Biogenic, anthropogenic and sea salt sulfate size-segregated aerosols in the Arctic summer
Bibliographic record
Abstract
Abstract. Size-segregated aerosol sulfate concentrations were measured on board the Canadian Coast Guard Ship (CCGS) Amundsen in the Arctic during July 2014. The objective of this study was to utilize the isotopic composition of sulfate to address the contribution of anthropogenic and biogenic sources of aerosols to the growth of the different aerosol size fractions in the Arctic atmosphere. Non-sea-salt sulfate is divided into biogenic and anthropogenic sulfate using stable isotope apportionment techniques. A considerable amount of the average sulfate concentration in the fine aerosols with a diameter < 0.49 µm was from biogenic sources (> 63 %), which is higher than in previous Arctic studies measuring above the ocean during fall (< 15 %) (Rempillo et al., 2011) and total aerosol sulfate at higher latitudes at Alert in summer (> 30 %) (Norman et al., 1999). The anthropogenic sulfate concentration was less than that of biogenic sulfate, with potential sources being long-range transport and, more locally, the Amundsen's emissions. Despite attempts to minimize the influence of ship stack emissions, evidence from larger-sized particles demonstrates a contribution from local pollution. A comparison of δ34S values for SO2 and fine aerosols was used to show that gas-to-particle conversion likely occurred during most sampling periods. δ34S values for SO2 and fine aerosols were similar, suggesting the same source for SO2 and aerosol sulfate, except for two samples with a relatively high anthropogenic fraction in particles < 0.49 µm in diameter (15–17 and 17–19 July). The high biogenic fraction of sulfate fine aerosol and similar isotope ratio values of these particles and SO2 emphasize the role of marine organisms (e.g., phytoplankton, algae, bacteria) in the formation of fine particles above the Arctic Ocean during the productive summer months.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".