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Micronutrient Fractionation in Coal Mine-Affected AgriculturalSoils, India
Rahul Agrawal1 • Bijendra Kumar1 • Kumari Priyanka1 • Chandravir Narayan1 •
Kriti Shukla1 • Jhuma Sarkar1 • Anshumali1
Received: 10 April 2015 / Accepted: 1 February 2016
� Springer Science+Business Media New York 2016
Abstract Assessment of the anthropogenic impacts on
bioavailability, mobility, immobility and toxicity of four
micronutrients (Cu, Fe, Mn, and Zn) were carried out by
Community Bureau of Reference (BCR) fractionation
scheme in agricultural soils (n = 10) around Jharia coal-
field, eastern India. The relative abundance of micronutri-
ents was as follows: Fe[Mn[Zn[Cu. The enrichment
factor was[1 for Zn (6.1) and Cu (1.8) near coal mining
area indicated toward soil pollution due to coal mining
activities and application of inorganic fertilizers. The Igeovalues of micronutrients were\0 suggest no pollution with
respect to Cu, Fe, Mn and Zn. Correlation analysis showed
geogenic origin of soil micronutrients and derived mainly
from weathering of minerals present in the parent rock. The
mean values of Cu, Mn and Zn were less than certified
reference material indicating highly leached agricultural
soils in the study region. BCR fractionation of micronu-
trients showed that a single element could not reveal all
types of chemical reactions occurring in soil consortium.
Keywords Acid digestion � Sequential extraction � Soil �Coalfield
Coal plays an important role in energy generation and
approximately 27 % of the world’s energy consumption
originates from the incineration of coal (Bhuiyan et al.
2010). In India, coal based energy generation accounts for
55 % of country energy needs and open cast mines
produced 91.65 % of total coal production (463 MT) dur-
ing 2012–2013 (Ministry of Coal 2013). It is reported that
4 m3 of overburden produced per ton of mined coal
(Juwarkar and Jambhulkar 2008) and the production of 463
MT of coal through opencast mining will result in
1850 Mm3 overburdens. For producing this much amount
of coal it is estimated that land at the rate of about 60 km2
is degraded in direct mining and approximately 75 km2 per
year for external overburden and spoil dumps (Kundu and
Ghose 1997).
The Jharia Coal Field (JCF) is located in the eastern
India, has the potential of contributing significantly to
resolving the current energy crisis in the subcontinent. The
expected production target during 2014–2015 for JCF is 35
MT. The cumulative effects of exploration activities at
multiple sites have the potential to drive environmental
change, particularly from a larger regional perspective. A
report on Indian opencast mine showed dust emission from
haul, transport, and communication roads was 78–124.5,
48–98.2, and 38.7–50.3 t/km2/month, respectively (Chau-
lya et al. 2011). Mandal et al. (2012) reported higher dust
deposition in summer (26.56 t/km2/month) than monsoon
(12.68 t/km2/month). Some of the trace elements present in
coal are of health concern (Masto et al. 2011) and they may
be enriched in the coal dusts. Understanding the risk of
agricultural soil pollution due to enrichment of trace ele-
ments around coal mining areas is of utmost importance in
view of implications for environmental health. Soil is a
prominent sink for trace elements originated from geogenic
and anthropogenic sources. Trace metals in the soil derived
from weathering of country rock and, in some cases,
anthropogenic inputs from industrial process (Kersten and
Forstner 1989). Rout et al. (2013) reported higher con-
centrations of Cu, Pb, and Zn in dust samples around the
JCF. Recent studies on ecological risk assessment of soil
& Rahul Agrawal
1 Laboratory of Biogeochemistry, Department of
Environmental Science and Engineering, Indian School of
Mines, Dhanbad, Jharkhand 826004, India
123
Bull Environ Contam Toxicol
DOI 10.1007/s00128-016-1745-3
contamination by trace elements in the vicinity of JCF
reveal pollution load due to coal mining activities, mine
fires, windblown dust, dumping of crust materials etc.
(Masto et al. 2011; Pandey et al. 2015a, b). But, these
studies were mainly focused on total metal concentrations
in airborne particulate matter and soils. Previous studies do
not highlight that what happens with micronutrients in soil
system contributed by anthropogenic sources. Answer to
this question basically reveals the fate of micronutrients in
the agricultural soils, especially in the vicinity of mining
facilities. The optimum plant growth and crop yield
depends not only on the total amount of micronutrients
present in the soil at a particular time but also on their
chemical forms that may influence their environmental
mobility and availability to organisms. The biogeochemi-
cal reactions of micronutrients depend on their different
chemical forms in soil consortium and sensitive to soil
texture, organic matter, pH, electrical conductivity etc. To
address this, selective chemical extraction methods can be
used to estimate the concentrations of micronutrients
bound to particular soil phases (Rao et al. 2008). The
modified version of the three-steps Community Bureau of
Reference (BCR) procedure (Ure et al. 1993; Sahuquillo
et al. 1999) was used for trace metal fractionation and
assess the spatial variation in the concentrations of differ-
ent chemical forms of micronutrients in agricultural soils
around JCF. Exchangeable fraction involves weakly
adsorbed trace metals retained on the solid surface by
relatively weak electrostatic interaction and can be released
by ion-exchangeable processes etc. Remobilization of
metals can occur in this fraction due to adsorption des-
orption reactions and lowering of pH (Narwal et al. 1999).
Reducible fraction involves trace metals that are released in
reducible conditions such as those bound to hydrous oxides
of Mn and Fe. The fraction obtained when trace metals
bound to iron and manganese oxides, a reducing solution is
used as the extractant (Gleyzes et al. 2002). The informa-
tion obtained with the analysis of soil after sequential
chemical extraction may be useful to better understand the
mobility/immobility, adsorption/desorption, bioavailability
and finally origin of metal contamination in agricultural
soils of the JCF region.
Materials and Methods
Jharia Coal Field (JCF) is one of the most important coal
mining areas in India containing proven coal reserves of
approximately one billion tones in a crescent-shaped basin
of approximately 400 km2. It is roughly elliptical or sickles
– shaped, located in Dhanbad district of Jharkhand lies
between 23�390N to 23�500N latitudes and 86�050E to
86�300E longitudes (Fig. 1). The main natural drainage is
the Damodar River, which is supplemented by perennial
streams (e.g. Tisra, Chatkari, Katri, Khudia, Jamuniya,
Kumari and Bansjora). The region is important for its large
reserves of lower gondwana coal distributed in the JCF.
The average elevation of the area is 201 m above msl.
Climatically the JCF is of tropical monsoonal nature with
its hot summer, dry and cold winter. The annual average
temperature is about 25�C and it receives annually about
900–1300 mm of rainfall. The total land covered in the JCF
is 392.85 Km2 in which the agricultural land area is
10.08 %. From the cropping area data, it can be inferred
that the unirrigated kharif (monsoon) crops continue to
cover 95 % of the total cropped area. Rabi (winter) irri-
gated crops cover only 3 % of the total cropped area.
Summer irrigated crops are only 1 %. Rabi crops and
summer crops are not popular in the district due to lack of
irrigation facilities (CGWB 2013). Agriculture is mostly
rain fed and comprises Kharif crop, while Rice is the main
crop. Maize, gram, wheat, oil seeds, vegetables, etc. are the
main food crops in the district. Guava, papaya and jack
fruit are the main horticultural crops. The agricultural
activities are concentrated in the eastern and western
regions of JCF. The agricultural soils are red (mostly of the
residual type is known as lateritic soils are formed at high
temperature and high rainfall) and sandy intertwined with
rolling undulation. The entire Jharia is drained by two
small streams Ekra Nala and Kori Jore River. Water bodies
in Jharia region are not perennial and become dry during
the hot seasons and filled during monsoon seasons. The
surface drainage pattern and its surrounding area in the
coalfield have undergone a major change due to mining and
other anthropogenic activities, resulting in low irrigation
facility on the one hand and poor ground water recharge on
the other. The whole study area is under direct/indirect
impact of the coal mining activities, therefore the selection
of control site is not possible for the comparison of the
data, if we select control site in outside the study area then
there is chances of changes in geological formations.
Hence, in this study we could not select any control site.
Ten soil samples were collected in the monsoon (August
2014) from agricultural fields located in the eastern (four
sampling sites) and western regions (six sampling sites)
around JCF. In each site, a plot of one hectare was selected
and five soil cores (5 cm inner diameter each) of 0–15 cm
depth were randomly sampled from five points (north,
south, east, west and central) and mixed to obtain a com-
posite sample. The soil samples were stored in acid-cleaned
HDPE bottles in frozen state using portable ice box to
minimize the biogeochemical alterations and transported to
the laboratory for analytical processing. In laboratory, the
bulk soil samples air-dried, broken into pieces, grinded well
in the mortar and pestle to crush the aggregate particles for
further physico-chemical and metal extraction analysis.
Bull Environ Contam Toxicol
123
The pH and electrical conductivity (EC) were measured
on a 1:2.5 soil: water (w/v) ratio (Tan 2005); water holding
capacity (WHC) was determined by keeping fresh soil
overnight with water at a 1:2 ratio (Harding and Ross
1964); bulk density (BD) by Core method (Blake 1965);
soil organic carbon (SOC) and soil organic matter (SOM)
by using the Walkley and Black dichromate oxidation
method (1934). The total concentration of micronutrients
was determined by digestion with aqua regia
(HCl:HNO3 = 3:1), according to the ISO 11466 (ISO
1995).
Micronutrient fractionation in soil samples were ana-
lyzed with the modified version of the BCR three-steps
sequential extraction procedure (Rauret et al. 1999): First
step (Exchangeable and weak acid soluble fraction, F1-
Exc): 1 g of soil sample was extracted with 40 mL of
0.11 mol/L acetic acid solution by shaking in a mechanical,
end-over-end shaker at 30 ± 10 rpm at 22 ± 5�C for 16 h.
The extract was separated by centrifugation at 30009g for
20 min, collected in polyethylene bottles and stored at 4�Cuntil analysis. The residue was washed by shaking for
15 min with 20 mL of doubly deionised water and then
centrifuged, discarding the supernatant. Second step (Re-
ducible fraction, F2-Reduc): 40 mL of 0.5 mol/L hydrox-
ylammonium chloride solution was added to the residue
from the first step, and the mixture was shaken
30 ± 10 rpm at 22 ± 5�C for 16 h. The acidification of
this reagent is by the addition of a 2.5 % (v/v) 2 mol/L
HNO3 solution. The extract was separated and the residue
was washed as in the first step. Third step (Oxidizable
fraction, F3-Oxi): 10 mL of 8.8 mol/L hydrogen peroxide
solution was carefully added to the residue from the second
step. The mixture was digested for 1 h at 22 ± 5�C and for
1 h at 85 ± 2�C, and the volume was reduced to less than
3 mL. A second aliquot of 10 mL of H2O2 was added, the
mixture was digested for 1 h at 85 ± 2�C, and the volume
was reduced to about 1 mL. The residue was extracted with
50 mL of 1 mol/L ammonium acetate solution, adjusted to
pH 2.0, at 30 ± 10 rpm and 22 ± 5�C for 16 h. The
extract was separated and the residue was washed as in
previous steps. Residue from the third step (Residual
fraction, F4-Res): the residue from step 3 was digested with
aqua regia, following the ISO 11466 (ISO 1995). In this
case, the amount of acid used to attack 1 g of sample was
reduced to keep the same volume/mass ratio: 7.0 mL of
HCl (37 %) and 2.3 mL of HNO3 (70 %) were added.
Three independent replicates were performed for each
sample and blanks were measured in parallel for each set of
analysis using aqua regia extraction and BCR procedure,
respectively. Micronutrients concentrations in the extracts
obtained at each step were determined by using an atomic
absorption spectrophotometer (GBC Avanta PM).
To determine the deficiency or enrichment of micronu-
trients, comparisons are made to background concentration
in the Earth’s crust. The enrichment factor (EF) was cal-
culated with respect to Fe according to the following
equation: EF = (Cx/CFe)Soil/(Cx/CFe)Earth’s crust where (Cx/
CFe)Soil is the ratio of concentration of the element being
determined (Cx) to that of Fe (CFe) in the soil sample and
(Cx/CFe)Earth’s crust is the ratio in the reference Earth’s crust
(Atgin et al. 2000). Iron was selected as a reference ele-
ment because it is a major sorbent phase for trace metals,
and is a quasi conservative tracer of the natural metal-
bearing phases in environmental components (Schiff and
Fig. 1 Study area of Jharia coalfield (ten sampling sites)
Bull Environ Contam Toxicol
123
Weisberg 1999; Turner and Millward 2000). Contamina-
tion factor (CF) was calculated by dividing the concen-
tration of examined element (Ci) by geochemical
background value (Bi) of that element (Hakanson 1980):
CF = Ci/Bi. Pollution Load Index (PLI) was calculated by
the expression given by Tomlinson et al. (1980):
PLI = (CF1 9 CF2 9 CF3 9 ��� 9 CFn)1/n where n is set
of polluting elements. The geoaccumulation index (Igeo)
for the metals was determined using Muller’s expression
(1979): Igeo = Log2 (Cn)/1.5(Bn) where Cn is the concen-
tration of metals examined in soil samples and Bn is the
geochemical background concentration of the metal,
average shale (Turekian et al. 1961). The factor analysis of
BCR fractions was carried out by using ‘‘Statistical
Package for Social Sciences (SPSS), version 16.0.’’ The
‘‘principal component analysis’’ and ‘‘Varimax rotation’’
were used for extracting and deriving factors, respectively.
Results and Discussion
Physico-chemical properties of the agricultural soils are
presented in Table 1. The soil pH ranged from 6.3 to 7.8.
The electrical conductivity varied from 49.6 to 1295 lS/cm. The water holding capacity showed variation from
20.5 % to 51.5 %. Bulk Density of soils varied from 1.3 to
1.6 gm/cc. Soil organic matter (SOM) varied from 1.2 %
to 6.1 %. The mean value of SOM is high (3.8 %) indi-
cating deposition of orthodox (simple) organic carbon in
form of coal dust.
Based on aqua regia acid digestion for pseudo-total
metal contents in soils, the descending order of micronu-
trients was Fe[Mn[Zn[Cu. The mean concentrations
of Cu, Fe, Mn and Zn were 31.2, 19,786.2, 215.0 and
126.7 mg/kg, respectively. The Cu and Zn showed high
values than the world normal limit and less than the critical
soil concentration. Critical soil concentrations of trace
elements are the threshold concentrations in the soil
beyond which detrimental effects on vegetations are evi-
dent (Alloway 2013). The EF value between 0 and 1
suggest that the element is completely from crustal sources
or natural process, while the EF values [1 suggest
anthropogenic origin of trace elements (Zsefer et al. 1996).
The EF value of Fe and Mn indicates weathering of coarser
quartzitic sandstone and grits in the study area (Table 1).
The EF value of Mn (0.7) shows its conservative behavior
in the agricultural soils. Higher enrichment values of Zn
(6.1) and Cu (1.8) in mining areas with negligible Igeovalues indicating anthropogenic factors increasing pollu-
tion of soils due to coal mining activities. Bhuiyan et al.
(2010) reported that the soil with higher Zn attributed to
the geochemical weathering of sulfide minerals derived
from mine drainage. Long-term coal mining activities, coal Table
1Summaryofphysico-chem
ical
param
etersandmicronutrients
Range/meanvalues
pH
EC(ls/
cm)
MC
(%)
WHC
(%)
BD
(g/
cc)
SOC
(%)
SOM
(%)
Cu(m
g/
kg)
Fe(m
g/kg)
Mn(m
g/
kg)
Zn(m
g/
kg)
PLI
Range
6.3–7.8
49.6–1295
2.0–5.6
20.5–51.5
1.3–1.6
0.8–3.5
1.2–6.1
22.5–42.6
9718–33,032
113–323.23
61.7–158.9
0.4–0.7
Mean
7.0
240
3.3
39
1.4
2.2
3.8
31.2
19,786.2
215.0
126.7
0.6
EF
1.8
10.7
6.1
CF
0.8
0.5
0.3
1.2
I geo
\0
\0
\0
\0
WorldNorm
al(Bhuiyan
etal.2010)
24
26,000
550
60
Indianstatus(Singh2009)
1.8–960
4000–273,000
37–11,500
7–2960
Criticalsoilconcentration(A
lloway
2013)
60
–1500
70
Bull Environ Contam Toxicol
123
burning, and mine fires have been primary contributors of
Cu. Oorts (2013) and Pandey et al. (2015a, b) also found
high concentrations of Cu in PM10 in coal mining and mine
fire affected areas. Mandal and Sengupta (2006) found that
the topsoils and the soils collected from the different depth
profiles surrounding a coal industries in India were enri-
ched in the trace elements. The mean CF values of Cu, Fe
and Mn showed medium contamination category (\1) for
while moderate ([1 to\2) for Zn in the JCF. Based on PLI
(0.6) agricultural soils were not polluted because greater
number of elements (Cu, Fe and Mn) in medium contam-
ination category than moderate polluting element (Zn).
Hence, the soils near coal mining area or distant from
mining activities were showing no pollution load. The Igeovalues of micronutrients were\0 suggest no pollution with
respect to Cu, Fe, Mn and Zn.
The agricultural sites in the vicinity of coal mining areas
showed higher concentrations of Cu and Fe, especially in
the western Jharia region (JCF 5, JCF 6, JCF 7, JCF 8, JCF
9 and JCF 10) (Fig. 2). The area under open cast mining is
greater in the western JCF than eastern JCF region.
Moreover, the distance between agriculture land and min-
ing areas are physically separated by geomorpholical bar-
riers in the eastern Jharia. This imparts greater degree of
remoteness in the eastern Jharia compared to the western
Jharia. Thus soil/coal soil sources seems reasonable, par-
ticularly in the light of the fact that large exposed surface
areas of earth and stockpiles of coal piled around the mines
and at railway sidings often serve as a source of fugitive
dust. Hence, the general tendency for the levels to decline
gradually towards the non-mining areas, especially in the
eastern JCF and clearly point towards mining operations as
the primary source of suspended particulate matter (SPM)
in the region. In the monsoon, the mean value of SPM was
135 and 110 lg/m3 in the western and eastern JCF,
respectively (Agrawal 2015). Singh et al. (2012) studied
the geogenic sources of Cu, Mn, Fe and Zn in the Damodar
basin. Banerjee (2000) reported high concentrations of
trace elements in coal of JCF.
Pearson correlation coefficient was analyzed to ascertain
the sources of micronutrients in agricultural soils (Table 2).
The strong association corresponding to the couples Cu–
Zn, and Mn–Zn indicates geogenic origin of soil
micronutrients and derived mainly from weathering of
minerals present in the country rock. This also shows co-
precipitation of Cu with (hydro)oxides in soil material. The
positive correlation between Mn–pH and Mn–EC indicates
complex behavior of Mn in soils and is controlled by dif-
ferent environmental factors of which pH–EC conditions
are the most important (Kabata-Pendias 2000). These
chemical processes result into the formation of a large
number of oxides and hydroxides of Mn that reflect vari-
able stability and properties in agricultural soils around
JCF region. The oxides of Mn show large surface area,
which is not only important for soil reactions but also
highly associated with activities of microbes in agricultural
Fig. 2 Spatial variation in concentrations of a Cu, b Fe, c Mn, and d Zn
Bull Environ Contam Toxicol
123
soils (Kabata-Pendias 2011). The significant correlation
between Zn and organic matter (0.55) indicates biogenic
sources of Zn (Singh 2008). Correlation analysis by Pandey
et al. (2015a, b) shows natural and anthropogenic sources
of soil trace elements around JCF. Global comparison
shows higher concentrations of Fe, Mn and Zn in the coal
mine affected agricultural soils in northern Bangladesh
(Bhuiyan et al. 2010) and Gangreung coal field in South
Korea (Kim and Chon 2001).
In order to identify the fractions of micronutrients, the
results based on the three-step BCR fractionation proce-
dure is given in Table 3. The recovery of the BCR proce-
dure was calculated by dividing the sum of sequential
extractions of micronutrients with the values of micronu-
trients obtained by aqua regia digestion: Recovery
(%) = [(F1 ? F2 ? F3 ? F4)/(aqua regia diges-
tion)] 9 100. The mean recovery values indicate good
agreement between the total concentration and the sum of
BCR results. This shows that the precision and accuracy of
the sequential extraction procedure is inherently good, the
limiting factor being the inherent heterogeneity of the soil
samples (Tessier et al. 1979; Burt et al. 2003). In this study,
the mean values of Cu, Mn and Zn were less than certified
reference material indicating highly leached agricultural
soils in the JCF region.
The high concentrations of Exc and Reduc fractions of
micronutrients (Cu and Zn) were found in the soils around
western JCF region (Fig. 3). The Oxi fractions of Cu and
Zn showed less spatial variations in eastern and western
JCF region. The large spatial variation in the Res fraction
of Fe reveals loss of clay minerals in the agricultural soils
in JCF region. The fractions of Mn show some similarities
with that of Cu and Mn, thus, Mn shows higher availability
than Fe in most samples.
The descending order of Exc, Reduc and Oxi fraction are
as follows: Exc-Zn (44.1)[Mn (43.3)[Cu (14.6)[ Fe
(0.1); Reduc-Cu (48.2)[Mn (45.7)[Zn (31.7)[ Fe
(10.9); Oxi-Cu (18.6)[Zn (11.2)[Mn (2.5)[ Fe (1.4);
Res-Fe (87.7)[Cu (18.7)[Zn (12.9)[Mn (8.5). The
extraction of Zn was greater in the Exc fraction, while Cu
was dominantly extracted as Reduc fraction. The Mn was
more or less equally fractionated in Exc and Reduc frac-
tions. The percent values of micronutrients based on the
sums of the first three fractions (F1 ? F2 ? F3) show
following order: Mn (91.5 %)[Zn (87.1 %)[Cu
(81.3 %)[ Fe (12.4 %). The less concentration of
micronutrients in the Oxi fraction indicates highly oxidized
nature of soil microclimate and might be responsible for
the greater organic matter mineralization and insignificant
complexation of micronutrients in the soil organic residues
in the JCF region. The results show that the most mobile
and bioavailable micronutrient is Mn followed by Zn and
Cu, and least mobile and conservative element is Fe. The
Res fraction of Fe shows its strong affinity to minerals and
resistant components of the solid matrix, strongly bounded
to clay minerals and biologically unavailable (Kartal et al.
2006).
BCR fractionation of micronutrients reveals soil pollu-
tion in the JCF region. For example, anthropogenically
enriched Zn is dominantly found in the Exc and Reduc
fractions. Beckett (1989) showed that the Exc fraction
involves weak electrostatic interaction and ion-exchange-
able processes such as adsorption–desorption reactions and
lowering of pH. The micronutrients recovered in these
conditions may be thought to have been present as co-
precipitated with carbonate minerals but also as specifically
sorbed to some sites of the surface of clays, organic matter
Table 2 Summary of Pearson correlation matrix
Cu Fe Mn Zn pH EC OM
Cu 1
Fe -0.01 1
Mn 0.03 0.38 1
Zn 0.52 0.16 0.60 1
pH 0.43 -0.08 0.5 0.43 1
EC -0.03 0.36 0.7 0.15 0.58 1
OM 0.33 -0.43 0.17 0.55 0.12 -0.15 1
Table 3 Summary of comparative results of analysis of BCR fractions and the aqua regia digestion
Elements Sum of Extraction fractions
(F1 ? F2 ? F3 ? F4)
Pseudo-total Digestion (aqua
regia)
Recovery
(%)
BCR-141 R BCR-
142
NIST
2711
Mean Mean Mean Mean Mean Mean
(Pueyo et al.
2008)
(Bakircioglu et al.
2011)
Cu 29.4 31.2 94.7 47 25.3 114
Fe 19,113 19,786 95.7 – – –
Mn 198.9 215 93.1 270 527 –
Zn 131.5 126.7 104.7 – 79.6 350.4
Bull Environ Contam Toxicol
123
and Fe/Mn oxyhydroxides. The Cu pollution in soils shows
its greater concentrations in Reduc and Oxi fractions and
indicates the prevalence of strong redox conditions in soils.
The Reduc fraction act as sink for heavy metals because Fe
and Mn oxyhydroxides present as coating on mineral sur-
faces or as fine discrete clay particles in soil matrix. This
may involve precipitation, adsorption, surface complex
formation and ion exchange. The amorphous Fe and Mn
oxide have greater potential to sink micronutrients than its
crystalline Fe/Mn oxyhydroxides (Dong et al. 2000). Low
concentrations of micronutrients in Res fraction, except Fe,
show presence of highly weathered secondary minerals in
agricultural soils. The high Res Fe shows crystalline
structures of minerals responsible for greater leaching of
Cu and Zn (Davidson et al. 1998; Kartal et al. 2006).
Leaching of micronutrients accounts for poor correlation
between BCR fractions and pH/organic carbon and
indicates their multiple sources in the soils (Table 4),
hence, increase the potential exposure risk associated with
anthropogenic enrichment of metals.
PCA analysis shows that the factor 1 (F1) of Reduc, Oxi
and Res fractions have positive loading on Cu, Mn and Zn
(Table 5). Hence, F1 may be classified as geogenic factor
due to crustal origin of micronutrients in these fractions
and the similar geology of the eastern and western JCF
regions. The F1 of Exc fraction shows negative loading on
Cu, Mn and Zn except Fe indicating greater variation in the
origin of readily extractable micronutrient in soil. Similar
trend is shown by the factor 2 (F2) of BCR fractions
highlights that anthropogenically contributed metals are
weakly bound to soil constituents. Thus results of PCA not
only substantiate the geologic origin, but also reveal
specific differences in the anthropogenic origin of
micronutrients in agricultural soils in the JCF region.
Fig. 3 BCR fractions of micronutrients: a Cu, b Fe, c Mn and d Zn
Table 4 Summary of Pearson
correlation matrix for BCR
fractions
Element Exch Reduc Oxi Res Total BCR
pH OC pH OC pH OC pH OC pH OC
Cu -0.15 -0.19 0.39 0.31 0.73 0.26 -0.33 0.31 0.50 0.24
Fe -0.69 -0.07 0.00 -0.33 0.15 -0.57 -0.10 -0.43 -0.09 -0.46
Mn 0.10 0.49 0.34 -0.01 -0.23 0.23 -0.33 0.31 0.24 0.24
Zn 0.18 0.42 0.47 0.31 -0.18 0.41 -0.17 -0.11 0.28 0.48
Bull Environ Contam Toxicol
123
Acknowledgment
Authors are grateful to Ministry of Human Resource
Development, Government of India for funding the
research project of Mr. Rahul Agrawal (2013MT0143) at
Indian School of Mines, Dhanbad, Jharkhand, India. We
appreciate the anonymous reviewers for their valuable
comments, criticisms, and suggestions.
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Exc-Fe 0.93 -0.16 Reduc-Fe 0.85 0.11 Oxi-Fe 0.15 0.82 Res-Fe 0.80 0.05
Exc-Mn -0.76 -0.43 Reduc-Mn -0.09 0.93 Oxi-Mn 0.89 0.00 Res-Mn -0.01 0.95
Exc-Zn -0.16 0.89 Reduc-Zn 0.79 -0.19 Oxi-Zn 0.77 -0.01 Res-Zn 0.62 0.57
Eigen value 1.53 1.53 1.78 1.26 1.94 1.22 1.80 1.23
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