Editorial: the main results of the European CONFIDENCE project

Abstract

In nuclear emergency management and long-term rehabilitation, dealing with uncertain information on the current situation, or predicted evolution of the situation, is an intrinsic problem for decision making. Uncertain information related to, for instance, incomplete information on the source term and the prevailing weather can result in dose assessments that differ dramatically from reality. Uncertainty is also an intrinsic part of model parameters. In the presence of uncertainty, ineffective decisions are often taken (e.g. too conservative or optimistic predictions, inadequately accounting of non-radiological risks), which may result in more overall harm than good due to secondary causalities as observed following the Chernobyl and Fukushima accidents. Therefore, the reduction of uncertainty, and how to deal with uncertain information, is essential to improve decision making for the protection of the affected population and to minimise disruption of normal living conditions.Decisions on early countermeasures (e.g. evacuation, sheltering, and provision of iodine tablets) are often taken based on deterministic calculations considering the best available source term information and the state of the art numerical weather prediction data as inputs. The source term uncertainty is large and quantification difficult. Uncertainty in meteorological forecasts is routinely quantified by "ensemble predictions". However, these predictions are not used in emergency management. One reason for this is the effort and time required to process 30 to 100 different weather sequences within atmospheric dispersion models.At present, decision making in the early phase is mainly based on modelling followed by a period where monitoring has made enough progress to provide a robust contamination and dose map. However, in between some monitoring data will be available; however, no operational tool exists to combine simulated dose estimations with monitoring data to obtain a more consolidated picture of the radiological situation.The key endpoint for all decision making is the dose and associated risk to affected population groups. However, in the case of the Fukushima accident, only order-of-magnitude dose bands were estimated from (local) contamination and model predictions, with no accounting for individual human behaviour patterns or location. Individual dose measurements could greatly reduce this uncertainty but are limited by capacity.Completely missing from emergency management is the assessments of risk in the early and the transition phases. However, this is important for decision making on the need for medical surveys and long-term support of the affected population.Operational decisions concerning land and food chain management rely on radioecological models that are mostly based on simple, but highly uncertain, transfer ratios to predict contamination in foodstuffs (though such data are few for some climatic areas, (e.g. Mediterranean) and foodstuff-radionuclide combinations). Process-based models might provide an approach to red...

Radiation risks and uncertainties: a scoping review to support communication and informed decision-making

“…For instance, uncertainties linked to exposure assessment may be related to the physicochemical behaviour and transport of radionuclides, transfer to biota, dosimetry and dose assessment in humans and biota (Hinton et al 2013). Another uncertainty concerns the possible relationship between background irradiation and cancer occurrence, particularly in children as they are substantially more sensitive to radiation exposure than adults (Wakeford et al 2009, UNSCEAR 2013, 2017, Hoeschen 2018. Moreover, assessment of occupational exposure from incorporated radionuclides is still subject to major uncertainties, due to activity measurement errors, individual variability, limited biokinetic and dosimetric models and unknown parameters of exposure (Boice 2010, Kreuzer et al 2018).…”

“…For instance, related to nuclear emergencies, many gaps and issues have been identified (especially after the Chernobyl and Fukushima accidents) that need to be addressed. Such issues involve creating and advancing different modelling and monitoring techniques; dealing with contaminated goods; improving decision support systems; issuing reliable and trustworthy information to the public in due time; as well as analyzing the public's perceptions of risks and uncertainties (Raskob 2017, Schneider et al 2017. Similarly, the TERRITORIES project under H2020 (Guillevic et al 2018) has clearly argued that more scientific attention needs to be paid to the impact of uncertainty on decision-making regarding long -term radiological exposure situations (e.g.…”

“…It is worth mentioning though, that grey literature (e.g. reports, narratives) have taken these uncertainties into consideration (IAEA 2016, Raskob 2017, Guillevic et al 2018, but they were not present in the scientific literature in which we were particularly interested in.…”

Redesigning the FDMT Food Chain Transfer Model: Now Probabilistically Enabled and Fully Flexible

“…A key observation of the recent EC funded CONFIDENCE project considering uncertainties in modelling and decision making after nuclear accidents [20] was that uncertainty management for simulation models in decision support systems (such as ARGOS and JRODOS), was far from satisfactory [21]. One of the key problems identified was the current inability to incorporate process-based models (i.e.…”

“…models who's parameterisation take into account soil and potentially plant characteristics [2]), in the context of simulating food-chain transfer, to potentially reduce the uncertainties associated with the existing empirical ratiobased transfer approaches. Raskob and Duranova [21] considered quantification and reduction of uncertainties to be an essential step towards improving decision making to protect affected populations and minimise the disruption of normal living conditions.…”