Literature DB >> 32222664

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

Chunmao Zhu1, Yugo Kanaya2, Ryota Nakajima3, Masashi Tsuchiya3, Hidetaka Nomaki4, Tomo Kitahashi3, Katsunori Fujikura3.   

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.
Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.

Entities:  

Keywords:  Filter substrate; Hyperspectral imaging; Microplastics; Minimum detection size; Near-infrared

Mesh:

Substances:

Year:  2020        PMID: 32222664     DOI: 10.1016/j.envpol.2020.114296

Source DB:  PubMed          Journal:  Environ Pollut        ISSN: 0269-7491            Impact factor:   8.071


  6 in total

1.  Label-free identification of microplastics in human cells: dark-field microscopy and deep learning study.

Authors:  Ilnur Ishmukhametov; Läysän Nigamatzyanova; Gӧlnur Fakhrullina; Rawil Fakhrullin
Journal:  Anal Bioanal Chem       Date:  2021-10-31       Impact factor: 4.142

2.  Classification and distribution of freshwater microplastics along the Italian Po river by hyperspectral imaging.

Authors:  Ludovica Fiore; Silvia Serranti; Cristina Mazziotti; Elena Riccardi; Margherita Benzi; Giuseppe Bonifazi
Journal:  Environ Sci Pollut Res Int       Date:  2022-02-23       Impact factor: 5.190

3.  Optimization of a hyperspectral imaging system for rapid detection of microplastics down to 100 µm.

Authors:  Chunmao Zhu; Yugo Kanaya; Masashi Tsuchiya; Ryota Nakajima; Hidetaka Nomaki; Tomo Kitahashi; Katsunori Fujikura
Journal:  MethodsX       Date:  2020-12-08

Review 4.  Advanced microplastic monitoring using Raman spectroscopy with a combination of nanostructure-based substrates.

Authors:  Nguyễn Hoàng Ly; Moon-Kyung Kim; Hyewon Lee; Cheolmin Lee; Sang Jun Son; Kyung-Duk Zoh; Yasser Vasseghian; Sang-Woo Joo
Journal:  J Nanostructure Chem       Date:  2022-06-18

5.  Probing nanoplastics derived from polypropylene face masks with hyperspectral dark-field microscopy.

Authors:  Svetlana Batasheva; Farida Akhatova; Nail Abubakirov; Rawil Fakhrullin
Journal:  Sci Total Environ       Date:  2022-09-06       Impact factor: 10.753

6.  Nanomechanical Atomic Force Microscopy to Probe Cellular Microplastics Uptake and Distribution.

Authors:  Farida Akhatova; Ilnur Ishmukhametov; Gölnur Fakhrullina; Rawil Fakhrullin
Journal:  Int J Mol Sci       Date:  2022-01-12       Impact factor: 5.923

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.