Séverine Le Dizès Environment and Emergency Operations Division Department for the Study of Radionuclide Behavior in Ecosystems Environmental Modelling Laboratory Cadarache, St Paul-lez-Durance, France September 28 th, 2009 TOCATTA : Transfer Of Carbon 14 And Tritium in Terrestrial and Aquatic environments

EMRAS II, Paris, 09/28/2009 Plan v Presentation of VATO v Conclusions & perspectives v Presentation of TOCATTA Ø Conceptual model Ø Mathematical model

EMRAS II, Paris, 09/28/2009 C and H specificities Presentation of TOCATTA 1. Integration of these radionuclides to living organic matter 2. Carbon14 and Tritium transfers within biotic compartments occur in the form of : § Organic matter and carbon dioxide (for 14 C) § Organic matter and tritiated water (for tritium) Ø More specifically, dynamic modeling of 14 C and 3 H in plants requires knowledge of plant growth dynamics Ø 14 C and 3 H modeling (stocks, fluxes, residence time) does require dynamic models of biomass evolution (plant, animal and/or microbial) All these chemical forms are directly related to biomass (spatial and temporal growth), unlike other radionuclides

EMRAS II, Paris, 09/28/2009 Current 14 C and 3 H modeling in TOCATTA Presentation of TOCATTA § Multiple source term kinetics : normal / accidental modes § Main environmental media : agricultural systems (soil, plant & animals) § Atmospheric and/or liquid releases § Temporal scales : ü Daily time step ü During one or several years § Dose man calculations through ingestion of contaminated foodstuffs (SYMBIOSE)

Presentation of TOCATTA Diffusion 14 CO 2 HTO vapor Precipitation Source HT O 14 CO 2 NetPrimaryProductio n Foliar absorptio n Evapotranspiratio n irrigation Root absorption 14 C pathways 3 H pathways 14 C and 3 H pathways infiltration Microbial activity HTO 14 C organic Évaporation HTO OBT translocatio n Literfall HTO Biological decay EMRAS II, Paris, 09/28/2009

Conceptual model Presentation of TOCATTA Plant (Organ) OrganicMatter RadioactiveDecay BiologicalGrowth Grazing* RestOfPlant NetPrimaryProduction Diffusion RestOfWorld Ø Carbon 14 Plant (Organ ) Water RadioactiveDecay BiologicalDec ay Grazing* OrganicMatter RadioactiveDecay BiologicalGrowth Grazing * RestOfPlant FoliarAbsorption WetInputPlant  Translocati on RootUptake  Translocation NetPrimaryProductionRestOfWorl d Ø Tritium *For grass only Winter cereals Spring cereals Fruit vegetable Root vegetables Leaf vegetables Grass Winter cereals Spring cereals Fruit vegetable Root vegetables Leaf vegetables Grass

Mathematical model (1) EMRAS II, Paris, 09/28/2009 Presentation of TOCATTA § First order differential equations § Mass conservation balance of pollutant in each compartment § Example : Transfer of 14 CO 2 from Air to Grass : NetPrimaryProduction Diffusion Grazing RadioactiveDecay Plant dry density Logistic or exponential model

Mathematical model (2) EMRAS II, Paris, 09/28/2009 Presentation of TOCATTA Assumptions : 1. Use of a daily time step (current version) 2. Isotopic equilibrium between newly created plant biomass and surrounding air, at each time step 3. Growth curves are logistics (cereals) or exponential (grass, leaf-, fruit- or root vegetables) 4. Isotopic discrimination factor for tritium entering plant organic matter

EMRAS II, Paris, 09/28/2009 VATO VAlidation of TOcatta Presentation of VATO Séverine Le Dizès 1, Denis Maro 2 & Didier Hébert 2 1 IRSN/DEI/Environmental Modelling Laboratory/Cadarache, St-Paul-lez- Durance 2 IRSN/Laboratory of Continental Radioecology/Cherbourg-Octeville

EMRAS II, Paris, 09/28/2009 Goals v Estimate fluxes of 14 C and 3 H in a grassland ecosystem (Raygrass), in relation with : - 14 C and 3 H concentrations in air, - Climate conditions, - Land use (grazing, maïze silage and hay). v Study transferts of 14 C and 3 H to cows and cowmilk in function of the alimentary diet. In order to validate the TOCATTA model Presentation of VATO

EMRAS II, Paris, 09/28/2009 Agenda Carbon : Transfers between air, grass and soil Tritium 2010 : Measurement (speciation of 3 H releases in air) : Transfers to cow : Model-measures comparisons 2010 : Publication : Transfers between air, rain water, grass and soil 2012 : Transfers to cow 2012 : Publication : Model-measures comparison Presentation of VATO

Site location EMRAS II, Paris, 09/28/2009 « Atelier Nord » : a well located experimental site, considering the most frequent wind directions Important concentrations in the environment Presentation of VATO    Important releases of 14 C and 3 H by the AREVA NC La Hague reprocessing plant

Experimental design Presentation of VATO Continuously Recording Field Monitor for Krypton m mast with sonic anemometer (turbulence) Weather station Lab Meteorological data acquisition CO 2 measurement acquisition (LICOR 7000) Fram Grass (Raygrass) 14 C trapping device (bubbe gas through soda)

EMRAS II, Paris, 09/28/2009 Presentation of VATO 1. Use of a daily time step 3. Air concentration data are measured each month Ø Daily air concentration inputs are assumed to be constant over the month 2. Grass growth is linear based on monthly dry weight data Ø Estimation of a daily growth rate Main assumptions of the plant submodel

EMRAS II, Paris 09/28/2009 Comparison of measured and calculated 14 C specific activities Presentation of VATO Measured Grass 14 C activities > Measured Air 14 C activities > Simulated Grass 14 C activities

EMRAS II, Paris 09/28/2009 Two ways of improving the comparison between modeled/measured activities : 1. Regarding the model itself : the specific activity concept is adapted for chronic releases Need to improve the model in terms of kinetics to adapt it to time varying releases and meteorology Use of an hourly-based growth model for grass in function of local meteorological data 2. Regarding the 14 C releases : the atmospheric 14 C concentrations are measured on a monthly basis Need to improve the calculations in terms of kinetics (e.g. every hour) Presentation of VATO Use of the hourly 85 Kr data

EMRAS II, Paris 09/28/2009 Presentation of VATO A model of grass growth Johnson et al. (1983) A model of Grass Growth, Ann. Bot. 51, Johnson and Thornley (1983) Vegetative crop growth model incorporating leaf area expansion and senescence, and applied to grass, Plant, Cell and Environment 6, § A compartmental model based on an hourly time step Storage dry weight, W S Light interception Photosynthesis Root growth and maintenance Structural dry weight, W G Growth respiration, R g Maintenance respiration, R m Senescence Growth, G

EMRAS II, Paris 09/28/2009 Presentation of VATO Calculation of atmospheric 14 C on an hourly basis Krypton 85 : a good indicator of 14 C atmospheric dispersion over a short periodicity Hourly 14 C atmospheric concentration

EMRAS II, Paris 09/28/2009 Comparison of measured and calculated aboveground dry matter Presentation of VATO

EMRAS II, Paris 09/28/2009 Comparison of measured and calculated 14 C specific activities Presentation of VATO

EMRAS II, Paris 09/28/2009 Conclusions Presentation of VATO § To adapt the model to time varying releases and meteorology, an hourly time-step is required : § The VATO projects supports the approach to use plant physiological parameters within 14 C (and tritium) models Ø To estimate 14 C air concentration inputs to the model, based on hourly 85 Kr data Ø To simulate photosynthesis and plant growth dynamics

EMRAS II, Paris 09/28/2009 Perspectives Presentation of VATO § To adress dynamic modeling of 14 C and 3 H in plants, ongoing effort should be addressed to improve the modelling of photosynthesis and dry matter production § Concerning 3 H modelling in case of time varying releases and meteorology, it is also necessary to consider most of the relevant water transfer processes with a dynamic approach based on a short time step. § Use of PASIM*, a biogeochemical grassland ecosystem model that simulates fluxes of C, N, water and energy at the soil-plant atmosphere interface. *Riédo et a., A Pasture Simulation Model for dry matter production, and fluxed of carbon, nitrogen, water and energy. Ecol. Model. 105, A collaboration starts in October with INRA (Clermont-Ferrand).

EMRAS II, Paris, 09/28/2009 Compartment models (1) Advantages ü Simple structure (e.g. Model of Johnson, 2 compartments) ü Generic, flexible : can be used to test scenarios ü Simple ordinary differential equations ü A simplification of the mathematical model (variables are represented as singli scalars instead of spatially distributed fields)

EMRAS II, Paris, 09/28/2009 Compartment models (2) Drawbacks ü Can not be spatially explicit (e.g.PaSim : no spatial heterogeneity) ü The model parameters are less likely to be physiological (constant coefficients)

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