Simulation tool for assessing the release and environmental distribution of nanomaterials

Everything falls apart: How solids degrade and release nanomaterials, composite fragments, and microplastics

To ensure the safe use of materials, one must assess the identity and quantity of exposure. Solid materials, such as plastics, metals, coatings and cements, degrade to some extent during their life cycle, and releases can occur during manufacturing, use and end-of-life. Releases (e.g., what is released, how does release happen, and how much material is released) depend on the composition and internal (nano)structures of the material as well as the applied stresses during the lifecycle. We consider, in some depth, releases from mechanical, weathering and thermal stresses and specifically address the use cases of fused-filament 3D printing, dermal contact, food contact and textile washing. Solid materials can release embedded nanomaterials, composite fragments, or micro- and nanoplastics, as well as volatile organics, ions and dissolved organics. The identity of the release is often a heterogenous mixture and requires adapted strategies for sampling and analysis, with suitable quality control measures. Control materials enhance robustness by enabling comparative testing, but reference materials are not always available as yet. The quantity of releases is typically described by time-dependent rates that are modulated by the nature and intensity of the applied stress, the chemical identity of the polymer or other solid matrix, and the chemical identity and compatibility of embedded engineered nanomaterials (ENMs) or other additives. Standardization of methods and the documentation of metadata, including all the above descriptors of the tested material, applied stresses, sampling and analytics, are identified as important needs to advance the field and to generate robust, comparable assessments. In this regard, there are strong methodological synergies between the study of all solid materials, including the study of micro- and nanoplastics. From an outlook perspective, we review the hazard of the released entities, and show how this informs risk assessment. We also address the transfer of methods to related issues such as tyre wear, advanced materials and advanced manufacturing, biodegradable polymers, and non-solid matrices. As the consideration of released entities will become more routine in industry via lifecycle assessment in Safe-and-Sustainable-by-Design practices, release assessments will require careful design of the study with quality controls, the use of agreed-on test materials and standardized methods where these exist and the adoption of clearly defined data reporting practices that enable data reuse, meta-analyses, and comparative studies.

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.

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.

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.

A critical analysis of environmental sustainability metrics applied to green synthesis of nanomaterials and the assessment of environmental risks associated with the nanotechnology

Nanotechnology is one of the most relevant scientific areas today due to its multiple applications in fields such as medicine, environmental remediation, information technology and energy conversion. This importance has led to the need to advance in the development of environmentally sustainable and safe nanomaterials by incorporating the principles of green chemistry during their synthesis and in their applications. However, this qualitative framework of thought does not offer minimum criteria for the use of the term "green", and therefore, this adjective is commonly used to refer to bio-based or nanotechnological processes without taking into account their net ecological impact. In this context, environmental sustainability metrics can be applied to nanotechnology to compare, optimize and quantify the environmental sustainability of synthesis procedures. This review provides an overview of green chemistry and its application in nanotechnology, but also an analysis of the use of green chemistry principles in the development of bio-based nanobiotechnology and nanosynthesis, with special emphasis on the use of sustainability's metrics for the quantitative analysis of nanomaterial synthesis protocols. These include: Atom Economy, E-factor, Process Mass Intensity, Energy Intensity, and Life Cycle Analysis.

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.

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.

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.

Bayesian network as a support tool for rapid query of the environmental multimedia distribution of nanomaterials

An approach is presented describing the development of a Bayesian network (BN) based tool for rapid assessment of the distribution of engineered nanomaterials (ENMs). The methodology was demonstrated via the construction of a BN model for estimating the exposure concentrations of nanomaterials (BN-nanoExpo) based on simulation data derived from a mechanistic multimedia compartmental fate and transport model. The results of simulations of the distribution of six ENMs in eight different regions were generated for a broad range of geographical and meteorological parameters as well as ENM release rates to the air, water and soil major compartments. Test cases with the constructed BN-nanoExpo demonstrated the capability of the BN based model to portray a wide range of simulation results that can be obtained with the mechanistic fate and transport model. Moreover, BN-nanoExpo is shown to be a suitable tool for estimating both ENM concentrations and release rates given partial information, while also enabling assessment of the impact of uncertainties in input data on the predicted outcomes. The results of the current study suggest that there is merit in exploring the utility of the approach to more complex models, which would provide decision makers with powerful tools for rapid assessment of the behavior of nanomaterials in the environment.

Envisioning Nano Release Dynamics in a Changing World: Using Dynamic Probabilistic Modeling to Assess Future Environmental Emissions of Engineered Nanomaterials

The need for an environmental risk assessment for engineered nanomaterials (ENM) necessitates the knowledge about their environmental emissions. Material flow models (MFA) have been used to provide predicted environmental emissions but most current nano-MFA models consider neither the rapid development of ENM production nor the fact that a large proportion of ENM are entering an in-use stock and are released from products over time (i.e., have a lag phase). Here we use dynamic probabilistic material flow modeling to predict scenarios of the future flows of four ENM (nano-TiO₂, nano-ZnO, nano-Ag and CNT) to environmental compartments and to quantify their amounts in (temporary) sinks such as the in-use stock and ("final") environmental sinks such as soil and sediment. In these scenarios, we estimate likely future amounts if the use and distribution of ENM in products continues along current trends (i.e., a business-as-usual approach) and predict the effect of hypothetical trends in the market development of nanomaterials, such as the emergence of a new widely used product or the ban on certain substances, on the flows of nanomaterials to the environment in years to come. We show that depending on the scenario and the product type affected, significant changes of the flows occur over time, driven by the growth of stocks and delayed release dynamics.

Assessment of agglomeration, co-sedimentation and trophic transfer of titanium dioxide nanoparticles in a laboratory-scale predator-prey model system

Nano titanium dioxide (nTiO₂) is the most abundantly released engineered nanomaterial (ENM) in aquatic environments. Therefore, it is prudent to assess its fate and its effects on lower trophic-level organisms in the aquatic food chain. A predator-and-prey-based laboratory microcosm was established using Paramecium caudatum and Escherichia coli to evaluate the effects of nTiO₂. The surface interaction of nTiO₂ with E. coli significantly increased after the addition of Paramecium into the microcosm. This interaction favoured the hetero-agglomeration and co-sedimentation of nTiO₂. The extent of nTiO₂ agglomeration under experimental conditions was as follows: combined E. coli and Paramecium > Paramecium only > E. coli only > without E. coli or Paramecium. An increase in nTiO₂ internalisation in Paramecium cells was also observed in the presence or absence of E. coli cells. These interactions and nTiO₂ internalisation in Paramecium cells induced statistically significant (p < 0.05) effects on growth and the bacterial ingestion rate at 24 h. These findings provide new insights into the fate of nTiO₂ in the presence of bacterial-ciliate interactions in the aquatic environment.

Considerations of Environmentally Relevant Test Conditions for Improved Evaluation of Ecological Hazards of Engineered Nanomaterials

Engineered nanomaterials (ENMs) are increasingly entering the environment with uncertain consequences including potential ecological effects. Various research communities view differently whether ecotoxicological testing of ENMs should be conducted using environmentally relevant concentrations-where observing outcomes is difficult-versus higher ENM doses, where responses are observable. What exposure conditions are typically used in assessing ENM hazards to populations? What conditions are used to test ecosystem-scale hazards? What is known regarding actual ENMs in the environment, via measurements or modeling simulations? How should exposure conditions, ENM transformation, dose, and body burden be used in interpreting biological and computational findings for assessing risks? These questions were addressed in the context of this critical review. As a result, three main recommendations emerged. First, researchers should improve ecotoxicology of ENMs by choosing test end points, duration, and study conditions-including ENM test concentrations-that align with realistic exposure scenarios. Second, testing should proceed via tiers with iterative feedback that informs experiments at other levels of biological organization. Finally, environmental realism in ENM hazard assessments should involve greater coordination among ENM quantitative analysts, exposure modelers, and ecotoxicologists, across government, industry, and academia.

Environmental Effects of Nanoceria on Seed Production of Common Bean (Phaseolus vulgaris): A Proteomic Analysis

The rapidly growing literature on the response of edible plants to nanoceria has provided evidence of its uptake and bioaccumulation, which delineates a possible route of entry into the food chain. However, little is known about how the residing organic matter in soil may affect the bioavailability and resulting impacts of nanoceria on plants. Here, we examined the effect of nanoceria exposure (62.5-500 mg/kg) on kidney bean (Phaseolus vulgaris) productivity and seed quality as a function of soil organic matter content. Cerium accumulation in the seeds produced from plants in organic matter enriched soil showed a dose-dependent increase, unlike in low organic matter soil treatments. Seeds obtained upon nanoceria exposure in soils with higher organic matter were more susceptible to changes in nutrient quality. A quantitative proteomic analysis of the seeds produced upon nanoceria exposure provided evidence for upregulation of stress-related proteins at 62.5 and 125 mg/kg nanoceria treatments. Although the plants did not exhibit overt toxicity, the major seed proteins primarily associated with nutrient storage (phaseolin) and carbohydrate metabolism (lectins) were significantly down-regulated in a dose dependent manner upon nanoceria exposure. This study thus suggests that nanoceria exposures may negatively affect the nutritional quality of kidney beans at the cellular and molecular level. More confirmatory studies with nanoceria along different species using alternative and orthogonal "omic" tools are currently under active investigation, which will enable the identification of biomarkers of exposure and susceptibility.