County-level indoor radon concentration mapping and uncertainty assessment in South Korea using geostatistical simulation and environmental factors.

This paper presents a geostatistical simulation approach to not only map the county-level indoor radon concentration (IRC) distributions in South Korea, but also quantify the uncertainty that can be used as decision-supporting information. For county-level IRC mapping in South Korea, environmental factors including geology, radium concentration in surface soil, gravel content in subsoil, and fault line density, which are known to be associated with the source and migration of radon gas, were incorporated into IRC measurements using multi-Gaussian kriging with local means. These four environmental factors could account for about 36% of the variability of noise-filtered IRCs, implying that regional variations of IRCs were affected by these factors. Sequential Gaussian simulation was then applied to generate alternative realizations of county-level IRC distributions. By summarizing the multiple simulation results, we identified some counties that lay on the great limestone series showed elevated IRCs. In addition, there were some counties in which the proportion of grids exceeding the recommended level was high but the uncertainty was also large according to the analysis of several uncertainty measures, which indicates that additional sampling is required for these counties. From the local cluster analysis in conjunction with simulation results, we found that the counties with higher levels of IRC belonged to the statistically significant clusters of high values, and these counties should be the prime targets for radon management and in-depth survey. The geographical distributions of IRC and uncertainty measures presented in this study provide guidance for effective radon management if they are consistently combined with both future IRC measurements and a geogenic radon potential map.

Source term estimation in the presence of nuisance signals.

Many source-term estimation algorithms for atmospheric releases assume the measured concentration data are influenced only by the releases of interest. However, there are situations where identifying a short-term release from an unknown location in the presence of long-term releases from a different location is of interest. One such example is determining if part or all of a typical magnitude concentration of a radioactive isotope in a sampler came from a nuclear explosion, such as the explosion announced by DPRK in 2013, while medical isotope facilities and nuclear power plants were also operating in the region. An estimation algorithm has been developed for the case where a short-duration release is confounded by a long-term nuisance signal associated with an additional release location. The technique is demonstrated using synthetic release data for a hypothetical medical isotope production facility and a hypothetical puff release from a different location. The algorithm successfully determines the location (within 30 km) and time-varying release rate (within a factor of 2) for the medical isotope production facility and the location (within 60 km), time (within 6 h), and release magnitude (within a factor of 4) of the puff release.

Utility of atmospheric transport runs done backwards in time for source term estimation.

One of the difficulties encountered in source-term analyses for airborne contaminants is the large computational effort required to predict air concentrations for all possible release scenarios. In some cases, analysts use atmospheric ATM runs with complex models done in the reverse-time direction because one ATM run done backwards in time for each sample can yield as much information as potentially hundreds or thousands of ATM runs done forwards in time. Unfortunately, the effective atmospheric dilution between the source and sampling locations differ depending on the time direction of the ATM run, with runs in the forward time direction being more realistic. No general studies have been published comparing the agreement between runs in the two time directions. Over 18000 ATM runs at 14 release locations were used to explore the agreement between dilution factors for the forward and reversed time directions at distances up to 1000 km from the release point. Ten of the release locations have a correlation below 0.9, with the lowest correlations occurring over mountainous terrain. The release locations were estimated using the time-reversed ATM runs, with 26% of the estimated release points being within 10 km of the modeled release point, 61% within 25 km, and 80% within 50 km. Most of the location differences greater than 50 km occur for two release locations in mountainous terrain. Good time-reversibility cannot be guaranteed for a new analysis, so we recommend any source-term solution using time-reversed ATM runs should include comparisons based on forward time ATM runs.

Confluent impact of housing and geology on indoor radon concentrations in Atlanta, Georgia, United States.

Radon is a naturally released radioactive carcinogenic gas. To estimate radon exposure, studies have examined various risk factors, but limited information exists pertaining to the confluent impact of housing characteristics and geology. This study evaluated the efficacy of housing and geological characteristics to predict radon risk in DeKalb County, Georgia, USA. Four major types of data were used: (1) three databases of indoor radon concentrations (n = 6757); (2) geologic maps of rock types and fault zones; (3) a database of 402 in situ measurements of gamma emissions, and (4) two databases of housing characteristics. The Getis-Ord method was used to delineate hot spots of radon concentrations. Empirical Bayesian Kriging was used to predict gamma radiation at each radon test site. Chi-square tests, bivariate correlation coefficients, and logistic regression were used to examine the impact of geological and housing factors on radon. The results showed that indoor radon levels were more likely to exceed the action level-4 pCi/L (148 Bq/m3) designated by the U.S. Environmental Protection Agency-in fault zones, were significantly positively correlated to gamma readings, but significantly negatively related to the presence of a crawlspace foundation and its combination with a slab. The findings suggest that fault mapping and in situ gamma ray measurements, coupled with analysis of foundation types and delineation of hot spots, may be used to prioritize areas for radon screening.

Exploring the relationship between social deprivation and domestic radon levels in the East Midlands, UK.

The natural radioactive gas radon is widely present in the built environment and at high concentrations is associated with enhanced risk of lung-cancer. This risk is significantly enhanced for habitual smokers. Although populations with higher degrees of social deprivation are frequently exposed to higher levels of many health-impacting pollutants, a recent study suggests that social deprivation in the UK is associated with lower radon concentrations. The analysis reported here, based on published data on social deprivation and domestic radon in urban and rural settings in the English East Midlands, identifies a weak association between increasing deprivation and lower radon areas. This is attributed to the evolution of the major urban centres on low-permeability, clay-rich alluvial soils of low radon potential. In addition, the predominance of high-rise dwellings in towns and cities will further reduce average exposure to radon in populations in those areas.

Analytical method for evaluating (and correcting) the impact of outdoor radon concentration on the estimates of percentage of dwellings exceeding reference levels.

Outdoor radon concentration contributes to indoor radon levels, generally causing a shift from lognormal distribution of measured radon concentration data distribution, and it makes more challenging the estimation of radon distribution parameters on the basis of the lognormal assumption. In particular, lognormal assumption with no correction could lead to a significantly biased estimate of the percentage of dwellings exceeding a certain level, e.g. a reference level (RL), since this is based on biased estimates of geometric mean (GM) and geometric standard deviation (GSD) of radon concentration distribution. Subtracting to each measured data a constant outdoor radon level can usually compensate data distribution departure from log-normality (except for low radon levels), if the appropriate outdoor level value is chosen by means of a lognormal fit of the data. This approach - already (but not always) used in literature - cannot be applied in cases where all the data of radon concentrations are not available (e.g., for a review study). For these cases, this work presents an analytical method to quantitatively evaluate and correct the impact of outdoor on the lognormal distribution parameter estimates and, in particular, on the percentages of dwellings exceeding radon reference levels. The proposed method is applied to a number of possible situations, with different values of outdoor radon level, GM and GSD. The results show that outdoor radon levels generally produce an underestimation of the actual GSD parameter, which increases as the outdoor level increases, and in the worse cases, could lead to an underestimation higher than 50%. Consequently, if the outdoor contribution is not properly taken into account, the percentage of dwellings exceeding a certain RL is almost always underestimated, even by 80%-90% for RL equal to 300 Bq/m3. This could have implications for the classification of areas as regards radon concentration and for the estimation of avertable lung cancers attributable to radon levels higher than some possible RLs.

Estimation of radon diffusivity tensor for fractured rocks in cave mines using a discrete fracture network model.

This study develops a numerical model for predicting radon effective diffusivity tensor for fractured rocks using a two dimensional discrete fracture network (DFN) model. This is motivated by the limitations of existing techniques in predicting the radon diffusion coefficient for the fractured zones of cave mines. These limitations include access to the fractured zones for the purpose of conducting field studies as well as replication of the degree of fracturing in these zones for laboratory studies. The caving of a rock mass involves the fracturing and breaking of intact and naturally fractured rock, which creates migration pathways for radon gas trapped within uranium-rich rock. Therefore, this study develops a stochastic DFN model with equations derived from radon transport to predict diffusivity. Our simulation results reveal the establishment of a representative elementary volume (REV) for diffusivity tensor; approximately equal principal and cross diffusivity magnitudes for each of the DFN domain; a range of diffusivity with porosity (calculated based on the fractures in the domain); and a significant effect of fracture density on diffusivity tensor. These results are essential in developing proactive measures for mitigation of radon gas in cave mines.

Assessment of radon concentrations and exposure doses in dwellings surrounding a high capacity gas turbine power station using passive measurements and dispersion modeling.

A continuous passive measurement of indoor and outdoor radon R222n, concentration is carried out in the nearby residential areas surrounding a high capacity gas-fired power station. The mean value for indoor measurements was 26.5 ±â€¯1.75 Bq/m3 that is below the worldwide indoor mean of 40 Bq/m3 and for outdoor was 39.4 ±â€¯4.04 Bq/m3 which is higher than the worldwide average outdoor radon concentration of 10 Bq/m3. The annual estimated effective doses were found to vary from 0.54 to 1.05 mSv/y with an average value of 0.67 ±â€¯0.04 mSv/y for indoor dose and from 0.23 to 0.57 mSv/y with an average value of 0.37 ±â€¯0.03 mSv/y for outdoor dose with an overall mean annual effective dose of 1.03 mSv/y. Furthermore, the measured and modeled radon excess levels due to plant operation, both, show that the effect of power plant emission on atmospheric radon levels in the surrounding region is not significant.

A practical approach to limit the radiation dose from building materials applied in dwellings, in compliance with the Euratom Basic Safety Standards.

Individuals receive a significant part of their radiation exposure indoors. We anticipate that this exposure is likely to increase in the near future, due to a growing use in the building industry of recycled materials and materials previously regarded as waste. Such materials often contain elevated levels of natural radionuclides. Directive 2013/59/Euratom ('Basic Safety Standards', BSS) pays comprehensive attention to indoor exposure from natural radionuclides, but proper implementation of all corresponding BSS regulations is not straightforward, especially when regarding the regulation of building materials containing so-called Annex XIII materials. In this paper, we discuss the most relevant deficiencies in the BSS and present a practical approach to cope with these. Our most important observation is that adequate methods for assessing the annual dose due to gamma radiation from building materials are not provided by the BSS. This is in particular difficult because compliance of single building materials has to be tested, but the corresponding BSS reference level refers to gamma radiation emitted by all building materials present in a room. Based on a simple model of three layers of building materials, we present a set of operational conditions for building materials, either used for construction purposes ('bulk layers') or for the finishing of walls, floors and ceilings ('superficial layers'). Any customary combination of building materials meeting these conditions will stay below the BSS reference level for gamma radiation. This statement holds for the middle of a reference room, but is not always the case close to the walls, especially when low density materials with a relatively high content of natural radionuclides are present at the inner side of the room. This can be avoided by applying more strict conditions for those kind of materials than presented in this paper. We further focus on the indoor exposure to thoron progeny. Building materials that pass the test for gamma radiation can still be a significant source for indoor air concentrations of thoron progeny. When the average annual thoron inhalation dose were to be restricted to 1 mSv a-1 - a level comparable to the BSS reference level for gamma radiation - the activity concentration of Ra-224 in (especially porous) building materials used for wall finishing purposes should be limited to a value of typically 50 Bq kg-1. Even if our suggested approach of the BSS regulations is fully implemented, it still allows for a significant increase in the average radiation exposure in dwellings due to external radiation and thoron progeny. However, the situation will be worse if a less strict interpretation of the BSS regulations will be applied.

Evidence for a recent increase in delivery of atmospheric 210Pb to Oualidia lagoon, coastal Morocco.

Two sediment cores were collected from the Oualidia lagoon, on the Atlantic coast of Morocco, and analyzed for 210Pb and 137Cs activity by gamma spectrometry. The 210Pb profiles were characterized by high activity at specific depths in each core, which were attributed to substantial increases in atmospheric 210Pb input to the sediment. A modified CRS model was applied to develop age-depth relations (chronologies) for the cores and calculate sediment accumulation rates, taking into account changing unsupported 210Pb delivery and specifying the year when the increase began. Calculated 210Pb inventories (activity/area) and fluxes (activity/area/time) depend strongly on sedimentation rates and were much higher than mean values in similar coastal systems worldwide. We attempted to use 137Cs as a time marker to support the modified CRS chronologies for both cores. The 137Cs profiles, however, were affected by post-depositional cesium migration in the sediment which made it difficult to identify the 1963 atmospheric bomb-testing peak, especially in the core with low sedimentation rate. We conclude that the high activities of 210Pb detected at specific depths in the Oualidia lagoon sediment cores are a consequence of decay of radioactive 222Rn, which displayed periodic high concentrations in the overlying atmosphere.

18 years of continuous observation of tritium and atmospheric precipitations in Ramnicu Valcea (Romania): A time series analysis.

To get more information on the origin of tritium and to evidence any possible presence of anthropogenic sources, between January 1999 and December 2016, the precipitation level and tritium concentration were monthly recorded and investigated by the Cryogenic Institute of Ramnicu Valcea, Romania. Compared with similar data covering a radius of about 1200 km westward, the measurements gave similar results concerning the time evolution of tritium content and precipitation level for the entire time interval excepting the period between 2009 and 2011 when the tritium concentrations showed a slight increase, most probable due to the activity of neighboring experimental pilot plant for tritium and deuterium separation. Regardless this fact, all data pointed towards a steady tendency of tritium concentrations to decrease with an annual rate of about 1.4 ±â€¯0.05%. The experimental data on precipitation levels and tritium concentrations form two complete time series whose time series analysis showed, at p < 0.01, the presence of a single one-year periodicity whose coincident maximums which correspond to late spring - early summer months suggest the existence of the Spring Leak mechanism with a possible contribution of the soil moisture remobilization during the warm period.

Radon-222 related influence on ambient gamma dose.

Ambient gamma dose, radon, and rainfall have been monitored in southern Bucharest, Romania, from 2010 to 2016. The seasonal cycle of background ambient gamma dose peaked between July and October (100-105 nSv h-1), with minimum values in February (75-80 nSv h-1), the time of maximum snow cover. Based on 10 m a.g.l. radon concentrations, the ambient gamma dose increased by around 1 nSv h-1 for every 5 Bq m-3 increase in radon. Radon variability attributable to diurnal changes in atmospheric mixing contributed less than 15 nSv h-1 to the overall variability in ambient gamma dose, a factor of 4 more than synoptic timescale changes in air mass fetch. By contrast, precipitation-related enhancements of the ambient gamma dose were 15-80 nSv h-1. To facilitate routine analysis, and account in part for occasional equipment failure, an automated method for identifying precipitation spikes in the ambient gamma dose was developed. Lastly, a simple model for predicting rainfall-related enhancement of the ambient gamma dose is tested against rainfall observations from events of contrasting duration and intensity. Results are also compared with those from previously published models of simple and complex formulation. Generally, the model performed very well. When simulations underestimated observations the absolute difference was typically less than the natural variability in ambient gamma dose arising from atmospheric mixing influences. Consequently, combined use of the automated event detection method and the simple model of this study could enable the ambient gamma dose "attention limit" (which indicates a potential radiological emergency) to be reduced from 200 to 400% above background to 25-50%.

Indoor radon regulation using tabulated values of temporal radon variation.

Mass measurements of indoor radon concentrations have been conducted for about 30 years. In most of the countries, a national reference/action/limit level is adopted, limiting the annual average indoor radon (AAIR) concentration. However, until now, there is no single and generally accepted international protocol for determining the AAIR with a known confidence interval, based on measurements of different durations. Obviously, as the duration of measurements increases, the uncertainty of the AAIR estimation decreases. The lack of the information about the confidence interval of the determined AAIR level does not allow correct comparison with the radon reference level. This greatly complicates development of an effective indoor radon measurement protocol and strategy. The paper proposes a general principle of indoor radon regulation, based on the simple criteria widely used in metrology, and introduces a new parameter - coefficient of temporal radon variation KV(t) that depends on the measurement duration and determines the uncertainty of the AAIR. An algorithm for determining KV(t) based on the results of annual continuous radon monitoring in experimental rooms is proposed. Included are indoor radon activity concentrations and equilibrium equivalent concentration (EEC) of radon progeny. The monitoring was conducted in 10 selected experimental rooms located in 7 buildings, mainly in the Moscow region (Russia), from 2006 to 2013. The experimental and tabulated values of KV(t) and also the values of the coefficient of temporal EEC variation depending on the mode and duration of the measurements were obtained. The recommendations to improve the efficiency and reliability of indoor radon regulation are given. The importance of taking into account the geological factors is discussed. The representativity of the results of the study is estimated and the approach for their verification is proposed.

Comparisons between a new point kernel-based scheme and the infinite plane source assumption method for radiation calculation of deposited airborne radionuclides from nuclear power plants.

Radiation from the deposited radionuclides is indispensable information for environmental impact assessment of nuclear power plants and emergency management during nuclear accidents. Ground shine estimation is related to multiple physical processes, including atmospheric dispersion, deposition, soil and air radiation shielding. It still remains unclear that whether the normally adopted "infinite plane" source assumption for the ground shine calculation is accurate enough, especially for the area with highly heterogeneous deposition distribution near the release point. In this study, a new ground shine calculation scheme, which accounts for both the spatial deposition distribution and the properties of air and soil layers, is developed based on point kernel method. Two sets of "detector-centered" grids are proposed and optimized for both the deposition and radiation calculations to better simulate the results measured by the detectors, which will be beneficial for the applications such as source term estimation. The evaluation against the available data of Monte Carlo methods in the literature indicates that the errors of the new scheme are within 5% for the key radionuclides in nuclear accidents. The comparisons between the new scheme and "infinite plane" assumption indicate that the assumption is tenable (relative errors within 20%) for the area located 1 km away from the release source. Within 1 km range, the assumption mainly causes errors for wet deposition and the errors are independent of rain intensities. The results suggest that the new scheme should be adopted if the detectors are within 1 km from the source under the stable atmosphere (classes E and F), or the detectors are within 500 m under slightly unstable (class C) or neutral (class D) atmosphere. Otherwise, the infinite plane assumption is reasonable since the relative errors induced by this assumption are within 20%. The results here are only based on theoretical investigations. They should be further thoroughly evaluated with real measurements in the future.

Predicted cumulative dose to firefighters and the offsite public from natural and anthropogenic radionuclides in smoke from wildland fires at the Savannah River Site, South Carolina USA.

The contaminated ground surface at Savannah River Site (SRS) is a result of the decades of work that has been performed maintaining the country's nuclear stockpile and performing research and development on nuclear materials. The volatilization of radionuclides during wildfire results in airborne particles that are dispersed within the smoke plume and may result in doses to downwind firefighters and the public. To better understand the risk that these smoke plumes present, we have characterized four regions at SRS in terms of their fuel characteristics and radiological contamination on the ground. Combined with general meteorological conditions describing typical and extreme burn conditions, we have simulated potential fires in these regions and predicted the potential radiological dose that could be received by firefighting personnel and the public surrounding the SRS. In all cases, the predicted cumulative dose was a small percent of the US Department of Energy regulatory limit (0.25 mSv). These predictions were conservative and assumed that firefighters would be exposed for the duration of their shift and the public would be exposed for the entire day over the duration of the burn. Realistically, firefighters routinely rotate off the firefront during their shift and the public would likely remain indoors much of the day. However, we show that even under worst-case conditions the regulatory limits are not exceeded. We can infer that the risks associated with wildfires would not be expected to cause cumulative doses above the level of concern to either responding personnel or the offsite public.

High Radon Areas and lung cancer prevalence: Evidence from Ireland.

This paper examined the relationship between radon risk and lung cancer prevalence using a novel dataset combining spatially-coded survey data with a radon risk map. A logit model was employed to test for significant associations between a high risk of indoor radon and lung cancer prevalence using data on 5590 people aged 50+ from The Irish Longitudinal Study on Ageing (TILDA) and radon risk data from Ireland's Environmental Protection Agency (EPA). The use of data at the individual level allowed a wide range of potentially confounding factors (such as smoking) to be included. Results indicate that those who lived in an area in which 10%-20% of households were above the national reference level (200 Bq/m3) were 2.9-3.1 times more likely to report a lung cancer diagnosis relative to those who lived in areas in which less than 1% of households were above the national reference level.

A review of numerical models to predict the atmospheric dispersion of radionuclides.

The field of atmospheric dispersion modeling has evolved together with nuclear risk assessment and emergency response systems. Atmospheric concentration and deposition of radionuclides originating from an unintended release provide the basis of dose estimations and countermeasure strategies. To predict the atmospheric dispersion and deposition of radionuclides several numerical models are available coupled with numerical weather prediction (NWP) systems. This work provides a review of the main concepts and different approaches of atmospheric dispersion modeling. Key processes of the atmospheric transport of radionuclides are emission, advection, turbulent diffusion, dry and wet deposition, radioactive decay and other physical and chemical transformations. A wide range of modeling software are available to simulate these processes with different physical assumptions, numerical approaches and implementation. The most appropriate modeling tool for a specific purpose can be selected based on the spatial scale, the complexity of meteorology, land surface and physical and chemical transformations, also considering the available data and computational resource. For most regulatory and operational applications, offline coupled NWP-dispersion systems are used, either with a local scale Gaussian, or a regional to global scale Eulerian or Lagrangian approach. The dispersion model results show large sensitivity on the accuracy of the coupled NWP model, especially through the description of planetary boundary layer turbulence, deep convection and wet deposition. Improvement of dispersion predictions can be achieved by online coupling of mesoscale meteorology and atmospheric transport models. The 2011 Fukushima event was the first large-scale nuclear accident where real-time prognostic dispersion modeling provided decision support. Dozens of dispersion models with different approaches were used for prognostic and retrospective simulations of the Fukushima release. An unknown release rate proved to be the largest factor of uncertainty, underlining the importance of inverse modeling and data assimilation in future developments.

Radon and NO2 levels and related environmental factors in 100 underground subway platforms over two-year period.

In this study, the environmental factors that affect radon (Rn) and nitrogen dioxide (NO2) levels in subway-station underground platforms are evaluated, and the outdoor NO2 levels are compared with those obtained for the underground platforms. The Rn and NO2 levels from May 2013 to September 2015 are determined for lines 1-4 of the Seoul Metro, via calculation of the arithmetic means of the Rn and NO2 levels with their standard deviations (SDs). The underground Rn levels in 2013 are found to be significantly higher than those recorded in 2015 for the Seoul Metro. In addition, the Rn levels are related to the station depth and construction year. Further, the underground NO2 levels are shown to be significantly higher than the outdoor levels for all four Seoul Metro subway lines. The Rn levels are also found to vary significantly between months, and are shown to increase gradually with depth from 8 to 20 m. The Rn levels are also higher for stations constructed in the 1980s. Therefore, stricter monitoring of Rn level may be required for stations constructed in the 1980s and/or having platform depths within the 8-20 m range. Island-type platform stations based on granite areas may also require careful attention.

Indoor radon measurements in south west England explained by topsoil and stream sediment geochemistry, airborne gamma-ray spectroscopy and geology.

Predictive mapping of indoor radon potential often requires the use of additional datasets. A range of geological, geochemical and geophysical data may be considered, either individually or in combination. The present work is an evaluation of how much of the indoor radon variation in south west England can be explained by four different datasets: a) the geology (G), b) the airborne gamma-ray spectroscopy (AGR), c) the geochemistry of topsoil (TSG) and d) the geochemistry of stream sediments (SSG). The study area was chosen since it provides a large (197,464) indoor radon dataset in association with the above information. Geology provides information on the distribution of the materials that may contribute to radon release while the latter three items provide more direct observations on the distributions of the radionuclide elements uranium (U), thorium (Th) and potassium (K). In addition, (c) and (d) provide multi-element assessments of geochemistry which are also included in this study. The effectiveness of datasets for predicting the existing indoor radon data is assessed through the level (the higher the better) of explained variation (% of variance or ANOVA) obtained from the tested models. A multiple linear regression using a compositional data (CODA) approach is carried out to obtain the required measure of determination for each analysis. Results show that, amongst the four tested datasets, the soil geochemistry (TSG, i.e. including all the available 41 elements, 10 major - Al, Ca, Fe, K, Mg, Mn, Na, P, Si, Ti - plus 31 trace) provides the highest explained variation of indoor radon (about 40%); more than double the value provided by U alone (ca. 15%), or the sub composition U, Th, K (ca. 16%) from the same TSG data. The remaining three datasets provide values ranging from about 27% to 32.5%. The enhanced prediction of the AGR model relative to the U, Th, K in soils suggests that the AGR signal captures more than just the U, Th and K content in the soil. The best result is obtained by including the soil geochemistry with geology and AGR (TSG + G + AGR, ca. 47%). However, adding G and AGR to the TSG model only slightly improves the prediction (ca. +7%), suggesting that the geochemistry of soils already contain most of the information given by geology and airborne datasets together, at least with regard to the explanation of indoor radon. From the present analysis performed in the SW of England, it may be concluded that each one of the four datasets is likely to be useful for radon mapping purposes, whether alone or in combination with others. The present work also suggest that the complete soil geochemistry dataset (TSG) is more effective for indoor radon modelling than using just the U (+Th, K) concentration in soil.

Nuclear accident consequence assessment in Hong Kong using JRODOS.

The JRODOS (Java-based Real-time Online DecisiOn Support) is a decision support system for off-site emergency management for releases of radioactive material into the environment. This paper documents the application of JRODOS by the Hong Kong Observatory in accident consequence assessment and emergency preparedness studies. For operational considerations, the most computational efficient dispersion model in JRODOS, ATSTEP, is adopted. Verification studies for JRODOS's ATSTEP model have been conducted. Comparison with tracer experiment results showed that under neutral atmospheric conditions and distances up to 50 km, the JRODOS simulation outputs were in general of the same order of magnitude with the tracer data. To further evaluate the capability of JRODOS in short-range simulation, a case study on the Fukushima nuclear power plant accident was also carried out. JRODOS was able to produce realistic simulation results which were comparable to the actual airborne monitoring data of the Cs-137 ground deposition from the Fukushima accident. Furthermore, the results of a comprehensive study to assess the potential consequences of accidents at a nearby nuclear power station are presented. Simulation using the French S3 source term for the Guangdong Nuclear Power Station at Daya Bay showed that the projected effective doses within Hong Kong remain far below the IAEA generic criteria of projected dose for urgent protective actions in sheltering/evacuation, while the projected equivalent dose in thyroid may meet the IAEA generic criteria for use of thyroid blocking agent at some areas in the northeastern part of Hong Kong, at distances of up to about 40 km from Daya Bay depending on the prevailing weather conditions in different seasons.