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
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
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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
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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.
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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
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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
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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
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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).
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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.
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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)
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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
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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).
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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
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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