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Record W4252745785 · doi:10.5194/acpd-12-28559-2012

Air-snow transfer of nitrate on the East Antarctic Plateau – Part 1: Isotopic evidence for a photolytically driven dynamic equilibrium

2012· preprint· en· W4252745785 on OpenAlexfundno aff
Joseph Erbland, W. C. Vicars, Joël Savarino, Samuel Morin, M. M. Frey, Daniele Frosini, Erwann Vince, Jean Martins

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicCryospheric studies and observations
Canadian institutionsnot available
FundersInstitut national des sciences de l'UniversCentre National de la Recherche ScientifiqueAgence Nationale de la RechercheInstitut Polaire Français Paul Emile VictorAlberta Agricultural Research Institute
KeywordsPlateau (mathematics)NitrateSnowδ18OFractionationChemistryTransectAtmospheric sciencesGeologyStable isotope ratioOceanographyGeomorphologyChromatography

Abstract

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Abstract. Here we report the measurement of the comprehensive isotopic composition (δ15N, Δ17O and δ18O) of nitrate at the air–snow interface at Dome C, Antarctica (DC, 75° 06' S, 123° 19' E) and in snow pits along a transect across the East Antarctic Ice Sheet (EAIS) between 66° S and 78° S. For each of the East Antarctic snow pits in most of which nitrate loss is observed, we derive apparent fractionation constants associated with this loss as well as asymptotic values of nitrate concentration and isotopic ratios below the photic zone. Nitrate collected from snow pits on the plateau have average apparent fractionation constants of (−59±10)‰, (+2.0±1.0)‰ and (+8.7±2.4)‰, for δ15N, Δ17O and δ18O, respectively. In contrast, snow pits sampled on the coast show distinct isotopic signatures with average apparent fractionation constants of (−16±14)‰, (−0.2±1.5)‰ and (+3.1±5.8)‰, for δ15N, Δ17O and δ18O, respectively. From a lab experiment carried out at DC in parallel to the field investigations, we find that the 15N/14N fractionation associated with the physical release of nitrate is (−8.5±2.5)‰, a value significantly different from the modelled estimate previously found for photolysis (−48‰, Frey et al., 2009) when assuming a Rayleigh-type process. Our observations corroborate that photolysis is the dominant nitrate loss process on the East Antarctic Plateau, while on the coast the loss is less pronounced and could involve both physical release and photochemical processes. Year-round isotopic measurements at DC show a close relationship between the Δ17O of atmospheric nitrate and Δ17O of nitrate in skin layer snow, suggesting a photolytically-driven isotopic equilibrium imposed by nitrate recycling at this interface. The 3–4 weeks shift observed for nitrate concentration in these two compartments may be explained by the different sizes of the nitrate reservoirs and by deposition from the atmosphere to the snow. Atmospheric nitrate deposition may lead to fractionation of the nitrogen isotopes and explain the almost constant shift on the order of 25‰ between the δ15N values in the atmospheric and skin layer nitrate at DC. Asymptotic δ15N(NO3−) values and the inverse of snow accumuation rates are correlated (ln(δ15N(as.) + 1) = (5.76±0.47) · (kg m−2 a−1/A) + (0.01±0.02)) confirming the strong relationship between the snow accumulation rate on the residence time of nitrate in the photic zone and the degree of isotopic fractionation, consistent with with previous observations by Freyer et al. (1996). Asymptotic Δ17O(NO3−) values on the plateau are smaller compared to the values found in the skin layer most likely due to oxygen isotope exchange between the nitrate photo-products and water molecules from the surrounding ice. However, the overall fractionation in Δ17O is small thus allowing the preservation of an atmospheric signal.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.092
GPT teacher head0.275
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations4
Published2012
Admission routes1
Has abstractyes

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