Research on the Prediction of Mine Drainage and the Colloidal Transport of Metals

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1 Research on the Prediction of Mine Drainage and the Colloidal Transport of Metals Heather Jamieson, Martha Buckwalter-Davis, Jessica Dongas and Lindsay Fenwick Department of Geological Sciences and Geological Engineering Queen s University, Kingston, ON

Jessica Dongas and Lindsay Fenwick Department of Geological

2 (Environmental Decision) Mine permits require prediction of the quality of drainage from tailings and waste rock: 1. ph between 4 and 9 2. Dissolved metals less than concentrations toxic to aquatic life Canadian Metal Mine Effluent Regulations Static and kinetic tests are used for prediction, and results form basis for permitting decisions.

Dissolved metals less than concentrations toxic to aquatic life Canadian Metal Mine

3 (Environmental Decision) (Geological Research) Mine permits require prediction of the quality of drainage from tailings and waste rock: 1. ph between 4 and 9 New prediction tool using mineralogical rather than chemical test 2. Dissolved metals less than concentrations toxic to aquatic life Characterizing metal-bearing colloids that enhance mobility and reduce toxicity

ph between 4 and 9 New prediction tool using mineralogical rather than chemical test 2.

4 New Calumet Mine ( ) Gobi Desert GD Beaver Dam BV 90km to Ottawa Mount Sinai MS 200m metamorphosed massive sulfide deposit Pb, Zn, Ag 2.8 million tonnes of tailings Privately owned

5 Mount Sinai (MS) Gobi Desert (GD) Glory hole with exposed massive sulfide Drainage from Calumet tailings is consistently ph-neutral

6 Acid-base accounting (ABA) Static test, commonly-used tool for permitting Prediction of acid drainage based on the balance of acid-producing minerals (Fe sulfide) and acidneutralizing minerals (mainly carbonate) AP (Acid Potential) Based on total S less sulfate-s NP (Neutralization Potential) Based on total inorganic carbon

sulfide) and acidneutralizing minerals (mainly carbonate) AP (Acid Potential)

7 Typical results: NPR = NP/AP chemical tests independent of determinative mineralogy even though their purpose is to predict the weathering behavior of the minerals in the tested samples J. Jambor, 2003 Can ABA be evaluated based on mineralogy?

predict the weathering behavior of the minerals in the

8 ABA results for Calumet tailings Sample NPR from chemical tests Classification Paste ph BV-non VEG 0.64 PAG 7.76 BV-VEG PAG 7.87 GD-non VEG 1.08 Uncertain 7.80 Acidconsuming GD-VEG GD-VEG Uncertain 8.07 MS-non VEG 0.14 PAG 6.70 Paste ph is consistent with neutral drainage observed in the field

08 Uncertain 7.80 Acidconsuming GD-VEG1 7.47 8.15 GD-VEG2 1.08 Uncertain 8.

9 Mineral Liberation Analysis (MLA) Quantitative, automated 100,000 s particles in a single thin section Scanning electron microscopy back scatter electron (BSE) image analysis energy dispersive X-ray (EDS) analysis Many operationally defined parameters

microscopy back scatter electron (BSE) image analysis energy

10 Mineral Liberation Analysis- Step 1 Back Scatter Electron Image 1 mm

11 Mineral Liberation Analysis Step 2 Definition of particles, EDS X-ray spectra collected 1 mm

12 Mineral Reference Library Higher resolution image of Mineral Reference Library to go HERE

13 Mineral Liberation Analysis Step 3 EDS spectra used with Mineral Reference Library to classify sample Biotite Pyrrhotite Chalcopyrite 1 mm

14 Acid Potential (AP) calculated from % sulfide S Sample % sulfide S Total S less HClsoluble S (sulfate) Based on 100,000 to 200,000 particles per thin section % MLA-measured pyrite. pyrrhotite, arsenopyrite, sphalerite, chalcopyrite BV-non VEG BV-VEG GD-non VEG GD-VEG GD-VEG MS-non VEG chemical test mineralogical test

pyrrhotite, arsenopyrite, sphalerite, chalcopyrite BV-non VEG 2.21 3.20 BV-VEG1 2.87 4.

15 Neutralization Potential (NP) calculated from % Ca carbonate kg CaCO 3 /tonne Based on 100,000 to 200,000 particles per thin section Sample Carbonate-NP calculated from total inorganic carbonate Carbonate NP calculated from MLA corrected for FeCO 3 BV-non VEG BV-VEG GD-non VEG GD-VEG GD-VEG MS-non VEG chemical test mineralogical test

Carbonate NP calculated from MLA corrected for FeCO 3 BV-non VEG 44.2 40.0 BV-VEG1 66.7 50.

16 Neutralization Potential Ratio NPR = NP/AP Sample NPR from chemical tests NPR from MLA only Paste ph BV-non VEG BV-VEG GD-non VEG GD-VEG GD-VEG MS-non VEG Good agreement between chemical and mineralogical prediction methods. But why do Calumet tailings produce neutral drainage?

80 GD-VEG1 7.47 6.62 8.15 GD-VEG2 1.08 0.98 8.07 MS-non VEG 0.14 0.13 6.

17 Further sampling of Mt. Sinai tailings Captured variations in colour, grain size and depth

18 Sample NPR from chemical tests NPR from MLA only Paste ph BV-non VEG BV-VEG GD-non VEG GD-VEG GD-VEG MS-non VEG S1-JD S2-JD S3-JD S4-JD S7-JD

80 GD-VEG1 7.47 6.62 8.15 GD-VEG2 1.08 0.98 8.07 MS-non VEG 0.14 0.

19 ph = 6.2 Higher ratio of carbonate to sulfide may be present deeper in tailings pile or Another mineral may be providing neutralization

20 Water samples filtered to <0.45 µm may include metals as colloids and solutes (truly dissolved) Metal-bearing colloids may enhance metal transport (disadvantage) reduce metal bioavailability (advantage)

21 Colloids: Beaver Pond drainage Colloid fraction: Fe, Pb, Zn Water is prefiltered to <0.45µm Ultrafiltration cell <.01µm Fe oxyhydroxide Flocculate in downstream settling pond

22 Colloids: Mt. Sinai Zn oxide or carbonate Structures formed after filtration Zn colloids But <1% of Zn in colloid fraction Most Zn in water sample is truly dissolved

23 SUMMARY: Detailed mineralogy remains non-routine and expensive tool for mine drainage prediction BUT new tools have potential to provide critical information in complex or controversial cases. Acknowledgements: Heather Jaggard, Golder Associates, Sudbury John MacLatchy, owner, New Calumet Mine NSERC Discovery (HEJ)

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