Chemosphere 61 (2005) 1587–1593

www.elsevier.com/locate/chemosphere

Seasonal distribution and contamination levels of totalPHCs, PAHs and heavy metals in coastal waters of the

Alang–Sosiya ship scrapping yard, Gulf of Cambay, India

M. Srinivasa Reddy, Shaik Basha, H.V. Joshi, G. Ramachandraiah *

Central Salt and Marine Chemicals Research Institute, Gijubhai Badheka Marg, Bhavnagar 364 002, Gujarat, India

Received 18 November 2004; received in revised form 15 April 2005; accepted 18 April 2005

Available online 29 June 2005

Abstract

Alang–Sosiya situated on the Gulf of Cambay is one of the largest ship breaking yard in the world. The seasonal

distribution and contamination levels of dissolved and/or dispersed total petroleum hydrocarbons (PHCs), total poly-

cyclic aromatic hydrocarbons (PAHs) and heavy metals in seawater during high tide are investigated. The concentra-

tions of petroleum hydrocarbons and heavy metals are higher in the winter than in the monsoon and summer. The

concentrations of total PHCs and PAHs are about three times higher in the winter and two times in the monsoon

or summer at Along–Sosiya and about twice in all seasons at two stations one on either side 5 km away from it as com-

pared to the reference station at Mahuva, 60 km away towards the south. Further, the levels of PHCs are correlated

with salinity and compared with those of other regions. The concentration of all metals is the highest in the winter sea-

son followed by the monsoon and summer. We carried out the quantitative analysis of the possible relationships among

13 variables such as Al, Fe, Pb, Mn, Cu, Zn, Cd, Cr, Co, pH, NO�3 , NO2 and PO3�

4 .

� 2005 Elsevier Ltd. All rights reserved.

Keywords: Petroleum hydrocarbons; Heavy metal; Seasonal effects; Ship scrapping yard; Alang–Sosiya; Gulf of Cambay

1. Introduction

Of the total world�s ocean-going ships, about 1400

ships are being taken out of service every year and sent

to scrapping yards mainly in Asia for their dismantling

with an aim to recycle the materials for diverse purposes.

To date, about 70% of these ships are being sent to the

Alang–Sosiya ship scrapping yard, Gulf of Cambay,

India (Srinivasa Reddy et al., 2003). While dismantling

the ships, the industry generates all kinds of wastes in

0045-6535/$ - see front matter � 2005 Elsevier Ltd. All rights reserv

doi:10.1016/j.chemosphere.2005.04.093

* Corresponding author. Tel.: +91 278 2567760; fax: +91 278

2566970/2567562.

E-mail address: grama@csmcri.org (G. Ramachandraiah).

the form of solids, liquids and gases. Both miscible

and immiscible waste materials accumulate over the soil

and then ramify incrementally to seawaters in a stepwise

manner through tidal and sub-tidal zones, deep sea and

their respective sediments. The pollutants mainly consti-

tute heavy metals, petroleum hydrocarbons and bacte-

rial contaminants (Islam and Hossain, 1986; Tewari

et al., 2001; Srinivasa Reddy et al., 2003). Among these

contaminants, heavy metals and petroleum hydrocar-

bons are considered as the most serious pollutants due

to their toxicity and tenacity (Forstner and Wittmann,

1981; Sinex and Wright, 1988).

Petroleum products are carcinogens and affect a vari-

ety of biological processes and potent cell mutagens

ed.

Fig. 1. Geographical location of the study area of Alang–

Sosiya and Mahuva on the Gulf of Cambay.

1588 M. Srinivasa Reddy et al. / Chemosphere 61 (2005) 1587–1593

(Neef, 1990; Capone and Bauer, 1992; Owen et al.,

1995). Estimates revealed that about 6.1 million metric

tons of petroleum products were being released to global

oceans annually (Capone and Bauer, 1992). The bulk of

this rapidly associates with hydrophobic organic matter

and suspended particulates, while the volatile portion

evaporates. The non-volatile (emulsion or mousse) part

of these petroleum products eventually sink to the bot-

tom and settle on to the sediment (Capone and Bauer,

1992). The worst impacts of lighter and suspended frac-

tions of the spilled petroleum hydrocarbons are on lar-

vae, low motility organisms and the drastic changes in

feeding or reproductive cycles that ultimately affect pop-

ulation size and fecundity. On the other hand, the petro-

leum hydrocarbons settled in the sediments affect the

filter feeders and benthic organisms with the bioaccumu-

lation of toxic compounds in tissues, genetic mutations

and cell atrophy (Peters et al., 1997).

Heavy metals once entered in water system are accu-

mulated by marine invertebrates, associated with partic-

ulates and subsequently removed to the maximum

extent by adsorption onto the sediments leaving par-

tially in waters in a suspended or soluble complex form

leading to serious bioaccumulation atrophy (Goldberg

et al., 1977; Finney and Huh, 1989; Larsen and Jensen,

1989; Rainbow, 1990).

The Alang–Sosiya ship breaking yard, established way

back in 1982, is the world�s largest ship scrapping zone on

the Gulf of Cambay, India, with an annual turnover of

US$1.3 billions (Gujarat Maritime Board, 2003). Re-

cently, we have reported the contamination levels of hea-

vy metals in intertidal sediments of this coastal region

(Srinivasa Reddy et al., 2004). However, the study on sea-

sonal distributions and infectivity levels of dissolved and/

or dispersed petroleum hydrocarbons and heavymetals in

seawaters of this basin, which is of utmost importance,

has not extensively been surveyed before. Presumably,

one can expect the highest degree of contamination within

the intertidal zone wherein ships are broken for such a

long period. The present paper describes the degree of dis-

tributions and infectivity levels of dissolved/dispersed

petroleum hydrocarbons and heavy metals in seawaters

of intertidal zones at high tides during three successive

seasons of 10 locations, separated by 1 km along the coast

covering the entire ship scrapping yard, two stations one

on either side 5 km away from the first and last stations

and at one reference station at Mahuva, 60 km away to-

wards the south of Alang–Sosiya. Further, the marine

pollution based on the observed data at the Alang–Sosiya

ship breaking yard is also evaluated.

2. Study area

The Alang–Sosiya ship scrapping yard is geographi-

cally situated 21�5 0 21�29 0 towards the north and 72�5 0

72�15 0 towards the east on the Western Coast of the

Gulf of Cambay (Fig. 1). The average highest tide at this

place is believed to be around 13 m, second in the

world�s range. It has a gentle sloping with a hard and

firm rocky bottom, which is more convenient for bring-

ing the ships right up to the scrapping yard afloat with

minimum investment and risk factors. The yard

stretches to about 14 km along the north–south, encom-

passing a total area of approximately 67 km2 with a

small creek bifurcating into nearly two equal parts.

The southern part is designated as Alang while the other

is known as Sosiya, popularly called the Alang–Sosiya

ship scrapping yard. In all, there are 112 ship breaking

plots in Alang and 80 plots in Sosiya, each having a

length of 50–240 m and a width of 30–120 m and giving

succor to about 40000 people with a progressive annual

increase (Gujarat Maritime Board, 2003). The statistical

data till March 2002 reveal that about 3600 (approxi-

mately 195 per year) ships mainly cargo vessels, oil tank-

ers, passenger liners and warships having about 26–27

million MT light dead tonnage (LDT) were beached in

a span of 20 years (Gujarat Maritime Board, 2003).

The shipbreakers on an average dismantle a ship of

about 10000–13000 tons in a day or two (Gujarat Mar-

itime Board, 2003). Consequently, a considerable level

of sediment and seawater contamination is envisaged

at the intertidal zone along the coast.

3. Materials and methods

The detailed description of the study area and the

sampling locations under investigation is dealt with in

Figs. 1 and 2. The entire ship scrapping yard covering

the first and the last ship breaking units was divided into

approximately 10 equal parts to have 10 sampling loca-

tions marked as SS1 to SS10 (Fig. 2) at a kilometer dis-

Fig. 2. Locations of sampling stations (SS0–SS11) along the Alang–Sosiya ship breaking yard.

M. Srinivasa Reddy et al. / Chemosphere 61 (2005) 1587–1593 1589

tance. Seawater samples were collected from all the sam-

pling stations at a 1 m depth from the surface during

high tides covering the three seasons, summer (May

�03), monsoon (Aug. �03), and winter (Dec. �03) using

4 l amber bottles. In order to assess the hydrodynamic

mixing and distribution of the contaminants along the

Alang–Sosiya coast, samples were also collected under

similar conditions from SS0 and SS11 which are at

5 km distance from SS1 and SS10, respectively. Further,

to evaluate the relative level of pollution at Alang–Sos-

iya, reference samples from five different places at a dis-

tance of half a kilometer were also taken during the high

tide at Mahuva (SSM, Fig. 1), 60 km away towards the

south from the Alang–Sosiya coast, wherein the conta-

mination by anthropogenic activity is the lowest. The

mean observed value of all these five stations at SSMwas considered for a comparative study.

The total petroleum hydrocarbons (TPHCs) and

total polycyclic aromatic hydrocarbons (TPAHs) in

seasonal concentrations of seawater samples were ex-

tracted three times using 20 ml, each time, of pesticide

grade n-hexane (Ehrhardt et al., 1983; Zanardi et al.,

1999). All the extracts were mixed and evaporated to

dryness in a rotary evaporator under reduced pressure

(IOC/UNEP, 1984; MOOPAM, 1999). The fluores-

cence of the samples was measured by a Perkin–Elmer

luminescence spectrophotometer (LS 50 B) using

310 nm as excitation and 360 nm as emission wave-

lengths for TPHCs, while following 265 nm as excitation

wavelengths (IOC/UNEP, 1984; Owen et al., 1995;

MOOPAM, 1999) for TPAHs analyses. A calibration

curve was produced with an artificially weathered crude

oil (Kuwait) for TPHCs and Chrysene for TPAHs stan-

dards. Samples falling outside the calibration curve were

diluted appropriately with n-hexane. The average con-

centration in the blank was measured to be 0.05 lg/l,which was subtracted from all readings of all samples

under study.

The seawater samples were collected separately in a

clean plastic bucket for heavy metal analyses. They were

filtered through a 0.45 lm Millipore membrane filter,

acidified to pH 2 with concentrated HNO3 and were

stored at a freezing temperature. The samples were

pre-concentrated using APDC and MIBK solutions

(Brooks et al., 1967; Tsukaijan and Young, 1978) and

estimated by employing a Flame Atomic Absorption

Spectrophotometer (Shimadzu AA-680). All pH mea-

surements were made up to decimals on a digital pH

meter. Nutrients like NO�2 , NO�

3 and PO3�4 were deter-

mined calorimetrically. All experiments were repeated

thrice and their average values are only recorded.

4. Results and discussion

4.1. Petroleum hydrocarbons

The seasonal concentrations of total petroleum

hydrocarbons (PHCs) and polycyclic aromatic hydro-

carbons (PAHs) found in seawaters of stations SS1–

SS10 at Alang–Sosiya, SS0 and SS11 5 km away on either

side of it, and SSM, the reference station at Mahuva are

presented in Tables 1 and 2. The measured concentra-

tions were more at Alang–Sosiya than those 5 km away

from it and the reference station. However, the concen-

trations were high in the winter than that in the mon-

soon followed by that in the summer at all stations.

The PHCs and PAHs were three times more in the win-

ter and two times in the summer/monsoon at Along–

Sosiya and about twice in all seasons at SS0 and SS11

Table 1

Seasonal effects on concentrations of dissolved/dispersed total

petroleum hydrocarbons (TPHs) in the coastal waters of

Alang–Sosiya (SS0–SS11), and the reference station at Mahuva

(SSM)

Sampling

station

Seasonal concentrations of TPHCs (lg/l)

Summer

(May �03)Monsoon

(Aug. �03)Winter

(Dec. �03)

SS0 657 ± 32 765 ± 37 875 ± 34

SS1 1259 ± 28 2325 ± 33 2390 ± 36

SS2 1198 ± 24 1688 ± 26 2605 ± 32

SS3 1375 ± 31 1638 ± 28 2163 ± 28

SS4 1089 ± 27 1620 ± 29 2950 ± 29

SS5 1281 ± 30 1648 ± 22 2388 ± 26

SS6 1439 ± 22 1845 ± 32 2575 ± 27

SS7 1171 ± 34 2176 ± 34 2395 ± 30

SS8 1077 ± 25 1894 ± 35 2313 ± 27

SS9 1415 ± 22 1976 ± 29 3540 ± 32

SS10 1174 ± 24 1678 ± 34 3137 ± 32

SS11 730 ± 21 783 ± 22 871 ± 26

SSM 257 ± 12 453 ± 14 550 ± 13

Table 2

Seasonal effects on concentrations of dissolved/dispersed total

polycyclic aromatic hydrocarbons (TPAHs) in the coastal

waters of Alang–Sosiya (SS0–SS11), and the reference station

at Mahuva (SSM)

Sampling

station

Seasonal concentrations of TPAHs (lg/l)

Summer

(May �03)Monsoon

(Aug. �03)Winter

(Dec. �03)

SS0 336 ± 12 455 ± 14 547 ± 18

SS1 511 ± 16 663 ± 18 913 ± 16

SS2 504 ± 13 634 ± 16 1420 ± 13

SS3 509 ± 11 674 ± 13 938 ± 12

SS4 513 ± 17 881 ± 17 977 ± 11

SS5 719 ± 13 709 ± 13 1446 ± 14

SS6 687 ± 14 756 ± 11 907 ± 17

SS7 466 ± 17 889 ± 15 1003 ± 13

SS8 532 ± 16 698 ± 18 1565 ± 13

SS9 497 ± 19 770 ± 16 1497 ± 17

SS10 473 ± 14 676 ± 19 1347 ± 16

SS11 359 ± 13 483 ± 17 503 ± 14

SSM 78 ± 7 99 ± 6 120 ± 91

Fig. 3. Correlation between total petroleum hydrocarbons and

salinity in the Alang–Sosiya ship breaking yard.

1590 M. Srinivasa Reddy et al. / Chemosphere 61 (2005) 1587–1593

as compared to the reference station SSM. The high

water-residence time could be an important factor influ-

encing the accumulation and retention of hydrocarbons

in seawaters in the winter season. The low concentration

levels of hydrocarbons during the monsoon and summer

seasons show that they are being diluted significantly.

The high incoming fresh waters and river discharges

during the monsoon season dilute the petroleum hydro-

carbons effectively into the sea. In the case of the

summer season, the evaporation of petroleum hydrocar-

bons due to high temperatures and low atmospheric

pressures may occur to a considerable extent.

Fig. 3 shows the correlation of PHCs with the respec-

tive seasonal salinity. The highest positive correlation

was observed during the winter (R2 = 0.82) followed by

that of the monsoon (R2 = 0.71) and the summer

(R2 = 0.69). In fact, according to Estevs and Commenda-

tore (1993), the high salinity could also be responsible for

the rise in the water-residence time. Comparing the pres-

ent data on PHCs in Table 1 with those reported for other

coastal regions by different authors (Laubier, 1978; Sen

Gupta et al., 1980; Fileman and Law, 1988; Estevs and

Commendatore, 1993), it is evident that the hydrocarbon

concentrations are significantly 10–100 times higher in

the coastal waters of the Alang–Sosiya region, indicating

the expansion of hydrocarbon contamination on account

of ship scrapping activities in this region.

4.2. Heavy metals

Table 3 depicts the seasonal variations in the average

heavy metal concentrations in seawaters of all stations

studied here. A trend of higher metal concentrations at

stations SS1–SS10 in Alang–Sosiya than at SS0, SS11and SSM was observed. Among the three seasons, the

concentrations of all metals were the highest in the win-

ter season followed by in the monsoon and summer. The

high degree of metal dispersion into waters at low tem-

peratures and low tides during the winter may be an

explanation for the highest concentration of heavy met-

als. The enrichment of heavy metals in the monsoon sea-

son may be accounted for the inflow of fresh metal

contaminants from working yards and the domestic

wastes along with the rain waters, while the low concen-

trations in the summer season is probably due to the

maximum precipitation and adsorption of metals onto

the sediments being influenced by high temperature.

4.3. Correlation analysis

In order to observe the characteristics shared by

the different communalities of the individuals these

Table 3

The average concentrations of heavy metals in the coastal waters of Alang–Sosiya (SS1–SS10), 5 km (SS0 and SS11) away on either side

of it and the reference station at Mahuva (SSM)

Sampling

station

Season

in 2003

Concentration of heavy metal (lg/l)

Cd Co Cr Cu Fe Mn Ni Pb Zn

SS1–SS10 Summer 341 ± 14 1226 ± 45 621 ± 26 3122 ± 113 2889 ± 142 4139 ± 243 522 ± 126 1570 ± 146 4271 ± 136

Monsoon 435 ± 12 1400 ± 42 648 ± 28 3552 ± 118 3095 ± 126 4015 ± 221 621 ± 127 1700 ± 136 4940 ± 231

Winter 561 ± 17 1665 ± 43 765 ± 24 3939 ± 123 3662 ± 132 4920 ± 232 944 ± 132 2036 ± 167 5832 ± 123

SS0 and

SS11

Summer 131 ± 11 474 ± 26 280 ± 25 1895 ± 106 1225 ± 119 2550 ± 137 177 ± 14 1218 ± 68 3122 ± 156

Monsoon 252 ± 12 599 ± 41 365 ± 23 2820 ± 122 1370 ± 98 3420 ± 156 197 ± 34 1470 ± 98 3152 ± 135

Winter 310 ± 13 642 ± 46 445 ± 29 2900 ± 132 1546 ± 114 3155 ± 164 219 ± 28 1560 ± 123 3895 ± 146

SSM Summer 34 ± 9 36 ± 8 35 ± 6 32 ± 5 29 ± 5 31 ± 6 28 ± 5 30 ± 3 33 ± 8

Monsoon 38 ± 8 40 ± 5 39 ± 5 36 ± 4 33 ± 2 35 ± 4 32 ± 7 34 ± 6 37 ± 6

Winter 58 ± 7 60 ± 9 59 ± 9 56 ± 10 53 ± 8 55 ± 11 52 ± 6 54 ± 6 57 ± 11

Table 4

Correlation matrix for the winter season

Ni Fe Pb Mn Cu Zn Cd Cr Co pH PO4 NO3 NO2

Ni 1.00

Fe 0.90** 1.00

Pb 0.88** 0.86** 1.00

Mn 0.87** 0.93** 0.94** 1.00

Cu 0.74** 0.80** 0.83** 0.89** 1.00

Zn 0.76** 0.79** 0.92** 0.93** 0.90** 1.00

Cd 0.67** 0.66* 0.69* 0.79** 0.66* 0.75** 1.00

Cr 0.79** 0.85** 0.78* 0.89** 0.89** 0.81** 0.68* 1.00

Co 0.93** 0.94** 0.92** 0.94** 0.86** 0.87** 0.71** 0.83** 1.00

pH 0.83** 0.69** 0.82** 0.79** 0.64* 0.77** 0.65* 0.68* 0.74** 1.00

PO4 0.55 0.72** 0.67* 0.77** 0.82** 0.74** 0.39 0.78** 0.68* 0.56 1.00

NO3 0.93** 0.93** 0.93** 0.96** 0.84** 0.89** 0.72** 0.90** 0.94** 0.85** 0.74* 1.00

NO2 0.83** 0.74** 0.81** 0.75** 0.74** 0.73** 0.59 0.63* 0.86** 0.69* 0.46 0.79** 1.00

* Correlation is significant at the 0.05 level (2-tailed).** Correlation is significant at the 0.01 level (2-tailed).

Table 5

Correlation matrix for the summer season

Ni Fe Pb Mn Cu Zn Cd Cr Co pH PO4 NO3 NO2

Ni 1.00

Fe 0.74** 1.00

Pb 0.56* 0.81** 1.00

Mn 0.69** 0.91** 0.74** 1.00

Cu 0.52 0.91** 0.66* 0.89** 1.00

Zn 0.58 0.83** 0.75** 0.96** 0.84** 1.00

Cd 0.75** 0.87** 0.78** 0.79** 0.72** 0.73** 1.00

Cr 0.65* 0.76** 0.82** 0.61* 0.60* 0.62* 0.63* 1.00

Co 0.72** 0.79** 0.51 0.69** 0.77** 0.59 0.61* 0.60* 1.00

pH 0.51 0.44 0.16 0.19 0.22 �0.03 0.41 0.26 0.35 1.00

PO4 0.37 0.62* 0.59 0.77** 0.73** 0.87** 0.49 0.55 0.40 �0.31 1.00

NO3 0.79** 0.94** 0.76** 0.93** 0.88** 0.86** 0.83** 0.75** 0.81** 0.36 0.64* 1.00

NO2 0.75** 0.91 0.70** 0.87** 0.84** 0.75** 0.80** 0.68* 0.76** 0.52 0.52 0.94** 1.00

* Correlation is significant at the 0.05 level (2-tailed).** Correlation is significant at the 0.01 level (2-tailed).

M. Srinivasa Reddy et al. / Chemosphere 61 (2005) 1587–1593 1591

Table 6

Correlation matrix for the monsoon season

Ni Fe Pb Mn Cu Zn Cd Cr Co pH PO4 NO3 NO2

Ni 1.00

Fe 0.90** 1.00

Pb 0.72** 0.80** 1.00

Mn 0.68* 0.85** 0.92** 1.00

Cu 0.68* 0.85** 0.93** 0.91** 1.00

Zn 0.63* 0.79** 0.90** 0.96** 0.87** 1.00

Cd 0.85** 0.84** 0.57 0.67* 0.64* 0.67* 1.00

Cr 0.65* 0.73** 0.69** 0.74** 0.79** 0.76** 0.84** 1.00

Co 0.81** 0.92** 0.80** 0.87** 0.85** 0.79** 0.82** 0.81** 1.00

pH 0.16 0.28 0.46 0.41 0.44 0.35 �0.03 0.11 0.30 1.00

PO4 0.74** 0.85** 0.76** 0.83** 0.77** 0.84** 0.82** 0.77** 0.87** 0.20 1.00

NO3 0.68** 0.74** 0.83** 0.84** 0.77** 0.85** 0.65* 0.76** 0.83** 0.48 0.78** 1.00

NO2 0.43 0.55 0.73** 0.79** 0.66* 0.86** 0.48 0.58 0.61* 0.54 0.75** 0.85** 1.00

* Correlation is significant at the 0.05 level (2-tailed).** Correlation is significant at the 0.01 level (2-tailed).

Fig. 4. Dendogram.

1592 M. Srinivasa Reddy et al. / Chemosphere 61 (2005) 1587–1593

characteristics were classified further, into categories

(Bisquwrra, 1989) by employing both correlative/dis-

criminatory and cluster analyses. The quantitative ana-

lyses of the possible relationships were carried out

among 13 variables such as Al, Fe, Pb, Mn, Cu, Zn,

Cd, Cr, Co, pH, PO3�4 , NO�

2 and NO�3 , and the data ob-

tained for three seasons are presented in Tables 4–6. The

data show very high levels of correlation (�6) with

mostly positive values except very few negative values

among different pairs of variables. All the heavy metals,

except few, present a high level of correlation with PO3�4 ,

NO�2 and NO�

3 during all seasons. The element Zn

showed a negative correlation during the summer and

monsoon with pH. All the other heavy metals have a high

positive correlation with each other and pH. Mn showed

the highest positive correlation (0.94) with Pb during the

winter, Zn during the summer (0.96) as well as during the

monsoon (0.96).

4.4. Cluster analysis

The dendogram (Fig. 4) shows the results of applying

the nearest neighbor aggregation strategy for all the

three seasons. In this strategy, the two elements present-

ing the nearest distance in the matrix will form the first

group. The distance between a new element to a group

already formed will be taken as the nearest distance be-

tween that element and its closest element in the group.

The first level of aggregation is established for the pair

Pb–Fe, which at the same time forms a cluster with

the pair Mn–Zn. These two pairs, associated with each

other and with Cu forming a cluster on the right side

of the dendogram, show a first level of association with

Co–pH, and later the other variables NO�3 , PO

3�4 , NO�

2 ,

Cr, Ni and Cd are added. Thus, the variables are classi-

fied as NO�3 –NO�

2 –PO3�4 –pH–Cr–Ni–Cd–Co (Cluster 1)

and Pb–Cu–Fe–Mn–Zn (Cluster 2).

On the basis of correlation matrix data, all the

variables analyzed here are grouped into two (NO�3 –

PO3�4 –NO�

2 –pH–Cr–Ni–Cd–Co as Group I and Pb–

Fe–Cu–Zn–Mn as Group II) indicating their high degree

of interrelationship with a low multiple correlation coef-

ficient. A high level of association was observed within

the Group II variables due to ship scrapping activities

(Islam and Hossain, 1986). The factorial analysis tech-

nique has revealed a high dependence of Group II vari-

ables on ship scrapping activities while Group I

variables on tidal influence as well as domestic dis-

charges (Grande et al., 2000; Borrego et al., 2001; Te-

wari et al., 2001).

5. Conclusions

The seasonal distribution and infectivity levels of dis-

solved and/or dispersed petroleum hydrocarbons and

heavy metals in surface seawaters at the intertidal zone

M. Srinivasa Reddy et al. / Chemosphere 61 (2005) 1587–1593 1593

of the Alang–Sosiya ship breaking yard and a reference

station at Mahuva were investigated. The concentra-

tions of total petroleum hydrocarbons (PHCs) and total

polycyclic aromatic hydrocarbons (PAHs) were about

three times higher in the winter and two times in the

summer/monsoon at Along–Sosiya as compared to the

reference station. The concentration of all metals was

the highest in the winter season followed by in the mon-

soon and summer. It is evident from this study that both

heavy metals and hydrocarbons are significantly high in

coastal waters of the Alang–Sosiya region and are being

affected by ship scrapping activity in this region.

References

Assistant Commissioner, 2003. Gujarat Maritime Board,

Alang; personal discussions.

Bisquwrra, R., 1989. Introduction conceptual analysis multi-

variable. PROMOC PUBLIC UNIV, SA Barcelona.

Borrego, J., Morales, J.A., De La Torre, M.L., Grande, J.A.,

2001. Geochemical characteristics of heavy metal pollution

in surface sediments of the Tinto and Odiel rivers estuary

(SW Spain). Environmental Geology 41, 785–796.

Brooks, R.R., Presley, B.J., Kaplan, I.R., 1967. Determination

of microgram amounts of some transition metals in sea

water by methyl iso-butyl ketone-nitric acid successive

extraction and flameless atomic absorption spectrophoto-

meter. Talanta 14, 809–814.

Capone, D.G., Bauer, J.E., 1992. Environmental microbiology.

Clarendon Press, Oxford.

Ehrhardt, M., Kremling, K., Grasshoff, K., 1983. Determina-

tion of dissolved/dispersed hydrocarbons. Methods of sea

water analysis, second revised and extended ed. Verlag

Chemie Weinheim, New York (pp. 190–281).

Estevs, Jose Luis, Commendatore, Marta Graciela, 1993. Total

aromatic hydrocarbons in water and sediments in a coastal

zone of Patagonia, Argentina. Marine Pollution Bulletin 26,

341–342.

Fileman, T.W., Law, R.J., 1988. Hydrocarbon concentrations

in sediments and water from the English Channel. Marine

Pollution Bulletin 25, 390–393.

Finney, B.P., Huh, C.A., 1989. History of metal pollution in the

Southern California Bight. Environmental Science and

Technology 23, 294–303.

Forstner, U., Wittmann, G.T., 1981. Metal pollution in the

aquatic environment. Springer, London (pp. 450–486).

Goldberg, B.D., Gambles, E., Griffin, I.J., Koide, M., 1977.

Pollution history of Narragansett Bay as recorded in its

sediments. Estuarine and Coastal Marine Science 5, 549–561.

Grande, J.A., Borrego, J., Morales, J.A., 2000. Study of heavy

metal pollution in the Tinto–Odiel estuary in Southwestern

Spain using spatial factor analysis. Environmental Geology

39 (10).

IOC/UNEP (International Oceanographic Commission/United

Nations Environment Program), 1984. Manual for moni-

toring oil and dissolved/dispersed petroleum hydrocarbons

in marine waters and beaches. Manual and Guides, pp. 13–

19.

Islam, K.L., Hossain, M.M., 1986. Effect of ship scrapping

activities on soil and sea environment in the coastal area of

Chittagong, Bangladesh. Marine Pollution Bulletin 17, 462–

463.

Larsen, B., Jensen, A., 1989. Evaluation of the sensitivity of

sediment monitoring stations in pollution monitoring.

Marine Pollution Bulletin 20, 556–560.

Laubier, L., 1978. The Amoco Cadiz oil spill. Lines of study

and early observations. Marine Pollution Bulletin 9, 285–

302.

MOOPAM (Manual of oceanographic observations and pollu-

tant analyses methods), 1999. Regional organization for the

protection of the marine environment, Kuwait.

Neef, J.M., 1990. Composition and fate of petroleum and spill

treating agents in marine environment. In: Geraci, J.R.,

Aubin, D.J.St. (Eds.), Sea mammals and oil: confronting the

risks. Academic Press, San Diego, pp. 1–34.

Owen, C.J., Axler, R.P., Nordman, D.R., Schubauer, M.,

Lodge, K.B., Schubauer, J.P., 1995. Screening for PAHs by

fluorescence spectroscopy: a comparison of calibrations.

Chemosphere 31.

Peters, E.C., Gassman, N.J., Firman, J.C., Richmonds, R.H.,

Power, E.A., 1997. Ecotoxicology of tropical marine

ecosystems. Environmental Toxicology and Chemistry 16,

12–40.

Rainbow, P.S., 1990. Heavy metals in marine invertebrates. In:

Furness, R.W., Rainbow, P.S. (Eds.), Heavy metals in the

marine environment. CRC Press, Boca Raton, FL, pp. 67–

80.

Sen Gupta, R., Quasim, S.Z., Fondecar, S.P., Topgi, R.S.,

1980. Dissolved petroleum hydrocarbons in some regions of

the Northern Indian Ocean. Marine Pollution Bulletin 11,

65–68.

Sinex, S.A., Wright, D.A., 1988. Distribution of trace metals in

the sediments and biota of Chesapake Bay. Marine Pollu-

tion Bulletin 19, 425–431.

Srinivasa Reddy, M., Basha, Shaik, Sravan Kumar, V.G.,

Joshi, H.V., Ghosh, P.K., 2003. Quantification and classi-

fication of ship scrapping waste at Alang–Sosiya, India.

Marine Pollution Bulletin 46, 1609–1614.

Srinivasa Reddy, M., Shaik Basha, Sravan Kumar, V.G., Joshi,

H.V., Ramachandraiah, G., 2004. Distribution enrichment

and accumulation of heavy metals in coastal sediments of

Alang–Sosiya ship scrapping yard, India. Marine Pollution

Bulletin 48, 1055–1059.

Tewari, A., Joshi, H.V., Trivedi, R.H., Sravankumar, V.G.,

Raghunathan, C., Khambhaty, Y., Kotiwar, O.S., Mandal,

S.K., 2001. Studies the effect of shipscrapping industry and

its associated waste on the biomass production and biodi-

versity of biota ‘‘in situ’’ condition at Alang. Marine

Pollution Bulletin 42, 462–469.

Tsukaijan, K., Young, D.R., 1978. Analytical Chemistry 50,

1250–1253.

Zanardi, E., Bicego, M.C., Miranda, L.B., Weber, R.R., 1999.

Distribution and origin of hydrocarbons in water and

sediment in Sao Sebastiao, SP, Brazil. Marine Pollution

Bulletin 38, 261–267.