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Record W2051001000 · doi:10.1029/2007jd009510

Mercury concentrations and foliage/atmosphere fluxes in a maple forest ecosystem in Québec, Canada

2008· article· en· W2051001000 on OpenAlexaffabout
Laurier Poissant, Martin Pilote, Emmanuel Yumvihoze, D. R. S. Lean

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of OttawaEnvironment and Climate Change Canada
Fundersnot available
KeywordsMapleMercury (programming language)Environmental scienceFlux (metallurgy)Deposition (geology)Environmental chemistryAceraceaeAtmosphere (unit)ChemistryAtmospheric sciencesHorticultureBotanyBiologyMeteorologyGeologyGeography

Abstract

fetched live from OpenAlex

This paper presents mercury (Hg) concentrations and foliage/atmosphere fluxes in a maple forest ecosystem in southern Québec, Canada. The average total gaseous mercury (TGM) concentration measured at an open field site was significantly (p < 0.001) higher than that measured at an adjacent maple forest site, some 300 m away (1.40 ng m −3 versus 1.03 ng m −3 , respectively). Foliage/atmosphere flux of TGM, measured with a dynamic flux bag device, indicated an average deposition flux of 0.39 ± 0.38 ng m −2 h −1 in the maple tree foliage. Although, bi‐directional Hg fluxes were observed, the compensation point in the maple forest was low (∼0.6 ng m −3 ) explaining a net Hg deposition process at TGM background levels. Foliage mercury concentrations increased from 8.7 ± 1.5 ng g −1 to 30.8 ± 3.0 ng g −1 during the leaf‐growing season. The average Hg deposition flux was in a similar range to the Hg accumulation rate in the maple tree foliage assuming a foliage productivity rate of 220 g m −2 a −1 (i.e., 0.39 versus 0.55 ng m −2 h −1 ). Although significant Hg accumulated in foliage, its transport to non‐organic surface topsoil was not significant. When the uptake of mercury measured in this experiment was extrapolated to include all of the maple forest in North America (12.5 million ha), it amounted potentially to more than 600 kg of mercury per year. This represents approximately 0.5% of mercury emissions in Canada and the United States (approximately 120 metric tons).

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)0.001
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 score0.202
Threshold uncertainty score0.546

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.028
GPT teacher head0.289
Teacher spread0.261 · 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

Citations85
Published2008
Admission routes2
Has abstractyes

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