Stratospheric influences on surface ozone increase during the COVID-19 lockdown over northern China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Surface ozone increased unexpectedly over northern China during the COVID-19 lockdown (CLD) period (23 January–29 February 2020), which was characterized by vigorous emission reduction. The reasons for this ozone enhancement have been speculated from perspectives of chemical responses to the emissions and meteorology. As known, the processes of natural stratospheric ozone injecting to the troposphere are most active in winter and spring. Yet, little attention was paid to stratospheric influences on this ozone enhancement. Here we report a stratospheric intrusion (SI) that reached the surface over northern China on 15–17 February during the CLD. The coevolution of enhanced ozone and sharply declined carbon monoxide and relative humidity (RH) was indicative of the SI occurrence. We show that the SI was facilitated by a cutoff low system that led to abnormally high surface ozone in most part of northern China. We estimate that over the SI period, the injected stratospheric ozone constituted up to 40–45% of the surface ozone over northern China. If the stratospheric ozone inputs were scaled over the entire CLD period, these inputs would account for 4–8% of the surface ozone. In view of the unexpected ozone increase during the CLD, this SI event could explain up to 18% of the ozone increase in some cities, and average 5–10% over larger areas that were affected. Hence, the nonnegligible stratospheric influences urge extra consideration of natural ozone sources in disentangling the role of emission reduction and meteorological conditions during the CLD in China and elsewhere in the world.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 it