THESIS REPORT

FOR

PRS 4599 : MSc. PROJECT

Project Title :

Development of sediment reference sample for toxicity

testing using Microtox Solid Phase test and Metal

Fractionation using single extractions

Student Name: Amitkumar Christian

Student number: M00082846

Module Leader: Mr.John Watt

Project Supervisors:1) Prof. D M Revitt

2)Dr. Lian Scholes

Submitted in partial fulfilment of the requirements of

Middlesex University for the Degree of Master of

Science in Environmental Pollution Control

September, 2008.

1

Abstract

Chemical characterisation of pollutants using fractionation techniques and

bioassays are useful monitoring tools for sediment quality assessment. However,

a common criticism of sediment bioassays is the lack of an appropriate

reference sediment sample to which sample sediment toxicity can be

comparatively assessed. In this study an approach of obtaining a reference

sediment sample by cleaning the sediment samples with metals was tested.

Metal fractionation was carried out by applying single extraction techniques

modified from a sequential extraction scheme proposed by Tessier et al (1979).

The total metal concentrations were characterised using nitric acid digestion.

The sediment samples before and after the extractions were analysed using the

Microtox Solid Phase Test (SPT). Comparison of total metal concentration with

various sediment quality guidelines suggests that the sediments are polluted due

to higher concentrations of Cu , Ni , Pb , Cd and Zn. The fractionation studies

reveal that metals are contained mainly within Fe-Mn Oxide phase.The

comparison of the results of the SPT with various sediment classification

methods suggests that the sediments are moderately toxic to non toxic.

However, the results of changes in the toxicity of sediment residues obtained

after each extraction compared to unprocessed sediment toxicity results are not

statistically significant. But the comparison of toxicity results of sediment

residues obtained after HNO3 and NaOAc digestion with the toxicity value of

replicate1 of unprocessed sediment suggests a marginal decrease in the toxicity

of sediments while the comparison of toxicity values of MgCl2 , NH2OH.HCl,

HNO3+H2O2 indicates an increase in the toxicity of sediment residues. The

comparison of toxicity values of all sediment residues with that of replicate2 of

unprocessed sediment indicates an increase in the toxicity of the sediments after

extractions.

Key Words: Sediments, Metal Fractionation, Bioassays, Microtox, Solid Phase Test.

2

CONTENT

Table of content Pages 3-5

List of Tables Page 6

List of figures and Appendix Page 7

Acknowledgement Page 8

Table of content

Page

Chapter 1 :Introduction

Background 9-10

Aims and Objectives 11

Chapter 2 : Literature Review

2.1. Urban River sediments and Pollution 12

2.2 Water Framework Directive (WFD) 13

2.3 Sediment and Pollutant sources in Urban Rivers 13-14

2.4 River sediment composition and dynamics 14-15

2.5 Sediment Quality Assessment 15-16

2.6 Metals in Urban Sediments and Sources 16-17

2.7 Toxic Metals and their forms in sediments 17

2.7.1 Exchangeable Metals 18

2.7.2 Metals bound to Carbonates 19

2.7.3 Metals bound to Fe-Mn Oxides 19

2.7.4 Metals bound to Organic Matter 19

3

2.8 Sequential Extractions 19-20

2.9 Advantages and Problems of sequential extractions 21

2.10 Single Extractions 22

2.11 Bioassays : A useful monitoring tool 22-23

2.12 Sediment Toxicity Tests 23-25

2.13 Sediment toxicity tests and problem of reference sediment 25-28

2.14 Bio Luminescence based bacterial bioassays : 28-29

2.15 Biochemical mechanism of Luminescence in vibrio

fischeri

29-30

2.16 Microtox Test system 30

2.17 Comparison of Microtox with other bioassays 31

Chapter 3 Materials and Methods

3.1 Study area and sample collection 32

3.2 Sediment Drying 33

3.3 Sediment Sieving and sample storage 33

3.4 Chemicals and Reagents 33

3.5 Laboratory glassware and equipments 33

3.6 Nitric acid digestion 33-34

3.6.1 Preparation of sediment residue sample for microtox 34

3.7 Metal speciation using single extractions 34-36

3.8 Inductively Coupled Plasma –Optical Emission

Spectrometry (ICP-OES).

37

3.8.1 Stock solutions and Standard preparations 37

3.8.2 Calibration of Instrument 37

4

3.8.3 Analysis of samples 38

3.8.4 Calculations 39

3.9 Toxicity analysis of sediments 39

3.9.1 Reagents , Solutions and accessories 39

3.9.2 Microtox analyzer 40

3.9.3 Phenol Standard Test 40

3.9.4 Solid Phase Test 40-41

Chapter 4 : Results and Discussion

4.1 Total metal concentrations 42-43

4.1.1 Relative abundance of metals 43

4.1.2 Comparison with Sediment Quality Guidelines(SQGs) 44-46

4.1.3 Association of metals and source identifications 46-49

4.2 Metal Fractionation using single extractions 49-52

4.2.1 Partitioning patterns of metals in different fractions 52-54

4.2.2 Comparison of sum total of fractions with total metal

digestion

54-55

4.3 Sediment Toxicity Results 55-56

4.3.1. Sediment Classification on the basis of toxicity results 56-57

4.4 Toxicity results of the sediment residue of single

extractions

58

4.4.1 Evaluation of change in the toxicity after extractions of

metals

59-64

Chapter 5 Conclusions and Recommendations

5.1 Metal concentrations 65

5

5.2 Metal Fractionation 66

5.3. Toxicity Results for unprocessed sediments and change in

toxicity of sediment residues

67

5.4 Recommendations for further research work 68

References 69-79

Appendix 80-85

Tables:

Table 2.1: Concentration of metals in urban river sediments (µ g/g)

Table2.2: Summary of Microtox correlation coefficient with three most

common acute toxicity tests.

Table 3.1: Operating conditions and Stages of Tessier Scheme

Table 3.2 Operating Conditions and wavelengths for ICP-OES

Table 4.1 Total metal concentration in sediments

Table 4.2 Comparative analysis of metal concentrations with reference values

for fresh water sediments (units in µ g/g):

Table 4.3 Spearman’s Rank Correlation Matrix for metal concentrations in

sediment (n=10)

Table 4.4 Metal Concentrations Obtained using Single Extractions (Means ±

S.D.)

Table 4.5 Metal Fractions obtained from single extractions (Means ± S.D. of 2

replicates)

Table 4.6 Microtox Solid Phase Test (SPT) Results for Unprocessed Sediment

samples

Table 4.7 Sediment toxicity classification (Adopted from Kwan and Dutka

(1995)

6

Table 4.8 : Microtox Solid Phase Results of Sediment residue after Single

Extractions.

Table 4.9 Kruskal-Wallis test results on EC50 values of sediment samples.

Figures:

Fig.2.1. Relationship between metal mobility in the different operationally

defined phases and leaching strength of common reagents used for sequential

extractions.

Fig 3.1: Flow diagram of Single Extraction procedure Fig.

4.1 : Probability plot of Total Metal Concentrations Fig. 4.2

Partitioning Pattern of Metals in different fractions

Fig.4.3 Box plot of EC50 values of unprocessed sediment sample and sediment

residues after each single extraction.

Fig.4.4 Individual Value plot of EC values of unprocessed sediment and

sediment residues after each single extraction step.

Appendix:

Appendix 1: Strength and weaknesses of bioassays according to route of

exposure

Appendix 2: Microtox Test System

7

Acknowledgement

I express gratitude to my supervisors Prof. Mike Revitt and Dr. Lian

Scholes for their support during this project work. Especially I am

sincerely grateful to Dr. Lian Scholes for providing constructive

criticism on my thesis write up and moral support at each phase of the

project. I am also thankful to Alan La Grue and Manika Chaudhry for

their support to perform the laboratory analysis. Generations of

Middlesex University students would be obliged to their ever friendly

and always ready support to perform the project laboratory work.

Finally I thank my family for their tremendous support and

motivation during this lengthy adventure of pursuing higher education

in the world’s number one education system. It was my mother’s

desire that I study in the UK education system and thus I dedicate this

thesis to my mother for her inspirations, care and loads of love and

training.

“Get wisdom, get understanding. Wisdom is supreme; therefore get

wisdom. Though it costs all you have, get understanding (Proverbs 4:

5,7). Then you will know the truth, and the truth will set you free

(John 8: 32)”.

8

CHAPTER 1

INTRODUCTION

Background:

With the increasing awareness in the rules that regulate the fate of pollutants in

urban environments, the sediments of urban rivers pose a predominantly

demanding scientific problem as many persistent contaminants (e.g. metals,

persistent organic pollutants (POPs)) tend to concentrate in river bed sediments

and thus the assessment of sediment quality is recognised as a vital step in

knowing the risks associated with man made pollution in the riverine system

(De Miguel et al , 2005). Depending upon the conditions in the river, pollutants

bound to sediment may become bioavailable and impose toxicity on aquatic

organisms. Chemical analysis alone is not adequate to justify effects of

chemicals present in the sediment (Beg and Ali, 2008) as they do not

demonstrate that harmful effects are occurring (Luoma et al , 1995) , thus for

best possible characterisation and assessment of pollution , issues related to both

concentration and toxicity should be addressed (Mowat et al , 2001).

Therefore, because of the necessity to determine a cause –effect relationship

between the concentration of pollutants and resultant environmental damage

and to measure the potential synergistic-antagonistic effect of composite

combination of chemicals(Girotti et al , 2008), Microbial toxicity tests based

on bacteria have been widely used in environmental toxicity inspection

becauseof the similarity of complex biochemical function in bacteria and higher

organisms (Mowat et al , 2001) .Among the bioassays solid phase tests are

useful and widely used as test organisms are exposed to whole sediments which

9

include water soluble and non polar substances and thus offer a high relative

realism for toxicity assessment of sediments. However, sediment toxicity tests

require reference sediment exclusive of contaminant with similar physico –

chemical characteristics as the test sediments (Guzzella , 1998).

The microtox test based on bacterial bioluminescence which utilises V. Fischeri

bacteria as test organism represents one of the most appropriate test for

sediment toxicity assessment as it can be used on extracts as well as directly to

the sediment (solid phase test) ( Calace et al , 2005).

As it is now widely recognised that the total concentrations of Heavy Metals

specify the extent of contamination, but they offer modest information about the

forms in which Heavy Metals are present, or about their possibility for mobility

and bioavailability in the environment (Lake et al , 1987) , understanding of

metal speciation in the sedimentary environment may be of more importance for

risk assessment than the total metal concentrations( Farkas et al , 2007). For

this reason, sequential extraction processes are frequently used because they

present information about the fractionation of metals in the different lattices of

the sediments and other solid samples (Margui et al , 2004).

It is against this background that an investigation into establishing a reference

sediment sample for solid phase bioassays was undertaken in relation to

Microtox solid phase test utilising single extractions of metal fractions using -

same conditions and procedures described in the sequential extraction procedure

mentioned in Tessier et al 1979 .

10

Aims and Objectives:

The main aim of the study is to assess whether the approach of cleaning the

sediment with metals using single extraction steps of sequential extraction is an

appropriate alternative to develop a sediment reference sample or not.

In order to obtain a reference sample exclusive of metals, the following

procedure was adopted:

Each extraction step described in the Tessier scheme was applied to separate

aliquots of sediment samples using the same extraction conditions and

chemicals described in the scheme (see section 3.8 for details). After the

extraction step washed and dried residue sediment samples were analysed for

toxicity using the Microtox solid phase test. A reduction in the toxicity could be

expected as the metals were removed using chemicals. Microtox solid phase test

was also conducted on unprocessed sediment so that a relative comparison

between toxicity measurements could be made.

The objectives of the investigation are summarised as follows:

• To characterise the sediments for total metal concentration for eight

heavy metals (Cd, Cr, Cu, Fe, Mn, Zn, Pb, Ni) using nitric acid digestion

method.

• To characterise various fractions of metals as described in the Tessier

Scheme using single extraction procedures.

• To determine the level of toxicity associated with unprocessed and

processed sediment sample using the Microtox solid phase test.

11

CHAPTER 2

LITERATURE REVIEW

2.1 Urban River Sediments and Pollution:

Urban rivers have been linked with water quality issues since the nineteenth

century when it was common tradition to discharge untreated domestic and

industrial waste into water courses. Since then the situation has been improved

due to e.g. the management curtailment of pollution at sewage treatment plants.

However, because of soaring population densities in urban areas with associated

of sources of pollution, the deprivation of urban rivers is still focal today

(Goodwin et al , 2003).

When discharged into the river environment many anthropogenic chemicals

bind or adsorb on to particulate matter and, depending upon river morphology

and hydrological conditions such particulate matter along with associated

contaminants can settle out along the water course and become part of the

bottom sediments (Vigano et al , 2003). Thus, sediments are considered as

storehouse for physical and biological remains and for many pollutants

(Calmano et al , 1996).

Further more , under a range of physical , biological and chemical conditions

(e.g. aqueous solubility ,pH, redox , affinity for sediment organic carbon , grain

size of sediments , sediment mineral constituents and quantity of acid volatile

sulfides) these contaminants may become bioavailable and result in a toxic

impact on aquatic biota(Ingersoll et al , 1995).

Nowdays, escalating evidence of environmental degradation have been

confirmed where water quality guidelines for contaminants are not surpassed

but, still organisms in or near the sediments are badly affected (Ingersoll et al ,

1995).

12

Thus, with a vision to protecting aquatic biota, improving water quality and

managing problems of resuspension and the land deposition of dredged

materials, sediment quality assessment has been a crucial scientific and

legislative issue in recent years. ( Calmano et al 1996 ; Nipper et al 1998).

2.2 Water Framework Directive (WFD):

The European Union’s(EU) Water Framework Directive (WFD) which came in

effect on the 22 December 2000, is one of the most important pieces of

environmental legislation and is likely to change the manner water quality is

being monitored within all member states ( Allan et al , 2006).

The main objective of the Directive is to improve, protect and prevent further

deterioration of water quality across Europe and it aims to attain and ensure

“good quality” status of all water bodies throughout Europe by 2015. Thus the

requirement of addressing water quality issues associated with urban rivers has

been increased within Member States (Goodwin et a, 2003). Under the WFD,

three modes of monitoring strategies are identified and at each strategy level

chemical monitoring, biological/ecological assessment, physico-chemical and

hydro morphological tools have been included to assess the water quality status

of the body (Allan et al,2006).

In the WFD, EU commission places emphasis on establishing quality standards

related to the concentrations of priority substances and substances which may

cause harm in water, sediment or biota. (Crane , 2003).

2.3 Sediment and Pollutants Sources in Urban Rivers:

Urban river system is much more complex in its sediments and pollutant

sources. Sediments may be released into urban rivers due to erosion of land

surface through variety of physical and chemical processes, the rapid run off

from impervious surfaces, routing through drainage network, retention tanks

13

and winter gritting roads (Goodwin et al, 2003). These sediments may contain

or associated with pollutants such as hydrocarbons , garden and animal wastes ,

fertilisers , pesticides , oils , detergents , deicing chemicals , street litter (Hall,

1984 ; Chapman, 1996) and trace and heavy metals (Collins et al, 2007).

Moreover, Combined Sewer Overflow (CSO) events also augment the pollutant

and sediment load because of its own contaminant load and the erosion and

wash out of in-sewer sediments (Fierros et al , 2002). Due to the wide variety of

sources and river dynamics there exist a wide spatial and temporal variation in

the properties of sediments.

2.4 River Sediment Composition and dynamics:

River sediments are mainly composed of mineral particles originated from the

parent rocks due to erosion process, particulate organic matter adsorbed on

mineral particles or particle sized organic matter which originates from plant

detritus and animal debris, adsorbed nutrients and toxic inorganic and organic

pollutants (Chapman , 1996). However , with respect to their behaviour in

nature , sediments can be classified in two distinctively different groups a) fine

sediments with particles smaller than 50µ m (i.e silt and clay) and b) coarse

sediments with size exceeding 50µ m ( i.e. sands and gravels) (Salomons et al ,

1984).

The erosion, transportation and deposition of sediment is a function of river

flow velocity, particle size, water content of the material (Chapman , 1996) ,

channel structure and degree of turbulence(Goodwin et al , 2003). Under certain

hydraulic conditions sediments can be transported in suspension or by traction

along the bottom which is often called ‘Bed Load’. The suspension mechanism

initiates the movement of fine particles while the Bed Load causes the

movement of coarse particles (Chapman , 1996). More over, within urban

catchments rapid runoff and CSO events trigger river flow events with short

14

peak times and high peak flows which step up transport of sediments and

associated pollutants (Goodwin et al , 2003).

2.5 Sediment Quality Assessment:

Historically, the evaluation of sediment quality has often been restricted to

chemical characterisation. It facilitates to classify what are the contaminants and

what is their concentrations(McCauley et al , 2000) and it imparts information

about the situation of sediments and processes within them(Wolska et al , 2007).

However, quantifying contaminant concentration alone can not impart enough

information to assess effectively probable adverse effects, possible relations

among chemicals or the time dependent availability of these substances to

aquatic organisms ( Ingersoll et al , 1995) because it is impractical to analyse all

the compounds and their synergistic/antagonistic effects contributing to

toxicity(Plaza et al , 2005). As the bioavailability of pollutants to aquatic biota

and their effects on the biota is of vital interest in sediment risk assessment ,

ecotoxicological testing (bioassays) of sediments which investigate the toxic

effects of sediment contaminants on living organisms ( e.g. fish , plants ,

bacteria , algae) has been broadly used ( Rand et al , 1995).

Thus, to understand the fate of pollutants in sediments and their influence on

aquatic biota , a tiered biological and chemical assessment methods have been

implemented (Calmano et al , 1996) . The sediment quality triad methodology,

one of the most widely used tiered methodology based on weight of evidence

combines 1) Identification and quantification of contaminants (i.e. chemical

analyses ) , 2) Measurement and quantification of Toxicity based on bioassays

(toxicity tests) and 3) Evaluation of in situ biological effects(e.g. Benthic

community structure) (Calmano et al , 1996 ; McCauley et al , 2000 ).

15

Principal advantages are that it can be used for any sediment type (Calmano et

al ,1996) and as both biological and chemical elements are used , environmental

significance of contaminated sediments is addressed (McCauley et al , 2000).

However the cause –effect relations are not always differentiated because of the

synergistic/antagonistic effects of chemicals causing toxicity in sediments

(Calmano et al , 1996 ; McCauley et al , 2000) . Furthermore, the assessment is

very site specific and does not allow practical calculations of chemical specific

guidelines ( Mc Cauley , 2000).

2.6 Metals in Urban Sediments and Sources :

Metals are natural part of biosphere (Luoma , 1983) and they are initiated in to

the aquatic environment through many lithogenic and anthropogenic

sources(Zhou et al , 2008). Chemical leaching of bedrocks , water drainage

basins and run off from banks are believed to be the major lithogenic sources of

metals (Zhou et al , 2008) while emissions from industrial processes ( e.g.

mining , smelting , finishing , plating , paint and dye manufaturing) (Rand et al ,

1995) and through urban sewage, house hold effluents, drainage water,

business effluents , atmospheric deposition and traffic related emissions

transported with storm water (Karvelas et al , 2003) are the major anthropogenic

sources of metals in the aquatic environment. Upon released to the aquatic

environment metals are partitioned between solid and liquid phase (Luoma ,

1983) and finally as a result of settling metals associated with solid phase gather

in bottom sediments(Farkas et al , 2007).Thus , sediments are main basin of

metals in aquatic environment(Morillo et al , 2002).

A comparison of typical concentration of metals in urban river sediments is

presented in the Table 2.1.

16

Table 2.1 : Concentration of metals in urban river sediments(µg/g)

(reproduced from De Miguel et al , 2005)

Cr Cu Fe(%) Mn Ni Pb Zn

River Henares,

Spain

(97-180) (7-270) (0.8-

3.16)

(150-445) (11-128) (17-1280)

River Seine , France 84 2.91 162 429

River Sowe , UK 47.9 164 411 786

Semarang ,

Indonesia

(12.3-448) (5.2-

2666)

(53.7-

1257)

Danube River,

Austria

43.5 53.9 187

Tiber river , Italy (18.2-

54.2)

(13.3-45.5) (3.6-

33.5)

(12.4-

43.1)

(53.4-

417.6)

River Po, Italy (118-223) (45.2-

179.9)

(4.5-5.2) (355-

1159)

(99-237) (39.3-

71.8)

(127-519)

River Sherbourne 38 71 2.9 481 19 118 196

River Manzanares (18-1260 (11-347) (1.9-9.1) (305-

1276)

(5-47) (42-371) (70-591)

In brackets : minimum- maximum values ; in italic :arithmatic mean values

2.7 Toxic metals and their forms in sediments :

Although some metals are fundamental micronutrients (e.g. Mn, Fe, Cu,Zn) ,

almost all metals are toxic to aquatic organisms and human health if exposure

levels are sufficiently high (Luoma , 1983). Among the toxic metals cadmium,

chromium, copper, lead, nickel, zinc, mercury and arsenic are of principal

importance due to their relationship with anthropogenic inputs. Under diverse

physical, biological or chemical conditions the toxicity of metals in sediments is

a subject of bio availability (Jennett et al ,1980).

17

Thus in order to assess the bio availability of metals and their potential toxicity

it is required not only to determine the total concentration but also the different

chemical forms or ways of binding between metals and sediments (Albores et

al , 2000).

In sediments depending upon various physical, chemical and biological

conditions , metals are partitioned into different chemical forms related to a

selection of organic and inorganic phases (Farkas et al , 2007). Thus, in river

sediments metals can be bound to various compartments e.g. adsorbed onto clay

surfaces or iron and manganese oxy hydroxides, present in lattice of secondary

minerals such as carbonates, sulphates or oxides, occluded within amorphous

material such as iron and manganese oxyhydroxides, complexed with organic

matter or lattice of primary minerals such as silicates (Gismera et al , 2004).

Due to natural and anthropogenic environmental changes these associations can

be modified and metals can become more or less bio available or mobilised

within different phases. These influential factors include pH, temperature, redox

potential, organic matter decomposition, leaching and ion exchange processes

and microbial activity (Filgueiras et al ,2002). Thus in relation to their mobility

and bioavailability, in order of decreasing interest the major metal fractions are :

1) Exchangeable ,2) Bound to carbonates , 3) Bound to Fe-Mn Oxides , 4)

Bound to organic matter and 5) Residual .

2.7.1 Exchangeable Metals :

In this fraction, weakly adsorbed metals held on the solid surface by

comparatively weak electrostatic forces that can be liberated by ion exchange

processes in the sediment are included (Filgueiras et al , 2002). These metals are

considered the most available forms of metals present in the sediments

(Morrison , 1985).

18

2.7.2 Metals Bound to Carbonates:

Metals in this fraction are co-precipitated with carbonates which present as

cement and coating (Morrison , 1985) and this phase can be an important

adsorbent for metals in the absence of organic matter and Fe-Mn oxides

(Filgueiras et al , 2002).

2.7.3 Metals bound to Fe-Mn Oxides:

Metals in this fraction are related with Iron and Manganese oxides which are

present as nodules, concretion and cement between particles or plainly as a

coating on particles. Iron and Manganese oxides are considered as exceptional

scavengers of metals and are thermodynamically changeable under anoxic

conditions (Tessier et al , 1979).

2.7.4 Metals bound to organic matter:

In this fraction metals associated with a variety of organic materials such as

living organisms, plant and animal detritus or coatings on mineral particles are

included. This fraction is believed to be less mobile due to its alliance with

humic substances of higher molecular weights (Filgueiras et al , 2002).

2.8 Sequential Extractions:

A sequential extraction procedure (SEP) also recognised as sequential

extraction scheme (SES) can be used to determine above mentioned binding

fractions of metals in the sediment. In this process, given sediment sample is

subjected to a series of gradually more strong, phase specific reagents under

controlled conditions which remove out metals from the particular physic-

chemical phase of concern (Bird et al , 2005).

Depending upon fractions of interest, a broad range of chemical extractants can

be used (see fig.2.1) and thus in the literature numerous sequential extraction

19

schemes are available which vary in the use of extractant, target phase and the

order of attack to separate particular form of metals. The bulk of the schemes

are deviations of a scheme proposed by Tessier et al (1979) (Filueiras et al ,

2002). Many researchers have reported difficulties in comparing the results of

SES due to their wide variation in the use of chemicals and target phase. Thus,

in an effort to synchronise the diverse methodologies and to facilitate the

comparison of results easier , Community Bureau of Reference (BCR) proposed

a three step extraction procedure along with a reference sediment material to

certify the protocol (Mossop and Davidson , 2003).

Fig.2.1. Relationship between metal mobility in the different operationally defined pahses and leachant strength of common

reagents used for sequential extractions(Reproduced from Filgeuiras et al (2002)).

20

2.9 Advantages and problems of sequential extractions:

The use of sequential extraction techniques , though lengthy furnish important

information about the origin , mode of occurrence, biological and physico-

chemical availability , mobilisation and transport of metals within the

sedimentary matrices(Tokalioglu et al , 2000).However, since their early

advancement , sequential extraction schemes have been criticized for the lack of

selectivity of reagents, issues of re adsorption and redistribution of metals

solubilised during extraction and changes in speciation due to sample pre-

treatment and its general methodology ( Gleyzes et al , 2002).

In the sequential extraction scheme, the reagents are supposed to attack only the

target phase without solubilising the other phases. However, it has been

discovered that the reagents are not selective and may have an effect on other

phases also. Thus the sequential extractions are called “operationally defined”

fractionation techniques. This lack of selectivity may cause re-adsoprtion and re

distribution of metals among the target phases. Moreover, incomplete

dissolution of some phases and changes in pH may also lead toward re

adsorption and redistribution problems (Gleyzes et al, 2002). Various

researchers have reported the problem of re adsorption and redistribution for

many sequential extractions for each phase.

Despite these limitations sequential extractions are widely acknowledged for

metal fractionation in sediment samples to assess the mobility and

bioavailability of metals.

21

2.10 Single Extractions:

To cut down lengthy procedures and thus make sequential extractions a part of

routine analysis, various alternatives (e.g. microwave heating and ultrasonic

shaking) to conventional extraction procedures have been employed (Albores et

al , 2000). One of the alternatives to reduce the lengthy and laborious sequential

process is to use single extractions. In single extractions the same reagents and

operating conditions as the sequential extractions are employed to different sub-

sample (Albores et al ,2000) and, except for first step , the metal concentrations

in each individual step can be obtained by subtracting the results obtained in

two successive steps(Filgueiras et al , 2002). Initially this technique was

suggested by Tack et al (1996) in which first three steps mentioned in Tessier’s

Scheme were extracted simultaneously while, for organic matter bound metals,

it was suggested that the sample should be extracted first for reducing metals

and should then be re treated with hydrogen peroxide step to remove organic

matter and thus release metals bound to this phase.

2.11 Bioassays : A useful monitoring tool

Bioassays assess modifications in physiology and activities of living organisms

resulting from stress produced by biological or chemical toxic compounds

which can cause disturbance of e.g. metabolism. Thus, bioassays assist to

establish cause / effect relationship between the concentrations of pollutants and

resultant environmental damage (Girrotti et al , 2008).

Traditionally fish and macro invertabrates bioassays are the first in the series of

toxicity bioassays comprising animals. As these bioassays were found effective

in assessing the acute toxicity of chemicals and effluents and often predicted

their effects on aquatic biota and habitat, they have been greatly used in the

screening of chemicals and regulatory compliance monitoring (Blaise et al ,

22

1998). However, these conventional bioassays require longer test period along

with additional time (e.g. acclimatisation) for setting up of the test (Ribo and

Kaiser, 1987). Moreover toxicity was found a trophic level property and thus it

was appreciated that safeguard of aquatic resources could not be guaranteed by

performing bioassays exclusively at macro organism level (Rand et al , 1995).

Therefore an earnest requirement of cost effective, multi trophic and faster

bioassays was strongly felt which led to development of micro scale testing

procedures involving bacteria, protozoa, micro algae and micro invertabrate

(Blaise et al , 1998). Definite benefits of microbial testing procedures include:1)

ease of handling ,2 ) short testing time , 2) reproducibility of results (Mowat et

al , 2001) and 4) cost effectiveness (Wadhia and Thompson , 2007).

2.12 Sediment Toxicity Tests:

As Van Beelen (2003) stated, toxicity is not a substance property only , but it is

the combination of the substance , the organisms , the conditions and the

exposure duration that can produce toxic effects. Thus on the basis of this basic

principle sediment toxicity tests can be classified according to: 1) test end

points , 2) test organisms and 3) routes of exposure (Nipper et al , 1998) .

According to test end points most sediment bioassays can be classified as acute

(having a short period of exposure from hours to days) or chronic (having

longer period of exposure from days or ,weeks to months) types ( Burton , 1991 ;

Nipper et al 1998).With a view to identifying polluted areas , acute tests can be

applied as screening tools in the first tier of a risk assessment while chronic tests

can be employed in later stages to estimate the long term consequences of

contaminants on organisms (Nipper et al , 1998).

23

Based on the goals and stages of assessment a wide variety of organisms have

been utilised within sediment bioassays. A complete list has been compiled by

other authors (e.g. Nendza , 2002 ). The majority of tests have utilised bacteria,

rotifers, amphipods, insects, polychaetes, crustaceans, bivalve, echinoid and fish

(Nendza , 2002).

According to the routes of exposure or test phases sediment bioassays can be

catagorised in four major groups: 1) Elutriate tests (Water extractable), 2)

Extractable (with solutes other than water), 3) interstitial or pore water and 4)

whole sediment or solid phase tests (Burton , 1991 ; Nipper et al ,1998).

Each type of test has its own strengths and weaknesses (see appendix 1).

Elutriates may characterise only a part of multiple sources of contamination due

to varied degree of solubility of each contaminant in water. Moreover, water

elutriation could underestimate the types and concentrations of bioavailable

organic contaminants present as many organic contaminants are not water

soluble (Ronnpagel et al , 1995). Solvent extract tests are useful in screening the

sediments for the existence of toxic chemicals but these tests do not provide a

reasonable assessment of sediment toxicity to benthic biota as the extraction

procedures can liberate the contaminants from the sediments which are

otherwise not bioavailable(Nipper et al , 1998). As pore waters are considered

as foremost path of exposure to many contaminants to some organisms, toxicity

tests incorporating sediment pore waters have been widely used. However their

“sensitivity” may be meaning less relative to other exposure routes due to

manipulation and laboratory artefacts (Chapman et al , 2002a).

Whole sediment tests offer much more realism and ecological importance

compared to other tests as the organisms are directly tested against the

sediments (Burton , 1991). The solid phase tests recognise the toxicity due to

soluble /insoluble and organic/inorganic material without extraction (Calace et

24

al , 2005) and as the test provides direct contact between the test organisms and

sediment particles , it enhances the prospects for the measurement of responses

to particle bound and marginally soluble toxicants(Qureshi et al , 1998) .

However, they present a string of limitations due to sediment typology, loss of

organisms which can lead to an overestimation of sediment toxicity due to

sorption of bacteria on particles during the tests (Calace et al , 2005).

2.13 Sediment Toxicity Tests and Problem of Reference Sediment :

In conventional sediment risk assessments, the toxicity of test sediment is

compared to that of reference sediment or to a reference condition as this would

permit an assessment of whether the chemicals present in the sediment pose a

hazard or not (Chapman et al, 2002b). Moreover, as test organisms are

responsive to the sediment properties (Van Beelen ,2003) it is required to

differentiate the response of the test organism to the sediment properties along

with the associated contaminants. Thus, a source of representative,

uncontaminated and non toxic sediment is of prime importance to the sediment

toxicity assessment (Suedel and Rogers , 1994) .

A reference sediment may be defined as a sediment having similar

characteristics (e.g. pH, redox potential, particle size distribution and percent

organic carbon) to the test sediment but without chemicals that might be a

trouble ( Burton Jr. et al , 1992 ; Chapman et al, 2002b) . This reference

sediment can be used as a pointer of sediment conditions exclusive of the

specific pollutant(s) of interest and presents site specific basis for evaluating the

results of test sediment with that of the non toxic sediment (Lamberson et al ,

1992).

25

As no natural sediment is expected to be totally uncontaminated and have the

same characteristics as the sediment being assessed, obtaining a reference

sediment for comparison is a central problem with sediment toxicity testing

(Beg and Ali , 2008).

Ideally the reference sediment is collected from a neighbouring unpolluted area

near to the site of interest. The potential advantages of field collected sediment

as reference sediment are: a) sediment properties and characteristics are close to

the test sediments and b) preparations are not time consuming (Suedel and

Rogers , 1994). However , field collected sediments may contain pollutants

other than the pollutants of concern which may show back ground toxicity to

the test organism and thus lead to false positive results for toxicity comparisons.

In case of highly urbanised catchments, it is particularly difficult to find a

nearby clean area for reference sediment as there are chances that the whole

catchment is heavily polluted (e.g. River Brent which passes from highly

urbanised catchment). Moreover, Walsh et al (1991) noted variable

compositions among samples collected at different time and locations which

makes relative comparison more difficult.

As a contribution to addressing the issue of representative reference sediment

sample for toxicity assessment, formulated reference sediment samples were

developed (Suedel and Rogers , 1994).With the intention of matching the

physical and chemical characteristics of natural sediments , formulated

sediments are prepared using various combinations of sand , silt and clay sized

particles , organic matter and calcium carbonate (Still et al , 2000). To optimise

the formulated sediment’s representativeness and quality, artificial sediments

are preconditioned for each constituent (Verrhiest et al 2002). Gonzalez (1996)

has also tried to improve the ‘natural characteristics’ of formulated sediments

26

through the addition of components such as Acid Volatile Sulfide (AVS) to

formulated sediments.

There fore, formulated sediments can offer several advantages over field

collected sediments which include a) absence of background contaminants, b)

well characterised and reproducible composition and c) absence of indigenous

biota (Burton , 1996). However, the principal limitation with formulated

sediments is to match the organic carbon content qualitatively, key factor

affecting the fate and kinetics of sediment bound materials and thus

bioavailability (Suedel and Rogers , 1994).

A possible solution to the problem of reference sediment could be provided if

naturally contaminated sediment can be ‘cleaned’ through the removal of

pollutant(s) and then tested for toxicity testing. This technique could help retain

the sediment physical and chemical characteristics of the natural sediment in the

reference sediment with the exception of the contaminant(s) of interest.

In an experiment of involving the development of a non toxic reference sample,

Kwan and Dutka (1996) washed natural field collected sediment with water

until a negative response was obtained in the monitoring bioassay (Toxi-

chromotest). They found the sediment sample non toxic at the ratio of 1:5

(sediment: ToxiChromotest test reaction mixture). In another experiment Beg

and Ali (2008) extracted organic contaminants from two different sediment

samples using solvents of varying polarity in Soxhlet extraction. The extraction

was done overnight using hexane followed by 2nd

overnight extraction using

dichloromethane which further followed 3rd

overnight extraction using methanol.

The toxicity of both sediment samples was analysed before and after the

extraction. A drastic reduction in toxicity of PAHs rich sediment sample was

observed while the toxicity of metal rich sediments which were extracted for

PAHs reduced marginally after the extraction.

27

Thus, with a view to establishing reference sediment for robust toxicity testing

previous studies suggest that sediment can be washed for the contaminant of

interest using chemical extraction processes and a non toxic reference sediment

for the toxicity comparison can be obtained.

Therefore, in an experimental design, sediments contaminated with metals

could be treated with chemicals and conditions applied in sequential extractions

of metals which extract out particular form of metals from the sediments. As the

bioavailability of metals is dependent on the metals forms , after extraction of

these metals from the sediment a reduction in the toxicity of sediment could be

expected and a reference sediment sample for robust sediment toxicity analysis

by washing/cleaning to remove all bio available forms of metal from the

sediment, established.

2.14 Bio Luminescence based Bacterial Bioassays:

As sediment micro organisms are essential for the biodegradation of organic

matter and the cycling of nutrients and while these microorganisms are

vulnerable to toxic pollutants(Van Beelen , 2003) , observing microbial

responses has been proposed as an early alarming signs of ecosystem stress and

a tool of setting up toxicant criteria for terrestrial and aquatic eco systems

(Burton , 1991).

Bacterial bioassays can be clustered in five major categories: 1) Population

growth , 2) Substrate consumption , 3) respiration , 4) ATP luminescence and 5)

B i o l u m i n e s c e n c e ( P a r v e z e t a l , 2 0 0 7 ) . S i n c e b i o a s s a ys b a s e d o n

bioluminescence are rapid , sensitive , reproducible and cost effective and more

over the y provide an easy evidence of the effects produced on living

organisms , they are often chosen as the first screening method in a test battery

supporting their widespread application in aquatic toxicity tests. The most

28

suitable species for bioluminescence tests are vibrio fischeri (v. fischeri) ,

vibrio harvey (v.harvey) , p. leiognathi and pseudomonas fluoresence (Girotti et

al , 2007).

Bioluminescence assay based on v. fischeri has been accounted as one of the

most responsive across a broad range of chemicals , compared to other bacterial

assays such as Nitrification Inhibition , Respirometry , ATP lulminescnece and

enzyme inhibition(Girotti et al , 2007). In this assay a suspension of v.fischeri

bacteria in saline water is exposed to chemical of concern and the decrease in

light output of its natural luminescnece is measured to assess the toxic

consequences of chemical(Kaiser , 1998) .

Several commercial test kits such as MicroTox (Azure Environmental) ,

Lumistox (Dr. Lange GmbH, Berlin , Germany) and biotox (Bioorbit , Turku ,

Finland) are available (Kaiser , 1998) . Moreover a version of v.fischeri test

called Deltatox has been also developed for field testing (Wadhia and

Thompson , 2007).

2.15 Biochemical mechanism of Luminescence in Vibrio Fischeri :

In luminescent organisms, light emission usually results from an interaction

between the enzyme luciferase, reduced flavin and a long chain aldehyde in the

presence of oxygen and constitutes part of the cell’s electron transport system

and the emission of light depends upon on this flow of electrons and therefore

the level of light output reflects any changes in the metabolic activity and health

of the organisms (Ribo and Kaiser , 1987) .

Reduced flavin mononucleuotide (FMNH2) is the fundamental constituent in the

bioluminescence reaction.

29

Flavin mononucleotide(FMN) is reduced to FMNH2 upon reaction with the

reduced form of nicotinamide adenine dinucleotide phosphate ( NAD(P)H ) in

presence of flavin reductase enzyme (Parvez et al , 2006).

NAD(P)H + H + FMN NAD(P) + FMNH2

Reduced FMNH2 gets oxidized into FMN and H20 upon reaction with molecular

oxygen in the presence of aldehyde and luciferase enzyme which emits blue

green light of wavelength 490nm(Parvez et al 2006).

FMNH2 + 02 + R- CHO FMN + H20 + R-COOH + light

2.16 MicroTox®

Test System :

Since its development by Beckman Instruments, Microtox ® has recognised as

the most popular aquatic bio assay due to its advantages as mentioned

previously. The test uses a non pathogenic naturally luminescent marine

baterium v. fischeri (Strain NRRL B -11117). It is a short term acute toxicity

test which determines the decrease in bioluminescence of the bacteria upon

exposure to toxic substances and express the toxicity as EC50 (Effective

Concentration : concentration which causes a 50% reduction in the level of

bioluminescence) with values measured at 5 , 15 , 30 minutes invervals

depending on the types of test used . (Qureshi et al , 1998).

The microtox test system (appendix 2) includes four toxicity tests: 1) The

microtox acute toxicity test, 2) The microtox solid phase toxicity test, 3) The

microtox chronic toxicity test and 4) the Mutatox Genotoxicity test (Johnson et

al ,1998).

30

2.17 Comparison of MicroTox with other bioassays:

The microtox test has been employed and evaluated with other toxicity

bioassays in a number of studies. A description of all studies which have

compared the microtox test with at least one other acute toxicity bioassay is out

of the scope of this work. A summary of correlation co-efficient of microtox test

results with three common acute bioassays (e.g. Fathead minnows, Rainbow

Trout and Daphnids) has been given in the table below ( Qureshi et al , 1998) .

Table 2.2: Summary of Microtox correlation coefficient with three most

common acute toxicity tests. ( Reproduced from Qureshi et al , 1998).

Bioassays Correlation

Coefficient(r)

Fathead Minnows 0.41,0.80,0.80,0.85,0.85

0.85,0.86,0.90,0.91,1.00

Rainbow Trout 0.74 , 0.81 , 0.84 , 0.85 , 0.89

Daphnids 0.80,0.85 , 0.85,0.85 ,0.85

0.85,0.86,0.87

As the correlation coefficient indicates the degree of relationship between the

two datasets , the good correlations of microtox test results with other test

indicates same or increased sensitivity of microtox compared to the three

bioassays (Qureshi et al , 1998).

31

CHAPTER 3

MATERIALS AND METHODS

3.1 Study Area and Sample Collection:

The study area is the River Brent which flows through north-west London. It is

a minor tributary to the River Thames and is 17.9 miles long. It is a highly

urbanised catchment and has gone through many periodic alterations for the

avoidance of flood. After second worldwar it was channelized in U-shaped

concrete channel and thus had lost almost all of its wild life and the

characteristics of a natural river. A river restoration project has been initiated in

1999 to restore the river in 2 km section of the river within Tokyngton Park

(Wembley , North London).

The river upstream of the park is surrounded by heavy vegetation and industrial

estates. The North circular road is located just down stream of the sampling

location and further up-stream is the Great Central Way(major London road)

and the Northern Line tube line. Mitchell Brook is the upstream tributary to the

site which drains water from nearby residential estates (St. Raphael’s). The

River collects diversified pollution loads due to treated and untreated sewage,

urban road runoff in it which carries a wide variety of pollutants within it(see

section 2.3). Surface sediment samples were collected from an area of deposited

sediment (sediment bar) located within the restored section of the river. Samples

were collected using a plastic scoop and transferred to plastic bags and were

frozen until analysed.

32

3.2 Sediment Drying:

The frozen samples were defrosted overnight at room temperature and dried in

oven at 50ºC for 24 hours period or until the cracks appeared in the samples.

After drying the crucibles containing sediment samples were allowed to cool in

the dessicator.

3.3 Sediment Sieving and sample storage:

The dried sediments were ground using a pestle and mortar and any large

surface debris were removed from the sample. Sediments were sieved to collect

the <1 mm sediment fraction. All sieved sediment samples were stored in

plastic bag at 4ºC.

3.4 Chemicals and Reagents:

Analytical grade chemicals and reagents (supplied by Fisher Ltd.) were used for

the extraction of metals. The required concentrations of chemicals (see Table

3.1) were prepared on a daily basis. Deionised water (obtained from Milli Q

filtration system) was used for dilution and the preparations of all solutions.

3.5 Laboratory Glass ware and Equipments:

All glassware and equipment used in the extraction of metals were washed in a

10% nitric acid bath, rinsed with deionised water. The equipments were dried in

an oven at 30ºC.

3.6 Nitric Acid digestion:

To determine the environmentally available metals, a strong acid digestion

method described as below was used for the metal release.

Two replicates of 10g sediment were divided in to subsamples of 5 g

sediment .The subsamples were transferred to 100ml teflon beakers to which 50

33

ml of concentrated nitric acid was added. Beakers were left on a sand bath at

80-110ºC overnight. Following digestion 1% nitric acid solution was added and

the samples were filtered using Whatman filter No.41 and the filtrate was

collected in 100ml volumetric flask. The volume of the filtrate was made up to

100 ml using 1% nitric acid and stored at 4ºC prior to analyse by ICP-OES.

3.6.1 Preparation of Sediment Residue samples for Microtox test :

The sediment residues from the subsamples of each replicate were then

transferred to centrifuge tube and washed with 64 ml of deionised water. The

samples were centrifuged at 3000 rpm for 30 min. After the centrifuge the

samples were collected in crucible and were dried at 50ºC for 24 hours period.

The dried samples were stored in plastic bags at 4ºC for microtox solid phase

test analysis.

3.7 Metal Speciation using single extractions:

To determine the speciation of metals in different forms associated with

sediments, single extractions were carried out using the chemicals and

conditions as described in Tessier Scheme (see Table 3.1 for details of the

scheme).

34

Table 3.1 : Operating conditions and Stages of Tessier Scheme

Stage Fraction Reagent (per gram of sediment

sample) Shaking Time and

temperature

1. Exchangeable 8 ml 1M MgCl2(pH 7) 1h at room temperature

2. Associated to

Carbonates 8 ml 1M NaOAc(pH 5) 5 h at room

temperature

3. Associated to Fe-Mn

Oxides(or reducible) 20 ml 0.04m NH2OH.HCl in 25% (v/v)

HOAc 6h at 96±3ºC with

occasional agitation

4. Bound to organic

matter (Oxidizable) 3 ml 0.02M HNO3 , 5 ml 30% H2O2

+

3 ml 30% H2O2

+

5 ml 3.2 M NH4OAc

3 h at 85±2ºC 2 h at 85±2ºC

30 min at room

temperature with

continous agitation

For the first three fractions of the Tessier Scheme, single extractions were

carried out on separate subsamples using the methodology described in

Tessier’s Scheme. For organic matter bound metals extractions the two step

method described by Tack et al was employed. In this method the sediment

samples were first treated for Fe-Mn oxides bound metal extraction and the

residue of the samples were then treated for organic matter bound metal

extraction using HNO3/H2O2 step.

Except for exchangeable and organic matter bound metal, the metal content

corresponding to carbonate and Fe-Mn Oxides bound metals were calculated by

subtracting the results obtained in the consecutive steps.

The extractions were carried out in 75 ml polyethylene tubes. As the volume of

the tubes was not sufficient to accumulate the amount of reagents required, two

replicates of 10g samples were divided in subsamples of 5g samples. Morever,

during the collection of sediment residue after extraction, some amount of

samples loss was observed. Thus to compensate the amount of sediment loss

35

during collection , for Fe-Mn Oxides and organic matter bound fractions two

replicates of 12 g sample were subdivided in aliquots of 3 g sample.

After single extractions the subsamples were centrifuged at 3000 rpm for 30

min. The supernatant liquid was separated from the solid phase and for the

adjacent subsample of each replicate, it was collected in a single volumetric

flask of either 100 ml or 250 ml size.

Bulk Sediment

Two replicates of 10g

sample

Two replicates of 10g

sample

Subdivided in aliquots of 5 g Subdivided in aliquots of 3

g

Treated for Exchangeable

and carbonate bound metal

Treated for Fe-Mn oxides

and organic matter bound

metals

Extractants stored and analyzed for metals and residues of sediments

dried at 50°C

Fig 3.1: Flow diagram of Single Extraction procedure

36

3.8 Inductively Coupled Plasma –Optical Emission Spectrometry (ICP-

OES):

Samples were analysed for eight heavy metals (Cd, Cr, Cu, Pb, Fe, Mn, Ni, Zn)

using Perkin Elmer Plasma 40 ICP-OES instrument. The details of the

procedure are given as below:

3.8.1 Stock Solutions and Standards Preparations:

To prepare standards for each metal, from 1000ppm stock solutions of all 8

metals , 10 ml of the stock solution was pipetted out into 100ml flask to prepare

a stock solution of 100ppm concentration. From these 100 ppm stock solutions

1ml , 0.5 ml and 0.1 ml solution of each metal were transferred into 100ml flask

and made up to the required mark to obtain the multi element standards of

1000ppb , 500ppb and 100 ppb for the metals.

To obtain matrix matched calibration curves, standard solutions were prepared

using the same chemical/reagents present in the analyte (e.g. for exchangeable

metal analytes , standards were prepared using MgCl2). Calibration blanks were

also prepared using the same chemicals/reagents as the analyte.

3.8.2 Calibration of instrument:

To calibrate the instrument for measurement of the eight heavy metals , the

elements were selected and by running 1000ppb standard solution , the

wavelength of each element was calibrated and the measurement of the

emission was adjusted at the peak of the emission line . Using an artificial

intelligence algorithm, the background corrections were calculated by the

computer software automatically and these background corrections were

subtracted from the total emission at the wavelength of measurement for each

element. The wavelengths and background correction details are summarised in

37

Table 3.2. Once the wavelength calibration of all metals was completed, the

standards including blank were run to obtain the calibration curve and the

emissions for each element were recorded by the computer.

3.8.3 Analysis of Samples

Samples were run in the instrument to determine the concentrations of elements

in it. Between samples deionised water blank was run to reduce the chance of

carry over from the previous sample.Where concentrations exceeded the highest

standard, appropriate dilutions were made.The concentrations in the analytes

were obtained in µ g/l .

Table 3.2 Operating Conditions and wavelengths for ICP-OES

Element Wavelength

(nm)

Lower

Background

Correction

(nm)

Upper

Background

Correction

(nm)

PMT

(v)

Element

time (ms)

Spectral

time (ms)

Read

Delay

(s)

Cr 205.552 -0.041 0.047 701 100 32 20

Zn 213.856 -0.053 0.034 600 100 32 20

Cd 241.438 -0.083 0.028 701 100 32 20

Pb 220.355 -0.044 0.032 701 100 32 20

Ni 221.656 -0.036 0.042 701 100 32 20

Fe 238.204 -0.052 0.039 600 100 32 20

Cu 324.754 -0.050 0.036 600 100 32 20

Mn 257.610 -0.050 0.098 701 100 32 20

38

3.8.4 Calculations:

From the concentrations obtained in analytes using ICP-AES, the final

concentrations of the metals per gram of sediment(dry weight) were calculated

as follows :

Final concentration in analyte (µ g/l) = ICP conc. In sample (µ g/l) X DF

Where DF ( Dilution Factor) = final volume of dilution sample analysed in

ICP(ml)/ volume of sample taken for dilution(ml)

Conc. In sediment sample (µ g/g) = (final conc. X total volume of analyte) /

(sediment weight X 1000)

3.9Toxicity Analysis of Sediments:

The toxicity analysis of the bulk sediment and residue sediment samples from

each metal extraction step was carried out using Microtox Solid Phase Test

(SPT) protocol. Microtox analyzer (model 500) connected to Microtox data

collection and reduction system through an IBM compatible computer was used

to generate and process the data.

3.9.1 Reagent , Solutions and Accessories :

The Microtox SPT toxicity tests were carried out reconstituting a freeze dried

strain of marine bacterium v. fischeri ( NRRL number B-11177). This reagent

approximately contains 108

bacteria and 2% NaCl in it. The microtox diluent, a

non toxic solution to test organisms which contains 2% NaCl was used to

reconstitute the bacteria and the same solution was used to prepare serial

dilutions for phenol standard test. For solid phase test, solid phase diluent was

used for serial dilutions of the sediment suspension solutions. The test were

carried out using cuvettes supplied by Microbic Ltd.(Carlsbad , CA) , Solid

phase tubes and filter columns. Micro pipetters of 0-20µ l , 0-1000µ l and 1-5 ml

39

were used to prepare the dilutions and a water bath at 15ºC was used for the

incubation of the bacteria with solutions.

3.9.2. Microtox Analyzer:

The SDI model 500 analyzer is a dual purpose instrument which serves both as

an incubator and luminometer. The incubation is carried out at two

temperatures : 1) the thirty cuvettes : located on the luminometer as rows A

through F and columns 1 to 5 (used for test samples) are incubated at 15°C

and 2) the reagent well : used for storing one stock culture cuvette of luminous

bateria is incubated at 5°C (Johnson et al , 2005).

The luminometer contains a photomultiplier tube that measures the light

emission from bioluminescence bacteria. The analyser was operated under

standard working conditions using a PC containing Microtox Omni software

package.

3.9.3. Phenol Standard Test:

A reference test was conducted using phenol as a reference toxicant. To prepare

the phenol standard approximately 0.050 g of crystalline phenol was added to

volumetric flask of 500 ml and diluent was added up to the mark. The solution

was mixed well by inverting the flask several times and it was covered with

aluminium foil to protect the phenol standard from light. This phenol standard

has a (EC50)5min of 13-26 mg/lit. A phenol standard was run prior each day’s

analysis.

3.9.4 Solid Phase Test :

The sediment residues from the single extractions were washed with deionised

water and centrifuged at 3000 rpm for 30 min. The supernatant was then

discarded and the sediment residue for each replicate was collected in crucible

40

and dried at 50ºC for 24 hours. After drying the sediment residue samples were

stored in plastic bags at 4ºC for MicroTox analysis.

To analyze the toxicity of sediment samples using solid phase test, 7g of

sediment sample was weighed carefully. To this sample 35 ml of solid phase

diluent was added and a sediment suspension was prepared in a disposable

beaker. This sediment was stirred using magnetic stirrer for 10 min to allow

homogenized mixing .1500µ L of sample suspension was transferred to a series

of solid phase tubes and twelve 1:2 serial dilutions of the suspension were

prepared including two controls. Both the controls and serial dilutions were

prepared in replicates .Dilutions and controls were prepared in solid phase tubes

placed in a water bath at 15ºC. 20µ L of reconstituted bacteria were transferred

to each solid phase tube and bacteria were incubated in the tubes for 20 minutes.

Filter columns were inserted and the bacteria along with solution were filtered

out. From this filtered solution 500µ L of solution was transferred to cuvettes

placed in the microtox analyzer and luminescence readings were obtained to

generate EC50 values.

41

CHAPTER 4

RESULTS AND DISCUSSION

4.1 Total Metal concentrations:

The results of total metal concentration (defined as metals obtained using nitric

acid digestion) are presented in Table 4.1

Table 4.1 Total metal concentration in sediments

Metal Mean of samples (µg/g) ±SD (Standard deviation) Cd 3.39 0.36 Cr 15.20 5.63 Cu 115.10 10.72 Fe 17290 5343 Mn 358.20 27.50 Ni 11050 802 Zn 521.5 43.8

Pb 244.0 61.2

(Note: Sample size n=2 , Results are expressed as mean of samples).

Al most all metals were extracted above the detection limit of the ICP-OES

instrument. The concentrations of metals in the both sediment samples ranged

from 3.01 µ g/g to 3.9 µ g/g for Cd , 9.0 µ g/g to 23.00 µ g/g for Cr , 102µ g/g to

130 µ g/g for Cu , 11850 µ g/g to 23900 µ g/g for Fe , 328 µ g/g to 397µ g/g for

Mn , 9900 µ g/g to 12400 µ g/g for Ni , 167 µ g/g to 332 µ g/g for Pb and for Zn

465 µ g/g to 574 µ g/g. In statistical analysis of data , standard deviation of the

finite population is used to measure the variability of the data from the mean of

the population and along with mean it is reported .It provides useful

information about the degree of variability of two data sets with similar means

However , in case of variables which are measured on incomparable scales

relative standard deviation which is the ratio of standard deviation to mean , is

calculated to examine the variability of the data set(Moore and Cobby , 1998).

42

The relative standard deviations (RSD) for Cd , Cu , Mn , Ni , Zn were 10.61% ,

9.32 % , 7.68 % , 7.26% and 8.39% respectively . While for Cr, Fe and Pb the

relative standard deviations were 37.06% , 30.90% and 25.10% respectively.

The relative standard deviation for the five metals ( Cd, Cu, Mn, Ni,Zn) were

found within acceptable range while for Cr , Fe and Pb RSD values indicates

high variability in the measurements of the metals in the sediment samples. This

variability can be attributed to many factors which include a) difficulties in

obtaining representative samples, b) contamination of instrument and apparatus

used in the analysis due to presence of elements in the atmosphere and c)

impartial digestion of particular elements from the sediment matrices due to

certain forms of metals which are difficult to put in solution (Gaines ,2003).

As the sediments are collected from highly polluted urbanised area which has

varying sources and input of pollutants to the river course, there are chances of

wide variations in sediment metal concentrations and thus obtaining a

representative sample might be a principal factor leading towards high

variability in the results.

4.1.1 Relative abundance to metals:

The relative abundance of metals in increasing order is Cd< Cr< Cu < Pb < Mn

< Zn < Ni < Fe with Cd the least abundant metal and Fe the most.The range of

concentration and sequence of relative abundance of metals in the sediment of

Brent river at the sampling location reveals similar pattern observed in the urban

rivers in European Union and UK(see Table 2.1). However, straight

comparisons with different studies may be confused because of the variation in

digestion protocols and strength of pollution releases into the rivers (De Miguel

et al 2005). Moreover, the sediment typology, river hydrodynamic conditions

and geographical conditions of the river catchments highly influence the

concentration of metals in the river sediments.

43

4.1.2 Comparison with Sediment Quality Guide lines(SQGs) : As sediment

quality guidelines can provide scientific benchmarks , or reference points for

appraising the capability of scrutinizing adverse biological effects in aquatic

systems(CCME ,2001) , a relative comparison of the chemical concentration of

the pollutant with the guidelines is recommended in screening level risk

assessment. However for metals in sediment, various guidelines are available

which differ in their method of deriving sediment quality assessment values. To

make a good comparison with selected guidelines, a comparative analysis of

metal concentrations in the sediment samples with selected guidelines values

has been presented in table 4.2.

Table 4.2 Comparative analysis of metal concentrations with reference

values for fresh water sediments (units in µg/g):

Element US DOE a Ontario MOEb Dutch Intervention

values c

Canadian SQG

d Metal

concentration

in the

sediment

samples

TEC PEC NEC Low Severe Target

Values

Intervention

Values

ISQG

L

PEL

Cd 0.592 11.7 41.1 0.6 10 0.8 12 0.6 3.5 3.39

Cr 56 159 312 26 110 100 380 37.3 90.0 15.20

Cu 28 77 54.8 16 110 36 190 35.7 197 115.10

Fe --- --- 2(%) 4(%) 85 530 -- -- 17290

Mn 1673 1081 819 460 1100 -- -- -- -- 358.20

Ni 39.6 38.5 37.9 16 75 35 210 -- -- 11050

Zn 159 1532 541 120 820 --- --- 123 315 521.5

Pb 34.2 396 68.7 31 250 85 530 35 91.3 244

Note : 1) TEL : Threshold Effect Level concentration ; 2) PEC : Probable Effect Level concentration

3) NEC : No Observed Effect concentration ; 4) Low : Lowest Effect Level

5) Severe : Severe Effect Level ; 6) ISQGL : Interim Sediment Quality Guideline

7) PEL : Probable Effect Level

a. Jones et al (1997) ; b. Ontario Ministry of Environment and Energy(1998) ; c Dutch Ministry of

Environment ; d. Environment Canada (2002) ;

44

While comparing the metal concentrations with Sediment Quality Guidelines

(SQGs) set by US DOE , it is found that with the exception of Cr and Mn, all

other metal concentrations exceeded the Threshold Effect concentrations (TEC) .

The concentration of Cu and Ni exceeded Probable Effect Level Concentration

(PEL) and High No Effect Concentrations (NEC) which indicate that adverse

effects are likely to occur on the aquatic ecosystem of river sediments due to

these metals. The concentration of Pb was also found higher than NEC

concentration indicating a risk of adverse effects in the sediments.

The comparison of sediment metal concentrations with Ontario’s guidelines

also followed similar pattern. Except for Mn and Cr for all metals Lowest Effect

Level concentrations (Low) were exceeded while for Cu and Ni Severe Effect

Level concentration(Severe) were also exceeded . This comparison indicates

that toxic effects might become apparent and might have affected the benthic

organisms in the sediments due to Cu and Ni.

When comparing with Dutch Intervention values, it was found that all metal

concentrations were higher than Dutch Target Values except for Cr metal

indicating a risk of metal pollution. The concentration of Ni was found far

higher than the Dutch Intervention values (11050 µ g/g in sediments compared

to 210 µ g/g Intervention values). For Fe also similar trend was observed while

comparing with Dutch Intervention values but Iron is not considered as

potentially toxic element. The concentrations of Cu and Pb in the sediments

were close to the Dutch Intervention values indicating possible pollution of

sediments due these metals. Thus, according to Dutch intervention values

sediments were found to be polluted due to high concentrations of Cu,Fe , Ni

and Pb. For Mn and Zn the comparison with Dutch guidelines could not be

made as no target and intervention values are available for these metals.

45

The Interim Sediment Quality Guideline Level (ISQGL) set in Canadian SQGs

were exceeded for Cd , Cu , Zn , Pb and for Cd , Zn and Pb even the Probable

Effect Level(PEL) were also exceeded indicating possible adverse effect on

ecosystem life might occur in sediments due to these elements.

Thus, comparison with various sediment quality guidelines indicates that for

Cu ,Ni ,Pb ,Cd and Zn the higher threshold levels are exceeded for one of the

guidelines and thus there are chances that adverse effects are likely to occur on

aquatic ecosystems associated with river sediments due to these metals. While

the concentrations of Cr and Mn were within the guideline limits posing no

possible or severe threat due to these metals and Fe is not considered as toxic

metal thus the higher concentration of Fe might not pose any threat to the

aquatic ecosystems.

4.1.3 Association of metals and Source Identification:

In order to understand behaviour, origin and transport of metals within riverine

environment, correlation statistical analysis is applied to the total metal

concentrations (Farkas et al , 2007).Various researchers ( Farkas et al 2007 ;

Camusso et al 2002 ; Zheng et al 2008; Yalcin et al 2008 ) have used correlation

analysis to identify the associations of metals and their relations in the

sediments.

Correlation co-efficient is the estimation of the intensity of relationship

between two or more variables (Ott , 1988). The value of correlation coefficient

lies between -1 to +1. The positive values indicate that one variable tends to

increase while the other increases. On the other hand negative values indicate

that one variable tends to decrease while the other variable increases. In

statistical analysis for environmental data sets, Pearson’s correlation coefficient

and Spearman’s Rank coefficient are widely used. Pearson’s correlation

46

Perc

ent

coefficient is used for normal data. However when the data is non-normal , the

approach is to rank the data set and then on the ranked data set Pearson’s

correlation coefficient is calculated which is then called Spearman’s Rank

Correlation Coefficient .

To estimate the normality of data, a probability test was conducted on the data

sets and the probability plot of the total metal concentrations is plotted in the

following figure (Fig. 4.1).

Fig. 4.1 : Probability plot of Total Metal Concentrations

Normality Graphs for Total Metal concentrations

Normal - 95% CI

99

95

90

80

70

60

50

40

30

20

10

5

1

0 10000

20000

30000

Metal

C d

C r

C u

F e

Mn

Ni

P b

Zn

40000

Mean StDev N A D P

3.396 0.3635 10 0.481 0.178

15.2 5.633 10 0.562 0.109

115.1 10.72 10 0.563 0.108

17290 5343 10 1.197 <0.005

358.2 27.50 10 0.652 0.062

11050 801.7 10 0.247 0.673

244 61.23 10 0.414 0.269

521.5 43.75 10 0.605 0.083

Mass of metal in sedi(microg/g)

Looking at the P – values, it is evident that the data is loosely normal for Cd, Cr,

Cu, Pb and certainly non-normal for Fe(p Value < 0.005). While for Nickel the

data has been emerged normal. The p values for Managanese (0.062) and Zinc

(0.083) also provide weak evidence against the data to be considered as normal.

Thus, considering the data to be non-normal, to evaluate the relationship

between the metal concentrations in the sediment spearman’s rank correlation

47

on the metal concentrations was performed and the correlation coefficient

matrix is presented in Table 4.3.

Table 4.3 Spearman’s Rank Correlation Matrix for metal concentrations in

sediment (n=10)

Cd Cr Cu Fe Mn Ni Pb

Cr 0.134

Cu 0.200 0.372

Fe 0.442 0.305 0.794

Mn 0.267 0.309 0.979 0.796

Ni 0.274 -0.107 0.754 0.650 0.768

Pb 0.636 0.341 0.624 0.782 0.596 0.541

Zn 0.103 0.245 0.839 0.802 0.796 0.646 0.723

Cell Contents: Spearman’s Rank correlation coefficient

Depending upon the calculated values of correlation coefficients , Moore and

Cobby (1998) suggested that a correlation coefficient value < 0.6021 provides

no meaningful evidence of any association. The authors further suggested that a

coefficient in the range of 0.6021 to 0.7348 would provide some evidence of

association while a coefficient in the range between 0.7348 and above would

suggest a strong association.

Thus , based upon above range of classification , three distinct groups of metals

having strong associations can be identified as :1) Cu-Fe-Mn-Zn (r2

range

0.796-0.979) , 2) Ni-Cu-Mn (r2

range 0.754- 0.979) and 3) Pb-Fe-Zn (r2

range

from 0.723-0.802)and thus suggesting similar sources and behaviour patterns

for the associations of these metals. The correlation coefficient of 0.636

48

between Cd and Pb is significant suggesting some relationship between the two

metals indicating similar sources for these two metals. With this exception poor

correlation coefficients of Cd and Cr were found with other metals indicating

these metals were derived in the sediments from different sources compared to

other metals.

As it is well recognised that metal pollution has a diffuse (non-point source)

nature and due to the complex nature of association of metals, it is difficult to

characterize the sources of individual metals or group of metals from the above

correlation analysis. The distinct groups of associations indicates that metals in

the sediments might have been derived from multiple sources within the urban

environment which include CSOs, un treated waste water discharges , urban

road run-off, roof run-off , combined and separate residential sewage flows and

industrial waste water released in to the river (Thevenot et al , 2007). Moreover,

automotive pollution is considered as one of the major source of Pb, Zn,Cu and

Cd pollution in the urban aquatic environment (Rose and Shea , 2007). The

correlations between Pb,Zn and Cu and between Pb and Cd also support that the

automotive pollution might be a major source of pollution in the river sediments.

The usage of River Brent as a receiver for treated and untreated discharges and

the proximity of the sampling location to motorway, residential and industrial

areas also support the source identification analysis made above.

4.2 Metal Fractionation using single extractions:

The results of metal concentrations obtained using single extraction steps as

described in the Tessier Scheme are given in the table 4.4.

49

Table 4.4 Metal Concentrations Obtained using Single Extractions (Means

± S.D.)

Metal Extraction Step

MgCl2

(A)

NaOAc

(B)

NH2OH.HCl

(C)

NH2OH.HCl +

H2O2/HNO3

(D)

Mean

(µg/g)

±SD Mean

(µg/g)

±SD Mean

(µg/g)

±SD Mean

(µg/g)

±SD

Cd 0.22 0.10 0.47 0.01 1.44 0.28 0.05 0.04

Cr 0.29 0.14 ND -- 2.48 1.05 3.17 0.65

Cu 1.78 0.43 2.10 0.41 5.32 0.15 62.92 1.84

Fe 2.05 0.86 9.6 1.7 3006.94 595 249.38 20.87

Mn 52.41 6.42 81.83 5.66 647.08 29.25 18.88 0.66

Ni 8.80 0.79 16.88 3.04 3950 1475 194.58 21.34

Pb 1.18 1.24 8.33 2.65 647.7 141.3 117.60 19.93

Zn 11.01 1.54 57.92 4.53 1325.4 68.5 62.34 2.5

All metals were detected in each fraction except Chromium in carbonate

fraction. Certain difficulties were observed while quantifying the metals

extracted with NaOAc. Each time the analyte sample was introduced into ICP

instrument, the plasma torch was shifted to ‘Switch-OFF’ mode which made the

analysis difficult.

This problem of ‘Switching-OFF’ of plasma was associated with the matrix

effect of NaOAc which caused change in the plasma operating conditions. As

sodium has low ionization potential, analytes containing sodium can originate

matrix effect inside the plasma and/or in the liquid sample introduction system.

The existence of sodium can alter the plasma local temperatures and electronic

density as well as the spatial distribution of the emitting species (Maestre etl al ,

50

2002). Similar types of problems are thought to have arosed during the current

analysis due to sodium metal and subsequent malfunctioning nebulizer.

To address this issue, samples were analysed using Flame Atomic Absorption

Spectrometry (FAAS) but the results obtained with AAS were not compatible

due to non-linearity of the calibration curves. However, after one month when

the ICP instrument was serviced, the samples were again analysed in the ICP

and an attempt was made to quantify the metals. But during the trial and error

runs of the samples in ICP and AAS much amount of sample was lost and in

diluted samples Chromium was found below detection limits.

In the above table (Table 4.4), the amount of metal extracted with MgCl2

represents the ‘exchangeable’ metals. To calculate the amount of ‘carbonate

bound’ bound metals, the metals extracted with MgCl2 were subtracted from the

metals extracted with NaOAc. Similarly to obtain the amount of metal

associated with ‘Fe-Mn Oxides (defined as reducible fraction)’ , the metal

concentrations obtained using NaOAc extractions were subtracted from the

NH2OH.HCl extracted metal concentrations. For the H2O2/HNO3 step, the

extraction was carried out on the residue sediments of the NH2OH.HCl

extraction step , therefore the amount of metal obtained using this two step

extraction procedure is taken to represent the ‘organic matter bound’ or

‘oxidisable’ fraction of metals . The results of metal concentration obtained in

each fraction are presented in Table 4.5.

51

Table 4.5 Metal Fractions obtained from single extractions (Means ± S.D.

of 2 replicates)

Metal Extraction Step Approximate

Sum total of

metal

extracted in

each step

Exchangeable

(A)

Carbonate

bound

(B-A)

Fe-Mn oxides

bound

(C-B)

Organic

Matter bound

Mean

(µg/g)

±SD Mean

(µg/g)

±SD Mean

(µg/g)

±SD Mean

(µg/g)

±SD (µg/g)

Cd 0.22 0.10 0.25 0.002 1.22 0.02 0.05 0.04 1.74

Cr 0.29 0.14 ND ND 2.18 0.95 3.17 0.65 5.64

Cu 1.78 0.43 0.32 0.065 3.23 0.58 62.92 1.84 68.25

Fe 2.05 0.86 7.54 0.46 2997 559 249.38 20.87 3255.97

Mn 52.41 6.42 29.42 2.01 565.25 7.42 18.88 0.66 665.96

Ni 8.80 0.79 8.14 0.43 3933 1944 194.58 21.34 4144.52

Pb 1.18 1.24 8.82 1.34 637.7 118.6 117.60 19.93 765.3

Zn 11.01 1.54 46.91 2 1267.5 0.59 62.34 2.5 1387.76

4.2.1 Partitioning Patterns of Metals in different fractions:

Partitioning of the eight metals in all four operationally defined fractions is

given in the fig.4.2 below. Each fraction is presented as the percentage of the

sum total of all fractions.

52

Mean

of

% c

on

centratio

n

Fig. 4.2 Partitioning Pattern of Metals in different fractions

Partitioning Patterns of Elements

100

80

60

40

20

F raction

O rganic Matter

F e-Mn O xides

Exchangeable

C arbonate

0

Metal Cd Cr

Cu Fe Mn Ni

Pb Zn

From the partitioning pattern, it is evident that Cd is the only metal associated

with exchangeable and carbonate fractions in higher amount compared to other

metals. As these fractions are considered as weakly bound and thus might

become bioavailable rapidly (Jain , 2004). But as the amount of Cd available as

in these fractions is below the guideline values given in the table 4.2, it can be

concluded that Cd might not pose any harm to the aquatic life in the river

sediments.

The fractionation profile of Cr indicates that the metal is mainly partitioned

between Fe-Mn Oxides and Organic matter bound phase. Cu shows the highest

association with Organic matter with 92% of metal extracted in this fraction.

The association of Cr with organic matter can be attributed to the sewage

outfalls and industrial discharge. In a speciation study for Thames river estuary

O’ Reilly Weise et al (1997) has found similar association of Cr with organic

matter bound fraction and the pollution of estuary through sewage outfalls and

53

various industrial sewage sources. The higher proportion of Cu with organic

matter also can be explained with the sewage discharges in the River Brent

which carries organic matter in it favouring the intake of Copper into organic

matter bound fraction through formation of organic complexes of this element.

Baruah et al (1996) and Morillo et al (2002) have found similar results for

Copper association with organic matter bound fraction in river and estuary

sediments receiving high amount of sewage discharge.

From the partitioning pattern it is evident that the Fe-Mn oxide fraction is the

dominant fraction carrying maximum amount of metals in it except for

Chromium and Copper .Bird et al (2005) suggested that metals derived from

anthropogenic sources are largely partitioned in non-residual phases in the

sediments and thus the associations of the metals with Fe-Mn oxides bound and

organic matter (for Cr, Cu , Pb) fractions indicates anthropogenic pollution of

sediment. These findings are in agreement with the parallel research carried out

in various European rivers polluted with heavy metals (e.g. Farkas et al 2007;

Klavins et al 2000, Filgueiras et al 2004 and Relic et al 2005).The speciation

pattern of metals strongly indicates that Fe-Mn Oxides are acting as major sinks

of metals and thus contain most of the metal within this fraction. However,

depending upon the redox potential and pH changes this fraction might become

mobile thus bio available to aquatic biota (Jain ,2004).

4.2.2 Comparison of sum total of fractions with total metal digestion:

While comparing the sum total of metals extracted in the four stages of

extractions with nitric acid digestion, it was found that all most all metals except

Mn, Pb and Zn were extracted in significant higher amount in nitric acid

digestion (see Table 4.1 and 4.5).These differences can be accounted to the fact

that the nitric acid digestion is not a complete digestion procedure. Similar

results for Pb and Cu were observed by Tack et al(1996) for aqua regia

54

digestion and sum total of single extraction obtained using Tessier Scheme. In

another experiment Sastre et al (2002) compared aqua regia and nitric acid

digestion for total metal analysis of Cd, Cu, Zn and Pb and he observed that

nitric acid digestion could led to underestimation of Zn in the samples. However,

he concluded that for samples containing higher organic matter nitric acid

digestion can be an alternative for aqua regia digestion but for samples

containing lower organic matter and carbonate content there are chances of

underestimation or over estimation of metal contents in the samples. Thus, the

low organic matter and carbonate content of the sediments might have caused

the discrepancies in the metal results obtained using sequential extractions and

nitric acid digestion.

4.3 Sediment Toxicity Results:

The results of the Microtox Solid Phase Test (SPT) expressed as EC50 values

for unprocessed sediment samples are summarised in Table 4.6.

Table 4.6 Microtox Solid Phase Test (SPT) Results for Unprocessed

Sediment samples

Parameter Replicate1 Replicate2

EC50 ( g/l ) 6.585 19.090

R2

Value 0.9058 0.9561

Average Control

Value

19.07 29.17

95% confidence

range (g/l)

4.239 to 10.230 15.140 to 24.060

The results of all reference toxicity tests conducted using Phenol as a reference

toxicant were found within the limits of IC50 5min 13-26 mg/l which indicates

that correct test protocol was followed and the system was working

55

satisfactorily. As Doe et al (2005) recommended R2

value of ≥ 0.9 for Solid

Phase Test(SPT) results , We can conclude that the test results of both the

replicates were satisfactory.

The mean EC50 value of the two sediment replicate was 12.84 g/l with a

standard deviation of 8.84. The high standard deviation indicates significant

variation in the toxicity results of sediment sample obtained using SPT.

For toxicity analysis of sediments using SPT, sediment composition has been

found to be the most influential factor affecting the SPT results and many

researchers (Benton et al 1995; Ringwood et al 1997) have reported false

positive and negative results for SPT due to variation in sediment particle

composition. Ringwood et al (1997) has observed loss of light output due to

adherence of bacteria to silt particles indicating higher toxicity in the sediments.

Therefore there are chances that the difference in the toxicity results might have

been originated from the difference in the sediment composition of the two

replicates and thus problem of obtaining a representative sample might have

caused the possible variations in the toxicity results of the sediment samples.

4.3.1 Sediment Classification on the basis of Toxicity Results:

To classify the sediment samples on the basis of toxicity results obtained in

Solid Phase Test (SPT) , Kwan and Dutka (1995) suggested classification of the

sediments as presented in Table 4.7.

56

Table 4.7 Sediment toxicity classification (Adopted from Kwan and Dutka

(1995)

EC50 values (%of sediment sample) Rating

< 0.5 % Very toxic

>0.5 % but ≤ 1% Moderately toxic

>1 % Non toxic

Comparing the unprocessed sediment samples at mean EC50 values of 12.84 g/l

(which is 1.284% of the sediment sample) with the above scheme, the sediment

sample can be categorised as non-toxic. In comparing the individual EC50

values of the sediment replicates , replicate1 can be categorised as moderately

toxic (an EC50 value of 6.585 g/l (0.658%) of sediment sample) and replicate2

can be categorised as non toxic (an EC50 value of 19.090 g/l (1.9 %) of

sediment sample).

Another classification method used by Environment Canada as described by

Doe et al(2005) , suggest that if EC50 values are <1000mg/l then the sample

should be considered as toxic . While for the samples having EC50 values

≥1000 mg/l the guidelines suggest that it should be compared with a clean

reference sample and if the test sample EC50 values are 50% less than the clean

reference sample then the test sample can be considered as toxic sample.

However, as a reference sediment sample was not available, the second

guideline could not be applied to this sediment toxicity study.

Using the various approaches described above, it can be concluded that the

unprocessed sediment samples assessed within this study can be considered

moderately toxic to non toxic.

57

4.4 Toxicity Results of the Sediment Residue of Single Extractions:

The results of Solid Phase Test (SPT) carried out on the sediment residue of

single extractions are presented in Table 4.7.

Table 4.8: Microtox Solid Phase Results of Sediment residue after Single

Extractions.

Parameter Extraction Step

MgCl2

(Exchangeable

)

NaOAc

(acid-soluble)

NH2OH.HCl

(reducible)

NH2OH.HCl

+H2O2/HNO3

(oxidizable)

HNO3

(total)

Rep1 Rep2 Rep1 Rep2 Rep1 Rep2 Rep1 Rep2 Rep1 Rep2

EC50 ( g/l ) 2.990 4.877 7.016 10.13

0

2.442 2.505 22.64

0

3.463 7.882 7.223

Mean EC50

(g/l) , ±S.D.

3.93 g/l , ± 1.33 8.57 g/l , ± 2.2 2.47 g/l , ± 0.04 N/A 7.55 g/l , ± 0.46

R2

Value 0.9399 0.823 0.888 0.902 0.917 0.902 0.220 0.835 0.858 0.786

Average

Control

Value

55.99 30.48 22.30 37.44 48.17 19.36 32.06 29.99 14.32 37.07

95%

confidence

range (g/lit)

2.250

to

3.975

3.104

to

7.661

4.792

to

10.27

7.211

to

14.23

1.875

to

3.181

1.848

to

3.397

6.122

to

83.71

2.004

to

5.984

5.701

to

10.90

4.534

to

11.51

Except for sediment residue replicate1 of oxidisable metal extracted using

H2O2/HNO3, for all other sediment residue samples, the R2

values obtained were

reasonable though not meeting the criteria of R2≥0.90 for all replicates.The R

2

value obtained for ‘oxidizable’ metal extracted sediment residue was 0.2207

which cannot be accepted as lower R2

value represents manual errors in

conducting the test and thus the EC50 values obtained can not be considered as

a valid estimation of toxicity of the sample.

58

4.4.1 Evaluation of change in the Toxicity after Extraction of Metals:

In sequential extraction schemes, reagents applied at each stage extract out

metals associated with particular metal binding fraction which may impose

toxicity on the aquatic environment. Thus, after each single extraction step as

metals associated with each fraction were removed, a reduction in the toxicity

of the sediment residue could be anticipated.

However, comparing the mean EC50 values of sediment residue with the mean

EC50 values of unprocessed sediments samples, a reverse trend was observed.

The comparison of mean EC50 value of MgCl2 treated sediment residue (3.83

g/l) with unprocessed sediment EC50 values (12.84 g/l) indicated an increase in

toxicity of the residue sediment.The comparison of mean EC50 values of

NaOAc treated sediment residue(8.57 g/l) also revealed an increase in the

toxicity of sediment residue after extraction process. Similarly the comparison

of EC50 values of NH2OH.HCl (2.4735 g/l) , H2O2/HNO3(3.463 g/l) and HNO3

(7.553 g/l) treated sediment residue also showed an increase in the toxicity of

sediment residue after the extraction process. The box plot (Fig.4.3) of the

EC50 values of unprocessed sediment and residue sediment samples after each

extraction step showed the same trend found while comparing the mean EC50

values of sediment residues with the EC50 values of unprocessed sediment

sample.The lower locations of mean lines of EC50 values for sediment residues

compared to EC50 values of unprocessed sediment indicates an increase in the

toxicity of the sediment residue samples. The box plot also reveals that the

increase in the toxicity of MgCl2 and NH2OH.HCl treated sediment residue is

quite higher compared to other sediment residues treated with NaOAc and

HNO3.

59

EC50

Va

lue

E

C5

0 v

alu

e(g

/lit

)

Fig.4.3 Box plot of EC50 values of unprocessed sediment sample and sediment residues after

each single extraction.

B o x p l o t o f E c 5 0 v a l ue s o f b a r e s e di me nt a nd s e d i me nt r e s i d ue s

2 0

1 5

1 0

5

0

M g C l2

Na O A c

NH2 O H.HC l

HNO 3

Ba r e

Fig.4.4 Individual Value plot of EC values of unprocessed sediment and sediment

residues after each single extraction step.

20

15

10

5

0

Rep

Individual Value Plot of EC50 Value

Treatment

60

Furthermore , as there was a large difference between the EC50 value of two

replicates of unprocessed sediment sample ,it would worthwhile to compare the

toxicity of sediment residue samples after single extractions with the replicates

of unprocessed sediment individually using individual value plot (Fig.4.4) .

Looking at the individual value plot, it is evident that toxicity of all sediment

residues is increased compared to rep2 of unprocessed sediment. The

comparison of toxicity values of MgCl2, NH2OH.HCl and NH2OH.HCl+H2O2

treated sediment residue to toxicity value of rep1 of unprocessed sediment

indicates an increase in the toxicity. While HNO3 and NaOAc treated sediment

residue shows a marginal decrease in the toxicity compared to toxicity of rep1.

In statistical analysis in order to assess the significance of the difference

between the three or more samples, analysis of variance (ANOVA) is used. It is

a single test of significance which helps to minimize the Type-I error rate which

otherwise might be high in case of increasing number of two sample t-tests

while comparing more than three sample means (Le Blanc , 2004). The

randomized data, normality assumption and equal variance assumption are

fundamental assumptions for ANOVA. However, in case of non parametric data

sets a non-parametric Kruskal-Wallis (KW) test can be performed and this test

is less sensitive to non equal variances than F-test used for ANOVA. This test

procedure tests the hypothesis that the population medians are equal versus not

equal (Le Blanc , 2004).

The probability plot of EC50 value data of all sediment samples is presented in

Fig.4.5.

61

Mean 6.746 StDev 4.799 N 11 A D 0.741 P-Value 0.037

Perc

ent

Fig. 4.5 Normality Graph of EC50 values of sediments

Probability Plot of EC50 Value

Normal

99

95

90

80

70

60

50

40

30

20

10

5

1

-5 0 5 10

15 20

EC50 Value

The p-value (0.037) of normality test of the data set indicates that the data is

non-normal as the p –value is less than 0.05. Thus, in order to assess the

significance of difference between the population means of EC50 values of

sediment samples, KW test was performed and the results of the test are

presented in table 4.9.

The test procedure of KW test is similar to Mann-Whitney test, the data are first

ranked together and then the calculations are carried out on the ranked data to

produce necessary statistical results ( Siegel and Morgan , 1996).

62

Table 4.9 Kruskal-Wallis test results on EC50 values of sediment samples.

Treatment N (sample size) Median Rank Z

HNO3 2 7.553 8.5 1.18

MgCl2 2 3.934 4.0 -0.94

NaOAc 2 8.573 8.5 1.18

NH2OH.HCl 2 2.474 1.5 -2.12

NH2OH.HCl+

H2O2 1 3.463 4.0 -0.63

Unprocessed 2 12.838 8.5 1.18

Overall 11 6.0

H = 8.18 , DF = 5 , P = 0.146

Note : Note : 1)Unprocessed :Unprocessed sediment

2)MgCl2 : MgCl2 treated sediment residue

3)NaOAc : NaOAc treated sediment residue

4) H202/HNO3 : H202/HNO3 treated sediment residue

5) HNO3 : HNO3 treated sediment residue

6) H = H- statistics of Kruskal-Wallis test

7) DF = Degrees of freedom

8) P = P value of Kruskal-Wallis test.

The P-value (0.146) of the test suggests that there is insufficient evidence that

the population medians of the EC50 values of different sediment samples differ

statistically. Though the statistical test results are not significant the observed

increase or decrease in the toxicity of sediment residue samples can be

contributed to many factors.

63

As during the sequential extraction schemes , due to rigorous extraction

conditions (e.g. pH, temperature) the equilibrium within the sediment is

modified releasing toxic substances which might become bioavailable causing

toxicity to the test organism and thus might have increased the toxicity of the

sediment residues after MgCl2,NH2OH.HCl and H2O2/HNO3 extractions.

Moreover, sequential extractions are condemned for re adsorption and

redistribution of some metals due to their partial dissolution and pH changes but

it would not be significant enough to doubt the results of the sequential

extraction (Gleyzes et al 2002). However , as complete understanding on the

effects of reagents on each phase during single extraction is not available

(Gleyzes et al ,2002) , there are chances of re adsorption and redistribution of

metals in the sediment residues after single extractions which require further

investigation on these(re adsorption and redistribution) phenomena in single

extraction schemes.

Furthermore, sediments are a heterogeneous medium which differ in its

physico-chemical properties with depths (Chapman , 1995) and distance from

one location to another location. Thus, there are chances that the sediment

samples might have a wide variation in the composition of toxic substances in it

which might become bio available after the single extraction procedures and

thus causing increase or decrease in the toxicity of the sediment residues.

64

CHAPTER 5

CONCLUSION AND RECOMMENDATIONS FOR FURTHER WORK:

5.1 Metal Concentrations:

The relative abundance of metals in the sediment in increasing order

found to be: Cd< Cr< Cu < Pb < Mn < Zn < Ni < Fe. The comparison of

total metal concentrations with various sediment quality guidelines

suggests that the threshold effect levels set by various guidelines above

which adverse effects are likely to occur in the sediment are exceeded for

Cu , Ni , Pb , Cd and Zn. This comparison demonstrates that the

sediments are polluted due to these metals and raises concerns about their

adverse effects on aquatic ecosystems of this part of the river. But as

these guidelines are established on the total metal concentrations rather

than the concentrations of most bio available fractions of metals and more

over the bioavailability of sediment contaminants is manipulated by

various factors, there are chances of false positive and negative

conclusions (Burton , 2002). Thus, the evaluation of biological effects on

aquatic biota (e.g. benthic community characterization) is required to

confirm whether adverse effects have been occurred on aquatic biota or

not.

The correlation analysis identified three distinct groups of metals 1) Cu-

Fe-Mn-Zn , 2 )Ni-Cu-Mn and 3) Pb-Fe-Zn . As the correlation between

the metal concentrations indicates similar behaviour and origin, these

three associations of metals indicates that instead of single source

contributing to metals in the sediments, there might be many sources

which influx the metals in the sediments supporting the hypothesis that

metals have diffuse source of pollution in the urban aquatic environment

65

and could be originated from many point and non point sources of

pollution. The metals could have been derived from CSOs, un treated

waste water discharges, urban road run off, combined and separate

residential sewage flows and industrial waste water releases.

5.2 Metal Fractionation:

The partitioning pattern of the metals obtained using single extractions

indicates that except Cr and Cu all other metals are contained within the

Fe-Mn Oxides phase in the range of 70-94% of total metals extracted

using the single extraction steps of Tessier’s sequential extraction

scheme.This fraction is considered as less mobile compared to

exchangeable and carbonate phase and act as a sink for the metals. 56 %

of extracted Cr and 92 % of extracted Cu are contained within the organic

matter bound phase indicating sewage outfalls as their major sources in

the sediments. Except Cd the amount of metals contained within

exchangeable and carbonate phase is less than 10%. However 12% of

extracted Cd contained within Exchangeable phase and 14% within

carbonate bound phase. As metals associated with exchangeable and

carbonate fractions are considered as rapidly bioavailable and the Fe-Mn

Oxides and organic matter have a scavenging effect on metals

(Jain ,2004) , the less amount of metals associated with exchangeable and

carbonate fractions indicates that the metals are less susceptible

bioavailability while the higher concentrations of metals in Fe-Mn oxides

and organic matter fractions indicates scavenging effects reducing the

bioavailability of the metals. Thus , though the total metal concentrations

are exceeding the guidelines for some of the metals , the metal

fractionation patterns indicates that sediment might be less susceptible to

66

metal toxicity due to their less availability in the most available fraction

and scavenging effects of Fe-Mn Oxides and organic matter.

5.3 Toxicity Results for unprocessed sediments and change in toxicity of

sediment residues:

The comparison of the results of Microtox SPT with various sediment

classification methods indicates that the sediments are moderately toxic

to non toxic. The toxicity rating suggests that the sediments may or may

not pose harm to the aquatic ecosystems. However, the test results could

not help to identify particular cause of toxicity in the sediments. The

integrated analysis of total metal concentration, fractionation studies and

toxicity testing indicates that though total concentrations are exceeding

in the sediments, they are not indicative of adverse effects as the toxicity

tests suggest moderate to low toxicity of the sediments. Furthermore the

results of fractionation studies also indicates that due to scavenging of

metals in relatively less available fractions , metals might be minor

contributors to sediment toxicity and there are chances that some other

pollutants might be contributing to the toxicity. As toxicity is a trophic

level property, a battery of toxicity tests representing multiple trophic

levels is further recommended to evaluate the adverse effects on aquatic

biota in the sediments.

Though the Kruskal-Wallis test results of EC50 values of sediment are

not statistically significant to assess the difference in sediment toxicity

due to extraction of metals, the comparison of toxicity value for

replicate1 of unprocessed sediment with the toxicity values of HNO3

and NaOAc treated sediment residues indicates a reduction in toxicity

while toxicity of MgCl2 , NH2OH.HCl and NH2OH.HCl+H2O2 treated

sediments indicates increase in the sediment toxicity. The comparison of

67

toxicity value of replicate 2 of unprocessed sediment with the toxicity

values of all sediment residues obtained from the single extraction

indicates an increase in the sediment toxicity after metal extraction.

However, it was identified that problem of obtaining a representative

sample might be affecting the overall trend of the test results.

5.4 Recommendations for further research work:

The experiment could be performed with larger sample populations for

toxicity test results so that statistical inferences can be made from the test

results and toxicity data representative of the sediments can be obtained.

One possible approach is instead of cleaning the sediments for one

particular group of pollutants (e.g. metals or PAHs), using various

chemical extraction techniques (e.g. metal extractions, solvent extraction

using solvent of increasing polarity) the sediment can be cleaned for all

possible pollutants and they can be extracted simultaneously from the

sediment retaining the basic properties of the sediments which are

exclusive of these pollutants. The sediment residue after these chemical

extractions can be tested for toxicity and the results of these toxicity tests

could be used as reference toxicity value for comparison in the toxicity

tests. However, in order to assess the effect of these extractions on

sediment properties, an analysis of sediment properties which include

particle size characterization, pH, redox potential, CEC, organic matter

content could be performed on the sediments before and after extraction.

68

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