Chemical Speciation and Bioavailability (2012), 24(1)
1
Speciation of heavy metals in the surface waters of a
former tin mining catchment
Muhammad Aqeel Ashrafa, Mohd. Jamil Maaha, Ismail Yusoffb
and Mohamadreza Ghararibrezab
a
Department of Chemistry University of Malaya, Kuala Lumpur 50603, Malaysia
Department of Geology, University of Malaya, Kuala Lumpur 50603, Malaysia
E-mail: [email protected]
b
ABSTRACT
This study was conducted to investigate the chemical speciation of dissolved and particulate elements (Pb,
Zn, Cu, Cr, As and Sn) in the mining wastewater. Speciation patterns of dissolved elements were
estimated by adsorptive stripping voltammeter while particulate elements were analysed using a newly
developed sequential extraction leaching procedure. The procedure has been operationally defined among
five host fractions, namely exchangeable, carbonate, reducible, organic bound and residual. A total of six
elements (Pb, Zn, Cu, Cr, As and Sn) were analysed in 30 samples at 10 locations (P1 – P10) representing
three subsequent samples at the same location to obtain the average value from ex-tin mining catchment.
The results showed that the heavy metal pollution in P4 and P8 was more severe than in other sampling
sites, especially Sn and Pb pollution. In the water samples at P4 and P8, both the total contents and the
most dangerous non-residual fractions of Sn and Pb were extremely high. More than 90% of the total
concentrations of As and Cr existed in the residual fraction. Cu and Zn mainly (more than 60%) occurred in
the residual fraction. However, Pb and Sn were predominantly present in the non-residual fractions of the
surface water. For all the six dissolved elements, the less labile species formed the predominant fraction in
their speciation patterns. We conclude that the speciation patterns of particulate elements show that most
of the Pb, Zn, Cu, Cr, As and Sn were found in the reducible fraction whereas Pb and Sn were mainly
associated with the organic fraction.
Keywords: particulate metals, dissolved metals, anodic stripping, sequential leaching, fractions
INTRODUCTION
Metals and metalloids are ubiquitous in the environment.
They exist naturally as ions, compounds and complexes.
The earth’s crust is the natural reservoir for all the chemical
elements. Over 99% of its total mass is made up of oxygen
(46.4%), silicon (28.15%), aluminium (8.23%), iron
(5.63%), calcium (4.15%), sodium (2.36%), magnesium
(2.33%) and potassium (2.09%). The remaining 80
elements of the Periodic Table that occur naturally make
up less than 1% of the composition of the earth’s crust
(Markert et al., 2000). During the earth’s long geologic
history, the solid rocks have weathered, and the mountain
ridges have eroded. The eroded materials are suspended and
dissolved in river water and rainwater, transported in ice
and wind. These processes have caused the distribution of
the chemical elements (Kabata-Pendias and Pendias, 2001).
Natural waters acquire their chemical compositions from
various sources. They collect the suspended and dissolved
components through contact with the solids, liquids, and
gases they encounter during their hydrologic cycles. The
composition of surface waters and ground waters changes
on time scales from minutes to years, however, the
composition of the oceans has been constant over millions
of years (Puxbaum and Limbeck, 2008) The main factors
affecting the composition of natural waters are the interactions between water and the gases, liquids, and solids that
the waters contact when they pass through the hydrologic
cycle. These interactions determine the chemical environments where trace elements exist and influence the transport, fate and environmental behaviours of the elements
(Philos and Philos, 1995).
Heavy metals exist in a wide range of chemical forms in
environmental systems. In surface waters, they are present
in both dissolved and particulate phases. The former phase
includes the hydrated ions, inorganic and organic
complexes, and the species associated with heterogeneous
colloidal dispersions and organometallic compounds. The
latter phase contains the chemical associations ranging from
weak adsorption to binding in the mineral matrix. It has
doi: 10.3184/095422912X13259575370081
www.chemspecbio.co.uk
2
Heavy metals in surface waters
been generally accepted that the distribution, mobility,
bioavailability and toxicity of chemical elements depend
not only on their total concentrations, but also on their
chemical forms. The changes in the environmental conditions such as redox potential, pH, complexing ligands and
adsorbing sites can greatly alter the chemical forms of the
elements, and thus influence the physical and chemical
associations which they undergo in environmental systems
(Dodge and Theis, 1979).
Toxicity occurs when an organism cannot deal with the
additional element concentration (Angelika et al., 1998;
Nicole et al., 2001; Huang et al., 1995; Du et al., 1996;
Petersen et al., 1997). The interactions between elements
and intracellular components depend strongly on their
chemical forms. Some species may be able to react directly
with proteins, enzymes and other biological molecules,
while others may diffuse through cell membranes and
interfere with the enzyme reactions.
The distribution of an element among different inorganic
compounds and organic complexes profoundly impacts its
transport and bioavailability by determining its physical and
chemical properties such as charge, solubility, and diffusion
coefficient. To fully understand the environmental chemistry of an element, it is necessary to establish the concentrations and chemistry of its various species under the
different conditions possible in natural environments.
Speciation science aims to characterize the forms of the
elements in order to understand the transformations between
different forms, and to discover the environmental
processes controlling these transformations (Gjerde et al.,
1993). According to IUPAC recommendations, chemical
species are the chemical compounds that differ in isotopic
composition, conformation, oxidation or electronic state, or
in the nature of their complexes or covalently bound
substances (Templeton et al., 2000).
For analysis of chemical speciation, different methods
have been employed by different researchers such as
voltammetry (Bard and Faulkner, 1980; Bond, 1980),
liquid – liquid extraction (Meera et al., 2001; Francis et al.,
2001), ion exchange and adsorption columnsyresins (Morel
et al., 2008; Sweileh et al., 1987), gas chromatography
(Dietz et al., 2000; Rodil et al., 2002), liquid chromatography (Ibrahim et al., 1984; Weber et al., 2002), capillary
electrophoresis (CE) (Rocha et al., 2000; Yin et al., 2002)
as well as inductively coupled plasma mass spectrometry
(ICP-MS) (Medel et al., 2003; Butcher, 2007). ICP-MS
could be useful tool for sensitive speciation analyses of
many environmentally important elements. The analysis of
heavy metal species in soil, dust or sediment, can be
undertaken by either acid digestion or sequential extraction
techniques. Sequential extraction (SE) techniques (Tessier
et al., 1979) use successive chemical extractants of various
types in order of greater destructive ability and therefore
possess greater sensitivity than a single extraction procedure. Speciation, using sequential extraction schemes has
been developed for assessing geochemical forms in soil and
sediment (Lagerwerff and Specht, 1970; Harrison et al.,
1981; Ma and Rao, 1997; Zufiaurre et al., 1998).
Figure 1 Map of Bestari Jaya catchment.
Fractionation by selective chemical extraction removes or
dissociates a specific phase with the associated metal
bonded to it. The geochemical fractions most commonly
analysed for are: exchangeable, bound to carbonates,
reducible, oxidisable and residual. Among the sequential
extraction schemes proposed to investigate the distribution
of heavy metals in soil and sediments, the five-step and sixstep extraction schemes developed by Tessier et al. (1979)
and Kersten and Forstner (1986), respectively, were the
most widely used. Following these two basic schemes,
some modified procedures with different sequences of
reagents or operational conditions have been developed
(Borovec et al., 1993; Campanella et al., 1995; Zdenek,
1996; Gomez Ariza et al., 2000).
Water bodies are important in the ecological system. In
recent years, due to rapid industrialization and excessive
mining activities, these water bodies have been contaminated by different forms of heavy metals. These contaminations pose severe ecotoxicological threats to aquatic wildlife
and humans. The biogeochemical behaviour, nutritional
bioavailability and toxicity of metals are largely dependent
on their chemical speciation. These areas have been extensively studied in recent years. The objective of this study is
to investigate the speciation of heavy metals and arsenic by
developing a suitable sequential extraction procedure
followed by ICP-MS detection in the water bodies of the
former tin mining catchment, Betsria Jaya, Peninsular,
Malaysia.
STUDY AREA
Morphological characterization
The study area Bestari Jaya catchment is located at
3 24 0 40.41 00 N and 101 24 0 56.23 00 E is part of Daerah
Kuala Selangor in Selangor state that includes three towns
Mukim Batang Berjuntai, Mukim Ulu Tinggi, Mukim
Tg.karang (Figure 1). Bestari Jaya was formerly known as
Batang Berjuntai. Bestari Jaya has a tropical, humid
climate, with very little variations in temperature throughout
the year. The average temperature of the area is 32 C
during the day and 23 C at night. It has an annual
average rainfall of 2000 mm and 3000 mm with a potential
evaporation of 1600 mm per year (Department of Irrigation
Muhammad Aqeel Ashraf, Mohd. Jamil Maah, Ismail Yusoff and Mohamadreza Ghararibreza
and Drainage, 2009). The Bestari Jaya has been an old tin
mining area for over 10 years.The whole catchment covers
an area of 2656.31 hectares which is located downstream at
the embankment of Kampung Bestari Jaya and University
Industry Selangor (UNISEL) main campus. The catchment
flow downstream to Sungai Ayer Hitam and Sungai Udang
which ultimately ends up with Sungai Selangor at 5 km
upstream of Batang Berjuntai Water Treatment Plants SSP1
and SSP2 which are also major water distributors to the
federal territory (Kuala Lumpur and Putrajaya) and
Selangor state (Ashraf et al., 2011). The area consists of
myriad ecosystems which can be subdivided into several
categories such as degraded land, large open lakes and
small ponds, earth drains and wetlands area, tin tailings
(sand and slime tailings), and logged peat swamp forest
land in the east. The contribution of storm water, peat
swamp forest water and recent sand mining activity has
caused severe environmental pollution due to drainage
problems in the area. The area has many big lakes and
small ponds that are interconnected by earth drains. Excess
water from these lakes and ponds is discharged to the
existing earth drains downstream of the lakes and ponds.
Precipitation rate is high in some stagnant ponds (Ashraf
et al., 2011).
Geological characterization
Tin mining at the Bestari Jaya catchment was carried out
mainly in the alluvium for the rich concentration of
cassiterite that was found in the catchment soil or was
trapped within the troughs of the pinnacled limestone
bedrock. However, in a few areas such as the north east
or west, mining was carried out in the residual granitic soil
(Widya and Tresna, 1984). Cassiterite was also mined from
lodes which dipped steeply into the limestone bedrock,
forming what is known as pipes. The end result of mining
in almost all cases, except for the stripping of cassiterite
disseminated residual soil from the hill slopes, is the
formation of lakes. The bed rock underlying the alluvium,
mine tailings and ex-mining lakes in the Bestari Jaya
catchment consists mainly of limestone with interbeds of
schists, shale and rarely quartzite (Sarif, 1990). The most
common type of bed rock found in the floor of mine pits is
limestone. Sarif (1990) stated that the close association of
rich alluvium tin deposits with limestone is the result of a
fortuitous combination of several geological events and
factors such as the style of mineralization, past paleoclimatic conditions, changes in sea levels and base levels of
erosion, weathering characteristics of bed rock and the
sequence of occurrence of these events (Widya and
Tresna, 1984).
In the Bestari Jaya, the most common method of mining
was to use traditional gravel pumps. This method, which is
labour-intensive, was very popular with the local miners.
Another widely used method was to use the capital
intensive dredges. Most of these dredges were European
owned. Other methods which included mining cassiteritedisseminated residual soil from hill slopes and lode mining
along pipes were rare. Often, areas which had been mined
3
Table 1 Geography of sampling locations
Sampling
site
P1
P2
P3
P4
P5
P6
P7
P8
P9
P10
Geographic position
3 27 0 04.86 00 N
3 26 0 59.53 00 N
3 26 0 52.72 00 N
3 26 0 41.82 00 N
3 26 0 38.16 00 N
3 26 0 26.70 00 N
3 26 0 17.65 00 N
3 25 0 46.98 00 N
3 25 0 20.74 00 N
3 24 0 27.34 00 N
101 26 0 08.69 00 E
101 26 0 33.19 00 E
101 26 0 31.64 00 E
101 26 0 11.55 00 E
101 26 0 30.58 00 E
101 26 0 46.43 00 E
101 26 0 20.04 00 E
101 26 0 28.12 00 E
101 26 0 12.91 00 E
101 25 0 55.22 00 E
Total depth
(m)
pH
6.8
5.4
8.1
9.8
7.9
10.6
6.4
3.2
1.6
1.9
4.3
3.9
4.6
4.4
3.8
4.1
4.9
5.2
5.3
6.7
with dredges were often remined with gravel pumps, the
reason, being that the buckets in the dredges could not
recover cassiterite-rich alluvium trapped within the troughs
of the lime stone pinnacles. There are total 442 mined out
ponds at Bestari Jaya catchment that includes 273 dredged
ponds, 27 dredged sedimentation ponds, 167 gravel pump
mine pits and 108 open cast tailings (Chow and Yunus,
1992).
MATERIALS AND METHODS
Sampling and sample pre-treatment
Due to the large study area, GPS was used to determine the
actual coordinates of the sampling sites and to reconfirm the
location of the sampling site during subsequent sampling
periods. Physico-chemical parameters of water [pH,
temperature, electric conductivity, dissolved oxygen (DO),
total dissolved solids (TDS), chlorides, and ammonium,
nitrates] were analysed in situ by using hydrolab MS5, USA
on a boat. The hydrolab was recalibrated every three hours
or every third site, depending upon which came first. The
meter electrodes were rinsed with de-ionized water before
and after each measurement. A total of 30 water samples
were collected for speciation analysis from 10 different
locations at the catchment in December 2010 (Table 1,
Figure 2). Water samples were collected using a Van Dorn
horizontal (KC-Denmark) water sampler. The sampler was
made of sturdy transparent PVC and had a double release
valve, activated by a drop messenger. The sampler had a
capacity of 5 litres (Figure 3a). The total depth of the each
sampling station was measured with a Garmin Fish Finder
160C (Figure 3b). Three subsequent water samples were
collected at the same location from the midstream after
calculating the total depth at the sampling point. The
samples then transferred to 1 L acid-washed polyethylene
water sampling bottles and refrigerated ( 4 C) immediately to avoid changes in heavy metal distribution among
different phases.
A new sequential extraction leaching procedure for
particulate phase of water samples
Sequential extraction procedures available in the literature
are limited to the analysis of soil and sediments samples
(Borovec et al., 1993; Campanella et al., 1995; Zdenek,
4
Heavy metals in surface waters
Figure 2 Land use map of Bestari Jaya catchment. The yellow area shows the water sampling site for the speciation studies.
1996; Gomez Ariza et al., 2000). A new sequential leaching
procedure was developed followed the five-step and sixstep extraction schemes of Tessier et al. (1979) and Kersten
and Forstner (1986). The method identifies the metal among
five operationally-defined host fractions, namely exchangeable, carbonate, reducible, organically bound and residual
(Figure 4).
Determination of total, dissolved and particulate metal
concentrations
The total metals in water were measured by inductively
coupled plasma optical emission spectrometry ICP-OES
(Perkin-Elmer AA Analyst). The working standards for
chemical analyses were prepared from Perkin-Elmer stock
solutions. The methodology for total metal concentration in
soil was referenced using the (SRM-1643e) Standard
Reference Material (National Institute of Standards &
Technology NIST, USA) and was analysed concurrently
with the water samples. Recoveries of metals were 99% for
tin, 97% for arsenic, 112% for copper, 99% for zinc and
94% for lead. The coefficient of variation was between 3%
and 10% when analysed in triplicate.
To determine the total dissolved and particulate metals,
samples were centrifuged at 8000 rpm for 20 min and the
supernatants filtered through 0.45 mm membrane filters to be
separated into particulate and dissolved fractions. Exactly
40 mL of the filtrate was digested in a Teflon bomb with
5 mL concentrated HNO3 using a microwave digester
(a)
(b)
Figure 3 (a) Van Dorn horizontal water sampler. (b) Garmin fish finder 160C.
Muhammad Aqeel Ashraf, Mohd. Jamil Maah, Ismail Yusoff and Mohamadreza Ghararibreza
5
labile species gives the moderately labile species. Effluent
from the resin column was shaken with the Chelex resins
for 72 h to determine the slowly labile and inert metal
species using the batch procedure (Figura and McDuffie,
1980). The concentrations of Chelex-labile, moderately and
slowly labile as well as the inert metal species were
determined using inductively coupled plasma optical emission spectrometry ICP-OES (Table 2).
Figure 4 Sequential extraction leaching procedure for particulate
phase of water samples.
(Multiwave 3000, Perkin-Elmer) (Horowitz and Elrick,
1987; Moore et al., 1989; Tam and Wong, 2000; Che
et al., 2003) and the digested sample was analysed for the
total dissolved metal concentration using ICP-OES.
The membrane filter after filtration together with the
residue after centrifusion was dried in an oven at 103 C
for 24 h. A known weight of the particulate was digested in
Teflon bomb with 5 mL 30% H2O2 and 5 mL 65% HNO3
using a microwave digester (Usero et al., 1998; Martin
et al., 1998; Morillo et al., 2004; Guevara-Riba et al., 2004;
Yuan et al., 2004) and the digested sample was analysed for
the total particulate metal concentration using graphite
furnace AAS.
Speciation study of dissolved metals
Heavy metals species in the dissolved phase were differentiated utilizing adsorptive stripping voltammeter (ASV)
and their labilities towards the ammonium form of Chelex
resin in successive column and batch procedures (Figura
and McDuffie, 1980). Briefly, an aliquot of the filtered
sample was set aside for the determination of ASV-labile
metal species by differential pulsed ASV using a Metrohm
693 VA processor in combination with a Metrohm 694 VA
stand (multimode electrode operation with a hanging
mercury drop electrode, a AgClyAg reference and a Pt
counter electrode). The remaining sample was passed
through a column packed with the ammonia form of the
Chelex-100 resin of 50 – 100 mesh size (Riley and Taylor,
1968). The difference between the Chelex-labile and ASV-
Speciation study of particulate metals
The sequential extraction leaching procedure for particulate
phase of water samples (Figure 4) generally follows that of
Tessier et al. (1979) and Kersten and Forstner (1986) except
that 1.0 M ammonium acetate instead of 1.0 M magnesium
chloride at pH 7.0 was used as the extraction reagent for the
exchangeable fraction due to lower matrix effect of the
former reagent in the ICP-OES determination. This procedure was developed for the partitioning of particulate metals
into the exchangeable, carbonate, reducible, organicysulfide
and residual fractions. 0.2 g of particulate samples in
triplicate were weighed accurately and put through the
sequential extraction leaching procedure in acid-washed
50 mL polyethylene centrifuge tubes with screw caps.
Each successive extraction was then separated by centrifusion at 3000 rpm for 30 min. All extracts were stored in acid
pre-washed polyethylene bottles for trace metals determinations.
Quality assurance of data
All reagents used were at least of analytical grade. Ultrapure
water of resistivity 18 MW cm was used for the blank and
the preparation of standard solutions. All glassware and
plastics used for the experiments had been previously
soaked in 10% nitric acid (vyv) and rinsed with deionized
water. To evaluate the reproducibility and accuracy of the
method, a lake water reference material (SRM-1643e) was
subjected to the extraction protocol. Three subsamples (sets
A, B and C) were taken through the sequential extraction
leaching procedure in parallel. The results and the relative
standard deviations (RSD) are listed in Table 3.
An internal check was performed on the results of the
sequential extraction by comparing the total amount of
metals extracted by different reagents during the sequential
extraction procedure with the results of the total digestion.
The recovery of the sequential extraction was calculated as
follows:
Recovery ¼
ðC FractionA þ C FractionB þ C FractionC þ C FractionD Þ
C Total Digestion
6100
Results shown in Table 4 indicate that the sums of the four
fractions are in good agreement with the total digestion
results with the satisfactory recoveries (77.7 – 116.7%) and
the method used is reliable and repeatable.
Specification
ASV Labile
Labile
Slowly Labile
Inert
ASV Labile
Labile
Slowly Labile
Inert
ASV Labile
Labile
Slowly Labile
Inert
ASV Labile
Labile
Slowly Labile
Inert
ASV Labile
Labile
Slowly Labile
Inert
ASV Labile
Labile
Slowly Labile
Inert
Metals
Arsenic
Chromium
Copper
Zinc
Lead
Tin
P2
0.1 + 0.06
0.16 + 0.09
0.19 + 0.08
0.17 + 0.03
0.83 + 0.07
0.78 + 0.10
0.67 + 0.41
0.87 + 0.34
1.20 + 0.15
1.64 + 0.12
1.85 + 0.10
1.90 + 0.14
4.34 + 3
2.94 + 2
1.77 + 3
3.54 + 2
8.90 + 3
4.60 + 5
7.96 + 3
4.92 + 2
13.36 + 3
10.11 + 1
18.44 + 5
17.52 + 4
P1
0.30 + 0.1
0.22 + 0.2
0.14 + 0.1
0.40 + 0.1
0.90 + 0.2
0.86 + 0.08
0.97 + 0.04
1.0 + 0.04
1.62 + 0.18
1.90 + 0.90
1.72 + 0.20
1.80 + 0.80
2.34 + 1
3.92 + 2
4.64 + 3
1.93 + 1
10.32 + 3
12.52 + 2
4.25 + 3
6.37 + 2
11.13 + 3
5.49 + 3
20.05 + 4
31.0 + 8
14.08 + 5
6.38 + 2
17.05 + 3
19.48 + 4
5.66 + 2
8.44 + 3
9.67 + 2
9.22 + 4
2.83 + 3
3.96 + 3
2.12 + 2
1.58 + 3
1.52 + 0.18
1.62 + 0.11
1.43 + 0.10
1.79 + 0.14
0.71 + 0.12
0.96 + 0.24
0.65 + 0.18
0.42 + 0.20
0.31 + 0.07
0.25 + 0.12
0.29 + 0.09
0.36 + 0.10
P3
Table 2 Mean dissolved metal concentration at different sampling locations
22.03 + 3
13.57 + 2
24.06 + 3
38.68 + 3
12.04 + 4
10.43 + 3
11.07 + 2
14.39 + 3
2.86 + 3
3.18 + 3
3.94 + 4
2.97 + 3
1.92 + 0.20
1.85 + 0.18
2.0 + 0.20
1.93 + 0.14
0.98 + 0.17
0.87 + 0.14
1.0 + 0.21
0.93 + 0.18
0.72 + 0.20
0.87 + 0.09
0.80 + 0.12
1.0 + 0.21
P4
16.37 + 2
9.25 + 3
16.63 + 2
28.50 + 5
7.44 + 2
8.68 + 3
10.58 + 3
9.34 + 3
2.19 + 3
2.98 + 2
2.05 + 3
2.98 + 2
1.38 + 0.12
1.72 + 0.20
1.64 + 0.12
1.90 + 0.90
0.38 + 0.12
0.56 + 0.10
0.71 + 0.16
0.59 + 0.23
0.25 + 0.12
0.14 + 0.1
0.16 + 0.09
0.14 + 0.1
P5
19.44 + 4
8.82 + 2
18.90 + 3
18.00 + 2
8.28 + 2
4.74 + 1
6.39 + 3
7.60 + 2
1.94 + 2
2.66 + 3
2.26 + 2
1.73 + 3
1.29 + 0.10
1.52 + 0.18
1.80 + 0.15
1.80 + 0.15
0.67 + 0.13
0.73 + 0.11
0.45 + 0.21
0.63 + 0.11
1.1 + 0.07
1.3 + 0.09
0.8 + 0.07
1.3 + 0.03
P6
15.58 + 3
10.06 + 3
19.07 + 4
23.05 + 3
9.47 + 3
8.83 + 2
11.46 + 2
6.46 + 3
2.13 + 3
2.95 + 3
1.95 + 2
2.03 + 2
1.20 + 0.15
1.60 + 0.15
1.68 + 0.12
1.38 + 0.12
0.82 + 0.12
0.65 + 0.10
0.39 + 0.09
0.84 + 0.20
1.0 + 0.03
1.4 + 0.04
1.8 + 0.03
0.14 + 0.1
P7
26.07 + 4
18.90 + 4
25.00 + 2
40.06 + 5
12.06 + 3
14.06 + 3
16.60 + 4
18.00 + 3
3.64 + 4
4.07 + 3
3.49 + 3
3.56 + 2
14.58 + 3
7.52 + 2
13.38 + 3
21.22 + 3
9.66 + 3
10.32 + 2
8.17 + 4
7.43 + 3
1.95 + 2
2.05 + 3
1.67 + 3
2.13 + 3
1.38 + 0.12
1.45 + 0.17
1.68 + 0.12
1.80 + 0.15
0.72 + 0.09
0.58 + 0.02
0.69 + 0.01
0.82 + 0.01
1.02 + 0.24
0.98 + 0.30
1.10 + 0.29
0.91 + 0.32
2.12 + 0.23
1.95 + 0.18
1.88 + 0.19
2.08 + 0.15
0.21 + 0.08
0.18 + 0.32
0.14 + 0.1
0.30 + 0.10
P9
1.2 + 0.28
1.6 + 0.21
0.92 + 0.11
1.0 + 0.23
P8
15.93 + 3
9.27 + 2
14.72 + 4
28.42 + 4
3.88 + 1
6.63 + 2
9.00 + 2
8.31 + 3
2.03 + 3
1.33 + 2
1.87 + 2
1.66 + 2
1.43 + 0.12
1.60 + 0.15
1.82 + 0.11
1.29 + 0.10
0.50 + 0.04
0.69 + 0.05
0.83 + 0.05
0.56 + 0.07
0.28 + 0.12
0.19 + 0.08
0.21 + 0.09
0.10 + 0.02
P10
6
Heavy metals in surface waters
Muhammad Aqeel Ashraf, Mohd. Jamil Maah, Ismail Yusoff and Mohamadreza Ghararibreza
7
Table 3 Reproducibility of sequential extraction procedure
Element
Step
Set A
(n ¼ 3)
Set B
(n ¼ 3)
Set C
(n ¼ 3)
Set D
(n ¼ 3)
Meana
RSDb
Meana
RSDb
Meana
RSDb
Meana
RSDb
Grand
meana
RSDb
Pb
A
B
C
D
E
1.82
1.01
9.7
7.08
8.73
3.12
5.8
2.28
2.2
0.16
2.02
0.02
10.78
6.26
8.28
1.65
3.67
6.01
1.62
0.52
1.95
0.02
10.2
6.69
8.85
2.46
1.24
2.16
1.89
0.48
1.88
1.78
2.1
0.98
1.93
0.91
0.65
0.56
0.34
1.53
1.93
0.02
10.23
6.68
8.62
5.2
34.4
5.3
6.1
3.5
Zn
A
B
C
D
E
4.14
7.03
11.6
15.17
23.78
0.89
0.91
0.7
0.35
0.5
4.59
7.99
11.68
13.1
20.13
1.56
1.62
2.1
1.12
0.56
4.66
7.58
11.42
10.21
26.35
2.88
0.55
0.42
0.58
0.16
4.84
6.91
8.36
13.78
19.25
1.23
0.91
0.65
0.34
0.88
4.46
7.53
11.9
12.46
23.46
6.3
6.4
5.7
3.6
5.9
Cu
A
B
C
D
E
0.26
1.66
2.52
4.56
10.62
1.08
1.46
0.76
0.72
0.66
0.33
1.78
2.72
8.42
5.13
2.13
2.18
0.65
0.96
1.56
0.29
1.59
2.81
10.58
4.82
1.56
0.95
3.33
0.21
0.55
1.46
2.34
1.98
2.71
1.14
1.02
0.48
0.76
0.91
1.42
0.29
1.68
2.68
14.59
4.46
12.2
5.7
5.6
6.2
6.3
AS
A
B
C
D
E
0.2
0.26
0.13
0.2
0.18
2.93
3.97
2.19
1.1
1.23
0.25
0.28
0.12
0.15
0.17
1.65
1.85
2.79
1.71
0.68
0.24
0.33
0.11
0.15
0.19
1.75
1.48
0.99
1.89
2.16
1.72
1.98
1.46
0.91
2
0.21
0.3
0.18
0.25
0.27
0.23
0.32
0.12
0.27
0.18
12.2
6.1
10.2
7.4
4.5
Sn
A
B
C
D
E
65.1
420.98
297.42
123.56
106.26
0.75
0.86
2.46
0.98
0.89
71.87
210.28
136.68
207.02
104.04
2.31
0.62
1.14
2.08
1.96
70.08
228.85
144.9
184.15
106.65
3.11
0.49
0.13
2.28
4.23
71.23
212.67
132.1
276.55
156.02
4.14
0.42
0.1
1.21
5.26
70.08
214.65
144.9
198.38
106.65
6.2
2.6
5.2
2.9
2.6
Cr
A
B
C
D
E
0.49
2.64
19.91
12.1
81.16
2.42
1.68
0.95
0.62
0.33
0.68
2.68
18.84
13.55
74.8
2.81
0.95
0.31
0.29
0.21
0.6
2.71
19.32
12.22
78.16
2.24
0.86
0.64
0.22
0.38
2.1
1.88
5.88
12.76
19.45
1.34
0.93
0.45
1.1
0.45
0.6
2.71
19.32
21.1
69.28
12.8
3.2
2.8
2.8
3.4
a
mg g 1.
b
%.
RESULTS AND DISCUSSION
Water quality characterisation
Water quality parameters for the whole study area are
shown in Figure 5. This shows that there is a variation in
the trend of water quality at the catchment. Average values
for the water quality parameters in the catchment are:
temperature 32.51 C, pH 5, conductivity 1756 mMhosycm,
dissolved oxygen 5.82 mg L 1, total dissolved solids
2998 mg L 1. Downstream (Junction of River Ayer
Hitam þ Sungai Selangor) water quality parameters are:
temperature 32.19 C, pH 6.47, conductivity 1640 mMhos
cm 1, dissolved oxygen 6.59 mg L 1, total dissolved
solids 2654 mg L 1. This shows that variation trends at
Table 4 Recovery of the sequential extraction leaching procedure and the total digestion
Concentration (mg g 1)
Element
Pb
Zn
Cu
As
Sn
a
Sumc
Total
Reference value
25.54 + 0.41
59.82 + 2.74
19.24 + 0.89
0.99 + 0.05
734.65 + 19.5
28.98 + 0.19
52.05 + 1.53
20.13 + 0.69
1.05 + 0.03
945.23 + 8.96
27.0 + 3.0
46.0 + 5.0
22.6 + 2.0
1.12 + 0.12
1013.0 + 44.0
Recovery (1)a
Recovery (2)b
88.1 + 2.1
114.9 + 2.8
95.6 + 3.6
97.4 + 1.9
77.7 + 1.9
107.3 + 2.7
113.2 + 4.2
89.1 + 2.4
93.4 + 1.5
93.3 + 2.4
Recovery (1): SumyTotal
Recovery (2): TotalyReference value
c
Sum ¼ Fraction A þ Fraction B þ Fraction C þ Fraction D þ Fraction E
Where: Fraction A corresponds to exchangeables; Fraction B corresponds to carbonates; Fraction C corresponds to reducibles; Fraction D
corresponds to organics; and Fraction E corresponds to residuals.
b
8
Heavy metals in surface waters
Temperature
pH
Dissolved oxygen mg l1
Electric conductivity mMh0s/cm
Total dissolved solids (mg L1)
Chlorides (mg L1)
Ammoniums (mg L1)
Nitrates (mg L1)
Figure 5 Water quality characterization of the catchment.
Muhammad Aqeel Ashraf, Mohd. Jamil Maah, Ismail Yusoff and Mohamadreza Ghararibreza
all the sampling stations are from upstream to downstream.
Possible factors involved in this variation might include
formation of wetlands, palm oil plantation and the dilution
factor of water as it flows downstream to the river Selangor.
Comparison with Malaysian Interim Water Quality
Standards (INWQS) showed that in all sampling stations
the temperature lies in the normal range, pH is class III,
electric conductivity falls to class III, dissolved oxygen is in
class III, and total dissolved solids are in class III. Acidic
pH and low dissolved oxygen is the characteristic of the
peat swamp water (flowing into the catchment) and also of
the metal and sand mining activity. The high conductivity
values indicate the high concentration of total dissolved
solids. The main source of high total dissolved solids value
is the recent sand mining activity going on in the study area.
This study shows that the water quality is highly degraded
in the area.
Speciation study of dissolved metals
The speciation patterns are controlled by the processes
occurring in the water column such as complexation,
coprecipitation and sorption. Research shows that
complexation is the most important mechanism in controlling speciation in wastewater (Jardim and Allen, 1984).
Complexation of the metal with ligands such as humic type
substances usually leads to the formation of high molecular
weight compounds resulting in an increase of the percentages of less labile species (slowly labile and inert).
Coprecipitation and sorption are basically scavenging
processes involving particulates which remove dissolved
metal species from the solution.
The mean concentrations of the ASV-labile, moderately
labile, slowly labile and inert metal species along the
treatment path are shown in Table 2 whereas the dissolved
metal speciation patterns are depicted in Figure 6. Slowly
labile and inert species formed the dominant fraction. It was
also observed that there was an increase in the less labile
fractions at the expense of the more labile fractions at P4
and P8. This can partly be explained by the complexation
process as evidenced by the decreasing complexing capacity from the mining source to the river outlet. However,
this study could not ascertain what was the dominant
process controlling the metal speciation patterns among
the processes involved, namely complexation, coprecipitation and sorption.
Speciation study of particulate metals
The concentrations of metals in the water samples from
each extraction step are shown in (Figures 7A – C). The
discussion of the distribution patterns of the elements is
divided into four groups depending on the degree of their
association with the different phases. As and Cr are
assigned to a group that are present mainly in the residual
fraction (more than 90% of the total concentration), Cu and
Zn in a group presenting in the residual fraction dominantly
(60% of the total concentration), Sn and Pb in a group with
the large proportion of the total concentration presenting in
the non-residual fractions (FA þ FB þ FC þ FD).
9
Arsenic and chromium
The distribution patterns of As and Cr are illustrated in
Figure 7A. These elements were found in all of the five
operationally defined aquatic phases. The dominant phase
was in the residual fraction, which accounted for more than
50% of the total concentration of metals. The phase
distribution of Cr in this study is similar to the results
reported by (Martin et al., 1998), who found that Cr was
mostly retained in the residual fraction. Metals associated
with the residual fraction are likely to be incorporated in
aluminosilicate minerals and are therefore unlikely to be
released to pore waters through dissociation. The nonresidual fraction (exchangeable þ carbonates þ reducibles
þ organics) for Cr and As were high at P5 and P6
respectively. Since there are only low concentrations of
these elements in the residual fractions, these elements are
unlikely to pose a direct and significant threat to the
surroundings. It should be noted that sediments always
act as reservoir for metals, so their potential risk of
pollution to environment must be considered.
Copper and zinc
The distribution patterns of copper and zinc metals are
illustrated in Figure 7B. These metals were found in all of
the five operationally defined aquatic phases. The dominant
phase was in the residual fraction, which accounted for
more than 50% of the total concentration of metals at most
of the sampling sites, notably for Cu at P8, more than 70%
of the total concentration of metals was in the residual
fraction while for Zn at P6, more than 60% of the total
concentration of metals was in the residual fraction. There
was lift variation in phase distribution for Cu and Zn among
sampling sites except for P8 and P3 in which 22% of the
total Zn was in the fraction B (carbonates). A high copper
content in the residual fraction of river sediments was also
found by Budimir and Marko (1995). The high proportion
of Cu in this fraction is likely due to Cu chemisorbtion on
or incorporated into clay minerals (Pickering, 1986). About
60% of Zn on average was found in the non-residual
fraction in our study. This was higher than 40% reported
by Usero et al., 1998.
Lead and tin
The results of sequential extraction leaching method for Pb
and Sn are illustrated in Figure 7C. Much concern has been
focused on the levels of Pb in water because of their high
toxicity. In the literature, several sequential extraction
procedures, including the BCR protocol, have been used
to obtain information about the distribution of Pb in
sediments (Zdenek, 1996; Serife et al., 2000; Ngiam and
Lim, 2001). Not only sediments but also other samples,
such as soil (Stalikas et al., 1999) and fly ash samples
(Ildiko et al., 1996) have been studied by sequential
extraction methods to find the Pb phase distribution. The
Pb in the organic fraction is the most labile; hence, it may
be available for uptake by the total biota. Higher concentration of metals in this fraction could be regarded as a
pollution indicator (Forstner and Whittmann, 1979). A
10
Heavy metals in surface waters
Figure 6 Speciation of dissolved metals in wastewaters from Bestari Jaya catchment.
considerable amount of Sn was found in all of the five
analysed fractions. The adsorption of metals is directly
related to changes in water ionic strength that probably
affect sorption – desorption processes (Tessier et al., 1979),
and it is known that the carbonates in water contain
significant metal concentrations, which are sensitive to
changes in pH (Thomas et al., 1994).
Moreover, the distributions of Sn also differed significantly with the sampling site. About 80% of Sn is in the
non-residual fractions (exchangeable þ carbonates þ
reducible þ organic) at the site P1 while almost 70% of
the total Sn was found in the organic fraction at site P7.
Evidently the pollution by Sn was mainly from the ex-tin
mining catchment bound with organics, since the sites (P4,
P5, P6 and P7) with higher concentrations of Sn are close to
the rivers and all of them are at the flow directions of River
Ayer Hitam that ultimately ends up in the River Selangor.
The distribution pattern of Pb may be explained by 70% of
the Pb being bound to the organic matter and sulfides at P2.
Whereas approximately 80% of the Pb was bound to the
non residual fraction and 66% was found in the oxidizable
fraction at P4, although the acid soluble proportion was
small but the sum concentration of the non-residual fractions was significant. The metals in this fraction may be
Muhammad Aqeel Ashraf, Mohd. Jamil Maah, Ismail Yusoff and Mohamadreza Ghararibreza
11
(a)
(b)
(c)
Figure 7 Speciation of metals in wastewaters from Bestari Jaya catchment. (a) As and Cr. (b), Cu and Zn. (c), Pb and Sn.
released into environment if conditions become more
oxidising. The planar distribution of the metals indicated
the high pollutions (especially Sn and Pb) at P2, P4 and P7.
The non-residual fractions of Sn and Pb in the water were
found to be high at P4 and P8 (Figures 7a – c). Our results
have verified the assumption that the sampling sites P4 and
P8 are thought to be at the risk of being heavily polluted.
CONCLUSIONS
The newly developed sequential extraction leaching method
for particulate phase of water has been successfully applied
to the analysis of the metal distributions in the mining waste
waters of former tin mining catchment Bestari Jaya,
Peninsular, Malaysia. The results obtained provide the
following information:
(1) As and Cr were found predominantly in the residual
fraction in the studied region. The other elements were
found in all of the fractions with different proportions.
The significant proportion of the total concentration was
also in the residual fraction. The dominant proportion
was found in the non-residual fractions for Sn and Pb,
the sum concentration of the non-residual fractions was
significant.
(2) Overall, the planar distribution of metals indicated that
P4 and P8 were more severely polluted than other
sampling sites by heavy metals, especially by Sn and
Pb. Interventions should be made to reduce anthropogenic discharges in this region.
ACKNOWLEDGEMENTS
This work was carried out at Analytical Laboratory,
Department of Chemistry and partially at Department of
Geology, University of Malaya. We thank the Ministry of
Higher Education, Malaysia for providing a scholarship.
Thanks also go to Institute Pengurusan Dan Pemantauan
Penyelidikan, (IPPP) University of Malaya for funding
(Project No. PS355y2009C).
12
Heavy metals in surface waters
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