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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 1
Laboratory of Radioecology & Ecotoxicology
Laboratory of Radioecology & Ecotoxicology, IRSN/DEI/SECRE/LRE, Cadarache, France
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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
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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
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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
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STEPS INVOLVED IN THE ACCUMULATION OF U(VI)
BY BIVALVES
External
solution
1
Inhalant
siphon
[UO2]T
Internal
solution
UO22+
2
Cell
interior
UO2-X
UO2Li
Exhalant
siphon
Ventilation
rate
Li (OH-, PO4, CO3)
Transporter –
U(VI) complex
Internalised
U(VI)
If ventilation rate varies as a function of water composition this will
confound interpretation of U(VI) accumulation in terms of solution
speciation
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THE BEHAVIOUR OF THE ORGANISMS IS MODIFIED
BY THE EXPOSURE MEDIUM
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Effect of pH on valve opening (no U)
Valve open time/ %
70
Effect of uranium on valve opening
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N = 94
60
60
50
50
N = 96
40
40
30
30
20
20
10
10
0
0
5.5
pH
6.5
0
1
-3
[U] / µmol dm
2
Objective of this study: Investigate effects of chemical speciation on
uranium bioavailability
To minimise behavioural effects isolated gill tissues exposed
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PROCESSES INVOLVED IN METAL ACCUMULATION
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4.
3.
4.
2.
1.
1.
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
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ASSUMPTIONS OF THE EQUILIBRIUM PARADIGM
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SLOW
FAST
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 conditions
Application of equilibrium based models requires measurement
or prediction of the metal’s speciation
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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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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)
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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
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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
ENCODING
N
F
NATURAL
FORMAL
SYSTEM
SYSTEM
DECODING
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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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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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EXPERIMENTAL DESIGN FOR URANIUM
ACCUMULATION EXPERIMENTS
Factors influencing the solution speciation of U(VI) were varied
independently:
Uranium concentration: 10 nM – 10 µM
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)
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U(VI) UPTAKE BY EXCISED GILLS
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EFFECT OF CITRATE
10-5
[UO2]T = 500 nM
Uptake rate/ mol g-1 h-1
pH 5
pH 6
10-6
10-7
0
10-6
10-5
10-5
[Citrate]/ mol dm-3
10-5
10-5
10-8
10-7
[UO22+]/ mol dm-3
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U(VI) UPTAKE BY EXCISED GILLS
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EFFECT OF pH AND [UO2]T
10-4
Uptake rate/ mol g-1 h-1
pH 5
pH 6
pH 7
10-5
10-6
10-7
10-8
10-7
10-6
[UO2]T/ mol dm-3
10-5
10-10
10-9
10-8
10-7
2+
[UO2 ]/ mol dm-3
10-6
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U(VI) UPTAKE BY EXCISED GILLS
EFFECT OF pH AND [CO3]T
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U(VI) UPTAKE BY EXCISED GILLS
EFFECT OF [Ca] AND [Mg]
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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
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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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MODELS TESTED
1, 2 or 3 Uranium species
considered to form
NON-COMPETITIVE
H+ INTERACTION
transporter complexes: UO22+, UO2OH+,
1, 2 or 3 Uranium
species considered to form
UO2(OH)20, UO2CO30, UO2HPO40
transporter complexes
Single or multiple membrane transporters
Stability constant
Transporter
kinetics
of vary
metalas
species
a function
– of pH
+
Potential Hcomplex
competition
site
transporter
variesfor
astransporter
a function of
pH
10 MODELS
62 MODELS
10 MODELS
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 conditions
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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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•Summary of model fitting:
Increasing model complexity
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
Increasing domain
Modelling performed with mean-value thermodynamic database
pH variable, PCO2=1, [Cit]=0
pH variable, PCO2=1, [Cit] variable
pH variable, PCO2 variable, [Cit]=0
pH variable, PCO2 variable, [Cit] variable
passes 0.1
passes 0.01
fails 0.01
Modelling performed integrating thermodynamic database uncertainty
pH variable, PCO2=1, [Cit]=0
pH variable, PCO2=1, [Cit] variable
pH variable, PCO2 variable, [Cit]=0
pH variable, PCO2 variable, [Cit] variable
% that pass 0.01
1 - 25
25 - 50
> 50
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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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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)
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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
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