Long-term monitoring of waste-rock weathering at the Antamina mine, Peru

Accepted Manuscript Long-term monitoring of waste-rock weathering at the Antamina mine, Peru Bas Vriens, Holly Peterson, Laura Laurenzi, Leslie Smith, Celedonio Aranda, K. Ulrich Mayer, Roger D. Beckie PII:

S0045-6535(18)31966-0

DOI:

10.1016/j.chemosphere.2018.10.105

Reference:

CHEM 22367

To appear in:

ECSN

Received Date: 18 June 2018 Revised Date:

5 October 2018

Accepted Date: 16 October 2018

Please cite this article as: Vriens, B., Peterson, H., Laurenzi, L., Smith, L., Aranda, C., Mayer, K.U., Beckie, R.D., Long-term monitoring of waste-rock weathering at the Antamina mine, Peru, Chemosphere (2018), doi: https://doi.org/10.1016/j.chemosphere.2018.10.105. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Long-term monitoring of waste-rock weathering at the Antamina mine, Peru Bas Vriens1,*, Holly Peterson2, Laura Laurenzi3, Leslie Smith1, Celedonio Aranda4, K. Ulrich Mayer1, Roger D. Beckie1

Department of Earth, Ocean and Atmospheric Sciences, University of British Columbia, 2020-

2207 Main Mall, Vancouver BC, V6T 1Z4, Canada 2

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Department of Geology, Guilford College, 5800 West Friendly Avenue, Greensboro NC,

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27403, USA

BGC Engineering Inc., 500-980 Howe Street, Vancouver BC, V6Z 1N9, Canada

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Compañia Antamina Minera S.A., Av. El Derby No. 055, Santiago de Surco, Lima, Peru

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Corresponding author e-mail: [email protected]

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Word count: Abstract: 206 Introduction: 796 Methods: 966 Results: 3821 Conclusions: 240 Total: 5,823 5 Figures, 3 Tables 1

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Abstract

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The weathering of mine waste rock can cause release of metal-laden and acidic drainage that

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requires long-term and costly environmental management. To identify and quantify the

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geochemical processes and physical transport mechanisms controlling drainage quality, we

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monitored the weathering of five large-scale (20,000 t) instrumented waste-rock piles of variable

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and mixed-composition at the Antamina mine, Peru, in a decade-long monitoring program. Fine-

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grained, sulfidic waste rock with low-carbonate content exhibited high sulfide oxidation rates

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(>1 g S kg-1 waste rock yr-1) and within 7 years produced acidic (pH<3) drainage with high Cu

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and Zn concentrations in the g L-1 range. In contrast, drainage from coarse, carbonate-rich waste

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rock remained neutral for >10 years and had significantly lower metal loads. Efficient metal

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retention (>99%) caused by sorption and secondary mineral formation of e.g., gypsum, Fe-

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(oxy)hydroxides, and Cu/Zn-hydroxysulfates enforced strong (temporary) controls on drainage

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quality. Furthermore, reactive waste-rock fractions, as small as 10% of total mass, dominated the

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overall drainage chemistry from the waste-rock piles through internal mixing. This study

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demonstrates that a reliable prediction of the timing and quality of waste-rock drainage on

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practice-relevant spatiotemporal scales requires a quantitative understanding of the prevailing in-

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situ porewater conditions, secondary mineralogy, and spatial distribution of reactive waste-rock

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fractions in composite piles.

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Graphical abstract

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1. Introduction

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Displacement of rock by humans has become one of the largest geomorphic factors on

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Earth’s surface: the global mass moved for mineral ore extraction exceeded 60 Gt in 2000

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(Rajaram et al., 2005; Fyfe, 1981). The environmental impacts of mining are correspondingly

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large: waste generation is typically a multitude of profitable ore production and millions of tons

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of mine wastes such as tailings and waste rock are generated each year (Hudson-Edwards &

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Dold, 2015). The weathering and drainage of these mine wastes can produce metal-laden,

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sometimes acidic waters (“acid mine drainage”). With increasing demand and exploitation of

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lower-grade deposits (Lottermoser, 2010), the control and mitigation of mine-waste drainage is a

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long-lasting environmental challenge for mines worldwide (MEND, 2001; Simate & Ndlovu,

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2014).

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The quantity and quality of mine waste drainage vary from site to site due to differences in

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mining techniques, waste-rock properties, and climatic conditions. Acidic mine drainage is

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predominantly associated with wastes generated from mining of sulfidic mineral- and coal

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deposits, and waste rock is typically the largest waste fraction generated by open-pit mines

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(Hudson-Edwards & Dold, 2015; MEND, 2001). Many of the physical, hydrological,

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geochemical, and biological processes that control waste-rock drainage quality have been known

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for decades and are similar globally (Amos et al., 2015; Parbhakar-Fox & Lottermoser, 2015;

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Blackmore et al., 2018). Simplified, the composition of neutral or acidic rock drainage can be

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traced back to the waste-rock mineralogy: the balance between the rates of oxidation of sulfide

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minerals (acid-generation) and the dissolution rates of carbonate-, hydroxide-, and silicate

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minerals (acid-buffering) determines whether drainage will be acidic or pH-neutral, whereas the

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waste-rock metal content ultimately controls dissolved metal concentrations (Amos et al., 2015;

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Blowes et al., 2003). Physical factors (e.g., temperature), biological activity (e.g., of S- and Fe-

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oxidizing bacteria), or hydrological- and gas-transport (i.e. water infiltration and oxygen supply)

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may decelerate- or accelerate drainage release and affect its quality, and can, to a certain extent,

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be manipulated by humans, e.g., by covering waste-rock piles, blending reactive waste-rock with

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net-acid-buffering waste rock, or diverting surface- and groundwater flow (Amos et al., 2015;

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O’Kane et al., 1998; RoyChowdhury et al., 2015). To forecast and ultimately reduce the

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environmental impacts of waste-rock drainage, it is crucial to assess its volume and chemical

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characteristics, and the timing by which this drainage is released. Unfortunately, major obstacles

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complicate such predictions, namely: i) the heterogeneity of the generated waste rock and the

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site-specificity of the local weathering climate, ii) the intricate coupling of chemical kinetics and

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physical transport processes, and iii) the scale-dependency of these geochemical and physical

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processes (Stockwell et al., 2006; Strömberg & Banwart, 1999; Malmström et al., 2000), which

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confounds direct extrapolation of chemical weathering rates and hydrological flow regimes from

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small-scale experimental systems (e.g., humidity cells and laboratory experiments with volumes

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of (several) liter(s)) to real-world scenarios (e.g., hundreds of meters’ tall waste-rock piles, i.e.

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millions of tons of waste rock) (Amos et al., 2015). Previous studies have therefore suggested the

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use of scaling factors (Strömberg & Banwart, 1999; Malmström et al., 2000) and computational

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hydrogeochemical models (Brookfield et al., 2006; Mayer et al., 2004), but little verification of

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these scaling factors and models has been possible due to a lack of integrative field data from

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large-scale and long-term weathering experiments.

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Existing multi-year data on weathering waste-rock systems mainly originates from a limited

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number of field experiments, e.g., at the Diavik (Bailey et al.,2013; Smith et al., 2013a; Smith et

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al., 2013b), Key Lake (Stockwell et al., 2006), and Cluff Lake (Nichol et al., 2005; Hollings et

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al., 2001) mines in Canada and the Aitik mine (Strömberg & Banwart, 1999; Eriksson &

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Destouni, 1997; Linklater et al., 2005) in Sweden. These studies have assessed the geochemistry

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and hydrology of waste-rock piles by in-situ borehole- and drainage sampling (Linklater et al.,

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2005; Lefebvre et al., 2001; Sracek et al., 2004), partial deconstruction of waste-rock piles

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(Stockwell et al., 2006), or by building instrumented experimental waste-rock piles (Nichol et al.,

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2005; Smith et al., 2013c). However, most of the abovementioned mine sites are located in dry,

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arctic environments where low precipitation and periodic freezing strongly limit hydrological

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flow (Neuner et al., 2013). Furthermore, quantitative and field-based evaluations of discrete

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geochemical and hydrological processes that affect waste-rock drainage quality (e.g., sorption,

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secondary mineral formation, or preferential flow (Blowes et al., 2003; Eriksson & Destouni,

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1997; Neuner et al., 2013)) remain scarce.

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Therefore, the aims of this study were: i) to identify and quantify the major geochemical

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processes that affect the drainage quality from acid-producing (i.e. sulfide-rich and/or carbonate-

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poor) as well as non-acid producing (i.e. sulfide-poor and/or carbonate-rich) waste rock, and ii)

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to monitor and compare seasonality in - and long-term evolution of - weathering rates and

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drainage quality from these different waste-rock types under natural conditions.

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2. Materials and Methods

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2.1. Description of the study site

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The Antamina Mine is one of the world’s largest open-pit Cu-Zn-Mo mines, located at

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~4,200 m.a.s.l. elevation in the Peruvian Andes, approximately 270 km north of Lima

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(coordinates 274,041E; 8,943,054N; UTM system, Provisional South American Datum 1956,

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Zone 18L; Figure 1A). At Antamina, a Miocene quartz-monzonite porphyry intrusion created a

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skarn ore body hosted in Cretaceous carbonate limestone, marble and hornfels (Love et al.,

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2004). The two on-site waste-rock storage facilities are currently hundreds of meters tall, several

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kilometers wide and growing: by planned mine closure in 2029, the mine is expected to have

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produced 2.2 billion tons of waste rock (Harrison et al., 2012). The climate at Antamina

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(Köppen classification BSk to BWk; cold- to semi-arid desert climate (Peel et al., 2007)) is

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relatively cool with a mean annual temperature of ~6 ºC due to its altitude and rainfall shows a

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distinct monsoonal pattern with a wet season (October – April) accounting for ~80% of the mean

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annual precipitation of ~1200 mm (Figure 1C) (Blackmore et al., 2014; Lorca et al., 2016).

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2.2. Construction of experimental piles

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Between 2006 and 2008, five experimental waste-rock piles with dimensions of

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approximately 36×36×10 m (10,000±2,000 m3), containing ~20,000 tons of waste rock each,

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were constructed from run-of-mine waste rock (see schematic in Figure 1B). The piles were

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built in distinct tipping phases using a progressive end-dumping method, which creates coarse

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basal rubble zones and fining-upward layers that dip at the angle of repose (~37°) (Stockwell et

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al., 2006). All experimental piles were equipped with instrumentation to measure and sample in-

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situ water and gas content (further details are reported in (Blackmore et al., 2014; Lorca et al.,

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2016)) and included several lysimeters: three smaller (~13 m2) sub-lysimeters in the back,

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middle, and front of the piles below individual tipping phases, and one main basal lysimeter

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underlying the entire pile (Figure 1B). The lysimeters were constructed from impervious

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bituminous geomembrane (Coletanche NPT4) at a 3% gradient, surrounded by compressed

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berms, and covered with a compacted ~0.5 m thick protective layer of finer-grained (<5 cm)

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waste rock to ensure free flow and prevent larger boulders from damaging the geomembrane

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during end-dumping. Drainage of each lysimeter was funneled through HDPE tubing into

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calibrated tipping-bucket flow meters (PlasticSmith BC, equipped with Campbell CR1000 data

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loggers) to continuously record flows up to 60 L min-1. Missing or erroneous flow data caused by

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tipping-bucket malfunctioning (ranging between 18% and 29% of the 10 monitored years,

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respectively) was identified using the Random Sample Consensus (RANSAC) model (Fischler

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& Bolles, 1981) and corrected heuristically using regression analysis and interpolation with other

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lysimetry flow- or rainfall records.

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2.3. Characterization of primary waste rock and secondary mineral precipitates

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The five experimental piles were constructed from waste-rock types that span a wide range of

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physical and litho-geochemical properties. Prior to end-dumping, at least five waste-rock

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samples from each tipping phase were collected from a stockpile by a 16-tonne dump truck,

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thoroughly homogenized in a clean and flat processing area, and their sample-size reduced using

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the coning- and quartering method (details in the Supporting Information). Of the reduced waste-

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rock samples of each tipping-phase, particle size distribution, elemental composition,

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mineralogy, and acid-base-accounting (ABA) parameters were analyzed, and subsequently

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weight-averaged onto each entire pile. Methodological details of these analytical methods are

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given in the Supporting Information; a synopsis of the (weight-averaged) composition of the

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experimental piles is provided in Table 1; a detailed overview of the mineralogical and

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geochemical properties of the individual tipping phases is given in Table S1.

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Figure 1. Location of the Antamina mine in Peru (A); schematic sketch of one of the

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experimental waste-rock piles with the approximate locations and sizes of individual tipping-

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phases and internal lysimeters (not to scale, B); 10-yr record of average daily temperatures and

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precipitation for the Antamina mine (C); and daily drainage outflow from the main basal

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lysimeters of the five experimental piles (D).

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basal outflows of piles 1, 2, and 3, and on the respective lysimeters. On two occasions in 2011

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and 2014, a total of 52 samples of these precipitates were collected in duplicate from the

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concerned tipping-phases and/or corresponding lysimeters, by scraping ~150 g of material into 1

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L plastic bags. The mineralogy of these samples was investigated with XRD and Raman

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spectroscopy (see details in the Supporting Information).

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2.4. Analysis of the aqueous drainage chemistry

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Drainage samples from the main basal lysimeters and three sub-lysimeters of the

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experimental piles were collected on a biweekly to monthly basis from sampling ports near the

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tipping buckets in pre-cleaned 500 mL HDPE bottles. Drainage water temperature, pH,

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conductivity, and dissolved oxygen were analyzed directly in the field (WTW Multimeter

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electrode, model 340i). One aliquot was filtered with 0.45 µm cellulose-acetate filters and

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analyzed for alkalinity using an automated digital Hach titrator and 0.16 N H2SO4. Additional

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aliquots were similarly filtered, acidified to pH<2 with trace-metal grade HNO3, and stored at 4

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°C in the dark until submission to an external laboratory. The filtered and acidified aliquots were

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analyzed by an external laboratory for dissolved Al, As, Ca, Cu, Fe, K, Mg, Mn, Mo, Na, Pb, S,

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Sb, Se, Si, and Zn using ICP-OES and ICP-MS. Total elemental loads from the experimental

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piles were calculated from measured aqueous concentrations and flow rates recorded at the basal

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lysimeters.

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Geochemical equilibrium modeling of the aqueous drainage chemistry was performed with

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PHREEQC (Parkhurst & Appelo, 1999) and an adapted WATEQ4F database (Ball & Nordstrom,

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1991) that included additional Mo minerals (Conlan et al., 2012), schwertmannite

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[Fe8O8(OH)6(SO4)·nH2O] (Sánchez-España et al., 2011; Yu et al., 1999), hydrozincite

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[Zn5(CO3)2(OH)6] (Preis & Gamjäger, 2001), and aurichalcite [(Zn,Cu)5(CO3)2(OH)6] and

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rosasite [(Cu,Zn)2(CO3)(OH)2] (Alwan et al., 1980). For modeling, concentrations below their

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analytical detection limit were set to half that limit and a solution charge balance of <10% error

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was used as data quality threshold. All models assumed prevailing oxic conditions (pO2=0.05

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atm; O2-saturation of the drainage was typically 25% (data not shown)), and considered

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measured alkalinity concentrations to reflect dissolved carbonate only. Finally, basal mixing

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calculations were performed by mixing the average drainage captured by the three individual

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sub-lysimeters in pile 2 according to the weight-fractions of the respective overlying tipping

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phases 1, 2, and 3. Details for these calculations are given in the Supporting Information.

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Table 1. Summary of the major lithological, mineralogical, and geochemical properties of

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samples representative of the five experimental waste-rock piles. The reported values are weight-

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averages for the five experimental piles, based on analyses of the individual tipping phases in the

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respective piles (full details reported in the supporting information, Table S1).

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Pile 1 Pile 2 Pile 3 Pile 4 Pile 5 Marble and Intrusive Exoskarn Marble and Intrusive hornfels hornfels and hornfels Mineralogy (%) Sum of carbonates 48.8 0.2 13.6 70.3 26.4 Sum of silicates 47.9 95.5 81.3 27.8 72.8 Sum of sulfides 2.1 4.0 4.8 1.9 1.8 1 Acid-Base Accounting (t CaCO3 per 1000 t) AP 15 42 139 20 18 NP 587 11 164 714 507 NNP (=NP-AP) 572 -31 25 694 489 NPR (=NP/AP) 38 0.3 1.2 35 28 Elemental composition Al (%) 3.9 6.4 3.4 4.2 3.7 As (ppm) 67 113 348 67 102 C (%) 6.1 0.11 1.2 2.5 1.3 Ca (%) 28 2 21 32 26 Cu (ppm) 688 5,767 11,021 166 1,481 Fe (%) 1.9 4.4 11 1.5 1.9 K (%) 1.1 5.0 0.6 1.1 2.4 Mg (%) 1.3 0.6 1.6 1.8 1.1 Mo (ppm) 53 347 137 68 133 Na (%) 0.14 0.66 0.33 0.21 0.39 S (%) 0.5 1.6 3.8 0.5 0.6 Si (%) 35 51 24 17 21 Zn (ppm) 818 298 19,120 256 211 1 AP = acid-producing potential, NP = neutralizing potential, NNP = net neutralizing potential (=NP-AP), NPR = neutralizing potential ratio (=NP/AP)

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3. Results and Discussion

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3.1. Highly seasonal pile hydraulics

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The annual drainage patterns in the experimental piles were highly seasonal (Figure 1D),

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similar to the monsoonal variability in precipitation at Antamina (Figure 1C). Flow from basal

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lysimeters ranged from 25 m3 d-1 (e.g., after the relatively wet 2013) down to less than 0.05 m3 d-

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drainage, while the main basal lysimeter captured the remainder (Blackmore et al., 2014),

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representative of their respective plan-view surface areas. In contrast to field-barrel experiments

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at Antamina (Hirsche et al., 2017) and to waste-rock piles at other mine sites in Arctic

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environments (Smith et al., 2013c), year-round flow occurred. The annual flow cycle was

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characterized by: i) a wet-up stage at the start of the wet season (October–December), in which

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weekly precipitation exceeded effluent flow, ii) a dynamic equilibrium at the height of the wet

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season (January–mid-April), and iii) a drain-down stage at the end of the wet season (late April–

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September), in which effluent flow exceeded precipitation.

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(e.g., after the relatively dry 2010). The three sub-lysimeters each captured ~1% of the total

The cumulative annual drainage from the piles was comparatively stable over the years,

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resulting from little year-to-year variability in precipitation and evaporation at Antamina.

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Compared to precipitation patterns, drainage from the experimental piles was dampened and

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lagged by several months due to capillary action; mean residence times ranged from 0.4 to 1.7

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years for the different experimental piles (Blackmore et al., 2014). There was considerable pile-

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to-pile variability in drainage patterns: the flow regimes of piles 1, 4, and 5 showed more

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fluctuant behavior than piles 2 and 3 (Figure 1D). Considering that all piles experienced the

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same climate and had a similar geometry, variability in flow regimes was primarily related to

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particle size or particle properties such as shape. For instance, piles 1, 4, and 5 had larger waste-

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rock particle sizes than piles 2 and 3 (d50, i.e. the particle diameter that 50% of the waste rock

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mass in the pile was smaller than, was ~100 mm in piles 1, 4, and 5, but ~20 mm in piles 2 and 3;

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Figure S1) and therefore higher hydraulic conductivities. In addition, pile-to-pile differences in

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particle size led to variable evaporation from the experimental piles: calculated as the difference

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between observed yearly precipitation and pile drainage, evaporation ranged from 32% and 20%

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for finer-grained piles 2 and 3 to 57%, 39% and 40% for coarser-grained piles 1, 4 and 5,

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respectively, averaged over the entire study period (data not shown). In addition to variable

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mineralogy and chemical composition (Table 1), the experimental piles also exhibited clearly

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dissimilar hydraulic properties.

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3.2. Short- and long-term variability in waste-rock drainage chemistry

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The chemical composition of drainage from the basal lysimeters of the piles (Figure 2,

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additional elements in Figure S2) generally showed a strong seasonality, with distinct yearly

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oscillations of more than an order of magnitude, e.g., for dissolved SO4, Cu, or Zn

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concentrations. This seasonality mainly resulted from the abovementioned monsoonal variability

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in precipitation and pile outflow, with highest drainage concentrations typically occurring with

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flushing at the onset of the wet season, i.e., with re-dissolution of previously accumulated

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(evapoconcentrated) precipitates. For some parameters and piles, only limited (e.g., Mn, Pb, Mo)

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or no (e.g., pH) intra-annual seasonal variation occurred. In addition, annual oscillations were

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occasionally out-of-phase with respect to each other and flow response (e.g., alkalinity and Mn

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in piles 1-3 versus in piles 4 and 5). The observed pH ranges and drainage concentrations of

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measured elements (e.g., SO4: g L-1 range, or Cu, Zn, Ca, and alkalinity: mg L-1 range) generally

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fall within the large range of previously reported drainage concentrations from comparable

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waste-rock types (Amos et al., 2015; Langman et al., 2014; Smith et al., 2013b; Sracek et al.,

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2004). In addition to seasonal trends, long-term trends and clear differences in the drainage

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chemistry between the experimental piles can be observed. Most strikingly, the outflow from pile

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2 developed into an acidic (pH ~3) and heavily metal-laden drainage, with SO4, Fe, Cu, and Zn

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concentrations increasing by orders of magnitude within three years, to levels well above those

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from other piles (see below). All other piles generated drainage with comparably stable or

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slightly decreasing concentrations during the 10 monitored years (e.g., Ca (Figure 2) or Na, K,

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and Cl (Figure S2)), the only exceptions being more significantly decreasing Pb and Mn

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concentrations in drainage from pile 3, and slightly increasing Mo concentrations in drainage

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from pile 5 (Figure S3). Consistently high releases of alkalinity from pile 1, Mo from pile 2, and

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Zn, Cu, and Pb from pile 3 all appeared to be related to the primary waste-rock mineralogy: pile

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1 contained substantial neutralizing potential, whereas pile 2 contained the most Mo, and pile 3

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the most Zn, Cu, and Pb of all experimental piles (Table 1). Similarly, practically identical Ca,

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K, and Na drainage release from piles 1, 4, and 5 likely resulted from similar concentrations of

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these elements and their (aluminosilicate) source minerals in the waste rock in these piles (see

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elemental compositions and mineralogy data in Table S1). These examples thus support the

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general notion that long-term development of drainage chemistry may be dominantly linked to

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primary mineralogy, among other factors, whereas significant seasonal fluctuations may

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originate from variability in hydrological transport.

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Figure 2. Chemical composition of drainage from the basal lysimeters of the five

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experimental piles between 2007-2017. Legend applies to all frames. All y-axes except for pH 16

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and alkalinity are logarithmic. The black box on the x-axis indicates a data gap period for Ca.

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Additional elements are plotted in Figure S2. 3.3. Rapid acidification of drainage from reactive waste rock

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Although most intrusive waste rock at Antamina is hosted in a calcareous matrix and

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consequently contains significant overall NP, the intrusive waste rock placed in Pile 2 generated

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basal drainage that transitioned from neutral into acidic over the course of 3 years, with pH

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decreasing 5 units, and Cu and Zn concentrations concurrently increasing orders of magnitude

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(Figure 2). Based on the overall mineralogy and static-testing of pile 2 waste rock, this

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acidification may have been expected: pile 2 contained reactive, sulfide-rich waste rock with

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little carbonate (most of which was siderite, which effectively does not neutralize acidity (Dold,

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2017)), and low neutralization potential (Table 1). The acidification of pile 2 drainage was

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accompanied by a typical buffering sequence in which carbonates, Al-hydroxides, Fe-

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hydroxides, and silicates sequentially dissolve while buffering acidity at decreasing pH (Amos et

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al., 2015; Blowes et al., 2013). This sequence is reflected in the drainage chemistry of pile 2, as:

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i) neutralization capacity from carbonates (i.e. dissolved alkalinity) was fully depleted after 2013

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when pH decreased below 5, ii) significantly higher Al- and Fe-release rates follow alkalinity

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depletion when pH dropped below pH<4 in 2014, and iii) slightly higher Si release rates are

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observed after 2015, which suggests the onset of aluminosilicate dissolution at pH~2, although a

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data gap prior to 2015 obstructs defining the exact start of this buffering reaction (Figure 2,

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Figure S2).

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Drainage acidification times similar to those in pile 2 have been observed previously:

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modeling studies with various waste-rock types from the Aitik mine revealed acidification times

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on the order of 3-4 years (Linklater et al., 2005), and the timescales with which major changes in

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the drainage chemistry from humidity cells at the Diavik mine occurred were also several years

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(Langman et al., 2014). Acidification of waste-rock drainage to pH 5 has even been reported

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after initial flushing of freshly-exposed (<1 year) sulfides (Smith et al., 2013b), but similarly

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rapid drainage acidification rates were not observed at Antamina. In summary, the decade-long

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field-experiments at Antamina reveal that orders-of-magnitude changes in drainage chemistry

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can occur rapidly, i.e. within one season, but that continued monitoring is necessary to

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distinguish between short-term (seasonal) variability and long-term evolution in drainage quality.

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3.4. Estimation of sulfide oxidation rates

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The drainage composition and basal outflow rates were used to estimate element loads and

278

apparent element release rates (i.e. release from primary mineral dissolution minus retention).

279

These were subsequently converted into elemental depletion factors by integrating the release

280

rates over the study period and normalizing this cumulative release to the initial primary waste-

281

rock composition (Table 2).

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Calculated apparent element release rates were relatively constant over the 10-yr study period

283

(<50% relative standard variation, averaged over all elements, Table 2), with the exception of

284

release rates from pile 2, which increased considerably due to the acidification after 2011. The

285

highest apparent element release rates in all piles were generally those for Ca and S, and the 10-

286

year-average release rates of Ca and S were highly similar for all piles but pile 2. This reflects

287

the relatively constant 1:1 stoichiometric ratio of dissolved Ca over SO4 in drainage from these

288

piles (Figure 3A), indicating open, well-buffered carbonate systems (Amos et al., 2015; Dockrey

289

et al., 2014) with a consequently stable drainage pH for all piles but pile 2 (Figure 2). Despite

290

having distinct and variable mineralogical compositions (Table 1), experimental piles 1, 4, and 5

291

exhibited surprisingly similar release rates with little inter-annual variation for most elements,

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and the comparable Ca and alkalinity release rates from all experimental piles are similarly

293

striking (Table 2, in molar units). The otherwise quite dissimilar element release rates may, in

294

addition to variable mineralogical composition, also be related to the particle size of the waste

295

rock, as previously observed (Langman et al., 2015; Schaider et al., 2007): experimental piles 1,

296

4, and 5 had tipping phases with as few as 2% of particles <0.25 mm and lower apparent S

297

release rates, whereas piles 2 and 3 had individual discharges with up to 22% of particles in the

298

more reactive <0.25 mm size fraction (Figure S1) and higher S release rates (Table 2). In

299

accordance with higher element release rates observed for acidic pile 2, the cumulative element

300

depletion was largest for pile 2, with e.g., 9% of its initial Cu content (5,767 ppm, hosted

301

primarily in chalcopyrite, Table S1), and up to 30% of its initial Zn content (298 ppm, mainly

302

hosted in sphalerite, Table S1) mobilized within 10 years (Table 2). Significantly smaller

303

element depletions were calculated for other piles and elements: e.g., 0.003% of 166 ppm Cu in

304

unidentified mineralogical hosts released from pile 4, and only 0.00002% of 11 wt-% Fe

305

associated with reactive sulfide minerals was released from pile 3 after 10 years of weathering

306

(Table 2).

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Table 2. Annual apparent element release rates (top) and cumulative element depletion

309

factors (bottom) calculated for the five experimental waste-rock piles at Antamina. Alkalinity

310

reflects dissolved carbonate only. Both the elemental depletion factors and the element release

311

rates are normalized to the elemental mass present in the original waste-rock piles. S

Fe

Ca

Cu -1

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Zn

-1

Alkalinity

Average apparent element release rates (mol kg waste rock yr ) for 2007-2017 (± rel. st. dev.) 4×10-4 (±18%)

3×10-8 (±72%)

4×10-4 (±17%)

4×10-9 (±29%)

7×10-7 (±18%)

6×10-5 (±20%)

Pile 2

3×10-3 (±87%)

5×10-4 (±159%)

7×10-4 (±16%)

1×10-3 (±122%)

2×10-4 (±92%)

5×10-5 (±98%)

Pile 3

1×10-3 (±18%)

6×10-8 (±41%)

1×10-3 (±13%)

8×10-8 (±35%)

2×10-5 (±35%)

6×10-5 (±18%)

Pile 4

5×10-4 (±28%)

3×10-8 (±71%)

5×10-4 (±28%)

1×10-8 (±79%)

4×10-7 (±26%)

4×10-5 (±37%)

Pile 5

7×10-4 (±32%)

2×10-8 (±70%)

7×10-4 (±29%)

7×10-9 (±74%)

2×10-7 (±27%)

4×10-5 (±37%)

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Cumulative elemental depletion of the waste rock (%) in 2017 (after 10 years of weathering) 8

0.00006

0.07

0.0004

0.06

0.06

Pile 2

4

0.5

0.8

9

30

20

Pile 3

2

0.00002

0.2

0.0004

0.06

0.2

Pile 4

7

0.00009

0.05

0.003

0.1

0.08

Pile 5

9

0.00005

0.08

0.0003

0.04

0.2

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Pile 1

The average S release rates (≜ apparent sulfide oxidation rates) calculated for the

314

experimental piles roughly varied between 0.01–0.1 g S kg-1 waste rock yr-1 (converted from the

315

molar units in Table 2). However, the acidification of drainage from pile 2 after 2014 increased

316

S release rates to over 10 g S kg-1 waste rock yr-1 in the wet season. Apart from this high release

317

rates from pile 2, the calculated average apparent sulfide oxidation rates are roughly an order of

318

magnitude lower than rates deduced from pore-gas monitoring in the experimental piles at

319

Antamina, which yielded oxidation rates ranging from 0.001 to 1 g S kg-1 waste rock yr-1 for

320

occluded, basal waste-rock, and exposed, reactive waste-rock, respectively (Lorca et al., 2016).

321

This suggests that direct monitoring of O2-consumption rates may yield more accurate intrinsic

322

sulfide oxidation rates than drainage monitoring (Hollings et al., 2001). Further, the apparent

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sulfide oxidation rates observed for non-acid-generating waste rock in this study (i.e. <0.001 kg

324

S kg-1 waste rock yr-1) are generally lower than rates observed from column experiments (e.g.,

325

<0.005 kg S kg-1 waste rock yr-1) (Strömberg & Banwart, 1999) and rates used in model

326

simulations (ranging from <0.001 to 0.02 kg S kg-1 waste rock yr-1) (Linklater et al., 2005;

327

Molson et al., 2005). This supports previous research that has shown that sulfide oxidation rates

328

may vary widely with different waste-rock mineralogies, particle sizes, and/or flow regimes

329

(Strömberg & Banwart, 1999; Sracek et al., 2006) and confirms that sulfide oxidation rates can

330

hardly be extrapolated across experimental scales or sites.

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3.5. Decoupling of waste rock- and drainage chemistry

332

Assuming congruent dissolution of primary waste-rock sulfides upon oxidation, the

333

disproportionally small release rates of Cu and Fe compared to those of S (Table 2) suggest that

334

>99% of Cu and Fe released from primary sulfide oxidation is retained in the experimental piles,

335

especially in those piles generating circumneutral drainage. Multivariate regression analyses of

336

the drainage concentrations indicated generally weak correlations between elements with known

337

lithological associations in the primary waste rock (Figure S3). For instance, correlations

338

between S and Fe or Cu (from pyrite and chalcopyrite, respectively) displayed correlation

339

coefficients -0.1 < r < 0.1 for all experimental piles but pile 2 (Figure S3). Although stronger

340

correlations were occasionally observed (e.g., for Zn and S from sphalerite ([Zn,Fe]S), Figure

341

3B), the stoichiometric ratios of these more-strongly-correlated elements in the drainage were

342

highly different from those in the waste rock (Figure 3B). Thus, various elements are

343

significantly and selectively retained in the experimental piles, as indicated by the quantitative

344

differences in the stoichiometry of the drainage chemistry versus that of the waste-rock

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mineralogy, evident from both multivariate regression analysis of individual drainage sample

346

concentrations and from comparison of long-term average release rates.

348

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Figure 3. Relationship between dissolved Ca and SO4 concentrations (A) and between

350

dissolved Zn and SO4 concentrations (double-logarithmic axes, B) measured in the drainage

351

from all five experimental piles in the studied period 2007-2017 (n=1,144). The dotted black line

352

in frame A indicates a 1:1 stoichiometric ratio, whereas the colored solid lines in frame B

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indicate linear-regression trend lines for which the corresponding coefficients of determination

354

(R2) and regression equations are given in the legend in the top left of frame B. Note that the

355

stoichiometry of the drainage chemistry in terms of Zn versus SO4 differs from that of the

356

average primary mineralogy (frame B, bottom right).

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3.6. Formation of discrete secondary mineral phases

359

Although the mineralogy of secondary precipitates in heterogeneous waste rock may be

360

variable due to the presence of ephemeral mineral phases that quickly appear, disappear, hydrate,

361

dehydrate, et cetera, as a result of variation of aqueous physicochemical environment (i.e. pH,

362

EH, chemical composition of the drainage), the analysis of collected secondary mineral

363

precipitates (Table 3, Figure S4, Figure S5) and equilibrium modeling (Figure 4) indicate that

364

substantial amounts of secondary mineral phases formed in the experimental waste-rock piles.

365

Although it is beyond the scope of this paper to address all identified secondary minerals in

366

detail, some relevant phases that relate to the observed element retention and decoupling between

367

drainage composition and waste-rock mineralogy will be discussed below.

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First, Ca concentrations in drainage from all experimental piles appeared to be controlled by

369

equilibrium with secondary gypsum: gypsum was identified in significant amounts in the

370

precipitates collected at the outflows of piles 1, 2, and 3 by XRD and Raman spectroscopy

371

(Table 3, Figure S4 and Figure S5), and the mineral was close to saturation in all piles during

372

the entire study period (Figure 4), while other Ca-phases were systematically undersaturated.

373

Because the solubility of gypsum is negligibly pH-dependent at 3
374

gypsum explains the relatively constant Ca drainage concentrations and release rates from the

375

experimental piles (Table 2) and the observed 1:1 stoichiometric ratio of Ca:SO4 drainage

376

concentrations (Figure 3A).

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Second, extensive precipitation of Fe-(oxy)hydroxides could be visually recognized near the

378

pile outflows, and equilibrium modeling indicated that various Fe-(oxy)hydroxides were

379

consistently and highly oversaturated (Figure 4) in all experimental piles, except in pile 2 when

380

it generated acidic drainage. No significant amounts of Fe-(oxy)hydroxides were implicated in

381

the precipitates from piles 1, 2, and 3 from XRD analyses, but various Fe-(oxy)hydroxides could

382

be identified by Raman spectroscopy (Table 3, Figure S4 and Figure S5). Precipitation of Fe-

383

(oxy)hydroxides has been previously observed in field-barrel experiments with Antamina waste

384

rock (Dockrey et al., 2014). The formation of secondary Fe-(oxy)hydroxides explains the

385

disproportionally low release rates of Fe compared to S (Table 2), and similarly, their re-

386

dissolution upon drainage acidification may explain the higher Fe drainage concentrations

387

observed from pile 2 after 2013, when e.g., secondary goethite became undersaturated (Figure

388

4). The fact that Fe-(oxy)hydroxides could be identified with Raman spectroscopy but not XRD

389

suggests that these secondary precipitates were extremely fine-grained (micro- or nano-

390

crystalline) or (partially) amorphous. This bears consequences for the release patterns of other

391

(trace) elements such as Sb, Se, and As, considering that microcrystalline and amorphous Fe-

392

and Al-(oxy)hydroxides provide excellent sorption sites for these oxyanions under the aqueous

393

conditions encountered in the drainage (Stumm & Morgan, 1995). In fact, elevated loads of the

394

oxyanionic metalloids Sb, As, and Se could be observed in pile 2 drainage after 2013 (Figure

395

S2), coinciding with increased Fe- and Al-releases at that time. Unfortunately, a quantitative

396

assessment of element retention by sorption versus by co-precipitation in secondary minerals is

397

challenging, due to the poor specificity of sequential leaching procedures, and by the

398

microcrystalline character of some secondary minerals that can therefore not be readily identified

399

using conventional XRD. Disentangling the quantitative contributions of sorption versus direct

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incorporation into secondary minerals on metal attenuation in waste rock is a topic of future

401

study. Finally, Cu and Zn drainage concentrations appeared to be controlled by multiple secondary

403

minerals: equilibrium modeling revealed that (mixed) Cu-/Zn-hydroxy-sulfates (e.g., antlerite

404

[Cu3(SO4)(OH)4], brochantite [Cu4SO4(OH)6], and namuwite [(Zn,Cu)4(SO4)(OH)6·n(H2O)) and

405

-hydroxy-carbonates (e.g., malachite [Cu2CO3(OH)2], hydrozincite [Zn5(CO3)2(OH)6], and

406

aurichalcite [(Zn,Cu)5(CO3)2(OH)6]) were at various times oversaturated or close to saturation in

407

drainage from pile 2 (Figure 4) and other piles (data not shown). Experimental analysis of

408

secondary precipitates indicated that Cu-, Zn-, and Fe-(hydroxy)-sulfates were abundant in piles

409

1,2, and 3, whereas Cu- or Zn- (hydroxy-)carbonates were only implicated in precipitates from

410

piles 1 and 3 (Table 3, Figure S4 and Figure S5), due to the limited stability of carbonates

411

under the acidic conditions in pile 2. The observed precipitation of (hydrated) Cu- and Zn-

412

hydroxy-sulfates appears similar to what has been found for Fe, i.e. the precipitation of goethite

413

[FeOOH],

414

copiapite [Fe5(SO4)6(OH)2·n(H2O)] and melanterite [FeSO4·nH2O] as a function of pH and SO42-

415

-availability (Bigham & Nordstrom, 2000).

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[Fe8O8(OH)6(SO4)·nH2O],

jarosite

[(K,Na)Fe3(OH)6(SO4)2],

EP

schwertmannite

A more complete appreciation of the controls of various secondary minerals on drainage

417

quality may be obtained by continued temporal (i.e. seasonal) sampling and by quantitatively

418

differentiating between the abundance and reactivity of various secondary precipitates that may

419

occur e.g., as intraclast and interclast precipitates, primary mineral pseudomorphs, et cetera. The

420

experimental waste-rock piles at Antamina are currently scheduled for disassembly in 2020,

421

enabling sampling of weathered waste rock from within the piles and a further in-depth

422

investigation of the secondary mineralogy and validation of the performed equilibrium modeling.

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423

Figure 4. Saturation indices of a selection of relevant secondary mineral phases in the

425

drainage of the experimental waste-rock piles during the studied period, inferred from

426

equilibrium modeling of the drainage chemistry from the basal lysimeters. Separate legends are

427

provided to the right of the individual panels.

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Table 3. Overview of a selection of relevant secondary mineral phases in the experimental

431

piles, inferred from equilibrium modeling of pile drainage chemistries, XRD analysis or Raman

432

spectroscopy. XRD analyses and Raman spectroscopy were performed on precipitate samples

433

collected from experimental piles 1,2, and 3 at Antamina in 2011 and 2014. XRD‡

Raman spectroscopy§

Mineral estimated in pile(s):

Mineral observed in pile(s):

Mineral observed in pile(s):

1,2,3,4,5 N.D. 2 2,3 N.D. 2 2 N.D. N.D. 3 2 1,2,3,4,5 1,2,3,4,5 1,2,3,4,5 4,5 2

1,2,3 (up to 95 w-%) 2 (up to 33 w-%) 1,3 (<0.5 w-%) 1,3 (up to 11 w-%) 2 (<0.5 w-%) 2 (<0.5 w-%) 2 (<0.5 w-%) 2 (<0.5 w-%) 2 (up to 2 w-%) 2,3 (<0.5 w-%) 1,3 (<0.5 w-%) 2,3 (<0.5 w-%) 2,3 (<0.5 w-%)

1,2,3 1,2,3 3 1, 3 2 2 2 2

SC

CaSO4 MnSO4·nH2O Cu3(CO3)2(OH)2 Cu2CO3(OH)2 Cu4(SO4)(OH)6·nH2O Cu4SO4(OH)6 Cu3SO4(OH)4 CuSO4·5H2O ZnSO4 Zn5(CO3)2(OH)6 (Zn,Cu)5(CO3)2(OH)6 5Fe2O3·9H2O FeOOH Fe8(SO4)O8(OH)6·nH2O Fe3(SO4)2(OH)6 FeSO4·nH2O

Equilibrium modeling†

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Gypsum Jokokuite/Szmikite Azurite Malachite Langite/Posnjakite Brochantite Antlerite Chalcanthite Zinkosite/Goslarite Hydrozincite Aurichalcite Ferrihydrite Goethite/Lepidocrocite Schwertmannite Jarosite Melanterite/Siderotil

Formula

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N.D. 2 (<0.5 w-%) 2 (<0.5 w-%)

N.D. 3 2 N.D. 1,2,3 3 2,3 2

N.D.: not determined with equilibrium modeling, and not detected with XRD or Raman analyses, respectively. † A secondary mineral phase was deemed potentially relevant when its saturation index in the drainage exceeded -1 for at least one year. The temporal evolution of the saturation indices of a selection of relevant secondary phases during the studied period is given in Figure 4. ‡ Quantitative evaluation of secondary mineral phases was limited to phases present at concentration >0.5 w-%. Qualitative XRD diffractograms of a selection of secondary mineral samples are provided in Figure S4. § A selection of Raman spectra of secondary mineral phases is provided in Figure S5.

444

Many precipitated secondary sulfate and carbonate minerals had mixed compositions and

445

structures that varied with sampling location and time, and that could not be resolved

446

experimentally due to sample heterogeneity, low mineral abundance, and/or poor crystallinity.

447

However, various additional relevant secondary minerals could be inferred from equilibrium

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modeling or chemical analytics, including Mn- and Zn-sulfates (Table 3) and Cu-, Ca-, and Zn-

449

molybdates (e.g., powellite [CaMoO4]), several of which have been previously observed in

450

humidity-cell- and field-barrel experiments with Antamina waste rock (Conlan et al., 2012;

451

Hirsche et al., 2017).

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Secondary mineral precipitation may not be quantitatively relevant until after a few years of

453

weathering (Smith et al., 2013b), but may have significant implications on longer timescales: the

454

accumulation of secondary minerals leads to underestimation of drainage-based intrinsic

455

weathering rates, their often amorphous structures provide excellent sorption sites for trace

456

elements, and changing porewater conditions past stability thresholds can lead to sudden re-

457

dissolution of previously-retained metals. The latter is exemplified, e.g., by the spike in Cu in the

458

drainage from pile 2 in 2011 (i.e. 3 orders of magnitude increase, Figure 2), which coincides

459

with sharply decreasing porewater pH/dissolved alkalinity and a declining saturation index of

460

secondary malachite (Figure 4) which readily dissolves below pH 6.3 (Ball & Nordstrom, 1991).

461

Because secondary minerals may govern metal retention and solubility, and thus waste-rock

462

drainage quality at large, their presence and stability under changing porewater conditions bears

463

direct consequences for drainage quality. Therefore, the design of on-site mine-wastewater

464

treatment systems may benefit from a quantitative assessment of secondary mineral formation

465

within waste-rock piles, e.g., using quantitative XRD or mineral liberation analysis (Fandrich et

466

al., 2007).

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467

3.7. Internal mixing controls the timing and composition of overall drainage

468

For adequate mine wastewater management, timing is at least as important as the rate of

469

drainage acidification. In this regard, the timing of acidification of pile 2 drainage may have been

470

unexpected: assuming that neutralization of acidity in pile 2 originates mainly from dissolution

28

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of carbonates or (Ca-)silicates (e.g., wollastonite [CaSiO3], andradite [Ca3Fe2Si3O12], and

472

diopside [MgCaSi2O6]; Table S1) (Harrison et al., 2012; Hirsche et al., 2017; Sherlock et al.,

473

1995), the apparent release rates and cumulative depletions of carbonate and Ca (Table 2)

474

suggest that only 16 t of the originally available acid neutralization potential in pile 2 was

475

consumed by 2017 (a total of 24 t or 150 t neutralization potential was estimated to be present

476

overall in pile 2, based on the measured C or NP concentrations, respectively, in waste rock in

477

the individual tipping phases; Table 1). This suggests that the basal drainage of pile 2 acidified

478

well before its overall neutralization capacity was depleted, which may be due to: i) ineffective

479

neutralization by carbonate (a mere total of <0.5% carbonate was present in pile 2, all of which

480

in the form of siderite that does not effectively buffer acidity (Dold, 2017) (Table S1), and the

481

neutralization efficiency of even pure limestone may be <30% (Skousen, 2014)), ii) slow

482

dissolution kinetics of silicates compared to carbonates (Eriksson & Destouni, 1997), iii)

483

occlusion of buffering minerals due to locking in primary waste rock or passivation by secondary

484

minerals, and iv) limited contact time and flushing due to preferential flowpaths (Eriksson &

485

Destouni, 1997; Blackmore et al., 2014; Fala et al., 2005; Pedretti et al., 2017). In addition to

486

the processes outlined above, mixing calculations with aqueous drainage compositions of the

487

three sub-lysimeters in pile 2 indicate that basal mixing strongly impacted the timing of

488

acidification and overall drainage composition of pile 2.

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Namely, drainage from the reactive tipping phase 3 in pile 2 acidified as early as 2013,

490

whereas drainage from less-reactive tipping phases 1 and 2 in pile 2 remains circumneutral to

491

date (Figure S6, Table S2). A mixing calculation, in which the drainages from individual sub-

492

lysimeters under these tipping phases were mixed according to their weight-fractions in pile 2

493

(details in the Supporting Information), could closely reproduce the drainage composition of the

29

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basal lysimeter of pile 2 (Figure 5B-E). This indicates that acidic leachate from reactive tipping

495

phase 3 in the front of pile 2 dominated the overall basal drainage quality of pile 2, which may be

496

understood by considering that carbonate-alkalinity concentrations in infiltrating porewater are

497

strongly solubility-limited, whereas acidity is not. In fact, additional mixing calculations with

498

hypothetical smaller weight fractions of the reactive tipping phase 3 suggest that reactive waste-

499

rock fractions as small as 10% of the total mass of pile 2 can lead to basal drainage compositions

500

similar to those measured (Figure 5).

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Although experimental pile 2 was the only pile with overall net-acid-producing potential

502

(Table 1), the individual tipping phases 1 and 2 in the back and middle of experimental pile 3

503

also contained substantial amounts of reactive sulfides (up to 7%) and a relatively small

504

neutralization potential ratio (Table S1). Yet, no significant drainage acidification was observed

505

in the basal- or sub-lysimeters of pile 3 within the studied period. This may be related to the

506

availability of carbonate in these tipping phases, but also to their location within pile 3 (i.e. back

507

and middle, respectively, compared to the frontal location of reactive waste rock in pile 2):

508

sulfide oxidation rates were previously found to be highest in the more exposed regions of an

509

experimental waste-rock pile at Antamina (Lorca et al., 2016). In summary, small fractions of

510

reactive waste rock incorporated in composite waste-rock piles, depending on their location, may

511

dominate the composition and temporal evolution of basal drainage. Thus, both the geochemical

512

and physical characteristics and the spatial distribution of waste rock would need to be known to

513

effectively optimize waste-rock storage and pile construction practices (e.g., blending strategies

514

(Pedretti et al., 2017; Parbhakar-Fox et al.,2018) for reduced environmental impacts.

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Figure 5. Schematic composition of pile 2 (reactive tipping phase 3 indicated in bold) and

518

the basal mixing process (A); and comparisons of the pH (B); Ca concentrations (C); SO4

519

concentrations (D); and Cu concentrations (E) measured in the basal drainage of experimental

520

pile 2 with those calculated by basal mixing of drainage from the individual tipping phases in

521

pile 2, using varying actual and hypothetical sizes of the reactive tipping phase 3. Plotted

522

concentrations and pH values are the observed and calculated annual averages for the years

523

2012-2015; error bars indicate the standard deviation of the averages measured in the

524

respective years. The legend (bottom) applies to all frames.

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4. Conclusions

527

Long-term field monitoring of waste-rock weathering at Antamina showed that both seasonal

528

and long-term variations in waste-rock drainage quality are only partially related to physical and

529

geochemical features of the waste rock, e.g., particle size or primary mineralogy, and to seasonal

530

variability in hydrological transport. The quantity and quality of drainage is also strongly

531

impacted by (temporary) element retention due to sorption and the precipitation of secondary

532

minerals, and by internal drainage mixing processes. These results illustrate that the timing and

533

quality of drainage released from waste rock can hardly be predicted based on conventional

534

static-testing and a priori evaluation of the waste-rock mineralogy alone, and that weathering-

535

and release rates may not be extrapolated across sites and scale ranges. Instead, the presented

536

results suggest that the design of future waste-rock piles and active management of existing

537

storage facilities at Antamina and other mines may be improved by relying on in-situ data (e.g.,

538

from boreholes or more representative, larger-scale pile experiments) rather than on classic static

539

testing or kinetic tests (i.e. humidity cells) alone. For instance, quantitative assessments of the

540

prevailing in-situ porewater conditions, secondary mineral formation, and the spatial distribution

541

of reactive waste-rock may be used to optimize waste-rock placement (i.e. blending) and develop

542

drainage-quality forecasting tools for full-scale facilities to support effective wastewater

543

management decisions that are targeted towards minimizing the impacts of reactive waste rock

544

oxidation through mitigation of peak concentrations or seasonal variations in drainage quality.

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Acknowledgements

547

We thank all involved Antamina staff for their assistance with the pile construction and their

548

longtime contributions to the project, ranging from equipment maintenance and technical

549

troubleshooting to sample and data collection. Vincent Marmier, Mikaela Frame, and Sarah

550

Raschella are acknowledged for support with data processing. We thank Matthijs Smit and

551

Melanie St.Arnault for technical support with Raman analyses, and Jenny Lai and Lan Kato for

552

assistance with XRD analyses. Funding provided by Compañia Minera Antamina S.A., the

553

Natural Science and Engineering Research Council of Canada (NSERC), and Teck Metals

554

Limited’s Applied Research and Technology Group is gratefully acknowledged.

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Disclosure

557

The authors declare no financial or other conflicts of interest.

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References Alwan et al., 1980: Alwan, A. K.; Thomas, J. H.; Williams, P. A. Mineral formation from aqueous solution. Part III. The stability of aurichalcite, (Zn,Cu)5(CO3)2(OH)6, and rosasite

563

(Cu,Zn)2(CO3)(OH)2. Transition Metal Chemistry 1980, 5, 3–5.

564 565

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Highlights Decade-long monitoring of waste-rock weathering under natural conditions

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Primary weathering rates vary with waste-rock composition and particle size

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Metal sorption and secondary mineral formation affect drainage chemistry

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Reactive waste rock dominates the overall drainage quality from composite piles

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Demonstration of partial decoupling of primary mineralogy and drainage quality

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