Authors Käppler, A. ; Fischer, M. ; Scholz-Böttcher, B. ; Oberbeckmann, S. ; Labrenz, M. ; Fischer, D. ; Eichhorn, K.-J. ; Voit, B.
Title Comparison of µ-ATR-FTIR spectroscopy and py-GCMS as identification tools for microplastic particles and fibers isolated from river sediments
Date 01.08.2018
Number 55504
Abstract In recent years, many studies on the analysis of microplastics (MP) in environmental samples have been published. These studies are hardly comparable due to different sampling, sample preparation, as well as identification and quantification techniques. Here, MP identification is one of the crucial pitfalls. Visual identification approaches using morphological criteria alone often lead to significant errors, being especially true for MP fibers. Reliable, chemical structure-based identification methods are indispensable. In this context, the frequently used vibrational spectroscopic techniques but also thermoanalytical methods are established. However, no critical comparison of these fundamentally different approaches has ever been carried out with regard to analyzing MP in environmental samples. In this blind study, we investigated 27 single MP particles and fibers of unknown material isolated from river sediments. Successively micro-attenuated total reflection Fourier transform infrared spectroscopy (µ-ATR-FTIR) and pyrolysis gas chromatography-mass spectrometry (py-GCMS) in combination with thermochemolysis were applied. Both methods differentiated between plastic vs. non-plastic in the same way in 26 cases, with 19 particles and fibers (22 after re-evaluation) identified as the same polymer type. To illustrate the different approaches and emphasize the complementarity of their information content, we exemplarily provide a detailed comparison of four particles and three fibers and a critical discussion of advantages and disadvantages of both methods.
Publisher Analytical and Bioanalytical Chemistry
Citation Analytical and Bioanalytical Chemistry 410 (2018) 5313-5327
Tags microplastics py-gcms atr ftir environmental samples comparison validation

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