Atmospheric three-dimensional inverse modeling of regional industrial emissions and global oceanic uptake of carbon tetrachloride
Bibliographic record
Abstract
Abstract. Carbon tetrachloride (CCl4) has substantial stratospheric ozone depletion potential and its consumption is controlled under the Montreal Protocol and its amendments. We implement a Kalman filter using atmospheric CCl4 measurements and a 3-dimensional chemical transport model to estimate the interannual regional industrial emissions and seasonal global oceanic uptake of CCl4 for the period of 1996–2004. The Model of Atmospheric Transport and Chemistry (MATCH), driven by offline National Center for Environmental Prediction (NCEP) reanalysis meteorological fields, is used to simulate CCl4 mole fractions and calculate their sensitivities to regional sources and sinks using a finite difference approach. High frequency observations from the Advanced Global Atmospheric Gases Experiment (AGAGE) and the Earth System Research Laboratory (ESRL) of the National Oceanic and Atmospheric Administration (NOAA) and low frequency flask observations are together used to constrain the source and sink magnitudes, estimated as factors that multiply the a priori fluxes. Although industry data imply that the global industrial emissions were substantially declining with large interannual variations, the optimized results show only small interannual variations and a small decreasing trend. The global surface CCl4 mole fractions were declining in this period because the CCl4 oceanic and stratospheric sinks exceeded the industrial emissions. Compared to the a priori values, the inversion results indicate substantial increases in industrial emissions originating from the South Asian/Indian and Southeast Asian regions, and significant decreases in emissions from the European and North American regions.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".