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 field measurements highlight very low values for ²²²Rn and higher values for ²²⁰Rn, suggesting a shallow source. Usually the measured ²²²Rn activity values are controlled by the radionuclide content in the soil, the temperature of the soil, the porosity of the soil, and the water content. We applied the Akerblom formula to calculate the radon at equilibrium with the activity concentration of the ²²⁶Ra on the collected soil samples, and the presence of ²²²Rn amounts higher than those naturally produced by the outcropping sediments is detected. These results demonstrate the presence of preferential gas pathways through the permafrost from a deep source. It is the first time that this type of study has been performed in Antarctica and can make a significant contribution to understanding the melting permafrost processes and its implications for the environment. 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., Tuccimei, P., Galli, G., Mazzini, A., Mazzoli, C., Tartarello, M. C., Florindo, F., Wilson, G., Mattia, M., Tositti, L., Morozzi, P., Benà, E., Bigi, S., Sassi, R., Anderson, J., and Ciotoli, G.: Study of the origin of soil 222Rn and 220Rn activities in Taylor Valley, Antarctica., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1604, https://doi.org/10.5194/egusphere-egu23-1604, 2023.

In poor-ventilated caves, indoor gases can seasonally reach concentrations much higher than normal atmospheric values, which may become a critical health risk. In this study, we investigate the cave atmosphere of the Rull cave in terms of assessing the cave air quality and understanding the cave dynamics. Rull cave is located in Vall d’Ebo (Alicante, southeast Spain). It is a karstic cave developed in massive Miocene conglomerates and Cretaceous limestones. Above the cave, the silty-silty loam soil profile has a thickness below 1 m. Inside the cave, calcite speleothems and cave sediments are widely present. The uranium and thorium concentrations are higher for the soil and cave sediments, and minor for host-rock, and lower for speleothems. Moreover, both soil and cave sediments are powder materials, and the emanation is enhanced in comparison to host-rock and speleothems, although their volume in the cave is higher than soil and cave sediments.

At the cave location and for a decade-long monitoring period (November 2012 - July 2022), the prevailing meteorological conditions in terms of temperature and relative humidity were 16.1 ºC and 69.9%, respectively, on daily average values. The average annual precipitation is 553 mm. In the cave interior and besides the presence of visitors (15000 visitors/year), mean temperature (16.2 °C) and relative humidity (97.6%) maintain stable values.

In an annual cycle, the cave presents two different gaseous stages (stagnation and ventilation). Maximum average values of CO₂ and ²²²Rn concentration (3966 ppm and 4185 Bq/m³) are reached within the stagnation stage (April/May to September). On the contrary, in the ventilation stage (October to March/April) the cave reaches the lowest concentrations in its inner atmosphere (478 ppm and 404 Bq/m³).

The spatial distribution of gases in the cave is dependent on the air density gradient between the cave and the outer atmosphere and controls the seasonal variations of both gases. The emanation of ²²²Rn from cave sediments, host-rock, and speleothems, contributes to increasing and maintaining a nearly ²²²Rn cave concentration during the stagnation stage. Dripping water degassing might also contribute to raising gas concentrations in caves. However, in Rull cave dripping waters are not abundant and thus the contribution of CO₂ or ²²²Rn degassing from seepage waters to increase cave gaseous concentration might be low.

The continuous monitoring of Rull cave provides substantial information about the environmental situation of the cave atmosphere in terms of air quality for visitors and cave guides. The maximum average concentrations of CO₂ and ²²²Rn in Rull cave and exposition times and doses comply with the recommendations of the legislation. Considering ²²²Rn, accurate planning of the cave guides and visitors during the stagnation stage is recommended to be less exposed to ionizing radiation due to the presence of radon gas.

How to cite: Benavente, D., Pla, C., Ruiz, M. C., Gil-Oncina, S., García-Martínez, N., Cañaveras, J. C., Cuezva, S., Fernández-Cortés, A., and Sánchez-Moral, S.: Radon dynamic and air quality in the Rull cave (southeast Spain), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4985, https://doi.org/10.5194/egusphere-egu23-4985, 2023.

Radon is a natural radioactive gas produced by the decay of its parent nuclide in bearing rocks and soils. Inhalation of radon gas poses a serious risk for human health and the World Health Organization stated the doubtless correlation between long exposure to radon gas and lung cancer. In this context, 76 indoor radon measurements in private and public buildings were performed in the Ciampino municipality. This study was carried out within the framework of the LIFE-Respire project. Indoor radon concentration was measured by using passive nuclear track detectors (CR-39) and analysed using RADOSYS system at INGV Radionuclides laboratory. Measurements were carried out in winter and summer seasons to assess the range of seasonal fluctuations, as recognised elsewhere. Results show a substantial increase of maximum indoor values in winter (up to 1575 Bq/m³) that are two times higher than those measured in the summer period (up to 764 Bq/m³). The annual mean and median values (283 and 203 Bq/m³, respectively) are both below the EU recommended limit of 300 Bq/m³.

Moreover, a questionnaire on radon risk perception was designed for the specific context of the LIFE-Respire project and distributed in a sample of residents and students in the Municipality of Ciampino to measure, among many other aspects, the salience of the hazard, knowledge of the hazard and of hazard mitigation strategies, perceived preparedness of and trust in officials, sources of received information and preferred methods of receiving information, and the level of interest in the project approach (including remediation measures).

How to cite: Sciarra, A., Pizzino, L., Ruggiero, L., Galli, G., Ricci, T., Ciotoli, G., Nave, R., Graziani, S., Beaubien, S. E., and Bigi, S.: Indoor Radon Measurements in public and private buildings in the Ciampino municipality and its risk perception assessment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1593, https://doi.org/10.5194/egusphere-egu23-1593, 2023.

The primary stone building material of ancient Rome from its initial settlement until recent times is constituted by the tuff; easy to cut, resistant to weathering, and an effective thermal insulator, with the disadvantage of a significant radionuclide content. An accurate monitoring of indoor radon in workplaces and residential dwellings constitutes a first step towards mitigating the exposure to the population. Since radon diffusion dynamics involves complex interactions among many environmental parameters on different time scales, a proper assessment of radon concentration variations can be better achieved by means of active monitoring approaches. We present here the results of continuous measurements conducted in 35 residential dwellings located in the municipality of Rome and its suburban area, and in a public building and workplace: the geophysical museum of Rocca di Papa.
The use of active devices makes it possible to discriminate between average indoor radon measured during the day, when workers and visitors are more likely present, and overnight, more relevant for the exposure of residents. Collecting long time series of radon concentration enables us to identify fluctuations over seasonal scales, with radon generally decreasing in the warm season. The simultaneous tracking of different floors of the same building shows an inversion of the dynamics of gas convection during the warm season compared to the cold one, likely depending on the chimney effect. Monitoring different rooms of the same dwelling reveals that values of gas concentration may greatly differ, indicating the importance of ventilation and/or heating system. Considering several dwellings allows us to question the general belief of a constantly higher exposure of the lowest floors to the indoor radon risk with respect to elevated floors (radon would enter mainly through foundation walls). Finally, the clustering of houses with high indoor radon levels in the historic center of Rome indicates the influence of geogenic radon and of building characteristics like age, typology, and construction materials.
With so many endogenous and exogenous factors affecting the healthiness of indoor environments in terms of radon concentration, a proper assessment of health hazard requires the knowledge of the dynamics of the gas generation and transport inside the buildings, and of its temporal fluctuations; our analysis provides the instruments to disclose the characteristics of such dynamics, with the final goal to select the most suitable preventive measures to reduce radon exposure. 

How to cite: Soldati, G., Ciaccio, M. G., Piersanti, A., Cannelli, V., and Galli, G.: Radon risk mitigation in urban environments: experiences from active monitoring, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12456, https://doi.org/10.5194/egusphere-egu23-12456, 2023.

Radon (²²²Rn) is a radioactive gas considered the major source of ionizing radiation exposure for the population and several epidemiological studies provided evidence of its detrimental effects on human health. As a consequence, the World Health Organization classified this gas as the second cause of lung cancer after cigarettes smoking. A significant fraction of lung cancer can be attributed to the indoor Rn exposure, i.e. houses and workplace. In particular, Indoor Radon Concentration (IRC) is the product of the Geogenic Radon Potential (GRP), conceptualised as the contribution of Rn released by the Earth. Therefore, in the characterisation of the potential risk over an area is fundamental considering the geological constraints under the dwellings, the building styles and living habits. In Europe, the Basic Safety Standards Directive 2013/59/EURATOM aims to reduce the human exposure to Rn in houses and workplace, on the one hand fixing some reference values, on the other hand requiring to the European states to delineate the Radon Priority Areas (RPA), i.e. that areas where IRC exceed the European Directive reference value. In particular, mapping the GRP as an indicator of the Rn related hazard is fundamental for: (i) delineate the RPAs through the quantification of geogenic Rn, that can potentially influx within buildings; (ii) understand how GRP can affect the vulnerability over an area thus contributing to the Rn risk. In this study, we focused on mapping the GRP of a specific study area located in the Pusteria Valley (Bolzano province, eastern Italy). This area is well-known from a geological and structural point of view and it is characterised by a wide non-seismically active fault zone showing a very high gas permeability.  In particular, we have applied a machine learning technique (i.e. Forest Regression), to construct a high resolution (50 m*50 m) GRP map of the study area considering several proxy variables related to the Rn sources (e.g., radionuclide content in rocks), to the Tectonically Enhanced Radon (TER) quantity and to the exhalation process towards the atmosphere. Furthermore, we have assessed the vulnerability of the area by introducing the location of inhabited areas to provide a preliminary map of RPAs. Results show that dwellings characterised by high vulnerability are located in the area with the highest GRP. This work represents the first attempt in Italy to define the RPAs.

How to cite: Benà, E., Ciotoli, G., Ruggiero, L., Petermann, E., Bossew, P., Mazzoli, C., Verdi, L., and Sassi, R.: Mapping the Geogenic Radon Potential as a first step to define the Radon Priority Areas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7476, https://doi.org/10.5194/egusphere-egu23-7476, 2023.

Accurate knowledge of indoor radon exposure is vital information for assessing radon-induced health effects, identifying radon prone areas or estimating the number of people affected by the exceedance of a specific radon concentration in a given area.

Large-scale measurement campaigns are usually the tool of choice for determining regional or national indoor radon exposure. These campaigns need to be representative in terms of all relevant factors governing indoor radon exposure (e.g., geogenic radon availability, distribution of people across floor levels, building types) for providing an unbiased estimate. In practice, creating a fully representative sample of the population is hardly achievable due to the multitude of relevant factors which cannot be fully controlled by sampling design. Further, estimating indoor radon exposure at a high spatial resolution (district or municipality scale) requires a large number of measurements which increases the financial and logistic effort dramatically. Therefore, predictive models are widely applied as a complementary tool for exposure assessment by utilizing available information on the relevant variables that determine indoor radon. However, these models are usually only able to explain a certain amount of the observed variability due to the absence of some relevant information (building-specific data on air tightness, ventilation rates etc.). As a consequence, model-based assessments tend to underestimate the true variability of indoor radon. 

In this study, we present a probabilistic approach that overcomes this shortcoming and intends to give a more realistic estimate of the true indoor radon distribution at several spatial resolutions. Our approach consists of the following steps:

1) fitting a random forest model utilizing 12 predictors to ~14,000 full-year indoor radon measurements in residential buildings in Germany;

2) predicting a range of quantiles of the expected indoor radon distribution for each floor level of each German residential building;

3) fitting a lognormal distribution to the estimated quantile data to approximate the building and floor level specific probability density function (PDF);

4) random sampling from this PDF with a sample size proportional to the population distribution;

5) aggregating results on several spatial scales. 

The benefits of this approach are 1) to allow an accurate exposure assessment even if surveys were not fully representative concerning the main controlling factors by utilizing high-resolution information on the spatial distribution of these factors via predictive models. 2) with a given amount of measurements, exposure distribution can be estimated at a much higher spatial resolution compared to basic aggregate statistics.  

How to cite: Petermann, E., Bossew, P., Suhr, N., and Hoffmann, B.: Estimating national indoor radon exposure at a high spatial resolution – improvements by a machine learning based probabilistic approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6423, https://doi.org/10.5194/egusphere-egu23-6423, 2023.

Radon (²²²Rn) is a radioactive gas of the uranium-radium decay chain and occurs naturally in soil air. Primarily by diffusion, radon migrates to the surface and can accumulate in buildings, where it is harmful to human health because of its radioactivity. To tackle this particular health hazard, radon mitigation was recently introduced into national law. Among other things, the law demanded the designation of radon priority areas by the end of 2020. These areas are defined as administrative areas with a large proportion of land affected by high radon concentrations inside buildings. In the state of Baden-Wuerttemberg these areas were selected at municipality level based on a 10x10 km national map of geogenic radon potential (GRP) provided by the German Federal Office for Radiation Protection (BfS) accompanied by a state-specific map of uranium concentrations. With the prospect of future designations, this work aims at replacing the national GRP map used in 2020 by a more sophisticated state-specific version. In doing so, we improve spatial resolution, focus on covariates that only represent the state-relevant features of geology and soil and move away from a kriging-based mapping approach towards machine learning.

This ongoing study is currently based on 580 radon measurements in soil gas at 1 m depth from different surveys spread irregularly over Baden-Wuerttemberg in southeast Germany. This point dataset is combined with a set of covariates from factors that influence radon concentrations such as soil parameters, geology, relief, climate and a map of uranium concentrations created from over 4000 heavy metal measurements. Modelling is done using a random forest (RF) approach as implemented in the R packages ranger and mlr3. Preliminary results indicate that the new GRP map with a spatial resolution of 250 m is highly useful in classifying communities as vulnerable areas, which were previously not called due to uncertain underlying data. In addition, model output confirms up to 80 % of already identified radon priority areas.

Machine learning algorithms such as RF with its precise learning progressions can be used to create GRP maps at regional scale at high resolution. Besides further improving the RF model, next steps will focus on explainable machine learning, i.e. to produce features that support policy makers in finding acceptance by the public in sight of a sensitive topic. This includes variable importance plots, uncertainty measures and maps representing areas of applicability. The latter will also be used to help guiding the ongoing radon measurement programme of Baden-Wuerttemberg, which currently comprises approximately 100 new locations per year.

How to cite: Kölbl, A. and Blaschek, M.: Identifying radon priority areas by mapping geogenic radon potential of soils in Baden-Wuerttemberg (Germany) using machine learning algorithms, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7114, https://doi.org/10.5194/egusphere-egu23-7114, 2023.

Radiometric surveys are used to investigate different scientific and practical issues in Earth’s science studies, ranging from basic geophysics to mineral exploration and natural radiation monitoring. The latter is a topic of growing interest. ²³⁸U, ²³²Th and ⁴⁰K, which occur in variable quantities in the Earth’s crust rocks, are the primary cause of natural, potentially hazardous, gamma-ray exposure. Another important environmental aspect of natural radioactivity regards the effects of  ²²²Rn resulting from the ²³⁸U decay. This paper proposes an experimental approach to investigate the relationship between uranium and indoor radon concentration. We combined ground gamma-spectrometry with alpha-track detector measurements. We tested this methodology in the Alpine geological units of western Liguria (Italy). This area is densely populated and characterised by various lithotypes, spanning from sedimentary to metasedimentary and metavolcanic rocks. The latter are known for their abundance of natural radionuclides. Due to the width of the surveyed area (408 km²), we carried out about 300 gamma-ray determinations on the more extensive geological formations, with particular reference to those hosting the main residential areas, together with about 130 measurements of indoor radon. By considering the nineteenth percentile of the recorded specific activity, the largest value of ²³⁸U was 93 Bq/kg. It was found in the more acid metamorphic rocks (metarhyolites and porphyric schists) where we carried out also the largest number of gamma-ray spectrometry measurements. In the metasedimentary rocks, the largest activities of ²³⁸U were observed in quartzschists and micaschists (89 Bq/kg). In the sedimentary lithotypes, specific activities are generally lower than 40 Bq/kg. We found that the number of buildings with ²²²Rn exceeding 200 Bq/m³ increases where the specific activity of ²³⁸U is larger. About 40% of dwellings and public buildings with ²²²Rn>200 Bq/m³ occurs in the lithotypes (metarhyolites and micaschists) with ²³⁸U>60 Bq/kg. A comparison between the indoor ²²²Rn concentration and the ²³⁸U specific activity measured on the same geological formation showed a linear correlation. Using the records of ²³⁸U specific activity, we developed a map of the expected radon concentration on the different geological formations of the surveyed area. Despite the limitations and uncertainties, mainly related to the uneven data coverage and the complex interaction between the building and the bedrock, the proposed approach showed that gamma-ray spectrometry can be a valuable tool to identify areas of more significant potential risk of radon emanation.

How to cite: Bonorino, L., Beccaris, G., Bisi, P., Chiozzi, P., Cogorno, A., Filippi, E., Narizzano, R., Prandi, S., and Verdoya, M.: An approach to relate uranium to indoor radon: a case study from the western Ligurian Alps (Italy), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12769, https://doi.org/10.5194/egusphere-egu23-12769, 2023.