GC51C-1105
Estimation of Energy Consumption and Greenhouse Gas Emissions considering Aging and Climate Change in Residential Sector

Friday, 18 December 2015
Poster Hall (Moscone South)
Mijin Lee1, Chan Park2, Jin Han Park1, Tae-Yong Jung3 and Dong Kun Lee1, (1)Seoul National University, Seoul, South Korea, (2)Korea research institute for humen settlements, Anyang, South Korea, (3)Yonsei University, Graduate School of International Studies, Seoul, South Korea
Abstract:
The impacts of climate change, particularly that of rising temperatures, are being observed across the globe and are expected to further increase. To counter this phenomenon, numerous nations are focusing on the reduction of greenhouse gas (GHG) emissions. Because energy demand management is considered as a key factor in emissions reduction, it is necessary to estimate energy consumption and GHG emissions in relation to climate change. Further, because South Korea is the world’s fastest nation to become aged, demographics have also become instrumental in the accurate estimation of energy demands and emissions. Therefore, the purpose of this study is to estimate energy consumption and GHG emissions in the residential sectors of South Korea with regard to climate change and aging to build more accurate strategies for energy demand management and emissions reduction goals. This study, which was stablished with 2010 and 2050 as the base and target years, respectively, was divided into a two-step process. The first step evaluated the effects of aging and climate change on energy demand, and the second estimated future energy use and GHG emissions through projected scenarios. First, aging characteristics and climate change factors were analyzed by using the logarithmic mean divisia index (LMDI) decomposition analysis and the application of historical data. In the analysis of changes in energy use, the effects of activity, structure, and intensity were considered; the degrees of contribution were derived from each effect in addition to their relations to energy demand. Second, two types of scenarios were stablished based on this analysis. The aging scenarios are business as usual and future characteristics scenarios, and were used in combination with Representative Concentration Pathway (RCP) 2.6 and 8.5. Finally, energy consumption and GHG emissions were estimated by using a combination of scenarios. The results of these scenarios show an increase in energy consumption and GHG emissions from 2010 to 2050. This growth is caused by increases in heating energy because the elderly generally spend more time at home, and cooling energy owing to rising temperatures. This study will be useful in the preparation of energy demand management policies and the establishment and attainability of GHG emissions reduction goals.