Tectonically enhanced geogenic radon (TEGR) Quentin Crowley (1), Giancarlo Ciotoli (2), Georgia Cinelli (3), Javier Elo (1), Peter Bossew (4), Jenny McKinley (5), Rouwen Lehn (6), Annemarie Militzer (6) School of Natural Sciences, Trinity College, Dublin, Ireland 2 Institute of Environmental Geology and Geoengineering, National Research Council of Italy 3 European Commission, JRC, Directorate for Nuclear Safety & Security, Ispra, Italy 4 German Federal Ofce for Radiation Protection (BfS), Berlin, Germany 5 School of Natural and Built Environment, Queens University Belfast, Belfast, Northern Ireland, UK 6 Hessian Agency for Nature Conservation, Environment and Geology, Wiesbaden, Germany 1 Session GI2.6/AS4.20/EMRP4.7/NH11.11 Geoscience applications of environmental radioactivity v 4.6.2018 Introduction Two main reasons for interest in Radon (Rn): 1. Powerful tracer of processes (hydrogeology, volcanic, pollutants) 2. Health hazard: Radioactive gas, radioactive decay products can cause lung cancer Hazard Main source: geogenic Rn from the ground. Can accumulate in enclosed spaces. Regulation: European Basic Safety Standards (BSS, 2013): requires delineation of radon priority areas (RPA), i.e. areas in which prevention, mitigation and remediation should be given priority. Challenge: mapping the radon potential (RP); a quantity which measures the degree of priority. Possible predictors: Rn concentration in soil gas, geological / geochemical attributes.
BUT also tectonic factors Radon Distribution & Faults Tectonic and faulting processes may locally increase the Rn concentration by: co-precipitation of parent nuclides in groundwater by local changes of radium activity in the soil increasing soil and rock permeability in the fracture zones surrounding active faults (also if buried under sedimentary cover) action of carrier gases (i.e., CO2, N2, and CH4) from deep sources that favour the advection and high velocity of gas migration along faults Rn vs Fault Geometry Rn anomalies above a fault vary in intensity and shape. Irregular spatial distribution of soilRn concentrations related to fault geometry (undivided and divided faults), and by the volume of fractured rock. (Annunziatellis et al., 2008, right). At the early stages, there are few large active faults (diffuse fault), whereas at the final stages the fault zone is largely dominated by a main fault (localised fault). Seminsky et al., 2014
1. main fault zone; 2. fracturing zone; 3. Rn cross-fault variation (dashed line shows the average value); 4. total field of the anomalous values Tectonically Enhanced Geogenic Radon (TEGR) Challenges: Tectonically relevant areas may be local features; mostly linear rather than areal; represent anomalies over background. How to identify faults with a high degree of certainty? (i.e. how to separate anomalies from background, without resorting to eld studies; time consuming and costly may not be feasible on continental scale). Are there proxies available in existing databases? Possibility of remote sensing? How to map small linear phenomena in a large-scale (e.g. European) map? Possible Solutions: Dene a quantity: tectonic enhancement potential (TEP), which measures the strength of a tectonic factor in influencing the local Geogenic Radon Potential or Indoor Radon Concentration. Calibrate and validate the statistical association between TEP and GRP or IRC in eld studies. These problems are mostly unresolved. Soil gas survey Soil gas survey has been used for identification of blind faults beneath an overburden. Soil gas probe A B A. In-situ measurements of Rn, CO2, CH4, H2, O2 and H2S concentrations by using portable devices connected to a steel probe. The probe samples at a depth ~80cm in the
sub-soil. Gas Vent B. In particular cases (the study of macroscopic gas emissions, i.e., gas vents), soil gas survey may also include CO2 and CH4 flux measurements accomplished using a static closed-chamber equipped with portable CO2 and CH4 infrared and optical (laser) sensors, respectively. Rn vs Fault Geometry (buried faults) Fucino plane (central Italy) is the largest high seismic intermontane basin in the Apennine range in central Italy. The plane is characterised by a carbonate substrate buried under a thick sequence of alluvial deposits (up to 900m in the eastern sector). The geometry of the main buried faults has been derived from analysis of available seismic proles. The map shows radon anomalies in log values. The continuous isoline 1.35 (about 26 kBq/m3) corresponds to the mean radon content produced by the decay of its parent nuclide (226Ra). Rn anomalies occur in correspondence with known buried faults (SBGMF, OF and TF) . Rn vs Fault Geometry (buried fault) Variogram surface SBGMF and OF area Experimental variograms + model Geostatistical analysis highlights a clear and sharp anisotropic behaviour of the radon activity in correspondence of OF and SBGMF (fault in the north & central
of the study area), in contrast radon shows a broader distribution of the anomalies around TF (Ciotoli et al., 2007). TF area This suggests a possible dip-slip high angle geometry for OF and SBGMF, and a low angle for TF with a wider fracturing zone. Faults & Indoor radon Irish data 31,910 indoor radon measurements Sampled by the Environmental Protection Agency of Ireland (EPA) An average indoor radon concentration was estimated over grids of 1x1 km Ordinary kriging applying a trans-Gaussian kriging with Box-Cox transformation Fault mapping by GSI Tectonic enhancement potential (TEP) 1. Challenges to identify tectonic features Usually unclear if faults (if shown at all) are active or otherwise prone to tectonically enhanced geogenic Rn (European stress map may help). Coverage depends on map scale, which does not necessary reflect relevance w.r.t. Rn enhancement. 2. Mapping small anomalies Anomalies are a problem in geostatistics; locally violate 2nd order stationarity and assumptions on distribution (but linear anomalies generally show anisotropic distribution and can be recognised with directional variograms). Anomalously high values which are spatially conned may not contribute to a block mean (e.g. per grid cell or municipality) and thus may not be honoured adequately.
- Possibility: map not the central tendency, but high quantile, or occurrence probability of extremes (outliers relative to the background distribution) . - Possibility: exclude anomalies from background mapping, and add them as symbols on top of the background. - Categorical Rn risk maps (e.g. France): include tectonics in a scoring system. 3. Estimation of tectonic enhancement potential TEP Inverse perpendicular distance of a target point from a fault Mean inverse distance of a point from all fault lines within a neighbourhood Lineament density within a grid cell as a simple block predictor, or kernel density estimation (e.g. Ciotoli et al. 2017) Unlikely that a geographically based TEP is linearly related to indoor or geogenic Rn! Case study 1 (Regional Scale) Region: Cantabria, N Spain 1: 200,000 IGME-Geological and mining institute of Spain, faults TEP chosen: fault density in each 10 km x 10 km cell as units of length per unit of area. lin e a m e n t d e n s ity p ro b (IR C > 3 0 0 ) 0 .2 2 -4 2 0 0 0 0 900 -4 2 0 0 0 0 800 0 .2 0 .1 8 0 .1 6 -4 4 0 0 0 0 700 -4 4 0 0 0 0
-1 0 0 0 0 0 0 R n p r io r ity m a p d e r iv e d fr o m f a u lt d e n s it y -4 2 0 0 0 0 source: Cinelli et al. TEERAS conf., Soa, 2017 there seems to be an association between fault line density and Indoor Radon Concentration But not convincing -4 4 0 0 0 0 Predicted Rn priority areas blue: no RPA with 80% condence red: RPA with 80% condence grey: undened -4 6 0 0 0 0 -4 8 0 0 0 0 -1 1 2 0 0 0 0 -1 1 0 0 0 0 0 -1 0 8 0 0 0 0 -1 0 6 0 0 0 0 -1 0 4 0 0 0 0 -1 0 2 0 0 0 0 -1 0 0 0 0 0 0
Application to Continental-Scale Maps? Case study 2 (Continental Scale) Region: Europe 1:5M IGME by BGR; only actual faults and thrusts chosen. TEP chosen: fault density in each 10 km x 10 km cell as units of length per unit of area. Indoor Rn database: European Atlas of Natural Radiation (Joint Research Centre; JRC) The regional variability of the GRP obscures the possible influence of local tectonic features on the Rn level; however, they may appear in the intra-cell dispersion (e.g., GSD), which is largely independent of the level. The presence of features which enhance Rn can be expected to increase dispersion due to higher probabilities of extremes. Under Log-Linear assumption, estimated from data as (n= data per cell) r=0.237 n ln k (k ) 2 1 t n 1 n 1 ln GSD r=0.248 restricted to cells with 20 IRC data correlation between GSD or (k) and fault density is signicant:
parametric categorical ROC analysis: Case study 2 (Continental Scale) 0 0 0 0 0 2000000 .0 .0 .1 .1 .2 0 5 5 9 7 8 2 to 0 .0 8 8 to 0 .1 to 0 .1 3 3 to 0 .2 to 0 .2 2 3 2500000 2500000 2000000 2000000 fa u lt d e n s ity 1500000 1000000
e p s (3 ):= p r o b th a t in a c e ll v a lu e s > 3 x G M ( c e ll) o c c u r , r e la tiv e t o p r o b ( G M ) 1000000 0 0 0 0 0 500000 0 -1 0 0 0 0 0 0 -2 5 0 0 0 0 0 -1 5 0 0 0 0 0 -5 0 0 0 0 0 500000 1500000 2500000 Fault density per 10km cell (data from 1:5M IGME by BGR; only actual faults and thrusts chosen) .1 .2
-2 0 0 0 0 0 0 -1 5 0 00 0 0 -1 0 0 0 0 0 0 -5 0 0 0 0 0 0 500000 1000000 1500000 2000000 2500000 3000000 Eps(3) = probability that a cell value is >3x Geometric Mean, relative to the probability of that Geometric Mean b lu e : e p s ( 3 ) < 0 . 2 w it h 8 0 % c o n fid e n c e g r e y : u n d e c id e d o r a n g e : e p s ( 3 ) > 0 . 2 w it h 8 0 % c o n f id e n c e -2 5 0 0 0 0 0 -2 0 0 0 0 0 0 -1 5 0 0 0 0 0 -1 0 0 0 0 0 0
-5 0 0 0 0 0 0 500000 1000000 1500000 2000000 2500000 3000000 Zones of occurrence of higher rate of anomalies dened as eps(3)>20%, as predicted by fault density, with 80% condence. blue: dens < 0.085 orange: dens > 0.116 Continental Scale Indoor Radon & Faults 2500000 2000000 1500000 1000000 500000 0 -5 0 0 0 0 0
-1 0 0 0 0 0 0 b lu e : e p s ( 3 ) < 0 . 2 w it h 8 0 % c o n fid e n c e g r e y : u n d e c id e d o r a n g e : e p s ( 3 ) > 0 . 2 w it h 8 0 % c o n f id e n c e -1 5 0 0 0 0 0 -2 5 0 0 0 0 0 Indoor Rn database: European Atlas of Natural Radiation (Joint Research Centre; JRC) 10km cell -2 0 0 0 0 0 0 -1 5 0 0 0 0 0 -1 0 0 0 0 0 0 -5 0 0 0 0 0 0 500000 1000000 1500000 2000000 2500000 Zones of occurrence of higher rate of anomalies dened as eps(3)>20%, as predicted by fault
density, with 80% condence. blue: dens < 0.085 orange: dens > 0.116 3000000 Conclusions It is proven that geogenic Rn is enhanced near certain tectonic features; the physical process is basically understood. Tectonically enhanced geogenic Rn should be represented in Rn maps which are used to inform a Rn mitigation action. Local scale informative, but at a cost Regional scale high-quality map data are needed. Tectonic effect is likely obscured by regional variability of background geological control factors, BUT correlation between intra-cell dispersion & fault density exists. Methodology is still in the experimental phase; some promising results, but problems have not yet been fully resolved Institute of Environmental Geology and Geoengineering Thank you! All about radon: http://radoneurope.org/
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