Selective Imaging of Microplastic and Organic Particles in Flow by Multimodal Coherent Anti-Stokes Raman Scattering and Two-Photon Excited Autofluorescence Analysis

Microplastic pollution is an urgent global issue. While spectroscopic techniques have been widely used for the identification of plastics collected from aquatic environments, these techniques are often labor-intensive and time-consuming due to sample collection, preparation, and long measurement times. In this study, a method for the two-dimensional detection and classification of flowing micro-plastic and organic biotic particles with high spatial and temporal resolutions has been proposed based on the simultaneous detection of coherent anti-Stokes Raman scattering (CARS) and two-photon excited autofluorescence (TPEAF) signals. Poly(methyl methacrylate) (PMMA), polystyrene (PS), and low-density polyethylene (LDPE) particles with sizes ranging from several tens to hundreds of micrometers were selectively detected in flow with an average velocity of 4.17 mm/s by CARS line scanning. With the same flow velocity, flowing PMMA and alga particles were measured using a multimodal system of CARS and TPEAF signals. The average intensities of both PMMA and alga particles in the CARS signals at a frequency of 2940 cm(-1) were higher than the background level, while only algae emitted TPEAF signals. This allowed the classification of PMMA and alga particles to be successfully performed in flow by the simultaneous detection of CARS and TPEAF signals. With the proposed method, the monitoring of microplastics in a continuous water flow without collection or extraction is possible, which is game-changing for the current sampling-based microplastic analysis.

Automated summary

This study proposes a method for the detection and classification of microplastic and organic biotic particles in flow based on the simultaneous detection of CARS and TPEAF signals, with high spatial and temporal resolutions. The method successfully classifies PMMA and alga particles in flow by simultaneously detecting CARS and TPEAF signals. This approach allows for the monitoring of microplastics in continuous water flow without the need for collection or extraction, revolutionizing the current sampling-based microplastic analysis.