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Identification of polystyrene nanoplastics from natural organic matter in complex environmental matrices by pyrolysis–gas chromatography–mass spectrometry
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Researchers used pyrolysis-gas chromatography-mass spectrometry to identify polystyrene nanoplastics in environmental samples containing natural organic matter, developing methods to distinguish nanoplastic signals from complex organic background matrices in water.
Due to the flux of plastic debris entering the environment, it becomes urgent to document and monitor their degradation pathways at different scales. At the colloidal scale, the systematic hetero-association of nanoplastics with the natural organic matter complexifies the ability to detect plastic signatures in the particle collected in the various environments. The current techniques used for microplastics could not discriminate the polymers at the nanoscale from the natural macromolecules, as the plastic mass in the aggregate is within the same order. Only a few methods are available concerning nanoplastics identification in complex matrices, with the coupling of pyrolysis with gas chromatography and mass spectrometry (Py-GC-MS) as one of the most promising due to its mass-based detection. However, natural organic matter in environmental samples interferes with similar pyrolysis products. These interferences are even more critical for polystyrene polymers as this plastic presents no dominant pyrolysis markers, such as polypropylene, that could be identified at trace concentrations. Here, we investigate the ability to detect and quantify polystyrene nanoplastics in a rich phase of natural organic matter proposed based on the relative ratio of pyrolyzates. The use of specific degradation products (styrene dimer and styrene trimer) and the toluene/styrene ratio (R) are explored for these two axes. While the size of the polystyrene nanoplastics biased the pyrolyzates of styrene dimer and trimer, the R was correlated with the nanoplastics mass fraction in the presence of natural organic matter. An empirical model is proposed to evaluate the relative quantity of polystyrene nanoplastics in relevant environmental matrices. The model was applied to real contaminated soil by plastic debris and literature data to demonstrate its potential.
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