Department of Chemical Engineering, University of Pretoria, Private Bag X20, Hatfield 0028, Pretoria, South Africa.
Environ Int. 2017 Mar;100:121-131. doi: 10.1016/j.envint.2017.01.002. Epub 2017 Jan 13.
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 nTiO>nZnO>nSiO>nAg, and nFeO. 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.
进入生态系统的工程纳米材料（ENMs）的种类和数量不断增加，其潜在风险仍难以量化。近年来，评估 ENMs 生态风险所需的信息有所增加。然而，这些数据高度分散、有限或严重缺乏。这限制了信息在支持潜在有害 ENMs 的整体筛选和优先级排序方面的有用性。为了筛选和优先考虑 ENMs 风险，我们采用了两阶段方法。首先，开发了一个整体框架模型，该模型集成了一组旨在评估特定消费类纳米产品中 ENMs 对生态系统潜在危害、暴露以及相应风险的多种因素。其次，我们利用已发表的文献创建了一个基于嵌入 ENMs 类型的消费类纳米产品类别和类型的数据库。该数据库包括 8 个消费产品类别、11 种不同类型的 ENMs 和 23 种纳米产品类型。模型结果表明，从防晒霜、纺织品、化妆品和油漆中释放的 ENMs 数量最多，按数量递减的顺序，主导的 ENMs 数量分别为 nTiO>nZnO>nSiO>nAg 和 nFeO。此外，根据这项研究的结果，发现来自洗衣机的 nAg 对环境的风险最大。总体而言，我们基于案例研究的模型推导结果表明：（i）整体框架筛选、优先排序、分级和比较不同纳米产品类别和类型的 ENMs 潜在暴露和风险的能力，（ii）推导的风险估计可以支持纳米废物分类，即使来自同一纳米产品类别（例如化妆品），纳米废物类别也可能存在不均匀性，（iii）缺乏针对 EMNs 的基于质量的标准，阻碍了生态系统中真实的暴露和风险评估。
