Identification and visualisation of microplastics/nanoplastics by Raman imaging (i): Down to 100 nm

Sobhani, Zahra; Xian, Zhang; Gibson, Christopher T.; Naidu, Ravi; Megharaj, Mallavarapu; Fang, Cheng

doi:10.1016/j.watres.2020.115658

Cited by 201 publications

(121 citation statements)

References 48 publications

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“…It can be used to characterise and quantify microplastics down to 1 µm and to visualise different microplastics simultaneously with minimal interference from water, organic matter, and fluorescence background signals. Therefore, Raman spectroscopy requires minimal preparation of samples, does not destroy the samples, and even allows the analysis of microplastics directly on the filters without first sorting visually [20,38].…”

Section: Optical Microscopy and Raman Spectroscopymentioning

confidence: 99%

Microplastics in Glaciers: First Results from the Vatnajökull Ice Cap

et al. 2021

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Microplastic particles, as a second-phase material in ice, may contribute to the effect such particles have on the melting and rheological behaviour of glaciers, and thus influence the future meltwater contribution to the oceans and rising sea levels. Hence, it is of the utmost importance to map and understand the presence and dispersal of microplastics on a global scale. In this work, we identified microplastic particles in snow cores collected in a remote and pristine location on the Vatnajökull ice cap in Iceland. Utilising optical microscopy and µ-Raman spectroscopy, we visualised and identified microplastic particles of various sizes and materials. Our findings support that atmospheric transport of microplastic particles is one of the important pathways for microplastic pollution.

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Section: Optical Microscopy and Raman Spectroscopymentioning

confidence: 99%

Microplastics in Glaciers: First Results from the Vatnajökull Ice Cap

et al. 2021

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“…Since the FTIR microscope uses a wide-band IR source, due to diffraction limits, there is a lower limit on the detectable particle size, which is in the order of 10 µm for FPA-based µFTIR microscopes, and a few micrometers for ATR-enabled FTIR microscopes, while for the Raman microscope this limit decreases to slightly below 1 µm, since visible light is used 13 , 23 . Some techniques provide nano-scale analysis, such as nano-FTIR which can achieve a spatial resolution of 20 nm 24 , and nano-Raman imaging which demonstrates a spatial resolution of 100 nm 25 , but these techniques are not suitable for scanning relatively large surface areas, and hence are not considered in this work.…”

Section: Introductionmentioning

confidence: 99%

A microfluidic chip enables fast analysis of water microplastics by optical spectroscopy

Elsayed

Erfan

Sabry

et al. 2021

Sci Rep

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Microplastics contaminating drinking water is a growing issue that has been the focus of a few recent studies, where a major bottleneck is the time-consuming analysis. In this work, a micro-optofluidic platform is proposed for fast quantification of microplastic particles, the identification of their chemical nature and size, especially in the 1–100 µm size range. Micro-reservoirs ahead of micro-filters are designed to accumulate all trapped solid particles in an ultra-compact area, which enables fast imaging and optical spectroscopy to determine the plastic nature and type. Furthermore, passive size sorting is implemented for splitting the particles according to their size range in different reservoirs. Besides, flow cytometry is used as a reference method for retrieving the size distribution of samples, where chemical nature information is lost. The proof of concept of the micro-optofluidic platform is validated using model samples where standard plastic particles of different size and chemical nature are mixed.

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“…For MP, the random sampling is well applicable down to 10 μm [ 10 ]. However, for very small MP and especially nanoplastic [ 11 , 36 , 40 , 46 ], the complete filter cannot be imaged in a practical manner and the total particle number is not accessible; thus, another subsampling method has to be found. Of course, this problem is not restricted to MP analysis or a specific size range, it is rather universal and relevant whenever particles (points) have to be selected from a two-dimensional surface.…”

Section: Introductionmentioning

confidence: 99%

Which particles to select, and if yes, how many?

Schwaferts

Esch

et al. 2021

Anal Bioanal Chem

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Micro- and nanoplastic contamination is becoming a growing concern for environmental protection and food safety. Therefore, analytical techniques need to produce reliable quantification to ensure proper risk assessment. Raman microspectroscopy (RM) offers identification of single particles, but to ensure that the results are reliable, a certain number of particles has to be analyzed. For larger MP, all particles on the Raman filter can be detected, errors can be quantified, and the minimal sample size can be calculated easily by random sampling. In contrast, very small particles might not all be detected, demanding a window-based analysis of the filter. A bootstrap method is presented to provide an error quantification with confidence intervals from the available window data. In this context, different window selection schemes are evaluated and there is a clear recommendation to employ random (rather than systematically placed) window locations with many small rather than few larger windows. Ultimately, these results are united in a proposed RM measurement algorithm that computes confidence intervals on-the-fly during the analysis and, by checking whether given precision requirements are already met, automatically stops if an appropriate number of particles are identified, thus improving efficiency.

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Identification and visualisation of microplastics/nanoplastics by Raman imaging (i): Down to 100 nm

Cited by 201 publications

References 48 publications

Microplastics in Glaciers: First Results from the Vatnajökull Ice Cap

Microplastics in Glaciers: First Results from the Vatnajökull Ice Cap

A microfluidic chip enables fast analysis of water microplastics by optical spectroscopy

Which particles to select, and if yes, how many?

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