scholarly journals Probabilistic Dose Assessment from SB-LOCA Accident in Ujung Lemahabang Using TMI-2 Source Term

2017 ◽  
Vol 2017 ◽  
pp. 1-8
Author(s):  
Sunarko ◽  
Zaki Su’ud ◽  
Idam Arif ◽  
Syeilendra Pramuditya
Keyword(s):  
Source Term ◽  
Meteorological Data ◽  
Atmospheric Condition ◽  
Ground Level ◽  
Particle Dispersion ◽  
Dose Assessment ◽  
Air Concentration ◽  
Reactor Accident ◽  
3 Dimensional ◽  
Java Sea

Probabilistic dose assessment and mapping for nuclear accident condition are performed for Ujung Lemahabang site in Muria Peninsula region in Indonesia. Source term is obtained from Three-Mile Island unit 2 (TMI-2) PWR-type SB-LOCA reactor accident inverse modeling. Effluent consisted of Xe-133, Kr-88, I-131, and Cs-137 released from a 50 m stack. Lagrangian Particle Dispersion Method (LPDM) and 3-dimensional mass-consistent wind field are employed to obtain surface-level time-integrated air concentration and spatial distribution of ground-level total dose in dry condition. Site-specific meteorological data is obtained from hourly records obtained during the Site Feasibility Study period in Ujung Lemahabang. Effluent is released from a height of 50 meters in uniform rate during a 6-hour period and the dose is integrated during this period in a neutrally stable atmospheric condition. Maximum dose noted is below regulatory limit of 1 mSv and radioactive plume is spread mostly to the W-SW inland and to N-NE from the proposed plant to Java Sea. This paper has demonstrated for the first time a probabilistic analysis method for assessing possible spatial dose distribution, a hypothetical release, and a set of meteorological data for Ujung Lemahabang region.

scholarly journals Individual Effective Dose and Nuclear Emergency Planning for Muntok NPP Area using TMI-2 Source Term

2020 ◽  
Vol 22 (2) ◽  
pp. 65
Author(s):  
Sunarko Sunarko ◽  
Zaki Su'ud
Keyword(s):  
Nuclear Power ◽  
Source Term ◽  
Meteorological Data ◽  
Ground Level ◽  
Particle Dispersion ◽  
Air Concentration ◽  
Release Point ◽  
Loss Of Coolant Accident ◽  
Accident Data ◽  
Dry Conditions

Probabilistic dose analysis from a postulated nuclear accident is performed for the Muntok area in the western Bangka region. Three-Mile Island unit 2PWR-type Nuclear Power Plant (TMI-2) source-term is compiled and used as accident data. The accident is also known as the Small-break Loss of Coolant Accident (SB-LOCA) accident. The isotopes used in the simulation are Kr-88, I-131, Xe-133, and Cs-137. The release point is a 50 m stack. Lagrangian particle dispersion method (LPDM) is used along with a 3-dimensional mass-consistent wind-field. Surface-level time-integrated air concentration and spatial distribution of ground-level total dose were obtained for dry conditions. Meteorological data is taken from hourly records obtained from an on-site meteorological tower in Muntok area for the 2014-2015 period. Effluent is released at a uniform rate during a 6-hour period and the dose is integrated for 12 hours from the beginning of the release until most of the plume left the model boundaries. The regulatory limit for the general public of 1 mSv was detected in an area located 2.5 km from the release point. Radioactive plume is spread from the postulated plant location to uninhabited areas consisted of bushes and farming areas in the SE-SSE direction and to W-NW direction to the Bangka Sea.

Assessment of Control Room Radiological Habitability of High-Temperature Reactor Pebble-Bed Module in Shidao Bay Multi-Reactor Nuclear Power Site

2018 ◽  
Author(s):  
Xinpeng Li ◽  
Sheng Fang
Keyword(s):  
High Temperature ◽  
Nuclear Power ◽  
Source Term ◽  
Meteorological Data ◽  
Dose Calculation ◽  
Dose Assessment ◽  
Specific Information ◽  
Control Room ◽  
Pebble Bed ◽  
High Temperature Reactor

The control room radiological habitability (CRRH) is important for staff safety in a nuclear power plant, which is also a licensing requirement of the High-temperature Reactor Pebble-bed Module (HTR-PM) in China. Meanwhile, the complexity of the dose assessment increases for the multi-reactor site, which put forward higher requirements for building layout. The CRRH is investigated comprehensively for the multi-reactor site at Shidao Bay in this study. For a large-break loss of coolant accident of HTR-PM and CAP1000 in Shidao Bay nuclear power site, this study estimates doses of body, thyroid and skin due to three exposure pathways using NRC-recommended ARCON96 and dose calculation method in RG 1.195. To perform a realistic evaluation, the latest design and site-specific information are utilized as the input parameters, including the unique accidental source term of HTR-PM and the RG1.183-recommended source term of CAP1000, the release and ventilation parameters, the final layout and the meteorological data in a whole year. The evaluation results demonstrate that the individual dose level of staff in the control room is far below the requirement of the regulatory guide, which guarantees the CRRH of HTR-PM. The contribution of primary radionuclides suggests that tellurium and iodine are primary contributors of the inhalation dose of body and thyroid, which is worthy of paying particular attention to the CRRH design in HTR-PM.

Operational evaluation of volcanic source terms (volcanic ash and SO2) from inverse modelling for aviation

2020 ◽  
Author(s):  
Mariëlle Mulder ◽  
Delia Arnold ◽  
Christian Maurer ◽  
Marcus Hirtl
Keyword(s):  
Source Term ◽  
Dispersion Model ◽  
Meteorological Data ◽  
A Priori ◽  
Radar Data ◽  
Particle Dispersion ◽  
Volcanic Emissions ◽  
Volcanic Source ◽  
Computational Resources ◽  
Different Sources

<p>An operational framework is developed to provide timely and frequent source term updates for volcanic emissions (ash and SO<sub>2</sub>). The procedure includes running the Lagrangian particle dispersion model FLEXPART with an initial (a priori) source term, and combining the output with observations (from satellite, ground-based, etc. sources) to obtain an a posteriori source term. This work was part of the EUNADICS-AV (eunadics-av.eu), which is a continuation of the work developed in the VAST project (vast.nilu.no). The aim is to ensuring that at certain time intervals when new observational and meteorological data is available during an event, an updated source term is provided to analysis and forecasting groups. The system is tested with the Grimsvötn eruption of 2011. Based on a source term sensitivity test, one can find the optimum between a sufficiently detailed source term and computational resources. Because satellite and radar data from different sources is available at different times, the source term is generated with the data that is available the earliest after the eruption started and data that is available later is used for evaluation.</p>

Langjährige Be7 -Bodenluftmessungen lassen Änderung des atmosphärischen Austauschverhaltens während der letzten Jahrzehnte vermuten

1996 ◽  
Vol 51 (10-11) ◽  
pp. 1139-1143 ◽  
Author(s):  
S. Hartwig
Keyword(s):  
Exchange Process ◽  
Ground Level ◽  
Eddy Diffusivity ◽  
Source Distribution ◽  
Air Concentration ◽  
Minimum Concentration ◽  
Exchange Processes ◽  
Yearly Maximum ◽  
Heat Source Distribution ◽  
Ground Level Air

Abstract An analysis covering three decades (1964-1994) of monthly Be7 ground-level-air concentration measurements at Braunschweig shows a systematic trend of the data. This trend is related to the yearly maximum/minimum concentration ratio. The observation may be due to a continuous mitigation of exchange processes between stratosphere and troposphere. This finding is commensurate with the hypothesis that, due to the growing concentration of anthropogenic infrared active gases, the heat source distribution in the stratosphere and consequently the eddy diffusivity and exchange process between stratosphere and troposphere are altered. This results in a shorter irradiation period of stratospheric air portions by cosmic rays and consequently can lower the concentration of isotopes of stratospheric origin in ground level air.

Calculated Ground Level Concentration of Pollutants From Gas Turbine Using an Air Quality Display Model Computer Program

1974 ◽  
Author(s):  
N. R. Dibelius ◽  
George Touchton ◽  
Thomas Kane
Keyword(s):  
Air Quality ◽  
Computer Program ◽  
Gas Turbine ◽  
Meteorological Data ◽  
Ground Level ◽  
The United States ◽  
Combined Cycle ◽  
Ground Level Concentration ◽  
Model Computer ◽  
Two Machines

This paper contains the calculated ground level concentrations of air pollutants from 11 gas turbine models. These calculations were made using Charlotte, N.C. meteorological data. Four of these are simple cycle machines covering a range of size from 5050 hp to 65 MW and four are regenerative machines. Another three are combined cycle (STAG) machines, two machines having unfired and one having a fired heat recovery steam generator. The calculations were made using a slightly modified version of the United States Environmental Protection Agencies Air Quality Display Model Computer Program.

Take one dispersing plume and add some precipitation: using ensembles to simulate deposition uncertainty

2020 ◽  
Author(s):  
Susan Leadbetter ◽  
Peter Bedwell ◽  
Gertie Geertsema ◽  
Irene Korsakissok ◽  
Jasper Tomas ◽  
...  
Keyword(s):  
High Resolution ◽  
Dispersion Model ◽  
Meteorological Data ◽  
Weather Prediction ◽  
Radioactive Material ◽  
Positional Error ◽  
Multiple Model ◽  
Dispersion Models ◽  
Air Concentration ◽  
Initial State

<p>In the event of an accidental airborne release of radioactive material, dispersion models would be used to simulate the spread of the pollutant in the atmosphere and its subsequent deposition. Typically, meteorological information is provided to dispersion models from numerical weather prediction (NWP) models. As these NWP models have increased in resolution their ability to resolve short-lived, heavy precipitation events covering smaller areas has improved. This has led to more realistic looking precipitation forecasts. However, when traditional statistics comparing precipitation predictions to measurements at a point (e.g. an observation site) are used, these high-resolution models appear to have a lower skill in predicting precipitation due to small differences in the location and timing of the precipitation with respect to the observations. This positional error is carried through to the dispersion model resulting in predictions of high deposits where none are observed and vice versa; a problem known as the double penalty problem in meteorology.</p><p>Since observations are not available at the onset of an event, it is crucial to gain insight into the possible location and timing errors. One method to address this issue is to use ensemble meteorological data as input to the dispersion model. Meteorological ensembles are typically generated by running multiple model integrations where each model integration starts from a perturbed initial state and uses slightly different model parametrisations to represent uncertainty in the atmospheric state and its evolution. Ensemble meteorological data provide several possible predictions of the precipitation that are all considered to be equally likely and this allows the dispersion model to produce several possible predictions of the deposits of radioactive material.</p><p>As part of the Euratom funded project, CONFIDENCE, a case study involving the passage of a warm front, where the timing of the front is uncertain in relation to a hypothetical nuclear accident in Europe was examined. In this study a ten-member meteorological ensemble was generated using time lagged forecasts to simulate perturbations in the initial state and two different model parameterisations. This meteorological ensemble was used as input to a single dispersion model to generate a dispersion model ensemble. The resulting ensemble dispersion output and methods to communicate the uncertainty in the deposition and the resulting uncertainty in the air concentration predictions are presented. The results demonstrate how high-resolution meteorological ensembles can be combined with dispersion models to simulate the maximum impact of precipitation and the uncertainty in its position and timing.</p>

scholarly journals Sensitivity of Precipitation Phase over the Swiss Alps to Different Meteorological Variables

2014 ◽  
Vol 15 (2) ◽  
pp. 685-696 ◽  
Author(s):  
S. Froidurot ◽  
I. Zin ◽  
B. Hingray ◽  
A. Gautheron
Keyword(s):  
Relative Humidity ◽  
Air Temperature ◽  
Meteorological Data ◽  
Explanatory Power ◽  
Surface Air Temperature ◽  
Ground Level ◽  
Swiss Alps ◽  
Meteorological Variables ◽  
Study Region ◽  
Precipitation Phase

Abstract In most meteorological or hydrological models, the distinction between snow and rain is based only on a given air temperature. However, other factors such as air moisture can be used to better distinguish between the two phases. In this study, a number of models using different combinations of meteorological variables are tested to determine their pertinence for the discrimination of precipitation phases. Spatial robustness is also evaluated. Thirty years (1981–2010) of Swiss meteorological data are used, consisting of radio soundings from Payerne as well as present weather observations and surface measurements (mean hourly surface air temperature, mean hourly relative humidity, and hourly precipitation) from 14 stations, including Payerne. It appeared that, unlike surface variables, variables derived from the atmospheric profiles (e.g., the vertical temperature gradient) hardly improve the discrimination of precipitation phase at ground level. Among all tested variables, surface air temperature and relative humidity show the greatest explanatory power. The statistical model using these two variables and calibrated for the case study region provides good spatial robustness over the region. Its parameters appear to confirm those defined in the model presented by Koistinen and Saltikoff.

scholarly journals Detailed source term estimation of the atmospheric release for the Fukushima Daiichi Nuclear Power Station accident by coupling simulations of an atmospheric dispersion model with an improved deposition scheme and oceanic dispersion model

2015 ◽  
Vol 15 (2) ◽  
pp. 1029-1070 ◽  
Author(s):  
G. Katata ◽  
M. Chino ◽  
T. Kobayashi ◽  
H. Terada ◽  
M. Ota ◽  
...  
Keyword(s):  
Dose Rate ◽  
Nuclear Power ◽  
Source Term ◽  
Dispersion Model ◽  
Atmospheric Dispersion ◽  
Air Concentration ◽  
Power Station ◽  
Release Rates ◽  
Surface Deposition ◽  
Fukushima Daiichi

Abstract. Temporal variations in the amount of radionuclides released into the atmosphere during the Fukushima Daiichi Nuclear Power Station (FNPS1) accident and their atmospheric and marine dispersion are essential to evaluate the environmental impacts and resultant radiological doses to the public. In this paper, we estimate the detailed atmospheric releases during the accident using a reverse estimation method which calculates the release rates of radionuclides by comparing measurements of air concentration of a radionuclide or its dose rate in the environment with the ones calculated by atmospheric and oceanic transport, dispersion and deposition models. The atmospheric and oceanic models used are WSPEEDI-II (Worldwide version of System for Prediction of Environmental Emergency Dose Information) and SEA-GEARN-FDM (Finite difference oceanic dispersion model), both developed by the authors. A sophisticated deposition scheme, which deals with dry and fog-water depositions, cloud condensation nuclei (CCN) activation, and subsequent wet scavenging due to mixed-phase cloud microphysics (in-cloud scavenging) for radioactive iodine gas (I2 and CH3I) and other particles (CsI, Cs, and Te), was incorporated into WSPEEDI-II to improve the surface deposition calculations. The results revealed that the major releases of radionuclides due to the FNPS1 accident occurred in the following periods during March 2011: the afternoon of 12 March due to the wet venting and hydrogen explosion at Unit 1, midnight of 14 March when the SRV (safety relief valve) was opened three times at Unit 2, the morning and night of 15 March, and the morning of 16 March. According to the simulation results, the highest radioactive contamination areas around FNPS1 were created from 15 to 16 March by complicated interactions among rainfall, plume movements, and the temporal variation of release rates. The simulation by WSPEEDI-II using the new source term reproduced the local and regional patterns of cumulative surface deposition of total 131I and 137Cs and air dose rate obtained by airborne surveys. The new source term was also tested using three atmospheric dispersion models (Modèle Lagrangien de Dispersion de Particules d'ordre zéro: MLDP0, Hybrid Single Particle Lagrangian Integrated Trajectory Model: HYSPLIT, and Met Office's Numerical Atmospheric-dispersion Modelling Environment: NAME) for regional and global calculations, and the calculated results showed good agreement with observed air concentration and surface deposition of 137Cs in eastern Japan.

scholarly journals Real-time use of inverse modeling techniques to assess the atmospheric accidental release from a nuclear power plant

2020 ◽  
Vol 55 (2) ◽  
pp. 107-115
Author(s):  
O. Saunier ◽  
I. Korsakissok ◽  
D. Didier ◽  
T. Doursout ◽  
A. Mathieu
Keyword(s):  
Inverse Modeling ◽  
Nuclear Power ◽  
Source Term ◽  
Atmospheric Dispersion ◽  
Air Concentration ◽  
Fukushima Accident ◽  
Modeling Tool ◽  
Modeling Techniques ◽  
Atmospheric Dispersion Models ◽  
Key Issues

The assessment of the source term including the time evolution of the release rate into the atmosphere and its distribution between radionuclides is one of the key issues in the understanding of the consequences of a nuclear accident. Inverse modeling methods, which combine environmental measurements, and atmospheric dispersion models have been proven to be efficient in assessing the source term due to an accidental situation. We developed our own tool, which has been applied to the Fukushima accident by using dose rate measurements and air concentration measurements. The inverse modeling tool has been implemented and tested during exercises implying fictitious radioactive releases with the aim of testing this method for emergency management. The exercises showed the relevance of the inverse modeling tool and it is a rewarding experience, which helped us to identify the required developments for the purpose of an operational use.

scholarly journals Long-term trends of ambient nitrate (NO<sub>3</sub><sup>−</sup>) concentrations across China based on ensemble machine-learning models

2020 ◽  
Author(s):  
Rui Li ◽  
Lulu Cui ◽  
Yilong Zhao ◽  
Wenhui Zhou ◽  
Hongbo Fu
Keyword(s):  
Tibetan Plateau ◽  
Sichuan Basin ◽  
Meteorological Data ◽  
Ground Level ◽  
Absolute Error ◽  
River Delta ◽  
Gradient Boosting ◽  
Observation Data ◽  
Extreme Gradient Boosting

Abstract. High loadings of nitrate (NO3−) in the aerosol over China significantly exacerbates the air quality and poses a great threaten on ecosystem safety through dry/wet deposition. Unfortunately, limited ground-level observation data makes it challenging to fully reflect the spatial pattern of NO3− level across China. Up to date, the long-term monthly NO3− datasets at a high resolution were still missing, which restricted the assessment of human health and ecosystem safety. Therefore, a unique monthly NO3− dataset at 0.25° resolution over China during 2005–2015 was developed by assimilating surface observation, satellite product, meteorological data, land use types and other covariates using an ensemble model combining random forest (RF), gradient boosting decision tree (GBDT), and extreme gradient boosting (XGBoost). The new developed product featured excellent cross-validation R2 value (0.78) and relatively lower root-mean-square error (RMSE: 1.19 μg/m3) and mean absolute error (MAE: 0.81 μg/m3). Besides, the dataset also exhibited relatively robust performance at the spatial and temporal scale. Moreover, the dataset displayed good agreement with (R2 = 0.85, RMSE = 0.74 μg/m3, and MAE = 0.55 μg/m3) some unlearning data collected from previous studies. The spatiotemporal variations of the developed product were also shown. The estimated NO3− concentration showed the highest value in North China Plain (NCP) (3.55 ± 1.25 μg/m3), followed by Yangtze River Delta (YRD (2.56 ± 1.12  g/m3)), Pearl River Delta (PRD (1.68 ± 0.81 μg/m3)), Sichuan Basin (1.53 ± 0.63 μg/m3), and the lowest one in Tibetan Plateau (0.42 ± 0.25 μg/m3). The higher ambient NO3− concentrations in NCP, YRD, and PRD were closely linked to the dense anthropogenic emissions. Apart from the intensive human activities, poor terrain condition might be a key factor for the serious NO3− pollution in Sichuan Basin. The lowest ambient NO3− concentration in Tibetan Plateau was contributed by the scarce anthropogenic emission and favorable meteorological factors (e.g., high wind speed). In addition, the ambient NO3− concentration showed marked increasing tendency of 0.10 μg/m3/year during 2005–2014 (p 

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