Issue 5, 2021

Identification of black microplastics using long-wavelength infrared hyperspectral imaging with imaging-type two-dimensional Fourier spectroscopy

Abstract

Despite recent progress in focal plane array Fourier transform infrared spectroscopy (FPA-FT-IR) for automatic microplastic (MP) discrimination, the analysis time is still too long (e.g., 9 h for a sample with a diameter of 47 mm) and the equipment is expensive. As a solution, a hyperspectral camera restricted to the near-infrared or short-wavelength infrared band could be applied. However, with these bands, the minimum discriminable size is only about 100 μm, and discrimination among darkly colored plastics is difficult. The long-wavelength infrared (LWIR) band is reportedly effective for discrimination among darkly colored plastics. In this study, we constructed a palm-sized LWIR hyperspectral camera (105 mm × 90 mm × 50 mm, 1.25 kg) for imaging-type two-dimensional Fourier spectroscopy. Our system used a general-purpose, inexpensive, and compact microbolometer for the LWIR band. This system could record the absorbance of black MPs (polystyrene, polyethylene, and polypropylene) in a 3.8 mm × 3.0 mm area in 36 s, which was less than 1/6th of the time required for FPA-FT-IR. Additionally, our system could obtain spectra for a 12 μm × 12 μm area. Because our device is cheaper and more compact than a FPA-FT-IR, it will be easier to take out in the field or on a research vessel.

Graphical abstract: Identification of black microplastics using long-wavelength infrared hyperspectral imaging with imaging-type two-dimensional Fourier spectroscopy

Supplementary files

Article information

Article type
Paper
Submitted
12 Sep 2020
Accepted
28 Dec 2020
First published
15 Jan 2021
This article is Open Access
Creative Commons BY-NC license

Anal. Methods, 2021,13, 647-659

Identification of black microplastics using long-wavelength infrared hyperspectral imaging with imaging-type two-dimensional Fourier spectroscopy

K. Nogo, K. Ikejima, W. Qi, N. Kawashima, T. Kitazaki, S. Adachi, K. Wada, A. Nishiyama and I. Ishimaru, Anal. Methods, 2021, 13, 647 DOI: 10.1039/D0AY01738H

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