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Record W2101724193 · doi:10.1071/en12164

In search of potential source regions of semi-volatile organic contaminants in air in the Yukon Territory, Canada from 2007 to 2009 using hybrid receptor models

2013· article· en· W2101724193 on OpenAlexafffundabout
John N. Westgate, Uwayemi M. Sofowote, Pat Roach, Phil Fellin, Ivy D’Sa, Ed Sverko, Yushan Su, Hayley Hung, Frank Wania

Bibliographic record

VenueEnvironmental Chemistry · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsEnvironment and Climate Change CanadaDairy Farmers of OntarioMcMaster UniversityAir CanadaAboriginal Affairs Northern Dev CanadaUniversity of Toronto
FundersAboriginal Affairs and Northern Development CanadaGovernment of Ontario
KeywordsContext (archaeology)Environmental scienceContaminationEnvironmental chemistryPlumeTrajectoryMeteorologyChemistryEcologyGeographyArchaeology

Abstract

fetched live from OpenAlex

Environmental context Some long-lived organic contaminants, such as chlorinated organics, brominated flame retardants and polycyclic aromatic hydrocarbons, can undergo transport through the atmosphere to remote regions. A series of measurements of these compounds taken over almost 3 years in the air at a remote location was combined with meteorological data to try to reveal potential source areas. After adjusting several parameters to optimise the method’s ability to identify sources it was found that for most contaminants no definitive sources are revealed. Abstract A suite of brominated flame retardants, chlorinated organic pesticides and some metabolites thereof were analysed in week-long and day-long air samples collected at Little Fox Lake in Canada’s Yukon Territory from 2007 to 2009. Several trajectory-based methods for source region identification were applied to this dataset, as well as to polycyclic aromatic hydrocarbon (PAH) concentrations in those same samples reported previously. A type of concentration weighted trajectory (CWT) analysis, using a modified grid to avoid difficulties near the Earth’s poles, and removing trajectory endpoints at altitudes greater than 700 m did not identify distinct source regions for most analytes. Decreasing the spatial resolution of the grid made interpretation simpler but reinforced patterns that may have stemmed from single trajectories. The potential source contribution function (PSCF) is similar to CWT but treats the concentration data categorically, rather than numerically. PSCF provides more distinct results, highlighting the Arctic Ocean as a potential source of para,para'-dichlorodiphenyldichloroethene and both northern Siberia and Canada’s Yukon and Northwest Territories as potential sources of PAHs. To simulate the uncertainty associated with individual trajectories, a set of trajectories was also generated for six points surrounding the sampling station and included in the trajectory analyses. This had the effect of smoothing the CWT and PSCF values for those analytes with no clearly definable sources, and highlighting the source regions for the two that did. For the bulk of the analytes discussed here, Little Fox Lake is well positioned to act as a background monitoring site.

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 score0.030
Threshold uncertainty score0.061

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.006
GPT teacher head0.191
Teacher spread0.185 · 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

Citations10
Published2013
Admission routes3
Has abstractyes

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