Highly weathered mineral soils have highest transfer risk of radiocaesium contamination after a nuclear accident: A global soil-plant study.

Accidental release of radiocaesium (137Cs) from nuclear power plants may result in long-term contamination of environmental and food production systems. Assessment of food chain contamination with 137Cs relies on 137Cs soil-to-plant transfer data and models mainly available for regions affected by the Chornobyl and Fukushima accidents. Similar data and models are lacking for other regions. Such information is needed given the global expansion of nuclear energy. We collected 38 soils worldwide of contrasting parent materials and weathering stages. The soils were spiked with 137Cs and sown with ryegrass in greenhouse conditions. The 137Cs grass-soil concentration ratio varied four orders of magnitude among soils. It was highest in Ferralsols due to the low 137Cs interception potential of kaolinite clay and the low exchangeable potassium in these soils. Our results demonstrate, for the first time, the high plant uptake of 137Cs in tropical soils. The most recent 137Cs transfer model, mainly calibrated to temperate soils dominated by weathered micas, poorly predicts the underlying processes in tropical soils but, due to compensatory effect, still reasonably well predicts 137Cs bioavailability across all soils (R2 = 0.8 on a log-log scale).

A radioecological model with moisture-dependent Kd: Application to 129I and 79Se natural release to a grassland.

A radioecological model previously developed to simulate chlorine cycling in a Scots pine forest was modified to examine the effect of soil hydrochemical conditions on the fate of 129I and 79Se released to a grassland through natural discharge of contaminated groundwater. To this end, the constant solid-liquid distribution coefficient (Kd) in the original model was replaced by a parametric equation to estimate 129I and 79Se Kd values from soil saturation - as a proxy for soil redox potential - and a set of Kd values determined experimentally under oxic and anoxic conditions. Additionally, the multi-compartment Scots pine tree module was replaced by a two-compartment module to represent 129I and 79Se cycling in grass. Simulations undertaken with the model indicated a considerable effect of soil redox conditions on 129I and 79Se accumulation in the soil column, especially in the saturated subsoil above the water table. The constant Kd overestimated 129I accumulation in the soil in relation to the parametric Kd. In contrast, the constant Kd underestimated 79Se accumulation in the soil. These results have implications for radiological impact assessments, specifically regarding the degree of conservatism in the Kd used in the assessment. In respect of bioavailability to grass, the simulated soil-to-plant transfer factors of 129I and 79Se compared favourably with values reported in the literature for similar soils and plant species, giving confidence in the model performance. The model presented here is a step forward in radioecological modelling as it includes the key processes that drive radionuclide transfers in soil-plant systems and the effect of soil redox conditions on sorption. The model can be readily extended to other cultivated lands and release scenarios to predict radionuclide transfer up the food chain.

Towards dynamic and process-based modelling of radionuclides cycling in terrestrial radioecology.

Mathematical models are frequently used in terrestrial radioecology to interpret observations and to assess the detrimental impacts of radioactive releases to the environment. Conventional radioecological models are largely based on equilibrium and empirical relationships with reasonable data requirements, making them practical tools for long-term assessments. But conventional models may be inadequate to simulate radionuclide dynamics in terrestrial environments realistically. Specifically, the structure of such models seldom conforms to the physics of water flow and solute transport in soils. The equilibrium relationships may fail to predict seasonality in radionuclide transfer between environmental compartments; model transferability between sites is often hampered by its empirical nature. Numerous studies have highlighted the need to circumvent these limitations. In this paper, we introduce dynamic and process-based modelling to a conventional radioecological model by coupling an empirical plant module to a process-based soil module that simulates water flow, solute transport and root uptake in the soil column. Illustrative simulations are presented using the coupled model and stable chlorine cycling in a temperate Scots pine (Pinus sylvestris L.) stand as an example. The model satisfactorily reproduced soil moisture dynamics and the inventory of inorganic chlorine in the tree and forest floor compartments. The inventory of organic chlorine in the stand, however, was overestimated, indicating that processes pertinent to organochlorine cycling at the stand were missing from the model. The approach proposed in this paper is a step towards dynamic and process-based modelling in terrestrial radioecology and impact assessment. It can be particularly useful for modelling transfer of elements, such as redox-sensitive radionuclides, whose behaviour in soil-plant systems is moisture-dependent.

Fit-for-purpose modelling of radiocaesium soil-to-plant transfer for nuclear emergencies: a review.

Numerous radioecological models have been developed to predict radionuclides transfer from contaminated soils to the food chain, which is an essential step in preparing and responding to nuclear emergencies. However, the lessons learned from applying these models to predict radiocaesium (RCs) soil-to-plant transfer following the Fukushima accident in 2011 renewed interest in RCs transfer modelling. To help guide and prioritise further research in relation to modelling RCs transfer in terrestrial environments, we reviewed existing models focussing on transfer to food crops and animal fodders. To facilitate the review process, we categorised existing RCs soil-to-plant transfer models into empirical, semi-mechanistic and mechanistic, though several models cross the boundaries between these categories. The empirical approach predicts RCs transfer to plants based on total RCs concentration in soil and an empirical transfer factor. The semi-mechanistic approach takes into account the influence of soil characteristics such as clay and exchangeable potassium content on RCs transfer. It also uses 'bioavailable' rather than total RCs in soil. The mechanistic approach considers the physical and chemical processes that control RCs distribution and uptake in soil-plant systems including transport in the root zone and root absorption kinetics. Each of these modelling approaches has its advantages and disadvantages. The empirical approach is simple and requires two inputs, but it is often associated with considerably uncertainty due to the large variability in the transfer factor. The semi-mechanistic approach factorises more soil and plant parameters than the empirical approach; therefore, it is applicable to a wider range of environmental conditions. The mechanistic approach is instrumental in understanding RCs mobility and transfer in soil-plant systems; it also helps to identify influential soil and plant parameters. However, the comlexity and the large amount of specific parameters make this approach impractical for nuclear emergency preparedness and response purposes. We propose that the semi-mechanistic approach is sufficiently robust and practical, hence more fit for the purpose of planning and responding to nuclear emergencies compared with the empirical and mechanistic approaches. We recommend further work to extend the applicability of the semi-mechanistic approach to a wide range of plants and soils.

Radioecology in CONFIDENCE: Dealing with uncertainties relevant for decision making.

The CONFIDENCE project is performing research on uncertainties in emergency management and post-accident recovery. It concentrates on the early and transition phases of an emergency, but considers also longer-term decisions made during these phases. To ensure success, the project brings together expertise from four European Radiation Protection Research Platforms (NERIS, MELODI, ALLIANCE and EURADOS) and also from the area of social sciences and humanities. This paper presents an overview of the CONFIDENCE project with a focus on CONFIDENCE's consideration of the radioecology required to support emergency management and post-accident recovery. For instance, operational decisions concerning land and foodchain management rely on radioecological models that are at present mostly based on simple, but highly uncertain, transfer ratios to predict contamination in foodstuffs. CONFIDENCE will investigate if process-based models are better suited to reducing uncertainties associated with empirical ratio based models. Model improvements and uncertainty reduction might be also possible by better evaluating past experience from Chernobyl and Fukushima.

Derivation of irrigation requirements for radiological impact assessments.

When assessing the radiological impacts of radioactive waste disposal, irrigation using groundwater contaminated with releases from the disposal system is a principal means of crop and soil contamination. In spite of their importance for radiological impact assessments, irrigation data are scarce and often associated with considerable uncertainty for several reasons including limited obligation to measure groundwater abstraction and differences in measuring methodologies. Further uncertainty arises from environmental (e.g. climate and landscape) change likely to occur during the assessment long time frame. In this paper, we derive irrigation data using the crop growth AquaCrop model relevant to a range of climates, soils and crops for use in radiological impact assessments. The AquaCrop estimates were compared with actual irrigation data reported in the literature and with estimates obtained from simple empirical methods proposed for use in radiological impact assessments. Further, the AquaCrop irrigation data were analysed using mixed effects modelling to investigate the effects of climate, soil and crop type on the irrigation requirement. Irrigation estimates from all models were within a reasonable range of the measured values. The AquaCrop estimates, however, were at the higher end of the range and higher than those from the empirical methods. Nevertheless, they may be more appropriate for conservative radiological assessments. The use of mixed effects modelling allowed for the characterisation of crop-specific variability in the irrigation data, and in contrast to the empirical methods, the AquaCrop and the mixed effects models accounted for the soil effect on the irrigation requirement. The approach presented in this paper is relevant for obtaining irrigation data for a specific site under different climatic conditions as well as for generic dose assessments. To the best of our knowledge, this is one of the most comprehensive analyses of irrigation data in the context of radiological impact assessment currently available.