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  5. All black: a microplastic extraction combined with colour-based analysis allows identification and characterisation of tire wear particles (TWP) in soils
 
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2024
Zweitveröffentlichung
Artikel
Verlagsversion

All black: a microplastic extraction combined with colour-based analysis allows identification and characterisation of tire wear particles (TWP) in soils

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TUDa URI
tuda/13191
URN
urn:nbn:de:tuda-tuprints-292683
DOI
10.26083/tuprints-00029268
Autor:innen
Foetisch, Alexandra
Grunder, Adrian
Kuster, Benjamin
Stalder, Tobias
Bigalke, Moritz ORCID 0000-0002-6793-6159
Kurzbeschreibung (Abstract)

While tire wear particles (TWP) have been estimated to represent more than 90% of the total microplastic (MP) emitted in European countries and may have environmental health effects, only few data about TWP concentrations and characteristics are available today. The lack of data stems from the fact that no standardized, cost efficient or accessible extraction and identification method is available yet. We present a method allowing the extraction of TWP from soil, performing analysis with a conventional optical microscope and a machine learning approach to identify TWP in soil based on their colour. The lowest size of TWP which could be measured reliably with an acceptable recovery using our experimental set-up was 35 µm. Further improvements would be possible given more advanced technical infrastructure (higher optical magnification and image quality). Our method showed a mean recovery of 85% in the 35–2000 µm particle size range and no blank contamination. We tested for possible interference from charcoal (as another black soil component with similar properties) in the soils and found a reduction of the interference from charcoal by 92% during extraction. We applied our method to a highway adjacent soil at 1 m, 2 m, 5 m, and 10 m and detected TWP in all samples with a tendency to higher concentrations at 1 m and 2 m from the road compared to 10 m from the road. The observed TWP concentrations were in the same order of magnitude as what was previously reported in literature in highway adjacent soils. These results demonstrate the potential of the method to provide quantitative data on the occurrence and characteristics of TWP in the environment. The method can be easily implemented in many labs, and help to address our knowledge gap regarding TWP concentrations in soils.

Freie Schlagworte

Microplastic

Tire wear

Optical microscopy

Machine learning

Segmentation

Soil pollution

Sprache
Englisch
Fachbereich/-gebiet
11 Fachbereich Material- und Geowissenschaften > Geowissenschaften > Fachgebiet Bodenmineralogie und Bodenchemie
DDC
500 Naturwissenschaften und Mathematik > 550 Geowissenschaften
Institution
Universitäts- und Landesbibliothek Darmstadt
Ort
Darmstadt
Titel der Zeitschrift / Schriftenreihe
Microplastics and Nanoplastics
Jahrgang der Zeitschrift
4
ISSN
2662-4966
Verlag
SpringerOpen
Ort der Erstveröffentlichung
Cham
Publikationsjahr der Erstveröffentlichung
2024
Verlags-DOI
10.1186/s43591-024-00102-9
PPN
534318401
Artikel-ID
25
Ergänzende Ressourcen (Forschungsdaten)
https://doi.org/10.5281/zenodo.13925411

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