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Selection of Suitable Methods for the Detection of Microplastics in the Environment
Summary
This review evaluated and compared methods for sampling and detecting microplastics across different environmental matrices, recommending density separation with high-density solutions like ZnBr2 for best recovery rates and highlighting the importance of selecting methods matched to the specific research context and environment.
Microplastics (MPs) currently cause an environmental risk due to their transport to all components of the environment. The review article aims to evaluate and compare selected methods for the sampling of different matrices and detection of microplastics. To choose suitable sampling methods, the available equipment, goal of research, and kind of environment should be considered. Through the separation of microplastics from samples, NaI and ZnBr2 can provide high recovery rates (99%) and tight error bars. There exist image analysis software and also computer vision based systems (e.g., SMACC) that can be used for the identification, automatic calculation, and classification of MPs in the environment with shorten data calculation time and reduction of human error. Fourier-transform infrared microscopy and Raman spectroscopy were found to be the most appropriate methods for the characterization of MPs.