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Automated analysis of microplastics based on vibrational spectroscopy: are we measuring the same metrics?


The traditional manual analysis of microplastics has been criticized for its labor-intensive, inaccurate identification of small microplastics, and the lack of uniformity. 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 their performances in terms of quantification, detection limit, size measurement, and material identification accuracy and speed by analyzing the same standard and environmental samples. LDIR-based particle analysis provides the fastest analysis speed, but potentially questionable material identification and quantification results. The number of particles smaller than 60 μm recognized by LDIR-based particle analysis is much less than that recognized by Raman-based particle analysis. Misidentification could occur due to the narrow tuning range from 1800 to 975 cm−1 and dispersive artifact distortion of infrared spectra collected in reflection mode. Raman-based particle analysis has a submicrometer detection limit but should be cautiously used in the automated analysis of microplastics in environmental samples because of the strong fluorescence interference. FPA-FTIR imaging provides relatively reliable quantification and material identification for microplastics in environmental samples greater than 20 μm but might provide an imprecise description of the particle shapes. Optical photothermal infrared (O-PTIR) spectroscopy can detect submicron-sized environmental microplastics (0.5–5 μm) intermingled with a substantial amount of biological matrix; the resulting spectra are searchable in infrared databases without the influence of fluorescence interference, but the process would need to be fully automated.

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Data availability

The authors declare that all the data supporting the findings of this study are available within the article. Further information and requests for samples and resources should be directed to and will be fulfilled by the Lead Contact, Mingtan Dong (


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We acknowledge Agilent Technologies (China) Co., Ltd.; Bruker (Beijing) Scientific Technology Co., Ltd.; Quantum Design (Beijing) Co., Ltd.; Purency GmbH; Photothermal Spectroscopy Corp.; and WITec (Beijing) Scientific Technology Co., Ltd. for providing technical support. We acknowledge Benedikt Hufnagl, Guiping Chen, Hailong Hu, Jingjing Wang, Lukas Wander, Michael Stibi, Michael Tang, Wanghua Wu, William Zhao, Xi Hu, and Yang Gao for their assistance in this study.


This research was funded by the National Key Research and Development Program (2020YFC1806804).

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Mingtan Dong: conceptualization, methodology, formal analysis, writing—original draft;

Zhenbing She: resources, writing—review and editing;

Xiong Xiong: writing—review and editing;

Guang Ouyang: writing—review and editing;

Zejiao Luo: resources, funding acquisition, writing—review and editing

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Correspondence to Mingtan Dong or Zejiao Luo.

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The authors declare no competing interests.


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Dong, M., She, Z., Xiong, X. et al. Automated analysis of microplastics based on vibrational spectroscopy: are we measuring the same metrics?. Anal Bioanal Chem 414, 3359–3372 (2022).

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