Relative changes in CO emissions over megacities based on observations from space
Bibliographic record
Abstract
Urban areas are large sources of several air pollutants, with carbon monoxide (CO) among the largest. Yet measurement from space of their CO emissions remains elusive due to its long lifetime. Here we introduce a new method of estimating relative changes in CO emissions over megacities. A new multichannel Measurements of Pollution in the Troposphere (MOPITT) CO data product, offering improved sensitivity to the boundary layer, is used to estimate this relative change over eight megacities: Moscow, Paris, Mexico, Tehran, Baghdad, Los Angeles, Sao Paulo, and Delhi. By combining MOPITT observations with wind information from a meteorological reanalysis, changes in the CO upwind‐downwind difference are used as a proxy for changes in emissions. Most locations show a clear reduction in CO emission between 2000–2003 and 2004–2008, reaching −43% over Tehran and −47% over Baghdad. There is a contrasted agreement between these results and the MACCity and Emission Database for Global Atmospheric Research v4.2 inventories.
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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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".