Modeling of geogenic radon in Switzerland based on ordered logistic regression

Influence of rock type and geophysical properties on radon flux density

The most significant source of human exposure to ionizing radiation is the radioactive gas radon (basically 222Rn) and its daughter decay products, creating more than half of the effective dose from all natural sources. Radon enters buildings mainly from dense rocks, which are below building foundations at depths of 1 m and more. In this paper long-term measurements of radon flux density are analyzed, with radon exhalation from the surface of the most common rocks-loams, sandy loams, clays, clay shales, several types of sandy-gravel-pebble deposits, clay and rocky limestone. The influence of geophysical properties of rocks on radon flux density due to exhalation from surfaces of those rocks was studied. Based on the results obtained, a method of local assessment of the hazard from radon and its progeny in buildings is proposed, which is based on the geophysical properties of rocks below the foundations of those buildings.

Spatial modeling of geogenic indoor radon distribution in Chungcheongnam-do, South Korea using enhanced machine learning algorithms

Prolonged inhalation of indoor radon and its progenies lead to severe health problems for housing occupants; therefore, housing developments in radon-prone areas are of great concern to local municipalities. Areas with high potential for radon exposure must be identified to implement cost-effective radon mitigation plans successfully or to prevent the construction of unsafe buildings. In this study, an indoor radon potential map of Chungcheongnam-do, South Korea, was generated using a group method of data handling (GMDH) algorithm based on local soil properties, geogenic, geochemical, as well as topographic factors. To optimally tune the hyper-parameters of GMDH and enhance the prediction accuracy of modelling radon distribution, the GMDH model was integrated with two metaheuristic optimization algorithms, namely the bat (BA) and cuckoo optimization (COA) algorithms. The goodness-of-fit and predictive performance of the models was quantified using the area under the receiver operating characteristic (ROC) curve (AUC), mean squared error (MSE), root mean square error (RMSE), and standard deviation (StD). The results indicated that the GMDH-COA model outperformed the other models in the training (AUC = 0.852, MSE = 0.058, RMSE = 0.242, StD = 0.242) and testing (AUC = 0.844, MSE = 0.060, RMSE = 0.246, StD = 0.0242) phases. Additionally, using metaheuristic optimization algorithms improved the predictive ability of the GMDH. The GMDH-COA model showed that approximately 7 % of the total area of Chungcheongnam-do consists of very high radon-prone areas. The information gain ratio method was used to assess the predictive ability of considered factors. As expected, soil properties and local geology significantly affected the spatial distribution of radon potential levels. The radon potential map produced in this study represents the first stage of identifying areas where large proportions of residential buildings are expected to experience significant radon levels due to high concentrations of natural radioisotopes in rocks and derived soils beneath building foundations. The generated map assists local authorities to develop urban plans more wisely towards region with less radon concentrations.

Detailed Geogenic Radon Potential Mapping Using Geospatial Analysis of Multiple Geo-Variables-A Case Study from a High-Risk Area in SE Ireland

A detailed investigation of geogenic radon potential (GRP) was carried out near Graiguenamanagh town (County Kilkenny, Ireland) by performing a spatial regression analysis on radon-related variables to evaluate the exposure of people to natural radiation (i.e., radon, thoron and gamma radiation). The study area includes an offshoot of the Caledonian Leinster Granite, which is locally intruded into Ordovician metasediments. To model radon release potential at different points, an ordinary least squared (OLS) regression model was developed in which soil gas radon (SGR) concentrations were considered as the response value. Proxy variables such as radionuclide concentrations obtained from airborne radiometric surveys, soil gas permeability, distance from major faults and a digital terrain model were used as the input predictors. ArcGIS and QGIS software together with XLSTAT statistical software were used to visualise, analyse and validate the data and models. The proposed GRP models were validated through diagnostic tests. Empirical Bayesian kriging (EBK) was used to produce the map of the spatial distribution of predicted GRP values and to estimate the prediction uncertainty. The methodology described here can be extended for larger areas and the models could be utilised to estimate the GRPs of other areas where radon-related proxy values are available.

The Impact of Formality, Integration, and Commitment on the Performance of Latino-Owned Small Businesses

Supporting the growth of minority-owned small- and medium-sized enterprises (SMEs) is an important goal in many countries. In the US, Latinos start businesses faster than any other demographic group, yet Latino wealth and income have not kept pace with the broader society. In this study, we explore the impact of different business and owner characteristics on the performance of Latino-owned small businesses. Using a survey of over 200 Latino small business owners in Silicon Valley, we apply ordered logistic regression to measure the effect of several variables on firm revenue. Our findings suggest that in addition to the gender and education of the owner, the most important factors impacting business performance are the owner’s commitment to the business, formal registration of the business, and the degree to which the business is integrated into the broader business community. This research adds to our understanding of the factors that significantly impact the economic success of Latino-owned small businesses. The results will be helpful to organizations that support the development and sustainability of Latino entrepreneurship.

RADON-PRONE AREAS IN SLOVAKIA PREDICTED BY RESCALED RADON POTENTIAL MAPS

Several scientific studies have shown that high content of radon in the soil environment can be a precursor of increased indoor radon levels. Inhabited areas where elevated indoor radon concentration appears for natural (geogenic) reasons are commonly referred to as radon-prone areas. In this study, radon-prone areas in the Slovak Republic were predicted on the basis of radon potential maps after its specific rescaling. In total, 99 municipalities have been identified in Slovakia where the annual average indoor radon concentration is expected to exceed the reference level of 300 Bq m-3; five of those are even expected to exceed 1000 Bq m-3. In these municipalities it is then required to conduct a survey of indoor radon measurements. Compared with a nationwide survey, the proposed approach of searching for houses with potentially high radon exposure is more efficient.

Consumers' purchase intention of wild freshwater fish during the COVID-19 pandemic

The association between the COVID-19 pandemic and the wildlife trade in the seafood market in Wuhan has raised public concern regarding wildlife consumption and public health safety. Considering several coronavirus transmission incidents related to aquatic products and the location of wild freshwater fish in aquatic consumption in China, the effects of COVID-19 on the purchase intention of wild freshwater fish was investigated. Based on 1163 online questionnaires from eight provinces (including two province-level municipalities) in the Yangtze River Basin, ordered logistic regression was carried out to analyze the influencing factors of purchase intention of wild freshwater fish during the COVID-19 pandemic. The empirical results indicated that the COVID-19 pandemic had changed consumers' perceived risk and purchase frequency of wild freshwater fish. External stimulus caused by the COVID-19 pandemic had little influence on perceived risk and purchase intention. Consumer preference had a significant impact on perceived risk and purchase intention. Therefore, efforts should be put to strengthen the popularization of aquatic product knowledge, guide the public to develop scientific and civic eating habits, and improve the traceability system of aquatic products. [EconLit Citations: D12-Consumer Economics: Empirical Analysis, Q22-Fishery; Aquaculture].

The assessment of local geological factors for the construction of a Geogenic Radon Potential map using regression kriging. A case study from the Euganean Hills volcanic district (Italy)

The assessment of potential radon-hazardous environments is nowadays a critical issue in planning, monitoring, and developing appropriate mitigation strategies. Although some geological structures (e.g., fault systems) and other geological factors (e.g., radionuclide content, soil organic or rock weathering) can locally affect the radon occurrence, at the basis of a good implementation of radon-safe systems, optimized modelling at territorial scale is required. The use of spatial regression models, adequately combining different types of predictors, represents an invaluable tool to identify the relationships between radon and its controlling factors as well as to construct Geogenic Radon Potential (GRP) maps of an area. In this work, two GRP maps were developed based on field measurements of soil gas radon and thoron concentrations and gamma spectrometry of soil and rock samples of the Euganean Hills (northern Italy) district. A predictive model of radon concentration in soil gas was reconstructed taking into account the relationships among the soil gas radon and seven predictors: terrestrial gamma dose radiation (TGDR), thoron (²²⁰Rn), fault density (FD), soil permeability (PERM), digital terrain model (SLOPE), moisture index (TMI), heat load index (HLI). These predictors allowed to elaborate local spatial models by using the Empirical Bayesian Regression Kriging (EBRK) in order to find the best combination and define the GRP of the Euganean Hills area. A second GRP map based on the Neznal approach (GRP_NEZ) has been modelled using the TGDR and ²²⁰Rn, as predictors of radon concentration, and FD as predictor of soil permeability. Then, the two GRP maps have been compared. Results highlight that the radon potential is mainly driven by the bedrock type but the presence of fault systems and topographic features play a key role in radon migration in the subsoil and its exhalation at the soil/atmosphere boundary.

Modelling work- and non-work-based trip patterns during transition to lockdown period of COVID-19 pandemic in India

COVID-19 pandemic has significantly affected the transportation sector across the world. Implementation of lockdown (that includes restricted travel activities) is a prevention strategy executed by various governments to minimize the spread of COVID-19. India went into complete lockdown from 25th March 2020; however, change in commuter's travel behavior was observed from the third week of March (termed as transition to lockdown) due to pandemic fear. In total 1945 participants participated in the travel behaviour survey and their responses with respect to work-based and non-work-based trips during transition period were analysed to understand their adaptation towards COVID-19. The study also attempted to quantify the effects of influencing factors which can explain change in the commuters' travel behaviour. The findings revealed that one-year increment in traveller's age had 2% reduced probability of no travel during transition than pre-transition. For non-work-related travel, chances of lower travel frequency were significantly greater during the transition period as compared to pre-transition. Compared to the non-essential trips, the chances of reduced travel frequency for the essential trips were found to be lower by 92%. By examining these behavioural changes, the present study aims to assist the policymakers in understanding the dynamics of fluctuating travel demand with respect to trip purpose during pandemic situations like COVID-19.

A Study of Natural Radioactivity Levels and Radon/Thoron Release Potential of Bedrock and Soil in Southeastern Ireland

Radon (²²²Rn) and thoron (²²⁰Rn) account for almost two-thirds of the annual average radiation dose received by the Irish population. A detailed study of natural radioactivity levels and radon and thoron exhalation rates was carried out in a legislatively designated “high radon” area, as based on existing indoor radon measurements. Indoor radon concentrations, airborne radiometric data and stream sediment geochemistry were collated, and a set of soil samples were taken from the study area. The exhalation rates of radon (E²²²_Rn) and thoron (E²²⁰_Rn) for collected samples were determined in the laboratory. The resultant data were classified based on geological and soil type parameters. Geological boundaries were found to be robust classifiers for radon exhalation rates and radon-related variables, whilst soil type classification better differentiates thoron exhalation rates and correlated variables. Linear models were developed to predict the radon and thoron exhalation rates of the study area. Distribution maps of radon and thoron exhalation rates (range: E²²²_Rn [0.15–1.84] and E²²⁰_Rn [475–3029] Bq m⁻² h⁻¹) and annual effective dose (with a mean value of 0.84 mSv y⁻¹) are presented. For some parts of the study area, the calculated annual effective dose exceeds the recommended level of 1 mSv y⁻¹, illustrating a significant radiation risk. Airborne radiometric data were found to be a powerful and fast tool for the prediction of geogenic radon and thoron risk. This robust method can be used for other areas where airborne radiometric data are available.

Residential radon - Comparative analysis of exposure models in Switzerland

Residential radon exposure is a major public health issue in Switzerland due to the known association between inhaled radon progeny and lung cancer. To confirm recent findings of an association with skin cancer mortality, an updated national radon model is needed. The aim of this study was to derive the best possible residential radon prediction model for subsequent epidemiological analyses. Two different radon prediction models were developed (linear regression model vs. random forest) using ca. 80,000 measurements in the Swiss Radon Database (1994-2017). A range of geographic predictors and building specific predictors were considered in the 3-D models (x,y, floor of dwelling). A five-fold modelling strategy was used to evaluate the robustness of each approach, with models developed (80% measurement locations) and validated (20%) using standard diagnostics. Random forest consistently outperformed the linear regression model, with higher Spearman's rank correlation (51% vs. 36%), validation coefficient of determination (R² 31% vs. 15%), lower root mean square error (RMSE) and lower fractional bias. Applied to the population of 5.4 million adults in 2000, the random forest resulted in an arithmetic mean (standard deviation) of 75.5 (31.7) Bq/m³, and indicated a respective 16.1% and 0.1% adults with predicted radon concentrations exceeding the World Health Organization (100 Bq/m³) and Swiss (300 Bq/m³) reference values.

Ambient gamma dose rate as an indicator of geogenic radon potential

Radon is the second cause of lung cancer after smoking, therefore is acknowledged as a major indoor air pollutant. Geogenic radon potential indicates regions where for natural reasons elevated indoor radon levels or elevated probability of their occurrence can be expected. The most common procedure for establishing geogenic radon potential includes measurements of soil permeability and soil gas radon concentrations. These measurements are time-consuming and expensive therefore a limited number of measurements is carried out and their results are extrapolated to the specific area. Our research aimed to analyse the usefulness of ambient gamma dose rate survey to assess radon concentration in the environment and therefore geogenic radon potential. The measurements were carried out on two granite massifs with higher (Karkonosze) and lower (Strzelin) radioactive elements contents. Seasonal variations of atmospheric radon concentrations and ambient gamma dose rates were registered with higher values during warmer and lower during colder seasons. The opposite seasonal variations were observed for soil gas radon concentrations. No distinctive seasonal variations were recorded in results of uranium, thorium and potassium contents in soil measured in situ by the gamma-ray spectrometer. The correlation coefficients were calculated on the base of annual average data. The correlations between ambient gamma dose rate and radon concentration in soil and in the atmosphere were 0.83 and 0.62 respectively, which may suggest that ambient gamma dose rate can be a useful parameter to indicate geogenic radon potential.

Developing a method for predicting radon concentrations above a reference level in new montenegrin buildings

Dependence of indoor radon concentrations (IRCs) in the ground floors of 1200 buildings across Montenegro on 11 factors was analyzed. A group of 734 buildings, for which none of the analyzed factors was missing, was further analyzed using the logistic regression method, in order to develop a prediction model for IRC occurrence above the national reference level for new buildings (200 Bq/m³). Applying the forward stepwise method, and based on likelihood ratios, five explanatory variables-municipality, type of building, presence of basement, window frames, and period of construction-were selected for including into the final logistic regression model for predicting probability of IRC > 200 Bq/m³. The final model explained 77.1% of the observed IRCs, while the obtained Area under the Curve of 0.8018 classified the model as having a very high predictive ability. Achieving similar values for both the final prediction model and the validation model, for sensitivity, specificity, and accuracy, confirmed the applicability of the developed model.

Radon-222: environmental behavior and impact to (human and non-human) biota

As an inert radioactive gas, ²²²Rn could be easily transported to the atmosphere via emanation, migration, or exhalation. Research measurements pointed out that ²²²Rn activity concentration changes during the winter and summer months, as well as during wet and dry season periods. Changes in radon concentration can affect the atmospheric electric field. At the boundary layer near the ground, short-lived daughters of ²²²Rn can be used as natural tracers in the atmosphere. In this work, factors controlling ²²²Rn pathways in the environment and its levels in soil gas and outdoor air are summarized. ²²²Rn has a short half-life of 3.82 days, but the dose rate due to radon and its radioactive progeny could be significant to the living beings. Epidemiological studies on humans pointed out that up to 14% of lung cancers are induced by exposure to low and moderate concentrations of radon. Animals that breed in ground holes have been exposed to the higher doses due to radiation present in soil air. During the years, different dose-effect models are developed for risk assessment on human and non-human biota. In this work are reviewed research results of ²²²Rn exposure of human and non-human biota.

Residential radon exposure and hypertensive disorders of pregnancy in Massachusetts, USA: A cohort study

BACKGROUND

Exposure to ionizing radiation has been associated with hypertension, but the relationship between residential radon exposure and hypertensive disorders of pregnancy (HDP) has not been examined.

METHODS

We used the Massachusetts Birth Registry of Vital Records from 2001 to 2015 including women with a singleton pregnancy without prior hypertension. The binary outcome (HDP) included gestational hypertension and pre-eclampsia cases and was assessed using birth certificate data. We obtained 141,665 basement radon measurements from Spruce Environmental Technologies, Inc. and modeled the monthly zip code basement radon level. We used a logistic regression model adjusted for sociodemographic covariates, maternal comorbidities, PM_2.5, season, temperature, and relative humidity. We examined effect modification by maternal age, race, and maternal education as an indicator of socio-economic status.

RESULTS

Of 975,528 women, 3.7% (36,530) of them developed HDP. Zip code level radon ranged from 22 to 333 mBq/m³. An interquartile range (IQR) increase in zip code radon level throughout pregnancy was associated with a 15% increase in the odds of HDP (95% CI 13% to 18%). In women less than 20 years old, an IQR increase in zip code level radon was associated with 38% increase in the odds of HDP (95% CI 24% to 50%), while the effect was smaller in older women. There was no effect modification by maternal race or education.

CONCLUSIONS

In this cohort, higher levels of residential radon are associated with increased odds of HDP. After stratifying by age, this effect was stronger in participants younger than 20 years old. Since the burden of hypertensive disorders of pregnancy is increasing and affects women's future cardiovascular health, identification of modifiable risk factors is of great importance.

Development of a Geogenic Radon Hazard Index-Concept, History, Experiences

Exposure to indoor radon at home and in workplaces constitutes a serious public health risk and is the second most prevalent cause of lung cancer after tobacco smoking. Indoor radon concentration is to a large extent controlled by so-called geogenic radon, which is radon generated in the ground. While indoor radon has been mapped in many parts of Europe, this is not the case for its geogenic control, which has been surveyed exhaustively in only a few countries or regions. Since geogenic radon is an important predictor of indoor radon, knowing the local potential of geogenic radon can assist radon mitigation policy in allocating resources and tuning regulations to focus on where it needs to be prioritized. The contribution of geogenic to indoor radon can be quantified in different ways: the geogenic radon potential (GRP) and the geogenic radon hazard index (GRHI). Both are constructed from geogenic quantities, with their differences tending to be, but not always, their type of geographical support and optimality as indoor radon predictors. An important feature of the GRHI is consistency across borders between regions with different data availability and Rn survey policies, which has so far impeded the creation of a European map of geogenic radon. The GRHI can be understood as a generalization or extension of the GRP. In this paper, the concepts of GRP and GRHI are discussed and a review of previous GRHI approaches is presented, including methods of GRHI estimation and some preliminary results. A methodology to create GRHI maps that cover most of Europe appears at hand and appropriate; however, further fine tuning and validation remains on the agenda.

Indoor radon concentrations in residential houses, processing factories, and mines in Neyriz, Iran

PURPOSE

This study aimed to determine radon concentrations in mines, stone processing factories, residential houses, and public areas, as well as calculating its effective dose in Neyriz, Iran.

METHOD

A total of 74 alpha Track detectors (CR-39 detector) were installed at the desired locations based on the US-EPA's protocol. After 3 months the detectors were collected and delivered to a Radon Reference Laboratory for analyzing.

RESULTS

Mean ± SD, minimum and maximum radon concentrations in the sampling buildings were 29.93 ± 12.63, 10.33, and 66.76 Bq/m³, respectively. The effective annual dose was calculated to be 0.75 mSv/year, which was lower than the recommended value. Significant positive correlations were found between radon concentrations and some studied variables including smoking cigarettes, number of cigarettes smoked, duration of smoking, building's age, number of floors, having cracks, use of colors in the building, use of ceramic for flooring, use of stone for flooring, and gas consumption. The number of cigarettes smoked by the residents was the most important predictor of radon concentrations. Radon concentrations were lower than standard values in all sampling locations.

CONCLUSION

It is necessary to conduct further studies in the field of regional geology and determine the sources that release radon in these areas to prevent further increases in radon concentration due to the proximity and plurality of mines and factories.

Logistic regression model for detecting radon prone areas in Ireland

A new high spatial resolution radon risk map of Ireland has been developed, based on a combination of indoor radon measurements (n=31,910) and relevant geological information (i.e. Bedrock Geology, Quaternary Geology, soil permeability and aquifer type). Logistic regression was used to predict the probability of having an indoor radon concentration above the national reference level of 200Bqm^-3 in Ireland. The four geological datasets evaluated were found to be statistically significant, and, based on combinations of these four variables, the predicted probabilities ranged from 0.57% to 75.5%. Results show that the Republic of Ireland may be divided in three main radon risk categories: High (HR), Medium (MR) and Low (LR). The probability of having an indoor radon concentration above 200Bqm^-3 in each area was found to be 19%, 8% and 3%; respectively. In the Republic of Ireland, the population affected by radon concentrations above 200Bqm^-3 is estimated at ca. 460k (about 10% of the total population). Of these, 57% (265k), 35% (160k) and 8% (35k) are in High, Medium and Low Risk Areas, respectively. Our results provide a high spatial resolution utility which permit customised radon-awareness information to be targeted at specific geographic areas.