• Journal of Korea Port Economic Association
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• v.39 no.4
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• pp.107-125
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• 2023

The pace of sustainability transition within the maritime industry has been accelerating. This shift primarily necessitates changes in the industry's heavy reliance on fossil fuel-driven ecosystems. Additionally, numerous sustainability laws and regulations, such as the EU's CBAM and IMO's EEXI, have been implemented. This transition is poised to amplify the competitive edge of firms equipped with greater resources, as it introduces substantial operational burdens due to expensive eco-friendly fuel adoption and regulatory compliance. To diverge from the traditional competitive landscape, this paper aims to explore innovative maritime finance models enabling domestic firms to gain competitive advantages on a global scale. Employing analogical reasoning and modeling as a research method, this paper demonstrates that maritime firms can leverage the sustainability transition by aligning sustainable maritime operations with ETS (Emission Trading Schemes). Expanding on this novel approach, the paper delves into potential connections between CCM (Compliance Carbon Market), VCM (Voluntary Carbon Market), and digital asset exchanges. This newly proposed digital/net-zero maritime ecosystem holds the potential to significantly impact the shipping, shipbuilding, and ship finance industries, positioning Busan as a sustainable maritime finance hub. This study holds significance as pioneering research that may stimulate subsequent case-based studies and offer strategic guidance to market participants and policymakers as the maritime industry moves towards a net-zero transition

• Journal of the Korean Society for information Management
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• v.38 no.3
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• pp.23-39
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• 2021

This study aims to explore research trends in Blockchain studies in South Korea using dynamic topic modeling and network analysis. To achieve this goal, we conducted the university & institute collaboration network analysis, the keyword co-occurrence network analysis, and times series topic analysis using dynamic topic modeling. Through the university & institute collaboration network analysis, we found major universities such as Soongsil University, Soonchunhyang University, Korea University, Korea Advanced Institute of Science and Technology (KAIST) and major institutes such as Ministry of National Defense, Korea Railroad Research Institute, Samil PricewaterhouseCoopers, Electronics and Telecommunications Research Institute that led collaborative research. Next, through the analysis of the keyword co-occurrence network, we found major research keywords including virtual assets (Cryptocurrency, Bitcoin, Ethereum, Virtual currency), blockchain technology (Distributed ledger, Distributed ledger technology), finance (Smart contract), and information security (Security, privacy, Personal information). Smart contracts showed the highest scores in all network centrality measures showing its importance in the field. Finally, through the time series topic analysis, we identified five major topics including blockchain technology, blockchain ecosystem, blockchain application 1 (trade, online voting, real estate), blockchain application 2 (food, tourism, distribution, media), and blockchain application 3 (economy, finance). Changes of topics were also investigated by exploring proportions of representative keywords for each topic. The study is the first of its kind to attempt to conduct university & institute collaboration networks analysis and dynamic topic modeling-based times series topic analysis for exploring research trends in Blockchain studies in South Korea. Our results can be used by government agencies, universities, and research institutes to develop effective strategies of promoting university & institutes collaboration and interdisciplinary research in the field.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.627-646
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• 2022

Recently, the seriousness of climate change-related problems caused by global warming is growing, and the average temperature is also rising. As a result, it is affecting the environment in which various temperature-sensitive creatures and creatures live, and changes in the ecosystem are also being detected. Seasons are one of the important factors influencing the types, distribution, and growth characteristics of creatures living in the area. Among the most popular and easily recognized plant seasonal phenomena among the indicators of the climate change impact evaluation, the blooming day of flower and the peak day of autumn leaves were modeled. The types of plants used in the modeling were forsythia and cherry trees, which can be seen as representative plants of spring, and maple and ginkgo, which can be seen as representative plants of autumn. Weather data used to perform modeling were temperature, precipitation, and solar radiation observed through the ASOS Observatory of the Korea Meteorological Administration. As satellite data, MODIS NDVI was used for modeling, and it has a correlation coefficient of about -0.2 for the flowering date and 0.3 for the autumn leaves peak date. As the model used, the model was established using multiple regression models, which are linear models, and Random Forest, which are nonlinear models. In addition, the predicted values estimated by each model were expressed as isopleth maps using spatial interpolation techniques to express the trend of plant seasonal changes from 2003 to 2020. It is believed that using NDVI with high spatio-temporal resolution in the future will increase the accuracy of plant phenology modeling.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.20 no.3
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• pp.55-64
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• 2017

The problem of the population number of honeybees that is decreasing not only domestically but also globally, has a great influence on human beings and the entire ecosystem. The habitat of honeybees is recognized to be superior in urban environment rather than rural environment, and predicting for habitat assessment and conservation is necessary. Based on this, we targeted Cheonan City and neighboring administrative areas where the distribution of agricultural areas, urban areas, and forest areas is displayed equally. In order to predict the habitat preferred by honeybees, we apply the Maxent model what based on the presence information of the species. We also selected 10 environmental variables expected to influence honeybees habitat environment through literature survey. As a result of constructing the species distribution model using the Maxent model, 71.7% of the training data were shown on the AUC(Area Under Cover) basis, and it was be confirmed with an area of 20.73% in the whole target area, based on the 50% probability of presence of honeybees. It was confirmed that the contribution of the variable has influence on land covering, distance from the forest, altitude, aspect. Based on this, the possibility of honeybee's habitat characteristics were confirmed to be higher in wetland environment, in agricultural land, close to forest and lower elevation, southeast and west. The prediction of these habitat environments has significance as a lead research that presents the habitat of honeybees with high conservation value of ecosystems in terms of urban space, and it will be useful for future urban park planning and conservation area selection.

• Journal of Korean Society on Water Environment
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• v.28 no.1
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• pp.1-9
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• 2012

It has been known that Golf course could impose negative impacts on water-ecosystem if pollutant-laden runoff is not treated well. It is important to control non-point source and re-use treated wastewater from the golf course to secure water quality of receiving waterbodies. At golf courses, the rainfall-runoff is affected by various practices to manage grasses. In many hydrological modelings, especially in simple rainfall-runoff modeling, effects on runoff of plant growth and cutting are not considered. In the study, the water erosion prediction project (WEPP), capable of simulating plant growth and various management, was evaluated for its runoff prediction from golf course under grass cutting and irrigation. The %Difference, $R^2$ and the NSE for runoff comparisons were 1.15%, 0.93 and 0.92 for calibration, and 18.12%, 0.82 and 0.88 for validation period, respectively. In grass cutting scenario, grass height was managed to be 18~25 mm. The estimated runoff was decreased by 27%. The difference in estimated total runoff was 11.8% depending on irrigation. As shown in this study, if grass management and irrigation are well-controlled, water quality of downstream areas could be obtained.

• 한국신재생에너지학회:학술대회논문집
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• 2006.11a
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• pp.40-43
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• 2006

Public demand for the heat pump system as a next generation energy equipment is increasing for its eco-friendly and cost-effective advantage. Many researches have been concentrated on how to calculate and develop its own efficiency, while the possible effect of the heat pump operation on the whole subsurface temperature distribution is relatively less considered, During the current study, subsurface temperature disturbance caused by seasonal surface temperature cycle in Busan area and general W-tube heat pump operation is simulated in 3-dimensional heterogeneous medium. It shows that subsurface deeper than 10m from the surface remains nearly unchanged throughout the 4 seasons and groundwater convect ion in highly permeable layer near the surface acts like a main path of heat plume from heat pump system, This implies the significance of detail descript ion in shallow sedimentary layer or highly permeable layer which plays an important role on the regional flow advection and heat transfer. Also, the effect of groundwater convection increases when the arrangement of the 2 injection pipes and 2 extract ion well is maintained parallel to groundwater flow. Therefore, more careful and detail investigation is required before installation and operation of heat pump system that it may not cause any possible change of microbial ecosystem in the shallow subsurface environment or 'contamination of temperature' for groundwater use as well as the loss of efficiency of the equipment itself. This can also help to design the optimized grouting system for heat pump.

• Proceedings of KOSOMES biannual meeting
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• 2006.11a
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• pp.217-219
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• 2006

This study focused an water quality response to land-based pollution loads and the appropriate pollutant load reduction in Chinhae Bay using an eco-hydrodynamic model. Land-based discharge foam urban areas, industrial complex and sewage treatment plant was the greatest contributor to cause red-tide blooms and summer hypoxia. Tidal currents velocity af the ebb tide was about 10 cm/s stronger than that of the flood tide. A residual current was simulated to. have a slightly complicated pattern with ranging from 0.1 to. 2.7 cm/s. In Masan Bay, pollutant materials cannot flaw from the inner to the outer bay easily because af residual currents flaw southward at surface and northward at the bottom. The simulation results of COD distribution showedhigh concentrations aver 3 mg/L in the inner part of Masan Bay related pollutant discharge, and charge, and lower levels less than 1.5mg/L in the central part of Chinhae Bay. For improvement water quality in Chinhae Bay, it is necessary to reduce the organic and inorganic loads from paint sources by mare than 50% and ameliorate severe polluted sediment.

• Journal of Korean Society for Atmospheric Environment
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• v.24 no.3
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• pp.310-320
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• 2008

Concentration of tropospheric ozone ($O_3$) was investigated for the South Korea. And then the critical ozone levels, expressed as AOT40 (Accumulated exposure over a threshold of 40 ppb) to vegetation have been used in this region within the UNECE (United Nations Economic Commission for Europe) Convention on Long-Range Trans-boundary Air Pollution (CLRTAP). Hourly ozone concentration data from 1996 to 2001 at 26 air monitoring stations was used to estimate the exceedance of the critical levels. It was calculated for daylight hours for each station, and mapped using surface interpolation over the South Korea. The critical levels of ozone have shown the highly exceeded value in the Gyeonggi region, southern coastal region and central inland of the South Korea. It was some different from the typical ozone distribution which represented highly in the western inland and coastal regions. The area exceeding the critical level for crops was founded to be more than 40% of the whole South Korean territory. While that for trees was to be about 17% of the South Korea. The critical ozone critical level was based upon data from experiments on specific species, and thus may not be fully representative for all types of vegetation. Nevertheless, the critical level and its exceedance of the ozone concentration would be one of the useful tools for international agreements on abatement strategies to prevent ecosystem damage.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.26 no.4
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• pp.363-368
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• 1993

Short-term forecasting of fish catch is of practical importance in fisheries management. Ecosystem models and multi-species models as well as traditional single-species models fall short of predicting power needed for practical management of fisheries resources due to the lack of sufficient data or information for the required parameters. Univariate time series analysis, on the other hand, extracts the information on the stochastic variability from the time series itself and makes estimates of the future stochastic variability. Therefore, it can be used for short-term forecasting with minimum data requirements. ARIMA time series modeling has been applied to the monthly Korean catches of hairtail (Trichiurus lepturus) for $1971{\sim}1988$. Forecasts of hairtail catch were made and compared with the actual catch data from $1989{\sim}1990$ which were not included in the parameter estimation. The results showed a good agreement (r=0.938) between the forecasts and the actual catches with a mean rotative error of $59.5\%$

• Korean Journal of Environment and Ecology
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• v.28 no.4
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• pp.393-403
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• 2014

The aim of this study was to use the information deduced from biotopemap in Boryeong, Chungnam province conducted in 2011 and to select the wildlife survey point. The information used for the study was deduced from the knowledge and experience of wildlife specialists and was realized by 6 environmental variables (Outside distance from food vegetation, Outside distance from farm land, Outside distance from forest, Human density, Outside distance from road, Outside distance from water). 6 environmental variables were modeled by map overlay method and the model could deduce the correlation of 94.72% as a result of comparing with occurrence information. The areas predicted to have many occurrences were rural landscapes, forests, and valleys, and they can be used to deduce the quality wildlife survey results in the limit of survey range (area, schedule, and budget). However, it had the limit points such as the inside of forests was excluded, all species did not prefer the same habitat. The following studies are needed for this part in the future.