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Record W1667829866 · doi:10.1021/acs.est.5b01033

Ice Core Perspective on Mercury Pollution during the Past 600 Years

2015· article· en· W1667829866 on OpenAlexaffabout
Samuel Beal, E. C. Osterberg, Christian Zdanowicz, David Fisher

Bibliographic record

VenueEnvironmental Science & Technology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Ottawa
FundersNational Science Foundation
KeywordsIce coreMercury (programming language)Gold rushDeposition (geology)Environmental sciencePeriod (music)PollutionSummitEarth sciencePhysical geographyEnvironmental chemistryAtmospheric sciencesClimatologyGeologyGeographyChemistryArchaeologyEcologyPaleontologySediment

Abstract

fetched live from OpenAlex

Past emissions of the toxic metal mercury (Hg) persist in the global environment, yet these emissions remain poorly constrained by existing data. Ice cores are high-resolution archives of atmospheric deposition that may provide crucial insight into past atmospheric Hg levels during recent and historical time. Here we present a record of total Hg (HgT) in an ice core from the pristine summit plateau (5340 m asl) of Mount Logan, Yukon, Canada, representing atmospheric deposition from AD 1410 to 1998. The Colonial Period (∼1603-1850) and North American "Gold Rush" (1850-1900) represent minor fractions (8% and 14%, respectively) of total anthropogenic Hg deposition in the record, with the majority (78%) occurring during the 20th Century. A period of maximum HgT fluxes from 1940 to 1975 coincides with estimates of enhanced anthropogenic Hg emissions from commercial sources, as well as with industrial emissions of other toxic metals. Rapid declines in HgT fluxes following peaks during the Gold Rush and the mid-20th Century indicate that atmospheric Hg deposition responds quickly to reductions in emissions. Increasing HgT fluxes from 1993 until the youngest samples in 1998 may reflect the resurgence of Hg emissions from unregulated coal burning and small-scale gold mining.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.527
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.015
GPT teacher head0.256
Teacher spread0.241 · 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.

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

Citations76
Published2015
Admission routes2
Has abstractyes

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