sampling analysis testing mine wastes geochemical predictions risk assessment kmorin

Análisis de Prácticas Actuales de Gestión de Aguas Ácidasen Chile y en el Mundo

Sampling, Analysis, and Testing of Mine Wastes for Geochemical

Predictions and Risk Assessment

Kevin A. Morin, Ph.D., P.Geo., L.Hydrogeo.Minesite Drainage Assessment Group

www.mdag.com

3.1. Visión general, objetivos y alcances de la caracterización de residuos mineros

3.2. Muestreos y análisis

3.3. Tests de laboratorio- Tests estáticos- Tests cinéticos

3.4. Tests de campo

Outline of This Presentation

Each proposed, operating, and closed minesite may have differentsets of objectives for waste characterization. These objectivesoften focus on the waters draining from a minesite and its components, like mine walls, waste rock, low-grade ore, and tailings.

Objectives can include:- predicting future drainage chemistry, including changes through time;- understanding current drainage chemistry for operating or closed

minesites;- estimating costs for preventing or controlling drainage-chemistry

problems;- choosing among prevention/control options based on their

effectiveness, risk, and cost;- evaluating whether wastes exceed sediment/toxicity levels and thus

must be physically confined.


The scope of studies to address these objectives can be minimal to intensive. The scope depends on factors like severity of environmental degradation, issues and questions, available funds, and public concerns.

Although objectives and scopes may differ among minesites, the same combination of geochemical tests can be used. This combination of tests is discussed in Sections 3.3 and 3.4 of this presentation.


Each proposed, operating, and closed minesite may identify and collect samples in different ways. The sizes, numbers, and types of samples can differ, depending on objectives (Section 3.1). For example:

- one site may collect hundreds of samples from core, whereas others may collect only dozens of samples from outcrop rock;

- one site may collect 2 m sections of drill core, whereas others may collect short, 10 cm sections;

- one site may conduct detailed tests on tailings, whereas another may not;

- one site may collect on-site drainage waters, whereas another may not.

There is no one approach to sampling - it is unique to each minesite and each objective. By showing the results of laboratory analyses, the next section also illustrates the sampling programs undertaken by mining companies and their consulting companies.


For proposed minesites and proposed expansions, sampling can coincide with mineral exploration, using the same core, rejects, and pulps assayed earlier for ore. In this way, the reliability of environmental predictions is tied closely to the reliability of economic and resources estimates.

Once appropriate samples are collected, they should be analyzed as explained in Sections 3.3 and 3.4 below.


The easiest way to explain the laboratory and on-site field tests is by using the analogy of a “wheel”.

I call this the “Wheel Approach” for predicting, scaling, and understanding mine-waste geochemistry and minesite-drainage chemistry.

3.3. Tests de laboratorio y 3.4. Tests de campo

• Acid Rock Drainage (ARD) is basically the result of a geochemical battle within rock or soils containing sulphide minerals like pyrite. Upon exposure to air and moisture, sulphide minerals like pyriteoxidize, which releases acidity and leaches metals into nearby water.

• Frequently, there are also fast-acting acid-neutralizing minerals in rock and soil that dissolve in response to the acid generation. These neutralize and eliminate the acidity and, by raising the pH to near-neutral values, minimize the leaching of metals into nearby waters.

• This geochemical battle continues until either:• (1) the sulphide minerals are depleted before the fast-acting neutralizing

minerals and thus there is no ARD or major leaching of metals, or

• (2) the fast-acting neutralizing minerals are depleted first, leading to significant ML/ARD.

Wheel Approach for Minesite-Drainage Chemistry

Ref. B0001, B0002, A1957This is a list of relevant references that can be downloaded for free from

www.mdag.com/presentations/iquique-2010.html

• Metal leaching (ML) is the release of metals from rock or soil into any water flowing over/through these materials. The extent and degree of leaching are typically unique for each metal, reflecting a site’s unique combination of mineralogy, water chemistry, water flow, and solid-liquid interactions.

• In a general sense, the solubilities of several metals are highest at acidic pH and lower around neutral pH, so that ML is more severe with ARD. However, there are documented cases where ML was more severe around neutral pH, so the leaching of metals at a particular site must be examined even when ARD is not present.


Ref. B0001, B0002, A1957

• Because drainage-chemistry from mixed-mineral systems is difficult to predict and understand, a suite of tests have been developed and combined over the last century.

• Each test has strengths and weaknesses, so no one test is sufficient for drainage chemistry.

• For simplicity, this suite of tests is depicted on the next slide as a “wheel” with spokes. It is important to perform as many of these types of tests as feasible.

• The tests can be mostly divided into:• “static” tests performed only once to measure sample

composition• “kinetic” tests using repeating analyses to measure a sample’s

reactivity and leaching capacity


Ref. B0001, B0002, A1957

On-SiteMonitoring

Data

Acid-BaseAccounting

Total Elements &Whole Rock

Mineralogy Retention/ Soluble-MineralTests

LaboratoryKinetic Tests

FieldKinetic Tests

Drainage ChemistryKinetic; usually small scale

Kinetic; usually medium scale

Kinetic; usually full scale

~Static; usually small scale

Static; usually small scale



NAG Testing:Single, Sequential,Kinetic, and ABCC

Static and Kinetic; usually small scale


For a proposed minesite, full-scale On-Site Monitoring Data may not be available. Other “Wheel” tests will lead to predictions of full-scale drainage chemistry.

For a historical minesite, full-scale On-Site Monitoring Data may be available. However, to understand the origin of the full-scale drainage chemistry, and to predict changes through time, the other “Wheel” tests are needed

Ref. B0001, B0002, A1957

Secondary-mineral-distorted rates of acid generation, acid neutralization, and metal leaching from an existing mined area, possibly of unknown volumes and weights, under

on-site conditions; check for equilibrium

On-Site Monitoring

Secondary-mineral-distorted rates of acid generation, acid neutralization, and metal leaching from relatively large samples with known volumes and weights under on-site

conditions; upscaling calibration of laboratory kinetic tests; check for equilibrium

Field Kinetic Tests

Primary rates of acid generation, acid neutralization, and metal leaching from relatively small samples under controlled laboratory conditions; lag times to net acidity; site-specific

ABA criteria; check for equilibrium, especially in initial flushes

Laboratory Kinetic Tests

Concentrations and amounts of readily soluble and leachable metals and other elements, and of elements accumulated during past oxidation and reactions; check for equilibrium

Retention/ Soluble Tests

Identities and abundances of specific mineralsMineralogy

Bulk solid-phase amounts of metals and other elementsTotal Element/ Whole Rock

Net acid generating capacity based on rapid oxidation with hydrogen peroxideNAG Tests

Bulk amounts of (1) acid-generating sulphide and non-acid-generating sulphate minerals and (2) fast-neutralizing carbonate and slow-neutralizing minerals; overall net balances of

acid-generating and acid-neutralizing capacities

Acid Base Accounting

(ABA)

DescriptionName

Summary Descriptions of Testwork under the “Wheel” Approach for Predicting Minesite-Drainage Chemistry


• Good explanations, strengths, and weaknesses of these tests under the Wheel can be found in Price (2009).


Ref. A1957

Most testwork and modelling for minesite-drainage chemistry may extend above and below the Scale Transition.

This greatly complicates the interpretations of testwork, and can lead to errors.

Increasing Scale, Weight, Volume, Time, Solid:Liquid Ratio,Reaction Rate, Residence Time, or Distance Along Flowpath

Incr

easi

ng A

queo

us C

once

ntra

tion

(mg/

L) Maximum “equilibrium” concentrations apply in this part of the curve,caused by thermodynamics, metastability, emergence, etc.

Kinetic rates apply in this part of the curve

ScaleTransition

At what scale, weight, time, ratio, etc., is the Scale Transition met for a particular minesite component and element?

geochemical modelling

1-kg humidity cell

20-50-kg column

1-t leach pad

“full-scale” minesite component

100-g shake flasks

a few grains of minerals

“mesoscale”

“microscale”

Ref. CS0026


Increasing Size (Scale), Residence Time, or Distance Along Flowpath

Incr

easi

ng A

queo

us C

once

ntra

tion

(mg/

L)Equilibrium

The smaller-scale kinetic tests of the Wheel may measure only kinetic conditions. Larger-scale kinetic tests may measure only equilibrium conditions. For a particular minesite component, all kinetic tests may measure only kinetic or only equilibrium conditions.

The tests do not tell us which condition applies. We have to determine that.

Kin

etic


Ref. CS0026

Not all tests under the Wheel may be applicable or feasible for all minesite components.


Ref. B0001, B0002, A1957

On-SiteMonitoring

Data

Acid-BaseAccounting




FieldKinetic Tests











Wheel Approach – Acid-Base Accounting (ABA)

• In more detail, expanded ABA can include:• paste pH in a mixture of pulverized rock and water, • total sulphur,• measured sulphide,• leachable sulphate (both HCl and carbonate leach techniques), • calculated sulphide by subtracting sulphate from total sulphur,• barium-bound sulphate calculated from barium analyses,• calculation of acid potentials based on sulphide levels plus any unaccounted-for sulphur

(Sulphide Acid Potential, SAP),• Sobek (U.S. EPA 600 compliant) neutralization potential (NP) by acid bath and base

titration, • inorganic carbonate for mathematical conversion to Carbonate NP (Inorg CaNP), • total carbon for mathematical conversion to Carbonate-equivalent NP (Total CaNP),• excess carbon calculated from the difference between total carbon and inorganic carbon,• CaNP calculated from calcium (Ca CaNP),• CaNP calculated from Ca + Mg (Ca+Mg CaNP),• various Net Neutralization Potential (NNP) balances of acid neutralizing capacities minus

various acid generating capacities, and• various Net Potential Ratio (NPR) balances of acid neutralizing capacities divided by

various acid generating capacities

Indefinitely near neutral or alkalineNPR > 2 or NNP > +20 kg/t

Uncertain without further testwork1<NPR<2 or 0<NNP<+20 kg/t

Eventually acidic after some “lag time”NPR < 1 or NNP < 0 kg/t

Based on NPR or NNP

Currently alkaline; future unknownPaste/rinse pH > 9-10

Currently near neutral; future unknown5-6.5 < Paste/rinse pH < 9-10

Currently acidic; future unknownPaste/rinse pH < 5-6.5

Based on paste or rinse pH

Prediction or Current ConditionCriteria

Generic Non-Site-Specific ABA Criteria for Assessing or Predicting the pH Range of Minesite Drainage Chemistry

(many exceptions are known, so site-specific criteriamust be developed to replace these)

Part of ABA includes measuring the pH of a mixture of powdered sample and water (“paste pH”) and the calculation of Net Potential Ratio (NPR = Neutralization Potential / Sulphide Acid Potential, or NP/SAP). These parameters can be used to explain the current conditions and predict future ML/ARD using ABA Criteria.

Wheel Approach – Acid-Base Accounting (ABA) - Criteria

AvailableAcid Potential (Av AP)

Available NeutralizationPotential (Av NP)

The “bad guys”trying to create ARDthrough sulphideoxidation

The “good guys”trying to neutralizethe acidity fromsulphide oxidation

Net Potential Ratio (NPR)

• For NP to win the long-term geochemical battle and prevent ARD, there must be more Available NP than Available AP. That is, NPR must be greater than 1.0, often greater than 2.0. An NPR criterion of 2.0 is typical for minesites, but values below 1.0 and above 4.0 have been reported.

• ABA has implicit limitations, like it assumes all sulphide will generate acidity and all NP can be measured within several hours of testing. If Available AP and/or Available NP from ABA are wrong, then NPR-based predictions could be wrong.

Wheel Approach – Acid-Base Accounting (ABA) - NPR

This is a scatterplot of sulphide and total sulphur from ABA at a minesite, It showed that most sulphur was potentially acid-generating sulphide.

Another part of the “Wheel”, mineralogy, was used to confirm this sulphide was primarily pyrite. Pyrite is a common acid-generating mineral when exposed to air and moisture.

0.001 0.01 0.1 1 10% S (Total)

0.001

0.01

0.1

1

10

% S

(S

ulp

hid

e)

1 : 1

Wheel Approach – Acid-Base Accounting (ABA) - Sulphur

0 1 2 3 4

600

500

400

300

200

100

0

Dri

llho

le D

epth

(m

)

0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4 0 1 2 3 4

FeS2 (%)

DDH 106 DDH 107 DDH 143DDH 110 DDH 112 DDH 112 DDH 113 DDH 142 DDH 144

At this site, dozens of drillholes contained FeS2 (pyrite), often around 0.5-2%. This means that a few ABA would not be sufficient to evaluate NPR reliably for thus site. Normally,

hundreds to thousands of ABA are required.

Wheel Approach – Acid-Base Accounting (ABA) - Sulphur

• One of the largest sources of errors, and misunderstood concepts in minesite-drainage chemistry, is Neutralization Potential (NP). Problems and errors related to NP will be shown later in this presentation.

• These problems and errors can be traced to three major NP issues:• NP is an extrinsic rather than an intrinsic property• Several incompatible methods exist for measuring NP, but the

results of all are called “NP”• Available NP for NPR calculations is typically not equal to

measured NP

Wheel Approach – Acid-Base Accounting (ABA) - NP

Ref. CS0032

• NP is an extrinsic rather than intrinsic property

• A sample of rock, overburden, tailings, or other minesite material contains a specific amount of copper or sulphur or other element in the Periodic Table, and has a certain mass. These are called intrinsic properties. An intrinsic property can be defined as a property that is specific to a sample or minesite component, and wholly independent of any other object, action or consequence.


Ref. CS0032

• NP is an extrinsic rather than intrinsic property• Extrinsic properties depend on, or are defined by, external conditions.

• For example, two dry sponges have masses of 100 grams. If one sponge is squeezed hard and the other softly, they both still have the same mass, but different volumes. In this example, volume is anextrinsic property that depends on the pressure (squeezing) applied to the sponges.

• As another example, two identical sponges are squeezed by the same amount, but for different lengths of time. The one squeezed longer will compress more through time, and thus have a smaller volume at the end. So time also can affect extrinsic properties.

• In these example, would you call one volume “right” and the other volume “wrong”? This happens with NP methods.


• NP for minesite materials is an extrinsic property that depends on external conditions like pH, temperature, and time.• The lower the pH in the NP test (more aggressive testing), the greater the

neutralization that may be obtained from some mixed-mineral samples. This does not apply to all mixed-mineral samples.

• The higher the “pH endpoint” of the NP test (additional neutralization, the greater the neutralization that may be obtained from some mixed-mineral samples. This does not apply to all mixed-mineral samples.

• The higher the temperature of the NP test (faster reaction rates), the greater the neutralization that may be obtained from some mixed-mineral samples. This does not apply to all mixed-mineral samples.

• The longer the time of the NP test (longer reaction times), the greater the neutralization that may be obtained from some mixed-mineral samples. This does not apply to all mixed-mineral samples.


Ref. CS0032

• NP is an extrinsic rather than intrinsic property• As an extrinsic property, NP is defined by the method to measure it.

This is the same for the aqueous parameters of alkalinity and acidity.

• Confusingly, there are many methods to measure NP (see next slides), each using different analytical conditions, but the results from all methods are called “NP”. For any particular sample, three different methods may yield three different NP values for that sample, but all are called NP.

• Some people and experts argue which NP method is “right”. None are inherently “right” or “wrong”, but reflect the analytical conditions.

• It is critical that a mining project or minesite select and use one NP method consistently, so that all NP values can be compiled and interpreted consistently and correctly for that site.


Ref. CS0032

REFERENCE:Morin, K.A., and N.M. Hutt. 2009. On the Nonsense of Arguing the Superiority of an Analytical Method for Neutralization Potential.

MDAG Internet Case Study #32, www.mdag.com/case_studies/cs32.htmlIn response to comments on this case study, we saw value in expanding and elaborating some points in the following documents:

NP - Additional Discussion on Its Non-Intrinsic NatureNP - Arguments on NP-Method Superiority Translated into Varieties of Oranges


Ref. CS0032

For any sample, the various NP methods may provide similar or notably different values. Modified NP can be higher or lower than Sobek NP.


46155.793182032320.72.5Carbonate CaNP

4612519161932510Mineralogical NP

55153.8301624283.32.83.0Lapakko NP

5820158225303325117.7BC Research NP

723.22.96120272814339.6Modified NP

997.53.846182728153512Sobek NP

TL6TL5TL4TL3TL2TL1RK4RK3RK2RK1Sample (RK = rock;TL = tailings)

Neutralization Potential (kg CaCO3 eq/tonne)

Comparison of Five NP Techniques for Acid-Base Accounting

The problem with NP methods is that not all measured NP is available, effective, and reactive.

The International Static Database is a compilation of more than 19,000 ABA from around the world. It showed that, as NP decreased, towards zero, acidic pH values were sometimes encountered (left).

Therefore, some amount of measured NP is “unavailable” for neutralization.

19,232 datapoints

Ref. M0002, M0015

Based on studies at various scales, Available NP for NPR calculations can be estimated from:

Available NP =

Measured NP

- Unavailable NP

+ Slow-Reacting NP

COMPLICATIONS:

Measured NP is method specific.

Unavailable NP is discussed on the next slide

Slow-Reacting NP is dependent on factors like time, scale, and mineralogy


Ref. CS0030, CS0031, CS0032

Unavailable NP (UNP) =

Analytical-method UNP + Sample-specific UNP + Upscaling-effect UNP

UNP from:

- artifacts in analytical methods,

- sample-specific conditions, like siderite,

- upscaling emergent effects, like the encapsulation of reactive NP rendering it unavailable at the existing grain size.


Ref. CS0030, CS0031, CS0032


• Estimates of Unavailable NP can be obtained from ABA, NAG (ABCC) testing, laboratory kinetic tests, and larger-scale on-site kinetic tests.

• The following slides show ABA results from actual minesites and mining projects.

• The objective of each was to estimate Unavailable NP, relatively quickly and cheaply using only ABA (paste pH) results. WARNING: This quick approach works only if samples are well weathered and oxidized, and some have become acidic. This approach does not work for fresh, unoxidized samples.

Ref. B0001, B0002, A1957


-10 0 10 20 30 40 50 60 70 80 90 100

2

4

6

8

10

Initial Estimate ofUnavailable NP =10 kg/t at pH 5 and 6

But what about theseanomalous acidic sampleswith NP > 10 kg/t?

Pas

te p

H

Neutralization Potential (kg CaCO3 eq/t)Ref. CS0030


0 20 40 60 80 100

2

4

6

8

10

Rock Unit 1

Rock Unit 2 (excluding 2a)

Rock Unit 2a

Rock Unit 3

Rock Unit 4

Undifferentiated Waste Rock

Pas

te p

H

Neutralization Potential (kg CaCO3 eq/t)

Initial Estimate ofUnavailable NP =3 kg/t

Ref. CS0030


0 40 80 120 160 200

0

2

4

6

8

10

Andesite

Argillite

Contact Zone

Rhyolite

Rhyolite Massive

Rhyolite Flow

Rhyolite Breccia

Dacite

Ore

Mudstone


Pas

te p

H


Higher values ofNP truncated

Ref. CS0030


1 10 100 1000

4

5

6

7

8

9

ZoneOre Zone #1

Ore Zone #2

Ore Zone #3

If d a ta w a s repo rted as < de tection lim itha lf the detection lim it is show n an d w asused in subse que n t ca lcu la tion s .

UnavailableNP = 15 kg/tfor Zone #1

UnavailableNP = 5 kg/tfor Zone #2

Pas

te p

H

Neutralization Potential (kg CaCO3 eq/t) Ref. CS0030


-40 -20 0 20 40

0

2

4

6

8

10

Three limestone sampleswith NP ~ 900 kg/t not shown


Pas

te p

H

Neutralization Potential (kg CaCO3 eq/t)Ref. CS0030


0.1 1 10 100 1000

2

4

6

8

10

Rock Unit

BRK (Zone #1)

CBS (Zone #1)

MXZ (Zone #1)

OVB (Zone #1)

OXZ (Zone #1)

SPR (Zone #1)

SUL (Zone #1)

BRK (Zone #2)

CBS (Zone #2)

MXZ (Zone #2)

OVB (Zone #2)

OXZ (Zone #2)

SPR (Zone #2)

SUL (Zone #2)

Pas

te p

H


Initial Estimate ofUnavailable NP =

10 kg/t at pH 6 and 5

Ref. CS0030

• The most common value for Unavailable NP is around 10 kg/t, but site-specific values from 0 to >50 kg/t have been reported. UNP should be subtracted from all measured NP values to obtain an Available NP for net-balance NPR calculations.

• In the past, there were rules of thumb, like only 1/3 of measured NP should be used in ARD predictions.

• Also, in the old days of NNP, the common criterion of +20 kg/t implicitly recognized up to 20 kg/t of NP would be unavailable.

• I have seen >95% ARD reports not subtracting Unavailable NP (UNP), but using all the measured NP. With low-NP samples, this can lead to major ARD errors. Such errors have occurred, as shown later in this presentation.


Sulphide Net Potential Ratio (SNPR) equals Neutralization Potential divided by Sulphide-based Acid Potential. “Adjusted” means Unavailable NP has been subtracted before the NPR calculation.

In this example, 33% of these 230 samples are net acid generating, based on generic criteria. Many are not acidic at this time. The lag time until they become acidic is determined from kinetic tests.

16% of the samples are “uncertain” until further kinetic testing. This testing will provide the site-specific values of SNPR and thus eliminate the uncertain category.

0.001 0.01 0.1 1 10 100 1000Adjusted SNPR

2

4

6

8

10

Pas

te p

H

If S (Sulphide+del) <0.01 thenAdjusted SNPR = 200,if (NP - 5) = < 0 thenAdjusted SNPR = 0.001.

Net acid generating,

already acidic

Net acid generating, not

yet acidic

Theoretically not possible

Net acidneutralizing

Unc

erta

inU

ncer

tain


50% of the existing waste rock has a sulphide content of 0.3%S and less.

Based on an SNPR criterion of 1.0, 32% of the waste rock is net acid

generating (55% with a criterion of 2.0). However, water-chemistry

monitoring shows this waste rock does not affect pH or add sulphate to the water, so it is not highly reactive.

0 20 40 60 80 100% of Total Rock in Waste Rock Dump

0.01

0.1

1

10

% S

(S

ulp

hid

e)

=<

=<

=<

=<

0 20 40 60 80 100% of Total Rock in Waste Rock Dump

0.01

0.1

1

10

100

SN

PR

=<

=<

=<

=<

=<

Net acid neutralizing

Net acid generating


On-SiteMonitoring

Data

Acid-BaseAccounting




FieldKinetic Tests











• Total-element analyses determine the total solid-phase levels of metals and other elements in small-scale homogenized samples.

• Such analyses include four-acid-digestion ICP-MS and x-ray-fluorescence whole rock.

• The purposes of such analyses include:• comparison to worldwide crustal abundances• comparison to environmental sediment-toxicity values• correlations among solid-phase elements, suggesting mineralogical

associations• correlations of aqueous leaching rates from kinetic tests with initial

solid-phase levels of sulphur or other elements• predicted times of solid-phase depletions of elements based on

aqueous leaching rates from kinetic tests

Wheel Approach – Total Element Analyses

Ref. B0001, B0002, A1957

• IMPORTANT: Solid-phase levels do not say whether aqueous leaching rates will be high or low.

• A high solid-phase level may create a high or low aqueous leaching rate.

• A high solid-phase level may be high, because it leaches slowly.

• Kinetic tests provide aqueous leaching rates, not solid-phase static tests.

• For some elements, some site-specific correlations are sometimes seen between aqueous leaching rates and solid-phase levels.


Ref. B0001, B0002, A1957

• As examples for comparisons to crustal abundances or sediment-toxicity criteria:• “This showed that [this site’s] rock samples were:

• frequently elevated in silver, bismuth, copper, sulphur, and selenium;

• occasionally elevated in arsenic, mercury, molybdenum, and antimony; and

• rarely elevated in cadmium, chromium, cesium, indium, phosphorus, lead, tungsten, and zinc.

• At least one tailings composite was elevated in silver, arsenic,bismuth, copper, sulphur, antimony, and selenium.”

• “This showed that [this site’s] samples were:• frequently elevated in silver, bismuth, copper, molybdenum,

sulphur, antimony, selenium, and tungsten; and,• occasionally to rarely elevated in arsenic, cadmium, cesium, lead,

and zinc.”


In this example, a correlation of sulphide with arsenic suggested the rate of arsenic leaching may depend on the rate of sulphide oxidation.

In that case, any reduction in the rate of sulphide oxidation will also reduce arsenic leaching.

0.001 0.01 0.1 1 10% S(Sulphide)

0.001

0.01

0.1

1

Ars

enic

(%

)

FeAs

S +

AsS

There is more arsenic than sulphide in this

region, so the arsenic can occur in forms other

than FeAsS and AsS

All arsenic in this region can exist as

FeAsS and AsS

Wheel Approach – Total Elements

This example showed that measured NP in most samples was, as a minimum, carbonate based (lower left), but many samples contained some non-carbonate NP.

Solid-phase manganese generally correlated with NP (lower right). Thus, a significant portion of manganese was likely contained in carbonate minerals. In turn, any acceleration of NP dissolution, such as by underwater disposal or acid generation, could lead to accelerated leaching of manganese.


1 10 100 1000Neutralization Potential (kg CaCO3 equivalent/tonne)

10

100

1000

10000

Man

gan

ese

(pp

m)

Mitchell - IntrusiveMitchell - MetasedimentaryMitchell - VolcanicMitchell - Other/UnknownSulphurets - IntrusiveSulphurets - MetasedimentarySulphurets - VolcanicSulphurets - Other/UnknownKerr - IntrusiveKerr - MetasedimentaryKerr - VolcanicKerr - Other/Unknown

If data was reported as < detection limit,half the detection limit is shown andwas used in subsequent calculations.

10 100 1000Neutralization Potential (kg CaCO3 equivalent/tonne)

1

10

100

1000

Ino

rgan

ic C

aNP

Wit

h a

NP

> 1

5 (k

g C

aCO

3 eq

uiv

alen

t/to

nn

e)

Mitchell - IntrusiveMitchell - MetasedimentaryMitchell - VolcanicMitchell - Other/UnknownSulphurets - IntrusiveSulphurets - MetasedimentarySulphurets - VolcanicSulphurets - Other/UnknownKerr - IntrusiveKerr - MetasedimentaryKerr - VolcanicKerr - Other/Unknown

If data was reported as < detection limit,half the detection limit is shown andwas used in subsequent calculations.

Samples close to this line suggest mostof the measuredNP was composedof carbonate. Most samples hadadditional, non-carbonate NP.

Modelos Geoestadísticos por Proyecto de Las Cristinas en Venezuela en 1995 (ABA = 2500)

Wheel Approach – Large-Scale Three-Dimensional Modelling of ABA/Total-Element Data

• The two approaches for three-dimensional modelling of acid-base-accounting data at this site indicated 3.6-5.1% of the pit rock, by volume, was net acid generating. This rock was not scattered throughout the pit area, but occurred in distinct masses, within the black mesh zones below. The much greater volume of rock was be net neutralizing.


• Based on small-scale ABA samples, about 13% of samples were net acid generating. This is greater than the 3.6-5.1% from large-scale 3D modelling. Therefore, this modelling showed that small-scale sample percentages overestimated the large-scale 3D volume percentage.

• In other cases, sample percentages can underestimate large-scale volumes of net-acid-generating rock.


For open-pit mines before mining, ABA samples are collected in three dimensions from drillholes (black straight lines below). Geostatistical modelling in three

dimensions highlights net-acid-generating zones (red areas below) within the proposed pits (grey surfaces) that will become waste rock.


For underground mines, ABA samples are not usually collected in three dimensions as with open pits. This is because underground mines are often linear tunnels. Thus, samples for ABA and total elements are collected in more linear patterns.

Wheel Approach – Acid-Base Accounting and Total Elements

D-66-001

D-66-046D-66-040

D-66-034

D-66-026

D-66-022D-66-015

D-66-012D-66-007

D-66-067D-66-075

D-66-080D-66-083

D-66-062

D-66-059

D-66-054

D-66-049

D-66-088

D-66-095D-66-099

D-66-102

D-66-155

D-66-147D-66-145

D-66-141D-66-133

D-66-130D-66-124

D-66-119

D-66-114

D-66-109D-68-055

D-68-051

D-68-030

D-68-001

D-68-010

D-68-036

D-68-024

D-68-005

D-68-060D-68-066

D-68-071D-68-075

D-68-081D-68-090

D-68-097D-68-102

D-68-109 D-68-014

D-68-021

150

No

rth

Ad

it

150

So

uth

Ad

it

161 South Adit

161

No

rth

Ad

it

D-68-041

D-68-046

D-68-112

D-68-117D-68-124

D-68-130D-68-137

D-68-142

D-68-248D-68-258

D-68-242

D-68-144

D-68-155D-68-236

D-68-156D-68-164D-68-176D-68-188D-68-200D-68-215

D-68-232

Main Adit

Po

rtal

~500 ft~150 m

Bowser(Skeena

SedimentaryRock)

Hazelton Volcanics(predominantly tuffs)

Granodiorite(ore zone)

N

Sampling Locations

The resulting analyses, like solid-phase arsenic below, are interpreted in a different manner than 3D open pits.

6.5

0.83.9

1.5

1.9

15.3

14.8

1.97.2

1.31.7

3.8

1.5

2.4

2.8

1.9

1.51

4

2.1

2.364.7

2.73.8

7.61.9

2.5

3.5

4.93.5

3.2

1.4

2.2

9.1

7.5

1.2

8

1.22

1.71.2

1.25.4

1.51.4

1.2 5.8

92.9

150

No

rth

Ad

it

150

So

uth

Ad

it

161 South Adit

161

No

rth

Ad

it

25.7

2

2.1

3.61.2

7.51.8

2

1.81.4

4.2

1.2

41.6

2.42.7

11.81.62.5

2.2

Main Adit

Po

rtal

~500 ft~150 m

Bowser(Skeena

SedimentaryRock)

Hazelton Volcanics(predominantly tuffs)

Granodiorite(ore zone)

N

Arsenic(ppm)

92.9 Red means As > 3times crustal abundance


Based on drillhole distance from the ore zone, net-acid-generating samples in the footwall were common at least 40 m from the ore zone.

Net-acid-generating samples of the hanging wall were occasionally encountered at distances up to approximately 20 m from the ore zone, and less frequently at distances up to 134 m.

-200 -160 -120 -80 -40 0 40 80 120 160 200Minimum Distance from Ore Zone along Drillhole (m)

0.001

0.01

0.1

1

10

100

1000

Ad

just

ed T

ota

l-S

ulp

hu

r-B

ased

Net

Po

ten

tial

Rat

io

Recent - FootwallHistorical - FootwallRecent - Hanging WallHistorical - Hanging WallHistorical - Ore ZoneHistorical - Location Unknown

If % S(Total) < 0.01 then TNPR = 200If % S(Total) > 0.01 and (NP-15) < = 0 then TNPR = 0.001

Footwall Hanging Wall

Samples below the lineare net acid generating

(Adj TNPR < 2.0)

Note: the ore zone is depicted here aszero width, but has an apparent

thickness of 4-35 m according to Western Keltic Mines in the

drillholes used here.

These three samples with <0.12%S werefrom the adit, and their Adj TNPR values

would not rise above 2.0 unlessUnavailable NP was below 3 kg/t.


Strong ARDModerate ARDWeak ARDNear neutral,High Leaching

ARD Rock Units

pH~7

<3

pH~7

<3

pH~7

<3

pH~7

<3

Near neutral,Low leaching


Segregation of ARD RockUnits during Mining

La mina

Deposito de lastres

Año 1 y 2

Año 3 y 4Año 5 y 6

Año 7 y 8

Año 9 y 10

Años

pH

7

3

0 1042 6 8

5



ARD Rock UnitsNear neutral,Low leaching

No Segregation of ARD RockUnits during Mining

ARD Rock Units Occur inDistinct Layers

¿Meses, años o décadas?

pH

7

3

La mina

Deposito de lastres




No Segregation of ARD RockUnits during Mining

ARD Rock Units Do Not Occur inDistinct Layers

Months, Years, or Decades?

All ARD Rock TypesMixed Together

pH

~7

<3

Segregated ARD Rock Types

pH~7

<3

pH~7

<3

pH~7

<3

pH~7

<3




On-SiteMonitoring

Data

Acid-BaseAccounting




FieldKinetic Tests











Ref. B0001, B0002, A1957

K-feldspar2 Plagioclase

5

Quartz50

Sericite40

Biotite1

Epidote1.5

Granite - Petrographics (ABA Sulphide = 0.02%S, NP = 5 kg/t)

Plagioclase7.1

Quartz58.7

Kaolinite0.8

Muscovite33.1

Calcite0.3

Granite - Rietveld XRD

As part of the “Wheel”, mineralogy identifies the major and minor minerals in a sample using optical, microscopic, laser, mass-spectroscopy, and x-ray techniques. Trace minerals, typically less than 0.1%, cannot typically be identified this way.

Wheel Approach – Mineralogy

• The “Holy Grail” Premise: Minerals create drainage chemistry. So, if we know mineralogy accurately, we can predict aqueous concentrations accurately.

• This is incorrect. Minerals contain site-specific impurities and non-idealities like solid solutions. These affect the site-specific composition, reaction rates, and effects on water chemistry.

• Question: Can we delineate mineralogy of a sample accurately using “everyday” techniques?


Quartz20

Plagioclase15

Sericite42

Chlorite5

Carbonate8

Sub-opaque10

Mudstone/Siltstone - Petrographics (ABA Sulphide = 0.25%S, NP = 108 kg/t)

Quartz45.6

Muscovite26.4

Kaolinite10.7

Pyrite0.3

Ankerite-Dolomite12.8

Siderite4.2

Mudstone/Siltstone - Rietveld XRD

In this sedimentary sample, visual observations indicated 15% plagioclase, whereas Rietveld XRD reported no feldspar.

Rietveld detected the pyrite at a low level, whereas visually it was not reported.

The NP of 10.8 wt-% was similar to the visual 8 vol-% and the Rietveld sum of 17.0 vol-%, but the type of carbonate was not characterized visually.

VISUAL XRD


• Some reasons for mineralogical discrepancies among methods:

• Different splits are analyzed. XRD is based on small, pulverized samples, whereas petrographics require non-pulverized, larger samples.

• XRD cannot detected nearly/fully amorphous phases, like some iron and aluminum oxyhydroxides. These can form large portions of some samples associated with ARD. This lack of detection by XRD will cause the percentages of detected minerals by Rietveld to be higher.

• Mineral names and ideal formulae can vary with country and laboratory, so two different names for virtually the same compound may appear.


• Some reasons for mineralogical discrepancies among methods:

• Ideal formulae are just that, ideal. In reality, impurities andelemental substitutions in minerals create broad spectrums and solid-solution series. Selecting the right mineral name for a naturally occurring “mixture” can be difficult. In this real-world situation, peak matching used by XRD will not be reliable when using ideal peaks in a database.

• Detection limits are variable, but probably often between 0.1 and 1 vol-%. Petrographics has the option of including “trace” or “rare” if requested to identify a few particles that may be encountered by chance during observations. Rietveld detection limits are sensitive to the grain size and spatial orientation of grains.


On-SiteMonitoring

Data

Acid-BaseAccounting




FieldKinetic Tests











Ref. B0001, B0002, A1957

Wheel Approach – Soluble/Retention Tests

• The objectives of this testwork are to:• characterize the short-term leaching of soluble elements from fresh samples

• characterize the leaching of soluble elements accumulated or retained on weathered and oxidized samples

• To interpret the results of soluble/retention tests correctly, it is important to know:• the length of time since the sample was last rinsed well by water or rainfall

• the solid:liquid ratio used in the testing (use several ratios to estimate equilibrium levels)

• the length of contact time between the solids and water (use longer times to estimate equilibrium levels

• The types of tests providing this information are:• the early weeks of humidity-cell testing (another test under the Wheel,

discussed later in this presentation)• “shake flasks” or similar sealed containers with water and solids that are

rolled or tumbled for a day or more

On-SiteMonitoring

Data

Acid-BaseAccounting




FieldKinetic Tests











Ref. A1957, B0001, B0002, CS0010

• The hydrogen peroxide method was originally developed to measure only sulphide in a sample. Section 3.2.11 of Sobek et al. (1978) lists the technique. It required the removal of all neutralizing minerals and leachable sulphate prior to testing, so that sulphide could be measured through a titration with base.

• This method was later changed so that no neutralizing minerals or leachable sulphate had to be removed, and the remainder of the method remained basically intact. The rationale was:

• If the addition of hydrogen peroxide created acidic conditions, then that sample would generate net acidity some day, and the pH from the test was called the “NAG pH” (NAG pH < 4.5)

• If acidic conditions developed, then the titration with base (part of the original procedure) would indicate the strength of the net acid generation and this was called the “NAG capacity” (NAG > 0 kg H2SO4/t)

• If the addition of hydrogen peroxide did not create acidic conditions, then that sample would never generate net acidity (NAG pH ≥ 4.5 & NAG = 0).

Wheel Approach – NAG Testing

Ref. A1957, B0001, B0002, CS0010

• As with all methods, there are weaknesses. For example,• Hydrogen peroxide is unstable in the presence of ferrous iron, and

pyrite and siderite are about one-half ferrous iron. Although ferrous iron will be oxidized by hydrogen peroxide, which is a desired effect, the iron can also apparently act as a catalyst for degrading theperoxide. This has apparently led to the development of the “Sequential NAG test”.

• Not all acid-generating and acid-neutralizing minerals may react within several hours of NAG testing. This has led to the development of the “Kinetic NAG test” and subsequent columns.

• Hydrogen peroxide solutions are often sold at acidic conditions (pH < 4.5), so the simple addition of the hydrogen peroxide to a sample can lead to acidic NAG pH.

• The NAG test does not provide any information on the neutralizing capacity of a sample, or how much external acid addition it can withstand. This led to the Acid Buffering Characteristic Curve (ABCC) and the pre-test requirement of NAPP (basic ABA) results.

• Due to the fast reactions and metal leaching, sulphide minerals can become coated with precipitants and thus not react fully.


Ref. A1957, B0001, B0002, CS0010

• As a example of using the Wheel approach, a minesite sample was analyzed by NAG testing. The NAG results showed that the NAG capacity was much less than that expected from NAPP (basic ABA) testing based on total sulphur.

• So the mineralogy of the sample was evaluated. This showed that about half the sulphide minerals were non-acid-generating (galena and sphalerite under certain conditions). Based on the Wheel, we would say that only half the measured sulphide should be included in NNP and NPR values for predictions.

• This showed that1. both methods could provide questionable results until mineralogy

was done, and2. thus proved the value of the integrated Wheel approach


• Today, NAG testing can involve elaborate and time-consuming procedures, including the following.

• The Single Addition NAG Test: For example, 250 mL of 15% H2O2 is added to 2 g of sample, allowed to react overnight, then gently heated to accelerate any remaining oxidation, then boiled to decompose any remaining H2O2. The NAG pH and NAG capacity are then measured after the solution cools. NAG capacities can be defined at pH 4.5 and 7.0. This is appropriate only for samples with less than ~1%S.

• The Sequential NAG Test: For samples with elevated sulphide or catalytic destruction of H2O2, the Single Addition NAG Test is basically repeated until there is no more oxidation. The NAG capacity is the sum of each test’s NAG capacity.


Ref. A1957, B0001, B0002, CS0010

• The Kinetic NAG Test: The pH, temperature, and electrical conductivity are recorded during a Single Addition NAG Test. The “pH trend gives an estimate of relative reactivity and may be related to prediction of lag times and oxidation rates similar to those measured in leach columns”. “Qualitative” lag times to net acidity under on-site can be estimated.

• The Acid Buffering Characteristic Curve (ABCC): The ABCC test involves slow titration of a sample with acid while continuously monitoring pH. This data will provide an indication of the portions of Available and Unavailable NP.


Ref. A1957, B0001, B0002, CS0010

Non Acid Forming (NAF)= Net Acid Neutralizing Uncertain

UncertainPotentially Acid Forming (PAF)

= Net Acid Generating

NAG pH = 4.5

NA

PP

= 0

NA

G p

H

1.0

10.0

4.5

NAPP (kg H2SO4/t)-1000 +1000

Wheel Approach – NAG Testing“Barren” under NAG Testing is defined as Total %S < 0.1 and NP < 5 kg/t. WARNING: Such

samples can sometimes generate ARD and leach metals based on kinetic tests and case studies

For example, at this site, NAG testing indicated 56% were net acid generating and 4% uncertain, which agreed well with ABA that indicated 57% and 1%, respectively.


The first ABCC curve shows that available NP was 5 kg/t, whereas measured NP was 11 kg/t. Therefore, Unavailable NP was 6 kg/t, in agreement with ABA-based UNP of ~10 kg/t.

The second ABCC curve shows that available NP was 4 kg/t greater than measured NP, indicating there was additional NP. This was probably slow reacting NP, that was not detected by ABA.


The first Kinetic NAG test shows a low-NP, low-sulphur sample producing a NAG pH below 4.5 in roughly 80 minutes.

This Kinetic NAG test shows a peak in temperature due to the elevated sulphur levels. The relatively low NP was depleted within ~ 40 minutes.


0.001 0.01 0.1 1 10 100

TNPR

0

2

4

6

8

NA

G p

H

A Sediments

B Sediments

C Sediments

Phaneritic Igneous

Aphanitic Igneous

Net Acid Neutralizing

Net Acid Generating

Disagreement

Disagreement

At this site, NAG pH from the NAG test and Net Potential Ratio (NPR) from ABA agreed well in their predictions.

The samples marked “Disagreement” required further testing to explain the discrepancies.


Ref. A1957, B0001, B0002, CS0010

On-SiteMonitoring

Data

Acid-BaseAccounting




FieldKinetic Tests











Ref. B0001, B0002, A1957

• There are two basic types of humidity cells:• Traditional “well-rinsed” humidity cells• Recent “trickle-leach” humidity cells

• Well-rinsed humidity cells have been in use for at least 50 years around the world. The following presentation on cells applies only to well-rinsed cells.

• Trickle-leach cells are similar in objectives to “leach columns”, which are discussed next after humidity cells.

Wheel Approach – Lab Kinetic Tests – Humidity Cells

• The basic objective of (well-rinsed) humidity cells is to wash a sample regularly, usually weekly, with excess water. Gentle stirring during rinsing improves rinsing of all particle surfaces.

• For at least the first six months, every cycle (week) of rinse water should be analyzed for proper accuracy. Reducing analyses to every second week or less frequently can then be determined after six months.


Ref. B0001, B0002, A1957

• The detailed objectives of humidity cells are:• Virtually all weekly reaction products are rinsed each week.

Analyses of the weekly rinse waters, combined with water volume recovered, provide bulk reaction and leaching rates for many elements and parameters. For example, mg of copper/kg of sample/week.

• Excess rinse water increases the probability that kinetic conditions apply and that maximum equilibrium levels are not reached in the weekly rinse water.

• However, in some cells, the Scale Transition can be surpassed and equilibrium conditions apply. For example, this may happen during the initial weeks of rinsing any very soluble, previously retained reaction products. When this does happen, the equilibrium levels cannot be used as rates, because they underestimate rates by ignoring secondary minerals, etc.


• The detailed objectives of humidity cells are:

• The analyses of weekly rinse waters are not intended to be direct predictions of drainage chemistry in mg/L, but are intentionally diluted.

• They become direct predictions only when the Scale Transition is surpassed and equilibrium is reached. Predictions of larger-scale, equilibrium chemistry can require larger laboratory leach columns and on-site larger-scale kinetic tests.



AIR

OUTRINSE

WATER

IN

PLEXIGLASS

CONTAINER

DRY AIR &

MOIST AIR IN

MINE-

MATERIAL

SAMPLE

LEACHATE

OUT

PERFORATED

SUPPORT

The typical weekly operation of a humidity cell is:1) three days of dry air pumped through / over a sample2) three days of moist air pumped through / over a sample3) one day for rinse-water addition, gentle stirring, and rinse-water draining.

Analysis of the rinse water, combined with the volume of water recovered, provides bulk reaction rates in mg/kg/wk.Ref. B0001, B0002, A1957

• Production Rate (mg of parameter / kg of sample / week) =

• Measured rinse concentration (mg/L) *• Volume of rinse water recovered (L) /• [wt. of sample (kg) * No. of elapsed weeks

(wks)]


Ref. B0001, B0002, A1957

0 10 20 30 40 50 60 70 80 90 100 110 120

2

3

4

5

6

7

8

9

10

MR 97-12TH 98-09

Cycle (Week)


The following slides show some examples of humidity-cell results.

This one shows that one cell became acidic around Week 30. This a “lag time” of 30 weeks.

Humidity cells provide rates of metal leaching through time.

Sometimes the rates increase with time, sometimes decrease, and sometimes remain about the same.

0 2 4 6 8Week

0.001

0.01

0.1

1

10

Sb

(mg/

L)Wheel Approach – Lab Kinetic Tests – Humidity Cells

This well-rinsed humidity cell was sampled every week for 5.7 years. Acid-base accounting (ABA) predicted the sample would eventually become acidic, and it did so after 1.5 years, causing the metal leaching rate of copper to increase sharply. Kinetic tests do not always have to operate until they become acidic, because the time can often be calculated from earlier weeks of testing.

0 100 200 300Number of Weeks

2

4

6

8

10

Eff

luen

t p

H

0.001

0.01

0.1

1

10

100

1000

Pro

du

ctio

n R

ate

(mg

/kg

/wk)

Effluent pHSulphate Production RateCopper Production Rate


0 100 200 300 400 500Number of Weeks

4

6

8

10

12

Eff

luen

t p

H

0.0001

0.001

0.01

0.1

1

10

100

1000

Pro

du

ctio

n R

ate

(mg

/kg

/wk)

Effluent pHSulphate Production RateCopper Production Rate

This cell operated for about 9 years and did not show any major changes in chemistry. Rates after the first year could be used to predict future rates that would be accurate for at least 9 years into the future. This is not always the case, as explained below.


There are other samples which appear to be generally steady by the end of the first year. However, after a year or more, a rate like molybdenum leaching (below) will suddenly increase. There are no proven explanations for trends like this.

0 50 100 150 200 250Number of Weeks

2

4

6

8

10

Eff

luen

t p

H

0.001

0.01

0.1

1

10

100

1000

Pro

du

ctio

n R

ate

(mg

/kg

/wk)

Effluent pHSulphate Production RateMolybdenum Production Rate


0 40 80 120 160Week

0.001

0.01

0.1

1

10

100

1000

0

2

4

6

8

Cu RateRinse pHSO4 Rate

There are other samples which appear to be generally steady by the end of the first year. However, after two years or more, a rate like copper leaching (below) will suddenly increase. There are no proven explanations for trends like this.


Cells showed that arsenic leaching at this minesite was not influenced by pH (below left), but by the rate of sulphide oxidation (right). The reason for this was the arsenic occurred in sulphide minerals, based on mineralogy and total-element contents as part of the “Wheel”.

3 4 5 6 7 8Average pH

0.01

0.1

1

10

Ave

rage

As

Leac

hing

Rat

e (m

g/kg

/wk)

Acma/A4A Intrusive

Acma/A4A Sedimentary

Lewis Intrusive

Lewis Sedimentary

0.1 1 10 100 1000Average SO4 Rate (mg/kg/wk)

0.01

0.1

1

10

Ave

rage

As

Rat

e (m

g/kg

/wk)


• After 80 weeks of cell testing for this site, only three of the nine cells expected eventually to generate net acidity did so.

• The three cells became acidic within a few weeks of testing, and latest pH values were around 2.4-2.7.

• For the near-neutral cells, recent pH values were around 7.2 to 8.2, with one lower cell around pH 6.7.


0 20 40 60 80 100Week

2

4

6

8

10

Wee

kly

pH

A IntrusiveA GreywackeA SedimentaryL IntrusiveL GreywackeL Sedimentary


After any initial, soluble sulphate is rinsed from a cell, sulphate-production rates represent the rates of sulphide oxidation and total-acid generation. For this site, the acidic cells oxidized at rates roughly 10-100 times greater than the rates in the near-neutral cells (lower left).

Compared with other minesites, sulphate-production rates were not unusual, but typical to relatively low (lower right).

0.01 0.1 1 10Initial Solid-Phase Sulphide (%S)

0.1

1

10

100

1000

Late

-Ave

rage

Sul

phat

eP

rodu

ctio

nR

ate

(mg

SO

4/kg

/wk)

2.63

8.15

7.8

7.818.04

6.64

8.15

2.39

8.13

7.97

7.9

8.26

7.94

A IntrusiveA GreywackeA SedimentaryL IntrusiveL GreywackeL Sedimentary

2.69

7.2

7.96

Last-five-week-average pHshown next to datapoint

One-half detection limit used forany value below detection

Three acidic cells

0 2 4 6 8 10Average pH

0.01

0.1

1

10

100

1000

10000

Rat

eof

Sul

phat

eP

rodu

ctio

n( m

gS

O4/

kgof

sam

ple/

wee

k)

Cells to Week 82

Hig

hV

ery

Hig

hM

ode

r ate

L ow

Ve

ryL

ow

International Kinetic Database543 cells from 72 minesites worldwide

• Some observations from sites that operated large numbers of cells for long periods of time:

• 10 cells that operated for three to seven years indicated that there was roughly a 50% chance that the oxidation rate of a sample will stabilize geochemically (< factor of two fluctuations) within the first year. There were no pre-test or early indications of which cells would stabilize.

• Seven batches of cells, with at least 12 cells each, indicated that at least 12 cells were sufficient to show whether oxidationrates were clustering around certain ranges. However, the batches indicated more than 40 cells would be needed to delineate a reliable statistical distribution such as lognormal or normal.


Ref. M0017

• Some observations from sites that operated large numbers of cells for long periods of time:

• Carbonate Molar Ratio (molar rate of NP consumption divided by sulphate production) typically remained between 1.0 and 2.0, in near-neutral cells, even when rates fluctuate significantly. This supports the typical NPR criteria for acid-base accounting between 1.0 and 2.0.

• The CMR typically falls below 1.0 just before and during the onset of net acidity.

• If the sulphate rate falls below 5-30 mg/kg/wk, the CMR often rises to values well above 2.0, indicating physical factors likeflow rate can affect or dominate the geochemical predictions of acid drainage.


Ref. M0017

VALIDACIÓN GEOLÓGICA

• Tipo de mineralización y su ocurrencia• Volumen y tipo de arcillas presentes• Volumen y tipo de carbonatos presentes• Volumen y tipo de sulfatos• Volumen y tipo de Oxi-hidróxidos

PETROCALCOGRAFÍA

• 200 Muestras de mano

RECUENTO PETROCALCOGRÁFICO

• 200 recuentos de cabeza• 200 recuentos de ripios TCH• 200 recuentos de ripios TCH Mod• 200 recuentos de ripios TCF


Caracterización Geometalurgica de Detalle

Selección y mapeo de 200 muestras para pruebas cinéticas:

•Test Celda Humeda TCH•Test Celda Húmeda Modificada TCH Mod•Test Celda Forzada TCF

Estudio de Extracción Secuencial a cabezas y ripios

Estudios de extracción de Cu (QLT)


TEST CINÉTICOS

Test de Celda Húmeda (A)• 21 Ciclos de 14 días a T°Ambiente•3 días aire seco•3 días aire húmedo•3 días aire seco•4 días aire húmedo•1 día de inundación con agua destilada

Test Celda Húmeda Modificada (B)•21 Ciclos de 14 días a 40°C•13 días aire húmedo•1 día de inundación con agua destilada

Test de Celda Forzada (C)•21 Ciclos de 7 días a 40°C•6 días aire húmedo•1 día de inundación con H2SO4 + Férrico


TEST CINÉTICOS

Las soluciones obtenidas de cada ciclo serán caracterizadas por la siguiente batería química:

• pH• Acidez – Alcalinidad• Conductividad• Sulfatos• CuT• As• Mo• Fe Total• Ferroso• ICP Óptico de 27 elementos


Resultados Preliminares


pH A

0123456789

10

1 2 3 4 5 6 7 8 9 1011121314

Ciclos

pH

pH B

0123456789

10

1 2 3 4 5 6 7 8 9 10 11 12 13 14

Ciclos

pH

pH C

1.02.03.04.05.06.07.08.09.0

10.0

1 3 5 7 9 11 13 15 17 19 21

Ciclos

pH

Sample

PerforatedSupport

WaterOut

PlexiglassTube

SamplingReservoir

Reservoir forFeed Water

Wheel Approach – Lab Kinetic Tests – Leach Columns

Another type of laboratory kinetic test is a “leach column”. Water can be added to the top (or the bottom for saturation) of a column in many ways. So there is no one way to operate a leach column.

Normally, water is dripped or occasionally poured on the top of the column sample. The water then flows and “trickles” downward. This water contacts some but not all particle surfaces. The water then drains out the bottom. This is one major way columns differ from well-rinsed humidity cells, but is similar to trickle-leach humidity cells.

Non-RecirculatingLeach Column

Ref. B0001, B0002, A1957

Sample

PerforatedSupport

WaterOut

PlexiglassTube

PermanentReservoir (forRecirculating

Water)

TemporaryReservoir (forInitial Water;one time only)


The objective is for the rinse water NOT to contact all particle surfaces (unless fully saturated) and NOT to rinse off all weekly reaction particles. Instead, some particles continue to accumulate reaction products over the test period.

The solid:liquid ratio is much greater than for well-rinsed cells, so there is a greater potential that the Scale Transition will be exceed. As a result, aqueous concentrations in mg/L can reflect full-scale, maximum equilibrium concentrations. In this way, these columns can provide predictions of full-scale concentrations.

RecirculatingLeach Column

Ref. B0001, B0002, A1957

This is an example of laboratory leach columns.

Each column is almost 3 m high.

Water within the columns can be drawn out at water-sampling ports along the sides of the columns.


Wheel Approach – Lab Kinetic Tests – Leach Columns• Leach-column tests can vary with:

• variability in the sample, such as layers (left), resulting in averaged or altered drainage chemistry

• degree of pre-test weathering of sample

• particle size and mass

• length and diameter of column

• direction of flow and height of water table (e.g., saturated column with water forced into the bottom)

• internal conditions like temperature and oxygen

• frequency of monitoring and number of internal monitoring points

On-SiteMonitoring

Data

Acid-BaseAccounting




FieldKinetic Tests











Ref. B0001, B0002, A1957

mañana,Día 2

• There are many types and forms of larger-scale on-site kinetic tests. As photographs on the following slides show, they have many names, like “leach pads”, “barrels”, “cubes”, and “cribs”.

• Larger-scale on-site kinetic tests should be designed and operated with specific objectives in mind.

Wheel Approach – Field Kinetic Tests

Ref. B0001, B0002, A1957


These are the two types of larger-scale on-site kinetic tests

that I often use:barrels (to the left) and

cubes (below).

The major objective to have greater height than lateral area,

with the intent to exceed the Scale Transition.


At one site, these leach pads provide unexpected, anomalously low

concentrations in the drainage. The rock was moved into barrels, then higher, typical concentrations were

obtained.


There are also various types of “leach pads” elevated above ground.

At one site, the on-site leach pads were draining ARD (pH ~3) with lots of rusty iron-stained ARD. One day

the mining company called, very excited. The iron staining and rust

had disappeared from the leach pads. This must mean the ARD has

stopped – after only a few years!

The actual explanation was that the ARD draining from the pads had

become much worse (pH < 2). This stronger acidity dissolved the solid-

phase iron and carried it away.

Some sites have other on-site kinetic tests that contain hundreds to thousands of tonnes. In effect, full-scale minesite components with million to billion of tonnes are also field kinetic “tests”.


There are “cribs” that can hold 20 tonnes or more.


For one project, we used an airstrip at the site as an on-site kinetic test, monitoring its drainage for upscaled predictions.

Large-scale containers for heap-leach testwork can also be used for field kinetic testing.

Below the Scale Transition, kinetic conditions apply.

Above the Scale Transition, equilibrium conditions apply. This does not mean reactions stop, but that secondary-mineral precipitation and accumulation increase. Aqueous concentrations stabilize around average values.

In my work, I find equilibrium conditions exist at full scale for most minesites (not all) for most elements (not all). Full-scale equilibrium is discussed here, while full-scale kinetics are discussed later.Increasing Scale, Weight, Volume, Time, Solid:Liquid Ratio,

Reaction Rate, Residence Time, or Distance Along Flowpath

Incr

easi

ng A

queo

us C

once

ntra

tion

(mg/

L) Maximum “equilibrium” concentrations apply in this part of the curve,caused by thermodynamics, metastability, emergence, etc.

Kinetic rates apply in this part of the curve

ScaleTransition

Components of Scale:- grain: resolution or minimum

homogeneous unit- extent: study area or time duration

- coverage: sampling density- spacing: sampling interval

At what scale, weight, time, ratio, etc., is the Scale Transition met for a particular minesite component and element?

Scaling of Minesite-Drainage Chemistry

Ref. CS26

Full-Scale Drainage-Chemistry EquilibriumTo identify equilibrium in full-scale minesite-drainage chemistry, annual statistics and histograms are helpful. Histograms (below) of thousands of pH measurements, over years and decades of monitoring, from all components at a minesite, show a bimodal distribution. The near-neutral and acidic pH “cluster” together at certain values at a minesite, but the “preferred” pH values vary from minesite to minesite. Ref. CS033, CS0034

This minesite has more than 5000 analyses over ~30 years, including pit, waste rock, and

tailings. Dissolved copper correlated well with pH, but in

three pH-dependent segments.

0 4 8 12Lab/Field pH

0.0001

0.001

0.01

0.1

1

10

100

1000

Dis

solv

ed C

oppe

r (m

g/L)

Tailings and Related DamsRock Dumps and RelatedSurficial Pit LakeGroundwater

If data was reported as < detection limithalf the detection limit is shown.

Readily apparent errors in datahave been corrected or deleted.

When lab data was available it isshown, otherewise, field was used.

Two erroneousdatapoints

ignored

Best-Fit Equation for 3.0=>pH =>5.5, and Cu-D > 1 mg/L: log(Cu-D) = -0.48982*pH + 3.32581 Log standard deviation = 0.43962 Count = 499 Sum of prediction errors = -1.0E-06

Best-Fit Equation for pH <3.0, and Cu-D > 10 mg/L: log(Cu-D) = -1.17265*pH + 5.37432 Log standard deviation = 0.37011 Count = 137 Sum of prediction errors = +1.0E-06

Best-Fit Equation for pH>5.5: log(Cu-D) = -1.04518*pH + 6.38030 Log standard deviation = 0.81956 Count = 4757 Sum of prediction errors = -8.9E-13

-2 -1.8 -1.6 -1.4 -1.2 -1 -0.8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1Measured Minus Predicted Values

Above (+) or Below (-) the Best-Fit Line

0

20

40

60

Num

ber

of V

alue

s

Best-Fit Equation for pH <3.0, ignoring Cu-D < 10 mg/L: log(Cu-D) = -1.17265*pH + 5.37432 Log standard deviation = 0.37011 Count = 137 Sum of prediction errors = +1.0E-06

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2Measured Minus Predicted Values


0

40

80

120

Num

ber

of V

alue

s

Best-Fit Equation for 3.0=>pH =>5.5, and Cu-D > 1 mg/L: log(Cu-D) = -0.48982*pH + 3.32581 Log standard deviation = 0.43962 Count = 499 Sum of prediction errors = -1.0E-06

-4 -3 -2 -1 0 1 2 3 4Measured Minus Predicted Values


0

400

800

1200

Num

ber

of V

alue

s

Best-Fit Equation for pH>5.5: log(Cu-D) = -1.04518*pH + 6.38030 Log standard deviation = 0.81956 Count = 4757 Sum of prediction errors = -8.9E-13

Full-Scale Drainage-Chemistry Equilibrium

Full-Scale Drainage-Chemistry Equilibrium

1 10 100 1000 10000 100000Dissolved/Total Sulphate (mg/L)

10

100

1000

10000

Har

dnes

s (m

g/L)

Tailings and Related DamsRock Dumps and RelatedSurficial Pit LakeGroundwater

Best-Fit Equation for Sulphate > 100 mg/L: log(Hardness) = +0.98380*log(SO4) - 0.00500026 Log standard deviation = 0.176387 Count = 2482 Sum of prediction errors = +1.7E-13

If data was reported as < detection limithalf the detection limit is shown.

Readily apparent errors in datahave been corrected or deleted.

When lab data was available it isshown, otherewise, field was used.

-2 -1.6 -1.2 -0.8 -0.4 0 0.4 0.8 1.2 1.6 2Measured Minus Predicted Values


0

400

800

1200

Num

ber

of V

alue

s

Best-Fit Equation for Sulphate > 100 mg/L: log(Hardness) = +0.98380*log(SO4) - 0.00500026 Log standard deviation = 0.176387 Count = 2482 Sum of prediction errors = +1.7E-13

Another example showing a best-fit equation, but with sulphate rather than pH, and associated standard deviation.

Ref. CS0033, CS0034, M0008, M00101, M0012, M0018, M0032, M0053, M0058, M0061, M0066

• Each proposed, operating, and closed minesite may have different sets of objectives for waste characterization. These objectives often focus on the waters draining from a minesite and its components, like mine walls, waste rock, low-grade ore, and tailings.

• Each proposed, operating, and closed minesite may identify and collect samples in different ways. The sizes, numbers, and types of samples can differ, depending on objectives.

• There is no one approach to sampling - it is unique to each minesite and each objective.

• The easiest way to explain the laboratory and on-site field tests is by using the analogy of a “wheel”. I call this the “Wheel Approach” for predicting, scaling, and understanding mine-waste geochemistry and minesite-drainage chemistry.

CONCLUSION

On-SiteMonitoring

Data

Acid-BaseAccounting




FieldKinetic Tests










Wheel Approach for Minesite-Drainage ChemistryMost of these tests were described and illustrated. These were primarily smaller-scale tests. The larger-scale on-site field kinetic tests and on-site monitoring data will be discussed tomorrow.

Ref. B0001, B0002, A1957

THE END

sampling analysis testing mine wastes geochemical predictions risk assessment kmorin

Documents