Identification of Microplastics with Portable Raman Microscopy

Significance of the topic

The pervasive presence of microplastics in marine and coastal ecosystems has become a major environmental concern. Defined as plastic fragments smaller than 5 mm, microplastics originate from both manufactured products (primary microplastics) and the breakdown of larger plastic debris (secondary microplastics). Their small size and widespread distribution pose risks to aquatic life, food webs, and human health. Reliable identification of polymer type is essential for tracing pollution sources, understanding environmental fate, and informing mitigation strategies.

Study objectives and overview

This application note examines the use of a portable Raman microscopy system for in-field identification of microplastics collected from estuarine surface waters. Key goals include:

• Demonstrating rapid, non-destructive polymer identification using near-infrared Raman excitation.
• Comparing observed spectra against a reference library to confirm material composition.
• Evaluating challenges such as fluorescence, sample fragility, and limitations with certain particle types.

Methodology and instrumentation

Surface water samples were obtained from Delaware Bay using a 1 m diameter plankton tow net with 200 μm mesh. Samples were preserved in 4% formaldehyde, size-fractionated through stainless steel sieves (5,000, 1,000, and 300 μm), and digested via wet peroxide oxidation and density separation. Microplastics were collected on 200 μm mesh, dried, and manually categorized under a stereomicroscope. For polymer identification, an i-Raman® EX portable Raman spectrometer with 1064 nm laser excitation was employed to minimize fluorescence. A video microscope setup (50× objective, 42 μm spot size) facilitated sample alignment. Spectra were acquired with integration times of 30 s to 3 min, laser power below 165 mW, and intensity-corrected against a NIST standard. Polymer matches were determined using BWID® software and a reference spectrum library.

Instrumentation used

• i-Raman EX portable Raman system, 1064 nm excitation, InGaAs detector.
• Video microscope sampling stage with coaxial LED illuminator, 50× objective.
• BWSpec® for data acquisition and BWID® for spectral matching.

Main results and discussion

Analysis of various microplastic particles yielded clear Raman spectra for polyethylene (PE), polypropylene (PP), and polystyrene (PS). Example findings include:

• A 4.5 mm blue fragment identified as PE (hit quality index, HQI = 95.7).
• A small spherical bead confirmed as PS (HQI = 98.2), indicative of primary microplastics.
• A teal fiber matched to PP (HQI = 74.9), with additional spectral features corresponding to chlorinated copper phthalocyanine pigment used as a colorant.

Challenges encountered: black particles exhibited strong absorption and yielded inconclusive Raman signals; high laser power risked thermal damage to fragile microfibers.

Benefits and practical applications

Portable Raman microscopy allows on-site, non-destructive confirmation of microplastic types, reducing misclassification associated with visual inspection alone. The approach supports rapid screening in field laboratories, aids in source tracing through polymer and additive identification, and enhances quality control in environmental monitoring programs.

Future trends and potential applications

Advances in portable spectrometer sensitivity, expanded reference libraries, and automated spectral matching algorithms will further streamline microplastic analysis. Integration with hyperspectral imaging and machine learning may enable high-throughput identification and quantification of microplastics in complex matrices. Real-time data sharing could facilitate large-scale monitoring networks and citizen science initiatives.

Conclusion

Portable Raman microscopy with near-infrared excitation offers a robust, field-deployable solution for accurate microplastic identification. By mitigating fluorescence and leveraging spectral libraries, researchers can rapidly confirm polymer types and gain insights into particle origins and additive content. Ongoing improvements in instrumentation and data analytics will expand the utility of this technique for environmental research and pollution management.

References

1. Law KL, et al. Annual Review of Marine Science 9:205-229 (2017).
2. Galloway TS, Cole M, Lewis C. Nature Ecology & Evolution 1 (2017).
3. Jambeck JR, Geyer R, Wilcox C, et al. Science 347:768-771 (2015).
4. Hale RC, Seeley ME, La Guardia MJ, Mai L, Zeng EY. Journal of Geophysical Research: Oceans 125 (2020).
5. Clark JR, Cole M, Lindeque PK, et al. Frontiers in Ecology and the Environment 14:317-324 (2016).
6. Vermeiren P, Munoz CC, Ikejima K. Marine Pollution Bulletin 113:7-16 (2016).
7. Cohen JH, Internicola AM, Mason RA, Kukulka T. Environmental Science & Technology 53:14204-14211 (2019).
8. Masura J, Baker J, Foster G, Arthur C. NOAA Technical Memorandum NOS-OR&R-48 (2015).
9. Duran A, Franquelo ML, Centeno MA, Espejo T, Perez-Rodriguez JL. Journal of Raman Spectroscopy 42:48-55 (2011).