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Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis
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Shapes of Hyperspectral Imaged Microplastics.

Fan Liu1, Lasse A Rasmussen1, Nanna D R Klemmensen1

  • 1Department of the Built Environment, Aalborg University, 9220 Aalborg Ø, Denmark.

Environmental Science & Technology
|August 10, 2023
PubMed
Summary

Standardizing microplastic shape classification is crucial for comparable research. This study proposes and validates a clear set of shape categories for hyperspectral imaging analysis.

Keywords:
ground truthhyperspectral imagemanual classificationmicroplasticpixelizationshape

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Area of Science:

  • Environmental Science
  • Analytical Chemistry
  • Materials Science

Background:

  • Microplastic shape is critical for understanding their environmental fate and impact.
  • Current shape definitions for hyperspectral imaging are ambiguous, hindering data comparability.
  • A standardized classification system is needed for microplastic research.

Purpose of the Study:

  • To propose and validate a clear, concise set of microplastic shape categories for hyperspectral imaging.
  • To assess the distinguishability and representativeness of these categories across diverse environmental matrices.
  • To promote harmonization and reproducibility in microplastic research.

Main Methods:

  • An expert-based survey was conducted to define microplastic shapes.
  • Five experts validated proposed categories (fiber, rod, ellipse, oval, sphere, quadrilateral, triangle, free-form, unidentifiable) on 11,042 microplastic images.
  • Images were sourced from indoor air, wastewater, marine water, and stormwater samples.

Main Results:

  • Proposed shapes were found to be well-defined, representative, and visually distinguishable, particularly fiber and sphere.
  • Ellipse, oval, and rod shapes were less distinguishable but prevalent in water and solid matrices.
  • Smaller microplastics (<30 μm) in indoor air frequently appeared as unidentifiable shapes.

Conclusions:

  • The proposed shape categories enhance the clarity and consistency of microplastic analysis.
  • Assessing category recognizability is vital before data reporting to ensure comparability.
  • Standardized shape definitions are essential for advancing microplastic research and policy.