Microplastic Characterization by Infrared Spectroscopy

Abstract

A realistic risk assessment of microplastic pollution must stand on representative data on the abundance, size distribution, and chemical composition of polymers. Infrared spectroscopy is an indispensable tool for the analysis of microplastics (<5 mm). Spectral imaging, which provides simultaneous measurement of spatial (e.g., particle morphology) and spectroscopic information, is a promising approach toward automated microplastic analysis. This chapter aims at providing guidelines to assist with the analysis of spectral imaging data and summarizing the limitations and analytical challenges from a technical point of view. Topics, like automated particle selection for faster infrared mapping, spectral pre-processing to enhance signal quality, multivariate exploratory analysis, comprehensive reference spectral libraries, spectral matching approaches, and modelbased classification, will be exposed and some possible strategies and solutions given and discussed.We will demonstrate how to identify microplastic species by using Fourier transform infrared spectroscopy data in a stepwise manner, with detailed MATLAB command line scripts freely available to be downloaded. The reader is guided through every step and oriented in order to adapt those strategies to the user’s individual case.