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Using an Automatic Preparation System to Collect 100 μm Microplastics from Environmental Surface Waters

Technical notes | 2025 | ShimadzuInstrumentation
Sample Preparation
Industries
Environmental
Manufacturer
Shimadzu

Summary

Significance of the Topic


The growing presence of microplastics in environmental waters poses significant ecological and health concerns. Reliable detection and quantification of these particles are critical for understanding their distribution, assessing risks, and informing regulatory policies. Standardizing sample preparation enhances comparability across studies and reduces variability introduced by manual operations.

Objectives and Study Overview


This work aimed to extend the capabilities of Shimadzu’s MAP-100 automatic preparation system to reliably collect microplastic particles down to 100 µm. By redesigning key components and optimizing workflow parameters, the study sought to improve reproducibility and facilitate analysis of smaller microplastic fractions often overlooked in routine surveys.

Methodology and Instrumentation


The MAP-100 process flow comprises four main stages:
  • Decomposition: Organic matter is oxidized using 30 % hydrogen peroxide at 60 °C with continuous stirring to remove biogenic material.
  • Density Separation: Aqueous sodium iodide solution (specific gravity 1.6) is introduced to float microplastics while denser residues settle.
  • Overflow: Supernatant containing buoyant particles is directed into a glass collection vessel through repeated overflow cycles.
  • Particle Collection: The collected solution is filtered sequentially through a 90 µm stainless steel sieve and a 5 µm PTFE membrane to isolate microplastics for analysis.

Two field cases from Okinawan seawater were processed: one after a typhoon event requiring three days of digestion, and another with lower organic load requiring only 20 hours. Extracted particles were characterized by FTIR and Raman microscopy.

Used Instrumentation


  • MAP-100 automatic microplastic preparation system (configured with 100 µm strainer)
  • Infrared microscope (IRXross) with AIMsight analysis software
  • Raman microscope for polymer identification
  • 90 µm stainless steel sieve and 25 mm PTFE filter (5 µm pore size)
  • Reagent supply: Hydrogen peroxide (30 %) and aqueous sodium iodide solution (SG 1.6)

Main Results and Discussion


The modified MAP-100 system successfully collected and isolated microplastic particles down to 100 µm. FTIR and Raman analyses confirmed the presence of polypropylene and polyethylene fragments measuring approximately 240 µm by 120 µm. Reducing the strainer aperture size and optimizing overflow handling enabled finer particle recovery without compromising sample throughput. Variations in digestion time underscored the need to adjust parameters based on organic content to prevent filter clogging and ensure consistent yields.

Benefits and Practical Applications


The automated workflow offers:
  • Enhanced reproducibility by removing operator-dependent steps
  • Capability to capture smaller microplastics previously overlooked
  • Time savings through standardized digestion and separation protocols
  • Compatibility with downstream spectroscopic identification methods

Such improvements support environmental monitoring, risk assessment, and regulatory compliance efforts.

Future Trends and Opportunities


Further advancements may include integration of inline sensors for real-time particle detection, adaptation to soil and air matrices, and development of automated filter-exchange modules. Extending capabilities to sub-100 µm fragments and coupling with high-throughput imaging systems will enhance understanding of microplastic pathways and human exposure.

Conclusion


By refining key components and processes, Shimadzu’s MAP-100 system now standardizes the isolation of microplastics as small as 100 µm. This technological enhancement fosters greater analytical consistency, broadens the range of detectable particle sizes, and supports robust environmental assessments.

Content was automatically generated from an orignal PDF document using AI and may contain inaccuracies.

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