• Applied Chemistry for Engineering
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• v.33 no.5
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• pp.488-495
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• 2022

Activated carbon (AC) and carbon molecular sieve (CMS) have attracted attention as porous materials for recovery and separation of greenhouse gases. The carbon molecular sieve having uniform pores is used for collecting and separating gases because it may selectively adsorb a specific gas. The size and uniformity of pores determine the performance of the CMS, and chemical vapor deposition (CVD) is widely used to coat the surface with a predetermined thickness in order to control the CMS's micropores. This CVD method can be used to control the size of pores in CMS manufacturing, but it must be optimized because of its various experimental variables. Therefore, in order to produce AC and CMS for gas adsorption and separation, this review focuses on various activation processes and pore control technologies by CVD and surface treatment.

• Korean Journal of Materials Research
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• v.33 no.5
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• pp.175-188
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• 2023

Water electrolysis holds great potential as a method for producing renewable hydrogen fuel at large-scale, and to replace the fossil fuels responsible for greenhouse gases emissions and global climate change. To reduce the cost of hydrogen and make it competitive against fossil fuels, the efficiency of green hydrogen production should be maximized. This requires superior electrocatalysts to reduce the reaction energy barriers. The development of catalytic materials has mostly relied on empirical, trial-and-error methods because of the complicated, multidimensional, and dynamic nature of catalysis, requiring significant time and effort to find optimized multicomponent catalysts under a variety of reaction conditions. The ultimate goal for all researchers in the materials science and engineering field is the rational and efficient design of materials with desired performance. Discovering and understanding new catalysts with desired properties is at the heart of materials science research. This process can benefit from machine learning (ML), given the complex nature of catalytic reactions and vast range of candidate materials. This review summarizes recent achievements in catalysts discovery for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). The basic concepts of ML algorithms and practical guides for materials scientists are also demonstrated. The challenges and strategies of applying ML are discussed, which should be collaboratively addressed by materials scientists and ML communities. The ultimate integration of ML in catalyst development is expected to accelerate the design, discovery, optimization, and interpretation of superior electrocatalysts, to realize a carbon-free ecosystem based on green hydrogen.

• Korean Journal of Soil Science and Fertilizer
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• v.45 no.6
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• pp.1157-1163
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• 2012

This study was performed a comparative life cycle assessment (LCA) among three rice production systems in order to analyze the difference of greenhouse gases (GHGs) emissions and environment impacts. Its life cycle inventory (LCI) database (DB) was established using data obtained from interview with conventional, without agricultural chemical and organic farming at Gunsan and Iksan, Jeonbuk province in 2011. According to the result of LCI analysis, $CO_2$ was mostly emitted from fertilizer production process and rice cropping phase. $CH_4$ and $N_2O$ were almost emitted from rice cultivation phase. The value of carbon footprint to produce 1 kg rice (unhulled) on conventional rice production system was 1.01E+00 kg $CO_2$-eq. $kg^{-1}$ and it was the highest value among three rice production systems. The value of carbon footprints on without agricultural chemical and organic rice production systems were 5.37E-01 $CO_2$-eq. $kg^{-1}$ and 6.58E-01 $CO_2$-eq. $kg^{-1}$, respectively. Without agricultural chemical rice production system whose input amount was the smallest had the lowest value of carbon footprint. Although the yield of rice from organic farming was the lowest, its value of carbon footprint less than that of conventional farming. Because there is no compound fertilizer inputs in organic farming. Compound fertilizer production and methane emission during rice cultivation were the main factor to GHGs emission in conventional and without agricultural chemical rice production systems. In organic rice production system, the main factors to GHGs emission were using fossil fuel on machine operation and methane emission from rice paddy field.

• Journal of the Korean Applied Science and Technology
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• v.29 no.3
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• pp.450-458
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• 2012

In order to reduce the effects of greenhouse gas (GHG) emissions, the South Korean government has announced a special platform of technologies as part of an effort to minimize global climate change. To further this effort, the Korean government has pledged to increase low-carbon and carbon neutral resources for biofuel derived from biomass to replace fossil and to decrease levels of carbon dioxide. In general, second generation biofuel produced form woody biomass is expected to be an effective avenue for reducing fossil fuel consumption and greenhouse gas (GHG) emissions in road transport. It is important that under the new Korean initiative, pilot scale studies evolve practices to produce biomass-to-liquid (BTL) fuel. This study reports the quality characteristics of F-T(Fischer-Tropsch) diesel for production of BTL fuel. Synthetic F-Tdiesel fuel can be used in automotive diesel engines, pure or blended with automotive diesel, due to its similar physical properties to diesel. F-T diesel fuel was synthesized by Fischer-Tropsch (F-T) process with syngas($H_2$/CO), Fe basedcatalyst in low temperature condition($240^{\circ}C$). Synthetic F-T diesel with diesel compositions after distillation process is consisted of $C_{12}{\sim}C_{23+}$ mixture as a kerosine, diesel compositions of n-paraffin and iso-paraffin compounds. Synthetic F-T diesel investigated a very high cetane number, low aromatic composition and sulfur free level compared to automotive diesel. Synthetic F-T diesel also show The wear scar of synthetic F-T diesel show poor lubricity due to low content of sulfur and aromatic compounds compared to automotive diesel.

• Journal of Korean Society of Forest Science
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• v.109 no.1
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• pp.41-49
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• 2020

In this study, the effect of seed pre-treatments and pellet coating materials to enhance the efficiency of large-scale propagation of Aster koraiensis seeds were investigated. Seeds were immersed in water for one day, and only those that sank were used for pre-treatment to use filled seeds. Pre-treatments were divided into hormone treatments, with gibberellic acid (GA₃; 200 and 500 ppm) and 24-epibrassinolide (10^-6, 10^-7, and 10^-8M), and priming with potassium nitrate (100 mM of KNO₃). To produce pellet-coated seeds, pellet materials (DTCS or DTK) were applied to control (unprimed) and primed seeds with binders (PVA or CMC). The maximum germination percent (GP) of seeds before pellet coating was 65% (with the priming treatment), and there was no difference in the GP of seeds among hormone treatments. For seeds sown in a growth chamber on filter paper, GP was 41% for control (unprimed/uncoated) seeds, 65% for uncoated primed seeds, 71% for DTCS/PVA-pellet-coated seeds, and 42% for DTK/CMC-pellet-coated seeds. Seeds that were primed first and then pellet-coated showed greatly improved GP, mean germination time (MGT), and germination rate than seeds that were only pellet-coated. For seeds sown in commercial soil in a greenhouse, control seeds had a GP of 27%, whereas primed seeds had the highest GP (58%), and their MGT and GT were 9.4 days and 7.0%·day, respectively. In addition, DTK/PVA-pellet-coated seeds (40%) also had a GP higher than the control (27%), and their MGT was 15-27 days. For seeds sown in sandy-loam soil in a greenhouse, unprimed-pellet-coated seeds and primed-pellet-coated seeds both had GPs ranged of 39%, which were lower than that of control seeds. In general, the seeds that were pellet-coated with DTK had a higher GP than those pellet-coated with DTCS. Furthermore, the MGT of unprimed-pellet-coated seeds was 15.0-19.8 days, which was longer than the MGT of primed-pellet-coated seeds. These results suggest that priming enhances seedling emergence of Aster koraiensis seeds. Moreover, when priming is combined with pellet coating, DTK is a more suitable pellet material than DTCS, and PVA and CMC are equally suitable adhesives.

• Journal of Korean Society of Forest Science
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• v.96 no.3
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• pp.307-316
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• 2007

Yellow poplar (Liriodendron tulipifera L.) has low germination rate relatively other species, so the seedling production of Yellow poplar is a hard task. Accordingly this study was conducted to determine the optimal germination conditions for healthy seedling production and to promote survival rate after afforestation. Gemination percentage was examined at different media and seed covering materials using planting flats in the greenhouse. The best germination percentage was observed in sand for media and compound soil for covering materials. But it was time to transplant, seedlings became a poor character (i.e. height, root length, number of root, dry weight) in sand for media. In order to produce healthy seedlings, each different medium was compounded with TKS-2 (this is a gardening bed soil.) in the ratio 1:1 (v/v.), and compared two conditions. Quality of seedling was better than not mixed TKS-2 into each medium. Transplanting seedlings from greenhouse to nursery grew up rapidly 2 months later (early in August~early in October). Growth amount during two months corresponded to 85.6% and 71.3% in total growth amount of height and diameter at root collar, respectively. In the case of the competition-density effect on yellow-poplar seedlings, direct seedling produced the maximum 35 standard seedlings above 8 mm of root collar diameter per $m^2$, while transplanting seedling produced the maximum 64 standard seedlings per $m^2$. And produced seedlings of two way were significantly different rootlet while axial root and lateral root was not significantly different.

• Journal of Korean Society of Forest Science
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• v.98 no.4
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• pp.409-416
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• 2009

Forest biomass estimation is essential for greenhouse gas inventories and terrestrial carbon accounting. Remote sensing allows for estimating forest biomass over a large area. This study was conducted to estimate forest biomass and to produce a forest biomass map for Muju county using forest biomass conversion table developed by field plot data from the 5th National Forest Inventory and Landsat TM-5. Correlation analysis was carried out to select suitable independent variables for developing regression models. It was resulted that the height class, crown closure density, and age class were highly correlated with forest biomass. Six regression models were used with the combination of these three stand variables and verified by validation statistics such as root mean square error (RMSE) and mean bias. It was found that a regression model with crown closure density and height class (Model V) was better than others for estimating forest biomass. A biomass conversion table by model V was produced and then used for estimating forest biomass in the study site. The total forest biomass of the Muju county was estimated about 8.8 million ton, or 128.3 ton/ha by the conversion table.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.73-81
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• 2015

The objective of this study is in investigating the research for more accurately quantify the information on mountain forest by using the data on high density LiDAR. For the quantitative analysis of mountain forest resources, we investigated the method to acquire the data on high density LiDAR and extract mountain forest resources. Consequently, the height and girth of a tree each mountain forest resources could be extracted by using the data on high density LiDAR. When using the data on low density LiDAR of 2.5points/m² in average used to produce digital map, it was difficult to extract the exact height and girth of mountain forest resources. If using the data on high density LiDAR of 7points/m² by considering topography, the property of mountain forest resources, data capacity and process velocity, etc, it was found that multitudinous entities could be extracted. It was found that mountain topography and mixed topography were generally denser than plane topography and multitudinous mountain forest resources could be extracted. Furthermore, it was also found that the entity at the border could not be extracted, when each partition was individually processed and the area should be subdivided and extracted by considering the process time and property of target area rather than processing wide area at once. We expect to be studied more profoundly the absorption quantity of greenhouse gas later by using information on mountain forest resources in the future.

• Korean Journal of Environmental Agriculture
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• v.25 no.4
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• pp.339-345
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• 2006

Accumulation of nitrate in green vegetables is undesirable due to potential risks to human health. Lettuce was cultivated in pots under greenhouse conditions with compost applications of 2,000 and 4,000 kg/10a, and the growth and nitrate accumulation of lettuce were compared with those found in the lettuce cultivated with chemical fertilizers of recommended levels. Content of $NH_4-N$ in the soils of compost applications were much lower than those found in the soil of chemical fertilizer application. Two weeks after lettuce transplant $NH_4-N$ was not found in the soils of compost applications, and in the soils of chemical fertilizers application $NH_4-N$ was not found three weeks after lettuce transplant. One week after lettuce transplant content of $NO_3-N$ was much higher in the soils of compost applications, and the contents were rapidly decreased. While, the content of $NO_3-N$ in the soil of chemical fertilizers application was rapidly increased due to the nitrification of $NH_4$ released from the applied urea. At the time of harvest contents of $NO_3-N$ in the soils of compost applications were less than 1.4 mg/kg, but in the soil of chemical fertilizers application the content of $NO_3-N$ was 54.2 mg/kg. Contents of $NH_4$ in lettuce were about 20 mg/kg FW and were not much different among the treatments. However, contents of $NO_3$ in lettuce were significantly different between the treatments of chemical fertilizer and compost. There were significant differences in fresh and dry weights, and growth of lettuce in the compost treatment of 4,000 kg/10a was highest among the treatments. These results indicate that the cultivation with compost only as N source can produce higher yield of lettuce and significantly reduce nitrate accumulation as compared to the conventional cultivation with chemical fertilizers.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.211-218
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• 2012

Fossil fuel is used all over the world and it produces greenhouse gases due to fossil fuel use. Therefore, it cause global warming and is serious environmental pollution. In order to decrease the environmental pollution, we should use renewable energy which is clean energy. Among several renewable energy, wind energy is the most promising one. Wind power generation is does not produce environmental pollution and could not be exhausted. However, due to wind power generation has irregular power output, it is important to predict generated electrical energy accurately for smoothing wind energy supply. There, we consider use ramp characteristic to forecast accurate wind power output. The ramp increase and decrease rapidly wind power generation during in a short time. Therefore, it can cause problem of unbalanced power supply and demand and get damaged wind turbine. In this paper, we make prediction models using power ramp rate as well as wind speed and wind direction to increase prediction accuracy. Prediction model construction algorithm used multilayer neural network. We built four prediction models with PRR, wind speed, and wind direction and then evaluated performance of prediction models. The predicted values, which is prediction model with all of attribute, is nearly to the observed values. Therefore, if we use PRR attribute, we can increase prediction accuracy of wind power generation.