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Record W2001351643 · doi:10.5194/acp-10-6063-2010

Long range transport of mercury to the Arctic and across Canada

2010· article· en· W2001351643 on OpenAlex
Dorothy Durnford, Ashu Dastoor, D. Figueras-Nieto, Andrei Ryjkov

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAtmospheric chemistry and physics · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsTransCanada (Canada)Environment and Climate Change Canada
FundersMiljøstyrelsenGovernment of Canada
KeywordsSubarctic climateMercury (programming language)Middle latitudesArcticEnvironmental scienceThe arcticLatitudeAtmospheric sciencesChemical transport modelClimatologyCircumpolar starPhysical geographyGeographyTroposphereOceanographyGeology

Abstract

fetched live from OpenAlex

Abstract. This study is the most extensive study to date on the transport of mercury to the Arctic. Moreover, it is the first such study to use a fully-coupled, online chemical transport model, Environment Canada's Global/Regional Atmospheric Heavy Metals model (GRAHM), where the meteorology and mercury processes are fully integrated. It is also the only study to date on the transport of mercury across Canada. We estimated source attribution from Asia, North America, Russia and Europe at six arctic verification stations, as well as three subarctic and eight midlatitude Canadian stations. We have found that Asia, despite having transport efficiencies that were almost always lower than those of North America and often lower than those of Russia, was the dominant source of gaseous atmospheric mercury at all verification stations: it contributed the most mercury (29–37% at all stations, seasons and levels considered), its concentrations frequently explained nearly 100% of the variability in the concentrations produced by the simulation performed with full global emissions, particularly in the absence of local sources, and it generated the most long range transport (LRT) events, causing 43%, 67% and 75% of the events at the arctic, subarctic and midlatitude stations, respectively. For the Arctic, Russian transport efficiencies tended to be the strongest, as expected, while European and Asian efficiencies were lower and higher, respectively, than those found in the literature. This disagreement is likely produced by mercury's long lifetime relative to that of other pollutants. The accepted springtime preference for the trans-Pacific transport of Asian pollution was evident only in the midlatitude group of stations, being masked in the arctic and subarctic groups by the occurrence of atmospheric mercury depletion events. Some neighbouring arctic stations recorded dissimilar numbers of LRT events; despite their proximity, the behaviour of mercury at these stations was governed by different dynamics and transport pathways. The column burden of GEM in the lowest 5 km of the Northern Hemisphere was largest in summer from Asia, North America and Russia, but in winter from Europe. In the vertical, transport of mercury from all source regions occurred principally in the mid-troposphere.

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.

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 score0.152
Threshold uncertainty score0.965

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 head0.006
GPT teacher head0.218
Teacher spread0.213 · 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