Abstract
The development of the source inversion algorithm is described which allows for estimation of the release rates of multiple nuclides and source height with the use of gamma dose rate (GDR) measurements. The method is applicable for the dispersion problems of different spatial scales: from ~1 to ~1000 km. The variational formulation of source inversion problem is used in which unknown release rates of different nuclides are adjusted to minimize the difference of calculated values and measurements. The sensitivities of calculated results with respect to release rates of different radionuclides are calculated with the aid of atmospheric transport model DIPCOT and the source receptor matrix (SRM) is thus constructed. The source inversion problem is regularized using prior (first guess) estimation of release rates. The method is proposed to account for the restrictions on the ratios of the release rates of different radionuclides in formulation of source inversion problem which allows for the assessment of the nuclide composition in radioactive release. The above restrictions are evaluated using the first guess source term. Parameterizations for the regularization parameters of source inversion problem which include root mean squared errors of measurents, first guess release rates, calculated values etc., are developed. The method was successfully tested using artificial measurements precalculated for the conditions of the ETEX experiment. Pilot implementation of the developed algorithm in the European nuclear emergency response system JRODOS is described.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Andronopoulos S, Davakis E, Bartzis JG (2009) RODOS-DIPCOT model description and evaluation. Report RODOS(RA2)-TN(09)01. Available at: https://www.researchgate.net/publication/228862960_RODOS-DIPCOT_Model_Description_and_Evaluation, last accessed 2018/06/01
Andronopoulos S, Bartzis JG (2010) Gamma radiation dose calculation method for Lagrangian-puff atmospheric dispersion models used in real-time emergency response systems. J Radiol Prot 30(4):747–759. https://doi.org/10.1088/0952-4746/30/4/008
Andronopoulos S, Davakis E, Bartzis JG, Kovalets IV (2010) RODOS meteorological pre-processor and atmospheric dispersion model DIPCOT: a model suite for radionuclides dispersion in complex terrain. Radioprotection 45(5):S77–S84. https://doi.org/10.1051/radiopro/2010017
Andronopoulos S, Ievdin I, Kovalets I, Anulich S, Trybushnyi D (2016) New functionalities developed in the NERIS-TP project regarding meteorological data used by Decision Support Systems. Radioprotection 51(HS1):S13–S16. https://doi.org/10.1051/radiopro/2016004
Bocquet M (2008) Inverse modelling of atmospheric tracers: non-Gaussian methods and second-order sensitivity analysis. Nonlinear Process Geophys 15:127–143. https://doi.org/10.5194/npg-15-127-2008
Davakis E, Andronopoulos S, Kovalets I, Gounaris N, Bartzis JG, Nychas SG (2007) Data assimilation in meteorological preprocessors: effects on atmospheric dispersion simulations. Atmos Environ 41(14):2917–2932. https://doi.org/10.1016/j.atmosenv.2006.12.031
Davoine X, Bocquet M (2007) Inverse modeling-based reconstruction of the Chernobyl source term available for long term transport. Atmos Chem Phys 7:1549–1564. https://doi.org/10.5194/acp-7-1549-2007
De Haan P, Rotach MW (1998) A novel approach to atmospheric dispersion modelling: the puff-particle model. Q J R Meteorol Soc 124:2771–2792. https://doi.org/10.1002/qj.49712455212
Gryning SE, Batchvarova E, Schneiter D et al (1998) Meteorological conditions at the release site during the two tracer experiments. Atmos Environ 32(24):4213–4137. https://doi.org/10.1016/s1352-2310(98)00191-5
Hofman R, Seibert P, Kovalets I, Andronopoulos S (2015) Analytical source term optimization for radioactive releases with approximate knowledge of nuclide ratios. In: EGU general assembly 2015 conference abstracts, vol 17, EGU2015-3033
Ievdin Y, Trybushny D, Zheleznyak M, Raskob W (2010) RODOS re-engineering: aims and implementation details. Radioprotection 45(5):S181–S190. https://doi.org/10.1051/radiopro/2010024
Ievdin I, Trybushnyi D, Landman C (2015) JRODOS user guide, version 3.21. Karlsruhe Institute of Technology
Kovalets I, Andronopoulos S, Bartzis J, Gounaris N, Kushchan A (2004) Introduction of data assimilation procedures in the meteorological pre-processor of atmospheric dispersion models used in emergency response systems. Atmos Environ 38(3):457–467. https://doi.org/10.1016/j.atmosenv.2003.09.068
Kovalets I, Hofman R, Seibert P, Andronopoulos S (2014) Dispersion modelling and 1st-guess source term uncertainties. Report of the EU FP7 PREPARE project PREPARE(WP4)-(14)-05. https://doi.org/10.13140/rg.2.2.16116.86403
Kovalets I, Andronopoulos S, Hofman R, Seibert P, Ievdin I (2016) Advanced method for source term estimation and status of its integration in JRODOS. Radioprotection 51(HS2):S121–S124. https://doi.org/10.1051/radiopro/2016046
Landman C (2007) Scenario data sets and scenarios for RODOS PV6 final. Report RODOS(RA7)-TN(04)-02. Germany Karlsruhe: Karlsruhe Institute of Technology. Available at: https://resy5.iket.kit.edu/RODOS/Documents/Public/Handbook/Volume2/3_3_scenariodata.pdf, last accessed 2018/06/01
Lawson CL, Hanson RJ (1974) Solving least squares problems. Prentice-Hall, Inc., Englewood Cliffs, New Jersey
Raskob W, Schneider T, Gering F, Charron S, Zheleznyak M, Andronopoulos S, Heriard-Dubreuil G, Camps J (2016) Innovative integrative tools and platforms. Key results of the PREPARE European Project. Radioprotection 51(HS2), S59-S61. doi:https://doi.org/10.1051/radiopro/2016032
Saunier O, Mathieu A, Didier D, Tombette M, Quélo D, Winiarek V, Bocquet M (2013) An inverse modeling method to assess the source term of the Fukushima nuclear power plant accident using gamma dose rate observations. Atmos Chem Phys 13:11403–11421. https://doi.org/10.5194/acp-13-11403-2013
Seibert P, Frank A, Kromp-Kolb H (2002) Inverse modelling of atmospheric trace substances on the regional scale with Lagrangian models. In: Proceedings of the EUROTRAC-2 symposium. Garmisch-Partenkirchen, Germany, pp 11–15
Seibert P, Kristiansen NI, Richter A, Eckhardt S, Prata AJ, Stohl A (2011) Uncertainties in the inverse modelling of sulphur dioxide eruption profiles. Geomat Nat Hazards Risk 2(3):201–216. https://doi.org/10.1080/19475705.2011.590533
Stohl A, Forster C, Frank A, Seibert P, Wotawa G (2005) Technical note: the Lagrangian particle dispersion model FLEXPART version 6.2. Atmos Chem Phys 5:2461–2474. https://doi.org/10.5194/acp-5-2461-2005
Stohl A, Seibert P, Wotawa G, Arnold D, Bukhart JF, Eckhardt S, Tapia C, Vargas A, Yasunari TJ (2012) Xenon-133 and caesium-137 releases into the atmosphere from the Fukushima Dai-ichi nuclear power plant: determination of the source term, atmospheric dispersion, and deposition. Atmos Chem Phys 12:2313–2343. https://doi.org/10.5194/acp-12-2313-2012
Talerko N (2005) Reconstruction of 131I radioactive contamination in Ukraine caused by the Chernobyl accident using atmospheric transport modeling. J Environ Radioact 84(3):343–362. https://doi.org/10.1016/j.jenvrad.2005.04.005
Tarantola A (2005) Inverse problem theory and methods for model parameter estimation. SIAM Publishers, USA, Philadelphia. https://doi.org/10.1137/1.9780898717921
Tsiouri V, Kovalets I, Andronopoulos S, Bartzis J (2011) Development and first tests of a data assimilation algorithm in a Lagrangian puff atmospheric dispersion model. Int J Environ Pollut 44(1–4):147–155. https://doi.org/10.1504/IJEP.2011.038413
Tsiouri V, Kovalets I, Andronopoulos S, Bartzis JG (2012) Source function estimation with data assimilation of gamma dose measurements in Lagrangian atmospheric dispersion model DIPCOT. Radiat Prot Dosimetry 148(1):34–44. https://doi.org/10.1093/rpd/ncq592
US NRC (1990) Analysis of CDF from internal events: expert judgment. US NRC Report NUREG/CR-4550, vol 2. Available online: https://www.nrc.gov/docs/ML0634/ML063460465.pdf, last accessed 2018/06/01
Winiarek V, Vira J, Bocquet M, Sofiev M, Saunier O (2011) Towards the operational estimation of a radiological plume using data assimilation after a radiological accidental atmospheric release. Atmos Environ 45(17):2944–2955. https://doi.org/10.1016/j.atmosenv.2010.12.025
Wotawa G, DeGeer L-E, Denier P, Kalinowski M, Toivonen H, D’Amours R, Desiato F, Issartel J-P, Langer M, Seibert P et al (2003) Atmospheric transport modelling in support of CTBT verification overview and basic concepts. Atmos Environ 37(18):2529–2537. https://doi.org/10.1016/S1352-2310(03)00154-7
Zhang X, Raskob W, Landman C, Trybushnyi D, Li Y (2017) Sequential multi-nuclide emission rate estimation method based on gamma dose rate measurement for nuclear emergency management. J Hazard Mater 325(5):288–300. https://doi.org/10.1016/j.jhazmat.2016.10.072
Acknowledgements
The presented research was supported with the EURATOM grant No.323287. I. Kovalets was also supported with the grant of the President of Ukrane No. Φ78/40053.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Singapore Pte Ltd.
About this chapter
Cite this chapter
Kovalets, I., Andronopoulos, S., Hofman, R., Seibert, P., Ievdin, I., Pylypenko, O. (2019). Advanced Source Inversion Module of the JRODOS System. In: Agarwal, R., Agarwal, A., Gupta, T., Sharma, N. (eds) Pollutants from Energy Sources. Energy, Environment, and Sustainability. Springer, Singapore. https://doi.org/10.1007/978-981-13-3281-4_10
Download citation
DOI: https://doi.org/10.1007/978-981-13-3281-4_10
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-3280-7
Online ISBN: 978-981-13-3281-4
eBook Packages: EnergyEnergy (R0)