• Journal of Korean Port Research
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• v.11 no.2
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• pp.231-240
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• 1997

In the United States, a number of ocean outfalls discharge primary treated effluent into deep sea water and contribute for more efficient wastewater treatment. The long multiport diffuser connected by long pipe from a treatment plant discharge wastewater into deep water due to the steep slope of the sea bed. However, Plume discharged from the diffuser can have significant impacts on coastal communities and possibly immediate consequence on public health. Therefore, there have been growing interests about the dynamics of plume in the vicinity of the ocean outfalls. It is expected that the ocean outfall should be considered for more efficient and reliable wastewater treatments as soon as possible around coastal area in South Korea. A number of studies of plume ynamics have used various models to predict plume behavior. However, in many cases, the calculated values of plume behavior are in significantly poor agreement with realistic values. Therefore, in this study, it is recommended that improvements should be made in the application of the plume model to more simulate the actual discharge characteristics and ocean conditions. It should be noted that input parameters in plume models reflect realistic ocean conditions like waves as well as currents. In this study, as one of the new parameters, current and long wave-influenced plume rise and initial dilution have been taken into account by using simple linear wave theory under some specific assumptions for more reliable plume behavior description. Among the improved plume models approved by EPA (Environmental Protection Agency), the RSB(Roberts-Snyder-Baurngartner) and UM(Updated Merge) models were chosen for the calculation of plume behavior, and the variation calculated by both models on the basis of long period wave was compared in terms of plume rise and initial dilution.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1477-1482
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• 2023

This study examines marine heat wave (MHW) in the Northeast Asia region from 2012 to 2021, utilizing geostationary satellite Communication, Ocean, and Meteorological Satellite (COMS)/Meteorological Imager sensor (MI) and GEO-KOMPSAT-2A (GK-2A)/Advanced Meteorological Imager sensor (AMI) Sea Surface Temperature (SST) data. Our analysis has identified an increasing trend in the frequency and intensity of MHW events, especially post-2018, with the year 2020 marked by significantly prolonged and intense events. The statistical validation using Optimal Interpolation (OI) SST data and satellite SST data through T-test assessment confirmed a significant rise in sea surface temperatures, suggesting that these changes are a direct consequence of climate change, rather than random variations. The findings revealed in this study serve the necessity for ongoing monitoring and more granular analysis to inform long-term responses to climate change. As the region is characterized by complex topography and diverse climatic conditions, the insights provided by this research are critical for understanding the localized impacts of global climate dynamics.

• Journal of Environmental Policy
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• v.13 no.1
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• pp.69-93
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• 2014

The aim of this research was to develop a climate change vulnerability index at the district level (Si, Gun, Gu) with respect to the health care sector in Korea. The climate change vulnerability index was esimated based on the four major causes of climate-related illnesses : vector, flood, heat waves, and air pollution/allergies. The vulnerability assessment framework consists of six layers, all of which are based on the IPCC vulnerability concepts (exposure, sensitivity, and adaptive capacity) and the pathway of direct and indirect impacts of climate change modulators on health. We collected proxy variables based on the conceptual framework of climate change vulnerability. Data were standardized using the min-max normalization method. We applied the analytic hierarchy process (AHP) weight and aggregated the variables using the non-compensatory multi-criteria approach. To verify the index, sensitivity analysis was conducted by using another aggregation method (geometric transformation method, which was applied to the index of multiple deprivation in the UK) and weight, calculated by the Budget Allocation method. The results showed that it would be possible to identify the vulnerable areas by applying the developed climate change vulnerability assessment index. The climate change vulnerability index could then be used as a valuable tool in setting climate change adaptation policies in the health care sector.