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Programme INTERREG III A : STARDUST

Programme INTERREG III A : STARDUST. VLIZ. S patial and T emporal A ssessment of high R esolution D epth profiles U sing novel S ampling T echnologies. Model l ing metal speciation and behaviour in sediments. Lille, March 18, 2005.

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Programme INTERREG III A : STARDUST

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  1. Programme INTERREG III A : STARDUST VLIZ Spatial and Temporal Assessment of high Resolution Depth profiles Using novel Sampling Technologies Modelling metal speciation and behaviour in sediments Lille, March 18, 2005

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

  3. DGT in sediments • 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 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 • 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 • 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 • Metotal = Melabile + Menon-labile where Metotal = DET Melabile = DGT Menon-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 • Single site complexing model for the complexation of metals with humic materials: • 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 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 • 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)

  10. Results: Amino acids (log K1~ k2)

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

  12. DGT device in sediments • Diffusion only case • Fully sustained case • Intermediate case

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

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

  15. DIFS • R value (remobilisation rate) R= C-DGT • Introduce R in the model: Kdl and Tc can be calculated • 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 sedimentsDiagenetic modeling(CEMO, Yrseke)

  17. Diagentic modeling • Pathways of organic matter mineralisation • Coupling among the biogeochemical cycles of C, N, O, S, Mn, Fe, ... • 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 • Mineralisation • Precipitation/dissolution • Equilibria, ... • Establish mass balance calculations • Building of the model for each element which reactions are important • 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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