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How microplastic loads relate to natural conditions and anthropogenic activities in the Yangtze river basin

Chemosphere 2023 26 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 55 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.
Siqiong Li, Hua Wang, Yue He, Dongfang Liang, Yuhan Shen, Qihui Gu, Yichuan Zeng, Yichuan Zeng

Summary

Microplastic abundance across 366 sampling sites in the Yangtze River basin varied by up to five orders of magnitude, with Chengdu showing the highest levels. In the upstream, GDP-driven anthropogenic activity was the dominant pollution driver (r = 0.85), while in the middle and downstream, natural conditions and human activities contributed roughly equally.

Study Type Review

As the third largest river in the world, microplastic pollution in the Yangtze River basin is currently attracting worldwide attention. However, fragmented research information is insufficient to reveal the occurrence and driving mechanisms of microplastics throughout the Yangtze River basin. Building on a systematic review of 20 existing publications, this study constructed a dataset including microplastic data from 366 samples in the Yangtze River basin through a data filtering process, and data on natural conditions and anthropogenic activities from 101 basin municipalities. Further, multivariate statistical analysis was utilized to enhance the understanding of the abundance, composition and drivers of microplastics within the basin. Differences in microplastic abundance among the sampling sites were up to 5 orders of magnitude, with the highest abundance value found in the upstream city of Chengdu. The comprehensive diversity index used to describe the composition characteristics of microplastics ranged from 0.31 to 0.68, slightly higher than the national average. Based on a statistical analysis framework, natural conditions and anthropogenic activities were shown to jointly drive the distribution of microplastics, and the dominant driver shifted between the two with spatial variation. In the upstream, anthropogenic activities dominated by GDP (r = 0.85, P < 0.01) were the main positive factor. In the middle and downstream, natural conditions and anthropogenic activities had comparable driving forces as the stability of natural resistance increased, and both were positively correlated with microplastics. Combining the constructed normalized stepwise linear regression model with GIS spatial analysis, the basin-wide application demonstrated that microplastic pollution in the upstream and delta deserved more attention. After coupling the distance factors, microplastic pollution was concentrated in the middle and downstream of the Yangtze River basin, covering important drinking water sources. This study provided important data support for subsequent targeted microplastic reduction and treatment.

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