Emergency preparedness for the accidental release of radionuclides from the Uljin Nuclear Power Plant in Korea.

Site specific radionuclide dispersion databases were archived for the emergency response to the hypothetical releases of 137Cs from the Uljin nuclear power plant in Korea. These databases were obtained with the horizontal resolution of 1.5 km in the local domain centered the power plant site by simulations of the Lagrangian Particle Dispersion Model (LPDM) with the Unified Model (UM)-Local Data Assimilation Prediction System (LDAPS). The Eulerian Dispersion Model-East Asia (EDM-EA) with the UM-Global Data Assimilation Prediction System (UM-GDAPS) meteorological models was used to get dispersion databases in the regional domain. The LPDM model was performed for a year with a 5-day interval yielding 72 synoptic time-scale cases in a year. For each case hourly mean near surface concentrations, hourly mean column integrated concentrations, hourly total depositions for 5 consecutive days were archived by the LPDM model in the local domain and by the EDM-EA model in the regional domain of Asia. Among 72 synoptic cases in a year the worst synoptic case that showed the highest mean surface concentration averaged for 5 days in the LPDM model domain was chosen to illustrate the emergency preparedness to the hypothetical accident at the site. The simulated results by the LPDM model with the 137Cs emission rate of the Fukushima nuclear power plant accident for the first 5-day period were found to be able to provide prerequisite information for the emergency response to the early phase of the accident whereas those of the EDM-EA model could provide information required for the environmental impact assessment of the accident in the regional domain. The archived site-specific database of 72 synoptic cases in a year could have a great potential to be used as a prognostic information on the emergency preparedness for the early phase of accident.

Estimation of radionuclide (137Cs) emission rates from a nuclear power plant accident using the Lagrangian Particle Dispersion Model (LPDM).

A methodology for the estimation of the emission rate of 137Cs by the Lagrangian Particle Dispersion Model (LPDM) with the use of monitored 137Cs concentrations around a nuclear power plant has been developed. This method has been employed with the MM5 meteorological model in the 600 km × 600 km model domain with the horizontal grid scale of 3 km × 3 km centered at the Fukushima nuclear power plant to estimate 137Cs emission rate for the accidental period from 00 UTC 12 March to 00 UTC 6 April 2011. The Lagrangian Particles are released continuously with the rate of one particle per minute at the first level modelled, about 15 m above the power plant site. The presently developed method was able to simulate quite reasonably the estimated 137Cs emission rate compared with other studies, suggesting the potential usefulness of the present method for the estimation of the emission rate from the accidental power plant without detailed inventories of reactors and fuel assemblies and spent fuels. The advantage of this method is not so complicated but can be applied only based on one-time forward LPDM simulation with monitored concentrations around the power plant, in contrast to other inverse models. It was also found that continuously monitored radionuclides concentrations from possibly many sites located in all directions around the power plant are required to get accurate continuous emission rates from the accident power plant. The current methodology can also be used to verify the previous version of radionuclides emissions used among other modeling groups for the cases of intermittent or discontinuous samplings.

Spatial and temporal distributions of aerosol concentrations and depositions in Asia during the year 2010.

Aerosol Modeling System (AMS) that is consisted of the Asian Dust Aerosol Model2 (ADAM2) and the Community Multi-scale Air Quality (CMAQ) modeling system has been employed to document the spatial distributions of the monthly and the annual averaged concentration of both the Asian dust (AD) aerosol and the anthropogenic aerosol (AA), and their total depositions in the Asian region for the year 2010. It is found that the annual mean surface aerosol (PM10) concentrations in the Asian region affect in a wide region as a complex mixture of AA and AD aerosols; they are predominated by the AD aerosol in the AD source region of northern China and Mongolia with a maximum concentration exceeding 300 µg m(-3); AAs are predominated in the high pollutant emission regions of southern and eastern China and northern India with a maximum concentration exceeding 110 µg m(-3); while the mixture of AA and AD aerosols is dominated in the downwind regions extending from the Yellow Sea to the Northwest Pacific Ocean. It is also found that the annual total deposition of aerosols in the model domain is found to be 485 Tg (372 Tg by AD aerosol and 113 Tg by AA), of which 66% (319 Tg) is contributed by the dry deposition (305 Tg by AD aerosol and 14 Tg by AA) and 34% (166 Tg) by the wet deposition (66 Tg by AD aerosol and 100 Tg by AA), suggesting about 77% of the annual total deposition being contributed by the AD aerosol mainly through the dry deposition process and 24% of it by AA through the wet deposition process. The monthly mean aerosol concentration and the monthly total deposition show a significant seasonal variation with high in winter and spring, and low in summer.

Estimation of soil respiration using automated chamber systems in an oak (Quercus mongolica) forest at the Nam-San site in Seoul, Korea.

Soil respiration (R(soil)) is the largest component of ecosystem respiration produced by the autotrophic and heterotrophic respirations. Its variability on multiple time scales strongly depends on environmental variables such as temperature and moisture. To investigate the temporal variations of R(soil) in a cool-temperate oak (Quercus mongolica) forest at the Nam-San site in Seoul, Korea, continuous measurements of R(soil) using the automated chamber systems, air and soil temperatures and soil moisture are made for the period from April 2010 to March 2011. The observed data indicate that the R(soil) shows a remarkable seasonal variation in accordance with temperatures with high in summer and low in winter. The R(soil) is found to be strongly correlated with soil temperature (T(s)) at the 5cm depth throughout the year. However, the high fluctuation of R(soil) is found to be related with soil moisture content (M(s)) during the forest growing season. The estimated annual Q(10) value using the 1.5m-high air temperature is found to be 2.4 that is comparable with other studies in temperate forest ecosystems. The optimal regression equation of R(soil) with the T(s) at 5cm depth and the M(s) at 15cm depth is found to be R(soil)=124.3 exp (0.097T(s))-55.3 (M(s))(2)+2931.9 (M(s))-38516 for T(s)≥0°C and R(soil)=0 for T(s)<0°C with r(2)=0.97, P<0.01, suggesting the importance of T(s) and M(s) for R(soil). The annual total soil respiration estimated by the optimal regression equation is found to be 1264gCm(-2) with a maximum of 685gCm(-2) in the summer season and a minimum of 33gCm(-2) in the winter season. The present study can be implemented for the determination of the carbon balance of a cool-temperate Q. mongolica forest with the provision of photosynthesis.