• KDI Journal of Economic Policy
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• v.34 no.2
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• pp.55-93
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• 2012

In Korea, energy policies are actualized through various energy-related plans. Recently, however, as high-ranking plans, which are very vision-oriented, continually set higher sector-by-sector goals, subordinate action plans, which require consistency, encounter distortions in their establishment process. Also, each subordinate action plan reveals limitations in terms of securing flexibility of the plan in responding to uncertainties of the future. These problems pose potential risks such as causing huge social costs. In this regard, with an aim to provide empirical evidence for discussions on improving the procedure for developing and executing Korea's energy plans, this study mainly analyzes the Basic Plan on Electricity Demand and Supply-one of the most important subordinate action plans-in order to explain the problems of the Basic Plan in a logical manner, and potential problems that could occur in the process of sustaining consistency between the Basic Plan and its higher-ranking plans. Further, this paper estimates the scale of social costs caused by those problems assuming realistic conditions. According to the result, in the case of where maximum electric power is estimated to be 7% (15%) less than the actual amount in the Basic Plan on Electricity Demand and Supply, the annual generation cost will rise by 286 billion won and (1.2 trillion won) in 2020. Such social costs are found to occur even when establishing and executing the Basic plan according to the target goal set by its higher-ranking plan, the National Energy Master Plan. In addition, when another higher-ranking GHG reduction master plan requires the electricity sector to reduce emissions by additional 5% in the GHG emissions from the right mix in electricity generation with 'zero' cost of carbon emission, the annual generation cost will rise by approximately 915 billion won in 2020. On the other hand, the analysis finds that since economic feasibility of electric powers in Korea varies significantly depending on their type, Korea is expected to face very small potential social costs caused by uncertainties over the future price of carbon dioxide in the process of establishing the Basic Plan.

• Clean Technology
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• v.22 no.2
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• pp.132-138
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• 2016

The emission of SO₂ is inevitable in case of combustion of most fossil fuels except LNG in commercial power plant which has a bad effect on the durability of SCR catalyst. To develop a low temperature SCR catalyst which has a high NOx removal performance and excellent durability to SO₂, V₂O₅/TiO₂ catalysts were prepared by coating on the metal foam substrate with the impregnation amount of Sb₂O₃ as promotor. This study has evaluated the NOx removal performance and the durability to SO₂ on a laboratory scale atmospheric reactor and analyzed the properties of the prepared catalysts by means of porosimeter, BET, SEM (scanning electron microscope), EDX (energy dispersive x-ray spectrometer), XPS (X-ray photoelectron spectroscopy). It was found that the surface area of catalyst increased with the impregnation amount of Sb₂O₃ and the NOx removal performance showed the highest value at the 2 wt% impregnation of Sb₂O₃. This results was considered to be due to the optimum active site on the catalyst surface. And also, Sb₂O₃ impregnated catalysts presented that NOx removal performance was maintained despite the exposure to SO₂ for 5 hours. Therefore it was confirmed that metal foam SCR catalyst for low temperature could be manufactured with the optimum control of Sb₂O₃ impregnation according to the SO₂ presence or not.

• Journal of the Korean Institute of Gas
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• v.26 no.3
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• pp.45-53
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• 2022

In order to improve the emission of diesel engines, natural gas-diesel dual fuel combustion compression ignition engines are in the spotlight. In particular, a reactivity controlled compression ignition (RCCI) combustion strategy is investigated comprehensively due to its possibility to improve both efficiency and emissions. With advanced diesel direct injection timing earlier than TDC, it achieves spontaneous reaction with overall lean mixture from a homogeneous mixture in the entire cylinder area, reducing nitrogen oxides (NOx) and particulate matter (PM) and improving braking heat efficiency at the same time. However, there is a disadvantage in that the amount of incomplete combustion increases in a low load region with a relatively small amount of fuel-air. To solve this, sensitive control according to the diesel injection timing and fuel ratio is required. In this study, experiments were conducted to improve efficiency and exhaust emissions of the natural gas-diesel dual fuel engine at low load, and evaluate combustion stability according to the diesel injection timing at the operation point for power generation. A 6 L-class commercial diesel engine was used for the experiment which was conducted under a 50% load range (~50 kW) at 1,800 rpm. Two injectors with different spray patterns were applied to the experiment, and the fraction of natural gas and diesel injection timing were selected as main parameters. Based on the experimental results, it was confirmed that the brake thermal efficiency increased by up to 1.3%p in the modified injector with the narrow-angle injection added. In addition, the spray pattern of the modified injector was suitable for premixed combustion, increasing operable range in consideration of combustion instability, torque reduction, and emissions level under Tier-V level (0.4 g/kWh for NOx).

• Korean Journal of Environmental Biology
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• v.39 no.4
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• pp.526-535
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• 2021

Spatial sampling design plays an important role in GIS-based modeling studies because it increases modeling efficiency while reducing the cost of sampling. In the field of agricultural systems, research demand for high-resolution spatial databased modeling to predict and evaluate climate change impacts is growing rapidly. Accordingly, the need and importance of spatial sampling design are increasing. The purpose of this study was to design spatial sampling of paddy fields (11,386 grids with 1 km spatial resolution) in Korea for use in agricultural spatial modeling. A stratified random sampling design was developed and applied in 2030s, 2050s, and 2080s under two RCP scenarios of 4.5 and 8.5. Twenty-five weather and four soil characteristics were used as stratification variables. Stratification and sample allocation were optimized to ensure minimum sample size under given precision constraints for 16 target variables such as crop yield, greenhouse gas emission, and pest distribution. Precision and accuracy of the sampling were evaluated through sampling simulations based on coefficient of variation (CV) and relative bias, respectively. As a result, the paddy field could be optimized in the range of 5 to 21 strata and 46 to 69 samples. Evaluation results showed that target variables were within precision constraints (CV<0.05 except for crop yield) with low bias values (below 3%). These results can contribute to reducing sampling cost and computation time while having high predictive power. It is expected to be widely used as a representative sample grid in various agriculture spatial modeling studies.