Impacts of 14C discharges from a nuclear fuel reprocessing plant on surrounding vegetation: Comparison between grass field measurements and TOCATTA-χ and SSPAM14C model computations. (September 2015)

• Record Type: Journal Article
• Authors: Limer, Laura M.C.; Le Dizès-Maurel, Séverine; Klos, Ryk; Maro, Denis; Nordén, Maria
• Is Part Of: Journal of environmental radioactivity. Volume 147(2015:Sep.)
• Page Start: 115
• Page End: 124
• Publication Date: 2015-09
• Subjects: 14C compartment model -- Environment -- Plant physiological functioning -- Atmospheric exchange -- Pasture; Radioactivity -- Periodicals; Radiation, Background -- Periodicals; Radioecology -- Periodicals; Radioactive pollution -- Periodicals; Environmental Pollutants -- Periodicals; Radioactive Pollutants -- Periodicals; Radioactivity -- Periodicals; Radioécologie -- Périodiques; Pollution radioactive -- Périodiques; Fond de rayonnement -- Périodiques; 539.752
• DOI: 10.1016/j.jenvrad.2015.05.015
• Languages: English
• ISSNs: 0265-931X

Abstract

Abstract: This article compares and discusses the ability of two different models to reproduce the observed temporal variability in grass 14 C activity in the vicinity of AREVA-NC La Hague nuclear fuel reprocessing plant in France. These two models are the TOCATTA-χ model, which is specifically designed for modelling transfer of 14 C (and tritium) in the terrestrial environment over short to medium timescales (days to years), and SSPAM 14 C, which has been developed to model the transfer of 14 C in the soil–plant–atmosphere with consideration over both short and long timescales (days to thousands of years). The main goal of this article is to discuss the strengths and weaknesses of the models studied, and to investigate if modelling could be improved through consideration of a much higher level of detail of plant physiology and/or higher number of plant compartments. These models have been applied here to the La Hague field data as it represents a medium term data set with both short term variation and a sizeable time series of measurements against which to compare the models. The two models have different objectives in terms of the timescales they are intended to be applied over, and thus incorporate biological processes, such as photosynthesis and plant growth, at different levels of complexity. It was found that the inclusion of seasonal dynamics in the models improved predictions of the specific activity in grass for such a source term of atmospheric 14 C. Highlights: We model plant uptake of 14 C discharges from a nuclear fuel reprocessing plant. The two models have different timescales to which they are applied. Physical processes are represented with a varying degree of complexity. Inclusion of seasonal dynamics in the model improves predictions.