• Ocean and Polar Research
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• v.45 no.2
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• pp.71-87
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• 2023

Climate change causes ocean warming, ocean acidification, sea-level rise, dynamic coastal risk, change of ecosystem structure and function, and degradation of ecosystem services. Not only that, but it has negatively impacted the well-being of people, society, and culture, including food security, water resources, water quality, livelihood, health, welfare, infrastructure, transport, tourism, recreation, and so on, especially by particularly degrading indigenous communities and generating an inequitable distribution of benefits and costs. As pointed out here, these adverse impacts of climate change on the ocean have been emphasized at the international and national levels. In contrast, the ocean field has been neglected in the climate change conversation for too long. However, since the UNFCCC COP 25, the ocean has been drawn into the discussion as a solution to address climate change. Moreover, the U.S. Congress recently unveiled a bill called the 'Ocean-Based Climate Solution Act, OBCSA' that reflects the new paradigm of the international regime. The comprehensive legislative bill includes elements related to climate inequity, a blue economy, and a community-led bottom-up policy mechanism, which will have a significant bearing on the ocean-climate legal system. Therefore, this study reviews the OBCSA and deduces implications with regard to the ocean-climate legal system in Korea.

• Journal of Korean Society for Atmospheric Environment
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• v.32 no.4
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• pp.384-393
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• 2016

In this study, two kinds of industrial filter bags were tested for their filtration performance to apply the existing bag filter systems. Experimental variables were examined for pressure drop, cleaning interval, residual pressure drop, cleaning efficiency, fractional grade efficiency, total collection efficiency according to the filter bag structure. According to these results, the filter bags tested in this study demonstrated good performance in dust collection. This was also true for the double surface filter bag. The lifetime was longer than the round type filter bag because the filtration area was more than 1.6 times wider and the filter quality factor was much higher. Therefore, double surface filter bags are suggested to be used in order to increase filtration performance of the bag filter systems.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.232-238
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• 2021

The development of a low cost catalyst with high performance and small amount of carbon deposition on catalyst from toluene steam reforming were investigated by using coal ash as a support material. Ni-loaded coal ash catalyst showed similar catalytic activity for toluene steam reforming compared with the Ni/Al2O3. At 800 ℃, the toluene conversion was 77% for Ni/TAL, 68% for Ni/KPU and 78% for Ni/Al2O3. Ni/TAL showed similar toluene conversion to Ni/Al2O3. However, Ni/KPU produced higher hydrogen yield at relatively lower toluene conversion. Ni/KPU catalyst showed a remarkable ability of suppressing the carbon deposition. The difference in coke deposition and hydrogen yield is due to the composition of KPU ash (Ca and Fe) which increase coke resistance and water gas shift reaction. This study suggests that coal ash catalysts have great potential for the application in the steam reforming of biomass tar.

• Asia-Pacific Journal of Atmospheric Sciences
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• v.54 no.4
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• pp.611-622
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• 2018

Observed climate data are processed under the assumption that their time series are stationary, as in multi-step temperature and precipitation prediction, which usually leads to low prediction accuracy. If a climate system model is based on a single prediction model, the prediction results contain significant uncertainty. In order to overcome this drawback, this study uses a method that integrates ensemble prediction and a stepwise regression model based on a mean-valued generation function. In addition, it utilizes empirical mode decomposition (EMD), which is a new method of handling time series. First, a non-stationary time series is decomposed into a series of intrinsic mode functions (IMFs), which are stationary and multi-scale. Then, a different prediction model is constructed for each component of the IMF using numerical ensemble prediction combined with stepwise regression analysis. Finally, the results are fit to a linear regression model, and a short-term climate prediction system is established using the Visual Studio development platform. The model is validated using temperature data from February 1957 to 2005 from 88 weather stations in Guangxi, China. The results show that compared to single-model prediction methods, the EMD and ensemble prediction model is more effective for forecasting climate change and abrupt climate shifts when using historical data for multi-step prediction.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.37 no.3
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• pp.99-112
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• 2014

The purpose of this study is to examine the negative effects of silence climate on the innovation behavior and LMX (Leader-Member Exchange). In order to test our model, we conducted a survey based on the questionnaire. Results showed that silence climate had a negative effect on the innovation behavior and LMX. Secondly, The LMX had a positive effect on innovation behavior. Moreover, the LMX partially mediated silence climate and the innovation behavior. Finally, we drew a conclusion by discussing limitations and implications of the research, and suggested directions for further researches.

• International Journal of Contents
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• v.17 no.1
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• pp.61-70
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• 2021

As the resolution of climate change scenario data applied with regional models increased, Earth System Grid Federation (ESGF) was established around major climate-related organizations to jointly operated and manage large-scale climate data. ESGF developed standard software to provide model output, observation data management, dissemination, and analysis using Peer to Peer (P2P) computing technology. Roles of each institution were divided into index and data nodes. Therefore, ESGF data node was established at APEC Climate Center in Korea on behalf of Asia to share data on climate change scenarios of CORDEX-East Asia (CORDEX-EA) to study climate changes in Eastern Asia. Climate researchers are expected to play a large role in researching causes of global warming and responding to climate change by providing CORDEX-EA regional model data to the world through ESGF data node.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.2
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• pp.261-272
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• 2022

The purpose of this paper is to investigate the influence of ethical leadership in determining the organizations' individual-type ethical climate (self-interest, friendship, and personal morality ethical climate) in reducing employee turnover intention. It seeks to identify the role of individual-type climate in mediating the association between ethical leadership and employee turnover intention. Moreover, the moderation effect of emotional exhaustion among employees on the relationship between ethical leadership and turnover intention has been researched to establish the ethical degree of leadership. Using a sample of 260 questionnaires from employees working full-time in the banking sector, the results were analyzed in PLS-SEM. The results of the social exchange theory indicated that ethical leadership is vital in shaping the workplace's individual-type ethical climate and reducing employees' turnover intention. The findings demonstrate that the relationship between ethical leadership and turnover intention is mediated by an individual-type ethical climate, which means that employees in a positive ethical climate do not wish to leave immediately. Furthermore, emotional exhaustion was found to moderate the association between ethical leadership and employees' turnover intention under high emotional exhaustion, where low ethical leadership is experienced, reporting higher levels of turnover intention.

• Journal of Forest and Environmental Science
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• v.29 no.3
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• pp.181-193
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• 2013

Climate change is considered to be one of the most serious threats and its impact is felt by the most vulnerable world's poorest countries including Bangladesh. In particular, ethnic communities, whose livelihoods depend on the use of natural resources, are likely to bear the brunt of adverse impacts. A case study was conducted in a fragile ecosystem of Lawachara national park of Bangladesh, to know the indigenous knowledge of the ethnic communities, how they adapt with the climate change impact by using indigenous knowledge. They use various IK to protect their crops from climate change impact. Thus, government should design policies which will be helpful to make them more resilience to face climate change impact.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.5
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• pp.1414-1430
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• 2022

Due to the Internet of Things popularity, many agricultural data are collected by sensors automatically. The abundance of agricultural data makes precise prediction of rice yield possible. Because the climate factors have an essential effect on the rice yield, we considered the climate factors in the prediction model. Accordingly, this paper proposes a machine learning model for rice yield prediction in Taiwan, including the genetic algorithm and support vector regression model. The dataset of this study includes the meteorological data from the Central Weather Bureau and rice yield of Taiwan from 2003 to 2019. The experimental results show the performance of the proposed model is nearly 30% better than MARS, RF, ANN, and SVR models. The most important climate factors affecting the rice yield are the total sunshine hours, the number of rainfall days, and the temperature.The proposed model also offers three advantages: (a) the proposed model can be used in different geographical regions with high prediction accuracies; (b) the proposed model has a high explanatory ability because it could select the important climate factors which affect rice yield; (c) the proposed model is more suitable for predicting rice yield because it provides higher reliability and stability for predicting. The proposed model can assist the government in making sustainable agricultural policies.

• Environmental Engineering Research
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• v.16 no.3
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• pp.175-183
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• 2011

The climate of the $21^{st}$ century is likely to be significantly different from that of the 20th century because of human-induced climate change. An extreme weather event is defined as a climate phenomenon that has not been observed for the past 30 years and that may have occurred by climate change and climate variability. The abnormal climate change can induce natural disasters such as floods, droughts, typhoons, heavy snow, etc. How will the frequency and intensity of extreme weather events be affected by the global warming change in the $21^{st}$ century? This could be a quite interesting matter of concern to the hydrologists who will forecast the extreme weather events for preventing future natural disasters. In this study, we establish the extreme indices and analyze the trend of extreme weather events using extreme indices estimated from the observed data of 66 stations controlled by the Korea Meteorological Administration (KMA) in Korea. These analyses showed that spatially coherent and statistically significant changes in the extreme events of temperature and rainfall have occurred. Under the global climate change, Korea, unlike in the past, is now being affected by extreme weather events such as heavy rain and abnormal temperatures in addition to changes in climate phenomena.