1. Leaching and geochemical modelling of a metallurgical slag heap
Dr. Mojca Loncnar
Dr. Hans A. van der Sloot, Hans van der Sloot Consultancy, The Netherlands
Assist. Prof. Dr. Marija Zupančič, Faculty of Chemistry and Chemical Technology, University of Ljubljana, Slovenia
Assist. Prof. Dr. Ana Mladenovič, Slovenian National Building and Civil Engineering Institute, Slovenia
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

2. Outline: Case study: Metallurgical slag heap Javornik, Slovenia
Materials
Sampling of heap samples
Groundwater monitoring
Data comparison and geochemical modelling
Results and Discussion
Batch data
pH dependent data (composite sample)
Geochemical modelling
Comparison batch data, GW data and pH dependent data
Conclusions
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

3. Case study: Metallurgical slag heap Javornik
near the town of Jesenice in NW Slovenia
approx. 3 ha large
Landfill area 2 ha
approx t metallurgical wastes
Operation started in 1987
2009 landfilling stopped
73 % slags from carbon and stainless steel production
19 % EAF and VOD dust
8 % refractory material
other wastes
50 m
Source:
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

4. Sampling of heap samples
11 locations on the metallurgical heap
(batch extraction tests + pH dependence test (on composite sample)
Sampled at the depth of around cm below the landfill surface
Sampled at the depth of around 6m below the landfill surface L1 L9 L7 L4 L8 L2 L5
L10 L3 L6
L11
Source:
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

5. Groundwater monitoring (years 2011 – 2015)
7 piezometers
Twice annually
spring, autumn P1
P1 and P2: reference piezometers P4 P2 P3 P7 P5 P6
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

6. Data comparison and Geochemical modelling
The database / expert system LeachXSTM1:
Management of data (the pH dependent leaching data, the batch data, the GW data) and vizualization of the calculated and measured results (in MS Excel)
Geochemical speciation and chemical reaction/transport modelling:
Modelling environment ORCHESTRA
The geochemical modelling:
Mineral sorption (extended MINTEQ database)
Sorption on Fe-oxides (Dzombak & Morel)
Sorption on Al-oxide, dissolved organic carbon (DOC) and particular organic carbon (POM) (interaction according to NICA-DONNAN)
Multi-element modelling taking into the account all (33) measured elements
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

7. Total chemical composition
Chemical composition of the composite landfill sample
Chemical composition of the individual landfill samples
Sampled at the depth of around cm below the landfill surface
Sampled at the depth of around 6m below the landfill surface
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

8. Mineralogy (XRD analysis: the composite landfill sample)
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

9. Mineralogy (SEM-EDS: the micrograph of the prehydrated calcium aluminate grain)
Reaction rim is composed of C-A-H phase, with the typical microstructure of (prismatic) hexagonal cross section
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

10. One-stage batch test (CEN 12457)
Legend:
Inert limit
for waste
Non-hazardous limit for waste
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

11. Modelling of pH dependent data
Multi-element modelling taking into the account all (33) measured elements
Chemical speciation fingerprint (CFS) used for the speciation modelling of metallurgical slag heap
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

12. Modelling of pH dependent data: major elements
Legend:
pH-dep. data
model pred L/S = 10
model pred. L/S = 0.3
Major elements dictate the leaching conditions (pH, Eh, conductivity)
In the case of many elements the measured conc. at L/S = 10 correspond well with the model prediction
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

13. Modelling of pH dependence data: parameters of environmental concern
Legend:
pH-dep. data
model pred L/S = 10
model pred. L/S = 0.3
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

14. Geochemical modelling
Calculated speciation in the liquid and solid phases
Leaching of CALCIUM at pH > 12 was adequate describe by portlandite, calcite, CSH and CAH c
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

15. Geochemical modelling
Calculated speciation in the liquid and solid phases
Leaching of CHROMIUM at alkaline pH controlled by Cr substitution as a solid solution in ettringite
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

16. Comparison of the batch and pH dependent data
The batch data plot along the pH dependent leaching curve
The same solubility controlling phases control leachability
In some samples, Ca is affected by carbonation
Legend:
pH-dependent data batch data (L1-6) batch data (L7-11)
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

17. Comparison of GW data and pH dependent data
The GW data showed lower conc. or fall right on the pH dependent curve
Not big differences in the conc. between the reference piezometers and other piezometers indicating limited influence of the landfill area on the GW data
Legend:
pH-dependent data reference piezometers (P1, P2) piezometers 3-7
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

18. Comparison of the batch, GW data and pH dependent data
The main differences between the batch and pH-dependent data, on the one hand, and GW data, on the other hand, is the contact with the landfill material (solubility control), which is absent in the case of GW monitoring
Legend:
pH-dependent data reference piezometers (P1, P2) piezometers batch data (L1-L6) batch data (L7-L11)
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

19. Conclusion
The modelling approach used in this study provides benefits for understanding the observed leaching behaviour, which is needed in the case of decisions about future management of waste heap.
It can thus form the basis for the projection of the long-term leachate quality of the landfill under changing exposure conditions such as carbonation and oxidation.
Bringing together data from various laboratory leaching tests - in particular pH dependence - , field data, and geochemical modelling results, provides a much more complete picture of the release controlling factors in a landfill than can be provided by any single one of these data sources.
Fifth International Slag Valorisation Symposium │ Loncnar M, van der Sloot H.A., Zupančič M., Mladenovič A.
03/04/2017

20. We think green and profitable