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VLIZ Spatial and Temporal Assessment of high Resolution Depth profiles Using novel Sampling Technologies Lille, March 18, 2005 Modelling metal speciation.

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Presentation on theme: "VLIZ Spatial and Temporal Assessment of high Resolution Depth profiles Using novel Sampling Technologies Lille, March 18, 2005 Modelling metal speciation."— Presentation transcript:

1 VLIZ Spatial and Temporal Assessment of high Resolution Depth profiles Using novel Sampling Technologies Lille, March 18, 2005 Modelling metal speciation and behaviour in sediments

2 1. Trace metal speciation (multi- ligand model) 2. Kinetics of metal remobilisation in sediments (DIFS model) 3. Diagenetic model 3 different modelling approaches: From DGT-data

3 DGT in sediments Separates species according to size : Separates species according to size : –only small labile species can diffuse through the diffusive gel and be bound on the Chelex gel DGT separates species according to their lability : DGT separates species according to their lability : – DGT device acts as a sink for the metals in porewaters: the metal concentration in porewater will decrease unless there is a fast remobilisation from the solid phase –Remobilisation rate can be estimated by: DGT devices with different deployment times or different diffusive gel thicknesses DGT devices with different deployment times or different diffusive gel thicknesses Independant measurement of labile metal species Independant measurement of labile metal species

4 I. Modelling metal speciation in porewaters Adriano Agnese and Marco Santon Master Thesis (March 2005) Promotor W. Baeyens and M. Elskens

5 Objectives To obtain information about the extent to which metals are organically bound in natural waters To obtain information about the extent to which metals are organically bound in natural waters Two principal aims: Two principal aims: –Firstly to use DET and DGT measurements to determine total and labile metal fractions with a high resolution profile. –Secondly to use these measurements in a multi-element multi- ligand interaction model to provide free metal concentrations and investigate the extent to which these metals are organically bound.

6 Assumptions Me total = Me labile + Me non-labile Me total = Me labile + Me non-labile where Me total = DET Me labile = DGT Me non-labile = DET-DGT It is assumed that the labile fraction mainly represents inorganic metal species and the non-labile fraction the organically bound metal (strongly bound)

7 Tools Multi-element multi-ligand interaction model to provide free metal concentration and investigate the extent of inorganic metal complexation Multi-element multi-ligand interaction model to provide free metal concentration and investigate the extent of inorganic metal complexation Single site complexing model for the complexation of metals with humic materials: Single site complexing model for the complexation of metals with humic materials: Two-site complexing model for the complexation of metals with amino-acids Two-site complexing model for the complexation of metals with amino-acids

8 Procedures The multi-element multi-ligand interaction model represents a set of non-linear equations that are solved with a Weighted Least Squares technique The multi-element multi-ligand interaction model represents a set of non-linear equations that are solved with a Weighted Least Squares technique The free ion activity coefficients required to make activity corrections in the model is performed with the Davies Equation. It takes into account ionic strength and temperature effects. The free ion activity coefficients required to make activity corrections in the model is performed with the Davies Equation. It takes into account ionic strength and temperature effects. Uncertainty on the final model results are quantified with Monte- Carlo simulations Uncertainty on the final model results are quantified with Monte- Carlo simulations Stability constants for humic and amino-acids interactions are assessed using DOC profile and average molecular mass given by Schwarzenbach et al. [1993] Stability constants for humic and amino-acids interactions are assessed using DOC profile and average molecular mass given by Schwarzenbach et al. [1993]

9 Results: Humic acid (log K) RefSiteCuCdZn This study Warneton9.0–10.98.0-10.37.0-8.9 Mantoura et al. 1978 In vitro 8.9.0–11.44.6-5.14.8-5.9 Vanden berg et al. 1987 Scheldt11.8-14.08.6-10.6 Baeyens et al. 1993 Scheldt10.68.99.1

10 Results: Amino acids (log K 1 ~ k 2 ) RefSiteCuCdZn This study Warneton5.1-6.34.7-5.94.0-5.1 Valenta et al. 1986 In vitro 6.7-8.64.0-5.05.0 Baeyens et al. 1993 Scheldt7.86.97.0

11 II. DGT induced fluxes in sediments (DIFS) (Harper, 1998)

12 a)Diffusion only case b)Fully sustained case c)Intermediate case DGT device in sediments

13 DIFS: Assumptions Only two labile pools (dissolved, sorbed) Only two labile pools (dissolved, sorbed) First order reversible reaction First order reversible reaction C soln Csolid Only passive mobilisation due to a decrease in metal concentration in porewater Only passive mobilisation due to a decrease in metal concentration in porewater 1D model 1D model Homogeneous sediment Homogeneous sediment k1 K-1

14 removal Resin gel Diffusive gel diffusion C soln C lsolid k1 K-1 DIFS: model components Labile Kdl = C-labile-solid Response time Tc = 1 Large Tc- slow response Small Tc-rapid response C soln K1 + k-1

15 DIFS R value (remobilisation rate) R value (remobilisation rate) R= C-DGT Introduce R in the model: Kdl and Tc can be calculated Introduce R in the model: Kdl and Tc can be calculated Introduce all parameters in the model: simulation of DGT behaviour Introduce all parameters in the model: simulation of DGT behaviour C-labile porewater C-labile porewater: measured or calculated by speciation model

16 III. Modeling reactive transport in aquatic sediments Diagenetic modeling (CEMO, Yrseke)

17 Diagentic modeling Pathways of organic matter mineralisation Pathways of organic matter mineralisation Coupling among the biogeochemical cycles of C, N, O, S, Mn, Fe,... Coupling among the biogeochemical cycles of C, N, O, S, Mn, Fe,... Recent developments: build models in commercially available software: FEMLAB Recent developments: build models in commercially available software: FEMLAB (older models Fortran codes)

18 Diagentic modeling Identify for the test site (Warneton) most important reactions Identify for the test site (Warneton) most important reactions –Mineralisation –Precipitation/dissolution –Equilibria,... Establish mass balance calculations Establish mass balance calculations Building of the model for each element which reactions are important Building of the model for each element which reactions are important Model can then be used to reproduce porewater and solid phase constituents: Model can then be used to reproduce porewater and solid phase constituents: –Under present conditions –Under varying environmental conditions: higher oxygen concentrations, less organic matter,...


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