Analysis of size and concentration of microplastics in water using static light scattering combined with PCA and LDA

Abstract

Quantitative analysis of size and concentration of microplastics is a crucial step for having a better understanding of plastic pollution in the environment. Such information is typically obtained in a single particle mode that significantly increases the analysis time and can be a cumbersome task. Therefore, we demonstrate here a measurement technique based on Static Light Scattering (SLS) combined with chemometric methods such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) for resolving the size and concentration of multiple microplastic particles in water. Two sets of samples with uniform and non-uniform size distribution of microplastics, called “monodisperse” and “polydisperse”, respectively, are fully investigated. It is shown that a relationship exists between the scattering signals of mono- and polydisperse samples on the PCA space. Hence, a PCA-LDA model that is constructed on the PCA space of monodisperse samples is used to discriminate the size of the microplastics in polydisperse samples. By specifying the size of the particles, their concentration is determined using a simple linear fit.