LRE 1 URANIUM(VI) SPECIATION: MODELLING, UNCERTAINTY AND RELEVANCE TO BIOAVAILABILITY MODELS....
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Transcript of LRE 1 URANIUM(VI) SPECIATION: MODELLING, UNCERTAINTY AND RELEVANCE TO BIOAVAILABILITY MODELS....
1
LRE
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 1Laboratory of Radioecology & Ecotoxicology
Laboratory of Radioecology & Ecotoxicology, IRSN/DEI/SECRE/LRE, Cadarache, France
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LRE 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 UO2
2+ 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
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LRE MODELLING METAL BIOAVAILABILITY: A HISTORICAL PERSPECTIVE
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
Studies over the past 30 years have shown that a metal’s total concentration is a poor indicator of availability or toxicity
Various models built upon the equilibrium paradigm have been proposed: FIAM - Free Ion Activity Model
GSIM - Gill Surface Interaction ModelBLM - Biotic Ligand Model
This approach is analogous to Surface Complexation Modelling and therefore integrates easily with existing speciation models
4
LRE THE USE OF BIVALVES IN METAL – ORGANISM INTERACTION STUDIES
Bivalves are frequently used for biomonitoring studies, ideal for long duration monitoring due to:
• For benthic species, their location at the sediment-water interface exposes them to contamination from both sources
• Respiration and feeding by water ventilation ensuring a high throughput of environmental medium
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
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LRE
External solution
Internal solution
Cell interior
STEPS INVOLVED IN THE ACCUMULATION OF U(VI) BY BIVALVES
Internalised U(VI)
2
If ventilation rate varies as a function of water composition this will confound interpretation of U(VI) accumulation in terms of solution speciation
Ventilation rate
[UO2]T
Inhalant siphon
Exhalant siphon
UO22+
1
Transporter – U(VI) complex
Li (OH-, PO4, CO3)
UO2-
X
UO2Li
6
LRE
0
10
20
30
40
50
60
70
5.5 6.5pH
Va
lve
op
en
tim
e/ %
N = 94
N = 96
Effect of pH on valve opening (no U)
0
10
20
30
40
50
60
70
0 1 2[U] / µmol dm-3
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 bioavailabilityTo minimise behavioural effects isolated gill tissues exposed
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LRE PROCESSES INVOLVED IN METAL ACCUMULATION
1. Mass transport of metalfrom bulk solution
2. Metal’s speciation at biological interface
3. Formation of metal – transporter complex
4. Trans-membrane transport of metal
1.2.3.
4.
4.
8
LRE ASSUMPTIONS OF THE EQUILIBRIUM PARADIGM
1. Internalisation of metal rate-limiting step
SLOW FAST 2. Internalisation kinetics first order
Application of equilibrium based models requires measurement or prediction of the metal’s speciation
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
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LRE 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 predict speciation
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
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LRE URANIUM SPECIATION: STATE OF THE ART
Uranium(VI) has an extensive solution chemistry forming strong complexes with many ligands, both inorganic (OH-, CO3
2-, 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)
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LRE 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
LRE 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
N
NATURAL
SYSTEM
F
FORMAL
SYSTEM
ENCODING
DECODING
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LRE 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)
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LRE 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
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LRE EXPERIMENTAL DESIGN FOR URANIUM ACCUMULATION EXPERIMENTS
Factors influencing the solution speciation of U(VI) were varied independently:
All experiments were performed at constant ionic strength (0.01)
Citrate concentration: 0 – 10 µM
Carbonate concentration: 10 µM – 10 mM
Phosphate concentration: 0 – 100 µM
Uranium concentration: 10 nM – 10 µMpH: 5 – 7.5
Concentrations of potentially competing cations were varied:
Calcium and Magnesium concentrations: 10 µM – 2.5 mMSodium and Potassium concentrations: 300 µM – 4.3 mMProton concentration: 30 nM – 10 µM
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LRE U(VI) UPTAKE BY EXCISED GILLSEFFECT OF CITRATE
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LRE U(VI) UPTAKE BY EXCISED GILLSEFFECT OF pH AND [UO2]T
18
LRE U(VI) UPTAKE BY EXCISED GILLSEFFECT OF pH AND [CO3]T
19
LRE U(VI) UPTAKE BY EXCISED GILLSEFFECT OF [Ca] AND [Mg]
20
LRE OVERVIEW OF RESULTS
The expected decrease in uranium uptake on increasing complexation was observed for citrate and carbonate (pH 7 & 7.5)
No significant change in uptake was observed on varying calcium and magnesium concentrations at constant ionic strengthThe results cannot be explained by a simple dependence on the free uranyl–ion concentration
However, increasing complexation by carbonate (pH 5 & 6) did not decrease uptake – opposite effect for carbonate suggesting accumulation of a carbonate species
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
LRE 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
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LRE
1. 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 conditions1, 2 or 3 Uranium species considered to form
transporter complexes: UO22+, UO2OH+,
UO2(OH)20, UO2CO3
0, UO2HPO40
Single or multiple membrane transporters
Potential H+ competition for transporter site
62 MODELS
5. No significant modification of the biological interface occurs
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
6. The activity of the involved transport systems is constant for all conditions
5. No significant modification of the biological interface occurs
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
MODELS TESTED
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LRE 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
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LRE •Summary of model fitting:
Increasing model complexity
Increa
sing
do
main
Adjustable parameters 1 2 2 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6
Modelling performed with mean-value thermodynamic database
pH variable, PCO2=1, [Cit]=0pH variable, PCO2=1, [Cit] variablepH variable, PCO2 variable, [Cit]=0pH variable, PCO2 variable, [Cit] variable
passes 0.1passes 0.01fails 0.01
Modelling performed integrating thermodynamic database uncertainty
pH variable, PCO2=1, [Cit]=0pH variable, PCO2=1, [Cit] variablepH variable, PCO2 variable, [Cit]=0pH variable, PCO2 variable, [Cit] variable
% that pass 0.011 - 2525 - 50> 50
Adjustable parameters 1 2 2 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 5 6 6 6 6 6 6
Modelling performed with mean-value thermodynamic database
pH variable, PCO2=1, [Cit]=0pH variable, PCO2=1, [Cit] variablepH variable, PCO2 variable, [Cit]=0pH variable, PCO2 variable, [Cit] variable
passes 0.1passes 0.01fails 0.01
Modelling performed integrating thermodynamic database uncertainty
pH variable, PCO2=1, [Cit]=0pH variable, PCO2=1, [Cit] variablepH variable, PCO2 variable, [Cit]=0pH variable, PCO2 variable, [Cit] variable
% that pass 0.011 - 2525 - 50> 50
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LRE 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
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LRE 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
LRE ACKNOWLEDGEMENTS
IRSN-LREJacqueline 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