Optimization of sample preparation, fluorescence- and Raman techniques for environmental microplastics.

Autor: Konings MC; LaserLaB, Vrije Universiteit Amsterdam, the Netherlands. Electronic address: m.c.konings@vu.nl., Zada L; LaserLaB, Vrije Universiteit Amsterdam, the Netherlands., Schmidt RW; LaserLaB, Vrije Universiteit Amsterdam, the Netherlands., Ariese F; LaserLaB, Vrije Universiteit Amsterdam, the Netherlands. Electronic address: f.ariese@vu.nl.
Jazyk: angličtina
Zdroj: Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy [Spectrochim Acta A Mol Biomol Spectrosc] 2024 Oct 15; Vol. 319, pp. 124537. Date of Electronic Publication: 2024 May 26.
DOI: 10.1016/j.saa.2024.124537
Abstrakt: Microspectroscopic imaging techniques based on spontaneous Raman scattering, Stimulated Raman Scattering (SRS), or fluorescence (with a selective dye) can be used to detect environmental microplastics (MPs) and determine their chemical as well as physical properties. The present study first focuses on optimizing the sample preparation, including a new design for a density separation apparatus and optimization of the Nile Red staining procedure. Tests were carried out with both white and colored reference materials, as well as environmental MPs in a suspended matter sample from the Rhine river. The new 'MESSY' system has a mean recovery of 95 ± 5.5 % (three polymer materials, in duplicate). The optimized Nile Red staining allows coarse categorization of MPs into "polar" vs. "non-polar" materials based on their Fluorescence Index (emission wavelength), but fluorescent additives in the polymer can cause misclassification. For unambiguous identification of the polymer type, Raman spectroscopy can be used. Even colored polymers, with or without Nile Red staining, were readily identified by Raman spectroscopy using a red laser (785 nm), except for particles containing carbon black. A Deep-UV Raman microscope (ex = 248.6 nm) was constructed, which allowed identification of all colored plastics, even those pigmented with carbon black. Since unsupervised mapping with spontaneous Raman is very slow, point measurements are preferably used after preselection of particles of interest based on fluorescence imaging. SRS is several orders of magnitude faster than spontaneous Raman mapping but requires multiple scans at different z-heights and at multiple wavenumber settings to detect and identify all particles. The results are expected to contribute to the development of suitable methodologies for the detection and identification of environmental microplastics.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)
Databáze: MEDLINE
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