Application of the Bayesian approach for derivation of PDFs for concentration ratio values

Transfer of radionuclides through ecological systems: Lessons learned from 10 years of research within CERAD CoE

Norway's Centre of Excellence for Environmental Radioactivity (CERAD) research programme included studies on transfer of radionuclides in various ecosystems within the context of environmental risk assessment. This article provides highlights from 10 years of research within this topic and summarises lessons learnt from the process. The scope has been extensive, involving laboratory-based experiments, field studies and the implementation of transfer models quantifying radionuclide uptake directly from the surrounding environment and via food chains. Field studies have had a global span and have, inter alia, covered sites contaminated with radionuclides associated with particles, ranging from nanoparticles to fragments, due to nuclear accidents (e.g., Chornobyl and Fukushima accidents) along with sites having enhanced levels of naturally occurring radioactive materials (e.g., Fen Complex in Norway and Taboshar in Tajikistan). Focus has been put on speciation and kinetics in determining radionuclide behavior and fate as well as on the influence of environmental factors that are potentially critical for the transfer of radionuclides. In particular, seasonal factors have been shown to greatly affect the dynamics of 137Cs and 90Sr bioaccumulation and loss in freshwater fish. The work has led to the collation of organism-specific (i) parameters important for kinetic models, i.e., uptake and depuration rates, and (ii) steady-state concentration ratios, CRs, where the use of stable analogue CRs as proxies for radionuclides has been brought into question. Dynamic models have been developed and applied for radiocaesium transfer to reindeer, radionuclide transfer in Arctic marine systems, transfer to fish via water and feed and commonly used agricultural food-chain transfer models applied in the context of nuclear emergency preparedness. The CERAD programme should contribute substantially to the scientific community's understanding of radionuclide transfer in environmental systems.

Identifiability of sorption parameters in stirred flow-through reactor experiments and their identification with a Bayesian approach

This paper addresses the methodological conditions -particularly experimental design and statistical inference- ensuring the identifiability of sorption parameters from breakthrough curves measured during stirred flow-through reactor experiments also known as continuous flow stirred-tank reactor (CSTR) experiments. The equilibrium-kinetic (EK) sorption model was selected as nonequilibrium parameterization embedding the K_d approach. Parameter identifiability was studied formally on the equations governing outlet concentrations. It was also studied numerically on 6 simulated CSTR experiments on a soil with known equilibrium-kinetic sorption parameters. EK sorption parameters can not be identified from a single breakthrough curve of a CSTR experiment, because K_d,1 and k^- were diagnosed collinear. For pairs of CSTR experiments, Bayesian inference allowed to select the correct models of sorption and error among sorption alternatives. Bayesian inference was conducted with SAMCAT software (Sensitivity Analysis and Markov Chain simulations Applied to Transfer models) which launched the simulations through the embedded simulation engine GNU-MCSim, and automated their configuration and post-processing. Experimental designs consisting in varying flow rates between experiments reaching equilibrium at contamination stage were found optimal, because they simultaneously gave accurate sorption parameters and predictions. Bayesian results were comparable to maximum likehood method but they avoided convergence problems, the marginal likelihood allowed to compare all models, and credible interval gave directly the uncertainty of sorption parameters θ. Although these findings are limited to the specific conditions studied here, in particular the considered sorption model, the chosen parameter values and error structure, they help in the conception and analysis of future CSTR experiments with radionuclides whose kinetic behaviour is suspected.

A new version of the ERICA tool to facilitate impact assessments of radioactivity on wild plants and animals

A new version of the ERICA Tool (version 1.2) was released in November 2014; this constitutes the first major update of the Tool since release in 2007. The key features of the update are presented in this article. Of particular note are new transfer databases extracted from an international compilation of concentration ratios (CRwo-media) and the modification of 'extrapolation' approaches used to select transfer data in cases where information is not available. Bayesian updating approaches have been used in some cases to draw on relevant information that would otherwise have been excluded in the process of deriving CRwo-media statistics. All of these efforts have in turn led to the requirement to update Environmental Media Concentration Limits (EMCLs) used in Tier 1 assessments. Some of the significant changes with regard to EMCLs are highlighted.

Foliar interception of radionuclides in dry conditions: a meta-analysis using a Bayesian modeling approach

Uncertainty on the parameters that describe the transfer of radioactive materials into the (terrestrial) environment may be characterized thanks to datasets such as those compiled within International Atomic Energy Agency (IAEA) documents. Nevertheless, the information included in these documents is too poor to derive a relevant and informative uncertainty distribution regarding dry interception of radionuclides by the pasture grass and the leaves of vegetables. In this paper, 145 sets of dry interception measurements by the aboveground biomass of specific plants were collected from published scientific papers. A Bayesian meta-analysis was performed to derive the posterior probability distributions of the parameters that reflect their uncertainty given the collected data. Four competing models were compared in terms of both fitting performances and predictive abilities to reproduce plausible dry interception data. The asymptotic interception factor, applicable whatever the species and radionuclide to the highest aboveground biomass values (e.g. mature leafy vegetables), was estimated with the best model, to be 0.87 with a 95% credible interval (0.85, 0.89).

Evaluating variability and uncertainty in radiological impact assessment using SYMBIOSE

SYMBIOSE is a modelling platform that accounts for variability and uncertainty in radiological impact assessments, when simulating the environmental fate of radionuclides and assessing doses to human populations. The default database of SYMBIOSE is partly based on parameter values that are summarized within International Atomic Energy Agency (IAEA) documents. To characterize uncertainty on the transfer parameters, 331 Probability Distribution Functions (PDFs) were defined from the summary statistics provided within the IAEA documents (i.e. sample size, minimal and maximum values, arithmetic and geometric means, standard and geometric standard deviations) and are made available as spreadsheet files. The methods used to derive the PDFs without complete data sets, but merely the summary statistics, are presented. Then, a simple case-study illustrates the use of the database in a second-order Monte Carlo calculation, separating parametric uncertainty and inter-individual variability.

Establishing a database of radionuclide transfer parameters for freshwater wildlife

Environmental assessments to evaluate potentials risks to humans and wildlife often involve modelling to predict contaminant exposure through key pathways. Such models require input of parameter values, including concentration ratios, to estimate contaminant concentrations in biota based on measurements or estimates of concentrations in environmental media, such as water. Due to the diversity of species and the range in physicochemical conditions in natural ecosystems, concentration ratios can vary by orders of magnitude, even within similar species. Therefore, to improve model input parameter values for application in aquatic systems, freshwater concentration ratios were collated or calculated from national grey literature, Russian language publications, and refereed papers. Collated data were then input into an international database that is being established by the International Atomic Energy Agency. The freshwater database enables entry of information for all radionuclides listed in ICRP (1983), in addition to the corresponding stable elements, and comprises a total of more than 16,500 concentration ratio (CRwo-water) values. Although data were available for all broad wildlife groups (with the exception of birds), data were sparse for many organism types. For example, zooplankton, crustaceans, insects and insect larvae, amphibians, and mammals, for which there were CRwo-water values for less than eight elements. Coverage was most comprehensive for fish, vascular plants, and molluscs. To our knowledge, the freshwater database that has now been established represents the most comprehensive set of CRwo-water values for freshwater species currently available for use in radiological environmental assessments.

Approaches to providing missing transfer parameter values in the ERICA Tool--how well do they work?

A required parameter for the ERICA Tool is the concentration ratio (CR), which is used to describe the transfer from environmental media to a range of organisms. For the original parameterisation of the ERICA Tool, 60% of these values were derived using a variety of extrapolation approaches, including the application of allometric models, the use of values for a similar organism or element with similar biogeochemical behaviour and the use of values from a different ecosystem. Although similar approaches are applied in other assessment systems, there has been little attempt to see how well these approaches perform. In this paper, CR values in the ERICA Tool derived using extrapolation approaches are compared to more recently available empirical data from the IAEA wildlife transfer database. The primary purpose of the default CR database in the ERICA Tool, and other models, is to enable the user to conduct conservative screening assessments. Conservatism was therefore introduced to the analyses by selecting the 95th percentile CR values for subsequent calculations. The extrapolation methodologies are not guaranteed to provide conservative estimates of empirical 95th percentile CRs. For the terrestrial ecosystem, the extrapolation methods provide underpredictions of empirical 95th percentiles as often as they produce overpredictions. In a few cases the underestimation of CR values, when considering all ecosystems, is substantial - by orders of magnitude - which is clearly unacceptable for a screening assessment. Thus, although extrapolation approaches will remain an essential component of screening assessments in the future, because data gaps will always be present, diligence is important in their application. Finally, by synthesizing the results from the current analyses and through other considerations, some recommendations are provided with regards to modifying the original guidance on use of extrapolation approaches in the ERICA Tool.

An international database of radionuclide concentration ratios for wildlife: development and uses

A key element of most systems for assessing the impact of radionuclides on the environment is a means to estimate the transfer of radionuclides to organisms. To facilitate this, an international wildlife transfer database has been developed to provide an online, searchable compilation of transfer parameters in the form of equilibrium-based whole-organism to media concentration ratios. This paper describes the derivation of the wildlife transfer database, the key data sources it contains and highlights the applications for the data.

Evaluating summarised radionuclide concentration ratio datasets for wildlife

Concentration ratios (CR(wo-media)) are used in most radioecological models to predict whole-body radionuclide activity concentrations in wildlife from those in environmental media. This simplistic approach amalgamates the various factors influencing transfer within a single generic value and, as a result, comparisons of model predictions with site-specific measurements can vary by orders of magnitude. To improve model predictions, the development of 'condition-specific' CR(wo-media) values has been proposed (e.g. for a specific habitat). However, the underlying datasets for most CR(wo-media) value databases, such as the wildlife transfer database (WTD) developed within the IAEA EMRAS II programme, include summarised data. This presents challenges for the calculation and subsequent statistical evaluation of condition-specific CR(wo-media) values. A further complication is the common use of arithmetic summary statistics to summarise data in source references, even though CR(wo-media) values generally tend towards a lognormal distribution and should, therefore, be summarised using geometric statistics. In this paper, we propose a statistically-defensible and robust method for reconstructing underlying datasets to calculate condition-specific CR(wo-media) values from summarised data and deriving geometric summary statistics. This method is applied to terrestrial datasets from the WTD. Statistically significant differences in sub-category CR(wo-media) values (e.g. mammals categorised by feeding strategy) were identified, which may justify the use of these CR(wo-media) values for specific assessment contexts. However, biases and limitations within the underlying datasets of the WTD explain some of these differences. Given the uncertainty in the summarised CR(wo-media) values, we suggest that the CR(wo-media) approach to estimating transfer is used with caution above screening-level assessments.

Exploring methods to prioritise concentration ratios when estimating weighted absorbed dose rates to terrestrial Reference Animals and Plants

The ICRP and IAEA have recently reported Concentration Ratio values (CRwo-media--equilibrium radionuclide activity concentration in whole organism divided by that in media) for Reference Animals and Plants (RAPs) and a wide range of organism groups, respectively, based on a common online database. Given the large number of data gaps in both publications, there is a need to develop methods for identifying the relative importance of improving currently available CR(wo-media) values. A simple, transparent approach involving the derivation and comparison of predicted internal and external weighted absorbed dose rates for radionuclides considered by ICRP (2009) for terrestrial RAPs is presented. Using the approach of applying a reference value of CR(wo-soil) = 1 or using the maximum reported values where CR(wo-soil) >1, we provisionally identify terrestrial radionuclide RAP combinations which could be considered low priority, notably: Ca, Cr and Ni consistently; Mn for all RAPs except Deer and Pine Tree; and Tc for all RAPs but Wild Grass. Equally, we can systematically identify high priority elements and radioisotopes, which largely, but not exclusively, consist of alpha-emitters (especially isotopes of Ra and Th, but also consistently Am, Cf, Cm, Np, Pa, Po, Pu, U). The analysis highlights the importance of the radiation weighting factor default assumption of 10 for alpha-emitters in the ERICA Tool when comparing the magnitude of the internal dose and trying to identify high priority RAP-isotope combinations. If the unweighted Dose Conversion Coefficient (DCC) values are considered, those for alpha-emitters are often one order of magnitude higher than those due to some beta-gamma emitters for terrestrial RAPs, whereas with the radiation weighting factor applied they are two orders of magnitude higher.