Satellite reveals a steep decline in China’s CO <sub>2</sub> emissions in early 2022
Bibliographic record
Abstract
Response actions to the coronavirus disease 2019 perturbed economies and carbon dioxide (CO 2 ) emissions. The Omicron variant that emerged in 2022 caused more substantial infections than in 2020 and 2021 but it has not yet been ascertained whether Omicron interrupted the temporary post-2021 rebound of CO 2 emissions. Here, using satellite nitrogen dioxide observations combined with atmospheric inversion, we show a larger decline in China’s CO 2 emissions between January and April 2022 than in those months during the first wave of 2020. China’s CO 2 emissions are estimated to have decreased by 15% (equivalent to −244.3 million metric tons of CO 2 ) during the 2022 lockdown, greater than the 9% reduction during the 2020 lockdown. Omicron affected most of the populated and industrial provinces in 2022, hindering China’s CO 2 emissions rebound starting from 2021. China’s emission variations agreed with downstream CO 2 concentration changes, indicating a potential to monitor CO 2 emissions by integrating satellite and ground measurements.
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How this classification was reachedexpand
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".