Quantitative in situ mapping of elements in deep-sea hydrothermal vents using laser-induced breakdown spectroscopy and multivariate analysis

Tomoko Takahashi*, Soichi Yoshino, Yutaro Takaya, Tatsuo Nozaki, Koichi Ohki, Toshihiko Ohki, Tetsuo Sakka, Blair Thornton

*この研究の対応する著者

研究成果査読

10 被引用数 (Scopus)

抄録

This study describes a method to quantify the chemical composition of deep-sea hydrothermal deposits in situ using laser-induced breakdown spectroscopy (LIBS). Partial least squares (PLS) regression analysis is applied to spectra obtained using a long laser pulse with a duration of 150 ns. The number of measurements needed to address the spatial heterogeneity of samples is determined through high-resolution mapping of the elemental distribution in rock samples. PLS applied to laboratory measured seawater-submerged samples achieved an average relative error (RE) of 25% for Cu, Pb, and Zn compared to benchmark concentration values in cross-validation and validation studies, where both the benchmark concentration values and LIBS spectral data are made available with this publication. The PLS model was applied to LIBS signals obtained in situ from hydrothermal deposits at 1000 m depth in the ocean. The results show that target inhomogeneity limits the accuracy of the surface LIBS measurements compared to benchmark values from bulk analysis of samples. Making multiple measurements with small position offsets at each location improves the accuracy of estimates compared to an equivalent number of measurements at a single position. Maps of element distribution generated using quantified in situ data demonstrate how chemical survey outputs can be generated by combining LIBS with multivariate analysis. This enables real-time chemical feedback during deep-sea operations and chemical surveys in situations or with platforms where sample recovery is not possible.

本文言語English
論文番号103232
ジャーナルDeep-Sea Research Part I: Oceanographic Research Papers
158
DOI
出版ステータスPublished - 2020 4

ASJC Scopus subject areas

  • 海洋学
  • 水圏科学

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