GOSAT Mapping of Global Greenhouse Gas in 2020 and 2021
Bibliographic record
Abstract
Carbon dioxide and methane are the two most important greenhouse gases and are closely related to global warming and extreme weather events. To master their spatial and temporal variations, the CO2 and CH4 concentration data monitored by the GOSAT satellite in 2020 and 2021 were used to map and analyse the annual, seasonal and monthly changes in CO2 and CH4 concentrations in the world and major countries/regions. The results demonstrate that (1) in 2021, the average annual CO2 concentration over the global land area was 412.74 ppm, an increase in 0.64% compared with the same period last year, and there were spatial differences in the distribution of CO2 concentration, with high values mostly concentrated in the middle latitudes of the Northern Hemisphere; (2) compared with 2020, the CO2 concentration in China, the United States, India, the European Union and other countries/regions increased significantly; (3) in 2020 and 2021, the quarterly CO2 trend of the global and major countries/regions was the same, which was higher in the first (January, February, March) and second (April, May, June) quarters, significantly lower in the third (July, August, September) quarter, and gradually increased in the fourth (October, November, December) quarter. Further work on long time series and validation needs to be conducted.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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 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".