Mass Spectrometry Insight for Assessing the Destiny of Plastics in Seawater

质谱分析在评估海水中塑料归宿方面的应用

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Abstract

Plastic pollution has become an increasingly serious environmental issue that requires using reliable analytical tools to unravel the transformations of primary plastics exposed to the marine environment. Here, we evaluated the performance of the isotope ratio mass spectrometry (IRMS) technique for identifying the origin of polymer material contaminating seawater and monitoring the compositional alterations due to its chemical degradation. Of twenty-six plastic specimens available as consumer products or collected from the Mediterranean Sea, five plastics were shown to originate from biobased polymeric materials. Natural abundance carbon and hydrogen isotope measurements revealed that biopolymers incline to substantial chemical transformation upon a prolonged exposure to seawater and sunlight irradiation. To assess the seawater-mediated aging that leads to the release of micro/nano fragments from plastic products, we propose to use microfiltration. Using this non-destructive separation technique as a front end to IRMS, the fragmentation of plastics (at the level of up to 0.5% of the total mass for plant-derived polymers) was recorded after a 3-month exposure and the rate and extent of disintegration were found to be substantially different for the different classes of polymers. Another potential impact of plastics on the environment is that toxic metals are adsorbed on their surface from the seashore water. We addressed this issue by using inductively coupled mass spectrometry after nitric acid leaching and found that several metals occur in the range of 0.1-90 µg per g on naturally aged plastics and accumulate at even higher levels (up to 10 mg g(-1)) on pristine plastics laboratory-aged in contaminated seawater. This study measured the degradation degree of different polymer types in seawater, filling in the gaps in our knowledge about plastic pollution and providing a useful methodology and important reference data for future research.

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