High-Speed Measurement of Microplastics Smaller than 100 μm Collected on a Filter and Efficient Analysis

Importance of the Topic

Microplastics smaller than 100 µm are increasingly detected in drinking water and raise concerns about environmental and human health. Reliable methods to quantify, characterize and identify these particles at high throughput are essential for environmental monitoring, regulatory compliance and research into microplastic pollution pathways.

Objectives and Study Overview

This study demonstrates a workflow combining a Fourier transform infrared (FT-IR) microscope with a high-speed mapping program and a particle analysis software to accelerate detection and characterization of microplastics collected on a filter. The main goals are to reduce measurement time, automate polymer type identification, extract size metrics, and estimate particle volume and mass.

Methodology and Instrumentation

Samples of standard microplastics (polyethylene, polyethylene terephthalate, polystyrene, and protein) were dispersed in purified water and deposited onto a 10 mm × 10 mm silicon filter with 5 µm pores. The filter was mounted in a dedicated holder to flatten wrinkles and placed under the FT-IR microscope system.

• Instruments: IRTracer-100 FT-IR spectrometer, AIMsight infrared microscope, PF sample holder
• Software: High-Speed mapping program, Particle analysis program
• Optical setup: Transmission mode, resolution 8 cm⁻¹, apodization SqrTriangle
• Acquisition: 30 scans per confirmed peak, 20 µm × 20 µm aperture and step size
• Mapping area: 1.7 mm × 2.1 mm
• Detector: T2SL; peak detection in the 3 200–2 800 cm⁻¹ range; noise level 0.02; threshold 0.4; excluded ranges 4 000–3 200 and 2 800–700 cm⁻¹

Main Results and Discussion

The high-speed mapping program selectively measured only points where hydrocarbon peaks were detected, cutting the mapping time to approximately one-eighth of a full-area scan. Subsequent particle analysis automatically identified and color-coded polymer types, yielding:

• 1 polyethylene particle
• 1 polyethylene terephthalate particle
• 7 polystyrene particles

Size distributions were extracted (minor/major axes, Feret diameter, area) and histograms showed PS fragments ranging up to 400 µm in major axis. Enlarged images confirmed clusters of small PS fragments around larger particles. Volume and mass estimates were calculated using a log-linear relation between projected area and mass specific to microplastics.

Benefits and Practical Applications

The combined high-speed mapping and particle analysis workflow offers:

• Rapid screening of filters for microplastics under 100 µm
• Automated polymer identification and color-coded imaging
• Quantitative size, volume and mass data for individual particles
• Exportable summary tables and histograms for reporting and compliance

Future Trends and Potential Applications

Further developments may integrate machine learning for improved polymer classification, expand to Raman mapping for non-infrared-active materials, and couple with liquid chromatography for chemical leaching studies. Miniaturized, field-deployable IR microscopes could enable on-site monitoring of water and soil microplastics.

Conclusion

The presented approach significantly reduces analysis time for microplastics under 100 µm, while delivering reliable polymer identification and comprehensive particle metrics. This workflow supports high-throughput environmental monitoring and research, aiding efforts to assess microplastic pollution.

References

1. Tomoya Kataoka, Yota Iga, Rifqi Ahmad Baihaqi et al. The geometric relationship between the projected surface area and the mass of a plastic particle. Water Research. 2024;61:122061.
2. Ministry of the Environment. River and Lake Microplastics Investigative Guidelines. Water Environment Management Division, Environmental Management Bureau. March 2024.