BSc dissertation: Environmental Assessment of soil quality at the former Tomnadashan copper mine.

8/22/2019 BSc dissertation: Environmental Assessment of soil quality at the former Tomnadashan copper mine.

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Environmental Assessment of Soil Quality at the former Tomnadashan Copper Mine

Copyright 2013 of LabSearch, a working title of Dr Malcolm Sutherland

BSc (Hons) Laboratory dissertation:

ENVIRONMENTAL ASSESSMENT OF SOIL QUALITY AT

THE FORMER TOMNADASHAN COPPER MINE

By Malcolm Alexander Sutherland(matriculation no. 9805423)

This report was submitted in partial fulfilment of the BSc. (Hons) degree in Environmental

BioGeoChemistry, University of Glasgow, Monday 8th April 2002

REVISED IN JUNE 2013 (figures and appendices have been scanned)


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CONTENTS

ABBREVIATIONS page 3

SUMMARY page 4

1: INTRODUCTION pages 5 - 7

2: MATERIALS and METHODS pages 8 - 24

2.1 Field visit to Tomnadashan pages 8 - 11

2.2 Soil properties and composition pages 11 - 13

2.3 Total copper extraction pages 14 - 16

2.4 Analysis of copper fractions pages 17 - 20

2.5 Mineralogical analysis pages 21 - 24

Graphs 1 through 14 pages 25 - 38

3: RESULTS and DISCUSSION pages 39 - 60

3.1 Experimental Data pages 39 - 45

3.2 Statistical treatment of data pages 45 - 56

3.3 Discussion pages 56 - 60

4: CONCLUSIONS and RECOMMENDATIONS pages 61, 62

ACKNOWLEDGEMENTS page 63

REFERENCES pages 64, 65

APPENDICES pages 66 - 84

Appendix 1 page 66

Appendix 2 pages 67 - 69

Appendices 3a - 3d pages 70, 71

Appendix 4 page 72

Appendix 5 pages 73 - 80

Appendices 6a - 6b pages 81 - 64


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ABBREVIATIONS

% Total Cu The percentage of total copper being plant-available (Graph 6)

Organic-bound The copper fraction obtained using the H2O2-ammonium acetate extraction

procedure

Oxide-bound The copper fraction obtained using the hydroxyl-ammonium chloride

Extractant

Exchangeable The copper fraction obtained using the acetic acid extractant

Series 1/Step1 Exchangable copper

Step 2/Series 2 Oxide-bound copper

Step 3/Series 3 Organically bound copper

Residual Remaining copper extracted using aqua regia

EDTA Cu Copper extracted using this extractant

%edta (see % Total Cu)

EDTA for BCR The relevant data of EDTA-extractable copper for the (BCR) samples used inthe sequential/separate extraction methods

%step1 The percentage of the sum of all 3 extracted copper fractions which are

exchangeable

%step2 The percentage, of the sum of all 3 labile copper fractions, being held by

oxides

%step3 The percentage, of the sum of all 3 labile copper tractions, being held by

organic matter

%EDTA BC (see %Total Cu)

LOI for BCR Loss-on-Ignition values for the samples used in the BCR separate/sequential

extraction methods


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SUMMARY

A laboratory project was carried out to analyse the impact of copper mining at

Tomnadashan. This was an initial environmental assessment, which involved collecting soilsamples from the abandoned site and some exposed mine waste. The primary objective was

to study the levels and forms of copper which persisted in these samples, and mainly to

assess its potential toxicity and availability. 2 transects were surveyed: Transect 1 (crossing

in front of the mine), and Transect 2 (located where a smelter is said to have existed). Some

stream sediment was also sampled.

Total; plant-available (extracted using EDTA); exchangeable; oxide-bound; organically

complexed; and, mineral-bound copper was analysed. Copper levels were compared with

organic matter (determined by loss on ignition), soil pH, and levels of 4 other heavy metals

(Mo, Ni, Pb, Zn) which also occurred within the copper porphyry at Tomnadashan.

Levels of total copper, even in natural peaty soils, are generally above 100ppm, which partly

reflected the unique chemistry of the underlying geology. However, at one end of Transect

2, with the river sediment and 2 selected mine waste soils, levels of copper far exceed

1000mg/kg. However, this trend was not seen with plant-available copper, nor with the

other 4 heavy metals analysed. Levels of plant-available copper along Transect 1 were not

significant (usually 20 - 60mg/kg), nor were they affected by the local mine waste. Plant-

available copper occurred at around 200mg/kg at the mine waste, and concentrations

ascended from ~30mg/kg to that level along Transect 2.

Nevertheless, the levels of potentially plant-available copper (exchangeable, or bound to

oxides or organic matter) ranged between 100 and 250mg/kg along Trajectory 1, and

occurred from 100 to over 500mg/kg along Trajectory 2. These levels were as much as over

3000mg/kg at the mine waste. The river sediment was also heavily polluted with copper,

with potentially plant-available copper levels exceeding 2500mg/kg.

In general, most of the Tomnadashan soils which were analysed contained moderate levels

of copper, both in its total, and in its potentially phytotoxic forms. In localised areas, its

potential phytotoxicity may be a cause for concern, and further investigation is

recommended, particularly into where else this pattern may be occurring.


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1: INTRODUCTION

1.1: Location

Tomnadashan is located halfway along the south bank of Loch Tay, Perthshire (east of

Ardeonaig (N56: 30:07; W4: 09:15). The area is generally uninhabited, with rough grazing

being the only land use, and access to the former mining site is only via a narrow minor road

which follows this side of the loch. Geologically, the site is much more significant, with

enriched veins and disseminations of copper and pyritic ore, along with other heavy metals

such as molybdenum.

1.2: Mining Activity at Tomnadashan

During the early 19th

century, the awareness of this porphyry at Tomnadashan encouraged

initial mining tests to be carried out. It is said that a smelter was also raised slightly further

downhill. Lord Brealdabane, who was ambitious in his aim to convert this into a significant

copper-producing business, tried in vain over a few decades to make this become a

profitable site, in one way or another. Copper ore extraction and treatment was initiated,

but without success. A smelter was raised, and in the end, some copper was actually sold.

Allegedly, phosphate was extracted and used for fertiliser production. Sulphur production

was another practice which also failed, using the local pyrite source.

Today, only a set of derelict cottages, and a small incision into the bedrock with an equallyinsignificant mine waste tip marks this historic location. The smelter downhill no longer

exists, and, apart from a raised ledge structure seen up the slope, the whereabouts of each

building and structure depicted in the 1861 O.S. map (Appendix 1) are questionable

(Tomnadashan - a Re-examination; see References).

1.3: Environmental Implications of Mine Waste and Smelters

Typical concentrations of copper in soils above granitic parent material are usually below

20ppm (White, 1998). However, as Tomnadashan is located at a copper porphyry, thenatural copper levels are likely to exceed this margin.

The concern for, and investigation of these are firmly established today. Acid mine drainage

is a common issue associated with mine waste (especially "slag" heaps), uniting both coal

mining with non-ferrous extraction. A clue to this lies in the fact that copper porphyries,

although highly enriched in iron, cannot serve as an iron ore resource due to the Fe being

found as pyrite (FeS). The sulphur presents a potential lexicological hazard to both soils and

vegetation alike due to its oxidation under weathering (Barnes, 1988; Kontopoulos et al,

1995; Radojevic and Bashkin, 1999):

2FeS2 + 7O2 + 2H2O 4SO42- + 2Fe2+ + 4H+


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The resulting acidification is both deleterious, especially to aquatic life, and any subsequent

chemical reactions (e.g. the reaction with metal sulphides) will degrade both soil and water

quality.

The visible mine waste at Tomnadashan is not copious- However, according to the old map

(Appendix 1), the extent of mine waste seems to have been far more extensive, compared

to the few square metres of un-vegetated waste seen today.

Smelting, particularly of phosphate, is (and was) performed using sulphuric acid digestion,

and thus, a local source of S is required (making pyrite a useful commodity to this end)

(Barnes, 1988). During the mid-19th

century, phosphate was becoming an important

fertiliser (Tomnadashan - a Re-examination, 2000). Smelters, especially older designs,

release particulates which are deposited onto the soil in their vicinity, and thus metal

concentrations may become enriched in soils, with proximity to the site (Karczewska, 1996).

Environmental standards not only apply to the condition of former mine waste heaps, but tothe levels of metals being concentrated and dispersed into the surrounding soil and

vegetation. The Environmental Quality Criteria (EU) which provides a table of MACs

(Maximum Admissible Concentration) gives a spectrum of levels 10 be acknowledged, rather

than a set list of numbers; this may be due to natural variations (e.g. geology) in soils being

considered. For this project, cadmium, copper, nickel, lead, and zinc are considered,

although copper is the main issue (Table 1):

Table 1: the Environmental Quality Criteria (EU) guidelines for metal concentrations in soils

(this was relevant in 2002)

In reality, the use of total levels does not adequately reflect the actual toxicity which the

metal may present. At present however, the complex variation of methods used to analyse

available fractions of metals has yet to be harmonised, before a more useful table of limits is

produced (Rauret, 2000).

1.4: Aims and Objectives

As the first environmental survey of Tomnadashan, the study on the distribution and

behaviour of copper in soil samples collected from the site is an appropriate starting point.


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All chemicals, reagents and instruments used are listed in Appendix 2. The aims behind the

report are summarised:

1 To discuss findings on the levels (and possible toxicity) of copper, and some associatedmetals, in relation to the mine waste, and the smelter.

2 To investigate whether or not the mine waste is largely buried, and may be producingleachates alone with heavy metals, passing downhill.

3 To investigate the forms of copper which are present, and the environmentalimplications suggested by the findings.

4 To evaluate what strategy is required in the further study of copper (or other metals)distribution at Tomnadashan.


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2: MATERIALS AND METHODS

2.1: Field Visit to Tomnadashan

The Abandoned Mine

This is characterised by a hollow in the hillside. The mine appears as nothing more than a

small cave; a small heap of mine waste is found nearby down the gully, covering only a few

tens of square metres (Figure 1):

Figure 1: entrance to the copper mine, Tomnadashan, near Loch Tay

Pyrite, which is characterised by the tarnished golden brown colour and occasionally

brilliant yellow cubic crystals, is either smeared as fine scales across the rock, or

disseminated within fractures. Pyrite rarely appears in its native crystal form due to

weathering (Barnes, 1988), which makes Tomnadashan geologically unique. Molybdenite

(MoS2), chalcopyrite (CuFS2), galena (PbS) and quartz (SiO2) also occur (Plant et al, 1983).

Collecting the Soil Samples

As shown on the map in Figure 2 over-page, 2 trajectories were covered. Trajectory 1crossed in-front of the mine. Trajectory 2 was conducted at the area where the Jefferies'

acid plant may have stood. The top 10-15cm of the soil profile was dug out using a spade,

with samples taken from the top 10cm (except for one sample, where samples from the top

5cm, 10cm, and 20cm depth were taken at site T1 S8 (Trajectory 1, Sample 8). At the start of

each trajectory, a double compass bearing was taken to locate the starting point on the

map. All along the trajectory, the compass bearings between each sampling point was

recorded, and the distance in paces noted (around 26paces per 20m by the author). The

spade was cleaned of soil after each incision at every site. For the 3 samples taken where

the acid plant may (not) have stood, an auger was used instead (and also cleaned after each

incision).


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Observations made during Sampling

Trajectory 1 and the Bing

Undisturbed rough grass and heather was seen between sites T1S1 and T1S3. At T1S4 this

gave way to thin grassy topsoil as the gully in front of the mine was approached. The T1S5

and T1S6 soil samples were taken within the gully, not far from the exposed waste bings

(Figures 3a, 3b, over-page). T1S7 to T1S9 soils were taken further east, past the gully, and

the T1S10 sample was taken in the adjacent field. Thin grass covered the trajectory between

T1S4 and T1S8, before the return to longer grass. The soils along the trajectory ranged fromdark brown, peaty and root-dominated (at either end of the trajectory), to poorly

developed, light brown stony soils, particularly within the gully

Trajectory 2

The short trek from T2S1 to T2S5 crossed into a small watershed alongside the row of trees

(see 'nap), where some waste rock was seen. Long grass (seen at T2S1) gradually gave way

to bushes as the ground became increasingly waterlogged. The T2S4 and T2S5 samples were

taken behind the raised structure (T2S5 was taken nearby the river). The soils were

generally darker, peaty and water-saturated around the watershed.


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Figure 3a: the small rock waste mounds in front of the mine. Figure 3b: field notebook placed on poorly

developed soil taken for the West and East Bing samples.

Taking the "Building", Bing and River Samples

The raised structure appears as a grass-covered ridge where the smelter may have stood.

The building samples were extracted using a soil corer (Figure 4); soils taken from here were

strongly decolorised, characterised by orange, brown (even pale yellow colours), thin root

penetration and a fine sandy texture.

Figure 4: the soil corer

A thin coating of premature soil exists along the top of the bings, due to chemical

breakdown of the rock fragments. The bing samples were taken where no vegetation had


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yet colonised the exposure. The river sample was collected where the water emerges

further downhill, in a small pond filled with fine gravel.

2.2: Soil Properties and Composition

Observed soil properties

Shortly after being collected in the field (before being transported back to the Chemistry

Department, and stored in a windowless, refrigerated room (the "cool room")), aliquots of

soil from each sample were taken and described, as shown below and on page 12:

Properties of oven-dried soil aliquots

Grab-sampled soil broken up. Taken at random from original soil in bags. Oven-dried overnight at

105C. Soil structure often dominated by roots, esp. with peaty soils mine.

T1S1: medium greyish-brown colour. Roots dominate soil structure, with smaller clusters of rootlets holding

small lumps of soil together. Coarser coagulated soil lumps and roots removed by sieving.

T1S2: medium greyish brown. Rootlets coagulate large lumps of soil together. A few small rock fragments.

T1S3: pale orange-brown. Some > 1cm rock fragments (metamorphic). Small narrow rootlets seen. More even

distribution.

T1S4: medium brown. Some large (>Imm) rootlets. Some large metamorphic rock fragments (>1cm). Poorsorting.

T1S5: pale brown. Dominated by rootlets, coarse quartz fragments, pyrites and metamorphic rock fragments

(some > 1cm).

T1S6: orange brown. Roots narrow (


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T2S2: medium-pale orange brown. Soil significantly coagulated. Rock fragments persist.

T2S3: dark/medium brown soil. Roots present. Rock fragments mostly insignificant (


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Soil pH (Appendix 6b)

In general, a sample of fresh soil is immersed into distilled water, shaken for around 15 to

20 minutes, allowed to settle to the base of the container, and the water is then analysed

using a pH probe (usually a calomel electrode). Differences arise, as to what ratio of soil

(mass) to water (volume) is prescribed (Bashkin and Radojevic, 1999). In this instance, a

ratio of 4g of fresh soil (taken from the "cool room"), to 10mL of water was prepared. This

was not a precise measurement: a 50mL measuring cylinder was used for the water, and the

2-decimal weighing balance was used for the soil (to obtain 4.00g).

This was performed using groups of 4 samples at a time (to reduce delay in measurements

and lime for shaking). Once the soil and water were emplaced inside the glass jars (Figure),

these were intermittently shaken over around 15 minutes (this also is not entirely precise).

The calomel electode used was calibrated to pH4 and pH7, as recommended.

Air-dry soil moisture (Appendix 6c)

Fresh soil was shaken, before a sample was taken out using a hand shovel, and placed onto

plastic sheets laid out on the laboratory bench which was not exposed to sunlight. Between

obtaining each sample, the shovel was cleansed using distilled water and dried.

The soils were then left to dry. This could take as long as 3 days, as some samples were

derived from peat soils. Once dry, they were then sieved through a 2mm mesh, and the

coarse fraction was discarded.

Approximately 2 grams of soil were weighed out precisely, to 4 decimal points. The beakerinto which it was placed was initially weighed. (Beforehand, the beakers were placed into

the oven for about 2 hours, and placed into a desiccator using longs, in order to eliminate

moisture.) Each sample was weighed out in triplicate.

They were then placed into the oven (set at circa 105C), and left overnight. The next

morning, each beaker with its soil was transferred into as desiccator using tongs (so as not

to contaminate the surface). As was done with the beakers on the previous day, each one

(with its soil in this instance) was immediately weighed precisely, by taking it out from the

desiccator using tongs, before closing the desiccator lid. The calculations used for air-dry

soil moisture are provided:

The problem in applying this to the exact samples being analysed for specific copper

fractions, is that they cannot be pre-heated in order to analyse their moisture, as this wouldalter the nature by which copper is held within those samples.


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2.3: Total Copper Extraction

Acid digestion methods such as nitric and aqua regia, extract the "total" copper present in

the sample, although this may not scavenge all mineral-based copper (that within the crystal

matrix of sulphides or rock fragments) (Bashkin and Radojevic, 1999).

Acid digestion (Appendix 6d)

Preparation of samples and solutions, along with digestion and filtration, was all carried out

in the fume cupboard. Concentrated nitric acid (69% soln.) and aqua regia (prepared using

200mL of concentrated nitric acid, and 600 mL of 1:1 (HCl: distilled water)) were the

reagents used in this preparation. 0.5 grams of oven-dried soil of each sample was weighed

out accurately, then inserted into the long lubes used for block digestion, using a small

plastic scoop connected to a pipette (nick-named the boat). The scoop was then brushed

of remaining soil dust before being used for the next sample.

10mL of acid in a 50mL measuring cylinder was then dispensed into the tubes, which were

then placed as a rack on the digestion block. This was set to 120C, and the tubes were left

to boil for 4 hours, before being raised out and left to cool down for 30 minutes. These were

then filtered using 54 Whatman filter paper, collected in 50mL volumetric flasks, and made

to the mark using distilled water.

Sources of error in the preparation stage can have very significant implications on the

results obtained (Skoog, West and Holler, 2000). The incomplete extraction of heavy metals,

volatilisation of the solvent, evaporation, along with contamination within the acid and the

tube walls, will contribute to this. All glassware was cleaned for over 24 hours in Deconsolution, before being rinsed 3 limes with tap water, and another 3 times with distilled

water.

Another important source of error is the difference in mass of the weighed-out sample, and

that which actually enters the tube. The scoop was placed back on the balance before being

brushed, to account for this difference in mass, which could be as much as 0.005 grams

(around 1% of the sample).

Preparation of standards used for total metal analysis

If a solution prepared from the 1000ppm [Metal] standard stock solution was to be

dispensed to prepare standards, its volumetric flask was capped, and inverted each time

prior to its use, to maintain a uniform concentration.

Cadmium (Cd)

The linear range for this element is given as 2mg/L. For Cd, the standards prepared were

0.4, 0.8, 1.2, 1.6 and 2mg/L Cd solutions. A 4mg/L Cd solution was prepared by adding a

2mg/L aliquot of the 1000ppm Cd standard AAS stock solution, into a 500mL volumetric

flask, which was then made to the mark with distilled water. The standards were preparedas shown in Table 2 over-page ("water" refers to distilled water):


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Table 2: cadmium solutions prepared

Copper(Cu)

The linear range for measuring this element using AAS is 5mg/L. 10mL of the standard Cu

solution was pipetted into a 1L volumetric flask, which was then made to the mark, usingdistilled water. From this 10ppm [Cu] solution, the standards were prepared as shown, using

aqua regia, to produce a similar matrix to that of the samples (Table 3):

Table 3: copper solutions prepared

Lead(Pb)

The standard calibration involves the use of 4, 8, 12, 16 and 20 ppm Pb standards. 10mL of

1000ppm Pb was pipetted into a 500mL volumetric flask to prepare a 20ppm Pb solution.

The 4 standards were prepared as shown in Table 4. As the 20prm Pb solution did not

contain aqua regia, this could not be used for AAS due to matrix differences, which would

affect the signal being monitored.

Table 4: lead solutions prepared


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Nickel(Ni)

A 10ppm Ni solution was prepared from the 1000ppm standard AAS solution, by pipetting

5mL into a 500mL volumetric flask, before making it to the graduation mark using distilled

water. The procedure for preparing the 2, 4, 6, and 8ppm Ni standards are similar to that for

lead (above), in terms of volumes of diluted Ni solution, and aqua regia being used. As with

Pb, the 10ppm Ni "top standard" solution could not be used. Using a top standard of 8ppm

produced a greater absorbance signal.

Molybdenum (Mo)

The linear range for this element is 40mg/L. To prepare a solution of this concentration,

20mL of 1000ppm Mo was added to a 500mL volumetric flask, which was made to the mark

using distilled water. Again, the ratio of distilled water to the volume of aqua regia follows

the same pattern as for Ni and Pb (in this case, the standards are 8, 16, 24 and 32ppm Mo).

Zinc (Zn)

The linear range for Zn is 1mg/L. A 2ppm Zn solution was prepared by pipetting 1mL of the

1000ppm standard AAS solution into a 500mL volumetric flask. The preparation of the 0.2,

0.4, 0.6, 0.8 and 1ppm Zn standards follows the same pattern as for the copper standards.

All 5 standards were used.

Blanks

3 blanks were prepared along with the acid digestion samples during the experiment, andmade to 50mL with distilled water. These are listed beneath the AAS results for total copper

and other heavy metals in Appendix 5. Likewise, blanks were prepared for all experiments

which included analysis of copper using AAS.

Converting leachate Cu levels to Soil Cu levels

The calculation used for all AAS-based calculations is provided below:


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2.4: Analysis of Copper Fractions

Copper in soils is accommodated mostly by plants, organic matter and inorganic surfaces;

very small proportions of copper remain in solution. Under natural conditions, copper in

soil originates from the weathering of copper-bearing minerals. Copper then enters into

organic and inorganic complexes; it may be adsorbed onto precipitated solid surfaces,

diffuse into soil minerals, or be absorbed by plants, microorganisms and animals:

Figure 5: movement and phases of copper in soils (taken from White, 1997)

Copper (and any other metal) will never simply be transported from soil to plant. Because of

this, a total copper value doesnt prov ide enough information on the actual toxicity

presented by the metal.

Ethylene-diamine-tetra-acetic (EDTA) acid extraction

This is used for analysing the "plant-available" heavy metal in soil, i.e., that which can be

brought into the soil solution and quickly incorporated into the rhizosphere. The procedure

used was taken from the protocol given under Method 26 of The Analysis of AgriculturalMaterials (MAFF: RB427).

14.60 grams of EDTA salt were weighed out onto a 2-decimal weighing balance using a clean

plastic spoon (stainless steel spatulas are discouraged by Skoog, West and Holler (2000) due

in possible metal contamination). 950mL of distilled water were added into the volumetric

flask. 8mL of concentrated (37%) ammonia solution were added to this in the fume

cupboard, and more distilled water was added up to the graduation mark. Dissolution of the

salt could take as much as 15 minutes by inverting the flask.

10 g of air-dried soil was weighed out, and placed inside a glass jar, wherein 50mL of theEDTA solution (at about pH7 0.1) was pipetted. The jars were placed on the revolving


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shakers for an hour, and the solvent was then filtered using No.2 Whatman filter papers

(closest equivalent to No.40, as specified by MAFF).

The Standardised BCR Sequencial Extraction

This method determines three phases of copper: (1) readily exchangeable Cu; (2) oxide-

bound Cu; and, (3) organically complexed/chelated Cu. A residual fraction (the less readily

ayailable, mineral lattice-bound Cu) was also analysed.

Introduction

In addition to a sequential extraction method prescribed by Rauret et al (2000), samples

were also individually extracted using one of the 3 extractants. This arose due to difficulties

in decanting the filtrate after centrifugation, although a technique for this was developed,

which allowed some samples to undergo all 3 extraction methods.

For each extraction stage, the extractant added is equilibrated with the soil, by shaking the

mixture for several hours. The treated soil should he physically separated from the leachate,

when placed onto the centrifuge machine (which is set at 3000g, for 20 minutes). The liquid

fraction should then be decanted into a container.

As many samples chosen were organic soils, very fine particles were easily dispersed into

the liquid fraction once the centrifuge bottles were removed from the machine, which made

decanting, without losing some of the soil impossible. With care taken not to shake the

bottle whilst gently removing it out of the centrifuge machine, and when holding the bottle

down whilst unscrewing me lid (to minimise disturbance of the soil/water column), amoderately clean liquid could be dispensed. However, at least a few mL of liquid had to

remain as the angle of tipping the bottle reached a critical stage, when the soil began to

advance towards the neck of the bottle.

The liquid collected inside a polyethylene bottle was immediately filtered using Whatman

No.50 paper, before being made to the mark in its volumetric flask, and stored in the cool

room.

This experiment did not involve every soil collected at Tomnadashan. 12 soils were chosen,

with the second trajectory (T2) being the primary focus. All T2 sites were chosen. The Westand East Bing and River samples were selected. The B1 to B3 sites were not chosen due to

limited soil supply. Sites from the first trajectory included T1S1 (a normal soil for the

area); T1S4 (in front of the mine); and both the T1S8 (Org), and T1S8 (Sub) soil, in order to

compare the copper fractions obtained, with soil organic matter.

Stage 1 (Step 1)

The extractant solution required was 0.11 mol/L acetic acid. This was prepared from glacial

(pure) acetic acid in the fume cupboard. 25mL of this was pipetted into about 500mL of

disriiled water in a glass beaker, which was stirred, before being poured into a 1L glassvolumetric flask, before being made to the mark with distilled water.


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This was then stoppered and inverted, before 250mL of this was pipetted (using 100ml and

50mL pipettes) into another 1L glass volumetric flask, which was also made to the mark

using distilled water.

Approximately 1g of soil was weighed into each bottle, using the 4-decimal point weighing

balance. 40mL of acid was added to each sample using a burette, before the bottles were

tightly sealed, and placed onto the 30rpm soil shaker for 16 hours (overnight). Next

morning, centrifugation, decanting and filtration were performed as described. After

decanting, 20mL of distilled water from a burette was added into the centrifuge bottles,

which were put on the shaker for an hour and centrifuged for 20 minutes, before the waste

water was then decanted and disposed.

Stage 2 (Step 2)

On the same day, the extractant for this step was prepared. 34.75g of hydroxyammonium

chloride way weighed out on an Oertling JC-12 balance using a plastic spoon, before beingdissolved into (approximately) 400mL of distilled water. This solution was then transferred

into a 1L volumetric flask.

25mL of 2M nitric acid was pipetted into this, before the solution was made to the mark. To

prepare the 2M acid, around 128mL of concentrated nitric acid was used, and poured into a

half-full volumetric flask of distilled water, before being made to the mark. Both flasks were

sealed, and inverted, prior to their use. The acid solution was prepared in the fume

cupboard. Rubber gloves were used during the preparation of both solutions.

40mL of the extractant was added via a 50mL burette to the 1g of soil, which was weighedout using the 4 decimal-point balance. The soil mixtures were collected into glass jars, which

were put on the rotating shakers overnight (16 hours). The next morning, these were

filtered using Whatman No.50 filter papers, and the filtrate collected in the 50mL volumetric

flasks (made to the mark using distilled water) were transferred into polyethylene

containers, and stored in the coolroom prior to analysis.

Stage 3 (Step 3)

2 solutions were required for this extraction. Solution "C", which was concentrated

hydrogen peroxide, was used by the authors (Rauret et al). However, due to the highorganic content of some of the soil samples, the possible violent reactions and loss of

sample was averted, by diluting the 8.8 mol/L H2O2 to a fifth of its concentration. 50mL of

the concentrated solution was pipetted into a 250mL volumetric flask containing about

100mL of water, which was then made to the mark, capped, and inverted prior to use.

Solution "D", a 1.0 mol/L solution of ammonium acetate, was prepared by dissolving 77.08g

of the salt (weighed out on the 2-decimal point balance) into 800ml of deionised water in a

1L glass beaker in the fume cupboard. This was passed into a 1L volumetric flask through a

filter funnel inserted at the top to prevent spillage. This solution had to be established at

pH2 ( 0.1) using a calibrated pH meter, this adjustment was performed in the fumecupboard using concentrated nitric acid, which was added in aliquots, using a plastic


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pipeline. Once at around pH2 (the actual pH was 1.93), the solution was made to the 1L

graduation mark with de-ionised water, capped and inserted prior to use.

Had this; experiment been performed according to the journal, 10mL of solution C would

have been added to the remaining soil residue after Stages 1 and 2, in a centrifuge tube.

Instead, 1g soil aliquots were weighed out in duplicate into glass jars, and 10mL of Solution

C was pipetted into these in the fume cupboard, before the jars were capped loosely using

polyethylene screw-caps.

These were left to digest in the fume cupboard (at room temperature) for an hour, whilst

being occasionally shaken to allow the soil to equilibrate with the solution. Meanwhile, 2

water baths were heated, whereby the temperature, using the dials, was raised to around

85C; in reality, the temperature did not exceed about 75C. The samples were then placed

onto the water baths, and left for an hour with their caps intact (and were occasionally

shaken during the first 30 minutes). Thereafter, the caps were removed, and the solution

was allowed to evaporate until around 3mL remained, before another 10mL of Solution Cwas added to each sample.

These were capped again for an hour (shaken occasionally for the first 30 minutes), before

being allowed to evaporate until a slimy residue remained. (Rauret et al instructed the

analyst to "reduce the volume of liquid to about 1mL" due to the diameter of the jar; this is

difficult to predict as the samples were not allowed to evaporate to dryness, as instructed.)

50mL of Solution D was added to this, and the jars were then tightly capped, before being

placed on the shaker for 16 hours. Thereafter, the leachate was filtered using No.50

Whatman filter papers, collected into a 50mL volumetric flask, made to the mark, and

capped, before being taken into the cool room for storage.

The Residual Copper

Once these 3 fractions of copper had been extracted, the centrifuge bottles. After decanting

the Step 3 extract, were rinsed, by adding 50mL of distilled water via burette, and shaking

fur an hour, centrifuging, and then disposing of the water. Here, another alteration was

made to the method of analysing the remaining sediment: instead of adding aqua regia in

situ, as much of the sediment as possible was transferred out of the bottles, and into glass

beakers. These were then oven-dried, and 0.1 gram portions were weighed out to 4 decimal

places, before being transferred into the lung tubes used for the block digestion. 10mL ofaqua regia was added, and the samples were left to equilibrate over-night.

The next morning, the tubes were placed on the digestion block for 4 hours, before being

left to cool, and the samples filtered using No.50 Whatman paper. As with total copper, the

filtrate collected was made to 50mL in volumetric flasks, and stored in room temperature

conditions prior to AAS analysis.


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2.5: The River Sediment

Mineralogical Analysis of River Sediment using XRD

In the simplest terms, the instrument shown in Figure 6 records the intensity of X-rays

reflected off the surfaces of crystals and mineral powders (Walker, 1995). The angle at

which radiation is transmitted onto the surface is critical, as the the X-rays will be deflected

by the crystal structure of the mineral, when approaching at a fixed angle.

The river sediment sample alone was selected, mainly due to its low organic content, but

also as the river drains out from the slope below the waste rock. It was anticipated that

some of the minerals present in the sediment may have originated from the waste rock, or

that sulphides present within the soil due to the underlying geology, may exist.

2 samples were taken from the oven-dried, sieved river sediment. The first was a random

sample taken after shaking the soil bag; the second consisted of crystals and small rock

fragments, which were chosen in order to determine some of the sulphides present.

The samples were ground into powder, using a small (hand-held) mortar and pestle, which

were treated with acetone to produce a slurry. This was performed to enable the sample to

be poured onto the slide. The slurry was flattened out on the slide using a clean blade to

form a very thin but opaque layer with its thickness almost indistinguishable.

Figure 6: the XRD instrument used for analysis of river sediment samples (Phillips PW 1050/35)

The slide was inserted onto a clip beneath the centre cap on top of the XRD machine, and

the X-ray port was then switched on for around 55 minutes, using the computer software

which operated the machine. Afterwards, the slide was taken out, and the data collected onthe computer was used w produce a qualitative chart, on which the number of counts per


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minute (a measure of the X-ray radiation reflected by the sampler was plotted against the

angle of the radiation striking the sample surface (see Appendix 3).

Analysis of copper in particle size fractions

2mm, 0.5mm, 0.25mm, 0.125mm and 0.63mm mesh sieves were used, to give a general

overview of the particle size distribution itself. These were fitted on top of one another with

a collecting basin at the base, with the order of mesh size increasing upwards. About a

quarter of the fresh river sediment had been scooped out, and air-dried, before being

transferred into a heavy duty plastic bag. The contents were poured onto to 2mm mesh

sieve at the top of the sieve stack, and the entire stack was then shaken before and after

each sieve was removed, with the retained contents brushed into a wide plastic container.

Each fraction collected into the container was weighed using a 1-decimal point balance (as a

large quantity of the sediment was provided), after which the container was scrubbed clean

using a brush and paper towel. A portion of each fraction was transferred using a plasticspatula into a small glass beaker (except the 2mm fractions).

Triplicate 1g aliquots of the (0.063 to 0.125mm), (0.125 to 0.025mm), (0.25 to 0.5mm) and

(0.5 to 2mm) fractions were weighed out using a 4 decimal-point balance, each into another

small (50mL) glass beaker. 10ml of concentrated acid was poured onto this in the fume

cupboard, using a plastic 10mL measuring cylinder. The beakers were left over a weekend

for the acid to fully equilibrate with the sediment.

The following Monday, these were placed on the hotplate in the fume cupboard and heated

to 110C for 4 hours, and then left to cool for another hour. The extracts were filtered in thefume cupboard, using No.541 Whatman filter paper (a faster method in comparison to using

No.50 paper), and collected in 50mL glass volumetric flasks before being made to the mark

with distilled water. These were analysed for copper using the AAS method, using the aqua

regia calibration standard solutions (as these contain nitric acid. hence a similar matrix will

exist).


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3: RESULTS AND DISCUSSION

3.1: Experimental Data

(Although all tables of triplicate values are given throughout Appendix 5, the graphs are all

contained between pages 23 and 38. Some of the terms used in the data are explained

under Abbreviations.)

Baseline data and conversion factors

This includes lists of the masses of soil aliquots and their containers, calibration charts, and

results taken down during usage of the AAS facilities. The data presented in this chapter is

the final product of both the measurements taken, and the necessary calculations applied.

The baseline data is presented in Appendix 5 along with the results discussed.

The conversion of calculated concentrations of copper, from that in air-dry soil, to oven-dry

soil levels is calculated for the results obtained for samples treated with EDTA, and the

sequential extractants. The calculation is given:

Baseline data for calculating the moisture content of the samples is given in Appendix 5a.

Total Copper levels

Average values (Graph 1; Appendix 5c)

The most obvious feature is the outstanding contrast between Cu levels in the T2S5, bing

and river samples, compared to the other sites. This does not appear to influence sites T1S4

to T1S7, which are proximate to the bing sites by a few metres. It can be concluded from

this that copper-containing dust being wind-blown from the exposed waste does not pose a

particular threat to the surrounding soil. Both T2S5 and the River samples show much more

elevated copper levels, which suggests that contamination could be spreading downhill byinfiltration, possibly from a local source (the 1861 map shows waste covering all the area

between the mine and the smelter).

The second point to note, is that most samples show levels in breach of the EC standards (of

max. 140mg/kg Cu in dry soil), even the natural soils such as T1S1 and T1S10 show levels

above 100ppm, which may owe to the soil resting above a copper porphyry.

Replicate aqua regia extraction values for total copper(Graphs 2, 3a, 3b)

Graph 2 shows the variation in levels across Trajectory I. There appears to be a moderateincrease towards the centre, although the replicate values also tend to spread apart from


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one another (especially those ofT1S1). In terms of Cu having been extracted with nitric acid,

levels between T1S1 and T1S3 exist at around 150ppm, then rise to over 400ppm towards

T1S5, retreat sharply at T1S6 to 200ppm, then rise steadily towards T1S8, before decreasing

to just under 20Uppm in T1S10. This pattern is reflected by the aqua regia-extracted Cu

levels, although T1S7 shows a protruding value for one of its triplicates. On the whole, Cu

levels soar mainly around T1S5, and are moderately elevated between there and T1S9. T1S5

exists within the gully in front of the mine and near the waste, and the high levels may

reflect copper infiltrating thereto.

Graphs 3a and 3b show copper levels across Transect 2. Graph 3a displays the values on a

logarithmic scale - most triplicate values appear accurate, except for the B3 sample (where

one value is noticeably lower). The steady increase in levels from T2S1 to T2S5 is shown by

an exponential increase on Graph 3b (normal scale). Copper levels rise steadily from about

100ppm (perhaps a "normal" level) to those seen halfway along Transect 1 (around

400ppm), between T2S1 and T2S4. The higher the levels, the less agreeable the triplicate

values; the bing samples show triplicates which vary by as much as a few hundred mg/kg.

Other heavy metals (Graph 4, Appendix 5d)

Graph 4 compares copper with four of the five other heavy metals analysed (as cadmium

levels were negligible). This is depicted on a logarithmic scale as the relationship between

Cu and metals such as Pb are known to relate in this manner (Ngriau, 1979). The

comparisons are reasonable, although varied. Pb and Mo increase in conjunction with Cu

from T2S1 to T2S5. However, Ni and Zn do not share this pattern. Some elevated Pb and Mo

values are seen with the bing and river samples, and both show lower values with the

"Building" samples. Ni and Zn show very low values for the "Building" samples, but levels arenot elevated with the bing and river samples.

Soil limit values

With reference to Table 1, the levels of total copper nearly always (and sometimes far

exceeded) the EC limit values of 50-140 mg/kg. Although levels of cadmium are negligible, it

can be said that levels, even if exceeding 3mg/kg, only do so marginally. Levels of Zn and Ni

are moderate, and generally do not exceed legal limits. Levels of Pb are nearly all below the

300mg/kg threshold, except at T2S5, where they have "shot up" to almost 1000mg/kg at

that site exponentially (even on a logarithmic scale), from below 100mg/kg along the othersites at Trajectory 2.

EDTA-extracted Cu levels (Graphs 5a, 5b; Appendix 5e)

These are shown in Tables 4 and 5 in the appendix (but not in terms of oven-dry soil). Graph

5a shows the distribution of EDTA-extracted copper across Transect 1. The pattern is quite

different to that for Total Cu. There does not appear to be a significant increase towards the

centre of the transect; the only exception to the even spread of copper soil levels (circa 20-

25ppm) is at T1S8, due to the variation in extractable copper between the topsoil (T1S8

Org.) and subsoil (T1S8 Sub.). This sustained level may indicate that any past miningactivities and present waste does not appear to seriously affect the availability of trace


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elements in soils collected here.

Graph 5b shows EDTA-extracted levels along Transect 2, at the waste bings, within the river

sediment, and along the raised ground which may have been a building foundation. It

should be borne in mind that only limited samples were taken at the raised ground,

although the single values there show very low copper levels (circa 30ppm), which reflect

the low levels for total copper at these sites (90-120ppm).

However, there is less agreement amongst some of the triplicate data sets here. Those for

T2S5 are dubious, with the possibility that the low value of circa 25ppm is not

representative. Levels within the River sediment are also uncertain. The increase in levels

between T2S1 und T2S5 appears certain, approaching levels seen with the bing and river

sediment samples. This appears to suggest that the raised copper levels within the river

sediment and at T2S5 (which are proximate to each other), may be influenced by a point

source of copper.

EDTA-extractable Cu and Total Cu (Graph 6)

Graph 6 shows the proportion of Total Copper being plant-available ("%EDTA", i.e., the

proportion of total copper extracted by EDTA). Compared to the (50 to 90%) values

obtained by Schramel et al (2000), or the (60 to 80%) values obtained by Hogg et al (1993)

using agricultural and forest soil, the (5 to 30%) values (except for an anomalous 63% at

T2S4) are considerably lower.

The graph also depicts the Loss on Ignition values as percentages. There appears to be some

correlation between this, and the percentage of total Cu extracted by EDTA, particularlyalong Transect 1.

An exception 10 this is seen with the "Building" samples, with moderate EDTA-extractable

copper levels, in spite of almost negligible organic matter. It is also interesting to note that

very low levels of plain-available Cu exist at the poorly developed soils at the bings, possibly

since most of this material is inorganic, with Cu being retained within the mineral phase.

Along Transect 1, the levels of EDTA-extractable Cu appear to decrease slightly towards the

centre, although lower values occur in intervals (such as T1S5, T1S7 and T1S9). Along

Transect 2, the extractable levels decrease between T2S1 and T2S5, although there areerratic variations along the transect. The sharp decrease between T2S4 and T2S5 may owe

to the average value obtained for T2S5 being lower than it should (as one of the triplicate

values is considerably lower).

The organic-poor river sediment shows very low levels of EDTA-extractable Cu, which may

also indicate that most Cu is contained in the mineral fraction, which would be unavailable

to plants (White, 1998).


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Copper fractions obtained using selective extraction methods (Appendices 5g, 5h)

Comparison between Separate and Sequential extraction (Graph 7)

The issue of poor reproducibility in sequential extraction experiments has triggered

considerable debate in recent years (Rauret et al, 1998), with criticism on the methods

themselves as being non-specific in which copper binding sites are targeted (Schramel et al,

2000).

Caution should also be paid to the low number of samples used in the selective extraction

procedure (4 sites, hence 12 replicates). Graph 7 shows the comparison between the

separately, and sequentially-extracted Cu fractions in sites T2S2, T2S3, T2S80rg and West

Bing. These four were chosen to represent small-scale changes along a transect (with T2S2

and T2S3), the influence of organic matter (TISSOrg.), and the influence of copper mine

waste (West Bing).

The most striking feature is the larger quantity of copper extracted sequentially throughout

Steps 1, 2 and 3 (although this seems less important with Site T1S8Org.). The main

contributor to this is the organic fraction (extracted during Step 3), which appears more

successful, especially with the West Bing samples which were sequentially treated. This

pattern is generally not seen with Step 1 (extraction with hydroxylamine chloride). As these

levels are in air-dry values, the sites themselves cannot be compared.

Overall, it appears that removing copper fractions in sequence is more successful. Whether

this is due to reduced re-adsorption of copper back onto other fractions, or that other

fractions present with the separate extraction soil samples influence the behaviour of theextractant itself, requires further investigation.

Sequentially extracted Cu: results (Graphs 8, 9)

Graphs 8 and 9 present the levels of fractions obtained by sequential extraction. As all 4

fractions put together should represent the total copper present in a sample, the fractions

are presented as percentages of the total copper.

Graph 8 shows the percentages of fractions of all replicate samples used in the sequential

extraction. Although the variation in the proportions of exchangeable (Step 1), reducible(Step 2) and organic (Step 3) copper relate to one another, their increase occurs at the

expense of the residual copper fraction.

The organic complexation sites (in terms of copper-binding sites) are of primary importance

(with the exception of the West Bing samples). This is understandable since the other 3 sites

consist of peaty soils, which are enriched in organic matter which has accumulated, along

with the trace elements it contains (White, 1998). Of secondary importance are the oxides,

as shown by the fractions extracted in Step 2. These are particularly relevant with the T2S2

and T2S3 samples, but less so with the organic TISSOrg., and West Bing samples. Very low

(


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noticeable, but not very significant.

The residual copper fraction percentage levels show the most variation between triplicate

values, especially with the T2S2 soil samples. As a result, it is difficult to deduce, what levels

these may generally occur at with the four soils analysed, although it appears certain that

residual copper is more important at the West Bing.

In spite of the variations discussed, the average distribution of copper fractions is shown on

Graph 9. The freely exchangeable copper is insignificant, with the vast majority of copper

cations being bound to specific sites within the soil, and this may be reflected by the small

proportions of total copper present being extracted by EDTA. There is considerable variation

in the copper held by oxides, as indicated by that seen between sites T2S2 and T2S3,

although it may be suggested, that this fraction is less significant with sites affected by mine

waste (West Bing). The organic-bound copper appears to vary positively, in relation to

organic levels in the soil.

Separately extracted Cu fractions: results (Graphs 7, 10, 11, 12)

The great drawback in performing separate extractions is that a residual value cannot be

obtained as other fractions will account for it. Although there were differences between the

total sum of levels produced, between sequential and separate extraction methods, the

proportions of these fractions between the two methods was not highly dissimilar (Graph

7).

Graphs 10 and 11 show the amounts of copper obtained with each separate extraction step,

amongst the triplicate sets of data. Graph 9 shows the results which relate to lower levels ofcopper (sites T1S1, T1S4, TIS8Sub and TIS8Org., T2S1, T2S2, T2S3 and T2S4). There are a few

notable variations between triplicates, particularly sites T1S1 and T2S2 (with variations in

organic-bound copper - Step 3), and T2S4 (variations in the reducible copper - Step 2).

Overall though, most quantities and proportions of the fractions between triplicate sets

appear similar (particularly TIS8Org, and T1S4).

Graph 11 shows the triplicate results for copper fractions, for T2S5, the bing and river

sediment samples. The triplicate values for all 3 extractions appear to correlate more

strongly with one another, with the exception of T2S5, which shows contrasting levels of the

oxide and organic-held copper, even though the proportions arc similar.

Graph 12 shows the average proportions of the copper fractions in the samples analysed

using separate extraction methods. As was seen with the residue copper fraction

proportions in sequential extraction, it appears that copper fractions extracted using Steps 1

and 2, vary in direct proportion to one another, at the expense of the organic copper

fraction (Step 3). These fractions increase along Transect 2, from T2S1 to T2S5, and are

dominant in the subsoil sample (T1S8 Sub.), in sharp contrast to the organic (TIS8Org.)

sample. They are also dominant in the bing and river sediment samples.


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River fraction and XRD results (Graphs 13, 14, 15; Appendices 3a, 3b, 3c, 3d; 5b)

None of the graphs in Appendix 3 gave any indication of any of the sulphides within which

heavy metals including copper are found in the local geology. Appendix 3a contains the

abbreviations used for correlating each peak produced with the mineral that is likely to be

present. These are defined below:

As can be deduced from the magnitude of the peaks, quartz and feldspar dominate the

mineralogy of the sediment (each constituting over 25%). Muscovite appears to be a minorcomponent (between 5% and 25%), with kaolin, tremolite (a form of amphibole) and

chlorite occurring at trace levels (2mm particle size fraction, it appears that (had a 1mm mesh been used as well) the mass

of each fraction is equally distributed. (It is worth noting that a 0.032mm mesh was used,

but almost no sediment passed through this.) In general, the river sediment collected is very

poorly sorted.

Graph 14 shows the copper levels in Ig portions of each size Fraction. Copper levels increase

in inverse proportion to the particle size, which could be expected if chalcopyrite or Cu-

containing particles are present, with increasing surface area in relation to decreasing

particle size.


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Graph 15 shows this for all of the samples. Overall, the variations in pH appear sustained

between pH4.5 and pH5.5, with occasional and slight exceptions. There is no significant

contrast between the acidity of natural soils (such as T1S1, T1S10 or T2S1), and those

nearby the waste (such as T1S5 or T1S7), or the bing and river sediment samples

themselves. The "Building" samples show slightly lower levels, although these are not

detrimental. One feature worth mentioning is the progressive decrease in pH from T2S1

towards T2S5, where it suddenly recovers. Overall though, it can be concluded that since

copper levels do not relate to pH, the mine waste may not be inducing any significant acid

mine drainage.

3.2: Statistical Treatment of Data

Rejection of outliers: Dixon's Q test

The Q test was used occasionally during the project, especially as outlying values often

occurred in the data presented in this report. The equation used is depicted:

This is applied, whereby the experiment Q value (Qexp) is calculated by dividing the value (xQ

-xN) (of the difference between the outlying value and its nearest replicate value), by the

spread (the difference between the largest, and smallest value). The Dixon's Q test tablesgive a critical Q value of 0.970 for a triplicate set (95% confidence). If Q > the critical Q value,

the outlier is rejected (Skoog, West and Holler, 1996).

There are limits to this method. Inevitably, if 2 of the 3 values are the same, the third value

would have to be rejected, as Q would equal 1.000. The test cannot be applied in this

situation, and its use may also be dubious, where 2 values are almost identical, although all

3 values are relatively similar (particularly with larger numbers- e.g. 825, 826, 857).

Triplicate values which could be viewed with suspicion, may include sets, where, for

example, one value is more than double/less than half of the other 2 values.

The rejection of outliers was used on one occasion, with some of the pH values obtained for

soils T2S1, T2S2, T2S3, T2S4, and the River sediment. Whilst 2 of the replicate data sets

agreed almost exactly with one another, the third showed consistently lower values, and

further soil samples were analysed as a result, with the new data (in better agreement with

the first two sets) being accepted.

Although there were other cases where The triplicate values appear dubious (for example,

the EDTA-extracted copper values for T2S5 in Graph 5b), the other two results tended to

differ from one another, to the extent that the Q values produced did not exceed 0.97. As a

result, no other data sets included outliers which were rejected.


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Correlation and Multiple Regression

Statistical methods such as multiple and linear regression are 2 of the many methods which

can be used to identify possible relationships between sets of data with the same number of

entries.

Mathematics of correlation

Here is an example of the levels of copper and the other 4 heavy metals being analysed,

using the Correlation command on Minitab V13:

For each pair of data sets, 2 values are produced. The Pearson correlation (r) values range

from (-1) to (+1), whereby a value of (-1) indicates that the values along the x axis are

inversely proportional to those along the y axis; (+1) indicates the opposite trend. In either

case, values approaching zero indicate an increasingly unlikely correlation. The r value

obtained can be analysed using a t-test, to assess by what percentage the variation within

one group, is explained by that of the other group of data:

(r2) gives the decimal equivalent of the percentage value, showing how much (%) of the

variation in one group is explained by that in the other group (e.g. for Cu and Mo, r= 0.883,

hence r2

= 0,780, and so 78% of the variation in copper levels is determined by those of

molybdenum.

The p-value (also known as the population correlation coefficient, p) is used to test the

significance of the correlation between the 2 groups. The value is inversely proportional to

the certainty of a correlation between 2 sets of data; it statistically presents the evidenceagainst it.


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The relationship between copper and molybdenum is therefore highly significant as p =

0.000. Thep value for correlating zinc with nickel is 0.001, and when multiplied by 2 to give

the two-tailed R value, the new value (0.002) is considerably less than the 2-tailed value of

0.01. This implies that the correlation is significant at the 1% level (or that there is more

than a 99% certainty of this relationship existing) (Mendenhall et al, 1999).

Multiple Regression

A multiple linear regression is undertaken which takes more than 2 variables into account.

This is a flexible model, which is based on the equation given below-

Mendenhall et al (1999) explained the above equation (extract taken from lecture notes):

Although the outcome of this is similar to using correlation as a means of identifying

possible relationships, this method and the data produced allows such inter-relationships to

be examined more closely. The relationship between 2 variables is considered, in the

presence of the other variables. It is never enough to assume that 2 variables correlate with

one another, without considering the behaviour of others (as another factor may have

caused the 2 variables to behave in that manner).

Taking the example of Cu and the other 4 heavy metals again, here is the output by Minitab

using the Regression command:


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The regression equation is based on that seen on page 47, which shows how copper may be

determined by all 4 metals. In the next section a list oftandp values are produced. Next, an

r2 value is postulated, and from this, a percentage (in this case, 98.2%), which presents the

proportion of variation of total copper levels, being determined by the four metals

altogether.

The ANOVA (Analysis of Variance) reveals the degrees of freedom (DF), the Sum of Squares

(SS), Mean of Squares (MS), plus an F and a p value. The F value can be used to determine,

how significant the influence of the four metals are on copper, in comparison to any other

variations within the model. The F value in the output data is compared to statistical F

values. These align with:

(1) the regression degrees of freedom (or df1), or the DF value above beside"Regression'' - this is the number of variables (k) (4 metals); and,

(2) the degrees of freedom of error (or df2), or Residual Error DF, = (n 1k).If the experimental F value is greater than the F value in the table, it can be said, that at

least one of the variables (the metals) is influencing the levels of total copper. The t values

arc compared with those in the table, with (n - 1 - k) degrees of freedom. The p values are

treated in the same manner, as with those for correlation.

As seen on the previous page, the p value for Mo against Cu is 0.000 (as it was in correlation

analysis); however, this time, the p value for Ni against Cu is 0.011. The relationship

between Ni and Cu may still be significant at a 95% Confidence level. However, this can be

studied further using the t value (= 3.60). With 13 samples, (n 1 k) degrees of freedomequals 9. The t95% value for 9 degrees of freedom equals 3.25, and so the relationship

between Cu and Ni is still highly significant. It is interesting to note that Pb also relates to

copper, even though this was rejected using correlation alone. Again, copper does not

appear to be affected significantly by zinc.

The F95% value (against df1 = 4, and df2 = 9) equals 3.63. The experimental value is 79.3, and

so the relationship between copper and the metals altogether is highly significant.

Trends within the data

Copper and other heavy metals

Most of this has been discussed in the last section, where copper was found to correlate

very closely with molybdenum, and nickel. As 11 of the sites are studied here (and hence n-2

= 9), the t95% value used here is 3.25. Calculations for t are given below:


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It can be concluded from this alone, that the occurrence of copper at the bings, the river

and around Transect 2 appears to correlate linearly with some associated porphyry metals

including Mo and Ni. However, Graph 5 showed the relationship between the metals on a

logarithmic scale, whereby Pb appear to correlate closely with copper. This has been

documented by Nriagu (1979), with the logarithmic relationship between Cu and Zn (zinc

often occurs in partnership with lead). With all four metals though, their relationship with

copper varies, although, as expected, they associate with copper. Nevertheless, the

concentration of Cu is much greater in comparison to the other heavy metals.

Plant-available copper, pH and Loss-on-ignition (LOI)

It is already known that the proportion of total copper that is plant-available, does not

relate to soil pH. However, the actual amount of plant-available copper, along with the

plant-available proportion of total copper, pH and LIO were analysed:

Judging by the p values, the only likely relationship may be that between the quantity of

plant-available copper, and soil pH. A linear regression graph was produced (Figure 7):

Figure 7: correlation between soil pH, and the Cu extracted using EDTA


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This shows a very weak linear relationship, with only a 15-20% certainty of it being highly

significant. Furthermore, the r value given is 0.438, and so the t value for (23 - 2) degrees of

freedom is 0.2232, less than the t95% (df= 21) value of 0.2832. There is more than a 95%

certainty that soil pH does not relate to plant-available copper. No correlations amongst

total copper, plant-available copper, soil pH or the organic content are found to exist

(except between total, and plant-available copper).

Relationships with copper fractions (as determined by separate extraction methods)

Due to the low number of samples used for sequential extraction, it is inappropriate to

apply statistical analysis to these. Having taken into account, the differences between the

results relating to separate and sequential extraction, it is still worth investigating the

possible relationships with copper fractions, although no definite conclusions are proposed

at this stage.

The average values of all 3 copper fractions, plus the relevant loss-on-ignition and plant-

available values were compared. The results reflect the cycle shown on Figure 5; all 3 copper

fractions correlate with one another, and also correlate with plant-available copper. P

values of 0.000 and 0.001 indicate that these interactions are very apparent. This pattern is

further illustrated in Figures 8 through 13, and in Table 5.

It therefore appears that the quantity of plant-available copper is determined by all 3

fractions (solution-based, oxide-based and organically combined), although the oxide-

combined copper appears to be the most important source.

Table 5: statistical results for comparisons between different copper fractions


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Figure 8: fractions obtained by extraction steps 1 and 2. Values of Cu i mg/kg oven-dry soil

Figure 9: fractions obtained by extraction steps 2 and 3. Values of Cu i mg/kg oven-dry soil


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Organic Matter

The r values produced suggest an inversely proportional relationship between the amounts

of each copper fraction and plant-available copper, and organic matter. This is due to the

competition between oxide and organic sites. Organic soils strongly retain copper cations,

when even the extraction of the "organic" copper fraction is retarded by the presence of


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organic matter (Ngriau, 1979). However, the p values indicate that this may be uncertain,

and t values were calculated (Table 6):

Table 6: correlation between copper fractions

Knowing that t is negative in this case, if positive, those above would fall short of the t95%

value (except for LOI and the solution copper fraction). The level of organic matter therefore

inhibits the solution copper fraction obtained, but does not affect the oxide-bound or

organically-bound copper released.

When analysed altogether, the organic copper fraction (Step 3) and oxide-bound copper

fraction (Step 2) exert the most influence on plant-available copper levels. Overall, plant-

available copper is strongly influenced by the combination of these 3 variables, with a very

high F value (45.36), and an r value of 0.963 (96.3% of the variation explained by these 4

variables):

Finally, it is worth considering how the proportion of these copper fractions affect the

availability of copper to plants. The correlation output over-page compares the 3 fractions

with the amount of plant-available copper, and loss-on-ignition (over-page):


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As seen in Graph 12, the proportions of oxide-bound, and organically-bound copper levels

share an inverse relationship, which may indicate that each fraction could affect the release

of copper from the other. The proportion of solution copper (out of all 3 fractions) alsorelates strongly to the amount of plant-available copper, and from this, it can be suggested

(not concluded) that organic matter in soils at Tomnadashan retains copper, reducing the

proportion of extractable copper that is in solution, which subsequently affects that which is

available to plants (Figures 14, 15).

Both graphs show a correlation which appears to show a proportional relationship, although

most values deviate noticeably from either side of the straight line predicted. The lines are

also affected by a comparatively high value, and thus a conclusion cannot be reached

without further investigation with a much greater population of samples.

Figure 14: loss-on-ignition (%) and solution copper (Step 1 extraction) (mg/kg oven-dry soil)


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Figure 15: solution copper proportion (% of [Step 1 + Step 2 + Step 3 Cu fractions], and plant-available copper)

3.3: Discussion

Reliability of the data

Statistical analysis can only be used with data, which is randomly sampled, which contains

the same variance, and which originates from the same population. So, for example, whenpreparing each triplicate, these should be obtained from the same sample, and should be

prepared and treated simultaneously. This was not always the case.

The (BCR) separate extraction, Total Cu, and soil pH triplicates were not all performed

simultaneously. In both cases, 2 replicates were performed, followed by a third. Although

glass beakers containing portions of air-dried samples were used for the BCR extraction soil

aliquots (and thereby reducing systematic variability amongst the triplicates), conditions

such as temperature (e.g. water bath) may have varied between the 2 preparations.

There is also the variability which affects the results produced using the AASspectrophotometer. When a calibration chart is computed on the machine, even a

correlation coefficient of 0.999 may result from a line with each value deviating noticeably

on either side of it.

Appendix 2, in addition to listing the instruments used, also specifies the precision of the

glassware used (pipettes and volumetric flasks). The cleanliness of containers, jars, tubes,

etc., also pla

BSc dissertation: Environmental Assessment of soil quality at the former Tomnadashan copper mine.

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Transcript of BSc dissertation: Environmental Assessment of soil quality at the former Tomnadashan copper mine.