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DTSTART;TZID=Europe/Berlin:20240611T153000
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DTSTAMP:20240529T095147Z
CREATED:20240508T083345Z
LAST-MODIFIED:20240529T095147Z
UID:10000052-1718119800-1718125200@whatworksclimate.solutions
SUMMARY:Rebound effect in the era of energy transition
DESCRIPTION:This paper conducts a meta-analysis on rebound effects regarding the energy transition for household end-use services toward renewable energies (including photovoltaic\, biomass\, green electricity\, and heat pumps). The biomass and heat pump potentially lead to the highest size of rebound effect (approximately 33%). In addition\, the rebound effect regarding green electricity is about 1–3 % and even 11 % for low-income households. Focusing on residential solar/photovoltaic technologies\, it varies from a negative amount to nearly 30%. Only the solar domain supplies enough sample size to do the meta-regression. This model shows predictor variables driving the solar rebound effect(SRE) (estimated at around 15.49%) are feed-in-tariff (FIT) and the renewable share. A marginal percent in the renewable share or a one-cent change in FIT could result in a corresponding increase of SRE 0.21% and 0.34%\, respectively.
URL:https://whatworksclimate.solutions/presentation/rebound-effect-in-the-era-of-energy-transition/
LOCATION:H 0107
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