Materials science

Polycarbonate

Computer science

Spectral signature

Filter (signal processing)

Substrate (aquarium)

Chemical imaging

Geology

Oceanography

Polypropylene

Polymer

Physics

Microplastics

Optics

Environmental chemistry

Hyperspectral imaging

Polystyrene

Environmental science

Remote sensing

Composite material

Chemistry

Computer vision

Environmental Pollution

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.

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