Radon risk mapping in southern Belgium: an application of geostatistical and GIS techniques

Geologic, seasonal, and atmospheric predictors of indoor home radon values

Exposure to tobacco smoke and radon cause lung cancer. Radioactive decay of naturally occurring uranium in bedrock produces radon. Seasonality, bedrock type, age of home, and topography have been associated with indoor radon, but the research is mixed. The study objective was to examine the relationships of geologic (soil radon and bedrock) and seasonal (warm and cold times of the year) factors with indoor home radon values in citizen scientists' homes over time, controlling for atmospheric conditions, topography, age of home, and home exposure to tobacco smoke. We collected and analyzed indoor radon values, soil radon gas concentrations, and dwelling- and county-level geologic and atmospheric conditions on 66 properties in four rural counties during two seasons: (1) summer 2021 (n = 53); and (2) winter/spring 2022 (n = 52). Citizen scientists measured indoor radon using Airthings radon sensors, and outdoor temperature and rainfall. Geologists obtained soil radon measurements using RAD7 instruments at two locations (near the dwelling and farther away) at each dwelling, testing for associations of indoor radon values with soil values, bedrock type, topography, and atmospheric conditions. Bedrock type, near soil radon levels, home age, and barometric pressure were associated with indoor radon. Dwellings built on carbonate bedrock had indoor radon values that were 2.8 pCi/L (103.6 Bq m-3) higher, on average, compared to homes built on siliclastic rock. Homes with higher near soil radon and those built <40 ago were more likely to have indoor radon ⩾4.0 pCi/L (148 Bq m-3). With higher atmospheric barometric pressure during testing, observed indoor radon values were lower. Seasonality and topography were not associated with indoor radon level. Understanding relationships among bedrock type, soil radon, and indoor radon exposure allows the development of practical predictive models that may support pre-construction forecasting of indoor radon potential based on geologic factors.

Radon potential mapping in Jangsu-gun, South Korea using probabilistic and deep learning algorithms

The adverse health effects associated with the inhalation and ingestion of naturally occurring radon gas produced during the uranium decay chain mean that there is a need to identify high-risk areas. This study detected radon-prone areas using a geographic information system (GIS)-based probabilistic and machine learning methods, including the frequency ratio (FR) model and a convolutional neural network (CNN). Ten influencing factors, namely elevation, slope, the topographic wetness index (TWI), valley depth, fault density, lithology, and the average soil copper (Cu), calcium oxide (Cao), ferric oxide (Fe₂O₃), and lead (Pb) concentrations, were analyzed. In total, 27 rock samples with high activity concentration index values were divided randomly into training and validation datasets (70:30 ratio) to train the models. Areas were categorized as very high, high, moderate, low, and very low radon areas. According to the models, approximately 40% of the study area was classified as very high or high risk. Finally, the radon potential maps were validated using the area under the receiver operating characteristic curve (AUC) analysis. This showed that the CNN algorithm was superior to the FR method; for the former, AUC values of 0.844 and 0.840 were obtained using the training and validation datasets, respectively. However, both algorithms had high predictive power. Slope, lithology, and TWI were the best predictors of radon-affected areas. These results provide new information regarding the spatial distribution of radon, and could inform the development of new residential areas. Radon screening is important to reduce public exposure to high levels of naturally occurring radiation.

Radon risk mapping: A new geostatistical method based on Lorenz Curve and Gini index

In confined spaces such as living environments and workplaces, the concentration levels of radon (Rn²²²) can be very high as compared to the external environment. Since Rn has been classified as the second leading cause of lung cancer after cigarette smoking, to apply efficient locally based risk reduction actions, dense maps of indoor radon concentration are needed. These maps would provide information about the areas prone to high radon concentrations and therefore more dangerous to human health. The soil is the primary source of the Rn, hence the risk assessment and reduction for the radon exposure cannot disregard the identification of the local geology. In this regard, we propose an innovative method, based on the Gini index computation, for the realization of interpolated maps (kriging) to describe the distribution of concentration of Rn. To validate the method, a tool that simulates sets of radon concentrations is used, whose variability is, to the first order, controlled by a priori imposed different lithologies. A systematic comparison is made between the results achieved by means of a classically used geostatistical method and the proposed Gini-based tool. We show how, by using this latter tool, the kriging solutions appear to be more robust to resolve the different geogenic radon sources independently from the number of the available measurements.

Geovisualization Techniques of Spatial Environmental Data Using Different Visualization Tools

The appearance of online map services and frameworks (e.g., KML, QGIS) has increased the possibilities to easily, quickly and—in many cases—cost-effectively publish spatial data stored in databases. The aim of this study is to present the geovisualization of spatial databases of a Hungarian settlement on the web, using the open source webGIS system and Google application programming interfaces (APIs). The interactive point and interpolated distribution maps available online provide a detailed picture of the level of contamination, the spatial distribution of the ground water supply of the investigated settlement, and the changes which have occurred following the establishment of the sewage system. In the case of PO43− we determined that in the year before the sewage system was constructed, most of the area of the settlement could be considered contaminated, with the highest level of contamination measured in the central area of the settlement. Five years after the construction of the sewage system, the ratio of the contaminated areas had significantly decreased. In the case of NO3− we found a high level of contamination before the construction of the sewage system with a concentration increase in a North–West direction. After the establishment of the sewage system, the increase in concentration was the most intense in the central parts of the settlement, while the characteristic spatial distribution could no longer be observed. The geovisualization techniques developed are able to provide information about the different spatial data for users in a visual way, and also help to understand better the spatial information using a cognitive approach. The advantage of interactive web maps created with the technologies applied over traditional static maps is a new approach, which allows the user to manipulate the temporal and spatial data directly in the most appropriate way.

Qualitative overview of indoor radon surveys in Europe

The revised European Directive from 2013 regarding basic safety standard oblige EU Member States to establish a national action plan regarding the exposure to radon. At the same time, International Atomic Energy Agency started technical projects in order to assist countries to establish and implement national radon action. As a consequence, in recent years, in numerous countries national radon surveys were conducted and action plans established, which were not performed before. In this paper, a qualitative overview of radon surveys performed in Europe is given with a special attention to the qualitative and conceptual description of surveys, representativeness and QA/QC (quality assurance/quality control).

Implications of alteration processes on radon emanation, radon production rate and W-Sn exploration in the Panasqueira ore district

Alteration processes have strong impacts on the chemical and physical properties of rock masses. Because they can affect the contents and the distribution of U as well as enhance the permeability of the bedrock, they may lead to a significant increase of radon release to the environment. However, their influence on radon emanation and radon production rate has yet to be properly assessed. To investigate the impact of alteration processes on the radiological properties, samples were collected in the Panasqueira region under the influence of surface weathering, deuteric, hydrothermal and fault related alteration. Major and trace elements (U, Th), physical, and radiological properties were measured in metasedimentary and fault rocks. The degree of alteration and weathering progress were assessed through indices of alteration, porosity and bulk density. Overall, an increase of the radon emanation coefficient from (approximately) 0.1 to 0.4 and radon production rate (from 40 to over 160Bq·m^-3·h^-1) is observed with the progress of physicochemical alteration. Decoupling of physical and chemical alteration however implies both must be quantified towards a proper assessment of the degree of alteration. The behavior of radiogenic elements upon alteration is shown to be complex and contingent upon the alteration process. An atypical increase of radon emanation in the ore district due to U mobilization was caused by hydrothermal alteration. Because radon emanation is not dependent upon the pelitic nature of the metasedimentary rocks, it may thus become a proxy for W-Sn exploration. The dependency of radon production rate from the latter constrains its use for exploration. Nevertheless, it may provide a reliable estimation of the bedrock contribution to indoor radon concentrations. Higher indoor radon concentrations, hence, a higher risk of exposure to radon are expected in the ore district as well as within fault zones.

Iron and Manganese in Groundwater: Using Kriging and GIS to Locate High Concentrations in Buncombe County, North Carolina

For health, economic, and aesthetic reasons, allowable concentrations (as suggested by the United States Environmental Protection Agency) of the secondary contaminants iron (Fe) and manganese (Mn) found present in drinking water are 0.3 and 0.05 mg/L, respectively. Water samples taken from private drinking wells in rural communities within Buncombe County, North Carolina contain concentrations of these metals that exceed secondary water quality criteria. This study predicted the spatial distribution of Fe and Mn in the county, and evaluated the effect of site environmental factors (bedrock geology, ground elevation, saprolite thickness, and drinking water well depth) in controlling the variability of Fe and Mn in groundwater. A statistically significant correlation between Fe and Mn concentrations, attributable to bedrock geology, was identified. Prediction models were created using ordinary kriging and cokriging interpolation techniques to estimate the presence of Fe and Mn in groundwater where direct measurements are not possible. This same procedure can be used to estimate the trend of other contaminants in the groundwater in different areas with similar hydrogeological settings.

Lung and stomach cancer associations with groundwater radon in North Carolina, USA

Background

The risk of indoor air radon for lung cancer is well studied, but the risks of groundwater radon for both lung and stomach cancer are much less studied, and with mixed results.

Methods

Geomasked and geocoded stomach and lung cancer cases in North Carolina from 1999 to 2009 were obtained from the North Carolina Central Cancer Registry. Models for the association with groundwater radon and multiple confounders were implemented at two scales: (i) an ecological model estimating cancer incidence rates at the census tract level; and (ii) a case-only logistic model estimating the odds that individual cancer cases are members of local cancer clusters.

Results

For the lung cancer incidence rate model, groundwater radon is associated with an incidence rate ratio of 1.03 [95% confidence interval (CI) = 1.01, 1.06] for every 100 Bq/l increase in census tract averaged concentration. For the cluster membership models, groundwater radon exposure results in an odds ratio for lung cancer of 1.13 (95% CI = 1.04, 1.23) and for stomach cancer of 1.24 (95% CI = 1.03, 1.49), which means groundwater radon, after controlling for multiple confounders and spatial auto-correlation, increases the odds that lung and stomach cancer cases are members of their respective cancer clusters.

Conclusion

Our study provides epidemiological evidence of a positive association between groundwater radon exposure and lung cancer incidence rates. The cluster membership model results find groundwater radon increases the odds that both lung and stomach cancer cases occur within their respective cancer clusters. The results corroborate previous biokinetic and mortality studies that groundwater radon is associated with increased risk for lung and stomach cancer.

Quantile regression and Bayesian cluster detection to identify radon prone areas

Albeit the dominant source of radon in indoor environments is the geology of the territory, many studies have demonstrated that indoor radon concentrations also depend on dwelling-specific characteristics. Following a stepwise analysis, in this study we propose a combined approach to delineate radon prone areas. We first investigate the impact of various building covariates on indoor radon concentrations. To achieve a more complete picture of this association, we exploit the flexible formulation of a Bayesian spatial quantile regression, which is also equipped with parameters that controls the spatial dependence across data. The quantitative knowledge of the influence of each significant building-specific factor on the measured radon levels is employed to predict the radon concentrations that would have been found if the sampled buildings had possessed standard characteristics. Those normalised radon measures should reflect the geogenic radon potential of the underlying ground, which is a quantity directly related to the geological environment. The second stage of the analysis is aimed at identifying radon prone areas, and to this end, we adopt a Bayesian model for spatial cluster detection using as reference unit the building with standard characteristics. The case study is based on a data set of more than 2000 indoor radon measures, available for the Abruzzo region (Central Italy) and collected by the Agency of Environmental Protection of Abruzzo, during several indoor radon monitoring surveys.

Mapping radon hazard areas using 238U measurements and geological units: a study in a high background radiation city of China

In order to identify radon-prone areas and evaluate radon risk level, a soil gas radon survey combined with gamma-ray spectrometry measurements was carried out in Shenzhen City, south China. Meanwhile, the statistical analysis was applied to evaluate the distribution of measured results. This paper presents the methodology of the radon risk assessment. A radon risk map was accomplished based on a combination of soil gas radon concentration (RC), soil air permeability (Perm.) and uranium (²³⁸U) concentration. The results showed that the distribution of soil gas RC and radon-prone areas were closely related to geologic distribution of uranium (²³⁸U) and local lithology.

Improved predictive mapping of indoor radon concentrations using ensemble regression trees based on automatic clustering of geological units

PURPOSE

According to estimations around 230 people die as a result of radon exposure in Switzerland. This public health concern makes reliable indoor radon prediction and mapping methods necessary in order to improve risk communication to the public. The aim of this study was to develop an automated method to classify lithological units according to their radon characteristics and to develop mapping and predictive tools in order to improve local radon prediction.

METHOD

About 240 000 indoor radon concentration (IRC) measurements in about 150 000 buildings were available for our analysis. The automated classification of lithological units was based on k-medoids clustering via pair-wise Kolmogorov distances between IRC distributions of lithological units. For IRC mapping and prediction we used random forests and Bayesian additive regression trees (BART).

RESULTS

The automated classification groups lithological units well in terms of their IRC characteristics. Especially the IRC differences in metamorphic rocks like gneiss are well revealed by this method. The maps produced by random forests soundly represent the regional difference of IRCs in Switzerland and improve the spatial detail compared to existing approaches. We could explain 33% of the variations in IRC data with random forests. Additionally, the influence of a variable evaluated by random forests shows that building characteristics are less important predictors for IRCs than spatial/geological influences. BART could explain 29% of IRC variability and produced maps that indicate the prediction uncertainty.

CONCLUSION

Ensemble regression trees are a powerful tool to model and understand the multidimensional influences on IRCs. Automatic clustering of lithological units complements this method by facilitating the interpretation of radon properties of rock types. This study provides an important element for radon risk communication. Future approaches should consider taking into account further variables like soil gas radon measurements as well as more detailed geological information.

Predictive analysis and mapping of indoor radon concentrations in a complex environment using kernel estimation: an application to Switzerland

PURPOSE

The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information.

METHODS

We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map.

RESULTS

Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation.

CONCLUSIONS

IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

Lung cancer mortality and radon concentration in a chronically exposed neighborhood in Chihuahua, Mexico: a geospatial analysis

This study correlated lung cancer (LC) mortality with statistical data obtained from government public databases. In order to asses a relationship between LC deaths and radon accumulation in dwellings, indoor radon concentrations were measured with passive detectors randomly distributed in Chihuahua City. Kriging (K) and Inverse-Distance Weighting (IDW) spatial interpolations were carried out. Deaths were georeferenced and Moran's I correlation coefficients were calculated. The mean values (over n = 171) of the interpolation of radon concentrations of deceased's dwellings were 247.8 and 217.1 Bq/m³, for K and IDW, respectively. Through the Moran's I values obtained, correspondingly equal to 0.56 and 0.61, it was evident that LC mortality was directly associated with locations with high levels of radon, considering a stable population for more than 25 years, suggesting spatial clustering of LC deaths due to indoor radon concentrations.

Geographical distribution of the annual mean radon concentrations in primary schools of Southern Serbia - application of geostatistical methods

Between 2008 and 2011 a survey of radon ((222)Rn) was performed in schools of several districts of Southern Serbia. Some results have been published previously (Žunić et al., 2010; Carpentieri et al., 2011; Žunić et al., 2013). This article concentrates on the geographical distribution of the measured Rn concentrations. Applying geostatistical methods we generate "school radon maps" of expected concentrations and of estimated probabilities that a concentration threshold is exceeded. The resulting maps show a clearly structured spatial pattern which appears related to the geological background. In particular in areas with vulcanite and granitoid rocks, elevated radon (Rn) concentrations can be expected. The "school radon map" can therefore be considered as proxy to a map of the geogenic radon potential, and allows identification of radon-prone areas, i.e. areas in which higher Rn radon concentrations can be expected for natural reasons. It must be stressed that the "radon hazard", or potential risk, estimated this way, has to be distinguished from the actual radon risk, which is a function of exposure. This in turn may require (depending on the target variable which is supposed to measure risk) considering demographic and sociological reality, i.e. population density, distribution of building styles and living habits.

A statistical evaluation of the influence of housing characteristics and geogenic radon potential on indoor radon concentrations in France

Radon-222 is a radioactive natural gas produced by the decay of radium-226, known to be the main contributor to natural background radiation exposure. Effective risk management needs to determine the areas in which the density of buildings with high radon levels is likely to be highest. Predicting radon exposure from the location and characteristics of a dwelling could also contribute to epidemiological studies. Beginning in the nineteen-eighties, a national radon survey consisting in more than 10,000 measurements of indoor radon concentrations was conducted in French dwellings by the Institute for Radiological Protection and Nuclear Safety (IRSN). Housing characteristics, which may influence radon accumulation in dwellings, were also collected. More recently, the IRSN generated a French geogenic radon potential map based on the interpretation of geological features. The present study analyzed the two datasets to investigate the factors influencing indoor radon concentrations using statistical modeling and to determine the optimum use of the information on geogenic radon potential that showed the best statistical association with indoor radon concentration. The results showed that the variables associated with indoor radon concentrations were geogenic radon potential, building material, year of construction, foundation type, building type and floor level. The model, which included the surrounding geogenic radon potential (i.e. the average geogenic radon potential within a disc of radius 20 km centered on the indoor radon measurement point) and variables describing house-specific factors and lifestyle explained about 20% of the overall variability of the logarithm of radon concentration. The surrounding geogenic radon potential was fairly closely associated with the local average indoor radon concentration. The prevalence of exposure to radon above specific thresholds and the average exposures to radon clearly increased with increasing classes of geogenic radon potential. Combining the two datasets enabled improved assessment of radon exposure in a given area in France.

An approach to define potential radon emission level maps using indoor radon concentration measurements and radiogeochemical data positive proportion relationships

The aim of this paper is to present the first step of a new approach to make a map of radonprone areas showing different potential radon emission levels in the Quebec province. This map is a tool intended to assist the Quebec government in identifying populations with a higher risk of indoor radon gas exposure. This map of radon-prone areas used available radiogeochemical information for the province of Quebec: (1) Equivalent uranium (eU) concentration from airborne surface gamma-ray surveys; (2) uranium concentration measurements in sediments; and (3) bedrock and surficial geology. Positive proportion relationships (PPR) between each individual criterion and the 1417 available basement radon concentrations were demonstrated. It was also shown that those criteria were reliable indicators of radon-prone areas. The three criteria were discretized into 3, 2 and 2 statistically significant different classes respectively. For each class, statistical heterogeneity was validated by Kruskal-Wallis one way analyses of variance on ranks. Maps of radon-prone areas were traced down for each criterion. Based on this statistical study and on the maps of radon-prone areas in Quebec, 18% of the dwellings located in areas with an equivalent uranium (eU) concentration from airborne surface gamma-ray surveys under 0.75 ppm showed indoor radon concentrations above 150 Bq/m3. This percentage increases to 33% when eU concentrations are between 0.75 ppm and 1.25 ppm and exceeds 40% when eU concentrations are above 1.25 ppm. A uranium concentration in sediments above 20 ppm showed an indoor radon concentration geometric mean of 215 Bq/m3 with more than 69% of the dwellings exceeding 150 Bq/m3 or more than 50% of dwellings exceeding the Canadian radon guideline of 200 Bq/m3. It is also shown that the radon emission potential is higher where a uranium-rich bedrock unit is not covered by a low permeability (silt/clay) surficial deposit.

A geostatistical approach to assess the spatial association between indoor radon concentration, geological features and building characteristics: the case of Lombardy, Northern Italy

Radon is a natural gas known to be the main contributor to natural background radiation exposure and second to smoking, a major leading cause of lung cancer. The main source of radon is the soil, but the gas can enter buildings in many different ways and reach high indoor concentrations. Monitoring surveys have been promoted in many countries in order to assess the exposure of people to radon. In this paper, two complementary aspects are investigated. Firstly, we mapped indoor radon concentration in a large and inhomogeneous region using a geostatistical approach which borrows strength from the geologic nature of the soil. Secondly, knowing that geologic and anthropogenic factors, such as building characteristics, can foster the gas to flow into a building or protect against this, we evaluated these effects through a multiple regression model which takes into account the spatial correlation of the data. This allows us to rank different building typologies, identified by architectonic and geological characteristics, according to their proneness to radon. Our results suggest the opportunity to differentiate construction requirements in a large and inhomogeneous area, as the one considered in this paper, according to different places and provide a method to identify those dwellings which should be monitored more carefully.

Kriged and modeled ambient air levels of benzene in an urban environment: an exposure assessment study

BACKGROUND

There is increasing concern regarding the potential adverse health effects of air pollution, particularly hazardous air pollutants (HAPs). However, quantifying exposure to these pollutants is problematic.

OBJECTIVE

Our goal was to explore the utility of kriging, a spatial interpolation method, for exposure assessment in epidemiologic studies of HAPs. We used benzene as an example and compared census tract-level kriged predictions to estimates obtained from the 1999 U.S. EPA National Air Toxics Assessment (NATA), Assessment System for Population Exposure Nationwide (ASPEN) model.

METHODS

Kriged predictions were generated for 649 census tracts in Harris County, Texas using estimates of annual benzene air concentrations from 17 monitoring sites operating in Harris and surrounding counties from 1998 to 2000. Year 1999 ASPEN modeled estimates were also obtained for each census tract. Spearman rank correlation analyses were performed on the modeled and kriged benzene levels. Weighted kappa statistics were computed to assess agreement between discretized kriged and modeled estimates of ambient air levels of benzene.

RESULTS

There was modest correlation between the predicted and modeled values across census tracts. Overall, 56.2%, 40.7%, 31.5% and 28.2% of census tracts were classified as having 'low', 'medium-low', 'medium-high' and 'high' ambient air levels of benzene, respectively, comparing predicted and modeled benzene levels. The weighted kappa statistic was 0.26 (95% confidence interval (CI) = 0.20, 0.31), indicating poor agreement between the two methods.

CONCLUSIONS

There was a lack of concordance between predicted and modeled ambient air levels of benzene. Applying methods of spatial interpolation for assessing exposure to ambient air pollutants in health effect studies is hindered by the placement and number of existing stationary monitors collecting HAP data. Routine monitoring needs to be expanded if we are to use these data to better assess environmental health risks in the future.

Mapping of the geogenic radon potential in France to improve radon risk management: methodology and first application to region Bourgogne

In order to improve regulatory tools for radon risk management in France, a harmonised methodology to derive a single map of the geogenic radon potential has been developed. This approach consists of determining the capacity of the geological units to produce radon and to facilitate its transfer to the atmosphere, based on the interpretation of existing geological data. This approach is firstly based on a classification of the geological units according to their uranium (U) content, to create a radon source potential map. This initial map is then improved by taking into account the main additional parameters, such as fault lines, which control the preferential pathways of radon through the ground and which can increase the radon levels in soils. The implementation of this methodology to the whole French territory is currently in progress. We present here the results obtained in one region (Bourgogne, Massif Central) which displays significant variations of the geogenic radon potential. The map obtained leads to a more precise zoning than the scale of the existing map of radon priority areas currently based solely on administrative boundaries.

Environmental risk mapping of pollutants: state of the art and communication aspects

Risk maps help risk analysts and scientists to explore the spatial nature of the effects of environmental stressors such as pollutants. The development of Geographic Information Systems over the past few decades has greatly improved spatial representation and analysis of environmental information and data. Maps also constitute a powerful tool to communicate the outcome of complex environmental risk assessment to stakeholders such as the general public and policy makers. With appropriate cartography one can improve communication and thus bridge the gap between experts and users. Appropriate risk communication is pivotal to risk management, decision making and implementation and may prevent unnecessary concern about environmental pollutants. However, at present few risk maps are specifically tailored to meet the demands of such defined uses. This paper presents an overview of the most important types of risk maps that can be distinguished using examples from the scientific literature: contamination maps, exposure maps, hazard maps, vulnerability maps and 'true' risk maps. It also discusses, in a general way, the most important issues that need to be addressed when making risk maps for communication purposes: risk perception, target audience, scale and spatial aggregation and visualisation such as use of colours and symbols. Finally, some general rules of thumb are given for making environmental risk maps for communication purposes.

Probability mapping of indoor radon-prone areas using disjunctive kriging

After a reference to the use of maps of radon-prone areas for indoor radon risk management, and to the methods used to produce them, there is a brief illustration of the geostatistical method of disjunctive kriging (DK) introduced by G. Matheron as a substitute for conditional expectation. There are some good reasons of using this method for the mapping of radon-prone areas as follows: (1) spatial correlation is exploited; (2) unbiasedness is conserved even in the conditions of quasi-stationarity; (3) lognormality of the data is not required; (4) choosing the point estimation allows drawing up smooth probability maps. An application of DK is also presented for the production of probability maps in a campaign of indoor radon measurements conducted by Institute for Environmental Protection and Research, in the provinces of Rome and Viterbo (Central Italy). In the application, it is assessed in particular how much the spatial correlation, even though low, influences the results.

Groundwater quality mapping in urban groundwater using GIS

Konya City, located in the central part of Turkey, has grown and urbanized rapidly. A large amount of the water requirement of Konya City is supplied from groundwater. The quality of this groundwater was determined by taking samples from 177 of the wells within the study area. The purposes of this investigation were (1) to provide an overview of present groundwater quality and (2) to determine spatial distribution of groundwater quality parameters such as pH, electrical conductivity, Cl-, SO4(-2), hardness, and NO3- concentrations, and (3) to map groundwater quality in the study area by using GIS and Geostatistics techniques. ArcGIS 9.0 and ArcGIS Geostatistical Analyst were used for generation of various thematic maps and ArcGIS Spatial Analyst to produce the final groundwater quality map. An interpolation technique, ordinary kriging, was used to obtain the spatial distribution of groundwater quality parameters. The final map shows that the southwest of the city has optimum groundwater quality, and, in general, the groundwater quality decreases south to north of the city; 5.03% (21.51 km2) of the total study area is classified to be at the optimum groundwater quality level.

Assessment of the effectiveness of radon screening programs in reducing lung cancer mortality

The present study was aimed at assessing the health consequences of the presence of radon in Quebec homes and the possible impact of various screening programs on lung cancer mortality. Lung cancer risk due to this radioactive gas was estimated according to the cancer risk model developed by the Sixth Committee on Biological Effects of Ionizing Radiations. Objective data on residential radon exposure, population mobility, and tobacco use in the study population were integrated into a Monte-Carlo-type model. Participation rates to radon screening programs were estimated from published data. According to the model used, approximately 10% of deaths due to lung cancer are attributable to residential radon exposure on a yearly basis in Quebec. In the long term, the promotion of a universal screening program would prevent less than one death/year on a province-wide scale (0.8 case; IC 99%: -3.6 to 5.2 cases/year), for an overall reduction of 0.19% in radon-related mortality. Reductions in mortality due to radon by (1) the implementation of a targeted screening program in the region with the highest concentrations, (2) the promotion of screening on a local basis with financial support, or (3) the realization of systematic investigations in primary and secondary schools would increase to 1%, 14%, and 16.4%, respectively, in the each of the populations targeted by these scenarios. Other than the battle against tobacco use, radon screening in public buildings thus currently appears as the most promising screening policy for reducing radon-related lung cancer.

Indoor radon distribution in Switzerland: lognormality and Extreme Value Theory

Analysis and modeling of statistical distributions of indoor radon concentration from data valorization to mapping and simulations are critical issues for real decision-making processes. The usual way to model indoor radon concentrations is to assume lognormal distributions of concentrations on a given territory. While these distributions usually model correctly the main body of the data density, they cannot model the extreme values, which are more important for risk assessment. In this paper, global and local indoor radon distributions are modeled using Extreme Value Theory (EVT). Emphasis is put on the tails of the distributions and their deviations from lognormality. The best fits of distributions to real data set density have been computed and goodness of fit with Root Mean Squared Error (RMSE) is evaluated. The results show that EVT performs better than lognormal pdf for real data sets characterized by high indoor radon concentrations.

Investigations on indoor Radon in Austria, part 2: Geological classes as categorical external drift for spatial modelling of the Radon potential

Geological classes are used to model the deterministic (drift or trend) component of the Radon potential (Friedmann's RP) in Austria. It is shown that the RP can be grouped according to geological classes, but also according to individual geological units belonging to the same class. Geological classes can thus serve as predictors for mean RP within the classes. Variability of the RP within classes or units is interpreted as the stochastic part of the regionalized variable RP; however, there does not seem to exist a smallest unit which would naturally divide the RP into a deterministic and a stochastic part. Rather, this depends on the scale of the geological maps used, down to which size of geological units is used for modelling the trend. In practice, there must be a sufficient number of data points (measurements) distributed as uniformly as possible within one unit to allow reasonable determination of the trend component.

Mapping soil gas radon concentration: a comparative study of geostatistical methods

Understanding soil gas radon spatial variations can allow the constructor of a new house to prevent radon gas flowing from the ground. Indoor radon concentration distribution depends on many parameters and it is difficult to use its spatial variation to assess radon potential. Many scientists use to measure outdoor soil gas radon concentrations to assess the radon potential. Geostatistical methods provide us a valuable tool to study spatial structure of radon concentration and mapping. To explore the structure of soil gas radon concentration within an area in south Italy and choice a kriging algorithm, we compared the prediction performances of four different kriging algorithms: ordinary kriging, lognormal kriging, ordinary multi-Gaussian kriging, and ordinary indicator cokriging. Their results were compared using an independent validation data set. The comparison of predictions was based on three measures of accuracy: (1) the mean absolute error, (2) the mean-squared error of prediction; (3) the mean relative error, and a measure of effectiveness: the goodness-of-prediction estimate. The results obtained in this case study showed that the multi-Gaussian kriging was the most accurate approach among those considered. Comparing radon anomalies with lithology and fault locations, no evidence of a strict correlation between type of outcropping terrain and radon anomalies was found, except in the western sector where there were granitic and gneissic terrain. Moreover, there was a clear correlation between radon anomalies and fault systems.

"But there are no snakes in the wood": risk mapping as an outcome measure in evaluating complex interventions

OBJECTIVES

To complement biological and social behavioural markers in evaluating the complex intervention of sexual and reproductive health among adolescents in rural Zimbabwe, community-derived markers of effectiveness were sought. Through a participatory workshop with adolescent boys and girls, an innovative "risk map research workshop" was developed to be conducted throughout the study sites.

METHODS

78 gender-specific standardised workshops were conducted among secondary school students. Participants drew risk maps of their community. Focus group discussions explored each risk area identified on the map. Grounded Theory was used to create "categories" and "subcategories." Workshops continued to be held until "saturation", whereby no new categories emerged. "Axial coding" identified the inter-relationship between categories and subcategories according to their relevance to sexual and reproductive health risk.

RESULTS

Six "risk area" Grounded Theory categories emerged from the data: bush/rural terrain, commercial centres, homes, school environs, religious and spiritual venues, and roadsides. 17 subcategories emerged, grouped under each of the risk area categories, such as riverbeds, growth points, homesteads, classrooms, all-night prayer meetings and truck stops. Risks and the consequences of risks included sexually transmitted infections (including HIV), violence, sexual abuse, expulsion from school and illegal abortion.

CONCLUSIONS

Risk maps provide unique data that can be used to measure more subtle changes that occur as a result of social behavioural interventions aimed at addressing reproductive and sexual health. Another round of risk map research workshops will be held towards the end of the study to explore changes in milieu, behaviour and experiences, and will complement and triangulate the biological and other social behavioural outcome measures.

A geographic information systems (GIS) and spatial modeling approach to assessing indoor radon potential at local level

This study integrates residential radon data from previous studies in Southern California (USA), into a geographic information system (GIS) linked with statistical techniques. A difference (p<0.05) is found in the indoor radon in residences grouped by radon-potential zones. Using a novel Monte Carlo approach, we found that the mean distance from elevated-radon residences (concentration>74 Bq m(-3)) to epicenters of large (> 4 Richter) earthquakes was smaller (p<0.0001) than the average residence-to-epicenter distance, suggesting an association between the elevated indoor-radon and seismic activities.

Mitigation of a radon-rich Belgian dwelling using active subslab depressurization

In a radon prone area in Belgium, a dwelling with high indoor radon concentrations was identified through a passive measurement. Next, a continuous, active radon monitoring device was installed for one month. A 20-a retrospective radon assessment was also performed. The house was subsequently mitigated through active subslab depressurization with a radial fan. Afterwards the dwelling was actively monitored for several more months to observe the effects of the mitigation and to study the effect of reducing the fan power. Dose evaluations were made to evaluate the health benefit of the mitigation. It was seen that the results of the three measuring techniques before mitigation all yielded between 1700 and 2000 Bq/m3. Clear diurnal radon variations showed up only after mitigation. After mitigation, the average radon concentration fell to less than 200 Bq/m3. The yearly average dose was reduced from potentially 45 mSv/y to less than 4.5 mSv/y through mitigation. Reducing fan power to 50% did not clearly influence the amount of radon entering into the dwelling.

An assessment of gas emanation hazard using a geographic information system and geostatistics

This paper describes the use of geostatistical analysis and GIS techniques to assess gas emanation hazards. The Mt. Vulsini volcanic district was selected for this study because of the wide range of natural phenomena locally present that affect gas migration in the near surface. In addition, soil gas samples that were collected in this area should allow for a calibration between the generated risk/hazard models and the measured distribution of toxic gas species at surface. The approach used during this study consisted of three general stages. First data were digitally organized into thematic layers, then software functions in the GIS program "ArcView" were used to compare and correlate these various layers, and then finally the produced "potential-risk" map was compared with radon soil gas data in order to validate the model and/or to select zones for further, more-detailed soil gas investigations.