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Record W2123738243 · doi:10.5194/acp-11-1405-2011

Quantitative assessment of upstream source influences on total gaseous mercury observations in Ontario, Canada

2011· article· en· W2123738243 on OpenAlexafffundabout
Deyong Wen, John C. Lin, P. K. Gbor, Zhuanshi He, J. J. Sloan

Bibliographic record

VenueAtmospheric chemistry and physics · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCMAQEnvironmental scienceLagrangianAtmospheric sciencesEulerian pathHotspot (geology)MeteorologyAir quality indexGeologyPhysics

Abstract

fetched live from OpenAlex

Abstract. Hourly total gaseous mercury (TGM) concentrations at three monitoring sites (receptors) in Ontario were predicted for four selected periods at different seasons in 2002 using the Stochastic Time-Inverted Lagrangian Transport (STILT) model, which transports Lagrangian air parcels backward in time from the receptors to provide linkages to the source region in the upwind area. The STILT model was modified to deal with Hg deposition and high stack Hg emissions. The model-predicted Hg concentrations were compared with observations at three monitoring sites. Estimates of transport errors (uncertainties in simulated concentrations due to errors in wind fields) are also provided that suggest such errors can reach approximately 10% of simulated concentrations. Results from a CMAQ chemical transport model (CTM) simulation in which the same emission and meteorology inputs were used are also reported. The comparisons show that STILT-predicted Hg concentrations usually agree better with observations than CMAQ except for a subset of cases that are subject to biases in the coarsely resolved boundary conditions. In these comparisons STILT captures high frequency concentration variations better than the Eulerian CTM, likely due to its ability to account for the sub-grid scale position of the receptor site and to minimize numerical diffusion. Thus it is particularly valuable for the interpretation of plumes (short-term concentration variations) that require the use of finer mesh sizes or controls on numerical diffusion in Eulerian models. We report quantitative assessments of the relative importance of different upstream sources for the selected episodes, based on emission fluxes and STILT footprints. The STILT simulations indicate that natural sources (which include re-emission from historical anthropogenic activities) contribute much more than current-day anthropogenic emissions to the Hg concentrations observed at the three sites.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.013
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.207
Teacher spread0.193 · 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 source (direct Gemma or distilled Codex), 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

Citations15
Published2011
Admission routes3
Has abstractyes

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