Development of sediment reference sample for toxicity testing using Microtox Solid Phase test and Metal Fractionation using single extractions

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 (µg/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 µg/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 50µm ( 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)
Bioluminescence (Parvez et al, 2007). Since bioassays based on
bioluminescence are rapid , sensitive , reproducible and cost effective and more
over they 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 µg/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 (µg/l) = ICP conc. In sample (µg/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 (µg/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 0-20µl , 0-1000µl 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 µg/g to 3.9 µg/g for Cd , 9.0 µg/g to 23.00 µg/g for Cr , 102µg/g to
130 µg/g for Cu , 11850 µg/g to 23900 µg/g for Fe , 328 µg/g to 397µg/g for
Mn , 9900 µg/g to 12400 µg/g for Ni , 167 µg/g to 332 µg/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

Percent
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
Pb
Zn
40000
Mean StDev N AD 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

Meanof%concentration
Fig. 4.2 Partitioning Pattern of Metals in different fractions
Partitioning Patterns of Elements
100
80
60
40
20
F raction
O rganic Matter
Fe-Mn Oxides
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 R2
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

EC50Value
EC50value(g/lit)
Fig.4.3 Box plot of EC50 values of unprocessed sediment sample and sediment residues after
each single extraction.
Bo x plo t o f Ec 5 0 v alues o f bare sediment and sediment residues
2 0
1 5
1 0
5
0
M gCl2 NaOAc NH2OH.HCl HNO3 Bare
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
Percent
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 fractionis 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

Development of sediment reference sample for toxicity testing using Microtox Solid Phase test and Metal Fractionation using single extractions

Development of sediment reference sample for toxicity testing using Microtox Solid Phase test and Metal Fractionation using single extractions

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