Department of Chemical Engineering , McGill University , 3610 University Street , Montréal , Québec H3A 0C5 , Canada.
Acc Chem Res. 2019 Apr 16;52(4):858-866. doi: 10.1021/acs.accounts.8b00602. Epub 2019 Mar 29.
The vast amount of plastic waste emitted into the environment and the increasing concern of potential harm to wildlife has made microplastic and nanoplastic pollution a growing environmental concern. Plastic pollution has the potential to cause both physical and chemical harm to wildlife directly or via sorption, concentration, and transfer of other environmental contaminants to the wildlife that ingest plastic. Small particles of plastic pollution, termed microplastics (>100 nm and <5 mm) or nanoplastics (<100 nm), can form through fragmentation of larger pieces of plastic. These small particles are especially concerning because of their high specific surface area for sorption of contaminants as well as their potential to translocate in the bodies of organisms. These same small particles are challenging to separate and identify in environmental samples because their size makes handling and observation difficult. As a result, our understanding of the environmental prevalence of nanoplastics and microplastics is limited. Generally, the smaller the size of the plastic particle, the more difficult it is to separate from environmental samples. Currently employed passive density and size separation techniques to isolate plastics from environmental samples are not well suited to separate microplastics and nanoplastics. Passive flotation is hindered by the low buoyancy of small particles as well as the difficulty of handling small particles on the surface of flotation media. Here we suggest exploring alternative techniques borrowed from other fields of research to improve separation of the smallest plastic particles. These techniques include adapting active density separation (centrifugation) from cell biology and taking advantage of surface-interaction-based separations from analytical chemistry. Furthermore, plastic pollution is often challenging to quantify in complex matrices such as biological tissues and wastewater. Biological and wastewater samples are important matrices that represent key points in the fate and sources of plastic pollution, respectively. In both kinds of samples, protocols need to be optimized to increase throughput, reduce contamination potential, and avoid destruction of plastics during sample processing. To this end, we recommend adapting digestion protocols to match the expected composition of the nonplastic material as well as taking measures to reduce and account for contamination. Once separated, plastics in an environmental sample should ideally be characterized both visually and chemically. With existing techniques, microplastics and nanoplastics are difficult to characterize or even detect. Their low mass and small size provide limited signal for visual, vibrational spectroscopic, and mass spectrometric analyses. Each of these techniques involves trade-offs in throughput, spatial resolution, and sensitivity. To accurately identify and completely quantify microplastics and nanoplastics in environmental samples, multiple analytical techniques applied in tandem are likely to be required.
大量的塑料废物排放到环境中,以及对野生动物潜在危害的日益关注,使得微塑料和纳米塑料污染成为一个日益严重的环境问题。塑料污染有可能直接或通过吸附、浓缩和转移其他环境污染物对野生动物造成物理和化学伤害,而野生动物会摄入这些塑料。小的塑料污染颗粒,称为微塑料(>100nm 且<5mm)或纳米塑料(<100nm),可以通过大块塑料的碎裂形成。这些小颗粒特别令人担忧,因为它们的比表面积很大,能够吸附污染物,而且它们有可能在生物体中迁移。由于这些小颗粒的尺寸使得处理和观察变得困难,因此在环境样本中分离和识别它们具有挑战性。因此,我们对纳米塑料和微塑料在环境中的普遍存在的了解是有限的。一般来说,塑料颗粒越小,从环境样本中分离出来就越困难。目前用于从环境样本中分离塑料的被动密度和尺寸分离技术不太适合分离微塑料和纳米塑料。被动浮选受到小颗粒浮力低以及在浮选介质表面处理小颗粒困难的阻碍。在这里,我们建议从其他研究领域借用替代技术来改进对最小塑料颗粒的分离。这些技术包括从细胞生物学中采用主动密度分离(离心),并利用分析化学中的基于表面相互作用的分离。此外,塑料污染在生物组织和废水等复杂基质中通常难以量化。生物和废水样本是重要的基质,分别代表了塑料污染命运和来源的关键点。在这两种样本中,都需要优化方案以提高通量、降低污染潜力,并避免在样本处理过程中破坏塑料。为此,我们建议调整消化方案以适应非塑料材料的预期组成,并采取措施减少和考虑污染。在这方面,我们建议调整消化方案以适应非塑料材料的预期组成,并采取措施减少和考虑污染。在这方面,我们建议调整消化方案以适应非塑料材料的预期组成,并采取措施减少和考虑污染。在这方面,我们建议调整消化方案以适应非塑料材料的预期组成,并采取措施减少和考虑污染。一旦分离,环境样本中的塑料应在视觉和化学上进行理想的特征描述。使用现有技术,微塑料和纳米塑料难以进行特征描述,甚至难以检测。它们的低质量和小尺寸为视觉、振动光谱和质谱分析提供了有限的信号。这些技术中的每一种都在通量、空间分辨率和灵敏度方面存在权衡。为了在环境样本中准确识别和完全量化微塑料和纳米塑料,可能需要将多种分析技术串联应用。