TY - JOUR
T1 - Quantitative in situ mapping of elements in deep-sea hydrothermal vents using laser-induced breakdown spectroscopy and multivariate analysis
AU - Takahashi, Tomoko
AU - Yoshino, Soichi
AU - Takaya, Yutaro
AU - Nozaki, Tatsuo
AU - Ohki, Koichi
AU - Ohki, Toshihiko
AU - Sakka, Tetsuo
AU - Thornton, Blair
N1 - Funding Information:
The project is funded by the Japanese Ministry of Education, Culture, Sports, Science and Technology under the Program for the development of fundamental tools for the utilization of marine resources. We gratefully acknowledge the support from members of the steering panel; T. Takeuchi, T. Fujii, K. Iizasa, the late K. Tamaki, T. Ura, H. Sugimatsu, T. Yamamoto, K. Okino and J. Ishibashi. The study was supported in part by the JSPS Grant-in-Aid for JSPS Fellows (No. 268488 ). The authors thank the Hyper-Dolphin 3000 team and R/V Natsushima and R/V Shinseimaru crew for their assistance during the NT16-01 and KS-18-J03 cruises. We thank A. Matsumoto, M. Yelameli and S. Miyagawa for their support collecting and analysing samples and their help during experiments with ChemiCam, and T. Sato and K. Yasukawa for discussions and advice for analytical methods. The cross-validation and validation dataset, composition data for all measured elements, and raw spectra with calibration data are released with this publication for future benchmark studies: https://github.com/ocean-perception/chemicam_open_database .
Funding Information:
The project is funded by the Japanese Ministry of Education, Culture, Sports, Science and Technology under the Program for the development of fundamental tools for the utilization of marine resources. We gratefully acknowledge the support from members of the steering panel; T. Takeuchi, T. Fujii, K. Iizasa, the late K. Tamaki, T. Ura, H. Sugimatsu, T. Yamamoto, K. Okino and J. Ishibashi. The study was supported in part by the JSPS Grant-in-Aid for JSPS Fellows (No.268488). The authors thank the Hyper-Dolphin 3000 team and R/V Natsushima and R/V Shinseimaru crew for their assistance during the NT16-01 and KS-18-J03 cruises. We thank A. Matsumoto, M. Yelameli and S. Miyagawa for their support collecting and analysing samples and their help during experiments with ChemiCam, and T. Sato and K. Yasukawa for discussions and advice for analytical methods. The cross-validation and validation dataset, composition data for all measured elements, and raw spectra with calibration data are released with this publication for future benchmark studies: https://github.com/ocean-perception/chemicam_open_database.
Publisher Copyright:
© 2020 The Author(s)
PY - 2020/4
Y1 - 2020/4
N2 - 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.
AB - 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.
KW - Deep-sea explorations
KW - In situ chemical analysis
KW - Laser-induced breakdown spectroscopy (LIBS)
KW - Multivariate analysis
KW - Partial least squares regression analysis
KW - Seafloor mineral resources
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UR - http://www.scopus.com/inward/citedby.url?scp=85081237965&partnerID=8YFLogxK
U2 - 10.1016/j.dsr.2020.103232
DO - 10.1016/j.dsr.2020.103232
M3 - Article
AN - SCOPUS:85081237965
SN - 0967-0637
VL - 158
JO - Deep-Sea Research Part I: Oceanographic Research Papers
JF - Deep-Sea Research Part I: Oceanographic Research Papers
M1 - 103232
ER -