Resource mobilization for HCFC phase-out and climate mitigation co-benefits : a study prepared for the executive committee of the multilateral fund
Bibliographic record
Abstract
This study seeks to identify potential sources of co-financing to meet the additional costs of energy efficiency (EE) and climate mitigation benefits associated with the hydrochlorofluorocarbons (HCFC) phase-out supported by the Multilateral fund of the montreal protocol (MLF). As it stands, the policy of the multilateral fund is to support only the eligible incremental costs related to the phase-out of ozone depleting substances, and not to support the additional costs of additional EE related improvements of the equipment. Currently therefore, while the multilateral fund encourages exploring co-financing opportunities for improving energy efficiency, the fund does not directly support the uptake of the most energy efficient technology. HCFC phase-out management plans (HPMPs) approved by the MLF seek to facilitate the conversion of refrigeration - air conditioning (Ref-AC) manufacturing and foam manufacturing away from the use of HCFCs to non - ozone depleting substance (ODS) alternatives. This study explores pathways that may encourage the uptake of ozone- and climate friendly technologies through synergies between the MP, policies to promote EE, and climate finance instruments; thereby leading also to cost-effectiveness of public financing and economic efficiency where synergies exist and can be exploited. The study underscores, based on practical examples, that opportunities can be strategically engineered to encourage harmonization between the phase-out of the HCFCs and HCFC-using technologies with efforts to promote energy efficiency and reduce greenhouse gas emissions (GHG).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.032 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".