Skip to main content

Main menu

  • Home
  • Articles
    • Current
    • Special Feature Articles - Most Recent
    • Special Features
    • Colloquia
    • Collected Articles
    • PNAS Classics
    • List of Issues
  • Front Matter
    • Front Matter Portal
    • Journal Club
  • News
    • For the Press
    • This Week In PNAS
    • PNAS in the News
  • Podcasts
  • Authors
    • Information for Authors
    • Editorial and Journal Policies
    • Submission Procedures
    • Fees and Licenses
  • Submit
  • Submit
  • About
    • Editorial Board
    • PNAS Staff
    • FAQ
    • Accessibility Statement
    • Rights and Permissions
    • Site Map
  • Contact
  • Journal Club
  • Subscribe
    • Subscription Rates
    • Subscriptions FAQ
    • Open Access
    • Recommend PNAS to Your Librarian

User menu

  • Log in
  • My Cart

Search

  • Advanced search
Home
Home
  • Log in
  • My Cart

Advanced Search

  • Home
  • Articles
    • Current
    • Special Feature Articles - Most Recent
    • Special Features
    • Colloquia
    • Collected Articles
    • PNAS Classics
    • List of Issues
  • Front Matter
    • Front Matter Portal
    • Journal Club
  • News
    • For the Press
    • This Week In PNAS
    • PNAS in the News
  • Podcasts
  • Authors
    • Information for Authors
    • Editorial and Journal Policies
    • Submission Procedures
    • Fees and Licenses
  • Submit
Research Article

Dating glacier ice of the last millennium by quantum technology

View ORCID ProfileZhongyi Feng, Pascal Bohleber, Sven Ebser, Lisa Ringena, Maximilian Schmidt, Arne Kersting, Philip Hopkins, Helene Hoffmann, Andrea Fischer, View ORCID ProfileWerner Aeschbach, and Markus K. Oberthaler
  1. aKirchhoff-Institute for Physics, Heidelberg University, 69120 Heidelberg, Germany;
  2. bInstitute of Environmental Physics, Heidelberg University, 69120 Heidelberg, Germany;
  3. cInstitute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, 6020 Innsbruck, Austria;
  4. dAlfred Wegener Institute, Helmholtz Center for Polar and Marine Research, 27570 Bremerhaven, Germany;
  5. eHeidelberg Center for the Environment, Heidelberg University, 69120 Heidelberg, Germany

See allHide authors and affiliations

PNAS April 30, 2019 116 (18) 8781-8786; first published April 17, 2019; https://doi.org/10.1073/pnas.1816468116
Zhongyi Feng
aKirchhoff-Institute for Physics, Heidelberg University, 69120 Heidelberg, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Zhongyi Feng
  • For correspondence: iceArTTA@matterwave.de
Pascal Bohleber
bInstitute of Environmental Physics, Heidelberg University, 69120 Heidelberg, Germany;
cInstitute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, 6020 Innsbruck, Austria;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sven Ebser
aKirchhoff-Institute for Physics, Heidelberg University, 69120 Heidelberg, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lisa Ringena
aKirchhoff-Institute for Physics, Heidelberg University, 69120 Heidelberg, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Maximilian Schmidt
aKirchhoff-Institute for Physics, Heidelberg University, 69120 Heidelberg, Germany;
bInstitute of Environmental Physics, Heidelberg University, 69120 Heidelberg, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Arne Kersting
bInstitute of Environmental Physics, Heidelberg University, 69120 Heidelberg, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Philip Hopkins
bInstitute of Environmental Physics, Heidelberg University, 69120 Heidelberg, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Helene Hoffmann
bInstitute of Environmental Physics, Heidelberg University, 69120 Heidelberg, Germany;
dAlfred Wegener Institute, Helmholtz Center for Polar and Marine Research, 27570 Bremerhaven, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Andrea Fischer
cInstitute for Interdisciplinary Mountain Research, Austrian Academy of Sciences, 6020 Innsbruck, Austria;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Werner Aeschbach
bInstitute of Environmental Physics, Heidelberg University, 69120 Heidelberg, Germany;
eHeidelberg Center for the Environment, Heidelberg University, 69120 Heidelberg, Germany
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Werner Aeschbach
Markus K. Oberthaler
aKirchhoff-Institute for Physics, Heidelberg University, 69120 Heidelberg, Germany;
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  1. Edited by Philippe Bouyer, Institut d’Optique, Palaiseau, France, and accepted by Editorial Board Member Angel Rubio March 26, 2019 (received for review October 4, 2018)

  • Article
  • Figures & SI
  • Info & Metrics
  • PDF
Loading

Significance

Alpine summit glaciers have a characteristic age range between 100 and 1,000 years. Reliable dating is the key to access this valuable environmental archive, including the Little Ice Age. Glacier ice contains past air and thus also the rare radioisotope 39Ar, uniquely suitable as an age tracer for this time span. Only argon trap trace analysis (ArTTA), the adaptation of techniques from quantum optics to 39Ar, enables small sample sizes necessary for the application to glacier ice. We present the first dating of glacier ice using less than 2 mL STP of argon from ∼5 kg of ice, finally opening the door for radioargon dating in glaciology.

Abstract

Radiometric dating with 39Ar covers a unique time span and offers key advances in interpreting environmental archives of the last millennium. Although this tracer has been acknowledged for decades, studies so far have been limited by the low abundance and radioactivity, thus requiring huge sample sizes. Atom trap trace analysis, an application of techniques from quantum physics such as laser cooling and trapping, allows us to reduce the sample volume by several orders of magnitude compared with conventional techniques. Here we show that the adaptation of this method to 39Ar is now available for glaciological applications, by demonstrating the entire process chain for dating of alpine glacier ice by argon trap trace analysis (ArTTA). Ice blocks as small as a few kilograms are sufficient and have been obtained at two artificial glacier caves. Importantly, both sites offer direct access to the stratigraphy at the glacier base and validation against existing age constraints. The ice blocks obtained at Chli Titlis glacier at 3,030 m asl (Swiss Alps) have been dated by state-of-the-art microradiocarbon analysis in a previous study. The unique finding of a bark fragment and a larch needle within the ice of Schaufelferner glacier at 2,870 m asl (Stubai Alps, Austria) allows for conventional radiocarbon dating. At both sites the existing age information based on radiocarbon dating and visual stratigraphy corroborates the 39Ar ages. With our results, we establish argon trap trace analysis as the key to decipher so far untapped glacier archives of the last millennium.

  • glacier ice dating
  • argon-39
  • atom trap trace analysis

Nonpolar glaciers are dynamic archives of environmental change, covering altitudes where other climate records are sparse. In particular, the European Alps host a unique juxtaposition of glaciers and other climate archives, in close proximity to both anthropogenic sources of pollutants and the densest network of long instrumental climate records on Earth. However, only a few glaciers of the highest summit regions, typically above 4,000 m above sea level (asl), archive snow and thus past climate signals on a quasi-continuous basis such that a stratigraphic chronology based on layer counting may be obtained. Glaciers at summit locations of lower altitudes are more abundant and have recently been investigated for their potential as climate archives (1). Because periods without net accumulation or even prolonged mass loss can occur at these glaciers, their stratigraphy does not include layers of every single year, making dating by annual layer counting impossible. Hence, age constraints can only be obtained from radiometric methods yielding an absolute age information.

According to the age range accessible by their half-lives, 3H and 210Pb are established tools to constrain the age of glacier ice within the last 100 y (2). Microradiocarbon techniques building on analysis of particulate organic carbon extracted from glacier ice are now available for dating ice samples older than roughly 1,000 y (3, 4), but for ages younger than this, the 14C technique is hampered by ambiguities in the calibration curve as well as limited sample size (5, 6). Likewise as for glaciers in many nonpolar mountain ranges, a substantial part of the ice volume in the European Alps may not reach maximum ages that fall within the range of the 14C technique. Even if the lowermost layer of a glacier can be dated by radiocarbon methods, the larger portion of the stratigraphy is likely to be substantially younger and hence not suitable for the application of 14C. As a result, there is an immediate demand in the glaciological community for radiometric dating of glacier ice within the age range of 100–1,000 y. A particular example is the Little Ice Age period from late 13th to middle 19th century. For climate science, this is a key period for understanding climate variability and well suited for model calibration as instrumental and historical climate data are available for cross validation of climate proxies and model results, in the Alps from about 1500 CE onward (7).

A powerful tracer lies within the air bubbles enclosed in glacier ice: the rare isotope 39Ar. It is a unique tracer with a half-life of 269 y (8), hence matching the time span of 100–1,000 y. The 39Ar is produced by cosmic ray induced spallation of 40Ar in the atmosphere. As such, changes of the cosmic radiation flux over time do affect the atmospheric abundance of 39Ar (9), although these effects are smaller than the current measurement precision. The keys to practical use of the information stored in climate archives of glaciers are small ice samples of the order of kilograms to achieve the required spatial and thus temporal resolution. However, the entrapped gas content and low 39Ar abundance leads to only 2,000–20,000 39Ar atoms contained in 1 kg of modern ice, making quantitative detection extremely difficult.

A much larger number of atoms is required for classical analysis by low-level decay counting, implying the need for significantly larger sample sizes of the order of tons (9, 10). For this reason, environmental routine measurements of 39Ar have until today mainly been confined to groundwater reservoirs, where nearly unlimited sampling is possible, e.g., in ref. 11. A strong reduction in the required sample size has become feasible recently by the method of atom trap trace analysis. This technique utilizes the isotopic shift in optical resonance frequency to capture single atoms of the desired isotopic species. The required multiphoton scattering for this process yields perfect selectivity. It was originally developed for the isotope 81Kr (12) and has been applied in several studies (13). Dating old Antarctic ice has been demonstrated using samples of several hundred kilograms (14).

The adaptation of this method to 39Ar poses two main challenges, namely, the relative abundance that is lower by a factor of 1,000 and the lack of a proper reference isotope. We refer to it as argon trap trace analysis (ArTTA), and its application to environmental studies has been demonstrated with large groundwater (15) and recently with small ocean samples (16). ArTTA is thus the door-opener for broad application of radioargon dating in such research fields as glaciology that have so far been excluded, due to sample size requirements (17).

Site Description and Sample Selection

For the purpose of this study we selected two glacier sites (Fig. 1) offering artificial glacier caves, which make highly controlled sampling of suitable sample sizes for ArTTA possible. The cornice-type summit at Chli Titlis (3,030 m asl, central Switzerland) holds the glacier on its north-facing slope, with a tunnel dug for touristic purposes around 100 m into the ice along bedrock starting at the cable car station (18). Schaufelferner in the Stubai Alps (Austria) is part of the Stubai glacier ski resort and covers altitudes from 3,270 to 2,810 m asl. To enable access for tourists, the glacier cave was drilled close to the cable car station in 2013 CE.

Fig. 1.
  • Download figure
  • Open in new tab
  • Download powerpoint
Fig. 1.

Site maps of (A) Chli Titlis glacier cave and (B) Schaufelferner glacier cave with (C) schematic view of the Schaufelferner ice tunnel and sample locations. Due to the summit location, the ice at the Chli Titlis cave is nearly stagnant, showing horizontal layers allowing straightforward sampling and relative age control via stratigraphy, i.e., older ages at greater depth. The Schaufelferner glacier cave is located downstream of the summit and has undergone substantial ice flow. Inclined layers undisturbed by folding are visible within the cave. The GPS coordinates for Chli Titlis and Schaufelferner are reported in the Swiss grid and Gauss–Krüger system, respectively.

The glacier caves provide direct access to the internal glacier stratigraphy and thus relative age control. The visual stratigraphy of the ice at both sites shows abundant bubble-rich layers of white appearance, with occasional transparent, nearly bubble-free layers originating from refrozen meltwater. Due to the small size of these glaciers, their ice needs to be frozen to bedrock, and hence nearly stagnant, to become of substantial age, i.e., a few hundred years or more. At Chli Titlis cave, ice temperatures are below zero throughout the year aided by artificial cooling. At Schaufelferner cave, initial englacial temperature measurements also revealed ice frozen to bedrock. Continuous temperature monitoring is currently underway to further investigate the spatial distribution of seasonal variability of englacial temperatures. At Chli Titlis and Schaufelferner, ice flow velocities inside the caves (i.e., near bedrock) are close to zero, indicating the presence of old ice. This also means that the locations have remained nearly unchanged between the two sampling campaigns between 2014 and 2018 CE.

Both sites have been the subject of previous glaciological investigations but differ primarily by being located within the nearly stagnant summit region (Chli Titlis) vs. a site having undergone substantial ice flow (Schaufelferner). Accordingly, our sampling strategy was guided by the idea to obtain two samples (i) of neighboring layers significantly different in age (Chli Titlis) and (ii) within a single layer of the same age (Schaufelferner).

At Chli Titlis, ice blocks of ∼4 kg were cut out by chainsaw. The outermost layer exposed to the tunnel was removed before collecting sample blocks to avoid contamination due to cracks or melt water. Microradiocarbon dating revealed a strong vertical age gradient (Fig. 2A). For instance, 14C ages of a profile sampling 1.9 m of the lowermost ice of the glacier range from 1,246 (block 1-2) to 3,138 (block 1-9) y before 2018 CE. For later direct comparison with 39Ar, all calibrated radiocarbon ages have been adjusted to refer to the year 2018 CE as present. Further details regarding the sampling methods and the site characteristics of the Chli Titlis glacier cave can be found in ref. 19. Based on the 14C age constraints, we selected the two youngest ice blocks for our comparison with 39Ar, blocks 1-1 and 1-2.

Fig. 2.
  • Download figure
  • Open in new tab
  • Download powerpoint
Fig. 2.

(A) The sampling site at the summit of Chli Titlis. The wall in the cave shows a distinct horizontal layering, hence no evidence of layer folding. The 14C age constraints reveal a strong vertical age gradient within the sampled depths (19). The two uppermost blocks (1-1 and 1-2) have been analyzed for 39Ar. The results of 527−156+119 y before 2018 CE for the uppermost block 1-1 and 1,126−273+1286 y before 2018 CE for block 1-2 are realistic in view of existing age evidence provided by visual stratigraphy and 14C ages (see Site Description and Sample Selection). (B) Schaufelferner glacier cave. A bark particle (Inset) and a larch needle have been extracted from the wall and allow for macroscopic 14C dating (see ref. 20 for more details). The ice blocks of suitable size used for 39Ar dating have been taken in a later campaign, a few meters apart from the original location. Great care has been applied to select a layer for 39Ar as close as possible to the layer including the organic objects. The 39Ar dating results of 193−55+53 and 198−64+60 y before 2018 CE agree with 14C findings (see Discussion of ArTTA Results).

At Schaufelferner, the ice in the cave has flowed downward from the top yielding tilted layering without folding. A unique feature of this site is the rare finding of two macroscopic particles of organic origin, a bark and a larch needle, inside the ice (Fig. 2B). Both objects have been radiocarbon dated in a previous campaign. The age range obtained from the bark and needle is so far considered the best representation of the actual age of this ice layer (20). For 39Ar analysis, two adjacent blocks were obtained by chainsaw within one layer at the location indicated in Figs. 1C and 2B. The according location is at roughly 4 m horizontal distance from the macroscopic organic particles. The 39Ar sampling location has been chosen as close as possible to the layer containing the organic objects while permitting us to obtain kilogram-size ice blocks of undisturbed, bubble-rich ice. The layers sampled for 39Ar and the organic particles are stratigraphically in close proximity, despite the horizontal distance (as indicated in Fig. 1C).

Discussion of ArTTA Results

To ensure reliable performance of the ArTTA setup for the necessarily small sample sizes, artificial samples of known concentration have been prepared and analyzed. The results are shown in Fig. 3A (see SI Appendix, Table S1, and ref. 21 for more details). Samples with 2 mL STP argon and concentrations of 66, 33, and 10 pmAr have been produced by mixing modern argon with an 39Ar-free sample provided by the dark matter search collaboration, Darkside (22). These results confirm the capability for reliable dating by ArTTA within the age range of 100–1,000 y before 2018 CE.

Fig. 3.
  • Download figure
  • Open in new tab
  • Download powerpoint
Fig. 3.

(A) Proportionality of ArTTA with known samples. Three artificial concentrations have been produced by mixing an 39Ar-free sample with modern argon. The 10 and 33 pmAr samples have been measured once, whereas the mean values of three 66 pmAr and five 100 pmAr measurements (stars) are given (see ref. 21 for more details). The analysis is consistent within the given 1σ confidence interval and confirms the possible dating range of ArTTA. The line of perfect agreement is shown as guide to the eye. (B) Sequence of ice analysis. In weekly measurement runs, the local mean values of several references (stars) are used to infer the concentration of the samples. Background can be neglected for these measurements due to their 10× modern concentration and short measurement time of 2 h. Contrarily, the counts of sample measurements (circles) have to be corrected for background. This parameter is obtained by background measurements with 39Ar-free samples (triangles). To verify the necessary effort for ice sample decontamination, the similar ice blocks 17-1 and 17-2 from Schaufelferner have been prepared by two different approaches to yield samples A and B (Inset).

The glacier ice samples were analyzed by ArTTA; Table 1 provides an overview of all important parameters and measurement results (see SI Appendix, Table S2, for more details). Notably, due to very low air content, the samples of the two ice blocks of Chli Titlis yielded as little as 0.5 mL STP argon. However, count rates were still significantly above background (Materials and Methods) and allowed for reliable measurements.

View this table:
  • View inline
  • View popup
Table 1.

Results of ArTTA of glacier ice samples

The two adjacent ice blocks 17-1 and 17-2 from Schaufelferner were prepared for ArTTA following two different approaches, yielding samples A and B (Fig. 3B, Inset). For the Schaufelferner A sample, the core parts of both blocks were obtained by carefully removing a centimeter-thick layer of every surface exposed to the atmosphere, followed by additional scraping of the cut surface using a microtome. The Schaufelferner B sample combines these removed surface layers and was only cleaned of sections evidently containing refrozen (i.e., clear, bubble-free) ice. The fact that the results of samples A and B are not significantly different indicates that contamination by modern air is unlikely and that simple chainsaw sampling is indeed possible as it does not seem to spoil the radioargon dating.

Regarding the actual dating results of the ArTTA analyses, we performed a comparison with age constraints by 14C, carefully taking into account (i) the different 14C sample types (macroscopic vs. microscopic) and (ii) relative age information provided by the visible stratigraphy in the two caves.

The two ice blocks of Chli Titlis are dated at the far old end of the time span accessible to 39Ar dating. Block 1-1 is 39Ar dated at 527−156+119 y before 2018 CE, where the error is mainly given by finite counting statistics. The adjacent block below, block 1-2, is at least 170 y older, with a best-estimate argon age of 1,126−273+1286 y before 2018 CE. Constraints on the age by 14C dating exist only for block 1-2, where we obtain 1,246–1,378 y before 2018 CE (SI Appendix, Fig. S1). It is important to note that no macroscopic organic fragments were found at Chli Titlis, and all 14C analyses had to be performed on microscopic particulate organic carbon, for which known biases toward older ages can exist. Following the discussion of potential reservoir effects in ref. 3, the 14C age is thus regarded as upper age limit (19). Additionally, important relative age control is provided by the evident near-horizontal layering; that is, older ice is located at greater depth (Fig. 2A). The 14C results revealed that age differences of several hundred years occur at close range, even between two adjacent blocks. The large age gradient in the lowermost ice layers is not necessarily connected to layer thinning by deformation but can instead result from past hiatuses in glacier growth or intermittent melting periods (19). In this context, the 39Ar ages agree with what is known to date about the Chli Titlis glacier cave, namely, (i) that age differences of up to several hundred years can occur even between two adjacent blocks of ∼20 cm height and (ii) that the 39Ar age of 1,126−273+1286 y of block 1-2 is a match against the lower carbon age limit of 1,246 y before 2018 CE. The 39Ar age for block 1-1 of 527−156+119 y adds information and is consistent with the already known vertical age gradient connected to the intermittent ice build-up process.

At Schaufelferner glacier cave, the 39Ar results of samples A and B are consistent and reveal layer ages of 193−55+53 and 198−64+60 y before 2018 CE, respectively. The uncertainty in the conventional macroscopic 14C dating of the bark particle and larch needle is caused primarily by ambiguities in calibration of 14C ages within the respective time period. Using OxCal v4.3.2 (23) and the IntCal13 atmospheric calibration curve (6), the most likely age ranges assigned to the bark particle and the larch needle are 375–532 and 505–632 y before 2018 CE at 68 and 48% probability (SI Appendix, Figs. S2 and S3), respectively (20). Regardless of the calibration issue, the 14C age range of the macroscopic organic particles has to be considered as an upper estimate of the age of the glacier ice. This is due to the potential delay in deposition on the glacier surface after creation of the macroscopic organic fragments, e.g., death of the respective tree. No such age offset exists for 39Ar. In contrast to what is known from polar studies regarding systematic age offsets between the enclosed air and ambient ice matrix (24), no significant effect in this regard is expected within the 39Ar dating uncertainty. This is due to the rapid formation of ice at our study sites, typically of the order of a decade or less (25). Taking the most probable calibrated 14C range for comparison with 39Ar results in a difference of at least 85 y between the 14C and the 39Ar ages. This age difference is well within what can be explained based on glaciological considerations. The 39Ar and 14C dating results refer to neighboring layers. Likewise as for Chli Titlis, an age difference of the order of decades is reasonable at Schaufelferner due to hiatuses and melting periods.

Based on our results we find no evidence of contamination related to our sampling method by chainsaw. Thus, sampling is comparatively simple allowing us to obtain blocks of convenient size of ∼5 kg. The results of Chli Titlis and Schaufelferner are a demonstration of conclusive 39Ar dating of glacier ice with samples containing less than 2 mL STP argon. In concert with evidence provided by the visual stratigraphy, the comparison with 14C age constraints corroborates the ArTTA age dating method, both for its midend (Schaufelferner) and far-end (Chli Titlis) age range. At Chli Titlis, the 39Ar dating results show an age range and a vertical age gradient that reproduce and extend earlier findings obtained from 14C. For Schaufelferner, the most likely age ranges assigned by 14C dating of macroscopic organic objects are determined systematically older than the 39Ar dates but stay within a range that can be explained based on glaciological considerations. Furthermore, both 39Ar and 14C ages indicate that the ice at Schaufelferner is likely a remnant of the 1850 glacier maximum. The 39Ar dating tool provides a more reliable age constraint in this case, considering the ambiguity associated with the 14C age calibration. Thus, the ice in the Schaufelferner cave originates from the Little Ice Age maximum state.

The Future of Glacier Ice Dating with ArTTA

Since glaciers at other nonpolar mountain ranges, e.g., Central Asia, Himalaya, or Andes, are not much different from the Alps regarding their glaciological characteristics, e.g., size, accumulation, and englacial temperature, the impact of this study goes beyond the Alpine realm. However, the European Alps can provide a unique combination of (i) glaciers featuring expected age ranges suitable for 39Ar, (ii) access to kilogram-size ice samples at low cost through excellent infrastructure, and (iii) availability of multiproxy reconstructions of Holocene climate. With the introduction of the ArTTA ice dating technique, we can retrieve hitherto untapped paleoclimate records and validate them in the nexus of European archives. The main scientific potential of 39Ar dating of glacier ice is the interpretation of the ice layers formed during the last millennium, to reveal the past history of summit glacier growth in the Alps. This history includes a fundamental gap in knowledge in the context of the highly complex climate patterns during the core period of the Little Ice Age. It should be noted that in contrast to other glaciological dating methods such as surface exposure dating or the dating of wood fragments, 39Ar offers a radiometric dating technique of the glacier ice itself. Thus, it can be applied not only at glacier tongues but also at summits with access to cold stagnant ice. Here the ice has undergone no or very little ice flow, which substantially reduces uncertainties in the interpretation of the dating results. Even the analysis of ice dynamics during the last centuries can be done with 39Ar by sampling along the central flow line of a glacier. Past ice dynamics can be considered an important but fairly unknown parameter governing the reaction of glaciers to climate change. Accordingly, developing the full potential of dating by 39Ar will provide new opportunities for glaciological and glacier-based paleoclimatic research.

Because the glacier surface above both the Chli Titlis and Schaufelferner glacier caves is shrinking rapidly, it is seasonally covered by sheets to minimize summer ice melt. This provides clear evidence of prolonged negative mass balance and illustrates how current warming conditions pose an immediate threat to losing the precious information stored in such glaciers. In this respect, the dating tool of 39Ar arrives just in time in modern glaciological research. It also generates a broader impact in the field of Holocene climate science and other environmental research fields. Similar to the introduction of accelerator mass spectrometry for radiocarbon dating, the ArTTA technology opens application fields for 39Ar dating, including glacier ice. In this sense, the 39Ar dating technology has the potential to yield major scientific advances in our understanding of several environmental systems and paleoclimate archives.

Materials and Methods

Ice Processing and Argon Extraction.

The ice blocks were transported from the glaciers to a −20 °C cold storage at Heidelberg University. Before the extraction, they were cleaned by cutting off melted layers. Ice blocks of up to 8 kg were then put into a 12.6 L stainless steel container which was evacuated with a turbomolecular pump. The ice was melted and the gas was extracted by freezing it through a water trap onto a liquid nitrogen cooled activated charcoal trap.

ArTTA is highly selective and thus immune to impurities due to other elements. Still, a high argon purity and yield was desired to maximize the counting efficiency and minimize the sample amount. For this purpose, a specific argon purification system had been designed. The gas composition was analyzed with a quadrupole mass spectrometer before the gas was transferred to a 900 °C titanium sponge getter. With that, all gases were removed except for noble gases and hydrogen. At a second titanium sponge getter at room temperature the hydrogen was adsorbed, and the remaining gas fraction, consisting of >99% argon, was captured on a charcoal trap and transported to the ArTTA setup. With this system, an ice sample was processed within 4 h with an argon recovery rate of >98%.

ArTTA Setup.

A simplified scheme of the ArTTA apparatus is shown in Fig. 4. The purified Ar gas of the ice sample is first compressed into a buffer volume to compensate for different sample sizes while obtaining a constant flow into the main apparatus. Laser cooling is building on strong closed dipole transitions, which are available for metastable argon (Ar*). Thus, metastable argon is produced in an RF-discharge source. Liquid nitrogen cooling is applied to reduce the initial velocity of the atoms.

Fig. 4.
  • Download figure
  • Open in new tab
  • Download powerpoint
Fig. 4.

Setup of ArTTA. At location 1, the sample is compressed into a buffer to compensate for different sample volumes. At location 2, argon is excited into a metastable state for convenient optical transitions at 812 nm. At location 3, transversal laser cooling is applied to increase the 39Ar flux into the detection region. At location 4, 40Ar is deexcited to the ground state and provides a signal for flux monitoring. At location 5, longitudinal laser cooling slows the thermal atoms down to tens of meters per second. At location 6, single 39Ar atoms are captured in a magnetooptical trap, and the fluorescence is monitored by a photo diode. At location 7, several turbomolecular pumps (TMP) collect the gas from the apparatus. The sample is cleaned by a getter pump and is recompressed to the buffer volume. At location 8, enriched 39Ar outgasses from the vacuum walls and contaminates the sample. This effect scales with volume and limits the analysis for smaller samples.

The flux into the small detection region is increased by two transversal laser cooling stages. The first stage collects the divergent atoms from the effusive source and collimates them to a beam, whereas the second stage compresses the beam. Subsequently, the longitudinal velocity is reduced from thermal velocities to a few meters per second by a Zeeman slower. Single 39Ar atoms are finally captured and detected in a magnetooptical trap, thus guaranteeing perfect selectivity by millions of resonant photon scattering processes in a spatially confined region. To reduce the off-resonant scattering of the huge isotopic background of abundant 40Ar in the detection region, this isotope is selectively deexcited from the metastable state to the ground state by an additional quench laser. The fluorescence of this process provides a direct signal for flux monitoring.

Several turbomolecular pumps realize the necessary ultrahigh vacuum in the apparatus. Their collected gas is cleaned with a nonevaporative getter by removing any nonnoble gas contributions. The restored gas is compressed into the buffer volume again, thus enabling full recycling of the sample. With this procedure the required sample size is as low as 0.5 mL STP.

The sample size of the current ArTTA setup is limited by outgassing of embedded argon enriched in 39Ar. The contribution due to this contamination is dependent on sample size, concentration, and measurement time. A correction of about 10 pmAr is expected for a volume of 2 mL STP in a 20-h measurement.

Measurement Procedure.

ArTTA is currently capable of analyzing one sample per day with relative accuracy dependent on the actual concentration. A full measurement cycle starts with ∼20 h of sample measurement. This is directly followed by ∼2 h of referencing to an artificial sample with 10× enriched 39Ar compared with modern concentration. The apparatus is flushed with a krypton discharge while refilling the liquid nitrogen reservoir to remove any frozen content on the source and reduce cross sample contamination. Each sample is framed by at least two reference measurements, but more can be used if appropriate, e.g., weekly averages. It is this temporally local referencing which makes the measurement robust against long-term drifts (see ref. 21 for more details).

Data Processing.

To infer the sample concentration from the number of atoms detected, careful estimate of the background is necessary. The contribution due to embedded argon enriched in 39Ar can be determined by background measurements with 39Ar-free samples (22). This long-term memory effect is described by a constant outgassing of 39Ar yielding a time-dependent concentrationc(t)=csample+aoutVsamplet

with sample concentration csample, sample volume Vsample, and 39Ar outgassing rate aout. By integration over time, the detected total atom number Ntot is given byNtot=[csamplet+12aoutVsamplet2]λ0

with λ0 describing the count rate of a sample with modern concentration. This parameter is inferred from measurements of reference samples with 10× modern 39Ar concentration.

The model is used in a Bayesian analysis to obtain the probability density function for the sample concentration. The reported concentrations are the extracted most probable values and the uncertainties correspond to the 1σ confidence interval containing 68.3% of measurements (see ref. 21 for more details).

Notably, the contribution to the detected atoms due to the background is increasing quadratically in time, which limits the integration time and thus the accuracy of the inferred concentration.

Accuracy and Limit.

To show the potential of our apparatus, we perform numerical simulations of the current measurement routine by using the experimentally determined parameters λ0 and 39Ar outgassing rate aout. For each given concentration, the references and background as well as a total number of counted atoms have been generated numerically in 10,000 Monte Carlo simulations and analyzed in the same way as measured data. The most probable values of the inferred concentrations are shown in Fig. 5 by indicating the mode of this distribution as well as 1σ, 2σ, and 3σ intervals containing 68.3, 95.5, and 99.7% of the values, respectively. The contribution by the embedded contamination is especially dominant for small sample sizes and low concentrations. For the case of 0.5 mL STP samples and below 8 pmAr, the background cannot be statistically distinguished in most of the measurements, but a single measurement can yield concentrations significantly, i.e., 1σ, above zero (see ref. 21 for more details).

Fig. 5.
  • Download figure
  • Open in new tab
  • Download powerpoint
Fig. 5.

Simulated accuracy for 0.5-mL STP samples. For each given concentration, 10,000 Monte Carlo simulations of the here employed measurement routine have been performed using the experimentally determined parameters, i.e., outgassing rate and modern count rate. This yields distributions of the most probable values of the inferred concentrations indicated by the mode and SD. The range for measurable concentrations is exceeded as soon as the background contribution cannot be statistically distinguished anymore. For samples of 0.5 mL STP, this is the case for most measurements below 8 pmAr (Inset).

Acknowledgments

We thank V. Rädle for carefully reading the manuscript. We further thank the Bergbahnen Titlis-Engelberg and the Stubai Glacier ski resort for their assistance in logistics. This work was supported by the Deutsche Forschungsgemeinschaft in two joint projects (OB 164/11-1, AE 93/14-1, and OB 164/12-1, AE 93/17-1) and the Austrian Science Fund project Cold Ice (P29256-N36) as well as by the European Research Commission Advanced Grant EntangleGen (Project ID 694561).

Footnotes

  • ↵1To whom correspondence may be addressed. Email: iceArTTA{at}matterwave.de.
  • Author contributions: Z.F., P.B., L.R., M.S., A.K., P.H., A.F., W.A., and M.K.O. performed research; Z.F., P.B., S.E., and H.H. analyzed data; and Z.F., P.B., S.E., L.R., M.S., A.K., P.H., H.H., A.F., W.A., and M.K.O. wrote the paper.

  • The authors declare no conflict of interest.

  • This article is a PNAS Direct Submission. P.B. is a guest editor invited by the Editorial Board.

  • This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1816468116/-/DCSupplemental.

Published under the PNAS license.

References

  1. ↵
    1. Haeberli W,
    2. Frauenfelder R,
    3. Kääb A,
    4. Wagner S
    (2004) Characteristics and potential climatic significance of “miniature ice caps” (crest-and cornice-type low-altitude ice archives). J Glaciol 50:129–136.
    OpenUrl
  2. ↵
    1. Gäggeler H,
    2. Von Gunten H,
    3. Rössler E,
    4. Oeschger H,
    5. Schotterer U
    (1983) 210Pb-Dating of cold alpine firn/ice cores from Colle Gnifetti, Switzerland. J Glaciol 29:165–177.
    OpenUrl
  3. ↵
    1. Hoffmann H, et al.
    (2018) A new sample preparation system for Micro-14C dating of glacier ice with a first application to a high Alpine ice core from Colle Gnifetti (Switzerland). Radiocarbon 60:517–533.
    OpenUrl
  4. ↵
    1. Uglietti C, et al.
    (2016) Radiocarbon dating of glacier ice: Overview, optimisation, validation and potential. Cryosphere 10:3091–3105.
    OpenUrl
  5. ↵
    1. Ramsey CB
    (1995) Radiocarbon calibration and analysis of stratigraphy: The OxCal program. Radiocarbon 37:425–430.
    OpenUrlCrossRef
  6. ↵
    1. Reimer PJ, et al.
    (2013) IntCal13 and Marine13 radiocarbon age calibration curves 0–50,000 years cal BP. Radiocarbon 55:1869–1887.
    OpenUrlCrossRef
  7. ↵
    1. Dobrovolny P, et al.
    (2010) Monthly, seasonal and annual temperature reconstructions for Central Europe derived from documentary evidence and instrumental records since AD 1500. Clim Change 101:69–107.
    OpenUrl
  8. ↵
    1. Stoenner RW,
    2. Schaeffer OA,
    3. Katcoff S
    (1965) Half-lives of Argon-37, Argon-39, and Argon-42. Science 148:1325–1328.
    OpenUrlAbstract/FREE Full Text
  9. ↵
    1. Loosli H
    (1983) A dating method with 39Ar. Earth Planet Sci Lett 63:51–62.
    OpenUrl
  10. ↵
    1. Oeschger H,
    2. Stauffer P,
    3. Bucher P,
    4. Moell M
    (1976) Extraction of trace components from large quantities of ice in bore holes. J Glaciol 17:117–128.
    OpenUrl
  11. ↵
    1. Corcho Alvarado JA, et al.
    (2007) Constraining the age distribution of highly mixed groundwater using 39Ar: A multiple environmental tracer (3H/3He, 85Kr, 39Ar, and 14C) study in the semiconfined Fontainebleau Sands Aquifer (France). Water Resour Res 43:W03427.
    OpenUrl
  12. ↵
    1. Chen CY, et al.
    (1999) Ultrasensitive isotope trace analyses with a magneto-optical trap. Science 286:1139–1141.
    OpenUrlAbstract/FREE Full Text
  13. ↵
    1. Lu ZT, et al.
    (2014) Tracer applications of noble gas radionuclides in the geosciences. Earth Sci Rev 138:196–214.
    OpenUrl
  14. ↵
    1. Buizert C, et al.
    (2014) Radiometric 81Kr dating identifies 120,000-year-old ice at Taylor Glacier, Antarctica. Proc Natl Acad Sci USA 111:6876–6881.
    OpenUrlAbstract/FREE Full Text
  15. ↵
    1. Ritterbusch F, et al.
    (2014) Groundwater dating with Atom Trap Trace Analysis of 39Ar. Geophys Res Lett 41:6758–6764.
    OpenUrlCrossRef
  16. ↵
    1. Ebser S, et al.
    (2018) 39Ar dating with small samples provides new key constraints on ocean ventilation. Nat Commun 9:5046.
    OpenUrl
  17. ↵
    1. Collon P,
    2. Kutschera W,
    3. Lu ZT
    (2004) Tracing noble gas radionuclides in the environment. Annu Rev Nucl Part Sci 54:39–67.
    OpenUrl
  18. ↵
    1. Lorrain R,
    2. Haeberli W
    (1990) Climatic change in a high-altitude alpine area suggested by the isotopic composition of cold basal glacier ice. Ann Glaciol 14:168–171.
    OpenUrl
  19. ↵
    1. Bohleber P,
    2. Hoffmann H,
    3. Kerch J,
    4. Sold L,
    5. Fischer A
    (2018) Investigating cold based summit glaciers through direct access to the glacier base: A case study constraining the maximum age of Chli Titlis glacier, Switzerland. Cryosphere 12:401–412.
    OpenUrl
  20. ↵
    1. Hoffmann HM
    (2016) Micro radiocarbon dating of the particulate organic carbon fraction in Alpine glacier ice: Method refinement, critical evaluation and dating applications. PhD thesis (Heidelberg University, Heidelberg, Germany).
  21. ↵
    1. Ebser SC
    (2018) Dating of ice and ocean samples with Atom Trap Trace Analysis of 39Ar. PhD thesis (Heidelberg University, Heidelberg, Germany).
  22. ↵
    1. Agnes P, et al.
    (2016) Results from the first use of low radioactivity argon in a dark matter search. Phys Rev D 93:081101.
    OpenUrl
  23. ↵
    1. Bronk Ramsey C
    (2017) OxCal Version 4.3.2. Available at https://c14.arch.ox.ac.uk/oxcal.html. Accessed April 12, 2019.
  24. ↵
    1. Sowers T,
    2. Bender M,
    3. Raynaud D,
    4. Korotkevich YS
    (1992) δ15N of N2 in air trapped in polar ice: A tracer of gas transport in the firn and a possible constraint on ice age-gas age differences. J Geophys Res 97:15683–15697.
    OpenUrl
  25. ↵
    1. Ambach W,
    2. Eisner H
    (1966) Analysis of a 20 m. firn pit on the Kesselwandferner (Ötztal Alps). J Glaciol 6:223–231.
    OpenUrl
PreviousNext
Back to top
Article Alerts
Email Article

Thank you for your interest in spreading the word on PNAS.

NOTE: We only request your email address so that the person you are recommending the page to knows that you wanted them to see it, and that it is not junk mail. We do not capture any email address.

Enter multiple addresses on separate lines or separate them with commas.
Dating glacier ice of the last millennium by quantum technology
(Your Name) has sent you a message from PNAS
(Your Name) thought you would like to see the PNAS web site.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Citation Tools
Dating glacier ice of the last millennium by quantum technology
Zhongyi Feng, Pascal Bohleber, Sven Ebser, Lisa Ringena, Maximilian Schmidt, Arne Kersting, Philip Hopkins, Helene Hoffmann, Andrea Fischer, Werner Aeschbach, Markus K. Oberthaler
Proceedings of the National Academy of Sciences Apr 2019, 116 (18) 8781-8786; DOI: 10.1073/pnas.1816468116

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Request Permissions
Share
Dating glacier ice of the last millennium by quantum technology
Zhongyi Feng, Pascal Bohleber, Sven Ebser, Lisa Ringena, Maximilian Schmidt, Arne Kersting, Philip Hopkins, Helene Hoffmann, Andrea Fischer, Werner Aeschbach, Markus K. Oberthaler
Proceedings of the National Academy of Sciences Apr 2019, 116 (18) 8781-8786; DOI: 10.1073/pnas.1816468116
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Tweet Widget
  • Facebook Like
  • Mendeley logo Mendeley

Article Classifications

  • Physical Sciences
  • Environmental Sciences
Proceedings of the National Academy of Sciences: 116 (18)
Table of Contents

Submit

Sign up for Article Alerts

Jump to section

  • Article
    • Abstract
    • Site Description and Sample Selection
    • Discussion of ArTTA Results
    • The Future of Glacier Ice Dating with ArTTA
    • Materials and Methods
    • Acknowledgments
    • Footnotes
    • References
  • Figures & SI
  • Info & Metrics
  • PDF

You May Also be Interested in

Setting sun over a sun-baked dirt landscape
Core Concept: Popular integrated assessment climate policy models have key caveats
Better explicating the strengths and shortcomings of these models will help refine projections and improve transparency in the years ahead.
Image credit: Witsawat.S.
Model of the Amazon forest
News Feature: A sea in the Amazon
Did the Caribbean sweep into the western Amazon millions of years ago, shaping the region’s rich biodiversity?
Image credit: Tacio Cordeiro Bicudo (University of São Paulo, São Paulo, Brazil), Victor Sacek (University of São Paulo, São Paulo, Brazil), and Lucy Reading-Ikkanda (artist).
Syrian archaeological site
Journal Club: In Mesopotamia, early cities may have faltered before climate-driven collapse
Settlements 4,200 years ago may have suffered from overpopulation before drought and lower temperatures ultimately made them unsustainable.
Image credit: Andrea Ricci.
Steamboat Geyser eruption.
Eruption of Steamboat Geyser
Mara Reed and Michael Manga explore why Yellowstone's Steamboat Geyser resumed erupting in 2018.
Listen
Past PodcastsSubscribe
Birds nestling on tree branches
Parent–offspring conflict in songbird fledging
Some songbird parents might improve their own fitness by manipulating their offspring into leaving the nest early, at the cost of fledgling survival, a study finds.
Image credit: Gil Eckrich (photographer).

Similar Articles

Site Logo
Powered by HighWire
  • Submit Manuscript
  • Twitter
  • Facebook
  • RSS Feeds
  • Email Alerts

Articles

  • Current Issue
  • Special Feature Articles – Most Recent
  • List of Issues

PNAS Portals

  • Anthropology
  • Chemistry
  • Classics
  • Front Matter
  • Physics
  • Sustainability Science
  • Teaching Resources

Information

  • Authors
  • Editorial Board
  • Reviewers
  • Subscribers
  • Librarians
  • Press
  • Site Map
  • PNAS Updates
  • FAQs
  • Accessibility Statement
  • Rights & Permissions
  • About
  • Contact

Feedback    Privacy/Legal

Copyright © 2021 National Academy of Sciences. Online ISSN 1091-6490