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dc.contributor.authorGebregiorgis, Daniel  Concept link
dc.contributor.authorGiosan, Liviu  Concept link
dc.contributor.authorHathorne, Ed C.  Concept link
dc.contributor.authorAnand, Pallavi  Concept link
dc.contributor.authorNilsson-Kerr, Katrina  Concept link
dc.contributor.authorPlass, Anna  Concept link
dc.contributor.authorLuckge, Andreas  Concept link
dc.contributor.authorClemens, Steven C.  Concept link
dc.contributor.authorFrank, Martin  Concept link
dc.date.accessioned2020-06-29T20:44:20Z
dc.date.issued2020-01-12
dc.identifier.citationGebregiorgis, D., Giosan, L., Hathorne, E. C., Anand, P., Nilsson-Kerr, K., Plass, A., Lueckge, A., Clemens, S. C., & Frank, M. (2020). What can we learn from X-ray fluorescence core scanning data? A paleomonsoon case study. Geochemistry Geophysics Geosystems, 21(2), e2019GC008414.en_US
dc.identifier.urihttps://hdl.handle.net/1912/25917
dc.descriptionAuthor Posting. © American Geophysical Union, 2020. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geochemistry, Geophysics, Geosystems 21(2), (2020): e2019GC008414, doi:10.1029/2019GC008414.en_US
dc.description.abstractX‐ray fluorescence (XRF) core scanning of marine and lake sediments has been extensively used to study changes in past environmental and climatic processes over a range of timescales. The interpretation of XRF‐derived element ratios in paleoclimatic and paleoceanographic studies primarily considers differences in the relative abundances of particular elements. Here we present new XRF core scanning data from two long sediment cores in the Andaman Sea in the northern Indian Ocean and show that sea level related processes influence terrigenous inputs based proxies such as Ti/Ca, Fe/Ca, and elemental concentrations of the transition metals (e.g., Mn). Zr/Rb ratios are mainly a function of changes in median grain size of lithogenic particles and often covary with changes in Ca concentrations that reflect changes in biogenic calcium carbonate production. This suggests that a common process (i.e., sea level) influences both records. The interpretation of lighter element data (e.g., Si and Al) based on low XRF counts is complicated as variations in mean grain size and water content result in systematic artifacts and signal intensities not related to the Al or Si content of the sediments. This highlights the need for calibration of XRF core scanning data based on discrete sample analyses and careful examination of sediment properties such as porosity/water content for reliably disentangling environmental signals from other physical properties. In the case of the Andaman Sea, reliable extraction of a monsoon signal requires accounting for the sea level influence on the XRF data.en_US
dc.description.sponsorshipThe staff at the Bremen Core Repository is thanked for their help with core handling and Sam Müller at the University of Kiel provided technical assistance with the XRF scanner. We thank two anonymous reviewers for their insightful comments that improved the manuscript significantly. This work was partially funded through DFG Grant HA 5751/3. P. A. and K. N.‐K. acknowledge support from UK‐IODP and Natural and Environment Research Council, UK. The authors express their thanks to all those who contributed to the success of the National Gas Hydrate Program Expedition 01 (NGHP01) and Expedition 353. The data set supporting the conclusions of this article is available in the PANGEA repository (doi: https://doi.pangaea.de/10.1594/PANGAEA.910533).en_US
dc.publisherAmerican Geophysical Unionen_US
dc.relation.urihttps://doi.org/10.1029/2019GC008414
dc.titleWhat can we learn from X-ray fluorescence core scanning data? A paleomonsoon case studyen_US
dc.typeArticleen_US
dc.description.embargo2020-07-10en_US
dc.identifier.doi10.1029/2019GC008414
dc.embargo.liftdate2020-07-10


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