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Improving Microspectroscopic Microplastic Data Extrapolation: From Field of View to Full Sample, and from Fragment 2D-Morphology to Mass

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Researchers investigated methods to improve the reliability of microplastic data extrapolation from microspectroscopic subsampling, finding that current strategies result in 50% or greater error due to heterogeneous particle dispersion on filter substrates and proposing improved field-of-view protocols.

Microplastic (MP) analysis via microspectroscopy typically examines only 1–10% of filter substrates due to time constraints, requiring reliable extrapolation methods for quantitative environmental monitoring. Current subsampling strategies suffer from heterogeneous particle dispersion, leading to 50–80% error in MP quantification. Additionally, MP researchers require enhanced environmental MP mass datasets, necessitating reliable conversion algorithms from two-dimensional morphological data to mass estimates. This study introduces an area-based extrapolation technique for organic rich samples that compares the MP-to-generic particle area ratio within a rectangular field of view against total particle area on the entire filter membrane, combined with a simplified fragment morphology-to-mass conversion model (SFMM). First, two Sphagnum moss samples were analyzed using Raman microspectroscopy and critical angle darkfield illumination microscopy. The results demonstrated stable MP concentrations (17% RSD [n = 8]) despite heterogeneous generic particle distribution (31% RSD [n = 8]), with mean particle-area coverage of 2.4% per subsample. Then, twenty EasyMPTM fragment reference materials (10 µm to 1500 µm), of known composite mass, were used to calibrate two different volume (V) expressions, one based on analyzed particle area (A) and minimum Feret diameter (FMin, i.e., width), yielding V = 0.34 × FMin × A. A second more approximate expression based on only the maximum Feret diameter (FMax, i.e., length) yielded V = 0.097 × (FMax)3. These methods enable MP quantification and mass estimation from limited spectroscopic analysis.

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