Updated global radioxenon emission inventory from all types of nuclear facilities specific for the year 2014
Bibliographic record
Abstract
This presentation summarizes the currently best available estimates of radioxenon emissions from all nuclear facilities for a specific year. It is a unique data set to be used in studies to enhance data analysis from the noble gas component of the International Monitoring System (IMS). Global radioactivity monitoring for the verification of the Comprehensive Nuclear-Test-Ban Treaty (CTBT) includes the four xenon isotopes 131mXe, 133Xe, 133mXe and 135Xe. These four isotopes are serving as important indicators of nuclear explosions. The state-of-the-art radioxenon emission inventory uses generic release estimates for each known nuclear facility. However, the release amount can vary by several orders of magnitude from year to year. The year 2014 was selected for a single year radioxenon emission inventory with minimized uncertainty. Whenever 2014 emissions reported by the facility operator are available these are incorporated into the 2014 emission inventory.This presentation summarizes this newly updated radioxenon emission inventory. It comprises all relevant nuclear facilities. For the three strong sources ANSTO (Australia), CNL (Canada), and IRE (Belgium), stack release data with a high time resolution are available. Annual emissions are provided for all other medial isotope production facilities, including new updates for the NIIAR facility (Russia) and the Karpov Institute (Russia). For nuclear power plants (NPP) in Europe and the USA the reported release for the whole year is applied in combination with information about their operational schedule. For all other NPPs the best estimates are used. The estimated releases of nuclear research reactor sources are included as well. For the first time, estimates were made for radioxenon releases from spallation neutron sources and from spent nuclear fuel reprocessing plants. The new emission data are compared with previous studies highlighting discrepancies which in many cases are as large as several orders of magnitude.The global radioxenon emission inventory for 2014 can be used for studies to estimate the contribution of this anthropogenic source to the observed ambient concentrations at IMS noble gas sensors to support CTBT monitoring activities, including calibration and performance assessment of the verification system as described in the Treaty as well as developing and validating methods for enhanced detection capabilities of signals that may indicate a nuclear test. One specific application is the 1st Nuclear Explosion Signal Screening Open Inter-Comparison Exercise that was announced end of 2021 and conducted in 2022. The emission inventory in combination with radioxenon observations at IMS stations may as well be used for global or regional atmospheric tracer studies and for the validation of atmospheric transport simulation methods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
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 teacher head, 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".