Linking sulfide mineral oxidation and metal release in models of acid rock drainage from mine waste 1

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1 Linking sulfide mineral oxidation and metal release in models of acid rock drainage from mine waste 1 Houston Kempton 2, Cory Conrad 2, Cynthia Parnow 2, and Stephen Phillips 2 2 Knight Piésold and Co., 1580 Lincoln St., Suite 1000, Denver, CO USA ABSTRACT The oxidation of sulfide minerals and associated release of acidity and soluble metals from wall rock, adits, waste rock and tailings is a primary source of water quality degradation at hard-rock mines. While releases of direct oxidation products (sulfate, iron, and acidity) are generally proportional to sulfide oxidation, many metals dissolve from secondary mineral dissolution and desorption, and load rates for these are more difficult estimate from sulfide oxidation. Further, empirical metal-release models can introduce systematic errors, including: 1) direct application of operationally defined test results to field conditions (e.g., high water: rock ratios in humidity-cell tests produce effluent is les concentrated than field concentrations); 2) extrapolating short-term element-release rates using curve fitting, which usually violate charge and mass balance constraints; and 3) omission of estimates for element releases out to complete oxidation. There is thus an acute need for more reliable methods of estimating metal releases during oxidation of mine waste to better support predictive modeling. We propose a method for estimating solute release from sulfidic waste that preserves mass and charge balance, and also supports guidance for predictive environmental modeling (i.e., transparency, use of empirical data, conservation of mass, and uncertainty estimation). Solute releases are assumed to be proportional 2- to sulfide oxidation, where the solute/ SO 4 ratios are bounded between cumulative release from short humidity-cell tests and complete oxidation by hydrogen-peroxide. These two integrative solute-release tests bracket behavior where solutes accumulate, such as wall-rock leaching to mine pit lakes. Errors from lab-test dissolution artifacts (e.g., alkalinity release proportional to water: rock ratios) are reduced by decoupling these from solid-phase oxidation. Where Monte Carlo simulations are used to estimate uncertainty, the Bootstrap method, applied to combinations of complete water analyses, generates probability distributions for solute releases that are balanced in charge and mass. INTRODUCTION Most permits to create or expand contemporary hard rock mines rely heavily on model predictions of water quality impacts. The concern over water quality concerns is particularly acute where the ore is hosted in rocks that contain metal-sulfide minerals. In these cases, the excavated materials--waste rock, tailings, ore, and exposed pit walls oxidize by reaction with 1 Paper was presented at the 2009, Securing the Future and 8 th ICARD, June 22-26, 2009, Skellefteå, Sweden. 1

2 atmospheric oxygen, liberating soluble sulfate, acidity, and siderophile metals bound as sulfides (e.g., As, Se, Sb, Cd, Cu, Fe, Mo, Ni, Pb, Sb, and Zn). Formation of acidic pore water greatly enhances the solubility of many heavy metals. The magnitude of specific environmental impacts is a balance between rates of contaminant production (sufide mineral oxidation and release of soluble metals), transport (e.g., leaching of waste by groundwater or meteoric water), attenuation (dilution, adsorption, and chemical precipitation), and applicable water-quality standards in receiving water. While sulfate is the principle solute released by oxidation (and a common constituent of concern), significant impacts are often caused by heavy metals and metalloids, which have much lower risk-based concentration thresholds for human and ecological health. In response to environmental regulations, virtually all current mine projects include model predictions of metal concentrations in receiving surface and groundwater. To meet the demand for water-quality predictions, numerous models have been developed to predict solute releases from mines, initially estimating sulfide oxidation (e.g., Davis and Ritchie 1986), and later coupling the oxidation with down-gradient geochemical reactions (Wunderly et. al., 1996). Although well-established tests measure short-term rates of sulfide oxidation and metal release (e.g., humidity cells, typically 20 to 50 weeks), release rates for environmentally sensitive metals and metalloids are often highly non-linear, particularly when pore-water ph shifts in response to production of acid drainage. This complexity derives from their low relative concentrations, multiple mechanisms of release (dissolution, oxidation, and desorption), variable attenuation, and biological reactivity. Further, the quantitative methods used to estimate this complex (and critical) component in mine waste models are developed ad hoc for each project by consultants, operators, and/or academics with widely variable levels of experience and training. In the absence of demonstrated solute-release models for mine waste, project efficiency can drop from collection of irrelevant data, implementation of unnecessarily complex and error prone algorithms, and production of models that costly to implement and difficult to review and evaluate. Problems with solute-release models may explain in part the low reliability waterquality predictions at US hardrock metal mines. A comparison of predicted vs. actual waterquality impact at 25 mines (a subset of 183 major mines operating since 1975) found that of the nine that developed acid drainage, eight had predicted low acid drainage potential initially or had no information on acid drainage potential. And of eleven mines that produced surface water above standards, ten had predicted that surface water standards would not be exceeded (Kuipers et al., 2006). A 1998 US State law reflects this lack of confidence by prohibiting mining of sulfide ore until a mine in acid-generating rock has been operated and closed for 10 years without causing pollution of groundwater or surface water from acid... or the release of heavy metals (State of Wisconsin, 1998). We believe that efficiency and reliability of these predictive water-quality models can be dramatically improved by using solute-release algorithms that are simpler to execute and understand, framed by current policy guidance for environmental modeling, constrained by the fundamentals of mass and charge balance, founded on empirical characteristics of site-specific materials, and executed in a manner that provides reliable uncertainty brackets around results. Following is a method for estimating cumulative solute release from sulfide mine waste that moves toward attaining these goals. 2

3 Policy guidance for environmental modeling We suggest a short list of policy guidelines, extracted from the broader guidance reports on environmental modeling, as a framework for the implementation and review of predictive water quality modeling at hard-rock mines (Morgan and Henrion, 1991; NRC 2007). First, Begin with a clear conceptual model. This description of physical and chemical processes being modeled and key assumptions, accompanied by illustrations, should precede technical details. Second, make everything as simple as possible, but not simpler. This Einstein quote has been adopted in environmental model guidance (Morgan and Henrion, 1991). Empirical data is a foundation of modeling, but data overload is a common source of distraction. The key to good decision making is not knowledge. It is understanding. We are swimming in the former. We are desperately lacking in the latter (Gladwell, 2005). Third, provide independent calculations confirming major results (e.g., show mass balance for loads, charge balance when combining aqueous components, etc.) to demonstrate that calculations are generally correct (Morgan and Henrion, 1991). This also addresses US guidance that requires overseeing agencies to insure the professional integrity, including scientific integrity in environmental impact statements (CEQ 1978). Fourth, assess uncertainty in model predictions. Model guidance invariably requires uncertainty analysis (e.g., NRC 2007). Managers generally loathe uncertainty as it forces subjective decision making, but it s helpful to remember that results of unknown accuracy are worthless, or worse. A prediction, in a field where prediction is not possible, is no more than a prejudice (Gladwell 2008). A second benefit is that including parameter uncertainty as ranges (e.g., in probabilistic simulations) allows competing technical experts to agree to disagree, often improving efficiency of reviews. Background: Potential errors in predicting solute release As a background for developing a method for solute release from sulfide mine waste, we identify inappropriate assumptions that could lead to prediction errors. First, an Assumption of complete oxidation in kinetic weathering tests is generally unwarranted. While a 20-week humidity cell test indicates reaction rate, these typically oxidize much less than 5% of the total sulfide S. Explicit assumptions of complete oxidation in kinetic tests may be unlikely, but mine-wall oxidation models can assume this implicitly where solute release is based on an equivalent mass of completely oxidized wall rock. Better to estimate solute release directly from sulfate released by sulfide oxidation. Second, short-term kinetic tests may not accurately predict long-term solute release. Even 1-year long humidity cell tests generally don t oxidize more than 5 to 20 % of sulfide S, and curve-fit extrapolation of rates through complete oxidation can be wildly inaccurate. Better to bound solute release between partial and complete oxidation. Third, independent tracking of solutes released by oxidation may violate charge and mass balance. Better to calculate using linear combinations of complete solutions to preserve correlations among element. Fourth, operationally defined tests may produce inaccurate model artifacts. Using a laboratory humidity cell test as a direct proxy for effluent concentration under field conditions is an example--the water:rock ratio, and thus dilution, is hundreds of times greater in a humidity cell than under most field conditions. Accounting for solutes released by different mechanims (e.g., alkalinity from calcite dissolution, and sulfate from pyrite oxidation) presents a more complex dilemma. Better to track separately the critical constituents less related to sulfide oxidation (e.g., alkalinity), then add them later to geochemical mass-action models as chargebalanced species that are loaded in proportion to water flow. 3

4 MATERIALS AND METHODS The rock leachates in this study are from two hard-rock metal mines (Mine #1 and #2), each selected to represent a single geologic unit and contain moderate sulfide S (0.1 to 1 % w/w) and detectable metals. Mine 1 rock major lithogy includes metamorphosed quartz vein stocks (seracitized and carbonate-altered felspathic sandstone) and metamorphosed mudstone and claystone. Pyrite (FeS) is the primary sulfide, and electron microprobe analysis identified arsenopyrite (FeAsS) as a source of arsenic. Virtually all Mine 1 waste rock is net neutralizing (average net neutralizing potential = 3.2% CaCO 3 ) due to low sulfide (average sulfide S =0.1 % S, maximum = 0.9% S) and dispersed low-level calcite (average carbonate C = 3.5% CaCO 3 ). Mine 2 rock is primarily gneiss, with some schist, amphibolite, and zones dominated by ironoxides (hematite, magnetite, and specularite). Sulfides are macroscopic, dominantly pyrite but with some pyrrhotite. Most Mine-2 waste rock is non acid generating due to low sulfide S (virtually all rock has <1% S) and dispersed carbonate (average ~1.2% carbonate C). Acid neutralization potential was determined by the modified Sobek method (Lawrence and Wang, 1997). Sulphur Speciation was determined by extraction with HCl and HNO 3 (ASTM method D ). Humidity cell tests were conducted using ASTM method D Peroxide extraction was by the Net Acid Generating (NAG) method (Miller et. al., 1997). Metals in effluents were determined by inductively coupled plasma mass spectroscopy. Bootstrapping (Efron and Tibshirani, 1993) generated probability distributions from the empirical data sets by repeatedly sampling, with replacement, from measured values. RESULTS: A MODEL FOR ESTIMATING SOLUTE RELEASE FROM SULFIDE ROCK Results illustrate a method for estimating cumulative solute release from mine rock based on modeled sulfide oxidation and the cumulative effluents released by partial oxidation (20-week humidity cell) and total oxidation (extraction with hydrogen peroxide) from Mine #1 and Mine #2 rock. Sulfide mineral oxidation is typically the most important indicator of overall acid and metal release.in addition to the direct products of pyrite oxidation (sulfate, acidity, and iron), many metals of concern are bound with sulfide minerals, and are thus released along with sulfate by oxidation of mine rocks. This is directly true for siderophile elements, many of which are bound as sulfides and are thus solubilized by oxidation (Figure 1). But this also applies generally to elements that are more soluble at low ph, which dissolve when sulfide oxidation produces acidic water (e.g., metals adsorbed to mineral surfaces, calcium released by calcite dissolution, etc.). In net-acid generating rock, effluent composition can be particularly complicated as metals initially release by oxidation are adsorbed to iron or manganese hydroxides, then dissolve later when pore water ph drops. 4

5 Figure 1. Cumulative release of arsenic vs. SO 4-2 in 20-week kinetic tests (Mine #1). Based on this association, we pursued the use of sulfide oxidation (indicated by SO 4-2 production) as a basis for estimating metal releases. Sources of error in this approach can arise because: 1) solute unrelated to sulfide oxidation may appear correlated if they are released by steady dissolution, 2) dissolution of highly soluble salts shift dramatically over time as they leach. This method needs to be constrained by release at more complete oxidation. Cumulative solute release from mine rock typically varies widely between different samples and with the amount of oxidation in a single sample. For siderophile elements (arsenic and copper in this example), the cumulative amount released will tend to increase with sulfide oxidation. Thus a 20-week humidity cell tests that oxidizes only a small fraction of the sulfide will leach only a small fraction of the total available metal, as estimated by a complete oxidation using peroxide NAG extraction (Figure 2a and 2C). 5

6 Figure 2. Change in cumulative As and Cu release from Mine #1 rock samples by 20-week humidity cell tests and peroxide oxidation NAG test (a and c), and cumulative As and Cu release normalized to cumulative SO4-2 (b and d). The total range in metals released by NAG tests (Figure 2a and 2c) approximates the variability in total metal concentrations in the deposit. Normalizing the cumulative metal release to the corresponding cumulative SO -2 4 release then provides a basis for estimating the release of these metals based on sulfate production that incorporates variability across the deposit (Figure 2b and 2d). (Copper and As dissolution do in fact appear to be related to sulfide oxidation in these rocks because the metal/ SO -2 4 ratios from partial to complete oxidation vary much less than total metal releases.) This change in metal/ SO -2 4 ratio between slight oxidation (~0.3% of total sulfide S in Mine #1 rocks oxidized during the 20-week humidity cell test) and complete -2 oxidation (i.e., peroxide NAG extraction) provides reasonable brackets for the metal/ SO 4 ratio of cumulative solute released some intermediate amount of oxidation. Short-duration solute release rates are generally not reliable predictors of total solute release at complete oxidation. Extrapolation of metal release from short-term kinetic tests using simple curve fitting can yields wildly inaccurate predictions when applied to estimate total metal release during much more complete oxidation. This is true even when the metal/ SO -2 4 release is relatively linear. Of four equations forms fit to a humidity cell release from Mine #1 rock (cumulative As vs. cumulative SO -2 4 ), including R 2 = 0.98 for the linear fit, none were closer than a factor of 9 from the actual cumulative As release by complete oxidation (Figure 3). 6

7 Figure 3. Extrapolation of partial arsenic release (cumulative 20-week humidity cell) is often wildly inaccurate for estimating total arsenic (peroxide oxidation NAG test). Such unconstrained extrapolations based on curve fitting have no mechanism to preserve model mass balance or account for internal correlations among aqueous constituents, including charge balance. A probability distribution for the average release of a specific solute produced by partial oxidation can be estimated by bootstrapping a weighted average from measured solutes releases in humidity cell and NAG tests. Rather than extrapolating, this approach interpolates between slight (cumulative humidity cell effluent) and complete (peroxide extraction) oxidation of sulfide. The probability distribution for average cumulative element /SO 2-4 ratios is calculated from a bootstrapped average of ratios from slight to complete oxidation (Figure 4). Sulfide waste rock and pit walls are actually in various stages of oxidation, but the average ratio for cumulative element/sulfate ratio is reasonably bound by the two extremes. Here we estimate the probability distribution for overall average cumulative Ni/SO4 ratio based on a triangle distribution to weighing the end members a method suggested when the actual value is bound, and there is some central tendency (i.e., more likely between the bounds than at either extreme; Morgan and Henrion, 1991). Finally, to avoid an erroneous accounting of alkalinity (the alkalinity/so4 ratio is often an artifact of the water/solution ratio in lab tests), alkalinity is removed from the solutions in stoichiometric proportion to Ca 2+ (and if necessary, Mg 2+ ) to maintain charge balance (Table 1). (Most alkalinity in mine-waste effluent, such as pit-lake inflow, originates 7

8 primarily from regional groundwater, so better to calculate its load in proportion to water volume.) Figure 4. Bootstrapped probability distributions for average Ni/SO4 from Mine #2 using cumulative releases from: a) 20-week humidity cell, b) complete peroxide "NAG" test oxidation, and c) average using symmetric triangle distribution. The resulting probability distribution for element/so 4 ratio can then be multiplied by cumulative sulfate production (e.g., from oxidation modeling) to yield load estimates for the collection of elements in leachate that bracketed the release expected between slight to complete sulfide oxidation. And, because these are linear combinations of analyses, results remain as chargebalanced as the individual chemical analyses. 8

9 Table 1. Mine #2 rock analyses for a) cumulative solute released by 20-week humidity cell tests, and b) Cumulative release by complete oxidation (peroxide extraction NAG test). a) Peroxide Extraction (NAG Method Sample Sulfide 1 Alkalinity (meas.) Alkalinity (mod.) 2 SO 4 2- Ca (meas.) Ca (mod.) 3 Mg (measured) Mg (mod.) 3 Fe Ni (wt. %) ph mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg mg/kg , , , , , , , , , b) Humidity Cells , , , Notes: 1. Total initial sulfide S 2. Alkalinity reduced to zero to avoid erroneously adding alkalinity to effluent 3. Ca (and Mg if necessary) are reduced in stoichiometric proportion to alkalinity to maintain charge balance CONCLUSIONS The method presented here is to estimate cumulative solute release from sulfide mine waste based on estimated sulfide oxidation. The approach complies with general policy guidance standards for modeling, and avoids most the pitfalls in trace-element predictions. Uncertainty is bound by measuring cumulative solute release under partial (short-term humidity cells) and complete (peroxide extraction) oxidation, and interpolation between these bounds constrains the prediction mass balance using empirical limits. The laboratory-test artifact error of linking alkalinity to sulfate is eliminated while preserving charge balance by removing carbonate along with stoichiometric Ca 2+. This cumulative solute load method applies well for simulating accumulating systems, such as mine-pit lakes. Finally, using complete water analyses with the bootstrap method to estimate probability distributions for solute release, as used in Monte Carlo or other probabilistic water quality modeling, preserves internal chemical correlations and solution charge balance. 9

10 REFERENCES CEQ, Councel on Environmental Quality, Regulations for Implementing NEPA, Part : Envivronmental Impact Statement: Methodology and scientific accuracy. 43 FR 55994, Nov. 29, 1978, Davis, G.B., G. Doherty, and A.I.M. Ritchie, 1986, A model of oxidation in pyritic mine wastes: part 2, Comparison of numerical and approximate solutions, App. Math Modeling, (10) Efron, B., and R.J. Tibshirani An Introduction to the Bootstrap (Monographs on Statistics and Applied Probability), Chapman and Hall/CRC, Boca Raton, Florida. Gladwell, M Blink: The Power of Thinking Without Thinking. Boston, MA. USA. Little, Brown. Gladwell, M Most Likely to Succeed. The New Yorker. Dec. 15, 2008, pg. 42. Kuipers, J.R., Maest, A.S., MacHardy, K.A., and Lawson, G Comparison of Predicted and Actual Water Qality at Hardrock Mines: The reliability of predictions in Environmental Impact Statements. Kuipers & Associates. PO Box 641, Butte, MT USA Lawrence, R.W. and Wang, Y., Determination of Neutralization Potential in the Prediction of Acid Rock Drainage, Proc. 4th International Conference on Acid Rock Drainage, Vancouver, BC, p Miller, S., Robertson, A. and Donahue, T., Advances in Acid Drainage Prediction using the Net Acid Generation (NAG) Test, Proc. 4th International Conference on Acid Rock Drainage, Vancouver, BC, Morgan, G.M., and M.H. Henrion Uncertainty: A Guide to Dealing With Uncertainty in Quantitative Risk and Policy Analysis, 332p. (Cambridge University Press: New York). NRC, Models in Environmental Regulatory Decision Making. Committee on Models in the Regulatory Decision Process, National Research Council of the National Academy of Sciences, National Research Council Press, Washington, DC. State of Wisconsin, Moratorium on issuance of permits for mining of sulfide ore bodies, Statute , Enacted April 22, 1998, State of Wisconsin, U.S. Wunderly, M.D., Blowes, D.W., Frind, E.O. and Ptacek, C.J., Sulfide mineral oxidation and subsequent reactive transport of oxidation products in mine tailings impoundments: A numerical model. Water Resources Research, 32(10):

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