AI Article Synopsis

  • - The study focuses on analyzing microplastics (MPs) in water by measuring their size and concentration, using a method called "Goniophotometry," which pairs multi-angle light scattering with advanced data processing techniques.
  • - It investigates polystyrene MPs of various sizes (500 nm to 20 μm) in both uniform and non-uniform distributions, revealing how Principal Component Analysis (PCA) can identify relationships in scattering data for different size distributions.
  • - The research develops a Linear Discriminant Analysis (LDA) model to classify the size of MPs in different samples and applies a simple linear fit to determine their concentration, ensuring reliable and reproducible measurements through a Linear Least Square (LLS) model

Article Abstract

Size and concentration are two important parameters for the analysis of microplastics (MPs) in water. The analytical tools reported so far extract this information in a single-particle analysis mode, dramatically increasing the analysis time. Here, we present a combination of multi-angle static light scattering technique, called "Goniophotometry", with chemometric multivariate data processing for the batch analysis of size and concentration of MPs in water. Nine different sizes of polystyrene (PS) MPs with diameters between 500 nm and 20 μm are investigated in two different scenarios with uniform (monodisperse) and non-uniform (polydisperse) size distribution of MPs, respectively. It is shown that Principal Component Analysis (PCA) can reveal the existing relationship between the scattering data of mono- and polydisperse samples according to the size distribution of MPs in mixtures. Therefore, a Linear Discriminant Analysis (LDA) model is constructed based on the PCA of scattering data of PS monodisperse samples and is subsequently employed to classify the size of MPs not only in unknown mono- and polydisperse PS samples, but also for other types of MPs such as Polyethylene (PE) and Polymethylmethacrylate (PMMA). When the size of MPs is classified, their concentration is measured using a simple linear fit. Finally, a Linear Least Square (LLS) model is used to evaluate the reproducibility of the measurements.

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Source
http://dx.doi.org/10.1039/d2ay01215dDOI Listing

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