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Identification of marine microplastics based on laser-induced fluorescence and principal component analysis.
Meng, Xiongfei; Chen, Shimeng; Li, Dongqing; Song, Yongxin; Sun, Lanjun.
Afiliação
  • Meng X; Department of Marine Engineering, Dalian Maritime University, Dalian 116026, China; Department of Navigation and Shipping, ShanDong JiaoTong University, Weihai 264200, China.
  • Chen S; Department of Marine Engineering, Dalian Maritime University, Dalian 116026, China.
  • Li D; Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada.
  • Song Y; Department of Marine Engineering, Dalian Maritime University, Dalian 116026, China. Electronic address: yongxin@dlmu.edu.cn.
  • Sun L; Department of Navigation and Shipping, ShanDong JiaoTong University, Weihai 264200, China.
J Hazard Mater ; 465: 133352, 2024 Mar 05.
Article em En | MEDLINE | ID: mdl-38198873
ABSTRACT
Although the laser-induced fluorescence method shows great potential for microplastic particle detection, overlapping fluorescence signals make accurate type and proportion identification difficult. This paper presents the identification of marine microplastics based on laser-induced fluorescence and principal component analysis. This method works by measuring the fluorescence spectra of water-containing microplastic samples irradiated with a 405-nm laser, which are then analyzed using the principal component analysis (PCA) method. The nine types of microplastics were differentiated based on their positions in the PCA score plot. The mixed sample was positioned between the pure microplastic samples. The component ratio determines its position relative to that of the pure microplastic samples. The first two principal components of the mixed microplastics were linearly dependent. Natural seawater had less influence on the detection, and a mass concentration as low as 0.03% was detected.
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Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article