化学
聚合物
场流分馏
质谱法
聚苯乙烯
废水
基质(化学分析)
多角度光散射
色谱法
分馏
气相色谱法
聚氯乙烯
聚烯烃
光散射
有机化学
环境科学
环境工程
图层(电子)
散射
物理
光学
作者
Maria Hayder,Cloé Veclin,A. A. Ahern,Aleksandra Chojnacka,Erwin Roex,Florian Meier,Gert-Jan M. Gruter,Annemarie P. van Wezel,Alina Astefanei
标识
DOI:10.1021/acs.analchem.5c01766
摘要
Although nanoplastics are a widespread pollutant, their characterization and quantification in environmental samples remains challenging with no standard approach currently available. Here, we describe a novel workflow for nanoplastic analysis in environmental water samples, incorporating asymmetrical flow field-flow fractionation with multiangle light scattering (AF4-MALS) and pyrolysis-gas chromatography-mass spectrometry (Py-GC-MS) in an offline combination. The techniques complement each other as AF4-MALS enables sample cleanup and size separation down to about 1 nm, while Py-GC-MS identifies and quantifies polymers in each size fraction. Such a setup may provide comprehensive information about nanoplastic size distributions and polymer composition within a single workflow. After careful validation using standard polymer particles, we applied the method to wastewater samples. Our results show that the offline AF4-MALS-Py-GC-MS combination can identify certain nanoplastics in a complex environmental matrix. The mass quantification limits depend on the polymer type and range from 0.64 ng for PS to 180 ng for polyolefins. With our workflow, 8.8 ± 1.8 ng/mL polystyrene nanoplastics were quantified and polyvinyl chloride was potentially identified in untreated wastewater. Polyolefin and poly(ethylene terephthalate) signals were below detection limits. While still in its early stages, this novel approach provides a promising foundation for particulate polymer analysis and highlights areas for further refinement, with the low recovery and potential of matrix interferences as drawbacks.
科研通智能强力驱动
Strongly Powered by AbleSci AI