尼罗河红
染色
微塑料
粒子(生态学)
荧光
化学
粒径
纳米颗粒
色谱法
荧光染色
尼罗河蓝
生物物理学
纳米技术
环境化学
材料科学
生物
物理
生态学
遗传学
物理化学
量子力学
作者
Swarupa Chatterjee,Eva Krolis,Robert Molenaar,Mireille Maria Anna Elisabeth Claessens,Christian Blum
标识
DOI:10.1016/j.envc.2023.100744
摘要
The true extent of plastic particle pollution is largely unknown, particularly for particles <1 µm (nanoplastics), as they are difficult to detect. Here, we expand the Nile Red (NR) staining approach often used to visualize microplastics to the quantification of nanoplastics. Using NR staining for nanoplastic quantification is largely unexplored due to the formation of fluorescent NR aggregates which cause false positive counts in single particle counting. Here, we study the number and size of the NR aggregates formed as a function of NR concentration and show that with decreasing NR concentration, the number and size of the NR aggregates drops. At nanomolar concentrations, the number of NR aggregates is low, while staining of nanoplastics at these concentrations still results in signals that are sufficiently bright for single particle detection. To challenge and verify our approach, we spiked a drinking water sample with known amounts of nanoplastics. After quantification of the total amount of fluorescent nanoparticles and considering NR aggregates and the added amounts of nanoplastics, we find a stable number of NR positive nanoparticles for the drinking water sample, thus verifying our approach. To demonstrate the direct applicability of our method, without any pre-analytical treatment, we determined the number of NR positive nanoparticles in different drinking water samples. In water obtained from plastic bottles and plastic-lined cartons, we detected approximately 250 nanoparticles/nL, which is well above the level of detection of our method. In tap water, we found approximately 10 times fewer NR positive nanoparticles. Our study demonstrates that staining at nM NR concentrations combined with a careful characterization of the number of NR aggregates in solution allows for using single-particle counting for nanoplastic quantification in water samples. We foresee that this approach can contribute to filling the gap in knowledge on the abundance of nanoplastics.
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