Analysis of Heavy Metals in the Riverine Sediment of the

Slaney Catchment, Co. Wexford

Anna Barry

B.A. (Mod) Environmental Sciences Thesis 2015

School of Natural Sciences

University of Dublin

Trinity College

Supervisor: Professor Nick Gray

ii

Declaration

'I Anna Barry declare that this thesis is my own work except where stated through references or

in the acknowledgements and that it is 6,054 words in length'

_______________________

Anna Barry

iii

Abstract

The Water Framework Directive requires that sediment quality guidelines must be determined in

order to ensure quality status and monitoring of water bodies in Europe. In this study baseline

concentrations of heavy metals (Cd, Cu, Fe, Pb and Zn) were established for the Slaney River in

County Wexford.

Nineteen sites on the river were sampled at various points in the catchment. These sediments

were analysed for the following heavy metals: cadmium, copper, iron, lead and zinc. Sediment

enrichment factors and the Geoaccumulation Index was determined for the metals at each site.

The mean concentrations of these metals were: 0.48 µg/g for cadmium; 21.53 µg/g for copper;

26843 µg/g for iron; 20.36 µg/g for lead; and 116.15 µg/g for zinc, ranking mean metal

concentration in the order Fe >Zn >Cu >Pb >Cd. Significant levels of pollution were found at

three sites within the catchment. One site is majorly influenced by a nearby lead mine. The

remaining two sites of pollution are likely to be influenced by diffuse pollution of an agricultural

nature.

The Slaney catchment remains largely unaffected by the low heavy metal concentrations in the

sediment of the river. This study has identified areas of pollution that require further analysis and

investigation.

iv

Acknowledgements

I would like to express my sincere thanks to the following people:

Professor Nick Gray for his guidance, advice and help.

Mark Kavanagh for his assistance with lab work.

My family and friends for their encouragement and support. In particular to my sister

Lousie for helping me to sample during the summer.

To Erin- Jo Tiedeken for helping me with the statistical analysis and Mike Babechuk for

helping me with the geological aspect of the paper.

To my class for helping me to stay positive.

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Contents

Introduction ..................................................................................................................................... 1

1.1 Heavy Metals in the Environment ......................................................................................... 1

1.2 Sediment as an Environmental Indicator ............................................................................... 2

1.3 Sediments and the Law .......................................................................................................... 2

1.4 Description of the Catchment Area ....................................................................................... 3

1.5 Geology of the Area .............................................................................................................. 4

1.5.1. Soils ................................................................................................................................ 4

1.5.2. Bedrock .......................................................................................................................... 5

1.6 Water Quality and Pollutants in the Catchment Area ............................................................ 6

1.6.1 Diffuse Pollution ............................................................................................................. 7

1.6.2 Point Source Pollution .................................................................................................... 7

1.7 Aims and Objectives .............................................................................................................. 8

Materials and Methods .................................................................................................................... 9

2.1 Site Selection ......................................................................................................................... 9

2.2 Sample Collection................................................................................................................ 10

2.3 Laboratory Work ................................................................................................................. 11

2.3.1 Sample Preparation and Analysis ................................................................................. 11

2.3.2 Water Analysis .............................................................................................................. 11

2.3.3 Heavy Metal Analysis ................................................................................................... 11

Results ........................................................................................................................................... 13

3.1 Heavy Metal Analysis ......................................................................................................... 13

3.2 Bedrock ................................................................................................................................ 16

3.3 Stream Order........................................................................................................................ 17

3.4 Sub-catchment ..................................................................................................................... 17

3.5 Q-value ................................................................................................................................ 18

3.5.1 Copper ........................................................................................................................... 18

3.5.2 Iron, Zinc and Lead ....................................................................................................... 18

3.5.3 Cadmium ....................................................................................................................... 18

3.6 Co-occurrence ...................................................................................................................... 19

3.7 Enrichment Factors .............................................................................................................. 20

3.8 Geoaccumulation Index ....................................................................................................... 22

Discussion ..................................................................................................................................... 24

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4.1 Point and Diffuse Sources of Pollution ............................................................................... 24

4.2 Trends in Downstream Concentration ................................................................................. 25

4.3 Comparison with Non-Impacted Sites ................................................................................. 25

4.4 Similarity in Sub-catchments ............................................................................................... 26

4.5 Q-values and Water Quality Status ..................................................................................... 26

4.6 Bedrock ................................................................................................................................ 27

4.7 Correlation Matrix of Metals ............................................................................................... 27

4.8 Enrichment Factors and Geo-accumulation Index .............................................................. 27

4.9 Cluster Analysis ................................................................................................................... 28

4.10 Limitations of this Study ................................................................................................... 30

4.11 Formation of Sediment Quality Guidelines ....................................................................... 31

Conclusion ..................................................................................................................................... 32

References ..................................................................................................................................... 33

Appendices .................................................................................................................................... 39

vii

List of Figures

Figure 1.1 Map of Ireland depicting the Slaney catchment in the South East ……………........... 4

Figure 1.2 Map of bedrock geology in Central and North County Wexford……………..….….. 5

Figure 1.3 Map of River waterbody WFD status 2010-2012……………..........……..……..........6

Figure 2.1 Sample site locations, based on EPA sample sites……………...……..……….……. .9

Figure 3.1. Mean heavy metal concentrations (µg g-1) in the riverine sediments of the sampled

sites, nested in sub-catchment of the Slaney catchment: (a) Pb, (b) Cd, (c) Fe, (d) Zn, (e)

Cu…...............................................................................................................................................15

Figure 3.3. Cluster analysis of heavy metals in the Slaney catchment…………….…..….……. 23

Figure 4.1. Cluster analysis groupings at 0.97 similarity…………………………….…..…….. 28

Figure 4.2. Cluster analysis groupings at 0.90 similarity…………………………….……...…. 29

viii

List of Tables

Table 1.1 Background concentrations and quality objectives for heavy metal in sediments of

freshwater ecosystems …………………………………………………………………………... 3

Table 2.1 Sample site locations in the Slaney catchment……………...……...…...…..……...... 10

Table 3.1 Water pH, alkalinity, mean and standard deviation (SD) of metal concentrations in

riverine sediment of the Slaney catchment……………………………..……….…………….... 13

Table 3.2. Maximum, minimum, mean and median values for heavy metals in the Slaney sub-

catchment……………………………………………………………………………………….. 14

Table 3.3. Non-chemical data relating to the Slaney sub-catchment…………………………... 16

Table 3.4. Mean metal concentrations and standard deviations across various Q-values…...…. 18

Table 3.5. Correlation matrix of heavy metals (Pearson-moment correlation)……….…...…… 19

Table 3.6. Enrichment factors for each metal measured in the riverine sediment of the Slaney

catchment……………………..…...…………………………….……………………………… 21

Table 3.7. Muller’s classification for the Geo-accumulation Index ……………………...…..... 22

Table 3.8. Geo-accumulation index of heavy metals………………………………….……....... 23

Table 4.1. Total metal burden for site in the Slaney catchment……………………………...… 41

ix

List of Appendices

Appendix 1. Example of sample site (C4)…………………………………………………….…38

Appendix 2. Raw data from ICP:AES analysis…….……...…………………………………….39

1

Introduction

1.1 Heavy Metals in the Environment

Heavy metals are present in the soil and bedrock, and occur naturally in the riverine

environment. Metals that have an atomic density of greater than 6g cm3 are considered to be

heavy metals (Thornton et al., 1995). Though naturally occurring, these metals may be

considered a pollutant to the environment. Heavy metals exist largely as impurities in the rocks

in the Earth’s crust. Some metals are found collectively, and some even have synergistic or

antagonistic effects when combined (Chaperon and Sauve 2007). It is when levels of metals

exceed background values that pollution has occurred.

Humans can also contribute to heavy metal pollution, from mining sites, waste discharge, urban

runoff and industrial disposals. An example of this is of Minamata in Japan, where methyl

mercury pollution in the bay bioaccumulated in the food chain, causing serious harm to humans

(Harada, 1978). Heavy metals have the potential to bioaccumulate and bioconcentrate within

organisms (Gray 2010). It is due to this that heavy metals pose a serious health risk in polluted

environments. Various studies, like that undertaken by Mance (1987), give a comprehensive

review of the effect of various metals on a wide range or organisms.

Heavy metals are conservative pollutants that do not break down with biological, chemical or

mechanical degradation (Wilcock, 1999). Due to this they are considered permanent additions to

the environment. Heavy metals such as cadmium and lead are included in the pollutants on the

priority substance list under the Water Framework Directive (WFD) (European Commission,

2001). Other heavy metals such as zinc and copper are essential in limited quantities to aquatic

life, but can be toxic at high concentrations depending on their bioavailability, and the presence

of other pollutants with which they can react (Muyssen et al., 2004). These heavy metals enter

the environment through a variety of channels. Sources of diffuse pollution include road run-off

and land use activities that result in extensive run-off or infiltration, namely agriculture, forestry

and large-scale construction (Gray, 2010). Point sources of pollution include mine drainage,

industrial effluents and farmyard discharges (Gray, 2010).

2

1.2 Sediment as an Environmental Indicator

Sediment has widely been used as an environmental indicator, due its long retention time and its

ability to adsorb pollutants to its surface (Duzzin et al., 1988; Lietz and Galling, 1989). Heavy

metal cations are strongly attracted to the negative charge of sediment particles (Ozonzeadi and

Uzoamaka, 2014). In this respect, sediment acts as a sink for many chemicals, with a high

capacity to accumulate pollutants (Sternbeck and Östlund, 2001). This makes comparison

between the water column and sediment very difficult (Vandecasteele et al. 2004). Conversely,

there is also potential for these pollutants to become re-suspended through a change in

environmental conditions (Petersen et al. 1997). Presence of sediment in areas of fish spawning

and niche habitats for organisms provides opportunity for uptake of metals by these organisms.

In 2004 the Environmental Protection Agency (EPA) found that widespread pollution from the

metals and volatile organic compounds was not a problem in Ireland and was not likely to

become a problem in the near future (EPA, 2004). The EPA currently uses physicochemical

monitoring of rivers in Ireland to assess their pollution status as required by the WFD (EPA,

2006). Rivers are further assessed using biotic indices every three years (EPA, 2015a)

1.3 Sediments and the Law

The members of the European Union are currently in the process of forming environmental

sediment quality guidelines (SQGs) under the Water Framework Directive (WFD). The WFD is

a piece of legislation put in place to regulate and monitor all waterways in Europe (European

Commission, 2000). These SQGs are to help identify areas of pollution that are not identified

with traditional water and biological quality testing. The formation of SQGs is somewhat

controversial as enforced limits will be regulated on a pass/fail basis (Crane 2003). Due to this

correctly estimating the levels of contaminants is very important. Presently there are no

mandatory guidelines set in place regarding these heavy metal limits, but several countries have

appointed background concentration levels for sediment quality (Woitke et al. 2003: Table 1.1).

3

Table 1.1. Background concentrations and quality objectives for heavy metal in sediments of

freshwater ecosystems (Woitke et al. 2003).

There are three leading approaches to the development of sediment quality guidelines

(Ozonzeadi and Uzoamaka, 2014). These are (1) Effects based guidelines- based on effects to

organisms from field or laboratory exposure experiments; (2) equilibrium based guidelines-

applying existing water quality standards to sediment pore concentration (Di Toro et al. 1991);

and (3) background levels in the affected region- the oldest approach, comparing contaminants in

the sediment to background levels (Burton, 2002). All approaches have advantages and

drawbacks, and so difficulties arise with the formation of these guidelines.

In this study the third approach, background levels, is considered. Though sampling for this

assessment is comparatively easier that the other approaches, a major disadvantage of this

method of analysis is that there is no information regarding the ecological impact of metal

contaminants on organisms (Ozonzeadi and Uzoamaka, 2014).

1.4 Description of the Catchment Area

The catchment area of the river Slaney is located in the South-East of Ireland (Figure 1.1; EPA,

2015b). The river Slaney rises at Lugnaquilla in the Glen of Imaal in the Wicklow mountains. It

flows through the towns of Baltinglass, Rathvilly, Tullow and Bunclody before entering the

estuary at Enniscorthy and meeting the Irish Sea at Wexford harbour. The river is over 117km

long, and the catchment has an area of 1943.5km2 (SERBD, 2003). The Slaney catchment is one

of seven catchment areas that make up the South Eastern River Basin District (SERBD). The

main river channel is fed by Carriggower, Deereen, Derry, Clody, Bann, Urrin, Clonmore,

Ballyvoleen and the Boro tributaries (O’Reilly, 2004). The drainage pattern of these rivers is

primarily dendritic, and the streams combine, making the Slaney a fifth order stream.

Cd (µg/g) Cu (µg/g) Fe (µg/g) Pb (µg/g) Zn (µg/g)

Canadian background levels 1.1 25 31000 23 65

Minimum German background levels 0.15 10 - 23 88

Maximum German background levels 0.6 40 - 50 200

US background levels - 20 28000 23 88

Dutch target values 0.8 36 - 100 200

4

Figure 1.1. Map of Ireland depicting the Slaney catchment in the South East (EPA, 2015b).

The area of County Wexford is largely low lying fertile land. Due to the nature of this lan in

times of excessive rain extreme flooding can occur, and the Slaney usually breaks its bank in the

Enniscorthy area (OPW, 2015). The southern edges of the Wicklow Mountains provide a

boundary to the north of the county and the Blackstairs Mountains provide a boundary to the

west (WCC, 2013). The South East of Ireland experiences a temperate maritime climate, which

is primarily influenced by South Westerly winds from the North Atlantic Current. The relatively

mountainous terrain in the West of Ireland ensures that rainfall is lower in the South East,

averaging 800-1200mm a year. Average summer temperatures reach ~16oC and average winter

temperatures lower to ~7oC (Walsh, 2012).

1.5 Geology of the Area

1.5.1. Soils

During the last ice age most of County Wexford was covered with an ice-sheet, as the ice

retreated Wexford was one of the first areas to be covered with glacial till, leading to high

quality soils, suitable for a wide range of agriculture. This glacial till was deposited during the

5

Quaternary period approximately 1.6 million years ago (SERBD, 2003). The soils of the Slaney

catchment consist primarily of acid brown earth soil and brown podzolic soil (Gardiner and Ryan

1969).

1.5.2. Bedrock

The Slaney catchment area comprises mainly of lower-middle Ordovician slate, sandstone,

greywacke and conglomerate rock (Figure 1.2). This underlying bedrock trends in a north-east

to south-west pattern. The central region from Courtown to Waterford comprises of Ordovician

volcanic rock and Silurian deep marine mudstone, greywacke and conglomerate (Barry, 2015).

These rocks were deposited 495-410 million years ago during the Ordovician and Silurian

periods of the Palaeozoic era.

Figure 1.2. Map of bedrock geology in Central and North County Wexford (Barry, 2015).

6

1.6 Water Quality and Pollutants in the Catchment Area

Water quality in the Slaney catchment is moderate-good quality (Figure 1.3). The EPA (2014a)

report on river water quality in Wexford for 2013 states that river quality has improved slightly

from 2012. However, it is comparatively poor on a national scale with only 52% of river stations

reaching at least good status, compared to the national average of 65% (EPA, 2014a). In total out

of the 86 stations, 27 stations passed WFD compliance and 59 were of concern (EPA, 2014a).

The annual report uses biological oxygen demand, ammonia, ortho-phosphate and total oxidised

nitrogen to determine the quality status of the river station. It cites diffuse pollution from

agriculture and small point sources such as small urban waste water treatment plants (UWWT),

domestic waste water treatment systems and farmyards as key pressures contributing to the water

quality in the area (EPA, 2014a).

Figure 1.3. Map of River waterbody WFD status 2010-2012 (EPA, 2015c)

The Slaney primarily supports a spring salmon fishery, and it also supports a smaller sea-trout

and brown trout population. Despite practicing a catch and release programme a slowing in fish

catches has been observed by the Slaney River Trust (Slaney River Trust, 2014). This is one of

the many reasons that the quality needs to be accurately assessed.

7

1.6.1 Diffuse Pollution

The Slaney catchment is made up of four water management units (WMUs): the Slaney upper

WMU (not within the remit of this study), the Slaney lower WMU, the Slaney Estuary WMU

and the Boro-Urrin WMU. In these action plans, all three studied areas regard diffuse pollution

as the biggest impact to the WMUs; Slaney lower (72%), the Slaney Estuary (78%) and the

Boro-Urrin (98%). Agriculture makes up a significant portion of this impact accounting for 67%,

65% and 70% of the diffuse pollution in the WMUs respectively (WFD Ireland, 2010a; WFD

Ireland, 2010b; WFD Ireland, 2010c).

1.6.2 Point Source Pollution

Wastewater treatment plants (WWTP) are present at Bunclody, Camolin, Clonroche and

Enniscorthy (WCC, 2015). The plant at Camolin does not have any secondary treatment in place

(EPA, 2014b). A secondary treatment plant was added to the WWTP at Bunclody in 2010

(WCC, 2010).

There are some recorded historical mines in the Wexford area, including a small silver mine in

the Clonmine region and a zinc mine at Caim (Williams 2011; EPA, 2009). There is also

evidence of industrial Iron production in the Enniscorthy area (Barnard 1985).

8

1.7 Aims and Objectives

It was the aim of this study to establish reference concentrations of heavy metals in the

sediments of selected sites in the Slaney catchment, and to identify any possible factors

associated with the sediment metal burden in the river. Heavy metal concentrations were

compared to a variety of other factors in order to determine the degree of pollution in the

catchment area. The following hypotheses were tested:

1. Sediment metal burden is associated with known point or diffuse sources of pollution.

2. Sediment metal concentration increases downstream

3. Sediment metal burden is similar to other rivers at non-impacted sites.

4. Sediment metal burden is similar in geographically similar areas (sub-catchments).

5. Water quality status (Q-value) can be estimated on the basis of metal concentration.

9

Materials and Methods

2.1 Site Selection

The locations of the sample sites were chosen from existing Environmental Protection Agency

(EPA) sites (Figure 2.1; Table 2.1; EPA, 2014c). These sites are characterised by the EPA as

operational (aimed at protecting high status or restoring good status), surveillance (long-term site

assessment, aimed at providing background trends on water status) or pre Water Framework

Directive (WFD) (Mayes and Codling, 2009). In this study nineteen sites in the Slaney

catchment area were sampled. Site choice was primarily decided upon by accessibility to the

sites. Sampling was undertaken in June when there would be a high level of access to sites due to

low river discharge rates.

Figure 2.1. Sample site locations, based on EPA sample sites (EPA, 2014c)

10

Table 2.1. Sample site locations in the Slaney catchment (EPA, 2014c).

2.2 Sample Collection

At each site three sediment samples and one water sample were taken. Water samples were

collected and stored in 250ml polyethylene containers. The samples were then placed in a cool

box to avoid temperature changes.

Sediment samples were taken from the surface of the river bed using a plastic scoop. Each

sample consisted of approximately 1kg of sediment from the top 30mm of the river bed. The

sediment was then sieved into a shallow tray in the field using a standard 1 mm sieve. The sieved

fraction was collected and stored in a two litre polyethylene container. The sediment samples

were emptied from the polyethylene containers into aluminium trays and left to air dry. When

dry, the samples were removed from the trays and placed in polyethylene bags, in which they

were transported to the laboratory in a cool dark container (APHA 2005).

Site River Location

A1 Tinnokilla Stream Spring Bridge 292283.15 E 127974.99 N

A2 Clonmore Clonmore Bridge 294510.28 E 131098.51 N

A3 Clonmore Mackmine Bridge (On Side Road) 296539.00 E 131232.00 N

B1 Boro Garraun Bridge 286780.00 E 137871.00 N

B2 Boro Boro Bridge 286700.83 E 137630.76 N

B3 Boro Ballynapierce Bridge 295754.01 E 136488.09 N

C1 Urrin Askinvillar Bridge 284945.04 E 145823.49 N

C2 Urrin Mocurry Bridge 286452.00 E 146420.00 N

C3 Urrin Bridge South of Curraghgraigue 289704.61 E 143626.19 N

C4 Urrin Verona Bridge 294613.07 E 139930.84 N

D1 Clody Ford Bridge 3km upstream Bunclody 289685.00 E 154881.00 N

D2 Clody Clody Bridge Bunclody 291048.00 E 156871.00 N

E1 Borris Stream Bridge Upstream Slaney River Confluence 294484.86 E 153488.16 N

E2 Ballingale stream Ballycadden Bridge 298402.00 E 156354.00 N

E3 Ballycarney stream Bridge Downstream of Tinnashrule Bridge 299536.19 E 152471.65 N

F1 Bann Camolin Stream- Bridge Upstream of Bay Bridge 306226.76 E 152641.08 N

F2 Bann Doran's Bridge 302209.80 E 148485.72 N

G1 Ballyedmond Ballyedmond (Old) Bridge 312871.00 E 145168.00 N

G2 Tinnacross Stream Bridge upstream of Salsborough Bridge 300874.13 E 143713.69 N

Irish National Grid Co-ordinates

11

2.3 Laboratory Work

2.3.1 Sample Preparation and Analysis

In some cases it was necessary to dry the sediment samples in an oven at 40oC overnight. The

dry sediment samples were lightly broken up using a mortar and pestle and were then sieved

through a 63µm sieve to ensure that variance due to grain size was minimised (Birch et al.,

2001). A maximum amount of sediment was collected from each sample. Sediment samples

from the nineteen sites were analysed for heavy metal levels.

2.3.2 Water Analysis

Water samples were taken to assess pH and alkalinity. The pH levels were measured using a

Jenway 3030 meter with an Ag/AgCl reference electrode and expressed as mg/CaCO3

equivalent. Alkalinity was analysed by the gran titration method (APHA 2005). Water samples

were not tested for heavy metals as concentrations were expected to be below detection limits.

2.3.3 Heavy Metal Analysis

The samples were prepared by nitric acid digestion. Samples were weighed to approximately 1g

and placed into digestion tubes. Anti-bumping granules and 10mls of nitric acid were added to

the tubes. Two digestion tubes were used as blank controls for the experiment. The digestion

tubes were left overnight to allow complete digestion and placed in a Velp Scientifica DK

heating digestion block at 170oC for two hours the following day. When the digestion procedure

was completed a small amount of de-ionised water was added to dilute the solution, and the

tubes were left to cool. The samples were then filtered through Whatman no.1 filter paper into

50ml volumetric flasks. The digestion tubes were rinsed with de-ionised water to remove any

remaining residue. De-ionised water was further added to make the solution up to 50ml. The

samples were sealed with para film and inverted to achieve a uniform solution. The samples

were then placed in an inductively coupled plasma atomic emission spectrophotometer for

analysis (Varian Liberty AX Sequential ICP-AES). Merck CertiPur ICP multi-element standard

12

solution IV was used to calibrate the machine and Accustandard MES-04-1 ICP multi-element

standard solution IV was used as a quality control check. Two blank samples were added to act

as controls (APHA 2005). The heavy metals that were analysed in this study were cadmium

(Cd), copper (Cu), iron (Fe), lead (Pb) and zinc (Zn).

The following formula was used to calculate the concentration of metals per gram of dry

sediment (µg g-1 in dry weight).

µg g-1 in dry weight = mg l-1 in digest tube x 50 ml (volume of volumetric flask)

Weight of sample digested (g)

The values from the analysis were corrected for the controls before carrying out further

calculations.

The concentrations of the individual metals were checked for normality prior to analysis using

histograms, normal probability plots and box plots. Cadmium and zinc concentrations were not

normal, so they were 1/√(y) transformed. The remainder of the data were untransformed. The

data were analysed using analysis of variance (ANOVA) on Data Desk version 6.3.1, with

individual metal concentrations as the dependent variables and bedrock, stream order, river, sub-

catchment, pH, alkalinity and Q-value as the independent variable factors. Cluster analysis was

performed using PAST version 2.17c, paired group algorithm using Bray-Curtis similarity

measure (Hammer et al., 2001).

13

Results

3.1 Heavy Metal Analysis

The metals chosen for analysis were based on those analysed by Yau and Gray (2005), as they

are commonly mined minerals in Ireland and are associated with wastewaters (Gray, 2004). The

pH, alkalinity and mean concentrations of sediment metals, including standard deviations, for

each site are presented in Table 3.1.

Table 3.1. Water pH, alkalinity, mean and standard deviations (SD) of metal concentrations in

riverine sediment of the Slaney catchment.

Site pH Alkalinity

Mean SD Mean SD Mean SD Mean SD Mean SD

D2 7.26 15.16 0.17 0.04 16.12 3.79 16220.13 1572.53 11.51 3.18 71.93 33.96

D1 6.98 10.48 0.12 0.02 14.37 2.23 25499.45 2596.33 10.35 1.67 77.79 6.54

Borris Stream

E1 7.55 41.20 0.37 0.20 25.04 1.65 29448.69 1161.18 18.39 3.33 99.23 12.89

E2 7.09 28.16 0.38 0.07 20.72 0.91 28810.85 1300.00 13.32 1.21 89.24 4.90

E3 7.18 24.80 0.23 0.08 20.52 1.88 31067.06 1770.55 12.89 0.74 92.62 9.14

F1 7.22 29.92 0.19 0.04 24.61 0.63 31572.82 1299.45 19.15 1.33 127.30 3.75

F2 7.57 32.28 0.48 0.07 21.78 0.59 30349.24 2108.57 17.39 1.31 155.31 8.72

G2 7.87 80.20 0.69 0.10 22.30 0.78 33548.88 2906.63 17.07 1.18 136.40 13.33

C4 7.16 21.28 0.38 0.05 21.79 1.20 24223.03 2198.76 17.49 0.69 93.40 4.59

C3 7.18 16.56 0.31 0.09 19.04 1.86 25219.77 376.57 21.45 6.53 93.13 5.20

C2 7.04 12.40 0.39 0.14 23.94 2.81 24848.17 490.87 30.66 11.75 116.37 18.64

C1 7.09 16.87 0.29 0.01 14.94 0.70 21654.91 1463.93 10.08 0.12 75.32 4.09

B3 7.28 30.88 0.29 0.03 19.90 4.37 23460.17 2373.94 63.22 4.21 110.61 14.79

B2 7.27 26.04 0.28 0.02 16.74 3.20 23444.41 2746.41 13.84 2.41 74.03 3.79

B1 7.38 26.88 0.29 0.06 18.56 1.69 24448.75 1450.79 13.49 1.33 81.97 7.06

A3 7.54 54.40 1.12 0.26 24.69 2.20 31963.10 2597.25 26.02 2.13 224.09 9.23

A2 7.38 45.00 2.07 0.46 31.53 1.17 28753.21 3505.90 28.25 4.20 261.42 54.06

A1 7.22 39.24 0.50 0.23 28.86 4.34 26605.02 1089.52 26.44 2.45 128.64 9.80

G1 7.50 52.24 0.51 0.17 23.67 4.00 28872.79 3550.03 15.82 2.29 98.08 15.67

Tinnacross Stream

Cd Zn PbFeCu

(µg/g) (µg/g)(µg/g)(µg/g)( µg/g)

River Clody

Ballingale Stream

Ballycarney Stream

River Bann

River Urrin

River Boro

River Clonmore

Tinnokilla Stream

Ballyedmond Stream

14

There is great variation in metal concentrations across the tested sites (Table 3.2; Figure 3.1).

The majority of metals are lower than the maximum German background levels, except for site

B3 (pb= 63.22 µg/g), site G2 (cd= 0.69 µg/g), site A3 (cd= 1.12 µg/g; zn = 224.09 µg/g) and site

A2 (cd= 2.07 µg/g; zn= 261.42 µg/g) (Table 1.1: Table 3.1). Exceedances in iron were based on

Canadian background levels (Table 1.1).These occurred at sites E3 (31036 µg/g), G2 (33548

µg/g), F1 (31572 µg/g) and A3 (31963 µg/g) (Table 3.1).

Table 3.2. Maximum, minimum, mean and median values for heavy metals in the Slaney sub-

catchment.

Overall the sites show low metal concentrations throughout the catchment, except for site B3,

which has a very high lead level, and site A2, which has a very high cadmium level.

pH Alkalinity Cd Cu Fe Pb Zn

Maximum 7.87 80.20 2.07 31.53 33548.88 63.22 261.42

Site G2 G2 A2 A2 G2 B3 A2

Minimum 6.98 10.48 0.12 14.37 16220.13 10.08 71.93

Site D1 D1 D1 D1 D2 C1 D2

Mean 7.30 31.79 0.48 21.53 26842.66 20.36 116.15

Median 7.26 28.16 0.37 21.78 26605.02 17.39 98.08

15

Figure 3.1. Mean heavy metal concentrations (µg g-1) in the riverine sediments of the sampled

sites, nested in sub-catchments of the Slaney catchment: (a) Pb, (b) Cd, (c) Fe, (d) Zn, (e) Cu.

16

The metal concentrations were compared to a variety of different factors; bedrock, stream order,

sub-catchment and Q-value.

3.2 Bedrock

Bedrock types are shown in Figure 1.2 and Table 3.3. There is a significant difference between

the concentrations of lead amongst the bedrock in the catchment area (d.f.(2,16): f-ratio= 4.85; p=

0.023). There is a significant difference between the concentration of lead in Ordovician volcanic

rock and lower-middle Ordovician slate, sandstone, greywacke, conglomerate (Bonferroni post

hoc test; p= 0.021).

There is a significant difference between the concentrations of copper amongst the bedrock in

the catchment area (d.f.(2,16): f-ratio= 4.27; p= 0.033). There is a significant difference between

the concentration of lead between Ordovician volcanic rock and lower-middle Ordovician slate,

sandstone, greywacke, conglomerate (Bonferroni post hoc test; p= 0.030).

There is no difference between bedrock and the concentrations of cadmium, zinc or iron.

Table 3.3. Non-chemical data relating to the Slaney sub-catchment.

Site no. Q- value Status Station type Stream Order Bedrock

A1 3 Moderate Operational 1 Silurian deep marine mudstone, greywacke and conglomerate

A2 2 Poor Pre WFD 2 Silurian deep marine mudstone, greywacke and conglomerate

A3 3 Moderate Pre WFD 2 Lower-Middle Ordovician slate, sandstone, greywacke, conglomerate

B1 4 Good Operational 1 Lower-Middle Ordovician slate, sandstone, greywacke, conglomerate

B2 4 Good Pre WFD 2 Lower-Middle Ordovician slate, sandstone, greywacke, conglomerate

B3 3 Moderate Operational 3 Ordovician volcanic rock

C1 4 Good Operational 1 Lower-Middle Ordovician slate, sandstone, greywacke, conglomerate

C2 3 Moderate Pre WFD 2 Lower-Middle Ordovician slate, sandstone, greywacke, conglomerate

C3 4 Good Pre WFD 3 Lower-Middle Ordovician slate, sandstone, greywacke, conglomerate

C4 3 Good Pre WFD 3 Silurian deep marine mudstone, greywacke and conglomerate

D1 5 High Surveillance 2 Lower-Middle Ordovician slate, sandstone, greywacke, conglomerate

D2 5 High Pre WFD 2 Lower-Middle Ordovician slate, sandstone, greywacke, conglomerate

E1 4 Good Operational 2 Lower-Middle Ordovician slate, sandstone, greywacke, conglomerate

E2 2 Poor Operational 2 Lower-Middle Ordovician slate, sandstone, greywacke, conglomerate

E3 3 Moderate Pre WFD 1 Lower-Middle Ordovician slate, sandstone, greywacke, conglomerate

F1 3 Moderate Pre WFD 1 Silurian deep marine mudstone, greywacke and conglomerate

F2 4 Good Operational 3 Ordovician volcanic rock

G1 2 Poor Operational 2 Lower-Middle Ordovician slate, sandstone, greywacke, conglomerate

G2 4 Good Operational 2 Silurian deep marine mudstone, greywacke and conglomerate

17

3.3 Stream Order

The stream order of the rivers was determined. The various streams and rivers have stream

orders from 1 to 4, with the main river channel scoring a 5 (Table 3.3). There is no significant

difference between the stream orders and the concentrations of any of the tested metals.

Patterns of downstream sediment concentrations varied for the rivers in the catchment. Between

sites A3 and A2 on the Clonmore River the concentration of all metals, apart from iron,

decreased in concentration downstream. Between sites C1, C3 and C4 on the Urrin River an

increase in downstream concentrations was observed for all metals. No other clear patterns for

river metal concentrations were found.

3.4 Sub-catchment

Streams were collated into rivers sub-catchments. Some streams joined directly to the main river

channel of the Slaney. For sub-catchment purpose, sites E1, E2 and E3 were joined to form the

Borris catchment and sites G2 and G1 were joined to form the Tinnacross catchment. Site A1

was isolated, so it was added to the Clonmore catchment.

A nested ANOVA was performed on the sub-catchments. For this analysis replicates were nested

in site and site was nested in sub-catchment. The results of this ANOVA were significant but due

to the uneven sample sizes, there is good reason to question them and so they are not published.

The reason for this is that the overall test was found to be significant but none of the post hoc

tests were found to be significant.

18

3.5 Q-value

The values for Q-values and their corresponding average metal concentration are given in Table

3.4.

Table 3.4. Mean metal concentrations and standard deviations across various Q-values.

3.5.1 Copper

There is a significant difference between the Q-values for copper (d.f.(3,15): f-ratio= 4.40; p=

0.0207). There is a significant difference between 5 and 2 (Bonferroni post hoc test; p=0.0455).

3.5.2 Iron, Zinc and Lead

There is no significant difference between the concentrations of lead, zinc or iron for the various

Q-values.

3.5.3 Cadmium

There is a significant difference between the Q-values for cadmium (d.f.(3,15): f-ratio= 5.69;p=

0.0083). There is a significant difference between 5 and 2 (Bonferroni post hoc test; p=0.0059), 5

and 3 (Bonferroni post hoc test; p=0.0372) and 5 and 4 (Bonferroni post hoc test; p=0.0331).

Q-values Mean SD Mean SD Mean SD Mean SD Mean SD

2 0.98 0.85 25.31 5.29 28812 2578.5 19.13 7.35 149.58 88.59

3 0.46 0.35 23.75 3.97 28253 3813.4 29.73 17.09 133.27 44.7

4 0.39 0.15 20.02 3.45 26542 4238 16.15 4.12 101.1 28.98

5 0.14 0.04 15.25 2.94 20860 5433 10.93 2.36 74.86 22.1

Cd Cu Fe Pb Zn

19

3.6 Co-occurrence

The correlation matrix of heavy metals (Table 3.5.) shows a high correlation between 1/√Zinc

and 1/√cadmium (0.754). These metals are likely to occur together. Conversely, copper and

1/√zinc (-0.816), and 1/√cadmium and copper (-0.728) have a high negative correlation and are

unlikely to occur together.

Table 3.5 Correlation matrix of heavy metals (Pearson-moment correlation)

1/√Zn 1/√Cd Pb Cu Fe

1/√Zn 1.000

1/√Cd 0.754 1.000

Pb -0.416 -0.266 1.000

Cu -0.816 -0.728 0.330 1.000

Fe -0.64 -0.459 -0.017 0.554 1.000

20

3.7 Enrichment Factors

The reference values used to calculate enrichment factors are based on Canadian background

levels and an average of the four lowest sediment values derived from the catchment, sites B3,

C1, D2 and B2 (Table 3.1).

The enrichment factors were calculated using calculations from Sutherland (2000). Enrichment

factors are defined as;

EF(X) = (X/N) sample

(X/N) control

Where, EF(X) is the enrichment factor for the metal X,

(X/N) sample is the ratio of the concentration of metal X to major metal N (Fe or

AL) in the sample,

(X/N) control is the ratio of the concentration of the metal X to major metal N (Fe or

Al) in a reference material such as the control sample.

Aluminium and Iron can be used as reference materials for normalisation due to their low levels

in anthropogenic discharges, compared to natural sources. In this study metals were normalised

to iron.

Most metals in this study fall into the category of no enrichment (EF≤1) or minimal enrichment

(EF<2). Under Canadian sediment enrichment factors (CSEF) there is moderate enrichment (EF

2 -5) at site A2 for cadmium, and sites F2, C2, B3, A3, A2 and A1 for zinc. Under catchment

background values there is moderate enrichment (EF 2 – 5) at A3 for cadmium and A2 for zinc.

There is significant enrichment (EF 5 – 20) at site A2 for cadmium (Table 3.6).

21

Table 3.6. Enrichment factors for each metal measured in the riverine sediment of the Slaney

catchment.

Site

(SEF) (CSEF) (SEF) (CSEF) (SEF) (CSEF) (SEF) (CSEF)

River Clody

D2 0.86 0.29 1.24 1.23 0.61 0.96 1.13 2.12

D1 0.38 0.13 0.71 0.7 0.35 0.55 0.78 1.45

Borris Stream

E1 1.02 0.35 1.07 1.05 0.54 0.84 0.86 1.61

E2 1.08 0.37 0.9 0.89 0.4 0.62 0.79 1.48

E3 0.62 0.21 0.83 0.82 0.36 0.56 0.76 1.42

River Bann

F1 0.51 0.17 0.98 0.97 0.52 0.82 1.03 1.92

F2 1.31 0.45 0.9 0.89 0.49 0.77 1.31 2.44

G2 1.69 0.58 0.83 0.82 0.44 0.69 1.04 1.94

River Urrin

C4 1.27 0.44 1.13 1.12 0.62 0.97 0.98 1.84

C3 1.03 0.35 0.95 0.94 0.73 1.15 0.94 1.76

C2 1.28 0.44 1.21 1.19 1.06 1.66 1.2 2.23

C1 1.12 0.38 0.86 0.86 0.4 0.63 0.89 1.66

River Boro

B3 1.02 0.35 1.06 1.05 2.32 3.63 1.2 2.25

B2 0.97 0.33 0.89 0.89 0.51 0.8 0.81 1.51

B1 0.99 0.34 0.95 0.94 0.47 0.74 0.86 1.6

River Clonmore

A3 2.89 0.99 0.97 0.96 0.7 1.1 1.79 3.34

A2 5.91 2.02 1.37 1.36 0.84 1.32 2.32 4.34

A1 1.55 0.53 1.36 1.35 0.85 1.34 1.24 2.31

G1 1.44 0.49 1.03 1.02 0.47 0.74 0.87 1.62

Tinnacross Stream

Tinnokilla Stream

Ballyedmond Stream

Cd Cu Pb Zn

Ballingale Stream

Ballycarney Stream

22

3.8 Geoaccumulation Index

The geo-accumulation index was calculated using the following equation by Müller (1979),

according to (Boszke et al., 2004);

Igeo = log2 (Cn / 1.5 Bn),

Where; Cn = Measured concentration of heavy metal in the sediment,

Bn = Geochemical background value in the catchment.

For the Bn value, the four sites with the lowest iron concentrations were averaged. The

corresponding sites were averaged for the other metals, regardless of their corresponding

concentrations.

Sites were graded according to Müller’s classification for the Geo-accumulation Index (Table

3.7). The geo-accumulation index, calculated for all sites, is shown in Table 3.8. Most sites were

graded as 0 (unpolluted). Six sites were graded 1 (none or minimal pollution) for several of the

metals. Site G2 for cadmium, site A2 for copper, sites C2, A3, A2 and A1 for lead and sites F2,

G2, A3 and A2 for zinc. Two sites were graded as a 2 (moderately polluted), site B3 for lead and

site A3 for cadmium. One site was graded as a 3 (moderately polluted to strongly polluted), this

was site A2 for cadmium.

Table 3.7. Müller’s classification for the Geo-accumulation Index (Boszke et al., 2004).

Igeo Class Sediment Quality

≤0 0

Unpolluted

0-1 1

From unpolluted to moderately polluted

1-2 2

Moderately polluted

2-3 3

From moderate to strongly polluted

3-4 4

Strongly polluted

4-5 5

From strongly to extremely polluted

>6 6 Extremely polluted

23

Table 3.8. Geo-accumulation index of heavy metals

Cluster analysis of the metal concentrations at the sites gives a good idea of the overall spatial

autocorrelation, but cannot provide us with statistical differences between them (Figure 3.3).

Figure 3.3. Cluster analysis of heavy metals in the Slaney catchment

Site Cd Cu Pb Zn Fe

B3 -0.81 -0.65 1.34 -0.3 -0.79

C4 -0.44 -0.52 -0.52 -0.55 -0.74

C3 -0.69 -0.72 -0.22 -0.55 -0.68

C2 -0.39 -0.38 0.29 -0.23 -0.7

C1 -0.78 -1.07 -1.31 -0.86 -0.9

E3 -1.12 -0.61 -0.96 -0.56 -0.38

E2 -0.42 -0.59 -0.91 -0.61 -0.49

F2 -0.07 -0.52 -0.52 0.19 -0.42

G2 0.44 -0.49 -0.55 0 -0.27

G1 -0.01 -0.4 -0.66 -0.48 -0.49

D2 -1.58 -0.96 -1.12 -0.92 -1.32

D1 -2.11 -1.12 -1.27 -0.81 -0.67

E1 -0.47 -0.32 -0.44 -0.46 -0.46

F1 -1.38 -0.35 -0.38 -0.1 -0.36

A3 1.15 -0.34 0.06 0.72 -0.34

A2 2.03 0.01 0.18 0.94 -0.49

A1 -0.02 -0.12 0.08 -0.08 -0.61

B2 -0.87 -0.9 -0.85 -0.88 -0.79

B1 -0.79 -0.75 -0.89 -0.73 -0.73

24

Discussion

4.1 Point and Diffuse Sources of Pollution

Point sources of pollution were identified in the area. There does not seem to be any pollution in

these areas caused by the presence of the WWTPs. These discharges may have affected the water

quality values determined by the EPA, but there is no significant difference between metal levels

in these sub-catchments due to these wastewater discharges. This is expected as sewage

treatment has the ability to remove up to 98% of metals from wastewater (Gray, 2004).

Mine sites in the area provide potential for point sources of pollution. Site B3 is heavily

influenced by the presence of an unused mine in Caim. Although the mine has been closed since

1846, the presence of quad biking on site has the potential to re-suspend dust and continue to

cause pollution, along with run-off and seepage from solid waste heaps (EPA, 2009). Site B3 is

the only site that shows substantial lead pollution. At the mine site contamination levels reach

highly polluted levels (56,028 mg/kg) (EPA, 2009). This represents a point source of

contamination in the catchment that is influencing the sediment metal burden at site B3.

Diffuse sources of pollution in the area are mainly agricultural in nature. Pesticides, fertiliser and

organic waste contain metals. Some commercial fertilisers are made from phosphate rock. The

mineralogical and geological nature of this phosphate rock means it can contain an array of

heavy metals like cadmium, lead, mercury and chromium, among others (Chandrajith and

Dissanayake, 2009; Mortvedt, 1995). Fertilisers also contain zinc as an essential micro-nutrient

(Mortvedt, 1993). If these compounds are not utilised correctly by plants or if they do not soak

adequately in the soil, the potential for contamination of nearby water bodies with surface run-

off is high. Contamination from diffuse pollutants like these is difficult to quantify over large

areas. The extent to which agricultural diffuse pollutants are responsible for the metal

concentrations in the river sediment is unclear. Only two sites in the study were classified as

discontinuous urban fabric, and so a comparison of rural and urban setting was not undertaken

(EPA, 2015d).

25

4.2 Trends in Downstream Concentration

There is no evidence to suggest that there is an increase in heavy metal concentration

downstream due to metal enrichment from soil and bedrock in the area.

An exception to this is site B3. The high lead concentration at this site can probably be attributed

to the presence of a nearby mine. This previously mentioned point source of pollution is a

considerable source of lead to the area.

There is a decrease in metal concentration between sites A2 and A3. The reason for this is

unclear. It is possible that this may have occurred through excess use of fertiliser products in the

area, and entered the river as land run-off. The European average of cadmium in fertiliser is 138

mg/kg phosphorus (FEI, 2000). The majority of the study area consists of agricultural land. The

Department of Agriculture, Food and Rural Development (DAFRD) (2000) regard soil with

cadmium values in excess of 1 mg/kg (threshold level) as polluted. The pollution in the

Clonmore River may have occurred as run-off of agricultural products from the land. This is not

shown in the rest of the catchment, however, despite the area being predominately agricultural

land.

4.3 Comparison with Non-Impacted Sites

Sediment in the catchment shows no distinct distribution pattern. Apart from previously

mentioned sites (B3, A2, A1), most sites are unpolluted.

A study done by Audry et al. (2004) proposed natural background levels of approximately ~17,

~82, ~0.33 and ~28 mg/kg for copper, zinc, cadmium and lead respectively for the Lot River in

France. These values are based on the bottom sediments of the furthest downstream core that

was sampled. The sites in the Slaney catchment exceed these levels in the majority of cases, but

by very little. Most of the exceedances were just above the values given for the Lot River. It is

clear that the metal burden of the Slaney catchment is similar to that of the background levels of

the Lot River.

Baptista Neto et al. (2000) have similar values recorded for background levels to the Lot river

study, with values of 6.3-17.5, 21.2-132, 13,750-29,750 and 15-40 ppm of copper, zinc, iron and

lead respectively. This study was undertaken in an estuarine area absent from industrialisation,

26

but with uncontrolled discharge of untreated sewage and urban surface run-off (Baptista Neto et

al., 2000). The values represent core sediment samples taken to estimate background metal

concentrations in the area. Again the Slaney has a similar metal burden to this estuary.

4.4 Similarity in Sub-catchments

The sediment metal burden is similar in most sub-catchments in the study, apart from the

Clonmore sub-catchment. The Clonmore sub-catchment has a higher burden due to the high

levels of zinc and cadmium at the sites. The addition of site A1 (Tinnokilla Stream) to the

catchment reduces the distinctiveness of the difference between the catchments. It is likely that

there are not many differences in metal burdens across sub-catchments due to the lack of point

source pollution and general spatial autocorrelation patterns.

4.5 Q-values and Water Quality Status

Appropriate levels of each metal could not be found to correspond with Q-values in the

catchment. In the case of cadmium, it was possible to distinguish between sites based on the

concentration in sediment. It is likely that this correspondence gives a false view of the ease with

which cadmium could classify a river into a Q-value category, based on concentration in the

sediment alone.

Only two sites were classified as Q-value 2. The range in cadmium concentration for these two

sites was 0.51-2.07 µg/g, and the standard deviation was very high (0.85) (Table 3.4). This range

is hidden by the averages in the statistical analysis, and therefore we should be wary of the

ability of cadmium to determine Q-values in the catchment. Copper shows differences between

sites with Q-values of 5 and 2, but this information is not beneficial in terms of utilising copper

as a reference for Q-values.

This could indicate that biota in at these sites remain relatively unaffected by the concentrations

of metal in the sediment, if sediment is an important habitat for some of the reference organisms.

Furthermore, it suggests that these metals are not present in a bio-available form for the

organisms. Previous studies show, and it has been generally accepted that total metal analysis

does not indicate accurately the mobility of metals, their bio-availability or their environmental

toxicity (Sutherland and Tack, 2003),

27

4.6 Bedrock

Bedrock in the catchment is predominately of Ordovician and Silurian age, with most sites

falling into the Ordovician slate, sandstone, greywacke, conglomerate category (Figure 1.2,

Table 3.3). The difference in the concentrations of lead and copper in the samples is between the

two Ordovician rock types. The significant difference in lead levels is probably skewed due to

the high concentration found at site B3 and the low sample size of Ordovician volcanic rock.

Taking this into account, copper levels are the only concentrations that are significantly different

between the rock types. This indicates that the bedrock is a factor in determining the levels of

copper in riverine sediment in the Slaney catchment.

As the correlation of bedrock type and heavy metal concentration is not true for lead, cadmium,

iron or zinc, this implies that bedrock may not be a compelling factor causing metal pollution in

the area.

4.7 Correlation Matrix of Metals

There is a strong correlation between zinc and cadmium in the catchment. This suggests that

these metals may originate from the same source. This may also be because zinc and cadmium

have a similar geological affinity and weathering behaviour (Baskaran, 2011). Strong negative

correlations between copper and zinc, and cadmium and copper indicate that these metals are

unlikely to occur together. These metals are generally not associated with the same mineral, and

copper tends to be less mobile than copper or zinc (Gäbler, 1997).

4.8 Enrichment Factors and Geo-accumulation Index

The enrichment factors and geo-accumulation index of heavy metals highlight the contaminated

sites in the catchment. The sediment does not appear to be heavily enriched compared to local

iron levels, apart from previously mentioned polluted sites (B3, A2, A1). Iron levels in the

catchment area are at naturally high concentrations (>3%) in the soil (EPA, 2015e). It would

appear that these types of analyses work best when the bedrock naturally contains high levels of

contaminant metals.

28

The use of these methods of analysis are limited however, as the average of the lowest iron

levels and metals at the corresponding sites were used, instead of pre-industrial metal levels,

which were not available for this study.

4.9 Cluster Analysis

Cluster analysis showed some distinctive grouping of sites. At 0.965 similarity it grouped sites as

group 1 [C3, D1, C2, C4, B1], group 2 [E3, F1, A3, F2, G2] and group 3 [E2, G1, A2, E1]

(Figure 4.1). At 0.90 similarity it grouped sites as group 4 [A1, B2, B3, C3, D1, C2, C4, B1, C1]

and group 5 [E3, F1, A3, F2, G2, E2, G1, A2, E1] (Figure 4.2).

Figure 4.1. Cluster analysis groupings at 0.97 similarity.

29

Figure 4.2. Cluster analysis groupings at 0.90 similarity.

It is unclear why site D2 remains as an outlier (Figure 3.3). A possibility for this is that it has the

lowest total metal burden in the catchment (Table 4.1). Site D2 has a metal burden of 16,320

(µg/g), the lowest in the catchment. The highest metal burden occurs at site G2, where combined

metal concentrations are over double that of site D2 (33,725 µg/g). Iron concentrations heavily

influence these burdens, but even in the absence of iron the metal burden is still lowest at site D2

(99.73 µg/g). The highest burden in the absence of iron is site A2 (323.26 µg/g). Clear groupings

can be seen both to the east and to the west of the main river channel. It is difficult to interpret

the reasons for such grouping but it is clear that there are patterns of distribution.

30

Table 4.1. Total metal burden for site in the Slaney catchment, calculated with and without iron

Total Metal Burden (µg/g)

Site Without Iron Including Iron

B3 194.02 23654

C4 133.06 24356

C3 133.94 25354

C2 171.36 25020

C1 100.64 21756

E3 126.26 31193

E2 123.66 28935

F2 194.97 30544

G2 176.46 33725

G1 138.08 29011

D2 99.73 16320

D1 102.63 25602

E1 143.03 29592

F1 171.25 31744

A3 275.93 32239

A2 323.26 29076

A1 184.45 26789

B2 104.89 23549

B1 114.32 24563

4.10 Limitations of this Study

Sites were chosen on the basis that the location was the same as the EPA water quality sampling

locations. This proved problematic as many of the sites were inaccessible for sediment sampling.

Due to this the number of sites sampled was drastically cut down. This provided uneven sample

sizes along rivers, and meant that sites could not be sampled based on discharges and inputs to

the river. The main river channel of the Slaney could not be sampled because of this. This made

it difficult to see downstream patterns in the concentrations of heavy metals in the catchment.

The organic content of the sediment was not analysed due to time constraints.

The fractionation of the metals in the sediment was not examined. Metals can be found in five

categories; an exchangeable fraction, bound to carbonate, bound to organic matter, bound to

reducible phases (iron and manganese) and residual metals (Jain et al., 2008). Metals in these

different states have dramatically different bioavailability and toxicity in rivers. Due to this we

31

can only speculate as to what effects these metal levels will have on the biota of the river. The Q-

values and metals concentrations suggest that this needs to be assessed further.

4.11 Formation of Sediment Quality Guidelines

The significant differences between the bedrock types for the metal concentrations indicate that

values based on the underlying bedrock may need to be taken into account in the formation of

these guidelines. From these studies and others, it is clear that one set of values for the entirety of

Europe may not serve the SQG best.

More studies need to be done to assess the baseline values for metal concentrations in Irish

rivers. Catchments with different bedrock geologies would be of particular interest, to determine

to what extent other bedrock influences riverine sediment metal concentrations.

Even with the baseline metal concentrations of rivers in Ireland, metal concentration does not

guarantee impact to flora and fauna. It is clear that bioavailability must be accounted for when

assessing the ecological impact of heavy metal burden in riverine sediment. It is clear that the

formation of these guidelines will be difficult and that more research into the best way to analyse

metal concentrations in river sediment is necessary.

32

Conclusion

This study indicates that there is minimal pollution in the sediment of rivers in the Slaney

catchment. There are three identified sites with metal contamination. One site (B3) is thought to

be polluted by a nearby disused lead mine. Two sites (A3 and A2) on the Clonmore River have

high levels of cadmium and zinc, the source of this pollution is not known. It is possible that the

excess use of fertilisers and other sources of diffuse pollution account for the levels of metals in

the river sediments.

If these rivers were to be assessed under the proposed SQG under the WFD, only three sites

would show mild pollution. Under these circumstances it would be better to study urban sites

and continue to monitor sites of known pollution unless new sources of metal pollution are

identified. A programme to continually monitor sediments in non-polluted areas would be an

inefficient use of resources. Sediments should be subject to once off sampling to determine areas

of pollution. These areas of pollution can be monitored, while unpolluted sites could be

monitored on a more infrequent basis.

This study provides useful data about the Slaney catchment, allowing for the first records of

baseline heavy metal concentrations in sediment for the area. Polluted areas of known and

unknown contamination have been identified. The metal concentrations in the catchment area do

not tend to correspond with the Q-values given for water quality. This highlights the importance

of sampling the sediment to ensure all compartments of the river system have been accurately

assessed. This data could be useful in the development SQG’s for Ireland and the South Eastern

River Basin District management plan.

33

References

APHA (2005). Standard Methods for the Examination of Water and Wastewater. 21st edition.

American Public Health Association. Washington, District of Columbia.

Audry, S., Schäfer, J., Blanc, G. and Jouanneau, J. M. (2004). Fifty-year sedimentary record of

heavy metal pollution (Cd, Zn, Cu, Pb) in the Lot River reservoirs (France). Environmental

Pollution, 132 (3), 413-426.

Baptista Neto, J. B., Smith, B. J. and McAllister, J. J. (2000). Heavy metal concentrations in

surface sediments in a nearshore environment, Jurujuba Sound, Southeast

Brazil. Environmental Pollution, 109 (1), 1-9.

Barnard, T.C., (1985). An Anglo-Irish industrial enterprise: iron-making at Enniscorthy, Co.

Wexford, 1657-92. Proceedings of the Royal Irish Academy. Section C: Archaeology,

Celtic Studies, History, Linguistics, Literature, 101–144.

Barry, A. (2015). Bedrock Geology in Slaney Catchment Area [Map, January 21]. Scale

1:1,000,000. Data Layers: EPA:Rivers; EPA: River Water Qualtiy 2004 to present; GSI:

Bedrock Geology 1:1 million;CSO: 2001 Census Population by County. Trinity College

Dublin. Using: ArcGIS Online [GIS]. Version 10.3. Redlands, CA: Esri, 2014.

Baskaran, M. (2011). Handbook of Environmental Isotope Geochemistry. Springer Science &

Business Media. Berlin.

Birch, G.F., Taylor, S.E. and Matthai, C. (2001). Small-scale spatial and temporal variance in the

concentration of heavy metals in aquatic sediments: a review and some new concepts.

Environmental Pollution, 113 (3), 357–372.

Boszke, L., Sobczynski, T., Glosinska, G., Kowalski, A. and Siepak, J. (2004). Distribution of

mercury and other heavy metals in bottom sediments of the Middle Odra River

(Germany/Poland). Polish Journal of Environmental Studies, 13 (5), 495-502.

Burton Jr, G. A. (2002). Sediment quality criteria in use around the world. Limnology, 3 (2), 65-

76.

34

Chandrajith, R. and Dissanayake, C. B. (2009). Phosphate mineral fertilizers, trace metals and

human health. Journal of the National Science Foundation of Sri Lanka, 37 (3), 153-165.

Chaperon, S. and Sauve, S. (2007). Toxicity interaction of metals (Ag, Cu, Hg, Zn) to urease and

dehydrogenase activities in soils. Soil Biology and Biochemistry, 39 (9), 2329–2338.

Crane, M. (2003). Proposed development of sediment quality guidelines under the European

Water Framework Directive: a critique. Toxicology letters, 142 (3), 195–206.

DAFRD (2000). Report: Assessment of risks to health and the environment from cadmium in

phosphatic fertilisers for the South Eastern Region of Ireland. Department of Agriculture,

Food and Rural Development.

Di Toro, D.M., Zarba, C.S., Hansen, D.J., Berry, W.J., Swartz, R.C., Cowan, C.E., Pavlou, S.E,

Allen, H.E., Thomas, N.A. and Paquin, P.R. (1991). Pre-draft technical basis for

establishing sediment quality criteria for non-ionic organic chemicals using equilibrium

partitioning. Office of Science and Technology. USEPA. Washington, District of

Columbia.

Duzzin, B., Pavoni, B. and Donazzolo, R. (1988). Macroinvertebrate communities and sediments

as pollution indicators for heavy metals in the River Adige (Italy). Water Research, 22

(11), 1353-1363.

EPA (2004). Ireland’s environment 2004. Environmental Protection Agency. Wexford.

EPA (2006). EU Water Framework Directive Monitoring Programme. Prepared to meet the

requirements of th EU Water Framework Directive (200/60/EC) and National Regulations

implementing the Water Framework Directive (S.I. No. 722 of 2003) and National

Regulations implementing the Nitrates Directive (S.I. No. 788 of 2005). Environmental

Protection Agency. Wexford.

EPA (2009). Historic mine sites- Inventory and risk classification volume 1. Environmental

Protection Agency. Wexford.

EPA (2014a). Report on river water quality in Wexford 2013. Environmental Protection Agency,

Wexford.

35

EPA (2014b). Focus on urban waste water treatment in 2012. Environmental Protection Agency.

Wexford.

EPA (2014c). Surface water quality: River water quality 2004-present. [map]. Environmental

Protection Agency. Availabe from: http://gis.epa.ie/Envision [Accessed 29 May 2014].

EPA (2015a). EPA river quality surveys: Biological. Available from:

http://www.epa.ie/qvalue/webusers/ [Accessed 27 February 2015].

EPA (2015b). Water regions: River catchments. [map]. Environmental Protection Agency.

Availabe from http://gis.epa.ie/Envision [Accessed 30 January 2015].

EPA (2015c). Water framework directive status: River waterbody status 2010-2012. [map].

Environmental Protection Agency. Availabe from http://gis.epa.ie/Envision [Accessed 24

February 2015].

EPA (2015d). Land: corine 2012. [map]. Environmental Protection Agency. Availabe from

http://gis.epa.ie/Envision [Accessed 24 February 2015].

EPA (2015e). National soils database: Iron (Fe). [map]. Environmental Protection Agency.

Availabe EPA GIS, http://gis.epa.ie/Envision [Accessed 24 February 2015].

European Commission (2000). Directive 2000/60/EC of the European Parliament and of the

Council of 23 October 2000 establishing a framework for community action in the field of

water policy. L327, 1-72, 22nd December 2000. Official Journal of the European

Communities. Brussels.

European Commission (2001). Decision No 2455/2001/EC of the European Parliament and of

the Council. Establishing the list of priority substances in the field of water policy and

amending directive 2000/60/EC. Official Journal of the European Communities. Brussels.

FEI (2000). Cadmium in fertilisers: Risk to human health and the environment. Study report for

the Finnish Ministry of Agriculture and Forestry October 2000. Finnish Environment

Institute. Helsinki.

Gäbler, H. E. (1997). Mobility of heavy metals as a function of pH of samples from an overbank

sediment profile contaminated by mining activities. Journal of Geochemical

Exploration, 58 (2), 185-194.

36

Gardiner, M.J. and Ryan, P. (1969). A new generalised soil map of ireland and its land-use

interpretation. Irish Journal of Agricultural Research, 95–109.

Gray, N. F. (2004). Biology of Waste Water Treatment. 2nd edition. Imperial College Press.

London.

Gray, N.F. (2010). Water technology: An Introduction for Environmental Scientists and

Engineers. 3rd edition. IWA Publishing. London.

Hammer, Ø., Harper, D.A.T. and Ryan, P.D. (2001). PAST: Paleontological statistics software

package for education and data analysis. Palaeontologia Electronica 4 (1), 9.

Harada, M. (1978). Congenital Minamata disease: intrauterine methylmercury poisoning.

Teratology, 18 (2), 285–288.

Jain, C. K., Gupta, H. and Chakrapani, G. J. (2008). Enrichment and fractionation of heavy

metals in bed sediments of River Narmada, India. Environmental Monitoring and

Assessment, 141 (1-3), 35-47.

Lietz, W. and Galling, G. (1989). Metals from sediments. Water Research, 23 (2), 247-252.

Mance, G. (1987). Pollution Threat of Heavy Metals in Aquatic Environments. Elsevier. New

York.

Mayes, E. and Codling, I. (2009). Water Framework Directive and related monitoring

programmes. Biology & Environment: Proceedings of the Royal Irish Academy, 109 (3),

321-344. The Royal Irish Academy.

Mortvedt, J. J. and Gilkes, R. J. (1993). Zinc fertilizers, in Zinc in Soils and Plants (pp. 33-44).

Springer Netherlands.

Mortvedt, J. J. (1995). Heavy metal contaminants in inorganic and organic fertilizers. Fertilizer

Research, 43 (1-3), 55-61.

Müller, G. (1979). Schwermetalle in den sedimenten des Rheins-Veränderungen seit 1971.

Umschau, 79 (24), 778–783.

Muyssen, B. T. A., Brix, K. V., Deforest, D. K. and Janssen, C. R. (2004). Nickel essentiality

and homeostasis in aquatic organisms. Environmental Reviews, 12, 113-131.

37

OPW (2015). National flood hazard mapping. Office of Public Works. Available from:

http://www.floodmaps.ie/View/Default.aspx [Accessed 15 February 2015].

O’Reilly, P. (2004). Rivers of Ireland- A Fly Fisher’s Guide. 6th edition. Merlin Unwin Books.

Ozonzeadi, M. and Uzoamaka, N. (2014). River Sediment Sampling and Environment Quality

Standards: A Case Study of the Ravensbourne River. Thesis (PhD). University of

Westminster.

Petersen, W., Willer, E. and Willamowski, C. (1997). Remobilization of trace elements from

polluted anoxic sediments after resuspension in oxic water. Water, Air, and Soil Pollution,

99 (1-4), 515–522.

Slaney River Trust (2014). News July 10, 2014. Available from:

http://www.slaneyrivertrust.ie/?page_id=68 [Accessed 20 January 2015].

SERDB (2003). South Eastern river basin management plan initial characterisation report.

South Eastern River Basin District. Carlow.

Sternbeck, J. and Östlund, P. (2001). Metals in sediments from the Stockholm region:

Geographical pollution patterns and time trends. Water, Air and Soil Pollution: Focus, 1

(3-4), 151-165.

Sutherland, R.A. (2000). Bed sediment-associated trace metals in an urban stream, Oahu,

Hawaii. Environmental Geology, 39 (6), 611–627.

Sutherland, R. A. and Tack, F. M. G. (2003). Fractionation of Cu, Pb and Zn in certified

reference soils SRM 2710 and SRM 2711 using the optimized BCR sequential extraction

procedure. Advances in Environmental Research, 8, 37- 50.

Thornton, I., Ramsey, M. and Atkinson, N. (1995). Metals in the global environment: facts and

misconceptions, International Council on Metals in the Environment.

Vandecasteele, B., Quataert, P., De Vos, B. and Tack, F. M. (2004). Assessment of the pollution

status of alluvial plains: a case study for the dredged sediment-derived soils along the Leie

River. Archives of Environmental Contamination and Toxicology, 47 (1), 14-22.

Walsh, S, (2012). A summary of climate averages for Ireland. Met Eireann, Dublin.

38

WCC (2010). Bunclody and environs agglomeration licence register number: FD0030-01,

Annual environmental report. Wexford County Council. Wexford.

WCC (2013). County Wexford Biodiversity action plan 2013-2018. Wexford County Council.

Wexford.

WCC (2015). Sewerage services. Wexford County Council. Available from:

http://www.wexford.ie/wex/Departments/WaterServices/SewerageServices/ [Accessed 2

February 2015].

WFD Ireland (2010a). River basin management plans 2010, Slaney lower water management

unit. Water Framework Directive Ireland. Available from: http://www.wfdireland.ie/docs/

[Accessed 5 October 2014].

WFD Ireland (2010b). River basin management plans 2010, Slaney Estuary water management

unit. Water Framework Directive Ireland. Available from: http://www.wfdireland.ie/docs/

[Accessed 5 October 2014].

WFD Ireland (2010c). River basin management plans 2010, Boro-Urrin water management unit.

Water Framework Directive Ireland. Available from: http://www.wfdireland.ie/docs/

[Accessed 5 October 2014].

Wilcock, D. N. (1999). River and inland water environments, in Nath, B., Hens, L., Compton, P.

and Devuyst, D. eds. Environmental Management in Practice Volume 3. Routledge, New

York, pp. 328.

Williams, J. (2011). The Affair at Clonmines, in Robert Recorde, Tudor Polymath, Expositor

and Practitioner of Computation. Springer. London. pp. 35–52.

Woitke, P., Wellmitz, J., Helm, D., Kube, P., Lepom, P. and Litheraty, P. (2003). Analysis and

assessment of heavy metal pollution in suspended solids and sediments of the river

Danube. Chemosphere, 51 (8), 633-642.

Yau, H. and Gray, N.F. (2005). Riverine sediment metal concentrations of the Avoca--

Avonmore Catchment, South-East Ireland: A baseline assessment. Biology &

Environment: Proceedings of the Royal Irish Academy. 105B (2), 95–106.

39

Appendices

Appendix 1. Example of Sample Site (C4).

40

Appendix 2. Raw data from ICP:AES analysis.

Tube Sample Labels Cd (A) 228.802 Cu (A) 327.396 Fe (A) 260.709 Pb (A) 220.353 Zn (A) 213.856

S:2 Standard 1

S:3 Standard 2

S:4 Standard 3 5 5

S:5 Standard 4 0.5 2.5 2.5 2.5

S:6 Standard 5 0.2 1 1 1

S:7 Standard 6 0.05 0.25 0.25 0.25

S:8 Standard 7 500

S:9 Standard 8 300

S:10 Standard 9 100

S:11 Standard 10 10

S:1 Blank 0 0 0 0 0

01:01 QC Check Solution 3 1.001 0.98 0.042 0.966 1.013

01:02 QC 7 -0.001 -0.009 41.324 -0.011 -0.006

01:03 C2.1 0.015 0.573 696.24 0.478 2.771

01:04 C2.2 0.006 0.448 511.87 0.417 1.813

01:05 E2.1 0.011 0.535 707.93 0.343 2.33

01:06 E2.2 0.007 0.507 713.1 0.341 2.264

01:07 E3.1 0.006 0.659 945.01 0.408 2.964

01:08 E3.2 0.004 0.473 720.74 0.29 2.234

01:09 B3.1 0.008 0.643 649.28 1.671 3.278

01:10 B3.2 0.008 0.496 651.38 1.762 3.021

01:11 QC Check Solution 3 0.987 1.003 0.961 1.012

01:12 QC7 40.92

01:13 B3.3 0.008 0.5 640.65 1.812 2.978

01:14 C3.1 0.007 0.502 600.1 0.558 2.235

01:15 C3.2 0.012 0.529 729.8 0.785 2.95

01:16 C3.3 0.006 0.448 637.51 0.353 2.253

01:17 F1.1 0.004 0.596 813.37 0.442 3.2

01:18 F1.2 0.005 0.523 676.27 0.408 2.836

01:19 F1.3 0.005 0.67 800.87 0.543 3.332

01:20 D1.1 0.003 0.404 748.43 0.275 2.388

01:21 D1.2 0.003 0.329 601.55 0.248 1.894

01:22 QC Check Solution 3 0.991 0.986 0.951 0.997

01:23 QC 7 40.539

01:24 D1.3 0.003 0.374 624.76 0.272 1.898

01:25 G2.1 0.016 0.454 726.42 0.355 3.081

01:26 G2.2 0.021 0.665 948.89 0.488 4.051

01:27 G2.3 0.014 0.538 797.49 0.419 3.082

01:28 D2.1 0.003 0.298 337.15 0.208 1.174

01:29 D2.2 0.006 0.564 490.16 0.418 3.107

01:30 D2.3 0.004 0.372 402.16 0.257 1.432

01:31 G1.1 0.007 0.434 559.52 0.417 1.854

01:32 G1.2 0.013 0.611 702.61 0.327 2.498

01:33 G1.3 0.014 0.55 683.16 0.323 2.395

01:34 A1.1 0.015 0.514 584.44 0.609 2.934

01:35 A1.2 0.014 0.761 689.36 0.689 3.471

01:36 QC Solution 3 0.971 0.978 0.918 0.976

01:37 QC 7 39.92

01:38 A1.3 0.006 0.778 604.46 0.566 2.819

01:39 A2.1 0.05 0.69 704.34 0.675 6.648

41

01:40 A2.2 0.043 0.856 688.2 0.65 5.57

01:41 A2.3 0.068 0.927 844.84 0.878 8.224

01:42 E1.1 0.014 0.619 710.26 0.342 2.683

01:43 E1.2 0.005 0.5 606.22 0.443 1.911

01:44 E1.3 0.006 0.571 669.29 0.448 2.255

01:45 A3.1 0.018 0.497 748.27 0.602 4.675

01:46 A3.2 0.036 0.731 830.74 0.702 6.334

01:47 A3.3 0.032 0.634 805.05 0.639 6.001

01:48 QC3 0.967 0.96 0.933 0.983

01:49 Q7 39.698

01:50 Control -0.002 -0.001 -0.918 -0.009 0.029

01:51 B1.1 0.006 0.452 647.26 0.348 2.148

01:52 B1.2 0.008 0.473 594.03 0.344 2.118

01:53 B1.3 0.007 0.414 528.14 0.283 1.798

01:54 C1.1 0.008 0.374 519.88 0.265 1.897

01:55 C1.2 0.009 0.506 736.89 0.322 2.604

01:56 C1.3 0.006 0.297 445.88 0.203 1.568

01:57 B2.1 0.007 0.38 549.5 0.389 1.925

01:58 B2.2 0.008 0.454 676.18 0.341 2.205

01:59 B2.3 0.009 0.625 814.23 0.46 2.421

0.08 E3.3 0.007 0.401 640.34 0.263 1.845

02:01 F2.1 0.013 0.518 781.18 0.414 3.978

02:02 F2.2 0.016 0.706 943.55 0.59 4.926

02:03 F2.3 0.013 0.69 922.23 0.523 4.803

02:04 C4.1 0.008 0.503 474.16 0.395 1.966

02:05 C4.2 0.012 0.582 686.51 0.468 2.757

02:06 C4.3 0.009 0.588 722.15 0.482 2.652

02:07 C2.3 0.006 0.487 485.87 0.793 2.303

02:08 C2.4 0.008 0.678 633.87 0.889 3.541

02:09 Control -0.001 -0.003 -0.892 -0.012 0.064

02:10 E2.3 0.012 0.574 828.75 0.351 2.499