Glacio-chemical signature of grain boundaries and insoluble particle aggregates in ice core 2D impurity imaging

Identifying, understanding, and constraining post-depositional processes altering the original layer sequence in ice cores is especially needed in order to avoid misinterpretation of the oldest and most highly thinned layers. The record of soluble and insoluble impurities represents an important par...

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Bibliographic Details
Main Authors: Bohleber, Pascal, Stoll, Nicolas, Delmonte, Barbara, Pellilo, Marcello, Roman, Marco, Siddiqi, Kaleem, Stenni, Barbara, Vascon, Sebastiano, Weikusat, Ilka, Barbante, C.
Format: Conference Object
Language:unknown
Published: 2022
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Online Access:https://epic.awi.de/id/eprint/56288/
https://meetingorganizer.copernicus.org/EGU22/EGU22-4492.html
https://hdl.handle.net/10013/epic.eb443d52-9e2f-42f8-b84e-748bb4df9745
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Summary:Identifying, understanding, and constraining post-depositional processes altering the original layer sequence in ice cores is especially needed in order to avoid misinterpretation of the oldest and most highly thinned layers. The record of soluble and insoluble impurities represents an important part of the paleoclimate proxy set in ice cores but is known to be affected post-depositionally through interaction with the ice matrix, diffusion and chemical reactions. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has been recognized for its micron-scale resolution and micro-destructiveness in ice core impurity analysis. Important added value comes from employing LA-ICP-MS for state-of-the-art 2D chemical imaging. The latter has already revealed a close relationship between the ice grain boundary network and impurity signals with a significant soluble component, such as Na. Here we show the latest improvements in 2D chemical imaging with LA-ICP-MS, by increasing the spatial resolution from 35 to 20 and even 10 µm and extending the simultaneous analysis to cover also mostly insoluble impurity species, such as Al. The latter reveal clear signals of insoluble particle aggregates in samples of Greenland ice cores. Combining the chemical images with computer vision-based image analysis allows to separate the geochemical signals of grain boundaries and insoluble particles. Considering intensities as well as elemental ratios, this classification further highlights important differences in the geochemical signals depending on the location of the impurities in the ice matrix. Ultimately, we discuss how this refined approach may serve to investigate post-depositional changes occurring with increasing depth to the soluble and insoluble impurity components, based on grain growth and chemical reactions, respectively.