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SOFTWARE TOOL FOR ASSESSMENT OF FOOD CONTAMINATION AND FOOD BANS REGULATIONS

SOFTWARE TOOL FOR ASSESSMENT OF FOOD CONTAMINATION AND FOOD BANS REGULATIONS. Petr Pecha Radek Hofman Institute of Information Theory and Automation , Prague, Czech Republic. Emilie Pechova Nuclear Research Institute Řež, Czech Republic.

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SOFTWARE TOOL FOR ASSESSMENT OF FOOD CONTAMINATION AND FOOD BANS REGULATIONS

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  1. SOFTWARE TOOL FOR ASSESSMENT OF FOOD CONTAMINATION AND FOOD BANS REGULATIONS Petr Pecha Radek Hofman Institute of Information Theory and Automation , Prague, Czech Republic Emilie Pechova Nuclear Research Institute Řež, Czech Republic Activities are supported by the project No. VG20102013018: „Application of advanced statistical assimilation techniques of model predictions with observations from terrain in the form of modern software tool for emergency management support“ provided by the Ministry of the Interior of the Czech republic.

  2. CONSEQUENCES OF ACCIDENTAL RELEASE OF RADIOACTIVITY INTO ATMOSPHERE Best specific activities, food contamination, external irradiation: estimate their time integrals long-term evolution cloudshine, groundshine, output in air, deposition of deposition, internal activity intake: values on terrain, .... resuspension, .... inhalation and ingestion  Release of Atmospheric and Food chain dynamic Dose submodule nuclides eposition module module irradiation estim.

  3. SIGNIFICANT EUROPEAN DYNAMIC INGESTION MODELS Müller, H. and G. Pröhl. 1993. “ECOSYS’87: A Dynamic Model for Assessing Radiological Consequences of Nuclear Accidents.” Health Physics, Vol. 64, No. 3, March 1993. Müller, H., F. Gering and G. Pröhl. 2003. “Model Description of the Foodchain and Dose Module Terrestial in RODOS PV6.0”. Technical report RODOS(RA3)-TN(03)-06. Brown, J. and J.R. Simmonds. 1995. “FARMLAND-A Dynamic Model for the Transfer of Radionuclides through Terrestrial Foodchains.” Research Report NRPB-R273, Chilton, Didcot,UK.

  4. INTERACTIVE INPUTS Interactive regime offers wide range of input data and model parameters alternative options thus enabling fast examination of their variability and uncertainty on random fluctuations of theresulting outputs. INTERACTIVE INPUT SUBSYSTEMS: 1) Atm. dispersion model and release scenario definitions 2) Ingestion parametersdefinitions 3) LHS – (Latin HypercubeSampling) foruncertainty propagationthrough the model

  5. ADM input panel

  6. Ingestion data

  7. TYPES OF CALCULATIONS • Deterministiccalculations(design basisaccidents, worst- • case scenarios) • Variability examinations( sensitivity analysis, alternative • model parametrisation, categorialvariables,…) • Uncertaintyanalysis Variability reflects changes of a certain quantity over time, over space or across individuals in a population. Variability represents diversity or heterogeneity in a well characterized population. The true variability does not disappear with better measurement. The term uncertainty covers stochastic uncertainties, structural uncertainties representing partial ignorance or incomplete knowledge associated with poorly-characterized phenomena and uncertainties of input data. We can only reduce the uncertainties by obtaining the better information.

  8. Total effective committed doses for adults (pathways of cloudshine, groundshine, inhalation and ingestion– scenario “case 1” ). Intake in the first year (year of fallout, summer fallout in July 1 , the effect of local rain caused intensive wet removal . Real meteorologicalconditions: from archive : March 5, 2009, 20.00 CET, localrain, class D

  9. Depletion of specific activity of 137Cs (Bq.kg-1)in grains of harvested cereals in horizon of 25 years after the fallout - scenario “case 1” from Table 1. 0. year 1st year 5th year 25th year

  10. Illustration of agricultural countermeasures: Restricted area for harvest of cereals in the 2nd year after the fallout, given limit of 137Cs in grains is 1250 Bq/kg - scenario “case 1”

  11. THANK YOU FOR YOUR ATTENTION

  12. HARPFLOWCHART – deterministic and probabilistic components

  13. Model chain for probabilistic predictions of spatial distribution of random fields of output values Random specific activities, food contamination, external irradiation: fields of their time integrals long-term evolution cloudshine, groundshine, output in air, deposition of deposition, internal activity intake: values on terrain, .... resuspension, .... inhalation and ingestion  Release of Probabilistic Probabilistic Probabilistic irradiation nuclides ADM FCM doses estimation   Number of random input1, … , M1 1, … , M2 1, … , M3 parameters

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