• Journal of the Korean earth science society
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• v.28 no.2
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• pp.248-254
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• 2007

Recently lots of the Early Cambrian fauna were described from the Yunnan Province of China. The fauna occurs from the Maotiangshan shale that dated between 525 and 520 ma, which is about 10-20 million years earlier than the Burgess Shale fauna of Canadian Rocky Mountain and Sirius Passet fauna in North Greenland. The Chengjiang fauna comprises an extremely diverse faunal assembly, and soft body parts of the fauna are well preserved. Such condition probably resulted from repeated rapid burial environment that prevented the bodies from destruction by currents, bioturbation, and biolchemical activities.

• KIEAE Journal
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• v.13 no.2
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• pp.123-130
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• 2013

The primary goal of this research is to identify the impacts of window design on the energy use in buildings which takes up about 25% of the total energy consumption. Recently, efficient use of energy is gaining more importance in buildings. Window design, especially being dependent on glazing performance choices, is an important factor for reducing energy consumption in most of the buildings. It also is influenced by the latitude of the site and window orientation. This paper aims at identifying the influence of Window performance indicators(U-value, SHGC), orientation and latitude on the building energy consumption with systematically designed simulations. Comparative study has been performed for five different locations; Greenland, Korea, Singapore, Argentina and Chile along with the different window U-value and SHGC values. The results show that optimum window system with properly coordinated window performance indicators(U-value, SHGC), orientation achieves dramatic reduction of energy consumptions. Windows with low U-value could reduce heating loads and high SHGC could reduce cooling loads. The study also verifies that the windows installed at south facade is more energy efficient in the northern hemisphere while windows facing north is more energy efficient in the southern hemisphere.

• Ocean and Polar Research
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• v.23 no.1
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• pp.51-62
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• 2001

The Arctic consists of numerous sedimentary basins containing voluminous natural resources and two of the world's major oil and gas producing areas. The western Siberia Basin in the Arctic region has the largest petroliferous province with an area of 800 ${\times}$ 1,200 km and produces more than 60% of total Russian oil production. The North Slope of Alaska produces about 20% of the U.S. output, i.e., 11% of the total U.S. consumption. Being small compared to those regions, the Canadian Northwest Territories and the Pechora Basin in Russia produce only fair amount of oil and natural gas. There are also many promising areas in the northern continental shelf of Russia. In addition to Russia, Svalbard and Greenland have been investigated for oil and gas. Gas hydrates are widespread in both permafrost regions and arctic continental shelf areas. The reserves of gas hydrates in the Arctic Ocean are about 20${\sim}$32% of total estimated amounts of gas hydrates in the world ocean. Mineral mining is well developed, especially in Russia. The major centers are located around the Kuznetsk Basin and Noril'sk. They are major suppliers of gold, tin, nickel, copper, platinum, cobalt, iron ore, coal as well as apatite. There are also some minings of lead-zinc in Alaska and Arctic Canada.

• Journal of Coastal Disaster Prevention
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• v.4 no.3
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• pp.133-137
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• 2017

The Arctic region remains surrounded by sea ice during most of the period of the year. In the Arctic Ocean the Northern Sea Route (NSR) has been used as an important route for shipping. The arctic sea ice is decreasing since 1979; hence needs to be monitored. In this research work sea ice concentration in the recent years and sea ice concentration anomalies of few months with long term sea ice concentration are studied. The climatology of long term ice concentration data from various satellites, and the recent sea ice concentration data from Advanced Microwave Scanning Radiometer 2 (AMSR2) were used. The results show that sea ice concentration and sea ice extent in the Arctic region decreased by around 5% from 2015 to 2016, but in 2017 increased again in smaller amount in some areas like around Novaya Zemlya, and parts of the sea in between Greenland and Longyearbyen, and around Banks Island. The percentages of sea ice area in NSR for July 7 in 2015 to 2017 were 37%, 39% and 33%, respectively, indicating a large area (around ten thousand $km^2$) become ice free in 2017 compared to the previous year.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.586-594
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• 2011

Gravity Recovery and Climate Experiment (GRACE), launched in April, 2002, makes it possible to monitor Earth's mass redistribution with its time-varying gravity observation. GRACE provides monthly gravity solutions as coefficients of spherical harmonics, and thus ones need to convert the gravity spectrum to gravity grids (or mass grids) via the spherical harmonics. GRACE gravity solutions, however, include spatial alias error as well as noise, which requires to suppress in order to enhance signal to noise ratio. In this study, we present the GRACE data processing procedures and introduce some applications of time-varying gravity, which are studies of terrestrial water storage changes, Antarctic and Greenland ice melting, and sea level rise. Satellite missions such as GRACE will continue up to early 2020, and they are expected to be an essential resource to understand the global climate changes.

• Safety and Health at Work
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• v.2 no.3
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• pp.236-242
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• 2011

Objectives: To determine the feasibility of predicting static and dynamic peak back-compressive forces based on (1) static back compressive force values at the lift origin and destination and (2) lifting speed. Methods: Ten male subjects performed symmetric mid-sagittal floor-to-shoulder, floor-to-waist, and waist-to-shoulder lifts at three different speeds (slow, medium, and fast), and with two different loads (light and heavy). Two-dimensional kinematics and kinetics were captured. Linear regression analyses were used to develop prediction equations, the amount of predictability, and significance for static and dynamic peak back-compressive forces based on a static origin and destination average (SODA) backcompressive force. Results: Static and dynamic peak back-compressive forces were highly predicted by the SODA, with R2 values ranging from 0.830 to 0.947. Slopes were significantly different between slow and fast lifting speeds (p < 0.05) for the dynamic peak prediction equations. The slope of the regression line for static prediction was significantly greater than one with a significant positive intercept value. Conclusion: SODA under-predict both static and dynamic peak back-compressive force values. Peak values are highly predictable and could be readily determined using back-compressive force assessments at the origin and destination of a lifting task. This could be valuable for enhancing job design and analysis in the workplace and for large-scale studies where a full analysis of each lifting task is not feasible.

• Safety and Health at Work
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• v.4 no.2
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• pp.105-110
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• 2013

Background: To determine the influence of lifting speed and type on peak and cumulative back compressive force (BCF) and shoulder moment (SM) loads during symmetric lifting. Another aim of the study was to compare static and dynamic lifting models. Methods: Ten male participants performed a floor-to-shoulder, floor-to-waist, and waist-to-shoulder lift at three different speeds [slow (0.34 m/s), medium (0.44 m/s), and fast (0.64 m/s)], and with two different loads [light (2.25 kg) and heavy (9 kg)]. Two-dimensional kinematics and kinetics were determined. A three-way repeated measures analysis of variance was used to calculate peak and cumulative loading of BCF and SM for light and heavy loads. Results: Peak BCF was significantly different between slow and fast lifting speeds (p < 0.001), with a mean difference of 20% between fast and slow lifts. The cumulative loading of BCF and SM was significantly different between fast and slow lifting speeds (p < 0.001), with mean differences ${\geq}80%$. Conclusion: Based on peak values, BCF is highest for fast speeds, but the BCF cumulative loading is highest for slow speeds, with the largest difference between fast and slow lifts. This may imply that a slow lifting speed is at least as hazardous as a fast lifting speed. It is important to consider the duration of lift when determining risks for back and shoulder injuries due to lifting and that peak values alone are likely not sufficient.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.29-37
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• 2019

Synthetic Aperture Radar (SAR) observations are powerful tools to monitor surface's displacement very accurately, induced by earthquake, volcano, ground subsidence, glacier movement, etc. Especially, radar interferometry (InSAR) which utilizes phase information related to distance from sensor to target, can generate displacement map in line-of-sight direction with accuracy of a few cm or mm. Due to decorrelation effect, however, degradation of coherence in the InSAR application often prohibit from construction of differential interferogram. Offset tracking method is an alternative approach to make a two-dimensional displacement map using intensity information instead of the phase. However, there is limitation in that the offset tracking requires very intensive computation power and time. In this paper, efficiency of parallel computing has been investigated using high performance computer for estimation of glacier velocity. Two TanDEM-X SAR observations which were acquired on September 15, 2013 and September 26, 2013 over the Narsap Sermia in Southwestern Greenland were collected. Atotal of 56 of 2.4 GHz Intel Xeon processors(28 physical processors with hyperthreading) by operating with linux environment were utilized. The Gamma software was used for application of offset tracking by adjustment of the number of processors for the OpenMP parallel computing. The processing times of the offset tracking at the 256 by 256 pixels of window patch size at single and 56 cores are; 26,344 sec and 2,055 sec, respectively. It is impressive that the processing time could be reduced significantly about thirteen times (12.81) at the 56 cores usage. However, the parallel computing using all the processors prevent other background operations or functions. Except the offset tracking processing, optimum number of processors need to be evaluated for computing efficiency.

• Journal of Ecology and Environment
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• v.46 no.4
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• pp.282-291
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• 2022

Background: The Arctic permafrost stores enormous amount of carbon (C), about one third of global C stocks. However, drastically increasing temperature in the Arctic makes the stable frozen C stock vulnerable to microbial decomposition. The released carbon dioxide from permafrost can cause accelerating C feedback to the atmosphere. Soil organic matter (SOM) composition would be the basic information to project the trajectory of C under rapidly changing climate. However, not many studies on SOM characterization have been done compared to quantification of SOM stocks. Thus, the purpose of our study is to determine soil properties and molecular compositions of SOM in four different Arctic regions. We collected soils in different soil layers from 1) Cambridge Bay, Canada, 2) Council, Alaska, USA, 3) Svalbard, Norway, and 4) Zackenberg, Greenland. The basic soil properties were measured, and the molecular composition of SOM was analyzed through pyrolysis-gas chromatography/mass spectrometry (py-GC/MS). Results: The Oi layer of soil in Council, Alaska showed the lowest soil pH and the highest electrical conductivity (EC) and SOM content. All soils in each site showed increasing pH and decreasing SOC and EC values with soil depth. Since the Council site was moist acidic tundra compared to other three dry tundra sites, soil properties were distinct from the others: high SOM and EC, and low pH. Through the py-GC/MS analysis, a total of 117 pyrolysis products were detected from 32 soil samples of four different Arctic soils. The first two-axis of the PCA explained 38% of sample variation. While short- and mid-hydrocarbons were associated with mineral layers, lignins and polysaccharides were linked to organic layers of Alaska and Cambridge Bay soil. Conclusions: We conclude that the py-GC/MS results separated soil samples mainly based on the origin of SOM (plants- or microbially-derived). This molecular characteristics of SOM can play a role of controlling SOM degradation to warming. Thus, it should be further investigated how the SOM molecular characteristics have impacts on SOM dynamics through additional laboratory incubation studies and microbial decomposition measurements in the field.

• ALGAE
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• v.39 no.2
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• pp.75-96
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• 2024

Rhodomonas (Cryptophyceae) and species assigned to this genus have undergone numerous taxonomic revisions. This also applies to R. marina studied here as it was originally assigned as a species of Cryptomonas and later considered a variation of R. baltica, the type species. Despite being described more than 130 years ago, R. marina still lacks a comprehensive characterization. Light and electron microscopy were employed to delineate a strain from western Greenland. The living cells were 18 ㎛ long and 9 ㎛ wide, elliptical in shape with a pointed to rounded posterior and truncated anterior in lateral view. Two sub-equal flagella emerged from a vestibulum, where also a furrow extended. In transmission electron microscopy, the furrow was associated with a tubular gullet and the pyrenoid embedded in a deeply lobed chloroplast. The chloroplast contained DNA in perforations and was surrounded by starch grains. A tubular nucleomorph was enclosed within the pyrenoid matrix. In scanning electron microscopy, the inner periplast consisted of rectangular plates with rounded edges and posteriorly these were replaced by a sheet-like structure. The water-soluble pigment was Crypto-Phycoerythrin type I (Cr-PE 545). A phylogenetic inference based on SSU rDNA confirmed the identity of strain S18 as a species of Rhodomonas as it clustered with congeners but also Rhinomonas, Storeatula, and Pyrenomonas. These genera formed a monophyletic clade separated from a diverse assemblage of other cryptophyte genera. To further explore the phylogeny of R. marina a concatenated phylogenetic analysis based on the SSU rDNA-ITS1-5.8S rDNA-ITS2-LSU rDNA region was performed but included only closely related species. The secondary structure of nuclear internal transcribed spacer 2 was predicted and compared to similar structures in related species. Using morphological and molecular signatures as diagnostic features the description of R. marina was emended.