One of the largest natural thermal lakes in the world, Lake Hévíz is located in the southwestern part of the Transdanubian Range’s karst system (Hungary). It is fed by springs with different temperatures, which are located in a cave beneath the lake. The mixing of cold and hot waters generates the lake’s sulphuric therapeutic water, and it is responsible for the cave formation at the bottom, resulting in the lake's unique ecosystem. The presented research aimed at the comprehensive geochemical characterization of waters in the wider surroundings of the lake (lake water, springs, observation, drinking water, and thermal water wells). Investigating the geochemical characteristics of water took on a novel perspective through the innovative application of radionuclides as natural tracers. Within the framework of this investigation, we utilized uranium, radium, and radon isotopes to identify the mixing of fluids and infer the mixing end members in the Hévíz karst system. Alpha spectrometry was applied on selectively adsorbing Nucfilm discs as an inventive approach to measure uranium and radium isotopes. Moreover, stable isotopic ratios of hydrogen and oxygen (δ²H and δ¹⁸O) were determined to supplement the information on waters with different origins. Hydrochemical water analysis for measuring the concentration of major ions and trace elements was carried out using ICP-MS, ion chromatography, and UV-Vis spectrophotometry. The inferred fluid end members and their compositions are anticipated to provide insightful information on the hydrogeological functioning of the Lake Hévíz karst system, which is indispensable in sustainable water resource management and understanding climate change's impact.

Keywords: Thermal lake; Hydrogeochemical characteristics; Mixing fluids; Radionuclides; Stable isotopes; ICP-MS, Nucfilm, Alpha spectroscopy

How to cite: Bidar Kahnamuei, S., Hegedűs-Csondor, K., Baják, P., Horváth, Á., Szieberth, D., Czuppon, G., Vargha, M., Izsák, B., and Erőss, A.: Identifying Mixing Components by Natural Tracers in the Lake Hévíz System, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-888, https://doi.org/10.5194/egusphere-egu24-888, 2024.

In Hungary, the drinking water supply relies upon groundwater resources of up to 98%. As a drinking water resource, groundwater must meet strict quality requirements in order to minimise any health effects arising from daily water consumption. Water-rock interactions enrich groundwater not only with essential elements (e.g. Ca, Mg) but also with undesired substances such as heavy metals or radioactive elements. In the last few years, a thorough drinking water quality monitoring campaign was carried out in Hungary, revealing that some parts of the country are characterised by relatively high uranium concentrations. The causes of these elevated activities have not been properly investigated, yet. However, understanding the controls of the release and mobility of uranium is critical in proper groundwater management.

Baják et al (2022) developed a one-dimensional (1-D) geochemical model using the code PHREEQC (Parkhurst and Appelo, 2013) to examine the processes that determine the fate of uranium in the siliciclastic Miocene-Quaternary aquifer system near Velence Hills, some 50 km off Budapest. Here, the geological build-up (granitic rocks on the surface) favours the high uranium content in groundwater, which is characterised by oxidising conditions. The 1-D model included redox-controlled kinetic reactions as well as other potential uranium-controlling processes (e.g., surface complexation). The results suggested that uranium distribution is sensitive to redox changes in the aquifer and its mobility in groundwater especially depends on the residence time of water compared to the reaction times controlling the consumption of oxidising species.

This study introduces a two-dimensional multicomponent reactive transport model developed using the PHT3D code (Prommer et al., 2003), which is a coupling between MODFLOW and PHREEQC. The model builds on and extends the capability of the 1-D model to simulate uranium mobility across the multiple flow paths of the aquifer systems. The model calibration accounts for 30 groundwater samples collected from drinking water wells in the study area. Physico-chemical parameters (temperature, pH, specific electric conductivity, redox potential) were measured on-site, and the samples were analysed for natural tracers (δ¹⁶O, δ²H, ²³⁴U, ²³⁸U, ²²⁶Ra) to gain further insight into the geochemical processes of the aquifer system.

This research was supported by the ÚNKP-23-4 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund and was supported by the János Bolyai Research Scholarship of the Hungarian Academy of Sciences. The research is part of a project which was funded by the National Multidisciplinary Laboratory for Climate Change, RRF-2.3.1-21-2022-00014.

References:

Baják, P., Csondor, K., Pedretti, D., Muniruzzaman, M., Surbeck, H., Izsák, B., Vargha, M., Horváth, Á., Pándics, T., Erőss, A., 2022. Refining the conceptual model for radionuclide mobility in groundwater in the vicinity of a Hungarian granitic complex using geochemical modeling. Applied Geochemistry 137, 105201.

Parkhurst, D.L., Appelo, C.A.J., 2013. Description of Input and Examples for PHREEQC Version 3—A Computer Program for Speciation, Batch-Reaction, One-Dimensional Transport, and Inverse Geochemical Calculations. (USGS Technical No. 6(A)43). U.S. Geological Survey, Denver, CO, USA.

Prommer H, Barry, D.A., Zheng, C. (2003). MODFLOW/MT3DMS based reactive multi-component transport modeling. Ground Water, 41(2).

How to cite: Baják, P., Pedretti, D., Csepregi, A., Muniruzzaman, M., Hegedűs-Csondor, K., and Erőss, A.: Preliminary results of two-dimensional multicomponent reactive transport modelling to understand the controlling factors on uranium mobility in a siliciclastic aquifer in Hungary, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12663, https://doi.org/10.5194/egusphere-egu24-12663, 2024.

Radon (²²²Rn) is a radioactive gas considered the major source of ionizing radiation exposure for the population and represents a significant health risk when it accumulates indoor environments. In Europe the regulation has been implemented in order to address the issue of indoor radon exposure, including pose national reference levels and the identification of the so-called Radon Priority Areas (RPAs). Although the European directive states that RPAs are defined as those areas where the annual average Indoor Radon Concentrations in a significant number of dwellings is expected to exceed the reference level the concept and interpretation of “significant number of buildings” in the European Directive remained unclear. According to this idea, radon is classified as an anthropogenic hazard since it has a strong correlation with IRC. However, indoor radon levels can vary significantly at the municipal level also among neighbouring dwellings, mostly due to differences in building characteristics and inhabitants’ habits. Since in this way the radon natural origin may be bypassed, many authors (mostly geologists) propose to use the Geogenic Radon Potential (GRP) as a hazard indicator. The GRP represents the amount of radon that can potentially influx within buildings from geogenic sources. Being the radon hazard and risk concepts still debated, in the last year, researchers proposed a clear transition from the radon hazard to the more comprehensive radon risk concept proposing that mapping this geo-hazard (GRP) is a fundamental step to define the collective radon risk exposure. The Collective Risk Areas (CRAs) are composed by many possible little Individual Risk Areas (IRAs). Considering that the radiation protection aimed to reduce the detriment, radon abatement policies have to take care of these CRAs not forgetting areas with high individual risk in order to protect individuals from high exposure. On the one hand the collective risk areas have proposed as geological-based risk areas; on the other hand, the individual risk areas are strictly linked to the Indoor Radon Concentration (IRC) and may be assimilated to the “classical” RPAs concept. Considering the absence of an unambiguous methodology at the European scale to define the RPAs and the proposed CRAs mapping as the first step to define the IRAs (“classical” RPA), with this work we aimed to lay the foundation to create a definitive methodology for the individual risk-based RAPs mapping considering, first of all, the number of people involved. The test area chosen for this study is the Bolzano province (Italy) due to the high availability of potential predictors variables and a detailed IRC survey campaign on the entire provincial territory. Starting from this we proposed the first IRAs map (i.e., the first individual risk-based RPAs definition) using a set of Machine Learning techniques allowing to connect and validate the geo-hazard with real IRC measured in the province, with the aim to predict both the collective risk and the possible individual detriment as required by the European regulation.

How to cite: Benà, E., Ciotoli, G., Bossew, P., Petermann, E., Verdi, L., Mazzoli, C., and Sassi, R.: From the collective to the individual radon risk exposure: an insight in the current European regulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5787, https://doi.org/10.5194/egusphere-egu24-5787, 2024.

The urbanized area of Rome is largely built over volcanic deposits, characterized by  a significant radionuclides content and radon emanation potential.  A first step towards the mitigation of the indoor radon exposure is the accurate monitoring of workplaces and residential dwellings. Due to the complex interactions among many environmental parameters on different time scales, a proper assessment of radon diffusion dynamics and concentration variations can be better achieved by means of active monitoring approaches. We present here the results of one year of continuous measurements conducted in 6 premises (5 apartments and a basement) at different floors of the same building in the Esquilino district, in the historical center of Rome. The simultaneous tracking of different floors should cancel the influence of geogenic radon and of building characteristics like age, typology, and construction materials, and reveal the characteristics of the gas emanation and transport inside the buildings, and of its temporal fluctuations, with the final goal to select the most suitable preventive measures to reduce radon exposure. Conducting the experiment in the Roman urban contest, we cannot ignore the specificity of the retrieved data, affected not only by endogenous factors like heating and ventilation of the apartments, but also by exogenous factors like the urban heat islands effect.

How to cite: soldati, G., ciaccio, M. G., piersanti, A., cannelli, V., and galli, G.: Multi-level continuous monitoring of residential radon in the urban contest of Rome, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19881, https://doi.org/10.5194/egusphere-egu24-19881, 2024.

Radon (²²²Rn) is a naturally occurring gas that represents a health threat due to its causal relationship with lung cancer. Despite its potential health impacts, several regions have not conducted studies, mainly due to data scarcity and/or economic constraints. This study aims to bridge the baseline information gap by building an interactive dashboard that uses inferential statistical methods to estimate indoor radon concentration’s (IRC) spatial distribution for a target area. We demonstrate the functionality of the dashboard by modelling IRC in the city of Bogotá, Colombia, using 30 in situ measurements. IRC measured were the highest reported in the country, with a geometric mean of 91 ±14 Bq/m³ and a maximum concentration of 407 Bq/m³. In 57 % of the residences RC exceeded the WHO's recommendation of 100 Bq/m³. A prediction map for houses registered in Bogotá’s cadastre was built in the dashboard by using a log-linear regression model fitted with the in-situ measurements, together with meteorological, geologic, and building specific variables. The model showed a cross-validation Root Mean Squared Error of 56.5 Bq/m³. Furthermore, the model showed that the age of the house presented a statistically significant positive association with RC. According to the model, IRC measured in houses built before 1980 present a statistically significant increase of 72 % compared to those built after 1980 (p-value = 0.045). The prediction map exhibited higher IRC in older buildings most likely related to cracks in the structure that could enhance gas migration in older houses. This study highlights the importance of expanding ²²²Rn studies in countries with a lack of baseline values and provides a cost-effective alternative that could help deal with the scarcity of IRC data and get a better understanding of place-specific variables that affect IRC spatial distribution.

How to cite: Dominguez Duran, M., Sandoval Garzón, M. A., and Huguet, C.: Indoor 222-Rn Modeling in Data-Scarce Regions: An Interactive Dashboard Approach for Bogotá, Colombia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8408, https://doi.org/10.5194/egusphere-egu24-8408, 2024.

This study, conducted about 30km south of Frankfurt in the Northern Upper Rhine Graben, focuses on deepening the understanding of Radon concentrations in soil air. The selected area, where neotectonic activity was proven in an accompanying project, provides an ideal setting for investigating Radon variability, particularly its potential correlation with fault zones in unconsolidated rocks or sedimentary basins. Understanding the factors influencing Radon levels in the environment is a complex task, as they are affected by a multitude of variables. Our work aims to decipher these influences and, if possible, quantitatively analyse the contributions of each variable. By doing so, we hope to gain a clearer understanding of how different environmental factors interact to determine Radon levels.

A central element of our research is the use of Random Forest models, chosen to handle our multidimensional dataset. This dataset includes a variety of parameters such as Radon measurements, nuclide content, soil grain sizes, weather data, and the distance to fault zones. Random Forest models are particularly effective for this type of complex data because they can analyse many different factors at once and uncover hidden patterns.

Contrary to initial hypotheses, our findings indicate that in unconsolidated rocks and sedimentary basins, the grain size of soil is the most influential factor in determining soil air Radon levels, closely followed by soil moisture. These results challenge the previously held belief that fault zones are the primary influencing factors on Radon concentrations in these geological settings.

How to cite: Mair, J., Petermann, E., Lehné, R., and Henk, A.: Deciphering Radon Variability in the Northern Upper Rhine Graben: An Analysis Using Passive and Active Detection with Random Forest Modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16925, https://doi.org/10.5194/egusphere-egu24-16925, 2024.

Given its unique properties as a radioactive chemically inert gas, radon can act as a valuable atmospheric tracer, for evaluating the performance of atmospheric transport models to calculate the sources of trace gases to the atmosphere. A radon flux map is the scientific starting point for simulating atmospheric radon concentrations using atmospheric transport models. As such, it is important to assess the available high resolution radon flux maps to ensure that simulated concentrations can be accurately interpreted. The spatial fluxes of radon primarily depend on soil and rock types, while temporal variations are influenced by soil moisture content.

The recent advancements in generating two high-resolution radon flux maps for Europe using two different soil moisture reanalysis, GLDAS Noah and the ERA5 maps¹, have significantly enhanced our understanding of radon flux dynamics. Yet, the radon flux values diverge notably between these two maps and sometimes these variations can be substantial, with differences as large as the absolute radon flux itself.

In our work, two available versions of European radon flux maps are coupled with two Lagranian particle dispersion models – the Met Office’s Numerical Atmospheric Modelling Environment (NAME) and the FLEXPART model – are used to simulate radon concentrations measured at four tall tower sites in the United Kingdom: Heathfield, Ridge Hill, Tacolneston and Weybourne. We calculate the differences between the modelled radon concentrations to the observed radon concentrations at these sites and use this to investigate the sensitivity of two radon flux maps: GLDAS Noah and ERA5.

References: ¹2022: https://doi.org/10.18160/2ST9-3NAD

How to cite: Howes, A., Kikaj, D., Chung, E., Karstens, U., Manning, A., Henne, S., Wenger, A., Foster, G., O'Doherty, S., Rennick, C., and Arnold, T.: Investigating the sensitivity of flux maps in simulating radon concentrations at greenhouse gas monitoring sites, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17300, https://doi.org/10.5194/egusphere-egu24-17300, 2024.

Ciampino area has been the subject, from 1999 onwards, to reiterated geochemical surveys on soil-gas, spring waters and groundwater, commissioned by the municipality to INGV (National Institute of Geophysics and Volcanology). Indeed, this area is affected by huge CO₂ emissions of volcanic origin and high levels of indoor radon. Both gases can constitute a big concern for local population known as Natural Gas Hazard (NGH). Accordingly, the distribution of the two gases in groundwater, soils and indoor buildings must be assessed in order to define sectors of the territory more exposed to NGH.
Interest in the Natural Gas Hazard arose mainly starting from November 1995, when several homes, basements and wells were affected by widespread exhalations, to the point of danger to human health.
The most area affected is characterized by abundant and concentrated gas leaks which caused the death of 29 cattle and some sheep in September 1999 and March 2000, until December 2000 when a paroxysmal episode caused the death of a man.
The main activities carried out in the last 25 years have concerned:
-    sampling of water sites (about 100 natural springs, public and private wells), measuring chemical-physical parameters, CO₂ and ²²²Rn contents;
-    monthly indoor radon measurements (around 500/year) in 14 selected sites (both private homes and workplaces, including schools);
-    measurements of radon in soils (about 300) to identify the areas with the greatest degassing and the possible relationship with existing tectonic structures;
-    continuous indoor radon measurements in a selected home;
-    spot measurements in groundwater and intervention in the event of reports from the municipality and/or private citizens of emergency situations resulting from gaseous emanations falling in areas of the municipal territory of Ciampino.
The data obtained include measurements of flux and concentration of soil gases, distribution of pCO₂ and radon in groundwater, radionuclide content in soils from different geological units, indoor radon measurements.
All this data has allowed us to define the sectors at greatest risk, by identification and delimitation of NGH risk areas. Dissemination and information activities on the NGH were carried out through public meetings, seminars and the drafting of brochures. Also training activities for the staff of the Civil Protection and Environment Offices of the Municipality were performed.
The experience gained has allowed the participation of INGV in a European project Life Respire for the monitoring and remediation of the radon problem.
Based on the distribution of the different samples collected: soil gas, terrestrial gamma dose rate and rock/soil samples by radionuclide content, we were able to provide the local authorities the map of the geogenic potential of radon for the whole municipal territory.

How to cite: Sciarra, A., Pizzino, L., Galli, G., Cinti, D., Ciotoli, G., and Bigi, S.: INGV experience on radon monitoring in the Ciampino Municipality (Rome, Italy): a link between research and territory, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17369, https://doi.org/10.5194/egusphere-egu24-17369, 2024.

The research aimed to analyse variations in soil gas radon concentrations and geogenic radon potential in areas of typical building plots located in regions known for high and low geogenic radon potential. The study was designated to address the following questions:

• Are spatial variations in soil gas radon concentrations and radon potential statistically important in the area of a typical building plot? Are these variations similar in regions known for high and low radon potential?
• How many measurement points should be proposed to properly evaluate geogenic radon potential and radon index on the building plot area?
• Can an in-situ gamma spectrometric survey, combined with soil properties, be useful in the defining radon index at the area of the building plot?
• Are seasonal variations of soil gas radon concentration significant at a depth of 0.8 m?  If so, which season is the most appropriate to evaluate geogenic radon potential?

The research was conducted in two counties: Wrocław and Dzierżoniów located in the Lower Silesian Voivodeship in the southwest part of Poland. Dzierżoniów County is among the counties listed in the Regulation of 18 June 2020 of the Minister of Health where the average radon concentration in a significant number of buildings may exceed the reference level of 300 Bq m⁻³. In both regions, three building plots, each of an area of 300 m² (which is the size of a typical building plot in an urban area in Poland) were identified. At each building plot, five measurement points were designated -  at the four corners and in the middle of each plot. The research at each measurement point included the following procedures:

• Soil gas radon concentration measurements at the depth of 0.8 m using solid nuclear track detectors have been performed. The detectors were replaced at the beginning of each season starting from summer 2023.
• The radionuclides contents in the soil were measured in situ using the gamma-ray spectrometer Exploranium RS-230.
• The ambient gamma dose rate was measured by the radiometer RK-100
• Various soil properties including grain size, permeability, and filtration coefficient were determined.

Additionally, at each building plot, the instantaneous radon concentration and soil permeability measurements were performed using Lucas cells and RADON-JOK.

The preliminary research results indicate that in Dzierżoniów County uranium contents were in the range from 1.6 ppm to 3.3 ppm and thorium from 5.4 ppm to 8.2 ppm, whereas in Wrocław County uranium contents were in the range from 1.6 ppm to 2.5 ppm and thorium from 4.3 ppm to 7.4 ppm. The instantaneous survey of radon concentration revealed that in Dzierżoniów County soil gas radon concentration varied from 10.338 kBq m^-3 to 31,050 kBq m^-3 and soil permeability from 1*10^-12 m² to 1*10 ^-13 m², whereas in Wrocław county the soil radon concentration varied from 0.102 to 0.266 kBq m^-3 and soil permeability form very low (impossible to measure by used equipment) to 2*10^-13m².

Research project supported by program „Excellence initiative – research university” for years 2020-2026 for University of Wrocław

How to cite: Tchorz-Trzeciakiewicz, D.: Variations of soil gas radon concentrations in a typical building plot area - preliminary results, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3352, https://doi.org/10.5194/egusphere-egu24-3352, 2024.

Radon (²²²Rn) is one of the most common naturally occurring radioactive elements and is particularly interesting to environmental issues, for it is considered a carcinogenic gas. It is a decay product of ²³⁸U, contained in most rocks and soils, and can easily escape from the ground to accumulate in closed spaces where it may become dangerous. The knowledge of its potential is vital to urban development plans and to protect people from potential hazards. We recently conducted monitoring campaigns in Liguria (NW Italy) to investigate the relations between the observed indoor radon concentrations and the geo-lithological background. We focused on the geological units of the Western Alps, characterized by various lithotypes, ranging from sedimentary to metasedimentary and metavolcanic rocks. The natural gamma radiation was measured on outcrops. Spectrometric measurements indicated that metamorphic acid rocks have the highest specific activity values of ²³⁸U (75-85 Bq/kg). In metasedimentary rocks, quartz and mica schists show the highest concentration of ²³⁸U, with an average specific activity of 56 Bq/kg. Sedimentary rock types are characterized by average specific activities < 40 Bq/kg., The dosimetric indoor surveys highlighted that about 40% of the investigated public and private buildings show indoor radon values above 200 Bq/m³. These preliminary campaigns revealed a relationship between the uranium content of the bedrock and the indoor radon. The correlation can be used to predict the geogenic radon potential based on a geological background when dosimetric data are few or scattered. In this paper, we refined our early analysis by integrating the dataset with further spectrometric and indoor dosimetric records, which were also coupled with soil radon measurements. The radon concentration in soil was investigated focusing on the sites where the previous monitoring campaigns showed high indoor radon concentrations. Soil radon was recorded at depths between 50 and 80 cm, where radon diffusion from the ground to the buildings very likely occurs. Soil radon concentrations substantially agree with spectrometric measurements. The largest concentration of ²²²Rn was found in the soils on more acid metamorphic rocks (porphyroid and porphyric shists) with values of about 100 kBq/m³. The lowest values about (20 kBq/m³) were recorded in soils occurring in sedimentary rocks. Despite the limitations and uncertainties, mainly related to the uneven data coverage and the complex interaction between the building and the bedrock, the combined techniques can identify areas of potentially high indoor radon concentrations.

How to cite: Bonorino, L., Beccaris, G., Bisi, P., Chiozzi, P., Cogorno, A., Filippi, E., Narizzano, R., Prandi, S., and Verdoya, M.: A combined approach for the correlation between indoor radon and geological background: application in the western Ligurian Alps (Italy), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9434, https://doi.org/10.5194/egusphere-egu24-9434, 2024.

Naturally occurring radon-222 (Rn) is a widespread indoor air pollutant, posing a potential health risk for humans, particularly elevating the risk of lung cancer in indoor living and working spaces. One highly promising solution for existing buildings, requiring relatively minimal technical effort to reduce indoor radon, is the installation of a ventilation system.

As a proof of concept, a series of different ventilation experiments, utilising a decentralised ventilation system with heat recovery (inVENTer GmbH, Germany) were performed in an unoccupied ground-floor flat in Bad Schlema (Germany).

The flat was divided into three individually controllable ventilation zones using strategically positioned ventilation devices, controlled by a novel real-time measurement system for indoor radon activity concentration [Rn] (Smart Radon Sensors by SARAD GmbH, Germany) in each room. This innovative approach to eliminate indoor radon by employing [Rn] as a control parameter enabled automated switching between different ventilation modes or the option to deactivate the system entirely.

Over three years, the different ventilation experiments successfully reduced elevated indoor radon levels from up to 7000 Bq/m³ to 300 Bq/m³ and below. The effectiveness varied based on factors such as the initial room-specific radon levels before each experiment, the performance level of the fans and meteorological parameters.

Furthermore, we developed a true-to-scale three-dimensional Computational Fluid Dynamics (CFD) model based on the actual flat, enabling the quantitative interpretation of various ventilation experiments within a CFD environment. The CFD model utilised a stationary k-ε turbulent flow model to simulate ventilation-induced airflow inside the flat and was coupled with a transient transport model for radon simulation.

For the development of the CFD model, the "Cross-Ventilation" experiment was chosen. This experiment successfully achieved a room-specific reduction of indoor radon levels from approximately 3,000 Bq/m³ to about 300 Bq/m³. To precisely capture the impact of ventilation on indoor radon, the initial radon values for each room were utilised as initial conditions for the transient radon transport model.

Base case results showed an overestimation by the model in radon level reduction due to ventilation. Parameter adjustments of the inflowing radon and the airflow velocity at the inlet resulted in good agreement between experimental values and the CFD model's outcome.

In summary, this study highlights CFD modeling as a versatile tool for evaluating and optimising ventilation systems, offering valuable insights into the mechanism of managing the air quality in complex real-world indoor environments with elevated radon levels.

How to cite: Altendorf, D., Wienkenjohann, H., Berger, F., Dehnert, J., Duzynski, M., Grünewald, H., Naumov, D., Trabitzsch, R., and Weiß, H.: Cross-Ventilation Strategies for Efficient Indoor Radon Reduction: Experimental Data and CFD Simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12397, https://doi.org/10.5194/egusphere-egu24-12397, 2024.

Fumaroles spread out several elements to the atmosphere and may include radon that contributes to environmental radioactivity. The long-lasting vigorous gaseous emissions of the Campi Flegrei volcanic caldera, i.e., Solfatara and Pisciarelli, occur in densely inhabited areas of Naples where the population may be exposed to ionizing radiation from 222-radon. In 2021, we started a study on radon levels from the Solfatara and Pisciarelli fumaroles by using the RAD7 commercial detector, one of the most widely used instruments for measuring ²²²Rn, either dissolved in water or in soil gas. However, the local high H₂S levels and hot temperatures did not allow direct measurements of Rn, resulting in the instrumentation (RAD7) damage. Thus, we developed a proper technique for sampling and measuring radon gas from fumarolic gases in such a “critical” areas to overcome the instrumental issue.

At fumarole sites i.e., Bocca Nuova and Bocca Grande within the Solfatara crater, and Pisciarelli, the gas was periodically sampled in Tedlar® bag of 1 or 3 liters in order to have the possibility to repeat the measurements two or three times to verify the accuracy of the data.

In laboratory, at first, H₂S traps were prepared by filling silicone tubes with lead acetate powder, bordered, at both ends, by hydrophilic cotton and closed. Then the fumarole gas was transferred from the Tedlar® bag into a glass tube. Finally, radon gas was measured via a closed loop by using the RAD7. Rn printouts obtained from RAD7 were corrected for the time lag between sampling and measurement. RAD7 and charcoal canister measurements were compared to check the obtained results.

Preliminary results, published in Iovine et al. (2023), demonstrate that the methodology utilized enables the analysis of Rn concentrations even in H₂S-bearing gases, discharged from the fumaroles of the Campi Flegrei volcano and, most importantly, without instrumental issues. Fumaroles sampled and analyzed over time according to the methodology adopted, may be suitable for environmental radioactivity assessment and volcanic monitoring purposes as well.

Iovine RS, Avino R, Minopoli C, Cuoco E, Caliro S, Galli G, Piochi M. (2023). A procedure to use the RAD7 detector for measuring ²²²Rn in soil gases exceeding instrumental limits: an application to chemically aggressive fumaroles of the Campi Flegrei area. Rapp. Tec. INGV, 473: 1­18, https://doi.org/10.13127/rpt/473.

How to cite: Iovine, R. S., Minopoli, C., Avino, R., Caliro, S., Galli, G., and Piochi, M.: Determination of 222Radon (222Rn) from the hot and acidic fumaroles gases to the atmosphere of the highly populated Campi Flegrei caldera (Naples, Southern Italy) by using a RAD7 detector: a procedure overcoming instrumental limits, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17908, https://doi.org/10.5194/egusphere-egu24-17908, 2024.

The Radon deficit technique is a promising screening method for identifying and mapping potential subsurface organic pollution hotspots and thus, for the optimization of intrusive characterization campaigns. Radon (²²²Rn) a naturally procuded radionucleid and particularly suitable for use as a natural tracer due to its preferential partitioning with non aqueos phase liquids (NAPLs) and and ease of in situ analytical detection (Kram et al., 2001). The ability of the ²²²Rn technique to locate organic pollution hotspots and provide a semiquantitative analysis has been widely assessed in sites affected by NAPLs (De Miguel et al., 2018, De Miguel et al. 2020). However, the Radon measurement is affected by several confounding factors, such as variations in soil water saturation and ground-level temperature. Machine learning can be used to study and model these confounding factors and improve the interpretation of in situ radon analytical information.

Machine learning is a class of statistical techniques that have proven to be a powerful tool for modelling the behaviour of complex systems in which response quantities depend on assumed controls or predictors in a complicated way (Janik, 2018). The first purpose of this work is the application of machine learning to analyse sampled data of time series outdoor ²²²Rn. The algorithms "learn" from complete sections of multivariate series (containing measurements of soil water content, soil temperature and meteorological information), derive a dependence model. The model trained in this work can be used to improve the accuracy and reliability of the radon deficit technique, making it a more valuable tool for identifying and mapping subsurface contamination.

De Miguel, E., Barrio-Parra, F., Elío, J., Izquierdo-Díaz, M., Jerónimo, García-González, E., Mazadiego, L.F., Medina, R., 2018. Applicability of radon emanometry in lithologically discontinuous sites contaminated by organic chemicals. Environ. Sci. Pollut. Res. 25, 20255–20263. https://doi.org/10.1007/s11356-018-2372-9

De Miguel, E., Barrio-Parra, F., Izquierdo-díaz, M., Fernández, J., García-gonzález, J.E., 2020. Applicability and limitations of the radon-deficit technique for the preliminary assessment of sites contaminated with complex mixtures of organic chemicals: a blind field-test. Environ. Int. 138, 105591. https://doi.org/10.1016/j.envint.2020. 105591.

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How to cite: Lorenzo, D., Barrio-Parra, F., Serrano-García, H., Izquierdo-Díaz, M., and De Miguel, E.: Application of machine learning methods to improve the radon deficit technique, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15380, https://doi.org/10.5194/egusphere-egu24-15380, 2024.