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

Area of Science:

• Environmental Science
• Analytical Chemistry
• Materials Science

Background:

• Environmental microplastics (MPs) pose a significant threat, necessitating accurate detection and characterization methods.
• Current microspectroscopic techniques like Raman scattering and fluorescence have limitations in speed and identifying colored MPs.

Purpose of the Study:

• To optimize sample preparation for microplastic analysis.
• To evaluate and improve microspectroscopic techniques for environmental microplastic detection and identification.
• To develop a comprehensive methodology for microplastic analysis in environmental samples.

Main Methods:

• Development of a new density separation apparatus ('MESSY' system) and optimization of Nile Red staining.
• Utilized spontaneous Raman spectroscopy, Stimulated Raman Scattering (SRS), and fluorescence imaging.
• Constructed a Deep-UV Raman microscope for enhanced identification of colored microplastics.

Main Results:

• The 'MESSY' system demonstrated a high recovery rate of 95% ± 5.5%.
• Nile Red staining provided coarse categorization of MPs, though fluorescent additives could cause misclassification.
• Raman spectroscopy, especially with a red laser and Deep-UV microscopy, successfully identified various colored MPs, including those with carbon black.

Conclusions:

• Optimized sample preparation and advanced spectroscopic methods significantly improve microplastic detection and identification.
• Deep-UV Raman microscopy offers a powerful solution for analyzing challenging samples, such as colored microplastics.
• The developed methodologies contribute to more effective environmental microplastic monitoring and research.