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Article Dans Une Revue Earth and Space Science Année : 2017

What we can learn from measurements of air electric conductivity in 222Rn-rich atmosphere

Résumé

Electric conductivity of air is an important characteristic of the electric properties of an atmosphere. Testing instruments to measure electric conductivity ranging from ~10-13 to 10-9 S m-1 in natural conditions found in the Earth atmosphere is not an easy task. One possibility is to use stratospheric balloon flights; another (and a simpler one) is to look for terrestrial environments with significant radioactive decay. In this paper we present measurements carried out with different types of Conductivity Sensors in two 222Rn-rich environments, i.e. in the Roselend underground tunnel (French Alps) and in the IRSN BACCARA chamber. The concept of the Conductivity Sensor is based on the classical time relaxation method. New elements in our design include isolation of the sensor sensitive part (electrode) from the external electric field and sensor miniaturization. This greatly extends the application domain of the sensor and permits to measure air electric conductivity when the external electric field is high and varies from few tens of V m-1 to up to few tens of kV m-1. This is suitable to propose the instrument for a planetary mission. Two-fold objectives were attained as the outcome of these tests and their analysis. First was directly related to the performances of the Conductivity Sensors and the efficiency of the Conductivity Sensor design to shield the external electric field. Second objective aimed at understanding the decay mechanisms of 222Rn and its progeny in atmosphere and the impact of the enclosed space on the efficiency of gas ionization. This article is protected by copyright. All rights reserved.
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Dates et versions

insu-01442086 , version 1 (11-03-2017)

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Elena Seran, Michel Godefroy, Éric Pili, Nathalie Michielsen, Sylvain Bondiguel. What we can learn from measurements of air electric conductivity in 222Rn-rich atmosphere. Earth and Space Science, 2017, 4 (2), pp.91-106. ⟨10.1002/2016EA000241⟩. ⟨insu-01442086⟩
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