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Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis
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Batch analysis of microplastics in water using multi-angle static light scattering and chemometric methods.

Mehrdad Lotfi Choobbari1, Leonardo Ciaccheri2, Tatevik Chalyan3

  • 1Vrije Universiteit Brussel, Department of Applied Physics and Photonics, Brussels Photonics, Pleinlaan 2, 1050 Brussels, Belgium.

Analytical Methods : Advancing Methods and Applications
|September 28, 2022
PubMed
Summary

This study introduces a novel batch analysis method for microplastics (MPs) in water using light scattering and chemometrics. The technique efficiently determines MP size and concentration, overcoming limitations of single-particle analysis.

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Area of Science:

  • Environmental Science
  • Analytical Chemistry
  • Materials Science

Background:

  • Accurate quantification of microplastic (MP) size and concentration in water is crucial for environmental monitoring.
  • Current single-particle analysis methods are time-consuming, limiting high-throughput environmental assessments.
  • Development of rapid, batch-analysis techniques for MPs is needed.

Purpose of the Study:

  • To develop and validate a novel method for simultaneous batch analysis of microplastic size and concentration in water.
  • To leverage multi-angle static light scattering (Goniophotometry) combined with chemometrics for MP analysis.
  • To demonstrate the method's applicability to various microplastic types and size distributions.

Main Methods:

  • Utilized Goniophotometry (multi-angle static light scattering) for batch analysis of microplastics.
  • Employed chemometric techniques, including Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA), for data processing.
  • Investigated polystyrene (PS) microplastics across a size range of 500 nm to 20 μm in monodisperse and polydisperse samples.
  • Validated the method for classifying sizes of PS, Polyethylene (PE), and Polymethylmethacrylate (PMMA) microplastics and quantifying their concentrations.

Main Results:

  • Principal Component Analysis (PCA) effectively correlated scattering data with microplastic size distributions in mixtures.
  • A Linear Discriminant Analysis (LDA) model successfully classified microplastic sizes in both monodisperse and polydisperse samples.
  • Concentration determination was achieved through a simple linear fit after size classification.
  • The Linear Least Square (LLS) model confirmed the reproducibility of the measurements.

Conclusions:

  • Goniophotometry combined with chemometrics offers an efficient alternative to single-particle analysis for microplastic quantification.
  • The developed method accurately determines microplastic size and concentration in batch mode.
  • This approach is applicable to diverse microplastic types and size distributions, enhancing environmental monitoring capabilities.