NANOADJUST · Metallic engineered nanomaterial in natural aquatic environments: data generation, management and integration into environmental exposure modelling

Metallic engineered nanomaterial in natural aquatic environments: data generation, management and integration into environmental exposure modelling

The nanoADJUST project had the primary objective of developing expertise in the application of instrumentation and methodologies used to identify, characterise and analyse the behaviour of metallic engineered nanomaterials (ENMs) in natural aquatic media. This expertise was then integrated into environmental exposure modelling and harmonised with risk management data requirements and processes. Process-based environmental fate and transport models for ENMs require relevant and reliable measures of nanoparticle behaviour. As nanoparticles may not reach a thermodynamic partitioning equilibrium in the same manner as ‘traditional’ chemicals (i.e. octanol-water (Kow) and solid/liquid (Kd) partition coefficients), methods and measurements from colloid science have been investigated, measurements such as attachment coefficient (α) to various surfaces. In this project a mixing method for measuring nanoparticle attachment (heteroaggregation to background materials) was developed and evaluated, and then validated with an equivalent static column system over a range of organic matter concentrations and ionic strengths. The theory behind observed nanoparticle attachment rates (αβB) to background particles in mixed systems was also experimentally validated, with both collision frequency (β) and background particle concentration (B) demonstrated to be separate and calculable factors for use in fate modelling. The size and surface properties (e.g. complex protein coronas) of ENMs mean that their transport and exposure routes can be complex and diverse. Mathematical models are a useful tool for handling this complexity and diversity of these materials (in both their composition and exposure routes). A mathematical model of trophic transfer was developed, driven by nanomaterial surface affinity (α) for environmental and biological surfaces, to be used in tandem with the mixing method previously developed. Nanoparticle surface affinity was found to be a strong predictor of uptake through ingestion in a simple food web consisting of algae and daphnids, with the mass of nanoparticles internalized by the daphnia through ingesting nanomaterial-contaminated algae varying linearly with surface-attachment efficiency. The trophic transfer model, coupled with the functional-assay (i.e. mixing method) approach, was found to provide a useful risk screening tool for existing materials (when combined with ecotoxicological assays) as well as a predictive model to ensure the minimisation of risk in the development of new materials. Although ENMs are currently being used in a variety of commercial products and processes (e.g. anti-microbial surfaces, sunscreen, paint, etc.), the material characteristics employed in standard regulatory fate models (e.g. FOCUS surface and ground water) do not fully capture nano-specific behaviours. One such instance is the use of partitioning coefficients (e.g. koc) to describe fate. The use of attachment efficiency and collision frequency in predicting the fate of silver ENMs was demonstrated in three model aquatic systems: a wastewater activated sludge unit, river and lake. In these scenarios, heteroaggregation with background environmental particles was considered in the removal of ENMs, with the collision rate (β) (modelled using Matlab) defined in terms of system (mixing rate; residence time), background particle (concentration; size; density) and ENM characteristics (size; density). Background particle size and concentration, attachment efficiency and residence time had the greatest influence on predicted removal. This work demonstrated the utility of ENM attachment efficiency in predicting environmental fate, employing both material and system characteristics. For this method to be applied as part of a regulatory scheme, a database of attachment efficiencies for different surfaces under varied conditions (e.g. ionic strength, pH, OM content, etc.) must be developed, with typical aquatic/porous systems further defined and standardized in terms of mixing rate and background material concentration and type. Fellow: niall.obrien@ucd.ie; Scientist in charge: enda.cummins@ucd.ie (School of Biosystems and Food Engineering, University College Dublin, Belfield, Dublin 4, Ireland).

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