scholarly journals Uncertainty propagation in atmospheric dispersion models for radiological emergencies in the pre- and early release phase: summary of case studies

2020 ◽  
Vol 55 ◽  
pp. S57-S68 ◽  
Author(s):  
I. Korsakissok ◽  
R. Périllat ◽  
S. Andronopoulos ◽  
P. Bedwell ◽  
E. Berge ◽  
...  
Keyword(s):  
Case Studies ◽  
Uncertainty Propagation ◽  
Atmospheric Dispersion ◽  
Health Impact ◽  
Fukushima Accident ◽  
Atmospheric Dispersion Models ◽  
Hypothetical Accident ◽  
Release Data ◽  
Accident Scenarios ◽  
Input Uncertainties

In the framework of the European project CONFIDENCE, Work Package 1 (WP1) focused on the uncertainties in the pre- and early phase of a radiological emergency, when environmental observations are not available and the assessment of the environmental and health impact of the accident largely relies on atmospheric dispersion modelling. The latter is subject to large uncertainties coming from, in particular, meteorological and release data. In WP1, several case studies were identified, including hypothetical accident scenarios in Europe and the Fukushima accident, for which participants propagated input uncertainties through their atmospheric dispersion and subsequent dose models. This resulted in several ensembles of results (consisting of tens to hundreds of simulations) that were compared to each other and to radiological observations (in the Fukushima case). These ensembles were analysed in order to answer questions such as: among meteorology, source term and model-related uncertainties, which are the predominant ones? Are uncertainty assessments very different between the participants and can this inter-ensemble variability be explained? What are the optimal ways of characterizing and presenting the uncertainties? Is the ensemble modelling sufficient to encompass the observations, or are there sources of uncertainty not (sufficiently) taken into account? This paper describes the case studies of WP1 and presents some illustrations of the results, with a summary of the main findings.

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 Estimation of Dietary Intake of Radionuclides and Effectiveness of Regulation after the Fukushima Accident and in Virtual Nuclear Power Plant Accident Scenarios

2018 ◽  
Vol 15 (8) ◽  
pp. 1589 ◽  
Author(s):  
Michio Murakami ◽  
Takao Nirasawa ◽  
Takao Yoshikane ◽  
Keisuke Sueki ◽  
Kimikazu Sasa ◽  
...  
Keyword(s):  
Cost Effectiveness ◽  
Power Plant ◽  
Nuclear Power Plant ◽  
Dietary Intake ◽  
Emergency Preparedness ◽  
Nuclear Power ◽  
Food Distribution ◽  
Fukushima Accident ◽  
Accident Scenarios ◽  
Effectiveness Of Regulation

Evaluation of radiation exposure from diet is necessary under the assumption of a virtual accident as a part of emergency preparedness. Here, we developed a model with complete consideration of the regional food trade using deposition data simulated by a transport model, and estimated the dietary intake of radionuclides and the effectiveness of regulation (e.g., restrictions on the distribution of foods) after the Fukushima accident and in virtual accident scenarios. We also evaluated the dilution factors (i.e., ratios of contaminated foods to consumed foods) and cost-effectiveness of regulation as basic information for setting regulatory values. The doses estimated under actual emission conditions were generally consistent with those observed in food-duplicate and market-basket surveys within a factor of three. Regulation of restricted food distribution resulted in reductions in the doses of 54–65% in the nearest large city to the nuclear power plant. The dilution factors under actual emission conditions were 4.4% for radioiodine and 2.7% for radiocesium, which are ~20 times lower than those used in the Japanese provisional regulation values after the Fukushima accident. Strict regulation worsened the cost-effectiveness for both radionuclides. This study highlights the significance and utility of the developed model for a risk analysis of emergency preparedness and regulation.

Dynamic Correcting Dispersion Parameters of Lagrangian Puff Model in Atmospheric Tracer Experiments

2014 ◽  
Author(s):  
Yuanwei Ma ◽  
Dezhong Wang ◽  
Zhilong Ji ◽  
Nan Qian
Keyword(s):  
Numerical Simulation ◽  
Dispersion Model ◽  
Fitness Function ◽  
Atmospheric Dispersion ◽  
Correction Procedure ◽  
Model Errors ◽  
Dispersion Parameters ◽  
Fitness Functions ◽  
Atmospheric Dispersion Models ◽  
Atmospheric Tracer

In atmospheric dispersion models of nuclear accident, the empirical dispersion coefficients were obtained under certain experiment conditions, which is different from actual conditions. This deviation brought in the great model errors. A better estimation of the radioactive nuclide’s distribution could be done by correcting coefficients with real-time observed value. This reverse problem is nonlinear and sensitive to initial value. Genetic Algorithm (GA) is an appropriate method for this correction procedure. Fitness function is a particular type of objective function to achieving the set goals. To analysis the fitness functions’ influence on the correction procedure and the dispersion model’s forecast ability, four fitness functions were designed and tested by a numerical simulation. In the numerical simulation, GA, coupled with Lagrange dispersion model, try to estimate the coefficients with model errors taken into consideration. Result shows that the fitness functions, in which station is weighted by observed value and by distance far from release point, perform better when it exists significant model error. After performing the correcting procedure on the Kincaid experiment data, a significant boost was seen in the dispersion model’s forecast ability.

Assessment of atmospheric dispersion and radiological impact from the Fukushima accident in a 40-km range using a simulation approach

2014 ◽  
Vol 7 (2) ◽  
pp. 209-227 ◽  
Author(s):  
C. V. Srinivas ◽  
P. T. Rakesh ◽  
K. B. R. R. Hari Prasad ◽  
R. Venkatesan ◽  
R. Baskaran ◽  
...  
Keyword(s):  
Atmospheric Dispersion ◽  
Simulation Approach ◽  
Fukushima Accident ◽  
Radiological Impact

scholarly journals Flexibility during the COVID-19 Pandemic Response: Healthcare Facility Assessment Tools for Resilient Evaluation

2021 ◽  
Vol 18 (21) ◽  
pp. 11478
Author(s):  
Andrea Brambilla ◽  
Tian-zhi Sun ◽  
Waleed Elshazly ◽  
Ahmed Ghazy ◽  
Paul Barach ◽  
...  
Keyword(s):  
Case Studies ◽  
Assessment Tool ◽  
Healthcare Facility ◽  
Health Impact ◽  
Design Guidelines ◽  
Assessment Tools ◽  
Validity And Reliability ◽  
Evaluation Tool ◽  
Healthcare Operations ◽  
Healthcare Facilities

Healthcare facilities are facing huge challenges due to the outbreak of COVID-19. Around the world, national healthcare contingency plans have struggled to cope with the population health impact of COVID-19, with healthcare facilities and critical care systems buckling under the extraordinary pressures. COVID-19 has starkly highlighted the lack of reliable operational tools for assessing the level sof flexibility of a hospital building to support strategic and agile decision making. The aim of this study was to modify, improve and test an existing assessment tool for evaluating hospital facilities flexibility and resilience. We followed a five-step process for collecting data by (i) doing a literature review about flexibility principles and strategies, (ii) reviewing healthcare design guidelines, (iii) examining international healthcare facilities case studies, (iv) conducting a critical review and optimization of the existing tool, and (v) assessing the usability of the evaluation tool. The new version of the OFAT framework (Optimized Flexibility Assessment Tool) is composed of nine evaluation parameters and subdivided into measurable variables with scores ranging from 0 to 10. The pilot testing of case studies enabled the assessment and verification the OFAT validity and reliability in support of decision makers in addressing flexibility of hospital design and/or operations. Healthcare buildings need to be designed and built based on principles of flexibility to accommodate current healthcare operations, adapting to time-sensitive physical transformations and responding to contemporary and future public health emergencies.

Evaluation of new generation atmospheric dispersion models

2002 ◽  
Vol 18 (1) ◽  
pp. 22 ◽  
Author(s):  
D.J. Hall ◽  
A.M. Spanton ◽  
M. Bennett ◽  
F. Dunkerley ◽  
R.F. Griffiths ◽  
...  
Keyword(s):  
Atmospheric Dispersion ◽  
Dispersion Models ◽  
Atmospheric Dispersion Models ◽  
New Generation

Building Off of Evidence-Based Policies: The CDC’s Health Impact in 5 Years (HI-5) Initiative and CityHealth, an Initiative of the de Beaumont Foundation and Kaiser Permanente

2019 ◽  
pp. 407-424
Author(s):  
Elizabeth Skillen ◽  
Shelley Hearne
Keyword(s):  
Case Studies ◽  
Health Impact ◽  
Evidence Based ◽  
Strategic Partnerships ◽  
Critical Factors ◽  
Kaiser Permanente ◽  
Science And Art ◽  
State And Local ◽  
Local Levels

This chapter discusses the importance of evidence and describe work in the CDC's HI-5 Initiative and the de Beaumont Foundation's CityHealth program to distill the broad range of evidence on effective policies into a form more readily actionable at state and local levels. Successful policymaking does not have to be mysterious; the chapter argues. The science and art of good policymaking involves identifying evidence-based options, conducting feasibility assessments, and fostering strategic partnerships. The chapter presents some critical factors for developing and implementing policy. The chapter relates these to the work in the two case studies it presents.

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