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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao The Science of The T...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
The Science of The Total Environment
Article . 2020 . Peer-reviewed
License: Elsevier TDM
Data sources: Crossref
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Spatial-temporal distribution of microplastics in surface water and sediments of Maozhou River within Guangdong-Hong Kong-Macao Greater Bay Area

Authors: Pengfei Wu; Yuanyuan Tang; Miao Dang; Siqing Wang; Hangbiao Jin; Yunsong Liu; Hao Jing; +3 Authors

Spatial-temporal distribution of microplastics in surface water and sediments of Maozhou River within Guangdong-Hong Kong-Macao Greater Bay Area

Abstract

Concerns over the negative impacts of microplastics on human health have led to growing attention on the occurrence of microplastics in aquatic environment. Recent studies have extended their focus from marine to inland waters, especially on the spatial-temporal distribution of the microplastics in urban rivers. In this study, Maozhou River, the largest river in Shenzhen, a tributary of the Pearl River, was selected as a representative inland waterway of Guangdong-Hong Kong-Macao Greater Bay Area. The spatial-temporal investigation was performed on microplastics in the surface water and sediments of 17 sites along the mainstream of the Maozhou River. Results show that microplastics were widely and unevenly distributed along the river and reached the high abundances on the site most intensively surrounded by industries as well as the sites downstream. The abundances in dry season ranged from 4.0 ± 1.0 to 25.5 ± 3.5 items·L-1 in water and 35 ± 15 to 560 ± 70 item·kg-1 in sediments, which were relatively higher than those observed in the wet season (water: 3.5 ± 1.0 to 10.5 ± 2.5 items·L-1; sediments: 25 ± 5 to 360 ± 90 item·kg-1; p value < 0.05). The dominant types of the microplastics were identified as: PE Polyethylene (PE, water: 45.0%, sediments: 42.0%), polypropylene (PP, water and sediments: 12.5%), polystyrene (PS, water: 34.5%; sediments 14.5%) and polyvinyl chloride (PVC, water: 2.0%; sediments: 15%). Moreover, metals like Al, Si, Ca were discovered on the rough surface of the microplastics, indicating the interactions between the microplastics and the aquatic environment. Through a comprehensive comparison with other major inland waters in China, this work provides valuable data on the microplastics pollution of a representative inland water in the Greater Bay Area, and will further contribute to a better understanding on the land-based input of microplastics from the intensively affected inland waters.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
233
Top 0.1%
Top 10%
Top 0.1%
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