Japan Geoscience Union Meeting 2022

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[E] Oral

M (Multidisciplinary and Interdisciplinary) » M-IS Intersection

[M-IS07] Developments and applications of XRF-core scanning techniques in natural archives

Fri. May 27, 2022 3:30 PM - 5:00 PM 304 (International Conference Hall, Makuhari Messe)

convener:Jyh-Jaan Steven Huang(Institute of Oceanography, National Taiwan University), convener:Atsuko Amano(National institute of Advanced Industrial Science and Technology), Masafumi MURAYAMA(Faculty of Agriculture and Marine Science, Kochi University), convener:Ludvig A Lowemark(National Taiwan University), Chairperson:Jyh-Jaan Steven Huang(Institute of Oceanography, National Taiwan University), Atsuko Amano(National institute of Advanced Industrial Science and Technology), Masafumi MURAYAMA(Faculty of Agriculture and Marine Science, Kochi University), Ludvig A Lowemark(National Taiwan University)

X-ray fluorescence (XRF) core scanning techniques have revolutionized element proxy-based paleo-research over the last decade and have now become an indispensable tool for many research areas. However, despite being fast, non-destructive, and providing records of elemental variations at the submillimeter resolution, science applications of XRF-core scanning results also encounter numerous challenges due to its intrinsically semi-quantitative and ultra-high resolution nature, such as the influences of down-core physical and organic variations, parameter optimizations of machinery, as well as quantitative calibrations and evaluations of the voluminous and complex scanning data. Therefore, the implications of shifts and trends in the elemental data remain difficult to interpret in many settings.
It is therefore considered timely to bring together international specialists using high-resolution XRF-core scanners in all fields of science to present new research, stimulate new collaborations and discussions, as well as to propose new technological developments.

Introduction (3:30 PM - 3:35 PM)

3:55 PM - 4:10 PM

[MIS07-02] Applying machine learning to quantify CaCO3 and TOC data from XRF core scanning spectra of sediment records

★Invited Papers

*Weng-Si Chao1, An-Sheng Lee3,2, Ralf Tiedemann 1, Bernd Zolitschka 2, Sofia Ya Hsuan Liou3, Lester Lembke-Jene1 (1.Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung, Bremerhaven, Germany, 2.University of Bremen, Institute of Geography, Bremen, Germany, 3.National Taiwan University, Department of Geosciences and Research Center for Future Earth, Taipei, Taiwan)

Discussion (4:40 PM - 5:00 PM)

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