Goßmann, Isabel; Halbach, Maurits; Scholz-Böttcher, Barbara (2023): Car and truck tire wear particles in road dust samples - A quantitative comparison with traditional microplastic polymer mass loads [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.959716
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Published: 2023-07-04 • DOI registered: 2023-08-02
Abstract:
This data set provides quantitative mass loads of tire wear particles (TWP) and traditional microplastics (C-PE, C-PP, C-PS, C-PVC, C-PMMA, C-PET, C-PC, C-MDI-PUR) in the urban environment. A differentiation between car and truck tire wear (CTT and TTT) was presented. The C-PVC cluster might be interfered by additional anthropogenic sources, as the C-PVC indicator naphthalene is highly unspecific, accordingly the given results primarily reflect the order of magnitude. In this study, road dusts were analyzed and measured with pyrolysis-gas chromatography-mass spectronomy (Py-GC/MS). Pyrolysis was performed at 590°C in a micro-furnace pyrolizer (EGA/Py-3030D, FrontierLabs) connected to an auto-shot sampler (AS-1020E, FrontierLabs). A gas chromatograph (6890 N, Agilent) equipped with a DB-5MS column was used for separation. The mass spectrometer (MSD 5973, Agilent) operated with full-scan mode. A gas chromatograph (6890 N, Agilent) equipped with a DB-5MS column was used for separation. The mass spectrometer (MSD 5977A) operated with full-scan mode. Additional information are found in the supplementary information of the related study. Road dust samples were collected in a mid-sized German city (Oldenburg). Road dust were contaminated with traditional microplastics and tire wear particles. The here presented data are part of a study, which has been published in February 2021 (doi: 10.1016/j.scitotenv.2021.145667).
Related to:
Goßmann, Isabel; Halbach, Maurits; Scholz-Böttcher, Barbara (2021): Car and truck tire wear particles in complex environmental samples – A quantitative comparison with "traditional" microplastic polymer mass loads. Science of the Total Environment, 773, 145667, https://doi.org/10.1016/j.scitotenv.2021.145667
Project(s):
Coverage:
Median Latitude: 53.127085 * Median Longitude: 8.187105 * South-bound Latitude: 53.108330 * West-bound Longitude: 8.141940 * North-bound Latitude: 53.148060 * East-bound Longitude: 8.210830
Date/Time Start: 2019-11-01T00:00:00 * Date/Time End: 2020-01-27T00:00:00
Event(s):
2019_TWP_A (A) * Latitude: 53.148060 * Longitude: 8.182500 * Date/Time: 2019-11-01T00:00:00 * Location: Oldenburg, Germany * Method/Device: Shovel (SHOVEL)
Parameter(s):
| # | Name | Short Name | Unit | Principal Investigator | Method/Device | Comment |
|---|---|---|---|---|---|---|
| 1 | Event label | Event | Goßmann, Isabel | |||
| 2 | Name | Name | Goßmann, Isabel | optional event label | ||
| 3 | DATE/TIME | Date/Time | Goßmann, Isabel | Geocode | ||
| 4 | LATITUDE | Latitude | Goßmann, Isabel | Geocode | ||
| 5 | LONGITUDE | Longitude | Goßmann, Isabel | Geocode | ||
| 6 | Car tire wear particles | Car TWP | g/kg | Goßmann, Isabel | Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) | |
| 7 | Truck tire wear particles | Truck TWP | g/kg | Goßmann, Isabel | Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) | |
| 8 | Polyethylene, cluster | C-PE | g/kg | Goßmann, Isabel | Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) | |
| 9 | Polypropylene, cluster | C-PP | g/kg | Goßmann, Isabel | Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) | |
| 10 | Polyethylene terephthalate, cluster | C-PET | g/kg | Goßmann, Isabel | Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) | |
| 11 | Polystyrene, cluster | C-PS | g/kg | Goßmann, Isabel | Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) | |
| 12 | Polyvinyl chloride, cluster | C-PVC | g/kg | Goßmann, Isabel | Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) | interfered |
| 13 | Polycarbonate, cluster | C-PC | g/kg | Goßmann, Isabel | Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) | |
| 14 | Polymethylmethacrylate, cluster | C-PMMA | g/kg | Goßmann, Isabel | Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) | |
| 15 | Polyamide 6, cluster | C-PA6 | g/kg | Goßmann, Isabel | Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) | |
| 16 | Diphenylmethane diisocyanate-Polyurethane, cluster | C-MDI-PUR | g/kg | Goßmann, Isabel | Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) | |
| 17 | Sum | Sum | Goßmann, Isabel | Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) | sum of ""traditional"" microplastics |
License:
Creative Commons Attribution 4.0 International (CC-BY-4.0)
Status:
Curation Level: Enhanced curation (CurationLevelC)
Size:
169 data points
Data
| 1 Event | 2 Name | 3 Date/Time | 4 Latitude | 5 Longitude | 6 Car TWP [g/kg] | 7 Truck TWP [g/kg] | 8 C-PE [g/kg] | 9 C-PP [g/kg] | 10 C-PET [g/kg] | 11 C-PS [g/kg] | 12 C-PVC [g/kg] | 13 C-PC [g/kg] | 14 C-PMMA [g/kg] | 15 C-PA6 [g/kg] | 16 C-MDI-PUR [g/kg] | 17 Sum |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2019_TWP_A | A | 2019-11-01T00:00:00 | 53.14806 | 8.18250 | 7.98 | 0.24 | 0.17 | 0.00 | 0.16 | 0.11 | 0.03 | 0.00 | 0.02 | 0.00 | 0.00 | 0.51 |
| 2019_TWP_B | B | 2019-11-01T00:00:00 | 53.14333 | 8.19278 | 10.77 | 0.58 | 0.00 | 0.00 | 0.11 | 0.03 | 0.04 | 0.00 | 0.42 | 0.00 | 0.00 | 0.60 |
| 2019_TWP_C | C | 2019-11-01T00:00:00 | 53.14111 | 8.20861 | 10.08 | 0.26 | 0.00 | 0.00 | 0.13 | 0.06 | 0.04 | 0.00 | 0.39 | 0.00 | 0.00 | 0.62 |
| 2019_TWP_D | D | 2019-11-01T00:00:00 | 53.13889 | 8.21083 | 7.28 | 0.25 | 0.00 | 0.00 | 0.03 | 0.06 | 0.02 | 0.00 | 0.38 | 0.00 | 0.00 | 0.49 |
| 2019_TWP_E | E | 2019-11-01T00:00:00 | 53.13306 | 8.19278 | 7.29 | 2.58 | 0.00 | 0.00 | 0.19 | 0.04 | 0.03 | 0.00 | 0.20 | 0.00 | 0.00 | 0.45 |
| 2020_TWP_F | F | 2020-01-27T00:00:00 | 53.13167 | 8.19278 | 4.54 | 0.02 | 0.00 | 0.00 | 0.06 | 0.13 | 0.06 | 0.00 | 0.11 | 0.00 | 0.00 | 0.37 |
| 2020_TWP_G | G | 2020-01-27T00:00:00 | 53.12586 | 8.18945 | 4.10 | 0.20 | 0.00 | 0.00 | 0.38 | 0.05 | 0.10 | 0.00 | 0.25 | 0.00 | 0.00 | 0.79 |
| 2020_TWP_H | H | 2020-01-27T00:00:00 | 53.12597 | 8.19099 | 2.41 | 0.05 | 0.00 | 0.00 | 0.02 | 0.04 | 0.04 | 0.00 | 0.03 | 0.00 | 0.00 | 0.13 |
| 2020_TWP_I | I | 2020-01-27T00:00:00 | 53.12083 | 8.19194 | 3.37 | 0.20 | 0.00 | 0.00 | 0.05 | 0.04 | 0.04 | 0.00 | 0.08 | 0.00 | 0.00 | 0.22 |
| 2020_TWP_J | J | 2020-01-27T00:00:00 | 53.11472 | 8.19083 | 1.70 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.02 | 0.00 | 0.10 | 0.00 | 0.00 | 0.13 |
| 2020_TWP_K | K | 2020-01-27T00:00:00 | 53.11139 | 8.18361 | 2.17 | 0.05 | 0.00 | 0.00 | 0.05 | 0.03 | 0.06 | 0.00 | 0.08 | 0.00 | 0.00 | 0.22 |
| 2020_TWP_L | L | 2020-01-27T00:00:00 | 53.10889 | 8.16333 | 2.70 | 0.02 | 0.00 | 0.00 | 0.00 | 0.10 | 0.11 | 0.00 | 0.13 | 0.00 | 0.00 | 0.34 |
| 2020_TWP_M | M | 2020-01-27T00:00:00 | 53.10833 | 8.14194 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.02 | 0.00 | 0.08 | 0.00 | 0.00 | 0.11 |