Identifying civil Xe-emissions: from source to receptor

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Identifying civil Xe-emissions: from source to receptor A. Bollhöfer, P. De Meutter, F. Gubernator, Benoît Deconninck, C. Schlosser, U. Stöhlker, G. Kirchner, 1 2,3,4 5 6 1 1 C. Strobl1, A. Delcloo3, J. Camps2 1 Federal Office for Radiation Protection (BfS), 79098 Freiburg, Germany SCK-CEN, 2400 Mol, Belgium 3 Royal Meteorological Institute of Belgium, Brussels, Belgium 4 Ghent University, B-9000 Ghent, Belgium 5 University Hamburg, Carl Friedrich von Weizsäcker-Centre for Science and Peace Research (ZNF) 6 Institute for Radioelements, Fleurus, Belgium 2 - Environmental Monitoring - Atmospheric Transport Modelling - Stack monitoring 5

The International Monitoring System

Sources of radioxenons Estimate of von dailytäglichen emissionsemissionen from single sources (blue) and Abschätzung einzelner Emittenten annual emissions (red) of Xe-133 (blau) und global globalen jährlichen Emissionen (rot) von Xe-133 Radioxenons are fission products: Nuclear explosions Nuclear power plants and research reactors Medical isotope production (99Mo/99Tc; 131I) 1.0E+19 1.0E+17 1.0E+15 Bq 1.0E+13 1.0E+11 1.0E+09 1.0E+07 1.0E+05

Underground test (#4), DPRK, Jan 2016 Successful nuclear weapons test announced, 6 Jan 2016 Waiting for the smoking gun From Feb 17 elevated Xe-133 activity (2-3 days) at station Takasaki, JP38, but no other isotopes > MDC

Underground test (#4), DPRK, Jan 2016

IAEA - Project CRP F23031 Sharing and Developing Protocols to Further Minimize Radioactive Gaseous Releases to the Environment in the Manufacture of Medical Radioisotopes, as Good Manufacturing Practice Belgium (ATM, Xe-mitigation) Canada (CNL emissions, monitoring data and ATM) Egypt (Xe-mitigation) Germany (stack monitoring, environmental data, ATM) Indonesia (Xe-mitigation) Korea (Xe-mitigation) Pakistan (emissions monitoring) Poland (Xe-mitigation) USA (Xe mitigation, stack monitoring, isotopic background)

Stack and near field monitoring 1) Masters University Hamburg, BfS Development and test of a compact spectrometric stack monitoring system Characterise emissions -> compare with IRE System 2) Investigate sensitivity of compact spectrometric systems (LaBr3, CdZT) in the vicinity of IRE, Fleurus Xe-environmental monitoring Comparison with Belgian Telerad. Measurement campaign Q3 2017 Cadmium Zinc Telluride detector Intergated electronics Compact Low energy usage FWHM ~2%, 662keV

Results: Stack monitoring IRE, Fleurus 1 hrhrspectrum 24 spectrum Nuclide 131mXe T1/2 Eγ (Pγ) 11.8 d 163.9 kev (1.95%) 133Xe 5.25 d 133mXe 2.19 d 135Xe 9.10 h 135mXe 15.3 m 81 kev (36.6%) 233.2 kev (10.1%) 249.8 kev (90%) 526.6 kev (80.5%)

Conclusions: Stack and near field monitoring Set-up of a CZT detector and a Raspberry Pi Simple Mobile Small Cheap Capable of detecting Xe-133, Xe-135, Xe-135m Detection Xe-131m, Xe-133m needs further development Preliminary data (800m N-E of IRE) indicate Xe-133 and Xe-135 easily detectable in the near field (LaBr3)

Comparison: Environmental data - ATM

Xenon measurements in the environment Noble Gas Lab at BfS Manual system: 85Kr & 133Xe Cryogenic sampling (1 week, 10 m³ air) GC for processing and purification 7 proportional gas counters + anticoincidence MDA for 133Xe: 0,01 Bq (2 m³ air) SAUNA Lab SAUNA Lab System: Xenons only Nuclide specific:131mxe,133xe,133mxe,135xe β-γ coincidence detection system MDAs (12 h meas.): 3 mbq

Atmospheric Transport Modelling SCK-CEN, Ghent University, RMI Belgium: ATM as part of the collaboration Stack monitoring data from IRE, Fleurus for 2014: - 15 min Xe-133 emission data as model input Meteorological data: ECMWF - 3 hourly weather for 2014 Model: FLEXPART FLEXible PARTicle dispersio odel - Lagrange transport and dispersion model - 0.5º horizontal resolution Emissions NPP: - Germany (quarterly), Switzerland (monthly),france, Belgium and Scandinavian countries (annually) Emissions CNL: - Hoffman et al 2009

2014 (weekly samples)

2014 (weekly samples)

Discussion & Future work ATM reproduces general trends at the stations but: Periods with higher measured vs modelled data and vice versa (1) miss-represe tatio of NPP s i a ulti-source region due to temporal variability of emission (e.g. during revisions) (2) local sources (3) emission data IRE (4) uncertainties in dispersion modelling (?)... Averaging reduces accuracy of measured and modelled data Weekly data depend on timing of arrival of cloud, Factor 2-3 difference. Daily sampling required Maximum travel time only 14 days. CNL under-represented? Time resolved emission data needed as input into ATM Further development and refinement of easy to use CSMS Phase out PC -> isotope specific Xe measurements using SAUNA only Continue collaboration: stack - near-field - far-field monitoring, Q3 2017

Questions?

Campaign planned for September 2017 MIPF Fleurus: ~ 10-16 September 2017 15 emissions data Measurements in near field (GDR + spectrometric) Daily noble gas samples: Freiburg, Schauinsland, Trier ATM (including near-field) Time-resolved data from German NPPs

2014 (daily samples) RN33 weekly samples Freiberg