Introduction of subsidisation in nascent climate-friendly learning technologies and evaluation of its effectiveness
AbstractGiven its importance as a practical phenomenon underlying the progress of learning technologies, attention should be paid to the role of subsidisation in learning theory, particularly in the case of nascent climate-related sociable learning technologies, in order to examine its benefits. Thus, this study focuses on subsidy procurement of energy technologies in several economies in the context of the component learning track in endogenous global clusters in order to suggest improvements to the adoption mechanism and examine the climate stabilization constraint. At the same time, the study attempts to determine the global progress ratio of the lithium-ion battery in order to analyse various endogenous learning scenarios for hybrid technologies. An integrated energy system model with highly disaggregated global regions (DNE21+) is used to execute this research in a medium time frame. Subsidisation of the learning track of battery technology encourages greater development of plug-in hybrid vehicles, promotes early diffusion of hybrid technologies, and relieves heavy dependency on crude oil and biofuels. The subsidies in the common learning domains in few economies benefit the nearby economies because of the technology spillover that occurs through numerous cross-feedback learning mechanisms. Endogenous learning with subsidies augments diffusion potentials, abates emissions, and shifts sectoral emissions.
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Bibliographic InfoArticle provided by Elsevier in its journal Energy Policy.
Volume (Year): 38 (2010)
Issue (Month): 1 (January)
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Web page: http://www.elsevier.com/locate/enpol
Plug-in hybrid Cluster learning of component Subsidy;
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- Rout, Ullash K. & Akimoto, Keigo & Sano, Fuminori & Oda, Junichiro & Homma, Takashi & Tomoda, Toshimasa, 2008. "Impact assessment of the increase in fossil fuel prices on the global energy system, with and without CO2 concentration stabilization," Energy Policy, Elsevier, vol. 36(9), pages 3477-3484, September.
- Rout, Ullash K. & Fahl, Ulrich & Remme, Uwe & Blesl, Markus & Voß, Alfred, 2009. "Endogenous implementation of technology gap in energy optimization models--a systematic analysis within TIMES G5 model," Energy Policy, Elsevier, vol. 37(7), pages 2814-2830, July.
- Akimoto, Keigo & Tomoda, Toshimasa & Fujii, Yasumasa & Yamaji, Kenji, 2004. "Assessment of global warming mitigation options with integrated assessment model DNE21," Energy Economics, Elsevier, vol. 26(4), pages 635-653, July.
- Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
- Fuminori Sano, Keigo Akimoto, Takashi Homma and Toshimasa Tomoda, 2006. "Analysis of Technological Portfolios for CO2 Stabilizations and Effects of Technological Changes," The Energy Journal, International Association for Energy Economics, vol. 0(Special I), pages 141-162.
- Larsen, Bjorn & Shah, Anwar & DEC, 1992. "World fossil fuel subsidies and global carbon emissions," Policy Research Working Paper Series 1002, The World Bank.
- Grubler, Arnulf & Nakicenovic, Nebojsa & Victor, David G., 1999. "Dynamics of energy technologies and global change," Energy Policy, Elsevier, vol. 27(5), pages 247-280, May.
- Rout, Ullash K. & Blesl, Markus & Fahl, Ulrich & Remme, Uwe & Voß, Alfred, 2009. "Uncertainty in the learning rates of energy technologies: An experiment in a global multi-regional energy system model," Energy Policy, Elsevier, vol. 37(11), pages 4927-4942, November.
- Irwin, Douglas A & Klenow, Peter J, 1994. "Learning-by-Doing Spillovers in the Semiconductor Industry," Journal of Political Economy, University of Chicago Press, vol. 102(6), pages 1200-1227, December.
- Kamp, Linda M. & Smits, Ruud E. H. M. & Andriesse, Cornelis D., 2004. "Notions on learning applied to wind turbine development in the Netherlands and Denmark," Energy Policy, Elsevier, vol. 32(14), pages 1625-1637, September.
- Loiter, Jeffrey M. & Norberg-Bohm, Vicki, 1999. "Technology policy and renewable energy: public roles in the development of new energy technologies," Energy Policy, Elsevier, vol. 27(2), pages 85-97, February.
- Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
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