Study of a predictive methodology for quantification and mapping of the radon-222 exhalation rate

Ielsch, Géraldine; Ferry, Cécile; Tymen, G.; Robé, M.C.

doi:10.1016/s0265-931x(01)00133-3

Cited by 42 publications

(32 citation statements)

References 17 publications

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“…The instrument we used in our study was compared in 2003 (Lynette Robertson, PhD Thesis, University of Edinburgh, 2005) to an instrument which has been widely used in East-Asia. The mean flux determined at six locations was 52 Bq m −2 h −1 (standard error 9 Bq m −2 h −1 ) with our instrument and compared well with the mean flux of 49 Bq m −2 h −1 (standard error 8 Bq m −2 h −1 ) measured with the instrument described in Iida et al (1996).…”

Section: Rn Flux Measurement Techniquessupporting

confidence: 64%

“…A larger proportion of 222 Rn produced within the soil profile will escape to the atmosphere from coarse grained soils with a large total pore volume than from compacted fine grained soils, whereas the escape of gamma rays is unlikely to be affected by this. There already exist models for 222 Rn flux prediction based on geological and pedological factors, but such models require numerous parameters which are not well known due to the complicated interactions between different geological and pedological units influencing the 222 Rn flux (Ielsch et al, 2002). Temperature differences between air and soil have also been found to be a factor influencing 222 Rn flux (Nazaroff, 1992), which is driven by diffusion and possibly mass flow.…”

Section: Factors Affecting 222 Rn Flux But Not Gdrmentioning

confidence: 99%

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Predicting terrestrial 222Rn flux using gamma dose rate as a proxy

2007

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Abstract. 222 Rn is commonly used as a natural tracer for validating climate models. To improve such models a better source term for 222 Rn than currently used is necessary. The aim of this work is to establish a method for mapping this source term by using a commonly measured proxy, the gamma dose rate (GDR). Automatic monitoring of GDR has been networked in 25 European countries by the Institute for Environment and Sustainability at the Joint Research Centre (JRC IES) in Ispra, Italy, using a common data format. We carried out simultaneous measurements of 222 Rn flux and GDR at 63 locations in Switzerland, Germany, Finland and Hungary in order to cover a wide range of GDR. Spatial variations in GDR resulted from different radionuclide concentrations in soil forming minerals. A relatively stable fraction (20%) of the total terrestrial GDR originates from the 238 U decay series, of which 222 Rn is a member. Accordingly, spatial variation in terrestrial GDR was found to describe almost 60% of the spatial variation in 222 Rn flux. Furthermore, temporal variation in GDR and 222 Rn was found to be correlated. Increasing soil moisture reduces gas diffusivity and the rate of 222 Rn flux but it also decreases GDR through increased shielding of photons. Prediction of 222 Rn flux through GDR for individual measurement points is imprecise but un-biased. Verification of larger scale prediction showed that estimates of mean 222 Rn fluxes were not significantly different from the measured mean values.

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Section: Rn Flux Measurement Techniquessupporting

confidence: 64%

Section: Factors Affecting 222 Rn Flux But Not Gdrmentioning

confidence: 99%

Predicting terrestrial 222Rn flux using gamma dose rate as a proxy

2007

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“…In reality this flux depends on soil bedrock type, total pore space, tortuosity, soil moisture and precipitation. Its mean variability in Western Europe soils is of the order of 30% (Nazaroff, 1992;Jutzi, 2001;Ielsch et al, 2002;Szegvary et al, 2007). Secondly, the 222 Rn measurement precision itself is ∼30% which translates into a relative error of the same magnitude in the inferred CO 2 surface flux.…”

Section: Case Studymentioning

confidence: 99%

Variability and budget of CO2 in Europe: analysis of the CAATER airborne campaigns – Part 2: Comparison of CO2 vertical variability and fluxes between observations and a modeling framework

et al. 2011

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Abstract. Our ability to predict future climate change relies on our understanding of current and future CO 2 fluxes, particularly on a regional scale (100-1000 km). CO 2 regional sources and sinks are still poorly understood. Inverse transport modeling, a method often used to quantify these fluxes, relies on atmospheric CO 2 measurements. One of the main challenges for the transport models used in the inversions is to properly reproduce CO 2 vertical gradients between the boundary layer and the free troposphere, as these gradients impact on the partitioning of the calculated fluxes between the different model regions. Vertical CO 2 profiles are very well suited to assess the performances of the models. In this paper, we conduct a comparison between observed and modeled CO 2 profiles recorded during two CAATER campaigns that occurred in May 2001 and October 2002 over Western Europe, as described in a companion paper. We test different combinations between a global transport model (LMDZt), a mesoscale transport model (CHIMERE), and different sets of biospheric fluxes, all chosen with a diurnal cycle (CASA, SiB2 and ORCHIDEE). The vertical profile comparison shows that: 1) in most cases the influence of the biospheric flux is small but sometimes not negligible, ORCHIDEE giving the best results in the present study; 2) LMDZt is most of the time too diffuse, as it simulates a too high boundary layer height; 3) CHIMERE better reproduces the observed gradients between the boundary layer and the free troposphere, but is sometimes too variable and gives rise Correspondence to: I. Xueref-Remy (irene.xueref@lsce.ipsl.fr) to incoherent structures. We conclude there is a need for more vertical profiles to conduct further studies to improve the parameterization of vertical transport in the models used for CO 2 flux inversions.Furthermore, we use a modeling method to quantify CO 2 fluxes at the regional scale from a chosen observing point, coupling influence functions from the transport model LMDZt (that works quite well at the synoptic scale) with information on the space-time distribution of fluxes. This modeling method is compared to a dual tracer method (the so-called Radon method) for a case study on 25 May 2001 during which simultaneous well-correlated in situ CO 2 and Radon 222 measurements have been collected. Both methods give a similar result: a flux within the Radon 222 method uncertainty (35%), that is an atmospheric CO 2 sink of −4.2 to −4.4 gC m −2 day −1 . We have estimated the uncertainty of the modeling method to be at least 33% on average, and even more for specific individual events. This method allows the determination of the area that contributed to the CO 2 observed concentration. In our case, the observation point located at 1700 m a.s.l. in the north of France, is influenced by an area of 1500×700 km 2 that covers the Benelux region, part of Germany and western Poland. Furthermore, this method allows deconvolution between the different contributing fluxes. In this case study, the biospheric sink contri...

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“…A is emanation concentration from Uranium decay through unit thickness in unit time (Bq·cm -3 ·sec -1 ). A can be expressed by (2) Where , the radon emanation coefficient; , the dry bulk density of the soil (kg·m -3 ); C Ra , the specific activity of radium in soil (Bq·kg -1 ); , the effective porosity.…”

Section: Theoretical Formulamentioning

confidence: 99%

“…It is a feasible way to predict the regional radon distribution quickly and efficiently by combining these data with radon migration theory. Based on a steady-state radon transport model in porous materials 1) , combined with the local geological and pedological parameters, several methodologies were also developed for predicting a regional radon concentration [2][3][4] .…”

Section: Introductionmentioning

confidence: 99%

Preliminary Study on a Regional Radon Concentration in Surface Soil Prediction Method

Hai-jing

Lin

et al. 2011

Progress in Nuclear Science and Technology

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A reformulated mathematical equation for predicting radon concentration in surface soil has been established based on the diffusive and convection theory. The parameters in the equation, such as radon emanation coefficient, convection velocity, diffusion coefficient, porosity of soil and so on, are closely related to the soil types. In order to determine these parameters, field measurement were carried out in totally 31 sites covering four types of soil in Chengdu Area, China. And least squares fitting algorithm and inversion fitting computation were also used. The prediction equation is ultimately applied to map the radon concentration in surface soil of Chengdu Area along with the geochemical databases of uranium content distribution in soil and soil texture distribution. According to the field measurement results on 17 sites in Chengdu, the prediction was verified to work property.

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Study of a predictive methodology for quantification and mapping of the radon-222 exhalation rate

Cited by 42 publications

References 17 publications

Predicting terrestrial <sup>222</sup>Rn flux using gamma dose rate as a proxy

Predicting terrestrial <sup>222</sup>Rn flux using gamma dose rate as a proxy

Variability and budget of CO<sub>2</sub> in Europe: analysis of the CAATER airborne campaigns – Part 2: Comparison of CO<sub>2</sub> vertical variability and fluxes between observations and a modeling framework

Preliminary Study on a Regional Radon Concentration in Surface Soil Prediction Method

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Study of a predictive methodology for quantification and mapping of the radon-222 exhalation rate

Cited by 42 publications

References 17 publications

Predicting terrestrial &lt;sup&gt;222&lt;/sup&gt;Rn flux using gamma dose rate as a proxy

Predicting terrestrial &lt;sup&gt;222&lt;/sup&gt;Rn flux using gamma dose rate as a proxy

Variability and budget of CO&lt;sub&gt;2&lt;/sub&gt; in Europe: analysis of the CAATER airborne campaigns – Part 2: Comparison of CO&lt;sub&gt;2&lt;/sub&gt; vertical variability and fluxes between observations and a modeling framework

Preliminary Study on a Regional Radon Concentration in Surface Soil Prediction Method

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Predicting terrestrial <sup>222</sup>Rn flux using gamma dose rate as a proxy

Predicting terrestrial <sup>222</sup>Rn flux using gamma dose rate as a proxy

Variability and budget of CO<sub>2</sub> in Europe: analysis of the CAATER airborne campaigns – Part 2: Comparison of CO<sub>2</sub> vertical variability and fluxes between observations and a modeling framework