GEXPLO-04924; No of Pages 8
Journal of Geochemical Exploration xxx (2011) xxx–xxx
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Journal of Geochemical Exploration
journal homepage: www.elsevier.com/locate/jgeoexp
Differences in the bioaccessibility of metals/metalloids in soils from mining and
smelting areas (Copperbelt, Zambia)
Vojtěch Ettler a,⁎, Bohdan Kříbek b, Vladimír Majer b, Ilja Knésl b, Martin Mihaljevič a
a
b
Institute of Geochemistry, Mineralogy and Mineral Resources, Charles University in Prague, Faculty of Science, Albertov 6, 128 43 Praha 2, Czech Republic
Czech Geological Survey, Geologická 6, 152 00 Praha 5, Czech Republic
a r t i c l e
i n f o
Article history:
Received 29 September 2010
Accepted 13 August 2011
Available online xxxx
Keywords:
Bioaccessibility
Topsoil
Metals
Arsenic
Copperbelt
Zambia
a b s t r a c t
Differences in the total and bioaccessible concentrations of As and metals (Co, Cu, Pb, Zn) in topsoils
(n = 107) from the mining and smelting areas in the Zambian Copperbelt were evaluated. The mean total
concentrations of metals and As in topsoils were generally 2 to 7× higher in the smelting area, indicating significantly higher effect of smelter dust fallout on the degree of topsoil contamination. The contaminant bioaccessibility was tested by an US EPA-adopted in vitro method using a simulating gastric fluid containing a
0.4 M solution of glycine adjusted to pH 1.5 by HCl. Higher bioaccessibilities in the smelter area were observed for As and Pb, attaining 100% of the total metal/metalloid concentration. The maximum bioaccessibilities of As and Pb in the mining area were 84% and 81%, respectively. The ranges, mean and median
bioaccessibilities of Co, Cu and Zn were similar for the two areas. The maximum bioaccessibilities of Co, Cu
and Zn were 58–65%, 80–83% and 79–83%, respectively. The obtained data indicate that a severe health
risk related to topsoil ingestion should be taken into account, especially in smelting areas.
© 2011 Elsevier B.V. All rights reserved.
1. Introduction
The mining and smelting activities are responsible for extensive contamination of soils. The smelter emissions as well as wind-blown dust
from mine tailings and smelter slag dumps are generally the main
point sources of soil pollution (Ettler et al., 2005a, 2009, 2011; Kříbek
et al., 2010; Šráček et al., 2010; Vítková et al., 2010). Studies dealing
with the bioavailability and bioaccessibility of metals/metalloids contaminants in highly-polluted soils are extremely useful in understanding the possible effect on biota (Bosso and Enzweiler, 2008; Chen et
al., 2009; Douay et al., 2008; Juhasz et al., 2011; Roussel et al., 2010).
In particular, human exposure to contaminants in mining/smelting
areas has implications for health risk assessment (Banza et al., 2009;
Roussel et al., 2010).
The “bioaccessible” fraction is defined as the amount of contaminant
that is mobilized from the solid matrix (e.g. soil) in the human gastrointestinal tract and becomes available for intestinal absorption. The “bioavailable” fraction is the fraction of contaminant that can reach the
blood stream from the gastrointestinal tract (Morrison and Gulson,
2007; Roussel et al., 2010; Ruby et al., 1999). In the last two decades, a
number of laboratory methods (often called PBET, physiologicallybased extraction tests) have been developed to investigate in vitro the
oral (ingestion) or respiratory bioavailability/bioaccessibility of metals
from polluted geomaterials (soils, wastes) (Oomen et al., 2002, 2003a,
⁎ Corresponding author. Tel.: + 420 221 951 493; fax: + 420 221 951 496.
E-mail address: [email protected] (V. Ettler).
2003b; Ruby et al., 1993; Schroder et al., 2004). These methods and
their applications have recently been reviewed by Plumlee and Ziegler
(2006) and Plumlee et al. (2006) and have led to the development of
standardized tests adopted by the U.S. Environmental Protection Agency
(US EPA, 2007). Although this test was validated by in vivo tests only for
Pb and As (Ruby et al., 1993, 1996; Schroder et al., 2004), it has also been
widely adopted to study the bioaccessibility of other inorganic contaminants in polluted soils (e.g., Kim et al., 2002; Madrid et al., 2008a,
2008b).
The present study is based on our previous screening soil survey
discriminating the contaminant sources in the area of intense copper–
cobalt mining and smelting in the Zambian Copperbelt (Kříbek et al.,
2010). It has been reported that children can ingest between tens and
hundreds of milligrams of soil per day via hand-to-mouth behaviour.
Up to 200 mg soil/day was observed by van Wijnen et al. (1990) and,
for the 90th percentile, typically between 40 and 100 mg/day. More
recently, Özkaynak et al. (2011) used a USEPA Stochastic Human
Exposure and Dose Simulation Model (SHEDS) to show that up to
1367 mg soil/day can be ingested with a 95th percentile of 176 mg/day
and mean value of 41 mg/day. Thus, a severe risk of exposure to metallic
contaminants in highly polluted areas of the Zambian Copperbelt
can be anticipated. High exposure to metal contaminants expressed
particularly as high urinary Co concentrations was also reported
from the nearby Copperbelt mining and smelting district in the
Democratic Republic of Congo (Banza et al., 2009). As a result, this
study is focused on investigation of the differences in gastric bioaccessibility of metals (Co, Cu, Pb, Zn) and As in topsoils from two distinct areas with contrasting pollution sources (mining vs. smelting).
0375-6742/$ – see front matter © 2011 Elsevier B.V. All rights reserved.
doi:10.1016/j.gexplo.2011.08.001
Please cite this article as: Ettler, V., et al., Differences in the bioaccessibility of metals/metalloids in soils from mining and smelting areas
(Copperbelt, Zambia), J. Geochem. Explor. (2011), doi:10.1016/j.gexplo.2011.08.001
V. Ettler et al. / Journal of Geochemical Exploration xxx (2011) xxx–xxx
(US EPA, 2007). An aliquot part of each sample was finely ground in
an agate mortar (Fritsch Pulverisette, Germany) and used for subsequent bulk chemical analysis.
2. Materials and methods
2.1. Soil sampling
Based on extensive data on the spatial distribution of inorganic contaminants in the Zambian Copperbelt district (Kříbek et al., 2010), two
hot-spots with contrasting sources of pollution were selected for investigation of the metal/metalloid bioaccessibility: 1) a mining area in the
vicinity of Chingola with a number of active open-pit mines (Nchanga
and Chingola) (n = 52 soil samples) and 2) a smelting area in the vicinity of Kitwe with the Nkana Cu smelter active between 1932 and 2009
(n = 55 soil samples) (Fig. 1). According to Mihaljevič et al. (2010),
the prevailing wind direction in the studied areas is NE–SW between
November and February (wind speed up to 2 m/s) whereas, during
the rest of the year, stronger winds with a velocity of N 3 m/s in the direction SE-NW prevail. The wind direction has a significant effect on
the spatial distribution of airborne contamination in the vicinity of
point pollution sources in the Zambian Copperbelt (Ettler et al., 2011;
Kříbek et al., 2010; Mihaljevič et al., 2010). In the mining area, the
dust fallout originates mainly from open-pit mining operations, ore
crushers, ore/concentrate transport and mine tailings. In contrast, the
areas around smelters are mainly affected by the smelter emissions
and fine-grained slag dust generated by slag treatment plants (crushing
prior to further re-smelting and further metal recovery) (Kříbek et al.,
2010; Vítková et al., 2010).
Only topsoil samples (0–2 cm depth) were considered in this
study, being the most probable source of potential health risk due
to ingestion. According to Soil Taxonomy (Soil Survey Staff, 2010),
the soils were characterized as Oxisols. The samples were stored in
polyethylene (PE) bags, air-dried to constant weight on returning to
the laboratory and sieved through a clean 0.25-mm stainless steel
sieve (Retsch, Germany). The 0.25-mm sieved fraction was used for
the pH determination and bioaccessibility testing, because this particle size is representative of that which adheres to children's hands
2.2. Soil analysis
The pH measurements were performed according to Pansu and
Gautheyrou (2006) in a 1:5 (w/v) soil-deionized water suspension
after 1-h agitation using a Schott Handylab pH meter. Total organic
carbon (Corg) and total inorganic carbon (Ccarb) contents were determined using Eltra CS 500 analyzer (Eltra, Germany). Total sulphur
(Stot) was determined on Eltra CS 530 analyzer (Eltra, Germany).
The pseudo-total digests of soil samples were obtained by a standardized aqua regia extraction protocol according to ISO Standard
11466 (ISO, 1995). Certified reference material (CRM) BCR-483 (sewage sludge-amended soil) and standard reference material (SRM)
NIST 2711 (Montana soil) were used to control the accuracy of the
aqua regia pseudo-total digestion, yielding satisfactory values (Table 1).
Although NIST 2711 has element values certified for total digests, the
aqua regia pseudo-total digests were in good agreement with the certified values as well as with the aqua regia data recently published for
this SRM (Karadaş and Kara, 2011). Total digests were analyzed for the
content of Co, Cu, Pb and Zn by a Perkin Elmer 4000 flame atomic absorption spectrometer (FAAS) or by a Thermo Scientific Xseries 2 inductively
coupled plasma mass spectrometer (ICP-MS). The As concentrations
were determined by a Perkin Elmer 503 hydride generation atomic absorption spectrometer (HG-AAS) or by ICP-MS.
The bioaccessibility test was performed according to the US EPA
(2007) protocol, identical with the Simple Bioaccessibility Extraction
Test (SBET) adopted by the British Geological Survey (Oomen et al.,
2002). The extraction fluid contained 0.4 M glycine (30.028 g glycine
dissolved in 800 ml of deionized water), adjusted to pH 1.5 ± 0.05 by reagent grade HCl (Merck, Germany), finalized by diluting to 1 l by deionized water (MilliQ+, Millipore Academic, USA) and pH verification. A
o
o
24 E 25 E
DR CONGO
TANZANIA
ZAMBIA
o
MALAWI
2
ANGOLA
12 S
Chingola
study
area Copperbelt
Province
UE
IQ
B
AM
Z
MO
ZIMBABWE
N
Kitwe (Nkana)
r
ive
R
fue
Ka
smelter
mines
50 km
Fig. 1. The map of the Zambian Copperbelt location and study area (dashed line).
Please cite this article as: Ettler, V., et al., Differences in the bioaccessibility of metals/metalloids in soils from mining and smelting areas
(Copperbelt, Zambia), J. Geochem. Explor. (2011), doi:10.1016/j.gexplo.2011.08.001
V. Ettler et al. / Journal of Geochemical Exploration xxx (2011) xxx–xxx
concentrations of metals and As are significantly higher in the smelting
area (Table 2), indicating the higher exposure of these topsoils related
to the intense smelter dust fallout. The results of the spatial distribution
of As, Co, Cu, Pb and Zn (including selected data from Kříbek et al., 2010)
and their bioaccessible fractions are given in Figs. 2 to 6. The bioaccessible fraction of metals and As (expressed as % of the total concentration)
is reported in Table 3 and the relationships between the total and
bioaccessible concentrations are expressed as correlation coefficients
in Table 4.
Significant differences in As bioaccessibility were observed between
the mining and smelting areas, with generally significantly higher
values for the smelter site (Fig. 2, Table 3). The bioaccessible As in the
mining area varied from 2% to 84% of the total As concentration (median: 9%) and the highest values were observed in the vicinity of the
Nchanga open pit mine and the Mindolo mine tailing pond (Fig. 2). In
contrast, the As bioaccessibility in the smelting area varied from 19%
to 100% of the total As concentration (median: 38%). Topsoils with the
highest As bioaccessibility were located downwind (W and SW) and
in the direct vicinity of the smelter, with another hot-spot located in
the low As zone close to the active shafts in the N of the studied area
(Fig. 2). Relatively good linear relationships between bioaccessible
and bulk As concentrations were found particularly for the smelting
area (R = 0.973, p b 0.001), whereas a lower correlation was found for
the mining area (R = 0.878, p b 0.001) (Table 4).
The statistical data (Table 3) and Fig. 3 indicate that Co accessibility is similar for both zones. The Co bioaccessibility ranges from 12%
to 58% (median: 33%) in the mining area and from 7% to 65% (median: 38%) in the smelting area (Table 3). Zones with the highest Co
bioaccessibilities are generally located in the hot-spots corresponding
to the highest bulk Co concentrations (R = 0.914, p b 0.001 for the
mining area and R = 0.931, p b 0.001 for the smelting area) (Table 3).
Copper is the most important contaminant with concentration
attaining 10080 ppm in the mining area (median: 457 ppm) and
27410 ppm in the smelting area (median: 2027 ppm) (Table 2). The
bioaccessible fraction is similar in both areas, ranging from 38% to
83% of the total concentration (median: 58%) and 45–80% (median:
60%) in mining and smelting areas, respectively (Table 3). The highest
values of bioaccessible Cu in the mining area were observed in the vicinity of the active mines (N, NE of Chingola city center) and corresponded well to topsoils with the highest total Cu concentrations
(R = 0.973, p b 0.001) (Fig. 4 and Table 4). Statistically significant correlation was found between total and bioaccessible Cu in the smelting
area (R = 0.997, p b 0.001), with the highest bioaccessible fraction
downwind the smelter (Fig. 4 and Table 4).
Lead was found in topsoils in significantly lower concentrations
than Cu and Co (Table 2), being considered a minor contaminant
in the studied areas. Significant differences in Pb bioaccessibility
were observed between the mining and smelting areas (Fig. 5 and
Table 3). Significantly higher Pb bioaccessibilities were found in
Table 1
Quality control of the aqua regia pseudo-total digestion (mean ± standard deviation).
Code
Co (ppm)
Cu (ppm)
Pb (ppm)
Zn (ppm)
BCR 483 (n = 1)
measured
–a
certified
–
–
–
353
362 ± 12
554
501 ± 47
1014
987 ± 37
NIST 2711 (n = 3)
measured
91.2 ± 1.6
certifiedb
105 ± 8
7.5 ± 0.4
10c
104 ± 28
114 ± 2
1118 ± 25
1162 ± 31
335 ± 7
350.4 ± 4.8
a
b
c
As (ppm)
3
–, not given.
Certified for total content, not for aqua regia pseudo-total digestion.
Noncertified value (for information only).
solid-to-fluid ratio of 1/100 was used for the extraction. A mass corresponding to 0.5 g of sieved soil sample was placed in 100-ml highdensity polyethylene (HDPE) bottles (P-lab, Czech Republic), 50 ml of
extraction fluid was added and the mixture was agitated for 2 h at
37 °C. After the extraction procedure, the extract was filtered through
0.45-μm nitrocellulose membrane filters (Millipore, USA), diluted and
analyzed for the total contents of As, Co, Cu, Pb and Zn by HG-AAS,
FAAS or ICP-MS. The bioaccessible concentrations of metals and As
were expressed in mg/kg (ppm) and converted to % amount of total
content. The extraction was performed in triplicate for ten randomly selected samples and indicated that the reproducibility of the procedure
was generally below 10%, but never exceeded 20% RSD (higher standard
deviations were observed for some samples with bioaccessible concentrations below 5 ppm). The bioaccessibility test employed, simulating
gastric conditions with low pH, is a suitable predictor for estimation of
the “worst case” situation for physiologically relevant fasting conditions
(Oomen et al., 2002; Ruby et al., 1993).
2.3. Data treatment
The basic statistics of the obtained data were calculated by Excel
2003 (MS Office, Microsoft, USA). The grid was calculated and the results of the spatial distribution of metal/metalloid contaminants (bulk
concentrations and bioaccessibility data) were mapped using Surfer
8 (Golden Software, USA). The correlation coefficients were calculated using the NCSS statistical software (NCSS, USA).
3. Results
Basic statistical data for the two contrasting sites including selected
physico-chemical parameters and bulk concentrations of the studied
contaminants are given in Table 2. Both sites have similar pH values
ranging from acidic to circumneutral (~4 to 7, mean and median~ 5)
(Table 2). Slightly higher values of Stot, Ccarb and Corg were detected
for topsoils from the smelting area (Table 2). Similarly, the total
Table 2
Basic statistics for selected physico-chemical and chemical parameters of the studied soils.
Code
Mining area (Chingola) (n = 52)
Smelting area (Kitwe) (n = 55)
a
Min
Max
Mean
Q1 a
Q2 (Median)a
Q3 a
Min
Max
Mean
Q1 a
Q2 (Median)a
Q3 a
pH (std units)
Stot (%)
Ccarb (%)
Corg (%)
As (ppm)
Co (ppm)
Cu (ppm)
Pb (ppm)
Zn (ppm)
4.16
7.74
5.58
4.77
5.29
6.46
4.36
7.85
5.79
4.93
5.59
6.51
0.004
0.336
0.047
0.016
0.026
0.056
0.004
0.453
0.076
0.022
0.038
0.074
0.004
2.80
0.225
0.042
0.075
0.155
0.030
10.4
0.883
0.060
0.150
0.310
0.09
5.81
1.92
0.94
1.65
2.63
0.05
12.8
2.90
1.31
2.23
3.84
0.04
5.51
1.34
0.37
0.77
1.39
0.16
255
9.52
1.09
2.91
6.26
2.00
260
48.3
7.75
17.5
60.3
10
606
140
31.5
90
182
88.0
10080
1380
225
457
1585
365
27410
4010
990
2027
5932
4.00
63.0
17.0
4.00
11.0
22.0
4.00
480
35.6
4.00
16.0
36.5
6.00
159
33.0
15.0
24.0
36.5
7.00
450
62.7
17.0
44.0
74.5
Q1 = first quartile = 25th percentile; Q2 = second quartile = 50th percentile (Median); Q3 = third quartile = 75th percentile.
Please cite this article as: Ettler, V., et al., Differences in the bioaccessibility of metals/metalloids in soils from mining and smelting areas
(Copperbelt, Zambia), J. Geochem. Explor. (2011), doi:10.1016/j.gexplo.2011.08.001
4
V. Ettler et al. / Journal of Geochemical Exploration xxx (2011) xxx–xxx
Fig. 2. Spatial distribution of As in topsoils, bulk concentrations (ppm) and the bioaccessible fraction.
the smelting area, accounting for 25–100% of the total Pb concentration (median: 75%), corresponding well to the zones downwind
from the smelter stack and with the lowest bioaccessibility values
upwind and in the vicinity of active mine shafts (Fig. 5). The strong
correlation between the total and bioaccessible Pb concentrations in
the smelting area was indicated by the high value of the coefficient
of correlation (R = 0.996, p b 0.001) (Table 4). In the mining-affected
area, the bioaccessible Pb ranged from 11% to 81% of the total Pb
concentration (median: 40%). Lower statistical relationships were
observed between bioaccessible and total Pb concentrations (R=0.869,
pb 0.001), indicating that high values of bioaccessible Pb were also
found in zones with lower total contents, nevertheless located mostly
in the NE–SW direction, corresponding to the distribution of windblown dust from the active mines (Fig. 5).
The bioaccessible fraction of Zn was similar for both studied
areas (Fig. 6). In the mining area, the Zn bioaccessibility ranged
Fig. 3. Spatial distribution of Co in topsoils, bulk concentrations (ppm) and the bioaccessible fraction.
Please cite this article as: Ettler, V., et al., Differences in the bioaccessibility of metals/metalloids in soils from mining and smelting areas
(Copperbelt, Zambia), J. Geochem. Explor. (2011), doi:10.1016/j.gexplo.2011.08.001
V. Ettler et al. / Journal of Geochemical Exploration xxx (2011) xxx–xxx
5
Fig. 4. Spatial distribution of Cu in topsoils, bulk concentrations (ppm) and the bioaccessible fraction.
from 23% to 83% (median: 43) and the relationship between the
total and bioaccessible Zn was statistically significant (R = 0.959,
p b 0.001) (Tables 3 and 4). In the smelting area the Zn bioaccessibility accounted for 16–79% of the total Zn concentration (median:
50%) (Table 3). Slightly lower correlation between the total and
bioaccessible Zn concentrations was observed (R = 0.946, p b 0.001)
(Table 4).
4. Discussion
4.1. Spatial distribution and bioaccessibility of As and metals in mining
and smelting areas
Significant differences in the spatial distribution of metals and As
were observed between the mining and smelting areas. In addition
Fig. 5. Spatial distribution of Pb in topsoils, bulk concentrations (ppm) and the bioaccessible fraction.
Please cite this article as: Ettler, V., et al., Differences in the bioaccessibility of metals/metalloids in soils from mining and smelting areas
(Copperbelt, Zambia), J. Geochem. Explor. (2011), doi:10.1016/j.gexplo.2011.08.001
6
V. Ettler et al. / Journal of Geochemical Exploration xxx (2011) xxx–xxx
Fig. 6. Spatial distribution of Zn in topsoils, bulk concentrations (ppm) and the bioaccessible fraction.
to old mining activities, emissions from the Nkana smelter at Kitwe
contributed to higher concentrations of metals and As (Figs. 2–6,
Table 2). The dispersal of contaminants in the vicinity of mines and
smelters is highly dependent on the local meteorological conditions,
mainly on the prevailing wind direction (Ettler et al., 2005a, 2011;
Kříbek et al., 2010). In addition, dust emitted by the smelters generally consists of fine-grained materials with extremely high specific
surface area and high solubility, whereas particles generated by ore
crushers in mining areas are generally larger in size (Ettler et al.,
2005b, 2008; Kříbek et al., 2010). Thus, the areas affected by smelterderived particles are generally larger than areas polluted by mining
activities (Figs. 2–6). Kříbek et al. (2010) also emphasized the differences in the chemistry of the dust fallout in mining and smelting
areas. Dust samples collected in the vicinity of open pit mines
have only slightly increased concentrations of Cu (corresponding
to traces of chalcopyrite). In contrast, dusts trapped in the vicinity
of the Zambian smelters are more enriched in “volatile elements”,
such as Pb or As (Kříbek et al., 2010). The relationship between
Table 3
Bioaccessible fractions of As and metals expressed as a percentage of total concentrations in soils.
Code
Mining area (Chingola) (n = 52)
Smelting area (Kitwe) (n = 55)
Min
Max
Mean
Q1 a
Q2 (Median)a
Q3 a
Min
Max
Mean
Q1 a
Q2 (Median)a
Q3 a
As
Co
Cu
Pb
Zn
2
84
12
5
9
14
19
100
40
28
38
43
12
58
34
28
33
41
7
65
38
31
38
49
38
83
57
49
58
64
45
80
60
56
60
63
11
81
41
24
40
55
25
100
73
67
75
86
23
83
45
34
43
53
16
79
49
40
50
57
a
Q1 = first quartile = 25th percentile; Q2 = second quartile = 50th percentile (Median); Q3 = third quartile = 75th percentile.
these smelter-derived elements is also documented by their statistically significant correlation in smelter-affected soils (R = 0.896,
p b 0.001).
However, total concentrations of contaminants are not appropriate
for consideration of metal mobility and bioavailability (Rieuwerts,
2007). Thus, metal fractionation studies based on chemical extractions
are often used for this purpose (Ettler et al., 2005a, 2011; Rieuwerts,
2007). For example, significantly higher mobility of Pb and Zn, expressed
as the exchangeable fraction obtained by sequential extraction analysis,
was reported by Li and Thornton (2001) at smelting sites in comparison
with the mining sites in the Derbyshire district (England). In soils at other
smelting sites, high percentages of exchangeable (bioavailable) metals
attaining ~50% of the total concentration were also obtained by single
and sequential extractions (Chen et al., 2009; Ettler et al., 2005a, 2011).
Generally, the lower metal and As bioaccessibilities found in the
mining area close to Chingola (Figs. 2–6; Table 3) are in agreement
with numerous studies dealing with mining-related soil contamination.
It is important to note that the windblown dusts from mine wastes,
mine tailing ponds and ore crushers still correspond to the most important sources of soil pollution in the Zambian mining areas, but are generally more coarse-grained (N50 μm) than those from smelting facilities
(Kříbek et al., 2010; Šráček et al., 2010). Plumlee and Ziegler (2006)
state that predominant metal-bearing minerals in mine waste and tailings are primary metal sulphides and sulphosalts and, to a lesser extent,
secondary minerals formed by weathering of the ore deposit prior to
mining. However, taking into account the hour-scale residence in the
stomach, particles containing sulphides should not dissolve substantially under gastric conditions. Similarly, acid-stable Pb sulphates and
phosphates should not dissolve to a significant degree (Plumlee and
Ziegler, 2006; Ruby et al., 1999). The in vivo bioaccessibility studies of
Pb uptake by swine also indicated that Pb sulphides and sulphates are
significantly less dissolved than Pb oxides and carbonates (Casteel et
al., 2006; Plumlee et al., 2006).
In contrast, the smelter dusts are generally composed of more soluble metal-bearing compounds (Ettler et al., 2005b, 2008). Recent investigations of the pH-dependent leaching behaviour of the copper smelter
Please cite this article as: Ettler, V., et al., Differences in the bioaccessibility of metals/metalloids in soils from mining and smelting areas
(Copperbelt, Zambia), J. Geochem. Explor. (2011), doi:10.1016/j.gexplo.2011.08.001
V. Ettler et al. / Journal of Geochemical Exploration xxx (2011) xxx–xxx
7
Table 4
Correlation coefficients of the total (M) and bioaccessible As and metal concentrations (Mbio) for the studied soils.
Code
As
Co
Cu
Pb
Zn
Mining area
Smelting area
Asbio
Cobio
Cubio
Pbbio
Znbio
Asbio
Cobio
Cubio
Pbbio
Znbio
0.878*
0.607*
0.483*
0.205
0.511*
0.761*
0.923*
0.815*
0.151
0.230
0.610*
0.914*
0.973*
0.008
0.129
0.309
0.143
0.016
0.869*
0.528*
0.315
0.001
− 0.049
0.522*
0.959*
0.973*
0.483*
0.701*
0.899*
0.784*
0.252
0.931*
0.409
0.292
0.383
0.527*
0.706*
0.997*
0.594*
0.605*
0.882*
0.395
0.582*
0.996*
0.957*
0.643*
0.325
0.375
0.870*
0.946*
*Statistically significant correlation at the probability level p b 0.001.
flue dust from one smelter in the Zambian Copperbelt indicated that
primary chalcanthite (CuSO4·5H2O) was readily dissolved, especially
under acidic conditions and large amounts of Cu were released (Vítková
et al., 2011). Similarly, mineralogical analysis of the highly polluted topsoil collected close to the Nkana smelter revealed the presence of
smelter-derived dust with soluble Cu oxides and sulphates, which
were responsible for the high vertical mobility in the soil profile (Ettler
et al., 2011). Another important parameter of smelter-emitted dust particles is their small grain size with diameters generally below 10 μm and
subsequent high reactivity in aqueous and soil environments (Ettler et
al., 2005b; Vítková et al., 2011). Significantly higher contaminant bioaccessibilities were also recently reported for the finest fractions of the
highly polluted soils (Juhasz et al., 2011; Madrid et al., 2008a, 2008b).
The study by Roussel et al. (2010) was based on investigation of the
Cd, Pb and Zn bioaccessibilities in soils heavily polluted by Pb-Zn
smelters in northern France. They showed that the Pb and Zn gastric
bioaccessibilities were between 33% and 76% (median: 65%) and between 17% and 85% (median: 48%), respectively. These data correspond
well to the bioaccessible fractions of Pb and Zn from the studied topsoils
in the smelting area close to Kitwe (Nkana) (Table 3). Although the nature of smelter emissions is probably the main reason for higher metal/
metalloid bioaccessibilities in the smelting area, the slag particles emitted by slag crushers should also not be neglected. Such fine-grained
slags can also be partly dispersed in the vicinity of the Nkana processing
complex, where old Nkana slags are crushed and transported to the
Chambishi Co smelter for reprocessing and subsequent Co recovery
(Ettler et al., 2011; Kříbek et al., 2010; Vítková et al., 2010). Bosso and
Enzweiler (2008) studied the Pb bioaccessibility in highly polluted
soils from one Brazilian Pb smelting site and found that, under simulated gastrointestinal conditions, an average value corresponding to 70% of
bioaccessible Pb was observed. Morrison and Gulson (2007) investigated the bioaccessibility of metals in base metal smelter slags from North
Lake Macquaire, New South Wales, Australia and found particularly
high bioaccessibilities between 80% and 100% for fine grain-size fractions (b 20 μm). Together with the small size of particles emitted from
the smelter stacks and slag reprocessing units (crushers), the bioaccessibility of some metals/metalloids can be significantly higher in the
smelting areas, as observed in this study (Figs. 2–6; Table 3).
Unfortunately, no soil bioaccessibility data are available in the literature for Co and our study is the first investigation of the simulated gastric
Co bioaccessibility in the Copperbelt area. Nevertheless, the mineralogical investigations of mining and smelting wastes from the Copperbelt
province indicated that Co is mainly present as sulphides, intermetallic
compounds and spinels/silicates and to a lesser extent as secondary alteration products (e.g. carbonates) (Kříbek et al., 2010; Vítková et al.,
2010). Thus, compared to other contaminants, a smaller proportion of
Co is mobile (Ettler et al., 2011) and bioaccessible (Fig. 2 and Table 3).
This finding is consistent with the fact that Co alloys and spinels were
found to be resistant in the gastric fluids in contrast to Co carbonates,
sulphates and oxides (Stopford et al., 2003) (unfortunately, no data are
available for Co sulphides). Based on this research and previous screening studies (Ettler et al., 2011; Kříbek et al., 2010), the migration and bioavailability of Co in highly polluted soils should be further investigated.
4.2. Environmental and health implications
Ruby et al. (1996) in their pioneer study showed that the bioavailable fraction (i.e. entering the blood stream from the gastrointestinal
tract) of Pb and As obtained by a simple in vitro physiologically based
extraction test (PBET) correlated well with in vivo tests. Similarly,
Schroder et al. (2004) studied various in vitro methods to predict Pb
bioaccessibility in soils and found reasonable agreement with in vivo
bioavailable Pb estimated from blood data underlining that such simple extraction methods can be used for inexpensive, screening investigation of contaminated soils. Although the simple gastric conditions
simulations (similar to the model used in the present study) are
thought to overestimate the total bioaccessibility of metals/metalloids
due to the aggressive pH of ~ 1.5 (corresponding to the fasted conditions), such bioaccessibility models represent robust tools for human
risk assessment in areas with high levels of metals/metalloids in soils.
Based on the approach of Karadaş and Kara (2011), we calculated the
daily amount of ingested contaminants assuming a soil ingestion rate
of 100 mg per day (Table 5). The data were compared with the tolerable
daily intake (TDI) values calculated for a child weighting 10 kg using the
human-toxicity maximum permissible levels published by Baars et al.
(2001). In particular, Cu and Co in some smelting soil samples exceeded
and As and Pb approached the TDI values in agreement with other studies of metal bioaccessibility (Juhasz et al., 2011; Karadaş and Kara, 2011;
Roussel et al., 2010), indicating again that a higher risk can be expected
in smelter-affected areas. High Co levels in human urine recently
reported by Banza et al. (2009) in the Cu–Co mining districts of the
Democratic Republic of Congo indicate its relative bioavailability and
underline the importance of ecotoxicological studies in these areas.
Our study is the first step in the human risk assessment in the areas of
the mines and smelters of the Zambian Copperbelt and can significantly
contribute to the choice of strategies for reducing human exposure to
high levels of metals and metalloids in soils. More detailed epidemiological studies (similar to those carried out in the nearby mining
areas, e.g. Banza et al., 2009) examining the health effects of exposure
in various segments of the population, as well as the exact routes of exposure (diet, dust ingestion, dust respiration), should be performed.
Table 5
Calculated amounts of contaminant ingested (μg) assuming the soil ingestion rate of
100 mg per day for the studied soils.
Code
Mining area (Chingola)
(n = 52)
Smelting area (Kitwe)
(n = 55)
TDI (μg/day; child 10 kg)a
Min
Max
Mean
Median
Min
Max
Mean
Median
As
Co
Cu
Pb
Zn
0.004
0.08
0.01
0.004
0.01
6.77
0.35
0.09
10
0.20
8.70
1.69
0.70
0.20
36.5
5.90
3.20
14
4.30
579
84.3
22.3
19.6
1710
254
119
1400
0.40
4.90
0.896
0.40
0.40
34.2
2.69
1.60
36
0.30
10.8
1.59
0.90
0.40
22.5
3.05
1.90
5000
a
TDI = Tolerable daily intake calculated from the human-toxicity maximum permissible levels of Baars et al. (2001) in micrograms per day for a child weighting 10 kg.
Please cite this article as: Ettler, V., et al., Differences in the bioaccessibility of metals/metalloids in soils from mining and smelting areas
(Copperbelt, Zambia), J. Geochem. Explor. (2011), doi:10.1016/j.gexplo.2011.08.001
8
V. Ettler et al. / Journal of Geochemical Exploration xxx (2011) xxx–xxx
5. Conclusions
This study was focused on investigation of the bioaccessibility of
As and metals (Co, Cu, Pb, Zn) in highly contaminated topsoils from
contrasting areas in the Zambian Copperbelt (mining- vs. smeltingaffected sites). The contaminant bioaccessibility was tested by an in
vitro method using a simulating gastric fluid containing a 0.4 M solution of glycine adjusted to pH 1.5 by HCl. Significantly higher bioaccessibilities in the smelter area were observed for As and Pb, attaining
100% of the total metal/metalloid concentration. The maximum bioaccessibilities of As and Pb in the mining area were 84% and 81%, respectively. The bioaccessibilities of Co, Cu and Zn were similar for both areas,
with maximum values corresponding to 58–65%, 80–83% and 79–83%,
respectively. The obtained data and daily intakes calculated for a
child weighting 10 kg and assuming a soil intake of 100 mg per day
indicate that a severe health risk related to topsoil ingestion should
be taken into account, especially in smelting areas. Direct exposure
of inhabitants to high levels of metals (especially Cu and Co) in the
soils of the Zambian Copperbelt must be further evaluated.
Acknowledgements
This study was supported by the Czech Science Foundation (GAČR
205/08/0321) and the Ministry of Education, Youth and Sports of the
Czech Republic (MSM 0021620855). The research was carried out
within the framework of IGCP Project No. 594 (“Assessment of impact
of mining and mineral processing on the environment and human
health in Africa”). Dr. Madeleine Štulíková is thanked for revision of
the English in the manuscript. Three anonymous reviewers helped
significantly to improve the original version of the manuscript.
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Please cite this article as: Ettler, V., et al., Differences in the bioaccessibility of metals/metalloids in soils from mining and smelting areas
(Copperbelt, Zambia), J. Geochem. Explor. (2011), doi:10.1016/j.gexplo.2011.08.001