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Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon.

Arnaud Querel, Denis Quelo, Thierry Doursout

To cite this version:

Arnaud Querel, Denis Quelo, Thierry Doursout. Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon.. EGU General Assembly, EGU, Apr 2019, VIENNE, Austria. �hal-02635634�

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Faire avancer la sûreté nucléaire

MODELLING RESULTS CONCLUSION

Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

B

I 20 70 50100

- 10

i 7.0 I 5.0

- 2.0 1.0 Simulated dose rate

01 Sep 00:00 Réseau Téléray au 2<V11/2018

• Balises Téléray

EGU 2019 18762 April, 11th 2019 Arnaud QUÉREL Denis QUÉLO

Thierry DOURSOUT

© IRSN

OUTLOOK

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PHYSICS MODELLING RESULTS CONCLUSION OUTLOOK

A preliminary study showed encouraging results...

Local time

-.60

50

40

-30

- 20

- 10

-0

I RS []

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

Observeddoserate(nSv.h1)

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CONTEXT PHYSICS MODELLING RESULTS CONCLUSION OUTLOOK

- In the event of an incident or accident involving radioactive materials, IRSN provides guidance to public authorities on the technical, public health and medical measures to be taken to protect the population and the

environment.

The monitoring network Teleray in France: Hundreds of gamma dose rate monitoring stations recording data each ten minutes all year round.

Several times a year, alarms of this emergency monitoring network are triggered: these gamma dose rate peaks occurred during rainfall events because radon progenies concentrate in rain drops and fall down to the ground.

Although these peaks do not present any risks to the population or

environment, it is necessary to discriminate whether it comes from the natural radioactivity or if an accidental release of radioactive materials happened.

Réseau Téléray au 20/11/2018 ,-.vt

Is it possible to forecast peaks due to atmospheric radon?

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

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CONTEXT PHYSICS MODELLING RESULTS CONCLUSION OUTLOOK

Atmospheric transport of radon

© Radon

© Exhalation radon (gas)

daughters

(particles) i*

© Increase of dose

rate

© Fast radioactive

decay of daughters

Peak!

of dose

rate

time

© Deposit of

daughters © Radiation Monitoring station

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

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16-03-2011 oohoo (heure locale)

CONTEXT PHYSICS MODELLING RESULTS CONCLUSION OUTLOOK

Modelling

© Exhalation of radon (gas)

© Outputs

^Dose rate maps

© Dose rate computation

For each time step

^Dose rate at ground level (2D)

^Dose rate at a given location

^To be compared to the measurements

Teleray: the French monitoring network of gamma dose rate

^Hundreds of stations (~420)

^Freq : 10 min

©

Atmospheric transport model ldX

© Meteorological data

© Decay chain

&

Chem/phys form data

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

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PHYSICS

*#r>

MODELLING RESULTS

Source Term :

Exhalation of radon (gas)

/ Based on an exhalation flux of Rn- 222 computed by the IRSN.

In this study, considered constant in time

IRSN/BERAD source term

CONCLUSION OUTLOOK

Meteorological data

Météo-France

meteorological data: ARPEGE

^At:1h ; Ax=Ay=0.1°=10km METEO

FRANCE

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

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PHYSICS MODELLING RESULTS CONCLUSION OUTLOOK

Exhalation of Rn-222

Met data

Atmospheric transport model ldX

Plume transport Plume diffusion Dry déposition

Radioactive decay Decay chain

Wet deposition In-cloud scavenging Below-cloud scavenging Cloud diagnosis

Eulerian model

" Long range transport model of the operational response platform C3X

" Operated on several cases : Chernobyl, Fukushima, CTBTO, ...

For each radionuclides at each time step :

—"Air concentration (3D)

"Deposit (2D)

Eslinger, Paul W., TedW. Bowyer, Pascal Achim, TianfengChai, Benoit Deconninck, Katie Freeman, Sylva Generoso, et al. 2016. « International Challengeto Predictthe ImpactofRadioxenon Releases from Medical Isotope Productionon a Comprehensive Nuclear Test Ban Treaty Sampling Station ». JournalofEnvironmentalRadioactivity 157 (juin): 41-51.

https://doi.org/10.1016/i.ienvrad.2016.03.001.

Groëll, Jérôme, Denis Quélo, et Anne Mathieu. 2014. « Sensitivity analysis ofthe modelled deposition of 137 Cs on the Japanese land following the Fukushima accident ». InternationalJournalof EnvironmentandPollution 55 (1-4): 67-75. https://doi.org/10.1504/iiep.2014.065906.

Kajino, Mizuo, Tsuyoshi Thomas Sekiyama, Anne Mathieu, Irène Korsakissok, Raphaël Périllat, Denis Quélo, Arnaud Quérel, et al. 2018. « Lessons Learned from Atmospheric Modeling Studies after the Fukushima Nuclear Accident: Ensemble Simulations, Data Assimilation, Elemental Process Modeling, and Inverse Modeling». GeochemicalJournal52 (2): 85-101.

https://doi.org/10.2343/geochemi.2.0503.

Kitayama, K., Y. Morino, M. Takigawa, T. Nakajima, H. Hayami, H. Nagai, H. Terada, et al. 2018.

« Atmospheric Modeling of137 Cs Plumes From the Fukushima Daiichi Nuclear Power Plant- Evaluation ofthe Model Intercomparison Data ofthe Science Council of Japan ». Journalof Geophysical Research: Atmospheres, juillet. https://doi.org/10.1029/2017JD028230.

Mathieu, Anne, Irène Korsakissok, Denis Quélo, Jérôme Groëll, Marilyne Tombette, Damien Didier, Emmanuel Quentric, Olivier Saunier, Jean-Pierre Benoit, et Olivier Isnard. 2012. « Fukushima Daiichi: Atmospheric Dispersion and Deposition ofRadionuclides from the FukushimaDaiichi Nuclear Power Plant Accident». Elements8 (3): 195-200.

https://doi.org/10.2113/gselements.8.3.195.

Maurer, Christian, Jonathan Baré, Jolanta Kusmierczyk-Michulec, Alice Crawford, Paul W. Eslinger, Petra Seibert, Blake Orr, et al. 2018. « International Challengeto Model the Long-Range Transport of Radioxenon Released from Medical Isotope Production to Six Comprehensive Nuclear-Test-Ban Treaty Monitoring Stations ». JournalofEnvironmentalRadioactivity 192 (décembre): 667-86.

https://doi.org/10.1016/i.ienvrad.2018.01.030.

Quérel, Arnaud, Yelva Roustan, Denis Quélo, et Jean-Pierre Benoit. 2015. « Hints to Discriminate the Choice ofWet Deposition Models Applied to an Accidental Radioactive Release. » International Journal of Environmentand Pollution 58 (4): 268-79. https://doi.org/10.1504/IJEP.2015.077457.

Sato, Yousuke, Masayuki Takigawa, Tsuyoshi Thomas Sekiyama, Mizuo Kajino, Hiroaki Terada, Haruyasu Nagai, Hiroaki Kondo, et al. 2018. « Model Intercomparison of Atmospheric137 Cs from the Fukushima Daiichi Nuclear Power Plant Accident: Simulations Based on Identical Input Data ».

Journalof GeophysicalResearch:Atmospheres, octobre. https://doi.org/10.1029/2018JD029144.

Saunier, Olivier, Anne Mathieu, Damien Didier, Marilyne Tombette, Denis Quélo, Victor Winiarek, et Marc Bocquet. 2013. « An inverse modelling methodto assess the source term ofthe Fukushima Nuclear Power Plant accident using gamma dose rate observations ». AtmosphericChemistryandPhysics 13:11403-21. https://doi.org/10.5194/acp-13-11403-2013.

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

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CONCLUSION OUTLOOK For each time step

^Dose rate at ground level (2D)

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

I RS []

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RESULTS CONCLUSION OUTLOOK

^Dose rate at a given location

^Compared to the local observation

50

40

-20

10

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

I RS []

Observeddose rate(nSv.h!)

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Aiguille -du-Midi

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

CONTEXT

Source Met

term data

Atmospheric transport

Dose rate assessmentS

Output

Observations

PHYSICS MODELLING RESULTS CONCLUSION Teleray : the French monitoring network of gamma dose rate

^Hundreds of stations (~420)

^Freq : 10 min

OUTLOOK

IRS[]

(12)

CONTEXT PHYSICS MODELLIN^^^ RESULTS ^^CONCLUSION OUTLOOK

Model-to-data comparison...

Some comparisons of dose rate : model vs measurements

Some peaks are very well modelled in time and intensity

SATHONAY-CAMP

Local time

LYON

Local time

Day/night cyclic

variation is correctly reproduced

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

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CONTEXT PHYSICS MODELLIN^^^ RESULTS ^^CONCLUSION OUTLOOK

Model-to-data comparison...

Some comparisons of dose rate : model vs measurements

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

CLERMONT-FERRAND

Local time

Time shifting

I RS []

Some peaks are modelled but not observed

DIJON

The height of the

peaks can

also be

challenging

to model

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CONTEXT PHYSICS MODELLING RESULTS CONCLUSION

Other examples

Model-to-data comparison...

Some comparisons of dose rate : model vs measurements

OUTLOOK

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

I RS []

Observeddoserate(nSv.h1)Observeddose rate(nSv.h1)

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CONTEXT PHYSICS MODELLING RESULTS CONCLUSION OUTLOOK

Air concentrations: order of magnitude

0,001 0,000 1 0,000 01 0,000 001

Air concentrations in Bq/m

3

100­

10­

1 Bq/m3- 0,1­

0,01-

Hüü

0

l

V V .V V V ^

qO

^cT ^çT

qO'

I I

Activités simulées

Activités observées (Masson/

Sabroux)

Modelling : Lyon from may 2017 to may 2018

Rn-222 daughters

3.82 d

3.1 m

27 m 222

Rn

86___

Bi-210 is created very slowly and comes in a large part from

volcanoes

218

Po

214 214 Bi

Pb

214

Po 160 us y

210

84 210 Po

/li 84

«1

4

22 y

Bi «1

210 83 206

82Pb

5 d Pb

82

138 cl

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

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CONTEXT PHYSICS MODELLING RESULTS CONCLUSION OUTLOOK

Conclusion

^ This preliminary study shows encouraging results for the feasibility of atmospheric radon modelling at regional scale

^ To be done...

^ more realistic source term

/ take into account radar measurements for rain events

Observeddoserate(nSv.h

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CONTEXT PHYSICS MODELLING RESULTS CONCLUSION OUTLOOK

...perspectives

| Studying a large period in the past (5 years) : statistical analysis on French monitoring network

■ Where and when is the model able to reproduce the measurements?

| Analysing of specific events

■ Case studies to fully understand recent peaks for which additional information are easy to gather (meteorological observations).

| Daily learning

■ To experience routinely the operational product chain

■ To forecast potential risk of dose rate peaks for monitoring purpose

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

IRS[]

(18)

CONTEXT PHYSICS MODELLING RESULTS CONCLUSIO^^^ OUTLOOK

Improve the atmospheric transport model (wet déposition modelling)

• The Fukushima accident was a privileged case study for verification of the model capability to simulate accidentai releases.

• The newly available emission inventories of Radon-222, joined with a network of gamma dose rate stations, can be used as a suitable radiological case study for model validation and improvement.

3.0

2.5

£ 2.0

Ë

B 1.5

1.0

0.5

0.0

OnePoint/FullPeriod/Fukushima

Dose rate increase triggered by a rainfall = similarity between dose rate peaks observed during the plume passing of Fukushima and those attributed to radon

daughters

* # r?

Rain measured Rain detected

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

IRS[]

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CONTEXT PHYSICS MODELLING RESULTS CONCLUSIO^^^ OUTLOOK

Outdoor exposure to radon: the role of long-range atmospheric transport?

| When breathed, the radon-222 disintegrated inside the lung can damage the cells, increasing the risk of cancer.

| Radon-222 air concentration at one location is the combination of a potentially high local source - within few kilometres - and probably a long-distance origin - dozens or hundreds of kilometres.

Variability of Rn-222 air concentration at the ground-level for several times during August, 2107

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

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EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

CONTEXT PHYSICS MODELLING RESULTS CONCLUSIO^^^ OUTLOOK

Air concentrations of Rn-222

1 month September

1 year

...a site with a local radon exhalation VS a remote one

I RS []

«

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CONTEXT PHYSICS MODELLING RESULTS CONCLUSION OUTLOOK

Outdoor exposure to radon: annual mean

...similar patterns

Annual mean of air

concentration of Rn-222

Exhalation rate of Rn-222

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

IRS[]

Radonémissionflux(mBq.m

(22)

CONTEXT PHYSICS MODELLING RESULTS CONCLUSION OUTLOOK

Air concentrations of Bi-214

*#r>

EGU2019-18762 - Towards the forecast of false positives in nuclear network monitoring due to atmospheric radon

I RS []

Bi-214airconc.(Bq.m:!)

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