Atmospheric Dispersion Modeling for Emergency Response

Author(s):  
Roel M. van Aalst
2016 ◽  
Vol 2016 ◽  
pp. 1-6 ◽  
Author(s):  
Bo Cao ◽  
Junxiao Zheng ◽  
Yixue Chen

Atmospheric dispersion modeling and radiation dose calculations have been performed for a hypothetical AP1000 SGTR accident by HotSpot code 3.03. TEDE, the respiratory time-integrated air concentration, and the ground deposition are calculated for various atmospheric stability classes, Pasquill stability categories A–F with site-specific averaged meteorological conditions. The results indicate that the maximum plume centerline ground deposition value of1.2E+2 kBq/m2occurred at about 1.4 km and the maximum TEDE value of1.41E-05 Sv occurred at 1.4 km from the reactor. It is still far below the annual regulatory limits of 1 mSv for the public as set in IAEA Safety Report Series number 115. The released radionuclides might be transported to long distances but will not have any harmful effect on the public.


2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Kwame Gyamfi ◽  
Sylvester Attakorah Birikorang ◽  
Emmanuel Ampomah-Amoako ◽  
John Justice Fletcher

Abstract Atmospheric dispersion modeling and radiation dose calculation have been performed for a generic 1000 MW water-water energy reactor (VVER-1000) assuming a hypothetical loss of coolant accident (LOCA). Atmospheric dispersion code, International Radiological Assessment System (InterRAS), was employed to estimate the radiological consequences of a severe accident at a proposed nuclear power plant (NPP) site. The total effective dose equivalent (TEDE) and the ground deposition were calculated for various atmospheric stability classes, A to F, with the site-specific averaged meteorological conditions. From the analysis, 3.7×10−1 Sv was estimated as the maximum TEDE corresponding to a downwind distance of 0.1 km within the dominating atmospheric stability class (class A) of the proposed site. The intervention distance for evacuation (50 mSv) and sheltering (10 mSv) were estimated for different stability classes at different distances. The intervention area for evacuation ended at 0.5 km and that for sheltering at 1.5 km. The results from the study show that designated area for public occupancy will not be affected since the estimated doses were below the annual regulatory limits of 1 mSv.


2020 ◽  
Vol 55 ◽  
pp. S75-S79
Author(s):  
P. Bedwell ◽  
I. Korsakissok ◽  
S. Leadbetter ◽  
R. Périllat ◽  
Cs. Rudas ◽  
...  

Uncertainties were propagated through the chain of atmospheric dispersion and radiological assessment models based on an ensemble approach for a range of scenarios. It was apparent that the time taken to complete model runs, ranging from several hours to a few tens of hours, was not appropriate for an emergency response. Thus, for an operational method, there was a requirement to reduce the number of ensemble members and/or reduce model run time for a single ensemble member, such that a measure of uncertainty may be obtained within the timeframe of one hour, but without significant detriment to the model endpoints derived, the uncertainty estimated and the radiation protection advice inferred. This study proposes recommendations for operationalising an ensemble approach used in the description of uncertainty in atmospheric dispersion modelling and an emergency response.


2012 ◽  
Vol 2012 ◽  
pp. 1-20 ◽  
Author(s):  
Eugene Yee

A simple recursive method is presented for performing the inverse dispersion modeling of an unknown number of (localized) sources, given a finite number of noisy concentration data acquired by an array of detectors. Bayesian probability theory is used to address the problem of selecting the source model which is most plausible in view of the given concentration dataset and all the available prior information. The recursive algorithm involves subtracting a predicted concentration signal arising from a source model consisting of N localized sources from the measured concentration data for increasing values of N and examining the resulting residual data to determine if the residuals are consistent with the estimated noise level in the concentration data. The method is illustrated by application to a real concentration dataset obtained from an atmospheric dispersion experiment involving the simultaneous release of a tracer from four sources.


SIAM Review ◽  
2011 ◽  
Vol 53 (2) ◽  
pp. 349-372 ◽  
Author(s):  
John M. Stockie

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