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Enregistrement W2156490833

Comparison between HFC-134a and alternative refrigerants in mobile air conditioners using the GREEN-MAC-LCCP© model.

2014· article· en· W2156490833 sur OpenAlexaboutno aff
Stella Papasavva, William R. Moomaw

Notice bibliographique

RevuePurdue e-Pubs (Purdue University System) · 2014
Typearticle
Langueen
DomaineEngineering
ThématiqueRefrigeration and Air Conditioning Technologies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésRefrigerantMontreal ProtocolAir conditioningEnvironmental scienceAutomotive industryOzone layerGlobal warmingWaste managementGlobal-warming potentialGreenhouse gasFlammabilityEngineeringEnvironmental engineeringProcess engineeringOzoneMeteorologyClimate changeChemistryMechanical engineeringGas compressorEcologyGeography
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

The transition from CFC-12 (GWP=10,900) to HFC-134a (GWP=1,430) in the 1990’s in new vehicle air conditioners eliminated the potential contribution to ozone depletion from new vehicles and reduced the direct Global Warming Potential (GWP) by over 80%. One proposed alternative is HFC-1234yf (GWP=4). Despite the phase-in success of HFC-134a as a zero ODP automotive refrigerant it is still a potent greenhouse gas and the European Union (EU) issued Directive 2006/40/EC that prohibits the use of automotive refrigerants with GWP greater than 150, starting from January 1st, 2011. Due to such regulations, the automotive Original Equipment Manufacturers (OEMs), chemical manufacturers and Mobile Air Conditioning (MAC) industry have evaluated several alternative refrigerants considering a range of selection criteria that include: refrigerant engineering performance, system design impact, MAC system changes to optimize the use of new refrigerants, cost, flamability, and environmental impacts including global warming, and human toxicity risks. There has been remarkable success in eliminating refrigerant fluids that deplete the ozone layer, but many of their replacements have high GWP. There is now a major international effort for a third generation refrigerant fluids that are safe both for ozone depletion and climate protection. During 2013, the United States and China proposed phasing out high GWP HFCs that have been introduced to replace ODP substances through the provisions of the Montreal Protocol. Europe is currently debating between two alternative fluids for vehicle air conditioners, and the outcome is being watched closely. This paper will compare the alternatives. New MAC systems that meet the low GWP requirements of the EU Directive refrigerants should also be equally or more efficient than HFC-134a designs. Life Cycle Analysis (LCA) adds a step in the understanding of the dynamics of the industrial activities as a system and not as individual components, with implications for better policy decisions at the technological and environmental levels. This was recognized by the MAC industry and government and Life Cycle Climate Performance (LCCP) was accepted as one of the methods for selecting among alternative refrigerants. We consider and implement LCA for developing the Global Refrigerants Energy & Environmental-Mobile Air Conditioning-Life Cycle Climate Performance (GREEN-MAC-LCCP)© model which is the tool that evaluates the full cycle of Greenhouse Gas emissions of alternative refrigerant systems. The goal of this tool is to provide a superior basis for engineers and policy makers to make wise decisions of alternative competing technologies. In this presentation, we summarize the evolution of refrigerant fluids and how the world has arrived at the present point. The interplay between the evolution of technology and the regulatory system that governs it, the economic drivers and the environmental health and safety implications will be elucidated. We will also provide a short overview of the model and the results obtained by evaluating various alternative refrigerant MAC systems and compare them with the HFC-134a production baseline. Using GREEN-MAC-LCCP© we estimate the energy consumption and GHG of current vehicle MACs that operate with HFC-134a and compare these results with new systems that operate with alternative refrigerants.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,059
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,020
Tête enseignante GPT0,236
Écart entre enseignants0,216 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations3
Publié2014
Routes d'admission1
Résumé présentoui

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