Identification of microplastics in wastewater after cascade filtration using Pyrolysis-GC–MS

[Display omitted] The combination of a representative microplastic sampling method and a fast-quantitative analysis using Pyrolysis-GC–MS (Py-GC–MS) for investigation of the microplastic load and mass balances is presented in this work. A representative microplastic filtration requires a method allo...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:MethodsX 2020-01, Vol.7, p.100778-100778, Article 100778
Hauptverfasser: Funck, Matin, Yildirim, Aylin, Nickel, Carmen, Schram, Jürgen, Schmidt, Torsten C., Tuerk, Jochen
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:[Display omitted] The combination of a representative microplastic sampling method and a fast-quantitative analysis using Pyrolysis-GC–MS (Py-GC–MS) for investigation of the microplastic load and mass balances is presented in this work. A representative microplastic filtration requires a method allowing quick extraction of the sample. The developed steel based cascadic microplastic filtration uses steel basket filters with mesh sizes of 100 μm, 50 μm and 10 μm and a mean recovery of 86 % without cross contamination was achieved. Thermoanalytical methods have the advantage of minimal sample preparation with short analysis times. The presented platinum filament-based Py-GC–MS method requires little sample preparation and quantification limits for polystyrene (PS) and polyethylene (PE) were 0.03 μg and 1 μg absolute, respectively. The relative standard deviation of the analytical method is 11 %. The combined method allows representative sampling and analysis of MP from water bodies and waste water treatment plants within 48 h. •Presentation of a validated steel based cascadic microplastic filtration plant.•Fast and reproduceable Py-GC–MS analysis method for microplastic.•Py-GC–MS allows microplastic analysis with little sample preparation.
ISSN:2215-0161
2215-0161
DOI:10.1016/j.mex.2019.100778