Characterization of microplastics on filter substrates based on hyperspectral imaging: Laboratory assessments.

Environ Pollut

Marine Biodiversity and Environmental Assessment Research Center, Research Institute for Global Change, Japan Agency for Marine-Earth Science and Technology (JAMSTEC), Yokosuka, 2370061, Japan.

Published: August 2020

AI Article Synopsis

  • Microplastic pollution is a growing environmental concern, prompting the need for effective detection methods.
  • Researchers used near-infrared hyperspectral imaging to identify distinct spectral features of various plastics, allowing for automatic recognition of microplastics.
  • The study highlights the effectiveness of a gold-coated polycarbonate filter and glass fiber filters for detecting microplastics, with a focus on polyethylene, polypropylene, and polystyrene particles as small as 100 μm.

Article Abstract

Microplastic pollution has become an urgent issue because it adversely affects ecosystems. However, efficient methods to detect and characterize microplastic particles are still in development. By conducting a series of laboratory assessments based on near-infrared hyperspectral imaging in the wavelength range of 900-1700 nm, we report the fundamental spectral features of (i) 11 authentic plastics and (ii) 11 filter substrate materials. We found that different plastic polymers showed distinct spectral features at 1150-1250 nm, 1350-1450 nm and 1600-1700 nm, enabling their automatic recognition and identification with spectral separation algorithms. Using an improved hyperspectral imaging system, we demonstrated the detection of three types of microplastic particles, polyethylene, polypropylene and polystyrene, down to 100 μm in diameter. As a filter substrate, a gold-coated polycarbonate filter (GPC0847-BA) showed constant reflectance over 900-1700 nm and a large radiative contrast against loaded plastic particles. Glass fiber filters (GF10 and GF/F) would also be suitable substrates due to their low cost and easy commercial availability. This study provides key parameters for applying hyperspectral imaging techniques for the detection of microplastics.

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Source
http://dx.doi.org/10.1016/j.envpol.2020.114296DOI Listing

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