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Environmental Science and Pollution
Research
ISSN 0944-1344
Volume 19
Number 1
Environ Sci Pollut Res (2012) 19:269-281
DOI 10.1007/s11356-011-0530-4
Metal contamination of soils and
plants associated with the glass industry
in North Central India: prospects of
phytoremediation
Mayank Varun, Rohan D’Souza, João
Pratas & Manoj S.Paul
1 23
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RESEARCH ARTICLE
Metal contamination of soils and plants associated
with the glass industry in North Central India:
prospects of phytoremediation
Mayank Varun &Rohan D’Souza &João Pratas &
Manoj S. Paul
Received: 17 February 2011 / Accepted: 20 May 2011 / Published online: 7 July 2011
#Springer-Verlag 2011
Abstract
Introduction The effect of the glass industry on urban soil
metal characterization was assessed in the area of Firozabad,
India. A comprehensive profile of metal contamination was
obtained in five zones each containing five specific sites.
Findings Zn, Cd, and As showed a greater accumulation,
whereas accumulation of Ni and Cu was high in limited
samples. Positive correlation was found for the metal pairs
Cu-Zn, Cu-Co, and Cu-Cr at P<0.01. Moderate positive
correlation was also observed between Zn-Co, Mn-Cd,
Mn-As, Pb-As, and Ni-Cu at P<0.05. Integrated contam-
ination indices indicate that 60% of the sites were heavily
contaminated while 28% were moderately contaminated.
Phytoremedial potential of native flora (twenty herbs, three
shrubs, and two grasses) was also assessed by analyzing
their metal uptake. Individual elements displayed remark-
ably different patterns of accumulation in soils as well as in
plants. Mn, Zn, Cu, and As were predominantly partitioned in
shoots, Co and Cd in roots while Pb, Cr, and Ni almost equally
between shoots and roots. Most plants exhibited capabilities in
mobilizing Co, Pb, Cr, and Ni in the root zone.
Conclusion Potential phytoextractors include Datura
stramonium and Chenopodium murale while phytostabil-
izers include Calotropis procera and Gnaphalium luteo-
album. Poa annua showed potential in both categories.
None of the species showed phytoremedial potential for
Co and Ni.
Keywords Glass industry .Phytoextraction .
Phytostabilization .Metal pollution .Soil
1 Introduction
Metal contamination of soil is a threat to the quality and
well-being of all components of the biosphere. Contamina-
tion sources include, among others, mining and refining of
metals, sludge dumping, energy and fuel production, traffic
emissions, power transmission, and intensive agriculture.
These elements persist in the pedosphere and tend to
accumulate in animals and humans through food, air, and
water. Lead, cadmium, copper, zinc, nickel, chromium, and
arsenic are the elements most frequently reported to have
the highest impact on organisms (Vamerali et al. 2010).
Firozabad in North Central India is an old, rapidly
expanding town known for its thriving glass industry. It
produces excellent quality glassware which is exported all
over the world. Glass products manufactured in the city
include chandeliers, lanterns, decorative items, tableware,
bottles, bulbs, laboratory apparatus, and glass accessories
for automobiles as well as glass bangles and beads. As per
the District Industry Centre, there are about 185 registered
large- and medium-sized functional production units with
approximately 4,000 affiliated small- and micro-scale
processing and finishing units spread all over the town.
Employing about 40,000 workers, the industry melts
around 2,000 metric ton glass every day and boasts an
annual turnover of nearly 40 billion rupees (approx. $ 890
million). The industry utilizes almost 1.2 million m
3
natural
gas annually. Apart from the major raw materials like silica,
Responsible editor: Elena Maestri
M. Varun (*):R. D’Souza :M. S. Paul
Department of Botany, St. John’s College,
Agra (U.P.) - 282 002, India
e-mail: 30mayank@gmail.com
J. Pratas
Departmento de Ciências da Terra, Universidade de Coimbra,
Coimbra 3000 272, Portugal
Environ Sci Pollut Res (2012) 19:269–281
DOI 10.1007/s11356-011-0530-4
Author's personal copy
quartz, calcite, and feldspar, the glass industry uses refining
chemicals like KNO
3
, NaNO
3
,Na
2
SO
4
, ZnO, AsO
3
, and
SbO
3
and coloring agents like CuO, CoO, CrO
3
, PbCr
2
O
7
,
CdS, MnO
2
, and NiO
2
. The industry employs finishing and
decorating procedures like lustring and metallizing that
involve spraying or vacuum-coating metal salt and acid
mixtures. All this is done by workers, often in the open,
without any precautions taken for themselves or the
environment mostly in small units involving four to five
workers. This makes the task of regulating and monitoring
extremely difficult. Although all broken/scrap glass is
recycled as cullet, fine dust containing metals accumulates
at waste disposal sites. Besides, industrial effluents being
released into the drainage system or simply on wastelands
adjacent to factories also contain some metal salts. These
effluents are treated only in the larger, regulated factories
before being released, not in the numerous, scattered
workshops. As a result, the town and its residents are
subjected to high pollution levels. The main action taken by
the government is the provision of Compressed Natural Gas
to production units, thus, replacing conventional fuels like
residual furnace oil, diesel, kerosene, coal, wood, etc.,
which were responsible for increasing the pollution load of
air. However, combined efforts to remediate and reclaim
soil and water sources are urgently needed.
Phytoremediation involves the use of plants and their
associated microbes for environmental cleanup (Raskin et
al. 1994). Phytoextraction is one of the strategies of
phytoremediation, where plants are used to take up and
accumulate metals in aboveground biomass, which can be
harvested and removed from the site. Phytoextraction
efficiency is determined by two key factors: metal accu-
mulating capacity and biomass production (McGrath and
Zhao 2003). Thlaspi caerulescens and Alyssum bertolonii
are known metal hyperaccumulators which are able to take
up and accumulate appreciable amounts of metals in their
tissues. Their use in situ is limited because they grow
slowly, have shallow root systems, and are not very
widespread geographically. Phytostabilization, another phy-
toremedial technique, does not aim to remove but only to
reduce the mobility and bioavailability of pollutants in soil.
Allowing wild species to remediate soils is an attractive option
since they do not require any agronomic inputs. The outcome
is, thus, both site remediation and ecological restoration. A
range of native, well-adapted plants have been investigated
and used for metal bioindicatoring and phytoremedial
purposes including Sesbania, Avena, Crotalaria, Crinum
asiaticum,Calotropis procera, lemongrass, vetiver, and wild
grasses (Yang et al. 2003;Uraguchietal.2006;D’Souza et
al. 2010; Varun et al. 2011a).
Phytoremediators are often metal-specific and perform
well for a particular metal or a group of metals incombination.
Moreover, phytoremedial potential of plants is also influenced
by mobility and availability of metals in soil and plants, and
thus the Bioabsorption coefficient (BAC), Bioconcentration
factor (BCF), and Translocation factor (TF) can be used to
assess their phytoremedial potential. BAC is defined as metal
content in shoot/metal content in soil; BCF as metal content in
root/metal content in soil, and TF as metal content in shoot/
metal content in root. Plants exhibiting BAC and TF values
greater than 1 are generally considered promising phytoex-
tractors (Fitz and Wenzel 2002), while plants with high BCF
and low TF values are considered potential phytostabilizers
(Mendez and Maier 2008). Yoon et al. (2006)demonstrated
Phyla nodiflora having TF values of 12 and 6.3 for Cu and
Zn as a suitable phytoextractor and Gentiana pennelliana
having BCF values of 11, 22, and 2.6 for Pb, Cu, and Zn as a
phytostabilizer.
Stringent standards for maximum permissible limits of
metals in soils have been set by agencies like the World
Health Organization (WHO) and the United States Envi-
ronment Protection Agency (USEPA). In the past few years,
metal contamination of soils and water from industrial and
traffic sources in urban environment has been studied
(Crnkovićet al. 2006). Still, there is a paucity of detailed
studies on metal pollution and its remediation within
industrial zones in developing countries. Phytoremediation
is especially suited for such countries where techniques that
do not require extensive inputs in terms of labor, expertise,
and cost are vital due to lack of funds. Few in situ and ex
situ studies have concentrated on evaluating the phytoex-
traction potential of native species (D’Souza et al. 2010;
Zhuang et al. 2007; Saraswat and Rai 2009). In this context,
this study was carried out : (1) to determine the general
metal profile in a glass-manufacturing industrial zone; (2)
to compare metal extraction and/or stabilization potential of
these plants in order to identify potential candidate species
for efficient, practical phytoremediation, and (3) to recom-
mend plant(s) for phytoextraction/phytostabilization of a
specific metal or group of metals.
2 Materials and methods
2.1 Experimental design
A survey was carried out to identify the major clusters of glass
industries and/or finishing workshops in the study area. Five
zones were identified, and, in each zone, five sites were selected
for collecting samples. All zones were more than 1 km apart
except zones 2 and 5. All sites within a zone were more than
250 m apart. Soil from these 25 sites was analyzed to assess the
existing levels of Zn, Mn, Co, Cd, Pb, Cr, Ni, Cu, and As
contamination. Native plant species growing in these zones
were identified, and samples (shoot and root) were collected to
compare their accumulation and tolerance of metal(s).
270 Environ Sci Pollut Res (2012) 19:269–281
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2.2 Description of study area
Firozabad is located at 164 MSL in North Central India
27°09′N 78°24′E, around 240 km away from New Delhi.
The river Yamuna flows at a distance of 2 km. Situated on
one of the busiest highways (NH-2), Firozabad faces a lot
of traffic that includes transport vehicles that carry its
glass products as well as vehicles that pass through on
their way to various major cities. The five zones (Fig. 1)
in the studied area were selected on the basis of industrial
density. Zone 1 was along National Highway 2 in the heart
of the city. The area was characterized by dense population
of the working class and numerous small workshops in
every second or third household for processing and
finishing of glassware. Zone 2 was similar in narrower
lanes in a more backward area. Zone 3 was the newly
developed industrial estate with biggest production units.
Zone 4, another important production hub, was further along,
on a bypass. Zone 5 was a densely inhabited area along
railway tracks. The area is dotted with junk yards where glass
cullet is segregated for recycling and workshops.
2.3 Collection of samples
Five random soil samples were collected and combined
to get a composite sample for each site within a zone.
Thus, five composite samples were obtained for each
zone. The samples were collected from a depth of 0–
15 cm using a core sampler, air-dried, passed through an
80-mesh sieve, and stored in clean Ziplock polythene
bags until further use.
Shoot and root samples were collected from native plants
growing at sampling sites. Three samples each from
different plants were collected for each species. In all, 25
species were collected from five zones. In the lab, these
were first washed with distilled water to remove adhering
soil particles. They were further washed thoroughly three to
four times with de-ionized water and allowed to drip dry
completely in a dust-free chamber at room temperature.
Since this study concentrated on soil–plant interaction
alone, the washing also served to eliminate the risk of
plant metal content values being biased by foliar deposition
of suspended air particulate matter.
2.4 Analysis of soil and plant samples
Soil pH was measured in a soil-to-water ratio of 1:2.5 by a
pH meter (Systronics μpH system 361). Organic carbon
was measured by modified Walkley–Black rapid dichro-
mate oxidation method (Piper 1966). The value obtained
was multiplied by the factor 1.724 to obtain organic matter
content as reported.
Soil, shoot, and root samples from all sites were digested
using a microwave-assisted wet digestion method with
3 mL HNO
3
(69%, Merck)+9 mL HCl (30%, Merck) for
0.5 g soil, and 5 mL HNO
3
(69%, Merck)+2 mL H
2
O
2
ZONE 4
ZONE 3
ZONE 2
ZONE 1
ZONE 5
Railway track
National highway 2
INDIA
FIROZABAD
North Central India
N
City limits
Sampling sites
1 km
2000 ft
Fig. 1 Map of the study area
Environ Sci Pollut Res (2012) 19:269–281 271
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(30%, m/v; Merck) for 0.5 g plant sample. The filtrate was
analyzed for each metal by flame atomic absorption
spectrophotometry or by graphite furnace atomic absorption
spectrophotometry using a Solaar M2–Thermo Unicam
instrument. Certified references (Virginia tobacco leaves
CTA-VTL-2, Polish Certified Reference Material and NIST
2709–San Joaquin Soil) were also used to check the
accuracy of the results. The recovery rates for the elements
analyzed are 94% for Zn, 87% for Mn, 90% for Co, 92%
for Cd, 69% for Pb, 61% for Cr, 89% for Ni, 92% for Cu,
and 94% for As.
2.5 Assessment of metal contamination in soil samples
Soil contamination was assessed by calculating both
contamination index (P
i
) and integrated contamination
index (P
c
) as suggested by Huang (1987) and is expressed
by the fuzzy functions:
Pi¼Ci=Xaif CiXa
Pi¼1þCiXa
ðÞ=XbXa
ðÞif Xa<CiXb
Pi¼2þCiXb
ðÞ=XcXb
ðÞif Xb<CiXc
Pi¼3þCiXc
ðÞ=XcXb
ðÞif Ci>Xc
where C
i
is the observed content of the substance; X
a
is the
not-polluted threshold value; X
b
is the lowly polluted
threshold value, and X
c
is the highly polluted threshold
value. X
a
,X
b
, and X
c
in above functions could be defined
according to Class I, Class II, and Class III criteria (Table 1),
respectively, based on SEPAC, (1995). Class I (X
a
) criteria
was suitable to keep natural background values, and Class
II (X
b
) could be used as threshold values for protecting
human health, while Class III (X
c
) could be used as
threshold values for plant growth. Integrated contamination
index (P
c
) for each site was defined as the summation of the
difference between the contamination index for each metal
and 1. It could be calculated by the following formula:
Pc¼X
i¼1
7
Pi1ðÞ
For the description of integrated contamination index,
the following terminologies have been used—P
c
≤0no
contamination; 0<P
c
≤7 low contamination; 7< P
c
≤21
moderate contamination; P
c
>21 high contamination.
Threshold values for Co could not be obtained, and no
threshold for Mn exists since it is widespread in the earth’s
crust (Komnitsas and Modis 2009), hence these two metals
were not considered for these indices.
2.6 Statistical analyses
Pearson’s coefficient for correlation was statistically ana-
lyzed at a significance level of P< 0.05 and P< 0.01. The
statistical significance of differences among means was
determined by one-way analysis of variance (ANOVA)
followed by Tukey’s tests. Student’sttest was utilized to
compare difference in individual metal content values
within replicates of individual plant species.
3 Results and discussion
3.1 Soil characterization
The study area is a part of Indo-Gangetic alluvium of
quaternary age. The topsoil is sandy loam (sand 60–80%,
silt 10–24%, clay 8–16%). It has high exchangeable sodium
percentage values and moderate water retaining capacity.
The sub-soil is sandy throughout. The average available
nitrogen, phosphate, and potash contents are 65.9, 25.25,
and 335.75 kg/ha, respectively. The soils from all five
sampling zones had neutral pH values in the range 7.7–8.0
with soils from zones 1 and 3 having slightly greater pH
than others. The organic matter content of soil samples was
in the range 0.16—1.64%. Zones 2 and 5 were classified as
very low, zones 1 and 4 as low, and zone 3 as medium in
organic matter content, respectively. The above character-
istics of soils from zones 1 and 3 were similar, as were
those of soils from zones 2, 4, and 5. The electrical
conductivity of soils ranged from 0.38–0.52 dS/m.
3.2 Characterization of metal contamination in soils
On comparing the metal concentration of the 25 composite
soil samples, zones 1 and 3 showed consistently higher
concentrations except for Pb (Table 1). Zone 1 had highest
levels of Zn, Mn, Cd, Cr, Cu, and As as well as second
highest levels of Co and Ni. Zone 3 had highest levels of
Co and Ni as well as second highest levels of Zn, Cr, and
Cu. Zone 5 showed highest level of Pb contamination and
second highest levels of Cd and As contamination. It was
noted that values for Zn, Cd, Pb, Ni, Cu, and As in all
zones and in zones 1 and 3 for Cr exceeded the reported
median values for these elements (Sparks 2003). When
compared with the toxic levels for humans as reported in
soil (Huang 1987), all metals especially Cd exceeded the
levels prescribed, except for Ni (in three zones, i.e., 2, 4,
and 5), and Cu (zone 4). The other metals were also high
(especially zone 1, 3, and 5) in context of the thresholds for
industrial soils suggested by the Canadian Environmental
Quality Guidelines (2003). High to moderate As and Zn
contamination was observed in 64% samples, with levels of
272 Environ Sci Pollut Res (2012) 19:269–281
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Table 1 Metal content in soils (milligrams per kilogram)
Zones Category Zn Mn Co Cd Pb Cr Ni Cu As
1 Industrial/residential Range 86.9–934.6 16.08–46.7 16.96–63.7 3.77–107.05 92.95–638 133.72–158.4 25.78–217.85 37.5–300.04 10.3–204
Average 532.65a 33.56 30.00 34.32a 237.25 147.36a 100.62 178.70a 96.69a
SD 311.24 12.26 19.05 43.07 228.99 9.67 80.91 116.28 97.30
2 Industrial/residential Range 76.36–1247.08 17.15–13.37 14.76–35.21 7.99–37.73 35.54–780.50 19.11–34.43 23.07–48.44 22.38–191.25 9.25–60.34
Average 376.69a 24.23 20.07 17.05a 302.87 26.80b 30.79 75.99a 31.54a
SD 492.70 6.36 8.55 12.79 312.29 5.83 10.06 68.91 24.25
3 Industrial Range 198–974.08 21.23–32.40 13.31–54.30 6.7–17.58 50.38–354.0 32.88–106.58 24.64–285.19 37.27–265.43 18.93–43.20
Average 435.27a 26.88 32.34 11.99a 216.12 62.49a 131.04 132.90a 28.48a
SD 314.12 5.01 16.58 4.18 118.17 29.15 98.34 96.33 11.16
4 Industrial Range 78.6–122.65 21.2–41.20 16.43–26.20 3.64–5.50 47.58–86.66 35–57.35 30.94–61.20 26.17–51.2 22.3–57.70
Average 91.06b 31.13 21.67 4.58a 66.09 49.21a 46.80 34.41b 40.52a
SD 18.02 7.44 4.43 0.86 16.91 9.35 11.50 9.70 13.70
5 Industrial/residential Range 322.2–435.43 16.96–36.6 10.91–24.3 11.85–35.0 99.94–776.63 27.29–47.21 31.5–52.3 52.93–76.44 70.2–116.87
Average 389.85a 28.41 18.65 26.66b 377.62 37.94b 39.79 63.30a 91.81a
SD 50.33 7.64 5.08 8.89 255.96 8.76 8.55 10.13 17.76
Control/background
values of study area
269.56 16.42 18.37 4.41 39.40 25.34 22.66 19.32 5.20
Suggested thresholds
in soil
a
Industrial 360 ––22 600 87 50 91 12
Residential 200 ––10 140 64 50 63 12
Suggested thresholds
in soil
b
Background 140 –––– 100 35 –29
Intervention 720 –––– 380 210 –55
Threshold values
(SEPAC 1995)
X
a
100 ––0.2 35 90 40 35 15
X
b
200 ––0.3 250 150 60 50 30
X
c
500 ––1.0 500 300 200 400 40
Each average value is the mean of five composite sample values : SD Standard deviation
Different letters in the same column denote significant statistical difference (P≤0.07) in mean metal contents in soil at the different zones
a
Canadian environmental quality guidelines, 2003 proposed by The Canadian Council of Ministers of the Environment
b
Dutch Ministry of Housing, Spatial Planning and the Environment, ministerial circular on target and intervention values for soil remediation, 2000
Environ Sci Pollut Res (2012) 19:269–281 273
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As up to eight times higher than the thresholds. Significant
number of samples showed moderate contamination for Cu
(64%) and Ni (20%). Pb contamination was low to
moderate in 88% samples. Similar low contamination
results were obtained in the case of Zn and Cu from zone
4 and Ni from zone 5. No sign of Cr contamination was
obtained in approx. 76% samples. On comparing these with
the values suggested for soil remediation by VROM, The
Netherlands (2000), values of Zn in all zones were above
background values but below the intervention level. In the
case of Cr, the value is higher than background for zone 1;
however, it is much below the intervention value suggested.
In the case of Ni and As, above background levels were
detected in zones 3 and 4 while As levels were much higher
than intervention values in zones 1 and 5. It is significant to
note that, in studies similar to the present one, the degree of
contamination and the resulting ‘hazard indices’for soils
may vary when different thresholds, existing in only a few
countries are considered (Modis and Komnitsas 2007). To
increase the reliability of risk estimation due to contami-
nants, global consensus on such thresholds is urgently
needed.
Correlation among the various metal concentrations in
the soil (Table 2) of different zones was positive and highly
significant at (P< 0.01) for Cu with Zn, Co, and Cr.
Moderate positive correlation was also observed for Zn
with Co, Mn with Cd and As, Pb with As, and Ni with Cu
(P<0.05). One-way ANOVA indicated statistically signifi-
cant difference (P<0.05) in metal contents of soil samples
in the case of five metals viz.—Zn, Cd, Cr, Cu, and As.
Though the industrial thresholds for Pb (all five zones)
and Cd (three zones) were not crossed, the situation is
drastically different in the perspective of the residential
thresholds as these limits are exceeded in almost all zones.
This is extremely relevant since zones 1, 2, and 5 are
densely populated residential zones with small, virtually
unmonitored workshops in narrow lanes. Zones 3 and 4 are
established industrial areas with the larger production units,
hence there is some extent of planning and monitoring
involved.
Integrated contamination indices (P
c
) are shown in
Fig. 2.P
c
values indicate that 60% of the sites were in the
high contamination range, and 28% were in the moderate
contamination range with just 12% sites on the border of
the moderate to low contamination range. This was to be
expected with little or no monitoring of industrial processes
(including usage and disposal of hazardous chemicals) in
the area. Sites in zone 1 showed the widest range of metal
contamination with the highest and lowest P
c
values. Sites
in zone 3 and 5 showed consistently high P
c
values, all in
the high contamination range. The moderate contamination
profile of zone 4 could be due to the fact that many
factories here have been out of production for almost a
decade. The fact that no P
c
value fell within the low
contamination range was not really surprising, given the
fact that the study was carried out in an industrial city, but
high indices in nearly every zone are alarming because
these include densely populated areas of the lower
economic strata (zones 1, 2, and 5) that depends on this
industry for its livelihood. The local populace is, thus,
exposed to wide range of well-established toxins and even
carcinogens. In a preliminary survey carried out by the
authors, it was also found that most prevalent ailments
among the workers (and their families in the case of small
workshops) were lung-, kidney-, and eye-related. These are
in fact the most common health issues related to metal
toxicity (Vamerali et al 2010).
3.3 Metal concentrations in plants
Shoot and root samples of 25 plant species including 20
herbs, three shrubs, and two grasses were assessed for metal
concentrations. The results indicate that individual elements
and species displayed remarkably different trends of
accumulation in shoots and roots (Table 3). On considering
the translocation patterns, out of the 25 plants studied, 76%,
Table 2 Correlation coefficients
Mn Co Cd Pb Cr Ni Cu As
Zn 0.175 0.433* 0.150 0.364 0.358 0.166 0.830** 0.263
Mn 0.206 0.475* −0.174 0.329 −0.131 0.089 0.399*
Co −0.099 0.134 0.322 0.386 0.564** 0.276
Cd 0.161 0.232 0.087 0.154 0.251
Pb −0.014 −0.186 0.306 0.451*
Cr 0.329 0.616** 0.377
Ni 0.416* −0.193
Cu 0.195
* Correlation is significant at the 0.05 level (two-tailed; n= 25)
** Correlation is significant at the 0.01 level (two-tailed)
274 Environ Sci Pollut Res (2012) 19:269–281
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68%, 64%, and 56% of plants exhibited partition of Mn,
Zn, Cu, and As in their shoots, respectively. Pb, Cr, and Ni
were almost equally partitioned between shoots and roots. It
has been reported that As, Cr, and Pb are stored mainly in
root cells (Tiwari et al. 2009; Mellem et al. 2009), whereas
Zn is accumulated in green tissues like leaves (Probst et al.
2009). Co and Cd were predominantly partitioned in the
roots in 68% and 64% of plants studied, respectively,
displaying this pattern. In the one sample, ttests performed
separately for shoot and root samples of each plant species
for individual metal content, nearly all samples indicated
significant statistical difference (P≤0.05).
Poa annua at 742.06 mg of Cu per kg dry weight in
shoot was able to come near the threshold for Cu hyper-
accumulation (>1,000 mg/kg dry weight in shoot). P.annua
has been reported to accumulate up to 290 mg/kg dry
weight for As (Comino et al. 2009). Pedron et al. (2009)
have reported high removal efficiency in the species for Cu,
Zn, and Ni with accumulation up to 600, 460, and 350 mg/kg,
respectively, in shoot. Tamás and Kovács (2005)analyzedthe
relationship between metal contents (Pb, Zn, and Cu) and
vegetation in a mine-tailing. P.annua,anabundantspecies,
showed elevated Pb concentration with higher concentration
in the shoots.
None of the other species assessed in this investigation
displayed such high values as far as the hyperaccumulation
thresholds in aboveground biomass for different metals are
concerned. However, the uptake ranges are encouraging
when compared with reported toxic concentrations in plants
(Vamerali et al. 2010). In the case of Pb, Cr, and Cu, all 25
species were able to withstand the toxic levels. Croton
bonplandianum,Sida longifolia, and Eclipta alba accumu-
lated up to 4.5 times the toxicity threshold of Pb; Cannabis
sativa, and Rumex dentatus accumulated up to 20 times the
Cr threshold; and in the case of Cu, P.annua accumulated
above 35 times the toxicity threshold. In the case of As,
nearly all the species were able to withstand the reported
toxicity threshold with P.annua and E.alba displaying
nearly seven times the limit. The picture of Cd tolerance
across the species evaluated was also good with four species
crossing the limit in shoots and about eight species in roots. P.
annua, Datura stramonium, Rumex dentatus, and Lycopersi-
con esculentum were able to withstand toxic levels of Zn.
In general, soil pH seems to have the greatest effect as
the equilibrium between metal speciation, solubility, ad-
sorption, and exchange is intimately connected to soil pH
(Sauve et al. 1997). As mentioned earlier, all sites had a soil
pH in the range of 7–8. Due to lack of a large variation in
pH conditions, the results of correlation analysis (P< 0.05)
did not indicate correlation between metal accumulation in
plants and soil pH and organic matter content in soil in half
the cases (Table 4). In accordance with the changes in metal
bioavailability associated with a change in pH, many
studies have found that plant uptake of Mn and Zn is
negatively correlated to soil pH (Sauve et al. 1997; Turner
1994). Manganese can exist in soil as Mn(II), Mn(III), and
Mn(IV), however, only the reduced Mn(II) form is stable in
the directly bioavailable fraction, i.e., soil solution (Whitehead
2000). Divalent Mn ions are stable up to pH 7.5 (the average
soil pH in the present study); at higher values, a hydroxide
appears which will convert into a tetravalent bioxide
(MnO
2
). Accordingly, iron and manganese, separated from
primary minerals as ions, are easily oxidated and will
develop in higher valence forms as oxides or hydroxides.
Pb is mostly immobile in soil, which reduces its bioavail-
ability(Lombietal.2001) and subsequent uptake by the
plant. In the present investigation, limited positive correlation
was obtained between Mn, Pb, Ni, and Cu uptake in plants
and soil pH.
Organic matter forms metal complexes, so that it can
either reduce metal mobility or increase availability when
the complexes are soluble in the soil solution (Halim et al.
2003). Cu is often predominantly found bound to the
organic matter fraction in the soil which also affects the
bioavailability of Zn and Mn (del Castilho et al. 1993),
though not in a major way. In the case of Zn, Mn, Co, Pb,
and Cr, no correlation between plant uptake and organic
matter was seen. In the case of Ni, a low positive
correlation was obtained. We observed Cd uptake in plants
to be negatively correlated with soil pH and organic matter.
It has been reported that Cd is usually less adsorbed by soil
and organic matter which makes it more available to plants
(McLaughlin et al. 2000). The anionic behavior of As leads
to its greater mobility in conditions of high pH and organic
matter content (Hartley et al. 2009). As expected a positive
correlation was seen in this study between organic matter
content of soil and As concentrations in plants. All results
in this section were obtained at a 95% level of confidence.
Samplin
g
sites
0 5 10 15 20 25 30
Integrated contamination
index (P
c
)
0
20
40
60
80
100
120
140
160
180
ZONE 1 (sites 1-5)
ZONE 2 (sites 2-10)
ZONE 3 (sites 11-15)
ZONE 4 (sites 16-20)
ZONE 5 (sites 20-25)
Fig. 2 Integrated contamination indices (P
c
) of soil samples. Black
and gray lines are the upper threshold values of moderate and low
contamination, respectively
Environ Sci Pollut Res (2012) 19:269–281 275
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Table 3 Metal content in plants (mg/kg)
Plants Zones Zn Mn Co Cd Pb
Shoot Root Shoot Root Shoot Root Shoot Root Shoot Root
Amaranthus spinosus
a
1 79.78± 13.86 126.98 ± 14.27 35.66 ±4.60 31.59± 6.24 5.61 ± 1.5 5.81± 1.42 8.20± 1.45 11.68± 1.46 37.03 ± 13.42 86.62±5.5
Boerhaavia diffusa
a
58.76± 4.05 53.58 ± 1.91 69.38± 2.68 44.04 ± 2.45 7.97±1.84 6.63± 0.67 8.53± 1.2 6.71 ± 1.24 27.92± 3.14 40.32 ±2.6
Croton bonplandianum
a
45.85± 12.1 39.58 ± 4.35 79.48± 37.9 35.91 ± 2.11 5.06±0.22 7.04± 0.47 3.53± 0.7 4.11 ±0.25 89.76± 7.68 33.55 ±4.50
Cynodon dactylon
b
73.08± 6.7 87.10 ± 5.75 53.02 ± 2.13 25.80±2.0 5.24 ± 0.32 3.68 ± 0.17 5.46 ±0.82 7.22±0.63 31.53 ± 4.05 26.64 ±2.43
Eclipta alba
a
79.96± 6.20 125.30 ± 15.01 60.94±3.0 103.83±5.27 6.22±0.57 11.26 ±3.42 6.54 ±0.96 12.13±1.3 40.73±15.4 97.44± 15.6
Leucas cephalotes
a
42.80± 1.34 23.63 ± 2.67 41.08±2.83 17.85± 4.4 5.18 ± 0.9 11.56± 2.01 2.91 ± 0.5 2.72 ±0.58 49.11± 2.9 53.45 ± 5.02
Ricinus communis
c
88.65± 15.8 116.34 ±13.6 74.14 ±6.8 29.33±12.5 6.01±1.1 6.51 ±1.24 3.74±0.67 3.03±20.64 47.62±20.5 27.44 ± 7.12
Datura stramonium
c
2 141.53± 39.1 99.38 ± 61.7 60.27 ± 12.9 31.60±10.7 5.24 ± 0.8 5.02±0.6 12.88 ± 4.0 9.19 ± 2.05 41.33 ±19.17 44.05±4.78
Euphorbia hirrta
a
82.25± 5.9 73.43± 7.7 87.33 ± 5.51 61.74 ±4.38 8.42±0.8 11.74±1.3 9.03± 0.24 13.76± 0.51 61.55±4.01 46.94±10.70
Parthenium hysterophorus
a
52.52± 10.2 36.67 ± 9.06 54.56±18.4 32.52± 4.6 4.75 ± 0.75 4.39 ±0.7 4.27±1.14 3.98 ± 0.82 36.31 ± 11.2 48.78±31.9
Solanum nigrum
a
82.62± 6.01 47.83 ± 8.5 73.90 ± 7.01 25.71±6.08 7.59±2.26 6.18 ± 1.4 12.93 ±1.13 9.73±3.37 28.49 ± 5.2 23.85± 4.05
Tephrosia purpurea
a
75.16± 5.2 51.92± 6.05 79.71± 8.03 34.48 ± 3.86 4.14 ± 0.21 3.24±0.41 11.78± 2.8 8.25±2.5 50.73 ± 3.01 26.46 ± 7.1
Withania somnifera
a
84.48± 8.5 122.62± 22.3 33.47 ± 7.9 31.88± 6.8 10.05± 4.4 8.96±4.3 9.12± 2.4 10.46 ± 3.57 32.29 ±11.22 94.74±8.57
Argemone mexicana
a
3 57.80± 9.3 78.86± 4.0 31.51 ± 2.58 27.58 ±1.8 6.28±0.46 8.91±0.88 3.98±0.65 2.47± 0.15 31.08± 3.06 63.53 ± 7.21
Gnaphalium luteo-album
a
78.06± 9.0 66.10 ± 5.47 47.62 ± 9.12 68.33±8.5 6.07 ± 0.73 7.13 ± 0.93 6.04 ±1.08 6.14±2.07 25.25 ± 3.21 33.08 ±3.5
Poa annua
b
177.50± 24.6 286.34 ± 15.8 49.43 ± 15.4 91.76±6.3 6.56 ± 1.71 13.58 ± 4.91 9.15 ±5.01 16.70±5.52 297.66± 14.6 78.09 ± 22.8
Sida longifolia
a
51.69± 3.47 46.71 ± 3.14 55.58±6.43 73.33± 7.46 4.52 ± 0.7 6.70± 0.93 5.47 ± 0.65 7.54 ± 0.38 75.13±19.31 56.68± 6.95
Chenopodium murale
a
4 92.8± 33.03 63.62 ± 9.66 46.90±11.7 33.08± 8.27 5.08 ± 1.9 5.53± 1.09 9.62 ± 1.86 5.60 ± 0.47 58.84±3.2 37.35± 9.06
Lycopersicon esculentum
a
101.7± 12.6 166.97 ± 8.21 25.24 ±5.86 18.84±1.16 5.33 ± 1.4 7.29±2.08 5.20±1.21 4.25 ± 0.9 53.77 ± 8.6 49.98± 7.38
Calotropis procera
c
95.55± 10.03 136.77 ± 18.15 42.24 ± 15.29 66.72 ±7..3 7.11± 3.09 8.62 ± 2.5 6.91 ±3.9 12.71±0.67 49.75 ± 17.62 56.96 ±8.26
Physalis minima
a
5 45.59± 3.07 41.71 ± 2.8 81.97 ± 18.5 33.22±4.2 5.17±0.8 4.82± .81 3.57±0.79 1.99±0.32 39.73±21.8 26.43± 2.32
Cannabis sativa
a
63.19± 7.8 46.86± 4.75 51.04± 3.25 34.04 ± 1.14 8.30 ± 2.33 8.05±4.05 4.49±1.03 4.48±0.8 30.94 ± 6.35 53.91 ± 4.9
Heliotropium opium ellipticum
a
59.63± 13.3 56.28 ± 21.8 52.55± 14.7 36.19 ± 6.2 5.40± 2.1 4.95± 0.6 11.21±5.9 7.08± 2.51 35.16± 9.01 53.55±37.15
Rumex dentatus
a
116.61± 14.6 115.25 ± 14.2 42.35 ± 16.0 51.42 ±9.27 5.83±2.25 6.58 ± 1.7 6.68 ± 3.6 8.03±3.85 45.82±7.27 67.09± 21.4
Tridex procumbens
a
68.09± 17.12 97.13 ± 13.5 81.84± 12.7 69.48 ± 12.9 6.42±0.78 12.11± 1.65 7.36 ± 2.78 13.25± 1.12 34.78±9.3 21.48±4.92
Threshold for hyperaccumulation in above
ground biomass
d
(mg/kg)
>10,000 >10,000 >1,000 >100 >1,000
Phytotoxicity levels
d
(mg/kg) 150–200 170–2,000 60–170 5–10 10–20
276 Environ Sci Pollut Res (2012) 19:269–281
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Table 3 (continued)
Plants Zones Zn Mn Co Cd Pb
Shoot Root Shoot Root Shoot Root Shoot Root Shoot Root
Plants Zones Cr Ni Cu As
Shoot Root Shoot Root Shoot Root Shoot Root
Amaranthus spinosus
a
1 11.44± 3.9 7.84 ± 0.8 12.56±0.71 28.82 ± 2.4 34.06 ±3.7 94.67±7.3 7.97 ± 0.9 4.64 ± 1.5
Boerhaavia diffusa
a
13.19± 5.4 <1 17.85±4.87 11.78 ± 3.37 28.30 ± 4.91 25.30± 2.71 22.93 ± 3.12 12.95±1.81
Croton bonplandianum
a
8.26± 2.27 26.16± 2.05 16.13± 3.43 18.01 ± 3.10 50.79 ± 25.1 24.11±3.27 20.25±4.08 28.17±2.76
Cynodon dactylon
b
34.63± 4.23 18.67 ± 2.70 14.43 ±2.1 8.16±2.20 23.00 ± 3.90 16.93 ± 2.87 21.52±3.45 27.01± 3.72
Eclipta alba
a
21.20± 4.63 47.92 ± 8.42 10.86± 2.46 19.16 ± 2.42 23.05 ±3.28 55.36±6.4 84.28±10.2 145.74±11.6
Leucas cephalotes
a
24.92± 1.28 16.20 ± 3.23 9.38± 1.02 8.13± 0.6 123.53 ±8.16 50.52±18.31 15.32± 2.83 26.41 ± 5.75
Ricinus communis
c
38.81± 18.6 10.91 ± 6.6 17.26 ± 2.92 9.93±1.64 101.12±75.01 41.68±6.2 22.66± 5.87 12.45 ± 2.56
Datura stramonium
c
2 27.34± 18.66 6.66 ± 2.78 13.44 ± 0.26 11.86± 2.65 146.15 ± 4.66 40.41 ± 7.02 40.04 ± 14.8 15.74±12.6
Euphorbia hirrta
a
17.53± 2.08 20.84 ± 1.9 19.89 ±1.53 13.91±0.34 34.18 ± 2.92 17.61± 4.05 38.18 ± 2.26 19.40±1.54
Parthenium hysterophorus
a
5.72± 2.7 4.12 ± 1.6 11.13± 1.33 11.15±1.24 30.04± 6.04 47.55± 39.2 5.46 ±1.10 4.83±2.6
Solanum nigrum
a
1.62± o.53 <1 11.51± 2.6 9.29 ± 2.07 18.07 ±5.4 9.05± 1.57 9.48 ± 0.63 3.81 ± 1.08
Tephrosia purpurea
a
2.61± 0.75 3.90± 0.92 7.18 ± 1.4 11.72± 2.17 56.49 ± 8.41 22.69± 5.6 11.35±2.15 6.38±1.12
Withania somnifera
a
5.12± 1.5 5.68 ± 0.9 14.60±1.57 16.51 ± 4.17 33.22 ± 9.4 105.69 ±4.8 9.65±1.74 6.05±1.68
Argemone mexicana
a
3 18.47± 2.1 25.64± 4.05 8.56± 0.47 10.30± 0.77 31.03 ± 2.1 19.12±0.85 18.03± 3.16 21.73 ± 1.9
Gnaphalium luteo-album
a
13.42± 5.2 21.03 ± 2.92 14.22 ±2.8 17.45±1.58 27.29 ± 4.3 33.63 ±9.4 18.63±3.95 29.07 ± 9.0
Poa annua
b
33.30± 7.33 41.68 ± 8.5 11.44±1.61 18.60± 3.7 742.06± 32.8 66.27 ± 8.5 78.63± 17.2 147.01 ± 57.1
Sida longifolia
a
6.45± 1.35 10.82 ± 2.4 8.73 ±0.51 11.61± 2.71 92.43 ± 12.11 56.11±6.6 7.60 ±0.84 8.78±2.56
Chenopodium murale
a
4 8.09± 4.17 11.26 ±3.7 9.09 ±0.95 12.33±3.09 36.56± 19.4 13.75 ± 9.6 17.41±2.54 20.64± 5.42
Lycopersicon esculentum
a
22.18± 4.4 45.58 ± 13.4 16.62 ±3.67 13.61± 4.28 36.20 ± 2.7 30.49±4.2 48.03± 11.3 26.54 ± 4.04
Calotropis procera
c
19.50± 4.6 13.25 ± 3.2 17.15 ± 3.7 15.43±1.88 40.68± 9.94 53.64 ± 6.9 38.56 ±5.8 33.20±4.17
Physalis minima
a
5 10.99± 8.6 4.07 ± 2.8 10.29±2.13 6.48 ± 0.56 19.82 ± 3.12 18.41±2.4 18.46± 13.11 4.98 ± 2.07
Cannabis sativa
a
41.22± 2.6 15.05 ± 8.7 14.26 ±3.38 10.64± 2.32 28.16 ± 3.6 21.21±2.8 33.11± 3.4 18.66 ± 3.35
Heliotropium ellipticum
a
14.58± 2.22 11.77 ±4.6 14.55 ±3.8 12.26±1.82 28.82±4.6 58.00 ± 7.14 13.23 ± 12.08 142.41 ±15.4
Rumex dentatus
a
40.15± 10.5 102.07 ± 13.6 15.90 ±1.64 18.12±2.9 34.19±11.6 46.23±9.3 26.11± 6.01 28.63 ± 3.33
Tridex procumbens
a
18.73± 3.9 23.54 ± 3.5 15.80 ± 2.93 8.50± 1.81 28.99 ± 6.27 14.49 ± 2.7 25.19±3.8 23.60±5.61
Threshold for hyperaccumulation in above
ground biomass
d
(mg/kg)
>20,000 >1,000 >1,000 >1,000
Phytotoxicity levels
d
(mg/kg) 1–220–30 15–20 20
a
herb,
b
grass,
c
shrub
d
Vamerali et al. 2010
Environ Sci Pollut Res (2012) 19:269–281 277
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Clays and hydrous oxides, i.e., oxides of Al, Fe, and Mn,
play an important role in the availability of metals. Clays
and hydrous oxides determine metal availability mainly by
specific adsorption to surface hydroxyl groups, nonspecific
adsorption (exchange), co-precipitation, and precipitation as
the discrete metal oxide or hydroxide (Miller et al. 1987;
Basta and Tabatabai 1992; Martinez and McBride 1998;
Kavvadias et al. 2010). Hence, increasing clay and hydrous
oxide contents in soils provides more sites for adsorption of
metals thus reducing the directly bioavailable metal.
3.4 Metal accumulation characteristics
The BAC, BCF, and TF values (Table 5)helptoidentifythe
suitability of plants for phytoextraction and phytostabiliza-
tion by explaining the accumulation characteristics and
translocation behaviors of metals in plants. The BAC
values of the plant studied were >1 in 24 species for Mn;
four species each for As and Cu; three species each for Zn,
Cd, and Cr; but in only one species in the case of Pb. On
evaluating BCF, 20 species were found to have a ratio
greater than 1 for Mn; four species for As; three species for
Cd; two each in the case of Zn and Cu; and one in the case
of Cr. All studied plants had low BCF values for Co, Pb, Cr,
and Ni, indicating that the species had limited capabilities
of mobilizing these metals in the root zone at the
concentrations present in soil at all sites. Parent material
type, vegetation type, and soil physicochemical properties
are factors that control heavy metal distribution in surface
soils (Xu and Tao 2004). The ionic radii of Ni and Co, 69
and 65 pm (low spin), respectively (Shannon 1976) for the
same oxidation state (+2) are nearly similar, and they are
often able to substitute each other and thus get mixed in
minerals (Liu 1984;XuandTao2004). Probability of such
atomic substitutions decreases as difference in ionic radii
increases. Higher soil pH values can also facilitate
adsorption of metals by soil organic materials since protons
may compete with metal ions for adsorption sites.
Adsorbed metals generally show different behavior such
as low mobility in soil. For Ni and Co, Xu and Tao (2004)
observed not only similar adsorption behavior over a wide
range of pH values but also similar uptake and accumula-
tion among different plant species. Soil pH does not seem
to have an effect on the uptakes as all zones presented a
similar picture. Even among the remaining metals, plants
displayed ease in mobilizing Mn only.
TF values indicate that most of the plants allocated a
greater proportion of metal absorbed to aboveground
biomass. Nineteen species recorded a TF > 1 for Mn; 17
for Cu; 15 for Zn; 14 each for Ni and As; 13 for Cd; and 10
each for Co, Pb, and Cr. Several plants were found to have
a TF>1 for multi-metal combinations, indicating the fact
that they were naturalized to the contaminated matrix in
which they had germinated and grown and that their
metabolism could at least tolerate the multi-metal contam-
ination. The higher TF values recorded were 11.21 and 3.81
for Cu and Pb, respectively, in P.annua; 4.11 and 2.54 for
Cr and As, respectively, in D.stramonium; and 2.49 for As
in Solanum nigrum. Similar studies have shown that leaves
act as main sinks for metals in hyperaccumulator plants
(Salt et al. 1995; Psaras and Manetas 2001). This is
attributed to the efficient translocation of metals from roots
to shoots and is considered an advantageous strategy as the
root system is the primary target in metal toxicity (Baker et
al. 1994).
Plants exhibiting BAC and TF values > 1 are generally
considered promising phytoextractors (Fitz and Wenzel
2002). D.stramonium showed such values for Mn, Cr,
Cu, and As; Chenopodium murale for Zn, Mn, Cd, and Cu;
L.esculentum for Cd, Cu, and As; P.annua for Pb and Cu;
C.sativa for Mn and Cr; Tephrosia purpurea, S.nigrum, C.
bonplandianum, Physalis minima,Tridex procumbens for
Mn; and Euphorbia hirrta for As. These species exhibited
potential for possible use in phytoextraction. Highest BAC
values were observed in P.annua for Cu (5.58), As (2.76),
and Pb (1.38); in T.purpurea and S.nigrum, for Mn (3.39
and 3.09, respectively), and in C.murale for Cd (2.10).
According to Mendez and Maier (2008), a plant suitable for
Table 4 Correlation between metal concentration in plants and soil parameters
S. No. Metal content in plants Correlation coefficients
Soil pH Organic matter
1 Mn (root) 0.273 –
2 Cd (shoot) −0.272 −0.368
3 Pb (shoot) 0.329 –
4 Ni (root) 0.243 0.250
5 Cu (shoot) 0.278 –
6 As (root) –0.348
Correlation is significant at the 0.05 level (two-tailed; n= 75)
278 Environ Sci Pollut Res (2012) 19:269–281
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Table 5 Metal accumulation characteristics of plants
Bioabsorption Coefficient [BAC] Bioconcentration Factor [BCF] Translocation Factor [TF]
Zn Mn Co Cd Pb Cr Ni Cu As Zn Mn Co Cd Pb Cr Ni Cu As Zn Mn Co Cd Pb Cr Ni Cu As
Amaranthus 0.15 1.06 0.19 0.24 0.16 0.08 0.12 0.19 0.08 0.24 0.94 0.19 0.34 0.37 0.05 0.29 0.53 0.05 0.63 1.13 0.97 0.70 0.43 1.46 0.44 0.36 1.72
Boerhaavia 0.11 2.07 0.27 0.25 0.12 0.09 0.18 0.16 0.24 0.10 1.31 0.22 0.20 0.17 ND 0.12 0.14 0.13 1.10 1.58 1.20 1.27 0.69 ND 1.52 1.12 1.77
Croton 0.09 2.37 0.17 0.10 0.38 0.06 0.16 0.28 0.21 0.07 1.07 0.23 0.12 0.14 0.18 0.18 0.13 0.29 1.16 2.21 0.72 0.86 2.68 0.32 0.90 2.11 0.72
Cynodon 0.14 1.58 0.17 0.16 0.13 0.24 0.14 0.13 0.22 0.16 0.77 0.12 0.21 0.11 0.13 0.08 0.09 0.28 0.84 2.06 1.42 0.76 1.18 1.85 1.77 1.36 0.80
Eclipta 0.15 1.82 0.21 0.19 0.17 0.14 0.11 0.13 0.87 0.24 3.09 0.38 0.35 0.41 0.33 0.19 0.31 1.51 0.64 0.59 0.55 0.54 0.42 0.44 0.57 0.42 0.58
Leucas 0.08 1.22 0.17 0.08 0.21 0.17 0.09 0.69 0.16 0.04 0.53 0.39 0.08 0.23 0.11 0.08 0.28 0.27 1.81 2.30 0.45 1.07 0.92 1.54 1.15 2.45 0.58
Ricinus 0.17 2.21 0.20 0.11 0.20 0.26 0.17 0.57 0.23 0.22 0.87 0.22 0.09 0.12 0.07 0.10 0.23 0.13 0.76 2.53 0.92 1.23 1.74 3.56 1.74 2.43 1.82
Datura 0.38 2.49 0.26 0.76 0.14 1.02 0.44 1.92 1.27 0.26 1.30 0.25 0.54 0.15 0.25 0.39 0.53 0.50 1.42 1.91 1.04 1.40 0.94 4.11 1.13 3.62 2.54
Euphorbia 0.22 3.60 0.42 0.53 0.20 0.65 0.65 0.45 1.21 0.19 2.55 0.58 0.81 0.15 0.78 0.45 0.23 0.62 1.12 1.41 0.72 0.66 1.31 0.84 1.43 1.94 1.97
Parthenium 0.14 2.25 0.24 0.25 0.12 0.21 0.36 0.40 0.17 0.10 1.34 0.22 0.23 0.16 0.15 0.36 0.63 0.15 1.43 1.68 1.08 1.07 0.74 1.39 1.00 0.63 1.13
Solanum 0.22 3.05 0.38 0.76 0.09 0.06 0.37 0.24 0.30 0.13 1.06 0.31 0.57 0.08 ND 0.30 0.12 0.12 1.73 2.87 1.23 1.33 1.19 ND 1.24 2.00 2.49
Tephrosia 0.20 3.29 0.21 0.69 0.17 0.10 0.23 0.74 0.36 0.14 1.42 0.16 0.48 0.09 0.15 0.38 0.30 0.20 1.45 2.31 1.28 1.43 1.92 0.67 0.61 2.49 1.78
Withania 0.22 1.38 0.50 0.53 0.11 0.19 0.47 0.44 0.31 0.33 1.32 0.45 0.61 0.31 0.21 0.54 1.39 0.19 0.69 1.05 1.12 0.87 0.34 0.90 0.88 0.31 1.60
Argemone 0.13 1.17 0.19 0.33 0.14 0.30 0.07 0.23 0.63 0.18 1.03 0.28 0.21 0.29 0.41 0.08 0.14 0.76 0.73 1.14 0.70 1.61 0.49 0.72 0.83 1.62 0.83
Gnaphalium 0.18 1.77 0.19 0.50 0.12 0.21 0.11 0.21 0.65 0.15 2.54 0.22 0.51 0.15 0.34 0.13 0.25 1.02 1.18 0.70 0.85 0.98 0.76 0.64 0.81 0.81 0.64
Poa 0.41 1.84 0.20 0.76 1.38 0.53 0.09 5.58 2.76 0.66 3.41 0.42 1.39 0.36 0.67 0.14 0.50 5.16 0.62 0.54 0.48 0.55 3.81 0.80 0.62 11.20 0.53
Sida 0.12 2.07 0.14 0.46 0.35 0.10 0.07 0.70 0.27 0.11 2.73 0.21 0.63 0.26 0.17 0.09 0.42 0.31 1.11 0.76 0.67 0.73 1.33 0.60 0.75 1.65 0.87
Chenopodium 1.02 1.51 0.23 2.10 0.89 0.16 0.19 1.06 0.43 0.70 1.06 0.26 1.22 0.57 0.23 0.26 0.40 0.51 1.46 1.42 0.92 1.72 1.58 0.72 0.74 2.66 0.84
Lycopersicon 1.12 0.81 0.25 1.14 0.81 0.45 0.36 1.05 1.19 1.83 0.61 0.34 0.93 0.76 0.93 0.29 0.89 0.65 0.61 1.34 0.73 1.22 1.08 0.49 1.22 1.19 1.81
Calotropis 1.05 1.36 0.33 1.51 0.75 0.40 0.37 1.18 0.95 1.50 2.14 0.40 2.78 0.86 0.27 0.33 1.56 0.82 0.70 0.63 0.82 0.54 0.87 1.47 1.11 0.76 1.16
Physalis 0.12 2.89 0.28 0.13 0.11 0.29 0.26 0.31 0.20 0.11 1.17 0.26 0.07 0.07 0.11 0.16 0.29 0.05 1.09 2.47 1.07 1.80 1.50 2.70 1.59 1.08 3.71
Cannabis 0.16 1.80 0.44 0.17 0.08 1.09 0.36 0.44 0.36 0.12 1.20 0.43 0.17 0.14 0.40 0.27 0.34 0.20 1.35 1.50 1.03 1.00 0.57 2.74 1.34 1.33 1.77
Heliotropium 0.15 1.85 0.29 0.42 0.09 0.38 0.37 0.46 0.14 0.14 1.27 0.27 0.27 0.14 0.31 0.31 0.92 1.55 1.06 1.45 1.09 1.58 0.66 1.24 1.19 0.50 0.09
Rumex 0.30 1.49 0.31 0.25 0.12 1.06 0.40 0.54 0.28 0.30 1.81 0.35 0.30 0.18 2.69 0.46 0.73 0.31 1.01 0.82 0.89 0.83 0.68 0.39 0.88 0.74 0.91
Tridex 0.17 2.88 0.34 0.28 0.09 0.49 0.40 0.46 0.27 0.25 2.45 0.65 0.50 0.06 0.62 0.21 0.23 0.26 0.70 1.18 0.53 0.56 1.62 0.80 1.86 2.00 1.07
Environ Sci Pollut Res (2012) 19:269–281 279
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phytostabilization should have BCF > 1 and TF < 1. In plants
with low TF, there is less translocation of metals to the
aboveground portions which may be due to immobilization
of metals in roots by vacuole sequestration or cell wall
binding, thereby preventing interaction with high-
molecular-weight compounds in the plant cell cytoplasm
(Salt et al. 1995). In another study in the same locality,
Typha latifolia was assessed for phytoremediation of heavy
metals in the sediments of industrial discharge pits (Varun et
al. 2011b). The plant partitioned a major part of metals in the
root itself. Along with the especially low TF values, it was
found suitable as a phytostabilizer for Zn, Mn, Cr, and Aswith
some potential for Co, Cd, and Ni also. High BCF and low TF
values were observed in C.procera for Zn, Mn, Cd, and Cu;
P.annua for Mn, Cd, and As; Gnaphalium luteo-album for
Mn and As; Withania somnifera for Cu; and in Heliotropium
ellipticum for As, thus, establishing them as good phytosta-
bilizers for these metals and metal combinations.
4 Conclusion
The results of this study confirm that the ill-monitored
activities of the glass industry at Firozabad, India, have
caused significant accumulation of metals in both soils and
native wild flora suggesting that industrial pollution is an
important source contributing to urban environmental
deterioration in the study area and should be a matter of
great concern. Phytoremediation employing indigenous
species can be an ecologically viable option for sustainable
and cost-effective management. The results of the present
investigation indicate that:
&Individual elements displayed remarkably different
patterns of accumulation in soils. Of the nine elements
studied, Zn, Cd, and As showed a greater accumulation
in all soils, whereas, accumulation of Ni and Cu was
high in limited samples. Furthermore, observed differ-
ences in the magnitude of accumulation suggest that the
relative contribution of the individual elements to total
metal contamination varies.
&Native species have adapted themselves to multi-metal
contamination in the soil.
&Uptake as well as translocation patterns of metals in
plants differed remarkably. Generally, Mn was easily
absorbed by plants as compared to the other metals.
Studied plants had difficulties in mobilizing Co, Pb, Cr,
and Ni in the root zone as seen from their low BCF
values (root to soil ratio of metal).
&The following species can be recommended as phy-
toextractors—D.stramonium for Mn, Cr, Cu and As; C.
murale for Zn, Cd, and Cu; L.esculentum for Cd, Cr
and As; and P.annua for Pb and As.
&Furthermore, P.annua exhibited the greatest phytoex-
traction potential for Cu and As; T.purpurea as well as S.
nigrum for Mn; C.murale for Cd, and C.sativa for Cr.
&The following species can be recommended as
phytostabilizers—C.procera for Zn, Mn, Cd, and
Cu; P.annua for Mn, Cd, and As and GI. luteo-album
for Mn and As, either singly or for these multi-metal
combinations. W.somnifera,E.alba, and Helio-
tropium ellipticum are suggested for Cu, Mn and As,
respectively.
&None of the species assessed showed potential for
phytoextraction/phytostabilization of Co and Ni. Simi-
larly, no promising phytostabilizers were observed for
Pb and Cr in the native flora studied.
&It is strongly felt that stringent environmental measures/
regulations are urgently needed in the area considering
phytoremediation as a feasible option.
Acknowledgment Financial support from University Grants
Commission [F. no. 35-47/2008(SR)] is duly acknowledged.
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