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Record W2312416176 · doi:10.1021/es502601z

Determination of Monomethylmercury and Dimethylmercury in the Arctic Marine Boundary Layer

2014· article· en· W2312416176 on OpenAlexafffundabout
Pascale A. Baya, Michel Gosselin, Igor Lehnherr, Vincent L. St. Louis, Holger Hintelmann

Bibliographic record

VenueEnvironmental Science & Technology · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of TorontoUniversité du Québec à RimouskiUniversity of AlbertaTrent University
FundersNetworks of Centres of Excellence of CanadaAboriginal Affairs and Northern Development CanadaNatural Sciences and Engineering Research Council of CanadaArcticNet
KeywordsArcticBiogeochemical cyclePelagic zoneOceanographyEnvironmental chemistryEnvironmental scienceBayDeposition (geology)ChemistryGeology

Abstract

fetched live from OpenAlex

Our understanding of the biogeochemical cycling of monomethylmercury (MMHg) in the Arctic is incomplete because atmospheric sources and sinks of MMHg are still unclear. We sampled air in the Canadian Arctic marine boundary layer to quantify, for the first time, atmospheric concentrations of methylated Hg species (both MMHg and dimethylmercury (DMHg)), and, estimate the importance of atmospheric deposition as a source of MMHg to Arctic land- and sea-scapes. Overall atmospheric MMHg and DMHg concentrations (mean ± SD) were 2.9 ± 3.6 and 3.8 ± 3.1 (n = 37) pg m(-3), respectively. Concentrations of methylated Hg species in the marine boundary layer varied significantly among our sites, with a predominance of MMHg over Hudson Bay (HB), and DMHg over Canadian Arctic Archipelago (CAA) waters. We concluded that DMHg is of marine origin and that primary production rate and sea-ice cover are major drivers of its concentration in the Canadian Arctic marine boundary layer. Summer wet deposition rates of atmospheric MMHg, likely to be the product of DMHg degradation in the atmosphere, were estimated at 188 ± 117.5 ng m(-2) and 37 ± 21.7 ng m(-2) for HB and CAA, respectively, sustaining MMHg concentrations available for biomagnification in the pelagic food web.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.335
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.000
Open science0.0000.001
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 head0.009
GPT teacher head0.241
Teacher spread0.233 · 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

Citations65
Published2014
Admission routes3
Has abstractyes

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