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Amount, Sources, and Dissolution of Aerosol Trace Elements in the Canadian Arctic

2021· article· en· W3203260454 on OpenAlexafffundabout
Joan De Vera, Priyanka Chandan, William M. Landing, Geoff W. Stupple, A. Steffen, Bridget A. Bergquist

Bibliographic record

VenueACS Earth and Space Chemistry · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicArctic and Antarctic ice dynamics
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsArcticEnvironmental scienceAerosolGeotracesOceanographyEnvironmental chemistryDissolutionSeawaterPollutionSulfateAtmospheric sciencesGeologyChemistryMeteorologyGeographyEcology

Abstract

fetched live from OpenAlex

Atmospheric deposition is an important source of trace elements (TEs) to the Arctic, including both anthropogenic (e.g., Pb) and micronutrient (e.g., Fe) metals. This study measured TE loadings, Pb isotopes, and dissolution in aerosols collected at Alert, Nunavut, Canada, from spring to summer of 2013 and 2014 and during the Canadian Arctic GEOTRACES Cruises (GN02 and GN03) in the summer of 2015. The aerosol loadings were 5–8 times higher and more enriched with anthropogenic metals (Pb and Cd) in the spring than in the summer consistent with the Arctic haze phenomenon. Pb isotopes reveal that Russia, Europe, and China were the likely source regions of this pollution in spring. Comparison of the Pb and Cd concentrations and Pb isotope data with previous studies suggests that atmospheric pollution in the Canadian Arctic has been relatively stable for the last couple of decades. Dissolution experiments were also performed to estimate the fraction of aerosol TEs that can potentially be dissolved and become bioavailable in seawater. The minimum and maximum dissolution estimates for Fe were 8 ± 5 and 65 ± 20%, respectively, which translate to a potential input of 5–40 kT year–1 of dissolvable Fe to the Canada Basin of the Arctic Ocean, comparable to the riverine Fe input (10–20 kT year–1) from Mackenzie River. Thus, aerosols could be an important Fe source to Arctic surface waters, especially with decreasing sea ice coverage, changes in stratification and in places far from shelf and river sources.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score0.945

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.007
GPT teacher head0.188
Teacher spread0.181 · 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 teacher head, 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

Citations8
Published2021
Admission routes3
Has abstractyes

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