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Record W7018016723

Characterisation of Microphysical and Optical Properties of Atmospheric Aerosols in a High Arctic environment: Villum Research Station, NE Greenland

2023· dissertation· en· W7018016723 on OpenAlexaboutno aff

Bibliographic record

VenueSkemman · 2023
Typedissertation
Languageen
FieldEnvironmental Science
TopicScience and Climate Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAerosolParticle (ecology)Radiative transferParticle-size distributionArcticParticle numberAbsorption (acoustics)WavelengthPopulation
DOInot available

Abstract

fetched live from OpenAlex

Atmospheric aerosols are solid or liquid phase particles which are suspended in ambient air. These particles have an impact on the climate through direct and indirect radiative forcing, and their measurement presents challenges in high latitude environments where concentrations may fall under the detection limit of the responsible instruments. In order to both qualify and quantify the contribution of aerosol particles to environmental change at higher latitudes, it is important to understand their microphysical and optical properties, which control their interaction with visible wavelength radiation. This thesis focuses on the characterisation of the aforementioned aerosol properties in a High Arctic environment, Villum Research Station (Northeast Greenland), during two six-month observation periods in 2020 and 2021. The parameters presented in the analysis are particle total number concentration and size distribution in the 0.3 - 10 µm size range, particle scattering coefficients σsp, particle absorption coefficients σap, and Ångström exponents describing the wavelength dependence of both optical coefficients. The seasonal variability and distribution of these properties was analysed, and case studies of exceptional particle number concentration identified as particle transport events to evaluate the contribution of local and long-distance source regions to the overall aerosol population at the station. The results of the analysis show that there is a notable seasonality to both number concentration and optical characteristics of aerosol particles at Villum Research Station, with median values for these parameters at their highest in the winter, followed by the autumn and then the summer. The dominant species during episodes of exceptional particle number concentrations were found to be dust, Elemental Carbon/Organic Carbon (EC/OC) and mixed aerosols, with source regions across continental Greenland, the Canadian Archipelago and Arctic Ocean.

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 score0.310
Threshold uncertainty score0.617

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.032
GPT teacher head0.276
Teacher spread0.245 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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