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Improved Py-GC/MS Analysis of Nanoplastics in Environmental Waters via Organic-Free Flocculation-Based Preconcentration
Summary
Researchers developed an organic-free flocculation preconcentration method using polymerized ferrous sulfate to isolate five polymer types of nanoplastics from water, achieving recovery rates of 81–97% and detection limits of 0.01–0.02 μg/L when analyzed by pyrolysis GC/MS. This method addresses a critical analytical gap for nanoplastic quantification in drinking water and environmental monitoring, avoiding organic solvent interference that compromises existing extraction approaches.
Nanoplastics (NPs) have emerged as ubiquitous environmental contaminants, raising increasing concerns over their ecological impacts and potential risks to human health. However, accurate quantification of NPs in aquatic environments remain analytically challenging due to the lack of effective enrichment techniques capable of operating at trace concentrations. Herein, we developed a robust, rapid, and organic-free flocculation-based preconcentration strategy for NP quantification in water samples. Utilizing polymerized ferrous sulfate (PFS) as an flocculant, diverse NPs, including polystyrene (PS), poly(methyl methacrylate) (PMMA), poly(vinyl chloride) (PVC), polypropylene (PP), and poly(ethylene terephthalate) (PET), were efficiently coprecipitated with ferrihydrite (FeOOH) and subsequently isolated by centrifugation. The enriched NPs were analyzed by pyrolysis gas chromatography/mass spectrometry (Py-GC/MS), achieving high recoveries (≥92.8%) and low detection limits (0.01-0.02 μg/L). Field application revealed PS NP concentrations ranging from 0.11 to 0.36 μg/L, while recovery experiments in representative natural waters yielded consistent results (81.3-97.3%), confirming the method's accuracy and matrix tolerance. Compared with conventional extraction approaches (e.g., cloud point extraction), this protocol avoids the introduction of organic additives that may interfere with pyrolysis, thereby improving analytical sensitivity and reducing background complexity. Overall, the proposed method provides a reliable and practical platform for monitoring NP pollution in diverse aquatic systems.