Reproducing springtime Arctic tropospheric ozone depletion events in an outdoor mesocosm sea-ice facility
Bibliographic record
Abstract
Abstract. The episodic build-up of gas-phase reactive bromine species over sea ice and snowpack in the springtime Arctic plays an important role in the boundary layer, causing annual concurrent depletion of ozone and gaseous elemental mercury during polar sunrise. Extensive studies have shown that these phenomena, known as bromine explosion events (BEEs), ozone depletion events (ODEs) and mercury depletion events (MDEs), respectively, are all triggered by gas-phase reactive bromine species that are photochemically activated from bromide via multi-phase reactions under freezing air temperatures. However, major knowledge gaps exist in both fundamental cryo-photochemical processes causing these events and meteorological conditions that may affect their timing and magnitude. Here, we report an outdoor mesocosm-scale study in which we successfully reproduced ODEs at the Sea-ice Environmental Research Facility (SERF) in Winnipeg, Canada. By monitoring ozone concentrations inside large, acrylic tubes over bromide-enriched artificial seawater during entire sea ice freeze-and-melt cycles, we observed mid-day photochemical ozone loss in winter in the boundary layer air immediately above the sea ice surface in a pattern that is characteristic of BEE-induced ODEs in the Arctic. The importance of UV radiation and the presence of a condensed phase (experimental sea ice or snow) in causing such surface ozone loss was demonstrated by comparing ozone concentrations between UV-transmitting and UV-blocking acrylic tubes under different air temperatures. The ability of reproducing BEE-induced ODEs at a mesocosm scale in a non-polar region provides a new approach to systematically studying the cryo-photochemical and meteorological processes leading to BEEs, ODEs, and MDEs in the Arctic, their role in biogeochemical cycles across the ocean-sea ice-atmosphere interfaces, and their sensitivities to climate change.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".