NH8.5

As the scientific and knowledge service of the European Commission, the mission of the Joint Research Centre (JRC) is to support EU policies with independent evidence throughout the whole policy cycle. In particular, the JRC provides this support to the Directorate General for Energy by collecting, evaluating and reporting artificial environmental radioactivity measurements both for routine (REM database) and emergency preparedness (European Radiological Data Exchange Platform) purposes.
However, with the exception of potential large scale nuclear accidents, natural ionizing radiation is the largest contributor to the collective effective dose received by the world population. To gain a clearer overview of the natural sources of radioactivity, the JRC launched the European Atlas of Natural Radiation with the aim to provide insight into geographical variability of exposure components and their relative importance for total exposure to ionizing radiation.

The Atlas presents contributions from 100 experts in various fields, from 60 institutions such as universities, research centres, national and European authorities, and international organizations. In the first place, this Atlas aims to provide reference values and generate harmonised data for the scientific community and national competent authorities. It also offers an opportunity to the public to become familiar with the radioactive part of its natural environment. Intended as an encyclopaedia on natural radioactivity, the Atlas explains its different sources, i.e. cosmic and terrestrial radiation, and describes the current state-of-the art of knowledge by means of text, graphics and maps.

Being responsible for half of the natural dose, particular attention has been given to indoor radon, of which over one million measurements of long-term indoor radon concentration in ground-floor rooms of dwellings from 36 European countries were collected and aggregated as means within 10 km × 10 km grid cells. The updated version of the European Indoor Radon Map (December 2020) will be presented as well as the statistical analysis of the input data.

Geogenic Radon Potential and Geogenic Radon Hazard Index quantify the contribution of geogenic to indoor radon and are constructed using geogenic quantities, such as uranium concentrations in the ground, geology, soil permeability, soil radon concentration and terrestrial gamma dose rate.
Therefore, it was decided to focus the Atlas on the development of maps that display natural sources of radiation and also serve as quantities which predict geogenic radon. Maps of uranium, thorium and potassium concentrations in soil, covering most European countries, were created, while maps of uranium, thorium and potassium concentrations in bedrock are only available for some countries. A methodology for estimating the terrestrial gamma dose rate (based on ambient dose equivalent rate measurements) has been established, while the European terrestrial gamma dose rate map has been created using uranium, thorium and potassium concentration in soil. The practical use of the maps of the Atlas as geogenic quantities will be illustrated through different examples of scientific studies.

The Atlas is available in digital format and can be ordered as a printed version at https://remon.jrc.ec.europa.eu/ .

How to cite: Cinelli, G., Bossew, P., De Cort, M., Gruber, V., and Tollefsen, T.: Harmonized radon data in the European Atlas of Natural Radiation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-11052, https://doi.org/10.5194/egusphere-egu21-11052, 2021.

Warming global climate threatens the stability of the polar regions and may result in cascading broad impacts. Studies conducted on permafrost in the Arctic regions indicate that these areas may store almost twice the carbon currently present in the atmosphere. Therefore, permafrost thawing has the potential to magnify the warming effect by doubling the more direct anthropogenic impact from burning of fossil fuels, agriculture and changes in land use. . Permafrost thawing may also intensify the Rn transport due to the increase of fluid saturation and permeability of the soil. A detailed study of ²²²Rn and ²²⁰Rn activity levels in polar soils constitutes a starting point to investigate gas migration processes as a function of the thawing permafrost. Although several studies have been carried out in the Arctic regions, there is little data available from the Southern Hemisphere. The Italian – New Zealand “SENECA” project aims to fill this gap and to provide the first evaluations of gas concentrations and emissions from permafrost and/or thawed shallow strata of the Taylor Valley, Antarctica. Taylor Valley is one of the few Antarctic regions that are not covered by ice and therefore is an ideal target for permafrost investigations. Results from our first field observations highlight very low values for ²²²Rn (mean 621 Bq m^-3, max value 1,837 Bq m^-3) and higher values for ²²⁰Rn (mean 11,270 Bq m^-3, max value 27,589 Bq m^-3), suggesting a shallow source. These measured activity values are essentially controlled by the radionuclide content in the soil, by the permeability and porosity of the soil, and by the water content. This dataset also represents an important benchmark for future measurements to track the melt progress of Antarctic permafrost.

How to cite: Ruggiero, L., Sciarra, A., Galli, G., Mazzini, A., Mazzoli, C., Tartarello, M. C., Florindo, F., Wilson, G., Bigi, S., Sassi, R., Anderson, J., and Ciotoli, G.: First measurements of 222Rn and 220Rn activities in soil in Taylor Valley, Antarctica., EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5100, https://doi.org/10.5194/egusphere-egu21-5100, 2021.

The City of Mexicali and its Valley are located within the San Andrés fault system, a geological fault system generated by the activity of the Pacific and North American tectonic plates, as boudary plates the principal Faults are Imperial Fault and Cerro Prieto Fault. We present our results related to the search o traces of geological faults using ground penetrating radar combined with Radon gas ( 222Rn) measurements in the Instituto Tecnológico de Mexcali inner the urban area and Mexicali Valley.As extension of this studies we apply this approach to the urban area of Morelia City in Mexico.

How to cite: Lazaro-Mancilla, O., Ramirez-Hernandez, J., and Reyez-López, J. A.: Application of Ground Penetrating Radar combined with 222Rn (Radon) measurements  for serch geological faults in Mexicali Baja California, Mexico, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10533, https://doi.org/10.5194/egusphere-egu21-10533, 2021.

Radon (222Rn) is a naturally inert radioactive gas, originating from the radioactive decay of 226Ra in the 238U radioactive decay chain. 222Rn has a variety of geoscientific applications. 222Rn, however, represents the most significant source of ionizing radiation exposure and can be critical in underground working and living spaces with little or no ventilation. Particularly, caves are recognized as special indoor occupational environments where extremely elevated concentrations of 222Rn may occur during, at least, half-year during its recharged stage.

The measurement of radon activity concentration in air can be performed using different types of equipment and methodologies. However, it is characterized by the dispersion for relatively short exposition times and depends on the radon activity concentration and environmental parameters. This investigation aims to compare different types of equipment and methodologies to measure 222Rn under real cave conditions.

Rull Cave is located in Vall d’Ebo, in the south-east of Spain (Alicante province). The host rock of the cave is composed of Miocene conglomerates lying on Cretaceous limestones. Above the cave, the soil has a discontinuous thickness of approximately 1 m. The investigation is performed in winter where the cave remains discharged. During this period, the gas concentration reaches minimum values and presents low fluctuation of radon activity concentration. Temperatures in Rull Cave range between 17 and 20°C, the mean relative humidity reaches about 87%, and the constant pressure of 975 mBar. 222Rn measurements have been taken continually since 2016, ranging from 645 to 3959 Bq/m3.

We compare, firstly, cave air radon with three devices: AlphaGUARD DF2000, Radim 5WP, and RadonScout Plus. The second method involves the measurement of air radon samples after collecting them in sampling bags. We perform two types of measures: (i) in-situ measures of air samples and (ii) measure of the collected sampling bags 24-hours later (in the laboratory). For this purpose, we use opaque and transparent 1L-gas sampling bags (GSB), and we also evaluate the influence of the air volume (2 or 4 L) on radon activity concentration measurement using AlphaGUARD DF2000 at 0.3 L/min pump flow.

These findings reveal that i) all devices have similar values of radon activity concentration, with a difference between AlphaGUARD DF2000 with Radim 5WP, and RadonScout Plus of -32% and +19 %, respectively; ii) the use of transparent or opaque GSB provide similar 222Rn concentration; iii) 222Rn concentration after 24-hours is nearly the same than samples tested immediately after collecting; and iv) direct data and the one collected in GSB are equivalent, although 4L GSB often register higher values than 2L. Both methodologies highlight the known problem of radon fluctuations at a short scale. We do recommend collecting air samples in 4L-GSB. It presents practical advantages for cave studies. Thus, 222Rn can be measured in cave areas that are nor not easily accessible areas. In addition, this methodology allows increasing the number of measurements, as well as to safety keep the devices at the lab.

How to cite: Gil-Oncina, S., Pla, C., Valdes-Abellan, J., Garcia-Martinez, N., and Benavente, D.: Comparison of 222Rn measurement methods in caves, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7953, https://doi.org/10.5194/egusphere-egu21-7953, 2021.

INTRODUCTION

Following the recommendations of the National Prevention Plan, the Sardinia Region Department of Hygiene, Health and Social Security has promoted a programme dedicated to protecting the population from exposure to radon gas. The plan included: radon monitoring activities during a dedicated campaign based on geological mapping; radon Health Impact Assessment, HIA; drafting of “Guidelines for the construction/renovation of buildings”; community involvement and a radon risks communication campaign.

OBJECTIVES

To present the development of the HIA based on radon environment monitoring data and the communication process.

METHODS

Radon risk mapping combined the knowledge of geological composition of Sardinia Island and the results obtained by monitoring with dedicated devices.

HIA was implemented calculating cases attributable (CA) to radon exposure, combining the following parameters: Relative Risk (available by literature); mortality rate of lung cancer prevalence/incidence rate (baseline); exposed population size; radon concentration target.

The radon monitoring campaign required a widespread communication activity, while the results communication activity, based on a dedicated plan, involved multiple stakeholders.

RESULTS

On the basis of radon concentration data estimated by ARPAS, the HIA procedure estimated lung cancer deaths attributable to radon in areas of different exposure and throughout Sardinia. In the whole region, with an average concentration of 116 Bq/m3, radon-attributable cases were estimated at 143 out of 832 total expected deaths (attributable fraction 17.2%); in the area most at risk, including 49 municipalities, with an estimated average concentration of 202 Bq/m3, radon-attributable deaths were 13 out of 55 total (attributable fraction 23.6%).

The parameters of the algorithm and the results were presented and discussed with the local working groups.

A specific radon monitoring activity developed in schools helped to focus the efforts on the protection of school goers as vulnerable and susceptible groups. Urgent renovation and improvement activities in school and in other public administration buildings throughout the region were carried out.

Six guided discussions and four training sessions during six months were held to develop HIA and communication activities. A meeting to present the work was held in Nuoro town in October 2019, where information material was distributed and public attention raised around the issue.

The communication process aggregated several stakeholders including: civil servants in the field of health and the environment; public administrators; health professionals committed to spread knowledge about radon-free building.

CONCLUSIONS

The objectives of the regional program were focused to: - protect Sardinian population from radon risk, with special reference to vulnerable and susceptible subjects, particularly radon exposed smokers; - spread knowledge about risks; - inform about the opportunities to reduce risks.

Results indicate that the health of populations living in radon-exposed areas can be significantly improved by reducing exposure to radon and synergistic risk factors. It is essential to strengthen awareness-raising activities using historical and acquired knowledge and to monitor progress in order to reinforce further action, as these activities should be planned for the long term.

How to cite: Cori, L., Cappai, M., Dettori, I., Loi, N., Nurchis, P., Sanna, A., Serra, G., Sirigu, E., Tidore, M., and Bianchi, F.: Radon Health Impact Assessment and Risk Communication in Sardinia Region, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6339, https://doi.org/10.5194/egusphere-egu21-6339, 2021.

Indoor radon is considered as an indoor air pollutant due to its carcinogenic effect. Since the main source of indoor radon is the ground beneath the house, we use geogenic Rn as predictor for indoor Rn hazard mapping. In this contribution, we present a model to link geogenic to indoor Rn.

In a first step, we build a random forest model that utilizes observational data (n=6,293) of Rn concentration in soil gas and soil gas permeability across Germany in combination with auxiliary data (geology, soil physical and chemical properties, climate) to create spatially continuous map of a geogenic radon hazard index. Then, in a second step, this is geogenic radon hazard index map is linked to indoor radon data (n=44,629) via a logistic regression model for calculating the probabilities that indoor Rn exceeds 300 Bq/m³. The estimated probability was averaged for every municipality by considering only the estimates within the built-up area. Finally, the mean exceedance probability per municipality was coupled with the respective residential building stock for estimating the number of residential buildings with indoor Rn above 300 Bq/m³ for each municipality.

We found that (1) the municipal-scale maps of 300 Bq/m³ exceedance probability (individual hazard) and affected residential buildings (collective hazard) show contrasting spatial patterns, (2) the estimated number of buildings above 300 Bq/m³ in Germany is 345,000 (1.9 % of all residential buildings), (3) areas where 300 Bq/m³ exceedance is greater than 10 % comprise only 0.8 % of the German building stock but 6.3 % of buildings with indoor Rn exceeding 300 Bq/m³, and (4) most urban areas and most high-radon residential buildings (77 %) are located in low hazard regions.

The implications for Rn protection are twofold: (1) the Rn priority area concept is cost-efficient in a sense that it allows to find the most buildings that exceed a threshold concentration with a given amount of resources, and (2) for an optimal reduction of lung cancer risk areas outside of Rn priority areas must be addressed since most hazardous indoor Rn concentrations occur in low to medium hazard areas.

How to cite: Petermann, E. and Bossew, P.: Mapping indoor radon: individual vs. collective hazard, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1018, https://doi.org/10.5194/egusphere-egu21-1018, 2021.

Inhalation of radon gas exposes the lungs to ionizing radiation which significantly contributes to the equivalent dose received by a human body. European Union advises Member States to identify radon prone areas (RPA), characterized by a significant percentage of dwellings above the national reference level (RL).

The presented work aims to evaluate the use of Receiver Operating Characteristic (ROC) curve analysis to map RPAs at a small-scale (from 1:25 000 to 1:1 000, henceforward called “regional” and “local” scale respectably), using interpolated surfaces of total gamma radiation (TGR) as proxy and point data of radon concentration in dwellings as the observed variable.

The case-study areas are in the center of Portugal (Tondela and Oliveira do Hospital) where outcrops different coarse-grained biotite granites (Beira’s Granite) and metasediments of Beiras’ Group, frequently as small enclaves hosted in the granites. An intense network of faults is also characteristic of these regions.

At Tondela area the geospatial analysis and ordinary kriging interpolation of TGR, on a regional scale, evidenced: a) a geological control on this variable; b) a structural control on anomalies by N35ºW orientated faults and by the intersection of these structures with others, namely N75ºE and N55ºE; c) and an anisotropic covariance of equally spaced points with N35^oE oriented major axis. At Oliveira do Hospital, where at a regional scale just data of anomalies was available, the log-normal distribution of background values was simulated based on high-definition data obtained at a local scale. The results are consistent with the structural control pattern identified at Tondela. The best classifiers identified by the ROC analysis were 175 cps and 450 cps, respectably for Tondela and Oliveira do Hospital regions.

Establishing a 10% probability of dwellings with concentrations of radon above RL ( ) to define an RPA, all the areas were classified as RPAs. At Tondela region, the lowest risk area represents 25% probability of exceeding the RL and the highest risk area 52%. At Oliveira do Hospital almost the entire region represents 56% exceedance probability. The highest risk area is spatially related to intense anomalies and represent 78% exceedance probability.

For the geological context studied, the use of TGR proved to be suitable for radon gas risk mapping. The ROC curve analysis enabled to significantly classify higher and lower risk areas within high-risk regions, considering the small-scale variability. The ROC analysis did not produce a classifier properly calibrated to the RL but one that improves the cost-benefit of the classification relatively to the natural prevalence of the studied areas.

How to cite: Santiago, G. and Pereira, A.: Methodologies for risk mapping of radon gas at various scales in Tondela and Oliveira do Hospital region (center of Portugal), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7503, https://doi.org/10.5194/egusphere-egu21-7503, 2021.

Radon generation and migration from the soil toward the surface are natural processes that can lead to radon entry in buildings, thus constituting a health risk. The analysis and the modelling of these processes can be thought of as the contribution of different proxies representing the geological radon source (GRS) (e.g., geology, soil properties, radionuclide content), and the pathways (e.g., faults, karst) that favour the geological radon migration (GRM) in the subsoil. The aggregation of these quantities can be used to construct a geogenic radon hazard index (GRHI) map that can be understood as a measure of the susceptibility of an area to increased indoor radon concentration for geogenic reasons (Radon Priority Areas, RPA).

A number of direct and indirect models have been developed in order to create GRHI maps of a certain region by using both deterministic and probabilistic models. Here, we propose a bottom-up procedure through the integration of different factors (predictors and/or proxies) and by weighs their importance. In particular, we first propose to construct a GRHI map of the whole Italian territory using a GIS-based (spatial) multicriteria decision analysis (SMCDA). SMCDA uses the Analytical HierarchyProcess (AHP) to assess the importance of the factors and to derive their relative weights and, consequently, it determines the overall final scores.

Lithologies of the National Geological Map of Italy (1:1000000) were reclassified in few homogeneous classes and ranked according to the associated mean content of uranium, thorium and potassium available from GEMAS (http://gemas.geolba.ac.at/) and FOREGS (http://weppi.gtk.fi/publ/foregsatlas/index.php) database by using a multivariate statistical approach. In this way the intermediate map of the GRS was obtained. SMCDA was then applied by using the GRS map and the maps of other factors, such as the fine fraction of the soil (LUCAS top-soil database, https://esdac.jrc.ec.europa.eu/projects/lucas), the fault density map (Italian national/regional datasets), the map of the karst areas (https://www.whymap.org/whymap/EN/Maps_Data/Wokam/wokam_node_en.html) and the map of the heat flow of Italy. All these factors were standardised by using fuzzy classification to transform input data to a 0/1 scale. The standardised factors are weighted by using AHP and then summed to obtain the final GRHI map. All maps are constructed at the same grid resolution of the European Atlas of Natural Radiation (10x10km) (https://remon.jrc.ec.europa.eu/About/Atlas-of-Natural-Radiation) published by the Joint Research Centre (JRC) of the European Commission.

How to cite: Giustini, F., Procesi, M., Finoia, M., Sassi, R., Mazzoli, C., and Ciotoli, G.: Mapping the Geogenic Radon Hazard Index of Italy, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7343, https://doi.org/10.5194/egusphere-egu21-7343, 2021.

Exposure to indoor radon is recognized as a health hazard, which is why regulation aimed to its reduction has been developed. One important tool of radon (Rn) policy are Rn maps. They serve (1) for visualizing the geographical distribution of the hazard and (2) as data base for regionalized legal measures, i.e. action which should be appropriate for the Rn situation at a place.

(1) has as objective information of stakeholders (the public, administrations, legislators, Rn professionals) about magnitude and location of the problem;

(2) Objective is decision support for identification of regions in which certain measures should be applied, to comply with Rn regulation.

These two objectives correspond to asking different questions and imply different maps, in general. For visualizing, isopleth or choropleth maps are usually considered adequate, the latter for assigning hazard scores to geographical units such as municipalities. On the other hand, identification of areas where certain action applies, amounts to classification of areas according to the necessity of that action.

While sharing certain steps, these two type of maps entail different technical challenges. They basically origin in the high spatial variability of the Rn hazard, usually quantified by indoor Rn concentration in buildings, its probability to exceed a threshold, or the collective hazard (i.e. sum over affected persons). Due to the multitude and different nature of physical control factors, the scale of variability extends from small-scale local to continental.

Level maps (objective 1) raises the question of resolution (a) wanted by the stakeholders and (b) achievable with data; this acts back to data acquisition, i.e. Rn surveying. Resolution is related to the appearance of maps in terms of roughness and noise. For class maps (objective 2), the critical question is, in addition, reliability of defining an area as target of certain action, in terms of sensitivity and specificity (or likewise of 1^st and 2^nd kind error probabilities) of a decision.

In this presentation, we shall give real-world examples of the objectives and resulting Rn maps. Further we shall describe estimation methodology suited to create maps that comply with the quality targets addressed above.

How to cite: Bossew, P. and Petermann, E.: What do we want to learn from spatial data?  Asking the right questions – challenges in radon mapping, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-656, https://doi.org/10.5194/egusphere-egu21-656, 2021.