Methodology for the investigation of undeclared atmospheric releases of radionuclides: Application to recent radionuclide detections in Northern Europe from 2019 to 2022
Bibliographic record
Abstract
Traces of radionuclides have been frequently detected in the European atmosphere for several years. The measured concentrations are usually very low, ranging from 0.1 to 10 μBq m−3, and do not pose any health or environmental problems. This study aims to diagnose the origin of small undeclared radionuclide releases into the atmosphere. An inverse modelling approach that combines environmental measurements and atmospheric transport modelling is first used to assess the source location of the release. In addition, the type and process of the nuclear facility from which the release could originate are investigated by identifying the isotope production pathways and comparing them with known typical inventories. These two parts of the proposed method are complementary and allow us to extract as much information as possible from a set of radionuclide measurement data. In a previous study, the origins of detections of various radionuclides (60Co, 134Cs, 137Cs, 103Ru, 106Ru, 141Ce, 95Nb, 95Zr) in Finland, Sweden and Estonia in June 2020 have been investigated. In this paper, the previous investigation is extended by analysing two additional events that occurred in northern Europe in July 2019 and May 2022, as well an overview of other unknown releases detected in Finland over the last decade. A more detailed analysis of the 2020 event is also provided by analysing new available environmental measurements. The calculations indicate that the source location of the three events appears to be in the same region, in Russian Federation. The most probable origin of the June 2020 release seems to be a primary ion exchange resin, after 2 to 5 months of decay, of a pressurized water reactor with fuel cladding failure, and dispersion of fissile material in the primary. The July 2019 and May 2022 events are of particularly noteworthy due to the simultaneous presence of 46Sc, which is neither produced nor in the fuel, nor in the primary loop of PWR or RBMK nuclear power plants, and typical corrosion-activated products from power plants (60Co). Two hypotheses are proposed to explain this source term: a mixture of various solid wastes or recently irradiated graphite from a RBMK reactor. The reliability of the methodology is demonstrated, in particular in the section dedicated to atmospheric transport modelling, and the successful association with source term analysis provides a valuable tool for future studies and assessments of both minor and major radionuclide releases.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".