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Record W2314173845 · doi:10.1021/es200106q

Fate of Perfluorinated Carboxylates and Sulfonates During Snowmelt Within an Urban Watershed

2011· article· en· W2314173845 on OpenAlexafffundabout
Torsten Meyer, Amila O. De Silva, Christine Spencer, Frank Wania

Bibliographic record

VenueEnvironmental Science & Technology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsEnvironment and Climate Change CanadaUniversity of Toronto
FundersUniversity of Toronto ScarboroughNatural Sciences and Engineering Research Council of Canada
KeywordsSnowmeltWatershedEnvironmental scienceHydrology (agriculture)Environmental chemistryWater resource managementEnvironmental engineeringChemistrySnowGeologyComputer scienceGeomorphologyGeotechnical engineering

Abstract

fetched live from OpenAlex

The transport dynamics of perfluorinated carboxylic acids and sulfonates during snowmelt in the highly urbanized Highland Creek watershed in Toronto, Canada was investigated by analyzing river water, bulk snow, and groundwater, sampled in February and March 2010, by means of liquid chromatography-tandem mass spectrometry. Perfluorohexanoate, perfluorooctanoate, and perfluorooctane sulfonate were dominant in river water, with concentrations of 4.0-14 ng·L(-1), 2.2-7.9 ng·L(-1), and 2.1-6.5 ng·L(-1), respectively. Relatively high levels of perfluorohexanoate may be related to the recent partial replacement in various consumer products of perfluorooctyl substances with shorter-chained perfluorinated compounds (PFCs). Highest PFC concentrations were found within the more urbanized part of the drainage area, suggestive of residential, industrial, and/or traffic-related sources. The riverine flux of PFCs increased during the snowmelt period, but only approximately one-fifth of the increased flux can be attributed to PFCs present in the snowpack, mostly because concentration in snow are generally quite low compared to those in river water. The remainder of the increased flux must be due to the mobilization of PFCs by the high flow conditions prevalent during snowmelt. Run-off behavior was clearly dependent on perfluoroalkyl chain length: Dilution with relatively clean snowmelt water caused a drop in the river water concentrations of short-chain PFCs at high flow during early melting. This prevented an early concentration peak of those water-soluble PFCs within the stream, as could have been expected in response to their early release from a melting snowpack. Instead, concentrations of particle-associated long-chain PFCs in creek water peaked early in the melt, presumably because high flow mobilized contaminated particles from impervious surfaces in the more urbanized areas of the watershed. The ability to enter the subsurface and deeper groundwater aquifers increased with the PFCs' water solubility, that is, was inversely related to perfluoroalkyl chain length.

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)0.000
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 score0.200
Threshold uncertainty score0.397

Distilled classifier scores by category (both heads)

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

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 head0.012
GPT teacher head0.217
Teacher spread0.205 · 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

Citations36
Published2011
Admission routes3
Has abstractyes

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