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The monitoring of the emerging contaminant, microplastics, in the environment, in water supply, and for food safety is of major interest to science, consumers, and governments. While the chemical analysis of these particles is considered mandatory, a rapid and reliable method for the determination of particle sizes, shapes, and numbers is missing, as existing methods are not fitting into current laboratory measurement routines. In this study, we present an approach for circumventing these issues through the application of quantum cascade laser-based microscopy combined with an automated data analysis. This method allows the measurement of an area of 144 mm 2 in 36 min, with a pixel resolution of 4.2 μm, which is an appropriate timeframe and spatial resolution for routine measurements. The performance was compared to the existing state-of-the-art Fourier transform infrared microscopy analyses. Further, the application of the method on various environmental samples was investigated to examine its capacity to provide number and variety of present particles. The described analytical procedure overcomes the last restrictions for schedulable and rapid microplastic monitoring, resulting in a highly detailed data set for particle numbers, particle shapes, and polymer types.

Rapid Identification and Quantification of Microplastics in the Environment by Quantum Cascade Laser-Based Hyperspectral Infrared Chemical Imaging