HYDROCARBON DEGRADATION AND ACCUMULATION BY

POLLUTED

THE DEPARTMENT OF PLANT SCIENCE AND

BIOTECHNOLOGY

Ebere Omeje

AHUNDU, MAY NGUFAN

PG/MSc/12/62659

HYDROCARBON DEGRADATION AND ACCUMULATION BY

Sansevierialiberica Gerome and Labroy

POLLUTED WITH CRUDE OIL

THE DEPARTMENT OF PLANT SCIENCE AND

BIOTECHNOLOGY

FACULTY OF BIOLOGICAL SCIENCES

Ebere Omeje Digitally Signed by: Content manager’s

DN : CN = Webmaster’s name

O= University of Nigeria, Nsukka

OU = Innovation Centre

HYDROCARBON DEGRADATION AND ACCUMULATION BY

Labroy

FACULTY OF BIOLOGICAL SCIENCES

: Content manager’s Name

Webmaster’s name

a, Nsukka

i

HYDROCARBON DEGRADATION AND ACCUMULATION BY

Sansevierialiberica Gerome and Labroy

POLLUTED WITH CRUDE OIL

BY

AHUNDU, MAY NGUFAN

PG/MSc/12/62659

A PROJECT REPORT SUBMITTED IN PARTIAL FULFILMENT OF THE

REQUIREMENT FOR THE DEGREE OF MASTER OF SCIENCE IN PLANT

ECOLOGY IN THE DEPARTMENT OF PLANT SCIENCE AND

BIOTECHNOLOGY, FACULTY OF BIOLOGICAL SCIENCES, UNIVERSITY

OF NIGERIA NSUKKA

SUPERVISOR: ASSOC. PROF. A. O. NWADINIGWE

OCTOBER, 2015

ii

TITLE PAGE

HYDROCARBON DEGRADATION AND ACCUMULATION BYSANSEVIERIA LIBERICA GEROME AND LABROY

POLLUTED WITH CRUDE OIL

iii

CERTIFICATION

Ahundu, May Ngufan a postgraduate student in the Department of Plant Science and

Biotechnology with Registration number PG/M.Sc./12/62659 has satisfactorily completed the

requirement for the award of Master of Science Degree in Environmental Plant Ecology. The

work embodied in this project is original and has not been submitted in part or full for any

diploma or degree of this or any other institution.

Approved by

_______________________________ ______________________________ Assoc. Prof. A.O. NwadinigweDrMrs.Nkechi O. Nweze (Supervisor) (Head of Department)

____________________________________________

External Examiner

iv

v

DEDICATION

This work is dedicated to the Almighty God.

vi

vii

ACKNOWLEDGEMENT

I give thanks and praise to the Almighty Father for bringing me this far. My sincere

appreciation goes to my project supervisor, Assoc. Prof. A.O. Nwadinigwe for her diligent

supervision and motherly advice.Thank you Ma. My honest appreciation to my husband

Steven Igomu and children; Paula, Audrey and Caleb who suffered the absence of their

mother from time to time,I am grateful and may the good Lord bless you all. I am also

thankful to my mother in-law and father in-law who were always taking careof my family in

my absence. My parents and siblings especiallymy sister Claire and brother SoonenNinga, the

Lord bless you all. My thanks goes to my friend ChikodiliEzeh and her entire family for

showing me love and making me feel like a part of their family, the Lord bless you all. My

friend Jessica Gondo you really are a friend indeed, the Lord bless and increase you. How can

I forget Isaac Abon, a friend and colleague, the Lord will remember you always. This piece

will not be complete if I do not mention some of my friends who were there when I needed

them; ObioraOdoh, BenitaAgbo and EbereNjoku.I am also thankful to all the staff and

management of the Department of Plant Science and Biotechnology, University of Nigeria,

Nsukka for their support.

viii

ix

LIST OF TABLES

Table 1:Layout of Completely Randomized Design (CRD) of unvegetated andvegetated

soil with Sansevierialibericapolluted with different volumes of crude oil15

Table 2: Total petroleum hydrocarbon distribution (mg/kg) in soil, unvegetated and

vegetated with Sansevierialiberica polluted with different volumes of crude oil20

Table 3: Total petroleum hydrocarbon distribution (mg/kg) of leaf, stem and rootof

Sansevieria liberica polluted with different volumes of crude oil 21

Table 4a: Mean vegetative parameters of Sansevierialiberica before crude

oil pollution 27

Table 4b: Mean vegetative parameters of Sansevierialiberica after crude

oil pollution 27

x

LIST OF FIGURES

Figure 1: Percentage Total Petroleum Hydrocarbons (TPH) degraded in soils

unvegetated and vegetated with Sansevierialiberica polluted

with different concentrations of crude oil 22

Figure 2: Percentage TPH degraded by plant alone for different concentrations of crude

oil contamination23

Figure 3: Percentage accumulation of TPH in plant organs polluted with different

concentrations of crude oil 25

xi

LIST OF PLATES

Plate 1:Sansevierialiberica with no crude oil (0 ml) 28

Plate 2:Sansevierialiberica without crude oil pollution

(4weeks after others were polluted) 28

Plate 3:Sansevierialiberica (30 ml) before pollution 28

Plate 4:Sansevierialiberica polluted with 30 ml crude oil (4 weeks after pollution) 28

Plate 5:Sansevierialiberica (150 ml) before pollution 29

Plate 6:Sansevierialiberica polluted with 150 ml crude oil (4 weeks after pollution) 29

Plate 7:Sansevierialiberica (750 ml) before pollution 29

Plate 8:Sansevierialiberica polluted with 750 ml crude oil (4 weeks after pollution) 29

Plate 9: Some plants (150 ml and 750 ml volume contamination) that died

after crude oil pollution31

xii

ABSTRACT

The capability ofSansevierialiberica to withstand crude oil pollution, degrade and/or

accumulate the contaminant was investigated using 0.3, 1.3 and 6.3% v/w concentrations of

crude oil to pollute soil vegetated with the stem cuttings of the plant. These treatments were

repeated in unvegetated soils and the control had no crude oil pollution. The experiment was

carried out in 3 replicates in a completely randomized design. Total Petroleum Hydrocarbons

(TPH) were determined for all soil samples (vegetated and unvegetated)as well as the leaves,

stem and roots using Gas Liquid Chromatography (GLC). Vegetative parameters namely;

number of leaves, leaf area, plant height and stem circumference were determined for both

control and polluted plants before and after pollution. The results showed that percentage

TPH degraded in the vegetated soil was 95.8, 88.5 and 68.1% for 0.3, 1.3 and 6.3% v/w

concentrations, respectively. S liberica alone degraded 0.87, 2.92 and 2.29% for the same

treatments. Percentage accumulations of 0.3% v/w crude oil pollution for the leaf, stem and

root were 0.002, 0.036 and 0.209%, respectively, those of 1.3% v/w were 0.004, 0.067 and

0.315%, respectively while those of 6.3% v/w were 0.008, 0.085 and 0.43%, respectively.

Means for the vegetative parameters for the plant parts showed that there were significant (P<

0.05) differences in some vegetative parameters after contamination with crude oil. Therefore

there was phytoremediation and accumulation of hydrocarbons by S. liberica.

xiii

TABLE OF CONTENTS

Title page i

Certification ii

Dedication iii

Acknowledgement iv

List of tables v

List of figures vi

List of plates vii

Abstract viii

Table of content ix

CHAPTER ONE

1.0 Introduction 1

1.1 Crude oil/or hydrocarbon pollution 1

1.2Sansevierialiberica Gerome and Labroy 2

1.3 Scientific classification 3

1.4 Description of the plant 3

1.5 Cultivation of Sansevieriliberica4

1.6 Uses 4

1.7 Aim and objectives of the research work 4

CHAPTER TWO

2.0 Literature Review 6

2.1 Remediation approaches and hydrocarbon degradation 6

2.2 Impact of hydrocarbon contamination on environment and human health 8

2.3 Phytoremediation as a tool for soil clean up 9

xiv

2.3.1 Phytodegradation (Rhizodegradation)9

2.3.2 Phytostabilization 10

2.3.3 Phytoextraction (Phytoaccumulation) 10

2.3.4 Phytovolatilization 11

2.3.5 Rhizofiltration11

2.4Phytodegrading potential of plants 12

2.5 Phytoremediation of hydrocarbon contaminated soil12

CHAPTER THREE

3.0 Materials and methods 14

3.1 Collection of materials14

3.2 Methods/ experimental design 14

3.3 Determination of Total Petroleum Hydrocarbons (TPH) in the soil 16

3.4 Determination of TPH in leaves, stem and roots17

3.5 Determination of TPH degraded and accumulated18

3.6 Data Analysis 18

CHAPTER FOUR

4.0 Results19

4.1 Total Petroleum Hydrocarbon (TPH) degraded in the soil19

4.2 Percentage accumulation of TPH in the plant organs (leaves, stem and roots)24

4.3 Vegetative parameters of Sansevierialibericapolluted with crude oil26

CHAPTER FIVE

5.0 Discussion 32

5.1 Total Petroleum Hydrocarbons (TPH) degraded 32

5.2 TPH accumulation in the plant organs 33

xv

5.3 Vegetative parameters 35

5.4 Conclusion 36

REFERENCES

APPENDIX

1

CHAPTER ONE

1.0 INTRODUCTION

1.1 Crude oil/or hydrocarbon pollution

Crude oil is a crucial energy resource and vital industrial raw material. With increasing

industrial production, oil pollution has become a serious worldwide environmental problem,

especially at the oil mining stage in the field (Zhu et al., 2013). Large-scale crude oil spills on

soil, leakages from pipelines, underground and surface fuel storage tanks, indiscriminate

spills and careless disposal and mismanagement of wastes and other petroleum by-products

constitute the major sources of petroleum contamination in our environment. Oil spillage on

soil has many detrimental effects on the composition, structure and functioning of terrestrial

ecosystems, including loss of biodiversity (Osuji et al., 2004). Soil contamination arising

from oil spills is one of the most limiting factors to soil fertility. It affects growth of plants

thereby causing negative impacts on food productivity (Onwurahet al., 2007).

High levels of petroleum hydrocarbons which include alkanes (paraffin), alkenes (olefins)

and various aromatic hydrocarbons are found in crude oil (Oforkaet al., 2012). According to

a report by NNPC (2004), the Nigerian crude oil is characterized by high concentrations of

aromatics (40%) and polars (resins and asphaltenes, 47%). Oil pollutants can get transferred

via food chains and eventually cause adverse effect on human health. In addition, residual oil

hydrocarbons can persist in the soil for decades and have chronic effect on ecosystems and

human beings (Culbertson et al., 2008).The latter has attracted increasing attention because

of the carcinogenic, mutagenic and toxic effects (Imeh and Sunday, 2012).

2

Environmental remediation deals with the removal of pollutants or contaminants from

environmental media such as soil, groundwater, sediments or surface water (Zhu et al., 2004).

Phytoremediation (from Ancient Greek (phyto), meaning "plant", and Latin remedium,

meaning "restoring balance") describes the treatment of environmental problems by using

plants without the need to excavate the contaminant material and dispose of it elsewhere

(Ruiet al., 2012).

Total petroleum hydrocarbon (TPH) is defined as the measurable amount of petroleum-based

hydrocarbon in an environmental medium. It is thus, dependent on analysis of the medium in

which it is found (Adesodun and Mbagwu, 2007). Some chemicals that may be found in TPH

are hexane, jet fuels, mineral oils, benzene, toluene, xylenes, naphthalene and fluorine as well

as other petroleum products and gasoline components. However, it is likely that samples of

TPH will contain only some, or a mixture of these chemicals (USEPA, 2012).

Gas liquid chromatography (GLC) is one of the most powerful, popular, unique and versatile

analytical techniques used for the separation, identification and quantitative assay of

compounds in the vapour state. The popularity of GLC is absolutely centred on high

selectivity, sensitivity, high resolution combined with good accuracy and precision in a wide

dynamic concentration range (Sjaaket al., 2009).

1.2Sansevierialiberica Gerome and Labroy

The genus Sansevieria pronounced (san-se-vi-ee’-ri-ah) – is a member of theFamily

Asparagaceae and is popularly called Snake-plant, Mother-in-Law’s tongue or Bowstring-

3

hemp. The genus was named by Thunberg after the Prince of Sanseviero who was born in

Naples in 1710.Sansevieria tops the list as the most tolerant of all decorative plants that can

survive the most unsuitable growing conditions, abuse and neglect a plant could receive

(Chahinian, 2005).

1.3 Scientific classification

Kingdom: Plantae

Division: Magnoliophyta

Class: Liliopsida

Order: Asparagales

Family: Asparagaceae

Genus: Sansevieria

Species: Sansevierialiberica

(Source: Aigbokhan, 2014)

1.4 Description of the plant

Sansevierialibericais an evergreen perennial plant forming dense stands, spreading by way of

its creeping rhizome, which is sometimes above ground, sometimes underground with fibrous

roots. Its stiff leaves grow vertically from a basal rosette. Mature leaves are dark green with

light grey-green cross-banding and usually range between 70–90 centimetres (28–35") long

and 5–6 centimetres (2.0–2.4") wide. It bears milk coloured flowers that are bisexual and

pollinated by moths. Sansevierialiberica flowers from the month of March to June in West

Africa. Fruits are green when unripe and turn orange in colour when ripe.Both flowering and

fruiting are erratic and few seeds are produced. The raceme of Sansevieria is derived from the

4

apical meristem and a flowered plant will no longer produce new leaves but continues to

grow by producing plantlets via its rhizomes or stolons (Chahinian, 2005).

1.5 Cultivation ofSansevierialiberica

It can be propagated by leaf cutting; whole leaves are cut from the rosette and set aside for

several days to allow the cut to dry. At this point the leaf will be inserted cut side down into

moist porous potting medium to root. Over time the leaf will produce roots and a stolon from

the cut surface which will bear a new plant at its tip. The rhizome can also be cut and sown. It

is tolerant of salt and saline soils. It can tolerate drought and should not be over watered

(Chahinian, 2005).

1.6Uses

Like some other members of its genus, S. liberica yields bowstring hemp, a strong plant fibre

once used to make bowstrings and can be used in place of rubber (Osabohien and Egbo,

2008). It is now used predominantly as an ornamental plant, outdoors in warmer climates,

and indoors as a houseplant in cooler climates. It is popular as a houseplant because it is

tolerant of low light levels and irregular watering. A study by National Aeronautics and

Space Administration (NASA) found that it is one of the best plants for improving indoor air

quality by passively absorbing toxins such as nitrogen oxides and formaldehyde (Wolvertonet

al., 1989).

1.7Aim and objectives of the research work

The aim and objectives of this work are:

• to assess the capability ofSansevierialiberica to degrade petroleum hydrocarbons in

crude oil contaminated soil.

5

• to determine the quantity of total petroleum hydrocarbons

(TPH)Sansevierialibericacan accumulate.

• to establish the levels of crude oil contamination the plant can tolerate.

.to ascertain the effect of crude oil pollution on some vegetative parameters of S. liberica.

6

CHAPTER TWO

2.0LITERATURE REVIEW

2.1 Remediation and hydrocarbon degradation

Remediation approaches are generally classified as physical, chemical and biological. The

conventional methods include extraction of soil and landfill of the top contaminated soils (ex

situ). This is highly effective, clear-cut but often very expensive due to high cost involved in

the disposal of the contaminated soil, transportation and backfill of the original site with

clean soil (Zhu et al., 2004; Ryan et al., 2001). Hence, in situ bioremediation has been one of

the preferred methods for the remediation of petroleum-contaminated sites because it is cost-

effective and naturally converts the hydrocarbons to harmless by-products such as carbon

dioxide and water.

Hydrocarbon degradation, on the other hand, is believed to occur through a rhizosphere

effect; in this case, plants exude organic compounds through their roots, which increase the

density, diversity and activity of specific microorganisms in the surrounding rhizosphere,

which in turn degrade hydrocarbons. Cai et al. (2010) have examined ornamental plants for

phytoremediation of petroleum-contaminated soils. They observed that phytoremediation

using ornamental plants can effectively reduce the pollution and at the same time beautify the

environment rather than using crops which will have to be destroyed after the remediation

process is complete, hence the choice of the plant Sansevierialiberica for this research work.

7

Phytoremediation is a low-input approach depending on natural attenuation by

biodegradation and physiochemical mechanisms that decrease the pollutant concentration, in

which case sowing plants may be the only intervention (Ruiet al., 2012). In the past decade,

an extensive body of research on phytoremediation of both organic and inorganic

contaminants has been taking place (Smreczak and Maliszewska-Kordybach, 2003).

Plant species selection is a critical management decision in phytoremediation. Grasses are

thought to be the most suitable species because their fibrous rooting systems can stabilize soil

and provide a large surface area for root-soil contact (Kulakowet al., 2000). The application

of indigenous plant species for phytoremediation is often favoured as it requires less

management and acclimatizes successfully in native climate conditions and seasonal cycle.

However, some exotic plant species may perform better in remediation of specific metals and

can be safely used where the possibility of invasive behaviour has been eliminated (USEPA,

2000). The selection of plants is possibly the single most important factor for fruitful

phytoremediation strategy. Hemen (2011) suggested some important criteria in selecting

plant species for phytoremediation of metals viz:

• The levels of tolerance with respect to metal known to exist at the site.

• The level of adequate accumulation, translocation and uptake potential of metal.

• High growth rate and biomass yield.

• Tolerance to water logging and extreme drought conditions.

• Availability, habitat preference e.g., terrestrial, aquatic, semi-aquatic etc.

• Tolerance to high pH and salinity.

• Root characteristic and depth of the root zone.

These criteria are relevant to this study.

8

2.2 Impact of hydrocarbon contamination on environment and human

health

Hydrocarbon spills from petroleum products both on land and in water, have been a problem

since the discovery of crude oil as a fuel source. This can have devastating effects on the

biota of an environment. Oil spills and oil wastes discharged into the sea or land from

refineries, factories or shipping contain poisonous compounds that constitute potential danger

to plants and animals. The poisons can pass through the food web of an area and may

eventually be eaten by humans (Gibson and Parales, 2000). Environmental contamination by

hydrocarbons and petroleum products constitute nuisance to the environment due to their

persistent nature and tendency to spread into ground and surface waters, this has attracted

much attention in recent decades. Husaini et al. (2008) and Plohlet al. (2002) indicated that,

spent motor oils such as diesel or jet fuel contaminate natural environment with hydrocarbon.

The hydrocarbons may spread horizontally on the groundwater surface thereby causing

extensive groundwater contamination.

Aromatic hydrocarbons are considered to be the most acute, toxic component of petroleum

products, and are also associated with chronic and carcinogenic effects. Lighter mono-

aromatics (one ring) compounds include benzene, toluene, ethyl benzene, and xylenes

(BTEX). Aromatics with two or more rings are referred to as polycyclic aromatic

hydrocarbons (PAHs) (Anderson et al., 1974).Baker et al. (2002) reported that motor oil had

concentrations of benzene up to 29 to 66 mg/L but those of other BTEX compounds were

higher, typically 500 to 2000 mg/L. Hydrocarbon contamination of the air, soil, freshwater

(surface water and groundwater) especially by PAHs has drawn public concerns because

many PAHs are toxic, mutagenic, and carcinogenic (Clemente et al., 2001). Clinical studies

9

have shown that exposure of a mixture of highly concentrated PAHs may cause skin, lung,

stomach and liver cancers (ASTDR, 1990).

2.3 Phytoremediation as a tool for soil clean up

Phytoremediation is an eco-friendly approach for remediation of contaminated soil and waste

water using plants. It consists of two components, one by the root colonizing microbes and

the other by plants themselves, which accumulate the toxic compounds to further change to

non- toxic metabolites. Various compounds, viz: organic synthetic compounds, xenobiotics,

pesticides, hydrocarbons, heavy metals and radionuclides are among the contaminants that

can be effectively remediated by plants (Suresh and Ravishankar, 2004; Schroder et al.,

2002). Different mechanisms are employed in phytoremediation of petroleum hydrocarbons.

Both plants and microorganisms are involved directly and indirectly in the degradation or

transformation of petroleum hydrocarbons into products that are generally less toxic and less

persistent in the environment than the parent compound (Nwadinigwe and Onyeidu, 2012).

The primary mechanisms for plant-mediated remediation of soils contaminated with

petroleum hydrocarbons as outlined by Amanda(2006) are: phytodegradation

(rhizodegradation), phytostabilization, phytoextraction (phytoaccumulation),

phytovolatilization and rhizofiltration. The success of phytoremediation at a given site cannot

always be attributed to just one of these mechanisms because a combination of mechanisms

may be at work.

2.3.1 Phytodegradation (Rhizodegradation) involves the degradation of organic

contaminants directly, through the release of enzymes from roots, or through metabolic

activities within the plant tissues. In phytodegradation organic contaminants are taken up by

10

roots and metabolized in plant tissues to form less toxic substances. Gunther et al. (1996)

found higher microbial numbers and activity coupled with increased degradation in

hydrocarbon contaminated soil planted with ryegrass (Liliumperenne) compared to unplanted

soil. The authors suggested that the plant roots stimulated the microbes, which enhanced the

degradation of the hydrocarbons. Rhizodegradationinvolves attenuation of organic

contaminants into less toxic substances within the rhizospherethrough biodegradation by the

soil microbes. This process is facilitated by root exudates (organic molecules) that sustain

populations of soil microbes. Nwadinigwe and Onyeidu (2012) pointed out that greater

degradation of oil pollutants is carried out by a consortium of microorganisms than by one

microorganism.

2.3.2 Phytostabilization involves the use of plants to contain, or immobilize contaminants in

the soil or groundwater, thus, reducing the bioavailability of the contaminant. The

mechanisms involved may include absorption and accumulation by roots, adsorption onto

root surfaces, binding with soil organic matter, and incorporation into humic materials in the

rhizosphere. Aiyesanmi et al. (2012) in their work with Talinumtriangulare,

Chromolaenaodorata and Synedrellanodiflora ascertained the ability of these plants to

absorb lead (a heavy metal) from a lead contaminated soil which was amended with NPK

fertilizer to enhance growth of plants. In like manner, Kamelet al. (2012) reported that

Delonixregia could remediate lead and cadmium from soil.

2.3.3 Phytoextraction (Phytoaccumulation) uses plants or algae to remove contaminants

from soil sediments or water into harvestable plant biomass.The plants absorb contaminants

through the root system and store them in the root biomass and/or transport them up into the

stems and/or leaves. A living plant may continue to absorb contaminants until it is harvested.

11

After harvest, a lower level of the contaminant will remain in the soil, so the growth/harvest

cycle must usually be repeated through several crops to achieve a significant clean up. After

the process, the cleaned soil can support other vegetation. According to Alkorta and Garbisu

(2001) direct uptake of organic pollutants relies mainly on the physicochemical

characteristics of the target compounds, such as the log Kow factor (compounds with an

optimal uptake between log Kow 0.5 and 3 are easily transported to the xylem and

translocated to the shoot) and the water partition coefficient, among others.

2.3.4 Phytovolatilizationinvolves the uptake of contaminants by plant roots and its

conversion to a gaseous state, and release into the atmosphere. This process is driven by the

evapotranspiration of plants. Plants that have high evapotranspiration rate are sought after in

phytovolatilization. Organic contaminants, especially volatile organic compounds (VOCs) are

passively volatilized by plants. Genetic engineering has been used to allow plants to volatilize

specific contaminants. For example, the ability of the tulip tree (Liriodendron tulipifera) to

volatilize methyl-Hg from the soil into the atmosphere as mercury oxide was improved by

inserting genes of modified E. coli that encode the enzyme, mercuric ion reductase (merA)

(Kashiwa et al., 2001).

2.3.5 Rhizofiltration: In this process, contaminants are taken up by the plant and removed

from the site when the plant is harvested. In this case, the contaminant is removed from the

dissolved phase and concentrated in the root system. Rhizofiltration is typically exploited in

groundwater (either in situ or extracted), surface water, or wastewater for the removal of

metals or other inorganic compounds (USEPA, 2000).

12

2.4 Phytodegrading potentials of plants

Evidence for degradation of pollutants by plants has been reported by many researchers.

Chen et al. (2003)using 14C-labeled pyrene showed 38% and 30% pyrene mineralization for

tall fescue (Festucaarundinacea) and switchgrass (Panicumvirgatum L.), respectively,

compared with 4.3% in the unplanted control. Dixit et al. (2011) observed that transgenic

tobacco plant expressing a Trichodermavirens showed tolerance and degraded anthracene-A

(a 3 benzene ring compound) to naphthalene (a 2 benzene ring compound) when compared to

the wild type plants. Uwagboe (2008) recorded continuous reduction of total petroleum

hydrocarbons in the polluted soil he vegetated with guinea grass (Panicum maximum) and

water leaf (Talinumtriangulare). Using Azollafiliculoidesin aqueous solution, Mohammad et

al. (2014) reported that it removed bisphenol-A by phytodegradation. Nwadinigwe and Obi-

Amadi (2014) in their work reported the capability of Pennisetumglaucumto degrade more

crude oil from soils polluted at different levels thenunvegetated soil with same treatments.

They also observed that the plant might have enhanced biodegradation by stimulating the

proliferation of microorganisms in the soil as they recorded higher microbial count above

those of unvegetated soils. Onwukaet al. (2012) reported thatCynodondactylon L. could

degrade hydrocarbon from crude oil contaminated soil in a period of 2 months.

2.5 Phytoremediation of hydrocarbon contaminated soil

On-site phytoremediation of petroleum hydrocarbons can be enhanced by employing a

combination of common agronomic practices (e.g. fertilizer application, tillage and

irrigation).This is because available nutrient reserves can be quickly depleted as the microbial

community begins to degrade the contaminants (Farrell and Germida, 2002).Fertilizer

applications may enhance the degradation of petroleum hydrocarbons in soil by reducing

competition for limited nutrients. Nwadinigwe and Ezeamama (2007) reported that the use of

13

poultry manure produced the highest plant height, leaf area and numbers of flowers, pods and

seeds when compared with the use of PDA treatment. Palmrothet al. (2002) recorded 60%

loss of diesel fuel in 30 days in diesel-contaminated soil planted with pine tree and amended

with NPK fertilizer. Also, Vouillamoz and Mike (2009) maintained that compost addition

combined with phytoremediation, increased the rate of removal of diesel fuel from soil.

Agamuthuet al. (2010) found appreciable degradation of used lubricating oilin soil when the

growth of Jatrophacurcaswas enhanced with brewery spent grain.

Some researchers have recorded success of hydrocarbon uptake by plants with no

amendments. Edema et al. (2011) reported high levels of PAHs uptake by cowpea

(Vignaunguiculata), mushroom (Basidiomycetes) and algae (filamentous chlorophytes) in a

period of four weeks. They recommended the use of cowpea for phytoremediation of soils

contaminated with crude oil when they observed higher degradation of PAHs with cowpea

when compared to mushroom and algae. This theyattributed tothe ability of the plant to fix

nitrogen in the soil hence not necessarily needing nitrogen application for effective growth.

Dominguez-Rosado and Pichtel (2004) recorded appreciable reduction in oil/grease content

of soils contaminated with used motor oil (with no amendments) planted with soybean/bean,

sunflower/mustard, grass/maize and wheat/oats. Though, they observed that there was higher

reduction in oil content of planted soils amended with fertilizer as compared to soil planted

with no amendments.

14

CHAPTER THREE

3.0MATERIALS AND METHODS

3.1 Collection of materials

Top soil was collected at a depth of 10cm from the Botanic Garden, Department of Plant

Science and Biotechnology, University of Nigeria, Nsukka. Rhizomes of Sansevierialiberica

were also collected from the same garden. Poultry manure was obtained from the Department

of Animal Science, University of Nigeria, Nsukka. Crude oil was obtained from Pumpking

Oil Services, Port Harcourt, Rivers State.

3.2 Methods/experimental design

Top soil was mixed with poultry manure in the ratio of 3:1. Ninety six black perforated

polythene bags were each, filled with 12kg of the soil media. The bags were well labelled and

displayed in a completely randomized design (Table 1) under the sun in the Botanic Garden,

Department of Plant Science and Biotechnology, University of Nigeria, Nsukka. Rhizomesof

S. liberica of equal length (10cm each) with circumference of 5 to 6 cm were sown in 48 soil

bags. The remaining 48 bags were left unvegetated. Vegetated and unvegetated bags were

watered sparingly when necessary. On emergence of the plant shoots, vegetative parameters

were monitored (measurement of plant height, number of leaves, leaf area and stem

circumference) at an interval of 2 weeks. Plant height (cm) was measured from the soil

surface to the apex of the longest leaf with a meter rule. Leaf area (cm2) was determined by

measuring the leaf length and width with a meter rule and dividing with 0.75(Francis et al

1969). Number of leaves were determined by counting. Measuring tape was

15

Table 1: Layout of Completely Randomized Design (CRD) of unvegetated and vegetated soil with Sansevierialiberica polluted with different volumes of crude oil.

P750 A1 U0B1 P30D1 U150C1 P0 B1 U750A1 P150C1 U30D1

U30C1 P150B2 U750D3 P30C1 U150B2 P0A1 P750D3 U0A1

P0C2 U30B1 P150A2 U0C2 P750B3 U150A2 U750B3 P30B1

U150D2 P0D1 U30A3 P150D2 U0D1 P30A3 U750C3 P750C3

U0B3 P750D2 U150A1 P0B3 U750D2 P150A1 U30B2 P30B2

P30A1 U0C3 P750B2 U150D3 P0C3 U750B2 P150D3 U30A1

U750A3 P150B1 U30D2 P750A3 U150?B1 P30D2 U0A2 P0A2

P750C1 U0D2 P150A3 U30C3 P0D2 U750C1 P30C3 U150A3

U150C2 P30A2 U750B1 P150C2 U30A2 P0D3 P750B1 U0D3

P150B3 U0C1 P30D3 U750D1 P0C1 U30D3 U30D3 P750D1

U30C2 P150C3 U150C3 P0A3 U750C2 P750C2 U0A3 P30C2

P30B3 U750A2 P0B2 U30B3 P150D1 U0B2 P750A2 U750A2

Key: P0 = vegetated soil without crude oil pollution. P30= vegetated soil polluted with 30 ml crude oil.

P150= vegetated soil polluted with 150 ml crude oil.

P750= vegetated soil polluted with 750 ml crude oil.

U0= unvegetated soil without crude oil pollution.

U30=unvegetated soil polluted with 30 ml crude oil.

U150=unvegetated soil polluted with 150 ml crude oil.

U750= unvegetated soil polluted with 750 ml crude oil.

A, B, C and D are the number of samples. 1, 2, 3 are the number of replicates.

16

used to measure stem circumference. When all the plants had grown to a minimum height of

ten centimetres, both vegetated and unvegetated bags were polluted with crude oil.

Each of the 24 soil bags (12 with plants and 12 without plants) were polluted with 30ml

(0.3%v/w) of crude oil. This was repeated using 150ml (1.3%v/w) and 750ml (6.3%v/w)

instead of 30 ml. The control was not polluted with crude oil and the experiment was carried

out in 3 replicates

Sixty days after pollution, both vegetated and unvegetated soils were randomly collected

from the different treatments separately in amber bottles and labelled accordingly. The stems,

leaves and roots of plants treated with different concentrations of crude oil (as well as the

control) were also randomly collected and labelled accordingly. All samples were subjected

to Gas Liquid Chromatography (GLC) to determine the Total Petroleum Hydrocarbons

(TPH) degraded by the plants and those left in the soil. The unused crude oil was also

analysed to determine the TPH composition which served as the reference standard.

3.3 Determination of TPH in the soil

Samples were stored in the refrigerator at 40C and taken when needed. Anhydrous sodium

sulphate was added to 5.0 g of each soil sample and mixed until a dry mixture was obtained.

To the dried mixture of each sample, Analar grade Dichloromethane (DCM), Hexane and

Acetone (3:1:1, v/v/v) were added in an extraction bottle and covered tightly with Teflon cap

and shaken gently for 30 minutes using a mechanical shaker. The two phases were separated

by filtration using a 100 ml capacity sintered funnel to remove any particulates present and

poured into a clean 100 ml conical flask. The extracted organic phase was cleaned using

activated neutral alumina and concentrated to 0.5 ml using a rotary vacuum evaporatorand

17

transferred into 2.0 ml volumetric flask. One microliter of the final extract was injected in an

already calibrated GLC (Varian 3400) equipped with Flame Ionization Detector (FID).

Nitrogen was used as a carrier gas. The column temperature was set at 600C for 10min,

followed by a linear increase of 100C per minute to 2800C, and then the temperature was held

for 8.17min. Detector temperature was maintained at 3000C while injector temperature was

2000C and pressure program (set point) was 14.0 psi (EPA, 1996).

3.4 Determination of TPH in leaves, stem and roots Randomly collected plants treated with 0 ml, 30 ml, 150 ml and 750 ml were separately

dissected into leaves, stem and roots. These different parts from each treatment level was

crushed separately and put in beakers one at a time. Each crushed sample was carefully

mixed thoroughly using a glass rod. Five grams of each sample was mixed with anhydrous

sodium sulphate until a dry mixture was obtained. To the dried mixture of each sample,

Analar grade DCM, Hexane and Acetone (3:1:1, v/v/v) were added in an extraction bottle and

covered tightly with Teflon cap and shaken gently for 30 minutes using a mechanical shaker.

The two phases were separated by filtration using a 100 ml capacity sintered funnel to

remove any particulates present and poured into a clean 100 ml conical flask. The extracted

organic phase was cleaned using activated neutral alumina and concentrated to 0.5 mlusing a

rotary vacuum evaporator and transferred into 2.0 ml volumetric flask. One microliter of the

final extract was injected in an already calibrated GLC(Varian 3400) equipped with FID.

Nitrogen was used as a carrier gas. The column temperature was set at 600C for 10min,

followed by a linear increase of 100C per minute to 2800C, and then the temperature was held

for 8.17min. Detector temperature was maintained at 3000C while injector temperature was

2000C and pressure program (set point) was 14.0 psi (EPA, 1996).

18

3.5 Determination of TPH degraded and accumulated

Total TPH obtained for the soil and plant parts (Tables 2 and 3) is the sum of the remaining

hydrocarbons after degradation and accumulation under the column. The total TPH of the

unused crude oil is the standard and is regarded as 100%, since it is undegraded. The TPH

degraded for each soil treatment is obtained by subtracting the remaining TPH under the

treatment column from the total TPH of the standard. Percentage TPH for each column, on

the other hand, is obtained by dividing the total TPH degraded in the column by the standard

and multiplying it by 100.Percentage TPH degraded by the plant alone was obtained by

subtracting percentage TPH degraded in unvegetated soil from percentage TPH in vegetated

soil. TPH obtained under each column for the plant parts (Table 3) is the sum of the

remaining hydrocarbons under the column. Percentage accumulated by the plant part was

obtained by dividing the TPH under the plant part by the standard and multiplying by 100

(Nwadinigwe and Obi-Amadi, 2014).

3.6 Data Analysis

Vegetative parameters (number of leaves, plant height, leaf area and stem circumference)

were subjected to statistical analysis using analysis of variance (ANOVA). Means were

separated using Duncan’s multiple range tests at P ≤ 0.05. Vegetative parameters before and

after crude oil contamination was compared using T-test (Edafiogho, 2006).

19

CHAPTER FOUR

4.0 RESULTS

4.1 Total petroleum hydrocarbons (TPH) degraded in the soil

Results of GLC analysis forthe unused crude oil sample, which is the standard (undegraded),

showed the presence of high concentrations of straight chain hydrocarbons of C11 – C39

(Tables 2 and 3). Some other hydrocarbons like C1 – C10 were neither detected in the standard

nor in any of the polluted or unpolluted soil samples. Hydrocarbons C11 – C39 were detected

in all the polluted soil samples (vegetated and unvegetated) although in small numbers when

compared with the unused crude oil. No hydrocarbons were detected in the control.

Percentage TPH degraded in vegetated soil polluted with 0.3, 1.3 and 6.3 % v/w crude oil

treatments were 95.8%, 88.5% and 68.1%, respectively while the percentage TPH degraded

in unvegetated soil polluted with the same quantities of crude oil were 94.93%, 85.58% and

65.81%, respectively (Figure 1). Percentage TPH degraded by the plants alone was obtained

by subtracting the percentage TPH degraded in unvegetated soil from the percentage TPH

degraded in vegetated soil.Thus, for 0.3% v/w crude oil pollution, the plant degraded 0.87%,

for 1.3% v/w, it degraded 2.92% in and for 6.3% v/w it degraded 2.29% (Figure 2).

20

Table 2: Total petroleum hydrocarbon distribution (mg/kg) in soil, unvegetated and vegetated with Sansevierialiberica, polluted with different concentrations of crude oil.

Straight chain conc. of hydrocarbon in Polluted, vegetated soil samples (%v/w) Polluted, unvegetated soil samples (%v/w) group unused crude oil 0.0 0.3 1.3 6.3 0.0 0.3 1.3 6.3 C11 5009 0 136 254 958 0 254 254 532 C12 5473 0 99 342 758 0 188 342 453

C13 7834 0 89 452 865 0 189 452 872 C14 9983 0 102 432 6521 0 200 432 832 C15 7843 0 155 200 758 0 200 200 563 C16 8734 0 206 321 625 0 321 321 723 C17 8932 0 211 234 425 0 300 300 600 C18 7098 0 241 342 564 0 356 356 723 C19 7771 0 236 300 1002 0 352 352 777 C20 9812 0 245 684 548 0 324 762 762 C21 5891 0 158 213 358 0 234 342 657 C22 11141 0 250 1909 4568 0 309 2397 7864 C23 12015 0 399 1110 4823 0 456 2541 7675 C24 10872 0 459 2009 7580 0 654 2897 6678 C25 12458 0 652 2451 5468 0 754 2541 6890 C26 10587 0 781 2987 4560 0 791 3526 7900 C27 13221 0 542 2897 5250 0 674 3270 8000 C28 13897 0 489 2008 4540 0 896 2415 6754 C29 12048 0 654 1735 4562 0 832 2353 5578 C30 14771 0 800 1896 4358 0 643 3542 7657 C31 13562 0 542 2632 5621 0 734 2983 5009 C32 10589 0 569 1625 5689 0 864 2003 7678 C33 13487 0 654 1000 3254 0 764 2520 3421 C34 10486 0 891 579 2560 0 900 598 1324 C35 8124 0 456 583 2658 0 430 623 1323 C36 7592 0 322 587 2586 0 654 632 1352 C37 8723 0 456 678 2694 0 543 722 1753 C38 7624 0 186 390 1302 0 234 432 902 C39 5623 0 120 300 895 0 200 452 890 Total TPH (mg/Kg) 281200 0 1100 31150 88350 0 14250 40560 96142

0, means absence of hydrocarbons

21

Table 3: Total petroleum hydrocarbon distribution (mg/kg) of leaf, stem and root of Sansevierialiberica, polluted with different concentrations of crude oil. Straight chain conc. of hydrocarbon leaf (%v/w) stem (%v/w) root (%v/w) group in unused crude oil 0.0 0.3 1.3 6.3 0.0 0.3 1.3 6.3 0.0 0.3 1.3 6.3

C11 5009 0 0 0 0 0 0 0 0 0 0 0 0 C12 5473 0 0 0 0 0 0 0 0 0 0 0 0

C13 7834 0 0 0 0 0 0 0 0 0 0 0 0 C14 9983 0 0 0 0.6 0 2.1 3.56 0 0 0.9 2.1 8.5 C15 7843 0 0.11 0.23 0.5 0 5.03 8.25 10.5 0 2.1 3.2 6.9 C16 8734 0 0.11 0.21 1.2 0 3.12 5.64 8.21 0 2.43 0.9224.6 C17 8932 0 0.11 0.22 1.2 0 2.12 4.23 9.24 0 1.2 3.2 4.5 C18 7098 0 0.07 0.15 1.3 0 3.25 4.23 8.3 0 0.3 0.36 5.6 C19 7771 0 2.54 4.5 6.5 0 26.4 64.64 88.4 0 532.6 820.1 1073.6 C20 9812 0 0.23 0.45 0.6 0 5.6 8.9 8.3 0 4.5 6.2 7.1 C21 5891 0 0.24 0.45 0.3 0 5.1 6.5 8.12 0 3.2 4.5 5.5 C22 11141 0 0.07 0.14 0.8 0 1 3.2 0 0 1.8 0.54 6.5 C23 12015 0 0.21 0.42 0.5 0 5.9 9.2 9.25 0 4.2 4.2 6.5 C24 10872 0 0.1 0.37 1.6 0 6.2 11.2 10.25 0 3.2 6.2 7.3 C25 12458 0 0.25 0.45 0.8 0 1.2 4.5 0 0 1.6 4.3 9 C26 10587 0 0.4 0.8 0.5 0 5.3 10.25 13.46 0 4.6 3.85 4.5 C27 13221 0 0.155 0.33 0.5 0 5.2 8.35 11.3 0 4.5 4.2 5.3 C28 13897 0 0.1 0.2 0.5 0 5.2 9.2 11.3 0 3.6 4.1 6.5 C29 12048 0 0.3 0.6 0.6 0 5.3 9.36 13.2 0 3.5 4.2 6.9 C30 14771 0 0.25 0.5 0.6 0 5.1 6.32 8.34 0 2.3 5.6 6.2 C31 13562 0 0.25 0.5 0.5 0 5.1 9.32 8.15 0 5.6 0 5.6 C32 10589 0 0 0 0.4 0 1 2.1 0 0 0 2.3 0 C33 13487 0 0.1 0.26 1.38 0 1.8 0 4.96 0 3.3 0.3 9.5 C34 10486 0 0.15 0.3 0.6 0 0 0 0 0 0.9 0 0 C35 8124 0 0.15 0.3 0 0 0 0 0 0 0 0 0 C36 7592 0 0.43 0.1 0 0 0 0 0 0 0 0 0 C37 8723 0 0 0 0 0 0 0 0 0 0 0 0 C38 7624 0 0 0 0 0 0 0 0 0 0 0 0 C39 5623 0 0 0 0 0 0 0 0 0 0 0 0

Total TPH (mg/Kg) 281200 0 6.325 11.48 21.48 0 101.02 188.95 238.22 0 586.33 885.47 1210 0, means absence of hydrocarbons

22

Figure 1: Percentage Total Petroleum Hydrocarbons (TPH) degraded in soil

unvegetated and vegetated with Sansevierialiberica polluted with different

concentrations of crude oil.

0

20

40

60

80

100

120

0.3% v/w 1.3% v/w 6.3% v/w

Pe

rce

nta

ge

TP

H d

eg

rad

ed

Concentration of Crude oil

Vegetated Soil

Unvegetated Soil

23

Figure 2: Percentage Total Petroleum Hydrocarbons (TPH) degraded by plant alone for

different concentrations of crude oil pollution.

0

0.5

1

1.5

2

2.5

3

3.5

0.3 1.3 6.3

% T

PH

de

gra

de

d

Crude oil concentrations (% v/w)

24

4.2 Percentage accumulation of hydrocarbons in the plant organs

(leaves, stem and roots)

Hydrocarbons C11 – C13 and C37 –C39 (Table 3) were not detected in any of the plant organs

(leaves, stem and roots) even though they were found in the standard. No hydrocarbons were

detected in the unpolluted leaves, stem and roots (control).Hydrocarbon C14was detected in

all volumes of crude oil pollution in the root but in the stem it was detected in 0.3 and 1.3%

v/w and absent in 6.3% v/w. The reverse was the case in the leaf where in 0.3 and 1.3% v/w

hydrocarbon C14 was not detected but present in 6.3% v/w. HydrocarbonsC15 – C31 were

detected in all the plant parts and across the various volumes of crude oil pollution, except in

the stem at 6.3% v/w concentration where C22 was not detected and in the root at 1.3% v/w

concentration, C31 was not detected. HydrocarbonC32 was only present in 6.3% v/w of crude

oil pollution in the leaves and present in the stem of 0.3 and 1.3% v/w concentrations but in

the root it was present in only 1.3% v/w of crude oil pollution. C33 was recorded in all the

plant parts at all volumes of crude oil pollution while C34was detected in the leaves across all

the volumes butcompletely absent in the stem and was detected in the root of 0.3% v/w

concentration only. HydrocarbonsC35 and C36 were only detected in the leaf of 0.3 and 1.3%

v/w.

The leaf accumulated0.002%, 0.004% and 0.007% for 0.3, 1.3 and 6.3% v/w

concentrations,respectively. The stem accumulated0.036%, 0.067% and 0.085%for 0.3, 1.3

and 6.3% v/w concentrations, respectively. Similarly, the root at same volumes of crude oil

pollution accumulated 0.209%, 0.315% and 0.43%, respectively (Figure 3). It was observed

that the root had the highest accumulation of hydrocarbons when compared with those of the

stem and leaves. The leaves had the least accumulation level of hydrocarbons.

25

Figure 3: Percentage accumulation of Total Petroleum Hydrocarbons (TPH) in plant

organs polluted with different concentrations of crude oil.

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

0.3 1.3 6.3

% T

PH

acc

um

ula

ted

concentration of crude oil (% v/w)

stem

root

leaf

26

4.3 Vegetative parameters of S. libericapolluted with crude oil

The results of the mean maximum number of leaves of S. libericabefore pollution (Table 4a)

showed that the plants labeled 30 ml (Plates 3 and 4) gave significantly (P< 0.05)the lowest

mean number of leaves (2.17 ± 0.17) and 0 ml (Plates 1 and 2), 150 ml (Plates 5 and 6) and

750 ml(Plates 7 and 8) were the same. Analysis of variance (ANOVA) showed that this effect

was significant.After pollution number of leaves in all the treatments were thesame (Table

4b). ANOVA showed that this effect was not significant.In comparing the number of leaves

before and after pollution, the number of leaves increased significantly (P< 0.05) after

pollution 0 ml, 30 ml and 750 ml.

As regards leaf area before pollution, 750 ml gave significantly (P< 0.05) highest value of

80.0 ± 10.81 cm2, while 30 ml gave the lowest value of 45.25 ± 7.27 cm2. Zero milliliter, 30

ml and 150 ml were the same and 0 ml, 150 ml and 750 ml were the same. ANOVA showed

significance at P- 0.05. Values for mean maximum leaf area after pollution were the same

and ANOVA was not significant. In comparing leaf area before and after pollution, there was

no significant differences.

27

Table 4a: Mean vegetative parameters of Sansevierialiberica before crude oil pollution.

Crude oil concentrations

Vegetative Parameters 0 ml 30 ml 150 ml 750 ml

No of Leaves 3.08 ± 0.29a 2.17 ± 0.17b 3.33 ± 0.28a 3.00 ± 0.21 a

Leaf area (cm2)58.53 ± 9.52 a, b45.25 ± 7.27a55.65 ± 6.53a, b80.00 ± 10.81b

Height (cm) 23.75 ± 2.54a, b19.91 ± 1.95 a 22.18 ±1.93a, b 26.93 ± 1.98b

Stem circ. (cm) 5.36 ± 0.10a 5.28 ± 0.10a 5.52 ± 0.10 a5.86 ± 0.14b

Values represent means ± standard error. Means followed by the same letter(s) in a row are not significantly different at P ≤ 0.05.

Table 4b: Mean vegetative parameters of Sansevierialiberica after crude oil pollution. Crude oil concentrations

Vegetative Parameters 0 ml30 ml 150 ml 750 ml

No of Leaves 4.50 ± 0.31a 3.75 ± 0.35a4. 38 ± 0.60 a4.17 ± 0.40 a

Leaf area (cm2) 69.07 ± 11.55a53.47 ± 7.73a70.51 ± 5.88a59.53 ± 10.26a

Height (cm) 25.63 ± 2.65a 21.93 ± 1.83a26. 89 ± 1.96 a23.75 ± 1.98a

Stem circ. (cm) 5.52± 0.10a5.38 ± 0.10a5.53 ± 0.14a5.80 ± 0.23 b

Values represent means ± standard error. Means followed by the same letter(s) in a roware not significantly different at P ≤ 0.05.

28

Plate 2: Sansevierialiberica without crude oil pollution (4 weeks after others were polluted)

Plate 1: Sansevierialiberica with no crude oil (0 ml)

Plate 3: Sansevierialiberica (30 ml) before pollution

Plate 4: S. liberica polluted with 30 ml crude oil (4 weeks after pollution)

29

Plate 8: Sansevierialiberica polluted with 750 ml crude oil (4 weeks after pollution)

Plate 7: S. liberica before pollution Plate 7: Sansevierialiberica (750 ml) before pollution

Plate 5: Sansevierialiberica (150 ml) before pollution

Plate 6: Sansevierialibericapolluted with 150 ml crude oil (4 weeks after pollution)

30

The mean maximum height of S. liberica before pollution showed that plants labeled 750 ml

had significantly (P< 0.05) highest mean of 26.93 ± 1.98cm,while those polluted with 30 ml

had the lowest mean height of 19.91 ± 1.95cm. ANOVA showed that this effect was not

significant. Multiple comparisons for the different volumes also showedthat 0 ml, 150 ml and

750 ml treatments were the same and 0 ml, 30 ml and 150 ml were the same.After pollution

all the treatments gave the same values for height. ANOVA showed that this effect wasnot

significant.Comparing height before and after pollution, there were no significantdifferences.

Results forthe mean stem circumference before and after pollution showed that, 750 ml gave

the highest mean of 5.86 ± 0.14cm and 5.80 ± 0.23 cm, respectively (significant at P< 0.05)

while 0 ml, 30 ml and 150 ml were the same. ANOVA showed that this effect was significant

(P< 0.05) before pollution but after pollution it was not significant. In comparing stem

circumference before and after contamination, there wereno significant differences.

Two weeks after pollution up to the fourth week it was observed that 6 out of the 12 plants

polluted with 750 ml crude oil withered while 4 out of 12 plants polluted with 150 ml also

withered (Plate 10). All plants from the 30 ml and 0 ml pollution performed well.

Plate 7: S. liberica before pollution

31

Plate 10: Some plants (150 ml and 750 ml volume contamination) that died after crude oil

pollution

32

CHAPTER FIVE

5.0 DISCUSSION

5.1 Total petroleum hydrocarbons (TPH) degraded

Some straight chain groups of hydrocarbons like C1 – C10 were volatile and so could not be

detected by GLC for unused crude oil sample and the polluted soils as well as the plant

organs. No hydrocarbons were detected in the control (0 ml) for both vegetated and

unvegetated soil samples as well as the unpolluted plants as there was no crude oil pollution.

For the polluted vegetated and unvegetated soils, all hydrocarbons were found but in smaller

quantities when compared with the unused crude oil sample.This showed that

phytodegradation took place. The plant metabolized some of the hydrocarbons and used them

for growth as evident in their survival after pollution. In this experiment, more degradation of

hydrocarbons took place in the presence of Sansevierialiberica than in its absence. However,

the difference in the degradation levels between vegetated and unvegetated soil was

minimal.This indicates that other unseen factors in the soil (microorganisms) were

responsible forsome of the degradation of crude oil in the absence of the plant.This

phenomenon is in agreementwith the report of Wenzel (2009) who stated that,“the efficiency

of phytoremediation relies on the establishment of vital plants with sufficient shoot and root

biomass growth, active root proliferation and/or root activities that can support a flourishing

microbial consortium assisting phytoremediation in the

rhizosphere”.Sansevierialibericanourished the rhizospherevery well in support of microbial

consortium for phytoremediation.The findings of the present work agree with the work of

Nwadinigwe and Obi-Amadi (2014)who reported that

Pennisetumglaucumphytodegradedcrude oil polluted soils contaminated with varying

33

volumes of crude oil, and they showed that viable microbial count in vegetated soils was

significantly higher than that ofunvegetated soil, indicating that the plant enhanced

the biodegradation of crude oil by stimulating the proliferation of microorganisms in the soil.

In this present work, percentage TPH degraded in vegetated soil polluted with 0.3, 1.3 and

6.3% v/w were 95.8%, 88.5% and 68.1%, respectively, while percentage TPH degrade in

unvegetated soil polluted with the same quantities were 94.93%, 85.58% and 65.81%,

respectively, 60 days after pollution. Edema et al. (2011) in their work with mushroom,

cowpea and algaereported that degradation of PAHs in crude oil contaminated soils of

varying concentrations was achieved by these plants at the following levels; 98.93%

degradation for mushroom, 97.90% for cowpea and 97.07% for algae. Also Banks et al.

(2003) in their experiment with four varieties of Sorghum bicolor observed higher

degradation of TPH associated with vegetated soil (69%) than in unvegetated soils (35%).

Eulisset al. (2008) in a period of one year recorded 70% loss of TPH in crude oil polluted soil

planted with Carexexigua, Panicumvirgatum and Tripsacumdactyloides.Diab (2008)

observed that Viciafaba degraded 47% of TPH in petroleum contaminated soil in a 60 day

period.

5.2 TPH accumulation in the plant organs

In this work, after a period of 60 days the percentage accumulation in the roots contaminated

with various volumes of crude oil pollution was highest followed by that of the stem, while

the leaves had the lowest level of accumulation. This finding is similar to that of Sakinehet al.

(2013) who reported thatAvicennia marina showed higher level of TPH accumulation in the

root than the leaf in a period of three months. Denise et al. (2013) observed that

34

Heterantheracallifoliain a period of 4 weeks bioaccumulated TPH in the roots, petioles and

leaves,but in this case the leaves had the highest concentration of 0.434 ± 0.170 mg l-1

followed by the petioles (0.202 ± 0.116 ) mg l-1, while the roots had the least uptake of

0.096 ± 0.080 mg L-1. In like manner, Onwukaet al. (2012), working with

Cynodondactylonshowed that there was significant difference in accumulation of TPH in the

stem between polluted and unpolluted plants within a period of two months.The stem

accumulated more TPH than the leaves and roots. Edwin-Wosu and Albert (2010) reported

that two leguminous species,Leucaenaleucocephala and Bauhinia monandraaccumulated

TPH from the crude oil contaminated soil the plants were sown.Atagana (2011) reported

thatChromolaenaodorata (L) degraded more TPH in soils contaminated with used engine oil

(40 g kg-1) in 90 days. The researcher recorded the presence of TPH and some PAHs in the

roots and shoots of the plants sown in the contaminated soil. Plabitaet al. (2013) recorded

higher accumulation of TPH in plant shoots than in the roots, which is in contrast with this

work. They made a valid observation that,higher accumulations were achieved in the second

year when compared with the first year. In the first year the shoots had a minimum

concentration of 10000ppm while in the second year there was highest maximum of

50000ppm. This is an indication that the longer the plants are allowed on the pollution site,

the higher the level of accumulation which is in agreement with Kamathet al.(2004) who

stated that“degradation of organics may be limited by mass transfer, i.e., desorption andmass

transport of chemicals from soil particles to the aqueous phase and this may becomethe rate

determining step. Therefore, phytoremediation may require more timeto achieve clean-up

standards than other more costly alternativessuch as excavation or ex-situ treatment,

especially for hydrophobic pollutantsthat are tightly bound to soil particles. In many cases,

35

phytoremediation mayserve as a final ‘polishing step’ to close sites after more aggressive

clean-uptechnologies have been used to treat the hot spots”.

5.3 Vegetative parameters

Vegetative parameters after pollution showed increases,plants polluted with 150ml

concentration of crude oil particularly performed well, even better than the control (0 ml)

after pollution.Agbogidiet al. (2007) reported similar results in a study with five varieties of

maize contaminated with various volumes of crude oil pollution (0.0 ml, 5.2 ml, 10.4 ml, 20.

8 ml and 41.6 ml). They observed that 5.2 ml volume of crude oil pollution performed better

than all the treatments including the control (0.0 ml). In this present work, plants polluted

with 750 ml showed increase only in number of leaves, the other vegetative parameters (leaf

area, plant height and stem circumference) decreased.Nwadinigwe and Olawale(2010)

reported similar result when they plantedSorghum vulgare in crude oil polluted soil, they

observed that as the volumes of crude oil pollution increased, various vegetative parameters

decreased. Similarly,Ayotamuno and Kogbara (2007) reportedthat Zea mayscould not

withstand the high levelsof crude oil pollution and as such,the mean plant height, leaf area,

number of leaves and stem circumference were significantly reduced as the amount of crude

oil contamination increased.Nwadinigwe and Onyeidu (2012) also reported that, 200ml of

crude oil pollution impaired the growth of soybeans when compared with lower volumes of

150 ml and less.

Some plants polluted with 150 ml and 750 ml of crude oil died between 2 weeks and 4 weeks

after pollution with crude oil.However, plants that survived the initial shock from the crude

oil pollution thrived and did well up to the 60 days period before they were collected for

36

laboratory work. This shows that beyond 750 ml it might be impossible for the

plantSansevierialiberica) to survive.

This was in line with the work of Budhadevet al. (2004) who reported that, high

concentrations of crude oil pollution negatively affected the health and survival of plants. In

like manner Uzohoet al. (2004) in an experiment with maize polluted with crude oil recorded

mortality of some of the test plants with increasing levels of crude oil

contamination.Nwadinigwe and Uzodimma (2005) reported that high volumes of petroleum

hydrocarbons inhibited germination, flowering and pod production in groundnut

(ArachishypogaeaL.).

5.4 CONCLUSION

The results of this work confirmed that Sansevierialibericawas able to degrade petroleum

hydrocarbon. Though percentage degradation of hydrocarbons by the plant alone was

minimal, it indicates that the plant stimulated the activities of the microorganisms in their

bioremediative work. The experiment also showed that S. liberica could accumulate

hydrocarbons in its organs, and so there is the need to allow the remediative period to take

longer time for greater accumulation in future research. It was also observed that this plant is

more tolerant to small levels of crude oil contamination as such should not be exposed to

highly contaminated areas possibly it should be used for secondary phytoremediation.

37

REFERENCES

Adesodun, J. K.and Mbagwu, J.S.C. (2007). Distribution of heavy metals and hydrocarbon contents in alfisol contaminated with waste-lubricating oil amended with organic waste. BioresourceTechnology 99(8): 195-204. www.sciencedirect.com

Agamuthu, P., Abioye, O.P. and Abdul-Aziz, A. (2010). Phytoremediation of soil

contaminated with used lubricating oil using Jatropha curcas. Journal of Hazardous Materials179: 891 – 894.

Agbogidi, O. M., Eruotor, P. G and Akparobi, S. O. (2007). Effects of crude oil levels on

growth of maize (Zea mays). American Journal of Food Technology. 2: 529-535. ATSDR (Agency for Toxic Subtances and Disease Registry) (1990). Public health statement,

Polycyclic Aromatic Hydrocarbons (PAHs). U.S Department of Health and Human Services, Atlanta, Georgia.

Aigbokhan, E.I. (2014). Annotated checklist of vascular plants of southern Nigeria – a quick

reference guide to the vascular plants of southern Nigeria: a systematic approach. UNIBEN press, Benin City.345pp.

Aiyesanmi, A.F., Okoronkwo, A.E. and Sunday, O.M. (2012). Lead accumulations in Siam

weed (Chromolaena odorata), Node weed (Syndrella nodiflora) and Waterleaf (Talinum triangulare): Potential Phytoremediators. Archives of Applied Science Research4(1): 360-371.

Alkorta, I. and Garbisu, C. (2001). Phytoremediation of organic contaminants in

soils. Bioresource Technology 79: 273– 276.

Amanda, V.E. (2006). Phytoremediation of petroleum hydrocarbons. Report on environmental careers organization for U.S. Environmental Protection Agency (USEPA). Office of Solid Waste and Emergency Response. Office of Superfund Remediation and Technology Innovation Washington, D.C. 1-12 pp. http://www.epa.gov

Anderson, J.W., Neff, J.M., Cox, B.A., Totem, H. E. and Hightower, G.M. (1974).

Characteristics of dispersions and water soluble extracts of crude and refined oils and their toxicity to estuarine crustaceans and fish. Marine Biology 27: 75-88.

38

Atagana, H.I. (2011). The potential of Chromolaeneodorata (L) to decontaminate used engine oil impacted soil under greenhouse conditions. International Journal of Phytoremediation13(7): 627- 641.

Ayotamuno, M. and Kogbara, R. (2007). Determining the tolerance level of Zea mays to a

crude oil polluted agricultural soil. African Journal of Biotechnology 6(1): 1332-1337.

Baker, R.J., Best, E.W. and Boehr, A.L. (2002). Used motor oil as a source of MTBE, TAME and BTEX to ground water. Ground Water Monitoring and Remediation 22: 46-51.

Banks, M. K., Kulakow, P., Schwab, A.P. Chen, Z. and Rathbone, K. (2003). Degradation of

crude oil in the rhizosphere of Sorghum bicolor. International Journal of Phytoremediation 5(3): 225-234.

Budhadev, B., Rubul, S., Sabitry, B., Hamendra,C.D. and Hari, P.S. (2004). Assessment of

potential plant species for phytoremediation of hydrocarbon-contaminated areas of upper Assam, India. Journal of Chemical Technology and Biotechnology 87(9): 1329-1334.

Cai, Z., Zhou, Q.X., Peng, S.W. and Li, K.N. (2010). Promoted biodegradation and

microbiological effects of petroleum hydrocarbons by Impatiens balsamina L. with strong endurance. Journal of Hazardous Materials 183(1-3): 731- 738.

Chahinian, B.J. (2005). The splendid Sansevieria: an account of the species. B. Juan

Chahinian publishers, UK.178pp. ISBN 987-43-9250-9.

Chen, Y.C., Banks, M.K. and Schwab, A.P. (2003). Pyrene degradation in the rhizosphere of tall fescue (Festuca arundinaceous) and switchgrass (Panicumvirgatum L.). Journal of Environmental Science Technology 37: 5778- 5782.

Clemente, A.R., Anazawa, T.A. and Durrant, L.R. (2001). Biodegradation of polycyclic

aromatic hydrocarbons by soil fungi. Brazilian Journal of Microbiology 32: 255–261.

Culbertson, J.B., Valiela, I., Pickart, M, Peacock, E.E. and Reddy, C.M. (2008). Long-term consequences of residual petroleum on salt marsh grass. Journal of Applied Ecology 45: 1284–1292.

Denise, E.M., Akhere, M.A., Udoh, E. and Okpo, R. (2013). Phytoextraction of total

petroleum hydrocarbon inpolluted environment using an aquatic macrophyteHeterantheracallifolia Rchb.Ex Kunth. The International Journal of Engineering and Science 2(110): 37-41.

Diab, E. (2008). Phytoremediation of oil contaminated desert soil using the rhizosphere

effects. Global Journal of Environmental Research. 2(2): 66-73.

39

Dixit, P., Mukherjee, P.K., Sherkhane, P.D. and Sharad, P. (2011). Enhanced tolerance and remediation of anthracene by transgenic tobacco plants expressing a fungal glutathione transferase gene. Journal of Hazadous Materials 192 (1): 270-276.

Dominguez- Rosado, E. and Pichtel, J. (2004). Phytoremediation of soil contaminated with used motor oil: II greenhouse studies. Environmental Engineering Science 21(2): 169-180. Edafiogho, D. O. C. (2006). Computer graphics, spreadsheet (excel) and SPSS. University of

Nigeria press ltd., Nigeria. 237pp. Edema, C.U., Idu, T.E. and Edema, M.O. (2011). Remediation of soil contaminated

with polycyclic aromatic hydrocarbons from crude oil. African Journal of Biotechnology 10(7): 1146-1149. Edwin-Wosu, N.L. and Albert, E. (2010). Total petroleum hydrocarbon content (TPH) as an

index assessment of macrophytic remediation process of a crude oil contaminated soil environment. Journal of Applied Science, Environment and Management 14(1): 39-42.

EPA (Environmental Protection Agency). Method 8015B (1996). Nonhalogenated organics

using GC/FID. 1-28 pp. Euliss, K., Ho, C., Schwab, A.P., Rock, S. and Banks, M. K. (2008). Green house and field

assessment of phytoremediation for petroleum contamination in a riparian zone. Bioresource Technology. 99: 1961-1971.

Farrell, R. E. and Germida, J. J. (2002). Phytotechnologies: Plant based systems for

remediation of oil impacted soil. www.essa events.com/remtech/2002/pdf/09Farrellpaper.pdf

Francis, C.A., Rutger, J.N. and Palmer, A.F.E. (1969). A rapid method for plant leaf area estimation in maize. Crop Science 9(5): 537-539.

Gibson, D.T. and Parales, R. (2000). Aromatic hydrocarbon dioxygenases in environmental biotechnology. Current Opinion in Biotechnology 11: 236 – 243.

Gunther, T., Dornberger, U. and Fritsche, W. (1996). Effects of ryegrass on biodegradation of hydrocarbons in soil. Chemosphere. 33: 203-215.

Hemen, S. (2011). Metal hyperaccumulation in plants: A review focusing on phyto-remediation technology Journal of Environmental Science and Technology, 4: 118-138.

Husaini, A., Roslan, H. A., Hii, K. S. Y. and. Ang, C. H. (2008). Biodegradation of aliphatic hydrocarbon by indigenous fungi isolated from used motor oil contaminated sites. World Journal of Microbiology and Biotechnology 24: 2789 – 2797.

Imeh, J. O. and Sunday, C. E. (2012). Determination of total hydrocarbon content in soil afterpetroleuspillage. Proceedings of the World Congress on Engineering vol. iii, WCE 2012, July 4-6, London, U.K.

40

Kamath, R., Rentz, J.A., Schnoor, J.L. and Alvarez, P.J. J. (2004). Phytoremediation of hydrocarbon contaminated soils: principles and application.Petroleum Biotechnology: Developments and Perspectives 151: 447-478.

Kamel, M. M., Khater, H. A., Amira, S. S. and Nermeen, T. S. (2012). Effects of microbial inoculation and EDTA on the physiology and phytoremediation efficiency of Delonix regia plant growing in polluted soils. American–Eurosian Journal of Agricultural and Environmental Science 12(6): 719-729.

Kashiwa, M., Ike, M., Mihara, H., Esaki, N. and Fujita, M. (2001). Removal of soluble selenium by a selenate-reducing bacterium Bacillus sp. SF-1. Journal of Fermentation and Bioengineering 83: 517–522.

Kulakow, P. A., Schwab, A. P. and M. K. Banks. (2000). Screening plant species for growth

of weathered, petroleum hydrocarbon contaminated sediments. International Journal ofPhytoremediation 2: 297-317.

Mohammad, A.Z., Yousef, M., Edris, B. and Davoud, B. (2014). Phytodegradation potential

of bisphenol-A from aqueous solution by Azollafiliculoides. Journal of Environmental Health Science and Engineering 12: 66-70.

Nigerian National Petroleum Corporation (NNPC) Bulletin, June (2004).

Nwadinigwe, A.O. and Ezeamama, N.C. (2007). Combating the effects of crude oil pollution onSennaobtusifolia using fertilizer, poultry manure and Penicillium. Nigerian Journal of Botany 20(1): 133-137.

Nwadinigwe, A.O. and Obi-Amadi, A. (2014).Crude oil degrading potential of

Pennisetum glaucum(L.) R.Br. AfricanJournal of Biotechnology, 13(34):3489-3495.

Nwadinigwe, A. O. and Olawole, A. O. (2010). Effects of crude oil on the growth of Sorghum vulgare Pers. A possible use of the plant for phytoremediaion. International Journal of Botany.2 (1): 35- 39.

Nwadinigwe, A.O. and Onyeidu, E. (2012). Bioremediation of crude oil polluted soil using bacteria, monitored through Soyabean production. Polish Journal of Environmental Studies 21(1): 171- 176.

Nwadinigwe, A.O. and Uzodimma, N.S. (2005). Effects of petroleum spill on the germination and growth of groundnut (Arachishypogaea L.) Bioresearch 3(2): 101-105.

Oforka, N. C., Osuji, L. C. and Onojake, M. C. (2012). Petroleum hydrocarbon fingerprinting of crude oils from Umutu/bomu oil fields in Niger Delta, Nigeria. Archives of Applied Science Research 4(10): 246-253. http://scholarsresearchlibrary.com/ archive.html

Onwuka, F., Nwachoko, N. and Anosike, E. (2012). Determination of total petroleum

hydrocarbon (TPH) and some cations (Na+,Ca+ and Mg2+) in a crude oil polluted soil and possible phytoremediation by Cynodondactylon L. (Bermuda grass). Journal of Environment and Earth Science 2(6): 13-17.

41

Onwurah, I.N.E., Ogugua, V.N., Onyike, N. B., Ochonogor, A. E. and Otitoju, O. F. (2007). Crude oil spills in the environment, effects and some innovative clean-up biotechnologies. International Journal of Environment Research 1(4): 307-320.

Osabohien, E. and Egboh, S.H.O. (2008). Utilization of bowstring hemp fibre as a filler in natural rubber compounds. Journal of Applied Polymer Science 107: 210-214.

Osuji, L.C., Adesiyan S.O. and Obute G.C. (2004). Post-impact assessment of oil pollution in Agbada west plain of Niger Delta, Nigeria: Field reconnaissance and total extractable hydrocarbon content. Chemistry Biodiversity 1: 1569–1578.

Palmroth, M.R.T., Pichtel, J. andPuhakka, J.A. (2002). Phytoremediation of subarctic soil contaminated with diesel fuel. Bioresource Technology 84: 221 – 228.

Plabita, B., Partha, P.B. and Suresh, D. (2013). Removal of hydrocarbon from crude oil contaminated soil by CyperusbrevifdiusRottb. Bulletin of Environment, Pharmacology and Life Sciences 2(6): 123-130.

Plohl, K., Leskovsˇek, H. and Bricelj, M. (2002). Biological degradation of motor oil in water. ActaChimSlovenica 49: 279–289.

Rui, L.,Rajendrasinh, N.J.,Qixing, Z. and Zhe, L. (2012). Treatment and remediation of petroleum contaminated soils using selective ornamental plants. Environmental

Engineering Science 29(6): 494-501. Ryan, J.A., Zhang, P., Chou, J. and Sayers, D.E. (2001). Formation of chloropyromorphite

in a lead-contaminated soil amended with hydroxyapatite. Environmental Science and Pollution 50: 493–500.

Sakineh, L., Gunale, V.R. and Rajurkar, N.S. (2013). Petroleum hydrocarbons pollution in soil and its bioaccumulation in mangrove species, Avicennia marina from Alibaug mangrove ecosystem, Maharashtra, India. Journal of Advancement in Research and Technology 2(2): 1-7.

Schroder, P., Harvey, P. J. and Schwitzguebel, J. P. (2002). Prospects for phytoremediation of organic pollutants in Europe. Environmental Science and Pollution 9(1): 1-3. Sjaak, k. Hans, G.J. and Udo, A.B. (2009). Modern methods of sample preparation for

GC analysis.Chromatographic Supplement 69: 33-78.

Smreczak, B. and Maliszewska-Kordybach, B. (2003). Seed germination and root growth of selected plants in PAH contaminated soil. Fresenius Environmental Bulletin 12: 946-949. Suresh, B. and Ravishankar, G.A. (2004). Phytoremediation - A novel and promising

approach for environmental clean-up. Critical Review in Biotechnology 24: 97-124.

USEPA (United States Environmental Protection Agency) (2000). Introduction to Phytoremediation. EPA 600-R-99-107, Office of Research and Development.

USEPA (United States Environmental Protection Agency) (2012). What is Total Petroleum

Hydrocarbon? www.epa.gov

42

Uwagboe, A. I. (2008). Assessment of local tropical plants for phytoremediation of petroleum contaminated soil. Journal of Research in National Development 6(1): 16-20.

Uzoho, B.U., Oti, N.N. and Onweremadu, E. U. (2004). Effects of crude oil pollution on

maize growth and soil properties in Ihagwa, Imo State Nigeria. International Journal of Agriculture and Rural Development 5(1): 91-100.

Vouillamoz, J. and Mike, M.W. (2009). Effect of compost in phytoremediation of diesel contaminated soils. Water Science Technology 43(2): 291 – 295.

Wenzel, W.W. (2009). Rhizosphere processes and management in plant-assisted bioremediation (phytoremediation) of soils. Journal of Plant Soil321: 385-408.

Wolverton, B. C., Douglas, W. L. and Bound, K. (1989). A study of interior landscape plants for indoor air pollution abatement. Report NASA- TM- 108061.

Zhu, L., Zhao, X., Lai, L., Wang, J., Jiang, L., Ding, J., Liu, N., Yu, Y., Li, J., Xiao, N., Zheng, Y. and Rimmingtom, G.M. (2013). Soil TPH concentration estimation using vegetation indices in an oil polluted area of Eastern China. Public Library of Science (PLOS) ONE 8(1): 1-12.

Zhu, Y. G., Chen, S. B. and Yang, J. C., (2004). Effects of soil amendments on lead uptake by two vegetable crops from a lead-contaminated soil from Anhui, China. Environment International 30: 351–356.

43

APPENDIX I

Group statistics for 0 ml contamination

Vegetative Parameters

N Mean Std. deviation Std. error

Before pollution No. of leaves After pollution

12 12

3.0833 4.5000

0.99620 1.08711

0.28758 0.31382

Before pollution Leaf area After pollution

12 12

58.5267 69.0658

32.97924 40.02330

9.52029 11.55373

Before pollution Height After pollution

12 12

23.7500 25.6333

8.78278 9.19143

2.53537 2.65334

Before pollution Stem circ. After pollution

12 12

5.3583 5.5167

0.36296 0.35377

0.10478 0.10212

APPENDIX II

Group statistics for 30 ml contamination

Vegetative Parameters

N Mean Std. deviation Std. error

Before pollution No. of leaves After pollution

12 12

2.1667 3.7500

0.57735 1.21543

0.16667 0.35086

Before pollution Leaf area After pollution

12 12

45.2500 53.4675

25.19868 26.78223

7.27423 7.73136

Before pollution Height After pollution

12 12

19.9083 21.9333

6.74570 6.33136

1.94732 1.82770

Before pollution Stem circ. After pollution

12 12

5.2833 5.3833

0.33257 0.33530

0.09601 0.09679

44

APPENDIX III

Group statistics for 150 ml contamination

Vegetative Parameters

N Mean Std. deviation Std. error

Before pollution No. of leaves After pollution

12 8

3.3333 4.3750

0.98473 1.68502

0.28427 0.59574

Before pollution Leaf area After pollution

12 8

55.6475 70.5138

22.61364 16.63022

6.52799 5.87967

Before pollution Height After pollution

12 8

22.3083 26.8875

6.75997 5.54061

1.95144 1.95890

Before pollution Stem circ. After pollution

12 8

5.5167 5.5250

0.32983 0.38452

0.09521 0.13595

APPENDIX IV

Group statistics for 750 ml contamination

Vegetative Parameters

N Mean Std. deviation Std. error

Before pollution No. of leaves After pollution

12 6

3.0000 4.1667

0.73855 0.98319

0.21320 0.40139

Before pollution Leaf area After pollution

12 6

80.0033 59.5333

37.44117 25.12500

10.80833 10.25724

Before pollution Height After pollution

12 6

26.9333 23.7500

6.86656 5.90991

1.98221 2.41271

Before pollution Stem circ. After pollution

12 6

5.8583 5.8000

0.47950 0.55857

0.13842 0.22804

45

APPENDIX V Analysis of variance (ANOVA) for vegetative parameters before pollution with crude oil Vegetative Parameters

Sum of Squares

Df Mean Square

F-cal Sig.

Between groups No. of leaves Within groups Total

9.229 31.250 40.479

3 44 47

3.076 0.710

4.332 0.009

Between groups Leaf area Within groups Total

7664.746 39994.031 47658.778

3 44 47

2554.915 908.955

2.811 0.050

Between groups Plant height Within groups Total

313.306 2361.663 2674.968

3 44 47

104.435 53.674

1.946 0.136

Between groups Stem circ. Within groups Total

2.348 6.392 8.739

3 44 47

0.783 0.145

5.387 0.003

APPENDIX VI Analysis of variance (ANOVA) for vegetative parameters after pollution with crude oil Vegetative Parameters

Sum of Squares

Df Mean Square

F Sig.

Between groups No. of leaves Within groups Total

3.752 53.958 57.711

3 34 37

1.251 1.587

0.788 0.509

Between groups Leaf area Within groups Total

2056.555 30595.506 32652.062

3 34 37

685.518 899.868

0.762 0.523

Between groups Plant height Within groups Total

143.265 1759.777 1903.042

3 34 37

47.755 51.758

0.923 0.440

Between groups Stem circ. Within groups Total

0.695 5.208 5.903

3 34 37

0.232 0.153

1.512 0.229

46

APPENDIX VII

Multiple comparisons of vegetative parameters before crude oil pollution

Vegetative Parameters

Replicates

Mean diff.

Standard error

Significance

No. of leaves

0

30 150 750

0.91667 -0.25000 0.08333

0.34405 0.34405 0.34405

0.011 0.471 0.810

30

0 150 750

-0.91667 -1.16667 -0.83333

0.34405 0.34405 0.34405

0.011 0.001 0.020

150

0 30 750

0.25000 1.16667 0.33333

0.34405 0.34405 0.34405

0.471 0.001 0.338

750

0 30 150

-0.08333 0.83333 -0.33333

0.34405 0.34405 0.34405

0.810 0.020 0.338

Leaf area

0 30 150 750

13.27667 2.87917 -21.47667

12.30823 12.30823 12.30823

0.287 0.816 0.088

30 0 150 750

-13.27667 -10.39750 -34.75333

12.30823 12.30823 12.30823

0.287 0.403 0.007

150 0 30 750

-2.87917 10.39750 -24.35583

12.30823 12.30823 12.30823

0.816 0.403 0.054

750 0 30 150

21.47667 34.75333 24.35583

12.30823 12.30823 12.30823

0.088 0.007 0.054

Plant height

0 30 150 750

3.84167 1.56667 -3.18333

2.99093 2.99093 2.99093

0.206 0.603 0.293

30 0 150 750

-3.84167 -2.27500 -7.02500

2.99093 2.99093 2.99093

0.206 0.451 0.023

150 0 30 750

-1.56667 2.27500 -4.75000

2.99093 2.99093 2.99093

0.603 0.451 0.119

750 0 30 150

3.18333 7.02500 4.75000

2.99093 2.99093 2.99093

0.293 0.023 0.119

Stem circumference

0 30 150 750

0.07500 -0.15833 -0.50000

0.15560 0.15560 0.15560

0.632 0.314 0.002

30 0 150 750

-0.07500 -0.23333 -0.57500

0.15560 0.15560 0.15560

0.632 0.141 0.001

150 0 30 750

0.15833 0.23333 -0.34167

0.15560 0.15560 0.15560

0.314 0.141 0.033

750 0 30 150

0.50000 0.57500 0.34167

0.15560 0.15560 0.15560

0.002 0.001 0.033

47

APPENDIX VIII

Multiple comparisons of vegetative parameters after crude oil pollution

Vegetative Parameters

Replicates

Mean diff.

Standard error

Significance

No. of leaves

0

30 150 750

0.75000 0.12500 0.33333

0.51430 0.57500 0.62988

0.154 0.829 0.600

30

0 150 750

-0.75000 -0.62500 -0.41667

0.51430 0.57500 0.62988

0.154 0.285 0.513

150

0 30 750

-0.12500 0.62500 0.20833

0.57500 0.57500 0.68035

0.829 0.285 0.761

750

0 30 150

-0.33333 0.41667 0.20833

0.62988 0.62988 0.68035

0.600 0.513 0.761

Leaf area

0 30 150 750

15.60500 -1.44125 9.53917

12.24655 13.69206 14.99890

0.211 0.917 0.529

30 0 150 750

-15.60500 -17.04625 -6.06583

12.24655 13.69206 14.99890

0.211 0.222 0.688

150 0 30 750

1.44125 17.04625 10.98042

13.69206 13.69206 16.20066

0.917 0.222 0.503

750 0 30 150

-9.53917 6.06583 -10.98042

14.99890 14.99890 16.20066

0.529 0.688 0.503

Plant height

0 30 150 750

3.70000 -1.25417 1.88333

2.93707 3.28374 3.59716

0.216 0.705 0.604

30 0 150 750

-3.70000 -4.95417 -1.81667

2.93707 3.28374 3.59716

0.216 0.141 0.617

150 0 30 750

1.25417 4.95417 3.13750

3.28374 3.28374 3.88537

0.705 0.141 0.425

750 0 30 150

-1.88333 1.81667 -3.13750

3.59716 3.59716 3.88537

0.604 0.617 0.425

Stem circumference

0 30 150 750

0.13333 -0.00833 -0.28333

0.15978 0.17864 0.19570

0.410 0.963 0.157

30 0 150 750

-0.13333 -0.14167 -0.41667

0.15978 0.17864 0.19570

0.410 0.433 0.041

150 0 30 750

0.00833 0.14167 -0.27500

0.17864 0.17864 0.21137

0.963 0.433 0.202

750 0 30 150

0.28333 0.41667 0.27500

0.19570 0.19570 0.21137

0.157 0.041 0.202

48

APPENDIX IX Comparisons of vegetative parameters before and after pollution for 0 ml contamination Vegetative Parameters

Sig. (2-tailed) Mean difference Standard error diff.

No of leaves Equal variance assumed Equal variance not assumed

0.003 0.003

-1.41667 -1.41667

0.42566 0.42566

Leaf area Equal variance assumed Equal variance not assumed

0.489 0.489

-10.53917 -10.53917

14.97079 14.97079

Plant height Equal variance assumed Equal variance not assumed

0.613 0.613

-1.88333 -1.88333

3.66992 3.66992

Stem circ. Equal variance assumed Equal variance not assumed

0.291 0.291

-0.15833 -0.15833

0.14631 0.14631

49

APPENDIX X Comparisons of vegetative parameters before and after pollution for 30 mlcontamination

Vegetative Parameters

Sig (2-tailed) Mean difference Std. error difference

Equal variance assumed Number of leaves Equal variance not assumed

0.001 0.001

-1.58333 -1.58333

0.38844 0.38844

Equal variance assumed Leaf area Equal variance not assumed

0.447 0.447

-8.21750 -8.21750

10.61548 10.61548

Equal variance assumed Height Equal variance not assumed

0.456 0.456

-2.02500 -2.02500

2.67068 2.67068

Equal variance assumed Stem circumference Equal variance not assumed

0.471 0.471

-0.10000 -0.10000

0.13633 0.13633

50

APPENDIX XI Comparisons of vegetative parameters before and after pollution for 150 ml contamination Vegetative Parameters

Sig. (2-tailed) Mean difference Standard error diff.

No of leaves Equal variance assumed Equal variance not assumed

0.097 0.145

-1.04167 -1.04167

0.59455 0.66009

Leaf area Equal variance assumed Equal variance not assumed

0.129 0.108

-14.86625 -14.86625

9.35482 8.78551

Plant height Equal variance assumed Equal variance not assumed

0.129 0.116

-4.57917 -4.57917

2.88185 2.76503

Stem circ. Equal variance assumed Equal variance not assumed

0.959 0.961

-0.00833 -0.00833

0.16072 0.16598

51

APPENDIX XII Comparisons of vegetative parameters before and after pollution for 750 ml contamination Vegetative Parameters

Sig. (2-tailed) Mean difference Standard error diff.

No of leaves Equal variance assumed Equal variance not assumed

0.012 0.034

-1.16667 -1.16667

0.41143 0.45449

Leaf area Equal variance assumed Equal variance not assumed

0.247 0.191

20.47000 20.47000

17.03699 14.90071

Plant height Equal variance assumed Equal variance not assumed

0.348 0.329

3.18333 3.18333

3.29128 3.12255

Stem circ. Equal variance assumed Equal variance not assumed

0.820 0.832

0.05833 0.05833

0.25277 0.26676