Distribution Characteristics and Source Analysis of Microplastics in Urban Freshwater Lakes: A Case Study in Songshan Lake of Dongguan, China

Current studies on microplastic pollution mainly focus on marine systems. However, few studies have investigated microplastics in an urban lake. This research intends to use an urban lake (Songshan Lake) as an example to explore the pollution characteristics of microplastics and use the principal co...

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Bibliographic Details
Main Authors: Nian Tang, Yunjun Yu, Liqi Cai, Xiangling Tan, Lulu Zhang, Yihui Huang, Bo Li, Jinping Peng, Xiangrong Xu
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Water
Subjects:
Online Access:https://www.mdpi.com/2073-4441/14/7/1111
Description
Summary:Current studies on microplastic pollution mainly focus on marine systems. However, few studies have investigated microplastics in an urban lake. This research intends to use an urban lake (Songshan Lake) as an example to explore the pollution characteristics of microplastics and use the principal component as well as the heat map analysis to discuss the relationships between different shapes of microplastics. According to this study, the average abundance of microplastics in the surface water and surface sediments of Songshan Lake were, respectively, 2.29 ± 0.98 items/m<sup>3</sup> and 244 ± 121 items/kg; thin films were the major microplastics in both media; transparent this type of color has the most microplastic content. The particle size of microplastics was mainly 0.18–0.6 mm (43.3%) in surface water and 1–2 mm (48.3%) in surface sediments. The composition included five polymers: polyethylene (PE), polypropylene (PP), polypropylene–polyethylene copolymer (PP–PE copolymer), polystyrene (PS), and polyvinyl chloride (PVC), among which PE (47%) and PP (36%) were the main components. Principal component analysis (PCA) showed that there was a positive correlation among the four shapes of microplastics: films, fragments, foams, and fibers. The heat map analysis showed that the same category of shape distribution features may be similar for each sampling site.
ISSN:2073-4441