A novel framework-based meta-analysis for in-depth characterization of microplastic pollution and associated...

Among aquatic ecosystems, bays are ubiquitously contaminated with microplastics (MPs, size <5 mm), but a comprehensive understanding of their pollution characterization in Chinese Bays is largely elusive. The current study aims to systematically highlight factors intricating MP contamination as well as their geographic distribution, interactions, risk evaluation, and abundance prediction in bays. MPs' abundance was varied in different bays, at concentrations ranging between 0.26 ± 0.14-89, 500 ± 20, 600 items/m³ in water, 15 ± 6-6433.5 items/kg dry weight in sediment and 0.21 ± 0.10-103.5 items/individual in biota. Redundancy analysis, Permannova, and GeoDetector model revealed that the sampling and extraction/identification methods, and geographical locations were the major drivers affecting MP distribution and characteristics. The Mantel test highlighted that the MP characteristics changed with geographic distance, higher in water than that in sediment and biota. ANOSIM results showed that the different environmental media exhibit significant differences in MP characteristics (e.g., color, shape, and polymer). The ARIMA model predicted that Sanggou Bay and Hangzhou Bay have a higher potential for significantly increasing MP contamination in the future. The highest hazard index (HI) values for water, sediment, and biota were respectively reported at Jiaozhou Bay (18,844.16), Bohai Bay (11,485.37), and Dongshan Bay (48,485.11). The highest values for the ecological risk index (RI) in water, sediment, and biota were detected at Beibu Gulf (6,129,559.02), Haikou Bay (2229.14), and Dongshan Bay (561,563.05), respectively. Overall, this framework can be used at different scales and in different environments, which makes it useful for understanding and controlling MP pollution in the ecosystem.