Numerical transport models are important tools for nuclear emergency decision makers in that they rapidly provide early predictions of dispersion of released radionuclides, which is key information to determine adequate emergency protective measures. They can also help us understand and describe environmental processes and can give a comprehensive assessment of transport and transfer of radionuclides in the environment. Transport of radionuclides in air and ocean is affected by a number of different physico-chemical processes. Along with uncertainty arising from the input data, the model estimates will therefore involve a combination of numerous uncertain factors, caused by knowledge gaps and assumptions in the model system. As discussed in this paper, the major sources to uncertainty affecting the model results are release descriptions, driving data, process descriptions and parameters. Here, we give a synthesis of the most important improvements in atmospheric and marine models achieved through the CERAD programme. In the atmospheric transport model, an important improvement has been inclusion of uncertainties in the dispersion estimates. Recent developments also include adaption to high resolution forcing data and ensemble forecasts, inversion methods and long term analyses. Case studies clearly show improved predictions from ensemble mean values compared to single deterministic runs, and promises for future upgrades of preparedness decision support systems. A major improvement in the marine model system was implementation of dynamic speciation including transformation of species, identifying particle size and parameterizations to be key factors affecting radionuclide distribution. The model system was further developed in a case study involving the impact of changing environmental factors on the transport of aluminium river run-off to an estuary in southeastern Norway. Suggestions for future improvements include implementation of an operational preparedness model for marine transport, better quantification of uncertainties using ensemble methods and improved source identification with further development of inverse transport.

Experience from earlier nuclear accidents has clearly shown the need for maintaining and developing appropriate modelling capabilities. Dealing with complex issues such as human exposure following a nuclear accident necessitates the implementation of a set of interconnected models such as FDMT. FDMT is an integrated module within the two main European decision support systems for radiological emergency preparedness, ARGOS and JRODOS, to simulate the transfer of radionuclides along terrestrial food chains and to predict their activity concentrations in foodstuffs. In order to make the module more fit-for-purpose, FDMT has been implemented in a new modelling platform (ECOLEGO) which provides a high degree of flexibility with regard to conducting developmental work. This paper presents improvements in FDMT further through either the incorporation of new models or further elaboration of existing ones, as well as updates in default parameters. Models have also been made more fit-for purpose through consideration of regional-specific parameters. Specific improvements include modelling developments related to dry deposition, radioactive particle weathering, radiocaesium transfer influenced by soil characteristics and, for a region specific case, animal uptake. In addition, the paper presents new pathways and parameters (and updated values) to be considered for making FDMT more adapted for Norwegian conditions. Overall, the improvements made in the present work should significantly reduce the uncertainties associated with the outputs of the FDMT models.

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.

Methods for determining the radiation dose received by exposed biota require major improvements to reduce uncertainties and increase precision. We share our experiences in attempting to quantify external dose rates to free-ranging wildlife using GPS-coupled dosimetry methods. The manuscript is a primer on fundamental concepts in wildlife dosimetry in which the complexities of quantifying dose rates are highlighted, and lessons learned are presented based on research with wild boar and snakes at Fukushima, wolves at Chornobyl, and reindeer in Norway. GPS-coupled dosimeters produced empirical data to which numerical simulations of external dose using computer software were compared. Our data did not support a standing paradigm in risk analyses: Using averaged soil contaminant levels to model external dose rates conservatively overestimate the dose to individuals within a population. Following this paradigm will likely lead to misguided recommendations for risk management. The GPS-dosimetry data also demonstrated the critical importance of how modeled external dose rates are impacted by the scale at which contaminants are mapped. When contaminant mapping scales are coarse even detailed knowledge about each animal's home range was inadequate to accurately predict external dose rates. Importantly, modeled external dose rates based on a single measurement at a trap site did not correlate to actual dose rates measured on free ranging animals. These findings provide empirical data to support published concerns about inadequate dosimetry in much of the published Chernobyl and Fukushima dose-effects research. Our data indicate that a huge portion of that literature should be challenged, and that improper dosimetry remains a significant source of controversy in radiation dose-effect research.

A series of 131I tracer experiments have been conducted at two research stations in Norway, one coastal and one inland to study radioiodine transfer and dynamics in boreal, agricultural ecosystems. The hypothesis tested was that site specific and climatological factors, along with growth stage, would influence foliar uptake of 131I by grass and its subsequent loss. Results showed that the interception fraction varied widely, ranging from 0.007 to 0.83 over all experiments, and showing a strong positive correlation with biomass and stage of growth. The experimental results were compared to various models currently used to predict interception fractions and weathering loss. Results provided by interception models varied in the range of 0.5-2 times of the observed values. Regarding weathering loss, it was demonstrated that double exponential models provided a better fit with the experimental results than single exponential models. Normalising the data activity per unit area to remove bio-dilution effects, and assuming a constant single loss rate gave weathering half-times of 22.8 ± 38.3 and 10.2 ± 8.2 days for the inland and coastal site, respectively. Whilst stable iodine concentrations in grass and soil were significantly higher (by approximately a factor of 5 and 7 times for grass and soil respectively) at the coastal compared to the inland site, it was not possible to deconvolute the influence of this factor on the temporal behaviour of 131I. Nonetheless, stable iodine data allowed us to establish an upper bound on the soil to plant transfer of radioiodine via root uptake and to establish that the pathway was of minor importance in defining 131I activity concentrations in grass compared to direct contamination via interception. Climatological factors (precipitation, wind-speed and temperature) appeared to affect the dynamics of 131I in the system, however the decomposition of these collective influences into specific contributions from each factor remains unresolved and requires further study. The newly acquired data on the interception and weathering of radioiodine in boreal, agricultural ecosystems and the reparametrized models developed from this, substantially improve the toolbox available for Norwegian emergency preparedness in the event of a nuclear accident.

Predictions of radionuclide dose rates to freshwater organisms can be used to evaluate the radiological environmental impacts of releases from uranium mining and milling projects. These predictions help inform decisions on the implementation of mitigation measures. The objective of this study was to identify how dose rate modelling could be improved to reduce uncertainty in predictions to non-human biota. For this purpose, we modelled the activity concentrations of 210Pb, 210Po, 226Ra, 230Th, and 238U downstream of uranium mines and mills in northern Saskatchewan, Canada, together with associated weighted absorbed dose rates for a freshwater food chain using measured activity concentrations in water and sediments. Differences in predictions of radionuclide activity concentrations occurred mainly from the different default partition coefficient and concentration ratio values from one model to another and including all or only some 238U decay daughters in the dose rate assessments. Consequently, we recommend a standardized best-practice approach to calculate weighted absorbed dose rates to freshwater biota whether a facility is at the planning, operating or decommissioned stage. At the initial planning stage, the best-practice approach recommend using conservative site-specific baseline activity concentrations in water, sediments and organisms and predict conservative incremental activity concentrations in these media by selecting concentration ratios based on species similarity and similar water quality conditions to reduce the uncertainty in dose rate calculations. At the operating and decommissioned stages, the best-practice approach recommends relying on measured activity concentrations in water, sediment, fish tissue and whole-body of small organisms to further reduce uncertainty in dose rate estimates. This approach would allow for more realistic but still conservative dose assessments when evaluating impacts from uranium mining projects and making decision on adequate controls of releases.

In response to changing international recommendations and national requirements, a number of assessment approaches, and associated tools and models, have been developed over the last circa 20 years to assess radiological risk to wildlife. In this paper, we summarise international intercomparison exercises and scenario applications of available radiological assessment models for wildlife to aid future model users and those such as regulators who interpret assessments. Through our studies, we have assessed the fitness for purpose of various models and tools, identified the major sources of uncertainty and made recommendations on how the models and tools can best be applied to suit the purposes of an assessment. We conclude that the commonly used tiered or graded assessment tools are generally fit for purpose for conducting screening-level assessments of radiological impacts to wildlife. Radiological protection of the environment (or wildlife) is still a relatively new development within the overall system of radiation protection and environmental assessment approaches are continuing to develop. Given that some new/developing approaches differ considerably from the more established models/tools and there is an increasing international interest in developing approaches that support the effective regulation of multiple stressors (including radiation), we recommend the continuation of coordinated international programmes for model development, intercomparison and scenario testing.

The potential consequences for Norway should a nuclear accident at the Sellafield nuclear site occur, have been of concern for Norwegian authorities for several decades. Meteorological data from a 33-year period and the dispersion model 'SNAP' were used to evaluate meteorological conditions for which atmospheric transport of radionuclides from Sellafield to Norway would lead to the most severe impacts. The worst-case meteorological scenario for Norway, was found on 25th June 1989 for a low elevation (0-800 m) release and on 29th June 2001 for a higher elevation (800-1600 m) release. In both cases the western part of Norway was most affected. In general, the probability for depositions (>10 Bq/m2 of 137Cs) increased about 40% during the autumn and winter compared to the spring and summer months. An influence of climate change on the depositions was analysed, but not verified. Results from a number of simulations were also compared to identify how factors such as radioactive particle characteristics and initial release conditions could affect the predicted radionuclide deposition. The impact on predicted total depositions as well as hot-spot depositions by varying particle density and size as well as release elevation in worst-case scenario simulations amounted to about 40%-50%.

In Europe, the two main nuclear accident response decision support systems in use are ARGOS and JRODOS, both of which make use of the FDMT (Food Chain and Dose Module for Terrestrial pathways) model to simulate the transfer of radioactivity along terrestrial food chains and to predict radionuclide activity concentrations in human foodstuffs. FDMT was originally developed in the early 1990s for Southern German agricultural conditions. Its application to other geographical settings has raised concerns regarding its fitness for purpose. Furthermore, the FDMT model in its original format lacks transparency, flexibility, and the possibility to be run probabilistically. In order to improve FDMT's fitness for purpose and overcome its main shortcomings, it has been implemented in a new modelling platform which incorporates powerful numerical solvers and renders uncertainty and sensitivity analysis possible. The modelling structure of FDMT has been re-configured, and a library configuration has been introduced which offers flexibility in working such that model components can be tested, modified, or replaced easily. The new FDMT allows for the consideration of case/region-specific issues and to make predictions which are of more relevance and of better use with regard to decision making and management of risk. Furthermore, the default databases of FDMT have been updated and wherever possible PDFs have been assigned. In this paper, the transition of FDMT from an old to a new modelling structure is presented along with a demonstration of developments achieved.

The ALLIANCE Strategic Research Agenda (SRA) for radioecology is a living document that defines a long-term vision (20 years) of the needs for, and implementation of, research in radioecology in Europe.The initial SRA, published in 2012, included consultation with a wide range of stakeholders (Hinton et al., 2013).This revised version is an update of the research strategy for identified research challenges, and includes a strategy to maintain and develop the associated required capacities for workforce (education and training) and research infrastructures and capabilities.Beyond radioecology, this SRA update constitutes a contribution to the implementation of a Joint Roadmap for radiation protection research in Europe (CONCERT, 2019a).This roadmap, established under the H2020 European Joint Programme CONCERT, provides a common and shared vision for radiation protection research, priority areas and strategic objectives for collaboration within a European radiation protection research programme to 2030 and beyond.Considering the advances made since the first SRA, this updated version presents research challenges and priorities including identified scientific issues that, when successfully resolved, have the potential to impact substantially and strengthen the system and/or practice of the overall radiation protection (game changers) in radioecology with regard to their integration into the global vision of European research in radiation protection.An additional aim of this paper is to encourage contribution from research communities, end users, decision makers and other stakeholders in the evaluation, further advancement and accomplishment of the identified priorities.

Radioecological models used to make predictions of the radionuclide activity concentrations in human foodstuffs must be sufficiently robust and fit for purpose with uncertainties reduced where practicable. The CONFIDENCE project had a work package with the objective to improve the capabilities of radioecological models and this paper presents the key findings of this work. Recommendations for future radioecological studies/model developments are made based on the findings of the work conducted and consultations with end-users.

When a nuclear accident occurs, decision makers in the affected country/countries would need to act promptly to protect people, the environment and societal interests from harmful impacts of radioactive fallout. The decisions are usually based on a combination of model prognoses, measurements, and expert judgements within in an emergency decision support system (DSS). Large scale nuclear accidents would need predictive models for the atmospheric, terrestrial, freshwater, and marine ecosystems, for the connections between these in terms of radionuclide fluxes, and for the various exposure pathways to both humans and biota. Our study showed that eight different models and DSS modules could be linked to assess the total human and environmental consequences in Norway from a hypothetical nuclear accident, here chosen to be the Sellafield nuclear reprocessing plant. Activity concentrations and dose rates from 137Cs for both humans and the environment via various exposure routes were successfully modelled. The study showed that a release of 1% of the total inventory of 137Cs in the Highly Active Liquor Tanks at Sellafield Ltd is predicted to severely impact humans and the environment in Norway if strong winds are blowing towards the country at the time of an accidental atmospheric release. Furthermore, since the models did not have built-in uncertainty ranges when this Sellafield study was performed, investigations were conducted to identify the key factors contributing to uncertainty in various models and prioritise the ones to focus on in future research.

The Chernobyl nuclear power meltdown that took place in 1986 has left a radioactive contamination legacy that currently severely limits the economic potential of impacted regions including the Polessie State Radioecology Reserve in Southern Belarus. Extensive areas of forested land could potentially become economically viable for firewood and building materials if radioactive contamination, notably 137Cs, could be characterised faster, whilst closely adhering to regulatory limits. Currently, laboursome tree coring and unreliable transfer factors derived from limited soil sampling data are routinely employed in felling decision making, which has financial repercussions owed to the large amounts of waste produced and unnecessary transportation costs. In this study, it is demonstrated that a combination of targeted mobile gamma-ray spectrometry and a newly developed, lead shielded, in situ gamma-ray spectrometry method can significantly speed up the process of characterisation of 137Cs wood activity in the field. For the in situ method, Monte Carlo calibration routines were developed alongside spectral processing procedures to unfold spectra collected in the field allowing for separation of ground and tree spectral components. Isolated contributions from the tree could then be converted to activity. The method was validated at a test facility and then demonstrated at three separate sites with differing contamination levels. This technique showed that single trees could be measured within approximately 20% of the activity compared to conventional tree core data. However, some discrepancies were found which were attributed to under sampling using the tree corer and low count rates at the lowest activity site, prompting the need for further data collection to optimise the method. It was concluded that this real-time approach could be a valuable tool for management of contaminated forested areas, releasing valuable timber and ultimately reducing the risk associated with living and working in these areas.

During the Fukushima Daiichi Nuclear Power Plant (FDNPP) accident in 2011 significant amounts of radiocaesium were released into the atmosphere from the reactor units 1, 2 and 3. This caused a non-uniform deposition, in composition and direction, of 134Cs and 137Cs in the near field (<30 km) from the reactors. In this work, we elucidate the influence of speciation, including radioactive particles, on mobility and potential bioavailability of radiocaesium in soils and sediments from sites located in different directions and distances from the FDNPP. Samples collected in September 2016 were characterized and subjected to sequential chemical extractions and simulated gastrointestinal fluid leaching, and the 137Cs and 134Cs activities were determined in bulk, grain-size and extracted fractions. The results show that radiocaesium was mainly irreversibly bound and in an inert form. Combined, the two forms contained >90% of the activity present in soils and ~84% in sediments. Digital autoradiography revealed that the inert fraction was predominantly associated with heterogeneities, an indication of radioactive particles. The frequency of heterogeneities was correlated with 137Cs activity concentrations, and both were in agreement with the ambient equivalent air doses measured in situ during sampling. Moreover, in situ gamma spectrometry measurements were used in the InSiCal software tool to derive 134Cs and 137Cs surface contamination. Soil activity concentrations and contamination density estimations, decay-corrected to the day of the FDNPP accident, resulted in 134Cs/137Cs ratios that match the reported release and deposition plumes from the reactor units. Overall, these results demonstrate the persistence of the particle contamination in the Fukushima near field and highlight the importance of including radioactive particles in environmental impact assessments.

The objective of this paper is to consider the implications of employing process-based models on predictions for radionuclide activity concentrations in grass and cow milk. The FDMT (Food Chain and Dose Module for Terrestrial Pathways as used in the JRODOS and ARGOS decision support systems) model has been transferred to a modelling platform enabling sub-models to be modified and replaced. Primarily, this has involved invoking process-based models for 137Cs and 90Sr that account for soil chemistry in simulating bioavailability and plant transfer. The implementation of such models can lead to quite dramatic differences in predicted activity concentrations of radionuclides in grass and milk compared to a default FDMT set-up for time periods later than a few weeks post deposition. Considering transfer within a spatial context, by combining information from the outputs of process-based models with illustrative soil maps, leads to the observation that the most elevated 137Cs and 90Sr concentrations in grass and milk might not necessarily occur in areas where deposition is highest. Not accounting for soil type when modelling food chain transfer might lead to the sub-optimal allocation of resources or misidentification of the most vulnerable areas in the long-term after an accidental release.

Measurements of external contaminant exposures on individual wildlife are rare because of difficulties in using contaminant monitors on free-ranging animals. Most wildlife contaminant exposure data are therefore simulated with computer models. Rarely are empirical exposure data available to verify model simulations, or to test fundamental assumptions inherent in exposure assessments. We used GPS-coupled contaminant monitors to quantify external exposures to individual wolves (Canis lupus) living within the Belarus portion of Chernobyl's 30-km exclusion zone. The study provided data on animal location and contaminant exposure every 35 min for 6 months, resulting in similar to 6600 individual locations and Cs-137 external exposure readings per wolf, representing the most robust external exposure data published to date on free ranging animals. The data provided information on variation in external exposure for each animal over time, as well as variation in external exposure among the eight wolves across the landscape of Chernobyl. The exposure data were then used to test a fundamental assumption in screening-level risk assessments, espoused in guidance documents of the U.S. Environmental Protection Agency and U.S. Department of Energy, - Mean contaminant concentrations conservatively estimate individual external exposures. We tested this assumption by comparing our empirical data to a series of simulations using the ERICA modeling tool. We found that modeled simulations of mean external exposure (10.5 mGy y(-1)), based on various measures of central tendency, under-predicted mean exposures measured on five of the eight wolves wearing GPS-contaminant monitors (i.e., 12.3, 26.3, 28.0, 28.8 and 35.7 mGy y(-1)). If under-prediction of exposure occurs for some animals, then arguably the use of averaged contaminant concentrations to predict external exposure is not as conservative as proposed by current risk assessment guidance. Thus, a risk assessor's interpretation of simulated exposures in a screening-level risk analysis might be misguided if contaminant concentrations are based on measures of central tendency. We offer three suggestions for risk assessors to consider in order to reduce the probability of underestimating exposure in a screening-level risk assessment.

One potentially useful approach to fill data gaps for concentration ratios, CRs, is based upon the hypothesis that an underlying taxonomic and/or phylogenetic relationship exists for radionuclide transfer. The objective of this study was to explore whether these relationships could be used to explain variation in the transfer of radiocaesium to a wide range of marine organisms. CR data for 137Cs were classified in relation to taxonomic family, order, class and phylum. A Residual Maximum Likelihood (REML) mixed-model regression modelling approach was adopted. The existence of any patterns were then explored using phylogenetic trees constructed with mitochondrial COI gene sequences from various biota groups and mapping the REML residual means onto these trees. A comparison of the predictions made using REML with blind datasets allowed the efficacy of the procedure to be tested. The only significant correlation between predicted and measured activity concentrations was revealed at the taxonomic level of order when comparing REML analysis output with data from the Barents Sea Region. For this single case a correlation 0.80 (Spearman rank) was derived which was significant at the 0.01 level (1-tailed test) although this was not the case once a (Bonferroni) correction was applied. The application of the REML approach to marine datasets has met with limited success, and the phylogenetic trees illustrate complications of using predictions based on values from different levels of taxonomic organization, where predicted values for the order level can mask the values at lower taxonomic levels. Any influence of taxonomy and phylogeny on transfer is not immediately conspicuous and categorizing marine organisms in this way is limited in providing a potentially robust prognostic extrapolation tool. Other factors may plausibly affect transfer to a much greater degree in marine systems, such as quite diverse life histories and different diets, which may confound any phylogenetic pattern.

The results of radiological investigations (in 2001-2002) conducted near sites of the underground nuclear explosions Crystal and Kraton-3 in the Republic of Sakha (Yakutia) are presented. The sum of the current effective internal doses from 137Cs and 90Sr (from consumption of natural products) and the external dose from 137Cs deposition was about 21 μSv y-1 for adult residents of the urban settlements Aihal and Udachny. Intake of 137Cs and 90Sr (originating from global fallout) with reindeer meat contributes ~87% to the internal dose determined. At present, the consequences of the underground nuclear explosions, conducted in the 1970s, have no influence on the technogenic exposure of the local population.