Emissions of CFCs, HCFCs and HFCs from India
Bibliographic record
Abstract
Abstract. As the second most populous country and third fastest growing economy, India has emerged as a global economic power. As such, its emissions of greenhouse and ozone-depleting gases are of global significance. However, unlike neighbouring China, the Indian sub-continent is very poorly monitored by existing measurement networks. Of the greenhouse/ozone-depleting gases, India's emissions of synthetic halocarbons (here defined as chlorofluorocarbons (CFCs), hydrochlorofluorocarbons (HCFCs) and hydrofluorocarbons (HFCs)) are not well-known. Previous measurements from the region have been obtained at observatories many hundreds of miles from source regions, or at high altitudes, limiting their value for the estimation of regional emission rates. Given the projected rapid growth in demand for refrigerants in India, emission estimates of these halocarbons are urgently needed, to provide a benchmark against which future changes can be evaluated. In this study, we report the first atmospheric-measurement derived emissions of the ozone-depleting CFCs and HCFCs, and potent greenhouse gas HFCs from India. Air samples were collected at low-altitude during a 2-month aircraft campaign between June and July 2016. Emissions were derived from measurements of these samples using an inverse modelling framework and evaluated to assess India's progress in phasing out ozone-depleting substances (ODS) under the Montreal Protocol. Our CFC estimates show that India contributed 52 (26–83) Tg CO2eq yr−1, which were 7 (4–12) % of global emissions in 2016. HCFC-22 emissions at 7.8 (6.0–9.9) Gg yr−1 were of similar magnitude to emissions of HFC-134a (8.2 (6.1–10.7) Gg yr−1), suggesting that India used a range of HCFC and HFC refrigerants in 2016. We estimated India's HFC-23 emissions to be 1.2 (0.9–1.5) Gg yr−1 and our results are consistent with resumed venting of HFC-23 by HCFC-22 manufacturers following the discontinuation of funding for abatement under the Clean Development Mechanism. We report small emissions of HFC-32 and HFC-143a and provide evidence that HFC-32 emissions were primarily due to fugitive emissions during manufacturing processes. Lack of significant correlation among HFC species and the small emissions derived for HFC-32 and HFC-143a indicate that in 2016, India's use of refrigerant blends R-410A, R-404A and R-507A was limited, despite extensive consumption elsewhere in the world.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".