Analytical Solutions for Microplastics

Significance of the topic

Microplastics (particles <5 mm) are an emerging environmental and public-health concern because they persist, fragment, and travel through aquatic systems and food webs. Microplastics may cause physical harm to organisms, and they can carry intrinsic additives (plasticizers, flame retardants, fillers) and sorbed contaminants (PCBs, PAHs, PFAS) that can bioaccumulate. Reliable, reproducible methods for sampling, pretreatment, identification and quantification across a wide size range (≈1 µm–10 mm) are critical for monitoring, risk assessment, remediation, and circular-economy initiatives. Standardization efforts (ISO, ASTM, national guidelines) and instrument workflows that combine automation, imaging and molecular/elemental analysis are central to producing comparable, high-quality data.

Objectives and study overview

This whitepaper outlines Shimadzu’s integrated analytical solutions for microplastics: automated sample pretreatment, nondestructive spectroscopic identification (FTIR, infrared microscopy, Raman), high-throughput imaging (dynamic particle image analysis), destructive mass-based identification and quantification (pyrolysis-GC-MS), elemental screening (XRF/EDX), thermal analysis (DSC) and targeted chemical analysis (GC-MS/MS, LC-MS/MS) for sorbed contaminants. The material demonstrates workflows for environmental water, filter-based measurements, biota-derived particles, roadside debris, and blended plastics — emphasizing reproducibility, throughput, and methods that address degraded plastics.

Methodology and workflow

The general workflow described comprises three main steps: sampling, automated pretreatment, and measurement/analysis.

• Sampling strategies: neuston nets for surface ocean, bridge or grab sampling for rivers; filters for laboratory concentration.
• Automated pretreatment: MAP-100 automates digestion (H2O2 oxidation), density separation (NaI solution), sieving and filtration to isolate particles ~0.3–5 mm (limitations for heavy sediment loads noted).
• Measurement selection: nondestructive FTIR (benchtop IRSpirit-X, IRTracer) and infrared microscopy (AIMsight) for component ID; infrared/Raman microscopes (AIRsight) for particles down to a few µm; particle imaging (iSpect DIA-10) for counts, size distribution and shape (5–100 µm) per ASTM D8489; Py-GC-MS (EGA/PY pyrolyzer + GCMS) with F-Search MPs software for mass-based identification/quantitation of mixed particles; EDX/XRF for elemental analysis (e.g., Cu coatings); DSC for blend ratio estimation; GC-MS/MS and LC-MS/MS for quantifying adsorbed PAHs and PFAS, respectively.

Used instrumentation

• MAP-100 Microplastic Automatic Preparation Device (automated digestion, density separation, filtration)
• IRSpirit-X / IRSpirit-TX / IRTracer-100 Fourier Transform Infrared Spectrophotometers (with QATR-S ATR)
• AIMsight / AIRsight infrared and infrared/Raman microscopes (wide-field camera, 15× reflective objective; micro-ATR and transmission options)
• PF (Particle Filter) holders and high-speed mapping & particle-analysis software for infrared microscopy
• iSpect DIA-10 Dynamic Particle Image Analysis System (5–100 µm imaging, ASTM D8489 workflow)
• Pyrolysis systems (EGA/PY-3030D, Multi-Shot pyrolyzer) coupled to GCMS-QP2020 NX or GCMS-QP2020/2050 series and F-Search MPs 2.0 software
• Cryogenic mill (IQ MILL-2070) for homogenizing MPs prior to Py-GC-MS
• EDX-8000 / EDX-8100 energy-dispersive X-ray fluorescence spectrometers for elemental screening
• GC-MS/MS (GCMS-TQ8040 RX) and LC-MS/MS (LCMS-8060RX) for PAHs and PFAS analysis
• Differential Scanning Calorimeter (DSC-60 Plus Series) for melt-peak based compositional analysis

Main results and discussion

• MAP-100 automated pretreatment significantly reduces analyst labor, decreases variability between operators, and improves safety by minimizing manual handling of reagents (H2O2, NaI). The device efficiently removes organic and inorganic contaminants for particles sized ~0.3–5 mm; very sediment-rich samples remain challenging due to clogging.
• IRSpirit / Plastic Analyzer combined with a UV-Damaged Plastics Library improved identification of UV- or heat-degraded plastics. Example matches: PP (25 h UV) and PE (550 h UV) with high match scores (e.g., 876–904 points) after MAP-100 pretreatment.
• High-speed mapping on infrared microscopes reduced measurement time considerably (example cited approx. 1/8 of conventional mapping time) and, together with particle-analysis software, enabled automated counting, type assignment (PE, PP, PS, PET), size metrics (minor/major axes, Feret diameter, area), and estimated volume/mass (using an empirical geometric formula). These tools allow rapid screening of filter-collected MPs <100 µm.
• Particle Filter (PF) holders enable flat, wrinkle-free mounting of diverse filter types (PTFE, Al2O3, Au-coated PC, stainless steel), improving image quality and spectral acquisition. Filter material choice affects spectral windows (e.g., PTFE absorption near 1,200 cm−1, Al2O3 absorption 1,200–700 cm−1) and must be matched to target polymer chemistry.
• AIRsight infrared/Raman microscopy enabled combined IR and Raman measurements on the same stage; Raman extended identification down to ≈5 µm particles (examples: PE and PS identified by Raman, PP identified by IR). Length-measurement tools provided size context for compositional ID.
• iSpect DIA-10 particle imaging provides rapid concentration and shape metrics for 5–100 µm particles in compliance with ASTM D8489; synthetic mixtures showed expected size distributions and morphological variability from shredding.
• Py-GC-MS with calibrated MPs standard (12-plastic mix) and F-Search MPs enabled simultaneous identification and quantitation of multiple polymer types in complex roadside debris. Calibration curves were linear (R2 ≥0.995). Roadside debris typically contained PE (largest share), SBR (tire-derived), PMMA, PET, PS, etc.
• A combined river-water workflow (MAP-100 → FTIR → cryo-mill → Py-GC-MS) yielded complementary outcomes: FTIR provided number-based identification (dominant PP, PE, EVA in the analyzed sample set), while Py-GC-MS produced mass-based quantitation, revealing differences between number (%) and mass (%) distributions (e.g., PE/PP dominating mass fraction while counts reflect many small particles of other types).
• DSC melt-peak analysis can estimate component ratios in polymer blends. When melting peaks are well separated (e.g., LDPE vs PP), direct heat-of-fusion methods yield accurate ratios. For overlapping peaks (e.g., HDPE vs PP) partial-area approximation or total heat-of-fusion calibration curves can give approximate blend ratios, with reduced accuracy where peaks overlap substantially.
• Elemental screening of collected fishing nets by FTIR+ATR and EDX allowed polymer identification and detection of copper protective coatings: Cu content ranged from <0.03 wt% (beach-collected items) to ~8–15 wt% in some recycling-plant nets, indicating coated nets that raise ecological concerns.
• Adsorption tests of PAHs and PFAS onto PP, PE, PS showed that PAHs adsorbed preferentially to PP and PE in the tested conditions, while PFAS adsorption patterns were compound-specific. Analytical workflows using solvent extraction followed by GC-MS/MS (PAHs) and LC-MS/MS (PFAS) provide quantitative adsorption metrics useful for fate and exposure modelling.

Benefits and practical applications

• Standardized, automated pretreatment (MAP-100) improves throughput, reproducibility and safety for environmental surveys and regulatory monitoring.
• Combining imaging (iSpect DIA-10), nondestructive spectroscopic ID (FTIR, IR microscopy, Raman) and mass-based pyrolysis quantitation (Py-GC-MS) delivers complementary datasets: particle counts and morphology, polymer ID of individual particles, and accurate mass-based composition of mixed samples.
• High-speed mapping and PF holders enable practical, routine analysis of filter-collected MPs down to <100 µm for regional monitoring programs.
• Elemental (XRF/EDX) and thermal (DSC) techniques expand characterization to additives, coatings and blend composition—valuable for recycling, source identification, and impact assessment.
• Targeted GC-MS/MS and LC-MS/MS analyses allow quantification of hazardous sorbed chemicals (PAHs, PFAS) to inform risk assessments and remediation priorities.

Future trends and opportunities

• Method standardization: Continued development of harmonized sampling, preparation and analysis standards (ISO, ASTM WK87463 and related efforts) will improve data comparability and regulatory uptake.
• Lower-size detection: Improving sensitivity and spatial resolution to routinely analyze sub-10 µm particles will be critical as awareness of smaller-size MPs increases.
• Degraded-plastic libraries and spectral databases: Expanding spectral libraries (UV/heat-damaged spectra) will enhance identification of environmentally weathered plastics.
• Integrated automated workflows: Greater automation from sampling through data processing (robotic preparation, automated spectral matching, AI-assisted particle classification) will scale monitoring programs and reduce analyst bias.
• Mass-based quantitation and representative standards: Development of robust reference materials and mass-based calibration strategies will improve mass-fraction reporting and interlaboratory comparability (noting current differences between particle-count and mass-based results).
• Multi-modal analytics: Coupling imaging, spectroscopy and targeted mass spectrometry (including spatially resolved mass spec) will improve source attribution, additive and contaminant mapping, and lifecycle assessments for recycling applications.
• Toxicant–MP interaction studies: Systematic adsorption/desorption datasets (PAHs, PFAS, heavy metals) across polymer types, sizes and environmental conditions will refine exposure and bioaccumulation models.

Conclusion

Shimadzu’s suite of instruments and workflows demonstrates a pragmatic, multi-technique approach to microplastics analysis that balances throughput, sensitivity and specificity. Automated sample preparation (MAP-100), advanced infrared and Raman microscopy (AIMsight/AIRsight), high-speed mapping and particle analysis, dynamic particle imaging (iSpect DIA-10) and Py-GC-MS with dedicated libraries together address many analytical challenges: recovery and reproducibility, identification of degraded polymers, particle counting and morphology, and mass-based quantitation of polymer types. Complementary elemental and targeted chemical analyses expand the ability to assess ecological risk and recycling potential. Continued standardization, expanded degraded-plastics databases, lower-size-limit analytics, and end-to-end automation are key near-term directions to increase the reliability and usability of microplastics data for policy, remediation and research.

References

• Shimadzu Whitepaper: Analytical Solutions for Microplastics (C10G-E083B), First Edition June 2020; updated content to 2026.
• Tomoya Kataoka, Yota Iga, Rifqi Ahmad Baihaqi, et al. Geometric relationship between the projected surface area and mass of a plastic particle. Water Research. 2024;261:122061.
• ASTM D8489, Test Method for Determination of Microplastics Particle and Fiber Size, Distribution, Shape, and Concentration in Waters with High to Low Suspended Solids Using a Dynamic Image Particle Size and Shape Analyzer (2023).
• ASTM WK87463, New Test Method for Spectroscopic Identification and Quantification of Microplastic Particles in Water Using Infrared (IR) Spectroscopy (in development).
• ASTM D8402 and D8333 standard practices referenced for sample preparation of microplastic reference materials.
• Kühn S., Jamieson A., Keighley R., et al. Micro FTIR analysis of smallest particles from deep sea to polar ice; SHIMADZU NEWS (2018) summary of microplastics findings in polar regions.
• Yasojima M., Mizuka H., Mine T., et al. Adsorption Characteristics of Chemical Substances on Microplastics; Proceedings of conferences (Japan) on adsorption of PAHs and PFAS to microplastics (2019).
• Selected analytical system manuals and product literature: IRSpirit-X series, IRTracer series, AIMsight/AIRsight, MAP-100, iSpect DIA-10, EGA/PY pyrolyzers, GCMS-QP series, EDX-8000/8100, DSC-60 Plus, IQ MILL-2070.