URANIUM(VI) SPECIATION: MODELLING, UNCERTAINTY AND RELEVANCE TO BIOAVAILABILITY MODELS.

1. URANIUM(VI) SPECIATION: MODELLING, UNCERTAINTY AND RELEVANCE TO BIOAVAILABILITY MODELS. APPLICATION TO URANIUM UPTAKE BY THE GILLS OF A FRESHWATER BIVALVE Frank Denison University of Aix-Marseille 1 Laboratory of Radioecology & Ecotoxicology Laboratory of Radioecology & Ecotoxicology, IRSN/DEI/SECRE/LRE, Cadarache, France

2. URANIUM: A FRESHWATER CONTAMINANT Uranium is a widely distributed naturally occurring element In oxic surface-waters uranium is predominantly found in the +6 oxidation state, as the UO22+ oxyion Various industrial activities mainly related to the nuclear fuel cycle can result in environmental contamination Uranium has a double toxicity: both radiological and chemical To properly assess the impact of uranium contamination on the biota, factors that can modify its bioavailability and/or toxicity need to be accounted for Factors that influence a metal’s bioavailability include both the physico-chemical characteristics of the exposure medium and biological factors such as the behaviour or physiological status of the exposed organisms

3. MODELLING METAL BIOAVAILABILITY: A HISTORICAL PERSPECTIVE Studies over the past 30 years have shown that a metal’s total concentration is a poor indicator of availability or toxicity In many studies the measured or modelled concentration of the free metal ion found to be correlated with toxicity or availability Steady-state or equilibrium approaches to modelling metal – organism interactions, considering the equilibrium established between the exposure water and the biosurface, dominate the literature Various models built upon the equilibrium paradigm have been proposed: FIAM - Free Ion Activity Model GSIM - Gill Surface Interaction Model BLM - Biotic Ligand Model This approach is analogous to Surface Complexation Modelling and therefore integrates easily with existing speciation models

4. THE USE OF BIVALVES IN METAL – ORGANISM INTERACTION STUDIES Bivalves are frequently used for biomonitoring studies, ideal for long duration monitoring due to: • Respiration and feeding by water ventilation ensuring a • high throughput of environmental medium • For benthic species, their location at the sediment-water • interface exposes them to contamination from both sources Bivalves can respond to unfavourable conditions by reducing or stopping water ventilation (“clamming up”) This behavioural response may give difficulties for the interpretation of accumulation studies over time scales where this phenomenon is significant

5. External solution Internal solution Cell interior 1 2 Inhalant siphon UO2-X UO22+ [UO2]T UO2Li Exhalant siphon Li (OH-, PO4, CO3) Ventilation rate Transporter – U(VI) complex Internalised U(VI) STEPS INVOLVED IN THE ACCUMULATION OF U(VI) BY BIVALVES If ventilation rate varies as a function of water composition this will confound interpretation of U(VI) accumulation in terms of solution speciation

6. Effect of pH on valve opening (no U) Effect of uranium on valve opening THE BEHAVIOUR OF THE ORGANISMS IS MODIFIED BY THE EXPOSURE MEDIUM Objective of this study: Investigate effects of chemical speciation on uranium bioavailability To minimise behavioural effects isolated gill tissues exposed

7. 4. 3. 2. 1. 4. PROCESSES INVOLVED IN METAL ACCUMULATION • Mass transport of metal • from bulk solution 2. Metal’s speciation at biological interface 3. Formation of metal – transporter complex 4. Trans-membrane transport of metal

8. FAST 2. Internalisation kinetics first order SLOW 3. Metal’s speciation in the vicinity of the interface same as in bulk solution 4. Metal-transporter complex in equilibrium with dissolved metal species 5. No significant modification of the biological interface occurs 6. The activity of the involved transport systems is constant for all conditions ASSUMPTIONS OF THE EQUILIBRIUM PARADIGM • Internalisation of metal rate-limiting step Application of equilibrium based models requires measurement or prediction of the metal’s speciation

9. URANIUM SPECIATION: STATE OF THE ART Analytical techniques to directly measure the solution speciation of uranium not yet available for environmental concentrations Thermodynamic equilibrium models used to predictspeciation Structural chemical model generally well known, however thermodynamic model constants uncertain: literature values of constants quite disperse for some species • A new database was compiled to meet the requirements of: • Internal consistency • Coherent to domain of application • Traceability to original data sources • Containing uncertainty estimations for all values Data sources included: OECD-NEA, IUPAC and NIST databases, original articles

10. URANIUM SPECIATION: STATE OF THE ART Uranium(VI) has an extensive solution chemistry forming strong complexes with many ligands, both inorganic (OH-, CO32-, PO43-…) and organic (EDTA, Citrate, NOM…) Very significant changes to the distribution of U(VI) species occur on varying environmentally important solution composition parameters (e.g. pH, [CO3]T, [PO4]T)

11. URANIUM SPECIATION: UNCERTAINTY The modelled solution speciation of U(VI) is limited by the uncertainty of the thermodynamic constants A computer program was written to perform uncertainty calculations by Monte Carlo analysis

12. ENCODING N NATURAL SYSTEM F FORMAL SYSTEM DECODING THE MODELLING PROCESS The process of modelling involves the establishment of a relation between a natural system and the formal (model) system by the opposite processes of ENCODING and DECODING

13. THE MODELLING PROCESS The process of encoding is a creative act and depends on a number of poorly defined factors including: • What models have been successfully applied previously • State of knowledge of processes involved in natural system • Personal preference and scientific background of the modeller • Experimental design: • Input factors of natural system that are varied • Independence of input factors (interpretation of natural • system output can be confounded if input factors are • not varied independently) • Input parameter space investigated e.g. the chemical • composition domain (may be subject to bias • from preconceived ideas about the natural system)

14. EXPERIMENTAL DESIGN FOR URANIUM ACCUMULATION EXPERIMENTS The experimental design selected for performing the accumulation experiments was strongly influenced by the prevailing approaches to understanding metal – organism interactions: • Accumulation is governed by the formation of metal – • transporter complex(es) • These complexes are in equilibrium with dissolved metal • species • Competition between U(VI) and other cationic species for • the transporter binding site may occur Although these preconceptions may bias subsequent model encoding, this is a valid approach to test the prevailing equilibrium paradigm of metal – organism interactions

15. EXPERIMENTAL DESIGN FOR URANIUM ACCUMULATION EXPERIMENTS Factors influencing the solution speciation of U(VI) were varied independently: Uranium concentration: 10 nM – 10µM pH: 5 – 7.5 Citrate concentration: 0 – 10 µM Carbonate concentration: 10 µM – 10 mM Phosphate concentration: 0 – 100 µM Concentrations of potentially competing cations were varied: Calcium and Magnesium concentrations: 10 µM – 2.5 mM Sodium and Potassium concentrations: 300 µM – 4.3 mM Proton concentration: 30 nM – 10 µM All experiments were performed at constant ionic strength (0.01)

16. U(VI) UPTAKE BY EXCISED GILLS EFFECT OF CITRATE

17. U(VI) UPTAKE BY EXCISED GILLS EFFECT OF pH AND [UO2]T

18. U(VI) UPTAKE BY EXCISED GILLS EFFECT OF pH AND [CO3]T

19. U(VI) UPTAKE BY EXCISED GILLS EFFECT OF [Ca] AND [Mg]

20. OVERVIEW OF RESULTS The expected decrease in uranium uptake on increasing complexation was observed for citrate and carbonate (pH 7 & 7.5) However, increasing complexation by carbonate (pH 5 & 6) did not decrease uptake – opposite effect for carbonate suggesting accumulation of a carbonate species No significant change in uptake was observed on varying calcium and magnesium concentrations at constant ionic strength The results cannot be explained by a simple dependence on the free uranyl–ion concentration Several hypotheses may be forwarded to explain the observed pH dependence: accumulation of U – OH species, H+ competition for binding sites, or non-competitive H+ inhibition

21. MODELS TESTED A number of different uptake models can be proposed based on the equilibrium paradigm involving: • One or several metal species – transporter complex(es) • One or several independent membrane transporters • Competition for the transporter binding site(s) by H+ • Non–competitive inhibition of uptake by H+ A multi-hypotheses approach was adopted: a number of different models of increasing complexity were applied to the results

22. 5. No significant modification of the biological interface occurs 5. No significant modification of the biological interface occurs 6. The activity of the involved transport systems is constant for all conditions MODELS TESTED • Internalisation of metal rate-limiting step 2. Internalisation kinetics first order 3. Metal’s speciation in the vicinity of the interface same as in bulk solution 4. Metal-transporter complex in equilibrium with dissolved metal species 5. No significant modification of the biological interface occurs 6. The activity of the involved transport systems is constant for all conditions 1, 2 or 3 Uranium species considered to form transporter complexes: UO22+, UO2OH+, UO2(OH)20, UO2CO30, UO2HPO40 NON-COMPETITIVE H+ INTERACTION 1, 2 or 3 Uranium species considered to form transporter complexes Stability constant of metal species – transporter complex varies as a function of pH 10 MODELS NON-COMPETITIVE H+ INTERACTION 1, 2 or 3 Uranium species considered to form transporter complexes Transporter kinetics vary as a function of pH 10 MODELS Single or multiple membrane transporters Potential H+ competition for transporter site 62 MODELS

23. CHEMICAL COMPOSITION SUB-DOMAINS The chemical composition domain considered for the model fitting can influence the process of model encoding, potentially affecting both model selection and calibration In order to assess the importance of this effect, the chemical composition domain investigated was divided into a number of sub-domains of increasing chemical complexity Each model was then fitted to each chemical composition domain. The best-fit residual values were then tested against the chi-squared distribution, enabling the model hypothesis to be either rejected or retained at a defined probability

24. Summary of model fitting: Increasing model complexity Increasing domain

25. CONCLUSIONS Uranium uptake is strongly influenced by solution composition Equilibrium – based models are successful in describing the system behaviour for relatively simple solution composition domains However, as the chemical domain space increases, an increasing number of hypotheses can be falsified at a high confidence level Although the equilibrium paradigm cannot be rejected as a hypothesis, the level of model complexity required to describe the observed behaviour significantly limits the utility of such an approach Alternative modelling approaches (such as the non-competitive effects of H+ concentration presented) can be proposed to explain the observed uptake behaviour

26. PERSPECTIVES Thermodynamic constants used for predictive speciation modelling are uncertain Input uncertainty propagation limits the predictive ability of speciation modelling. This needs to be considered in order to assess the applicability of this technique The proper implementation of equilibrium – based bioavailability or toxicity models requires: • consideration of speciation modelling uncertainty • the testing of a large chemical composition domain space • (correlation of free metal-ion concentration with measured endpoint for a strong – ligand titration series is NOT sufficient evidence of equilibrium control)

27. ACKNOWLEDGEMENTS IRSN-LRE Jacqueline Garnier-Laplace Christelle Adam Jim Smith Claude Fortin Rodolphe Gilbin Marcel Morello Damien Tran Olivier Simon Danielle Poncet-Bonnard Arnaud Martin-Garin Laureline Février Jan van der Lee Claudine Van Crasbeck Brigitte Ksas Virginie Camilleri Gaëla Grasset