CALL FOR PROPOSALS:

ORGANIZERS

  • Harvey Thorleifson, Chair
    Minnesota Geological Survey
  • Carrie Jennings, Vice Chair
    Minnesota Geological Survey
  • David Bush, Technical Program Chair
    University of West Georgia
  • Jim Miller, Field Trip Chair
    University of Minnesota Duluth
  • Curtis M. Hudak, Sponsorship Chair
    Foth Infrastructure & Environment, LLC

 

Paper No. 11
Presentation Time: 4:50 PM

THE INAP PIT LAKES DATABASE – A TOOL FOR PREDICTING FUTURE PIT LAKE WATER QUALITY


JOHNSON, Emmon, Department of Earth and Atmospheric Sciences, SUNY Oneonta, 108 Ravine Parkway, Science 1, Room 203, Oneonta, NY 13820 and CASTENDYK, Devin N., Dept. of Earth and Atmospheric Sciences, State University of New York, College at Oneonta, Oneonta, NY 13820, johnep71@suny.oneonta.edu

On a global scale, pit lake monitoring programs have collected a wealth of data on the geochemistry of pit lakes. This global dataset could assist the develop numerical predictions of pit lake water quality, validate numerical predictions, and design of mine closure plans. To this end, the International Network for Acid Prevention (INAP) funded the development of the INAP Pit Lakes Database (http://pitlakesdatabase.org); an online tool that compares the surface water chemistry of existing pit lakes based on location, ore body type, host rock, and commodity. For a given ore body type, the database calculates the minimum, maximum, mean, and median concentrations of specific ions which can be used to estimate the likely range of concentrations in future pit lakes developing in similar ore bodies. The database also generates pH vs. concentration plots using all data. Currently, it contains data from 78 pit lakes from 3 continents reported in the published literature. Most of these pit lakes occur in Massive Sulfide, Taconite, or Carlin-Type Gold ore deposits.

The pH vs. concentration plots show two general water quality patterns: exponential trends and clusters. Al, Cd, Cu, Fe, Mn, Pb, SO4, Zn, Mg, and Ba show concentrations that exponentially decrease as pH increases, whereas Ag, As, Co, Cr, Hg, Mn, Mo, Ni, Sb, V, Cl, CHO3, K, Mg, Na, B, Be, F, Si, Sn, Sr, and NO3 tend to cluster within a narrow pH range. In general, ion concentrations span only one to two orders of magnitude. However, some ions like Sb and V span several orders of magnitude.

The following characteristics can be identified based on ore body types. Pit lakes in Massive Sulfide ore deposits tend to be clustered in the low pH range (2-3.5) and have higher ion concentrations than other ore types. For example, Fe ranges from 50 to 5000 mg/L between pH 1.2 and 3.2. Pit lakes in Taconite ore deposits tend to cluster in the high pH (6-9.5) range and show less variation in ion concentrations. Fe ranges from 0.05 to 0.5 mg/L over a pH range of 6.4 to 9.4 in this deposit. Pit lakes in Carlin-Type Gold deposits tend to cluster between pH 7 and 9, show wider variability in ion concentrations, and exhibit ion concentrations that decrease exponentially with pH. For example, Fe ranges from 0.001 to 100 mg/L over a pH range of 3 to 9.4. The utility of the database will increase as more data are added in the future.

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