• Journal of Korea Port Economic Association
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• v.35 no.4
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• pp.187-206
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• 2019

After reviewing the concept and previous studies related to green ports, this study analyzes the implications of green port policy of advanced ports in foreign countries and analyzes problems in terms of environmentally-friendly green port policy for Ulsan port, and to present sustainable green logistics establishment measures. The literature survey and Benchmarking methods are adopted as research methodology and the results are as follows. First, the pan-government climate change response management system, legislation of relevant laws, implementation of fiscal support policies, and roadmaps should be established. Second, the foundation for eco-friendly green growth should be established through the discovery of business models in conjunction with leading industries in the Southeastern Metropolitan Economic Area. Third, the Ulsan Port Greenport, such as AMP, in-port LNG propulsion ship, and ESI vessel incentive, should be built. Fourth, a low-carbon, high-efficiency sea-shuttle service shall be established through the introduction of the sea-shuttle service along the sea route. Fifth, energy self-reliant ports, including all institutions in the metropolitan Ulsan port area that have exceeded the level of Ulsan port Authority, should be built. Finally, water-type ports need to be built through the creation of coastal forests, the purification of marine water quality, and the introduction of colors to port.

• Journal of Agricultural Extension & Community Development
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• v.16 no.2
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• pp.363-384
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• 2009

This study aimed at finding directions for Korean agriculture to establish a new paradigm of sustainable development. Various problematic issues and concerns in the environment necessitate the transformation of Korea's development paradigm from unconditional growth to "Green Growth" through new policies on green value and review of various advanced researches. In this research, the environment-friendly agriculture's problems, particularly in agribusiness were analyzed. Drawing from Michael Porter's Value Chain Analysis, this research developed a value chain model in agriculture that reflects the environment and the present situations. Future directions in the agriculture sector were also discussed. Korea realized food self-sufficiency through the green revolution in the early 1970s. However, a lot of problems have also occurred, including ground and water pollution and the destruction of ecosystems as a result of the overuse of pesticides and chemical fertilizers. In the late 1970s, the growing interest on environment-friendly agriculture led to the introduction of sustainable methods and techniques. Unfortunately however, these were not innovative enough to foster environment-friendly agriculture. Thereafter, the consumers' distrust on agricultural products has worsened and concerns about health have increased. In view of this, the Ministry of Food, Agriculture, Forestry and Fisheries introduced in December 1993 a system of Quality-Certified Products for organic and pesticide-free agri-foods. Although a fundamental step toward the sustainability of the global environment, this system was not enough to promote environment-friendly agriculture. In 2008, Korea's vision is for "Low Carbon Green Growth" to move forward while also coping with climate change. But primary sectors in a typical value chain do not consider the green value of their operations nor look at production from an environmental perspective. In order to attain sustainable development, there is a need to use less resources and energy than what is presently used in Korean agricultural and value production. The typical value chain should be transformed into a "closed-loop" such that the beginning and the end of the chain are linked together. Such structure allows the flow of materials, products and even wastes among participants in the chain in a sustained cycle. This may result in a zero-waste sustainable production without destroying the ecosystem.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.4
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• pp.729-738
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• 2017

With the signing of the Paris Agreement, which is the new climate change agreement at the end of 2015, it will have a great impact on Korea environmental policy. The construction industry, which accounts for 42% of Korea's total $CO_2$ emissions, has been implementing various policies to improve the environmental problems. However, it is only applying passively to other projects except eco-friendly building certification. This is because most of the eco-related systems are based on building facilities. Therefore, there is a need for a new eco - friendly design evaluation model that can be widely applied not only to architecture but also to civil engineering facilities. In this study, a new model is developed based on the existing VE model, which adds new factors to evaluate the environmental friendliness, potential environmental pollution concept and environmental risk of facilities. This model is an eco-friendly design evaluation model that enables decision makers to effectively select alternative environmental criteria at the design stage. As a result of the case analysis of the block retaining wall and the alternative retaining wall, the value of the eco - friendly value of the alternative was 1.026 times higher than the original one. If this model is used at the design stage, it is expected to contribute not only to the construction of environmentally friendly facilities but also to the reduction of carbon emissions.

• Journal of Environmental Health Sciences
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• v.47 no.5
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• pp.384-397
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• 2021

Background: With volatile organic compounds (VOCs) containing aromatic and halogenated hydrocarbons such as benzene, toluene, and xylene that can adversely affect the respiratory and cardiovascular systems when a certain concentration is reached, it is important to accurately evaluate the source and the corresponding health risk effects. Objectives: The purpose of this study is to provide scientific evidence for the city of Seoul's VOC reduction measures by confirming the risk of each VOC emission source. Methods: In 2020, 56 VOCs were measured and analyzed at one-hour intervals using an online flame ionization detector system (GC-FID) at two measuring stations in Seoul (Gangseo: GS, Bukhansan: BHS). The dominant emission source was identified using the Positive Matrix Factorization (PMF) model, and health risk assessment was performed on the main components of VOCs related to the emission source. Results: Gasoline vapor and vehicle combustion gas are the main sources of emissions in GS, a residential area in the city center, and the main sources are solvent usage and aged VOCs in BHS, a greenbelt area. The risk index ranged from 0.01 to 0.02, which is lower than the standard of 1 for both GS and BHS, and was an acceptable level of 5.71×10^-7 to 2.58×10^-6 for carcinogenic risk. Conclusions: In order to reduce the level of carcinogenic risk to an acceptable safe level, it is necessary to improve and reduce the emission sources of vehicle combustion and solvent usage, and eco-car policies are judged to contribute to the reduction of combustion gas as well as providing a response to climate change.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.887-894
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• 2018

An electric vehicle is emerging as an alternative to the response of global climate change and sustainability. However, an Electric vehicle has not been popular due to the constraints such as its price or technical limitations. In order to analyze the effect of purchasing electric vehicles, this study conducted a binary logistic regression model that demonstrates the relation between purchasing and influencing variables. Variables which have high correlation were excluded from the model through the correlation analysis to prevent multicollinearity. Socio-economic variables such as the number of owned vehicles, sex, ages are not significant. On the other hand, Variables related to prices, charging and policy are found to have a significant to effect on the purchase of electric vehicles. In accordance with the model estimated result, it seems to be necessary to improve the charging incentives, or to provide electric car information and to expand opportunities for experience electric vehicles. The result is also expected to be helpful for spreading electric vehicles and formulating policies.

• The Korean Journal of Applied Statistics
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• v.34 no.5
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• pp.723-734
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• 2021

Wind energy is one of the rapidly developing renewable energies which is being developed and invested in response to climate change. As renewable energy policies and power plant installations are promoted, the supply of wind power in Korea is gradually expanding and attempts to accurately predict demand are expanding. In this paper, the ARIMA and ARIMAX models which are Time series techniques and the SVR, Random Forest and XGBoost models which are machine learning models were compared and analyzed to predict wind power generation in the Jeonnam and Gyeongbuk regions. Mean absolute error (MAE) and mean absolute percentage error (MAPE) were used as indicators to compare the predicted results of the model. After subtracting the hourly raw data from January 1, 2018 to October 24, 2020, the model was trained to predict wind power generation for 168 hours from October 25, 2020 to October 31, 2020. As a result of comparing the predictive power of the models, the Random Forest and XGBoost models showed the best performance in the order of Jeonnam and Gyeongbuk. In future research, we will try not only machine learning models but also forecasting wind power generation based on data mining techniques that have been actively researched recently.

• Journal of Korea Water Resources Association
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• v.54 no.9
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• pp.657-666
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• 2021

Ecosystem biodiversity is rapidly being lost due to changes in habitat, fragmentation of habitat, climate change, and land use changes by human activities. Recently, attempts have been made to approach the watershed management level to secure the health of the watershed, but studies on how to approach biodiversity and habitat management are still in lack. The purpose of this study is to evaluate the habitat quality of Geum river basin using Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) habitat quality model. The results of habitat quality was verified to eco-natural map and ecological watershed health evaluation results. The habitat quality of watershed was evaluated from 0 to 0.86 and the results showed that habitat quality was higher in upstream than downstream. Compared the habitat quality value in each eco-natural grade, the average habitat quality of 1st, 2nd and 3rd grades were 0.80, 0.76 and 0.71 respectively. The results of the correlation analysis with ecological watershed health data, the coefficient of determination (R²) was 0.58, and the person coefficient was 0.76. The results of this study may be used as foundation data to support habitat protection and implementation of long-term biodiversity-related policies.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.69-76
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• 2020

Global warming is a very important problem as it causes rapid climate change and natural disasters. Therefore, researches related to renewable energy are being actively conducted while promoting policies such as reducing carbon dioxide emission and increasing the proportion of renewable energy. Solar power generation is being applied in urban areas like BIPV as well as existing idle areas outside the city. Therefore, in this study, precast concrete blocks developed for paving roadways capable of solar power generation were designed and constructed. For the evaluation of field applicability for 6 months, skid resistance and block settlement were measured. As a result of the experiment, it was found that skid resistance satisfies the standard of general roadway in Korea, but not the standard of highway. The skid resistance tended to decrease as time passed. In addition, the settlement of the block gradually increased slightly, but it is much smaller than the allowable settlement of the roadway. Therefore, it is necessary to establish a maintenance period and method based on the periodic measurement results in the future.

• Journal of Environmental Health Sciences
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• v.48 no.2
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• pp.66-74
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• 2022

Background: The health effects of particulate matter (PM_2.5) bonded with various harmful chemicals differ based on their composition, so investigating and managing their concentrations and composition is vital for long-term management. As industrial complexes emit considerable quantities of pollutants, higher PM_2.5 concentrations and chemical component effects are expected than in other places. Objectives: We investigated the concentration distribution ratios of PM_2.5 chemical components to provide basic data to inform future major emissions control and PM_2.5 reduction measures in industrial complexes. Methods: We monitored five sites near the Ansan and Siheung industrial complexes from August 2020 to July 2021. Samples were collected and analyzed twice per week in spring/winter and once per week in summer/autumn according to the National Institute of Environmental Research in the Ministry of Environments' Air Pollution Monitoring Network Installation and Operation Guidelines. We investigated and compared composition ratios of 29 ions, carbon, and elemental components in PM_2.5. Results: The analysis of PM_2.5 components at the five sites revealed that ion components accounted for the greatest total mass at approximately 50% while carbon components and elemental components contributed 23~28% and 8~10%, respectively. Among the ionic components, NO₃^- occupies the greatest proportion. OC occupies the greatest proportion of the carbon components and sulphur occupies the greatest proportion of elemental components. Conclusions: This study investigated the concentration distribution ratios of PM_2.5 chemical components in industrial complexes. We believe these results provide basic chemical component concentration ratio data for establishing future air management policies and plans for the Ansan and Siheung industrial complexes.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.