The plastic fingerprint: Temporal and spatial variability in Flanders' riverine plastic pollution
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2024
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| _version_ | 1866901788679995392 |
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| author | Vercauteren, Maaike Sioen, Marie Catarino, Ana Devriese, Lisa Janssen, Colin Everaert, Gert Asselman, Jana |
| author_facet | Vercauteren, Maaike Sioen, Marie Catarino, Ana Devriese, Lisa Janssen, Colin Everaert, Gert Asselman, Jana |
| contents | Plastic pollution is increasingly recognized as a heterogeneous class of contaminants with varying physicochemical properties, recently described as "the microplastome". This new paradigm may, however, oversimplify the issue as local pollution sources and riverine characteristics can cause differences on a spatial scale. Additionally, temporal influences such as rainfall or wind might alter influx of micro- and mesoplastics into rivers. To better understand spatial and temporal dynamics in the plastic fingerprint and their association with local and temporal parameters, a coordinated monitoring study was setup in Flanders, Belgium. Between 2020 and 2022, 355 samples were collected in the River Scheldt and five harbors. These samples were distributed into four categories based on matrix (water or sediment) and plastic size (micro- and mesoplastic). All plastics were characterized by polymer type, size, color, and shape. Local and temporal descriptors, such as population density, weather data, and river characteristics, were gathered from open-source data portals and processed using QGIS. Hierarchical clustering based on principal component analysis was performed to identify sample clusters based on plastic characteristics. The association between these clusters and the local and temporal descriptors was then analyzed. The results showed different clustering patterns for the four sample types, indicating different behavioral patterns and fates of meso- and microplastics in water and sediment. For microplastics, clustering was mainly based on size and polymer composition, while for mesoplastics in water, shape was a key factor. In all sample types, plastic fingerprints shifted over time and space, influenced by riverine characteristics, land use and weather parameters, showcasing the complexity of plastic pollution. In conclusion, our study reveals substantial variations in plastic fingerprints across both spatial and temporal scales, as well as among different environmental matrices and between meso- and microplastics. This complexity underscores the need for localized analysis to address environmental plastic pollution. Also see: https://micro2024.sciencesconf.org/559019/document |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18388555 |
| institution | Zenodo |
| language | |
| publishDate | 2024 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | The plastic fingerprint: Temporal and spatial variability in Flanders' riverine plastic pollution Vercauteren, Maaike Sioen, Marie Catarino, Ana Devriese, Lisa Janssen, Colin Everaert, Gert Asselman, Jana coastal and transitional waters and sediment hierarchical clustering local and temporal descriptors plastic behavior plastic fingerprint pollution source Plastic pollution is increasingly recognized as a heterogeneous class of contaminants with varying physicochemical properties, recently described as "the microplastome". This new paradigm may, however, oversimplify the issue as local pollution sources and riverine characteristics can cause differences on a spatial scale. Additionally, temporal influences such as rainfall or wind might alter influx of micro- and mesoplastics into rivers. To better understand spatial and temporal dynamics in the plastic fingerprint and their association with local and temporal parameters, a coordinated monitoring study was setup in Flanders, Belgium. Between 2020 and 2022, 355 samples were collected in the River Scheldt and five harbors. These samples were distributed into four categories based on matrix (water or sediment) and plastic size (micro- and mesoplastic). All plastics were characterized by polymer type, size, color, and shape. Local and temporal descriptors, such as population density, weather data, and river characteristics, were gathered from open-source data portals and processed using QGIS. Hierarchical clustering based on principal component analysis was performed to identify sample clusters based on plastic characteristics. The association between these clusters and the local and temporal descriptors was then analyzed. The results showed different clustering patterns for the four sample types, indicating different behavioral patterns and fates of meso- and microplastics in water and sediment. For microplastics, clustering was mainly based on size and polymer composition, while for mesoplastics in water, shape was a key factor. In all sample types, plastic fingerprints shifted over time and space, influenced by riverine characteristics, land use and weather parameters, showcasing the complexity of plastic pollution. In conclusion, our study reveals substantial variations in plastic fingerprints across both spatial and temporal scales, as well as among different environmental matrices and between meso- and microplastics. This complexity underscores the need for localized analysis to address environmental plastic pollution. Also see: https://micro2024.sciencesconf.org/559019/document |
| title | The plastic fingerprint: Temporal and spatial variability in Flanders' riverine plastic pollution |
| topic | coastal and transitional waters and sediment hierarchical clustering local and temporal descriptors plastic behavior plastic fingerprint pollution source |
| url | https://doi.org/10.5281/zenodo.18388555 |