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Speeding up microplastics analysis with modern NIR spectroscopy

  • Annually vast amounts of plastics are produced world-wide. However, recycling and waste management is still insufficient resulting in large quantities of plastics being released into the environment. Degradation by sunlight, mechanical and biological factors lead to the breakdown of this waste into little fragments. By convention particles smaller than 5 mm are referred to as microplastics (MP). The occurrence of MP has been reported by researchers virtually all around the globe. Gaining knowledge on MP is currently a time-consuming process because analysis mainly relies on micro-infrared and micro-Raman methods. Prior to that the particles need to undergo purification and enrichment. Thus, only small numbers and volumes of samples can be investigated. Here we tested NIR spectroscopy combined with a multivariate data analysis as a means of speeding up the process of MP analysis. Experiments were performed using the most abundant polymers polyethylene, polypropylene, polyethyleneAnnually vast amounts of plastics are produced world-wide. However, recycling and waste management is still insufficient resulting in large quantities of plastics being released into the environment. Degradation by sunlight, mechanical and biological factors lead to the breakdown of this waste into little fragments. By convention particles smaller than 5 mm are referred to as microplastics (MP). The occurrence of MP has been reported by researchers virtually all around the globe. Gaining knowledge on MP is currently a time-consuming process because analysis mainly relies on micro-infrared and micro-Raman methods. Prior to that the particles need to undergo purification and enrichment. Thus, only small numbers and volumes of samples can be investigated. Here we tested NIR spectroscopy combined with a multivariate data analysis as a means of speeding up the process of MP analysis. Experiments were performed using the most abundant polymers polyethylene, polypropylene, polyethylene terephthalate and polystyrene. MP samples were obtained by adding the cryomilled and sieved (<125 µm) particles to approximately 1 g of standard soil at 0,5–10 mass%. Spectra were recorded with a fiber optic reflection probe connected to a FT-NIR spectrometer. 5–10 spectra recorded of each sample were used for the calibration of chemometric models (partial least squares regression, PLSR). “Unknown” test samples were then used to test the model’s capability to predict the type and amount of polymer. In samples containing 1–5 % of the polymers the prediction yielded the highest degree of agreement with the gravimetric reference values. At low polymer loads some false positive results in the identification were observed. Large amounts of polymers limited the prediction capability by a nonlinear behaviour of the absorption. Further testing was done with real world samples such as compost and washing machine filters. Even though the calibration did not account for these highly complex sample compositions, satisfactory results could be achieved.zeige mehrzeige weniger

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Metadaten
Autor*innen:Lukas WanderORCiD
Koautor*innen:Andrea Paul, Roland Becker, Michael Maiwald, Ulrike Braun
Dokumenttyp:Posterpräsentation
Veröffentlichungsform:Präsentation
Sprache:Englisch
Jahr der Erstveröffentlichung:2017
DDC-Klassifikation:Technik, Medizin, angewandte Wissenschaften / Ingenieurwissenschaften / Sanitär- und Kommunaltechnik; Umwelttechnik
Freie Schlagwörter:Mikroplastik
Chemometrics; Microplastics; NIR spectroscopy
Veranstaltung:Adlershofer Forschungsforum
Veranstaltungsort:Berlin, Germany
Beginndatum der Veranstaltung:10.11.2017
Enddatum der Veranstaltung:10.11.2017
Verfügbarkeit des Dokuments:Datei im Netzwerk der BAM verfügbar ("Closed Access")
Datum der Freischaltung:15.11.2017
Referierte Publikation:Nein
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