The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Suspended microplastics in the surface water of the Yangtze Estuary System, China: First observations on occurrence, distribution
Open accessAbstract
Levels of microplastics (MPs) in China are completely unknown. This study characterizes suspended MPs quantitatively and qualitatively for the Yangtze Estuary and East China Sea. MPs were extracted via a floatation method. MPs were counted and categorized according to shape and size under a stereomicroscope. The MP densities were 4137.3±2461.5 and 0.167±0.138 n/m(3), respectively, in the estuarine and the sea samples. Plastic abundances varied significantly in the estuary. Higher densities in three sea trawls confirmed that rivers were the important sources of MP to the marine environment. Plastic particles (>5mm) were observed with a maximum size of 12.46 mm, but MPs (0.5-5 mm) constituted more than 90% by number of items. The most frequent geometries were fibres, followed by granules and films. Plastic spherules occurred sparsely. Transparent and coloured plastics comprised the majority of the particles. This study provides clues in understanding the fate and potential sources of MPs.
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Metadata
- Authors
- Zhao, S., Zhu, L., Wang, T., & Li, D.
- Venue
- Marine Pollution Bulletin
- Publisher
- Elsevier BV
- Published
- 2014-09
- Volume
- 86
- Issue
- 1-2
- Pages
- 562-568
- ISSN
- 0025-326X (ISSN-L)
- OpenAlex
- W1994788768
- Cited by
- 1,060
- References
- 10
- FWCI
- 17.79
- Type
- journal article
- Language
- en
- Open access
- hybrid
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- Zhao, S., Zhu, L., Wang, T., & Li, D. (2014). Suspended microplastics in the surface water of the Yangtze Estuary System, China: First observations on occurrence, distribution. Marine Pollution Bulletin. https://doi.org/10.1016/j.marpolbul.2014.06.032
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
