A model for screening and prioritizing consumer nanoproduct risks: A case study from South Africa

Abstract

The potential risks of the increasing variety and volume of engineered nanomaterials (ENMs) entering into the ecosystem remain poorly quantified. In recent years, information essential to evaluate the ecological risks of ENMs has increased. However, the data are highly fragmented, limited, or severely lacking. This limits the usefulness of the information to support holistic screening and prioritization of potentially harmful ENMs. To screen and prioritize ENMs risks, we adopted a two-phased approach. First, a holistic framework model was developed to integrate a diverse set of factors aimed to assess the potential hazard, exposure, and in turn, risk to the ecosystem of ENMs from a given consumer nanoproduct. Secondly, using published literature we created a database of consumer nanoproduct categories, and types based on embedded ENMs type. The database consisted of eight consumer product categories, eleven different types of ENMs, and twenty-three nanoproduct types. The model results indicates the largest quantities of ENMs were released from sunscreens, textiles, cosmetics and paints with dominant ENMs quantities in descending order (based on quantity) as nTiO2>nZnO>nSiO2>nAg, and nFe2O3. In addition, according to the results from this study, nAg from washing machine were found to likely the highest risk to the environment. Overall, our model-derived results based on the case study illustrated: (i) the holistic framework's ability to screen, prioritize, rank, and compare ENMs potential exposure and risks among different nanoproducts categories and types, (ii) the derived risk estimations could support nanowastes classification with likelihood of non-uniformity of nanowastes classes even from the same nanoproduct category (e.g. cosmetics), and (iii) the lack of a mass-based criteria specific for EMNs impedes realistic exposure and risk evaluation in the ecological systems.