Locations of micro-inclusions identified with Raman spectroscopy in eleven samples (138-1340 m) from the EastGRIP ice core

• Main Authors: Stoll, Nicolas, Weikusat, Ilka, Eichler, Jan
• Format: Dataset
• Language: English
• Published: PANGAEA 2021
• Subjects: Air inclusion; Anatase; AWI_Glac; Binary Object; Blödite; carbonaceous particles; DEPTH; ice/snow; Diversity index; Dolomite; East Greenland Ice-core Project; EastGRIP; EGRIP; Epidote; Feldspar; Glaciology @ AWI; Greenland; Gypsum; Hematite; Holocene; Ice core; ICEDRILL; Ice drill; impurities; Jacobsite; Mica; microscopy; Minerals; luminescence; other; unidentified; Muscovite; Nitrates; Paragonite; Phlogopite; Potassium Sulfate; Prehnite; Pyromorphite; Quartz; Raman spectroscopy; Rutile; Sample code/label; Size; Sodium Nitrates; Sulfate; Titanite; Alfred Wegener Institute; East Greenland; Greenland ice core; Greenland Ice core Project; ice core; Ice Sheet; The Cryosphere
• Online Access: https://doi.pangaea.de/10.1594/PANGAEA.933053; https://doi.org/10.1594/PANGAEA.933053

Micro-inclusions in eleven samples from the upper 1340 m of the East Greenland Ice Core Project ice core in North-East Greenland were analysed with Raman spectroscopy. Ice samples were drilled and processed between 2016 and 2019, Raman analysis was performed between January 2020 and December 2020 at the Alfred Wegener Institute Helmholtz Centre for Polar and Marine Research. The samples are between 1.0 and 14.1 ka yr old and cover the Holocene, Younger Dryas, and Bolling Allerod. Ice sample sizes are usually 10 x 10 mm; micro-inclusions are only a few micrometers large. The first three or four numbers indicate the samples bag, the number after the underscore implies the section of the respective bag. Yellow dots are located micro-inclusions, colored dots are located and measured (with Raman spectroscopy) micro-inclusions. Images point in the direction of the ice sheet surface, i.e. top is upwards. Grain boundaries and inclusions were not totally counted/analysed for EGRIP2286_3 due to a too large amount of inclusions and thus unreliable data. The same set-up was used by Eichler et al. (2019).