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Protocol for Microplastics Sampling on the Sea Surface and Sample Analysis
Published on: December 16, 2016
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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
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.
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.
