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Updated: Oct 24, 2026

Sampling, Sorting, and Characterizing Microplastics in Aquatic Environments with High Suspended Sediment Loads and Large Floating Debris
Published on: July 28, 2018
Beyond particle counts: Mass-based assessment reshapes ecological risk evaluation of estuarine microplastics
Rupeng Du1, Weiming Wu2, Zhuoyun Chen2
1Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China; Marine Academy of Zhejiang Province, Hangzhou 310012, China.
Abstract:
This study investigates microplastic (MP) pollution in surface water and sediments of Xiamen and the Jiulong River estuary using laser direct infrared (LDIR) imaging, focusing on small-sized particles (20-500 μm). MP distribution and potential ecological risks were evaluated using number and estimated mass abundance together with the pollution load index (PLI), polymer hazard index (PHI), potential ecological risk index (PERI) and multi-scenario risk quotient (RQ). MPs were detected at all sites, with observed abundances varying among sites. In surface water, mean abundances were 518.4 ± 496.8 items L-1 and 125.1 ± 112.1 μg L-1, while sediments contained 54.8 ± 36.6 items g-1 and 27.5 ± 24.4 μg g-1. Particles <100 μm dominated all samples. A total of 18 polymer types were identified in water, primarily polypropylene (PP), whereas 19 polymer types occurred in sediments, dominated by polyethylene (PE) and PP. No significant correlation between number and mass abundances was observed in surface water, but a significant positive relationship was found in sediments. Risk assessment indicated low pollution (PLI, Class I) but elevated potential ecological risks (PHI, Class IV; PERI, Class V), driven mainly by polyurethane, polyvinyl chloride and polyacrylamide. Multi-scenario RQ analysis further showed that risk interpretation varied with MP concentration metrics and ecological effect thresholds. These findings demonstrate the value of integrating number- and estimated mass-based metrics and multiple risk assessment approaches for a more robust interpretation of MP pollution and ecological risk.
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