the level and distribution of selected...

ORIGINAL PAPER

The level and distribution of selected organochlorinepesticides in sediments from River Chenab, Pakistan

Syed Ali-Musstjab-Akber-Shah Eqani •

Riffat Naseem Malik • Ashiq Mohammad

Received: 6 July 2009 / Accepted: 15 April 2010

� Springer Science+Business Media B.V. 2010

Abstract Organochlorine pesticides (OCPs), viz.

b-hexachlorocyclohexane (b-HCH), c-HCH, aldrin,

dieldrin, endrin, heptachlor, endosulfan-I, endosulfan-

II, heptachlor endoepoxide, heptachlor exoepoxide,

mirex, dicofol, o,p0-dichlorodiphenyltrichloroethane

(o,p0-DDT), p,p0-dichlorodiphenyltrichloroethane (p,p0-DDT), dichlorodiphenyldichloroethane (DDD), and

dichlorodiphenyltrichloroethylene (DDE) and 12 other

physicochemical parameters were measured in surface

sediments from River Chenab during two sampling

seasons (summer and winter, 2007) to evaluate spatial

and temporal trends of sediment pollution. Hierarchical

agglomerative cluster analysis identified three groups of

sites based on spatial similarities in physicochemical

parameters and OCP residual concentrations. Spatial

discriminant function analysis (DFA) segregated 14

parameters, viz. dicofol, endosulfan-I, heptachlor

endoepoxide, dieldrin, DDD, DDE, endosulfan-II,

o,p0-DDT, p,p0-DDT, pH, electrical conductivity (EC),

Cl-1, total P (%), and silt, which explained 96% of total

variance between spatial groups. c-HCH was the most

frequently detected (63%) pesticide, followed by DDD

(56%). The ratio of DDTs to their metabolites

indicated current input and anaerobic biodegradation.

Temporal DFA highlighted aldrin, heptachlor endo-

epoxide, Cl-1, total P, and EC as important variables

which caused variations between summer and winter.

DDTs were relatively more prevalent as compared to

other OCPs in the sediments samples during both

seasons. DDT metabolites were detected at greater

frequencies and concentrations in winter, whereas DDT

isomers were more prevalent in summer sediment

samples. Factor analysis identified agricultural and

industrial activities as major sources of sediment OCP

contamination. Concentrations of c-HCH, heptachlor

endoepoxide, dieldrin, and DDTs (isomers and metab-

olites) in all sediment samples were well above interim

sediment quality guidelines (ISQGs) and probable

effect limits (PEL) given by Canadian Sediment Quality

Guidelines (CSQGs).

Keywords Organochlorine pesticides �DDT � HCH � Dicofol � Multivariate analysis �Probable effect limit � River Chenab �Pakistan

Introduction

Pesticides such as organochlorines (OCPs) along with

industrial-based chemicals have been discharged

in large quantities into the environment for the

last 50 years, mainly to control agricultural pests,

S. Ali-Musstjab-Akber-ShahEqani � R. N. Malik (&)

Environmental Biology Laboratory, Department of Plant

Sciences, Quaid-i-Azam University, Islamabad 46000,

Pakistan

e-mail: [email protected]

A. Mohammad

Ecotoxicology Research Program, National Agricultural

Research Center, Park Road, Islamabad 45500, Pakistan

123

Environ Geochem Health

DOI 10.1007/s10653-010-9312-z

insect-borne diseases, and termites (Malik et al.

2010). Widespread use of these chemicals for agri-

cultural and nonagricultural purposes in past years

has resulted in contamination of water, sediment, and

biological organisms, and is of major concern at

local, regional, and global level (Doong et al. 2002a,

b; Kishimba et al. 2004; Ioannis et al. 2006; Sarkar

et al. 2008). OCPs are toxic to biological organisms,

threaten ecosystem integrity due to their high lipo-

philic properties (Vashchenko et al. 2005), tend to

adsorb on particulate matter due to low water

solubility (Nowell et al. 1999; Yang et al. 2005),

and are transferred to higher trophic levels through

food chains (Lopez et al. 2005; Zhou et al. 2006;

Malik and Zeb 2009). OCPs, like other contaminants

such as inorganic chemicals, make their way into

natural aquatic ecosystems via industrial and muni-

cipal effluents, agricultural and urban nonpoint run-

off, and atmospheric deposition (Qadir et al. 2008),

ultimately accumulating and settling in bottom sed-

iments, which act as a sink (Sarkar et al. 2008).

Residue levels of chlorinated pesticides have

declined significantly in the last two decades (Zhang

et al. 2003), but some OCPs such as DDTs, HCHs,

cyclodiene, etc. are still used in developing countries,

including Pakistan (Malik et al. 2010); although most

of them are banned, their low cost and illegal use

cannot be ignored (Tariq et al. 2007). DDT was banned

in 1994 in Pakistan; however, thousands of kilograms

of DDTs along with other obsolete persistent organic

pollutants are still found in chemical warehouses (Jan

et al. 2008). According to Malik et al. (2010) and Tariq

et al. (2007), large stockpiles of outdated pesticides

exist, estimated at 3,805 tonnes in Punjab, 2,016 ton-

nes in Sindh, 179 tonnes in Khyber Pukhtoon Khawa

Province, 128 tonnes in Baluchistan, and an obsolete

stock of 178 tonnes in the Federal Department of Plant

Protection, from where these toxic chemicals find their

way into various environmental compartments via

surface runoff and possibly contamination of ground-

water. On the other hand, illegal use of these polluting

chemicals cannot be neglected due to poor enforce-

ment of environmental laws. Of the pesticides, 74% are

used as insecticides, 14% as herbicides, 9% as

fungicides, 2% as acaricides, and 1% as fumigants.

Of all pesticides used in Pakistan,[65% are applied on

cotton, while others are used on crops such as rice,

sugarcane, maize, fruits, vegetable, and tobacco (Eco-

nomic Survey of Pakistan 2005–2006).

To our knowledge, few studies have assessed OCP

residues in various environmental compartments

from Pakistan (Jabbar et al. 1993; Tehseen et al.

1994; Munshi et al. 2004; Saqib et al. 2005; Tariq

et al. 2007; Malik et al. 2010). However, there is no

information available regarding OCP concentrations

in sediments of River Chenab, which is one of the

largest rivers of the Indus Basin. The present study

aimed to determine the contamination level of OCPs

and to assess their spatial and temporal variation in

sediments of River Chenab, Pakistan.

Materials and methods

Sediment sample collection

A total of 16 sites were marked for sampling in

selected river stretches (Fig. 1), and surface sedi-

ments were collected in summer (May 24–30) and

winter (November 3–10) during 2007. Site S1 was

selected on River Jhelum before it meets River

Chenab, and one site (S2) was selected on

River Chenab before River Jhelum meets with River

Chenab. Site S3 was located on Trimun Headworks,

which provides water for irrigation of Punjab Prov-

ince. Sites S4, S5, S6, and S7 were located before the

River Ravi discharge into River Chenab. Site S8 was

located on River Ravi, 10 km upstream of the joining

point with River Chenab. Five sites (S9, S10, S11,

S12, and S13) were located in the cotton belt of

Khanewal District, where pesticides are used in large

quantities for agricultural purposes. Site S14 was

located after the joining of Suraj Maini drain line,

which brings municipal and industrial wastewater

from Multan City. Site S15 was located after the

joining of Indus link canal with River Chenab, near

Muzaffarghar, and site S16 was located at Shershah

Bridge. Each site was marked and located with the

help of global position system (GPS). Composite

surface sediment sample (0–5 cm) consisting of five

subsamples was collected from each site within the

vicinity of 100 m using a stainless-steel ladle, mixed

well, and kept in a glass bowl for immediate transfer

to the laboratory for storage at -20�C in refrigerator.

Samples were air-dried, sieved, and placed in airtight

glass bottles until extraction. All equipment used for

sampling, transportation, and preparation was free

from OCP contamination.


123

Laboratory analyses of physicochemical

properties of sediments

Parameters such as pH, EC, and total dissolved solids

(TDS) of each sediment sample were determined by

using portable combined meter (Milwaukee, model

SM802). Organic matter (OM) was determined by

Tyurin’s method (wet oxidation method) as described

by Nikolskii (1963). The proportions of sand, silt, and

clay were calculated using Bouycous hydrometer,

and sediment textural classes were determined on the

basis of relative proportion of soil particles using

textural triangle (Robert and Frederick 1995). Total

phosphorus (P) and total sulfur (S) percentages were

determined by the method described by Allen et al.

(1974), and nitrates (NO3–N) were determined by the

procedure described by Metson (1956). Total P, total S,

and NO3–N were finally estimated using spectropho-

tometer (Agilent 8453). Alkalinity and chloride (Cl-1)

were determined by titration method (AOAC 1995).

Extraction and clean-up of OCPs

Selected OCPs, viz. b-HCH, c-HCH (lindane), hepta-

chlor, heptachlor exoepoxide, heptachlor endoepoxide,

aldrin, dicofol, endosulfan-II, endrin, endosulfan-II,

dieldrin, DDD, DDE, o,p0-DDT, p,p0-DDT, and mirex,

were extracted from each sediment sample using

Automated Soxtec System (HT2 Tecator with 1,045

extraction unit and 1,046 service unit) using EPA

method no. 3541. Each sediment sample (5 g) was

premixed with an equal amount of anhydrous sodium

sulfate to form a free-flowing mixture, placed in a pre-

extracted cellulose extraction thimble, and extracted

with 60 ml n-hexane:dichloromethane 1:1 (v/v).

Extracts were concentrated, solvent-exchanged to

hexane, and purified on an 8-mm-i.d. alumina/silica

column packed, from bottom to top, with neutral

alumina (6 cm, 3% deactivated), neutral silica gel

(10 cm, 3% deactivated), 50% (w/w) sulfuric acid

silica (10 cm), and anhydrous sodium sulfate. Alu-

mina, silica gel, and anhydrous sodium sulfate were

pre-extracted for 48 h with dichloromethane (DCM).

Extraction thimbles were also pre-extracted with DCM

for 4 hours. The column was prewashed with

50 ml dichloromethane/hexane (1:1) and eluted with

50 ml dichloromethane/hexane (1:1) to yield OCPs

fraction. Organic fraction was solvent-exchanged to

ethyl acetate and concentrated to 0.5-ml gas chroma-

tography (GC) vials under a gentle nitrogen stream.

Fig. 1 Map of study area

showing the location of

sampling sites


123

Gas chromatographic analysis of OCP

Residual concentration of selected OCPs in extracted

samples was determined using gas chromatograph

(Perkin Elmer autosystem) equipped with an electron

capture detector (ECD-Ni63), fused silica capillary

column (P.E.No. N931-2414, 25 m length 9 0.32

inner diameter 9 0.5 lm film thickness, Perkin

Elmer, USA), and Turbochrom data analysis software.

During analysis, the injector (splitless mode) and

detector temperature were kept at 225�C and 300�C,

respectively. Initial oven temperature was set at

100�C, which was held for 5 min and then ramped

to 160�C at a rate of 15�C/min and to 190�C at a rate of

2�C/min. The backup pressure of carrier gas (N2) was

kept at 12 ml/min. The carrier flow rate was kept at

10 ml/min, whereas the pressure of the make-up gas

(N2) was 32 ml/min. Standard/sample measuring 1 ll

was injected using 10-ll Hamilton syringe by solvent

flush injection technique (Malik et al. 2010). The

results were confirmed by GC-ECD with Elite-CLP

fused-silica capillary column (P.E. no. N931-6664,

30 m length 9 0.32 mm inner diameter 9 0.5 lm

film thicknesses; Perkin Elmer, USA). The Elite-

CLP column was maintained at 110�C, which ramped

to 160�C at a rate of 30�C, programmed to 210�C at a

rate of 2�C, eventually temperature increased to 230�C

at a rate of 10�C and held for 10 min.

Quality control and assurance

All analytical methods were under accreditation, and

strict quality-control criteria were applied. Mixture of

standard solutions was injected into GC followed by

sample injection. Analytes of interest were identify on

the basis of their respective retention times matched to

the standards and quantified on the basis of peak areas,

which were used to calculate the concentration of

pesticide residues. For every set of ten samples a

procedural/laboratory blank and spiked sample

consisting of all reagents were run to check for

interference and cross-contamination. Instrument

performance was monitored using quality control

standards after every six samples analyzed on the

instrument. Method performance was assessed by

evaluating quality parameters such as recovery,

repeatability, correlation coefficients, and limits of

detections (LODs) and quantification (LOQs). Repeat-

ability and recovery were assessed by analyzing

uncontaminated sediment samples (n = 6) spiked at

50, 100, and 200 ng g-1 for each of the studied OCPs.

Mean recovery of OCPs ranged from 64% to 112%

with repeatability (relative standard deviation, RSD)

from 2% to 13%, while the correlation coefficient (r)

ranged from 0.993 to 0.999 (Table 1). LODs and

LOQs were calculated on the basis of signal-to-noise

ratio (S/N) of 3 and 10, respectively.

Chemical sources

Standard solutions of selected OCPs were purchased

from Dr. Ehrenstorfer GmbH (Ausburg, Germany).

Stock solution of pesticides were prepared by dissolving

precisely weighed amount of pesticides in n-hexane

containing 10–15% acetone, while working standard

solutions were made by diluting the stock standards. All

solvents and chemicals were of high-performance liquid

chromatography (HPLC) grade (Merck, Germany).

Extraction thimbles (31 9 91 mm) were purchased

from Macherey–Nagel (GmbH, Germany) and anhy-

drous sodium sulfate from Merck (Germany). All

sorbents, glassware, and GC vials were backed at

450�C before use. All sorbents and GC vials were stored

in sealed containers to avoid any possible contami-

nation.

Statistical analyses

Analytical results were compiled to form a multi-

elemental database using Excel software. Hierarchical

cluster analyses (HACA) was performed using Euclid-

ean distance as a distance matrix and unweighted pair

group method using arithmetic averages (UPGMA) as

a linkage method, to extract information regarding

spatial similarities/dissimilarities between sampling

sites based on 12 physicochemical parameters and

selected OCPs residual level.

Factor analysis based on principal component

analysis (FA/PCA) was employed for source identi-

fication of OCPs. Temporal FA/PCA was applied for

two sampling seasons, i.e., summer and winter,

whereas spatial FA/PCA was applied on the normal-

ized data set (25 variables) separately for three

groups of sites (region 1, region 2, and region 3) as

identified by HACA.

Discriminant function analysis (DFA) was applied

to study spatial and temporal trends of OCPs and

physicochemical parameters. Temporal DFA was


123

carried out on raw data, which was divided into two

seasons, i.e., summer and winter, while spatial DFA

was performed with the same 25 variables and three

groups of sites (region-1, region-2 and region-3). The

statistical software package Statistica (version 5.5)

for Windows was used for all statistical analyses.

Results and discussion

Physicochemical properties and OCPs

concentrations of surface sediments

Physicochemical parameters and OCPs concentrations

of sediments collected from River Chenab during

summer and winter seasons are presented in Table 2.

Sediments were slightly acidic to moderately alkaline

in winter, with pH varying from 6.6 to 8.9, while in

summer most sediments were moderately alkaline.

Sandy, loamy sand, and sandy loam were the dominant

textural classes. Higher values of EC, TDS, and

organic matter were recorded in winter, in contrast to

total P (%) and total S (%), which were measured

highest in summer. Greater alkalinity and concentra-

tion of Cl-1 and NO3–N were measured in winter. This

may be due to deposition of sediments, as water flow

was relatively low during winter. Clay content and OM

showed correlation with c-HCH (r = 0.65), dicofol

(r = 0.58), DDD (r = 0.72), and DDE (r = 0.61),

indicating strong adsorption with sediment particles.

DDTs and HCHs were frequently detected OCPs,

followed by dicofol and heptachlor (Table 2). Greater

concentrations of HCHs and DDTs were detected in

summer season; however, heptachlor was more fre-

quent (62%), followed by p,p0-DDT (50%), DDD

(43%), b-HCH (43%), and c-HCH (43%). Dicofol,

endosulfan-II, and o,p0-DDT were detected in few

samples. Aldrin and heptachlor endoepoxide were not

detected in any sediment samples. During winter, c-

HCH was the most frequently detected compound

(81%), followed by DDD (68%), o,p0-DDT (43%),

dicofol (43%), heptachlor (38%), DDE (32%), and b-

HCH (31%). Concentration of total OCPs was greater

in winter season, which may be due to weak desorption

of OCPs with sediment at lower temperature (Zhou

et al. 2006). The residual concentration of OCPs

detected in the current study was considerably high

compared with those measured in sediment from Da-

han and Erh-jen Rivers in Taiwan (Doong et al. 2002a,

b), from Arabian Sea (Sarkar et al. 1997), and from

Bay of Bengal, India (Babu et al. 2005).

Table 1 Percentage mean recovery (n = 6) with RSD (repeatability) of selected organochlorine pesticides at three spiking level

along with correlation coefficient (r), limit of detection (LOD), and limit of quantification (LOQ) of the optimized method

Pesticide Concentration (ng g-1) Correlation

coefficient, rLOD

(ng g-1)

LOQ

(ng g-1)50 100 200

b-HCH 87.20 ± 3.75 87.20 ± 1.88 77.40 ± 4.97 0.999 6 11

c-HCH 102.60 ± 3.34 99.20 ± 3.13 97.20 ± 4.50 0.998 2 3

Heptachlor 100.20 ± 4.90 92.20 ± 3.79 98.80 ± 5.15 0.999 7 14

Aldrin 82.60 ± 9.86 97.70 ± 9.10 100.20 ± 11.4 0.989 6 12

Dicofol 99.60 ± 4.41 104.50 ± 8.99 98.30 ± 11.87 0.998 6 12

Heptachlor exoepoxide 77.10 ± 2.29 110.90 ± 8.11 78.60 ± 13.47 0.998 8 15

Heptachlor endoepoxide 82.60 ± 9.32 88.00 ± 8.23 98.40 ± 11.19 0.998 7 13

Endosulfan-1 64.20 ± 6.17 64.80 ± 3.99 67.60 ± 9.67 0.997 5 9

Dieldrin 106.10 ± 2.55 106.40 ± 9.35 109.90 ± 11.2 0.999 6 12

DDD 106.40 ± 5.50 94.80 ± 8.08 112.60 ± 5.38 0.999 6 12

DDE 101.40 ± 3.62 104.00 ± 7.50 111.90 ± 8.30 0.993 5 10

Endrin 109.80 ± 4.01 105.50 ± 9.01 100.80 ± 9.50 0.998 5 9

Endosulfan-II 67.20 ± 14.51 71.90 ± 7.40 70.80 ± 11.07 0.999 2 3

o,p0-DDT 80.20 ± 5.37 76.50 ± 12.96 84.00 ± 9.70 0.995 3 6

p,p0-DDT 99.40 ± 6.35 102.40 ± 9.01 93.70 ± 10.40 0.997 7 14

Mirex 73.50 ± 9.02 105.00 ± 4.48 97.80 ± 8.37 0.993 5 10


123

The mean concentrations ofP

HCH measured in

the current study (4.7 and 5.7 ng g-1 in winter and

summer) were within the range detected in sediments

of the Kizilirmak River from Turkey (Bakan and

Ariman 2004) and of the Wu-Shi River from Taiwan

(Doong et al. 2002a). However, measured concentra-

tions were far greater than those reported from Pearl

River Estuary, PRC (Hong et al. 1999) and from

Xiamen Harbor, PRC (Hong et al. 1995), while Zhou

et al. (2006) measured far higher concentration ofP

HCH in river sediments from China as compared

with those recorded in this study. The concentration

of heptachlor detected in the current study suggested

continuing use for insect control and in seed and

wood preservation, and its presence can also be

related to surface runoff from agriculture cropland

and urban areas, municipal and industrial effluents,

and atmospheric deposition (Zhou et al. 2006). The

high detected concentration of dicofol could be due to

its use for protecting sugarcane, cotton, and fruit trees

in areas adjoining River Chenab. Dieldrin, aldrin,

endosulfan-I, and endosulfan-II were found at sam-

pling sites near cotton belt areas, but in small

quantities.

DDTs were more prevalent than HCHs and other

OCPs in sediments in both seasons. During winter,

Table 2 Descriptive statistics of OCP concentrations and physiochemical properties in sediment samples (n = 16) collected from

River Chenab, Pakistan during summer and winter season, 2007

Parameters Summer season Winter season CSQGs

N (detected) Min–Max Mean SD N (detected) Min–Max Mean SD ISQG

(ng g-1)

PEL

(ng g-1)

b-HCH (ng g-1) 7 6.20–11.89 9.13 2.12 5 5.78–8.23 7.01 1.05 – –

c-HCH (ng g-1) 7 1.77–7.59 3.84 2.25 13 1.73–4.69 3.06 0.89 0.94 1.38

Heptachlor (ng g-1) 10 14.11–36.11 21 7.31 6 19.50–33.66 27.6 6.47 – –

Aldrin (ng g-1) ND – – – 4 8.96–14.25 11 2.45 – –

Dicofol (ng g-1) 4 24.26–39.22 30.6 6.53 7 11.23–73.23 31.5 20.7 – –

Endosulfan-I (ng g-1) 2 8.25–11.32 9.79 2.17 ND – – – – –

Heptachlor

endoepoxide

(ng g-1)

ND – – – 3 7.95–13.25 10.9 2.69 0.6 2.74

Dieldrin (ng g-1) 2 14.35–18.26 16.3 2.76 4 19.25–32.59 25.2 5.52 2.58 6.67

DDD (ng g-1) 7 5.98–22.56 13.2 7.28 11 6.06–14.25 8.46 2.58 3.54 8.51

DDE (ng g-1) 3 9.17–16.95 13.2 3.9 5 9.42–22.94 16.3 4.96 1.42 6.75

Endosulfan-II (ng g-1) 6 1.93–3.67 2.87 0.71 4 2.14–7.19 5.14 2.41 – –

o,p0-DDT (ng g-1) 4 4.23–12.25 7.58 3.5 4 6.13–11.34 8.04 2.28 1.19 4.77

p,p0-DDT (ng g-1) 8 7.64–53.60 17.9 14.99 7 7.82–21.56 12.4 4.85

pH 7.7–9 8.65 0.32 6.6–8.9 7.88 0.79 – –

EC (lS cm-1) 0–190 33.1 45.71 0–210 90.62 61.7 – –

TDS (ppm) 0–120 20.6 29.31 0–140 57.5 39.4 – –

Alkalinity (mg g-1) 0.16–0.54 0.34 0.11 0.6–1.33 0.95 0.19 – –

Cl-1 (mg g-1) 0.16–0.55 0.24 0.08 0.58–0.83 0.65 0.06 – –

Total P (%) 0.03–0.07 0.04 0.008 0.02–0.06 0.03 0.01 – –

NO3–N (mg g-1) 0.042–0.49 0.15 0.1 0.118–0.61 0.23 0.12 – –

Total S (%) 0.0003–0.05 0 0.01 0.001–0.004 0.001 0 – –

OM (%) 0.06–1.37 0.49 0.4 0.29–4.43 2.21 1.4 – –

Clay (%) 0.8–20.05 7.63 5.63 0–16.6 6.85 5.43 – –

Silt (%) 0.2–21.3 7.75 8.68 0.1–17.7 5.43 6.14 – –

Sand (%) 67–98.9 85 11.81 71.2–100 88.6 10.1 – –


123

DDT metabolites were more prevalent, while in

summer DDT isomers were detected more frequently.

Greater concentration of DDTs can be linked to its

chronological use as well as excessive use of dicofol

as a pesticide. DDTs are used in the production of

dicofol as by products (Minh et al. 2007). The high

residual level of dicofol in sediments is related to its

use in agricultural activities as a cheaper pesticide

and it can also be identified as an additional source of

o,p0-DDT (Zhang et al. 2003; Leung et al. 2005; Wei

et al. 2008). Biodegradation of DDTs into its metab-

olites in riverine ecosystem cannot be neglected,

which may be another reason for the high concen-

tration of its metabolites in river sediments (Zhang

et al. 1999; Peris et al. 2005). Mean concentration ofP

DDTs detected in the current study during summer

(19.1 ng g-1) and winter (18.2 ng g-1) were rela-

tively lower than those measured in sediment from

Chinese rivers such as Haihe (15.9 ng g-1), Dagu

drainage (35.9 ng g-1), and Qiatang (21.62 ng g-1)

(Yang et al. 2005; Zhou et al. 2006), and Ebro River

(51.8 ng g-1) from Spain (Fernandez et al. 1998).

However, measured concentrations were greater than

those found in sediment of Minjiang River from

China (Zhang et al. 2003), Pearl River Estuary, PRC

(Hong et al. 1999), and Wu-Shi, Da-han, and Erh-jen

Rivers from Taiwan (Doong et al. 2002a, b).

Technical-grade DDT contains 75% p,p0-DDT,

15% o,p0-DDT, 5% p,p0-DDE, and\5% others (Hites

and Day 1992; Yang et al. 2005). DDT can be

biodegraded into DDD via reductive dechlorination

under anaerobic conditions and to DDE under aerobic

conditions through dehydrochlorination, an oxidative

process (Kalantzi et al. 2001; Luo et al. 2004).

Among metabolites, DDD was detected in greater

concentration, showing degradation of DDT during

both seasons, i.e., summer and winter. Among the

isomers, p,p0-DDT was the most frequently detected

compound in both seasons, indicating new input of

DDTs which have not yet been degraded. New inputs

of DDT can maintained high compositional percent-

age of DDT (Sarkar et al. 2008), while the DDT

proportion gradually reduces when there is no more

new input of DDT, accompanied by a gradual

increase in the concentration of metabolites (Doong

et al. 2002a). Figure 2 shows the compositional

percentage of DDTs in sediments during summer

and winter seasons. In summer season, p,p0-DDT in

sediment samples accounted for 46% of total DDTs,

followed by DDD (30%), DDE (12%), and o,p0-DDT

(9%). During winter season, p,p0-DDT accounted for

about 30% of total DDTs, while DDD, DDE, and o,p0-DDT accounted for 31%, 27%, and 10%, respectively,

indicating recent input of DDTs, aged DDT breakdown

products, as well as anaerobic conditions in River

Chenab.

Various indicative ratios such as (DDE ? DDD)/P

DDT, p,p0-DDT/P

DDT, and DDD/DDE are widely

used to assess decomposition of the parent compound

and recent DDT input (Phuong et al. 1998; Doong

et al. 2002b; Sarkar et al. 2008). In the current study,

(DDE ? DDD)/P

DDT was [0.5 during both sea-

sons, suggesting that sediments undergo a long-term

weathering process (Hong et al. 1999; Yang et al.

2005). In addition, p,p0-DDT/P

DDT ratios exceeded

0.5 at some sampling stations associated with recent

input of p,p0-DDT in both seasons. The DDD/DDE

ratio also exceeded unity for most sediment samples,

highlighting the high proportion of DDD in the

environment and indicating anaerobic environmental

conditions (Bossi et al. 1992) in River Chenab,

Pakistan.

Grouping of sites using hierarchical cluster

analysis (HACA) and identification of significant

parameters using discriminant function analysis

(DFA)

HACA grouped sampling sites into three regions based

on physicochemical properties and OCPs residue level;

however, site S1 located on Jhelum upstream was

identified as an outlier (Fig. 3). Region 1 consisted of

sites S2, S8, and S10, which were characterized by

relatively higher amounts of OCPs; EC, TDS, pH, and

Fig. 2 Composition of DDTs in sediments collected from

River Chenab, Pakistan during two sampling seasons


123

nutrients also showed higher concentrations. Site S8

was located at River Ravi, about 10 km above the

joining point of Rivers Ravi and Chenab. River Ravi

receives industrial and municipal waste from Lahore

and Qasoor Cities and OCPs from adjoining agricul-

tural fields. Site S2 receives toxic industrial waste from

Faisalabad City and agricultural runoff from adjoining

cotton cropland areas. Relatively high concentration of

heptachlor was found in the sediment of site S2,

indicating high usage of pesticide in upstream of River

Chenab. Cyclodienes, i.e., aldrin, dieldrin, endosulfan-

I, and endosulfan-II, were detected in considerably

higher concentration at sites S8 and S10, located in

cotton belt, indicating their usage in large quantities in

cotton belt as compared with rice- and sugarcane-

growing areas. Region 2 comprised five sites (S3, S4,

S6, S9, and S13) with the least OCPs contamination.

Sites viz., S3, S4, and S6 were located after the joining

of the River Jhelum to the River Chenab, which may

result in dilution of water thus improving the water

quality. The sediments at this site were also were

dominated by sand. Region 3 consisted of seven sites

(S5, S7, S11, S12, S14, S15, and S16). These sites were

located in cotton-growing areas, characterized by

severely eroded banks which incessantly slashed the

surrounded agricultural land into river. HCHs and

DDTs were measured in considerably higher concen-

tration in this region.

Temporal and spatial variation of OCPs in River

Chenab were further evaluated by discriminant func-

tion analysis (DFA). Forward and backward stepwise

spatial DFA modes generated 20 and 14 discriminant

variables with 100% and 96% classification accura-

cies. Backward stepwise DFA highlighted dicofol,

endosulfan-I, heptachlor endoepoxide, dieldrin, DDD,

DDE, endosulfan-II, o,p0-DDT, p,p0-DDT, pH, EC,

Cl-1, total P, and silt as significant parameters that

highlighted variations between the three spatial

regions defined by HACA (Fig. 4). Spatial DFA

discriminated parameters that showed higher concen-

tration in sites classified to region 1. These sites (S2,

S8, and S10) receive contaminant load mainly from

industrial, urban, and agricultural runoff. Sediment

samples collected from sites of region 2 showed high

residual level of endosulfan-I, endosulfan-II, hepta-

chlor endoepoxide, and DDD. Greater concentration of

endosulfan-I, endosulfan-II, and heptachlor endoep-

oxide reflected their widespread use for agricultural

activities. Greater residual level of DDD indicated

anaerobic degradation of DDT. Dicofol, endosulfan-I,

dieldrin, DDE, o,p0-DDT, p,p0-DDT, pH, EC, Cl-1,

total P, and silt showed higher values in sediments

collected from sites which comprised region 3. These

sites were situated in cotton belt, which receives

pesticide load from adjoining cropland land due to

severely eroded banks and agricultural runoff. River

Unweighted pair-group averageEuclidean distances

(Dlin

k/D

max

)*10

0

0

20

40

60

80

100

120

S-2 S-11

S-7 S-12

S-15 S-14

S-16 S-5

S-13 S-6

S-9 S-4

S-3 S-8

S-10 S-1

Fig. 3 Hierarchical dendrogram of sampling sites obtained using UPMGA as linkage method and Euclidean distance matrix


123

Ravi, which joins River Chenab, brings effluent from

major industrial cities such as Qasoor, Lahore, and

Gujarat and also contributed to deterioration of quality

of sediments of region 3. The results of HACA also

supported the trends identified by spatial DFA.

Standard, forward stepwise, and backward stepwise

temporal analysis generated 25, 16, and 5 discriminant

variables, respectively, giving CMs (Classification

Matrices) with 99.7% correct assignation. Temporal

DFA showed aldrin, heptachlor endoepoxide, Cl-1,

phosphorus, and EC to be the most important variables

discriminating between summer and winter seasons

(Fig. 5). The distribution and variability of OCPs are

largely dependent on the physicochemical properties

of the sediments, environmental behavior of contam-

inant, and geology of the area (Leonard 1990; Glynn

et al. 1995; Brasher and Wolf 2004). DFA proved to be

a valuable tool for determining the patterns of spatial

and temporal trends and highlighted residual concen-

trations of dicofol, endosulfan-I, heptachlor endoep-

oxide, dieldrin, DDD, DDE, endosulfan-II, o,p0-DDT,

and p,p0-DDT as important variables which require

more attention and future monitoring. Furthermore, all

sites of region 1 were more polluted as compared with

other sites and should be monitored regularly.

Source identification using FA/PCA

Temporal FA/PCA extracted seven varimax factors

(VFs) for each season with eigenvalue[1, explaining

84.77% and 87.44% of total variance for both winter

and summer, respectively. For summer season, of

seven VFs, VF1 explained 40.10% of total variance,

showing strong positive correlation with EC, TDS,

Cl-1, and NO3–N and sources mainly related with

agricultural runoff from adjoining fields and from the

natural mineral composition of river sediments. The

mineral composition of River Chenab sediments

mainly comprises thick deposits of calcareous, fine

and wind-laid sands, and silt originating from sand-

stones and shale rocks of the catchment area, espe-

cially Salt Range. This may have resulted in high

content of dissolved salts. Source of NO3–N is mainly

correlated with excessive use of nitrogenous fertiliz-

ers in agricultural fields. Nitrogenous fertilizers such

as urea are used in large quantities in Pakistan and

undergo extracellular enzymatic decomposition to

form ammonium compounds, which are either

absorbed by plant roots or converted to nitrates, get

absorbed or are lost by leaching, or are released to the

atmosphere to become part of the nitrogen cycle

(Singh et al. 1995). VF2 and VF3 explained 12.09%

and 9.22% of total variance, with positive correlation

with heptachlor, endosulfan-I, c-HCH, and DDD,

while total P showed strong negative correlation,

indicating input related to agricultural activities in the

catchment, and industrial and municipal input. VF3

represented the anaerobic degradation of DDT into

DDD while c-HCH residues contamination in river

sediments could have resulted due to partial sedimen-

tation from surrounding soils however, negative

loading of total P showed indicated that it is not

associated with parent rock material. VF4 explained

8.24% of total variation, strongly correlated with

dieldrin and organic matter, while VF5 explained

7.34% of total variance, with positive loading on silt

and negative loading on o,p0-DDT and sand. VF6 and

VF7 explained 5.28% and 4.64% of total variance,

with positive loading on p,p0-DDT and total S and

sources of these two parameters mainly related with

human activities in catchment of study area.

For winter season, of seven VFs, VF1 explained

25.19% of total variance, with significant positive

loading on pH, EC, TDS, clay, and silt and strong

negative loading on sand, indicating their source

related with parent rock material. VF2 explained

16.78% of total variance, with strong positive loading

on aldrin and o,p0-DDT but negative loading on total P

and organic matter. This factor can be interpreted as

indicating that aldrin and o,p0-DDT contamination are

due to excessive use of these pesticides in surrounding

agricultural fields, and detection in most samples

during winter may be due to weak desorption at low

temperature, while phosphorus contents decreased due

to low organic matter contents. VF3 explained 12.26%

of total variance, with positive loading on c-HCH and

negative loading on heptachlor and total S. This factor

indicates that c-HCH residues associated with sedi-

ment due to wet deposition and heptachlor and sulfur

entered the riverine ecosystem through municipal

sewage. VF4 explained 10.52% of total variance, with

positive loading on dicofol, heptachlor endoepoxide,

and NO3–N. VF5, V6 and VF7 explained\10% of total

variance and these factors highlighted the dominance

of b-HCH (VF5), Cl-1 (VF6) and endosulfan-11

(VF7). It suggested that b-HCH, Cl-1 and endosul-

fan-11 were found frequently during winter and mainly

originated from surface runoff from agricultural fields.


123

Dic

ofol

(ng

g-1)

-5

5

15

25

35

45

Region-1 Region-2 Region-3

Min-Max

25%-75%

Median value

EN

DO

-1 (

ngg-

1)

-2

0

2

4

6

8

10

12

14


Hep

tach

lor

endo

epox

ide

(ngg

-1)

-2

0

2

4

6

8

10

12

14

16


Die

ldrin

(ng

g-1)

-5

0

5

10

15

20

25

30

35


EN

DO

-II (

ngg-

1)

-1

0

1

2

3

4

5

6

7

8


DD

D (

ngg-

1)

-2

2

6

10

14

18

22

26


DD

E (

ngg-

1)

-2

2

6

10

14

18

22

26


a

c

e

g

f

d

b

Fig. 4 a–n Spatial variations identified by discriminant function analysis: dicofol, endosulfan-I, heptachlor endoepoxide, dieldrin,

DDD, DDE, endosulfan-II, o,p0-DDT, p,p0-DDT, pH, EC, chloride, phosphorus, and silt


123

o,p'

-DD

T (

ngg-

1)

-2

0

2

4

6

8

10

12

14


p,p'

-DD

T (

ngg-

1)

-5

5

15

25

35

45

55

65

Region-1 Region-2

pH

6.4

6.8

7.2

7.6

8.0

8.4

8.8

9.2


EC

(µS

/cm

)

-20

20

60

100

140

180

220

260


Chl

orid

es (

ngg-

1)

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9


P (

%)

-5

0

5

10

15

20

25

30

35


Silt

(%

)

-2

2

6

10

14

18

22

26


Region-3

h i

j k

lm

n

Fig. 4 continued


123

Spatial FA/PCA extracted five VFs for region 1

and six VFs for regions 2 and 3 with eigenvalue [1,

explaining 100%, 90.67%, and 84.80% of total

variance. For region 1, VF1 explained 34.94% of

total variance, in which aldrin, dieldrin, o,p0-DDT,

and alkalinity had strong positive correlation, while

heptachlor and total P showed negative correlation.

This factor indicated that high concentrations of

dieldrin, aldrin, and o,p0-DDT in region 1 were due to

anthropogenic activities (agricultural and industrial),

whereas source of alkalinity can be linked with

natural as well as anthropogenic processes in the

catchment, while the negative correlation of hepta-

chlor and phosphorus suggested the source of these

two parameters from agricultural activities. Hepta-

chlor is used in agricultural fields to protect citrus

trees and crops from insects. Phosphorous contents

may be correlated with use of fertilizers containing

high phosphorus contents. VF2 explained 30.57% of

total variance, and EC, TDS, Cl-1, total S, organic

matter, and clay showed strong positive loading; their

sources were mainly related with natural mineral

Ald

rin (

ngg-

1)

-2

0

2

4

6

8

10

12

14

16

WinterSummer

Min-Max

25%-75%

Median value

Hep

tach

lor

endo

epox

ide

(ngg

-1)

-2

0

2

4

6

8

10

12

14

16

EC

(µS

/cm

)

-20

20

60

100

140

180

220

260

Chl

orid

es (

ngg-

1)

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

P (

%)

-5

0

5

10

15

20

25

30

35

WinterSummer

WinterSummer

WinterSummer

WinterSummer

a

c

b

e

d

Fig. 5 a–e Temporal variations highlighted by discriminant function analysis: aldrin, heptachlor epoxide, EC, chloride, and P (%)


123

composition. VF3 explained 18.41% of total vari-

ance, showing strong positive loading on c-HCH,

dicofol, endosulfan-II, and nitrates, while pH showed

negative loading. This factor indicated surface runoff

from agricultural fields as a main contributing factor.

VF4 explained 10.19% of total variance and showed

positive loading on p,p0-DDT and negative loading on

endosulfan-I and silt. This factor represents the high

p,p0-DDT residue level from agricultural source.

For region 2, of six varimax factors (VFs), VF1

explained 27.15% of total variance and showed

positive loading on EC, TDS, alkalinity, Cl-1, and

organic matter. VF2 explained 17.15% of total

variance, positively related to dicofol and heptachlor

endoepoxide, indicating that their source was mainly

due to agricultural activities in sites comprising

region 2, where pesticides are being used to protect

crops from insects and various diseases. VF3


positive correlation with DDE and clay, indicating

adsorption capacity of clay with DDE. VF4 explained

13.88% of total variance, positively loaded on sand

but negatively loaded on endosulfan-I and silt. VF5


negative loading on dieldrin and p,p0-DDT. VF6

explained 6.57% of total variance, showing negative

loading on aldrin. Most of the factors highlighted the

role of agricultural, industrial, and urban activities in

OCP contamination.

For region 3, out of six variables, VF1 explained

26.34% of total variance and showed positive loading

on c-HCH and DDE. This factor represented the high

residue level of c-HCH and DDE from agricultural

fields. VF2 explained 24.59% of total variance,

showing positive loading on alkalinity, organic

matter, and Cl-1 and negative loading on pH. This

factor showed a decline of pH value due to high

organic matter content, which may affect many

reactions in the sediments (Cirmo et al. 2000). Acidic

conditions accelerated the fluxes of acidic anions

(e.g., SO2-4 and NO-3). On the other hand, increased

hydrogen ion concentration also associated with clay

particles, which resulted in chemical solution of

minerals. Hydrogen ions also removed Al3? ions held

within the structure of soil minerals and accelerated

formation of organic complexes (Brady and Weil

1996), while the source of alkalinity and Cl-1 was

from naturally occurring minerals in the river system.

VF3 explained 12.71% of total variance and showed

positive loading on total S, indicating its sources

related to municipal effluents. VF4 explained 8.31%

of total variance and showed positive loading on

dicofol, EC, and TDS. This factor shows that dicofol

concentration increases with EC and TDS. VF5 and

VF6 explained [5% of total variance and extracted

total P and p,p0-DDT as important variables, respec-

tively. VF5 and VF6 can be interpreted as indicating

that the source of phosphorus and p,p0-DDT were

mainly from agricultural activities.

Ecotoxicological concerns

OCP concentrations in assessed sediment samples

were compared with sediment quality guidelines for

the protection of aquatic life (CCME 1999) for

assessment of relative sediment quality and potential

risk to aquatic life in River Chenab. Concentration of

c-HCH in the detected samples ranged from 1.77 to

7.59 ng g-1 during both seasons, which exceeded

both ISQGs (0.94 ng g-1) and probable effect limit

(PEL) values (1.38 ng g-1). Concentrations of diel-

drin (14.35–32.59 ng g-1) and heptachlor epoxide

(7.95–13.25 ng g-1) in winter season were also

found to be well above their ISQGs and PEL values.

Concentrations of DDTs (o,p0-DDT and p,p0-DDT)

ranged from 5.63 to 53.60 ng g-1, which were far

greater than the ISQGs (1.19 ng g-1) and PELs

(4.77 ng g-1). Similarly, residual levels of DDD and

DDE also exceeded the ISQGs and PEL values,

indicating severe contamination of DDTs and their

metabolites. This highlights that River Chenab sed-

iments pose a serious threat to aquatic life, and urgent

restoration and management is warranted to safe-

guard the aquatic system.

Conclusions

The present study provides the first systematic data

on the distribution of OCPs in sediments of River

Chenab, Pakistan. The results highlight that OCPs

contamination should be considered as an important

environmental issue due to their excessive use in

agriculture and industrial sector. DDTs, HCHs,

heptachlor, and dicofol were the dominant OCPs

found in River Chenab sediments. High concentration

of p,p0-DDT in sediments in both seasons reflected

recent use of the parent DDT compound, while


123

presence of DDD in most sediment samples sug-

gested its contamination mainly from agricultural

soils aged under anaerobic environmental conditions.

HACA grouped sampling sites into three spatial

groups with varying proportion of OCPs contamina-

tion, whereas FA/PCA highlighted sources of OCPs

mainly related to agricultural and industrial activities.

DFA identified 6 variables (aldrin, heptachlor endo-

epoxide, Cl-1, total P, and EC) and 14 parameters

(dicofol, endosulfan-I, heptachlor endoepoxide, diel-

drin, DDD, DDE, endosulfan-II, o,p0-DDT, p,p0-DDT, pH, EC, Cl-1, phosphate, and silt) that

accounted for most of the total spatial and temporal

variations. Parameters identified by temporal and

spatial DFA require more attention for management

and conservation of River Chenab aquatic resources.

The residual level of OCPs measured in the sediments

indicates the need to study the associated risks to the

aquatic ecosystem and in particular to directly

associated communities.

Acknowledgments The first author thanks the Higher

Education Commission (HEC) for providing financial support

under the Indigenous 5,000 fellowship program towards his

PhD. We also acknowledge the Pakistan Wetland Program

(PWP) for providing transportation during fieldwork. Efforts of

research students of EBL, QAU during exhaustive fieldwork

are gratefully acknowledged.

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