Regression analysis for the determination of microplastics in sediments using differential scanning calorimetry

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Název: Regression analysis for the determination of microplastics in sediments using differential scanning calorimetry
Autoři: Sven Schirrmeister, Lucas Kurzweg, Xhoen Gjashta, Martin Socher, Andreas Fery, Kathrin Harre
Zdroj: Environ Sci Pollut Res Int
Informace o vydavateli: Springer Science and Business Media LLC, 2024.
Rok vydání: 2024
Témata: Geologic Sediments, Calorimetry, Differential Scanning, Microplastics, 0211 other engineering and technologies, Regression Analysis, Microplastic, Sediment, Polymers, Microplastics/analysis [MeSH], Regression Analysis [MeSH], Geologic Sediments/chemistry [MeSH], DSC, Research Article, Thermal analysis, Environmental Monitoring/methods [MeSH], Regression, Calorimetry, Differential Scanning [MeSH], 02 engineering and technology, 01 natural sciences, Environmental Monitoring, 0105 earth and related environmental sciences
Popis: This research addresses the growing need for fast and cost-efficient methods for microplastic (MP) analysis. We present a thermo-analytical method that enables the identification and quantification of different polymer types in sediment and sand composite samples based on their phase transition behavior. Differential scanning calorimetry (DSC) was performed, and the results were evaluated by using different regression models. The melting and crystallization enthalpies or the change in heat capacity at the glass transition point were measured as regression analysis data. Ten milligrams of sea sand was spiked with 0.05 to 1.5 mg of microplastic particles (size: 100 to 200 µm) of the semi-crystalline polymers LD-PE, HD-PE, PP, PA6, and PET, and the amorphous polymers PS and PVC. The results showed that a two-factorial regression enabled the unambiguous identification and robust quantification of different polymer types. The limits of quantification were 0.13 to 0.33 mg and 0.40 to 1.84 mg per measurement for semi-crystalline and amorphous polymers, respectively. Moreover, DSC is robust with regard to natural organic matrices and allows the fast and non-destructive analysis of microplastic within the analytical limits. Hence, DSC could expand the range of analytical methods for microplastics and compete with perturbation-prone chemical analyses such as thermal extraction–desorption gas chromatography–mass spectrometry or spectroscopic methods. Further work should focus on potential changes in phase transition behavior in more complex matrices and the application of DSC for MP analysis in environmental samples.
Druh dokumentu: Article
Other literature type
Jazyk: English
ISSN: 1614-7499
DOI: 10.1007/s11356-024-33100-8
Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38616225
https://repository.publisso.de/resource/frl:6518170
Rights: CC BY
Přístupové číslo: edsair.doi.dedup.....3f581d96d5345d684c10bd6a831002a5
Databáze: OpenAIRE
Popis
Abstrakt:This research addresses the growing need for fast and cost-efficient methods for microplastic (MP) analysis. We present a thermo-analytical method that enables the identification and quantification of different polymer types in sediment and sand composite samples based on their phase transition behavior. Differential scanning calorimetry (DSC) was performed, and the results were evaluated by using different regression models. The melting and crystallization enthalpies or the change in heat capacity at the glass transition point were measured as regression analysis data. Ten milligrams of sea sand was spiked with 0.05 to 1.5 mg of microplastic particles (size: 100 to 200 µm) of the semi-crystalline polymers LD-PE, HD-PE, PP, PA6, and PET, and the amorphous polymers PS and PVC. The results showed that a two-factorial regression enabled the unambiguous identification and robust quantification of different polymer types. The limits of quantification were 0.13 to 0.33 mg and 0.40 to 1.84 mg per measurement for semi-crystalline and amorphous polymers, respectively. Moreover, DSC is robust with regard to natural organic matrices and allows the fast and non-destructive analysis of microplastic within the analytical limits. Hence, DSC could expand the range of analytical methods for microplastics and compete with perturbation-prone chemical analyses such as thermal extraction–desorption gas chromatography–mass spectrometry or spectroscopic methods. Further work should focus on potential changes in phase transition behavior in more complex matrices and the application of DSC for MP analysis in environmental samples.
ISSN:16147499
DOI:10.1007/s11356-024-33100-8