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

Arnaud Querel, Denis Quelo, Thierry Doursout

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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

HAL Id: hal-02635634

https://hal.science/hal-02635634v1

Submitted on 27 May 2020

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Distributed under a Creative Commons CC BY 4.0 - Attribution - International License
IRSN

INSTITUT
DE RADIOPROTECTION
ET DE SÛRETÉ NUCLÉAIRE

Faire avancer la sûreté nucléaire

Simulated dose rate
01 Sep 00:00

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Réseau Téléray au 20/11/2018

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EGU 2019 18762

April, 11th 2019

Arnaud QUÉREL

Denis QUÉLO

Thierry DOURSOUT

© IRSN
A preliminary study showed encouraging results...

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

<figure><img src="image_8.png" /><figcaption>Réseau Téléray au 20/11/2018</figcaption></figure>

<figure><img src="image_9.png" /><figcaption>Balises Téléray</figcaption></figure>

Is it possible to forecast peaks due to atmospheric radon?

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# Atmospheric transport of radon

① Exhalation of radon(gas)

<figure><img src="image_13.png" /></figure>

③ Precipitation

<figure><img src="image_14.png" /></figure>

② Radon daughters (particles)

<figure><img src="image_15.png" /></figure>

⑦ Fast radioactive decay of daughters

<figure><img src="image_16.png" /></figure>

④ Deposit of daughters

<figure><img src="image_17.png" /></figure>

⑤ Radiation

Monitoring station

<figure><img src="image_18.png" /></figure>

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# Modelling

① Exhalation of radon(gas)

<figure><img src="image_21.png" /></figure>

<figure><img src="image_22.png" /></figure>

② Atmospheric transport model IdX

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① Meteorological data

<figure><img src="image_24.png" /></figure>

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① Decay chain & Chem/phys form data

③ Dose rate computation

<figure><img src="image_26.png" /></figure>

For each time step :

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Dose rate at ground level (2D)

④ Outputs

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Dose rate maps

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Dose rate at a given location

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To be compared to the measurements

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Teleray: the French monitoring network of gamma dose rate

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Hundreds of stations (~420)

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Freq : 10 min

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Source
term

Met
data

Atmospheric
transport

Dose rate
assessment

Output

Observations

## 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

<figure><img src="image_37.png" /></figure>

## Meteorological data

* Météo-France
meteorological data: **ARPEGE**

* $\Delta t$: 1h ; $\Delta x=\Delta y=0.1°\approx10km$

<figure><img src="image_38.png" /></figure>

METEO
FRANCE

Vent (m/s) le 16-03-2011 00h00 (heure locale)

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Source
term

Met
data

Atmospheric
transport

Dose rate
assessment

Output

Observations

Exhalation
of Rn-222

Met
data

Atmospheric transport model
ldX

Plume transport

Plume diffusion

Dry deposition

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., Ted W. Bowyer, Pascal Achim, Tianfeng Chai, Benoit Deconninck, Katie Freeman, Sylvia Generoso, et al. 2016. « International Challenge to Predict the Impact of Radionexon Releases from Medical Isotope Production on a Comprehensive Nuclear Test Ban Treaty Sampling Station ». *Journal of Environmental Radioactivity* 157 (juin): 41-51.
https://doi.org/10.1016/j.jenvrad.2018.03.001.

Groëll, Jérôme, Denis Quélé, et Anne Mathieu. 2014. « Sensitivity analysis of the modelled deposition of 137 Cs on the Japanese land following the Fukushima accident. » *International Journal of Environment and Pollution* 55 (1-4): 67-75. https://doi.org/10.1504/iep.2014.065906.

Kajino, Mizuo, Tsuyoshi Thomas Sekiyama, Anne Mathieu, Irène Korsakissok, Raphaël Péralat, Denis Quélé, Arnaud Quérél, et al. 2018. « Lessons Learned from Atmospheric Modeling Studies after the Fukushima Nuclear Accident: Ensemble Simulations, Data Assimilation, Elemental Process Modeling, and Inverse Modeling ». *Geochemical Journal* 52 (2): 85-101.
https://doi.org/10.2343/geochim_jou_20503.

Kitayama, K., Y. Morino, M. Takigawa, T. Nakajima, H. Hayami, H. Nagai, H. Terada, et al. 2018. « Atmospheric Modeling of ¹³⁰Cs Plumes From the Fukushima Daiichi Nuclear Power Plant: Evaluation of the Model Intercomparison Data of the Science Council of Japan ». *Journal of Geophysical Research: Atmospheres* juliet. https://doi.org/10.1029/2017/JD028230.

Mathieu, Anne, Irène Korsakissok, Denis Quélé, Jérôme Groëll, Marilyne Tombette, Damien Didier, Emmanuel Quentric, Olivier Saunier, Jean-Pierre Benoit, et Olivier Isnard. 2012. « Fukushima Daiichi Atmospheric Dispersion and Deposition of Radionuclides from the Fukushima Daiichi Nuclear Power Plant Accident ». *Elements* 8 (3): 195-200.
https://doi.org/10.2113/elements.8.3.195.

Maurer, Christian, Jonathan Bär, Jolanta Kusmierczyk-Michulec, Alice Crawford, Paul W. Eslinger, Petra Seibert, Blake Orr, et al. 2018. « International Challenge to Model the Long-Range Transport of Radioxonen Released from Medical Isotope Production to Six Comprehensive Nuclear-Test-Ban Treaty Monitoring Stations ». *Journal of Environmental Radioactivity* 192 (débutembre): 667-86.
https://doi.org/10.1016/j.jenvrad.2018.01.030.

Quérél, Arnaud, Yélva Roustan, Denis Quélé, et Jean-Pierre Benoit. 2015. « Hints to Discriminate the Choice of Wet Deposition Models Applied to an Accidental Radioactive Release. » *International Journal of Environment and Pollution* 58 (4): 288-79. https://doi.org/10.1504/IEP.2015.077457.

Sato, Yousuke, Masayuki Takigawa, Tsuyoshi Thomas Sekiyama, Mizuo Kajino, Hiroaki Terada, Haruyasu Nagai, Hiroaki Kondo, et al. 2018. « Model intercomparison of Atmospheric ¹³⁰Cs from the Fukushima Daiichi Nuclear Power Plant Accident: Simulations Based on Identical Input Data ». *Journal of Geophysical Research: Atmospheres*, octobre. https://doi.org/10.1029/2018JD029144.

Saunier, Olivier, Anne Mathieu, Damien Didier, Marilyne Tombette, Denis Quélé, Victor Vinarek, et Marc Bocquet. 2013. « An inverse modelling method to assess the source term of the Fukushima Nuclear Power Plant accident using gamma dose rate observations ». *Atmospheric Chemistry and Physics* 13: 11403-21. https://doi.org/10.1016/j.jenvrad.2013.08.001.

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Source
term

Met
data

Atmospheric
transport

Dose rate
assessment

Output

Observations

For each radionuclides at
each time step :

Air concentration (3D)

Deposit (2D)

<figure><img src="image_46.png" /></figure>

Dose rate
computation

<figure><img src="image_47.png" /></figure>

For each time step :

Dose rate at
ground level (2D)

<figure><img src="image_48.png" /></figure>

PARTICLE

Radiation emitted by
radioactive particles

<figure><img src="image_49.png" /></figure>

<figure><img src="image_50.png" /></figure>

GAS

Radiation emitted by
radioactive gases

Dose rate
measured near
the ground

<figure><img src="image_51.png" /></figure>

Radiation emitted by the radioactive deposit

<figure><img src="image_52.png" /></figure>

Deposit

<figure><img src="image_53.png" /></figure>

<figure><img src="image_54.png" /></figure>

<figure><img src="image_55.png" /></figure>
Source
term

Met
data

Atmospheric
transport

Dose rate
assessment

Output

Observations

Dose rate maps

<figure><img src="image_56.png" /></figure>

Dose rate at a given location

Compared to the local observation

<figure><img src="image_57.png" /></figure>

<figure><img src="image_58.png" /></figure>
Source
term

Met
data

Atmospheric
transport

Dose rate
assessmentS

Output

Observations

Teleray : the French monitoring network of gamma dose rate

Hundreds of stations (~420)

Freq : 10 min

Réseau Téléray au 20/11/2018

Balises Téléray

<figure><img src="image_59.png" /></figure>

<figure><img src="image_60.png" /><figcaption>Aiguille -du-Midi</figcaption></figure>

<figure><img src="image_61.png" /><figcaption>Clermont-Ferrand</figcaption></figure>

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# Model-to-data comparison...

Some comparisons of dose rate : **model** vs **measurements**

Some peaks are very well modelled in time and intensity

<figure><img src="image_63.png" /></figure>

<figure><img src="image_64.png" /></figure>

Day/night cyclic variation is correctly reproduced

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# Model-to-data comparison...

Some comparisons of dose rate : **model** vs **measurements**

Some peaks are modelled but not observed

<figure><img src="image_70.png" /></figure>

Time shifting

<figure><img src="image_71.png" /></figure>

The height of the peaks can also be challenging to model

<figure><img src="image_72.png" /></figure>

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# Model-to-data comparison...

## Some comparisons of dose rate : **model** vs **measurements**

<figure><img src="image_75.png" /></figure>

<figure><img src="image_76.png" /></figure>

Other
examples

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# Air concentrations: order of magnitude

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**Modelling :** Lyon
from may 2017 to
may 2018

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

Rn-222 daughters

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# 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

## Outputs for IRSN

* Forecast of dose rate peaks

* Improve the atmospheric transport model (wet deposition modelling)

* Atmospheric radon exposure

<figure><img src="image_87.png" /></figure>

<figure><img src="image_88.png" /></figure>
## ...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

<figure><img src="image_89.png" /></figure>

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Improve the atmospheric transport model (wet deposition modelling)

* The Fukushima accident was a privileged case study for verification of the model capability to simulate accidental 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.

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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

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# 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, 2017

<figure><img src="image_98.png" /></figure>

<figure><img src="image_99.png" /></figure>
## Air concentrations of Rn-222

1 year

<figure><img src="image_100.png" /></figure>

1 month
September

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

<figure><img src="image_101.png" /></figure>
# Outdoor exposure to radon: annual mean

## ...similar patterns

<figure><img src="image_102.png" /><figcaption>Exhalation rate of Rn-222</figcaption></figure>

<figure><img src="image_103.png" /></figure>

<figure><img src="image_104.png" /></figure>
Air concentrations of Bi-214

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