• Journal of the Korean Society for Marine Environment & Energy
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• v.11 no.1
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• pp.24-34
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• 2008

To mitigate the climate change and global warming, various technologies have been internationally proposed for reducing greenhouse gas emissions. Especially, in recent, carbon dioxide capture and storage (CCS) technology is regarded as one of the most promising emission reduction options that $CO_2$ be captured from major point sources (eg., power plant) and transported for storage into the marine geological structure such as deep sea saline aquifer. The purpose of this paper is to review the latest progress on the development of technologies for $CO_2$ storage in marine geological structure and its perspective in republic of Korea. To develop the technologies for $CO_2$ storage in marine geological structure, we carried out relevant R&D project, which cover the initial survey of potentially suitable marine geological structure fur $CO_2$ storage site and monitoring of the stored $CO_2$ behavior, basic design for $CO_2$ transport and storage process including onshore/offshore plant and assessment of potential environmental risk related to $CO_2$ storage in geological structure in republic of Korea. By using the results of the present researches, we can contribute to understanding not only how commercial scale (about 1 $MtCO_2$) deployment of $CO_2$ storage in the marine geological structure of East Sea, Korea, is realized but also how more reliable and safe CCS is achieved. The present study also suggests that it is possible to reduce environmental cost (about 2 trillion Won per year) with developed technology for $CO_2$ storage in marine geological structure until 2050.

• Economic and Environmental Geology
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• v.48 no.1
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• pp.25-39
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• 2015

$CO_2$ geological storage plays an important role in reduction of greenhouse gas emissions, but there is a lack of research for CCS demonstration. To achieve the goal of CCS, storing $CO_2$ safely and permanently in underground geological formations, it is essential to understand the characteristics of them, such as total storage capacity, stability, etc. and establish an injection strategy. We perform the impedance inversion for the seismic data acquired from the Ulleung Basin in 2012. To review the possibility of $CO_2$ storage, we also construct porosity models and extract attributes of the prospects from the seismic data. To improve the quality of seismic data, amplitude preserved processing methods, SWD(Shallow Water Demultiple), SRME(Surface Related Multiple Elimination) and Radon Demultiple, are applied. Three well log data are also analysed, and the log correlations of each well are 0.648, 0.574 and 0.342, respectively. All wells are used in building the low-frequency model to generate more robust initial model. Simultaneous pre-stack inversion is performed on all of the 2D profiles and inverted P-impedance, S-impedance and Vp/Vs ratio are generated from the inversion process. With the porosity profiles generated from the seismic inversion process, the porous and non-porous zones can be identified for the purpose of the $CO_2$ sequestration initiative. More detailed characterization of the geological storage and the simulation of $CO_2$ migration might be an essential for the CCS demonstration.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.4
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• pp.268-273
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• 2023

The present study estimated rumen fermentation characteristics and greenhouse gas emissions of different forages. Alfalfa, timothy, tall fescue, Italian ryegrass, and rice straw as the main forage sources for Hanwoo were used in the present study. Crude protein was highest in alfalfa but lowest in rice straw (p<0.05). Ether extract was higher in alfalfa and Italian ryegrass than in the other forages (p<0.05). Crude ash was highest in rice straw but lowest in tall fescue (p<0.05). Neutral detergent fiber was highest in tall fescue but lowest in alfalfa (p<0.05). Acid detergent fiber was highest in Italian ryegrass and rice straw but lowest in alfalfa (p<0.05). In vitro digestibilities of dry matter (DMD) and neutral detergent fiber (NDFD) were highest in timothy but lowest in rice straw (p<0.05). Rumen pH was highest (p<0.05) in alfalfa, while ammonia-N was higher (p<0.05) in alfalfa and Italian ryegrass than in the other forages. Total volatile fatty acid was highest (p<0.05) in timothy, while acetate and propionate were highest (p<0.05) in alfalfa and rice straw, respectively. Acetate to propionate ratio was higher (p<0.05) in alfalfa, timothy, and Italian ryegrass than in rice straw. Rice straw had lowest total gas (mL) (p<0.05) but highest its per DMD and NDFD. Rice straw had higher (p<0.05) CO₂ (per DMD and NDFD) compared to alfalfa (per DMD and NDFD), timothy (per DMD and NDFD), tall fescue (per NDFD), and Italian ryegrass (per DMD). Again, rice straw had higher (p<0.05) CH₄ (per DMD and NDFD) compared to timothy (per DMD and NDFD) and tall fescue (per NDFD). Therefore, this study indicates that timothy has a higher nutrient digestibility and volatile fatty acid in the rumen leading to a reduction of greenhouse gas emission.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.481-493
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• 2023

In high-density urban areas, the urban heat island effect increases urban temperatures, leading to negative impacts such as worsened air pollution, increased cooling energy consumption, and increased greenhouse gas emissions. In urban environments where it is difficult to secure additional green spaces, rooftop greening is an efficient greenhouse gas reduction strategy. In this study, we not only analyzed the current status of the urban heat island effect but also utilized high-resolution satellite data and spatial information to estimate the available rooftop greening area within the study area. We evaluated the mitigation effect of the urban heat island phenomenon and carbon sequestration capacity through temperature predictions resulting from rooftop greening. To achieve this, we utilized WorldView-2 satellite data to classify land cover in the urban heat island areas of Busan city. We developed a prediction model for temperature changes before and after rooftop greening using machine learning techniques. To assess the degree of urban heat island mitigation due to changes in rooftop greening areas, we constructed a temperature change prediction model with temperature as the dependent variable using the random forest technique. In this process, we built a multiple regression model to derive high-resolution land surface temperatures for training data using Google Earth Engine, combining Landsat-8 and Sentinel-2 satellite data. Additionally, we evaluated carbon sequestration based on rooftop greening areas using a carbon absorption capacity per plant. The results of this study suggest that the developed satellite-based urban heat island assessment and temperature change prediction technology using Random Forest models can be applied to urban heat island-vulnerable areas with potential for expansion.

• Journal of Environmental Impact Assessment
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• v.26 no.2
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• pp.127-139
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• 2017

Measurements of net ecosystem exchange (NEE) of $CO_2$ based on the eddy covariance technique provide reasonable carbon balance estimates in response to local environmental conditions. In South Korea, the forest ecosystems cover approximately 64% of the total area, thereby strongly affecting regional carbon balances. Cultivated croplands that cover about 17% of the total area should also be considered when calculating the carbon balance of the country. In this study, our objectives were (a) to quantify the range and seasonal variation of NEE at forest ecosystems, including deciduous, coniferous, and mixed forests, and agricultural ecosystems, including rice paddies and a potato field, in South Korea and (b) to compare NEE at ten Fluxnet sites that have the same or similar ecosystems as found in South Korea. The results showed that the forest and agricultural ecosystems were carbon sinks. In Korea, NEE at the forest ecosystems varied between -31 and $-362gC/m^2/yr$, and NEE at the croplands ranged from -210 to $-248gC/m^2/growing$ season. At the deciduous forest, NEE reached low values in late spring, early summer, and early autumn, while at the coniferous forest, it reached low values in spring, early summer, and mid autumn. The young mixed forest was a much stronger carbon sink than the old-growth deciduous and coniferous forests. During each crop growing season, beet had the lowest NEE value within six crops, followed by wither wheat, maize, rice, potato, and soybean. These results will be useful for designing and applying management strategies for the reduction of $CO_2$ emissions.