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Quantifying Microplastics in Complex Environmental Samples: Py-Gc/Ms vs. Hyperspectral Ftir – Potential and Limitations

30th International Meeting on Organic Geochemistry (IMOG 2021) 2021 2 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Sebastian Primpke, Marten Fischer, Claudia Lorenz, Gunnar Gerdts, B. Scholz-Boettcher

Summary

Researchers compared two analytical methods — pyrolysis gas chromatography-mass spectrometry and hyperspectral FTIR imaging — for quantifying microplastics in complex environmental samples. The study found both approaches have complementary strengths, with one providing particle counts and the other polymer masses, and that translating between the two metrics is challenging.

Study Type Environmental

Summary In a proof of principle, FTIR and PY-GC/MS are applied subsequently on identical filter for microplastics identification and quantification. Both approaches are of complementary scientific value since they result in particle numbers and sizes or polymer masses, respectively. Although the combined use of both methods is ideal, the transferability of particle related data, by far more referred in literature, into masses is an often-asked question. The filter represented different complex environmental samples (waters from wastewater treatment plants, North Sea sediments and water) prior treated for selective MP pre-concentration. Associated with data evaluation, a general harmonization step regarding distinct polymer clusters of both methods was performed. A comprehensive data comparison revealed that FTIR and Py-GC/MS resulted in polymer types and qualitative distribution. This is attributed mainly to the size-influenced detection of both methods resulting in deviant quantitative calculations. The determined polymer mass is increasing with particle size. Consequently, the impact of few big particles is high regarding relative calculations for Py-GC/MS. In contrast, an inverse effect occurs in FTIR since particle counts ascend with decreasing particle size. Any calculative might lead to overestimation. A complementary use of both methods is highly recommended for reliable data generation.

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