ReviewMolecules (Basel, Switzerland)2026
Molecular Fingerprinting for Source Attribution of Nanoplastics in Drinking-Water Systems.
Review in Molecules (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
3 authors.
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Abstract
Detection of nanoplastics in drinking-water systems is only the first analytical step toward exposure interpretation; the next challenge is source attribution. This review examines molecular fingerprinting and transformation pathways that can link nanoscale polymer signals to source waters, drinking-water treatment, distribution infrastructure, packaging materials, laboratory background, or aging processes across the potable-water chain. Nanoplastics are treated here as operationally defined particles below 1 µm, including intentionally manufactured primary nanoplastics and secondary nanoplastics generated by fragmentation, abrasion, weathering, treatment, storage, or packaging stress. The synthesis evaluates how polymer identity, particle morphology, surface oxidation, additive and oligomer profiles, thermal degradation markers, matrix context, and quality assurance/quality control (QA/QC) can be combined into defensible source assignments. Analytical platforms considered include surface-enhanced Raman spectroscopy (SERS), atomic force microscopy-infrared spectroscopy (AFM-IR), optical photothermal infrared spectroscopy (O-PTIR), stimulated Raman scattering microscopy (SRS), pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS), asymmetric flow field-flow fractionation coupled to Py-GC/MS (AF4-Py-GC/MS), matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), and chemometric workflows. The central conclusion is that source attribution cannot be inferred from polymer identity alone; robust interpretation requires convergent evidence from particle-level chemistry, polymer-specific mass, additive or marker-ion signatures, aging state, blanks, recovery, and contextual sampling design.
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