Like many countries responding to climate change, Korea also faces an unprecedented transformation of its power sector into a low-carbon system. To evaluate the most advantageous combination of technologies and necessary policies for achieving the goals of such a transformation, this study decomposes the historical development of the total cost of five major power technologies in Korea into three cost components and identifies the underlying driving forces and variabilities of each. We then project the likely distribution of costs in 2030 using Monte-Carlo simulation and simulate the possible impact of climate and environmental policies on the economic landscape of competing technologies. Our results show that the business-as-usual dynamics of key techno-economic-market factors are not likely to secure the economic viability of the proposed energy transition in Korea. Introducing carbon prices or strict environmental policy is imperative in Korea to make renewables and less carbon-intensive gas power remain cost-competitive with coal power.

The bottom-up model of the industrial energy system has hitherto been analyzed using linear programming. However, it has limitations in describing practical technology selection and reproducing base-year technology selection. Positive mathematical programming, which provides an interior solution without any subjective constraints, can be considered as an alternative method that overcomes the limitations of linear programming when constructing a bottom-up model of the industry sector. The purpose of this study is to apply positive mathematical programming and identify the plausibility of using it in a forward-looking optimization model of the industry sector. A bottom-up model based on positive mathematical programming has the advantages of avoiding impractical technology selection in the industry sector, describing more flexible reactions to external changes, and calibrating base-year technology selection without subjective constraints. Although optimal solutions and simulation responses are dependent on parameter identification, the dependence of positive mathematical programming on the identification method can be lower than that of linear programming on the subjective constraints.

The building sector in Korea is one of the key end-use sectors in terms of energy use and accompanying greenhouse gas (GHG) emissions. The sector currently accounts for about one-fifth of economy-wide final energy consumption and greenhouse gas emissions. In this study, we project a business as usual (BAU) scenario for energy and GHG emissions for the building sector based on the government energy forecast, and then develop a couple of policy scenarios which reflect the current state of energy policy. We compare each policy scenario and some combinations with already-pledged climate policy targets to determine whether energy and climate polices are inherently consistent and, if not, how much of an emission gap exists. The most aggressive energy policy combination can only curb the emissions level at 139 MtCO2e by 2020, which falls 14% short of the climate target of 123 MtCO2e. Beyond 2020, the lowest emissions pathway of the current energy policy can only go as low as 115 MtCO2e by 2035. These findings provide supporting evidence that there is a discrepancy between current energy policy and climate change policy and suggest that effective policy coordination is necessary among government ministries in setting a credible long-term climate policy target.

This paper summarizes the main characteristics of the RCP8.5 scenario. The RCP8.5 combines assumptions about high population and relatively slow income growth with modest rates of technological change and energy intensity improvements, leading in the long term to high energy demand and GHG emissions in absence of climate change policies. Compared to the total set of Representative Concentration Pathways (RCPs), RCP8.5 thus corresponds to the pathway with the highest greenhouse gas emissions. Using the IIASA Integrated Assessment Framework and the MESSAGE model for the development of the RCP8.5, we focus in this paper on two important extensions compared to earlier scenarios: 1) the development of spatially explicit air pollution projections, and 2) enhancements in the land-use and land-cover change projections. In addition, we explore scenario variants that use RCP8.5 as a baseline, and assume different degrees of greenhouse gas mitigation policies to reduce radiative forcing. Based on our modeling framework, we find it technically possible to limit forcing from RCP8.5 to lower levels comparable to the other RCPs (2.6 to 6 W/m(2)). Our scenario analysis further indicates that climate policy-induced changes of global energy supply and demand may lead to significant co-benefits for other policy priorities, such as local air pollution.

We are motivated by the question as to how much geoengineering would be considered if it were to be used to avoid overshoot even combined with a strong mitigation? How serious would the side effects be expected? This study focuses on stratospheric sulfur injections among other geoengineering proposals, the idea of which has been put forward by Crutzen (2006) and reviewed by Rasch et al. (2008). There are a number of concerns over geoengineering (e.g. Robock, 2008). But the concept of geoengineering requires further research (AMS, 2009). Studying geoengineering may be instructive to revisit the importance of mainstream mitigation strategies.