University of Nigeria Research Publications

UDOM, Bassey E. A

utho

r

PG/Ph.D/02/33437

Title

Bioremediation of Spent Oil-Contaminated Soil

Using Legume Plants and Poultry Manure

Facu

lty

Agricultural Sciences

Dep

artm

ent

Soil Science

Dat

e

March, 2008

Sign

atur

e

BIOREMEDIATION OF SPENT OIL - CONTAMIANTED SOIL

USING LEGUME PLANTS AND POULTRY MANURE"

BY

UDOM, BASSEY E.

PGIP h.Dl02133437

A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE

REQUIREMENTS FOR THE AWARD OF THE DEGREE OF DOCTOR

OF PHILOSOPHY (Ph.D) IN SOIL PHYSICS1 CONSERVATION

4

DEPARTMENT Or(' SOIL SCIENCE

UNIVERSITY Q,,F NIGERIA, NSUKKA - NIGERIA

, I . . .

MARCH, 2008.

CERTIFICATION

his is to certify that Udom, Bassey Etim, Postgraduate student in the Department of Soil

kience, with the Registration Number PG/Ph.D/02/33437, has satisfactorily completed the

equirements for research work for the degree of Doctor of Philosophy (Ph.D) in Soil Science

(Soil Physics1 Environmental Land Management).The work embodied in this thesis is original

and has not been published or submitted in part or full for any other diploma or degree of this, or

any other University.

(Supervisor) ead of Department

DEDICATION

This study is dedicated to Rose, Jane and Mfon-Obong, and to all those who played a major role

to keep the soil and the earth alive.

ACKNOWLEDGEMENT

I need to record my deep appreciation to a number of people and one hopes that the success of

this study will be an acceptable compensation for all their efforts. I will ever remain. most

grateful and indebted to my supervisor, Prof. J. S. C. Mbagwu for contributing valuable ideas,

materials and comments that served as the springboard for the success of this work. I wish to

express my deep appreciation to Prof. F. 0. R. Akamigbo, Prof. C. A. Igwe, Prof. M. E. Obi and

Prof. C. L. A, Asadu for their immense professional support, encouragement, aid fatherly

advice. I also wish to acknowledge the contributions of Chief T. A. Orji (Abia State Governor),

Dr. J. K. Adesodun and Dr. A. 0. Olojede for all their efforts and contributions toward the

success of this study.

I deeply wish to thank my wife, Mrs. Rose B. Udom, for providing unpaid material and

emotional support services, without which this work would not have been a success. I am

indebted to Dr. A. 0. Ano of the Soil Science Division, National Root Crops Research Institute,

Uinudike, who assisted in the soil analysis when financial handicap almost derailed the success

of this work. My appreciation also goes to Dr. M. J. Eka of Michael Okpara University of

Agriculture, IJmudike, and Mr.Lawrence Chukwu and Okon Udoh for their interest,

encouragement and support during the study. I also wish to acknowledge the contributions of all

laborat~ry staff in the Department of Soil Science who supervised the laboratory procedurcs in

the study . , ,, , . I . .?' % * '

I am also grateful to Bro. Godson Nnabuihe for painstakingly typing and putting this work

together, and to Bro. and Sis. W. N. 01010, for their encouragement and support. My appreciation also goes to all those who contributed in whatever form towards the success of this

1 f

study but whose names are not mentioned due to space.

BASSEY E. UDOM

TABLE OF CONTENTS

TITLE PAGE

CERTIFICATION

DEDICATION

ACKNOWLEDGEMENT

TABLE OF CONTENTS

LIST OF FIGURES

LIST OF TABLES

LIST OF PLATES

1,IST OF APPENDICES

ABSTRACT

CHAPTER ONE 1 .O INTRODUCTION

1.1 Objectives of the Study

CHAPTER TWO

Page

1

. . 11

. . . 111

iv

v . . .

Vl l l

ix

xi

xii . . .

Xlll

1

3 -

LITERATIJRB REVIEW 4

Properties of Spent Oil, Refine Gas Oils and Crude Oil 4

Petroleum Components and its Biodegradation 5

Physical and Chemical Properties of Petroleum Hydrocarbon 6

Properties Affecting the Fate and Transport of Organic Contaminants . , , . . w l . d . ')C

in the Environment 8

Solubility 11

Soil-Water Distribution Coefficient 11

Specify Gravity I S 12

Octanol-Water Partition Coefficient 13

Organic Carbon Partition Coefficient 13

Biodegradability 14

Effects of Petroleum and Oil-based Products on Soil Physical Properties 15

Effects of Petroleum and Oil-based Products on Soil Chemical Properties 16

Effects of Petroleum and Oil-based Products on Soil Health 17

Petroleum Products and Crop Production 18

Heavy Metals in Contaminated Soils

Methods of Cleaning Up Petroleum - contaminated Soils

Ex-situ Approach

Excavation

Soil-Washing

In-situ Approach

Bioremediation

Phytoremediation

Micro-organisms in Bioremediation

CHAPTER THREE 3.0 MATERIALS AND METHODS

3.1 Site Description 3 0

3.2 Experimental Design and Treatments 3 0

3.2.0 Waste Motor Oil 32

3.2.1 Legume Plants and Poultry Manure 32

3.3 Data Collection 32

3.4 Laboratory Studies 33

3.4.1 Particle Size Distribution, Pore-Size distribution and Bulk Density 3 3

3.4.2 Soil Moisture Retention and Hydraulic Conductivity 3 3

3.4.3 Measurement of Aggregate Stabgity .la ' 3 4

3.4.4 Measurement of Crusting Hazard and Dispersion Ratio 3 6

3.4.5 Soil pH, Total Organic Carbon and Nitrogen 36

3.4.6 Cation Exchange Capacity Total Exchangeable Acidity, Exchangeable Na, Mg, and I( and Available phosphorus . .' 3 6

3.4.7. Heavy Metal 3 6

3.4.8 Measurement of Electrical Conductivity, Salt Concentration and Osmotic Pressure 3 7

3.4.9 Sodium Adsorption Ratio (SAR) and Exchangeable Sodium Percentage (ESP) 37

3.4.10 Total Hydrocarbon Content (THC) 3 8

3.4.1 1 Biodegradation Rate (Hydrocarbon Loss) and Microbial Counts 3 8

CHAPTER FOUR

RESUL,TS AND DISClJSSION

Modifications in Soil Physical Properties

Texture

Aggregate Stability and Hydraulic Conductivity

Pore - Size Distribution, Organic Matter and Crusting Hazard

Bulk Density and Water Retention Characteristics

Salinity Characteristics

Relationships Among the Soil Physical Properties

Relationships Amongst Soil Physical and Salinity Properties

Chemical Properties

Distribution of Heavy Metals and Contaminant Limit (clp Index)

Other Chemical Properties

Total Hydrocarbon Content Distribution

Degradation of petroleum I-lydrocarbons and Correlation with heavy Metals

Biological Enhancement

Effects on Crop Performance

CHAPTER FIVE %

SUMMARY AND CONCLUSION

REFERENCES . , 1 . 0 )

Appendices

LIST OF FIGURES

Figure 1

Figure 2a

Figure 2b

Figure 3a

Figure 3b

Figure 4a

Figure 4b

Figure 5a

I

Figure 5b

Field Layout

Soil particle size distribution (0-30cm depth) at 3, 6, 12, and 18 months after oil applicatiori

Soil particle size distribution (0 - 30cin) depth) at 24, 30 and 36 months after oil application

Soil particle size distribution (30 - 60cm depth) at 3, 6, 12 and 18 months after oil application

Soil particle size distribution (30 - 60cin depth) at 24, 30 and 36 months after oil application

Voluinetric moisture content of the top 0 - 30cm at 3, 6, 12 and 18 months after oil application

Volumetric moisture content of the top 0 - 30cm at 24, 30 and 36 months after oil application

Volumetric moisture content of the top 30 - 60 cm at 3, 6, 12 and 18 months after oil application

Volumetric moisture content of the top 30 - 60 cm at 24, 30 and 36 months after oil ., ,, applicqJion + l *p

Page 3 1

4 1

4 2

4 3

44

66

67

6 8

69

LIST OF TABLES

Microbial genera degrading hydrocarbons in soil Table 1:

Table 2:

Table 3:

Concentration of heavy metals in soils

Some characteristics of the top 0 - 30cm soil of the experimental site, poultiy manure and spent oil used in the experiment

Table 4: Aggregate stability (MWD), of the oil-contaminated soil as influenced by the treatments.

Saturated hydraulic conductivity (cm hr-l) of the oil- contaminated soil as influenced by the treatments.

Table 5:

Unsaturated hydraulic conductivity (cm hr-l) of the oil- contaminated soil as influenced by the treatments.

Table 6:

Table 7: The state of aggregation of the oil-contaminated soil as influenced by the treatments.

Table 8: The potential structural enhancement index (PSEI) of the soil relative to the treatments.

Table 9: Pore-size distribution of the top 0 - 30cm of the oil-contaminated soil as influenced by the treatments.

<

Table 10: Pore-size distribution of the top 30 - 60 cm of the oil- contaminated soil as influenced by the treatments. . , 1 . 118

Table 1 1 : Soil organic matter (SOM) of the 0 - 30cm of the oil-contaminated site as influenced by the treatments.

Crusting hazard (%) of the top 0 - 30 cm of the oil-contaminated soil as influenced by the treatmeru .'

Table 12:

Table 13:

Table 14:

Bulk density of the soil relative to treatments.

Salinity characteristics of the top 0 - 30cm depth of the oil contaminated soil relative to treatments.

Table 15: Relationships among some physical properties of the oil contaminated soil

Table 16:

Tablc 17:

Table 18:

Table 19:

Table 20:

Tablc 2 1 :

Table 22:

Table 23:

Table 24:

Table 25:

Table 26:

Table 27:

Relationships among some physical and salinity p r o p d e s of the soil

Heavy metal concentration of the top 0 - 30cm soil of oil contaminated site

C/I-' index of the soil and some heavy metals as modified by the treatments

Chemical properties of the top 0 - 3Ocm soil of the oil contaminated site elative to treatments.

Chemical properties of the soil relative to treatment at the 30 - 60cm depth.

Changes in total hydrocarbon content (THC) of the soil by treatments.

Degradation of total hydrocarbon content (THC) of the top 0 - 30cm soil as influenced by the treatments.

Correlation between the residual tctal hydrocarbon content (mg kg-1) and heavy metals and nater holding capacity in the soil

Viable and hydrocarbon-degrading micro-organism populations in the contaminated soil as influenced by the treatments.

Mean height of maize plant in oil-contaminated soil under different treatments

Leaf area of maize plhht'dfl86r'aifferent treatments in the oil- contaminated soils

Effects of treatment on germination and grain yield of maize

LIST OF PLATES

1':) gc Plate 4.1 a: The Leucaena lziecocephala after 3.4 months of oil contamination 5 4

Plate 4.1 b: The Glicicidia sepium and Leucaena leucocephala at 36 months of oil contamination 5 4

Plate 4.2a: The experimental plots after 12 months of oil contamination 59

Plate 4.2b: 'The Gliricidia sepium after 36 months of oil contamination 5 9

LIST OF APPENDICES

P R ~ C Appendix 1 Particle size of distribution of the soil (g kg-') after 36 months

of oil application 131

Appendix 2 Volumetric moisture content (cm3 cm") of the soil as influenced by the treatments 133

ABSTRACT

Field experiment was conducted for three (3) years using legume plants and poultly manwc fo

improve the properties of spent-oil-contaminated soil, with a view to making it for crop

~ # F ? h m production. Three legume plants (Gliricidia sepiurn, Leucaena luecocephala, and Glapoj,

ctrerulean) alone or combination with 0.5% (w/w) poultry manure were tested for their abilitsr to

improve the physico-chemical properties of Nsukka sandy soil contaminatcd with equivalent of

50,000 mg kg-1 soil (5% wlw) spent lubricating oil, each for two years. The effects of this

bioremediation measures on crop performance were assessed using maize (Zea mnys) as test

crop. Contamination of the soil with spent oil increased soil bulk density, reduced saturated

hydraulic conductivity, decreased aggregate stability, and water retention at 0 kPa to -G kPa. At

12 and 18 months after oil contamination (AOC), the use of Gliricidia sepiunz combined with

0.5% (w/w) poultry manure increased the mean weight diameter (MWD) of water stable

aggregates by 58 and 94 percent respectively, and also increased saturated hydraulic conductivity Dtm J

by 1 36f1 87 percent respectively, when compared with the treatments without both G. sepium and

poultry manure (A5).The G. sepium combined with poultry manure also enhanced soil aggregate

sizc > 0.25 mm by 63.6 percent and showed a 3-fold positive modifications in soil macro-

por&~ity at 18 and 24 months after oil contamination. Water retention at -6 kPa, representing

field water capacity, increased with time in plots treated with the legume plants and poultry . ., .. I.,?. ' $ 8 '

manure, but very low in contaminated plots without any treatment. The legume plants

significantly (P < 0.05) reduced sodium adsorption ratio (SAR), exchangeable sodium

percentage (ESP), electrical conductivity, salt concentration, and osmotic pressure values of the

soil to negligible levels within 12 to 36 montjls after oil contamination. All treatments made

significant increases in soil organic matter over the control, whereas, plots treated with poultry

manure only showed significant (P < 0.05) reduction in organic matter from 20.6% in 3 months

to 19.2% in 36 months after oil contamination.

There was significant (P < 0.05) positive correlation (r = 0.795) between saturated hydraulic

conductivity (KsaJ and macro-porosity, and a highly significant (P < 0.01) negative correlation (r

= -0.91 8) between Ksat and micro-porosity. There was increase in Al, Ni, Pb, Zn, and Cu contents

xiv

in soils contaminated with spent oil and similar increases in soils treated with poultry manure. In

12 months after oil contamination, Al, Ni, Pb, Zn, and Cu concentrations in contaminated soil

increased by 43%, 158%, 702% 11 8% and 446% respectively, relative to the control. The

Gliricidia sepium with poultry manure significantly (P < 0.05) reduced the Al, Ni, Pb, Zn, and

Cu concentrations respectively by 21%, 96%, 90%, 42% and 50% relative to the A5 in 36 months

after oil contamination. The contaminant/pollution index (clp index) showed slight

contamination of the soil with Ni, slight to moderate contamination with Pb, moderate to severe

contamination with Zn, and very severe contamination with Cu via the oil contamination.

Available P, exchangeable, M ~ ~ ' ~ ca2+ and K' of the soil were low in the contaminated in

36 months after oil contamination, but showed increases in plots treated with legume plants and

poultry manure. High levels of total hydrocarbons (THC) persisted in the soil after 36 months of

oil contamination and were significantly detected in the subsoil. The Gliricidia sepium with 10

tons ha -' (0.5% w/w) poultry manure reduced 50,000 mg kg -' soil of spent oil to negligible level

in 208 days with total hydrocarbons (THC) degradation rate of 240 mg kg -' day ". In 36 months

after oil contamination, net loss of THC due to the effect of Gliricidia sepium combined with

poultry manure was 1 1.3% with THC degradation rate of 442 mg kg -' day -'. The numbers of

hydrocarbon-degrading micro-organisms (H-dms) were most abundant in the contaminated soil

than in the control

<

Maximum leaf area of 486.9 cm2 was measured at 91 DAP during the first planting, 449.7 cm2 at

96 DAP during the second planting seas~n,.~and~431.5 cm2 at 98 DAP during the third planting

season for A5+Gl+Pm. The G. sepium combined with poultry manure also gave maize grain

yield of 4.9 tons ha - I , 8.4 tons ha - I , and 6.5 tons ha -' during the first, second and third planting

seasons, respectively. Therefore, the oil clearly had detrimental effects on soil physical,

chemical, and biological properties. The oil alsot inhib'ited seed germination, depressed growth of

maize crop. The use of Gliricidia sepium , Luecaena luecocephala and Galapogonium caerulean

with poultry manure is effective in bioremediation of spent oil contaminated soils to enhance

growth and productivity of maize crop.

CHAPTER ONE

1.0 INTRODUCTION

The global emphasis on soil health and sustainable food security is persuading soil scientists

to consider rehabilitation of degraded lands, especially where oil-contamination limits the use

of land. Thus, information regarding the uce of legume plants species and organic manure to

improve the physical, chemical and biological properties of soils contaminated with

petroleum products, with a view to making them available for crop production, is very

important.

The indiscriminate discharge of petrol oils and grease into water drains, open vacant plots

and farm lands are becoming an acute environmental problem in Nigeria, particularly,'when

large areas of agricultural land are contaminated. In most cases, the soil may remain

unsuitable for crop growth for months or years, until oil is degraded to a tolerable level

(Anoliefo and Vwioko, 1995; Atuanya, 1987).

Spent lubricating oil, otherwise called waste engine oil, is usually obtained after servicing

and subsequent draining from automobile and generator engines by auto-repairers (Atuanya,

1987). It includes mono- and multi-grade crankcase oils from petrol engines, together with

gear oils and transmission fluids with significant levels of hydrocarbons and other

undesirable properties present in all petroleum products (Omoluobi, 1998). Government

efforts to monitor, control, .md/sr.v.regalate indiscriminate disposal of spent lubricating oil

onto agricultural lands have proven to be very difficult because of their short life span and

paucity of information. Thus, contamination of agricultural ecosystems arising from

discharge of petrol oils and grease is more widespread than crude oil pollution (Atuanya,

1987). ( 1

Depletion in the nutrient status (nitrogen and phosphorus), inhibition of microbial activities

and seed germination have been reported in spent-oil-contaminated soils (Atlas and Bartha,

1993; Kirk et al., 2005). The formation of waxy texture in soils contaminated with spent

lubricating oil has been reported to contribute to reduced oxygen content in such soils

(Anoliefo and Vwioko, 1995). The formiltion of oily scum, which impedes oxygen and

availability of water to biota as well as formation of hydrophobic micro-aggregates with clay

surfaces, are associated with oil-contaminated soils (Amadi et nl., 1993; Rasiah et al., 1990).

Decrease in soil water retention capacity at high potential (-I 0 to - 200 kPa), as a result of oil

succeeding water in the competition for pore spaces and also reduction in water film

thickness around macro-aggregates, are a few other effects of oil in soil (Rasiah et al., 1990).

Damage to cell membrane, chlorosis of leaves and dehydration in cereals has also been

reported in oil-impacted soils (Udo and Fayemi, 1975).

Literature reports many examples in which both singular bacterial strains and microbial

systems have been successfully utilized to reduce and/or transform selected pollutants in oil-

contaminated soil under laboratory conditions (Eschenhagen et al., 2003; Gallizia et al.,

2003; Harayama et al., 2004; Watanabe, 2001). The use of organic wastes, such as cow

dung, pig droppings and poultry manure (Adesodun 2004; Okurumeh and Okieimen, 1998)

and rubber processing sludge (Okieimen and Okieimen, 2002) have been reported to give

positive results in the remediation of oil-contaminated soils.

However, the use of green plants to rehabilitate soils contaminated with petroleum

hydrocarbons has recently become a subject of intense scientific interest in bioremediation

technologies (Merkl et al., 2005), Bioremediation of petroleum - hydrocarbon is presumed to

be based on the stimulation of microbial degradation in the rhizosphere. Plants can enhance

microbial degradation by providing oxygen in the root area along root channels and loosened

soil aggregates. Legumes are considered to be especially promising because of their nitrogen <

independence which is of significance in oil-contaminated soil (Merkl et al., 2005; Yeung et

al., 1997). . ,,. .*, T,. .>> '

Although major focus in the use of plants has been on heavy metal removal (Harayama et al.,

2004; Gallizia et al., 2003), information regarding the use of legume plants combined with

(or not with) organic nutrients to improve the properties of oil-contaminated soils, with a

view to making it available for crop production is limited (Rivera-Cruz et al., 2004; Mager

and Hernandez-Valencia, 2003). Hence, this study was conducted to bridge the gap in

information and experiences regarding the use of legume plant species and organic nutrient

to remediate oil-contaminated soils. Results will provide valuable input data in the

preservation of agricultural land and/or productivity with worldwide importance for the

establishment of bioremediation technology in tropical countries beyond Nigeria.

1.1 Objectives of the Study

The main objective of this study was to evaluate the effectiveness of three legume plants

(viz; Calopogonium cerulean, Gliricidia sepium and Leucaena le'ucocephala) and organic

manure (poultry manure) in restoring the physco-chemical properties of a spent-oil-

contaminated soil.

The specific objectives were to:

I. quantify some properties of spent-oil-impacted soil as influenced by three legumes

plants and poultry manure;

ii. study the effects of spent oil on soil and relate it to productivity of maize crop;

iii. assess the possibilities of the legume plants and poultry manure in bioremediation

technologies, and

iv. profer an effective and affordable scientific approach in remediation of soils

contaminated with petroleum hydrocarbons.

CHAPTER TWO

2.0 LITERATURE REVIEW

2.1 Properties of Spent Oil, Refine Gas Oils and Crude Oil

The spent or waste engine oil is usually obtained after servicing and subsequent draining

from automobile and generator engines by auto-repairers. It includes mono-and multi-grade

crankcase oils from petrol and diesel engines, together with gear oils and transmission fluids

with significant levels of hydrocarbons and other properties present in all petroleum products

(Omoluobi, 1998). In Nigeria, the Government has not been able to monitor and/or control

the discharge of petrol oils and grease from the thousand auto- repair workshops because

they have proven to be very difficult to regulate their activities by virtue of their small size.

Anon (1985) observed that Nigeria accounts for more than 87 million litres of spent oil

annually and that most heavy metals, such as Va, Pb, Al, Ni and Fe, which are below

detection in unused lubricating oil, showed high values in waste motor oil. Engine Oil, is a

petroleum product which aids in the reduction of friction between engine surfaces. It is

produced by vacuum distillation of crude oil and usually contains chemical additives

including amines, phenols, benzenes, calcium, zinc, barium, magnesium phosphorus, sulphur

and lead (Obidike, 1985; Kirk et al., 2005).

<

Crude Oil is largely formed biogenetically at temperatures below 2000°C from matter

deposited in shallow seas and sub~e~zrefitly'compressed by the overburden of deposited clays

and shales (Martin, 1990). An intermediate coal-like material, formed by bacterial action, on

the deposits, is known as kerogen. This, according to Martin (1990), may be one of these

types formed from algae, marine plankton or higher plants. The major compounds in crude

oil are alkanes and significant levels" of aromatic hydrocarbons. Crude oil is a highly

complex mixture, containing hundreds of thousands of hydrocarbons which can be divided

into three general classes consisting of saturated hydrocarbons aromatic hydrocarbons, and

polar organic compounds (Huesemann and Moore, 1993; Joner and Leyval, 2004; Kirk et al.,

2005).

Saturated hydrocarbons can be separated further into straight-chain and branched-chain

alkanes, as well as cyclic alkanes with varying numbers of saturated rings and side chains.

Aromatic Izydrocarbons contain one or more aromatic compounds such as benzene and

toluene to poly-aromatic compounds, such as pyrene. The polar fraction is made up of

compounds containing polar hetero atoms, such as nitrogen, sulphur, and oxygen (Kirk el al.,

2005; Joner and Leyval, 2003).

Crude oil from different locations varies in hydrocarbon composition. According to Martin

(1 99O), crude oil contains < 0.1 % to 5 - 6% sulphur, < 0.1 % to 0.9% nitrogen, and up to 20%

oxygen, on a weight basis. The most important trace metals in petroleum are vanadium and

nickel, both at concentrations of up to 300 mg kg-' and are present as organometallic

complexes. During the refining of crude oil, the various hydrocarbon products are separated

by fractional distillation at specific temperatures. Typical yields are: natural gas, gasoline,

kerosene, middle distillates (including heating oil, and jet and rocket fuels), wide-cut gas oil

(lubricating oils, waxes, feed stock for catalytic cracking), and residual fuel oil (bunker fuel

for ships and electrical utilities) (Nyer and Skladany, 1993). While these products are

generally spoken of as single entities, each is actually a complex mixture of many organic

compounds, with their distinct properties and behaviour when in contact with soil and.water

(Martin, 1990).

The source of the crude oil used for refining also has an effect on the composition of the final

petroleun~ products. For example, Nyer and Skladany (1993) observed that the gasoline

fraction, made from Controe, Texas crude oil contained 3.27% benzene and 16.9% toluene

on a volume basis, whereas the gasoline fraction made from Colinga, California crude oil,

contained only 2.22% benzene and 7.94% toluene on a volume basis.

Oils in general are relatively insoluble in water and are therefore associated primarily with

the particulate phase, especially, the organic matter. The contamination of soil and ground

water with mineral oils, hydrocarbons or mineral oil-based products is among the most

common negative effects of the industrial .s&iety. The causes of this contamination ranged

from production and transportation of mineral oil in the upstream areas to refining,

transportation and trading of oil-based products in the downstream areas (Brady a n d . ~ e i l ,

2002).

2.2 Petroleum Components and their Biodegradation

Crude oil is a complex mixture of several different structural classes of compounds such as

alkanes, aromatics, heterocyclic polar compounds, and asphaltenes. The rate of microbial

\,, degradation of crude oil depends on the interaction between the physical and biochemical

properties of these compounds (Uraizee, et al., 1998). The distribution of the various

structural classes and compounds present in petroleum influences the biodegradability of

individual hydrocarbon components. Walker et al. (1991) compared the biodegradation of

#6 fuel oil (Bunker C oil), which has significant amounts of sulphur, nitrogen, nickel,

vanadium, aromatics, resins and asphaltenes, to the biodegradation of #2 file1 oil, which has a

high aromatic content. The authors observed that 55% of the #2 oil was biodegraded

compared to only 11% #6 oil during the period. Biodegradation of South Louisiana crude

was also compared with Kuwait crude oil and found that biodegradation of light South

Louisiana oil, which is a low sulphur crude oil rich in saturates, was 82%, whereas Kuwait

crude oil, which is a high sulphur oil, rich in aromatics and resins, was degraded by only

51%. From these studies, it can be inferred that in addition to the different concentrations of

the various compounds in an oil, the distribution of the various oil fractions may play a key

role in influencing the availability of the biodegradable components. Katsivela (2005)

reported that the ability of mixed microbial cultures to utilize hydrocarbons present in four

crude oils depended not only on the concentration of the n - saturated fraction but also on the

asphaltene and nitrogen, sulphur, and oxygen (NSO) fraction of the oil.

2.3 Physical and Chemical Properties of Petroleum Hydrocarbon

Petroleum compounds can occur in a gaseous form that is often called nntural gas, as a

liquid called crude oil, or as a solid or semi-solid called asphalt or tar, associated with oil

sands and shales (Nyer and Skladany, 1993). These materials composed of hundreds of

complex molecular species,,.wLieh range from the gaseous hydrocarbon - methane with

molecular mass of only 16 g mole-' to substances having a molecular mass greater than 2000

g mole-' (Senn and Johnson, 1985). The major commercial products associated with

different distillation fractions of petroleum include gasoline, diesel, and fuel oils.

Gasoline is in general, a mixture of chemicals with boiling points less than that of decane

(those compounds with boiling points between 36°C and 173°C). Gasoline contains

relatively large concentrations of benzene, toluene, and xylene. Diesel fuels on the other

hand, consist primarily of higher boiling point, straight-chain alkanes. According to Kirk et

al. (2005), diesel fuel-contaminated soil is not expected to contain high concentrations of

aromatic compounds. Fuel oils are chemical mixture having boiling points greater than 68°C.

They can be distilled fractions of petroleum, residuum from refinery operations, crude

petroleum, or a mixture of two or more of these materials (Nyer and Skladany, 1993).

The number of carbon atoms present in gasoline, diesel, and fuel oils has a major effect on

the molecular weight, density, solubility, boiling point, and vapour pressure of these

compounds. Alkane chains up to 17 carbons in length, are liquid and have densities less than

that of water ( 4 g cm-').

Alkane chains, with 18 or more carbons in length are actually solids at room temperature and

commonly referred to as waxes (Nyer, 1993). Alkane solubility rapidly decreased as the

number of carbons present in the compound increased. The studies of Nyer and Skladany

(1 993), showed that pentane with a chain length of five carbons, has a solubility of 360 ppin

at 16"C, hexane (with six carbon atoms) has a solubility of 13 ppm and decane (with ten

carbon atoms) has a solubility of only 0.009 ppm at 20°C. They further observed that vapour

pressures decreased as alkane carbon numkers increased. High vapour pressure indicates that

a compound can easily volatilize whereas low vapour pressures are associated with chemicals

that are semi-volatile or non-volatile. Methane (a carbon), ethane (2 carbons), propane (3

carbons), and butane (4 carbons) are usually found as gases. For liquid alkanes, pentane has

a vapour pressure of 430mm of Hg at 20°C, hexane of 120 mm of Hg at 20°C, and decane of

only 27 mm of Hg at 20°C.

The aromatic fraction of petroleum products is perhaps the most important group of

chemicals from an environmental point of view. Benzene, toluene and xylene, each has

densities less than one. Bs;wenl;,,hashesn reported to be the most soluble aromatic fraction,

with solubility of 17.80 ppm at 20°C (Nyer, 1993) whereas toluene has a solubility of 5 15

ppm at 20°C. Vapour pressures for these compounds, according to Nyer and Skladany

(1993), are 760 mm Hg at 20°C for benzene, 22 mm Hg at 20°C for toluene and 6 mm Hg at

20°C for xylene. I,

For micro-organisms to biodegrade petroleum completely or attack even simpler refined oils,

thousands of different compounds must be metabolized. The chemical nature of these

petroleum components varies from the simple n-paraffin, mono-alicyclic, and mono aromatic

compounds, to the much more complex branched chains and condensed ring structures

(Premuzic et al., 1993). Therefore, many different enzymes are presumably necessary to

biodegrade these types of con~pounds.

Once petrolerrm hydrocarbons are introduced into lhe ra1\,'1 b+~~alr.nt, they inirrwt wiill fh.

surroundings soil environment. According to Joner and I ( - ' , \ ~ : r l (2003) and Glick V O 1 ) 3 ) ,

some of the ~najor processes affecting these chemicalc ; I * ( lwlc atlsorptio~~, r.11-wirnl

degradation, difrusion, volatilization, and biodegradation. P1:tty constitucnls nF ! ~ c t r . r % l r l ~ t t ~

products (such as the alkanes and aromatics) are non-polar ro~npounds and tlwrrrvrc hsve

only limited solubility in water. Cilick (2003) observctf r h t naturally occ~rrrin~: soil

compounds, such as humic and fi~lvic acids, may dissolve irl w t e r and help to c l i w d w 4 e r

non-polar compounds. Covalent bonding of contaminants In (he functional groups o f hrmic

molecules also served to immobilize contaminants. Thc s r ~ ~ d y further showcrl f lmt llie

cotnpounds that make up gasoline petroleum products had low solubility, low volatilit-i, and

strong adsorption characteristics and therefore, were the most prevalent in the, soil ~xchange

site. The compounds with high solubility were the most prevalent in the soil water, \v!icrcns

those with high volatility were most prevalent in the soil air. According to Ilraizee (lW8),

specific chemical properties affected the technologies that were used for remedialion as wcll

as for the methods used for analysis.

2.4 Properties Affecting the Fate and Transport of Organic Contaminants: in the

Environment

The environment plays a key role in the ultimate fate and transport of contaminants. The

specific fate of contaminants, following their release into the environment, depends on the I

chemical structure of the contaminants, which is highly variable (Brady and Weil, 2002).

Abiotic factors within the r.e~eidng mvironment (e.g organic carbon, pH, water, ctc), and

interactions with the biotic environment, can result in degradation, transformation, or bio-

concentration of the contaminants (Aichberger et al., 2005). When one of these critical

components was sub-optimal for conversion of organic contaminants (Aichberger el ul.,

2005) and biodegradation was slow mdid nit take place. Vezzulli et ol. (2004) and (iallizia

et al. (2005) observed that the rate of transformation of organic pollutants in soils was a

function of the availability of chemicals to the micro-organisms that can degrade them, the

quantity of those micro-organisms and the activity level of the organisms. Thus, contaminant

properties and soil characteristics can oiten provide a general indication of the applicability

of the treatment technologies available for remediation of the particular contamination

incident.

At given environmental conditions, the degree of hydrocarbon biodegradation is mainly

affected by the type of hydrocarbons in the contaminant matrix. Huesemann (1995) observed

that, of the various petroleum fractions, n-alkanes and branched-alkanes of intermediate

length (C10 - C20) were the preferred substrates for micro-organisms and were the most

readily degradable. Longer chain alkanes (> C20) are hydrophobic solids and are difficult to

degrade due to their inherent recalcitrance and their poor water solubility. Crude petroleum

and many of the refined petroleum products contain thousands of hydrocarbons and related

compounds. Some oils contain toxic hydrocarbons which may prevent or delay microbial

attack, whereas, some refined oils have additives, such as lead, which according to Katsivela

et al. (2005), inhibited microbial degradation of polluting hydrocarbons.

Under favourable conditions (Katsivela et al., 2005), micro-organisms will degrade 30 to

50% of crude oil residue. With favourablc conditions and the proper organisms (Mesarch et

al., 2000), virtually all kinds of hydrocarbons: - straight-chain, branched-chain, cyclic,

simple aromatic, polynuclear aromatic, and asphatic, have been found to undergo oxidation.

Each of these organic compounds has unique characteristics that dictate which mechanism or

a combination of mechanisms controls its movement and degradability. In another study,

Davis et a1.(2003) reported that for a s~rccessful biodegradation programme, the natural

heterogeneity of the soil system must be overcome, the rate- limiting factors must be

removed, and the microbial population prcxmoted to remove the organic contaminants.

According to Ram et al. (1993)? sjgnificant characteristics of organic wastes affecting their . ,,..* ,? .->

biodegradation included chemical composition of the waste, its physical state (ie. liquid,

slurry, and sludge), its carbon-nitrogen ratio, water content and solubility, volatility, pH,

biochemical oxygen demand (BOD) and chemical oxygen demand (COD). Boopathy (2002)

and Massias et al. (2003) observed that the'behaviour of toxic pollutants in the environment

also depended upon a variety of chemical processes (eg. hydrolysis, photolysis, oxidation,

reduction, hydration) and physical or transport processes (e.g advection, dispersion and

diffusion, sorption, volatilization, solubilization, viscosity and density).

Strong interactions between the soil matrix and hydrophobic pollutants, causing pollutant

retention or even irreversible binding to sorbents, had been observed (Huang et al., 2003).

This phenomenon, known as aging, increases with time and has been reported to

significantly reduce bioavailability of hydrophobic contaminants in the soil. Several studies

reported that the degree of hydrocarbon degradation was mainly affected by the type of

hydrocarbon in the contaminant matrix and only to a less extent by soil characteristics

(Nocentini et al., 2000; Breadveld and Sparrevik, 2001). This was true in particular, for soils

derived from further depths in the subsoil, where relatively low amounts of soil organic

matter (SOM) were present. Pollutant retention over time was governed by physical-

chemical characteristics of the pollutant and by soil characteristics. Strong or even

irreversible sorption onto soil (I-luang et al., 2003) was attributed to the soil organic matter.

Other factors, such as availability and type of electron acceptors, temperature, pH, moisture

content, availability of mineral nutrients and contaminants concentration, have been reported

to affect the degree of hydrocarbon degradation (Mohn and Stewart, 2000). Most petroleum-

related hydrocarbons are readily degraded via aerobic micro-organisms although, a number

of studies have shown that in the absence of oxygen with alternate electron acceptors, such as

nitrate, manganese (IV), iron (Ill), sulphatc and carbondioxide (Boopathy, 2002, Massias et

al., 2003), hydrocarbons can be biodegraded. Addition of nutrients was reported to have a

beneficiary effect on hydrocarbon degradation in the soil (Chaineau et al., 2003), whereby a

carbon: nitrogen: phosphorus (C:N:P) ratio of 100:lO: 1 was commonly proposed (Atagang et

al., 2003). Microbial activity proceeded optimally in the presence of water at between 50%

and 70% field capacity (Margesin et al., 2000).

The "quality" of organic matter (OM) is widely recognized to affect the rate and extent of <

OM decomposition and re-mineralization. Within the bulk of OM, proteins (PRT) and

carbohydrates (CHO) have been ., ,, identified .-,. ,, by several authors as the most bioavailable food

source for benthic microbial metabolism (Danovaro e t al., 1999; Meyer-Reil and Koster,

2000); in particular, PRT are more labile than CHO, and are considered the first organic

polymers to be degraded for bacterial metabolism, while CHO are more refractory to

consumption. According to Vezzulli e4, al. (2003), PRT and CHO concentrations can be

utilized as indicators of the biodegradation accruing in organic-rich soils.

Non-ionic and non-polar organic pollutants are normally adsorbed on soil humic materials

(Alloway and Ayres, 1997). Since most sc,il organic matter is found in the surface horizon,

there is a tendency for organic pollutants to be concentrated in the topsoil. Alloway and

Ayres (1997) further observed that migration of organic contaminants down the profile only

occurred to any marked extent in highly permeable sandy or gravelly soils, with low organic

matter contents and where large pores (macro pores) and fissures were present. Several other

physico-chemical parameters, which are useful in predicting the behaviour of organic

contaminants in soils, include a substance's solubility in water (mg L-I), its soil-water

distribution coefficient (kd), its specific gravity (dimensionless), its octanol-water partition

coefficient (b,) and its organic carbon partition coeficient (kc) and biodegradation

2.4.1 Solubility

Solubility is one of the most important properties affecting the fate and transport of organic

compounds in the environment. The solubility of a compound is described as the maximum

dissolved quantity of compound in pure water at a specific temperature (Nyer et al., 1993).

'I'he extent to which an organic compound (solute) dissolves in a solvent (water) is referred to

as the water-solubility of the compound and ranges from 1 - 100,000 mg L-' at ambient

temperature for most common organic compounds. Highly soluble compounds are easily

transported by the hydrologic cycle. The rate at which highly soluble compounds moved

through the unsaturated zone is controlled, to a greater extent, by the unsaturated hydraulic

conductivity in the porous media (Alloway and Ayres, 1997).

Compounds with high water solubility (fr.om spills) are reported to have shorter downward

travel times, low adsorption coefficients for soils and low bioconcentratio~i factors in aquatic

life (Nyer et al., 1993). Highly soluble compounds also tend to be more readily

biodegradable. For oil spills (Pfannkuch, 1985), the hydrocarbon components, with differing

solubilities, dissolved out differentially and produced a simultaneous aging and leaching

effect on the spills. Allowa~, and Ayms (1 997) observed that solubility usually decreased as

temperature increased due to an increase in water vapour pressure at the liquidlgas interface.

Degradation of polynuclear aromatic hydrocarbons (PAHs), in general, is limited because of

their lower solubility. Wiesel et al. (1993) observed that the order of degradation of PAHs

was related' to their water solubility, which -is invariably related to ring concentration. They

reported that the tetra cyclic compounds are less available than di-and-tri-cyclic compounds.

2.4.2 Soil-Water Distribution Coefficient

The soil-water distribution coefficient, k, is the proportion of the compound bound to the

solid relative to that remaining in solution at equilibrium. It is the simplest type of

adsorption isotherm, which assumes that the amount of contaminant sorbed is directly

proportional to the concentration of the compound in solution (Alloway and Ayres, 1997).

This adsorption coefficient (kd) of contaminants at different concentration is given by thc

equation:

where x = the amount sorbed per unit weight of soil c = concentration of substance in solution (,d~nl)

Brady and Weil (2002) defined kd as the coefficient of distribution between the sorbed and

solution portions of the organic compound. Thus,

kd = mg contaminantikg soil mg contaminant11 soil

It has been used to predict the behaviour of organic contaminant in soils.

2.4.3 Specific Gravity

Specific gravity is a dimensionless parameter derived from density. The specific

gravity of a compound is defined as the ratio of the weight of the compound of a given

volume and at a specified temperature to the weight of the same volume of water at the given

temperature. In environmental analysis, the primary reason for knowing the specific gravity

of a con~pound is to determine whether the liquids will float or sink in water. Pure

compounds that are lighter than water will form a layer on top of the water, whereas organic

compounds that are heavier than water will move through the aquifer until they are fully

adsorbed by soil matrix or-until~tby encounter an impenetrable layer (Nyer et al., 1993).

Migration of an immiscible organic liquid phase is governed largely by its density and

viscosity. Mckay et al. (1985) observed that density differences of about 1% significantly

influenced fluid movement on the!' surface soils. The authors further reported that the

presence of large quantities of high-density, low-solubility, non-aqueous - phase liquids

(NAPLs), such as gasoline and other petroleum distillates, was a potential source of long-

term contamination.

When a compound reaches an aquifer, its specific gravity will determine where it will most

likely concentrate. Low-density hydrocarbons have a tendency to float on water and may be

found in the upper portions of an aquifer, whereas high-density hydrocarbons will move to

the lower portions of the aquifer, if they are heavier than water. The studies of Allnwy and

Ayres (1997) showed that organic contaminants, such as gasoline, which is immiscible with

and less dense than water, migrated vertically through the soil to the water table and then

floated on the surface, spreading in the downward gradient direction.

2.4.4 Octanol-Water Partition Coefficient

The octanol-water partition coefficient (KO,) is defined as the ratio of a compound's

concentration in the octanol phase to its concentration in the aqueous phase of a two-phase

system. The coefficient, KO,, provides an indication of the hydrophobicity of a compound

(Alloway and Ayres, 1997). It is given by the equation:

where c, = the concentration of the substance in octanol, and

c = the concentration of tlie substance in water.

Low values (KO, < 10) indicate a relatively hydrophilic compound (low hydrophobicity) with

little likelihood of binding on soil organic matter. The greater the value of KO,, the greater

the pollutant affinity for lipids, and soil organic matter. KO, values for organic co~npounds

have been used to evaluate the fate of organic pollutants in the environment. The parameter,

according to Nyer et al. (1993), is related to the solubility in water and bioconcentration

effects, but mainly used to relate it to soil-sediment adsorption. When combined with the

organic matter content of the soil, I?,, values can be used to predict the amount of material

adsorbed in the soil and the retardation factor for movement through the aquifer. If the mass

of organic compound exceeds. .the,.adsorptive capacity of the soil, the contaminants will

continue to migrate until they reach tlie aquifer.

2.4.5 Organic Carbon Partition Coefficient

The organic carbon partition coefficient, ~ o c ' i s the amount of a compound adsorbed per kg

of organic carbon. It is given by the equation:

where k,, = soil - water distribution coefikient, and

f,, = the fraction of organic carbon in the soil.

Activated carbon has variable effectiveness in adsorbing organic compounds. Low

molecular weight polar compounds, are not well adsorbed. High molecular weight, lion-

polar compounds, such as pesticides, polychlorinated biphenyls, and aromatics are reported

to be readily adsorbed (USEPA, 1990). Nyer et al. (1993) used the activated carbon

adsorption isotherm data to evaluate the carbon adsorptive capacity for organic compounds

as well as the initial estimate of the organic mass that carbon will adsorb.

Brady and Weil (2002) noted that surface soil horizons, containing significant quantity of

humus, often exhibit much higher kd values because of the sorption of the organic

contaminant into the organic matter coatings. Thus, k,,, is often a better measure of a

compound's tendency to become immobilized in various surface soils.

Brady and Weil (2002) further observed that methods used to measure kd values involve

some disturbance of the soil material and consequently, may not accurately reflect the in-situ

soil conditions. Furthermore, kd values taken from the literature, may have been developed

using solid materials that differ significantly in physical and chemical characteristics from

the site of interest. They, however, concluded that, kd values from published literature can

provide a qualitative assessment of contaniinant's mobility in soils.

2.4.6 Biodegradability

This parameter is used to determine whether a compound is degradable, the most effective

biodegradation mechanism (aerobic vs anaerobic), and the biodegradation rate. Organic

compounds that are completely degradable, but slow, can be persistent in the soil

environment for a long period of time (Nyer ei al., 1993). Biodegradation potential of ., ... . . l ,r' , .13 '

organic contaminants has been studied, and classified as degradable, persistent, and

recalcitrant (IJSEPA, 1990). Readily degradable refers 10 compounds that have passed

biodegradability tests in a variety of aerobic environments. Persistent refers to chemicals that

remain in the environment for long periods.of time. These compounds according to USEPA I)

(1990) are not necessarily "non-degradable", but degradation requires long periods of

acclimation or modification of the envirmment to induce degradation. The study further

stressed that each organic compound must be evaluated to determine the estimated time to

complete the transformation of the chemicsl under optimal conditions.

Bossert and Bartha (1 994) reported an inverse correlation between the numbers of PAH rings

and their loss from soil. Biodegradation correlated positively with water solubility rather

than with the degree of condensation cluster against linear arrangement of the same number

of rings. Biodegradation has been shown to be a major removal mechanism for many PAMS

from soil. Its augmentation to accelerate hydrocarbon decomposition is an effective means

of hydrocarbon removal from the soil (Bossert and Bartha, 1994). Therefore, knowledge of

the mechanism of degradation and the factors controlling it, is necessary to achieve effective

bioremediation.

2.5 Effects of Petroleum and Oil-based Products on Soil Physical Properties

The presence of oily wastes makes soil constituents hydrophobic, but if the soil is properly

managed, the impact to the soil environment can be minimal. However, Rasiah et al. (1990)

reported that oil tends to accumulate in disposal sites in the long-term. Disposal of oily

wastes or oil spill may lead to formation of oily scum, which according to Amadi et al.

(1993), impedes Oz and water availability to biota and create anaerobic condition in the

subsoil, which aids the persistence of the oil.

Anoliefo and Vwioko (1995) observed that oil in soil created unsatisfactory conditions for

plant growth, probably due to insufficient aeration of the soil. The authors reported that this

condition was caused by the displacement of air from pore spaces by oil, and an increase in

the demand for oxygen brought about by activities of oil-decomposing micro-organisms.

McGill (1976) observed that oil occupied the macropores and coated macro aggregates,

reduced the water film thickness around macro aggregates and retarded the movement of

water into and out of micro aggregates. Rasiah et al. (1990) further observed tliat oil t

interacted with clay surfaces to form hydrophobic micro-aggregates. This suggests that

hydrophobicity and modification in hydraulic properties occur at the micro-aggregate level. . , 4 " . , ' 3 '

A general conclusion from studies on the effects of oil-based wastes on soil hydt-aulic

properties is that water retention is increased by their application to soil (Stevenson, 1987).

Kasiah et al. (1990) studied the soil physical conditions of a clay loam soil which had

received about 167,000 1 ha-' yr-' of oil from a waste water treatment plant, and observed tliat

water retention in the oily waste-contamillated soil was significantly low compared to the

non-contaminated soil. The low water retention suggested that oil had succeeded water in

the conlpetition for pore space. According to the study, the fact that the decreases in water

retention occurred at high potentials (-10 to -200 kPa) suggested that the competition

occurred for the macro-pores. The authors concluded that oily waste in the soil reduced

water retention at high water potentials while increasing the saturated hydraulic conductivity

and total pore volume. The unsaturated hydraulic conductivity was drastically reduced by

the oil waste. According to West et al. (1992) a reduction in porosity from 30 to 90%

resulted from the formation of structural crusts. Associated with the porosity decrease in

structural crust was a reduction in the mean size of pores. On the ability of soil micro

organisms to remediate oil-contaminated soils, Glick (2003) observed that the activity of soil

micro organisms on decomposition processes was found to be high at high water potential

than at low water potentials. Chenu el a/. (2001) observed that plant nutrition in oil

contaminated soils was controlled in part by the availability of nutrients within specific

layers or regions of soil aggregates and preferential movement of water. Soils contaminated

with oil, appeared waxy and usually did not allow water to penetrate from above.

2.6 Effects of Petroleum and Oil-based Products on Soil Chemical Properties

Depletion in the nutrient status (nitrogen and phosphorus) has been reported in spent oil-

contaminated soils (Atlas and Rartha, 1993). Amadi et a/. (1993) studied the effects of heavy

and moderate oil spill on soils and observed that the pH status of the soils in the

contaminated zones varied from acidic (4.0) to near neutral (6.0). The C content of the soils

decreased from 3.6% at the heavy impacted zones to 2.84% at the moderate impacted zones.

According to the study, total N in the heavy impacted and moderate impacted zones differed

by a fraction of 0.10%. Available P was higher at the moderate than heavy impacted zone,

while CEC decreased from a combined mean of 6.48 at the heavy impacted zones to 4.46 at

the moderate impacted zones.

Bossert and Compeau (1995) observed inhibition of microbial activities, such as nitrogen

fixation, algal photosynthesis.and.bacterial chemotaxis, in soils impacted with oily wastes,.

Studies of Amadi et a/. (1993) reported that organic C, total N, C/N ratio, available I',

exchangeable K and CEC were adversely affected in oil-contaminated lands. Alloway and

Ayres (1997) observed that the effect of oil and other pollutants on soil chemical properties

was determined by the soil pH, temperature, supply of oxygen, the structure of the

contaminant molecules, their toxicity and that of their intermediate decomposition products,

the water solubility of the contaminant and its adsorption to the soil matrix. It was further

observed that oxidation of organic pollutants occurred by the action of oxygenase enzymes

secreted by micro-organisms. In alkane hydrocarbons, the initial step in oxidation is the

conversion of a terminal CH3 groups to C02H group. According to the study, aromatic rings

were cleaved by the addition of OH to adjacent carbon atoms.

The decomposition products of some organic molecules are more toxic to soil micro-

organisms, animals and humans than the initial compound. For example, Alloway and Ayres

(1997) observed that the microbial oxidation products of PAH molecules were carcinogenic

because they were bonded to cellular DNA. Many organic pollutants are more rapidly

decomposed after they have been adsorbed on to the soil organic matter. Alloway and Ayres

(1997) reported that some xenobiotic organochlorine molecules, such as DDT, PCB's and

PCDDs, are generally regarded as being highly persistent in soils, with residence times of at

least 10 years. They have a very slow decomposition rate because the carbon-chlorine bond

is not found in nature and so most micro-organism species do not possess the enzymes to

break this bond.

2.7 Effects of Petroleum and Oil-based products on Soil Health

Soil is a complex microhabitat, regulating plant productivity and the maintenance of

biogeochemical cycles by the activity of micro-organisms able to degrade organic

compounds including xenobiotics. Petroleum and human industrial activities strongly affect

biological systems and more in particular, the soil status (Avidano et al., 2005).

According to Doran and Safly (1997), the soil health is the continued capacity of the soil to

function as a vital living system, within ecosystem and land-use boundaries, to sustain

biological productivity, promote the quality of air and water environments and maintain

plant, animal and human health'. Several bioindicators of soil health and quality have been

developed and reviewed (Nielsen et al., '2002; Anderson, 2003). Among them, micro-

organisms, due to their capability to respond quickly to environmental changes, are expected .,,, ... r . \ t , a

to be efficient bioindicators.

Microbial indicator has been defined as a microbial parameter that represents properties of

the environment or impacts to the environment which can be interpreted beyond the

information that the measured or observed parameter represents itself (Nielsen et al., 2002).

Microbial bioindicators could be based on functional land structural diversity of the bacterial

community. Functional diversity, according to Zak et al. (1994), is the number, type, activity

and rate at which a set of substrate is utilized by a bacterial community. Among the

functional diversity indicators, the carbon utilization pattern and the measurement of

enzymatic activities, expressed by the whole bacterial community, have been suggested as

useful tool to evaluate the soil status (Nielsen et nl., 2002). Structural diversity is the number

of parts or elements within a system, indicated by such measures as the number of species,

genes, communities or ecosystem. Several indices, such as species richness, diversity and

evenness have been used to describe the structural diversity of a community and to monitor

changes in microbial diversity due to environmental fluctuations, land management practices

and oil pollution and industrial activities (Ovreas, 2000), and was found to be very sensitive

to environmental pollution. Variation in microbial population and activity was reported to

function as a predictor of changes in soil health.

Avidano et al. (2005) observed a shiR in carbon substrate utilization patterns in soils

contaminated with oil and related it to the development of hydrocarbon utilizing bacterial

community. The study further showed that Pseudomonas and Bacillus micro-organisms were

prevalent in the oil-contaminated sites, whereas dramatic reduction occurred in the total

microbial community due to the additions of petroleum waste sludge. Katsivela et al. (2005)

reported that petroleum waste sludge sdversely affected the microbial population by

depleting essential inorganic nutrients and growth factors and lowering the pH immediately

around negatively charged surfaces.

Sensitivity of soil micro-organisms to petroleum hydrocarbons is a factor of the quantity and

quality of oil spilled and previous exposure of the native soil microbes to oil (Bossert and

Compeau, 1995). They observed that N-fixing and heterotrophic microbes relevant for

maintainace of soil health, were gradually eliminated in oil-spill sites. The very low NO3--

Nitrogen usually associated with oil-contaminated soils is the limiting factor to N-fixing and

heterotrophic microbes. Amadi et al. (1993) observed that N was limiting to oil degradation

by microbes because N and P,,ay.qiLbility were impeded by the presence of petroleum

hydrocarbons.

2.8 Petroleun~ Products and Crop Production

In petroleum-contaminated soils, plant growth is typically limited by nitrogen and

phosphorus as a result of the overabundance of carbon from the petroleum hydrocarbons

(Kirk er al., 2005). These authors further observed that because of the hydrophobic nature of

the contaminants, water and water-soluble nutrients are often limited. It was suggested that

arbuscular rnycorrhizal hngi (AMF) may reduce plant stress through an increase in water

availability and enhanced oxidative enzyme production (Joner and Leyval, 2004), thereby

increasing the volume of soil being remediated by the mycorrhizosphere.

The effect of oil on seed germination has been shown to be inhibitory due to unfavorable soil

conditions (Anoliefo and Vwioko, 1995). These authors reported that upon drying, the soils

contaminated with oil became too hard to allow germination. Also the reduced oxygen

content of the soil due to the blockage of pores in the soil, increased water stress on the seed

and imposed negative effects on germination (Atuanya, 1987).

Anoliefo and Vwioko (1995) observed that higher concentrations of spent lubricating oil in

the soil inhibited germination and growth of crops. Growth depression of Capsicum annum

L. and Lycopersicon esculenta when expressed in terms of height and leaf area reduction,

showed that C. annum plants exposed to 3% oil in soil after 84 days had grown to only 3.14

+ 0.6 cm tall, 16.3% of the control (19.2 + 0.2 cm) (Anoliefo and Vwioko, 1995). Also there

was more than 50% reduction in height when grown in soil treated with only 1% spent oil

compared to the control. Leaf area of C. annum was also affected by the oil, the degree of

reduction increasing with increasing oil concentration. The study further showed that the

effect of the spent lubricating oil was more pronounced on L. esculenta. They observed that

eighty-four days after sowing height and leaf area measurements were not possible as the few

plants which had germinated had died prematurely. It is generally agreed that contamination

of soil with petroleum hydrocarbons has pronounced effect on plant growth and that the

extent to which plants were affected differed due to an innate genetic response of the plant

system as modified by environmental influences (Atuanya, 1987). Baker (1970) reported

that oil penetrated and accumulated in plat.,& causing damage to cell membranes and leakage

of cell contents. Udo and Fayemi (1975) also reported that growth of cereals was adversely

affected by oil-polluted soil, resulting in chlorosis of the leaves and the plants became

dehydrated.

. ,, . . .x . \ t ' , .'.'

Merkl et al. (2005) observed that although Calopogonium mucunoides, Centrosema

hrasclianum and Stylosanthes capitata showed initial good germination and growth rates in

oil contaminated soils, all the plants died within six to eight weeks. Leaf length -of C.

mucunoides, C. brasilianum and S.1, capiiata was reduced by 60%, 65% and 66%,

respectively, compared to the uncontaminated control.

2.9 Heavy Metals in Contaminated Soils

Heavy metal is a general collective term applying to the group of metals and metalloids with

an atomic density greater than 6 g cm" (Alloway and Ayres, 1997). Although, it is only a

loosely defined term, it is widely recognized and usually applied to the elements such as Cd,

Cr, Cu, Hg, Ni, Pb and Zn, which are commonly associated with pollution and toxicity

problems.

The extent to which metals are adsorbed depends on the properties of the metal concerned

(valency, radius, degree of hydration and coordination with oxygen), the physio-chemical

environment (pH and redox potentials), the nature of the adsorbent (permanent and pH-

dependent charge, complex-forming ligands), other metals present and their concentration

and the presence of soluble ligands in the surrounding fluids (Alloway and Ayres, 1997).

Heavy metals tend to reach the environment from a vast array of anthropogenic sources as

well as natural geochemical processes.

Elements with no known essential biochemical functions are called non-essential elements

but are sometimes also referred to as 'toxic' elements. According to Ernst (1996), these

elements which include As, Cd, Hg and Pb, cause toxicity at concentrations which exceed the

tolerance level of the organisms, but do not cause deficiency disorders at low concentrations

like micronutrients. Ernst (1996) further reported that the toxic effects caused by excess

concentrations of these metals included competition for sites with essential metabolites,

replacement of essential ions, damage to cell membrane and reactions with phosphate groups.

Organisms have homeostatic mechanisms which enable them to tolerate small fluctuations in

the supply of most elements but prolonged excesses eventually exceed the capacity of the

homeostatic system to cope and toxicity occurs, which, if severe can cause the death of

organisms.

The danger of heavy metals is aggravated by their almost indefinite persistence in the

environment. Garbisu and Alkoqtq,.(2Qf)l) .. . observed that some metals are essential for life (i.e

they provide essential cofactors for metalhproteins and enzymes) but at high concentrations,

they can act in a deleterious manner by blocking essential functional groups, displacing other

metal ions or modifying the active conformation of biological molecules. In addition, they

are toxic to-both higher organisms and micr~organisms. Many metals affect directly various

physiological and biochemical processes, causing reduction in growth, inhibition of

photosynthesis and respiration as well as degeneration of main cell organelles (Vangronsveld

and Clijsters, 1994). Some metals have been reported to accumulate in roots (especially, Pb),

probably due to some physiological barriers against metal transport to aerial parts, while

others were easily transported in plants, for example, Cd (Udom et al., 2004).

According to Garbisu and Alkorta (2001) heavy metals cannot be destroyed biologically (no

degradation) but are only transformed from one oxidation state or organic complex to

another. The authors observed that as a consequence of the alteration of its oxidation state,

metal may become either: (i) more water soluble and are removed by leaching, (ii) inherently

less toxic (iii) less water-soluble, so that they precipitate and then become less bioavailable

or removed from the contaminated site, or (iv) volatilized and removed from the polluted

area. Devez et al. (2005) reported that, at high concentrations, copper (Cu) inhibited growth

and interfered with several cellular processes, including photosynthesis, respiration, enzyme

activity, pigment and protein synthesis and cell division.

Heavy metals exhibit toxic effects towards soil biota: they can affect key microbial processes

and decreased the number and activity of soil micro-organisms, thus affecting the biological

properties of such soils. Conversely; long-term heavy metal effects have been reported to

increase bacterial community tolerance (Baath et al., 1998) as well as the tolerance of fungi,

such as arbuscular mycorrhizal fungi (AMF), which can play an important role in the

restoration of contaminated ecosystem (Joner and Leyval, 2001). As a result of the adverse

effects of heavy metals and other contaminants, environmental agencies set critical levels in

soils, above which toxicity is considered to be possible. Nevertheless, micro-organisms

respond quickly to changes and can rapidly adapt to environmental conditions. Changes in

microbial population or activity can precede detectable changes in soil physical and chemical

properties, providing an early sign of soil improvement or an early warning of soil

degradation.

Micro-organisms can detoxifl , .~g\& .by valence transformation, extra cellular chemical

precipitation, or volatilization (Garbisu and Alkota, 2001). The study further showed that

some micro-organisms obtained energy growth by coupling the oxidation of simple organic

acids and alcohols, hydrogen, or aromatic compounds, to the reduction of Fe (IIl), or Mn

(1V). They suggested that bacteria that use iJ (IV) as a terminal electron acceptor may be

useful for removing uranium from contaminated sites and that the reduction of the toxic

selenate and selenite to the insoluble and much less toxic elemental selenium in the study

may be exploited to enhance removal of these anions from contaminated sites.

According to studies of Garbisu et al. (1 997), the more toxic form of chromium Cr (IV), can

also be detoxified by bacterially-mediated reduction of Cr (IV), to Cr (111) which is currently

being studied for commercial bioremediation. Another natural reduction process, being *

developed for commercial application, is the transformation of mercuric ion (Hg (II)), to

volatile metallic mercury, (Hg (0)). The studies of Lovely (1995) showed that micro-

organisms can also enzymaticlly reduce other metals such as technetium, vanadium,

molybdenum, gold, silver and copper.

Although it is true that micro-organisms that use metals as terminal electron acceptors or

reduce them as a detoxification mechanisms can be of use for the removal of metal pollutants

from the environment (Garbisu and Alkorta, 2001), it is certainly not less true that when

considering the remediation of a metal-polluted soil, metal- accumulating plants- offer

numerous advantages over microbial processes since plants call actually extract metals from

the polluted soils, theoretically rendering them clean (metal-free soils).

Heavy metals, with soil resilience times of thousands of years, have been reported to present

numerous health dangers to higher organisms (Garbisu and Alkorta, 2001). They are also

known to decrease plant growth, ground cover and have a negative impact on soil microflora.

liowever, a small group of plants can tolerate uptake, and translocation of high levels of

certain heavy metals that would be toxic to any other known organism. Such plants are

termed "lzyperaccumulrrtors". According to Brown et al. (1995), hyperaccumulator species

are those plants whose leaves may contain >I00 mg kg-' Zn and Mn (dry weight) when

grown in metal-rich soils.

C

2.10 Methods of Cleaning up Petroleum-contaminated Soils

Methods used in clean-up ofpetroleum~contaminated soils are often developed and evaluated

in order to conform with regulatory demands, which may require or suggest that residual

total petroleum hydrocarbon (TPH) concentrations in the soil are reduced below 100 mg kg-'

or in some areas, below 100 mg kg-' (TPH) (USEPA, 1991). There are many technologies

available for treating sites contaminated with petroleum hydrocarbons. However, selection

of any treatment method would depend upon contaminant properties itself, site

characteristics, regulatory requirements, costs, and time constraints. Two approaches have

been applied to enhance decontamination of soils with petroleum products. These are (i) ex-

situ, which involves removal of the polluted soil (excavation), transport to and cleaning

(washing) in a technical plant procedure and (ii) in-situ, which involves clean-up at the site

itself (Merkl et al., 2005, Van Gestel et al., 1992).

2.10.1. Ex-situ Approach

2.10.1.1. Excavation:

This is a common approach to dealing with contaminated soil. The excavated soil may be

treated on-site, treated off-site or disposed of in land fills without treatment. If treated, it

may then be returned to the excavation site. Excavation is easy to perform, and it rapidly

removes the contaminants from the site in a matter of hours, as opposed to other remediation

methods, which may require several months. It is often used when urgent and immediate

action is needed. However, the approach is often extremely costly and insufficient risk-

reducing (Van Gestel et al., 1992).

2.10.1.2. Soil-Washing

This is a variation of the soil flushing process, which is performed above ground in a reactor

and has been shown to be more effective than the in-situ flushing system (Alloway and

Ayres, 1997). Soil-washing approaches according to Alloway and Ayres (1997) overcome

some of the problems that may be encountered with the excavation methods. Soil-washing

systems include hot water system for removing oil from sandy soils, and a flotation process.

Other methods under the ex-situ approach include "enhance volatilization" process that

removes contaminants from soil by increasing their rate of volatilization through enclosed

mechanical aeration, mechanical volatilization, pneumatic conveyer systems, and low-

temperature thermal stripping (Alloway and Ayres 1997), Solidification/stabilizatio~z

approach incorporates chemical or biological stabilization processes to treat excavated,

contaminated soils. . ,, . ..,, %,. , . ,a

In-situ Approach ~4 1

t

This is the breakdown of organic sti organisms by breaking intra molecular

bonds. As a result, the micro-organisrris derive energy and may increase in biomass.

Naturally occurring micro-organisms may be able to biodegrade hydrocarbons and other

organic compounds in unsaturated soil and aquifers if the level of contaminations is low and

does not produce toxicity for the active bacteria (Molina- Barahona et al., 2004). Nyer and

Skladany (1993) observed that all the compounds found in gasoline, diesel, fuel oils and

grease were degradable by bacteria. Hydrocarbon biodegradation in soil can be limited by

many factors, for example: type of micro-organisms, nutrient, pH, temperature, moisture,

oxygen, soil properties and contaminant presence (Bundy et al., 2002; Molina-Barahoma et

nl., 2004).

2.10.2.1 Bioremediation

This is a natural or managed process, involving biodegradation of environmental

contaminants. Bioremediation treatment, in order to be effective, needs to fillfill some

requirements. These requirements are summarized by Margesin et al. (2000) as : (i) presence

of a suitable microbial community with the potential to enzymatically attack the target

compounds, (ii) presence of energy-rich electron donor, (iii) favourable environmental

conditions (temperature, pH, redox potential, etc), and (iv) pollutants (PAH, metals, phenols,

etc.), not in concentrations that cause inhibition to microbial metabolism.

Bioremediation involves the use of micro-organisms to degrade hazardous organic

constituents to harmless substances, such as carbon dioxide and water. The degradation

process according to Wilson and Jones (1992), may be enhanced by changing the chemical or

physical conditions in the soil, such as seil pH, moisture, and aeration, and also by nutrient

addition. The addition of nutrients was reported to have a beneficiary effect on hydrocarbon

degradation in soil (Chaineau et al., 2003; Breedveld and Sparrevik, 2001), whereby a

carbon: nitrogen: phosphorus (C : N : Pj ratio of 100 : 10 : 1 was commonly proposed.

Wilson and Jones (1992) observed that the addition of nutrient - an oxygen source (usually

hydrogen peroxide), and specifically adopted micro-organisms enhanced degradation and

that better results were achieved by drilling a series of walls throughout the contaminated

area and directly injecting the appropriate solutions. Wang and Bartha (1990) studies on

spills of the medium distillate fuels (i.e jet fuels, heating oil, and diesel, all of which contain

PAHs) showed< that bi~remediatian.~cooaisting of pH control, fertilization, and weekly filling

and involving the use of indigenous micro-organisms, was effective in increasing the rate of

biodegradation. They observed that after 20 weeks, the hydrocarbon content in the soil, for

all fuels, was reduced from 50 - 70 mg g-' soil to < 5 mg g-'. Soil contaminated with jet file1

was rapidly detoxified within two weeks. ~ h k toxicity of soil contaminated with the heating

and diesel oils initially increased but later decreased to background toxicity concentrations in

20 weeks. The authors further observed that phytotoxicity became insignificant after

hydrocarbon residues were reduced to < 15 mg g-' soil, which was attained after between

four and six weeks.

With the increasing attention towards environmental preservation, biological

decontamination of soils has become a valuable alternative to chemical treatment. Molina--

Barahonma et a1. (2004) looked at bioremediation as an ecologically acceptable technology

that uses micro-organisms to effectively degrade pollutants, such as oil and oil-products in

the environment. The authors considered biostimulation (improvement of pollutant

degradation by optimizing conditions such as aeration, addition of nutrients, pH and

temperature) as an appropriate remediation technique for diesel removal in the soil. The

study however, suggested the evaluation of both the intrinsic degradation capacities of the

autoclithonous microflora and the environmental parameters involved in the kinetics of the in

- situ process. One of such parameters was aeration which was improved by the use of plant-

crop residues that acted as bulking agent and also as bacterial biomass suppliers. The study

further showed that micro-organism metabolic activity increased significantly in the corn-

crop residue microcosm. The highest GO2 increase (25-fold) was observed on day 14,

followed by a 22-fold increase by day 22, and remained high about 4 - 5 fold by day 109 of

incorporating the corn - crop residue. During the first 66 days of the experiment, the C 0 2

production was significantly affected by factors such as C : N ratio (100 : lo), moisture

content (30%) and crop residue amount (3%) (Molina-Barahonma et ul., 2004). Changes in

the hydrocarbon-degrading microbial (H-dm) populations during the study showed that the

corn-crop residue microcosm produced the highest I-I-dm population count with 160,000 cfu

g" soil at day 55 and decreased to 16,000 cfu g-' at the end of the experiment.

2.10.2.2. Phytoremediation

Phytoremediation, otherwise called enhanced rhizosphere, degradation or plant-assisted

bioremediation, is the use of plants to provide a habitat conducive to microbial growth, as

well as contribute extra., d l u t a r .enzymes that assist in contaminant degradation.

Phytoremediation, according to Raskin el ul. (1997), is an emerging green technology that

uses plants to remediate soil, sediment, surface water, and groundwater environments

contaminated with toxic metals, organics, and radionuclides. Phytoremediation is an

effective, non-intrusive, and inexperisive rbeans of remediating soils. It is more cost-

effective than alternative mechanical or chemical methods of removing hazardous

compounds from the soil. Garbisu and Alkorta (2001) looked at phytoremediation as a

natural, aesthetically pleasing, technology that is socially accepted by surrounding

communities and regulatory agencies as a potentially elegant and beautiful technology.

Phytoremediation of organic contaminants has generally focused on three classes of

compounds: chlorinated solvents, explosives and petroleuln hydrocarbons. However, the

potential of phytoremediation in treating other organic contaminants including plynuclear

aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs), is still being studied.

Phytoremediation is a cost-effective in-situ technology that uses plants for the cleaning up of

soils contaminated with organics, inorganics or radionuclides. On petroleum contaminated

sites, phytoremediation can be applied at moderate contaminated levels or after the

application of other remediation measures as a polishing-step to further degrade residual

hydrocarbons and to improve soil quality (Garbisu and Alkorta, 2001).

According to Chen and Cutright (2001), central to phytoremediation are the plants and their

specific capabilities with regards to metal accu~nulation and resistance as well as their impact

on the rhizosphere microflora diversity, and metabolic activity. 111 the study of toxicity of

diesel fuel to germination, growth and colonization of Glomus intraradices in soil and in-

vitro transformed carrot root cultures, Kirk et al. (2005) observed that there were complex

interactions between plants, mycorrhizal fungi, other soil fungi, bacteria and the soil. Such

interactions, according to the study, influenced the plant/fungal relationships studied. They

concluded that since soil fungi and bacteria can degrade petroleum hydrocarbons, as well as

influence plant, the presence of all of these organisms affected the toxicity of petroleum

hydrocarbons to the plant and mycorrhizal fungi.

Phytoremediation of petroleum-hydrocarbons is presumed to be based on the stimulation of

microbial degradation in the rhizosphere. Plants can enhance microbial degradation by

providing oxygen in the root area along root channels and loosened soil aggregates (Yeung et

al., 1997). Micro-organisms are stimulated by root exudates. The authors studied 120 plant

species and found that each sp&~s,exudes a distinct set of compounds. They observed that

different species had varying effects on micro-organisms and their degradation activity.

At sites contaminated with heavy metals, phytoremediation can be applied as different

strategies based on the specific site conditidn. These may include phytoextraction where

metals are transported from the soil into the harvestable shoots (Garbisu and Alkorta, 2001),

rhizofiltration, where plant roots or seedlings grown in aerated water precipitate and

concentrate toxic metals (Raskin et al., 1997), phytovolatilization, in which plants extract

volatile metals (e.g Hg and Se) from soil and volatilize them from the foliage (Garbisu and

Alkorta, 2001), and phytostabilization, in which metal-tolerant plants are used to reduce the

mobility of heavy metals (Raskin et al., 1997). For sites contaminated with both heavy

metals and toxic organics, phytoremediation has been applied (Merkl et al., 2005), because

the rhizosphere association between plants and soil micro-organisms can be utilized to

degrade or transform complex organic - metal mixtures. This process has been called

phytotransformation or phytodegradation.

Merkl et al. (2005) used three legumes (Calopogonium mucunoides, Centrosema brasilianum

and Stylosanthes capitata) and three grasses (Brachiaria brizantha, Cyperus aggregates and

Eleusine indica) for phytoremediation of petroleum contaminated soils and observed that B

brizantha is a promising species for remediation of petroleum - contaminated soil. The plant

showed best biomass production and c.aused highest oil dissipation compared to the

unplanted soil. Ernst (1 996) observed that various grass species such as Festuca ovina, F.

rubra, Agrostis capillarus, A, delicarula and A. stolonifera, can evolve high degrees of metal

resistance. The author, however, reported that their potential for phytoremediation was low,

owing to low biomass production. The study further showed that slightly metal-polluted

soils can be decontaminated by enhancing growth of metal-resistant and accumulating plants

such as Cardaminapsis halleri, Thiaspi caerulescens and T. ceparifoluim and Alysum species.

Some authors (Stamps et al., 1994) also distinguished between indirect and direct

phjltoremediation. In the case of indirect phytoremediation (otherwise referred to as plant-

assisted bioremediation), plants participate in the detoxification of pollutants via their support

of symbiotic, root-associated, micro-organisms that actually accomplish contaminant

detoxification. On the other hand, plants could participate directly through contaminant

uptake and subsequent contaminant immobilization or degradation within the plant.

Phytoremediation is increasingly ., , , . . . . , being viewed as a cost-effective and user-friendly

alternative to traditional methods of environmental clean up. Ensley et al. (1997) concluded

that, optimizing agronomic practices, such as fertilization, planting and harvesting time and

the timing of amendment application will increase the efficiency of the phytoremediation

processes. ' I> . .

Micro-organisms in Bioremediation

Micro-organisms are the principal agents responsible for the recycling of carbon in nature.

Atlas and Bartha (1993) observed that in many soils, there is already an adequate indigenous

liydrocarbonoclastic microbial community, capable of extensive oil biodegradation, provided

that the environmental conditions are favourable for oil-degrading metabolic activity. It was

suggested by some researchers (Shailubhai, 1986; Atlas and Bartha, 1993) that all soils

except those that are very acidic, contained the organisms capable of degrading oil products,

and that the problem was actually one of supplying the necessary nutrients at the site.

According to Gibson (1982), the ability of micro-organisms to utilize hydrocarbons is widely

distributed among diverse microbial populations. Many species of bacteria, cyanobacteria,

filamentous fungi, and yeasts co-exist in natural ecosystems and may act independently or in

combination to metabolize aromatic hydrocarbons. Some of the common microbial genera

that can degrade hydrocarbons in the soil (Shailubhai, 1986) are shown in Table 1.

The overall effect of an organism on a complex substrate is measured by its capacity to attack

only certain substances or to accumulate intermediates that it cannot degrade. Gibson (1 982)

observed that extensive degradation of petroleum pollutants generally was accomplished by

mixed microbial populations, rather than single microbial species. Combinations of bacteria

and fungi provided twice as much degradation of mixed hydrocarbon substrates as do

bacterial or fungi strains individually.

It has been observed that in aquatic and terrestrial environments, micro-organisms are

the chief agents of biodegradation of environmentally important molecules (Alexander,

1980). He further reported that nearly 100 species of bacteria, yeasts, and mold representing

30 microbial genera had been discovered to have hydrocarbon - oxidizing properties.

Although many micro-organisms appear limited to degradation of a specific group of

chemicals, others have demonstrated a wide diversification of substrates they are capable of

metabolizing. Thus, heterotrophic bacteria are the most important organisms in the

transformation of organic hazardous compounds, and soil treatment schemes may be directed C

toward enhancing their activity.

Table 1: Microbial Genera Degrading Hydrocarbons in Soils

Bacteria Actinomycetes --- Fungi Yeast -- Achronohacter A ctiomyces Aspergillus Cnndida Bacillus Beijerinckia Clostridium Desztlforibrio Escherlchia Methanobacterium Micrococcus Mj~co bacterium Pseudomonas

Endomyces Cephalosporium Rhodotorula Nocardia Cunninghamella Torula

Trichoderma Saccharomj~ces

Thiobacillus Source: Shailubhai (1986)

CI-IAPrTER THREE

3.0 MATERIALS AND METHODS

3.1 Site Descripliw

'T'hc site was located on a 0.025ha. area on the Research Farm of' the 1Jniversity of Nigeria

Nsukka, (J,atitude 05" 52'N and Longitude 07" 24'E). l'hc soil is a Typic Kandizrstttlt

(Nwadialo, l989), derived from False - Fledded Sandstone (Akamigbo and Jgwe, 1990). The

mean sand, silt, and clay contents over the 0 - 30cm depth were 820, 60 and 120 g kg-',

respectively (Table 2). The average slope of the site is less than 5%. Rainfall in the area

occurs between March and October. More than 80% of the total annual rainfall is receivcd

between the months of May and October, with mean annual total in excess of 17001nni

(FORMECU, 1998). The mean annual maximum temperatuie varies from 27" to 32°C in the

period from March to May. The mean daiIy sunshine hours in the area are between 5 and 6 h

in the dry season and 3 to 5 h in the wet season (Inyang, 1978). In 2001, prior to the

establishment of the experiment, the site was planted to cassava.

3.2 Experimental Design and Treatments

The experiment was arranged as a Randomized Complete Block Design (RCBD), with nine

(9) treatments replicated in five (5) blocks, resulting in a total of 45 plots, each plot

measuring 2.5 x 1.5 m (Fig. I).

The treatments are: . , ,, . 4 * 7 . .P. . X J '

C Control (no soil contamination)

As Oil contamination alone

A5 + Le Oil contamination + Leucaena leucocephala

A5 + Ca - Oil contaminatioh + Calapogoniunz Caerulean

A5 + GI - Oil contamination + Gliricidia Sepiunz

A5 + Pm - Oil contamination 4- Poultry manure

Ag+Le+Pm - Oil contamination + L. leucocephala + Poultry rnanure

A5+Ca+Pn i - Oil contamination + C. caerulean + Poultry manure

A5+GI+Pm - Oil contamination + G. sepiunz + Poultry manure

Designation C t

As AS + Le As + Ca AS + G I AS + ym

Treatments Control (no soil conta ination) Oil contamination alon 1 Oil contamination + Leucaena leucocephala I

Oil contamination + Calapogonium Caerulean Oil contamination + Gliricidia Sepium Oil contamination + Poultrv manure

3.2.0 Waste Motor Oil

l'hc plots were impac(ed with equivalent of 50,000 mg kg-' (5% wlw) spent oil sorrrcetl

from petrol and diesel engines, together with gear oils and tt.~nwission fluids. T P nil was

applied in a single doses reached for two years.. Contami~infiw of the plots with the second

50,000 mg kg-' soil (5% wlw) load of spent oil was done 12 months afkr fhc first

contamination. By the second year of the experiment, oil -coilhminated plots had equivalent

of 100,000 nig kg-' soil, representing a total oil load of 10% (dw) . Some properties of the

spent oil used in the experiment are shown in Table 2. The control plots were prokcfed with

asbestos sheets driven to a depth of 30 cm i n the soil too prevrnt contamination ofthe control

plots from adjacent plots with spent oil. 'The plots were allowed for seven (7) days before the

introduction of the legume plants and poultry manure.

3.2.1 Legume Plants and Poultry Manure

Three (3) legumes: Calapogonium caerulean, Leucaena leucocephnln, and Gliricidia sepium

alone or combined with equivalent of 10 tons ha-' (0.5 wlw) of poultry manure were used lo

enhance biodegradation. The legume seeds and poultry manure were introduced to the plots

at (7) days after the oil contamination and allowed for incubation, fourteen (14) days, before

planting the maize crop. The Calapogonium caerulean was planted at 30 x 90 cm spacing,

giving a density of 37,000 plants ha-') The Gliricidia sepium and Leucaena le~mxaphnln

were planted at Im x 90 cm spacing, (density of 11,I 11 plants ha-'). FASR-W maize (Zea

ma-YS) cultivar was used as test crop, planted at 25 x 5 cm spacing, giving a density of 50,000

plants ha-'. The selection of . ,, the . . TI. ., lqp ,ye plants was based on their ability to grow fast,

generate high biomass, nitrogen - independent and encourage high population of petroleum -

degrading micro-organisms in the rhizosphere (Anderson et al., 1993). The Gliricidia and

Leucaenn are legume plants species, with massive root system, which penetrate the soil Tor

several metres (Stamp et al., 1994). The leguqie plants used were regularly pruned to prevent

shading of the maize and the biomass worked into the soil

3.3 Data Collection

Disturbed and undisturbed (core soil) samples were collected from the 0 - 30 and 30 - 60cm

depths in duplicates at 3, 6, 12, 18, 24, 30, and 36 months after oil-contamination, for

measurements of some physical, chemical, and biological properties. Soil samples for

microbial population counts were collected at 3, 12, 24 and 36 months after oil thc first oil

contamination.

The implication of the oil and treatments on maize pelfwm~!~cc, wcre evaluated using

germination index measurement, at 2-1 weeks after planting. h h i ? ~ plant heiglit nntl leaf area

were measured at thc crop's growth stages (FAO, 1979) viz: 0 - establishment (10% of

vegetative phase) (28 - 30 days after planting), 1 - vegetatiw (80% of vegetative phase) (10

- 48 DAP), 2 - tasseling (65 - 72 DAP), 3 - cob setting/coh filling (93 - 96 DAP) and grain

yield at maturity. The residual effects of the treatments on maize growth and development

were evaluated from the agronomic parameters collected tlr~ring the third planting season.

liarvesting took place in each year when the maize dried sufficiently in all treatments, thus,

harvesting occurred on different dates each year. The dry mnize cobs were shellccl, and the

grain yield measured at 14% moisture content.

Leaf area (A) was determined by the method of Shih and Gastro (1 990) as:

A = I(LB ( 5 )

where A = leaf area (cm2), L = Leaf length (cm), B = Breath at mid-point, and K = Reduction

factor determined for the crop under investigation.

Laboratory Studies

Particle Size Distribution, Pore-Size Distribution and Bulk Density

Particle size distribution was determined by the method of Gee and Bauder (1986) with

sodium hexametaphosphate (Galgon) as the dispersing agent. The pore-size distribution was

calculated using the Flint and Flint (2002) water retention data as:

Total porosity = Volume of water in the soil at 0 kPa ( ~ ~ 3 1 Volume of bulk soil (cm3)

Macro porosity - - - Volume of water drained out at -6 kPa ~ c n i ~ ) Volume of bulk soil (cni3)

Micro porosity - - M u m e of water retained out at -6 kPa (cm3) Volume of bulk soil (cm3)

Bulk density was determined by the method described by Black and Hartge (1986):

Bulk density (g = Mass of oven dry soil (g Volume of bulk soil (cm')

Soil Moisture Retention and Hydraulic Conductivity

Water retention capacity at 0 kPa to -1 0 kl'a was measured with the aid of tension tables by

standard gravimetric method as described bv Galganov et al. (1993). The eravimetric

n7Gst11re content was converted to volumetric moistwl. r w f ~ n t by mulliplying the

pvimetric moisture retention values with the correspondinr I . k r h density values. Sat~~ra(ed

hyrlraulic conductivity (kSat) was determined by the consf~111 VIVI permearnctor technique

(Klute and Dirksen, 1986). Volume of water draining out \ n r m - . r~?rasured over time periods

until flow was constant, at which time, the final flow rate wl: ~~(.trrmined from the equation:

K sat =Q.l AT A H

wliere Q is the vol~lrne of water (cm3) that flows through a cross-sectional area A in

time 'T (sec.), and AH is the hydraulic head difference imposed across the core sample of

length L, (cm). Unsaturated hydraulic conductivity, K(,,, was predicted from atad soil

moisture retention characteristics data as proposed by Campbell (1974), and confir~rred to be

reliable by Rasiah et al. (1990). In this procedure, the pressure potential, IJ,, is related to the

relative saturation water content (Q,/Qs) by a power function equation:

and

(26+3) K(,) = KWt [Qv /Qs ]

where b and c are fitting parameters, and H,, K(o), Q,, KSat, and Qs are, respectively, the

pressure potential, unsaturated hydraulic conductivity (cm hi'), volumetric moisture water *, ,, . "1. 7,. % .,*

content at any specific matrix potential (cm ~ m - ~ ) , saturated hydraulic conductivity (an hf'),

and volumetric moisture content at saturation (cm cm"). A soil water matrix polentin1 of -6

kPa (60 cm water suction or tension), representing field capacity which drained pores >50

pm equivalent cylindrical diameter (transmission pores), was used. 'The b estimate obtained

for equation (7) was used in equation (8) to predict K(,) for the soil.

3.4.3 Measurement of Aggregate Stability

Aggregate stability was measured by the mean weight diameter (MWD) of water- stable

aggregates as described by Kemper and Rssenau (1986). In this procedure, 20 g soil samples

of < 4.75 mm aggregates were placed in the topmost of a nest of sieves of diameters 2, 1, 0.5

and 0.25 mm,. presoaking the sample in distilled water for 10 minutes and oscillated

vertically at one oscillation per second in water 20 times using a mechanical agitator. The

resistant aggregates on each sieve were dried at 105'C for 24 hours and weighed. 'The mass

of < 0.25 mm fraction was obtained by difference between ( ' - 1 - initial sample weight mrd the

sum of sample weights collected on ihe 2, 1, 0.5, and 0.25 ~ 1 1 , sieve nest. The gerr,cntagc

ratio of the resistant aggregates on each sieve, represenfinr: (he water-stable aggrcgatcs

(WSA) was calculated as:

where, MR = the mass of resistant aggregates (g)

MT= the total mass of wet-sieved soil (g)

Aggregate stability was measured by the mean-weight diameter (MWD) of water-stable

aggregates, calculated as:

where X, = the mean diameter of each size fraction (mm) and Wi = the proportion ofthe total

aggregates in each size fraction.

The state of aggregation (SOA) was calculated using the Yoder (1936) method as:

where A = the aggregated particle with diameter > 0.25 min

and y = the original weight ., ,, + " I . ofovt;n-dried . soil.

Potential structural enhancement index (PSEl) was used to measure the effect of the

treatments on aggregate stability, and calculated as:

where PSEl = the potential structural enhancement index

MWD, = the mean weight diameter for control (tnm)

MWDt = the mean weight diameter for treated soil (mm)

Positive value indicates contribution to structural enhancement, whereas negative value

indicates no contribution

3.4.4 Measurement of Crusting Hazard and Dispersion Rnd;tb

Crusting hazard (risk of sealing) " R , was calculated and classified using the Van dcr Watt

and Claasens (1990) method as

%organic matter loo R(%) = - x --

% clay + %silt 1

According to Van der Watt and Claasens (lY90),

I< values - < 5% high, 7% threshold value, and >9% low

The dispersion ration (DR) was calculated using the Middleton (1 930) method as,

where, a = percent silt + clay in water - dicpersed sample

and b - percent silt + clay in sodium hexamctaphosphate-dispersed sample.

Soil pH, Total Organic Carbon and Nitrogen

Soil pH was measured with a glass electrode in a 1 : 2.5 soil/water aqueous solution

(McLean, 1982). Total organic carbon (TOC) was determined by the Walkley and nlack wet

dichromate oxidation method (Nelson and Sommer, 1982). Total nitrogen was measured by

the macro Kjeldahl digestion pmceldtl're iiS described by Bremner and Mulvancy (1 982).

Cation Exchange Capacity, Total Exchangeable Acidity, Exchangeable NR, Mg,

and K and Available Phosphorus

Cation exchange capacity (CEC) was betermined by the ammonium acetate displacement

method. Total exchangeable Ca and Mg were determined using the EDTA complexonietric

titration method, and exchangeable Na and K by flame photometry. Available P was

measured by the Bray 11 soil extractant method as described by McLean (1 982).

3.4.7.. Heavy Metal

Heavy metals (Pb, Ni, Zn and Cu) concentrations in the soil at each sampling period were

measured by atomic absorption spectrophotometer (AAS) after digesting 3 g air-dried soil

sample in concentrated I-IC104-FIN03 (Carter, 1993). The values were compared \ w i r l ~ the

widely used normal and critical levels of total concentrnfirw of heavy metals for soil by

Environmental Agencies given by Kabata-Pendias and Penclias (1984) as cited by Alloway

(1990) (Table 3). The contaminant limit (c/p index) was cal(wlated as the ratio between the

heavy metal content in the soil and the toxicity criteria ( the tolerable; levels) of Kahata-

Pendias and Pendias (1984). The c/p index values < 1 indicate soil contamination range,

values >1 indicate pollution range. The result was further classified according to Lacatusu

(1998) as: very slight (clp < 0.1). slight (0.1 - 0.25), moderak (0.26 - 0.50), sevrre (0.51 -

0.75) and very severe contamination (0.76 - 1.00), and that of pollution range as: slight (I. 1

- 2.0), moderate (2.1 - 4.0), severe (4.1 - 8.0), very severe (8.1 - 16.0) and excessive

pollution (> 16.0).

3.4.8.. Measurement of Electrical Conductivity, Salt Concentration and Osmotic

Pressure

Electrical conductivity, salt concentration and osmotic pressure were measured in 1 :2.5 (soil:

water) aqueous extract at 25OC as described by Black et al. (1965). Electrical conductivity

(Ecc) was measured with conductivity meter and calculated as:

E,, (mm hos Cm-') at 25'c = 0.001 4 1 18 x kXt x Rstd 1

where, 0.00141 18 = Electrical conductivity of the standard 0.01N KC1 solution at 25'c,

Re,, = Specific conductance of the extract ( S cm"),

Rstd = Specific conductance,of.the standard (S cm-I), Salt concentration (mg I-') = 640 x

Electrical conductivity (mm hos cm-'), Osmotic pressure (atm) = 0.36 x Electrical

conductivity (mm hos cm-I); Salinity hazards were classified according to Bernstein (1 964).

4.3.9.. Sodium Adsorption Ratio (SAR) Pnd Exchangeable Sodium Percentage (ESP)

Sodium adsorption ratio (SAR) was calculated using the United State Salinity Laboratory

Staff Procedure (USSLS, 1969) as:

SAR - Na'

and, exchangeable sodium percentage (ESP) calculated as:

3.4.11 0 Total Hydrocarbon Content (THC)

Total hydrocarbon (TI I) at each sampling date (MA A) wiv cfctermincd gravin~etrically ~ J J

toluene extraction (cold extraction) method as described by Odu et a/. (I989), to providc an

estimate of organic and bioavailable forms of total hydrocahn content (TI-IC). The liqllid

phase of the cold extract was measured with a spectroyhotrmeter and fitted into standard

curve derived from fresh spent oil treated with toluene

3.4.11 Biodegradation Rate (Hydrocarbon Loss) and Microhinl Count

Average biodegradation loss rates (mg kg-' day-') of hydrocarbons under different treatments

were estimated according to Yeung et al. ( 1 997) as:

where, AHI, = the average hydrocarbon loss (mg kg-' daym')

HCi,,, = the initial hydrocarbon content in soil (mg kg-')

llCend = the hydrocarbon content when the experiment ended (mg kg")

Timei,,, = the degradation time (d)

The viable counts and hydrocarbon-degrading micro-organisms (H-dm) were measured by

direct microscopic counts after treating the samples, with MacConkey Agar Crystal Violct

and nutrient Agar Plates media, as described by the National Research Council (1993) and

Horowitz et al. (1 978).

Table 2: Concentration of Heavy Metals in Soils

A g 0.01 - 8.0 20.0 AS 0.1 - 40.0 20.0-50.0 AU 0.001 - 0.02 Cd 0.0 1 - 2.0 3.0 -- 8.0 CO 0.5 - 65.0 25.0 - 50 Cr 5.0 - 1500 75.0 -- 100 C IJ 2.0 - 250 60 - 125 tlg 0.01 - 0.5 0.3 - 5.0 Mtl 20.0 - 1000 1 500 - 3000 MO 0.1 - 40.0 2.0- 10 Ni 2.0 - 750.0 100 Pd 2.0 - 300 100 - 400 Sb 0.2 - 10.0 5.0- 10 Se 0.1 -- 5.0 5.0- 10 Ti 0.1 -0.8 1 .O U 0.7 - 9.0 Zn --- 1.0-900 - 70 - 400 ---

Soarce: Kabata-Pendias and Pendias (1984)

CHAPTER FOUR

4.0 RESULTS AND DISCUSSlON

4.1 Modifications in Soil Physical Properties

4.1.0 Texture

The particle size analysis (Figures 2a, 2b, 3a and 3b) showed h t the site is sandy loam. The

sand, silt, and clay contents range from 654 - 818, 21 -- 100, and 121 - 197g kg-',

respectively. Siltlclay ratio is 1:2 at the fop 0 - 30 cni (Table 3). However, the ubsrrved

variations in the particle size fractions due to treatments did not alter the soil textural class.

This showed that application of oil to land does not alter the soil textural class. Rather, it is

the dominant particles from parent material that influence the soil textural class (Akamigbo

and Asatlu, 1983). The clay and silt contents were generally low, confirming highly

weathered soils of the South eastern Nigeria.

4.1.1 Aggregate Stability and Hydraulic Conductivity

Aggregate stability and hydraulic conductivity of the soil are shown in Tables 4 and 5. The

mean weight diameter (MWD) of water stable aggregates improved with time in all the

treatinents except in As (soil contaminated with oil without legumes andlor poultry manure)

and control (Table 4). The top soil MWD decreased from 1.44 mm at start of the experinletit

(Table 3), to 0.801 mm in 36 months ,, . .*!. in the As. After 12 and 18 months of oil contamination,

the combined effects of Gliricida sepium and poultry manure As+GI+PM gave an

improvement of 58% and 94% in MWD, respectively, with corresponding increases of 136%

and 187% in saturated hydraulic conductivity over the A5 (Table 5). This improvement

showed that the use of Gliricidiu sepium wiih 10 t ha" poultry manure was effective in

bioremediation of aggregate stability and saturated hydraulic conductivity of spent-oil-

contaminated soil. The subsoil aggregate stability showed similar trend as that of the topsoil.

There were significant (P < 0.05) modifications in aggregate stability and hydraulic

conductivity between 12 and 36 months.

Particle size distribution (g kg-1)

Partide size distribution (g kg-1)

Particle size distribution (9 kg-1

Particle size distribution (g kg-1)

-NwPvIQ)-Q)w 0000000 oooooooo88

, " = = . = = = a

(e) 24th March

Treatments

mSand .Silt OClay

S a n d

.Silt

OClay

r

S a n d

.Silt

OClay

Treatments

Fig. 2b. Soil particle size distribution (0-30 cm depth) at 24, 30 and 36 months after oil application.

Partide size distribution (9 kg-1

Particle size distribution (9 kg-1

Particle size distribution (9 kg-1 )

Particle size distribution (9 kg-1)

S a n d .Silt 0 Clay

Treatments

(9 30th Month .Sand m Silt 0 Clay

Treatments

9007 0

800. (g) 36th Month

700. Sand

5 - 6 0 0 . usit 56 500. 0 Clay Ex400. '5 S 300 d .- 200. r, loo* n. 0

I) . . Fig. 3b. Soil particle size distribution (30-60 cm depth) at 24, 30 and

36 months after oil application.

Table 3: Some characteristics of the top 0-30cm of lhe cxpcrimental site, ~ltry -_ manure and spent oil used in the e ~ e r i w c n t -- - - --- - -

Poultry Sperit I'aramcter - .- -- - - - U~nit Soil ~~ lan l~re oil -- - - Sand (200 -- 50 p r ) g kg-' 820 - - Silt (50 -- 2 /m5) g kg-' Clay (< 2 pnz) g kg-' Texture Organic carbon g kg-' Total N g kg-' C : N P" (F 120) Available P mg kg-' Ca C mol kg-'

M g C mol kg-' K C mol kg-' Na C tnol kg-' Exchangeable acidity C mol kg-' ECEC C mol kgs' Saturated hydraulic conductivity cm h i ' Aggregate stability (MWD) m m Bulk density g c ~ n - ~ Water holding capacity cm3 (;m-3 Macro-porosity ?4 Micro-porosity YO Total porosity O/o

Specific gravity - Pb mg kg-' N i mg kg-' Zn - ,< . 4 -1. 7,. ni'i kg" Cu -- -- mg kg-' --

a == nutrient determinations in poultry manure was by total extraction (I-IC104 - I-1~0.1)-

60 120

sandy lonrri 6.81 0.76 9: 1 4.7 8.68 1.93 0.98 0.19 0.10 2.6 5.8

20.44 1.44 1 .52 0.3 1

22.0 29.7 5 1.7

- 1.48 0.24

18.6 7.0

-

28.6 4.5 6: 1 6.5 13.7

9 9 s a 1 9.2a 5.1a 1 .9da

- -

- - - -

-

BDL 2.01

185.8 46.1

digestion method (ing k g 1 ) b = Values in mg I-' , BDL = Below detection limit

Table 6: Unsaturated hydraulic conductivity of the oil-contaminated soil -

as influenced by the treatments -- K,at (cm hi')

Treatment -- Months after oil application -

-- --- 3 6 12 18 24 30 36 -

Table 4: Aggregate stability (MWD) of the oil-contaminated soil as influenced by the treatments

-- - . - - M WD (mm) --

Months After Oil A p e a t i o n Treatment - 0 3 6 12 -- 18 24 3 0 _ - _ 36 _

C =- Control, As = 5% (wlw) Spent oil, GI = Gliricidia spp, Le = Leucaena spp, Ca = Calap6@fii~lm spp, Pm = 0.5% (wlw) Poultry manure

Saturated hydraulic conductivity, as low as 8.64 cm h i ' obtained for the top soil of Ag in 18

months and 8.62 cm h i ' in 36 months (Table 5) suggests that the oil succeeded water in the

competition for pore spaces, leading to reduction in water film thickness around the macro-

aggregates (Rasiah et nl., 1990). Also the relatively high value of 1.72 mm in MWD (Table

4), without corresponding increase in saturated hydraulic conductivity (10.15 cm hr") in 3

months (Table 5), was not surprising, as this may have been due to the formation of

hydrophobic macro-aggregates, reported for similar soil conditions by Amadi et al. (1993),

and Kirk et al. (2005).

After 36 months, the modifications in aggregate stability was in the order of A5 + GI + Pm >

A 5 + L e + P m > A s + C a ~ - P m > A 5 + P m > A s + C a > A S + G 1 > A s + L e > C > A 5 f o r t h e

top soil and that of the subsoil was in the order of As + GI + Pm > A=, + Le + Pm > As + Pm

> A5 + Ca + Pm > As + Ca > A5 + Le > AS + GI > C > As (Table 4). Modifications in

saturated hydraulic conductivity showed similar trend as that of aggregate stability (Table 5).

The oil reduced saturated hydraulic conductivity of the soil from 20.44 cm hi ' at the start of

experiment (Table 3), to 8.63 cm hr-'in 36 months. The Glivicidia sepiurn and Leucaena

Ieucocephala combined with 10 tons ha-' poultry manure, positively improved both aggregate

stability and saturated hydraulic conductivity of the spent-oil-contaminated soil. Poultry

manure with Gliricidia enhanced soil aggregate size > 0.25 mm by 67% and 78% between 12

and 36 months, respectively, (Table 7). The use of poultry manure alone led to improvement

of aggregate size > 0.25 mm by 60.7% in 12 months.

Table 5: Saturated hydraulic conductivity of the oil-contaminated soil as influenced by the treatments .-

Ksat (cm hr-') - --

Treatment Months after -- oil application -

-- -- 0 3 6 12 18 24 30 36 -- 0 - 30cm --

As 20.44 10.15 9.74 9.88 8.64 9.91 8.741 8.629 A5 -1 GI 20.44 13.08 15.99 20.74 20.98 20.99 20.98 20.96 A5 + Le 20.44 14.43 16.11 15.69 17.10 17.59 18.11 18.51 A5 + Ca 20.44 13.78 15.25 15.01 20.68 20.96 20.98 21.26 A5 + Pm 20.44 19.47 20.98 23.76 23.40 23.68 23.69 23.81 A5 + GI -1 Pm 20.44 20.64 22.19 23.28 24.77 24.96 24.98 24.98 A5 + Le+ Pm 20.44 20.25 20.96 23.78 23.45 23.99 23.94 23.99 A5+Ca+Pm 20.44 20.51 21.67 22.71 23.24 23.1 1 23.42 23.41 C 20.44 21.81 20.90 20.64 20.79 20.67 20.61 20.57 LSD(0.05) -- NS 1.14 -- 1.16 1.28 1.73 1.44 1.15 1.17

The positive enhancement in soil aggregate stability and hydraulic conductivity by the

Gliricidia, and Leucaena with poultry manure may be attributable to the fact that these

legume plants are characterized by their ability to grow fast, generate high biomass,

encouraged high population of petroleum-degrading micro-organisms in the soil rhizosphere

have massive root systems which penetrate the soil for several metres (Anderson et nl., 1993;

Stamps el al., 1994).

From the result (Table 6), the use of Gliricidia with poultry manure showed significant (P <

0.05) increases in unsaturated hydraulic conductivity of the top soil from 70.5% in 3 months

to 602.4% in 36 months after oil application over the AS. Other treatments showed

improvement in top soil unsaturated hydraulic conductivity in the order of As+Ca+Pm >

AS+Le+Pm > A5+GI > A5+Pm > AS+Ca > As+Le. This implies that the oil significantly

lowered the soil unsaturated hydraulic conductivity. General inference that can be drawn

from this result is that oil occupied the macro pores and coated macro aggregates, redwed

the water film thickness around the macro aggregates, which according to McGill (1976) and

Rasiah ef a/. (1 990) retarded the movement of water into and out of macro aggregates.

The potential structural enhancement index (PSEI), determined by the MWD of water stable

aggregates (Table 8), showed that treatments did not make positive contribution to the

enhancement of top soil structural stability during the first 12 months after applications,

except for A5+GI+Pm (10.0) and AS+Le+Pm (17.2). The mean topsoil PSEI, within months

of oil application, ranged from -1.4 to 25.4, whereas that within treatments ranges from -29.6 ., ,, . 4.1. .?, ,

to 19.5. However, the Gliricidia sepium with poultry manure progressively, enhanced lop

soil structural stability from 10 to 42.4% in 12 and 36 months (Table 8).

The Leucaena with poultry manure improved the structural stability from 17.2% to 36.8%

during the same period. The lack of positive contribution of the treatments in enhancement

of topsoil structural stability in 12 months implies that these materials cannot be used to

restore the structural stability of degraded soils within a short time. This is in agreement with

the observations of Niewczas and Witkowska-Walczak (2005) that improvement of

aggregate stability index required a reasonable length of time.

The improvement of aggregate size > 0.25 mm from 54.8% in 3 months to 63.7% in 36

months (Table 7), by the application of poultry manure alone to the soil is also in agreement

with the findings of Mbagwu (1 992) and Mbagwu et al. (199 1) also showed that poultry

manure is effective in short-term improvement of the structural properties of degraded soils.

Adesodun (2004) also made similar observation in a spent-oil-contaminated Alfisol

bioretnediated with organic wastes.

The predicted unsaturated hydraulic conductivity in the oil- contaminated soil (A5) at the

vicinity of saturated water content was in the order of magnitude less than that in the control

(C) (Table 6). The decrease in unsaturated hydraulic conductivity may be due to the

formation of an oil coating on soil aggregates which acted as a barrier to water flow.

Similarly, the sub soil potential structural enhancement index (PSEI) ranged from -8.0 to - 0.5, -29.8 to -0.1, -50.2 to 4.7, -64.5 to 14.8, -61.7 to 23.4, and -62.5 to 27.1 in 3, 6, 12, 18,

24, 30 and 36 months respectively, (Table 8). The relatively little or no enhancement of

subsoil structural stability within 18 months of treatment application indicates that their . , . . I 7 . '1)

influence on sub soil structural stability was slow. However, in 36 months, the use of

Gliricidia and Leucaeno with poultry manure showed positive contributions to the

enhancement of structural stability by 27.1 and 23.5%, respectively. This development was

probably due. to the deep rooting system Gliricidia and Leucaena as well as their 14 . . .

contributions to high biomass production, which had earlier been reported by Kirk et al.

(2005) in similar studies.

Plate 4.1a and b showed the Gliricidia sepium and Leucaena leucocephala with poultry

manure after 24 months. The massive rooting systems and high biomass production had

positive influence on the structural stability of the soil. The plants also grew fast and helped

to recondition the physical and chemical soil environment to the advantage of the crop.

Table 7: The state of aggregation of the oil-contaminated soil as influenced by the treatments -- --

-- State of aggregation (%) Treatment - Months after oil application ,

- -- 3 6 12 18 24 30 -- 36

Table 8: The potential structural enhancement index (PSEI) the soil relative to the treatments - - after 36 months

--- Months after oil - - Application Treatment - 3 6 12 18 24 30 36 Mean -

0-30cm A 5 20.8 -46.6 -42.6 -32.1 -34.9 -35.8 -35.7 -29.6 As + G I -3.0 -17.7 1.5 23.1 26.3 30.4 31.3 13.1 AS + Le 2.1 -49.8 -10.3 17.2 23.3 25.0 27.4 5.0 As + Ca -0.7 -47.8 -11.2 13.8 27.2 27.6 32.5 5.9 A5 + Pm -4.5 -14.6 -2.6 20.3 23.0 32.4 33.3 12.5 AS +GI + P m -8.6 -18.7 10.0 32.0 36.9 42.2 42.4 19.5 A5 + Le + Ptn -3.4 -1.6 17.2 20.3 28.8 35.8 36.8 19.1 As+ C a + P m -9.3 -21.0 -1.7 17.8 26.6 34.5 35.4 6.7 C - - - - - Mean -1.4 -27.2 -5.0 14.1 19.7 24.0 25.4

A5 A5 +GI A5 + Le AS + Ca A5 + Pm A 5 + G l + P m A 5 + L e + P m A g + C a + P m C Mean

Pore - Size Distribution, Organic Matter and Crusting Hazard

Pore - size distribution, organic matter and crusting hazards (risk of sealing) of the soil are

presented in Tables 9, 10, 1 1 and 12. Macro-porosity for As soil was low, ranging from 6%

in 36 months to 9% in 3 months (Table 9). Poultry manure alone showed the highest

improvement (26%) in macro-porosity in 18 months and decreased to 20% in 30 months,

with marginal changes in soil total porosity. The low macro- to micro-porosity, observed in

the As soil within 36 months, was probably due to the formation of waxy texture by the oil,

which according to Anoliefo and Vwioko, (1995), may impede oxygen and available water

content of the soil. The Gliricidia sepium, in combination with 0.5% poultry manure

(AS-tGI+Pm) showed a 3-fold positive modification in soil macro-porosity over the As

between 18 and 24 months (Table 9). The treatments showed significant (P < 0.05)

improvement in topsoil macro- to micro-porosity ratio within the 36 months.

The subsoil macro-porosity improved with time in all treatments except in the AS and control

soil ('Table 10). The positive role of Gliricidia and Leucaena spp. in the improvement of

macro- to micro-porosity ratio of the contaminated soil was related to the ability of these

legume plants to increase soil organic matter (SOM) content (Table 1 I), and the positive

influence of the root exudates on the rhizosphere soil (Merkl et al., 2005; Molina-Barahona

el al., 2004). Although micro-porosity did not show any significant difference (P > 0.05) in

the subsoil, highest positive improvement in soil macro-porosity (28 and 29%) was observed

within 30 and 36 months after oil contamination, respectively, in the AS+GI+Pm plots. The . , ,, . 4 " !. 3,. , .!*

high micro- to macro-porosity ratio observed in the oil- contatninated plots (AS), may be

detrimental to certain crops because it could lead to build-up of C02 and/or toxicity to both

plant roots and micro organisms. Low infiltration and high risk of soil erosion are also

associated with.soils under such conditions. . I) , .

Plates 4.2a and b showed the plots condition afler 12 months of oil contamination. The oil

reduced water penetration into the soil, through the formations of oily scum, which induced

crusting and degradation of other physical properties of the soil. Without additions of poultry

manure, the growth of Calapogonium caerulean was inhibited by the oil (Plate 4.2a). The

vigorous growth of the Gliricidia sepiunz combined with poultry manure (Plate 4.2b), helped

to modify the soil positively. The ability of these legume plants to thrive under oil

contaminated environment makes them promising in phytoremediation of oil contaminated

soils.

The Gliricidia spp., Calapogonium spp., and Leucnena spp. combined with poultry manure

significantly (1' < 0.05) improved organic matter content of the topsoil between 3 and 36

months, and that of the subsoil in 12 months. All the treatments made significant increases in

soil organic matter, except the use of poultry manure alone which showed organic matter

reduction from 20.6% in 3 months to 19.2% in 36 months (Table 11). Soil organic matter in

the AS depleted from 24.2% in 3 months to 18.1% in 36 months. This result implies that

where organic matter limits remediation of oil-contaminated soils, planting of legume plants

such as Gliricidia sepium, Leucaena leucocephala, and Calopogonium caerulean is a usefill

option, while the application of poultry manure alone is not sustainable in long-terms

remediation of oil-contaminated soil. Okurumeh and Okieimen (1998) examined the effect

of cow dung and poultry manure application on petroleum hydrocarbon contaminated soil

and observed that poultry manure showed short-term improvement due to its low quality of

organic matter.

Table 9: Pore-size distribution of the top 0 - 30cm of the oil-contaminated soil as influenced by the treatment .-

Months after oil application ---- Treatment -- Macro-porosity ( O h )

0 3 6 12 18 24 30 36

Table 10: Pore-size distribution of the 30 - 60 cm of the oil-contaminated soil as influence* - the treatments

Months after oil application Treatment -- -- Macro-~orositv (%)

-- 3 6 12 18 24 30 36 A 5 !I 10 10 10 I0 9 I 1

Micro - porositv (%) 34 36 34 36 35 34 35 34 37 36 34 33 37 35 33 34 36 38 36 36 33 38 39 32 32 37 33 31 34 32 32 33 31 34 34 33

NS 1.33 1.38 1.81

- - 3 1 - ; &&p2., - - .

Plate 4. la: The expesimental plots after 1 2 months of oil contamination

Plate 4.2b. The Glivicidh sepium a h 36 months of oil contamination. Its vigorous ~~ makes it promising in remediation of oil contaminated soils.

Table 11: Soil organic matter (SOM) of the 0 - 30cm of the oil-contaminated site as influenced by the treatment after 36 months

-. - -- Organic matter (g kg-')

Treatment -- Months after oil application 3 6 12 18 24 30 36

A5 A=, + GI AS + I,e As -t. Ca AS + Pm As + GI + Pm AS + L.e + Pm AS + Ca+ Pm C LSD (0.05)

A5 As -1 GI A5 + Le A5 4- Ca AS + Pm A s + G I +Pm A5 -t I,e t- Pm As -1 Ca + Pm C LSD (0.05) ---

Crusting hazard (risk of sealing) was high for As (5%). Such condition coupled with low

macro-porosity, could result in the formation of structural crusts which according to West et

al. (1992) is an indication of soil structural deformation and can be used to assess the

suitability of such soil for root growth and movement of soil organisms. At 12, 18,24,30 and

36 months (Table 12), all the treatments significantly (P < 0.05) reduced the risk of crusting

of the soil compared to the As, with the highest reduction observed for plots treated with

legume plants. The reduction in the risk of crusting may be attributable to high soil organic

matter generated by the legume plants. Pagliai et al. (1995) had reported that decrease in

organic matter content and population of living organisms was strongly associated with soil

sealing and crusting.

4.1.3 Bulk Density and Water Retention Characteristics

Bulk density and water retention characteristics of the soil are shown in Table 13 and Figures

(4a, 4b and 5a and 5b). Bulk density of the topsoil ranged from 1.39 g cm-3 for As-tGl+Pm to

1.69 g for A5 soil whereas, that of the subsoil ranged between 1.48 and 1.68 g ~ m - ~ .

Bulk density for As plot changed from 1 S 2 g ~ m ' ~ at the start of experiment (Table 3) to I .G9

g cm-3 in 18 months after oil contamination, and further increased from 1.61 to 1.69 g cm"

between 24 and 36 months after the second contamination of the oil (Table 13). Application

of poultry manure alone showed a 2.8% reduction in bulk between 3 and 12 months and later

showed a 12% increase between 24 and 36 months. Such development explains the temporal

influence of poultry manure on bulk density and other soil physical properties with the

possibility of structural crusting . , .an,d,por,~ .... blockage due to soil dispersion (Pagliai and I)e

Nobilli, 1993).

The combination of Gliricidia, Leucaena and Calapogonium with poultry manure showed

significant (P .< 0.05) reduction in the;, soil bulk density over the A5 and control soil.

Gliricidia, Leucaena and Calopogonium with poultry manure respectively, showed bulk

densities of 1.38, 1.39, and1.39 g cm" in 36 months (Table 13). Similarly, subsoil bulk

densities showed marginal decreases among treatments, with the lowest value of 1.48 g cm"

recorded for the plot treated with G'liricidic7 and poultry manure only.

The consistent, positive contribution of the legume plants to the improvements of soil bulk

density, saturated hydraulic conductivity, aggregate stability and porosity implies that they

can provide sustainable role and/or option in bioremediation technologies. Similarly, Merkl

et al. (2005) had earlier reported that legume plants were promising species for remediation

of petroleum - contaminated soil because they showed the best biomass production and

caused the highest oil dissipation, low nutrient demand, as well as modification of the soil

rhizosphere.

The top soil volumetric water content at saturation (Figures 4a and 4b) ranged from 33 to

36%, 32 to 38%, 30 to 42%, 30 to 45% 29 to 46%, 29 to 46% and 28 to 47% in 3,6, 12, 18,

24, 30 and 36 months respectively, after oil application. The -6 kPa water content

(representing field capacity) was 52% less than the saturation water content for the A5 in 3

months and 50% less in 36 months, after oil application. Water retention at saturation and

field capacity showed steady increases over time in plots treated with the legume plants and

poultry manure whereas that contaminated with oil without any treatment showed very low

water retention capacity at these water potentials during the same periods.

Table 12: Crusting hazard of the top 0 - 30 cm of the oil-contaminated soil as influenced by the treatments -

Crusting Hazard (%) Treatment --- Months after oil apjlication -- 3 6 12 18 24 30 36 A5 11 9 8 9 9 8 8 A5 + GI 1 1 9 9 10 10 1 1 I I A5 + I,e 10 11 9 10 10 1 1 10 A5 + Ca 7 8 10 11 11 1 1 10 A5 + Pm 9 9 9 10 11 9 8 A5+GI+Pm 10 10 12 11 12 12 I I A 5 + L e + P m 8 10 10 10 1 1 12 12 A5 + Ca + Pm 1 1 11 10 1 1 12 12 12 C 7 7 6 6 7 6 6 LSD(0.05) - NS NS 1.81 1.46 1.08 1.87 1 .06

R Values < 5% high 7% threshold value

> 9% low

Table 13: Bulk density of the soil relative to treatments

Bulk density (g cm") Treatment Months after oil application - -- 0 3 6 12 18 24 30 36

0-30cm As 1.52 1.56 1.58 1.58 1.63 1.61 1.67 1.69 A5 + G1 1.52 1.55 1.51 1.49 1.55 1.48 1.43 1.42 As + Le 1.52 1.58 1.54 1.52 1.58 1.51 1.46 1.45 A5 + Ca 1.52 1.56 1.53 1.51 1.55 1.49 1.45 1.45 A5 + Pm 1.52 1.45 1.44 1.41 1.46 1.42 1.54 1.59 A5+Gl+Pm 1.52 1.44 1.42 1.40 1.43 1.41 1.39 1.38 As+Le+Pm 1.52 1.45 1.43 1.42 1.45 1.42 1.41 1.39 A5 + Ca -t Pm 1.52 1.44 1.42 1.41 1.43 1.42 1.40 1.39 C 1.52 1.46 1.46 1.49 1.49 1.54 1.56 1.60 LSD (0.05) NS 0.18 0.09 0.04 0.07 0.08 0.05 0.09

A 5

As + GI As + Le As + Ca AS + Pm A5 + GI 4- Pm Ag+Le+Pm AS+Ca+Pm C LSD (0.05)

'The shapes of the soil moisture characteristics curves for the top soil showed that much water

was released between the 0 and -6 kpa vvater potentials in all the plots during the first 3

months (Figures 4a and 4b) indicating that sandy loam soils have a high percentage of the

soil water in the macro-sized pores (Mbagwu et al., 1983; Mbagwu et al., 2004). From 12 to

36 months, soil moisture retention was relatively high in the plots treated with poultry

manure, legume plants only or poultry manure and legume plants. Plots treated with a

combination of legume plants and poultry manure showed high water retention capacity in all

the water potentials. The low water holding capacity observed in the contaminated soil (A5)

(Figures 4a and 4b) with corresponding low saturated hydraulic conductivity (Table 5 ) , low

macro- to micro porosity ratio (Table 9) and high crusting hazard (Table 12), were not

surprising. Similar results had been reported by Rasiah et al. (1990) in an oily waste -

contaminated soil compared to the non-contaminated soil. The low water retention suggests

that oil had succeeded water in the competition for pore spaces. Most often, soil

contaminated with oil appeared waxy and usually does not allow water to penetrate it from

above.

(a) 3rd Month

-3 -6

Ressure potential (-Kpa)

(b) 6th Month

0.1 .I + 0 -3 -6 -10

Ressure potential (-@a)

(c) 12th Month

Ressure potential (-kpa)

(d) 18th Month

Ressure potential (+pa)

Fig. 4a. Volumetric moisture content of the top 0-30 cm at 3,6, 12 and 18 months after oil application.

(e) 24th Month

Ressure potential (&pa)

(f ) 30th Month

-3 -6

Ressure potential (+a)

(g) 36th Month

-3 -6 Ressure potential (&pa)

Fig. 4b. Volumetric moisture content of the top 0-30 cm at 24, 30 and 36 months after oil application.

(a) 3rd Month

Ressure potential (-kpa)

(b) 6th Month

Ressure potential (-@a)

(c) 12th Month 0.4

0.35 - I .= 2 0.3 - g ? 2 5 0.25 2 rn 2 5 0.2

0.15

0.1 0 -3 -6 -1 0

Ressure potential (-@a)

(d) 18th Month

Ressure potential (-@a)

Fig. 5a. Volumetric moisture content of the top 30-60 cm at 3,6, 12 and 18 months after oil application.

(e) 24th Month

-3 -6 Ressure potential (-@a)

(f) 30th Month

-3 -6 Ressure potentiil (-@a)

(g) 36th Month

-3 -6

Ressure potentiil (-@a)

Fig. 5b. Volumetric moisture content of the top 30-60 cm at 24,30 and 36 months after oil application.

On the other hand, the relatively high water retention observed with time in As+GI+Pm,

A5tLe+Pm and As+Ca+Pm may be attributable to high organic matter production

contributed to the soil by the legume plants, which according to Glick (2003) increased the

activity of soil micro organisms and decomposition processes. Mbagwu et al. (1991) and

Pagliai and Antisari (1 993) had reported of the positive influence soil organic matter content

played as a binding agent, and on water retention capacity of soils. The subsoil moisture

characteristic curves (Figures 5a and 5b) s'qowed a similar trend with that of the topsoil with

plots treated with legumes and poultry manure showing high water retention capacity.

4.1.4 Salinity Characteristics

The salinity parameters of the soil, measured in terms of sodium adsorption ratio (SAR),

exchangeable sodium percentage (ESP), electrical conductivity (Ece), salt concentration and

osmotic pressure are presented in Table 14. The SAR values of the soil ranged from 0.08 to

0.40, with the highest value of 0.40 recorded for the A5 soil in 36 months, indicating that a

high percentage of exchangeable sodium built-up in this soil via the contamination load of

10% (w/w) of spent oil. Such high SAR values can cause soil dispersion, with adverse

implications on infiltration rate and flooding.

Table 14: Salinity characteristics of the top O - 30cm depth of the oil contaminated soil relative to treatments

---- Osmotic

Ece Salt Con SAR (mm hns cm-') (mg I-') pressure Trentmen t Salinity hazard *

-- -- -- - (at m) 3" Month

A5

A5 + GI As 4- Le AS + Ca A5 + Pm A5 + GI + Pm Ag+Le+Pm A5 +Ca+Pm C L s n (0.05)

As

A5 + GI As + Le As + Ca A5 + Pm AS + GI -t Pm As+Le+Pm A5 Y Ca t- Pm C LSD (0.05)

A5

AS + GI AS + Le AS + Ca As + I'm AS+GI+Pm

A5+Le+Pm A5+Ca+Pm C LSD (0.05)

2.14

1.04 1.08 1.02 1.33 1.02 1.02 1 .O3 0.09 0.28

6th Month 2.03

0.15 0.09 0.13 1.08 1.08 0.88 0.81 0.04 0.08 ., , a . 4 .7. 4. , .>.'

1 2 ' ~ Month 3.18

0.4 1 0.72 0.86 0.99 1.20

1.43 1.33 0.07 0.05

Yields of very sensitive crops may be restricted

c c

c c

c c

c c

c c

cr

c c

Salinity effects negligible

Yields of very sensitive crops may be restricted Salinity effect negligible

G G

c c

c c

c c

c c

c c

Yields of many crops restricted Salinity effect negligible

c c

c c

c c

Yields of very sensitive crops may be restricted

c c

c c

Salinity effect negligible

1 8 ' ~ Month 3.19 Yields of many crop

restricted Salinity effect negligible

cc

66

Yields of vely sensitive crops may be restricted

LC As+Ca+Pm C LSD (0.05)

Salinity effect negligible

24th Month 3 .O3 Yields of many crops

restricted Salinity effect negligible

66

Yields of very sensitive crops may be restricted Salinity effect negligible

66

As -t GI + Pm AS + Le -1 Pm AS +Ca+Pm C LSD (0.05)

3oth Month 3.1 1 Yields of many crops

restricted Salinity effect negligible

LL

6L

6 6

66

66

As + G1 AS + Le AS + Ca AS -1 Pm AS+G1+Pm As .t Le + Pm As + Ca 4- Pm C LSD (0.05)

36'h Month As 0.40 8.10 3.14 896.0 1.13 Yields of many crops

restricted As + GI 0.13 2.71 0.35 224.0 0.13 Salinity effect negligible As + Le 0.12 2.45 0.6 1 390.4 0.22 " As t Ca 0.12 2.49 0.39 249.6 0.14 " As + Pm 0.13 2.60 0.72 460.8 0.26 " As -t GI + Pm 0.15 3.12 0.14 601.6 0.05 " As + l,e + Pm 0.14 2.88 0.16 422.4 0.06 " As + Ca+ Pm 0.14 2.83 0.28 454.4 0.10 " C 0.11 2.17 0.08 51.2 0.03 " LSD (0.05) 0.02 0.35 - 0.23 79.6 0.08

* Classification after Bernstein (1 964) SAR - Sodium adsorption ratio, ESP - Exchangeable sodium percentage, Ece - Electrical conductivity

Sodium adsorption ratio (SAR) showed a gradual decrease with time in plots treated with a

combination of legume plants and poultry manure (Table 14), but showed gradual increases

in contaminated plots without treatments or treated with only poultry manure, indicating

possible contribution to the soil of exchangeable sodium by the poultry manure to the soil.

Pagliai and DeNobilli (1993), McLaughlan et al., (1996) had reported high exchangeable

sodium as one of the detrimental effects and/or risks associated with the agricultural land

application of organic and oily wastes.

Electrical conductivity, salt concentration and osmotic pressure measurement occurred in a

similar pattern as that of the SAR and ESP, being significantly (P < 0.05) higher in the A5

soil. At 12, 18, 24, 30 and 36 months these values reached elevated levels in contaminated

soil such that it is difficult for the crop to survive (Table 14). The implication of this being

that, growth and yields of many crops sensitive to salt may be restricted, according to

Bernstein (1964) classification of soil salinity.

Such level of salt concentration, according to Magesin et al. (2000), may interfere with the

absorption of water by plants through reduction in the soil osmotic water potential and thus

decrease the amount of water that is readily available for plant uptake leading to wilting and

subsequent death of the plant. However, the use of Gliricidia, Leucaena and Calopogonizrnz

combined with poultry manure significantly (P < 0.05) reduced salinity parameters to

negligible levels within 12 and 36 months of oil contamination. This development is most

probably due to the ability of these legume plant to be tolerant to oil-contaminated ., ,, .d. \*. , '

environmental conditions at certain stages of growth (Kirk et al., 2005), and generate high

microbial biomass that helped reconditioned the soil (Merkl et al., 2005).

Relationships Among Soil Physical , Properties . .

The relationships among some physical properties of the soil are shown in Table 15. The

significant (P < 0.05) positive correlation (r=0.795) between saturated hydraulic conductivity

and macro-porosity may not be surprising because, macro-porosity influences hydraulic

conductivity in soils. On the other hand, the highly significant (P < 0.01) negative

correlation (r = -0.918) between micro-porosity and saturated hydraulic conductivity is an

indication that the micro- to macro-porosity ratio could be used as an important index to

evaluate the effect of oil application on the saturated hydraulic conductivity of the soil,

showing that as micro-porosity increases, saturated hydraulic conductivity decreases..

The correlation analysis (Table 15) also showed a significant (W0.01) positive relationship (r

= 0.907) between crusting hazard (R) and soil organic mater (SOM) content, confirming the

positive role of SOM in reducing soil crusting. The significant (P < 0.05) positive correlation

between R and macro-porosity (r = 0.628) and saturated hydraulic conductivity (P < 0.01) (r

= 0.841) is not surprising. The explanations are that increases in R (low crusting hazard) lead

to increases in saturated hydraulic conductivity and macro-porosity, indicating that soil

organic matter, saturated hydraulic conductivity and macro-porosity were positively modified

by the treatments. Thus, the reduction in crusting in plots treated with poultry manure and

legume plants is in agreement with the observations of Pagliai (1987) that reported positive

relationships amongst soil organic matter, aggregate stability and surface crusting in well-

managed soils.

Table 15: Relationships among some physical properties of the oil contaminated soil (N = 63)

-- - Correlation Coefficient (r)

K,,t Macro R D .R 0 .M MWD (cm hrl) porosity (9%) (&-I (mm)

(O/o)

ICWt (cm 11-') II___L__ -

Macro porosity 0.795* - (%I R (%) 0.841** 0.628* - D. R. -0.668* -0.821** 0.824** - 0. M. (g kg-') -0.496" 0.622* 0.907** -0.501" - MWD (mm) 0.694* 0.681* 0.881** -0.634* 0.733* - ** = Significant at P < 0.01, * =Significant at P < 0.05, ns = Not significant at P > 0.05 KSat = Saturated hydraulic conductivity, R = Crusting hazard, DR = Dispersion ratio, OM = Organic matter, MWD = Mean weight diameter

The low negative correlation (r = -0.501) between dispersion ratio (DR) and soil organic

matter (SOM) and significant (P < 0.05) correlation (r = -0.634) between dispersion ratio and

MWD of water stable aggregates further confirmed the high quality of SOM generated by

these legume plants in stabilizing soil aggregates.

4.1.6 Relationships Amongst Soil Physical and Salinity Properties

The correlation between soil physical parameters (crusting hazard, saturated hydraulic

conductivity and MWD) and some salinity parameters (SAR, ESP, Ece and salt

concentrations) are presented in Table 16. The significant (P < 0.05) negative correlation

between ESP and R, KSat and MWD (r = -0.642, -0.682 and -0.782, respectively) is evidence

that the high exchangeable sodium observed in the contaminated plots, and plots amended

with poultry manure alone contributed to the observed high risk of sealing, low permeability

and low stability of soil aggregates observed in these plots.

Electrical conductivity (Ece), SAR, and salt concentrations had similar negative effects on

KSab R and MWD (Table 16). This suggest that management of soil physical parameters

(infiltration, hydraulic conductivity, aggregate stability etc) requires practices that will

prevent and/or reduce high values of ESP, SAR, Ece and salt concentrations in soils. This is

because, they could lead to increased clay dispersion with consequential negative

implications on some soil physical, cIiemical, and biological properties as previously

reported by Pagliai et al. (1 995).

Table 16: Relationships among some soil physical and salinity properties of the soil (N = 63)

Correlation Coefficient (r) R Ksat MWD SAR ESP Ece Salt conc.

-- (%) (cm h-') (mm) (mm hos cm") (mg l y R (%) - Ksat (cm hi ' ) 0.841** - MW D (mm) 0.881** 0.694* SAR -0.635* -0.38111s -0.716** ESP -0.642* -0.682* -0.782** 0.894** - Ece (mm hos CU- -0.636* -0.673* -0.683* 0.793** 0.819** - '> Salt Conc. (mg L- -0.71 l* -0.634* -0.394ns 0.716** 0.856** 0.984** - ' 1 - .- --

** = Significant at P < 0.01, * =Significant at P < 0.05, ns = Non significant at P > 0.05 R - Crusting hazard, Ksat = Saturated hydraulic conductivity, MWD = Mean weight diameter, SAR = Sodium adsorption ratio, ESP = Exchangeable sodium percentage, Ece = Electrical conductivity

4.2. Chemical Properties

4.2.1 Distribution of Heavy Metals and Contaminant Limit (clp Index)

The distribution of a number of heavy metals, and their contaminant limit (c/p index), ie. the

ratio between the heavy metals content in soil and the toxicity criteria oFKabata-Pendias and

Pendias (1984) as further classified by Lacatusu (1998) are presented in Tables 17 and 18.

The results showed that there were build-ups of Al Ni, Pb, Zn and Cu in soils contaminated

with spent oil and similar build-up in soils treated with additions of poultry manure relative

to the control. This increase indicates that there was enrichment of the soil with these metals

via both the spent oil and poultry manure. In 3 months, Pb, Zn and Cu showed significant (P

< 0.05) difference in concentrations in the contaminated soil relative to control. Plots treated

with PM alone showed the highest values of 17.5, 43.6 and 48.3 mg kg-' of Pb, Zn and Cu

respectively, in 3 months and maintained similar trend at 6 months. In 12 months, the

increase in Al, Ni, Pb, Zn and Cu concentrations in the AS soil were 43%, 158%, 702% 118%

and 446%, respectively, compared to the control.

The high concentration of these metals in the As was an indication of the contamination of

the soil with Al, Ni, Pb, Zn and Cu via the oil. This further confirmed the observation of

Amadi et al. (1990) and Anon (1985) that most heavy metals, such as Va, Pb, Al, Ni and Fe

which are below detection, in unused lubricating oil showed high values in waste motor oil.

When disposed on soils, it leads to contamination of the soil. The implications are that at

high concentrations, these metals can block the essential functional groups in the soil,

displacing other metal ions, and modiQ the active conformation of biological molecules in ..(.... 7. .I . soil and plants. In addition, these metals are toxic to both higher and microorganisms (Emst,

1996). They also directly affect the various physiological processes in plants, causing

reduction in growth (Vangronsveld and Glisters, 1994).

Table 17: Heavy metal concentration of the top 0 - 30cm soil of oil contaminated site

Treatment Ai Ni Pb Zn Cu

As As + GI As + L e As + Ca As + Pm AS + GI + Pm A s + L e + P m A 5 + C a + P m C LSD (0.05)

A5 A5 + GI A5 + Le A5 + Ca A5 + Pm A 5 + G I + P m A s + L e + P m A s + C a + P m C LSD (0.05)

As A5 + GI A5 -t Le AS + Ca AS + Pm A s + G I + P m A S + L e + P m A S + C a + P m C LSD (0.05) '

A s Ag +GI As + Le AS + Ca AS + Pm A 5 + G I + P m A S + L e + P m A S + C a + P m C LSD (0.05)

15.3 15.2 15.9' 15.0 17.5 17.2 17.3 17.3

1 .o 0.5

6th Month 15.1 15 .O 14.8 15.0 17.1 16.0 16.2 15.2 1.2 0.1

12'~ Month 8.2 6.9 6.8 7.0 9.9 7.1 7.2 7.1 1 .o 0.2

lath Month 28.0 15.1 15.3 15.2 16.2 15.3 15.4 15.4 1.5

A5 A s + GI AS + Le A5 + Ca As + Pttl

A 5 + G I + P m A s + L e + P m A 5 + C a + P m C LSD (0.05)

As As -1 GI AS + Le As -t Ca A5 + Pm A5 + GI -t Pm A=,+Le+Pm A5 + Ca 4- Pm C LSD (0.05)

24'h Month 3.9 28.1 0.9 15.0 0.9 15.2 0.9 15.2 0.3 16.3 0.8 14.2 0.8 14.3 0.8 14.6 0.3 1.4 0.0 0.1

3oih Month 4.0 28.0 0.8 19.7 0.8 10.8 0.8 10.9 1.3 10.2 0.7 11.0 0.7 10.1 0.1 10.0 0.2 1.1 0.1 0.1

36th Month 4 .O 28. 0.8 10.5 0.8 10.6 0.8 10.7 1 .o 10.1 0.6 2.8 0.7 3.1

As + Ca -t- Pm .. 3.472,. , 0.6 3.3 C 30 15 0.2 1 .O LSD (0.05) 121.3 0.0 0.0

1 OOa 1 OOa 7od a = Threshold tolerable limit (Kabata-Pendias and Pendias, 1984).

On the other hand, within 18 to 36 months the Gliricidia, Leucaena and Calopogonium

combined with poultry manure showed steady reductions in all the heavy metals studied. At

36 months, the Gliricida seyium combined with PM significantly reduced the Al, Ni, Pb, Zn

and Cu concentrations in the soil by 21%, 96%, 90%, 42% and 50% respectively, relative to

the As soil. This implies that these legume plants may belong to the small group of plants

that can tolerate uptake and translocation of high levels of these metals that could be toxic to

other plants or organisms. Brown et al. (1995) had reported of certain plant species whose

leaves may contain > 100 mg kg-' Zn and Mn (dry weight) when grown in metal-rich soils.

Although the levels of these metals were reasonably high to impair plant growth and

microbial activities, they were less than the threshold limit (Kabata-Pendias and Pendias,

1984). The contaminant - pollution index (c/p index) calculated for Ni, Pb, Zn and Cu

concentration for the soil are shown in Table 18. At 3 months, Ni ranged from 0.003 - 0.024

mg kg-', Pb from 0.0 1 - 0. I8 mg kg-', Zn from 0.27 - 0.60 mg kg-', and Cu from 0.12 - 0.81

mg kg-'. The application of oil led to slight contamination of the soil with Yb, moderately to

severe contamination with Zn and Cu, whereas AS + PM showed very severe contamination

with Cu. At 6 and 12 months, Zn and Cu still showed moderately to severe contanlination,

whereas Pb showed slight and very slight contaminations between 6 and 12 months.

Table 18: Clp index of the soil and some heavy metals as modified by the --- treatments -- Treatment -- Ni Pb Zn Cu

3" Month 0.16~ 0.1 5b 0 .15~ 0 . 1 5 ~ 0.18" 0.17~ 0.1 gb 0.17~ 0.01"

6th Month 0.1 5b 0 .15~ 0 .15~ 0.1 5b 0 .17~ 0 .16~ 0.16~ 0.15~ 0.02" 1 2 ' ~

Month 0.08" 0.06" 0.07a 0.07" 0.10" 0.07" 0.07a 0.07a 0.0 1" 1 sth

Month 0.28' 0.1 5b

As As + GI A5 + Le A5 + Ca AS -t Pm AS +GI + I'm As + Le + Pm A5 4- Ca -t Pm C

24th Month 0.28" 0 .15~ 0 .15~ 0.16~ 0.1 4b 0.1 5b 0 .15~ 0.1 5b 0.02a 3oth

Month 0.28" 0.1 lb 0.1 2b 0.1 lb 0.1 ob 0.1 lb 0.1 ob 0. 1 ob

0.01 la 36th

Month 0.28' 0.1 lb 0.1 l b 0.1 lb 0. 1 ob 0.03" 0.03" 0.03a 0.01" --- . . 0.1 2b

a = Very slightly contaminated b = Slightly contaminated c = Moderately contaminated d = Severely contaminated I(

e = Very severely contaminated

In 18 months when additional load of spent oil and poultry manure were applied and at 36

months when the experiment ended, (Table 18), Zn reduced from moderately to severe

contamination in 18 months and also moderately contaminated in 24, 30 and 36 months, The

As soil maintained severe contamination levels with these metals during the months. The

contaminant levels of these metals in As soil further confirmed the observations of Alloway

and Ayres (1997) that elements such as Cd, Cr, Cu, Hg, Ni, Pb and Zn are commonly

associated with pollution and toxicity problems. Copper (Cu) at this concentration has been

reported to inhibit plant growth, and interfered with several cellular processes in plants,

including photosynthesis, respiration, enzyme activity, pigment and protein synthesis and cell

division (Devez et al., 2005), whereas, Yb and Zn at such levels had been reported to

suppress homeostatic mechanisms in micro-organisms (Ernst, 1996).

The gradual reduction in c/p index for Pb, Zn, and Cu observed in soils treated with the

legume plants, in combination with poult~r manure in 18, 24, 30 and 36 months indicate that

these legume plants are promising in phytoremediation of heavy metal removal from

contaminated sites and general improvement of the soil health (Avidano et al., 2005).

4.2.2 Other Chemical Properties

A number of other chemical properties of the soil are presented in Table 19 and 20. The soil

pH ranged from strongly to extremely acid at the top 0 - 30 cm for all the treatments (Table

19) and strongly to very strongly acid at the 30 - 60 cm depth (Table 20). The pH of the top

soil showed significant (P < 0.05)winpeqges with treatments relative to the contaminated soil - ,

(As).

A5 A5 + GI As + Le As -t Ca A5 + Prn A, + GI -t Pn? A, -+ LC -t Pm A, + Ca -t Pm C LSD (0.05)

' 4 5

A5 + GI A5 -t Le A5 + Ca AS + Pm A 5 + G I + P m A5 +- Le + Pm A 5 + C a + P m C LSD (0.05)

24* Month I3:l 1.02 0.50 11:l 2.69 2.03 8:l 2.51 2.14 4:l 2.32 1.95 6:l 2.40 1.96 6:l 2.94 2.30 6:l 2.86 2.28 6:l 2.81 2.37 7:l 1.75 1.06 8.18 0.09 0.1 1

3 0 ' ~ Month 13:l 0.93 0.50 11:l 2.73 2.12 7:l 2.63 2.21 4:l 2.47 2.20 5:l 2.57 1.90 6:l 2.78 2.36 6:l 2.94 2.40 6:1 2.91 2.41 8:l 1.76 1.06 1.00 0.26 0.08

36" Month 14:l 0.95 0.52 7:l 2.81 2.11 5:l 2.65 2.28 4:l 2.52 2.26 5:l 2.58 1.90 6:l 3.14 2/43 6:l 2.66 2.43 6:l 3.1 1 2.56 lo:! 1.81 1.03

LSD (0.05) - 0.37 1.25 0.29 0.48 0.94 0.03 . . -- ., ,. . . - 7 . .*. . I <

Apart from the inherent acidic nature of the highly weathered soil of the south-eastern

Nigeria earlier reported by Akamigbo and lgwe (1990), the oil contributed largely to the

extreme acidity of the As soil. Organic carbon content of the soil ranged from low to

moderate at the topsoil and very low to low in subsoil. From the results, the treatments

made positive contributions in the enrichment of both the topsoil and subsoil organic c,arbon;

with the legume plants showing high contribution to the soil organic carbon, with time.

Combination of Gliricidia, Leucaena and Calopogonium spp. increased the soil organic

carbon by 76%, 74% and 76% respectively in 6 months and a 2-fold increases in 24, 30 and

36 months relative to AS (Table 19).

Total N showed similar trend with that o; organic carbon with significant contribution to the

soil total N from the AStGI-tPm. The high total N content in the legume treated-plots

compared to the initial N (Table 3) is in conformity with Frick et al. (1999) and Merkl et al.

(2005) observations that legumes are considered to be especially promising in improvement

of oil-contaminated soils because of their nitrogen independence which is of significance in

oil-contaminated soils characterized by a high C/N ratio. The CM ratio was very high in

contaminated plot; reaching a 16:l ratio in 3 months, 13:l and 14:l in 12 and 36 months

respectively (Table 19). Similarly, the subsoil CM ratio (Table 20) ranged from 15: I in 3

months, to 19:l at 36 months, indicating contamination of the subsoil with the petroleum

hydrocarbons. The subsoil enrichment with petroleum hydrocarbon may have been

responsible for the very low saturated hydraulic conductivity earlier observed in this soil. The

legume plants, on the other band? lowered and maintained the CM ratio of the treated plots at . ,. . . .1. 3 -12

6:l at the end of the study, thus confirming the observations of Merkl et al. (2005) that OM

generated by these legume plants are in good amount and quality.

Table 20: Chemical properties of the soil relative to treatment at the

30 - 60cm depth after oil application -- --

'Treatment P OC TN Av. P C:N Ca ME K Na CEC Exch.

15: 1 1 .0 11:l 1.10 12:l 1.10 13:l 1 .0 13;l 1.21 1O:l 1.16 1O:l 1.13 11:l 1.13 11:l 1.3 0.13 N S

6'h Month 15:l 0.97 10:l 1.21 10:l 1.1 1 9:l 1.63 10:l 2.1 1 10:l 1.98 11:l 2.10 9:l 2.03 9: 1 1.2 0.26 0.05

12'~ Month 13:l 0.94 9 : 1.13 10:l 1.22 ?:I 1.08 11:l 1.95 8:l 1.86

18'~ Month 15:l 0.95 0.58 0.09 9: 1 1:33 0.81 0.20 tO:il 1131 0.76 0.20 9: 1 1.26 0.78 0.16 11:l 1.18 0.81 0.18 8: 1 1.66 0.96 0.21 8: 1 2.10 1.26 0.18 10: 1 1.2 0.60 0.08 10: 1 1.2 0.60 0.08 8 0.08 0.21 0.05

As A5 + GI A5 + Le AS + Ca A5 + I'm A5 C GI -t Ptn As + Le 4 Pm A 5 + C a tPm C LSD (0.05)

24Ih Month 15:l 0.94 9:l 1.10 9:l 1.32 9:1 1.28 12:l 1.34 8:l 1.86 8:l 2.12 8:l 2.11 10:l 1.2 0.10 0.16 30Ih Month 20: 1 0.94 9 : ; 1.10 9:l 123 4:l 1.38 17.1 1.18 8:1 1.21 8:l 7.14 8:l 2.18 11:l 1.3 0.30 0.05 36Ih Month 19:: 0.91 8:l 1.13 9: 1 1.24 9:l 1.28 15:l 1.31 8:l 2.14 7:l 2.09 8:l 2.16 10:l 1.2

Available P, exchangeable ca2+, mg2+ and K+ were low in A5 throughout the period but

ranged from low to medium in plots treated with legume plants and poultry manure during

the same period. For example, in 12 and 24 months after oil contamination, the ~ 2 ' content

in A5ffil+Pm plot was 2.94 C mol kg-' compared to 1.14 and 1.02 C rnol kg-', respectively

for As soil (Table 19). Similar increases of available P, exchangeable ca2+, mg2' and K+

were observed in the sub soil, It is believed that the root exudates from the legume plants

may have stimulated micro organisms and biogeochemical reactions which aided the

enrichment of both the topsoil and subsoil with these essential elements (Joner and Leyval,

2003).

Variations in CEC, exchangeable acidity, exchangeable Na and %l3S (Tables I9 and 20)

indicate significant (P < 0.05) increases in exchangeable acidity and exchangeable sodium

with the spent oil loading rate. In 6 months, CEC for the AS was 5.0 C rnol kg-' and that in

plots treated with only poultry manure was 7.9 C rnol kg-'. The Gliricidia, Leucaena and

Calopogonium spp. supplemented with poultry manure had CEC of 7.8, 7.6 and 7.8 C rnol

kg" respectively, in 6 months At 24 months the CEC value for As soil decreased from 5.0 C

rnol kg-' to 3.9 C mol kg-' (28% lower). The low values for CEC, %BS and exchangeable

bases were likely due to the fact that metals added to the soil via the oil may have formed an

insoluble complex, and caused decrease in the negative charge of clay surfaces in the soil.

Treatments showed significant (P < 0.05) modifications in both the top soil and sub soil

chemical properties (Table 19 and 20). The positive modifications confirmed that the legume

plants combined with poultry ., ,, . .,I% manuire ,* , are promising in improving the soil chemical properties

such as available P, exchangeable ca2', mg2+, K+, CEC and base saturation. Anoliefo and

Vwioko (1995) made similar assertion when they studied the effects of spent lubricating oil

on the growth of Capsicum annzm L. and Lycopersicon esculentum Miller. The low status in

the soil properties also confirmed,,the st.bdies of Okieimen and Okieimen ( 2002) that oil in

soil is accompanied by depletion in the nutrient status, especially N, P, and Mg, and increase

in soil acidity and exchangeable sodium.

4.2.3 Total Hydrocarbon Content

The distribution of total hydrocarbon content (THC) of the soil as modified by the treatments

is shown in Table 2 1. Mean residual total hydrocarbon contents after 36 months ranged from

2048 mg kg-' (in control soil) to 35064 nig kg-' (in contaminated soil without treatments) for

top 0 - 30 cm soil and 2145 mg kg" to 36128 mg kg-' respectively for 30 - 60 cm depth. In

12 months the residual THC for As+GI+Ptn, As+Le+Pm and Aj+Ca+Pm were 15471 mg kg'

', 15549 and 15816 mg kg-' respectively for the top soil compared to 30648 mg kg"

recorded for As. When additional load of 100 tons ha-' spent oil was applied after 12 months,

the residual soil THC in 18 months ranged from 15471 to 35473 mg kg", 15549 to 35718 mg

kg" and 15816 to 35736 mg kg-' for As-tGl+Pm, As+Le+Pm, and A5 + Ca + Pm relative to

30648 to 41033 mg kg" for As.

Treatments showed significant (P < 0.05) variation in THC from month to month. The As + GI + Pm showed the lowest mean THC in 36 months, for the topsoil. Ability of the

treatments to enhanced degradation of the petroleum hydrocarbon was in the order of AS 4- GI

+ P m > A s + L e + P m > A s + C a + P m > A 5 - f - G I > A 5 + L e > A g + C a + A 5 + A s + P m f o r

both the top soil and sub soil. The relatively high increases in the residual THC in the sub

soil of the As in 24 and 36 months was, 37182 and 36128 mg kg-' respectively and showed

that with time spent oil had moved significantly below the sub-surface 0 - 30cm depth. This

confirmed the sandy nature of Nsukka soils (Akamigbo and Igwe, 1990), which has been

reported to encourage high leaching and movements of soil material down the profile.

Table 21: Changes in total hydrocarbon content (THC) of the soil by treatments after 36 months ---

T H C (mg kg-') Treatments Months after dl application Mean

3 12 18 24 36

As 35492 30648 41033 36416 31731 As + GI 34784 17742 36617 2901 1 206 19 AS -I Le 34652 17886 36214 29930 21 174 AS + Ca 33964 1742 1 36347 30662 24366 AS t Pm 3401 1 16638 391 18 31457 28694 AStGI+Pm 28413 1 547 1 35473 21974 204 16 As+ Le -t Pm 285 19 15549 35718 22603 20544 As-t Ca + Pm 28944 15816 35736 23 146 20712 C 2390 2075 1964 19103 19004 Mean 290 18 16583 33 136 25234 21 128 LSD (0.05): Treatment = 9646, Months = 125.31 8, T x M = 594.437

Mean 21 159 19625 24853 23073 21 190 LSD (0.05): Treatment = 99.543, Months = NS, T x M = NS

The significantly low residual THC observed for the plots treated with Gliricidia, Leuca~na,

Calopogonitrm and poultry manure was not surprising. The degradation process may have

been enhanced by the positive changes in the chemical, and/or physical conditions of !he soil,

such as pH, moisture retention and aeration by the legume plants. Secondly, the plant.; may

have participated in hydrocarbon degradatim via their support of symbiotic root-associated

micro-organisms that actually accomplished hydrocarbon degradation (Stamps et a!., 1994;

Ensley et al., 1997; Merkl et al., 2005). Since different species of plant have varying cffccts

on rhizosphere micro-organisms and their degradation activity, the Gliricidia, Leucnena and

Calopogonium spp. supplemented with poultry manure showed promise in hydrocarbon

degradation.

4.2.4 Degradation of Petroleum Hydrocarbons and Correlation with Heavy Metals

Total hydrocarbon degradation and correlation analysis of heavy metals (Al, Ni, Pb, Zn and

Cu) with total hydrocarbon content of the soil are shown in Tables 22 and 23. Within the end

of 3 months, reductions in THC when the soil was contaminated with 50000 mg kg-' (5%)

spent oil were 29%, 30.4%, 30.7%, 32.1%, 32%, 43.2%, 43% and 42.1% for AS, &+GI,

&+Le, As+Ca, As+Pm, AS+GI+Pm, A5+Le+Pm and AS-tCa+Gl, Pm respectively. In

absolute terms, 14508, 15216, 15348, 16036, 15989, 21687, 21481 and 21058 mg kg-' of

hydrocarbons have been degraded from As, A5+GI, As+Le, A5+Ca, A5+Pm, AS+GI+Pm,

As+Le+Pm and As+Ca-t-Pm plots, respectively.

Tahlc 22: Degradation of total hydrocarbon content (THC) of the top 0 - 30cm soil as influenced by the treatments

- Sprv t oil Residual ~otf l l loss Net loss due to Degradation loadin5 THC in THC amendment rate

_I_mgW) _ l ! ! % L ~ ! . f (%) (YL~YI-

As

AS 4- GI

A5 t- J,e

A5 t - Ca

A5 -k Pm

A5-ttil+ Pm

A5t-Le + Pm

A5+Ca + Pm

A5

A5 + GI

A5 + Le

A5 + Ca

A5 + I'm

As+GI + Pm A5+Le + Ptn As-tCa -t- Pm

A5

A5 + GI

A5 + Le

A5 + Ca

A5 + Pm As-t-GI + Pm A5+Le + Pm As+-Ca -k Pm

29.0

30.4

30.7

32.1

32.0

43.2

43.0

412.1

1 21h Month

38.4

64.5

64.2

65.2

66.7

69.1

68.9

68.4 , ' I* '

181h Months

59.0

63.4

63:8 1 1 I .

63.7

60.9

64.5

54.3

64.3

A5

~5 + GI

A5 + Le

A5 + Ca

AS + Pni

&+GI + Pm

,451-Le 1- Pm

A5+ta + Pm

A 5

As + GI

A5 + Le

As + Ca

A5 + Pm

A+ GI + Pm

A5+Le + Pm

A5+Ca + Pm

24'h Month

63.6

71 ,O

70.1

69.3

68.5

78.0

77.4

76.9

36"' Month

68.3

79.4

78.8

75.6

71.3

79.6

73.5

79.3

Total loss (%) = [Spent oil loading - Residual THC (Treatment) / Spent oil loading ] x 100

Net loss (%) = % loss in THC (Treatment) = % loss in spent oil (Control)

THC Degratation = Initial THC - THC at the end / Degradation time. ., ,, . w T . ,*. , .I*. '

Similarly, in 12 months, 19352 mg kg-' C38.4%), 32258 mg kg-' (64.5%), 32114 mg kg-'

(64.2%), 32579 mg kg-' (65.2%), 33362 nlg kg-' (66.7%), 34529 mg kg-' (69.1%), 34451 mg

kg'' (68.9%) and 34 184 mg kg-' (68.4%) oil were lost from AS, A5+GI, As+Le, As+Pm,

As+GI+Pm, As+I,e+Pm and A5+Ca+Pm respectively, when 50,000 mg kg" of oil was

applied. In 18 months, soils contaminated with 100000 mg kg-' (10%) spent-oil showed

reductions in THC in the magnitude of 58967 mg kg'' (59%), 63383 mg kg-' (63.7%), 6378

mg kg" (63.8%), 63653 mg kg-' (63.7%), 60882 mg kg-' (60.9%), 64522 mg kg-' (64.5%),

64282 mg kg-' (64.3%) and 64264 mg kg" (64.3%), respectively for As, A5+GI, As+-Le,

AS+Pm, A5+GI+Pm, A5+Le+Pm and As+-Cai-Pm soil. In 36 months, the total loss in THC

when 100000 mg kg-' spent oil was applied were in the magnitude of 68.3%, 79.40/0, 78.8%,

75.6%, 71.3%, 79.6%, 79.5% and 79.3% ior As, A5+GI, A5+Le, As+Ca, AS+Pm, As+Cili-Pm,

As+Le+Pm and As+Ca+Pm. This corresponded to mean THC degradation rate of 379.3,

44 1, 437.9, 420.2, 396.1, 442. I, 44 1.4 and 440.5 mg kg-' day-' respectively. In 3 months, the

As+Le+Pm and As+Ca+Pm showed T l X degradation rate of about 240 mg kg-'day-'

indicating that it will take about 208 days (7 months) for 50,000 mg kgv1 spent oil to be

degraded completely from soil treated with any of Leucaena or Calapogonium with 10 t ha-'

of poultry manure. This result will be useful in designing bioremediation scheme aimed at

cleaning up petroleum contaminated soils. However, the Gliricidia sepium with poultry

manure consistently showed high potential in the removal of hydrocarbons from the soil.

This was followed by Leucaena and Calal9ogonium spp.

Within 3 and 12 months, net loss.of THC due to treatments was such that A5+GI+Pm > .,,,..1..I 'I*.

A5+Le+Pm > As+Ca+Pm > As+Ca > As+Pm > As+Le+As+GI, relative to AS. In 18 months

when additional 100 tons ha-' spent oil and 10 tons ha-' poultry manure were applied the net

loss in THC due to treatments was such that AS+GI-tPm > As+Le+Pm = As+Ca+Pm > A5+Le

> AS+GI >.A5+Pm (Table 22). In 36 months, net loss of THC due to combination of

Gliricidia sepium with poultry manure was 1 1.3% with mean degradation rate of about 442

mg kg-'day-'.~his value is about 1.4mg kg-'day-' less than the net loss in 24 months.

The implications of these results are that: in 12 months after oil contamination, the legume

plants with poultry manure enhanced milximum degradation of total hydrocarbons (Table

22). This agreed with studies of Odu et nl. (1989) and that of Molina-Barahona et ol. (2004)

that the numbers of hydrocarbon-utilizing micro-organisms are usually high in soil 1 year

after oil spillage. They observed that the total numbers of soil microbes increased greatly

after a petroleum spill, and that hydrocarbon-utilizing fungi in soil increased from 60 to 82%,

whereas hydrocarbon-utilizing bacteria increased from 3 to 50%, a few months following oil

spill. Secondly, the improvement in intrinsic soil properties by the legume plant residues

may have acted as bulking agent and/or as bacterial biomass suppliers, thereby supporting the

high THC loss observed in plots treated with the legume plants and poultry manure.

Correlation analysis (Table 23) between THC and some heavy metals and water retention at

field capacity (-6kpa) showed highly significant (P < 0.01) positive correlation with Pb ( r =

0.864) and with Cu (r = 0.716). The THC also showed significant (P < 0.05) positive

correlations with A1 (r = 0.572), Ni (r = 0.598) and Zn (r = 0.617). The high positive

correlation between THC and Pb and Cu indicate that THC in spent oil is directly related

with the high levels of Pb and Cu earlier observed in this study. The residual THC in soil

showed negative (P < 0.05) correlation with soil moisture content at field capacity.

Table 23: Correlation between the residual total hydrocarbon content (mg kg-') and heavy metals and water holding capacity in the soil after 36 months (N = 63)

- Correlation Coeff~cient (r) Water content at Ai Ni Pb Zn Cu 60cm tension

-- (cm3 cm) THC (mg kg-') 0 . 5 7 2 T S 5 9 8 * 0.864** 0.617* 0.716** - -- -0.63 1 *

** Significant at P < 0.01 * Significant at P < 0.05

-(ore, optimization of soil properties related to water holding capacity will determine the

r7lnolant of' liv~lrocnrbons being lost in the qoil and the effectiveness of any bioremediation

tw ,: 2;frilr. ' f i r ~ignificant (P < 0.05) positive correlations between the residual THC and Al,

Ni a r d %n sl~o~vrtl that as THC remaining in the soil is high, so also the concentration and

toxicity oTA1, Ni and Zn increase in that order. This development according to Ernst (1990)

will impose ncgative affects on microbial activities and plant development.

4.3. Biological Enhancement

The populations of viable and hydrocarbon-degrading micro-organisms in the soil are shown

in Table 24. The viable colony forming units (cfu) of microbial population at 3 months for

the 0 - 30cm depth ranged from 1.2 x lo6 to 2.6 x 107cfu g-l whereas hydrocarbon -

degrading micro-organisms (H-dms) ranged from 2.4 x 1 o2 to 8.1 x lo4 cells g" during the

same period. Total viable counts showed highest cfu g-' soil of 2.6 x lo9, but showed the

lowest I-I-dms of 2.4 x lo2 for the control soil (C). On the other hand, the As soil showed the

lowest total viable counts of 1.2 x lo6 cfu g-l soil, but high value of 5.3 x lo4 cells soil of

14 - dms, where as &+GI soil showed the highest H-dms of 8.1 x lo4 cells g-l soil in 3

months. At 12 months, total counts and H-dms respectively, showed a drastic reduction in

the AS soil (6.1 x 1 04cfug-I soil and 2 . 8 ~ 1 ~~ce l l s~ - ' so i l ) respectively. Highest I-I-dms

population of6.2 x lo7 cells g-l were recorded for the As + GI + Pm soil.

Tablc 24: Viable and hydrocarbon-degrading micro-organism populations in the contaminated soil as influeneed by the treatments, --

Treatment CFU g - y - (Cells g-') -- CFU g-') (Cells g-') -

0 - 30cm Depth -- 30 - 60cm Depth 3 Months

4.8 x lo7 1.1 x lo2

5.3 104

8.1 x lo4 7.0 x lo4 5.6 x lo4 1.9 x lo4 4.6 x lo5 4.2 x lo5 3.1 x lo5 2.4 x lo2

12 Months 2.8 x lo4 5.8 x lo5 5.0 x lo5 4.9 105 1.2 x lo5 6.2 x lo7 5.8 lo7 5.3 107 1.3 x lo2

24 Months 1.8 105 1.2 x lo5 3.6 x lo5 3.0 x lo6 1.6 105 8.5 x lo7 5.5 lo7

., ,,. . . p l x.11~7. < 103

36 Months 1.5 x lo4 5.1 x lo5 1.6x105 . 2.0d'105 - 1.3 x lo4 7.2 x lo5 7.4 lo5 6.1 x lo5

C -- 1 . 9 ~ 104 < lo3 f I-dm = Hydrocarbon degrading micro-organism a. = According to the method of ~ o r o w i tz-et al. (1 978)

'The results also showed that although plots treated with poultry manure only showed high

total viable counts at 3, 12 and 18 months, the M-dms were relatively low (1.9 x I 04, 1.2 x

lo5 and 1.6 x lo5 cells g-' soil), respectively, This development implies that the poultry

manure only did not encourage the proliferation of hydrocarbons-degrading microorganisms,

rather, their presence is encouraged with the availability of petroleum hydrocarbon via oil in

the soil and a suitable plant species.

The relatively higher H-dms recorded for plots treated with legume plants and the

contaminated soil (A5) is in conformity with Odu et a1 (1989) and Horowitz et al. (1978).

They observed that the presence of gasoline in the soil resulted in significant increase in

microbial population and metabolic activities. They further reported that the number of

hydrocarbon - utilizing organisms were most abundant in oil polluted sites than in the

unpolluted sites, and that the total numbers of hydrocarbon - utilizing microorganisms were

I00 to I000 times higher in a zone of contamination of an aquifer containing Jp-s Jet fuel

than the non polluted zone. Inference drawn from this result is that substantial adapted

population of micro organisms exist in hydrocarbon contaminated zones with the bacterial

biomass increasing as the organic contaminants are metabolized. Large population of H-dms

may have been stimulated by the legume plant root exudates or that their widely branched

root systems provided large root surface for the growth of large population of H-dms. Other

authors have reported that counts of hydrocarbon degraders are usually higher in soil with

addition of nitrogen and phosphorus (Huesemann and Moore, 1993).

. ,, . . .,. ,v . > J '

Generally, the viable counts and H-dms decreased with soil depth, reaching a maximum of

8.2 x lo6 cfu g-' and 2.9 x 10\ells g-', respectively for A5 + GI + Pm at 3 months, 4.6 x lo6

cfu g-', and 7.0 x lo3 cells g-'- respectively at 12 months, and 5.5 x 1 o8 cfu g-' viable counts

for A5 + GI + Pm, and 2.5 x 10' cells g-' W-dms for As + GI at 36 months. This trend is,

however, in agreement with Avidano et al. (2005), Katsivala et al. (2005) and Bossert and

Compeau (I 995) reported that microbial population decreased with soil depth.

4.4. Effects on Crop Performance

The maize plant height and leaf area were adversely inhibited during the establishment and

vegetative growth stages during the lS' planting season (Tables 25 and 26). When the spent

oil load was increased to 10% (wlw) in the second planting year, the plants died before 72

DAP (Table 25 and 26). Several factor? may have contributed to the death of the maize

plants, among which may include: lack of adequate oxygen, decrease in soil water retention

capacity, surface crusting and other undesirable soil phy,ical and chemical conditions

brought about by the spent oil pollution.

Similar observations have been made by Anoliefo and Vwioko (1995) in pepper (Capsicum

annum L.) and tomato (Lycopersicon esculentum Miller) and for maize and sugar cane by

Molina - Barahona (2004). Mean plant growth was higher (1 15.6 cm, 107.6 cm and 125.6

cm) for A5 + GI + Pm during the first, second and third plantings, respectively. Leaf area

attained a maximum of 486.9cm2 at 91 DAP during the first planting 449.7cm2 at 96 DAP

during the second planting and 43 I .5cm2 in 98 DAP during the third planting for AS+GI-kPm.

Maximum leaf area was attained during the cobsettinglfilling growth stage, when plant

height of 134.7cm, 166.5cm and 180.lcm were attained at 91, 96 and 98 DAP for the

A5+GI+Pm soil. When compared with the control soil, it was evident that spent oil depressed

plant height by 13% and 59% relative to control (C) during establishment and vegetative

growth stages of the crop respectively in the first planting season. During the second

planting, spent oil depressed plant growth by 89% and 49% at 30 and 48 DAP relative to the

control. In the third planting, when the residual effects of spent oil were tested, on the maize

plant the effect of the oil was still pronounced on plant height and leaf area during the

establishment and vegetative growth stages of the crop. Growth reduction at these growth

stages of the plant has been reported by Anoliefo and Vwioko (1995) to affect crop yield, as

the cobs are usually empty.

Table 25: Mean height of maize plant in oil-contaminated soil under different treatments -- -

Plant Height (cml Growth Stage (DAP)

Treatment Establishment Vegetative Tasselling Cobsettingl Mean (28 DAP) (40 DAP) (65 DAP) Filling

------- (91 DAP) -3f- 2004 (1 Planting Season)

AS As + GI A5 + Le AS + Ca AS + Pm As+Gl+Pm A5 + Le + Pm A5 + C a + P m C Mean

A5 As + GI A5 + Le AS + Ca A5 + Pm & + G I t P m As+Le+Pm AS +Ca+Pm C Mean

As As + GI As + Le AS + Ca AS + Pm AS + (31 + Prn As+Le+Pm As+Ca+Pm C

15.8 17.5 16.5 16.4 26.4 31.1 26.1 31.1 17.8 22.1

7.4 21.2 19.4 14.9 52.8 53.3 49.9 48.8 12.3 3 1.1

(28 DAP) 5.7

25.3 24.0 23.4 52.1 52.2 28.7 36.0 17.6

39.3 42.5 48.3 60.9 44.9 58.4 53.4 56.6 122.4 130.3 134.5 142.2 122.3 138.3 117.0 130.3 62.4 65.3 82.7 91.7

2005 (2" Planting Season) 9.0 O.O(D) 37.0 52.2 29.0 54.1 3 1.7 56.9 59.8 126.5 92.7 137.8 71. 128.0

64.3 143.9 13.4 28.7 43.2 8 1.2

2006 (Residual Effect) (45 DAP) (78 DAP

7.2 ,, * (, . r l 7 0 .O(D)

38.2 52.8 30.1 58.4 30.4 62.1 68.4 136.2 117.4 174.0 71.7 , .' 144.0 128.8 136.9 6.3 65.9

Mean 27.6 61.4 92.3 2004: LSD (0.05) Treatment = 21.740, Growth stages = 34.003, T x Gs = 28.636

44.7 74.7 73.6 62.4 156.6 134.7 152.7 152.7 67.2 105.0

O.O(D) 67.9 58.3 62.2 14 1 .O 166.5 144.2 152.8 34.5 92.0

(98 DAP) 0.0 (D)

67.3 62.6 75.2 154.6 180.1 166.7 142.5 79.8 103.2

2005: LSD (0.05) Treatment = 25.02, Growth stages = 40.86, T x Gs = 14.446, D = Death 2006: LSD (0.05) Treatment = 25.71, Growth stages = 41.984, T x Gs = 14.841, D = Death DAP = Day after planting

Table 26: Leaf area of maize plant under different treatments in the oil- contaminated soil

Leaf Area (cm2) ~ r & t h Stage (DAP)

Treatment Establishment Vegetative Tasselling Cobsetting/ Mean (28 DAP) (40 DAB) (65 DAP) Filling

- - (91 DAP) 2004 (1'' Planting Season)

As As + G1 AS + Le AS + Ca As + Pm AS + G1+ Pm As 4- Le + Pm As +Ca+Pm C Mean

As As + G1 AS + Le As + Ca As + Pm Ag+Gl+Pm A=, +Le + Pm As+Ca+Pm C Mean

As As + GI A=, + Le AS + Ca As + Pm As+GI+Pm As+Le+Pm AS +Ca+Pm C Mean

13.4 16.5 15.4 13.7 36.9 55.5 60.0 50.0 12.8 30.5

(30 DAP) 11.8 32.9 18.6 18.9 41.4 53.0 58.6 47.9 10.4 32.6

17.9 60.9 28.7 104.0 42.8 1 12.4 44.7 122.8 44.7 168.3 104.7 463.2 98.6 403.2 89.1 388.2 28.1 93.2 55.5 212.9

2005 (2"d Planting Season) (48DAP) (72DAP)

14.7 O.O(D) 42.0 114.1 41.2 116.8 43.1 121.5 53.3~ 156.7 112.5 447.4 93.1 416.0 91.4 394.1 22.3 82.4 57.1 205.4

2006 (Residual Effect) (28 lo..i DAP) v . - I , +. , (45 . la DAP) (78 DAP

12.5 O.O(D)

81.2 138.6 150.2 163.8 185.3 486.9 425.6 406.4 171.5 245.9

(96 DAP) 0.0 (D) 136.4 151.0 165.2 289.1 449.7 436.1 411,3 85.9

236.1

(98 DAP) O.O(D) 134.9 159.2 167.1 274.7 43 1.5 420.1 372.0 71.4

225.7 2004: LSD (0.05) Treatment = 42.501, Growth stages = 63.752, T x Gs = 21 .25 1 2005: LSD (0.05) Treatment = 47.091, Growth stages = 70.636, T x Gs = 23.545, D =

Death 2006: LSD (0.05) Treatment = 34.545, Growth stages = 51.817, T x Gs = 17.272, D =

Death DAP = Day after planting

Therefore, low or no yield of maize crop in spent oil contaminated soils is usually initiated

during germination, establishment and/or vegetative growth periods of the plant (between 14

to 48 DAP). Plant height (Table 25) and leaf area (Table 26) were significantly influenced

by the treatments (P < 0.05). They also varied significantly (P < 0.05) in growth stages and

across treatments, indicating that poultry manure with the legume plants modified the soil

environment positively to enhance growth and yields of maize in petroleum hydrocarbon-

contaminated soils.

The plots treated with a combination of legume plants and poultry manure showed high

percent germination (93, 90 and 88%) for As+Gl+Pm, AS+Le+Pm and A5+Ca+Pm,

respectively. After 24 months, the residual effects of the oil reduced germination index of the

maize seeds by 66% during the third planting season.

Grain yield of 4.9lt ha-' was obtained during the first planting and 8.25 t ha-' and 6.46 t ha-',

respectively during the second and third planting for A5+Gl+Pm. In the three planting

seasons, no yield was recorded for As and control soils. The zero yield in these plots were

caused by either low growth, due to nutrient deficiencies or the adverse affects of the oil

during the establishment and/or vegetative growth stages of the crop. Seventy-two days after

planting (72 DAP) during the second planting, plant height and leaf area measurements were

not possible, because the few maize plants that germinated (Table 25) died prematurely *,,,,..!. ,? , ' *

(Table 27). This result demonstrates that spent lubricating oil inhibits germination and

growth of maize crop.

Table 27: Effects of treatment on germination and grain yield of maize --- --

Maim grain yield (tons ha-') Germination Count (%).

Treatment 2004 2005 2OO6* 2004 2005 2006* - --

As 0.0" 0.0" 0 . 0 ~ 41R 36' 34a

- Yield and germination count followed by different letters within the years are significantly different at P < 0.05; * Residual Effect

The reasons for the no yield andlor death of plants after a few weeks may probably be due to

insufficient aeration of the soil, caused by the displacement of air from the pore spaces by the

oil, and an increase in the demand for oxygen brought about by the activities of oil-

clccomposing microorganisms. It could also be due to the fact that oil penetrated and

accum~~lated in the plants, causing damage to cell membranes and leakage of cell content

earlier reported by Udo and Fayemi (1 975) and Anoliefo and Vwioko (1 995).

CHAPTER FIVE

5.0 SUMMARY AND CONCLiUSION

Studies on the use of legume plants and poultry manure to improve the physical, chemical

and biological properties of petroleum-waste- contaminated soil were carried out in an

Nsukka sandy soil. Implications on crop productivity were assessed by evaluating the

growth, development and yield of maize (Zea mays L.) crop grown on this soil. Particle-size

analysis showed that the soil is sandy loam up to 60 cm depth.

Aggregate stability measured by the mean-weight diameter (MWD) of water stable

aggregates, was improved with time in all the treatments except in soils contaminated with

the waste motor oil without any treatment (As) and also in the control soil (C.). In 12 and 18

months after oil application, As + GI + Pm gave an improvement of 58% and 94% in MWD,

respectively, with concomitant increases of 136% and 187% in saturated hydraulic

conductivity. Saturated hydraulic conductivity was low for AS soil, following repeated

application of the spent oil, suggesting that oil succeeded water in the competition for pore

spaces, leading to reduction in water film thickness around macro-aggregates. The use of

Gliricidia sepuim combined with poultry manure showed significant (P < 0.05) increase in

unsaturated hydraulic conductivity from 70.5% in 3 months to 602.4% in 36 months.

The Gliricidia sepium with poultry manure showed progressive enhancement in structural

stability of the soil from I O%.t~,.'&4?4 between 12 and 36 months. This was due to the dccp

rooting system of Gliricidia sepiunl as well as to its high biomass production. Macro-

porosity for the contaminated soil (AS) was low, ranging from 6% to 9%. Top soil and sub

soil macro-porosity varied significantly (P < 0.05) among treatments and months after oil

application. The use of Gliricidia sepium and Leucaena leucocephala enhanced macro-to

micro-porosity ratio. This justifies that these legume plants generated and added high

organic matter to the soil. The low macro-to micro-porosity ratio, observed in thc

contaminated soil (A5), could lead to C02 build-up and toxicity to both plant roots and micro-

organisms as well as to low permeability resulting in high risk of soil erosion.

A combination of poultry manure with Gliricidia sepuim, Calopogorium cerulean and

Leucaena leucocephala improved organic matter after 24 months. The use of poultry manure

only (As + Pm) reduced soil organic matter content (SOM) from 20.6% 3 months to 19.2%

36 months, indicating that application of poultry manure alone is not a sustainable and viable

option in bioremediation technology. Crusting hazard (risk of sealing) was high for A5 and

control soil (5% and 6%) respectively. Significant (P < 0.05) reduction in crusting hazard

relative to As was observed between 12 and 36 months. The reduction was most attributable

lo high soil organic matter generated by the legume plants. Decrease in soil organic maler

content and population of living organisms were strongly associated with soil sealing and

crusting.

Application of poultry manure only reduced the soil bulk density by 2.8% between 3 and 12

months, and later showed a 12% increase between 24 and 36 months after oil application,

indicating that poultry manure had short-term effects in the improvement of the soil physical

properties. Bulk density of the soil reached a maximum of 1.65 g cm-3 in 36 months in the

contaminated plot (A5) due to the formation of structural crust and pore blockage caused by

the oil. In 36 months, top soil bulk densities were significantly improved in plots treated

with Gliricidia, Leucaena and Calopogonium combined with poultry manure. Therefore, the

legume plants are promising species in the bioremediation of soil bulk density, saturated

hydraulic conductivity, aggregate stability and macro-to micro porosity ratio.

Water retention at saturation (0 kPa) and field capacity (-6 kPa) showed steady increases with

time in plot treated with the legume plants and poultry manure whereas, that contaminated

with oil without these treatments showed very low water retention capacity at these water

potentials, during the same pv,iodq:,,.Tbg -6 kPa water content, representing field capacity,

was 52% less than water content at saturation for the A5 in 3 months and 50% less in 36

months after oil application. The low water retention capacity in the contaminated soil (A5)

suggests that oil succeeded water in the competition for pore spaces and made the soil to

appear waxy, 'preventing water penetrati,pn fro* above.

The sodium adsorption ration (SAR) values of the soil ranged from 0.08 to 0.40, with the

highest value of 0.40 recorded in 36 months in the A5 soil. The implication of this is that a

high percentage of exchangeable sodium was deposited in the soil via the spent-oil

application. Such values of SAR can increase the tendency of the soil to disperse. Plots

treated with a combination of legume plants and poultry manure, showed gradual decreases

in SAR with time. Electrical conductivity, salt concentration and osmotic pressure were

significantly (P < 0.05) high in the A5 soil than in soils treated with the legume plants and

poultry manure. In 12, 18, 24, 30 and 36 months, these parameters were above threshold

levels in the contaminated soil, such that growth and yield of the maize crop were restricted.

However, the use of Gliricidia, Leucaena and Culopogoniurn combined with poultry manure

significantly (P < 0.05) reduced the salinity parameters to negligible levels within 12 to 36

months after the oil contamination.

There were significant (P < 0.05) positive correlation (r = 0.795) between saturated hydraulic

conductivity (Ksat) and macro-porosity, and a very significant (P < 0.01) negative correlation

(I- -0.91 8) between KSat and micro-porosity. 'Therefore, micro-to macro-porosity ratio can be

used to evaluate the effects of oil application on soil water characteristics. The highly

significant (P < 0.01) positive relationship (1-0.907) between crusting hazard (R.) and soil

organic matter (SOM) confirmed the positive role of SOM in reducing soil crusting. Thus,

soil organic matter, saturated hydraulic conductivity and macro-porosity were positively

modified by the use of the legume plants and poultry manure.

Electrical conductivity, SAR and salt concentration had negative effects on Ksat, soil crusting

and MWD of water stable aggregates, suggesting that management of soil physical properties

such as infiltration, hydraulic conductivity and aggregate stability require practices that will

prevent and/or reduce high values of ESP, SAR, Ece and salt concentrations in soil.

Build-ups of Al, Ni, Pb, Zn and Cu were observed in soils contaminated with spent oil and

those treated with poultry manure alone relative to the control (C). At 3 months, Pb, Zn, and

Cu showed a significant (P < 0.05) difference in concentrations in the contaminated soil ., ( I . ..1. d

relative to the control. Plots treated with PM showed the highest values of 17.48, 43.6 and

48.3 mg kg-' for Pb, Zn, and Cu respectively in 3 months, and maintained similar trend after

6 months. In 12 months, the increase in Al, Ni, Pb, Zn and Cu concentrations in the A5 soil

were 43%, 158%, 702%, 1 1 8% and 44$%, respectively over the control; therefore the soil

was contaminated with Al, Ni, Pb Zn and Cu via the oil applications. The implications of

such levels of concentrations are that these metals can block the essential functional groups,

displaced other ions or modify the active conformation of biological molecules, and become

toxic to both higher and micro-organisms, All the legume plants (Gliricidia, Leucacna, and

Calapogonium spp.) when combined with poultry manure, showed positive reductions in

heavy metals concentrations in the soil. At 36 months, the Gliricidia sepium combined with

PM significantly reduced Al, Ni, Pb, Zn and Cu concentrations by 21%, 96%, 90%, 42% and

50%, respectively, relative to the A5 soil. This development is most attributable to the fact

that the legume plants belong to the small group of plants that can tolerate and/or accumulate

high levels of certain heavy metals.

'The contaminant - pollution index (~,/p index), evaluated for Ni, Pb, Zn and Cu

concentrations, indicated that the applications of oil and poultry manure led to slight

contamination of the soil with Pb, moderately to severe contamination with Zn and very

severe contamination with Cu. Within 18 to 36 months, there was general reduction in c/p

index for Pb, Zn, and Cu especially, in plots treated with legume plants. Therefore, these

legume plants can be exploited in clean-up of heavy metal contaminated soils.

Apart from the inherent acid nature of the soil of the experimental site, the oil contributed

largely to the extreme acidic nature of the A5 soil. The Gliricidia, Lezicaena and

Clrrlapogonium with poultry manure increased the soil organic carbon by 76%, 74% and 76%

respectively, within 6 months and a 2-fold increases in 24 months. The C/N ratio of the top

soil was rather very high in the contaminated soil, reaching 16:1 in 3 months, and 13:l and

14:l within 12 and 36 months respectively. Available P, exchangeable ca2+, M ~ ~ + and K+ of

the top soil were low throughout the 35 months in the A5 soil, but ranged from low to

medium in plots treated with legume plants and poultry manure. It is believed that the root

exudates from the legume plants may have stimulated the microbial environment and certain

biogeochemical reactions in the soil which enhanced the availability of essential plant

elements. However, the general observations were that contamination of the soil with spent

oil depleted the soil nitrogen, phosphorus and potassium status and increased soil acidity and . < , , . . . l . . P . , 42 '

exchangeable sodium.

Total hydrocarbon content (THC) of the soil, as modified by the treatments, showed that

mean residual THC in 36 months ranged from 1900 mg kg-' in the control to 41033 mg kg-'

in the contaminated soil without legume plants nor poultry manure for top 0 - 30 cm soil and

2102 mg kg" to 37311 mg kg", respectively for 30 - 60 cm depth. The ability of the

treatments to enhance degradation of TFTC was in the order of As+GI+Pm > As-tLe+Pm >

As+Ca+Pm > A5+GI > As+Le > As+Ca tPm > A5+Pm for top soil and sub soil. Significantly

low residual THC was recorded for the plots treated with Gliricidia, Letlcaenn,

Calopogonuim and poultry manure, an indication that the legume plants participated in

hydrocarbons degradation via their supports in symbiotic root-associated micro-organisms as

well as enhancement of the physical and chemical conditions of the soil such as pH, moisture

condition, aeration and additions of nutrients.

At the end of I2 months, 19352 rng kg-' (38.5%), 32258 mg kg-' (64.5%), 32114 mg kg"'

(64.2%), 32579 mg kg-' (63.2%), 33362 mg kg-' (66.7%), 34529 mg kg-' (69.1%), 34451 mg

kg-' (68.9%) and 34184 mg kg-' representing 68.4% of oil were lost from A5, A5 + GI, AF +

C, As + PM, As + GI + Pm, A5 + Le + Pm and A5 + Ca + Pm respectively, when 50,000 mg

kg-' (50%) of spent oil was applied. At the end of 36 months, loss in THC when 100000 mg

kg-' spent oil was applied were in the magnitude of 68.3% 79.4%, 78.8%, 75.6%, 71.3%,

79.60/0, 79.5% and 79.3% for A5, A5+GI, A5+Le, As +Ca, A5i-Pm, As-tGl+Pm, A5+Le+Pm

and A5+Cat-Pm respectively. This corresponded to mean THC degradation rate of 379.3,

441, 437.9, 420.2, 396.1, 442.1, 441.4 and 440.5 mg kg-' day-', respectively. The THC

degradation rate was at maximum in 12 months, which corresponded to the period of

maximum hydrocarbon-utilizing micro-organisms.

The total hydrocarbon content (THC) showed highly (P < 0.01) positive correlation with Pb

(r=0.864) and Cu (r =0.716). Aluminum (A!), Nickel (Ni) and Zinc (Zn) also showed

significant (P < 0.05) positive correlation with the THC, indicating that THC in spent oil is

directly related to the elevated and toxic'ity levels of Pb, Cu, Al, Ni and Zn in such soils.

Such concentration and toxicity levels have deleterious effects on soil microbial activities

and plant development.

. ,, ..!. 7 . ' t * '

Biological enhancement of the soil, measured by the number of viable counts and

hydrocarbon-degrading micro-organisms (H-dms), showed that H-dms was high or

maximum in 3 months after oil application, whereas poultry manure showed large number of

colony formlng units (cfir) of viable cq,unts afid very little (cells kg-') of Fl-dms. Substantial

population of H -dms was obtained in contaminated soils, with the bacterial number

increasing as organic contaminants were metabolized. The large population of H - dms may

have been stimulated by the legume plant root exudates and/or that their widely branched

root systems provided a large root surface for the growth of H -dm microbial pop11 a t' ion.

Generally, the viable counts and M-dms decreased with soil depth, reaching a maximum of

8.2 x lo6 cfu g'' and 2.9 x lo3 cells g-', respectively for A5+GI+Pm in 3 months, 4.6 x 10"

cfu g-' and 7.0 x 10%ells g-', respectively in 12 months and 5.5 x 10' cfu g' viable counts

for As+Glt-Pm, and 2.5 x lo4 cell g-' of 11-dms for A5+GI in 36 months.

Bio-test of the oil, using maize crop, showed that growth and development of the crop were

inhibited during the establishment and vegetative growth stages. When the spent oil load

was increased to 10% (w/w) during the sewnd planting year, a few plants that germinated

died hcfore 72 days in the As soil. Reasons for such development may have been due to'lack

of adcq~~ate nxygcn in the soil, increase in soil wilting coefficient due to decrease in soil

water retention capacity, and degradation in physical and chemical conditions brought about

by the oil pollution. Maximum leaf area was attained during the cob setting/filling growth

stage when plant height of 134.7cm, 166.3cm and 180.lcm were recorded at 91, 96 and 98

PAP for the A5 tGI-tPm soil. When compared with the control (C.), spent oil depressed plant

height by 13% and 59% at the establishment and vegetative growth stages respectively

during the first planting season. During the second season, the oil depressed plant growth by

89%and 49% at 30 and 48 DAP. When the residual effect of the oil was tested on the crop

during the third planting season, there was persistent reduction in plant growth at the

establishment growth stage. Growth reductions during the establishment, and vegetative

growth stages of the plant had deleterious effects on the maize grain yield as cobs were

usually empty.

The Gliricidia when combined with poultry manure (As+GI+Pm) significantly (P < 0.05)

increased the grain yield of maize plant. Yields of 4.91 tons were obtained during the first

planting, 8.25 tons ha-' and 6.4 tons ha-' obtained during the second and third planting

seasons, respectively. No yield was recorded for As and C (control soil), probably due to ., ,,. . * 3 " ,*. , '

nutrient efficiencies, and the fact that the plant growth and development were inhibited

during the critical growth stages of the crop. The no yield recorded in contaminated soil (As)

may have been caused by the unfavourable physical conditions due to the soil by tlie oil or

that the oil penetrated and accumulated in the plants, causing damage to cell menlbranes and I I

leakage of cell content.

Conclusions drawn from this study are that:

i. application of spent oil onto a sandy loam soil increased the soil bulk density, reduced

saturated and unsaturated hydraulic conductivities, aggregate stability and water retention A

capacity at saturation (0 kPa) and field capacity (-6 kPa). . . 11. The waste oil clearly had detrimental effects on germination, growth, development and

yield of maize crop as well as on the soil microbial populations. The effects of the oil

persisted in the soil after 36 months.

iii. Heavy metals (AI. Ni, Pb, Cu and Zn) accumulation and toxicity, including high salt

concentration, electrical conductivity, and degradation of the soil physical, chemical and

biological properties are the dominant adverse environmental impact of indiscriminate

disposal of waste motor oil onto farmlands.

iv. Gliricidin sepitml, Leucnena Le~cocq?hala and Calopogonitrm cerulean are promising

species in the removal of oil and hcavy metals from soils, as well as bioretnediation of

physical, chemical and biological properties of the soil, and

v. The legume plants enhanced maximum degradation of total hydrocarbons in 12 months.

The legume plants combined with poultry manure is effective in restoring the soil health

when petroleum hydrocarbon and heavy metals are the dominant problems. Extensive

and vigorous research on these legume plants and other species of tropical plants will

provide valuable answers to a number of questions concerning reclamation of petroleun~

contaminated lands.

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Appendix I: Particle size distribution of the soil after 36 months sf oil apglir .~!ba - ----. -- --

Treatment Sand Silt Clay Texture Sand Silt Clay, l irlnrt- 1 k -1 d g k R- (g g (gk a 3 (gk g-l) @k 15-l) (gk g- ) . --

42 182 22 1 62 2 1 171 50 183 54 184 52 151 42 183 23 I61 4 0 181

121h month 5 1 180 53 183 3 3 182 4 1 150 5 0 150 5 0 150 5 4 1 64 5 4 1 74 4 1 183

241h month 44 18 1 42 184 40 184 40 18 1 53 173

3hih month 65 175 50 180 4 3 173 50 180 5 1 184 50 180 5 0 166 4 5 16 1

4 3 184 4 3 18 1 34 151 4 1 183 5 1 182 5 0 174 43 1 73 44 173 44 153

lg th month 42 184 4 1 1 84 5 3 1 73 4 3 IGI 5 0 163 5 0 163 42 182 3 1 181 44 1 72

30"' month 4 183

42 184 5 4 153 4 1 18 1 50 1 82 4 8 178 4 1 1 74 42 169 46 161

SI d

Sf, SL SI, S L, SL SL SL SL

SI, SL; SL SL SL SL SL S1, SL

S L SL S I, SL SL S I> SL S I, SL

I\pi'"*!tli~ 1 Cont'd rd

- 3 ~nor~ths 30 - 60cm --- --8'GGzs--

Trca tment Sand Silt Clay Texture Sand Silt Clay ---- -. I~&C'L- ( @ - g ~ l ~ k ~ I ) - - - - 3 ' 1 ~ k _ ~ ( g k g ~ ' ~

100 121 S1, 769 110 121

1 2 ' ~ month 9 1 123 8 1 193 62 152 58 134 6 7 143 4 8 197 6 1 172 70 166 70 142

24"' month 92 123 SL 80 190 SL 60 152 SL 60 149 SL 65 150 SL 69 193 SL 5 1 W A "3 . -1. BL 5 8 173 SL 74 142 SL

36'h month 8 1 122 8 0 190 62 156 6 3 147 68 163 70 191 70 183 7 1 181

lath month 9 1 123 8 0 190 6 1 156 5 8 143 67 15 1 5 0 197 62 175 70 166 7 1 146

30'" month 92 124 80 190 65 156 GO 149 65 161 70 190 60 179 56 1 79 70 140

Appendix 11: Volumetric moisture content (cm3 cm") of the 30cm soil as influenced by the Treatment

Moisture Content (cm3 crnq3) Treatment Pressure Potential (-kpa)

0 -3 -6 -10 0 -3 -6 -10 3rd month G ' ~ month

12 '~ month 18 '~ month 0.23 0.14 0.12 0.35 0.24 0.14 0.34 0.26' 0.15 0.45 0.33 0.27 0.36 0.25 0.14 0.44 0.34 0.27 0.35 0.27 0.14 0.45 0.33 0.28 0.34 0.27 0.13 0.38 0.33 0.25 0.33 0.28 0.17 0.40 0.32 0.28 0.34 0.28 0.16 0.41 0.33 0.29 0.35 0.28 0.15 0.42 0.31 0.28 0.28 0.17 0.13 0.30 0.29 0.18

24'h month 30'~ month 0.2 1 0.15 0.13 0.29 0.22 0.14 0.34 0.28 0.25 0.45 0.34 0.29 0.33 0.27 0.26 0.43 0.34 0.28 0.32 0/28 ,I. 0% 0.43 0.33 0.28 0.30 0.26 0.2 1 0.30 0.31 0.26 0.33 0.29 0.26 0.46 0.33 0.29 0.31 0.27 0.25 0.45 0.34 0.28 0.34 0.28 0.26 0.46 0.34 0.28 0.29 0.17 0.13 . 0.30 0.29 0.17

I I

36'h month 0.21 0.14 0.34 0.29 0.34 0.27 0.33 0.27 0.3 1 0.26 0.33 0.28 0.31 0.28 0.34 0.29 0.28 0.17

30 - 60 cm (3rd month) 0.29 0.23 0.17 0.1 5 0.30 0.31 0.25 0.23 0.17 0.3 1 0.25 0.21 0.16 0.12 0.3 1 0.3 1 0.24 0.20 0.16 0.34 0.3 1 0.24 0.21 0.17 0.35 0.30 0.26 0.19 0.17 0.34 0.3 1 0.27 0.20 0.16 0.3 1 0.32 0.26 0.18 0.14 0.32 0.30 0.29 0.20 0.16 0.3 1

12'~ month 0.28 0.22 0.17 0.32 0.29 0.25 0.3 1 0.30 0.25 0.32 0.29 0.25 0.32 0.29 0.27 0.3 1 0.28 0.24 0.3 1 0.27 0.25 0.34 0.28 0.26 0.30 0.27 0.18

24th month 0.28 0.25 0.18 0.35 0.31 0.29 0.36 0.32 0.26 0.37 0.33 0.28 0.37 0.30 0.29 0.4 1 0.3 1 0.28 0.37 0.31 0.28 0.38 0.31 0.29 0.30 0.28 0-26 a.1.

36th month 0.29 0.25 0.17 0.16 0.39 0.31 0.29 0.20 0.39 0.35 0.29 0.20 . 0.40' 0.36 0.32 031 -. 0.34 0.30 0.29 0.20 0.44 0.39 0.34 0.2 1 0.40 0.37 0.31 0.19 0.40 0.39 0.31 0.1 8 0.32 0.27 0.24 0.18

6th month 0.23 0.18 0.27 0.26 0.28 0.25 0.28 0.23 0.25 0.27 0.26 0.20 0.28 0.20 0.27 0.26 0.28 0.18

1 8 ' ~ month 0.24 0.18 0.30 0.28 0.30 0.26 0.31 0.27 0.29 0.28 0.28 0.25 0.29 0.27 0.27 0.27 0.27 0.19

3oth month 0.26 0.18 0.34 0.28 0.34 0.28 0.35 0.30 0.31 0.26 0.38 0.31 0.37 0.29 0.38 0.30 0.28 0.25