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Record W7085592234 · doi:10.3929/ethz-c-000024267

Summertime pollution events in the Arctic and potential implications

2006· other· en· W7085592234 on OpenAlexaboutno aff

Bibliographic record

VenueRepository for Publications and Research Data (ETH Zurich) · 2006
Typeother
Languageen
FieldHealth Professions
TopicHealthcare professionals’ stress and burnout
Canadian institutionsnot available
Fundersnot available
KeywordsArcticThe arcticPollutionAir pollutionClimate change

Abstract

fetched live from OpenAlex

Arctic summertime aerosols are examined here on the basis of column integrated and surface aerosol measurements made at Barrow (North Slope of Alaska) between 1998 and 2003. Although the site generally exhibits low aerosol burden in the summer, events of high loadings occur 8 days per summer. During the pollution episodes, the potential source contribution function from Russia is dominant (being about 40%). The source locations in Russia are mainly situated in the central and eastern parts. South Asia, Europe and North America each contribute 6% to the observed high aerosol loading. Source locations in south Asia lie in northern China and northern Japan, while those in Europe lie mainly in northern U.K. and Estonia. The North American sources are situated in northern Canada and Alaska. Over the 6‐year period, 10 ± 4 days per summer season show elevated levels of surface aerosol absorption. The pollution events with the highest aerosol absorption appear to be associated with smoke from wild fires burning in northwest Canada. Diurnally averaged top of the atmosphere direct radiative forcing ΔFTOA (550 nm) at Barrow lie between −1.50 W m⁻² and 1.19 W m⁻² in summer with an annual mean of −0.53 ± 0.11 W m⁻². Given low Arctic summertime surface albedo (<30%), a positive ΔFTOA results when the single scattering albedo is 0.85 or lower. Summertime direct surface radiative forcing (550 nm) ranges between −3.2 W m⁻² and −29 W m⁻² for observed cases of aerosol optical depth at the 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 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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.391
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
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 head0.185
GPT teacher head0.506
Teacher spread0.321 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2006
Admission routes1
Has abstractyes

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