• Journal of Radiation Protection and Research
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• v.24 no.3
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• pp.131-142
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• 1999

By using the Korean demographic data and the modified relative risk projection model given in the Committee on the Biological Effect of Ionizing Radiation (BEIR) report-V under the U.S. National Academy of Science, the radiogenic excess risk in Korean population has been evaluated. On the basis of this risk, a safety goal for the safe operation of domestic nuclear power plants has been further derived in terms of personal dose. The baseline risk of death due to all causes in Korea and the trivial risk level, which the society considers safe, were estimated to be $5.2{\times}10^{-3}$ and $5.2{\times}10^{-6}$, respectively. The radiogenic excess cancer risk in Korea has been estimated to be $5.2{\times}10^{-3}$ for tie case of acute exposure to 0.1 Gy and $3.7{\times}10^{-3}$ for the case of chronic lifetime exposure to 1.0 mGy/y. On the basis of these risks estimate, the resulting safety goal for one year opeation of a reactor was 0.05 mSv, which is quite identical with the ALARA guideline prescribed by the USNRC in the Appendix I, 10CFR50.

• Journal of Radiation Protection and Research
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• v.17 no.1
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• pp.57-70
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• 1992

An excess risk of lung cancer mortality among Koreans, attributable to indoor $^{222}Rn$ daughters exposure, were quantitatively evaluated by applying a stochastic health risk projection model on the radiation exposure. The lung cancer rate in Korean males and females, based on the 1989 demographic data, were estimated to be $22.4/10^5-y\;and\;9.5/10^5-y$, respectively The lifetime baseline lung cancer risks, deduced from these rates, appeared to be 0.047 and 0.019 for males and females, respectively, and were lower than the corresponding 1984 values of 0.067 and 0.025 in the U.S.A. The excess risk coefficients, derived by modified relative risk projection model of the BEIR-IV Committee under the US National Academy of Science, per annual 1.0 WLM of exposure to indoor radon daughters were estimated to be 0.022/WLM for males, 0.009/WLM for females, and 0.017/WLM for both sexes. The resulting annual frequency of excess lung cancer mortality for the life expectancy in the Korean population appeared to be 230/10^6-WLM, which was an approximate median of $120{\sim}450/10^6-WLM$ reported so far in the world.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.197-197
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• 2016

Forecasting future drought events in a region plays a major role in water management and risk assessment of drought occurrences. The creeping characteristics of drought make it possible to mitigate drought's effects with accurate forecasting models. Drought forecasts are inevitably plagued by uncertainties, making it necessary to derive forecasts in a probabilistic framework. In this study, a new probabilistic scheme is proposed to forecast droughts, in which a discrete-time finite state-space hidden Markov model (HMM) is used aggregated with the Representative Concentration Pathway 8.5 (RCP) precipitation projection (HMM-RCP). The 3-month standardized precipitation index (SPI) is employed to assess the drought severity over the selected five stations in South Kore. A reversible jump Markov chain Monte Carlo algorithm is used for inference on the model parameters which includes several hidden states and the state specific parameters. We perform an RCP precipitation projection transformed SPI (RCP-SPI) weight-corrected post-processing for the HMM-based drought forecasting to derive a probabilistic forecast that considers uncertainties. Results showed that the HMM-RCP forecast mean values, as measured by forecasting skill scores, are much more accurate than those from conventional models and a climatology reference model at various lead times over the study sites. In addition, the probabilistic forecast verification technique, which includes the ranked probability skill score and the relative operating characteristic, is performed on the proposed model to check the performance. It is found that the HMM-RCP provides a probabilistic forecast with satisfactory evaluation for different drought severity categories, even with a long lead time. The overall results indicate that the proposed HMM-RCP shows a powerful skill for probabilistic drought forecasting.