Exploring the atmospheric sulfur trends and the potential contribution of sulfate-reducing microorganism activities to the atmospheric sulfur budget at Saturna Island, B.C
Bibliographic record
Abstract
Anthropogenic and biogenic activities, along with the fluxes of sea salt, volcanic, wildfire and oceanic sulfate-reducing microorganisms (SRM), contribute significantly to the atmospheric sulfur budget.(1,2) There is still uncertainty and debate between studies about the magnitude of the importance of oceanic hydrogen sulfide (H2S) produced by SRM, as well as its ability to diffuse to the upper water column and its contribution to the atmospheric sulfur budget. While some studies believe that the majority of H2S is re-oxidized and is less likely to reach the atmosphere (3,4), there is evidence of the existence of H2S in the upper water columns and even in the atmosphere (2,5). H2S produced by SRM, emitted to the atmosphere, along with the anthropogenic sulfur dioxide (SO2) and dimethyl sulfide (DMS), undergo atmospheric oxidation processes. Sulfate (SO42-), as one of the main oxidized products, may nucleate with water vapor, ammonia and organic oxides (6,7), and subsequently grow to bigger particle sizes. These particles affect the climate directly and indirectly and change the radiation balance of the Earth-atmosphere system. (8,9,10) This study assessed the seasonal trends of major atmospheric sulfur species including SO2, sulfate, and biogenic and anthropogenic sulfate of gas, aerosol and precipitation samples, collected by Canadian Air and Precipitation Monitoring Network (CAPMoN), Environment of Canada, at Saturna Island, B.C, between 1998-2010. We then explored the oceanic phytoplankton activities and DMS production, based on sulfur isotope composition and found the importance of DMS contribution to the summertime atmospheric sulfur budget. A handful of samples (~10-30%) displayed negative sulfur isotope compositions, outside the range of anthropogenic and biogenic isotope values. Potential factors that could produce such negative sulfur isotope composition values include isotopic fractionation, fluxes from mineral dust events, volcanic eruptions, wildfires and microbial sulfate reduction (MSR). Our study found that MSR was the only feasible explanation for these very negative sulfur isotope compositions in non-sea salt sulfate samples. H2S in our study was a 4th potential contributor to the atmospheric sulfur budget, along with the 3 major sources of anthropogenic, biogenic DMS, and sea-salt sulfate, in this long-term atmospheric sulfur study.
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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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".