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Employing X-ray computed tomography for the non-destructive ice cores analysis
https://doi.org/10.31857/S2076673420020032
Abstract
Computed tomography (CT) is a nondestructive high-resolution way to investigate the three-dimensional structure of samples (ice, rock, etc.). The results of CT analysis of glacial cores consisting of firn and ice extracted on the Western plateau of the Elbrus Mountain (5100–5150 m a.s.l.) in the summer of 2017 are presented in the article. The core taken from the depth of 20.31–21.87 m and consisting of three sections (average length is 52 cm each) was analyzed. In order to maintain the natural negative temperature of the glacial core, a special cryothermos has been created. It conserved the temperature at the level of −25 °C. Data on the structural features of the samples and the three-dimensional pattern of the ice-firn density were obtained. Correlations between the density and some chemical elements had been established. The CT data made it possible also to determine sizes of ice crystals. Comparison of cross sections of cores with firn and ice thin sections (30 in total) has shown that the crystal structure is best displayed in the ice inter-layers since it is impossible to determine reliably sizes of the firn grains at the given survey resolution. Also, the use of the CT method made it possible to determine inclination of the firn layers within the ice core, which is caused by the inheritance of the slope of the surface microrelief and internal inhomogeneities of the firn thickness. Calculations showed that the angle of inclination of the layers varies from 6 to 9°.
About the Authors
A. G. KhairedinovaRussian Federation
Moscow
S. S. Kutuzov
Russian Federation
Moscow
V. N. Mikhalenko
Russian Federation
Moscow
D. V. Korost
Russian Federation
Moscow
A. N. Khomyak
Russian Federation
Moscow
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Supplementary files
For citation: Khairedinova A.G., Kutuzov S.S., Mikhalenko V.N., Korost D.V., Khomyak A.N. Employing X-ray computed tomography for the non-destructive ice cores analysis. Ice and Snow. 2020;60(2):182-191. https://doi.org/10.31857/S2076673420020032
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ISSN 2076-6734 (Print)
ISSN 2412-3765 (Online)