Trinity College Dublin, The University of Dublin. Introduction. 1. Risk due to the inhalation of existing radon (222Rn) progeny attached to aerosols; i.e. ...
Correlation between topsoil geochemistry and indoor radon concentration J. Elío1, Q. Crowley1, R. Scanlon2, J. Hodgson2, V. Gallagher2, S. Long3, M. Cooper4 1) 2) 3) 4)
Trinity College Dublin (TCD) Geological Survey, Ireland (GSI) Environmental Protection Agency of Ireland (EPA) Geological Survey of Nortern Ireland (GSNI)
Introduction Radon and lung cancer 1.
Risk due to the inhalation of existing radon (222Rn) progeny attached to aerosols; i.e. suspended particles.
2.
Radon progeny may deposit in the respiratory tract.
3.
Radon progenies are also radioactive and emit alpha and beta particles.
4.
This radiation can interact with lung tissue leading to DNA damage and development of lung cancer.
GAS
SOLID
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Introduction Radon in dwellings
R.L. = 200 Bq m-3
GAS
Geology is the main factor controlling indoor radon concentration Can we detect radon priority areas based on geological information? Trinity College Dublin, The University of Dublin
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Introduction A new indoor radon risk map using geological information
However:
~
12 levels
10 levels
=
Topsoil geochemistry accounts for up to 40% of indoor radon variance in the UK (Ferreira et al. 2016). Can we use Tellus geochemical data to improve the radon risk map?
3 levels
Trinity College Dublin, The University of Dublin
5 levels
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Tellus Project www.tellus.ie Geological Survey, Ireland (GSI) and Geological Survey of Northern Ireland (GSNI) “Tellus is a ground and airborne geoscience mapping programme, collecting chemical and geophysical data that will inform the management of Ireland’s environment and natural resources” (data available on www.tellus.ie). National Surveys 1. Airborne: magnetic field, gamma-ray spectrometry and electrical conductivity
2. Geochemical surveys of soil: topsoil, steam water and stream sediment Radon Mapping 1. Airborne radiometrics: U, Th and K 2. Topsoil geochemical: pH, LOI and 52 analytes (ICP) (58 by XRFS); including U, Th and K Trinity College Dublin, The University of Dublin
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Geochemistry data Overview
Present study Topsoil data from Tellus Border
3,440 samples; pH, LOI and 52 analytes by ICP 5,755 indoor radon samples (EPA)
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Data preparation 1. Non-detected values: Impute values bellow D.L. using a Compositional Data approach (i.e. alr-EM algorithms) R software: • Package: zCompositions • Function: lrEM
Example: Arsenic: D.L. 1 mg kg-1 (Percentage of non-detected 6 %) 0.5 DL
< D.L.
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Multivariate CoDa method
< D.L.
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Data preparation 2. Outliers: Multivariate Outliers Detection for Compositional Data using robust Mahalanobis distances R software: • Package: mvoutlier • Function: mvoutlier.CoDa
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Data preparation 2. Outliers: Outliers are dominated by S, Na and Sr, which accounts for about 55% of the total variability (PC1) Sulphur is the dominant element in the first principal component (PC1) Outliers are related to soil properties, probably to its concentration in organic matter
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Data interpretation Cluster analysis: evaluate if there are samples with similar geochemical composition, and if these samples are clustering in a specific geographic area Isometric log-ratio transformed (ilr) and standardised; Ward clustering criteria, Euclidean distance
Note: pH, LOI and elements with more than 10% of values below detection limit were not taken into account. Trinity College Dublin, The University of Dublin
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Data interpretation Cluster analysis may be useful for analysing the provenance of quaternary deposits. For example:
G1 and G2 have the highest values of LOI and S, and the lowest pH, which may be associated to peat soils G4 is the cluster with the highest pH and the highest concentration in Sr, Ca, and Na, which may be related to a sea spray deposition along the west coast
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Data interpretation Uranium vs. cluster groups Call: lm(formula = log(U) ~ RCL6, data = TS) Residuals: Min 1Q Median 3Q Max -2.0373 -0.3355 -0.0370 0.2776 4.4300 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -0.76749 0.03265 -23.505 < 2e-16 *** G2 -1.13926 0.04342 -26.239 < 2e-16 *** G3 1.01958 0.03716 27.434 < 2e-16 *** G4 -0.37625 0.08661 -4.344 1.44e-05 *** G5 0.86149 0.03902 22.080 < 2e-16 *** G6 0.97222 0.04003 24.287 < 2e-16 *** --Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.6003 on 3434 degrees of freedom Multiple R-squared: 0.5995, Adjusted R-squared: 0.5989 F-statistic: 1028 on 5 and 3434 DF, p-value: < 2.2e-16 Trinity College Dublin, The University of Dublin
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Data interpretation Indoor radon vs. cluster groups Call: lm(formula = log(InRn) ~ RCL6, data = InRn) Residuals: Min 1Q Median 3Q Max -6.3158 -0.6701 -0.0218 0.6614 4.6197 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 3.91726 0.09587 40.858
