012-2022). It thoroughly discusses their strengths, weaknesses and common gaps in their modelling framework. Five main modelling types were classified as follows: hydrodynamic, process-based, statistical, mass-balance and machine learning models. Further, categorisations based on the water environments, location and published year of these applications were also adopted. It is concluded that addressed modelling types resulted in relatively reliable outcomes, yet each modelling framework has its strengths and weaknesses. However, common issues were found such as inputs being unrealistically assumed, especially biological processes, and the lack of sufficient field data for model calibration and validation. For future research, it is recommended to incorporate macroplastics' degradation rates, particles of different shapes and sizes and vertical mixing due to biofouling and turbulent conditions and also more experimental data to obtain precise model inputs and standardised sampling methods for surface and column waters.

Computational Nanotoxicology Models for Environmental Risk Assessment of Engineered Nanomaterials

Although engineered nanomaterials (ENMs) have tremendous potential to generate technological benefits in numerous sectors, uncertainty on the risks of ENMs for human health and the environment may impede the advancement of novel materials. Traditionally, the risks of ENMs can be evaluated by experimental methods such as environmental field monitoring and animal-based toxicity testing. However, it is time-consuming, expensive, and impractical to evaluate the risk of the increasingly large number of ENMs with the experimental methods. On the contrary, with the advancement of artificial intelligence and machine learning, in silico methods have recently received more attention in the risk assessment of ENMs. This review discusses the key progress of computational nanotoxicology models for assessing the risks of ENMs, including material flow analysis models, multimedia environmental models, physiologically based toxicokinetics models, quantitative nanostructure-activity relationships, and meta-analysis. Several challenges are identified and a perspective is provided regarding how the challenges can be addressed.

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.

Statistical analysis, machine learning modeling, and text analytics of aggregation attachment efficiency: Mono and binary particle systems

The aggregation attachment efficiency (α) is the fraction of particle-particle collisions resulting in aggregation. Despite significant research, α predictions have not accounted for the full complexity of systems due to constraints imposed by particle types, dispersed matter, water chemistry, quantification methods, and modeling. Experimental α values are often case-specific, and simplified systems are used to rule out complexity. To address these challenges, statistical analysis was performed on α databases to identify gaps in current knowledge, and machine learning (ML) was used to predict α under various particle types and conditions. Moreover, text analytics was employed to support knowledge from statistics and ML, as well as gain insight into the ideas communicated by current literature. Most studies investigated α in mono-particle systems, but binary or higher systems require more investigation. Furthermore, our work highlights that numerous variables, interactions, and mechanisms influence α behavior, making its investigation complex and difficult for both experiments and modeling. Consequently, future research should incorporate more particle types, shapes, coatings, and surface heterogeneities, and aim to address overlooked variables and conditions. Therefore, building a comprehensive α database can enable the development of more accurate empirical models for prediction.

A multimedia model to estimate the environmental fate of microplastic particles

Nano- and microplastic (NMP) is a diverse and challenging contaminant and data on NMP concentrations are therefore not fully available for all environmental compartments. For environmental assessments of NMP, screening-level multimedia models can fill this gap, but such models are not available. Here, we present SimpleBox4Plastic (SB4P) as the first multimedia 'unit world' model capable of addressing the full NMP continuum, explore its validity, and evaluate it based on a case study for microbeads and by comparisons with (limited) concentration data. SB4P links NMP transport and concentrations in and across air, surface water, sediment, and soil, taking into account processes such as attachment, aggregation, and fragmentation, by solving mass balance equations using matrix algebra. These link all concentrations and processes known to be relevant for NMP using first-order rate constants, which are obtained from the literature. The SB4P model, as applied to microbeads, provided mass or number concentrations of NMP as the total of 'free' particles, heteroaggregates with natural colloids, and larger natural particles in each compartment at steady state. Processes most relevant in explaining observed Predicted Exposure Concentrations (PECs) were determined using rank correlation analysis. Although the predicted PECs remained uncertain due to the propagating uncertainty, inferences regarding these processes and relative distribution across compartments can be considered robust.

Meta-analysis of engineered nanoparticles dynamic aggregation in freshwater-like systems using machine learning techniques

Predictive algorithms for exposure characterization of engineered nanoparticles (ENPs) in the ecosystems are essential to improve the development of robust nano-safety frameworks. Here, machine learning (ML) techniques were utilised for data mining and prediction of the dynamic aggregation transformation process in aqueous environments using case studies of nZnO and nTiO₂. Supervised ML models using input variables of natural organic matter, ionic strength, size, and ENPs concentration showed poor prediction performance based on statistical metric values of root mean square error (RMSE), mean absolute error (MAE), coefficient of determination (R²), and Nash-Sutcliffe efficiency (NSE) for both types of ENP. On the contrary, algorithms developed using model input parameters of zeta potential, pH, and time had good generalisation and high prediction accuracy. Among the five developed ML algorithms, random forest regression, support vector regression, and artificial neural network generated good prediction accuracy for both data sets. Therefore, the use of ML can be valuable in the development of robust nano-safety frameworks to optimise societal benefits, and for proactive long-term ecological protection.

Computational models to confront the complex pollution footprint of plastic in the environment

The threat posed by plastic in the environment is poorly characterized due to uncertainties and unknowns about sources, transport, transformation and removal processes, and the properties of the plastic pollution itself. Plastic creates a footprint of particulate pollution with a diversity of composition, size and shape, and a halo of chemicals. In this Perspective, we argue that process-based mass-balance models could provide a platform to synthesize knowledge about plastic pollution as a function of its measurable intrinsic properties.

Prediction of attachment efficiency using machine learning on a comprehensive database and its validation

Colloidal particles can attach to surfaces during transport, but the attachment depends on particle size, hydrodynamics, solid and water chemistry, and particulate matter. The attachment is quantified in filtration theory by measuring attachment or sticking efficiency (Alpha). A comprehensive Alpha database (2538 records) was built from experiments in the literature and used to develop a machine learning (ML) model to predict Alpha. The training (r-squared: 0.86) was performed using two random forests capable of handling missing data. A holdout dataset was used to validate the training (r-squared: 0.98), and the variable importance was explored for training and validation. Finally, an additional validation dataset was built from quartz crystal microbalance experiments using surface-modified polystyrene, poly (methyl methacrylate), and polyethylene. The experiments were performed in the absence or presence of humic acid. Full database regression (r-squared: 0.90) predicted Alpha for the additional validation with an r-squared of 0.23. Nevertheless, when the original database and the additional validation dataset were combined into a new database, both the training (r-squared: 0.95) and validation (r-squared: 0.70) increased. The developed ML model provides a data-driven prediction of Alpha over a big database and evaluates the significance of 22 input variables.

Ecotoxicity characterization of chemicals: Global recommendations and implementation in USEtox

Chemicals emitted to the environment affect ecosystem health from local to global scale, and reducing chemical impacts has become an important element of European and global sustainability efforts. The present work advances ecotoxicity characterization of chemicals in life cycle impact assessment by proposing recommendations resulting from international expert workshops and work conducted under the umbrella of the UNEP-SETAC Life Cycle Initiative in the GLAM project (Global guidance on environmental life cycle impact assessment indicators). We include specific recommendations for broadening the assessment scope through proposing to introduce additional environmental compartments beyond freshwater and related ecotoxicity indicators, as well as for adapting the ecotoxicity effect modelling approach to better reflect environmentally relevant exposure levels and including to a larger extent chronic test data. As result, we (1) propose a consistent mathematical framework for calculating freshwater ecotoxicity characterization factors and their underlying fate, exposure and effect parameters; (2) implement the framework into the USEtox scientific consensus model; (3) calculate characterization factors for chemicals reported in an inventory of a life cycle assessment case study on rice production and consumption; and (4) investigate the influence of effect data selection criteria on resulting indicator scores. Our results highlight the need for careful interpretation of life cycle assessment impact scores in light of robustness of underlying species sensitivity distributions. Next steps are to apply the recommended characterization framework in additional case studies, and to adapt it to soil, sediment and the marine environment. Our framework is applicable for evaluating chemicals in life cycle assessment, chemical and environmental footprinting, chemical substitution, risk screening, chemical prioritization, and comparison with environmental sustainability targets.

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.

Life Cycle Assessment of Microplastics Reveals Their Greater Environmental Hazards than Mismanaged Polymer Waste Losses

Concern about microplastic pollution sourced from mismanaged plastic waste losses to drainage basins is growing but lacks relevant environmental impact analyses. Here, we reveal and compare the environmental hazards of aquatic macro- and microplastic debris through a holistic life cycle assessment approach. Compared to polymeric debris, microplastics, especially smaller than 10 μm, exhibit higher freshwater ecotoxicity enhanced by watersheds' high average depth and low water temperature. High microplastic concentration within drainage basins can also cause air pollution regarding particulate matter formation and photochemical ozone formation. The environmental drawbacks of plastic mismanagement are then demonstrated by showing that the microplastic formulation and removal in drinking water treatment plants can pose more than 7.44% of the total ecotoxicity effect from plastic wastes' (microplastics') whole life cycle. Specifically, these two life cycle stages can also cause more than 50% of the plastic wastes' life cycle ecotoxicity effect related to organic chemical emissions. Therefore, reducing environmentally harmful plastic losses through advanced plastic waste recycling, collection, and effective microplastic removal technologies needs future investigation.

(Re)Conceptualizing decision-making tools in a risk governance framework for emerging technologies-the case of nanomaterials

The utility of decision-making tools for the risk governance of nanotechnology is at the core of this paper. Those working in nanotechnology risk management have been prolific in creating such tools, many derived from European FP7 and H2020-funded projects. What is less clear is how such tools might assist the overarching ambition of creating a fair system of risk governance. In this paper, we reflect upon the role that tools might and should play in any system of risk governance. With many tools designed for the risk governance of this emerging technology falling into disuse, this paper provides an overview of extant tools and addresses their potential shortcomings. We also posit the need for a data readiness tool. With the EUs NMP13 family of research consortia about to report to the Commission on ways forward in terms of risk governance of this domain, this is a timely intervention on an important element of any risk governance system.

Local Scale Exposure and Fate of Engineered Nanomaterials

Nanotechnology is a growing megatrend in industrial production and innovations. Many applications utilize engineered nanomaterials (ENMs) that are potentially released into the atmospheric environment, e.g., via direct stack emissions from production facilities. Limited information exists on adverse effects such ENM releases may have on human health and the environment. Previous exposure modeling approaches have focused on large regional compartments, into which the released ENMs are evenly mixed. However, due to the localization of the ENM release and removal processes, potentially higher airborne concentrations and deposition fluxes are obtained around the production facilities. Therefore, we compare the ENM concentrations from a dispersion model to those from the uniformly mixed compartment approach. For realistic release scenarios, we based the modeling on the case study measurement data from two TiO2 nanomaterial handling facilities. In addition, we calculated the distances, at which 50% of the ENMs are deposited, serving as a physically relevant metric to separate the local scale from the regional scale, thus indicating the size of the high exposure and risk region near the facility. As a result, we suggest a local scale compartment to be implemented in the multicompartment nanomaterial exposure models. We also present a computational tool for local exposure assessment that could be included to regulatory guidance and existing risk governance networks.

Screening Risk Assessment at the Production and Use Stage of Carbon Nanomaterials Generated in Hydrogen Manufacture by Methane Decomposition

We performed a screening evaluation of the human health risk posed by nanocarbon materials at the lifecycle stages of manufacturing and the use of the solid carbon generated in hydrogen manufacture by methane decomposition. We first estimated the atmospheric emission volumes of the solid carbon produced by small-, medium-, and large-scale hydrogen manufacturing plants. We then estimated the atmospheric emission due to tire wear, which largely contributes to the emission of solid carbon usage. Next, we estimated the atmospheric concentration of solid carbon in an atmospheric simulation using the METI–LIS model, which estimates the atmospheric distribution of a pollutant’s concentration near methane decomposition factories. We also used the AIST–ADMER model that estimated the regional atmospheric distributions around central Tokyo, where the traffic volume is the highest nationally. Finally, we performed a screening evaluation of human health risk in the surrounding areas, considering the permissible exposure concentrations of solid carbon. Our study identified no risk concerns at small- and medium-scale factory locations equipped with high-efficiency particulate air (HEPA) filtration facilities. At large-scale factories installed with HEPA filters, these emissions likely remain within the factory site. Furthermore, we determined that emissions from tire wear pose no risk to human health. The surroundings of small- and medium-scale factory sites installed with HEPA filters posed no risk to human health.

Safe-and-Sustainable-by-Design Framework Based on a Prospective Life Cycle Assessment: Lessons Learned from a Nano-Titanium Dioxide Case Study

Safe-and-sustainable-by-design (SSbD) is a concept that takes a systems approach by integrating safety, sustainability, and functionality throughout a product’s the life cycle. This paper proposes a framework based on a prospective life cycle assessment for early safety and sustainability assessment. The framework’s purpose is to identify environmental sustainability and toxicity hotspots early in the innovation process for future SSbD applicability. If this is impossible, key performance indicators are assessed. Environmental sustainability aspects, such as global warming potential (GWP) and cumulative energy demand (CED), and toxicity aspects, such as human toxicity potential and freshwater ecotoxicity potential, were assessed upon applying the framework on a case study. The case study regarded using nano-titanium dioxide (P25-TiO₂) or a modified nano-coated version (Cu₂O-coated/P25-TiO₂) as photocatalysts to produce hydrogen from water using sunlight. Although there was a decrease in environmental impact (GWP and CED), the modified nano-coated version had a relatively higher level of human toxicity and freshwater eco-toxicity. For the presented case study, SSbD alternatives need to be considered that improve the photocatalytic activity but are not toxic to the environment. This case study illustrates the importance of performing an early safety and environmental sustainability assessment to avoid the development of toxic alternatives.

Micro (nano) plastics in wastewater: A critical review on toxicity risk assessment, behaviour, environmental impact and challenges

With millions of tonnes of plastic pollution generated every year, small-sized plastic particles, including micro- and nanoplastics, end up in freshwater systems. Due to the very small size and very large specific surface area of nanoplastics, they are known to be persistent and toxic in our environment. These particles are also known to react with other water-borne contaminants and cause acute toxicity in organisms. Nanoplastics are prone to biomagnification and can be transported to humans through various pathways. This study aims to contribute towards understanding the behaviour of nanoplastics in our environment, specifically through identification of various sources, detection techniques, toxicity estimation, health risk in humans, environmental fate, recovery and reuse, and future challenges and limitations. Detailed review on the toxic effects of nanoplastics on various organisms and their degradation rates in soil and water matrices are provided. The suitability of small- and large-scale separation techniques for the removal of nanoplastics in wastewater treatment plants is also discussed. Current challenges and future perspectives in understanding the fate and transport of nanoplastics in the environment are also discussed. Research gaps, including the development of quantification techniques, estimation of degradation mechanisms, transport in marine ecosystems, and development of sensors to examine nanoplastics in the environment, are explored. Finally, we can limit the release of nanoplastics to the environment through reduction, reuse and recycling (3 Rs) of bulk plastic products.

Toward a Framework for Environmental Fate and Exposure Assessment of Polymers

Development of risk-assessment methodologies for polymers is an emerging regulatory priority to prevent negative environmental impacts; however, the diversity and complexity of polymers require adaptation of existing environmental risk-assessment approaches. The present review discusses the challenges and opportunities for the fate and exposure assessment of polymers in the context of regulatory environmental risk assessment of chemicals. The review discusses the applicability and adequacy for polymers of existing fate parameters used for nonpolymeric compounds and proposes additional parameters that could inform the fate of polymers. The significance of these parameters in various stages of an exposure-assessment framework is highlighted, with classification of polymers as solid or dissolved being key for identification of those parameters most relevant to environmental fate. Considerations to address the key limitations and knowledge gaps are then identified and discussed, specifically the complexity of polymer identification, with the need for characterization of the most significant parameters for polymer grouping and prioritization; the complexity of polymer degradation in the environment, with the need to incorporate the fate and hazards of degradation products into risk assessment; the requirement for development and standardization of analytical methods for characterization of polymer fate properties and degradation products; and the need to develop exposure modeling approaches for polymers. Environ Toxicol Chem 2022;41:515-540. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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.

Modelling local nanobiomaterial release and concentration hotspots in the environment

Nanobiomaterials (NBMs) are a special category of nanomaterials used in medicine. As applications of NBMs are very similar to pharmaceuticals, their environmental release patterns are likely similar as well. Different pharmaceuticals were detected in surface waters all over the world. Consequently, there exists a need to identify possible NBM exposure routes into the environment. As the application of many NBMs is only carried out at specific locations (hospitals), average predicted environmental concentrations (PECs) may not accurately represent their release to the environment. We estimated the local release of poly(lactic-co-glycolic acid) (PLGA), which is investigated for their use in drug delivery, to Swiss surface waters by using population data as well as type, size and location of hospitals as proxies. The total mean consumption of PGLA in Switzerland using an explorative full-market penetration scenario was calculated to be 770 kg/year. 105 hospitals were considered, which were connected to wastewater treatment plants and the receiving water body using graphic information system (GIS) modelling. The water body dataset contained 20,167 river segments and 210 lake polygons. Using the discharge of the river, we were able to calculate the PECs in different river segments. While we calculated high PLGA releases of 2.24 and 2.03 kg/year in large cities such as Geneva or Zurich, the resulting local PECs of 220 and 660 pg/l, respectively, were low due to the high river discharge (330 and 97 m³/s). High PLGA concentrations (up to 7,900 pg/l) on the other hand were calculated around smaller cities with local hospitals but also smaller receiving rivers (between 0.7 and 1.9 m³/s). Therefore, we conclude that population density does not accurately predict local concentration hotspots of NBMs, such as PLGA, that are administered in a hospital context. In addition, even at the locations with the highest predicted PLGA concentrations, the expected risk is low.

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.

Integrative approach in a safe by design context combining risk, life cycle and socio-economic assessment for safer and sustainable nanomaterials

Moving towards safe and sustainable innovations is an international policy ambition. In the on-hand manuscript, a concept combining safe by design and sustainability was implemented through the integration of human and environmental risk assessment, life cycle assessment as well as an assessment of the economic viability. The result is a nested and iterative process in form of a decision tree that integrates these three elements in order to achieve sustainable, safe and competitive materials, products or services. This approach, embedded into the stage-gate-model for safe by design, allows to reduce the uncertainty related to the assessment of risks and impacts by improving the quality of the data collected along each stage. In the second part of the manuscript, the application is shown for a case study dealing with the application of nanoparticles for Li-Ion batteries. One of the general conclusions out of this case study is that data gaps are a key aspect in view of the reliability of the results.

Setting guidelines for co-occurring nanoparticles in water medium

This study developed a framework termed as "mixNanohealthrisk" hereafter, for the first time as per literature review, to provide exposure limit or reference dose for co-occurring nanoparticles (NPs) in water for different regions of the world. The effect of interaction of NPs on (i) NP occurrence in environment and (ii) toxic effects were incorporated for estimating NP exposure dose and associated risks (in terms of risk quotient (RQ) and hazard index (HI). Reference dose (RfD) values for SiO₂, CeO₂, TiO₂, Al₂O₃, Fe₂O₃, CNT, C₆₀, ZnO and CuO NPs were calculated for the first time in this study based on toxicity studies. RfD values for top three risk-posing nanoparticles when co-occurring together were found to be 0.1 mg/kg/d (CuO), 0.12 mg/kg/d (ZnO) and 0.19 mg/kg/d (TiO₂). Calculated maximum allowable concentration values for these nanoparticles were found to be 70.8, 84.4 and 136 mg/L for CuO, ZnO and TiO₂ NPs. Exposures to nanoparticles aggregate (ZnO NP + CuO NP) in mixture suspension was found to have allowable ZnO and CuO concentration values of 24.7 mg/L and 175.2 mg/L respectively when present as aggregate. Top three regions identified with highest risk quotient were found to be USA followed by Switzerland and whole of Europe. During use of NP-interaction data for estimating risks, Ag, TiO₂ and CuO NPs were found to have lowest maximum allowable concentration values. The identified top three risk-posing NPs can be used for conducting toxicity studies for mixture of NPs and long-term monitoring so that it can be used for setting up guideline concentration values for NPs in mixture for water environment.

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.

Finding Nano: Challenges Involved in Monitoring the Presence and Fate of Engineered Titanium Dioxide Nanoparticles in Aquatic Environments

In recent years, titanium dioxide (TiO2) has increasingly been used as an inorganic ultraviolet (UV) filter for sun protection. However, nano-TiO2 may also pose risks to the health of humans and the environment. Thus, to adequately assess its potential adverse effects, a comprehensive understanding of the behaviour and fate of TiO2 in different environments is crucial. Advances in analytical and modelling methods continue to improve researchers’ ability to quantify and determine the state of nano-TiO2 in various environments. However, due to the complexity of environmental and nanoparticle factors and their interplay, this remains a challenging and poorly resolved feat. This paper aims to provide a focused summary of key particle and environmental characteristics that influence the behaviour and fate of sunscreen-derived TiO2 in swimming pool water and natural aquatic environments and to review the current state-of-the-art of single particle inductively coupled plasma mass spectrometry (SP-ICP-MS) approaches to detect and characterise TiO2 nanoparticles in aqueous media. Furthermore, it critically analyses the capability of existing fate and transport models to predict environmental TiO2 levels. Four particle and environmental key factors that govern the fate and behaviour of TiO2 in aqueous environments are identified. A comparison of SP-ICP-MS studies reveals that it remains challenging to detect and characterise engineered TiO2 nanoparticles in various matrices and highlights the need for the development of new SP-ICP-MS pre-treatment and analysis approaches. This review shows that modelling studies are an essential addition to experimental studies, but they still lack in spatial and temporal resolution and mostly exclude surface transformation processes. Finally, this study identifies the use of Bayesian Network-based models as an underexplored but promising modelling tool to overcome data uncertainties and incorporates interconnected variables.

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.

Stability and characterization of mixture of three particle system containing ZnO-CuO nanoparticles and clay

The aim of this study was to understand heteroaggregation of mixture of ZnO and CuO nanoparticles (NPs) with clay, for the first time as per the authors' knowledge. Aggregation studies of mixture of ZnO and CuO nanoparticles with clay was done (ionic strength =5 mM; pH 7; nanoparticles concentration = 0.1 mg/L, 1 mg/L, 10 mg/L; Clay concentration = 1, 10, and 100 mg/L and HA concentration = 0.1,1, and 10 mg/L as total organic carbon). Critical coagulation concentration (CCC) and attachment efficiency values of suspensions with ZnO: CuO ratio = 0.1, 1, 10 were also determined. Aggregation and liquid portions of mixture suspension at equal mass ratio were characterized for size, zeta potential (ZP), metal and ion contents, pH and conductivity. Results indicated that CCC was found to be 120.7 mM for ZnO: CuO ratio 10 and 1144 mM for ZnO: CuO ratio 1. Values of attachment efficiency were obtained to be 0.9 and 0.8 for these two ZnO:CuO ratio. At natural water ionic strength (IS) condition, aggregate rate constant of mixture of particles ranged from 0.281 to 8.63 nm/min for 10 mg/L NP concentration. Aggregation in suspension containing mixture of particles was found to be affected by NP concentration, clay concentration, and humic acid (p < 0.05). During a 1-h aggregation study, 2.67 mg Cu metal/g aggregate and 0.38 mg Zn/g aggregate were found in aggregates of 5 mM suspension. Overall, this study provided information on aggregation characterization of mixture of metal oxide nanoparticles (ZnO and CuO) in HA and clay presence, which is useful in understanding aggregation formation and in characterizing exposure dose for environmental risk assessment. More detailed information on a three -particle system with natural colloids is required for predicting their fate in aquatic system and defining risk.

Risk Management Framework for Nano-Biomaterials Used in Medical Devices and Advanced Therapy Medicinal Products

The convergence of nanotechnology and biotechnology has led to substantial advancements in nano-biomaterials (NBMs) used in medical devices (MD) and advanced therapy medicinal products (ATMP). However, there are concerns that applications of NBMs for medical diagnostics, therapeutics and regenerative medicine could also pose health and/or environmental risks since the current understanding of their safety is incomplete. A scientific strategy is therefore needed to assess all risks emerging along the life cycles of these products. To address this need, an overarching risk management framework (RMF) for NBMs used in MD and ATMP is presented in this paper, as a result of a collaborative effort of a team of experts within the EU Project BIORIMA and with relevant inputs from external stakeholders. The framework, in line with current regulatory requirements, is designed according to state-of-the-art approaches to risk assessment and management of both nanomaterials and biomaterials. The collection/generation of data for NBMs safety assessment is based on innovative integrated approaches to testing and assessment (IATA). The framework can support stakeholders (e.g., manufacturers, regulators, consultants) in systematically assessing not only patient safety but also occupational (including healthcare workers) and environmental risks along the life cycle of MD and ATMP. The outputs of the framework enable the user to identify suitable safe(r)-by-design alternatives and/or risk management measures and to compare the risks of NBMs to their (clinical) benefits, based on efficacy, quality and cost criteria, in order to inform robust risk management decision-making.

Key principles and operational practices for improved nanotechnology environmental exposure assessment

Nanotechnology is identified as a key enabling technology due to its potential to contribute to economic growth and societal well-being across industrial sectors. Sustainable nanotechnology requires a scientifically based and proportionate risk governance structure to support innovation, including a robust framework for environmental risk assessment (ERA) that ideally builds on methods established for conventional chemicals to ensure alignment and avoid duplication. Exposure assessment developed as a tiered approach is equally beneficial to nano-specific ERA as for other classes of chemicals. Here we present the developing knowledge, practical considerations and key principles need to support exposure assessment for engineered nanomaterials for regulatory and research applications.

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).

ChemFate: A fate and transport modeling framework for evaluating radically different chemicals under comparable conditions

With the ever-increasing development on novel chemicals and materials, with radically different properties and environmental behavior, it is challenging to compare their environmental behavior under similar conditions. For example, pesticides may be non-ionizable organics, ionizable organics, metal ion-based, or nanomaterials. These very different chemicals behave very differently. To date, no single modeling platform can handle all adequately, in a dynamic framework that accounts for actual variability in meteorology, rates of release to the environment, and the actual characteristics of the region of interest. Here we present ChemFate, a framework to address this challenge, by incorporating four different fate and transport models, each to address these four classes of chemicals (non-ionizable organics, ionizable organics, metal ion-based, or nanomaterials). We build upon established models, but have incorporated a number of additional processes. After demonstrating that the individual models comparable favorably with observed data and the previous models, under similar conditions, we conducted a case study with four radically different fungicides, used in the Central Valley, California. We found that although the concentrations of the non-ionizable and ionizable organic fungicide spike after application and temporarily may exceed toxicity thresholds for Daphnia Magna, they do not accumulate over time, while the metal ion and metallic nanoparticle result in increasing accumulation of Cu²⁺, eventually exceeding the toxicity threshold during runoff events. This case study demonstrates the value of a framework that allows the comparison of different classes of chemicals under the same conditions.

Nanomaterial Transformations in the Environment: Effects of Changing Exposure Forms on Bioaccumulation and Toxicity

In the environment, nanomaterials (NMs) are subject to chemical transformations, such as redox reactions, dissolution, coating degradation, and organic matter, protein, and macromolecule binding, and physical transformations including homo or heteroagglomeration. The combination of these reactions can result in NMs with differing characteristics progressing through a functional fate pathway that leads to the formation of transformed NM functional fate groups with shared properties. To establish the nature of such effects of transformation on NMs, four main types of studies are conducted: 1) chemical aging for transformation of pristine NMs; 2) manipulation of test media to change NM surface properties; 3) aging of pristine NMs water, sediment, or soil; 4) NM aging in waste streams and natural environments. From these studies a paradigm of aging effects on NM uptake and toxicity can be developed. Transformation, especially speciation changes, largely results in reduced potency. Further reactions at the surface resulting in processes, such as ecocorona formation and heteroagglomeration may additionally reduce NM potency. When NMs of differing potency transform and enter environments, common transformation reaction occurring in receiving system may act to reduce the variation in hazard between different initial NMs leading to similar actual hazard under realistic exposure conditions.

A Review on the Environmental Fate Models for Predicting the Distribution of Engineered Nanomaterials in Surface Waters

Exposure assessment is a key component in the risk assessment of engineered nanomaterials (ENMs). While direct and quantitative measurements of ENMs in complex environmental matrices remain challenging, environmental fate models (EFMs) can be used alternatively for estimating ENMs' distributions in the environment. This review describes and assesses the development and capability of EFMs, focusing on surface waters. Our review finds that current engineered nanomaterial (ENM) exposure models can be largely classified into three types: material flow analysis models (MFAMs), multimedia compartmental models (MCMs), and spatial river/watershed models (SRWMs). MFAMs, which is already used to derive predicted environmental concentrations (PECs), can be used to estimate the releases of ENMs as inputs to EFMs. Both MCMs and SRWMs belong to EFMs. MCMs are spatially and/or temporally averaged models, which describe ENM fate processes as intermedia transfer of well-mixed environmental compartments. SRWMs are spatiotemporally resolved models, which consider the variability in watershed and/or stream hydrology, morphology, and sediment transport of river networks. As the foundation of EFMs, we also review the existing and emerging ENM fate processes and their inclusion in recent EFMs. We find that while ENM fate processes, such as heteroaggregation and dissolution, are commonly included in current EFMs, few models consider photoreaction and sulfidation, evaluation of the relative importance of fate processes, and the fate of weathered/transformed ENMs. We conclude the review by identifying the opportunities and challenges in using EFMs for ENMs.

Toward the Development and Application of an Environmental Risk Assessment Framework for Microplastic

Emissions of plastic waste to the environment and the subsequent degradation into microplastic particles that have the potential to interact with biological organisms represent a concern for global society. Current understanding of the potential impacts on aquatic and terrestrial population stability and ecosystem structure and function associated with emissions of microplastic particles is limited and insufficient to fully assess environmental risks. Multistakeholder discussions can provide an important element in helping to identify and prioritize key knowledge gaps in assessing potential risks. In the present review, we summarize multistakeholder discussions from a 1-d International Council of Chemical Associations-sponsored symposium, which involved 39 scientists from 8 countries with representatives from academia, industry, and government. Participants were asked to consider the following: discuss the scientific merits and limitations of applying a proposed conceptual environmental risk assessment (ERA) framework for microplastic particles and identify and prioritize major research needs in applying ERA tools for microplastic particles. Multistakeholder consensus was obtained with respect to the interpretation of the current state of the science related to effects and exposure to microplastic particles, which implies that it is unlikely that the presence of microplastic in the environment currently represents a risk. However, the quality and quantity of existing data require substantial improvement before conclusions regarding the potential risks and impacts of microplastic particles can be fully assessed. Research that directly addresses the development and application of methods that strengthen the quality of data should thus be given the highest priority. Activities aimed at supporting the development of and access to standardized reference material were identified as a key research need. Environ Toxicol Chem 2019;38:2087-2100. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Development of a model (SWNano) to assess the fate and transport of TiO2 engineered nanoparticles in sewer networks

A new model, SWNano (Sewer-Water Nano), has been developed in the present study that quantitatively simulates the spatio-temporal changes in the concentrations of TiO₂ ENPs of dispersed and aggregated forms in the sewage water and sediment of a sewer network. As a brief example of SWNano applications, a small section of the entire sewer network of Seoul, Korea, was chosen to study where the sewage water was experimentally characterized. The predictions of SWNano present important findings that i) heteroaggregation is the most significant process following the advective transport among the fate and transport processes in the sewer pipes, ii) the heteroaggregation of TiO₂ ENPs with SPMs in the sewage water can substantially (a few % to more than 50%) reduce the freely dispersed TiO₂ ENPs depending on the magnitude of attachment efficiency, and iii) accurate determination of attachment efficiency is of critical importance in predicting the quantity of individual forms of ENPs exiting the sewer system. The predictions strongly suggest that the fate and transport of TiO₂ ENPs in the sewer networks be taken into account to improve the assessment of exposure to TiO₂ ENPs in the aquatic ecosystems, which warrants further development and use of models like SWNano.

Risk Governance of Nanomaterials: Review of Criteria and Tools for Risk Communication, Evaluation, and Mitigation

Nanotechnologies have been increasingly used in industrial applications and consumer products across several sectors, including construction, transportation, energy, and healthcare. The widespread application of these technologies has raised concerns regarding their environmental, health, societal, and economic impacts. This has led to the investment of enormous resources in Europe and beyond into the development of tools to facilitate the risk assessment and management of nanomaterials, and to inform more robust risk governance process. In this context, several risk governance frameworks have been developed. In our study, we present and review those, and identify a set of criteria and tools for risk evaluation, mitigation, and communication, the implementation of which can inform better risk management decision-making by various stakeholders from e.g., industry, regulators, and the civil society. Based on our analysis, we recommend specific methods from decision science and information technologies that can improve the existing risk governance tools so that they can communicate, evaluate, and mitigate risks more transparently, taking stakeholder perspectives and expert opinion into account, and considering all relevant criteria in establishing the risk-benefit balance of these emerging technologies to enable more robust decisions about the governance of their risks.

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

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

Computational models for the assessment of manufactured nanomaterials: Development of model reporting standards and mapping of the model landscape

Different types of computational models have been developed for predicting the biokinetics, environmental fate, exposure levels and toxicological effects of chemicals and manufactured nanomaterials (MNs). However, these models are not described in a consistent manner in the scientific literature, which is one of the barriers to their broader use and acceptance, especially for regulatory purposes. Quantitative structure-activity relationships (QSARs) are in silico models based on the assumption that the activity of a substance is related to its chemical structure. These models can be used to provide information on (eco)toxicological effects in hazard assessment. In an environmental risk assessment, environmental exposure models can be used to estimate the predicted environmental concentration (PEC). In addition, physiologically based kinetic (PBK) models can be used in various ways to support a human health risk assessment. In this paper, we first propose model reporting templates for systematically and transparently describing models that could potentially be used to support regulatory risk assessments of MNs, for example under the REACH regulation. The model reporting templates include (a) the adaptation of the QSAR Model Reporting Format (QMRF) to report models for MNs, and (b) the development of a model reporting template for PBK and environmental exposure models applicable to MNs. Second, we show the usefulness of these templates to report different models, resulting in an overview of the landscape of available computational models for MNs.

Engineering nanomaterials for water and wastewater treatment: review of classifications, properties and applications

Based on their characteristics and applicability, a new category of NMs is proposed for water and wastewater treatment.

Proxy Measures for Simplified Environmental Assessment of Manufactured Nanomaterials

Proxy measures have been proposed as a low-data option for simplified assessment of environmental threat given the high complexity of the natural environment. We here review studies of environmental release, fate, toxicity, and risk to identify relevant proxy measures for manufactured nanomaterials (MNMs). In total, 18 potential proxy measures were identified and evaluated regarding their link to environmental risk, an aspect of relevance, and data availability, an aspect of practice. They include socio-technical measures (e.g., MNM release), particle-specific measures (e.g., particle size), partitioning coefficients (e.g., the octanol-water coefficient), and other fate-related measures (e.g., half-life) as well as various ecotoxicological measures (e.g., 50% effect concentration). For most identified proxy measures, the link to environmental risk was weak and data availability low. Two exceptions were global production volume and ecotoxicity, for which the links to environmental risk are strong and data availability relatively decent. As proof of concept, these were employed to assess seven MNMs: titanium dioxide, cerium dioxide, zinc oxide, silver, silicon dioxide, carbon nanotubes, and graphene. The results show that none of the MNMs have both high production volumes and high ecotoxicity. Several refinements of the assessment are possible, such as higher resolution regarding the MNMs assessed (e.g., different allotropes) and different metrics (e.g., particle number and surface area). The proof of concept shows the feasibility of using proxy measures for environmental assessment of MNMs, in particular for novel MNMs in early technological development, when data is particularly scarce.

An assessment of applicability of existing approaches to predicting the bioaccumulation of conventional substances in nanomaterials

The experimental determination of bioaccumulation is challenging, and a number of approaches have been developed for its prediction. It is important to assess the applicability of these predictive approaches to nanomaterials (NMs), which have been shown to bioaccumulate. The octanol/water partition coefficient (K_OW ) may not be applicable to some NMs that are not found in either the octanol or water phases but rather are found at the interface. Thus the K_OW values obtained for certain NMs are shown not to correlate well with the experimentally determined bioaccumulation. Implementation of quantitative structure-activity relationships (QSARs) for NMs is also challenging because the bioaccumulation of NMs depends on nano-specific properties such as shape, size, and surface area. Thus there is a need to develop new QSAR models based on these new nanodescriptors; current efforts appear to focus on digital processing of NM images as well as the conversion of surface chemistry parameters into adsorption indices. Water solubility can be used as a screening tool for the exclusion of NMs with short half-lives. Adaptation of fugacity/aquivalence models, which include physicochemical properties, may give some insights into the bioaccumulation potential of NMs, especially with the addition of a biota component. The use of kinetic models, including physiologically based pharmacokinetic models, appears to be the most suitable approach for predicting bioaccumulation of NMs. Furthermore, because bioaccumulation of NMs depends on a number of biotic and abiotic factors, it is important to take these factors into account when one is modeling bioaccumulation and interpreting bioaccumulation results. Environ Toxicol Chem 2018;37:2972-2988. © 2018 SETAC.

Considering the forms of released engineered nanomaterials in probabilistic material flow analysis

Most existing models for assessing the releases of engineered nanomaterials (ENMs) into the environment are based on the assumption that ENMs remain in their pristine forms during their whole life cycle. It is known, however, that this is not always the case as ENMs are often embedded into solid matrices during manufacturing and can undergo physical or chemical transformations during their life cycle, e.g. upon release to wastewater. In this work, we present a method for systematically assessing the forms in which nano-Ag and nano-TiO₂ flow through their life cycle (i.e. production, manufacturing, use and disposal) to their points of release to air, soil and surface water. Input data on the forms of released ENMs were probability distributions based on peer-reviewed literature. Release data were incorporated into a probabilistic material flow analysis model to quantify the proportions of ENMs in product-embedded, matrix-embedded, pristine, transformed and dissolved forms in all technical and environmental compartments into which they flow, at the European scale. Releases of nano-Ag to surface water and soil were modelled to occur primarily in transformed forms (Q25 and Q75 of 34-58% and 78-86%, respectively, with means of 53% and 82%), while releases to air were mostly in pristine and matrix-embedded forms (38-46% and 36-44%, respectively, with means of 42% and 40%). In contrast, nano-TiO₂ releases to air, soil and water were estimated to be predominantly in pristine form (75-85%, 90-95%, 96-98%, respectively, with means of 80%, 91% and 97%). The distributions of ENM releases between forms developed here will improve the representativeness and appropriateness of input data for environmental fate modelling and risk assessment of ENMs.

Safety Assessment of Graphene-Based Materials: Focus on Human Health and the Environment

Graphene and its derivatives are heralded as "miracle" materials with manifold applications in different sectors of society from electronics to energy storage to medicine. The increasing exploitation of graphene-based materials (GBMs) necessitates a comprehensive evaluation of the potential impact of these materials on human health and the environment. Here, we discuss synthesis and characterization of GBMs as well as human and environmental hazard assessment of GBMs using in vitro and in vivo model systems with the aim to understand the properties that underlie the biological effects of these materials; not all GBMs are alike, and it is essential that we disentangle the structure-activity relationships for this class of materials.

Gold nanoparticle biodissolution by a freshwater macrophyte and its associated microbiome

Predicting nanoparticle fate in aquatic environments requires mimicking of ecosystem complexity to observe the geochemical processes affecting their behaviour. Here, 12 nm Au nanoparticles were added weekly to large-scale freshwater wetland mesocosms. After six months, ~70% of Au was associated with the macrophyte Egeria densa, where, despite the thermodynamic stability of Au⁰ in water, the pristine Au⁰ nanoparticles were fully oxidized and complexed to cyanide, hydroxyls or thiol ligands. Extracted biofilms growing on E. densa leaves were shown to dissolve Au nanoparticles within days. The Au biodissolution rate was highest for the biofilm with the lowest prevalence of metal-resistant taxa but the highest ability to release cyanide, known to promote Au⁰ oxidation and complexation. Macrophytes and the associated microbiome thus form a biologically active system that can be a major sink for nanoparticle accumulation and transformations. Nanoparticle biotransformation in these compartments should not be ignored, even for nanoparticles commonly considered to be stable in the environment.

Trade-offs in ecosystem impacts from nanomaterial versus organic chemical ultraviolet filters in sunscreens

Both nanoparticulate (nZnO and nTiO₂) and organic chemical ultraviolet (UV) filters are active ingredients in sunscreen and protect against skin cancer, but limited research exists on the environmental effects of sunscreen release into aquatic systems. To examine the trade-offs of incorporating nanoparticles (NPs) into sunscreens over the past two decades, we targeted endpoints sensitive to the potential risks of different UV filters: solar reactive oxygen production in water and disruption of zebrafish embryo development. First, we developed methodology to extract nanoparticles from sunscreens with organic solvents. Zebrafish embryos exposed to parts-per-million NPs used in sunscreens displayed limited toxicological effects; nZnO particles appeared to be slightly more toxic than nTiO₂ at the highest concentrations. In contrast, seven organic UV filters did not affect zebrafish embryogenesis at or near aqueous solubility. Second, to simulate potent photo-initiated reactions upon release into water, we examined methylene blue (MB) degradation under UV light. nTiO₂ from sunscreen caused 10 times faster MB loss than nZnO and approached the photocatalytic degradation rate of a commercial nTiO₂ photocatalysts (P25). Organic UV filters did not cause measurable MB degradation. Finally, we estimated that between 1 and 10 ppm of sunscreen NPs in surface waters could produce similar steady state hydroxyl radical concentrations as naturally occurring fluvic acids under sunlight irradiation. Incorporation of NPs into sunscreen may increase environmental concentrations of reactive oxygen, albeit to a limited extent, which can influence transformation of dissolved substances and potentially affect ecosystem processes.

Silver engineered nanoparticles in freshwater systems - Likely fate and behaviour through natural attenuation processes

Growth in the nanotechnology sector is likely introducing unnatural formations of materials on the nanoscale (10^-9m) to the environment. Disposal and degradation of products incorporating engineered nanomaterials (ENMs) are likely being released into natural aquatic systems un-intentionally primarily via waste water effluents. The fate and behaviour of metallic based nanoparticles (NPs) such as silver (Ag) in aquatic waters is complex with high levels of variability and uncertainty. In-situ physical, biological and chemical (natural attenuation) processes are likely to influence ENM fate and behaviour in freshwater systems. Surfaced functionalized particles may inhibit or limit environmental transformations which influence particle aggregation, mobility, dissolution and eco-toxic potential. This paper focuses on ENM characteristics and the influence of physical, chemical and biological processes occurring in aquatic systems that are likely to impact metallic ENMs fate. A focus on silver NPs (while for comparison, reporting about other metallic ENMs as appropriate) released to aquatic systems is discussed relating to their likely fate and behaviour in this dynamic and complex environment. This paper further highlights the need for specific risk assessment approaches for metallic ENMs and puts this into context with regard to informing environmental policy and potential NP influence on environmental/human health.

Modified MODFLOW-based model for simulating the agglomeration and transport of polymer-modified Fe0 nanoparticles in saturated porous media

The solute transport model MODFLOW has become a standard tool in risk assessment and remediation design. However, particle transport models that take into account both particle agglomeration and deposition phenomena are far less developed. The main objective of the present study was to evaluate the feasibility of adapting the standard code MODFLOW/MT3D to simulate the agglomeration and transport of three different types of polymer-modified nanoscale zerovalent iron (NZVI) in one-dimensional (1-D) and two-dimensional (2-D) saturated porous media. A first-order decay of the particle population was used to account for the agglomeration of particles. An iterative technique was used to optimize the model parameters. The model provided good matches to 1-D NZVI-breakthrough data sets, with R ² values ranging from 0.96 to 0.99, and mass recovery differences between the experimental results and simulations ranged from 0.1 to 1.8 %. Similarly, simulations of NZVI transport in the heterogeneous 2-D model demonstrated that the model can be applied to more complicated heterogeneous domains. However, the fits were less good, with the R ² values in the 2-D modeling cases ranging from 0.75 to 0.95, while the mass recovery differences ranged from 0.7 to 6.5 %. Nevertheless, the predicted NZVI concentration contours during transport were in good agreement with the 2-D experimental observations. The model provides insights into NZVI transport in porous media by mathematically decoupling agglomeration, attachment, and detachment, and it illustrates the importance of each phenomenon in various situations. Graphical Abstract ᅟ.

Environmental fate and exposure models: advances and challenges in 21st century chemical risk assessment

Environmental fate and exposure models are a powerful means to integrate information on chemicals, their partitioning and degradation behaviour, the environmental scenario and the emissions in order to compile a picture of chemical distribution and fluxes in the multimedia environment. A 1995 pioneering book, resulting from a series of workshops among model developers and users, reported the main advantages and identified needs for research in the field of multimedia fate models. Considerable efforts were devoted to their improvement in the past 25 years and many aspects were refined; notably the inclusion of nanomaterials among the modelled substances, the development of models at different spatial and temporal scales, the estimation of chemical properties and emission data, the incorporation of additional environmental media and processes, the integration of sensitivity and uncertainty analysis in the simulations. However, some challenging issues remain and require research efforts and attention: the need of methods to estimate partition coefficients for polar and ionizable chemical in the environment, a better description of bioavailability in different environments as well as the requirement of injecting more ecological realism in exposure predictions to account for the diversity of ecosystem structures and functions in risk assessment. Finally, to transfer new scientific developments into the realm of regulatory risk assessment, we propose the formation of expert groups that compare, discuss and recommend model modifications and updates and help develop practical tools for risk assessment.

Risk analysis and technology assessment in support of technology development: Putting responsible innovation in practice in a case study for nanotechnology

Governments invest in "key enabling technologies," such as nanotechnology, to solve societal challenges and boost the economy. At the same time, governmental agencies demand risk reduction to prohibit any often unknown adverse effects, and industrial parties demand smart approaches to reduce uncertainties. Responsible research and innovation (RRI) is therefore a central theme in policy making. Risk analysis and technology assessment, together referred to as "RATA," can provide a basis to assess human, environmental, and societal risks of new technological developments during the various stages of technological development. This assessment can help both governmental authorities and innovative industry to move forward in a sustainable manner. Here we describe the developed procedures and products and our experiences to bring RATA in practice within a large Dutch nanotechnology consortium. This is an example of how to put responsible innovation in practice as an integrated part of a research program, how to increase awareness of RATA, and how to help technology developers perform and use RATA. Integr Environ Assess Manag 2018;14:9-16. © 2017 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of Society of Environmental Toxicology & Chemistry (SETAC).