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박찬,Tatsuya, Hanaoka,Toshihiko, Masui,이동근,정태용 한국기후변화학회 2019 한국기후변화학회지 Vol.10 No.1
This study analyzes potential CO2 emission pathways in the Korean residential sector by using the bottom-up optimization model, AIM/Enduse. This study focuses on: 1) estimating potential emissions considering future changes in population, GDP, and temperature, 2) assessing the mitigation potential of CO2 with a mitigation measures including carbon tax. 3) discussing co-benefits of air pollutants mitigation such as NOx, SO2 in the context of climate mitigation measures in the Korean residential sector. As a result, population and GDP variation shows an overwhelming impact on CO2 emission. Climate change may help to reduce energy consumption and CO2 emission in Korea due to heating and hot-water use demand decreasing. The carbon tax of 20, 50, 100, 200, 300, 500, 1000 US$/tCO2 in 2050 can reduce 1.0%, 2.5%, 3.6%, 9.6%, 12.2%, 14.1%, and 19.7% of CO2 emission respectively compared to BaU scenario of SSP2 with current technology selection behavior based on life cycle cost. There is also a benefit of large reduction potential of air pollutants, in the range of 5-40% reductions in with CO2 mitigation measures.
( Masahiro Oguchi ),( Atsushi Terazono ),( Tatsuya Hanaoka ),( Tomohiro Tasaki ) 한국폐기물자원순환학회(구 한국폐기물학회) 2015 한국폐기물자원순환학회 3RINCs초록집 Vol.2015 No.-
End-of-life (EoL) consumer durables such as WEEE and ELVs have been an emerging issue in recent years. As a basis for planning the appropriate waste management scheme in Asian region, accurate estimation of future EoL generation is required. This study modeled the trend in in-use stocks of consumer durables in order to obtain basic data for estimating future EoL generation in Asian developing countries. We analyzed the data of passenger cars and several types of appliances for 60 countries including 26 non-OECD Asian countries. The number of in-use products per capita had a strong correlation with GDP per capita for each country. The slope was, however, different between countries, indicating other factors also affect the number of in-use products. We thus developed multiple linear regression models for the number of in-use products by using various socioeconomic indicators as explanatory variables. Since the trends in the number of in-use products were also different between countries’ economic development, the models were constructed for four groups of countries with different levels of GDP per capita. The developed multiple regression models showed good prediction of the number of in-use products for the target items.