Assessment of Russia’s production capacity for natural refrigerants in the context of the Kigali Amendment implementation: a case of transport refrigeration equipment
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In compliance with the Russian Federation’s obligations under the Kigali Amendment to the Montreal Protocol—mandating a phasedown of hydrofluorocarbon consumption—the transition to natural refrigerants has become a strategic priority. This study quantitatively assesses the alignment between domestic production capacity of natural refrigerants—propane (R290) and propylene (R1270)—and actual/prospective demand in the transport refrigeration sector. Statistical analysis of data from 2020 to 2023 reveals that production capacity at JSC “NPP Sintez” fully satisfies R290 demand but falls short of R1270 requirements. Notably, even in this relatively low-refrigerant-intensity segment, a supply gap for certain natural alternatives is evident—highlighting the urgent need for scaling up domestic manufacturing infrastructure. The findings underscore that a successful HFC phase-down in Russia necessitates not only equipment redesign and retrofitting but also targeted industrial policy to expand high-purity natural refrigerant production. This case study provides empirical grounding for evidence-based planning of the national refrigeration sector’s decarbonization pathway.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it