The identification of microplastics based on vibrational spectroscopy data – A critical review of data analysis routines

Jana Weisser, Teresa Pohl, Michael Heinzinger, Natalia P. Ivleva, Thomas Hofmann, Karl Glas

Research output: Contribution to journalReview articlepeer-review

13 Scopus citations

Abstract

With worldwide aims to monitor microplastics (MP) in the environment, food and drinking water, there is a growing need for fast, reliable and high-throughput analysis methods. While on the instrumental side, spectroscopic techniques are used widely as they proved suitable for identifying even micron-range plastic particles, there is a gap to fill on the data analysis side. Vibrational spectra of MP are highly complex, and often, large data sets need to be evaluated. Methods range from classical library search to complex artificial intelligence models, each of which has its strengths and weaknesses. This critical review discusses the accuracy, robustness and expenditure of data analysis routines proposed for identification of MP using vibrational spectra. Programs provided by the scientific community dedicated to MP analysis are introduced. Thereby, this review aims to provide guidance for everyone who wants to set up or enhance a data analysis routine for vibrational spectra of MP.

Original languageEnglish
Article number116535
JournalTrAC - Trends in Analytical Chemistry
Volume148
DOIs
StatePublished - Mar 2022

Keywords

  • Chemometrics
  • Database
  • Fourier-transform Infrared spectroscopy
  • Hyperspectral imaging
  • Library
  • Machine learning
  • Microplastics
  • Raman spectroscopy

Fingerprint

Dive into the research topics of 'The identification of microplastics based on vibrational spectroscopy data – A critical review of data analysis routines'. Together they form a unique fingerprint.

Cite this