VLIZ

Spatial and Temporal Assessment of high Resolution Depth profiles Using novel Sampling Technologies

Lille, March 18, 2005

ModelModellling metal speciation and ing metal speciation and behaviour in sedimentsbehaviour in sediments

ModelModellling metal speciation and ing metal speciation and

behaviour in sedimentsbehaviour in sediments

1.1. Trace metal speciation Trace metal speciation (multi-ligand model)(multi-ligand model)

2.2. Kinetics of metal Kinetics of metal remobilisation in remobilisation in sediments (DIFS model)sediments (DIFS model)

3.3. Diagenetic modelDiagenetic model

3 different modelling approaches:

From DGT-data

DGT in sedimentsDGT in sediments• Separates species according to sizeSeparates species according to size: :

– only small labile species can diffuse through the only small labile species can diffuse through the diffusive gel and be bound on the Chelex geldiffusive gel and be bound on the Chelex gel

• DGT separates species according to DGT separates species according to their labilitytheir lability::– DGT device acts as a sink for the metals in DGT device acts as a sink for the metals in

porewaters: the metal concentration in porewaters: the metal concentration in porewater will decrease unless there is a fast porewater will decrease unless there is a fast remobilisation from the solid phaseremobilisation from the solid phase

– Remobilisation rate can be estimated by:Remobilisation rate can be estimated by:• DGT devices with different deployment times or DGT devices with different deployment times or

different diffusive gel different diffusive gel thicknessesthicknesses • Independant measurement of labile metal speciesIndependant measurement of labile metal species

I. I. Modelling metal speciation in Modelling metal speciation in

porewatersporewaters Adriano Agnese and Marco SantonAdriano Agnese and Marco Santon

Master Thesis (March 2005)Master Thesis (March 2005)

Promotor W. Baeyens and M. ElskensPromotor W. Baeyens and M. Elskens

ObjectivesObjectives

• To obtain information about the extent to which To obtain information about the extent to which metals are organically bound in natural watersmetals are organically bound in natural waters

• Two principal aims:Two principal aims:– Firstly to use DET and DGT measurements to determine Firstly to use DET and DGT measurements to determine

total and labile metal fractions with a high resolution total and labile metal fractions with a high resolution profile. profile.

– Secondly to use these measurements in a multi-element Secondly to use these measurements in a multi-element multi-ligand interaction model to provide free metal multi-ligand interaction model to provide free metal concentrations and investigate the extent to which these concentrations and investigate the extent to which these metals are organically bound. metals are organically bound.

AssumptionsAssumptions

• MeMetotaltotal = Me = Melabilelabile + Me + Menon-labilenon-labile

where where MeMetotaltotal = DET= DET

MeMelabile labile = DGT= DGT

MeMenon-labilenon-labile = DET-DGT= DET-DGT

It is assumed that the labile fraction mainly represents It is assumed that the labile fraction mainly represents inorganic metal species and the non-labile fraction inorganic metal species and the non-labile fraction the organically bound metal (strongly bound)the organically bound metal (strongly bound)

ToolsTools

• Multi-element multi-ligand Multi-element multi-ligand interaction model to provide interaction model to provide free metal concentration and free metal concentration and investigate the extent of investigate the extent of inorganic metal complexationinorganic metal complexation

• Single site complexing model Single site complexing model for the complexation of for the complexation of metals with humic materials: metals with humic materials:

• Two-site complexing model Two-site complexing model for the complexation of for the complexation of metals with amino-acidsmetals with amino-acids

j

j

m

i i j i jj 1

n

j j i i ji 1

DGTMe Me Me L

TL L Me L

Hum freefree

DGT DETL

Me

free

21 free 1 2

free

DGT DETL L

Me

ProceduresProcedures

• The multi-element multi-ligand interaction model The multi-element multi-ligand interaction model represents a set of non-linear equations that are solved represents a set of non-linear equations that are solved with a Weighted Least Squares techniquewith a Weighted Least Squares technique

• The free ion activity coefficients required to make activity The free ion activity coefficients required to make activity corrections in the model is performed with the Davies corrections in the model is performed with the Davies Equation. It takes into account ionic strength and Equation. It takes into account ionic strength and temperature effects. temperature effects.

• Uncertainty on the final model results are quantified with Uncertainty on the final model results are quantified with Monte-Carlo simulationsMonte-Carlo simulations

• Stability constants for humic and amino-acids interactions Stability constants for humic and amino-acids interactions are assessed using DOC profile and average molecular are assessed using DOC profile and average molecular mass given by Schwarzenbach et al. [1993] mass given by Schwarzenbach et al. [1993]

Results: Humic acid (log K)Results: Humic acid (log K)RefRef SiteSite CuCu CdCd ZnZn

This studyThis study WarnetonWarneton 9.0–10.99.0–10.9 8.0-10.38.0-10.3 7.0-8.97.0-8.9

Mantoura Mantoura et al. 1978et al. 1978

In vitroIn vitro 8.9.0–11.48.9.0–11.4 4.6-5.14.6-5.1 4.8-5.94.8-5.9

Vanden Vanden berg et al. berg et al.

19871987

ScheldtScheldt 11.8-14.011.8-14.0 8.6-10.68.6-10.6

Baeyens et Baeyens et al. 1993al. 1993

ScheldtScheldt 10.610.6 8.98.9 9.19.1

Results: Amino acids (log KResults: Amino acids (log K11 ~~ k k22))

RefRef SiteSite CuCu CdCd ZnZn

This studyThis study WarnetonWarneton 5.1-6.35.1-6.3 4.7-5.94.7-5.9 4.0-5.14.0-5.1

Valenta et Valenta et al. 1986al. 1986

In vitroIn vitro 6.7-8.66.7-8.6 4.0-5.04.0-5.0 5.05.0

Baeyens et Baeyens et al. 1993al. 1993

ScheldtScheldt 7.87.8 6.96.9 7.07.0

II. DGT induced fluxes in II. DGT induced fluxes in sediments (DIFS)sediments (DIFS)

(Harper, 1998)

Sediment

Con

cent

ratio

n

g Distance into sediment

Ca

Cpw

Resin layer

diffusion gel

filter}diffusion layer

(c)(b)

(a)

a) Diffusion only caseb) Fully sustained casec) Intermediate case

DGT device in sediments

DIFS: AssumptionsDIFS: Assumptions

• Only two labile pools (dissolved, sorbed)Only two labile pools (dissolved, sorbed)

• First order reversible reactionFirst order reversible reactionC soln CsolidC soln Csolid

• Only passive mobilisation due to a decrease Only passive mobilisation due to a decrease in metal concentration in porewaterin metal concentration in porewater

• 1D model1D model

• Homogeneous sedimentHomogeneous sediment

k1

K-1

removal

Resingel

Diffusivegel

diffusion diffusion

C soln C lsolidk1

K-1

DIFS: model componentsDIFS: model components

Labile Kdl = C-labile-solid

Response time

Tc = 1

Large Tc- slow responseSmall Tc-rapid response

C soln

K1 + k-1

DIFSDIFS• R value (remobilisation rate)R value (remobilisation rate)

R= C-DGTR= C-DGT

• Introduce R in the model: Kdl and Tc Introduce R in the model: Kdl and Tc can be calculatedcan be calculated

• Introduce all parameters in the Introduce all parameters in the model: simulation of DGT behaviourmodel: simulation of DGT behaviour

C-labile porewater

C-labile porewater: measured or calculated by speciation model

III. Modeling reactive III. Modeling reactive transport in aquatic transport in aquatic sedimentssediments

Diagenetic modelingDiagenetic modeling(CEMO, Yrseke)(CEMO, Yrseke)

Diagentic modelingDiagentic modeling

• Pathways of organic matter Pathways of organic matter mineralisationmineralisation

• Coupling among the biogeochemical Coupling among the biogeochemical cycles of C, N, O, S, Mn, Fe, ...cycles of C, N, O, S, Mn, Fe, ...

• Recent developments: build models Recent developments: build models in commercially available software: in commercially available software: FEMLABFEMLAB(older models Fortran codes)(older models Fortran codes)

Diagentic modelingDiagentic modeling• Identify for the test site (Warneton) most important Identify for the test site (Warneton) most important

reactionsreactions– MineralisationMineralisation– Precipitation/dissolutionPrecipitation/dissolution– Equilibria, ...Equilibria, ...

• Establish mass balance calculationsEstablish mass balance calculations

• Building of the model for each element which Building of the model for each element which reactions are importantreactions are important

• Model can then be used to reproduce porewater Model can then be used to reproduce porewater and solid phase constituents:and solid phase constituents:– Under present conditionsUnder present conditions– Under varying environmental conditions: higher oxygen Under varying environmental conditions: higher oxygen

concentrations, less organic matter, ...concentrations, less organic matter, ...