Atmospheric observations and emission estimates of ozone-depleting chlorocarbons from India
Bibliographic record
Abstract
Abstract. While the Montreal Protocol has been successful in reducing emissions of many long-lived ozone-depleting substances, growth in the global emission rates of unregulated very short-lived substances (VSLS) poses a potential threat to the recovery of the ozone layer. The sources of these VSLS are not well-constrained, with major source regions poorly monitored by existing measurement networks. Given India's rapidly growing economy, its emissions of both regulated chlorocarbons and unregulated VSLS chlorocarbons are suspected to have global significance. Furthermore, VSLS from the Asian monsoon regions have a greater impact on ozone-depletion than those emitted elsewhere due to the ability of monsoon systems to rapidly transport pollutants to the lower stratosphere. Previous atmospheric measurements of chlorocarbons from the Indian sub-continent are scarce. Here we present a new set of observations, derived from flask samples collected during a 2-month aircraft campaign in India and use these measurements to infer India's chlorocarbon emissions. We show that emissions of carbon tetrachloride from northern and central India (2.3 (1.5–3.4) Gg yr−1), are likely due to inadvertent production and release during the manufacture of chloromethanes (specifically dichloromethane and chloroform) and account for approximately 7 % of the global total. Emissions of methyl chloroform from the same region were estimated to be 0.07 (0.04–0.10) Gg yr−1 which account for less than 5 % of remaining global emissions. We used a population scaling to estimate India's emissions of the very short-lived chlorocarbons dichloromethane, perchloroethene and chloroform, which were estimated to be 69.2 (55.8–82.9) Gg yr−1, 2.9 (2.5–3.3) Gg yr−1 and 25.7 (21.6–29.9) Gg yr−1 respectively. In the case of dichloromethane, our estimate is consistent with a 3-fold increase in emissions since the last estimate derived from atmospheric data in 2008.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".