Green Transition by Green Refrigerants for HVAC System
Bibliographic record
Abstract
Abstract Recently, the Climate Change has become a major challenge across the globe. It is disrupting national economies, costing us dearly today and will cost even more tomorrow. Therefore, ‘2015 Paris Climate Change’ marked a historic turning point as it arrived at a universal agreement on climate to keep global warming below 2 °C. HVAC (Heating, Ventilating & Air conditioning) system in general and its refrigerants (heat transfer media) in particular, has significantly impact Green House Gases (GHG) and climate change. Such systems contribute to GHG emission in terms of direct non-green refrigerant emissions and indirect CO2 emissions associated with the energy needed to operate / run the HVAC system. Hence, HVAC industry has been constantly supporting the global efforts for Green Transition. The two measures of environmental effect are Ozone Depletion Potential (ODP) and Global Warming Potential (GWP). ODP represents the relative ability of a refrigerant (CFC & HCFC), used in Air conditioning System, to destroy stratospheric ozone molecules when released to the atmosphere and thereby increasing the UV radiation reaching the earth. CFCs (Chloro Fluoro Carbons like R 11) have the highest ODP, HCFCs (Hydro Chloro Fluoro Carbons like R 22) have comparatively less and HFCs (no Chlorine Content, like R 410A) have zero ODP. The Montreal protocol stipulates that HCFCs (like R 22) are scheduled to be phased out by 2040 (likely to be advanced to 2030) in Article 5 countries like Middle East and others. In non-article 5 countries (developed countries), the environmentally friendly substitutes for HCFCs are being developed and used. Currently Middle East is under extended phase out schedule for R 22 till 2030. The local regulatory bodies (like EPA, MEW–Kuwait) have not yet published any recommendations for its environmentally substitute. Air conditioning & Refrigeration system is extensively used for Control Rooms, Electrical Substations and Offices etc. within KOC premises. This paper provides a detailed study of ‘Refrigerants Progression’ towards Green transition while providing excellent performance benefits. It also provides KOC best practices considering challenges & implementation while taking into account the merits and limitations of Refrigerant(s) for "KOC Air-conditioning system". It is worth broadening our choice of HVAC and applicable Green Refrigerant. This paper also discusses the steps being taken by KOC towards adopting "Green Refrigerants" to improve KOC's image in protecting our fragile environment, in line with the Paris COP 21Climate Change agreement.
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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) | 0.000 | 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 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".