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Record W2951699377 · doi:10.1021/acs.est.9b01338

Atmospheric Concentrations and Wet/Dry Loadings of Mercury at the Remote Experimental Lakes Area, Northwestern Ontario, Canada

2019· article· en· W2951699377 on OpenAlexafffundabout
Vincent L. St. Louis, Jennifer A. Graydon, Igor Lehnherr, Helen M. Amos, Elsie M. Sunderland, Kyra A. St. Pierre, Craig A. Emmerton, Ken A. Sandilands, Michael T. Tate, A. Steffen, Elyn Humphreys

Bibliographic record

VenueEnvironmental Science & Technology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsInternational Institute for Sustainable DevelopmentCarleton UniversityEnvironment and Climate Change CanadaUniversity of TorontoUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaFisheries and Oceans CanadaEnvironment and Climate Change CanadaManitoba HydroElectric Power Research Institute
KeywordsThroughfallEnvironmental scienceMercury (programming language)Environmental chemistryTrace gasDeposition (geology)Hydrology (agriculture)Biogeochemical cycleAtmospheric sciencesChemistrySoil waterStructural basinSoil scienceGeology

Abstract

fetched live from OpenAlex

Mercury (Hg) is a global pollutant released from both natural and human sources. Here we compare long-term records of wet deposition loadings of total Hg (THg) in the open to dry deposition loadings of THg in throughfall and litterfall under four boreal mixedwood canopy types at the remote Experimental Lakes Area (ELA) in Northwestern Ontario, Canada. We also present long-term records of atmospheric concentrations of gaseous elemental (GEM), gaseous oxidized (GOM), and particle bound (PBM) Hg measured at the ELA. We show that dry THg loadings in throughfall and litterfall are 2.7 to 6.1 times greater than wet THg loadings in the open. GEM concentrations showed distinct monthly and daily patterns, correlating positively in spring and summer with rates of gross ecosystem productivity and respiration. GOM and PBM concentrations were less variable throughout the year but were highest in the winter, when concentrations of anthropogenically sourced particles and gases were also high. Forest fires, Arctic air masses, and road salt also impacted GEM, GOM, and PBM concentrations at the ELA. A nested GEOS-Chem simulation for the ELA region produced a dry/wet deposition ratio of >5, suggesting that the importance of dry deposition in forested regions can be reasonably modeled by existing schemes for trace gases.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
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
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.000

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 head0.203
Teacher spread0.197 · 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

Citations49
Published2019
Admission routes3
Has abstractyes

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