Embed Size (px)
Citation preview
www.elsevier.com/locate/envint
Environment International 29 (2003) 935–948
Heavy metal distribution and controlling factors within coastal plain
sediments, Bells Creek catchment, southeast Queensland, Australia
Tania Liaghati*, Micaela Preda, Malcolm Cox
Received 24 November 2002; accepted 27 February 2003
Abstract
Bells Creek catchment in southeast Queensland (Australia) is a non-industrialised coastal plain limited to small settlements and agricultural
land. A study was initiated to examine elevated metal concentrations and to assess horizontal and vertical distribution of those elements. Ninety-
nine samples were analysed for Cr, V, Ni, Cu, Zn, Pb, As, Fe, Mn and Al. Total organic carbon, sulfur content and mineralogy of samples along
with land-use practices across the catchment were used to identify processes which influence metal distribution. A comparison between metal
concentration within the study area and mean heavy metal content of standard sandstone showed that except for Mn, all other metals showed
elevated levels throughout the catchment.Whenmetal concentrations were compared to parent bedrock, however, it was concluded that elevated
levels are likely to be natural. A normalisation procedure was applied to the data set and this analysis validated that elevated trace metal
concentrations in most samples are not due to artificial contamination. While surficial estuarine sediments were only enriched in V, soils were
dominantly enriched in Cr, Zn and V. Overall, geochemistry and mineralogy of the samples show the effect of both natural and anthropogenic
inputs to the catchment, however, natural processes are more dominant than anthropogenic inputs in concentrating metals.
D 2003 Elsevier Ltd. All rights reserved.
Keywords: Trace metals; Fluvial/estuarine sediments; Geochemistry; Mineralogy; Bells creek catchment; Normalisation; Enrichment factor
1. Introduction
Estuarine and marine sediments are sinks for various
metals transported from the land. Metals may be mobilised
as a result of natural processes (e.g. weathering and erosion
of geological formations) as well as by anthropogenic
activity. In the mobilisation process, trace elements may
be adsorbed by clays, can complex with organic compounds
or may co-precipitate with oxides and hydroxides. As many
metals occur naturally in weathered materials and drainage
systems due to their presence in local rocks, the relative
influence of natural and anthropogenic sources on the geo-
chemistry of coastal sediments is not always clear. There-
fore, for a better assessment of metal distributions within
such environment, it is important to distinguish between
metallic elements released by natural processes and those
introduced by human-related activities.
The amounts of trace elements in natural systems can be of
environmental significance because where elevated they may
0160-4120/$ - see front matter D 2003 Elsevier Ltd. All rights reserved.
doi:10.1016/S0160-4120(03)00060-6
* Corresponding author. Tel.: +61-7-3864-4185; fax: +61-7-3864-
1535.
E-mail address: [email protected] (T. Liaghati).
contaminate surface and shallow groundwater. In addition,
marine organisms and vegetation in coastal environments can
uptake metals, increasing the potential for the entry of some
metals into the food chain. Furthermore, while sediment data
is useful for describing trace metal occurrence and assessing
their distribution in coastal plains, in spatial or vertical trend
studies such as the present investigation, errors associated
with sampling and analysis can make it difficult to detect
differences between sites (e.g. Kelly et al., 1994).
To establish the potential environmental impact of con-
taminated sediments, vertical sediment profiles obtained by
coring are important because they can preserve the historical
sequence of pollution and, at the same time, enable a reaso-
nable estimation of the background levels and the variations
in input of pollutants over an extended period of time. Vertical
sediment sections provide a record of level of contamination
over time, if pollutants are persistent and the sediment stratum
has not been greatly disturbed by human activities such as
dredging (e.g. Forstner et al., 1984; Fung, 1993).
Preda and Cox (2000) conducted a baseline study of trace
metal distribution in the Pumicestone coastal area of south-
east Queensland. That study showed that regardless of the
sample origin and composition (bedrock, estuarine sediment,
soil or mangrove tissue), metal occurrence is systematic
T. Liaghati et al. / Environment International 29 (2003) 935–948936
which suggests an interaction between various natural sys-
tems. With respect to controls over adsorption and mobilisa-
tion of trace metals, the above study looked only at the
influence of grain size, and iron and manganese oxides. This
current study examines the occurrence and distribution of
metals within a sub-catchment of the Pumicestone region in
detail and investigates other factors which could control
metal chemical behaviour; factors considered are sediment
source (fluvial/estuarine), organic matter as organic carbon,
mineralogy (with special regard to clay speciation) and local
land-use practices (for example, pine plantations versus
native vegetation). Thus, the present study complements
previous investigations (Cox et al., 2000; Preda and Cox,
2000) that have focused on the geological settings and
occurrence of minor and trace metals within a broader area.
A range of studies have been conducted on trace metal
distribution in estuarine and coastal plain sediments
throughout the world. The majority of these studies, how-
ever, have concentrated on polluted areas with the objective
of describing trace metal concentration levels and/or iden-
tify sources of the pollutants (e.g. Ellaway et al., 1982;
Daskalakis and O’Connor, 1995; Schneider and Davey,
1995; Angelidis and Aloupi, 1997; Data and Subramanian,
1998; Power et al., 1999; Angelidis and Aloupi, 2000;
Owen and Sandhu, 2000; Chen et al., 2001; Ruiz, 2001;
De Carlo and Anthony, 2002). Determining background
metal levels in unpolluted areas, however, has not been
studied widely. Identifying naturally elevated metal concen-
tration is important because some metals can appear to be
enriched, although when compared to their source (e.g.
bedrock material), it is concluded that such elevation may
still be natural. Some studies have examined background
Fig. 1. Location of the study area in
levels (e.g. Windom et al., 1989; McMurtry et al., 1995),
and others have concentrated on identifying the major
factors which influence the geochemical character of sedi-
ments, their mobility and transport processes (Forstner et al.,
1982, 1984; Arakel and Hongjun, 1992). In addition,
broader studies on the natural physico-chemical processes
which affect metal levels within heterogeneous coastal
settings are scarce. Here we report an investigation into
the spatial and vertical distribution of trace elements within
a subtropical catchment; the study aimed to assess factors
such as land-use practices and sediment/soil character and
their role over trace metal concentrations within a non-
industrialised coastal plain. From a geochemical point of
view, the ability to establish the average composition of
metals in parent rock material is significant, as it can be used
as a basis for comparison and recognition of anomalous
concentrations of metals in soils and sediments. These metal
concentrations in soils and sediments were therefore com-
pared to parent material to identify enrichment in a setting
with potentially low levels of pollution and a variety of
material textures and land-use practices. Due to high varia-
tion in sediment characteristics, however, the large geo-
chemical data set produced could not be interpreted using
absolute concentration values in isolation. Thus, to enable a
more effective interpretation, a normalisation procedure was
applied to the data set.
2. Features of the study area
The study area is the Bells Creek catchment, which is
located 80 km north of Brisbane (Fig. 1) and is com-
relation to Pumicestone region.
T. Liaghati et al. / Environment International 29 (2003) 935–948 937
prised of three sub-catchments: Bells, Lamerough and
Halls (Fig. 2). This catchment is within the northern part
of the broader Pumicestone Catchment and drains into
Pumicestone Passage.
Pumicestone Passage forms a unique tidal water body in
southeast Queensland. It is semi-enclosed and occurs
between the narrow coastal plain of the mainland and Bribie
Island, a large sand barrier island. The mainland coastal
plain is underlain by sandstone bedrock (Preda et al., 2000).
The large input of suspended material carried by the 10
creek systems that flow into the passage has the potential to
contain nutrients and metals, which can affect local water
quality.
2.1. Geological setting
The Bells Creek coastal plain developed in the Late
Quaternary as a result of fluvial and marine processes. As
the sea level rose during the last marine transgression, the
river channel and floodplain drowned with formation of
estuarine settings. Overall, the highest sea level was
Fig. 2. Sampling sites with respect to surficial material
reached around 6500 years ago (Williams et al., 1998);
in the Pumicestone region, sea level fell to its present
position around 3000 years BP (Flood, 1981; Lester,
2000). The estuarine sedimentary units that formed due
to changing sea levels are important local features of this
coastal plain.
Landsborough Sandstone (Triassic–Jurassic) is the dom-
inant bedrock throughout the Pumicestone region. The
formation consists of quartzo-feldspathic sandstone with
significant amounts of lithic fragments of volcanic origin
and minor shale, pebble conglomerate and coal, deposited
in a Mesozoic fluvial environment (e.g. Murphy et al.,
1987). The mineralogy of this bedrock is significant, as it
is likely to have strongly influenced the natural background
levels of the metals investigated here (e.g. Preda and Cox,
2001).
Based on a report produced by Geological Survey of
Queensland (1999) and a soil survey conducted for the
study area (NSR Environmental Consultants, 1999b), four
distinct soil types were identified throughout the area: (1)
alluvial, (2) sand of marine origin, (3) organic clay and (4)
(after NSR Environmental Consultants, 1999a,b).
T. Liaghati et al. / Environment International 29 (2003) 935–948938
weathered bedrock (soils developed from the weathering
sandstone bedrock). The ‘‘organic clay’’ in the region varies
from clayey sand to medium heavy clay and typically occurs
below 80 cm depth (Fig. 2).
2.2. Climate and land use
The climate of the Bells Creek catchment like most of
southeast Queensland is subtropical humid with hot wet
summers and mild dry winters. Average monthly rainfall in
1998–1999 was 242 mm with the highest rainfall occur-
ring in late summer and autumn. Mean daily temperatures
range from 15 to 30 jC in summer and 9 to 20 jC in
winter.
Within the region there is a wide range of land-use
practices including pasture, forestry (pine plantation and
associated milling and timber processing), as well as urban
and rural residential; coastal native vegetation largely con-
sists of mangroves, Melaleuca and heath. Land-use patterns
within the catchment are changing continually, largely due
to population growth. As a result, from 1974 to 1991, the
amount of native vegetation decreased dramatically as other
land uses such as pine plantation and urban development
increased (NSR, 1999a) (Fig. 3).
Fig. 3. Land-use practices throughout
3. Sampling strategy and analytical methods
3.1. Sampling design
The following materials were analysed in this study to
determine the distribution of trace and major metals within
sediments of the catchment and to examine the effect of
various land-use and geological settings.
1. Bedrock samples (Landsborough Sandstone): to establish
the natural occurrence of trace metals (22 samples from 7
cores).
2. Soil samples of fluvial/estuarine origin referred to as
‘soils’: located above the water table and currently away
from direct tidal influence (53 samples from 15 cores).
3. Recent surficial fluvial/estuarine sediments referred to as
‘sediments’: 21 samples collected along the three major
creeks discharging into Pumicestone Passage.
3.2. Sample collection
Grab sediment samples (category 3) were collected from
creek banks; samples were analysed for extractable cations,
organic C, total S and mineral composition. Bedrock and
catchment and soil sample sites.
Table 1
Recovery of total metal concentration (mg/kg)
Element Certifieda Foundb Recovery
(%)
Precision
(%RSD)
V 133F 5 62F 1.7 46.6 3
Cr 90.7F 4.6 42F 1.2 46.3 3
Mo 5.43F 0.28 3.4F 0.4 62 12
Co 11.5F 0.3 8.2F 0.3 71 4
Ni 39.5F 2.3 25F 0.7 63 2
Cu 310F 12 289F 6 93 2
Zn 364F 23 346F 8 95 2
Pb 183F 8 166F 7 91 4
As 26.2F 1.5 21F 0.5 80 2
Fe 40,900F 6000 27,628F 828 68 3
Mn 440F 19 208F 6 47.3 3
Al 66,200F 3200 13,385F 534 20 4
a Certified Standard Reference Material, PACS-2 (harbour sediment,
Canada).b
T. Liaghati et al. / Environment International 29 (2003) 935–948 939
soil samples (categories 1 and 2) were powdered archive
material, provided by Queensland Acid Sulfate Soils Inves-
tigation Team (QASSIT). These samples were collected
from auger holes as part of a large program, the purpose
of which was to map pyritic sediments in southeast Queens-
land in 1997.
3.3. Physical and chemical analyses
Sediment pH was measured in the laboratory by inserting
a probe into unconsolidated samples which had been stored
under refrigeration. Extractable cations were analysed on
total sample, dried to 80 jC, by digesting the sediment in
aqua regia [1:3 nitric acid (HNO3)/hydrochloric acid (HCl)]
following a procedure described by Loring and Rantala
(1992). This acid mixture is significant in the above proce-
dure because it is not able to attack the silicate lattice, and
therefore, only cations absorbed by clays, organic matter and
oxides are extracted into solution and can be analysed. The
trace elements analysed included: V, Cr, Mo, Co, Ni, Cu, Zn,
Pb and As; minor metals analysed included: Fe, Mn and Al.
Extractable Al represents clay minerals, therefore, is consid-
ered to be a measure of grain size (Chao, 1984; Koljonen and
Malisa, 1991; Raisanen, 1996; Osterhom and Astrom, 2002).
Quantification was achieved using a Varian Liberty 200
inductively coupled plasma optional emission spectrometer
(ICP-OES). The instrument was calibrated using synthetic
standards and a reagent blank (Loring and Rantala, 1992).
Total S was measured using LECO and total organic carbon
(TOC) concentrations were obtained by digesting 0.5 g of
sample with dichromate according to the method of Walkey
and Black (in Loring and Rantala, 1992).
3.4. Quality control procedures
The precision and recovery level of the analytical proce-
dure for acid digestion (aqua regia) and metal determination
by ICP-OES were tested using marine sediment reference
standard PACS-2 (National Research Council Canada). This
is a certified material (CRM) for total digestion, as no CRM
was available for the extractable method using aqua regia.
Recoveries of most metals from the reference material were
>60%, except for V, Cr, Al and Mn (Table 1); vanadium and
Cr are refractory metals, which strongly adsorb to siliceous
materials. Moreover, Al is part of the aluminosilicate matrix
and the aqua regia digestion method is not robust enough to
extract these metals. A low recovery percentage for Cr and Al
had also been recorded by previous workers using similar
digestion method (Tam and Yao, 1998). Higher recovery can
be obtained if perchloric or hydrofluoric acids are used;
however, such digestion will bias results for environmental
assessment. Mean and standard deviations of the replicate
samples were calculated. A comparison between the standard
deviation of certified samples and replicate samples in this
study revealed that repeatability generally was < 5 (%RSD)
even when recoveries were low (Table 1).
3.5. Mineralogical analyses
Mineral composition of bedrock and unconsolidated
material was determined using X-ray diffraction (Philips
PW 1050 diffractometer equipped with a cobalt anticathode)
on non-oriented samples and on oriented specimens for clay
identification. Quantification of mineral phases was assisted
by SIROQUANT (quantification program which expresses
the composition of crystalline material within a sample as
percentage of dry weight).
3.6. Statistical methods
3.6.1. Descriptive data analysis and correlation coefficient
Descriptive data analyses (mean, standard deviation,
maximum and minimum concentrations) were carried out.
In addition, correlation factors were calculated to determine
relationships among different metals. Understanding such
relationships may help to clarify the path by which individ-
ual metals are carried and deposited within the estuary and
helps to determine the processes involved. Metal oxides
such as iron oxyhydroxides and manganese oxides, and
organic carbon commonly act as scavengers for heavy
metals. Therefore, correlations between any metal oxides
and individual heavy metals may help to understand the
processes which result in particular metal associations. As
geochemical data such as those produced in this study are
not normally distributed, Spearman’s rank correlations were
used as they are more appropriate than a simple linear
correlation (e.g. Pearson). Descriptive analysis was pro-
duced using Excel v.2000 and Spearman’s correlation
matrix was generated using SPSS v.10.
3.6.2. Normalisation procedure
It is well established that trace metals may be introduced
to coastal environments by both natural processes (e.g.
weathering and erosion) and human activities within the
catchment or adjacent to the coast (e.g. McConchie et al.,
Mean and standard deviation of three replicated extractions are shown.
Table 2
Concentration ranges of trace elements in different material types
Metals Mean heavy metal
content of standard
sandstone (mg/kg)
Concentration (mg/kg and % for S and TOC)
(a) (b)
(1) Bedrock,
n= 25
(2) Recent
estuarine
sediment,
n= 21
(3) Soils,
n= 53
V 30 nr 1.8–40.8 2.2–33 0.4–47.7
Cr 35 120 1.7–16.2 1.0–26.0 1.0–47.0
Mo 0.2 nr 1–14.4 1–4.9 1–15.3
Co 0.3 nr 1.2–3.3 1.2–4.7 1.2–6.6
Ni 9 nr 1.5–4.7 1.5–6.4 1.5–15.0
Cu 30 15 0.5–14.5 0.5–5.8 0.5–9.6
Zn 30 16 20.6–53.9 18.2–68.0 16.8–62.9
Pb 10 14 3–18.6 3–7.3 3–17.3
As 1 1 3–8.4 3–10.8 3–13.7
Fe nr 19,000 7600–27,000 9400–41,000 1800–35,000
Mn 460 392 0.4–20.8 0.4–229 0.4–45.0
Al nr 32,000 537–19,342 955–9821 210–28,112
S – – < 1–0.1 < 1–0.6 < 1–1.5
TOC – – < 1–8.6 0.3–5.5 < 1–10.3
(a) Adapted from Krauskopf (1967), Rose et al. (1979) and Alloway (1995).
(b) Leckie and Parks (1978).
nr = not reported.
T. Liaghati et al. / Environment International 29 (2003) 935–948940
1988; Chakrapani and Subramanian, 1993; Niencheski et
al., 1994; Balls et al., 1997; Power et al., 1999; Rubio et al.,
2000; Preda and Cox, 2001; Ruiz, 2001). Estuarine and
coastal sediments, which act as sinks for these metals, are
regarded as a mixture of inorganic and organic material. For
some metals, however (e.g. Cd and Hg), organic material
may be a metal carrier, but due to its low abundance ( < 5%
by weight) in most sediments, it is not usually considered as
major contributor to total metal levels (Loring, 1991).
Concentration of trace elements in natural estuarine and
coastal marine sediments are largely determined by inor-
ganic material resulting from physical and chemical weath-
ering of landmasses. Inorganic detritus is composed mainly
of a limited number of silicate minerals such as quartz,
feldspar, micas and clay minerals and smaller amounts of
metal oxides and sulfide phases. Of these minerals, the
clays are finer and tend to adsorb more metals than courser
material (Windom et al., 1989). Therefore, natural varia-
tions in metal concentrations have often been related to the
‘‘grain size effect’’ and analyses have been carried out on a
specific size fraction to correct for natural variability (e.g.
Forstner and Salomons, 1980). This approach, however,
requires a separation step and concentrations in a certain
size fraction may not reflect the concentration in the total
sediment.
To compensate for this natural variability, metal concen-
trations were normalized. This procedure can be done by
calculating the ratio of natural concentrations to that of a
normalizing factor whose concentration is not affected by
anthropogenic processes (Daskalakis and O’Connor, 1995).
There is no consensus on the appropriate sediment constit-
uent to be used for normalisation; however, two broad
categories have been well established: granulometric and
geochemical. Granulometric techniques rely on normalisa-
tion against total weight percent fines ( < 62.5 Am) or the
total clay size particles ( < 4 Am) present in the sediment
(Loring, 1991). Geochemical methods are based on a
comparison between metal concentration in sediment and
the concentration of other ‘‘reference’’ elements (Trimble
and Hoenstine, 1997). Reference elements that have been
used previously include aluminium, chromium, iron,
organic carbon and lithium (Windom et al., 1989; Loring,
1990, 1991; McMurtry et al., 1995; Daskalakis and O’Con-
nor, 1995; Balls et al., 1997; Trimble and Hoenstine, 1997;
Tam and Yao, 1998; Fang and Hong, 1999).
In all the above examples, normalisation of element con-
centration assumes a linear relationship between either
geochemical or sedimentological characteristics and the
element of interest. Regardless of the type of normalizing
method used, the concentration of normalizing metal is used
to establish the relationship between natural trace metal
concentrations in sediments from different areas. Overall,
geochemical normalisation is superior to granulometric
methods, as it compensates for both mineralogical and the
natural granular variability of trace metal concentrations in
sediments (Loring, 1991).
One of the drawbacks of the geochemical approach is
that it generates a ratio instead of a total concentration. This
problem can be overcome by standardising the contents to a
reference material and by defining an enrichment factor
(EF). For instance, EF (for Zn relative to Al)=(Zn/Al
sample)/(Zn/Al reference material). The validity of such
an enrichment factor will differ with values used for the
reference material. Most workers have used metal concen-
trations in the Earth’s crust as reference for interpreting the
results. This approach has several limitations, however, and
was not used in this study. Concentrations for crustal
abundances are not appropriate because they neither repre-
sent regional background level nor the analytical uncertain-
ties associated with their measurements (Loring, 1991).
Further, the metal concentration of the Earth’s crust reported
in the literature (e.g. Taylor, 1964) is based on total
digestion and the trace metal concentrations reported in this
study are only extractable cations. As a result, normalizing
with the metal concentration of the Earth’s crust will not
reflect the real situation (e.g. Fang and Hong, 1999). The
present study, therefore, has used a geochemical approach to
test correlations between concentrations of trace elements
and three candidate-normalizing factors: iron, aluminium
and total organic carbon.
4. Results and interpretation
4.1. Mineral and chemical character of the samples
While concentrations of trace metals determined within
each of the three categories of material analysed are broadly
similar, distinct differences do exist (Table 2).
nt International 29 (2003) 935–948 941
4.1.1. Soils developed on bedrock
Primary minerals such as quartz, feldspars (dominantly
plagioclase) and secondary minerals (e.g. hematite and
different types of clays) are major components of the
Triassic–Jurassic sandstone, which underlies the Late Qua-
ternary sediments. Due to variable degrees of weathering,
this bedrock is spatially heterogeneous and contains 48.5–
82% quartz. In fresher less weathered samples, feldspars
occur up to 14%. The most abundant type of clay through-
out bedrock samples is kaolinite followed by smectite and
traces of illite. Hematite was the only iron oxide detectable
in bedrock samples. Samples with a high proportion of
secondary minerals (e.g. kaolinite and smectite) contained
higher concentration of metals such as V, Cr and Zn as well
as Fe, showing the greater capacity of clay-rich weathered
sediments for metal adsorption. The dominant trace metals
were Zn and V, followed by Pb and Cr. Metals such as As,
Co, Cu, Ni and Mo occur at lower concentrations commonly
around the detection limit for the analytical method used.
4.1.2. Soils of fluvial/estuarine origin
The most abundant primary minerals were quartz (20–
100%) followed by feldspars (0–10%). The clay component
was made up of kaolinite (0–61%), smectite (0–7.3%),
illite–smectite mixed layers (0–33.7%) and occasional illite
(e.g. 3.6% in sample 661 at a depth of 80 cm). Minerals such
as pyrite, hematite and jarosite (oxidation products of pyrite)
occur only in some samples located in the estuarine section.
Of note was the positive correlation between these minerals
and the iron content of the sample in which they were found.
Further clay analysis revealed that in almost all samples, the
peak for kaolinite was asymmetrical. After glycolation not
only did the peak become more asymmetrical but also the d-
spacing increased (e.g. in sample 563–130, d-spacing
changed from 7.23 to 7.31 A). As smectite is the only type
of clay mineral in the study area that shifts after glycolation,
the asymmetrical kaolinite peak was believed to be due to the
presence of a kaolinite–smectite (K–S) mixed layer. Sam-
ples 563–130 and 655–380 were good examples because
they contained significant amounts of kaolinite (51.5% and
61%, respectively); therefore, the shift for the peak after
glycolation was easily detectable. The occurrence of K–S
mixed layer is significant as this phase is likely to have a
higher capacity to adsorb metals compared to kaolinite alone.
The reason for the occurrence of this mixed layer clay will
require a more detailed mineralogical investigation.
Due to existence of a bedrock with little lithological
variation (Landsborough Sandstone), the clay speciation is
homogeneous throughout the catchment regardless of sedi-
ment type and location. However, clay minerals may have
depositional significance within the catchment. For exam-
ple, due to limited physical and chemical reworking locally,
the alluvial material was expected to contain more smectite.
The results show that smectite was concentrated in the
upper, fresher sections of the catchment; downstream,
smectite disappears probably due to either weathering to
T. Liaghati et al. / Environme
kaolinite or physical removal by tidal currents. The latter
process has been documented in estuarine conditions where
the deposition of smectite is not favoured, as this mineral is
preferentially retained in suspension (because of its small
size and platy form) and tends to be transported directly to
the near-shore environment (e.g. Chamley, 1989).
Within the fluvial/estuarine soils, the dominant trace
metals were Zn and V, followed by Cr and Pb. This pattern
was preserved in the A- and C-horizons with exception of
some samples in which Cr concentration was higher than that
of V. In the B-horizon, however, this pattern was not clear,
possibly due to the limited number of samples taken from this
horizon. Fig. 4 shows the distribution of Vand Cr throughout
different soil horizons which demonstrates that regardless of
the metal, A is the most leached horizon, while B was the
horizon with the most metal concentration. Metal concen-
trations are shown to be strongly related to the mineralogy of
the materials. Figs. 5–7 summarise lateral (e.g. H1 and BN5
from upper and lower sections of the catchment) and vertical
(e.g. core 651) correlations between geochemistry and min-
eralogy of the samples. The influence of mineral composition
over trace element distribution (trends shown in graphs) is
very clear for all samples analysed.
4.1.3. Recent surficial fluvial/estuarine sediments
The mineralogy of recent fluvial/estuarine sediments was
very similar to soils of fluvial/estuarine origin and the parent
material. Distribution patterns for the primary minerals such
as quartz are very similar to that of soils (up to 89%);
feldspars, however, were more abundant compared to soils
(up to 23%). The clay assemblage was very similar to soil
samples: kaolinite (6.5–30%), smectite (0–5.5%), illite–
smectite mixed layers (0–3%) and occasional illite (e.g. in
H1 and BS4, 2.7% and 7.2%, respectively). The dominant
trace metals were Zn and V, followed by Cr and Pb, while Fe
occurred as pyrite, hematite and goethite in surficial sedi-
ments. The strong correlation between trace metal concen-
trations and sample mineralogy was preserved similar to that
seen in soil samples.
In summary, the comparison of metal concentration
between bedrock, recent surficial fluvial/estuarine, and soils
with fluvial/estuarine origin showed that the feldspathic
signature of the sandstone was preserved in all unconsoli-
dated sediments. In terms of metal occurrence, Zn was the
dominant trace metal followed by V and Cr. In unconsoli-
dated sediments this overall pattern was also preserved, with
the exception of Cr, which in some areas was more abundant
than V. Elevation of Cr levels may be due to the overall
immobility of the metal. Considering the mineralogical and
geochemical data, it can be concluded that the Landsborough
Sandstone is the primary source of unconsolidated sediments.
4.2. Relationship between trace and minor metals
There are inorganic (e.g. clay minerals, Fe and Mn
oxides) and organic (represented by organic carbon) scav-
Fig. 4. Metal distribution patterns throughout different horizons. The graphs show that A-horizon is always the most leached horizon. While C-horizon shows
some metals depletion, due to the high heterogeneity of this horizon, adding a trend line could be misleading. The same pattern was observed for other trace
elements measured in this study. Outliers in both figures belong to B-horizon where most of the A-horizon elements accumulate.
T. Liaghati et al. / Environment International 29 (2003) 935–948942
engers influencing metal mobility and distribution within
coastal sediments and soils. Spearman’s rank coefficient
matrices enabled the identification of relationships between
metals and potential controlling factors in metal mobility. In
order to understand variability in metal correlations with the
controlling scavengers in different populations (sediments
and soils), correlation matrices were calculated for each of
the above categories separately.
Based on the correlation matrix obtained for sediments
(Table 3), inorganic scavengers (clays followed by Fe andMn
oxides and S) are the dominant factors controlling trace metal
distribution in the catchment. Organic carbon (OC) showed
weak or no association with trace metals. This confirms the
observation that OC is not a strong metal scavenger as are
oxides or clays in nonmarine environments. Metals such as
Cu and Ni (r = 0.6 and 0.5, respectively) were exceptions due
to their tendency to be kept in solution by chelation with
organic material (e.g. fulvic acids) (Thornton, 1981). As for
trace metals such as Mo and Co, concentrations were low
(around detection limit) for most samples and their correla-
tions were considered unreliable.
A weak correlation between Fe and S (r = 0.4) together
with the results of mineralogical analysis suggested that iron
is not predominantly present as pyrite but is in the form of
oxides such as goethite (FeO.OH) and/or hematite (Fe2O3). A
strong correlation between Fe and Al (r = 0.7) confirmed that
iron was primarily associated with the silt–clay fraction.
Finally, a moderate to strong correlation between Al and trace
elements demonstrated that these elements are associated
with clays.
In order to interpret vertical metal distribution within each
soil profile, cores were treated individually and subdivided
into A-, B- and C-horizons (based on descriptions and logs
provided by QASSIT). Cores were then regrouped according
Fig. 5. Lateral variation of metal distribution and its correlation with
mineralogy. Sample H1 contains larger amounts of clay minerals and
significantly more V and Cr compared to BN5. Sites shown in Fig. 2.
Fig. 6. Vertical variation of metal distribution with regard to mineralogy.
The above samples belong to the same core and were taken from different
depths: 0 cm (A-horizon), 130 cm (B-horizon) and 330 cm (C-horizon),
respectively. Sites in Fig. 3.
Fig. 7. Comparison of clay-rich with sand-rich material shows that sample
661 (80 cm) has a higher metal content than 662 at a similar depth.
T. Liaghati et al. / Environment International 29 (2003) 935–948 943
to their horizons and correlation matrices calculated for each
horizon separately (Table 4). The correlationmatrix for the A-
horizon (generally 0–100 cm deep) showed that all metal
scavengers (clays followed by Fe, Mn, S and OC) were
present. While OC is not necessarily a good terrestrial metal
scavenger, the A-horizon samples showed the highest organic
carbon and, therefore, the presence of OC as a scavenger in
this horizon was not surprising. In samples from the B-
horizon (about 50–280 cm deep), the role of S and C as
scavengers is reduced probably due to their lower concen-
Table 3
Spearman’s rank correlation matrix for surficial sediments (n= 21)
V Cr Mo Co Ni Cu Zn Pb As Mn Fe AL S OC
V 1.0
Cr 0.9 1.0
Mo 0.4 0.5 1.0
Co 0.8 0.7 0.3 1.0
Ni 0.7 0.7 0.5 0.6 1.0
Cu 0.6 0.7 0.4 0.6 0.9 1.0
Zn 0.5 0.4 0.5 0.6 0.7 0.7 1.0
Pb 0.8 0.8 0.3 0.7 0.6 0.6 0.4 1.0
As 0.4 0.3 0.1 0.2 0.5 0.3 0.2 0.3 1.0
Mn 0.6 0.5 0.5 0.5 0.6 0.6 0.5 0.3 0.2 1.0
Fe 0.9 0.8 0.4 0.6 0.6 0.5 0.5 0.5 0.5 0.6 1.0
AL 0.8 0.9 0.4 0.7 0.7 0.6 0.4 0.8 0.3 0.5 0.7 1.0
S 0.5 0.6 0.4 0.5 0.8 0.7 0.4 0.5 0.5 0.3 0.4 0.5 1.0
OC 0.2 0.2 0.0 0.4 0.5 0.6 0.3 0.4 0.3 0.0 � 0.1 0.2 0.7 1.0
Bold text shows strong correlations.
0.60–1.00 = strong correlation; 0.50–0.59 =moderate; 0.40–0.49 =weak;
0.00–0.39 = little or no association.
Table 4
Correlation matrices for A-, B- and C-horizons in soils
V Cr Mo Co Ni Cu Zn Pb As Fe Mn Al S OC
A-horizon
V 1.0
Cr 0.6 1.0
Mo 0.7 0.6 1.0
Co 0.4 0.1 0.4 1.0
Ni 0.4 0.8 0.6 0.2 1.0
Cu 0.4 0.5 0.3 0.3 0.4 1.0
Zn 0.6 0.6 0.6 0.2 0.3 0.4 1.0
Pb 0.8 0.4 0.8 0.5 0.2 0.3 0.7 1.0
As 0.4 0.1 0.2 0.7 0.2 0.1 0.0 0.2 1.0
Fe 0.9 0.7 0.7 0.5 0.6 0.5 0.7 0.6 0.5 1.0
Mn 0.8 0.6 0.6 0.6 0.6 0.6 0.6 0.7 0.5 0.9 1.0
Al 0.9 0.5 0.8 0.5 0.3 0.3 0.7 0.9 0.3 0.8 0.8 1.0
S 0.8 0.6 0.6 0.6 0.4 0.5 0.6 0.7 0.5 0.8 0.9 0.8 1.0
OC 0.6 0.5 0.6 0.3 0.5 0.0 0.5 0.7 0.2 0.6 0.6 0.7 0.7 1.0
B-horizon
V 1.0
Cr 0.3 1.0
Mo 0.7 0.4 1.0
Co 0.5 0.2 0.5 1.0
Ni 0.0 0.9 0.2 0.2 1.0
Cu 0.4 � 0.1 0.1 0.4 � 0.2 1.0
Zn 0.2 0.0 0.3 0.7 0.0 0.5 1.0
Pb 0.7 0.3 0.9 0.7 0.2 0.2 0.4 1.0
As 0.7 0.3 0.6 0.7 0.1 0.6 0.4 0.7 1.0
Fe 0.8 0.4 0.6 0.6 0.1 0.2 0.3 0.7 0.8 1.0
Mn 0.8 0.5 0.4 0.6 0.4 0.4 0.2 0.6 0.8 0.9 1.0
Al 0.8 0.5 0.9 0.7 0.4 0.2 0.4 0.9 0.7 0.8 0.7 1.0
S 0.4 0.0 0.3 0.4 0.0 0.2 � 0.1 0.5 0.5 0.6 0.5 0.5 1.0
OC 0.4 � 0.2 0.5 0.5 � 0.3 0.3 0.2 0.6 0.5 0.4 0.3 0.5 0.7 1.0
C-horizon
V 1.0
Cr 0.9 1.0
Mo 0.4 0.5 1.0
Co 0.2 0.3 0.0 1.0
Ni 0.4 0.4 0.2 0.8 1.0
Cu 0.6 0.5 0.0 0.1 0.3 1.0
Zn 0.6 0.6 0.2 0.4 0.5 0.5 1.0
Pb 0.6 0.6 0.4 0.3 0.3 0.3 0.5 1.0
As 0.5 0.5 0.2 � 0.1 0.2 0.7 0.3 � 0.1 1.0
Fe 0.5 0.5 0.1 0.5 0.6 0.4 0.3 0.0 0.5 1.0
Mn 0.4 0.5 0.2 0.5 0.7 0.6 0.4 0.0 0.4 0.7 1.0
Al 0.9 0.8 0.4 0.3 0.4 0.5 0.7 0.8 0.3 0.3 0.3 1.0
S 0.1 0.1 0.0 0.5 0.7 0.4 0.4 0.0 0.1 0.5 0.8 0.1 1.0
OC 0.1 0.1 � 0.2 0.2 0.3 0.4 0.5 0.2 � 0.1 0.0 0.3 0.3 0.5 1.0
Indices indicate the distinct change of main scavengers over metal distribution as the soil horizons change.
T. Liaghati et al. / Environment International 29 (2003) 935–948944
tration in this horizon. Trace metals such as V, Pb and As
continue to be strongly correlated with clays, Fe and Mn
oxides, as this horizon is where the clays, Fe and Mn oxides
leached from the above horizons tend to accumulate. How-
ever, Zn, Cu and Cr showed only weak, little or no association
with the main scavengers. This may be due to the fact that
these metals tend to be adsorbed by clay minerals such as
smectite and illite (e.g. Alloway, 1995). In the majority of
samples, kaolinite was the dominant clay while smectite only
occurred in very low concentration. In the C-horizon the
dominant scavenger was Al, which showed a strong correla-
tion with all elements except for Cu (r= 0.5), which showed a
moderate correlation. This distribution is because the C-
horizon is comprised mainly of unconsolidated rock material
and is less affected by the leaching processes, which occur in
the upper horizons.
4.3. Approach to normalisation
As the samples analysed in this project were from a wide
range of unconsolidated material taken from various loca-
tions within the catchment, the data produced represent a
T. Liaghati et al. / Environment International 29 (2003) 935–948 945
heterogeneous geochemical data set controlled by a number
of sediment characteristics. Therefore, normalisation was
required to interpret data in more detail and to describe
patterns of distribution.
After testing Fe and OC, Al was chosen as the most
suitable normalizing element. Extractable Al is likely to be
associated with finer particles and is also one of the
conservative metals which is not affected by anthropogenic
activities. Therefore, aluminium has been used successfully
by several workers to account for grain size effect (Ryan and
Windom, 1988; Sinex and Wright, 1988; Balls et al., 1997;
Rubio et al., 2000). After choosing the best normalizing
factor, the next step was deciding on the most appropriate
sample as a reference to use in calculating EF. A mean of
five samples from the B-horizon (130–280 cm deep),
containing older sediments, most likely deposited under
preindustrial conditions, was chosen as reference. Further-
more, unlike A- and C-horizons, the B-horizon is more
structured and consistent (neither too close to surface nor
bedrock), and therefore, is more representative of sedimen-
tary environment (Murphy, 1991). The reference samples
were also located in the lower section of the catchment
within native vegetation, which has never been disturbed by
modern activities and, therefore, represented the background
values of the metals for the local area. Due to natural
mineralogical differences of the sediments and analytical
uncertainty, only sediments with an EF greater than 2 were
considered as enriched (e.g. Angelidis and Aloupi, 1997).
The EFs calculated for sediments revealed that they were
only enriched in V. The enrichment factor varied from 2 to 9.5
in enriched sites (B3, BN1, BN3, BS1, BS4, H1 andH2) (Fig.
2). All sites were located in native vegetation (Melaleuca and
mangroves) and the fact that they have not been disturbed
suggests that enrichment was in situ. Vanadium in sediment
solutions occurs predominantly in the + 5 and + 4 oxidation
states as the vanadate forms and as the vanadyl cation, VO2 +.
Under oxidised conditions with pH from neutral to alkaline,
V (e.g. V3 +) has high mobility and bioavailability. Under
reduced conditions, humus promotes easy reduction of vana-
date to vanadyl and causes the immobilisation of V when it is
bound to organic material (McBride, 1994). The immobiliz-
ing factors mentioned above are likely to be present in the
various enriched sites analysed. In samples B3, BN1 and
BS1, organicmatter probably was the main factor influencing
in immobilisation of V as they have 4.7%, 4.3%, and 5.5%
total organic carbon, respectively (the highest OC for this
sample set is 5.5%). Unstable forms of V may substitute
readily for Fe3 + in minerals such as Fe oxides and/or layer
silicate clays. This may be the case for some sites where Fe
oxides are abundant such as samples BN3 and BS4 with
hematite 2% and 0.6%, respectively. Pyrite and goethite
(0.8% and 0.5%, respectively) were found in sample H1,
while sample H2 contained extremely high goethite (in order
of tens of percent).
Soil samples (Fig. 3) were found to be enriched in Cr, Zn
and V. Chromium enrichment was found at two sites (542
and 509) and varied from 2.2 to 5. This element may be
present here as Cr3 + (chromic form), a very immobile cation
whose solubility decreases above pH 4 while above pH 5.5
complete precipitation occurs (pH in these sites varied
between 4.7 and 5.7) (McBride, 1994; McGrath and Smith,
1995). Mineralogically, while site 542 contained up to 3%
smectite, which is a strong adsorbent for trace elements, site
509 was very sandy. The high Cr at both sites (542 and 509)
may have originated from agricultural material (e.g. nitrate
fertilizers), as these sites are located close to turf and sugar
cane farms. Whan (2002) reported that the concentration of
nutrients (e.g. nitrate) for sites 542 and 509 was 784 and
1038 mg/kg, respectively (nitrate concentration was
between 61 and 1718 mg/kg for 21 sites and the above
sites were among those with highest nitrate).
Only three sites (509, 652 and 655) of surficial samples
(0–80 cm) were enriched in Zn with the EFs that varied from
4.6 to 6. In acid, aerobic soils, Zn has medium mobility as it
is held in exchangeable forms on clays and organic matter. At
higher pH (as is the case with enriched samples), chemi-
sorption on oxides and aluminium silicates, and complex-
ation with humus can decrease the solubility and mobility of
Zn2 +. The enriched sites here are all very sandy (up to 99%
quartz) and located in the lower section of the catchment; due
to intense leaching and weathering, these samples contain
relatively low amount of clays and other secondary minerals.
Cause of enrichment may be related to current land use in the
area. Sites 509 and 652 are adjacent to a sugar cane farm, and
655 is located within a golf course, thus fertilizer impurities
may be the reason for increased Zn concentration at the
above sites (e.g. Alloway, 1995; McMurtry et al., 1995).
Sites 562 and 651 were enriched in V (EF from 2 to 3.5).
Both cores are very clayey (55–60% kaolinite and 3–6% of
mixed layers of illite–smectite). Therefore, V enrichment
may be due to the high clay abundance in these cores.
Mineralogy of surficial sediments is an effective way to
explain the metal distribution among these samples. Samples
are typically recent, less reworked and contained significant
amounts of secondary minerals and organic carbon. More-
over, as there were not any point sources of pollution close to
the enriched sites, in situ enrichment due to significant
occurrence of organic and inorganic metal adsorbents was
the best explanation. For soil samples, however, land use in
the area is an additional means of explaining the enrichment
and of showing that there are several point sources for metals
such as Zn, Cr and V. Therefore, the limited amount of
scavenger materials at the sandy sites of the lower catchment
suggests that the enrichment cannot be natural and most
likely related to local land use.
To obtain a better understanding of enrichment factors, a
comparison between absolute and normalized metal con-
tents in soil cores with respect to Al content was made.
Values of Al (Fig. 8) demonstrate an irregular distribution
with core depth, indicating a lack of pattern in clay content
within the profile. While in cores with higher clay content
(high Al) absolute and normalized values covary, in sandier
Fig. 8. A comparison between absolute and normalised metal (V and Zn) content for cores 652, 562 and 651, and a comparison between absolute and
normalised values for Zn, V and Al.
T. Liaghati et al. / Environment International 29 (2003) 935–948946
cores with lower clay content, the positive correlation
becomes negative. Therefore, in a sandy core as the metal
concentration decreases, EF increases and a lower absolute
metal content does not necessarily demonstrate lower values
for EF and vice versa (Fig. 8). Overall, this comparison
showed that in a highly heterogeneous environment, such as
this setting, interpretations based on absolute concentration
of different elements alone could be misleading. Therefore,
normalizing the data is the best approach for sensible
interpretation of geochemical data.
5. Conclusions
The chemical analyses of three types of material (sedi-
ments, soils and bedrock) in this study helped to explain the
spatial and vertical distribution of trace elements within the
area. Analysing bedrock samples established the background
values for elements which is essential when assessing levels
occurring in the adjacent unconsolidated sediments. Overall,
mineral and chemical characteristics of the three categories of
samples analysed were systematic. However, varying degrees
of weathering have resulted in the heterogeneous nature of
the material, which in turn governs the trace metal distribu-
tion. Quartz was an important component in all three cate-
gories analysed; feldspars, however, were in more abundance
in surficial sediments compared to soils and some weathered
bedrock samples. The dominant trace metals were Zn and V,
followed by Cr and Pb. This overall pattern is preserved
throughout the study area, except for Cr, which was occa-
sionally present in higher concentrations than V, presumably
due to its immobility.
T. Liaghati et al. / Environment International 29 (2003) 935–948 947
In comparing sediment and soil samples, the correlation
matrix showed that while inorganic scavengers such as clay
minerals are dominant factors controlling trace metal dis-
tribution in sediments, in soil cores the relationships
between metals were different in each horizon. Both organic
and inorganic metal scavengers are present in the A-horizon;
in the B-horizon, OC and S occur in lower concentrations
and the Al is the strongest scavenger here. Finally, in the C-
horizon, Al is almost the only scavenger present. This is
probably because this horizon had been less affected by the
leaching processes, which were dominant in other horizons.
Data produced in this study represent a heterogeneous
geochemical data set controlled by various processes. The
enrichment factors calculated for sediments showed that
they had been enriched only in V. All enriched sites were
located within natural undisturbed vegetation so enrichment
was most likely due to the presence of organic material and/
or secondary minerals such as clays, hematite and goethite.
In soil samples, however, the enriched metals were Cr, Zn
and V. As most enriched sites contained relatively low
amount of clays and were located close to agricultural lands,
the current land use in the area is more likely to be the cause
of the enrichment, e.g. fertilizer impurities.
Thus, the main findings of this study were:
(1) Metal elevation was many times due to natural enrich-
ment and not to contamination.
(2) When analysing a large data set consisting of samples
from a variety of settings, it is essential to apply norma-
lisation as a tool to transform the heterogeneous geo-
chemical data and compensate for grain size effect.
(3) Natural sediment/soil characteristics such as mineralogy
are more important in controlling metal occurrence and
spatial/vertical distribution compared to anthropogenic
activities such as local land-use practices in the Bells
Creek catchment.
Acknowledgements
This study was funded by Lensworth Group. Authors
would like to thank Hayden McDonald from Mipela for the
GIS database as well as Queensland Acid Sulfate Soils
Investigation Team (QASSIT) for providing soil and
bedrock samples. We also wish to thank Bill Kwiecien,
Whatsala Kumar and Tony Raftery for practical assistance
with chemical and mineralogical analyses. Our colleague,
Tim Ezzy, is also thanked for assisting with fieldwork and
additional mapping information. Graham Kimber is greatly
appreciated for his inputs regarding data quality control
procedures.
References
Alloway BJ. Heavy metals in soils. Glasgow, UK: Blackie Academic &
Professional, an imprint of Chapman & Hall; 1995. p. 368.
Angelidis MO, Aloupi M. Assessment of metal contamination in shallow
coastal sediments around Mytilene, Greece. Int J Environ Anal Chem
1997;68(2):281–93.
Angelidis MO, Aloupi M. Geochemical study of coastal sediments influ-
enced by river transported pollution: southern Evoikos Gulf, Greece.
Mar Pollut Bull 2000;40(1):77–82.
Arakel AV, Hongjun T. Heavy metal geochemistry and dispersion pattern in
coastal sediments, soil and water of Kedron Brook floodplain area,
Brisbane. Environ Geol Water Sci 1992;20:219–31.
Balls PW, Hull S, Miller BS, Pirie JM, Proctor W. Trace metal in Scottish
estuarine and coastal sediments. Mar Pollut Bull 1997;34:42–50.
Chakrapani GJ, Subramanian V. Heavy metals distribution and fractiona-
tion in sediments of the Mahanadi River basin, India. Environ Geol
1993;22:80–7.
Chamley H. Clay sedimentology. Berlin: Springer-Verlag; 1989.
Chao TT. Use of partial dissolution techniques in geochemical exploration.
J Geochem Explor 1984;20:101–35.
Chen Z, Kostaschuk R, Yang M. Heavy metals on tidal flats in the Yangtze
Estuary, China. Environ Geol 2001;40(6):742–9.
Cox ME, Preda M, Brooke B. General features of the geo-setting of the
Pumicestone region. In: Cox ME, editor. PASSCON 2000. Brisbane:
School of Natural Resource Sciences, Queensland University of Tech-
nology; 2000. p. 7–12.
Daskalakis KD, O’Connor TP. Normalization and elemental sediment con-
tamination in the coastal United States. Environ Sci Technol 1995;
29(2):470–7.
Data DK, Subramanian V. Distribution and fractionation of heavy metals in
the surface sediments of the Ganges-Brahmaputra-Meghna river system
in the Bengal basin. Environ Geol 1998;36(1–2):93–101.
De Carlo EH, Anthony SS. Spatial and temporal variability of trace element
concentrations in an urban subtropical watershed, Honolulu, Hawaii.
Appl Geochem 2002;17:475–92.
Ellaway M, Hart BT, Beckett R. Trace metals in sediments from the Yarra
river. Aust J Mar Freshw Res 1982;33:761–78.
Fang T, Hong E. Mechanisms influencing the spatial distribution of trace
metals in surficial sediments off the Southwestern Taiwan. Mar Pollut
Bull 1999;38(11):1026–37.
Flood PG. Carbon-14 dates from the coastal plains of Deception Bay,
Southeastern Queensland. Queensl Gov Min J 1981;82:19–23.
Forstner U, Salomons W. Trace metal analysis on polluted sediments: Part
I. Assessment of sources and intensities. Environ Technol Lett 1980;1:
494–506.
Forstner U, Calmano W, Schoer J. Metals in sediments from the Elbe,
Weser and Ems estuaries and from the German Bight: grain size effects
and chemical forms. Thalass Jugosl 1982;18(1–4):97–122.
Forstner U, Wolfgang A, Wolfgang C, Kersten M, Salomons W. Mobility
of heavy metals in dredged harbour sediments. In: Sly PG, editor. Sedi-
ment and water interaction: proceedings of the third international sym-
posium on interactions between sediments and water. New York:
Springer-Verlag; 1984. p. 371–80.
Fung YS. Analysis and assessment of heavy metal pollution in Hong Kong’s
marine environment. Mar Biol South China Sea 1993;261–72.
Kelly AG, Wells DE, Fryer RJ. Sampling strategy to detect a change in
concentration of trace organic contaminants in marine sediment. Sci
Total Environ 1994;144:217–30.
Koljonen T, Malisa E. Solubility in aqua regia of selected chemical ele-
ments occurring in the fine-grained fraction of till. In: Pulkkinen E,
editor. Environmental geochemistry in northern Europe, special paper
9. Helsinki: Geological Survey of Finland; 1991. p. 49–52.
Krauskopf KB. Introduction to geochemistry. New York: McGraw-Hill;
1967.
Leckie JO, Parks GA. Geochemistry and environmental impact. In: Ho-
ward AD, Remson I, editors. Geology in environmental planning. New
York: McGraw-Hill; 1978. p. 276–88.
Lester J. Geomorphology, sedimentology and shoreline processes impact-
ing on the stability of the Bribie Island Spit. Honours thesis, Queens-
land University of Technology; 2000.
T. Liaghati et al. / Environment International 29 (2003) 935–948948
Loring DH. Lithium—a new approach for the granulometric normalization
of trace metal data. Mar Chem 1990;29:155–68.
Loring DH. Normalization of heavy-metal data from estuarine and coastal
sediments. J Mar Sci 1991;48:101–15.
Loring DH, Rantala RTT. Manual for geochemical analyses of marine
sediments and suspended particulate matter. Earth-Sci Rev 1992;32:
235–83.
McBride MB. Environmental chemistry of soils. New York: Oxford Univ
Press; 1994. 406 pp.
McConchie DM,MannAW, LinternMJ, LongmanD, Talbot V, GabelishAJ,
Gabelish MJ. Heavy metals in marine biota, sediments and waters from
the Shark Bay area, Western Australia. J Coast Res 1988;4(1):37–58.
McGrath SP, Smith S. Chromium and nickel. In: Alloway BJ, editor. Heavy
metals in soils. New York: Blackie, Wiley; 1995.
McMurtry GM, Wiltshire JC, Kauahikaua JP. Heavy metal anomalies in
coastal sediments of Oahu, Hawaii. Pac Sci 1995;49:452–70.
Murphy BW. The soil profile. In: Charman PEV, Murphy BW, editors.
Soils their properties and management. Sydney: Sydney University
Press in association with Oxford University Press Australia, 1991.
Murphy PR, Trezise DL, Hutton LJ, Cranfield LC. 1:100,000 Geological
map commentary. Caboolture, sheet 9443, Queensland. Department of
Mines, Geological Survey of Queensland: Brisbane; 1987.
Niencheski LF, Windom HL, Smith R. Distribution of particulate trace
metal in Patos Lagoon estuary (Brazil). Mar Pollut Bull 1994;28(2):
96–102.
NSR Environmental Consultants. Caloundra Downs informal land use in-
vestigation: Pumicestone Passage study. Report prepared for Lensworth
Group, Brisbane, Queensland; 1999a.
NSR Environmental Consultants. Caloundra Downs informal land use in-
vestigation: consolidated data report, main volume. Report prepared for
Lensworth Group, Brisbane, Queensland; 1999b.
Osterholm P, Astrom M. Spatial trends and losses of major and trace
elements in agricultural acid sulphate soils disturbed in the artificially
drained Rintala area, W. Finland. Appl Geochem 2002;17:1209–18.
Owen RB, Sandhu N. Heavymetal accumulation and anthropogenic impacts
on Tolo Harbour, Hong Kong. Mar Pollut Bull 2000;40(2):174–80.
Power M, Attrill MJ, Thomas RM. Heavy metal concentration trends in the
Thames estuary. Water Res 1999;33(7):1672–80.
Preda M, Cox ME. Sediment–water interaction, acidity and other water
quality parameters in a subtropical setting, Pimpama River, Southeast
Queensland. Environ Geol 2000;39(3–4):319–29.
Preda M, Cox ME. Trace metals is acid sediments and waters, Pimpama
River, Southeast Queensland. Environ Geol 2001;40(6):755–68.
Preda M, Price S, Cox ME. Trace metal occurrence in estuarine sediments
and mangroves, Pumicestone Passage. In: Cox ME, editor. PASSCON.
Brisbane, Australia: Queensland University of Technology; 2000. p. 161.
Raisanen ML. Geochemistry of podzolized tills and the implications for
aluminium mobility near industrial sites: a study in Kuopio, eastern
Finland. PhD dissertation, University of Abo, Finland; 1996.
Rose AW, Hawkes HE, Webb JS. Geochemistry in mineral exploration.
London: Academic Press; 1979.
Rubio B, Nombela MA, Vilas F. Geochemistry of major and trace elements
in sediments of Ria de Vigo (NW Spain): an assessment of metal
pollution. Mar Pollut Bul. 2000;40(11):968–80.
Ruiz F. Trace metals in estuarine sediments from southwestern Spanish
coast. Mar Pollut Bull 2001;42(6):482–90.
Ryan JD, Windom HL. A geochemical and statistical approach for
assessing metal pollution in coastal sediments. In: Seeliger U, editor.
Metals in coastal environments of Latin America. Berlin: Springer;
1988. p. 47–58.
Schneider PM, Davey SB. Sediment contaminants off the coast of Sydney,
Australia: a model for their distribution. Mar Pollut Bull 1995;31(4–12):
262–72.
Sinex SA, Wright DA. Distribution of trace metals in the sediments and
biota of Chesapake Bay. Mar Pollut Bull 1988;19:425–31.
Tam NFY, Yao MWY. Normalization and heavy metal contamination in
mangrove sediments. Sci Total Environ 1998;216:33–9.
Taylor SR. Abundance of chemical elements in the continental crust: a new
table. Geochim Cosmochim Acta 1964;28:1273–85.
Thornton I. Geochemical aspects of the distribution and forms of heavy
metals in soils. In: Lepp NW, editor. Effects of heavy metal pollution on
plants. London and New Jersey: Applied Science Publishers, 1981.
Trimble CA, Hoenstine RW. Baseline investigation of estuarine sediment
metals for the Steinhatchee River area of the Florida Big Bend. Environ
Geosci 1997;4(2):95–103.
Whan E. Nutrient chemistry of the surface drainage system and sediments
in Bells Creek catchment: sources, controls and relation to land use.
Honours, Queensland University of Technology; 2002.
Williams M, Dunkerley D, De Deckker P, Kershaw P, Chappell J. Quater-
nary environments. London: Arnold, Hodder Headline Group; 1998.
Windom HL, Schropp SJ, Calder FD, Ryan JD, Smith RG, Burney LC,
Lewis FG, Rawlinson CH. Natural trace metal concentrations in estuar-
ine and coastal marine sediments of the southern United States. Environ
Sci Technol 1989;23(3):314–20.
