NASA’s role in monitoring stratospheric ozone. Are ozone layer protection measures effective?
Bibliographic record
Abstract
The stratospheric ozone layer (10–50 km) absorbs biologically harmful ultravioletradiation, enabling life to persist on Earth. Early NASA measurements from the1960s–1970s showed that natural ozone levels are controlled by trace nitrogen oxides,hydrogen oxides, and halogens. Approximately 20 NASA missions, together withNOAA, ESA, and other international partners, have contributed to global ozone monitoring.Observations revealed a severe springtime ozone depletion over Antarcticain 1984–1985. NASA recorded the lowest ozone value ever measured over the SouthPole—73 DU on September 30, 1994—and the largest single-day ozone hole extent of29.9 · 10⁶ km² on September 9, 2000. The Montreal Protocol (1987) led to a 99% phaseoutof regulated ozone-depleting substances. According to the latest WMO/UNEP assessment,the ozone layer is projected to return to 1980 levels by approximately 2066over Antarctica, 2045 over the Arctic, and 2040 globally, assuming current controlsremain in place. Although episodic deep ozone depletion occurred in 2023, NASA’s2025 data show continued long-term recovery. In 2025, the minimum Antarctic ozoneconcentration was 147 DU on October 6, and the maximum ozone hole extent was23 · 10⁶ km² on September 9—the largest ever recorded hole was about 30% bigger.These observations confirm that Montreal Protocol regulations are driving the gradualrestoration of the ozone layer.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".