Skip to main content

Prediction of Acid Rock Drainage from Automated Mineralogy

  • Chapter
  • First Online:
Environmental Indicators in Metal Mining

Abstract

Automated mineralogy tools are now commonly used during mineral processing for particle characterization to help mine operators evaluate the efficiency of the selected mineral processing techniques. However, such tools have not been efficiently used to assist in acid rock drainage (ARD) prediction . To address this, the computed acid rock drainage (CARD) risk grade protocol was developed. The CARD risk grade tool involves: (1) appropriate selection of samples (i.e., following a geometallurgical sampling campaign); (2) careful preparation of a particle mount sample; (3) analysis on a mineral liberation analyser (MLA) using the X-ray modal analysis (XMOD) function; (4) processing of the XMOD data to produce a whole particle mount backscattered electron (BSE) image and a corresponding image of classified XMOD points; (5) fusion of both images to obtain particle area data; (6) calculation of the CARD risk ratio based on carbonate and sulfide particle areas, relative reactivities (\( {\text{pH}}_{{{\text{CaCl}}_{2} }} - {\text{pH}}_{{{\text{mineral}} + {\text{CaCl}}_{2} }} \)) and acid forming/neutralizing values (calculated based on mineral chemistry and stoichiometric factors, kg H2SO4/t); and (7) classification of CARD risk ratios ranging from extreme risk to very-low risk. Testing of the CARD risk grade tool was performed on materials selected from several mine sites representative of both run-of-mine ore and waste. This testing proved that CARD can be effectively used to map ARD risks on a deposit scale and forecast geoenvironmental risk domains at the earliest life-of-mine phases.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • American Society for Testing and Materials (ASTM) 766 D4972–01(2013) (2013) Standard test method for pH of soils.767 ASTM International, West Conshohocken, PA. www.astm.org

  • Aranda CA, Klein B, Beckie RD, Mayer KU (2009) Assessment of waste rock weathering characteristics at the Antamina Mine based on field cell experiments. In: Proceedings from the 8th international conference on acid rock drainage, Skelleftea, pp 1–10

    Google Scholar 

  • Blowes DW, Jambor JL (1990) The pore-water geochemistry and the mineralogy of the vadose zone of sulphide tailings, Waite Amulet, Quebec, Canada. Appl Geochem 5:327–346

    Article  Google Scholar 

  • Brough C, Warrender R, Bowell RJ, Barnes A, Parbhakar Fox A (2013) The process mineralogy of mine wastes. Min Eng 52:125–135

    Article  Google Scholar 

  • Bruckard WJ, Davey KJ, Jorgensen FRA, Wright S, Bew DRM, Haque N, Vance ER (2010) Development and evaluation of an early removal process for the beneficiation of arsenic-bearing copper ores. Min Eng 23:1167–1173

    Article  Google Scholar 

  • Buckwalter-Davis M, Jaggard H, Jamieson H (2012) Automated mineralogy of mine tailings using mineral liberation analysis. In: Proceedings from the 9th international conference on acid rock drainage, Ontario, pp 942–949

    Google Scholar 

  • Chapman NA, Shackleton NJ, Maysiak V, O’Connor CT (2011) The effect of using different comminution procedures on the flotation of platinum group minerals. Min Eng 24:731–736

    Article  Google Scholar 

  • Dold B (2010) Basic concepts in environmental geochemistry of sulphide minewaste management. In: Kumar S (ed) Waste management, INTECH Open Access Publications, pp 173–198. ISBN 978-953-7619-84-8

    Google Scholar 

  • Downing BW (1999) ARD sampling and sample preparation. http://technology.infomine.com/enviromine/ard/sampling/intro.html

  • Downing BW, Madeisky HE (1997) Lithogeochemical methods for acid rock drainage studies and prediction. Explor Min Geol 6:367–379

    Google Scholar 

  • Egiebor NO, Oni B (2007) Acid rock drainage formation and treatment: a review. Asia Pac J Chem Eng 2:47–62

    Article  Google Scholar 

  • Fandrich R, Gu Y, Burrows D, Moeller K (2007) Modern SEM-based mineral liberation analysis. Int J Miner Process 84:310–320

    Article  Google Scholar 

  • GARD (Global Acid Rock Drainage) guide (2015) The international network for acid prevention (INAP). http://www.gardguide.com/

  • Gottleib, P (2008) The revolutionary impact of automated mineralogy on mining and mineral processing. In: 24th international Mineral Processing Congress. Science Press, Beijing, pp 165–174

    Google Scholar 

  • Graham SD, Brough C, Cropp A (2015) An introduction to ZEISS mineralogic mining and the correlation of light microscopy with automated mineralogy: a case study using BMS and PGM analysis of samples from a PGE-bearing chromite prospect. In: Precious metals 2015, Cornwall, UK, pp 1–12

    Google Scholar 

  • Grant WH (1969) Abrasion pH, an index of chemical weathering. Clays Clay Miner 17:151–155

    Article  Google Scholar 

  • Gu Y (2003) Automated scanning electron microscope based mineral liberation analysis—an introduction to JKMRC/FEI mineral liberation analyser. J Miner Mat Character Eng 2:33–41

    Google Scholar 

  • Gunsinger MR, Ptacek CJ, Blowes DW, Jambor JL, Moncur MC (2006) Mechanisms controlling acid neutralization and metal mobility within a Ni-rich tailings impoundment. Appl Geochem 21:1301–1321

    Article  Google Scholar 

  • Hartner R (2012) Integration and analysis of optical and MLA-based microscopy for optimisation of geometallurgical modelling and ore deposit characterisation. PhD thesis, University of Queensland, Australia

    Google Scholar 

  • Hartner R, Walters S.G, Berry R (2011) Integration and analysis of optical and SEM-based microscopy for automated mineralogical characterisation. In: Proceedings from the 10th International Congress for Applied Mineralogy, Trondheim, Noway, pp 319–326

    Google Scholar 

  • Hunt J, Berry RF, Bradshaw D (2011) Characterising chalcopyrite liberation and flotation potential: Examples from an IOCG deposit. Min Eng 24:1271–1276

    Article  Google Scholar 

  • Jackson L, Parbhakar-Fox A, Hughes A, Agius J, Ferguson T, Lester D (2015) Microan-alytical evaluations of the Savage River old tailings dam, north-west Tasmania. In: AUSIMM tailings and mine waste management for the 21st century, Sydney, Australia, pp 1–14

    Google Scholar 

  • Jambor JL, Dutrizac JE, Raudsepp M (2007) Measured and computed neutralization potentials from static tests of diverse rock types. Environ Geol 52:1019–1031

    Article  Google Scholar 

  • Lawrence RW, Wang Y (1996) Determination of neutralization potential for acid rock drainage prediction. MEND Project Report 1.16.3, MEND, Ottawa, ON

    Google Scholar 

  • Lawrence RW, Scheske M (1997) A method to calculate the neutralization potential of mining wastes. Environ Geol 32:100–106

    Article  Google Scholar 

  • Moncur MC, Jambor JL, Ptacek CJ, Blowes DW (2009) Mine drainage from the weathering of sulfide minerals and magnetite. Appl Geochem 24:2362–2373

    Article  Google Scholar 

  • Moncur MC, Jambor JL, Ptacek CJ, Blowes DW (2015) Long-term mineralogical and geochemical evolution of sulfide mine tailings under a shallow water cover. Appl Geochem 57:178–193

    Article  Google Scholar 

  • Noble TN, Lottermoser BG, Parbhakar-Fox A (2015) Evaluation of pH testing methods for sulfidic mine waste. Mine Water Environ. doi:10.1007/s10230-015-0356-2

    Google Scholar 

  • Paktunc AD (1999) Mineralogical constraints on the determination of neutralising potential and prediction of acid mine drainage. Environ Geol 39:103–112

    Article  Google Scholar 

  • Parbhakar-Fox A, Edraki M, Walters S, Bradshaw D (2011) Development of a textural index for the prediction of acid rock drainage. Min Eng 24:1277–1287

    Article  Google Scholar 

  • Parbhakar-Fox A, Lottermoser BG (2014) Domaining acid rock drainage risks using geometallurgical data. In: Proceedings from the 8th Australian workshop on acid and metalliferous drainage, pp 483–494

    Google Scholar 

  • Parbhakar-Fox AK, Edraki M, Hardie K, Kadletz O, Hall T (2014) Identification of acid rock drainage sources through mesotextural classification at abandoned mines of Croydon, Australia: implications for the rehabilitation of waste rock repositories. J Geochem Explor 137:11–28. doi:10.1016/j.gexplo.2013.10.017. ISSN 0375-6742

  • Plante B, Bussiere B, Benzaazoua M (2012) Static test response on 5 Canadian hard rock mine tailings with low net acid-generating potentials. J Geochem Explor 114:57–69

    Article  Google Scholar 

  • Plumlee GS (1999) The environmental geology of mineral deposits. In: Plumlee, GS, Logsdon MJ (eds) The environmental geochemistry of mineral deposits part A: processes, techniques and health issues. reviews in economic geology, vol 6A, pp 71–116

    Google Scholar 

  • Price WA (2009) Prediction manual for drainage chemistry from sulphidic geologic materials. CANMET Mining and Mineral Sciences Laboratories, Canada

    Google Scholar 

  • Rizmanoski V (2011) The effect of microwave pre-treatment on impact breakage of copper ore. Min Eng 24:1609–1618

    Article  Google Scholar 

  • Stevens RE, Carron MK (1948) Simple field test for distinguishing minerals by abrasion pH. Am Miner 33:31–50

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Anita Parbhakar-Fox .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Parbhakar-Fox, A., Lottermoser, B., Hartner, R., Berry, R.F., Noble, T.L. (2017). Prediction of Acid Rock Drainage from Automated Mineralogy. In: Lottermoser, B. (eds) Environmental Indicators in Metal Mining. Springer, Cham. https://doi.org/10.1007/978-3-319-42731-7_8

Download citation

Publish with us

Policies and ethics