| 24 Sep 2026
Airborne Microplastics in the PM2.5 Fraction: Empirically Calibrated µFTIR-ATR Imaging Detects Particles Down to 2 µm
Abstract. Reliable identification of airborne microplastics (AMPs) in the PM2.5 fraction remains challenging. Conventional µFTIR imaging studies of atmospheric aerosol have generally targeted larger particles, and the reliability of library-matching scores at this smaller size range has not been systematically examined. We present a µFTIR-ATR imaging workflow that separates spectral processing for chemical identification from image processing for physical characterisation. For chemical identification, particle-level spectra were smoothed and evaluated through library matching combined with diagnostic-band interpretation. For physical characterisation, PCA-based image processing and blank-derived intensity thresholds defined particle boundaries for Feret-dimension measurement and morphological classification. We defined the TopHit ratio as the proportion of top-ranked library assignments agreeing with diagnostic-band interpretation within each maximum-correlation-coefficient (Rmax) interval. Among 674 particles, this ratio rose from 41.1% at Rmax = 0.4–0.5 to 96.0% at Rmax = 0.8–0.9 and 100.0% at Rmax = 0.9–1.0; a Richards growth model best described this relationship across four tested library/bin-width combinations. The workflow also enabled identification and measurement of an airborne polyethylene terephthalate particle collected in the PM2.5 fraction, with an apparent minimum Feret dimension of 2.3 µm. To our knowledge, this is the first study to combine µFTIR-based polymer identification of an airborne PM2.5 particle approaching 2 µm with explicit empirical calibration of spectral-matching confidence.
Competing interests: Yasuhiro Niida is an employee of PerkinElmer Japan G.K., the manufacturer of the FTIR imaging instrument and software used in this study. The other authors declare that they have no conflict of interest.
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