We can't find the internet
Attempting to reconnect
Something went wrong!
Hang in there while we get back on track
Automated analysis of microplastics based on vibrational spectroscopy: Are we measuring the same metrics?
Summary
Researchers compared three automated spectroscopy-based methods for identifying microplastics and found they produce inconsistent results in particle counts and material identification. Each technique has specific strengths and limitations, and results from different methods should not be assumed to be directly comparable.
The traditional manual analysis of microplastics has been criticized because it is labor intensive, inaccurate for identifying very small microplastics, and difficult to standardize or compare. There are already three automated analysis strategies for microplastics based on vibrational spectroscopy, laser direct infrared (LDIR)-based particle analysis, Raman-based particle analysis, and focal plane array-Fourier transform infrared (FPA-FTIR) imaging. We compared the performances of these strategies in terms of their quantification, detection limit, size measurement, and material identification accuracy and analysis speed by analyzing the same standard and environmental samples. Unfortunately, the automated analysis strategies are not consistent in terms of the quantification and material identification results. The number of particles smaller than 60 μm recognized by Raman-based particle analysis is far greater than that recognized by LDIR-based particle analysis. Raman-based particle analysis has a submicrometer detection limit but should not be used in the automated analysis of microplastics in environmental samples because of the strong fluorescence interference. LDIR-based particle analysis provides the fastest analysis speed, but we suggest using a reliable detection limit of approximately 60 μm and considering the material identification results and reference database used because the wavenumbers LDIR spectra are in the range of 975-1800 cm-1. FPA-FTIR imaging provides relatively reliable quantification and material identification for microplastics in environmental samples but might provide an imprecise description of the particle shapes. As a technological advancement, automated analysis of microplastics should be encouraged, but we need to foster the strengths and circumvent the weaknesses of different strategies. The automated analysis of microplastics should be further validated and standardized.