Journal of Environmental Protection, 2011, 2, 710-719
doi:10.4236/jep.2011.26082 Published Online August 2011 (
Copyright © 2011 SciRes. JEP
Ecotoxicity and Ecosystem Health of a Ramsar
Wetland System of India
U. P. Nasir1*, P. S. Harikumar2
1Senior Scientific Assistant, Central Pollution Control Board, Zonal Office-Vadodara, Gujarat, India; 2Scientist & In-Charge, Central
Water Analysis Laboratory, Centre for Water Resources Development and Management, Kozhikode, Kerala, India.
Received March 22nd, 2011; revised May 4th, 2011; accepted June 14th, 2011.
In this study one econ omically important Ramsar wetland system of India, Vembanad wetlan d system, is studied to de-
termine the environmental pollutio n. Six surfa ce sediment samples collected from two extreme zones of the wetland sys-
tem were analyzed for heavy metals such as Copper, Zinc, Manganese, Cadmium, Lead, Nickel and Mercury. Highest
metal concentration was found at industrial zone and lowest concentration was detected at southern upstream of the
wetland system. The results showed that the pollution level is significant in the industrial zone. Comparison of the re-
sults with different sediment quality g uidelines indicated ultra high degree of contamination in th e industrial zone. The
numerical value of degree of contamination, pollution load index, sum of toxic units, enrichment factor and geo-accu-
mulation index confirmed the above fact. Based on National Oceanic and Atmospheric Administration Guidelines, the
health of the ecosystem was seriously impaired with frequent occurring of biological effects in the industrial zone. The
percentage of heavy metal calculated with respect to the industrial zone as the base line and the correlation analysis
with organic matter indicated that, mobility of the specific metal has higher impact on its concentration at the fresh
water region of the wetland.
Keywords: Heavy Metal, Sediment Quality Guidelines, Degree of Contamination, Pollution Load Index, Index of
1. Introduction
Sediments are the layers of relatively finely divided mat-
ter covering the bottom of rivers, streams, lakes, reser-
voirs, bays, estuaries and ocean. Unlike water quality
which is susceptible to seasonal variation, dependent on
in and out flow and weather, sediment quality is more
constant and will have more farfetched implications. As-
sessment of sediments in a complex aquatic system re-
sulted in a better understanding of the adverse impacts
that contaminants in sediments pose to fish, wild life and
humans who depend this impacted waterways. Therefore
apart from polluted water, fate of contaminated sediment
has been chosen as one of the aspects responsible for
ecological decline. Lake sediments provide a useful ar-
chive of information on changing lacustrine and water-
shed ecology [1]. The composition of the sediment se-
quences provides the best natural achieves of recent en-
vironmental changes [2].
Sediment is a habitat and major nutrient source for
aquatic organisms. Sediment analysis is important in eva-
luating qualities of total ecosystems of a water body in
addition to water sample analysis practiced for many
years because it reflects the long term quality situations
independent of the current inputs [3] and it is the ultimate
sink of contaminants in the aquatic system [4]. Accumu-
lation of heavy metals occur in upper sediment of the
aquatic environment by biological and geochemical
mechanisms and becomes toxic to sediment dwelling
organisms and fish, resulting in death, reduced growth, or
in impaired reproduction and lower species diversity [5].
Trace elements also occur naturally in rock forming
minerals; hence they can reach the environment from
natural processes [6]. The occurrence of metals in aquatic
ecosystems in excess of natural background loads has
become a problem of increasing concern. Heavy metals
in environment may accumulate to toxic levels without
visible signs. This may occur naturally from normal
geological phenomenon such as ore formation, weather-
ing of rocks and leaching or due to increased population,
urbanization, industrial activities, agricultural practices,
exploration and exploitation of natural resources [7].
Ecotoxicity and Ecosystem Health of a Ramsar Wetland System of India711
One of the major problems that heavy metals cause
with respect to their effects on aquatic organisms is their
long biological half-life. Therefore, they are among the
most frequently monitored micropollutants, and reliable
techniques have been established for their extraction and
quantification [8-10], since sediment contamination by
heavy metals in rivers and estuaries has become an issue
of increasing environmental concern. Such contamina-
tion is often caused by human activities, including min-
ing, smelting, electroplating and other industrial proc-
esses that have metal residues in their wastes, and by
non-point source surface runoff.
It is accepted that without defensible sediment quality
guidelines it would be difficult to assess the extend of
sediment contamination [11]. Sediments were classified
as non-polluted, moderately polluted and heavily pol-
luted, based on Sediment Quality Guidelines of United
State Environmental Protection Agency [12]. Hakanson
et al. [13] had suggested a contamination factor (Cif) and
the degree of contamination (Cd) to describe the con-
tamination of given toxic substance. Tomlinson et al. [14]
had employed a simple method based on pollution load
index (PLI) to assess the extent of pollution by metals in
estuarine sediments. The need for chemical guidelines
that could be used to predict adverse biological effects in
contaminated sediments lead to the development of
sediment quality guidelines [15-18]. The ecotoxicologi-
cal sense of heavy metal contamination in sediments was
determined using sediment quality guidelines developed
for marine and estuarine ecosystem [19]. The potential
acute toxicity of contaminants in sediment sample can be
estimated as the sum of the toxic units (TU) defined as
the ratio of the determined concentration to PEL value
[20]. Pollution will be measured as enrichment factor
(EF), which is the amount or ratio of the sample metal
enrichment above the concentration present in the refer-
ence station or material [21,22]. Sediment geo accumula-
tion index (GeoI) is the quantitative check of metal pol-
lution in aquatic sediments [23]. These impacts were
assessed by means of the geo-accumulation index (Igeo)
[24] and Igeo classification is reported based on the
chemical analysis of the bulk sediments. The Igeo has
been widely utilized as a measure of pollution in fresh-
water [25-27] and marine sediments [28-30].
The over all objective of this research work was to
evaluate the degree and extend to which the heavy metal
contamination has affected the Vembanad wetland sys-
tem, one of the Ramsar site in the south west coast of
India. In this study heavy metals such as copper, zinc,
manganese, cadmium, lead, nickel and mercury in sur-
face sediments were analysed using different sediment
quality guidelines. The numerical value of different
sediment quality indices such as degree of contamination,
pollution load index, sum of toxic units, enrichment fac-
tor and geo-accumulation index were also calculated for
the data interpretation. Hence the present study aimed to
understand the pollution load at industrial region of the
wetland system and its impact towards the fresh water
region of the Vembanad Lake.
The Vembanad wetland system (Latitude 9˚30' and
10˚12'; Longitude 76˚10' and 76˚29') is a complex aquatic
system of coastal backwaters, lagoons, marshes, man-
groves and reclaimed lands with an intricate network of
natural and man made channels and its associated drain-
age basins are situated in the humid tropical region on
the south west coast of the Indian peninsula. The total
area of the wetland system is 2195 km2. This system in-
cludes the Vembanad backwaters and the lower reaches
of the five rivers draining in to it. The five rivers which
drain in to the Vembanad Lake are Muvattupuzha,
Meenachil, Manimala, Pamba and Achenkoil. All these
rivers originate from the Western Ghats, flow westwards
through the wetland system and join the Lakshadweep/
Arabian Sea. The wetland is typically divided into two
distinct segments, the freshwater dominant southern zone
and the salt-water dominant northern zone both separated
by a bund at Thanneermukkom. The estuarine zone and
organically rich sedimentary substratum of the inshore
region makes it a highly preferred and desirable habitat
for shrimps breeding. Vembanad is renowned for its live
clam resources and sub-fossil deposits. Vembanad wet-
land has been designated as a Ramsar Site in November
The wetland system is facing many problems, which
include; pollution due to industrial, agricultural and do-
mestic effluents. It is estimated that nearly 260 million
liters of effluents reach the estuaries daily form the in-
dustries located in the northern part of the wetland sys-
tem [31]. The Cochin estuarine system receives effluents
containing a large dose of heavy metals [32]. The distri-
bution and toxicity of heavy metals in core sediments
also indicated severe pollution in the wetlands [33,34].
The increasing loads of sewage and industrial waste have
created conditions that are extremely destructive to flora
and fauna. During the tidal activity pollutants from the
northern side moves towards the southern side making
the fresh water system also threatened. In addition agri-
cultural inputs from the lands located around the lake
also pollute the freshwater region of the lake.
Sampling Stations
Six sampling stations were selected in the wetland sys-
tem starting from the northern industrial region to the
southern fresh water region. Six surface sediment sam-
ples were collected from each site, using a gravity corer
with PVC core-liner. Four centimeters of the surface
Copyright © 2011 SciRes. JEP
Ecotoxicity and Ecosystem Health of a Ramsar Wetland System of India
sediments were extracted from the core-liner and placed
in labeled polythene bags. In the laboratory the sediments
were air-dried [23] to a constant weight and homoge-
nized with a pestle and mortar, in order to normalize for
variation in grain size distribution. The sampling sites are
marked in the area map (Figure 1).
2. Analytical Methods
For the digestion of the sediment sample one gram of
dried and homogenized sediment sample was weighed
into 250 ml beaker. An empty beaker was included in the
analysis as a reagent empty blank. 50 ml of distilled wa-
ter was added to the sample. The digestion was per-
formed with a mixture HNO3 and HClO4. Digestion was
continued until the volume was reduced to about 15 ml.
The beakers were allowed to cool to room temperature.
The digests were then filtered into a 50ml volumetric
flask and made up to the volume with distilled water [35].
The digested samples were analyzed for heavy metal
following Atomic Absorption Spectrophotometer [15] by
Thermo M5 series. The concentration of manganese,
cadmium, copper, lead, nickel, zinc and mercury were
determined in sediment samples and the values are re-
ported in units of mg/Kg.
The contamination factor for the sediment samples
were calculated by the equation;
Figure 1. Area map of Vembanad wetland system showing
the sediment sampling sites.
Contamination Factor (CF) = Metal content in sedi-
ment/Background level of metal (1)
The method proposed by Tomlinson et al. [14] had
employed in the present study to find the sediment pollu-
tion load index (PLI) which is given by the equation;
PLI = (Product of n number of CF values)1/n (2)
Enrichment factors (EF) for metal concentration in
sediments at all the stations was calculated and used for
comparison. The following equation was used to calcu-
late the EFc values.
EFc = X/Fe (sediment)/X/Fe (Earth’s crust) (3)
where X is the metal studied and X/Fe is the ratio of the
concentration of element X to iron. Iron was chosen as
the element of normalization because natural sources
(98%) vastly dominate its input. The crustal abundance
data of Bowen [36] were used for all EF values.
The geoaccumulation index Igeo values were calcu-
lated for different metals as introduced by Muller [37] is
as follows:
Igeo = Log2(Cn/1.5*Bn) (4)
where Cn is the measured concentration of element n in
the sediment simple and Bn is the geochemical back-
ground for the element n which is Esther directly meas-
ured in pre civilization sediments of the area or taken
from the literature (average shale values). The factor 1.5
was introduced to include the possible variation of the
background values that are due to lithological variations.
3. Results
One of the simple ways of assessing the level of pollu-
tion in an aquatic ecosystem is the comparison with dif-
ferent sediment quality guidelines. The range and the
mean concentration of heavy metals determined in the
sediment samples and their comparative assessment with
different international sediment quality guidelines are
tabulated in Tabl e 1. The concentration of copper varied
from 38.7 mg/Kg to 1723.75 mg/Kg. Zinc has a variation
from 70.7 mg/Kg to 1963.67 mg/Kg. Manganese con-
centration in the surface sediments according to the pre-
sent investigation varied from 320.51 mg/Kg to 15586.88
mg/Kg. Cadmium in the sediment ranges from 0.27
mg/Kg to 6.35 mg/Kg. The concentration of lead ranged
from 21.70 mg/Kg to 162.59 mg/Kg. Nickel has a varia-
tion from 49.59 mg/Kg to 75.70 mg/Kg.
The level of contamination in aquatic system can be
assessed by determining a factor called the degree of
contamination (mCd). Elemental background concentra-
tion reported for continental crust was used as the refer-
ence value. The calculated value for the degree of con-
tamination ranges from 1.47 to 35.39. The extend of pol-
lution in an aquatic environment can be evaluated by a
Copyright © 2011 SciRes. JEP
Ecotoxicity and Ecosystem Health of a Ramsar Wetland System of India
Copyright © 2011 SciRes. JEP
Table 1. Concentration range of different heavy metals and its comparison with different SQGs.
mg/Kg Mean Range
Cu 799.15 38.87 - 1723.75 16 110 34 270 18.711035.719760 - 125 <25 25 - 50>50
Zn 528.21 70.07 - 1963.67 120 820 150410 124.0270 70 - 400 <90 90 - 200>200
Mn 4928.9 320.51 - 15586.88 460 1110 1500 - 3000 - - -
Cd 6.63 0.27 - 26.35 0.6 10 1.29.6 0.684.200.6 3.53 - 8 - - -
Pb 66.40 21.70 - 162.59 31 250 46.7218 30.211035 91.3100 - 400 <40 40 - 60>60
Ni 64.35 49.59 - 75.70 16 75 20.951.615.943 123315100 <20 20 - 50>50
ERL-Effect Range Low, ERM- Effect Range Median, TEL-Threshold Effect Level, PEL-Probable Effect Level, IGM-Interim sediment quality Goals, NP-Non
Polluted, MP-Moderately Polluted, HM-Heavily Polluted.
simple method based on pollution load index (PLI). The
world average concentration of elements reported for
Shale was taken as the reference for PLI. Station 6/VL
reported lower PLI value (1.02) and the highest (12.92)
was reported for station 2/VL. The potential acute toxic-
ity of contaminants in sediment samples can be estimated
as the sum of toxic units (TU) defined as the ratio of
determined concentration to PEL values. The TU values
also show the same trend as like mCd and PLI. The dif-
ferent values observed for degree of contamination, pol-
lution load index and sum of toxic units are summarized
in Table 2. All the values indicated metal contamination
in the Vembanad Lake.
A common approach to estimate how much the sedi-
ment is impacted (naturally and anthropogenically) with
heavy metal is to calculate the enrichment factor (EF) for
metal concentrations above uncontaminated background
levels. The average standard reported for Shale was used
as the reference value in the present study. The enrich-
ment factors for different metals in different stations are
tabulated in Tabl e 3 . Index of geochemical accumulation
(Igeo) has been used widely to evaluate the degree of
metal contamination or pollution in terrestrial, aquatic
and marine environment. World average reported for
Shale was used as the control in the present study. Geo-
accumulation index for different stations is summarized
in Table 4.
Correlation matrix provides clues about the carrier
substances and the chemical association of these metals
in the ecosystem. In the present study Pearson’s correla-
tion has employed for different metals with organic mat-
ter. The correlation matrix is given in Table 5.
4. Discussion
4.1. Spatial Variation of Heavy Metals
Figure 2 represents the spatial variation of different
heavy metals in the surface sediments of Vembanad wet-
land system. The mean concentration of different heavy
metals follows the order manganese > copper > zinc >
lead > nickel > cadmium > mercury. The average con-
centration of copper is 799.15 mg/Kg, which was above
the all compared sediment quality guidelines. The high-
est deposition was found in the Cochin bar mouth and
lowest was reported in the station 6/VL, which is in the
southern end. High level of copper indicates a higher
input of organic matter deposition, which might be from
urban and industrial waste water sediment deposition.
The average concentration of zinc is 528.21 mg/Kg,
which was also above the all sediment quality guidelines.
Manganese in earth crust is 1060 mg/Kg; in soils it is 61 -
1060 mg/Kg. The station 2/VL has reported 15586.88
which is far away from the guideline values. A uniform
decreasing trend was observed for manganese except for
the station 1/VL. The average abundance of cadmium in
the earth crust is 0.16 ppm; in soils it is 0.1 - 0.5 mg/Kg.
Increased cadmium concentration might be related to
industrial activity, atmospheric emission and deposition
of organic and fine grain sediments. Lead is considered
as a good indicator of pollution by urban run-off water.
The use of gasoline is mainly responsible for the lead
pollution especially in urban area. The average concen-
tration of lead in the present study is 66.40 mg/Kg, which
is in the category of highly polluted sediments according
to United State Environmental Protection Agency Guide-
lines. The background value of nickel in the earth crust is
1.2 mg/Kg; in soil it is 2.5 mg/Kg. Nickel is used princi-
pally in its metallic form combined with other metals and
nonmetals as alloys. The mean value of nickel is 64.35
mg/Kg, which is above the United State Environmental
Protection Agency Guidelines for highly polluted sedi-
ments. The mercury pollution is severe in the sediments
of the Cochin bar mouth with a concentration of 4.91
Ecotoxicity and Ecosystem Health of a Ramsar Wetland System of India
Table 2. Spatial variation of heavy metals and different index values.
Element/Stations 1/VL 2/VL 3/VL 4/VL 5/VL 6/VL Continental Crust Average shale
Cu mg/Kg 1346.25 1588.13 1723.75 47.60 50.30 38.87 55.00 45.00
Zn mg/Kg 578.11 1963.67 70.07 223.00 156.68 177.75 70.00 95.00
Mn mg/Kg 4040.00 15586.88 8714.38 501.67 320.51 410.00 950.00 900.00
Cd mg/Kg 7.03 26.35 5.23 0.27 0.35 0.55 0.20 0.30
Pb mg/Kg 27.18 78.27 162.59 28.65 80.03 21.70 12.50 20.00
Ni mg/Kg 70.56 72.82 49.59 64.73 75.70 52.67 75.00 68.00
Hg, mg/Kg 0.56 0.23 4.91 0.136 0.345 0.270
mCd 12.54 35.39 13.55 1.51 2.11 1.47
PLI 5.48 12.92 5.52 1.09 1.23 1.02
SUM TU 17.94 30.39 19.81 3.09 3.61 2.56
mCd: Degree of Contamination, PLI- Pollution Load Index, SUM TU- Sum of Toxic Units.
Table 3. Enrichment factor calculated for the sediment samples of Vembanad wetland system.
Enrichment Factor
1/VL 2/VL 3/VL 4/VL 5/VL 6/VL
Cu 19.94 23.53 25.54 0.71 0.75 0.58
Zn 4.06 13.78 0.49 1.56 1.10 1.25
Mn 2.99 11.55 6.46 0.37 0.24 0.30
Cd 15.61 58.56 11.61 0.59 0.79 1.21
Pb 0.91 2.61 5.42 0.95 2.67 0.72
Ni 0.63 0.71 0.49 0.63 0.74 0.52
Table 4. Sediment geo-accumulation index (Igeo) calculated for sediments of Vembanad wetland system.
Index of Geo-accumulation
1/VL 2/VL 3/VL 4/VL 5/VL 6/VL
Cu 4.32 4.56 4.67 0.50 0.42 0.80
Zn 2.02 3.78 1.02 0.65 0.14 0.32
Mn 1.58 3.53 2.69 1.43 2.07 1.72
Cd, 3.96 5.87 3.54 0.75 0.35 0.28
Pb, 0.14 1.38 2.44 0.07 1.42 0.47
Ni 0.67 0.49 1.04 0.66 0.43 0.95
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Ecotoxicity and Ecosystem Health of a Ramsar Wetland System of India715
Table 5. Pearson Correlation Matrix for different heavy metals with organic matter.
Cu Zn Mn Cd Pb Ni Hg O.M
Cu 1.00 0.50 0.84 0.68 0.57 0.08 0.57 0.27
Zn 1.00 0.81 0.97 0.04 0.48 0.32 0.53
Mn 1 0.93 0.50 0.08 0.29 0.11
Cd 1.00 0.19 0.34 0.07 0.37
Pb 1.00 0.31 0.87 0.31
Ni 1.00 0.65 0.86
Hg 1.00 0.70
O.M 1.00
O.M: Organic Matter.
Figure 2. Spatial variation of different heavy metals in the surface sediments.
4.2. Sediment Quality Indices
The index value of various sediment quality indices such
as degree of contamination, pollution load index and sum
of toxic units are depicted in Figure 3. The degree of
contamination (mCd) in an ecosystem is usually ex-
pressed by the following terminologies.
mCd 1.5 nil to very low degree of contamination
1.5 mCd < 2 low degree of contamination
2 mCd <4 moderate degree of contamination
4 mCd <8 high degree of contamination
8 mCd < 16 very high degree of contamination
16 mCd <32 extremely high degree of contamination
mCd 32 ultra high degree of contamination
Comparison of the results with the above terminol-
ogies indicated that ultra degree of contamination is ob-
served at the station 2/VL which is located near the out-
lets of many industries. The other two stations 1/VL and
2/VL, near by the industrial units indicated very high
degree of contamination. Moving towards the south a
comparative decrease in the contamination was observed.
The two stations, 4/VL and 5/VL experienced low degree
of contamination. Sediment in the southern end indicated
very low degree of contamination. The spatial variation
of degree of contamination indicated that the movement
of contaminated water and sediments from estuarine re-
gion to southern half of Vembanad wetland system at the
time of high tide contaminated the fresh water region to
some extend.
The pollution load index of the wetland follows the
same order as the degree of contamination. If the PLI
value is greater than one it indicates pollution and if it is
less than one it shows no pollution. The PLI can provide
information about the quality of the environment, which
provides valuable information to the decision makers on
the pollution level of the area. Hence according to PLI
values all the stations in the wetland system is polluted.
The sediment quality guidelines of the National Ocea-
nographic and Atmospheric Administration (NOAA) of
the Unite States shows Effect Range Low (ERL) and
Effect Range Median (ERM) values, which represents
the percentile ranges of toxicity tolerance in bioassay
Copyright © 2011 SciRes. JEP
Ecotoxicity and Ecosystem Health of a Ramsar Wetland System of India
Figure 3. Variation of different sediment quality index val-
ues for Vembanad wetland system.
tests for aquatic and benthic biota. These effects are
given by
Metal < ERL minimal effect range biological effects
are rarely observed
ERL < Metal < ERM moderate effect range biological
effects occur occasionally
Metal > ERM probable effect range biological effects
occur frequently
The mean concentration of copper and zinc exceeded
the ERM limits, which represents a probable effect range
with in which adverse biological effects frequently occur.
Spatial variation of trace elements indicated that biologi-
cal effects are rare in southern half and frequent in estua-
rine side. The potential acute toxicity for the sediments
were determined by calculating the sum of toxic units
and showed similar trend like mCd and PLI.
The enrichment factor method normalizes the meas-
ured heavy metal content with respect to a sample refer-
ence such as iron. It can be used to differentiate between
the metal originating from anthropogenic activities and
those from natural procedure, and to assess the degree of
anthropogenic influence. Five contamination categories
are recognized on the basis of the enrichment factor,
which are
EF < 2 deficiency to minimal enrichment
EF 2 - 5 moderate enrichment
EF 5 - 20 significant enrichment
EF 20 - 40 very high enrichment
EF > 40 extremely high enrichment
A value of 0.5 EF 1.5 suggests that traces of metal
may be due to crystal materials or natural weathering
processes. Samples having EF value greater than 5 are
considered to be contaminated with that particular ele-
ment. Figure 4 represents all the EF values of the heavy
metals. The station 2/VL showed very high enrichment
for the metal cadmium. It is presumed that high EF val-
ues indicate an anthropogenic source of heavy metals,
mainly from activities such as industrialization and ur-
banization. Comparatively less enrichment was observed
in samples of southern region. But according to Khan et
al. [38] EF value less than one are considered significant.
Areas with EF values <1 should be viewed with caution
as they imply preferential release of these metals, making
them bioavailabe.
The Index of geo-accumulation calculated for the de-
gree of metal pollution is assessed in terms of seven con-
tamination classes based on the increasing numerical
value of the index as follows:
Igeo < 0 unpolluted
0 <= Igeo < 1 unpolluted to moderately polluted
1 <= Igeo < 2 moderately polluted
2 <= Igeo < 3 moderately polluted to strongly polluted
3 <= Igeo < 4 strongly polluted
4 <= Igeo < 5 strongly polluted to very strongly pol-
Igeo >= 5 very strongly polluted
Figure 5 represents the geo-accumulation index for
different heavy metals in the wetland. It indicates strong
pollution in the industrial zone and unpolluted to moder-
ate pollution in the freshwater region. Elements copper
Figure 4. Variation of enrichment factor along different
Figure 5. Variation of geo-accumulation index for different
Copyright © 2011 SciRes. JEP
Ecotoxicity and Ecosystem Health of a Ramsar Wetland System of India717
and cadmium have higher values in northern half where
as it is very low in southern side.
4.3. Pearson’s Correlation Matrix
Correlation analysis of heavy metals with organic matter
present in the sediment was carried out. Zinc and nickel
have good correlation with organic matter where as
mercury have a strong negative correlation. The element
cadmium has good correlation with all other elements
except mercury. Copper also has good correlation with
other metals except nickel and organic matter. The per-
centage of different metals in the sediments of fresh wa-
ter region with reference to industrial zone was calcu-
lated. The concentration of nickel in both the regions was
same, which indicated the higher mobility of the metal
nickel. The lowest percentage was reported for copper,
which indicated its lower mobility. The above facts were
conformed from the correlation matrix, where nickel has
good correlation with organic matter and copper have no
correlation. Hence the concentration of the heavy metals
in fresh water is a proportionate of the mobility of metal
and contamination load at industrial side.
5. Conclusions
The study of “Ecotoxicity and ecosystem health of a
Ramsar wetland system of India” showed a clear pattern
of anthropogenic impact on Vembanad wetland system.
From the observation it is clear that manganese and cop-
per showed more pronounced level followed by zinc,
lead, nickel, cadmium and mercury. Comparison of
heavy metal concentration with different international
sediment quality guidelines indicated that most of the
heavy metal concentration in the northern side of the
wetland system has crossed the extreme limits where as
southern half is with in the range of guideline values. The
assessment of level of contamination by calculating the
degree of contamination for different stations confirmed
ultra degree of contamination at station near by industrial
area. Enrichment factor determined for the deferent
heavy metals indicated anthropogenic origin of heavy
metal in estuarine side. Index of geo-accumulation was
also showed the same trend like enrichment factor. Ac-
cording to NOAA guidelines the health of the ecosystem
was seriously impaired with frequent biological effects
were occurring in estuarine side. The extend of pollution
at the fresh water region also depends on the mobility of
the specific metal. Nickel has higher mobility which has
hundred percentage contribution, where as copper is less
mobile which indicated its lowest contribution from the
industrial zone. Anthropogenic source from the industrial
activities at the upstream of the wetland contributed huge
load of heavy metals to the estuarine region which is
seriously attacking the fresh water region of the Vemba-
nad wetland system.
6. Acknowledgements
The authors wish to express their gratitude to the De-
partment of Science and Technology (DST), Government
of India for the financial assistance to carryout the re-
search work.
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