Identification of microplastics with Raman microscopy

Significance of the Topic

The accumulation of microplastics in aquatic ecosystems poses significant environmental and health risks. Understanding the chemical composition of particles smaller than 5 mm is essential to trace their sources, assess their biological impacts and inform mitigation strategies. Raman microscopy offers a fast and non-destructive approach to polymer identification, especially for particles under 100 μm, overcoming limitations of other spectroscopic methods.

Objectives and Study Overview

This study demonstrates the use of a portable 1064 nm Raman microscope to rapidly identify microplastic particles recovered from surface waters of an estuary. Key goals include:

• Isolate and categorize environmental microplastic samples
• Evaluate the effectiveness of 1064 nm excitation in reducing fluorescence
• Match unknown spectra to polymer reference libraries using correlation algorithms

Methodology and Instrumentation

Surface water was collected from the Delaware Bay and fixed with 4 % formaldehyde. Samples were sieved into size fractions (5000, 1000 and 300 μm), dried, then subjected to wet peroxide oxidation and density separation to remove organic matter. Microplastics were captured on 200 μm nitex mesh, imaged under a stereomicroscope and morphologically classified by type (fragment, fiber, bead, film, foam, rubber).

• Portable Raman spectrometer: i-Raman EX with 1064 nm CleanLaze laser (max 165 mW) to suppress fluorescence
• Video microscope: BAC151C, 50× objective (9.15 mm working distance, 42 μm spot size)
• Acquisition: integration times 30 s to 3 min, laser power below 50 % to prevent burning
• Data analysis: BWID software comparing first-derivative spectra against custom and commercial polymer libraries, reporting a hit quality index (HQI) from 0 to 100

Results and Discussion

Secondary microplastics such as irregular blue fragments (~4.5 mm) yielded clear polyethylene spectra with HQI of 95.7. Primary particles included polystyrene beads matched at HQI 98.2. Colored fibers produced polypropylene matches (HQI 74.9) alongside additional peaks attributable to chlorinated copper phthalocyanine green pigment, illustrating the method’s ability to detect both base polymer and additives. A summary of 22 analyzed samples showed:

• Polyethylene: 11 samples
• Polypropylene: 4 samples
• Polystyrene: 2 samples
• Inconclusive (often black particles): 5 samples

Challenges include spectral interference from pigments and risk of thermal alteration at high laser powers. Using 1064 nm excitation and low power settings mitigates these issues.

Benefits and Practical Applications

Portable Raman microscopy enables on-site analysis of microplastics, rapid differentiation of polymer types and detection of colorants or contaminants. This capability supports environmental monitoring, source attribution studies and routine quality control in laboratories and field deployments.

Future Trends and Potential Applications

Emerging developments may include:

• Integration of automated particle recognition and mapping workflows
• Expansion of spectral libraries to cover emerging polymer blends and additives
• Combination with complementary techniques (e.g., hyperspectral imaging, FTIR) for multimodal identification
• Machine learning algorithms for improved classification accuracy and speed
• Portable devices for real-time, in situ surveys of remote or challenging environments

Conclusion

Raman microscopy with 1064 nm excitation provides a robust approach for rapid, non-destructive identification of microplastic particles in environmental samples. The method’s portability, low fluorescence background and reliable software matching make it a valuable tool for research and monitoring efforts addressing microplastic pollution.

Reference

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