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Record W2912238320 · doi:10.1021/acs.est.8b05353

Polycyclic Aromatic Hydrocarbons Not Declining in Arctic Air Despite Global Emission Reduction

2019· article· en· W2912238320 on OpenAlexafffundabout
Yong Yu, Athanasios Katsoyiannis, Pernilla Bohlin‐Nizzetto, Eva Brorström‐Lundén, Jianmin Ma, Yuan Zhao, Zhiyong Wu, David Mindham, Ed Sverko, Enzo Barresi, Helena Dryfhout-Clark, Phil Fellin, Hayley Hung

Bibliographic record

VenueEnvironmental Science & Technology · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsEnvironment and Climate Change Canada
FundersMiljødirektoratetCrown-Indigenous Relations and Northern Affairs CanadaNaturvårdsverket
KeywordsEnvironmental scienceEnvironmental chemistryPolycyclic aromatic hydrocarbonArcticThe arcticWaste managementEnvironmental engineeringEnvironmental protectionChemistryEcologyOceanographyEngineeringBiology

Abstract

fetched live from OpenAlex

Two decades of atmospheric measurements of polycyclic aromatic hydrocarbons (PAHs) were conducted at three Arctic sites, i.e., Alert, Canada; Zeppelin, Svalbard; and Pallas, Finland. PAH concentrations decrease with increasing latitude in the order of Pallas > Zeppelin > Alert. Forest fire was identified as an important contributing source. Three representative PAHs, phenanthrene (PHE), pyrene (PYR), and benzo[ a]pyrene (BaP) were selected for the assessment of their long-term trends. Significant decline of these PAHs was not observed contradicting the expected decline due to PAH emission reductions. A global 3-D transport model was employed to simulate the concentrations of these three PAHs at the three sites. The model predicted that warming in the Arctic would cause the air concentrations of PHE and PYR to increase in the Arctic atmosphere, while that of BaP, which tends to be particle-bound, is less affected by temperature. The expected decline due to the reduction of global PAH emissions is offset by the increment of volatilization caused by warming. This work shows that this phenomenon may affect the environmental occurrence of other anthropogenic substances, such as more volatile flame retardants and pesticides.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.572
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.002

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 head0.005
GPT teacher head0.230
Teacher spread0.225 · 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

Citations147
Published2019
Admission routes3
Has abstractyes

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